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Author’s full name :
MOHD AFFENDI BIN ISMAIL
Date of birth
:
16 DECEMBER 1987
Title
:
WEIGHTAGE FACTORS FOR MALAYSIA GREEN HIGHWAY ASSESSEMENT
Academic Session :
SEM 1 2013/2014
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Date
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:
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WEIGHTAGE FACTORS FOR MALAYSIA GREEN HIGHWAY ASSESSMENT
MOHD AFFENDI BIN ISMAIL
A thesis submitted in fulfilment of the requirements for the award of the degree of Master of Engineering (Construction)
Faculty of Civil Engineering Universiti Teknologi Malaysia
NOVEMBER 2013
ii
“I declare that this thesis entitled ‘Weightage Factors for Malaysia Green Highway Assessment’ is the result of my research except as cited in the references. The thesis has not been accepted for any degree and is not concurrently submitted in candidature of any other degree.”
Signature : _________________________ Name
: Mohd Affendi Ismail
Date
: 25 November 2013
iii
To my beloved; Ismail Mohamed, Zainab Abd. Rahman, Rozana Zakaria and Assoc. Prof. Ir. Dr Rosli Mohamad Zin, and to all my research partners. May God bless all of us.
iv
ACKNOWLEDGEMENTS
Foremost, I would like to express my utmost gratitude to my supervisor Dr Rozana Zakaria for providing incessant support, patience, motivation and enthusiasm as well as for sharing immense knowledge. Her guidance helped me throughout conducting the research and writing of this thesis. I could not have a better advisor and mentor for my postgraduate study. My appreciation goes to my co-supervisor, Assoc. Prof. Ir. Dr Rosli Mohamad Zin, for his great effort in helping me especially in the absence of my supervisor.
I would like to thank our faculty members especially Prof Dr. Muhd Zaimi Abd, Majid as the project leader, the project coordinator Mr Hasrul Haidar Ishak, Malaysia Highway Authority (LLM) and the rest of Malaysia green highway index Flagship research group for their encouragement, funding, insightful comments, and hard questions. I thank my fellow research mates for the stimulating discussions, for the sleepless nights that we were working together to meet the deadlines and for all the enjoyable moments that we shared in the last few months.
Last but not the least, I would like to thank my family; my parents, for giving birth to me in the first place and supporting me spiritually throughout my life.
v
ABSTRACT
A green highway is an effort to achieve sustainable approach for sustainable infrastructure. Key requirements for realizing green highway goals comprise of the fulfilment of Green Highway Index (GHI). GHI development and establishment of its criteria provide alternative and appropriate options for highway assessments. The weightage factors help to set the priorities of green highway elements according to their numbering value. The aim of this research is to establish weightage factors for the green highway criteria to be used in the Malaysia Green Highway assessment. An extensive literature review was undertaken on five major criteria identified in the Malaysia green highways assessment which are Sustainable Design and Construction Activities (SDCA), Energy Efficiency (EE), Material and Technology (MT), Environmental and Water Management (EWM), and Social and Safety (SS). In overall, 133 variables were selected from five main criteria to run the weightage Factor Analysis of Malaysia Green Highway Assessment. The elements were confirmed by 140 respondents, participating in questionnaire surveys, and were analysed using SPSS 18.0. A pilot analysis was undertaken by the reductions of factors to select a number that was easy to analyse but explained most of the variance using Factor Analysis. Factor score was calculated for each variable by multiplying the mean value of criterion with respective Factor Loading. The calculation of weightage factor was done by determining the ratio of percentage of population over the percentage of sample in a main criterion. Criterion with higher weightage was considered more important than another. Out of 133 criteria, 7 criteria were chosen for SDCA: 4 for EWM, another 4 for MT, 6 for EE and 7 for SS. The results show that all of these five main criteria served as essential basis for the development of Malaysia Green Highway Assessment.
vi
ABSTRAK
Lebuhraya hijau adalah suatu pendekatan lestari ke arah mencapai prasarana yang mampan. Kunci kehendak dalam mencapai sasaran lebuhraya hijau merangkumi kepatuhan terhadap Indeks Lebuhraya Hijau (GHI). Pembangunan GHI dan kewujudan kriterianya menyediakan alternatif dan pilihan yang bersesuaian terhadap penilaian lebuhraya hijau. Faktor pemberat membantu menetapkan keutamaan elemen lebuh raya hijau berdasarkan nilai penomboran mereka. Matlamat kajian ini adalah untuk menghasilkan faktor pemberat kepada kriteria yang mana akan digunakan dalam cadangan Penilaian Lebuhraya Hijau Malaysia. Sebuah kajian literatur telah dijalankan secara menyeluruh terhadap lima kriteria utama yang dikenalpasti dalam cadangan Penilaian Lebuhraya Hijau Malaysia iaitu Rekabentuk Lestari dan Aktiviti Pembinaan (SDCA), Kecekapan Tenaga (EE), Bahan dan Teknologi (MT), Pengurusan Air dan Alam Sekitar (EWM), serta Sosial dan Keselamatan (SS). Secara keseluruhan, 133 pembolehubah telah dipilih daripada lima kumpulan utama untuk menjalani Analisis Faktor pemberat bagi Penilaian Lebuhraya Hijau Malaysia. Elemen-elemen ini ditentusahkan oleh 140 responden, yang menyertai kajian soal selidik dan dianalisis menggunakan perisian SPSS 18.0. Satu analisis awalan dijalankan dengan pengurangan faktor untuk memilih bilangan faktor yang senang dianalisis tetapi menerangkan keseluruhan varian menggunakan kaedah Analisis Faktor. Skor Faktor dikira untuk setiap pembolehubah dengan mendarabkan Nilai Purata dengan Beban Faktor masing-masing. Pengiraan Faktor Pemberat dilakukan dengan menentukan nisbah peratusan populasi terhadap peratusan sampel dalam satu kriteria utama. Daripada 133 kriteria, 7 kriteria dipilih untuk SDCA, 4 kriteria bagi EWM, 4 kriteria untuk MT, 6 kriteria untuk EE dan 7 kriteria bagi SS. Keputusan menunjukkan kesemua lima kriteria utama menyediakan asas yang diperlukan kepada pembangunan penilaian lebuhraya hijau Malaysia.
vii
TABLE OF CONTENTS
CHAPTER
TITLE
PAGE
DECLARATION
ii
DEDICATION
iii
ACKNOWLEDGEMENTS
iv
ABSTRACT
1
v
ABSTRAK
vi
TABLE OF CONTENTS
vii
LIST OF TABLES
xi
LIST OF FIGURES
xiv
LIST OF ABBREVIATIONS
xvi
LIST OF TERMINALOGIES
xvii
BACKGROUND AND INTRODUCTION
1
1.0
Background of the Research
1
1.1
Problem Statement
2
1.2
Aim and Objectives
3
1.3
Scope of the Study
4
1.4
Brief Research Methodology
5
1.5
Significance of the Research
5
1.6
Outline of the Thesis
5
viii
2
LITERATURE REVIEW
6
2.0
Introduction
6
2.1
History of Green Highway
7
2.2
Highway, Sustainability and Green Ideas
7
2.3
Conceptual and Definitions of Green Highway Assessment
8
2.4
The Proposed Malaysia Green Highway Assessment Criteria
12
2.4.1
Sustainable Design and Construction Activities
12
2.4.2
Material and Technology
13
2.4.3
Energy Efficiency
14
2.4.4
Environmental and Water Management
15
2.4.5
Social and Safety
17
2.5
2.6
3
Statistical Approach on Weightage Analysis
18
2.5.1
The Conceptual of Research Survey and Data Set
18
2.5.2
Optional Statistical Method
21
Summary
25
RESEARCH METHODOLOGY
26
3.0
Introduction
26
3.1
Research Design and Procedure
26
3.1.1
Phase 1 – Green Highway Review
27
3.1.2
Phase 2 – Expert Discussion
27
3.1.3
Phase 3 – Questionnaire Survey
28
3.1.4
Phase 4 – Factor Score Calculation
30
3.1.5
Phase 5 – Weightage Factor Calculation
30
3.2
Instrumentation
30
3.3
Operational Framework
31
3.4
Data Analysis Procedures
32
3.4.1
Data Types Analysis
32
3.4.2
Missing Value Analysis using SPSS
36
3.4.3
Mean Value Analysis using SPSS
38
3.4.4
Factor Analysis using SPSS
38
ix
3.5
3.4.4.1 Fundamental of Factor Analysis
39
3.4.4.2 Steps in Factor Analysis Operation
42
Weightage Factor for the Malaysia Green Highway Assessment
51
3.5.1
Calculation of Factor Score
51
3.5.2
Calculation of Weightage Factor
52
3.5.2.1 Scale weighting
52
3.5.2.2 Proportional weighting
52
3.5.2.3 Mixed or integrated weighting
53
Applying Weightage Factor
54
3.5.3.1 Applying Weightage Factor Analysis for
54
3.5.3
Elements Description (Variables) 3.5.3.2 Applying Weightage Factor Analysis for
54
Sub Criteria 3.5.3.3 Applying Weightage Factor Analysis for Criteria
54
3.5.3.4 Applying Weightage Factor Analysis for Main
54
Criteria
4
3.6
Research Schedule
56
3.7
Summary
59
DATA ANALYSIS AND RESULTS
60
4.0
Introduction
60
4.1
The Analysis
60
4.1.1
Part I: Demographic of Respondents
61
4.1.1.1 Type of Company
61
4.1.1.2 Position in Company
62
4.1.1.3 Education Level
64
4.1.1.4 Working Experience
65
4.1.1.5 Involvement in Highway Development
66
4.1.1.6 Level of Awareness on Green Development
67
4.1.1.7 Involvement in Green Development
68
x
4.1.2
Part II: Criteria and Elements of Malaysia Green Highway 69 Assessment 4.1.2.1 Missing Value Analysis using SPSS
69
4.1.2.2 Mean Value Analysis using SPSS
71
4.1.2.3 Factor Analysis using SPSS
92
4.1.2.4 Weightage Factor for Malaysia Green Highway
102
Assessment 4.2
5
Summary
117
CONCLUSION AND RECOMMENDATIONS
122
5.0
Introduction
122
5.1
Summary of Findings
123
5.2
Problems Faced During the Study
128
5.3
Suggestions for Future Works
128
5.4
Conclusion
129
REFERENCES
130
LIST OF APPENDICES
141
xi
LIST OF TABLES
TABLE NO.
TITLE
PAGE
Table 2.1
Variety Definitions of Green Highway
8
Table 2.2
Simplified Comparison of Various Green Highway
9
Assessment/Model Table 2.3
Simplified Criteria of Various Green Highway Assessment
10
Table 2.4
Proposed Elements of Malaysia Green Highway
10
Table 2.5
Comparison between Principle Component Analysis and Factor
19
Analysis Table 2.6
Comparison of Various Statistical Decision Making Methods
23
Table 3.1
Template for Questionnaire Design
27
Table 3.2
Differences between Parametric and Non-Parametric Statistic
32
Table 3.3
Test of Parametric and Nonparametric Statistics
33
Table 3.4
Selecting a Statistical Test in Details
34
Table 3.5
Factors Set for Social and Safety
38
Table 3.6
Assumptions in Factor Analysis Model
39
Table 3.7
Applications of Factor Analysis
40
Table 3.8
Critical Chi-Square Values
42
Table 3.9
Research Schedule for Two Years Project Period
56
Table 3.10
Description of Research Schedule
57
Table 4.1
Respondent’s Type of Company
60
Table 4.2
Respondent's Position in Company
61
Table 4.3
Respondent's Education Level
63
Table 4.4
Respondent's Work Experience
64
Table 4.5
Involvement of Respondents in Highway Development
65
Table 4.6
Level of Awareness of Respondents on Green Development
66
Table 4.7
Involvement of Respondents in Green Development
67
xii
Table 4.8
Original Raw Data of Material and Technology
69
Table 4.9
Replaced Missing Values
69
Table 4.10
Final Mean of Material and Technology
69
Table 4.11
Mean of Sustainable Design and Construction Activities
70
Table 4.12
Template for Sustainable Design and Construction Activities
72
Table 4.13
Mean of Material and Technology
73
Table 4.14
Template for Material and Technology
75
Table 4.15
Mean of Environmental and Water Management
77
Table 4.16
Template for Environmental and Water Management
80
Table 4.17
Mean of Energy Efficiency
82
Table 4.18
Template for Energy Efficiency
85
Table 4.19
Mean of Social and Safety
87
Table 4.20
Template for Social and Safety
89
Table 4.21
Final Variables for Each Main criteria after Mean Value Analysis 90
Table 4.22
Statistical test of Chi-Square with Critical Chi-Square Values
92
Table 4.23
Kendal’s W Test Statistic
95
Table 4.24
Kaiser-Meyer-Olkin and Bartlett's Test
95
Table 4.25
Cronbach’s Alpha Test
95
Table 4.26
Total Variance Explained
96
Table 4.27
Pattern Matrix Tabulation
99
Table 4.28
Legend for Pattern Matrix Tabulation
101
Table 4.29
Final Factors and Variables for Every Main criteria
102
Table 4.30
Factor Score for Element’s Description, Sub Criteria
103
and Criteria Table 4.31
Factor Score of Malaysia Green Highway Assessment
104
Table 4.32
Comparison of Percentage of Categories from Major Rating
105
System Table 4.33
Weightage Factor for Elements Description
107
Table 4.34
Weightage Factor for Sub-Criteria
109
Table 4.35
Weightage Factor for Criteria
111
Table 4.36
Weightage Factor for Main criteria
113
Table 4.37
Tabulation of Weightage Factors from Highest to Lowest
115
Table 4.38
Weightage Factor for All Main Criteria
118
Table 5.1
Simplified Major Elements of Green Highway
125
xiii
Table 5.2
Criteria & Sub-Criteria of Malaysia Green Highway Assessment 126
Table 5.3
Tabulation of Weightage Factors from Highest to Lowest
128
xiv
LIST OF FIGURES
FIGURE NO.
TITLE
PAGE
Figure 2.1
Breakdown of Roads into State Roads and Federal Roads
7
Figure 2.2
Various Green Highway Research of Interest
9
Figure 2.3
Graphic of HDI versus Energy Consumption
14
Figure 2.4
CO2 Emissions by Sector in Malaysia by 1999
16
Figure 2.5
Average CO2 Emissions per Kilometres from New Passenger Cars 17
Figure 3.1
Operational Framework
30
Figure 3.2
Determining the Type of Variables
35
Figure 3.3
Missing Value Analysis Patterns
35
Figure 3.4
Descriptive Missing Value Analyses
36
Figure 3.5
Relations between F, X and e
40
Figure 3.6
Variable Relationship Test
43
Figure 3.7
Descriptive Analysis
44
Figure 3.8
Reliabilty Analysis
45
Figure 3.9
Scree Plot Test
48
Figure 4.1
Respondent’s Type of Company
60
Figure 4.2
Respondent's Position in Company
62
Figure 4.3
Respondent's Education Level
63
Figure 4.4
Respondent's Working Experience
64
Figure 4.5
Involvements of Respondents in Highway Development
65
Figure 4.6
Level of Awareness of Respondents on Green Development
66
Figure 4.7
Involvements of Respondents in Green Development
67
Figure 4.8
Mean and Average Index of Sustainable Design and
71
Construction Activities
xv
Figure 4.9
Mean and Average Index of Material and Technology
74
Figure 4.10
Mean and Average Index of Environmental & Water Management 78
Figure 4.11
Mean and Average Index of Energy Efficiency
83
Figure 4.12
Mean and Average Index of Social and Safety
88
Figure 4.13
Scree Plot Test
98
Figure 4.14
Factor Score of Malaysia Green Highway Assessment
105
Figure 4.15
Comparison of Percentage of Categories of Major Rating System 106
Figure 4.16
Main criteria Weightage and Percentage
118
xvi
LIST OF ABBREVIATIONS
ANOVA
Analysis of Variance
BTU
British Thermal Unit
DID
Department of Irrigation and Drainage
DOE
Department of Environment
DWNP
Department of Wildlife and National Parks
EE
Energy Efficiency
EWM
Environmental and Water Management
GREENLITES
Green Leadership in Transportation Environmental Sustainability
GREENROADS
Greenroads Rating System
HDI
Human Development Index
ID
identification of criteria within a main criteria
I-LAST
Illinois-Livable and Sustainable Transportation Rating System
ILH@M
Indeks Lebuhraya Hijau Malaysia
KMO
Kaiser-Meyer-Olkin
LLM
Malaysia Highway Authority
MASMA
Manual Saliran Mesra Alam Malaysia
MT
Material and Technology
MVA
Mean Value Analysis
NWSC
National Water Services Commission
PCA
Principle Component Analysis
PWD
Public Works Department
REAM
Road Engineering Association of Malaysia
SDCA
Sustainable Design and Construction Activities
SPSS
Statistical Package for the Social Science
SS
Social and Safety
TEP
Tons Equivalent Petroleum
xvii
LIST OF TERMINALOGIES
Assessment
a process of gather, analyse, interpret, using information
Criteria
standard/rule/test on which a judgment/decision can be based
Eigenvalues
special set of scalars associated with linear equations
Element Description brief explanation of the sub criteria Factors
group of variables within the same tendency
Factor Loading
correlation coefficients between the variables and factors
Factor Score
scoring to evaluates something according to numerical value
Main criteria
five main criteria of proposed Malaysia Green Highway Assessment (SDCA, EE, MT, EWM and SS)
Models
rating index/collaboration/framework/initiatives
Stratum
a subset (part) of the population which is being sampled
Sub Criteria
a subset of main criteria
Variables
element description used in factor analysis
Variance
a measure of how far a set of numbers is spread out
Weightage
value/importance of something compared with another thing
CHAPTER 1
BACKGROUND AND INTRODUCTION
1.0
Background of Research
A green highway is a roadway constructed in a way that integrates transportation functionality and ecology. An environmental approach is used throughout the planning, design, and the construction. Green highways have invaluable benefits to environment; A green highway will benefit transportation, the ecosystem, urban growth, public health and surrounding communities. Landfill usage is favourably reduced as construction involves recycled materials. In addition, by using cutting-edge technologies in design, critical habitats and ecosystems are protected from the encroachment of highway infrastructure. Furthermore, a green highway provides superior watershed-driven storm water management that prevents leaching of metal and toxins flow into the streams and rivers. Accomplishment of green highway infrastructure calls for focus on integrating transportation needs. This objective can be realized by considering ecological protection, by avoiding subsequent environmental destruction and excessive resource consumption as well as by incorporating sustainable development concepts into infrastructure projects. A green highway necessitates commitment from all parties involved, such as business concerns, drivers and the government as their involvement can ensure that the green concept is long lasting. Reducing the pollution and preserving the nature must be the aim of every green development.
2
To achieve a green highway, harmonization of highway needs with local ecological protection considerations needs to be focussed. Moreover the questions such as how to avoid subsequent environmental destruction and excessive resource consumption and how to incorporate sustainable development concepts into highway projects need to be answered. In this regard, development of the green highway assessment system is the key to promoting sustainability and green highway construction. Hence, this study will come out with several fundamental elements of green highway development within Malaysian context. These elements will ultimately provide an essential guidance for the establishment of Malaysia’s green highway framework model of assessment. Additionally, many parties in Malaysian highway industry will much benefit by incorporating green characteristics in managing and developing roads, pathways, expressways and other such concerns.
1.1
Problem Statement
The effects on local environment, economic and social along the pathway are significantly contributed by highway development. Present days have witnessed the raise in awareness and concern among government, concessions, and public on the importance of making the world a convivial place to live in, ensuring progressive growth as well as achieving sustainability. In addition to ideas of green highway, the world countersigned various efforts of assessments like the establishment of Greenroads® and GreenLITES®. Greenroads® is a rating system that distinguishes more sustainable, new, reconstructed and rehabilitated roads. Greenlites® is a selfcertification program that distinguishes transportation projects and operations based on the extent to which they incorporate sustainable choices. However, these contemporary models and assessments of green highway performance has encountered several problems for instance, each single assessment is only valid to be used in a certain areas, as the criteria underlined in the model are restricted to particular areas only.
3
Practically, every single assessment model of green highway is different from the other. This is because each model is generally being designed and built based on local capacity in particular regions, encompassing local needs only. For instance, an assessment model for a region is sometimes not suitable to be applied to other areas. This problem might be contributed by different elements of weightage used in every single model.
The elements of current highway assessment are limited and not do vary in terms of practicability, as for example, if ‘Model A’ does not have assessment criteria for social and safety for ‘Highway B’, the models are not dependable and cannot be used, as the weightage factor is being affected. On the other hand, there is no standardization between models of assessment as they come out with their own interpretation. In order to adapt with this problem, Malaysia highway authority and other responsible parties will have to come up with some kind of new list of elements to be considered in developing the weightage of Malaysia green highway assessment elements. This can be accomplished by undertaking several studies involving indepth analysis of several key phases, which is planning, designing, construction, operation and maintenance of highway development.
1.2
Aims and Objectives
The aim of this research is to establish green highway weightage factor of green highway criteria to be used in Malaysia Green Highway assessment. The study was carried out based on the following objectives:
i. to determine critical criteria and elements of green highway, ii. to develop green highway weightage factor for green highway assessment, and iii. to analyse the weightage factor for Malaysia green highway.
4
1.3
Scope of the Study
This research determines factors and elements to be used for Malaysia Green Highway assessment. Possible elements, criteria and sub criteria related to highway were gathered from various assessments, ratings, initiatives and collaborations. The statistical and mathematical models in the market were studied to calculate weightage factors. A pilot analysis was conducted through reductions of factors conduct using factor analysis method. To carry out the weightage factor analysis, 133 variables were selected. Factor score and weightage factors were calculated for each variable. Several parties from government and private sectors, including Malaysia Highway Authorities, highway concessionaires like PLUS and MTD, contractors, suppliers and others related personnel, were approached for comments, views, perceptions and suggestions towards the problems. The weightage factors for criteria, sub criteria and element descriptions were established for Malaysia green highway assessment model.
1.4
Brief Research Methodology
The research methods employed for this study included the review of literature including books, journals and information from Internet. Data were collected using questionnaire; the respondents were individuals who were involved with the highway construction. Several analyses were conducted to identify the elements, contributing most in the green highway, this would establish green highway weightage factor to be used in developing Malaysia green highway assessment model.
5
1.5
Significance of Research
Effective green highway infrastructures enable people to access vital services such as healthcare and education, to travel for employment, to transport and sell goods, to access social networks, and to make their voices heard in the political arena. Ultimately, a green highway will support the sustainable principles as it leads to improved social development, economic growth and friendly environment. Thus, providing a weightage factor of green highway criteria is a sustainable goal to achieve more reliable, comfortable and convenient highway assessment system.
1.6
Outline of the Thesis
This thesis consists of 5 Chapters. A brief summary of each is outlined as follows: Chapter 1 comprises of introductory section which develops the reason for the direction of this research. It is also states the research background, research problems, research objectives, brief discussion on methodology, research scope and significance of the research. Chapter 2 describes the key terms used in the research as well as summarises the current state of knowledge by examining relevant background literature. This chapter also comprises the literature review on the history of green highway, the relation between highway, sustainability and green ideas, the concepts and definitions of green highway assessment, the proposed Malaysia green highway assessment criteria and statistical approaches to weightage analysis. Chapter 3 describes the research methodology in detail including the research plan, data collection method, type of data collected, respondents involved, pilot study, reliability, validity and data analysis. This chapter also explains how the data were acquired and how the respondents were selected and approached. Chapter 4 presents the analysis and interpretation of qualitative data using SPSS 18.0 software. The end of this chapter summarise the weightage factors for Malaysia green highway assessment. Chapter 5 concludes the findings from the research. This chapter also shows the most relevant factors for Malaysia green highway assessment, the limitations of the research and the suggestions for the future study.
CHAPTER 2
LITERATURE REVIEW
1.0
Introduction
In the recent years, world has recognised the importance of green highway for the recent years. During the early 21st century several researches have been done particularly with reference to assessing the green highway performance. It is observed that a green highway rating system provides a way to update current highway management practices, which include advanced recycling techniques, extended environmental mitigation and extensive energy reduction. Thus, the system classifies the various parts of highway construction processes and then rates them based on their environmental sustainability. This approach focuses on ways to reduce the life cycle cost through more sustainable highway construction rather than the initial cost of construction.
2.1
History of Green Highway
This chapter discusses the basis of green highway concept. In 2007, Greenroads® was developed in Washington as a rating system for measuring sustainability of highways (Muench et. al., 2011). Preliminary research on Greenroads® exposes that it can be implemented in Washington with promising outcome but needs extensive research to be implemented outside Northwest. In addition, the research further adduced that many technologies either are not relevant
7
to every U.S. region or cannot be transferred to different regions without extensive retrofitting (Bryce, 2008). Malaysia as a developing country has plans to build extensive infrastructure including vast network of highways as their development agenda. In 2000, the total length of roads in Malaysia was approximately 65,445km. The total length of roads has increased by 33 per cent from 2000 to 2005. From 2005 to 2007, the length of roads increased by 35 per cent. Figure 2.1 presents the breakdown of roads into state roads and federal roads in Malaysia (Second National Communication to the United Nations Framework Convention on Climate Change, 2007). 140000 120000 100000 80000 60000 40000 20000 0
100812 state
70749 49814
federal
15631
16276
16899
2000
2005
2007
Figure 2.1: Breakdowns of State Roads and Federal Roads in Malaysia
2.2
Highway, Sustainability and Green Ideas
Highway can be defined as any interconnected set of highways and can be variously referred to as a ‘highway system’, a ‘highway network’, or a ‘highway transportation system’. Thus, the highway development should also meet the concept of Sustainable Development which is the development that meets the needs of the present without compromising the ability of future generations (World Commission on Environment and Development, 1987). The idea of Green Construction refers to a structure and using process that is environmentally responsible and resource-efficient throughout a construction's life cycle; from sitting to design, construction, operation, maintenance, renovation, and demolition. A green highway assessment gives us a meaning of evaluation or estimation on criteria of green highway, their performance, rating and other factors with a view to having an ideal highway that support the aims of sustainability.
8
2.3
Conceptual and Definitions of Green Highway Assessment
Existing studies on green highway construction have addressed the subject from different angles. Chiu (2002) and Shen (2001) explore environmental considerations throughout the stages of the project lifecycle, including feasibility research, planning, design, construction, maintenance, and management. To that direction, Hsieh and Lin (2004) investigate implementation strategies of ecological construction techniques for different road components, which include slope stabilization, drainage, bridges, tunnels, culverts, railings, lighting, traffic control, service areas, and interchanges. On the other hand, Huang and Kou (2002) look at things from three perspectives viz. environment, society and economy. They use 10 assessment items which are natural conservation, energy conservation, water/soil conservation, waste reduction, re-vegetation, materials, safety and comfort, fair development, cultural preservation, and cost-effectiveness to perform summary assessments of different types of projects. While the aspects considered by the latter researchers are completely in line with the spirit of sustainable development, they are not specifically connected with road construction (Huang and Yeh, 2008). Chen, Chou and Yu in 2001 classify project types as roadways, railways, watersides, slopes, and draft valuation indicators for the three assessment categories namely environment, ecology, and resources.
The foregoing review of the literature reveals that there is a complex array of environmental factors that need to be taken into consideration in road construction projects, and each stage in a project life cycle has a different impact on the environment. Huang and Yeh in 2008 categorize green highway assessment topics into six groups, namely ecology, landscaping, materials, waste reduction, water conservation, and energy conservation. They have established indicators for each aspect for use in actual assessment work. This shall form a guide upon which the study will be undertaken. To date, most attention and effort in the development of sustainable construction in countries all over the world has been devoted to buildings. Several other definitions are also shown in the Table 2.1.
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Table 2.1: Variety Definitions of Green Highway REFERENCE OF PUBLICATIONS Development of an Assessment Framework for Green Highway Construction (Huang and Yeh, 2008)
DEFINITIONS highway construction that comply with the principles of sustainable or green construction
Developing Sustainable Transportation Infrastructure (Bryce, 2008)
five broad topics which are watershed driven storm water management, lifecycle energy & emissions reduction, recycle, reuse & renewable, conservation and ecosystem management, and overall societal benefits
New Road Construction Concepts: Towards Reliable, Green, Safe & Smart and Human Infrastructure in Europe (Adesiyun, Arnaud & Bueche, 2008)
reduction of production temperatures leads to a decrease of energy consumption, a decrease of CO2 emissions and other harmful emissions
Green Building with Concrete: Sustainable Design and Construction (Sabnis, 2011) Mid-Atlantic Green Highways Initiative (Initiative, 2010)
recycling industrial by-products and construction materials in highway construction, where the usage of virgin materials and large amounts of energy is avoided integrating stewardship, safety, and sustainability into the planning, design, construction, and maintenance of transportation infrastructure
RATING INDEX
COLLABORATION
FRAMEWORK
INITIATIVES
Green Roads GreenLites
Green Performance Contracting on Highway Construction Projects
Development of an Assessment Framework for Green Highway Construction
Use of Be2st in Highways for Green Highway
Figure 2.2 Various Green Highway Research of Interest
Figure 2.2 shows the various research interests towards green highway, comprising of rating index such Greenroads® and GreenLites®, and collaboration research Green Performance Contracting (GPC) on Highway Construction Projects. The figure also presents some framework like “Development of an Assessment Framework for Green Highway Construction”, and initiatives such as “Use of Be2st in Highways for Green Highway”. All of these can be considered as models of assessment for green highway. In order to facilitate a green highway construction, therefore, the experience and knowledge acquired in the process of developing sustainable or green buildings certainly make constructive contribution. The elements from various green highway models have been gathered and simplified in order to establish the criteria for Malaysia Green Highway as shown in the Table 2.2.
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water
energy
ecosystem
social
innovation
3R
cost
safety/health
gas emission
Original Main Criteria
material
Green Highway Assessment/Model
Simplified Main Criteria
construction
Table 2.2: Simplified Comparison of Various Green Highway Assessment/Model
8 √
4 √
5 √
6 √
3 -
3 -
2 -
5 √
1 -
2 -
1 -
Ecology landscaping Development of an Assessment Framework materials for Green Highway waste reduction Construction water conservation energy conservation material related Developing Sustainable strategies equipment and Transportation energy efficiency green life cycle Infrastructure strategies clean energy development watershed driven storm water lifecycle energy ® and emissions conservation and Greenroads reduction ecosystem recycle, reuse and management renewable overall societal benefits reliable Green Performance infrastructure green Contracting on Highway infrastructure safe/smart Construction Projects infrastructure human infrastructure human health / safety greenhouse gases emission material reuse / Green Highways recycling Partnership energy use life cycle cost water consumption sustainable design material & resources New Road Construction storm-water management Concepts innovation construction activities energy & environmental innovative control Use of Be2st in Highways watershed‐driven conservation & for Green Highway storm water ecosystem recycling and protection total = 40reuse average score 3.64, hence take > 3.64
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The elements presented in Table 2.2 were then shortlisted, selecting the ones with most contribution towards the model, and generalized into simplified elements (presented in Table 2.3) according to respective categories to be used as proposed Malaysia Green Highway criteria. The significant difference between Table 2.2 and Table 2.3 is the number of simplified main criteria being reduced from eleven main criteria (construction, material, water, energy, ecosystem, social, innovation, 3r, cost, safety/health, gas emission) to a smaller number of five, which are construction, material, water, energy and 3R (recycle, reuse, reduce). Research has found that the construction, material, water and energy are the most discussed criteria by the previous rating and assessment. It is noted that the recycle, reuse and reduce criteria is neglected as the category itself can be merged into all other criteria according to the theory of sustainability.
Table 2.3: Simplified Main Criteria of Various Green Highway Assessment/Model SIMPLIFIED MAIN CRITERIA
Construction
Material
Water
Energy
Recycle, Reuse, Reduce
CRITERIA landscaping equipment life cycle green strategies reliable green infrastructure safe smart related strategies recycle, reuse, reduce resources conservation consumption conventional watershed driven storm-water innovative management conservation usage efficiency control clean lifecycle reduce reuse recycle renewable
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It is proposed that to establish Malaysia Green Highway assessment model, the content will be called as main criteria, criteria, sub-criteria and elements description. The main criteria identified are known as Energy Efficiency (EE), Sustainable Design and Construction Activities (SDCA), Material and Technology (MT), Environmental and Water Management (EWM) and Social and Safety (SS). The key finding of proposed major elements for Malaysia Green Highway Assessment can be simplified as shown in Table 2.4.
Table 2.4: Proposed Elements of Malaysia Green Highway n MAIN CRITERIA CODE 1 Energy Efficiency EE 2 Sustainable Design and Construction Activities SDCA 3 Material and Technology MT 4 Environmental and Water Management EWM 5 Social and Safety SS
2.4
The Proposed Malaysia Green Highway Assessment Criteria
The following are the deliberations on how each of the main criteria of proposed Malaysia Green Highway Assessment being initiated. As mentioned before, the proposed assessment consists of Energy Efficiency (EE), Sustainable Design and Construction Activities (SDCA), Material and Technology (MT), Environmental and Water Management (EWM), and Social and Safety (SS). The detailed explanation of each of the main criteria is exhaustively described onwards.
2.4.1
Sustainable Design and Construction Activities
Highway construction phases are not so much different from building construction. When talking about planning phase, there are several criteria to be looked in to viz. the alignment and geometric features of highway, green highway partnership characteristics, access to public transport and green technology & material. While in design phase, the criteria are green point rating system, pavement,
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creepers of highway structure, solar energy, light emitting diode (LED) for street and landscaping alongside the highway (Thompson, 2007). While building a green highway, construction phase always puts a burden on the developer’s account. They not only have to match and incorporate the ideas of green highway into proper site work line, but also keep to the budget provided by the investor. Their challenges include using local material, reducing emission from construction equipment & machinery and innovative technologies. The other phase to be looked into is the operation and maintenance phase (Chang, 2000). This phase cannot be neglected in the attention since among the major obstacles in green highway development is the cost of operating and maintaining the greenness of the highway, as well as the highway itself.
2.4.2
Material and Technology
Several green pavement technologies are available that reduce environment impacts, reuse roadway materials, or use recycled material in pavement application. One of the criteria in reducing environment effect is using warm mix asphalt, which will reduce the energy cost. By reducing pavement noise, the roadways noise pollutions are also reduced. Moreover, using porous pavements will reduce storm water runoff. The second technology in green pavement is reusing roadway materials. It can be done by full depth reclamation of particular area of project in which the in-place roadway materials will be reused. In practice, reusing high quality aggregates like Taconite aggregates resources could supply a high quality, low cost aggregate for roadway use, especially in areas where aggregates are becoming scarce (Clyne, 2010). Another technology, in connection with greener highways is recycling the roadways materials. The old asphalt pavement can be recycled in hot mix asphalt to produce some kind of new fresh asphalt. Meanwhile, recycling the base material of old concrete and asphalt roadways contribute to cost saving. In addition, a greener highway can also be achieved by recycling both tear and manufacture shingles. Green highways are built with permeable materials that provide superior watersheddriven storm water management, thus preventing metals and toxins from leaching into streams and rivers and consequently helping to improve water quality. Likewise
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recycled materials are also being used for construction, thereby reducing landfill usage. Further, the green highway is designed using cutting-edge technologies to protect critical habitats and ecosystems from the encroachment of highway infrastructure (Green Highways Partnership, 2007).
2.4.3
Energy Efficiency
Many researchers from various agencies and academia have been investigating and implementing ways to make our roads greener, while maintaining or improving roadway quality. There is considerable potential for energy efficiency in green highway infrastructure, whereas the transportation sector is the biggest energy consumer. It is inclusive of infrastructure design, planning and material which enhance the reduction.
On the other hand, developing countries have problems related to energy consumption as the statistics shows that higher Human Development Index (HDI) is equal to higher energy consumption (Smith, 1993). Figure 2.3 describes how HDI relate with energy consumption. It can be noticed in 1999, the Human Development Index (HDI) of Malaysia is 0.774 and the energy consumption per capita (tons of equivalent petroleum; TEP) value is 1.9. Qatar, with more than 8.000 TEP, has greater value than USA with 5.950 TEP, although both these countries have only a slight difference in the value of HDI. One of the focuses of this research is transportation infrastructure, which is to provide quality of life with an appropriate British Thermal Unit (BTU) (Dias et al., 2004). Plotting HDI as a function of energy use per capita shows that countries with high HDI values have higher values of energy use per capita than those with a low value. Among countries with a high value of HDI (> 0.85), there is a wide range of energy intensity values, with Bahrain consuming 6.5 × 1011 J/capita (612 million BTU/capita) but having an HDI value of 0.859, which is somewhat lower than that of Canada with 0.950 HDI and 442 million BTU/capita (Wee, 2008 and Haub, 2011). Significantly, green highway will help to have less BTU, which will reflect as less carbon footprints.
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Figure 2.3: Graphic of HDI versus Energy Consumption (Dias et al., 2006)
2.4.4
Environmental and Water Management
Reduction of storm water runoff from highways is vital along with management of the runoff. The incorporation of storm water management practices in highway design is a feature of green highway. Such practices as the setting up of bio-swales and wetlands are integrated in highway projects to serve as effective tools for managing storm water runoffs from neighborhood roads, impervious parking lots and highways. Bio-swales are provided along neighborhood roads and along impervious parking lots to slow and treat storm water runoff while wetlands act as natural water treatment processes, alongside the highway (Struck, 2010). Highway construction is an inter-industry field related to both the construction and transportation sectors. Although highway construction is typically considered as being emission intensive (Truitt, 2009), it is not usually addressed as the major greenhouse gas emission source from either the construction or transportation industry. After all, highway construction has its unique features compared with onroad sources or buildings. However, very few studies have focused on greenhouse gas emissions from the whole life cycle of highway infrastructure development and construction. Nor are there any comprehensive studies to explore the strategies to integrate emission reduction and sustainability into highway project planning and the delivery process (Cui et al., 2011).
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The green highway is conducive to reduce the emission of the carbon dioxide, carbon monoxide or any of the green effect gasses. By reducing the emission of these gasses, it will help to decelerate the thinning of ozone layer, increase of the earth temperature, pollution and other factors to help conserve and preserve the earth. There are variety of long-term threats to public health and global environment and one of the most significant causes is the climate change. The excessive production of greenhouse gases (GHG) in the atmosphere effectively traps some of Earth’s heat that would otherwise escape into space. The GHG is a group of gases such as carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O), the emission of which contributes to the greenhouse effect, measured in grams of CO2 equivalent. As for example, Carbon Dioxide emissions from all transportation include emissions from combustion of fossil fuels for road, rail, air, and other forms of transportation, and agricultural vehicles while they are on highways (Schipper, 1999). Figure 2.4 explains that transportation as a part of highway components is among the largest contributor of CO2 emissions by sector in Malaysia by 1999.
other sectors 7% residences 2%
electricity and heat production 28%
transportation 28%
manufacturing and construction 23%
other energy industries 12%
Figure 2.4: CO2 Emissions by Sector in Malaysia by 1999 (Saidur, 2007)
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The average of Carbon Dioxide, CO2 emissions per kilometres (gCO2 per km) from new passenger cars in European countries can be seen in Figure 2.4. The figure portrays the estimation on the amount of CO2 emitted alongside our highway. It is computed by multiplying the total length of Malaysia road in 2007, inclusive of federal and state roads (117,711 kilometres (km) with average CO2 emissions per km from new passenger for the same year (158 gCO2 per km) resulting in 18598338 gCO2 (18598 kg) (An, 2007). This disappointing number entails the need for a serious action to reduce the emission from this hazardous gas.
Figure 2.5: Average CO2 Emissions per Kilometres from New Passenger Cars (gCO2/km) (An, 2004)
2.4.5
Social and Safety
The development of green highway has its overall social value to the public. The supply of tax income, local jobs and infrastructures erection with properly designed of green highway invite business activities into a society. At first glance, a green highway may not look much different from a normal highway, but a driver will notice subtle differences at closer inspection. Wildlife buffers consist of more plant life along the shoulder. Highways become more aesthetically pleasing in towns, and come to be a more natural part of the environment in rural areas (Bryce, 2008). Malaysia Highway Authority (LLM) encourages that the research shall also consider social and safety to be among of major criteria in Malaysia Green Highway
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Assessment. This is because the end user satisfaction and acceptance are a major concern, to suit with National Key Result Area (NKRA) (Zakaria et. al, 2011).
2.5
Statistical Approaches on Weightage Analysis
There are multiple statistical approaches on weightage analysis in the market. Each method has its own significance, operation, specialities, availability and as well as other aspects. Hence, this section will discuss the conceptual research survey and data set, and available optional statistical methods.
2.5.1
The Conceptual Research Survey and Data Set
Robert K. Yin (2008) categorised research into two types viz. exploratory research and conclusive research. He explains that exploratory research is an insight study and understanding of the research problem. Sometimes this type of research loses definition of information needed. Whereas, an exploratory research is a flexible or unstructured research process. It has small and no representatives’ samples to be taken into account. The exploratory research needs qualitative data analysis of primary data usually a preliminary step of further research. On the other hand, a conclusive research relies on to have a quantitative data analysis. This research tests specific hypothesis and examines relationships of samples. Normally, a conclusive research is a formal and structured research process. The advantage of this type of research is that it has clear definition of information needed as compared to exploratory research. It is a representative and requires large samples to be studied. A conclusive research has the conclusive results for decision-making process. In general, data can be categorised into three types. Quantitative data, as a number set, usually a continuous decimal number to a specified number of significant digits and sometimes a whole counting number. While a categorical data is a set of data that falls into several categories, the Qualitative data, as the third category, is a pass/fail or the presence or lack of a characteristic (Yin, 2008).
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The analysis of a research survey shall be directed by the research objectives. On the other hand, the type of analysis should also be driven by the type of scales used in the research survey. The types of scales vary and among them is nominal scale. It can be analysed either by using frequency distributions, proportions, and mode or cross tabulation. The same condition goes to ordinal scales, as they can be analysed using same analyses. While for interval and ratio scales, one can use frequency distributions, analysis of proportions plus analyses of means and standard deviations (Weisberg, Krosnick, & Bowen, 1996). Before doing these analyses, sometimes there is a need to sort the data or recode some of the data. In calculating and determining the weightage factor value, it is a need to prepare the raw data set into analysable data distributions. The data should be prepared and coded accordingly. Several cleaning and consistency checks should be carried out in order to have credible data.
There are usually two statistical techniques applied worldwide, which are univariate techniques and multivariate techniques. A univariate technique is the assumption of response variable, which is influenced only by one other factor. Meanwhile, a multivariate technique is an assumption of response variables to be influenced by multiple factors (Kachigan, 1986). Both techniques refer to expression, equation, function or polynomial. In highway development, it is impossible to apply univariate techniques since the highway itself consist of various factors neither in planning, designing, construction and maintenance phase. Among the factors are construction activity, material used, energy produced and much more. When talking about variables give a meaning that all of these factors have their very own variable to be considered within green highway development (Erzini, Inejih, and Stobberup, 2005). There are varieties of multivariate techniques, including Principle Component Analysis (PCA) and Factor Analysis. These two techniques are well-known techniques since years, especially to those doing analysis on research survey.
20
In determining the appropriate statistical analysis for a research question, one should know the behaviour of the data and theory of the method. Principle Component Analysis provides correlated variables purposely to reduce the numbers of variables and describe the same amount of variance with fewer variables. While Factor Analysis estimates factors, provide underlying construct that cannot be measured directly. Table 2.5 shows the comparison between PCA and Factor Analysis.
differences
criteria
model
purpose
Table 2.5: Comparison between Principle Component Analysis and Factor Analysis Principle Component Analysis one of simplest multivariate methods to take n variables X1, X2,…, Xn and find combinations to produce indices Z1, Z2,…, ZQ that are uncorrelated
Factor Analysis similar to PCA. to describe a set of n variables X1, X2, …, Xn in terms of a smaller number of m factors and to highlight relationship between these variables Z1 = a11ϰ1 + a12ϰ2 + ...+ a1n ϰn X1 = a11F1 + a12ϰ2 + ...+ a1m Fm + e1 Z2 = a21ϰ1 + a22 ϰ2 +…+ a2nϰn X2 = a21F1 + a22ϰ2 + ...+ a1m Fm + e2 Zn = an1ϰ1 + an2ϰ2 +…+ annϰn Xn = an1F1 + an2ϰ2 + ...+ anm Fm + en used when variables are highly hypothesizes an underlying construct, correlated a variable not measured directly reduces number of observed variables can describe and identify the number to a smaller number of principal of latent constructs (factors) components which account for most includes unique factors, error due to of variance of the observed variables unreliability in measurement a large sample procedure to explore possible underlying factor structure of a set of measured variables without imposing any preconceived structure on outcome (Shur, 2005) retained account for a maximal amount factors account for common variance of variance of observed variables in the data analysis decomposes correlation matrix analysis decomposes adjusted correlation matrix ones on the diagonals of the correlation diagonals of correlation matrix matrix adjusted with unique factors minimizes sum of squared estimates factors which influence perpendicular distance to component responses on observed variables axis component scores are a linear observed variables are linear combination of the observed variables combinations of the underlying and weighted by eigenvectors unique factors
21
Compared to other methods, Factor Analysis comes with a package of advantages. It offers much more objective methods of traits’ testing such as intelligence in humans. The Factor Analysis also allows satisfactory comparison between the results of intelligence tests. This process provides support for theories that would be difficult to prove otherwise (Ivancevic, 2009). Along with its advantages Factor Analysis also has a few of disadvantages highlighted by its practitioners. Stenberg in 1977 said that each orientation is equally acceptable mathematically. But different factorial theories proved to differ as much in terms of the orientations of factorial axes for a given solution as in terms of anything else, so that fitting model did not prove to be useful in distinguishing among theories. In other words, one’s data collection would have to be perfect and unbiased, which will probably never happen. It is believed that Factor Analysis is a tool that could be applied to the study of behaviour and might yield results with an objectivity and reliability rivalling those of the physical sciences. Interpreting Factor Analysis is based on using a ‘heuristic’, which is a solution that is ‘convenient even if not absolutely true’ (Darlington, 2008). More than one interpretation can be made of the same data factored the same way. Table 2.5 also explained that Factor Analysis is much suitable for observed, multivariate analysis. By methodology, the criteria of Malaysia green highway assessment can be predefined by literature review from various studies around the world. The criteria will go through further revision with professionals in highway by reviewing suitability of the short-listed criteria with the Malaysia environment.
2.5.2
Optional Statistical Method
Decision making is a kind of process to produce a final output that can be an action or opinion. It can be referred to as a problem solving activity which will be terminated once a satisfactory solution is achieved. This yields the idea of establishment of multi-criteria decision analysis (MCDA). The MCDA is also known as multi-criteria decision-making (MCDM) and involves varieties of methods, a few salient ones are listed as follows (Wikipedia, 2012).
22
1.
Aggregated Indices Randomization Method (AIRM)
2.
Analytic hierarchy process (AHP)
3.
Analytic network process (ANP)
4.
Data envelopment analysis
5.
Decision Expert (DEX)
6.
Dominance-based rough set approach (DRSA)
7.
The evidential reasoning approach (ER)
8.
Goal programming
9.
Grey relational analysis (GRA)
10.
Inner product of vectors (IPV)
11.
Measuring Attractiveness by Categorical Based Evaluation Technique (MACBETH)
12.
Disaggregation – Aggregation Approaches (UTA, UTAII, UTADIS)
13.
Multi-Attribute Global Inference of Quality (MAGIQ)
14.
Multi-attribute utility theory (MAUT)
15.
Multi-attribute value theory (MAVT)
16.
New Approach to Appraisal (NATA)
17.
Nonstructural Fuzzy Decision Support System (NSFDSS)
18.
Potentially all pairwise rankings of all possible alternatives (PAPRIKA)
19.
PROMETHEE (Outranking)
20.
Superiority and inferiority ranking method (SIR method)
21.
Technique for Order of Prioritization by Similarity to Ideal Solution (TOPSIS)
22.
Value analysis (VA)
23.
Value engineering (VE)
24.
The VIKOR method
25.
Fuzzy VIKOR
26.
Weighted product model (WPM)
27.
Weighted sum model (WSM)
23
According to Baker et al. (2001), decision-making should start with the identification of the decision maker(s) and stakeholder(s) in the decision, reducing the possible disagreement about problem definition, requirements, goals and criteria. Then, a general decision-making of green highway assessment process can be divided into the following steps:
1. Step 1. Define the problem 2. Step 2. Determine requirements 3. Step 3. Establish goals 4. Step 4. Identify alternatives 5. Step 5. Define criteria 6. Step 6. Select a decision making tool 7. Step 7. Evaluate alternatives against criteria 8. Step 8. Validate solutions against problem statement
The various decision methodologies are differentiated by the way they determine the objective and alternative weights, as prescribed by each one’s axiomatic or rule-based structure. Among these decision-making methods, the AHP and ANP emerge as the most well-known models in the area of decision making with multiple objectives (Alkahtani, 2003). Table 2.6 shows a brief comparison between some statistical decision making methods. Analytic Hierarchy Process (AHP) and Analytic Network Process (ANP) are chosen to be compared since both of them are widely used globally. This table also gives a brief understanding of Multi-Attribute Utility Theory (MAUT), a moderately used method and Potentially All Pairwise Rankings of All Possible Alternatives (PAPRIKA), which is not very popular decision-making method.
24
definition
ANP An evolution of AHP through the introduction of the concepts of interdependence and feedback into the model
conflict resolution environmental applications general resource allocation & optimization group decision making
to identify two best football teams in US to play in a national championship
uses a unidirectional hierarchical relationship among decision elements in problem modelling
addition to network of criteria and sub criteria that control the interactions network of influences of elements allows one to include all the factors and criteria, tangible and intangible, which influence on the decision making process. It considers interdependencies among the criteria and strict hierarchy need not be followed is able to represent problems in which the importance of the alternatives may in turn modify the importance attributed to the criteria (Saaty, 2003) allows more complex interrelationships among decision elements to be studied
advantages
method
AHP express general decision operation by decomposing a complicated problem into a multilevel hierarchical structure of objective, criteria and alternatives (Sharma et al., 2008)
example
Table 2.6: Comparison between Various Statistical Decision Making Methods
straightforward and convenient to be applied in data processing offers simplicity and versatility in comparing variables using pair-wise comparison simple, practical and handy tool in analysing the data. o help to digest since one-to-one qualitative and quantitative comparison is clear can be combined with other decision-making tools like SWOT analysis to generate better result accepted and widely being used by various organization, enterprises and country all over world
PAPRIKA coupled with conjoint analysis, is that by using the principle of transitivity, people can run through the trade-offs between competing goals, visions, measures, desires referring patients for rheumatology, nephrology, geriatrics and gastroenterology services in Canada specifically applies to additive multiattribute value models with performance categories least cognitively demanding proponents claim that reliability and validity of the choices captured in this method is higher than with other methods
MAUT a structured methodology designed to handle the tradeoffs among multiple objectives
A Case Study of the US Conservation Reserve Program A Study of Alternative Locations for a New Airport in Mexico City in Early 1970s deals with choosing among a set of alternatives which are described in terms of their attributes (Ncube,2002) help improve repeatability, transparency, auditability and robustness of natural resource project and program evaluations can take uncertainty into account and represent it directly into its decision support model provides a practical solution to multiattribute decision problems, mimics natural decision making process, provides a structured analytic framework, allows a broad range of information, both quantitative and qualitative
25
disadvantages
Table 2.6: Comparison of Various Statistical Decision Making Methods (cont’d) needs subjective evaluations o the need of conversions from verbal to numeric scale, o inconsistencies imposed by 1 to 9 scale o the conflict between decision maker and the decision maker capacity
2.6
involved judgments are made explicitly the value information can be used in many ways to help clarify a decision process a decision maker, typically learns a great deal through these joint efforts to construct their views
a snapshot in time. no guarantee for same thing to happen again principle of transitivity remains untested in this type of frame variables (>10) and alternatives are included, process becomes unwieldy and complex
very difficult to apply and no real applications are known (M Bertoni et. al, 2011) high degree of respondent interaction required in the development of utility between objectives
Summary
The development of a green highway is a wide-ranging field integrating stewardship, safety, and sustainability into the planning, design, construction, and maintenance of transportation infrastructure (Initiative, 2010). A highway has to be assessed to determine its greenness and compliance with the sustainable principle. Various assessment, rating and ranking methods of green highway have been established and implemented around the world such as Greenroads, I-LAST and GreenLITES (Clevenger, Ozbek and Simpsons, 2013). The understanding of the fundamentals and the practicability of green highway is a must in order to achieve its sustainable goal. Green assessment tools for highway in Malaysia need to be developed in order to evaluate the local highway performance, as well as to ensure the aim of green highway is achievable and in-line with local needs. A great deal of effort needs to be put in by all parties involved in highway construction like Malaysia Highway Authority, contractors, concessionaires and even the end-user. To establish the Malaysia Green Highway Assessment model therefore, selection elements or criteria that meet with local needs should be focused. Here in the next chapter the discussion is based on how the elements and criteria for Malaysia Green Highway Assessment can be carefully chosen using statistical approach on weightage analysis.
CHAPTER 3
RESEARCH METHODOLOGY
3.0
Introduction
This chapter discusses the methods used or applied in conducting this research. A methodology is a way or approach adopted in order to achieve the research objectives through data collection and analysis. Thus, the methodology chosen must be able to fulfil the needs of the research, which are the set of data needed and a method of analysing it. Several methods are applied to achieve the objectives of this research by obtaining as much required information to establish green highway factor weight analysis of green highway elements.
3.1
Research Design and Procedure
The phased methods were used to initiate a proper guideline and to meet the research objectives, which are:
Phase 1 – Green Highway Review
Phase 2 – Expert Discussion
Phase 3 – Questionnaire Survey
Phase 4 – Factor Score Calculation
Phase 5 – Weightage Factor Calculation
27
3.1.1
Phase 1 – Green Highway Review
Literature Review discusses published information in a particular subject area, and sometimes information in a particular subject area within a certain period. A literature review presents a simple summary of the sources and usually has an organizational pattern and combines both summary and synthesis. A summary is a recap of the important information of the source, while synthesis is a re-organization, or a reshuffling, of that information. For this research, the literature review is done by doing content analysis on several criteria and elements of green highway from a number of previous green highway assessment models and rating systems. It is significant to select the appropriate green highway assessment criteria, which are relevant to the Malaysia highway infrastructure.
3.1.2
Phase 2 – Expert Discussion
Groups of experts in the areas are encouraged to discuss various issues related to the project base on green highway. They are also encouraged to review the proposed green highway criteria to achieve a consensus before the weightage factor for green highway criteria being designed. For this particular research, a pre-expert discussion was conducted in UTM among 16 researchers and 5 group moderators including lecturers. Subsequently a workshop, namely Expert Discussion was held in Malacca on April 2nd, 2012. Among the 60 participants involved were related Government bodies led by Malaysia Highway Authority (LLM), concessionaires, consultants and contractors. This workshop discussed the preliminary studies of Malaysia Green Highway elements from various Green Highway assessments, within the respective 5 main criteria identified earlier which are Sustainable Design and Construction Activities (SDCA), Energy Efficiency (EE), Material and Technology (MT), Environmental and Water Management (EWM), and Social and Safety (SS).
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A set of standardised questionnaires was drafted at the end of the workshop and this questionnaire survey form was used during data collection. This questionnaire column is grouped by L1 – criteria, L2 – sub criteria, L3 – element descriptions. L1 (criteria) and L2 (sub criteria) contents were shortlisted of common criteria from previous assessment, rating or initiatives. A pre-expert discussion done earlier also added some additional contents for both criteria and sub-criteria to suit with local needs. For L3 (element descriptions), the contents were filled during 1st expert discussion in Malacca, with series of parallel discussions among groups were held afterwards to achieve a most comprehensive questionnaire template. Table 3.1 shows the template for questionnaire design.
Table 3.1 Template for Questionnaire Design
element description
economy
job opportunity
number of job created during project life
*
The complete table is attached in Appendix C1
3.1.3
Phase 3 – Questionnaire Survey
5
strongly agree suggestion if disagree
sub- criteria
strongly disagree
ID
criteria
SS1
1
L4 agreement level 2 3 4 agree
Variables L3
moderate
L2
disagree
Factors L1
√
Questionnaires are designed to gather either qualitative or quantitative data; however, designing qualitative questions demands much more care, administration and interpretation. Generally, it requires more considerations from the participant, whereas quantitative questions are more exact if compared to qualitative questions. Questionnaire was used in this research to elicit information. A few careful steps needed to be taken in order to design a questionnaire for this study purpose. Initially, the objectives of the survey were defined. After that, the sampling group of respondents was determined. Then, the questionnaire was designed and administered.
29
Respondents were requested to tick in the appropriate box provided alongside each statement to indicate whether they Strongly Disagree, Disagree, Moderate, Agree or Strongly Agree during the survey sessions. The questionnaire survey forms were filled alongside the explanation from respective researchers for each main criterion. The criteria from questionnaire template were verified by respondents, if they were satisfied with the tabulation and grouping of variables cluster according to respective level which were L1 – Criteria of Green Highway (ID), L2 – Sub-Criteria for Green Highway, L3 – Criteria Descriptions and L4 – Level of Agreement. The respondents were also encouraged to give suggestion for those elements they were disagreeing with, or with inserting points in the survey form if they have additional information to be put in.
The questionnaires were distributed to the targeted 170 respondents, which consisted of experts in highway construction industry, especially those who were involved in the development of green highway, from July 9th, 2012 until July 18th, 2012. These respondents were selected randomly from the identified list from Malaysia Highway Authority (LLM). The completed list of respondents and full template of questionnaire survey are attached in the Appendix C1. The survey was conducted by face-to-face interview with the respondents in order to help them to fill the questionnaire survey form based on their expertise. Researchers managed to collect 140 out of total targeted respondents at the end of the data collection. Another 30 respondents’ survey forms could not be considered into data analysis since some of the respondents chose to answer according to their expertise only. Finally, the results of the survey were collected and analysed using computer software.
30
3.1.4
Phase 4 – Factor Score Calculation
The findings from the questionnaire survey were analysed to produce significant number of factors and elements, as well as the value for Factor Score of the proposed Malaysia Green Highway Assessment. The calculations of Factor Score are described in details at Chapter 3.4.3.1. The establishment and confirmation of score point were discussed during 2nd expert discussion which was conducted on October 18, 2012.
3.1.5
Phase 5 – Weightage Factor Calculation
Weightage factor calculation was done using the score point calculated in Phase 4 – Factor Score Calculation. By using formulae listed in 3.4.3.3, the weightage factor for main criteria, criteria, sub criteria, and elements descriptions could be computed.
3.2
Instrumentation Microsoft Excel 2010 and Statistical Package for the Social Science (SPSS
version 18.0) were used to analyse the data for this research. The SPSS is one of the most widely available and powerful statistical software packages used by social scientists. Moreover, SPSS is an effective data management tool, with wide range of options and produce better output organization (Karp, 1995 and Sweet, 1999).
31
3.3
Operational Framework The flowchart of research methodology and operational framework for this
Methodology
Literature Review
research is shown in Figure 3.1.
Problem Identification
Sustainable Principle Preliminary Guide for Green Highway Sustainability in Highway Construction
Review on Highway Construction Development
Phase 1 – Green Highway Review Review on previous and current green highway rating/framework L1 – Criteria of Green Highway (proposed from literature review)
Highway Development & Sustainable Construction Previous & current highway planning Green Highway Elements and Criteria
Phase 2 – Expert Discussion Confirmation/discussion on:
L2 – Sub-Criteria for Green Highway L3 – Criteria Descriptions
Phase 3 – Questionnaire Survey L4 – Level of Agreement
Data Analysis
i.
Parametric/ Nonparametric
ii. Missing Value Analysis iii. Mean Value Analysis
Result
iv. Factor Analysis
Phase 4 - Factor Score Calculation
Phase 5 - Weightage Factor Calculation
Figure 3.1: Operational Framework
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3.4
Data Analysis Procedures
This is the stage where all the data obtained were processed and analysed, and the findings from this analysis were evaluated, discussed, validated and summarized. Several analyses were done before the weightage factor for Malaysia Green Highway Assessment could be achieved.
3.4.1
Data Types Analysis
Primarily, the data is needed to be justified of what types of data are being collected along the way, whether it is parametric statistic or non-parametric statistic. A parameter is a number computed from a population. A parameter is a constant, unchanging value. There is no random variation in a parameter. If the size of the population is large, a parameter will be difficult or even impossible to be computed.
This is an example of parametric statistic since there is a reference variables for the last year to be an assumption, even though there are no specific parameters mentioned and their independence; “Mel’s Diner has been surveying their customers for the past couple of years about their dining experience in the restaurant. The survey uses a scale of one to five, five being best to indicate customer satisfaction. Mel’s customer satisfaction averaged 2.5 last year, but this year it is 2.9. Is this difference statistically significant?”
This is an example of Non-parametric statistic since there is no such assumption being made earlier. “From a written survey where the respondents were asked to rate an individual on a scale of 1 to 5, one group rated an individual a 3.7, another group rated the individual a 4.3. Is the difference statistically significant?”
To give more understanding on this matter, David Sheskin (2004) and Elise Whitley and Jonathan Ball (2002) listed some differences between Parametric and Non-Parametric Statistic as shown in Table 3.2.
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Table 3.2: Differences between Parametric and Non-Parametric Statistic definition example
assumption
advantages
Parametric data can be measured heights weight depth amount of money normality equal variances independence (interval scale) (Eachus, 2000) if assumption is correct,
produce more accurate & precise estimates. said to have more statistical power
disadvantages
if the assumption is incorrect, can be very misleading; they are often not considered robust
Non-parametric data does not rely on parameters qualitative data like: comparing two different colours evaluating customer feedback measuring the benefit of internet no assumption # nonparametric methods were developed to be used in cases when the researcher knows nothing about the parameters of variable of interesting population (Varon, 2010) statements are exact probabilities, regardless of shape of population distribution from which random sample was drawn if sample sizes as small as n=6, there is no alternative to use a nonparametric test treat samples made up of observations from several different populations data inherently in ranks as well as data whose seemingly numerical scores have strength in ranks available to treat classificatory data easier to learn and apply losing precision/ wasteful of data low power false sense of security lack of software testing distributions only higher-ordered interactions
For this particular research, one of the examples of parametric data is when the experts were asked to finalize the questionnaire survey form template. They were influenced by the limitations of the concept of sustainable and highway development criteria when choosing which of the variables to be put in, this constrains can be called as parameter. The example of nonparametric data is when the respondents were asked to rate an individual scale for ‘provide buffer zone’ from 1 to 5. Respondent A rates the score as 1, while Respondent B and C rated rank score of 4 and 2 respectively. There were no such inter-rater agreements among independent respondents when giving the rank even though they ranked the same questionnaire section.
34
Table 3.3 shows list of tests involved when dealing with Parametric Statistics and Nonparametric Statistic as studied by Mumby in 2002. Table 3.3: Test of Parametric and Nonparametric Statistics
Independent
statistics 2 samples multiple groups
parametric t-test for independent samples analysis of variance (ANOVA)
Nonparametric Wald-Wolfowitz Mann-Whitney U Kolmogorov-Smirnov 2 Sample Kruskal-Wallis Analysis of Ranks Median Test
dependent
groups
Sign Test Wilcoxon’s Matched Pairs Test 2 variables t-test for variables are in same dependent dichotomous in nature McNemar’s Chisample samples (i.e., “pass” vs. “no square pass”) Friedman’s 2-Way Analysis of Variance more than 2 repeated variables in measures changes in frequencies Cochran Q same sample ANOVA across time Spearman R standard correlation Kendall Tau coefficient Coefficient Gamma variables are Chi Square relationships between correlation categorical in nature Phi Coefficient variables coefficient (i.e., "male" vs. "no Fisher Exact Test female") inter-rater agreement Kendall among independent Coefficient of judges who are rating Concordance* (ranking) same stimuli * Concordance: a measurement of the agreement between two variables
The following Table 3.4 shows the factors when considering the test of statistical data in details. Nonparametric tests are also referred to as distribution-free tests. They compare medians rather than means and, as a result, if the data have one or two outliers, their influence is neglected. There is at least one nonparametric test equivalent to a parametric test. These tests fall into several categories, which are the tests of differences between groups (independent samples), tests of differences between variables (dependent samples), and the tests of relationships between variables.
35
Table 3.4: Selecting a Statistical Test in Details
Goal
describe one group compare one group to a hypothetical value compare two unpaired groups
Measurement (from Gaussian Population)
Mean, SD
Type of Data Rank, Score, or Measurement (from NonGaussian Population) Median, interquartile range
Binomial
Proportion
One-sample test
Wilcoxon test
Chi-square or Binomial test
Unpaired t test
Mann-Whitney test
Fisher's test (chi-square for large samples)
Survival Time
Kaplan Meier survival curve
Log-rank test or MantelHaenszel Conditional proportional hazards regression Cox proportional hazard regression Conditional proportional hazards regression
compare two paired groups
Paired t test
Wilcoxon test
McNemar's test
compare three or more unmatched groups
One-way ANOVA
Kruskal-Wallis test
Chi-square test
compare three or more matched groups
Repeatedmeasures ANOVA
Friedman test
Cochrane Q
quantify association between two variables
Pearson correlation
Spearman correlation
Contingency coefficients
Nonparametric regression
Simple logistic regression
Cox proportional hazard regression
Multiple logistic regression
Cox proportional hazard regression
predict value from another measured variable predict value from several measured or binomial variables
Simple linear regression or Nonlinear regression Multiple linear regression or Multiple nonlinear regression
36
3.4.2
Missing Value Analysis using Statistical Package for Social Science
Missing Values Analysis was done to check, replace and rearrange the data using appropriate value set in SPSS. Initially, variables were determined to be group as quantitative or categorical set as shown in Figure 3.2. The scale variables were selected into quantitative variables’ box for estimating statistics and optionally imputing missing values. Same was applicable on numeric or string variables which were put in the categorical variables’ box.
Figure 3.2: Determining the Type of Variables
Then, the variables were sorted by missing value pattern. Each case with a missing value was tabulated for each analysis variable as shown in Figure 3.3.
37
Figure 3.3: Missing Value Analysis Patterns
After that, by choosing the descriptives, univariate statistics helped to identify the general extent of missing data as shown in figure 3.4. For each variable, the number of nonmissing values and number or percentage of missing values were displayed. For quantitative (scale) variables, mean value, standard deviation and also the number of extremely high and low values could also be displayed.
Figure 3.4: Descriptive Missing Value Analyses
38
3.4.3
Mean Value Analysis using Statistical Package for Social Science
Next, Mean Value Analysis (MVA) was done by eliminating non-significant elements having mean value ≥ 3.50 (Majid and Mccaffer, 1997). MVA is done by computing an average of n numbers of computed by adding the numbers of agreement level value and dividing by n numbers of respondents. For example, respondent A chose 2, respondent B chose 3 and respondent C chose 1 for ‘number of job created during the project life’. The mean value for this particular element description can be computed by adding 2, 3 and 1 to yield 6 in total. When 6 are divided by 3 respondents, there we can have 2 in mean value. This number is less than average index value of 3.50 and should be neglected.
3.4.4
Factor Analysis using Statistical Package for Social Science
Factor Analysis is a method to identify underlying variables, or factors, that explain the pattern of correlations within a set of observed variables. Factor Analysis was chosen because it has always been used in data reduction to identify a small number of factors that explain most of the variance observed in a much larger number of manifest variables. Factor Analysis can also be used to generate hypotheses regarding causal mechanisms or to screen variables for subsequent analysis, for example, to identify co-linearity prior to performing a linear regression analysis. Factor Analysis helps to reduce large number of variables in the criteria for Malaysia Green Highway Assessment to such a number that is easy to analyse but explains most of their variances. The key points in Factor Analysis can be simplified as follows:
Factor Analysis is a data reduction tool
Removes redundancy or duplication from a set of correlated variables
Represents correlated variables with a smaller set of ‘derived’ variables
Factors are formed that are relatively independent of one another
Two types of ‘variables’ are study; latent (factors, F) and observed variables
39
Statistical Package for Social Science or SPSS is software that is embedded with Factor Analysis application in the system. Hence, the usage of SPSS will help to facilitate and to produce the good results in the analysis as discussed in 3.4.4.2. For this particular research, Factor Analysis was used to determine number of factors in main criteria and the group of variables that they fell into. The ‘factors’ refer to ‘criteria’, and ‘variables’ refer to ‘elements description’. The details explanations are discussed in Chapter 4.
3.4.4.1 Fundamental of Factor Analysis
Factor Analysis is a method for investigating whether a number of variables of interest X1, X2, : : :, X3, are linearly related to a smaller number of unobservable factors F1, F2, : : :, Fk . The fact that the factors are not observable disqualifies regression and other methods previously examined. However, under certain conditions the hypothesized factor model has certain implications and these implications in turn can be tested against the observations. Exactly what these conditions and implications are, and how the model can be tested, must be explained with some care. Table 3.5 shows the example of factor set for Social and Safety which consist of relation between variables and the unobservable factors.
Table 3.5: Factors Set for Social and Safety Respondents Contractors Concessions Highway Authority
X1 3 7 10
Criteria for Social and Safety X2 6 3 9
X3 5 3 8
It has been suggested that these ‘Criteria for Social and Safety’ are functions of two underlying factors, F1 and F2, tentatively and rather loosely described as quantitative ability and verbal ability respectively. It is assumed that each X variable is linearly related to the two factors, as shown in Eq.1, Eq.2 and Eq.3.
40 X1 = λ10 + λ11F1 +λ12F2 + e1
Eq. 1
X2 = λ20 + λ21F1 +λ22F2 + e2
Eq. 2
X3 = λ30 + λ31F1 +λ32F2 + e3
Eq. 3
Where,
F is latent (i.e. unobserved, underlying) variable
X’s are observed (i.e. manifest) variables
ej is measurement error for Xj
λj is the “loading” for Xj The error terms e1, e2, and e3, serve to indicate that the hypothesized
relationships are not exact. In the special vocabulary of Factor Analysis, the parameters λij are referred to as loadings. For example, β12 is called the loading of variable SS1 on factor F2. The orthogonal one factor model with classical test theory idea is shown in Eq. 4 and Eq.5. Ideal:
X1= F + e1var (ej) = var (ek), j ≠k X= F + e2 … Xm= F + em
Eq. 4
Reality:
X1= λ1F + e1var (ej) ≠var (ek), j ≠k X2= λ2F + e2 … Xm= λmF + em
Eq. 5
There are a few assumptions made in Factor Analysis model, which can be simplified as in Table 3.6. Mulaik (1972) suggests that in application of Factor Analysis model, there exist some optional assumptions that are also shown in Table 3.6. This means that we will deal with ‘correlations’ versus ‘covariance’. This automatically happens when using correlation in Factor Analysis, so it is not an extra step. Table 3.6: Assumptions in Factor Analysis Model (Mulaik, 1972) Assumptions measurement error has constant variance and is, on average, 0 no association between the factor and measurement error no association between errors factor and observed variables are independent of one another F is “standardized” (think “standard normal”) X’s are standardized
Equation Var(ej) = σj2E(ej) = 0 Cov(F,ej) = 0 Cov(ej,ek) = 0 Cov( Xj,Xk| F ) = 0 Var (F) = 1E (F) = 0
41
On the other hand, another important characteristic of Factor Analysis that should be considered is the method of operation of Factor Analysis. Given the factor and the observed variables are independent of one another, as shown in Eq.6. Cov (Xj, Xk| F) = 0
Eq.6
X’s are only related to each other through their common relationship with F. Figure 3.5 shows the relationship between F, X and e.
Figure 3.5 Relations between F, X and e Notes:
λj2 is also called the “communality” of Xj in the one factor case (notation: hj2)
For standardized Xj, Correlation (F, Xj) = λj
The % variability in (standardized) Xj explained by F is λj2. (like an R2)
If Xj is N(0,1), then λj is equivalent to the slope in a regression of Xj on F or the correlation between F and Xj
Interpretation of λj: o standardized regression coefficient (regression) o path coefficient (path analysis) o Factor Loading (from Factor Analysis)
Correlation (Xj, Xk)= λjλk Note that the correlation between Xj and Xk is completely determined by the
common factor. Recall Covariance (ej,ek) =0. Factor Loadings (λj) are equivalent to correlation between factors and variables when only a single common factor is involved. As summary, Table 3.7 shows various applications of Factor Analysis techniques that made it very suitable for the research (Thompson, 2004. and Basilevsky, 2009).
42
Table 3.7 Applications of Factor Analysis Applications Descriptions underlying factors to cluster variables into homogeneous sets to creates new identification variables (i.e. factors) and to gain insight to categories to identify groupings to select one variable to represent variables screening many and useful in regression (recall co-linearity) summary to describe many variables using a few factors to select small group of variables of representative variables sampling variables from larger set to put objects (or people) into categories depending on objects clustering factor scores
3.4.4.2 Steps in Factor Analysis Operation
Following are the steps taken in exploratory Factor Analysis using SPSS. These principles shall be essential guidelines in forthcoming analysis of green highway criteria and elements before they can be considered as the substances into Malaysia Green Highway Assessment. The steps taken comprise of Data Collection and Exploration, Extraction of Initial Factors, Choosing a Number of Factors to be Retained, Rotation and Interpretation of Factor, Elimination of Data and Constructing a Scale Model. The detailed application of Factor Analysis using SPSS is discussed in Chapter 4.
i.
Data Collection and Exploration
As pre-analysis stage, irrelevant variables should be erased. The total number of variables should not be more than the total number of respondents. If this first principle of conducting Factor Analysis is passed, then several other analyses like Data Validation analysis, Variables’ Relationship Test, Descriptive Analysis and Reliability Test should be conducted.
a. Data Validation Analysis - Critical Chi-Square Values
43
Data Validation analysis is conducted to detect the gross error. Gross error is error that may occur when a measurement process is occasionally subjected to large inaccuracies (Li, Wang, and Yang, 2001). Since the data is nonparametric, ChiSquare Test (Global Test) is selected as the data validation test (Reilly and Carpani, 1963). The chi-square values for each variable are compared with Critical ChiSquare values as shown in Table 3.8. A comparison of the value of the objective function of variables χ²cal with a given percentile Pɑ of the probability density function of a chi-square distribution (χ²cri) is presented in Table 3.8, (e.g. the 95th percentile for a 95% confidence) gives an indication of whether a gross error exists: If χ²cal ≤ P95, then no gross errors exist with 95% probability. Table 3.8: Critical Chi-Square Values Critical Chi-Square Values Left Tail
Right Tail
Degrees Freedom
0.50%
1%
2.50%
5%
10%
90%
95%
97.50%
99%
99.50%
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 50 100
0.00004 0.01 0.072 0.207 0.412 0.676 0.989 1.34 1.74 2.16 2.6 3.07 3.56 4.07 4.6 5.14 5.7 6.26 6.84 7.43 8.03 8.64 9.26 9.89 10.52 11.16 11.81 12.46 13.12 13.79 27.99 67.33
0.00016 0.02 0.115 0.297 0.554 0.872 1.24 1.65 2.09 2.56 3.05 3.57 4.11 4.66 5.23 5.81 6.41 7.01 7.63 8.26 8.9 9.54 10.2 10.86 11.52 12.2 12.88 13.56 14.26 14.95 29.71 70.06
0.00098 0.051 0.216 0.484 0.831 1.24 1.69 2.18 2.7 3.25 3.82 4.4 5.01 5.63 6.26 6.91 7.56 8.23 8.91 9.59 10.28 10.98 11.69 12.4 13.12 13.84 14.57 15.31 16.05 16.79 32.36 74.22
0.00393 0.103 0.352 0.711 1.145 1.64 2.17 2.73 3.32 3.94 4.58 5.23 5.89 6.57 7.26 7.96 8.67 9.39 10.12 10.85 11.59 12.34 13.09 13.85 14.61 15.38 16.15 16.93 17.71 18.49 34.76 77.93
0.0158 0.211 0.584 1.064 1.61 2.2 2.83 3.49 4.17 4.86 5.58 6.3 7.04 7.79 8.55 9.31 10.08 10.86 11.65 12.44 13.24 14.04 14.85 15.66 16.47 17.29 18.11 18.94 19.77 20.6 37.69 82.36
2.71 4.6 6.25 7.78 9.24 10.64 12.02 13.36 14.68 15.99 17.28 18.55 19.81 21.06 22.31 23.54 24.77 25.99 27.2 28.41 29.62 30.81 32.01 33.2 34.38 35.56 36.74 37.92 39.09 40.26 63.17 118.5
3.84 5.99 7.82 9.49 11.07 12.59 14.07 15.51 16.92 18.31 19.68 21.03 22.36 23.68 25 26.3 27.59 28.87 30.14 31.41 32.67 33.92 35.17 36.42 37.65 38.88 40.11 41.34 42.56 43.77 67.5 124.34
5.02 7.38 9.35 11.14 12.83 14.45 16.01 17.54 19.02 20.48 21.92 23.34 24.74 26.12 27.49 28.84 30.19 31.53 32.85 34.17 35.48 36.78 38.08 39.36 40.65 41.92 43.2 44.46 45.72 46.98 71.42 129.56
6.64 9.21 11.34 13.28 15.09 16.81 18.48 20.09 21.67 23.21 24.72 26.22 27.69 29.14 30.58 32 33.41 34.8 36.19 37.57 38.93 40.29 41.64 42.98 44.31 45.64 46.96 48.28 49.59 50.89 76.15 135.81
7.88 10.6 12.84 14.86 16.75 18.55 20.28 21.96 23.59 25.19 26.76 28.3 29.82 31.32 32.8 34.27 35.72 37.16 38.58 40 41.4 42.8 44.18 45.56 46.93 48.29 49.64 50.99 52.34 53.67 79.49 140.17
44 b. Variables’ Relationship Test-Kendall Coefficient of Concordance
Kendall Coefficient of Concordance (known as Kendall’s W) in SPSS 18.0, is a strength-of-relationship index test. The range of coefficient of concordance is from 0 to 1, with higher values indicate a stronger relationship. Figure 3.6 shows the sequence involved when conducting the test.
(i)
(ii) (iii) Figure 3.6: Variable Relationship Test
45
c. Descriptive Analysis-KMO and Bartlett's Test
The descriptive analysis is initiated in order to check the suitability of Factor Analysis to the data set. For this purpose, KMO and Bartlett's Test can be used to check the suitability of Factor Analysis for large data set. The KMO ranges should be in range from 0-1 with higher values indicating greater suitability, a value greater than 0.750 is much better. For Bartlett Test, each variable correlates perfectly with itself if r=1 but has no correlation with the other variables if r=0. The statistical significance value should be less than value significance level α = 0.001 (0.1%). Figure 3.7 shows the sequence of descriptive analysis steps.
(i)
(ii)
Figure 3.7 Descriptive Analysis
46 d. Reliability Analysis - Cronbach’s Alpha
Then, reliability test is undertaken in the beginning of the section analysis to check the reliability of data; the range is between low and high consistency. If the value of Cronbach’s Alpha below 0.6, it shows that the data has low internal consistency and it is assumed that the understanding level of repondents regarding the questionnaire is very low. Figure 3.8 shows the steps taken in carrying out reliability analysis.
(i)
(ii)
Figure 3.8 Reliabilty Analysis
47
ii.
Extraction of Initial Factors using PCA
There are varieties of extraction methods used in SPSS application¸ including Unweight Least-Squares Method, Generalized Least-Squares Method, MaximumLikelihood Method, Principal Axis Factoring, Alpha Method, Image Factoring and Principal Component Analysis.
Unweight Least-Squares Method is a factor extraction method that minimizes the sum of the squared differences between the observed and reproduced correlation matrices by ignoring the diagonals. Generalized Least-Squares Method is a factor extraction method that minimizes the sum of the squared differences between the observed and reproduced correlation matrices. Correlations are weighted by the inverse of their uniqueness, so that variables with high uniqueness are given less weight than those with low uniqueness (Kim and Mueller, 1978). MaximumLikelihood Method is a factor extraction method that produces parameter estimates that are most likely to have produced the observed correlation matrix if the sample is from a multivariate normal distribution. The correlations are weighted by the inverse of the uniqueness of the variables, and an iterative algorithm is employed.
Principal Axis Factoring is a method of extracting factors from the original correlation matrix, with squared multiple correlation coefficients placed in the diagonal as initial estimates of the communalities. These Factor Loadings are used to estimate new communalities that replace the old communality estimates in the diagonal. Iterations continue until the changes in the communalities from iteration to the next satisfy the convergence criterion for extraction. Alpha Method is a method that considers the variables in the analysis to be a sample from the universe of potential variables. This method maximizes the alpha reliability of the factors. Guttmann develops Image Factoring and it is based on image theory. The common part of the variable, called the partial image, is defined as its linear regression on remaining variables, rather than a function of hypothetical factors.
48
For this particular research, the Principal Component Analysis was used. Principal Components Analysis is a factor extraction method used to form uncorrelated linear combinations of the observed variables. The first component has maximum variance. Successive components elucidate progressively smaller portions of the variance and are all uncorrelated with each other. Principal components analysis is used to obtain the initial factor solution. It can be used when a correlation matrix is singular (Guttman, 1952). Principal components analysis is used to obtain the initial factor solution. It can be used when a correlation matrix is singular.
iii.
Choosing a Number of Factors to be Retained – Scree Plot Test
There are many ways of choosing number of factors to retain, for example by observing eigenvalue having minimum of 1 or, using scree plot test as depicted in Figure 3.9. Cattell in 1966 suggests finding the place where the smooth decrease of eigenvalues appears to level off to the right of the plot. To the right of this point, presumably, the "factorial scree" where "scree" is the geological term referring to the debris, which collects on the lower part of a rocky slope. The total factors can be estimated by observing cumulative number of dots along steep slope until a distinct break towards the gradual trailing of the rest (Oreski and Peharda, 2008). The other ways of determining the number of factors to be extracted are Determination Based on Eigenvalues, A Priori Determination, Determination Based on Percentage of Variance, Determination Based on Split-Half Reliability, Determination Based on Split-Half Reliability, and Determination Based on Significance Tests (Malinowski, 1977).
49
nth factor
Figure 3.9: Scree Plot Test (Cattell, 1966)
iv.
Rotation and Interpretation of Factor
Rotation method allows us to select the method of factor rotation. The available methods are varimax, direct oblimin, quartimax, equamax, and promax. The varimax method is an orthogonal rotation method that minimizes the number of variables that have high loadings on each factor. This method simplifies the interpretation of the factors. Meanwhile, Direct Oblimin is a method for oblique rotation. When delta equals to 0 (the default), solutions are most oblique. As delta becomes more negative, the factors become less oblique. Conversely, Quartimax Method is a rotation method that minimizes the number of factors needed to explain each variable. This method simplifies the interpretation of the observed variables. The Equamax is a combination of the varimax method, which simplifies the factors, and the quartimax method, which simplifies the variables. The number of variables that load highly on a factor and the number of factors needed to explain a variable
50
are minimized. Finally, Promax Rotation as an oblique rotation allows factors to be correlated. This rotation can be calculated more quickly than a direct oblimin rotation, so it is useful for large datasets. varimax, quartimax, and equamax are commonly available orthogonal methods of rotation; direct oblimin, quartimin, and promax are oblique. Orthogonal rotations produce factors that are uncorrelated, oblique methods allow the factors to correlate.
v.
Elimination of Data
The decision should be made, as to drop item(s) or to include the item(s) if changes are needed. The consideration in determining the optimum number of item is done by referring to the principle of factor analysis and requisite stated by SPSS 18.0.
vi.
Constructing a Scale Model
A scale model is constructed so that it can be used in further analysis. The models consist of Factor Loading and the grouping of the respective factors, and will be used in calculating the Factor Score. It can be seen that the terms variables and factors are inconsistently being used from line to line. It is important to note that, the factors refer to a group of variables (criteria), while variables themselves are the elements description within a particular group.
51
3.5
Weightage Factor for the Malaysia Green Highway Assessment
Evaluation can only be made if and approach is available for quantifying what is to be evaluated. It is a need to establish a set of criteria to be measured so that two or more elements can be compared and choices can be made accordingly. The calculation of weightage factor can be done when the factor scores have been achieved.
3.5.1
Calculation of Factor Score
Factor Score evaluates something according to the numerical value assigned to the elements. Factor Score may be used to give a general indication on justifying whether a highway can be considered as green highway or otherwise. Factor Score can be used when evaluation needs to be carried out, especially when a number of elements in green rating need to be compared. In this set of data, Factor Score helps to determine which variable has more weight than another. The establishment and confirmation of score point is discussed during expert discussion. The Factor Scores being used as a reference to calculate the weightage. Calculation of Factor Score, FS can be made by multiplying the mean scores,
with the Factor Loading, FL as shown
in Eq.7 (Dien and Frishkoff, 2005).
FS = x FL
Eq.7
52
3.5.2
Calculation of Weightage factor
Weightage factor is a value that shows a comparison of the importance or influence of each item in the group against each other. The purpose of assigning weightage factor is to help us separate the work by priority. Weight factors are always positive and non-zero in value (Maletta, 2007).
3.5.2.1 Scale Weighting
In a simple random sample, there is only one overall sampling ratio, hence a weightage scale available through the product of all the N/n. This overall scale factor can be represented by v and is defined as in Eq. 8 (Levesque, 2005).
v=N n
Eq. 8
3.5.2.2 Proportional Weighting
In a complex sampling design, like stratified sampling or clustered sampling, the sampling ratio is different. This yields a result in which a part in overall sampling is inaccurate with the proportion of a group. This can be fixed using proportional weights, specifically to each subdivision of the sample for which the sampling ratio is homogenous (Tietjen, 2007). It can be designed as the general form πk=% of stratum in population/ % of stratum in the sample, as shown as Eq.9.
πk = Nk /N nk/n
Eq.9
53 A proportional weight π = 1 if the group represented in the sample appears in total population in the same proportion. Meanwhile, when πk1 whereby the group was under-sampled (the proportion in the sample is smaller than its proportion in the population). Hence, these proportional weights inflate undersampled case, and deflate the over-sampled ones (Maletta, 2007).
3.5.2.3 Mixed or Integrated Weighting
Weighted proportional solely of Eq.9 does not extend the results to the population size. Only the part is restored. Instead, we have seen that only increase in the population scale sampling results by the uniform factor N/n is not correct in the sample (Maletta, 2007). In order to achieve two functions mixed weight can be obtained by multiplying the two:
wk= vπk
Eq. 10
If the scale factor of Eq. 8 multiplied by a factor proportional to Eq. 9, the result is reduced to a simple expression for the ratio of the reciprocal of sampling strata in question, as shown in Eq. 10 (Chen 2002).
wk= Nk /N x N =Nk nk/n n nk
Eq. 11
54
3.5.3
Applying Weightage Factor
In mathematical terms, a factor is any of the numbers multiplied together to form the product of a multiplication problem. Weightage numbers allow us to give more importance to one number over another number. The proportions in overall sample may not match with proportions in population as a result of variety of sampling ratio in complex sampling designs (Sarraf and Chen, 2007). A significant action, like using proportional weights specifically in each division of homogenous sampling ratio, can be designed in general form as Eq. 12. weightage factor ,πk = % of stratum in population % of stratum in the sample
Eq.12
For this particular research, in finding weightage factor for variable, the stratum refers to the Factor Score for elements description and sub-criteria respectively. Following are the amended formula based on Maletta (2007) and Levesque (2005) in determining weightage factor for Malaysia Green Highway Assessment. 3.5.3.1 Applying Weightage Factor Analysis for Elements Description (variables) πelements = % of stratum in variables % of stratum in sub criteria
Eq. 13
3.5.3.2 Applying Weightage Factor Analysis For Sub Criteria πsub criteria = % of stratum in sub criteria % of stratum in criteria
Eq. 14
3.5.3.3 Applying Weightage Factor Analysis For Criteria πcriteria = % of stratum in criteria % of stratum in main criteria
Eq. 15
3.5.3.4 Applying Weightage Factor Analysis For Criteria πmain criteria = % of stratum in main criteria % of all stratum
Eq. 16
55
The followings are few steps taken when establishing weightage factor for green highway assessment. First, a Factor Score is calculated for each element description (variable) by multiplying its mean value with respective Factor Loading. As for example, the Factor Loading, FLed for variable X is equal to 0.876, while the mean value, X is 3.45, hence yielding a Factor Score for variable, FSed which is 3.022 (adjustment to the nearest 3 decimal places). After adding up the Factor Score in the same subcriteria, cumulative of Factor Score for sub-criteria is obtained, FSsc. Then we can change the value of the ratio in terms of percentile,%. The same procedure is repeated to compute the Factor Score for overall criteria, FSc. % of stratum in population
FSed x 100% = %ed = element weight FSsc
Eq. 17
% of stratum in the sample
FSsc x 100% = %sc = sub-criteria weight FSc
Eq. 18
Hence,
πed = %ed %sc
Eq. 19
πsc = %sc %c
Eq. 20
πc = %c %g
Eq. 21
where… FSed FSsc FSc FSg %ed %sc %c %g
= Factor Score for each element = Factor Score for each sub-criteria = Factor Score for each criteria = Factor Score for each main criteria = element weight = sub-criteria weight = criteria weight = main criteria weight
e ample… FSed
= (FLed x X): (0.876 x 3.45) = 3.022 ≈ 3
(FSed / FSsc)
= 3/21 = 0.143 ≈ 14.3%
weightage factor for variable
56
3.6
Research Schedule
Table 3.9 portrays the research schedule for two years project period. Meanwhile, Table 3.10 describes in details the research schedule timeline. As shown in both figures, the research was started at the end of November 2012 and is expected to be finished on November 2013. The research started with the development of problems. At this stage, the concept of sustainable development was internalized and the planning to implement this concept in the construction of a highway was initiated. It was found that green assessments were carried for many buildings out all over the world, but for highway such assessment was yet to be carried out comprehensively. It was also noticed that a few of green highway assessments, either published or still in the development process, were too much focused on the respective local environment.
An initiative has been taken to establish an assessment that suits the Malaysia condition, namely Malaysia Green Highway Assessment. A group of 16 students and 5 lecturers cooperated with the Malaysia Highway Authority, concessionaires, contractors and several other agencies to organise an Expert Discussion in Malacca on April 2nd, 2012. This workshop succeeded in highlighting the importance of this kind of assessment, and came out with the draft of the assessment criteria. To evaluate these criteria, Data Collection took place from 9th July till 18th July 2012 around Selangor, Kuala Lumpur and Johor. 170 respondents were approached to gain their views and justification, 140 of them managed to evaluate the criteria.
On 19th November 2012, another series of Expert Discussion was conducted in Port Dickson. This workshop aimed to give and confirm the weightage for the analysed criteria from Data Analysis. From this workshop, experts and researchers agreed to finalize 133 variables from all 5 main criteria involved, which were Energy Efficiency (EE), Sustainable Design and Construction Activities (SDCA), Material and Technology (MT), Environmental and Water Management (EWM), and Social and Safety (SS), to be put in proposed Malaysia Green Highway Assessment. This weightage factors were hoped to be an essential guideline for this assessment model.
year
Nov
2011 Dec
Jan
Feb
Mac
Apr
May
2012 June
July
Aug
Sep
Oct
Nov
Dec
activity
final submission
3
review
research paper
progress report 2
2
model development
weightage confirmation
data analysis
1
data collection
progress report 1
expert discussion
Stage
literature study
problem development
months
57
Table 3.9: Research Schedule for Two Years Research Period 4
58 Table 3.9 Research Schedule for Two Years Research Period (cont’d) Jan Feb Mac Apr May 2013
June July Aug Sep Oct Nov
Table 3.10 Description of Research Schedule Research Activity Duration (Days) Start Problem development 30 days Fri 25-11-11 Literature study 90 days Fri 06-01-12 Expert discussion 70 days Fri 11-05-12 Research Progress Report 1 10 days Fri 17-08-12 Data collection 60 days Fri 31-08-12 Data analysis 75 days Fri 23-11-12 Weightage confirmation 30 days Fri 08-03-13 Model development 90 days Fri 19-04-13 Research Progress Report 2 10 days Fri 23-08-13 Research paper 45 days Fri 06-09-13 Review 10 days Fri 08-11-13 Final submission 2 days Fri 22-11-13 Milestone and dates: 1-End of 12thmonth (end report writing for phase 1) 2-End of 24thmonth (end report writing for phase 3)
Finish Thu 05-01-12 Thu 10-05-12 Thu 16-08-12 Thu 30-08-12 Thu 22-11-12 Thu 07-03-13 Thu 18-04-13 Thu 22-08-13 Thu 05-09-13 Thu 07-11-13 Thu 21-11-13 Mon 25-11-13
59
Several papers* related to the research have been published and among of them are: i.
Mushairry, M., Rosli, M. Z., Rozana, Z., Mohd Affendi, I., Sani, B. A., Foo, K. S., Ain Naadia, M., Hasrul Haidar, I., Norhaliza, H. & Nurfatimah, M. 2013. Fundamental Elements of Malaysia Green Highway. Applied Mechanics and Materials, 284, 1194-1197.
ii.
Majid, M. Z. A., Zin, R. M., Hainin, M. R., Yaacob, H., Rozana, Z., Mohd Affendi, I., Foo, K. S., Ain Naadia, M., Ainee, F. & Hasrul Haidar, I. 2013. Energy Consumption and Potential Retrofitting of Rest and Service Areas (RSAs) in Malaysia Case Study. Applied Mechanics and Materials, 284, 13111314. * See Appendix B for the list of publications
3.7
Summary
The methodologies used to calculate the weightage for Malaysia Green Highway Assessment are based on conventional methods, which have been practiced around the world. Mean Value Analysis (MVA) has gained great popularity and widely applied especially for isolating parametric data to have smaller numbers of data in which are more relevant (Reiser. 1979). MVA helps to segregate variables in proposed Malaysia Green Highway Assessment model, which contribute most in presenting the relevant variables of green highway. Nevertheless, the integration with new methods used in other research also has been taken into account in order to have more comprehensive outputs. For example, the Factor Analysis helps to reduce the number of insignificant criteria and produce variables with most significance variance. The Factor Analysis also produces the Factor Loading, a solution that explains sufficient variance for all of the shortlisted variables in the analysis. This method previously has been applied by Vikneswaran (2012), Hanley et al (2002) and Mai et al (2000).
CHAPTER 4
DATA ANALYSIS AND RESULTS
4.0
Introduction
The questionnaires were distributed to the respondents to be completed manually. The respondents were the experts in highway construction industry, especially those involved in development of green highway. About 140 respondents, mostly from concessionaires were sampled to have their feedback, response and justification for the proposed template of Malaysia Green Highway Assessment.
4.1
The Analysis
The questionnaires booklet consisted of two parts. The first part was generally to gather the demographic of respondents, which were the type of company, the position in company, education level, working experience, involvement in highway development, level of awareness on green development and respondents’ involvement in green development. The second part of questionnaire was to identify the criteria suitable and appropriate to be considered in the development of Malaysia green highway assessment based on experience, study and practice. The five major main criteria identified in earlier studies with the experts were Energy Efficiency (EE), Sustainable Design and Construction Activities (SDCA), Material and Technology (MT), Environmental and Water Management (EWM) and last but not least Social and Safety (SS).
61
4.1.1 Part I: Demographic of the Respondents
This section reviewed the demographics of the respondents as the type of firms, the position of respondent in respective company, the educational level, working experience, involvement in highway development, level of awareness on green development, as well as involvement in green development.
4.1.1.1 Type of Company
Figure 4.1 and Table 4.1 show the tabulation of respondents’ company background. It can be seen that majority of respondents were highway concessionaires at about 71.4% of total respondents. Highway concessionaires being directly involved in highway development could provide meaningful insight into the issues. The highest percentage of respondents from concessionaire also gives a significant reflection of understanding and awareness among concessionaires as they themselves will implement this green assessment criteria for future highway construction. This was followed by 12.1% of respondents from consultants, 3.6% from government agencies, moreover 11.4% respondents refused to mention their firms’ type, the smallest percentage of respondents was from maintenance and operation firms. Table 4.1: Respondent’s Type of Company TYPE OF COMPANY Concession Consultant Government Maintenance & Operation Unspecified Total
Maintenance & Operation; 1%
FREQUENCY 100 17 5 2 16 140
PER CENT 71.4 12.1 3.6 1.4 11.4 100.0
Unspecified; 11%
Government; 4% Consultant; 12% Concession; 72%
Figure 4.1: Respondent’s Type of Company
62
4.1.1.2 Position in Company Table 4.2 and Figure 4.2 show the position of 140 respondents’ in their respective company. The civil engineers were a majority with 27.9% followed by 25 general managers which contributed 17.9%. Both Head of Engineering and Engineer Manager had 9 respondents each. Six of the respondents did not specify their job title. Another 5 of the respondents were Planning Engineers and 5 were Principle Engineers. Two respondents were from the Department General Manager, Executive Project Engineer, Head Mechanical and Electrical Department, Manager and Senior Executive. Finally, the rest of the job titles had one respondent each. Table 4.2: Respondent's Position in Company POSITION IN COMPANY Assistant Executive Assistant Executive Mechanical and Electrical Assistant Manager Assistant Vice President (Asset) Assistant Vice President (Project Coordinator) Civil Engineer Construction Engineer Corporate Department General Manager Electrical Engineer Engineer Engineer Manager Executive Operation Executive Project Engineer Executive General Manager (Operation) Head Head Mechanical and Electrical Department Head of Department Head of Engineering Head of Infrastructure Head of Mechanical & Electrical Mechanical and Electrical Engineer Manager unknown Operation Manager Planning Engineer Principle Engineer Project Manager Senior Engineer Senior Executive Senior Vice President Technical Assistant Technical Executive Vice President Assistant Executive Assistant Executive Mechanical and Electrical Total
FREQUENCY 1 1 6 1 1 39 1 1 2 1 1 9 1 2 1 25 1 2 1 9 1 1 1 2 6 5 5 1 1 1 2 1 1 1 2 2 1 140
% 0.70 0.70 4.30 0.70 0.70 27.9 0.70 0.70 1.40 0.70 0.70 6.40 0.70 1.40 0.70 17.9 0.70 1.40 0.70 6.40 0.70 0.70 0.70 1.40 4.30 3.60 3.60 0.70 0.70 0.70 1.40 0.70 0.70 0.70 1.40 1.40 0.70 100.0
11 1 1 1
Head
2 Executive
Executive Operation
2
Engineer
11
Department General Manager
11
Construction Engineer
11
Assistant Vice President (Project Coordinator)
Assistant Manager
42 40 38 36 34 32 30 28 26 24 22 20 18 16 14 12 10 8 6 4 2 0 Assistant Executive
111
Figure 4.2: Respondent's Position in Company 22
Assistant Executive Mechanical and Electrical
111 Vice President
2 Technical Assistant
111 Senior Executive
2 Project Manager
6
Planning Engineer
6
unknown
9
Mechanical and Electrical Engineer
1
Head of Infrastructure
2 Head of Department
63
39
25
9 55 1
64
4.1.1.3 Education Level
Table 4.3 and Figure 4.3 show the tabulation of respondents’ educational background. Generally, 77.9% or 109 respondents had bachelor degree, 7.1% (10 respondents) has master degree, while only 0.7% or 1 person accomplished PhD and 14.3% had other qualifications. It can be said that most of the respondents only have bachelor degree. This portrays the respondents were capable of understanding and appreciating the importance of achieving the aim of the research.
Table 4.3: Respondent's Education Level EDUCATION LEVEL FREQUENCY % Bachelor 109 77.9 Master 10 7.10 PhD 1 0.70 others 20 14.3 Total 140 100
others
20
PhD
1
Master
10
Bachelor
109 0
20 40 60 80 100 Figure 4.3: Respondent's Education Level
120
65
4.1.1.4 Working Experience
Figure 4.4 and Table 4.4 portray the respondents’ work experience. The working experience of the respondents is grouped into four categories, which are, less than 5 years, 5 to 10 years, 10 to 15 years and more than 15 years. The data revealed that the number of respondents based on working experience was almost equally distributed among the four groups. Forty-one personnel had 5 to 10 years’ experience while the other 37 had 10-15 years. Another 22.1% or 31 of the respondents had more than 15 years of experience and the rest of 22.1% had than 5 years of experience. For this project, it was crucial to have experienced experts so that they could give a good judgement and interpretation to listed criteria since the variables used were mostly from literature review and not from laboratory test. The respondents with years of experience at their back were considered experts and believed to provide valuable feedback regarding green highway.
Table 4.4 Respondent's Working Experience WORKING EXPERIENCE FREQUENCY % Less than 5 yrs. 31 22.1 5 – 10 yrs. 41 29.3 10 – 15 yrs. 37 26.4 More than 15 yrs. 31 22.1 Total 140 100
More than 15 yrs.
31
10 – 15 yrs.
37
5 – 10 yrs.
41
Less than 5 yrs.
31 0
5
10
15
20
25
30
35
Figure 4.4: Respondent's Working Experience
40
45
66
4.1.1.5 Involvement in Highway Development
Table 4.5 and Figure 4.5 show the percentage of respondents involved in highway development in their construction practice. According to the data, 11% of the total respondents (15 persons) were involved in highway development for more than 15 years. Another 22.1% or 31 people had 10 to 15 years of experience while 29.3% (41 respondents) had 5 to 10 years of experience. It can be seen that majority of respondents had less than 5 years of experience.
Table 4.5: Involvement of Respondents in Highway Development INVOLVEMENT IN HIGHWAY DEVELOPMENT FREQUENCY % Less than 5 yrs. 53 37.9 5 – 10 yrs. 41 29.3 10 – 15 yrs. 31 22.1 More than 15 yrs. 15 10.7 Total 140 100
11%
38% 22%
Less than 5 yrs. 5 – 10 yrs. 10 – 15 yrs. More than 15 yrs.
29%
Figure 4.5: Involvements of Respondents in Highway Development
67
4.1.1.6 Level of Awareness on Green Development
The respondents were also asked about the level of their awareness of the green development as shown in Table 4.6 and Figure 4.6. This level of awareness was classified as ‘know nothing’, ‘heard about it’, ‘moderate’ and ‘expert’. Only 0.7% or 1 respondent claimed to be ‘an expert’ in Green Development out of 140 total respondents surveyed. The two highest percentages of the respondents were in the category of ‘moderate’ and ‘heard about it’ at 54.3% or 76 persons and 42.9% or 60 persons, respectively. Interpretation can be made from figure that most of respondents were aware of Green Development since there were only 2% or 3 persons who were unaware of the concept.
Table 4.6: Level of Awareness of Respondents on Green Development AWARENESS ON GREEN DEVELOPMENT FREQUENCY PERCENT Know nothing 3 2.1 Heard about it 60 42.9 Moderate 76 54.3 Expert 1 0.7 Total 140 100
1 3 1% 2%
76 54%
60 43%
Know nothing Heard about it Moderate Expert
Figure 4.6 Level of Awareness of Respondents on Green Development
68
4.1.1.7 Involvement in Green Development
As shown in Table 4.7 and Figure 4.7, the findings of respondents’ involvement in green development are in contrast with their awareness level. As mentioned in the previous section, 4.1.1.6, most of the respondents were aware of green development. But the findings regarding respondents' involvement in green development show that majority of the respondents’ was involvement was for not more than 10 years of experience. This is proven by 52.1% or 73 persons who were never involved in green development, followed by 32.1% or 45 persons who had less than 5 years of involvement. While 15% or 21 persons were involved for 5 to 10 years, only 0.7% or 1 person was involved for more than 10 years. It can be interpreted that the green development is yet to be a main concern for those who are involved in highway construction. Most of respondents stated that they were facing numerous problems, mainly because of the great cost and budget to be allocated in implementing green development for highway construction.
Table 4.7: Involvement of Respondents in Green Development INVOLVEMENT IN GREEN DEVELOPMENT FREQUENCY PERCENT Never 73 52.1 < 5 yrs. 45 32.1 5 – 10 yrs. 21 15 More than 10 yrs. 1 0.7 Total 140 100 1% 15% Never < 5 yrs 52% 32%
5 – 10 yrs More than 10yrs
Figure 4.7: Involvements of Respondents in Green Development
69
4.1.2 Part II: Criteria and Elements of Malaysia Green Highway Assessment
Initially, the data was predetermined whether they can be clustered as parametric or nonparametric data. One of the examples of parametric data is when the experts were asked to finalize the questionnaire survey form template. They were influenced by the limitations of the concept of sustainable highway development criteria when choosing which of the variables to be put in; this constrains can be called as parameter. The example of nonparametric data is when the respondents were asked to rate an individual scale to ‘provide buffer zone’ from 1 to 5. Respondent A rates the score as 1, while Respondent B and C rate rank score of 4 and 2, respectively. There were no such inter-rater agreements among independent respondents when giving the rank even if they rank the same questionnaire section. These findings helped to determine the future statistical test that suits with the data.
4.1.2.1 Missing Value Analysis using Statistical Package for Social Science
Afterwards, the missing values analysis was done to check, replace and rearrange the data using appropriate value set in SPSS 18.0. Following are the example of Missing Value Analysis on 13 variables in Material and Technology group. Table 4.8 shows the number of missing data in the original raw data of Material and Technology found from questionnaires. Meanwhile, table 4.9 presents output of replacing missing values using ‘series mean’ in SPSS. The final mean of material and technology that underwent Factor Analysis is depicted in table 4.10. These tables are the result of Missing Value Analysis using SPSS as discussed in Chapter 3.
70
Table 4.8: Original Raw Data of Material and Technology (N=140) No. 1 2 3 4 5 6 7 8 9 10 11 12 13
Missing Count Per cent 37 26.4 34 24.3 33 23.6 36 25.7 37 26.4 36 25.7 35 25.0 38 27.1 39 27.9 40 28.6 40 28.6 34 24.3 31 22.1
Element Description reuse top soil reuse and recycle of non-hazardous material reuse and recycle of industrial by-products recycle material for subgrade improvement/soil stabilization usage of local material earthwork balance long lasting pavement design life reflectance of sunlight energy (ALBEDO and SRI) usage of RAP and RCM storm water runoff quality and flow water control reduction of noise level soil biotechnical engineering treatment green techniques
Table 4.9: Replaced Missing Values (N=140) No. 2 3 4 5 6 7 8 9 10 11 12 13
Result Variables Result Variable reuse and recycle of non-hazardous material reuse and recycle of industrial by-products recycle material for subgrade improvement/soil stabilization usage of local material earthwork balance long lasting pavement design life reflectance of sunlight energy (ALBEDO and SRI) usage of RAP and RCM storm water runoff quality and flow water control reduction of noise level soil biotechnical engineering treatment green techniques
N of Replaced Missing Values 34 33 36 37 36 35 38 39 40 40 34 31
Table 4.10: Final Mean of Material and Technology (N=140) No. 1 2 3 4 5 6 7 8 9 10 11 12 13
Descriptive Statistics Element Description reuse top soil reuse and recycle of non-hazardous material reuse and recycle of industrial by-products recycle material for subgrade improvement/soil stabilization usage of local material earthwork balance long lasting pavement design life reflectance of sunlight energy (ALBEDO and SRI) usage of RAP and RCM storm water runoff quality and flow water control reduction of noise level soil biotechnical engineering treatment green techniques
Min 2.00 2.00 2.00 1.00 0.00 2.00 1.00 1.00 1.00 1.00 2.00 2.00 2.00
Max 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00 5.00
Mean Std. Deviation 3.9320 .76113 3.7453 .62400 3.6168 .65310 3.6058 .70372 3.7864 .79251 3.9231 .68585 3.9619 .79498 3.5000 .64317 3.7030 .65200 3.7100 .61510 3.7200 .55074 3.8113 .63601 3.9358 .61487
71
4.1.2.2 Mean Value Analysis using Statistical Package for Social Science
Next, Mean Value Analysis (MVA) was done based on the mean data from Missing Value Analysis. Only 133 out of 218 variables from all five main criteria were analysed to have mean value greater or equal to average index of 3.50 and was considered in Factor Analysis. The new tables for every main criterion were formed after eliminating non-significant elements.
i.
Mean Value Analysis for Sustainable Design and Construction Activities Table 4.11 shows the comparison between mean value for Sustainable Design
and Construction Activities (SDCA). There are 3 variables which provided Noise Mitigation Plan, water pollution control measures on site, however, reduce undeveloped land was eliminated from analysis since its mean value was lower than average index of 3.50. In other words, out of 29 variables identified earlier, only 26 variables were taken into consideration in Malaysia Green Highway Assessment as shown in Figure 4.8. The final template for SDCA can be described as presented in Table 4.12. Table 4.11: Mean of Sustainable Design and Construction Activities ELEMENT DESCRIPTION provide CWMP method of waste minimization waste disposal site recycling plan GHG emission reduction dust control noise mitigation technique use alternative construction methods operate stationary equipment use efficiency method water tracking system provide erosion and sedimentation control plan use efficient method of erosion and sedimentation control fossil fuel reduction equipment emission reduction paving emission reduction quality management system environment training on site contractor warranty site maintenance provide 100ft buffer avoid impact to environment avoid impact to socio-eco adjust highway features utilize visual enhancement reduce urban heat island
NOTATION EDSDCA01 EDSDCA02 EDSDCA03 EDSDCA04 EDSDCA05 EDSDCA06 EDSDCA07 EDSDCA08 EDSDCA09 EDSDCA10 EDSDCA11 EDSDCA12 EDSDCA13 EDSDCA14 EDSDCA15 EDSDCA16 EDSDCA17 EDSDCA18 EDSDCA19 EDSDCA20 EDSDCA21 EDSDCA22 EDSDCA23 EDSDCA24 EDSDCA25 EDSDCA26
MEAN 4.12 4.10 4.17 4.01 3.77 3.90 3.86 3.90 3.72 3.85 3.60 4.15 4.16 3.55 3.62 3.63 4.13 4.20 3.92 4.24 3.68 3.93 3.96 3.86 4.02 4.03
2.50
2.00
1.50
1.00
0.50
0.00 3.86 3.90
EDSDCA08
Activities
3.92
Figure 4.8 Mean and Average Index of Sustainable Design and Construction 4.02 4.03
EDSDCA25
EDSDCA26
3.86
3.96
EDSDCA23
EDSDCA24
3.93
EDSDCA22
EDSDCA21
4.24
4.20
4.13
4.50
EDSDCA20
EDSDCA19
EDSDCA18
3.68
3.63
EDSDCA16
EDSDCA17
3.62
EDSDCA15
3.55
4.16
EDSDCA14
4.15
EDSDCA13
3.60
3.85
EDSDCA12
EDSDCA11
EDSDCA10
3.72
3.90
EDSDCA09
4.17 4.01
EDSDCA07
3.77
EDSDCA06
EDSDCA05
EDSDCA04
EDSDCA03
4.10
3.00
EDSDCA02
3.50 4.12
4.00
EDSDCA01
72
5.00
73
Table 4.12: Template for Sustainable Design and Construction Activities
SDCA1
ID
CRITERIA
construction management plan
SUBCRITERIA
waste management
air pollutants
SDCA2 SDCA3
equipment and machineries efficiency
natural source and emission reduction
SDCA4
quality management
management plan and training
SDCA5
context sensitive design
design flexibility
erosion and sedimentation control
erosion and sedimentation plan
alignment selection
environmental impact reduction
SDCA7
noise mitigation control
SDCA6
innovation technique equipment
ELEMENT DESCRIPTION provide construction and demolition waste management plan (CWMP) during construction use efficient method of waste minimization use efficient method of water conservation provide site recycling plan as a part of CWMP during construction use appropriate approach for waste disposal onsite construction equipment’s that reduce emissions of localized air pollutants dust control use water tracking system use alternative construction methods with lownoise or quieter machineries use proper noise mitigation techniques on-site operate stationary equipment 50 ft. from noise sensitive receptor fossil fuel reduction paving emission reduction
MEAN 4.12 4.10 3.85 4.01 4.17 3.77 3.90 3.60 3.90 3.86 3.72 3.55 3.63
equipment emission reduction
3.62
provide site maintenance plan provide quality management system to improve construction quality contractor warranty provide environmental training on-site design to adjust highway features using design flexibility design to utilize visual enhancement design to avoid impact to socio-economic resources provide erosion and sedimentation control plan
4.24
use efficient method of temporary erosion and sediment control design to provide >100 ft. buffer between highway and high quality area design to avoid impacts to environmental resources design to reduce urban ‘heat island’ effect
4.13 3.92 4.20 3.86 4.02 3.96 4.15 4.16 3.68 3.93 4.03
74
ii.
Mean Value Analysis for Material and Technology
Table 4.13 shows the mean value for elements description in Material and Technology (MT). No variables were eliminated from analysis since they had mean value greater than average index of 3.50. All of 13 variables were taken into consideration in Malaysia Green Highway Assessment as shown in Figure 4.9. The final template for Material and Technology can be described as presented in Table 4.14. Table 4.13 Mean of Material and Technology ELEMENT DESCRIPTIONS locally industrial by-products to be reused and recycled in highway construction either in flexible or rigid pavement such as by using steel slag, fly ash, crumb rubber, etc. usage of recycled materials for sub-grade improvement / soil stabilization, if it can be proved that the process will reduce the consumption of virgin materials, cost of project, and will not bring any harm / effect to the road users and environment. any surface of pavement with lighter colour has higher albedo effect, which indicates high reflectance of sunlight from surface pavement whereas darker colour has lower albedo effect, which shows the low reflectance of sunlight from surface pavement. reuse of top soil that has been removed from grading as long as it is noncontaminated soils reused and recycled of non-hazardous materials in design or during highway construction for other base layers, shoulder, drainage, and highway furniture (signage, guardrail, etc.) balancing cut and fill quantities can reduce need for transport usage of local materials in highway project depending on the location of the project site, whenever practical long lasting pavement design life to avoid frequent rehabilitation, thus depending on the Average Daily Traffic (ADT) and types of pavement being constructed use of Reclaimed Asphalt Pavement (RAP) to produce new pavement that can minimize dumping of RAP in landfill, reduce consumption of virgin materials, and protecting the environment either using hot in-place recycling (HIPR) or cold in-place recycling (CIPR) methods. Application of Recycled Concrete Material (RCM) also known as crushed concrete, is a reclaimed PCC pavement material to use as coarse aggregate in aggregate surface courses, granular embankments, stabilized bases, sub-base courses and aggregate in membrane waterproofing and in drainage layers as protection against erosion Low Impact Development storm-water controls must be considered in highway project that construct porous pavement the speed > 80 km/h could contribute noise disruption and range of noise level depends on types of surface pavement utilize soil biotechnical engineering treatments, which is the combination of plant materials and structural elements that can protect slope and control the erosion. for examples, vegetated gabion, vegetated crib wall, etc. implement green techniques to control soil erosion, protect slope and embankment such as turfing, planting native vegetation, hydro seeding, soil-tire vegetation, etc.
NOTATION
MEAN
EDMT01
3.62
EDMT02
3.61
EDMT03
3.50
EDMT04
3.93
EDMT05
3.75
EDMT06
3.92
EDMT07
3.79
EDMT08
3.96
EDMT09
3.70
EDMT10
3.71
EDMT11
3.72
EDMT12
3.81
EDMT13
3.94
2.00
1.50
1.00
0.50
0.00 3.72
EDMT11
Figure 4.9: Mean and Average Index of Material and Technology
EDMT13
3.94
3.81
3.71
EDMT10
EDMT12
3.70
3.96
3.92
3.93
3.79
3.75
EDMT09
EDMT08
EDMT07
EDMT06
EDMT05
3.50
4.00
EDMT04
EDMT03
3.61
2.50
EDMT02
3.00 3.62
3.50
EDMT01
75
ELEMENT DESCRIPTIONS
5.00
4.50
76
MT1
ID
Table 4.14: Template for Material and Technology CRITERIA
innovation technology
SUBCRITERIA reused and recycled industrial byproducts recycled materials for sub-grade improvement / soil stabilization reflectance of sunlight energy (ALBEDO and SRI)
MT2
reuse of top soil reduce, reuse and recycle
reused and recycled of nonhazardous materials earthwork balance usage of local materials
MT3
long lasting pavement design life
economical materials and pavement
usage of Reclaimed Asphalt Pavement (RAP) and Recycled Concrete Material (RCM)
storm-water runoff quality and flow water control improvement reduction of noise level
ELEMENT DESCRIPTIONS locally industrial by-products to be reused and recycled in highway construction either in flexible or rigid pavement such as by using steel slag, fly ash, crumb rubber, etc. usage of recycled materials for sub-grade improvement / soil stabilization, if it can be proved that the process will reduce the consumption of virgin materials, cost of project, and will not bring any harm / effect to the road users and environment. any surface of pavement with lighter colour has higher albedo effect, which indicates high reflectance of sunlight from surface pavement whereas darker colour has lower albedo effect, which shows the low reflectance of sunlight from surface pavement. reuse of top soil that has been removed from grading as long as it’s non-contaminated soils reused and recycled of non-hazardous materials in design or during highway construction for other base layers, shoulder, drainage, and highway furniture (signage, guardrail, etc.) balancing cut and fill quantities can reduce the need for transport of earthen materials usage of local materials in highway project depending on the location of the project site, whenever practical. long lasting pavement design life to avoid frequent rehabilitation, thus depending on the Average Daily Traffic, ADT and types of pavement to be constructed use of Reclaimed Asphalt Pavement (RAP) to produce new pavement that can minimize the dumping of RAP in landfill, reduce consumption of virgin materials, and protecting environment either using hot in-place recycling (HIPR) or cold in-place recycling (CIPR) methods. Application of Recycled Concrete Material (RCM) also known as crushed concrete, is a reclaimed PCC pavement material to use as coarse aggregate in aggregate surface courses, granular embankments, stabilized bases, sub-base courses and aggregate in membrane waterproofing and in drainage layers as protection against erosion
MEAN
3.62
3.61
3.50
3.93
3.75
3.92 3.79
3.96
3.70
Low Impact Development storm-water controls must be considered in any highway project that constructs porous pavement
3.71
the speed more than 80 km/h could contribute noise disruption and the range of noise level depends on the types of surface pavement
3.72
77
MT4
Table 4.14: Template for Material and Technology (cont’d)
green scenery
soil biotechnical engineering treatments implement green technique to control soil erosion
utilize soil biotechnical engineering treatments, which is the combination of plant materials and structural elements that can protect slope and control the erosion. for examples, vegetated gabion, vegetated crib wall, etc. implements green techniques in order to control the soil erosion, protect the slope and embankment such as turfing, planting native vegetation, hydro seeding, soil-tire vegetation, etc.
3.81
3.94
78
iii.
Mean Value Analysis for Environmental and Water Management
Table 4.15 shows the mean value for elements description in Environmental and Water Management (EWM). Only one variable namely “overpass/underpass structure that provides favourable features for animals, human ecosystem connectivity” was eliminated from analysis since the mean value 3.40 is lower than average index of 3.50. In other words, only 29 variables out of 30 variables identified earlier were taken into consideration in Malaysia Green Highway Assessment as shown in Figure 4.10. The final template for Environmental and Water Management is described as in Table 4.16.
Table 4.15: Mean of Environmental and Water Management ELEMENT DESCRIPTION NOTATIONMEAN firm shall meet the requirement of ISO 14001 EDEWM01 3.75 firms shall establish, document, implement, maintain and continually improve an EDEWM02 3.81 EMS for the entire duration of the project reduce runoff quantity during design and construction stage (Malaysia Urban EDEWM03 3.80 Stormwater Management Manual and Malaysia Highway Authority Manual) storm water control facilities (detention or retention) EDEWM04 3.79 determine critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, EDEWM05 3.75 Public Works Department, Department of Irrigation and Drainage) minimize the increase of impervious area due to the project EDEWM06 3.68 conduct LCCA for storm-water impact in design stage EDEWM07 3.60 manage water flow dissipation on road surface during design stage EDEWM08 3.63 drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater EDEWM09 3.73 Management Manual ) detect and eliminate any non-storm water discharges from unpermitted EDEWM10 3.67 sanitary/other residential, commercial/ industrial sources detect non-storm water discharges from unpermitted sanitary or other residential, EDEWM11 3.50 commercial or industrial sources ensure entire waste water treatment (toll plaza, R and S areas, roadway landscape) to comply with local authority requirement level of water quality EDEWM12 3.80 before discharge to natural water bodies (river, lake, bay) - National Water Services Commission, Department of Environment demonstrate, through the use of models, reduction of pollutant loadings to EDEWM13 3.68 adjacent water resources by the use of Best Management Practice instrument to monitor and analyse pollutants in runoff /water bodies EDEWM14 3.77 use of Low Impact Development in Best Management Practice (wet or dry EDEWM15 3.58 swales , sand filters, bio retention) sound erosion and sediments control practices to protect highly erodible soils, EDEWM16 3.56 special provisions for soil erosion control at stream crossing protect materials enter waterway on bridge demolition/ construction EDEWM17 3.59 wetland restoration, reduce the total disturbed cut and fill areas off Right of EDEWM18 3.68 Way to minimum level provide buffer zone (Department of Wildlife and National Parks , Department of EDEWM19 3.67 Environment ) no open burning EDEWM20 3.80 limiting trees cutting within 5 meters off Right of Way each side EDEWM21 3.87
79
Table 4.15: Mean of Environmental and Water Management (con’t) planting trees to replace those cut within Right of Way, planting shrubs/native plants alongside Right of Way avoid irrigative and invasive plants -slope protection as soon as clearing work completed replanting/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments wildlife crossing that allow for safe passage of wildlife roadways/provide road barriers to avoid road kills within sensitive ecosystem; bridge/ culvert use of the natural – bottomed culvert connectivity; mitigation of habitat fragmentation through techniques enhancement of existing wildlife
EDEWM22
3.91
EDEWM23
3.70
EDEWM24
3.86
EDEWM25
3.87
EDEWM26
3.85
EDEWM27 EDEWM28 EDEWM29
3.92 3.73 3.76
ELEMENT DESCRIPTION 5.00
4.00
3.75 3.81 3.80 3.79 3.75 3.68 3.60 3.63 3.73 3.67 3.50 3.80 3.68 3.77 3.58 3.56 3.59 3.68 3.67 3.80 3.87 3.91 3.70 3.86 3.87 3.85 3.92 3.73 3.76
4.50
3.50
3.00
2.50
2.00
1.50
1.00
0.50
EDEWM01 EDEWM02 EDEWM03 EDEWM04 EDEWM05 EDEWM06 EDEWM07 EDEWM08 EDEWM09 EDEWM10 EDEWM11 EDEWM12 EDEWM13 EDEWM14 EDEWM15 EDEWM16 EDEWM17 EDEWM18 EDEWM19 EDEWM20 EDEWM21 EDEWM22 EDEWM23 EDEWM24 EDEWM25 EDEWM26 EDEWM27 EDEWM28 EDEWM29
0.00
Figure 4.10 Mean and Average Index of Environmental and Water Management
80
ID
SUBCRITERIA
environmental management system (EMS)
EMS certification
EWM2
CRITERIA
EWM1
Table 4.16: Template for Environmental and Water Management
storm water runoff quantity
runoff flow control (rate and quantity)
EWM3
disaster cost analysis drainage system (network)
storm water runoff quality
water pollution reduction
ELEMENT DESCRIPTION
MEAN
meet the requirement of ISO 14001 firms shall establish, document, implement, maintain and continually improve an EMS for the entire duration of the project manage water flow dissipation on the road surface during design stage reduce runoff quantity during design and construction stage (Malaysia Urban Stormwater Management Manual and Malaysia Highway Authority Manual) storm water control facilities (detention or retention) determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) minimize the increase of impervious area due to project (Inclusion of “permeable pavement” such as grid pavers if practical) conduct lifecycle cost analysis (LCCA) for storm-water impact in design stage drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) detect and eliminate any non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources detect non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources that enter the Right of Way or flows that ultimately discharge to the Right of Way but which cannot be eliminated ensure entire waste water treatment (toll plaza, R and S areas, roadway landscape) comply with local authority requirement level of water quality before discharge to natural water bodies (river, lake, bay) - National Water Services Commission, Department of Environment demonstrate, through the use of models reduction of pollutant loadings to adjacent water resources using Best Management Practice
3.75 3.81 3.62
3.80
3.79
3.74
3.66 3.60 3.62
3.67
3.49
3.79
3.67
81
EWM3
Table 4.16 Template for Environmental and Water Management (cont’d)
storm water runoff quality
runoff treatment and water bodies protection
EWM4
habitat restoration & protection
ecosystem protection and preservation
site vegetation
tree & plants communities
ecological connectivity
Instrumentation to monitor and analyse pollutants in runoff and water bodies use of Low Impact Development and Best Management Practices (wet or dry swales, sand filters, bio retention, storm water treatment systems, grass channels, buffer zone, use of highly permeable soil, etc.) to address 90% of annual rainfall event to meet regulatory requirements (Malaysia Urban Stormwater Management Manual , Public Works Department, Department of Irrigation and Drainage) erosion and sedimentation control plan: design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control at stream crossings, and staging construction to minimize soil exposure protection from materials entering waterway on bridge demolition and construction wetland restoration, reduce the total disturbed cut and fill areas off Right of Way to minimum level provide buffer zone (Department of Wildlife and National Parks , Department of Environment ) no open burning limiting trees cutting within 5 meters off Right of Way each side planting trees to replace those cut within the Right of Way, planting shrubs and native plants alongside the Right of Way avoid irrigative and invasive plants -slope protection as soon as clearing work completed replant/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments wildlife crossing allow safe passage roadways and provide road barriers to avoid road kills within sensitive ecosystem; bridge and culvert use of the natural – bottomed culvert Mitigation of habitat fragmentation through techniques such as eco-viaducts provide enhancement to existing wildlife
3.76
3.71
3.56
3.59 3.67 3.66 3.79 3.87 3.89 3.71 3.86 3.88 3.85 3.72 3.73 3.76
82
iv.
Mean Value Analysis for Energy Efficiency
Table 4.17 shows the mean values for elements description in Energy Efficiency (EE). Twenty-three variables were eliminated from analysis since they had mean value lower than average index of 3.50. In other words, out of 55 variables identified earlier, only 32 variables were taken into consideration in Malaysia Green Highway Assessment as shown in Figure 4.11. The final template for Energy Efficiency is depicted in Table 4.18.
Table 4.17: Mean of Energy Efficiency ELEMENT DESCRIPTIONS NOTATIONMEAN plan to promote green energy EDEE01 3.51 % utilization of renewable energy EDEE02 3.57 plan for reduced electrical consumption EDEE03 3.63 % operational energy reduction EDEE04 3.62 providing training for Rest and Service Area management staff EDEE05 4.06 updating Rest and Service Area building operation plan EDEE06 3.86 apply Energy Maintenance Plan (EMP) EDEE07 3.63 luminosity of the street light EDEE08 3.52 the lighting for car park EDEE09 3.57 the lighting for landscape EDEE10 3.66 provide signboard to inform drivers to switch off engine EDEE11 3.85 reduced electrical consumption 1 EDEE12 3.75 reduced electrical consumption 2 EDEE13 3.78 lighting zone(internal building) 1 EDEE14 3.74 lighting zone(internal building) 2 EDEE15 3.61 lighting zone(internal building) 3 EDEE16 3.73 electrical sub-metering energy use ≥ 100kVA. EDEE17 3.62 electrical sub-metering lighting and power each floor/tenancy EDEE18 3.64 renewable energy at toll plaza EDEE19 3.59 installation of lighting system with high efficiency type EDEE20 3.53 improvement to toll plaza's major energy- using system to optimize energy EDEE21 3.68 performance develop a commission/on- going commission plan for toll plaza's major energyEDEE22 3.62 using system providing training for toll plaza management staff EDEE23 3.80 updating toll plaza operation plan EDEE24 3.72 unitary air- conditioners EDEE25 3.71 sensor/ automatic control devices EDEE26 3.71 unitary air- conditioners for toll booth EDEE27 3.67 sensor/ automatic control devices for toll booth EDEE28 3.73 emission reduction EDEE29 3.71 reduced electrical consumption EDEE30 3.51 lighting design / illumination levels EDEE31 3.66
EDEE01 EDEE02 EDEE03 EDEE04 EDEE05 EDEE06 EDEE07 EDEE08 EDEE09 EDEE10 EDEE11 EDEE12 EDEE13 EDEE14 EDEE15 EDEE16 EDEE17 EDEE18 EDEE19 EDEE20 EDEE21 EDEE22 EDEE23 EDEE24 EDEE25 EDEE26 EDEE27 EDEE28 EDEE29 EDEE30 EDEE31
3.86
4.00 3.63 3.52 3.57 3.66 3.85 3.75 3.78 3.74 3.61 3.73 3.62 3.64 3.59 3.53 3.68 3.62 3.80 3.72 3.71 3.71 3.67 3.73 3.71 3.51 3.66
3.51 3.57 3.63 3.62 4.06
83
5.00
4.50
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
Figure 4.11: Mean and Average Index of Energy Efficiency
84
ID
Table 4.18: Template for Energy Efficiency CRITERIA
SUB-CRITERIA
EE1
enhanced commissioning / decommissioning of building energy systems
rest & service area (RSAs) reduced electrical consumption
sustainable infrastructures
enhanced commissioning / decommissioning of building energy systems
EE2
toll booth (air quality for indoor environment) toll plaza electrical sub metering
lighting zone
ELEMENT DESCRIPTIONS update Rest and Service Area building operation plan provide training for Rest and Service Area management staff implement improvement to Rest and Service Area building's major energy- using system to optimize energy performance for project designs that reduce electrical consumption beyond typical measures. specifically: solar/battery powered street lighting/warning signs replacement of overhead sign lighting with higher type retro-reflective sign panels. energy efficiency street lighting for project designs that include more traditional practices to reduce electrical consumption; specifically: use of energy efficient warning signs/flashing beacons install existing street/sign lighting with high efficiency types. signboard to inform drivers to switch off engine luminosity of the street light installation of lighting system with high efficiency providing training for toll plaza management staff implement improvement to toll plaza's major energy-using system to optimize energy performance develop a commissioning or on-going commissioning plan for toll plaza's major energyusing system renewable energy update toll plaza operation plan unitary air- conditioners for toll booth sensor/ automatic control devices for toll booth sensor/ automatic control devices for airconditioning system unitary air conditioners for air-conditioning system Provide separate sub-metering for 1) Lighting, and 2) Power at each floor or tenancy Provide separate sub-metering for all energy use ≥ 100kVA provision of auto-sensor controlled lighting in conjunction with delighting strategy for all perimeter zones and daylight areas, if any provision of motion sensors or equivalent to complement lighting zoning for at least 25% NLA all individual or enclosed spaces to be individually switched; and size of individually switched lighting zones shall not exceed 100m² for 90% of Natural Lighting Area (NLA); with switching clearly labelled and easily accessible by building occupants
MEAN
3.86 4.06 3.96
3.75
3.78
3.85 3.52 3.53 3.80 3.68
3.62 3.51 3.72 3.67 3.73 3.71 3.71 3.64 3.62 3.74 3.61
3.73
85
Table 4.18: Template for Energy Efficiency (cont’d)
electrical submetering
green energy policies
EE4
compound and car park
energy efficiency performance
EE5
interchange
lighting control policy
energy plan for maintenance
sustainable highway maintenance
EE3
energy plan for Green Performance (GPC) strategies
EE6
lighting zone
unitary air- conditioners for Air-Conditioning System Provide separate sub-metering for 1) Lighting, AND 2) Power at each floor or tenancy Provide separate sub-metering for all energy use ≥ 100kVA. provision of auto-sensor controlled lighting in conjunction with delighting strategy for all perimeter zones and daylight areas, if any provision of motion sensors or equivalent to complement lighting zoning for at least 25% NLA all individual or enclosed spaces to be individually switched; and the size of individually switched lighting zones shall not exceed 100m² for 90% of the Natural Lighting Area (NLA); with switching clearly labelled and easily accessible by building occupants % utilization of renewable energy in completed works plan for promotion of green energy % operational energy reduction throughout the project life cycle plan for reduced electrical consumption the lighting for car park
3.71
the lighting for landscape
3.66
lighting design / illumination levels equipment that can achieve reduction of energy consumption apply Energy Maintenance Plan (EMP)
3.66
emission reduction
3.71
3.64 3.62 3.74 3.61
3.73
3.51 3.51 3.62 3.63 3.57
3.51 3.63
86
v.
Mean Value Analysis for Social and Safety
Table 4.19 shows the comparison between value man value for Social and Safety (SS). The number of eliminated variables was 58 as they had mean value lower than average index of 3.50. In other words, out of 91 variables identified earlier, only 33 variables were taken into consideration in Malaysia Green Highway Assessment as shown in Figure 4.13. The final template for Social and Safety can be described as in Table 4.20.
Table 4.19: Mean of Social and Safety ELEMENTS DESCRIPTION traffic volume increase in access/interchange number of retail/biz area Rest and Service Area number of retail/biz area highway promotion of local identity provide stall/kiosk/shop lot new development job opportunity and business enhancement property value promoting tourism activity environment - landscaping - 20% - 30% provide any aesthetic initiative along the highway provide any means of temperature control application budget for R&D activities to improve sustainability level for highway innovation of green technology that is customized to the projects conduct periodically (once every 2 years) Road Safety Audit Report provide session to engage for public complaints regular sound level check, provide sound mitigation police beat base Kiosk open area for emergency purposes workshop exhaust fan to reduce thermal comfort Emergency Telephone System (ETS) Close circuit television system (CCTV) Variable message sign (VMS), provided before ingress/egress Other Traffic Control and Surveillance System (TCSS) Vehicle Detection System (VDS) Automatic Incident Detection System Control Centre System (CCS) navigation system corporate social responsibility social impact assessment session for public complaint
NOTATION MEAN EDSS01 EDSS02 EDSS03 EDSS04 EDSS05 EDSS06 EDSS07 EDSS08 EDSS09 EDSS10 EDSS11 EDSS12 EDSS13 EDSS14 EDSS15 EDSS16 EDSS17 EDSS18 EDSS19 EDSS20 EDSS21 EDSS22 EDSS23 EDSS24 EDSS25 EDSS26 EDSS27 EDSS28 EDSS29 EDSS30 EDSS31 EDSS32 EDSS33 EDSS34
3.79 3.70 3.73 3.71 3.77 3.76 3.83 3.81 3.92 3.83 3.71 3.62 3.59 3.73 3.84 3.71 3.58 3.51 4.13 3.65 3.80 3.71 3.69 3.92 4.13 4.07 4.14 3.97 3.81 4.00 3.70 3.98 3.91 3.81
Figure 4.12: Mean and Average Index of Social and Safety
4.00 3.98 3.91 3.81
3.70
3.81
4.13
4.13 4.07 4.14 3.97
3.80 3.71 3.69 3.92
3.65
3.79 3.70 3.73 3.71 3.77 3.76 3.83 3.81 3.92 3.83 3.71 3.62 3.59 3.73 3.84 3.71 3.58 3.51
4.00
EDSS01 EDSS02 EDSS03 EDSS04 EDSS05 EDSS06 EDSS07 EDSS08 EDSS09 EDSS10 EDSS11 EDSS12 EDSS13 EDSS14 EDSS15 EDSS16 EDSS17 EDSS18 EDSS19 EDSS20 EDSS21 EDSS22 EDSS23 EDSS24 EDSS25 EDSS26 EDSS27 EDSS28 EDSS29 EDSS30 EDSS31 EDSS32 EDSS33 EDSS34
87
5.00
4.50
3.50
3.00
2.50
2.00
1.50
1.00
0.50
0.00
88
SS1
ID
Table 4.20: Template for Social and Safety CRITERIA
services and facilities
SUB-CRITERIA
ITS (intelligent traffic system) installation any additional of IT application
any basic facilities additional facilities
SS2
business enhancement economy
SS3
pollution reduction
air and noise pollution
SS4
number of job creation new development tourism
public acceptance
perception
SS5
environmental friendly environment
user thermal comfort
SS6
management issue
road safety audit (RSA)
SS7
landscaping
innovation
technology research and development
ELEMENTS DESCRIPTION variable message sign (VMS), provided before ingress/egress other traffic control and surveillance system (TCSS) vehicle detection system (VDS) close circuit television system (CCTV) for critical area, cover all alignment along highway automatic incident detection system (AIDS) control centre system (CCS) emergency telephone system (ETS) navigation system workshop kiosk police beat base open area for emergency purposes exhaust fan for thermal comfort number of retail/biz area along highway number of retail/biz area at Rest and Service Area increase in access/interchange traffic volume job opportunity property value promoting tourism activity provide session to engage public complaints regular sound level check, provide sound mitigation to maintain level of 50-60 dB all time session for public complaint corporate social responsibility social impact assessment provide any aesthetic initiative provide any means of temperature control application 20%-30% of total highway length conduct Road Safety Audit Report periodically (once every 2 years) green technology budget for R and D activities to improve sustainability level
MEAN 4.07 4.14 3.97 4.13 3.81 4.00 3.92 3.70 3.71 4.14 4.13 3.70 3.61 3.71 3.73 3.70 3.79 3.81 3.92 3.83 3.58 3.51 3.81 3.98 3.91 3.62 3.59 3.71 3.74 3.84 3.73
89
Table 4.21 shows the final variables for each main criterion after Mean Value Analysis. It can be seen that 133 variables out of 218 variables were selected to have mean value greater than average index value of 3.50. All of these 133 variables underwent Factor Analysis before the final variables and factors could be obtained. The detailed explanation of Factor Analysis is discussed in sub-heading 4.1.2.3.
Table 4.21 Final Variables for Each Main criteria after Mean Value Analysis ELEMENTS Energy Efficiency Sustainable Design and Construction Activities Material and Technology Environmental and Water Management Social and Safety TOTAL
∑variables CODE before analysis EE 55 SDCA 29 MT 13 EWM 30 SS 91 218
∑variables after analysis 32 26 13 29 33 133
90
4.1.2.3 Factor Analysis using Statistical Package for Social Science Based on preliminary observations from the study, it was found that too much division factor is done by SPSS application. To some extent, this complicated the researcher’s job to determine how, what, and where the variables were contained within a single factor. The reductions factors needed to be done to solve this problem to further optimize the number of factors to an easy to analyse number. Factor Analysis has been done to optimize the number of factors and variables for Malaysia Green Highway Assessment. It is done by using the application of Statistical Package for Social Science (SPSS), as previously discussed in Chapter 3.4.4.2.
i. Exploration of Data
Before the Factor Analysis can take place, several tests should be performed during exploration of data like Descriptive Analysis, Reliability Test, Data Validation, and Variables’ Relationship Test.
a. Data Validation Analysis using Critical Chi-Square Values
The chi-square values for each variable were compared with Critical ChiSquare values as shown in Table 4.22. This is an example of comparison between χ²cal and χ²cri (see table 3.8) for ‘a highway that allow minimum buffer distance of 100 feet between highway and high quality wetland or water resources’ under ‘Alignment Selection’ criteria for Sustainable Design and Construction Activities. Since χ²cal = 76.086 > χ²cri = 15.09 for 5 degree of freedom, therefore, it can be said that there exist gross errors while conducting data collection. Large number of χ²cal happened when some of the cells had large discrepancies between observed and expected frequencies. It can be said that when the value of χ²cal is extremely large as compared to χ²cri, the probability of getting a value this large, due to chance variation is only 1 out 100 (Michael, 2001).
91
The gross errors tend to occur through carelessness. This might have happened because of writing down the wrong value during face to face interview, reading the questionnaires incorrectly, measuring to the wrong mark and many more. Such errors can be caused by people, computer software, weather conditions and various other things. The gross errors need to be dealt with by careful procedures and relentless checking of work. Table 4.22: Statistical Test of Chi-Square with Critical Chi-Square Values Test Statistics Elements description provide 100ft buffer avoid impact to environment avoid impact to socio-eco adjust highway features utilize visual enhancement reduce urban heat island provide CWMP method of waste minimization waste disposal site recycling plan GHG emission reduction dust control noise mitigation technique use alternative construction methods operate stationary equipment use efficiency method water tracking system provide erosion and sedimentation control plan efficient method of erosion and sedimentation control fossil fuel reduction equipment emission reduction paving emission reduction quality management system environmental training on site contractor warranty site maintenance Reuse Top Soil Reuse and Recycle of non-hazardous material Reuse and Recycle of industrial by-products Recycle material - subgrade improvement/soil stabilization Usage of local material Earthwork Balance Long Lasting Pavement Design Life Reflectance of sunlight energy (ALBEDO and SRI) Usage of RAP and RCM Storm water runoff quality and Flow water control Reduction of noise level Soil biotechnical engineering treatment Green Techniques Firm shall meet the requirement of ISO 14001 establish, document, implement, maintain and continually improve EMS for entire project duration
χ²cal 76.086 47.286 61.143 46.071 63.071 66.357 65.357 90.743 80.514 77.886 80.629 48.714 101.714 95.543 81.314 48.786 77.800 13.886 12.971 73.171 93.229 76.857 21.143 24.171 65.800 77.429 27.714 65.929 53.429 76.343 108.200 40.786 66.571 92.886 89.543 97.514 67.357 59.143 68.071 13.729
df Asymp. Sig. 5 .000 4 .000 4 .000 4 .000 4 .000 4 .000 4 .000 5 .000 3 .000 5 .000 5 .000 4 .000 5 .000 5 .000 5 .000 4 .000 5 .000 3 .003 3 .005 5 .000 5 .000 5 .000 3 .000 3 .000 5 .000 4 .000 4 .000 4 .000 4 .000 5 .000 6 .000 4 .000 5 .000 5 .000 5 .000 5 .000 4 .000 4 .000 4 .000 2 .001
12.700 2
.000
χ²cri 15.09 13.28 13.28 13.28 13.28 13.28 13.28 15.09 11.34 15.09 15.09 13.28 15.09 15.09 15.09 13.28 15.09 11.34 11.34 15.09 15.09 15.09 11.34 11.34 15.09 13.28 13.28 13.28 13.28 15.09 16.81 13.28 15.09 15.09 15.09 15.09 13.28 13.28 13.28 9.21 9.21
92
Table 4.23: Statistical Test of Chi-Square with Critical Chi-Square Values (Cont’d) Reduce runoff quantity during design and construction stage (Malaysia Urban Stormwater Management Manual and Malaysia Highway Authority Manual) Storm water control facilities (detention or retention) Determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) Minimize increase of impervious area due to the project Conduct Lifecycle Cost Analysis (LCCA) for storm-water impact in design stage Manage water flow dissipation on road surface during design stage Drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) detect and eliminate any non-storm water discharges from unpermitted sanitary/ other residential, commercial /industrial sources detect non-storm water discharges from unpermitted sanitary/other residential, commercial/ industrial sources ensure entire waste water treatment (toll plaza, Rest and Service Area, roadway landscape) to comply with local authority demonstrate, through use of models reduction of pollutant loadings to adjacent water resources using Best Management Practice instrumentation to monitor and analyse pollutants in runoff and water bodies use of Low Impact Development best management practices wet or dry swales, sand filters, bio retention design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control at stream crossing protection from materials entering waterway on bridge demolition/ construction wetland restoration, reduce the total disturbed cut and fill areas off Right of Way to the minimum level Provide buffer zone (Department of Wildlife & National Parks, Department of Environment ) no open burning limiting trees cutting within 5 meters off Right of Way each side planting trees to replace those cut within the Right of Way, planting shrubs and native plants alongside Right of Way avoid irrigative/invasive plants -slope protection as soon as clearing work completed replanting/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments wildlife crossing that allow for safe passage of wildlife roadways and provide road barriers to avoid road kills within sensitive ecosystem; bridge and culvert use of the natural – bottomed culvert overpass/underpass structure should provide favourable features for animals, human ecosystem connectivity connectivity; mitigate of habitat fragmentation through techniques enhancement to existing wildlife plan for promote green energy % utilization of renewable energy plan for reduced electrical consumption % operational energy reduction Implement improvement to Rest and Service Area building's major energy- using system to optimize energy performance Providing training for Rest and Service Area management staff Updating Rest and Service Area building operation plan Apply Energy Maintenance Plan (EMP) Luminosity of the street light The lighting for car park
20.414 2.000 9.21 22.300 2.000 9.21 78.114 3.00011.34 68.857 3.00011.34 90.000 3.00011.34 89.200 3.00011.34 80.171 3.00011.34 32.329 2.000 9.21 134.6434.00013.28 25.043 2.000 9.21 97.771 3.00011.34 60.743 3.00011.34 85.771 3.00011.34 93.086 3.00011.34 83.714 3.00011.34 76.571 3.00011.34 30.271 2.000 9.21 87.257 3.00011.34 73.771 3.00011.34 57.429 3.00011.34 64.286 3.00011.34 66.800 3.00011.34 70.457 3.00011.34 58.686 3.00011.34 90.643 4.00013.28 126.2864.00013.28 134.5714.00013.28 120.0714.00013.28 129.1435.00015.09 139.6005.00015.09 107.3574.00013.28 107.0714.00013.28 110.4294.00013.28 64.286 3.00011.34 110.1434.00013.28 133.9435.00015.09 120.0575.00015.09 45.571 4.00013.28
93
Table 4.23 Statistical test of Chi-Square with Critical Chi-Square Values (Cont’d) the lighting for landscape signboard to inform vehicle drivers to switch off engine Renewable Energy at Rest and Service Area reduced electrical consumption 1 reduced electrical consumption 2 lighting zone(internal building) 1 lighting zone(internal building) 2 lighting zone(internal building) 3 electrical sub-metering 1 electrical sub-metering 2 installation of lighting system with high efficiency type implementing improvement to toll plaza's major energy- using system to optimize energy performance developing a commissioning or on- going commissioning plan for toll plaza's major energy- using system providing training for toll plaza management staff updating toll plaza operation plan Equipment unitary air- conditioners sensor/ automatic control devices unitary air- conditioners for toll booth sensor/ automatic control devices for toll booth emission reduction lighting design / illumination levels number of job creation traffic volume increase in access/interchange elements numb of retail/biz area Rest and Service Area numb of retail/biz area highway property value promoting tourism activity dedicated landscaping area that provide along highway provide any aesthetic initiative provide any means of temperature control application R and D budget to improve sustainability for highway 20%-30(%) budget for R&D to improve sustainability innovation of green technology customized to projects periodically/every 2 years road safety audit report provide session to engage for public complaints regular sound level check, provide sound mitigation to maintain of 50-60 dB police beat base Kiosk open area for emergency purposes workshop exhaust fan (for thermal comfort purposes) Emergency Telephone System (ETS) Close circuit television system (CCTV) Variable message sign (VMS), before ingress/egress Other Traffic Control & Surveillance System (TCSS) Vehicle Detection System (VDS) Automatic Incident Detection System (AIDS) Control Centre System (CCS) navigation system corporate social responsibility social impact assessment session for public complaint
52.214 4.00013.28 74.357 4.00013.28 144.7864.00013.28 138.5715.00015.09 110.9294.00013.28 70.000 3.00011.34 126.5715.00015.09 156.0575.00015.09 97.514 5.00015.09 109.1715.00015.09 185.5435.00015.09 137.2005.00015.09 146.0714.00013.28 121.4294.00013.28 130.5714.00013.28 151.0714.00013.28 157.9435.00015.09 97.714 4.00013.28 145.0005.00015.09 154.3435.00015.09 102.2864.00013.28 154.1715.00015.09 115.7144.00013.28 85.714 3.00011.34 134.8574.00013.28 116.2864.00013.28 133.4294.00013.28 164.7864.00013.28 144.7144.00013.28 93.786 4.00013.28 91.357 4.00013.28 81.314 3.00011.34 73.143 3.00011.34 70.171 3.00011.34 35.243 2.000 9.21 84.857 4.00013.28 98.571 4.00013.28 95.786 4.00013.28 65.543 3.00011.34 118.0714.00013.28 126.7144.00013.28 89.500 4.00013.28 109.3574.00013.28 110.2864.00013.28 69.143 3.00011.34 13.086 2.001 9.21 33.443 2.000 9.21 62.400 3.00011.34 45.657 3.00011.34 12.014 2.002 9.21 101.2144.00013.28 112.7864.00013.28 33.100 2.000 9.21 115.1434.00013.28
94
b. Variables’ Relationship Test using Kendall Coefficient of Concordance
The value of Kendall's Coefficient of Concordance, as in Table 4.23, is 0.192 and it is a fairly strong difference among the variables. In other words, the inter-rater agreements among independent judges who rated (ranking) same stimuli in the questionnaire form were very weak and independent of each other.
Table 4.23 Kendal’s W Test Statistic Test Statistics N 140 Kendall's Wa .192 Chi-square 134.079 df 5 Asymp. Sig. .000 a. Kendall's Coefficient of Concordance
c. Descriptive Analysis using KMO and Bartlett's Test
Table 4.24 shows that the value of KMO is 0.594 and ranges from 0.5001.000, with higher value indicating greater suitability; where a value greater than 0.750 is much better. The Bartlett’s test is significant since χ2 (4186) = 10535.667, p5000 The operational energy reductions are estimated at § 1< % ≤2 renewable § 2< % ≤3 renewable § 3< % ≤4 renewable § 4< % ≤5 renewable § Greater than 5% If use green highway criteria like installation of energy efficiency equipment’s such as Solar Panel Reduction of § 40 ≤ % < 60 § 60≤ % < 80 § 80≤ % < 100 Energy consumption can be achieved for the installation of sensor device at interchanges. Street lighting light up and dim gradually depending on the vehicle movement.
153
APPENDIX C1
154
Questionnaires Survey Form
SD-1
ID
SUSTAINABLE DESIGN and CONSTRUCTION ACTIVITIES CRITERIA
Alignment Selection
SUB- CRITERIA
Design to reduce the area of undeveloped land
Design to provide buffer between highway and high quality area
Design to avoid impacts to environmental resources
SD-2
Context Sensitive Design
Design to avoid impact to socioeconomic resources
Design to adjust highway features using design flexibility
Design to utilize visual enhancements
CA-1
Design to reduce urban ‘heat island’ effect Construction Waste Management
Waste Reduction
ELEMENT DESCRIPTION Avoid impact to high quality undeveloped land via alignment section decision making e.g. selection of an alternate which skirts the edge of a resource, rather than bisecting the resource. Reduce impact to prime farmland or forested tracts >10 acres in size via alignment selection decisions above and beyond typical considerations. § 11 – 15 acres § 16 – 20 acres Allow minimum buffer distance of 100 feet between highway and high quality wetland / water resources. § 100 – 150 feet § >151 feet Avoid or minimize the impacts to environmental resources (e.g. KSAS area) and area with threatened or endangered species. As long as it is adequate to avoid or minimize direct impact via alignment selection decisions above e.g. re-routing of the alignment, using retaining wall to minimize right of way takes, or bridging of the resource. As long as it is adequate to avoid or minimize impacts to socio-economic resources e.g. parks, historic sites, recreation areas, residential buildings and commercial buildings providing employment. Allow design to incorporate highway features to respond to unique character of project or sense of place (both natural & built) specifically (if they are applicable). E.g.: placing mosque on retention pond (become attractive area in the design) Allow design to provide scenic view or obstructed an objectionable view. As long as the design utilize natural scenery to enhance nice scenery to users or natural resources (hill etc.) to obstruct unpleasant view. Use any mitigation for urban ‘heat island’ effects from project in designing the highway e.g. increase the amount of vegetative or tree cover, replacing pavement with planted areas, or using cool pavements. Provide Construction and Demolition Waste Management Plan (CWMP) during roadway construction.
AGREEMENT LEVEL 1 2 3 4 5
APPENDIX C1 Questionnaires Survey Form
CA-2
GHGs Emission Reduction
Air Pollution Control
CA- 3
Dust Control
Noise and Vibration Control
Noise and Vibration Mitigation
Use efficient method of waste minimization from its sources on-site. As long as there is method for waste minimization to eliminate the discharge of pollutants into drainage system or to watercourses e.g. proper storage of oil and grease, put schedule waste on-site or as required by environmental standard of the project. Use appropriate approach for waste disposal on-site. As long as it contributes to decrease pollution impact e.g. avoid dumping on rivers, apply fast drying bitumen etc. Provide Site Recycling Plan as part of the CWMP during construction. Allow any method to be applied to minimize waste generated e.g. by divert waste, reuse, recycling etc. Use construction equipment’s that reduce emissions of localized air pollutants. Allow any technique as long as it reduces emission in all diesel engines used on site during construction e.g. reduce idle, enhance maintenance practices, replace older equipment with newer, cleaner engines & equipment, retrofitting engines with technologies designed etc. Reduce vehicle emission to reduce air pollution during construction. The emission factors based on certain average value for speed, vehicle age and ambient temperature. Allow any mitigation measures to reduce vehicle emission factor e.g. as long as it meets, whichever is possible: § 85 dB Department of Environment allow average noise level during highway construction between cannot exceed L90 + 10. Use alternative construction methods with low-noise or quieter equipment’s /machineries /plants. As long as there is any methods applied
155
APPENDIX C1 Questionnaires Survey Form
Water Consumption
CA-4
Water Pollution Control Water Management
CA-5
Temporary Erosion and Sediment Control
Equipment / Machinery Efficiency
Fossil Fuel Reduction
Equipment
to have with low-noise or quieter equipment’s /machineries /plants e.g. placing the pad on the place of applied or reduce vibration impact from the equipment’s. Operate stationary equipment (air compressor, generator etc.) from noise sensitive receptor. Allow the distance >50 feet between stationary equipment and noise sensitive receptor. § 51 – 55 feet § >55 feet Use efficient method of water conservation. As long as any method applied to conserve water during highway construction can reduce >10% from normal water consumption. § 11 – 15 % § >16% Use water tracking system to develop data of monitoring and controlling water consumption in construction. Use appropriate water pollution control measures on-site. Allow the measure to control the amount of water polluted to flow into drainage and to the watercourse e.g. put stockpile away from concentrated runoff, provide physical diversion to protect stockpile from concentrated runoff, keeping vehicles and equipment clean to prevent excessive accumulation of oil and grease etc. Provide Erosion and Sedimentation Control Plan. All water pollution control measures should be included in the plan as long as it meets project specification and requirements. Use efficient method of temporary erosion and sediment control. As long as there is any methods applied for temporary erosion and sediment control e.g. e.g. place erosion and siltation control devices, filter water discharge before release to watercourse etc. Reduce fossil fuel used in construction equipment by using alternative fuel as a replacement for fossil fuel. Allow >25% use of alternative fuel as replacement e.g. bio-fuel etc. (Measure the amount of fossil fuel that being replaced) § >25% replacement § 10-24% replacement Apply emission reduction technologies to
156
APPENDIX C1 Questionnaires Survey Form Emission Reduction
Paving Emission Reduction
CA-6
Quality Management System
Quality Construction Environmental Training On-Site
CA-7
Contractor Warranty
Construction Maintenance
Site Maintenance
the construction equipment’s. Allow providing>75% of construction equipment installed with emission reduction exhausts retrofits and add-on fuel technologies. § >75% installation § 50-74% installation § 29 where higher the value SRI indicated coolest material. (Formula of SRI according to Standard ASTM E1980-01)
159
APPENDIX C1
T-3
Reuse Pavement
Usage of Reclaimed Asphalt Pavement (RAP) and Recycled Concrete Material (RCM)
T-4
Permeable Pavement
Storm-water runoff quality & flow water control improvement
T-5
Quiet Pavement
Reduction of noise level
T-6
Questionnaires Survey Form
Erosion Control
Soil biotechnical engineering treatments
Use of Reclaimed Asphalt Pavement (RAP) to produce new pavement that can minimize the dumping of RAP in landfill, reduce the consumption of virgin materials, and protecting the environment either using hot in-place recycling (HIPR) or cold in-place recycling (CIPR) methods. Application of Recycled Concrete Material (RCM) also known as crushed concrete, is a reclaimed PCC pavement material to use as coarse aggregate in aggregate surface courses, granular embankments, stabilized bases, sub-base courses and aggregate in membrane waterproofing and in drainage layers as protection against erosion. Allow the use of RAP in hot mix asphalt (HMA) % RAP in mixtures = 5%-10% Allow the use of RAP in warm mix asphalt (WMA) % RAP in mixtures = 5%-10% Allow use of RAP in other than ones listed above % RAP in mixtures = 5%-10% Allow the use of RCM in highway construction % RCM in mixtures = 5%-10% (as long as it meets highway design specifications, safety, and environmental quality) Low Impact Development (LID) stormwater controls must be considered in any highway project that construct porous pavement. The main elements that need to be considered in porous pavement construction: Reduction of average annual rainfall from surface porous pavement is at least 50%. At least 25 mg/L of total suspended solids (TSS) are being removed from surface porous pavement. The range of noise level is depending on the types of surface pavement: Open graded asphalt friction course (OGPC) = 69-77 dB(A) Hot mix asphalt (HMA) = 72-79.5 dB(A) Portland cement concrete (PCC) = 76-85 dB(A) Other than types of pavement listed above ≤ 80 dB(A)
Any highway project that utilize soil biotechnical engineering treatments which is combination of plant materials
160
APPENDIX C1
161
Questionnaires Survey Form
Green techniques
and structural elements that can protect slope and control erosion. For examples, vegetated-gabion, vegetated crib wall, etc. Total area of embankment/slope that covered by soil biotechnical engineering treatments ≥ 20% Any highway project that implement green techniques in order to control the soil erosion, protect the slope and embankment such as turfing, planting native vegetation, hydro seeding, soiltire vegetation, etc. Total area of embankment/slope that covered by green techniques ≥ 20%
ID
CRITERIA
WE1
WATER AND ENVIRONMENTAL MANAGEMENT
Environment al Management System (EMS)
SUBCRITERIA
EMS certification
WE2
Runoff flow control ( rate & quantity) Storm water Runoff Quantity
Disaster Cost Analysis
WE3
Drainage System (Network)
Storm water Runoff
Water pollution
ELEMENT DESCRIPTION Firms shall meet the requirement of ISO 14001 Firms shall establish, document, implement, maintain and continually improve an EMS for the entire duration of the project Manage water flow dissipation on the road surface during design stage Reduce runoff quantity during design and construction stage (Malaysia Urban Stormwater Management Manual & Malaysia Highway Authority Manual) Storm water control facilities (detention or retention) Determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) Minimize the increase of impervious area due to the project (Inclusion of “permeable pavement” such as grid pavers if practical). Conduct Lifecycle Cost Analysis (LCCA) for storm-water impact in design stage Manage water flow dissipation on the road surface during design stage Determine the critical volume of water to be stored by hydrograph Drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) Detect and eliminate any non-storm water discharges from unpermitted sanitary or
AGREEMENT LEVEL 1 2 3 4 5
APPENDIX C1 Questionnaires Survey Form Quality
Reduction
Runoff Treatment and Water Bodies Protection
WE4
Habitat Restoration & Protection
Ecosystem Protection & Preservation
Site Vegetation
Tree & Plants Communities
other residential, commercial or industrial sources Detect non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources that enter the Right of Way or flows that ultimately discharge to the Right of Way but which cannot be eliminated Ensure entire waste water treatment (toll plaza, R&S areas, roadway landscape) to comply with local authority requirement level of water quality before discharge to natural water bodies (river, lake, bay) National Water Services Commission, Department of Environment Demonstrate, through the use of models reduction of pollutant loadings to adjacent water resources by the use of Best Management Practices Instrumentation to monitor and analyze pollutants in runoff and water bodies Use of Low Impact Development and Best Management Practices (wet or dry swales, sand filters, bio retention, storm water treatment systems, grass channels, buffer zone, use of highly permeable soil, and so on) to address 90 percentile of annual rainfall event to meet regulatory requirements (Malaysia Urban Stormwater Management Manual , Public Works Department, Department of Irrigation and Drainage) Erosion and Sedimentation control plan: Design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control at stream crossings, and staging construction to minimize soil exposure Protection from materials entering waterway on bridge demolition and construction Wetland restoration, reduce total disturbed cut and fill areas off Right of Way to minimum level provide buffer zone (Department of Wildlife and National Parks , Department of Environment ) No open burning Limit trees cutting within 5 meters off Right of Way each side planting trees to replace those cut within the Right of Way, planting shrubs and native plans alongside the right-of way avoid irrigative and invasive plants -slope protection as soon as clearing work completed Replanting/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments
162
APPENDIX C1
163
Questionnaires Survey Form
Ecological connectivity
Wildlife crossing that allow for safe passage of wildlife roadways and provide road barriers to avoid road kills within sensitive ecosystem; bridge and culvert Use of the natural – bottomed culvert overpass/underpass structure should provide favorable features for animals, human ecosystem connectivity connectivity; mitigate of habitat fragmentation through techniques such as eco-viaducts Provide enhancement to existing wildlife utilize construction of wildlife safe passage such as over pass or under pass structures utilize the construction of bottomed culvert structures utilize replanting vegetation in reclaimed work areas or in abandoned old alignments utilize wetland restoration, reduce the total disturbed cut and fill areas of Right of Way (Right of way) utilize planting of trees plants alongside the right-of way Utilize the use of barriers to avoid road kills of animals such as fencing on the roadway sides.
ID
SOCIAL and SAFETY (SS) CRITERIA
SUBCRITERIA Job Opportunity
SS1
Business Enhancement
Economy New development
SS2
Tourism
Environment
Landscaping
ELEMENT DESCRIPTION Number of job creation and opportunity will be increased Population growth Registered vehicle volume Traffic volume Increase in access / interchange elements Number of retail/business area (shop lot /hotel/petrol pump) in Rest and Service Area / Lay-by Number of retail/business area (shop lot /hotel/petrol pump) along the highway Promotion of local identity Provide stall/kiosk/shop lot that can promote local goods New development along highway corridor Job opportunity and business enhancement Property value Promoting tourism activity Promoting local identity Provide Tourism Information Initiative / Centre in Highway through Variable Message Sign, Kiosk, Billboard, Signage. 20%-30% from total % dedicated highway length landscaping area that will 10%-20% from total
AGREEMENT LEVEL 1 2 3 4 5
APPENDIX C1 Questionnaires Survey Form provide along highway
Environmental friendly
SS3
User Thermal Comfort
Innovation
Sustainable Technology
SS4
Management Issue
SS5
Safety regulation
Pollution Reduction
Road Safety Audit (RSA)
Air & Noise Pollution
SS6
Services
User Services And Facilities Facilities
highway length 0% - 10% from total highway length Along the highway Between interchange Provide any Toll Plaza aesthetic Rest and Service Area initiative Lay-by Comfort temperature of highway facilities Provide any means of temperature control application Budget for R&D activities to improve sustainability level for highway 1-5% of total project Dedicate budget amount / 5-10% of total project budget to budget R&D >10% of total project activities budget Environmental Training Plan Innovation of Green technology that is customized to the projects Compliance on Occupational Safety & Health aspects (OSHA& FMA) or any safety regulation. Periodical Road Safety Audit during operation Conduct periodically (once every 2 years) Road Safety Audit Report Public complaints Provide session to engage for public complaints Regular sound level check, provide sound mitigation in order to maintain the level of 50 to 60 dB for all time Highway maintenance team Provide any Patrol team basic Disaster management team services Emergency traffic control along the team highway Medical team Covered walkway Covered drop off point Police beat base Sick bay Kiosk Vending machine Playground Provide any Wi-Fi hotspot basic Picnic area facilities Open area for emergency along the purposes highway Disabled facilities Helipad / helicopter landing area Workshop Recycle Bin Covered parking Hotel/motel
164
APPENDIX C1 Questionnaires Survey Form
SS7
ITS (intelligent traffic system)
Public acceptance
Perception
Digital information system Basement parking (extra parking) Exhaust fan to reduce (thermal comfort), public announcement (PA system) Pedestrian Bridge (underpass/overpass) Scenic Viewpoint (provide access from the highway to the scenic viewpoints) Continuation walkway (parking area to building) Basement parking (extra parking) Exhaust fan (For thermal comfort purposes) Provide any Public announcement (PA system) additional Motorcycle lane services Contingency parking area along Helipad / helicopter landing highway such as:area Ambulance base (service) Watching TV Area Leisure Area Telephone charging area Touch ‘n Go Reload Service Emergency Telephone System (ETS) Emergency lane Close circuit television system (CCTV) – for critical area, cover all alignment along highway Variable message sign (VMS), provided before Installation ingress/egress any Other Traffic Control & additional of Surveillance System IT (TCSS) application Vehicle Detection System along the (VDS) highway Automatic Incident Detection System Weather Detection System (WDS) Control Centre System (CCS) Navigation system Signage system (innovation) Corporate Social Responsibility Information, presentation to community involve around the project Social Impact Assessment Session for Public Complaint
165
APPENDIX C2
166
Point Score Sheets
POINT SCORE SHEETS
ILH@M SUSTAINABLE DESIGN AND CONSTRUCTION ACTIVITIES ENVIRONMENTAL AND WATER MANAGEMENT MATERIAL AND TECHNOLOGY SOCIAL AND SAFETY ENERGY EFFICIENCY
INDEKS LEBUHRAYA HIJAU MALAYSIA (ILH@M) DEVELOPMENT OF ASSESSMENT FRAMEWORK FOR MALAYSIA GREEN HIGHWAY ASSESSMENT UNIVERSITI TEKNOLOGI MALAYSIA AND LEMBAGA LEBUHRAYA MALAYSIA
APPENDIX C2
167
0.70
4.01
3
0.43
4.17
2
0.60
3.77
2
0.64 0.52
3.90 3.60
2 2
0.89
3.90
3
0.89
3.86
3
3.94 3.83
0.65 0.81
3.72
2
fossil fuel reduction
0.92
3.55
3
paving emission reduction
0.84
3.63
3 3.60
0.64
0.83
2 0
8
operate stationary equipment 50 ft. from noise sensitive receptor
3.62
9
0.74
3
provide site maintenance plan quality management system to improve construction quality contractor warranty provide environmental training on-site design to adjust highway features using design flexibility design to utilize visual enhancement
0.96
4.24
4
0.72
4.13
3
0.69 0.68
3.92 4.20
0.67
3.86
3
0.72
4.02
3
design to avoid impact to socio-economic resources
0.55
3.96
2
provide erosion and sedimentation control plan
0.87
4.15
4
use efficient method of temporary erosion and sediment control
0.83
4.16
provide >100 ft. buffer between highway & high quality area
0.85
3.68
design to avoid impacts to environmental resources
0.55
3.93
4.15
3.95
4.12
equipment emission reduction
0.76
total FS each main criteria % of FS
3 2
average mean
4.10 3.85
total FS of criteria
FL x Mean = Factor Score (FS)
0.73 0.64
average FL
4
3 3
1 3
8
7 3 3
3.88
environmental impact reduction
4.12
0.65
context sensitive design
erosion and sedimentation plan
SDCA5
design flexibility
erosion and sedimentation
management plan and training
alignment selection
natural source & emission reduction
SDCA6
equipment and machineries efficiency
equipment
quality management
noise mitigation control
technique
SDCA7
SUSTAINABLE DESIGN CONSTRUCTION ACTIVITIES SDCA4 SDCA3 SDCA2
innovation
0.97
0.85
air pollutants
provide construction and demolition waste management plan (CWMP) during roadway construction use efficient method of waste minimization use efficient method of water conservation provide site recycling plan as a part of CWMP during construction use appropriate approach for waste disposal on-site use construction equipment’s that reduce emissions of localized air pollutants dust control use water tracking system use alternative construction methods with lownoise or quieter machineries use proper noise mitigation techniques on-site
0.62
waste management
ELEMENT DESCRIPTION
mean
SUB-CRITERIA
Factor Loading (FL)
CRITERIA construction management plan
SDCA1
MAIN CRITERIA ID
Point Score Sheets
7 2
7 2
2 0
APPENDIX C2
168
ENVIRONMENTAL AND WATER MANAGEMENT
disaster cost analysis drainage system (network)
storm water runoff quality
EWM3
water pollution reduction
runoff treatment and water bodies protection
4.03
firms shall meet the requirement of ISO 14001
0.94
3.75
firms shall establish, document, implement, maintain and continually improve an EMS for the entire duration of the project
0.72
3.81
0.76
3.62
3
0.84
3.8
3
0.87
3.79
3
0.76
3.74
0.61
3.66
2
0.84
3.60
3
0.75
3.62
3
0.82
3.67
3
0.85
3.78 3.69
manage water flow dissipation on road surface during design stage reduce runoff quantity during design and construction stage (Malaysia Urban Stormwater Management Manual & Malaysia Highway Authority Manual) storm water control facilities (detention or retention) determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) minimize increase of impervious area due to project (Inclusion of “permeable pavement” such as grid pavers if practical) conduct lifecycle cost analysis for storm-water impact in design drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) detect and eliminate any non-storm water discharges from unpermitted sanitary/other residential, commercial/industrial detect non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources that enter the Right of Way or flows that ultimately discharge to the Right of Way but which cannot be eliminated ensure entire waste water treatment (toll plaza, R&S areas, roadway landscape) to comply with local authority requirement level of water quality before discharge to natural water bodies (river, lake, bay) - National Water Services Commission, Department of Environment demonstrate, through models reduction of pollutant loadings to adjacent water resources using Best Management Practices Instrumentation to monitor and analyse pollutants in runoff and water bodies use of Low Impact Development and Best Management Practices (wet or dry swales, sand filters, bio retention, storm water treatment systems, grass channels, buffer zone, use of highly permeable soil, etc.) to address 90% of annual rainfall event to meet regulatory requirements (Malaysia Urban Stormwater Management Manual , Public Works Department, Department of Irrigation and Drainage) erosion and sedimentation control plan: design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control
4 3
3
7
2 0
8 6 0.77
3.49
3
0.72
3.79
3
0.78
3.67
0.81
3.76
3
0.73
3.71
3
0.89
3.56
3
3.66
runoff flow control (rate & quantity)
0.45
0.78
EMS certification
2
design to reduce urban ‘heat island’ effect
0.79
storm water runoff quantity
EWM2
EWM1 environmental management system (EMS)
Point Score Sheets
3
2 4
APPENDIX C2
169
Point Score Sheets
reflectance of sunlight energy (ALBEDO & SRI) reuse of top soil reused and recycled of nonhazardous materials earthwork balance usage of local materials long lasting pavement design life
3.66
2
0.76
3.79
3
0.8
3.87
3
0.82
3.89
3
0.44
3.71
0.71
3.86
3
0.48
3.88
2
0.86
3.85
3
0.81
3.72
3
0.85
3.73
3
0.79
3.76
3
0.80
3.62
3
0.74
3.61
3
0.99
3.78
0.62
0.72
3
3.57
recycled materials for sub-grade improvement / soil stabilization
3.67
3.50
2
3 3
9
3 4 0
0.92
3.93
4
0.89
3.75
0.61
3.92
2
0.96
3.79
4
0.63
3.96
3.87
innovation technology reduce, reuse and recycle
MT3 economical materials and pavement
MATERIAL AND TECHNOLOGY MT2
MT1
reused and recycled industrial byproducts
0.69
3
9
1 4
3.78
ecological connectivity
3
0.85
tree & plants communities
3.59
0.81
site vegetation
0.81
0.73
ecosystem protection and preservation
EWM4
habitat restoration and protection
at stream crossings, and staging construction to minimize soil exposure protection from materials entering waterway on bridge demolition and construction wetland restoration, reduce the total disturbed cut and fill areas off Right of Way to the minimum level provide buffer zone (Department of Wildlife and National Parks , Department of Environment ) no open burning limiting trees cutting within 5 meters off Right of Way each side, planting trees to replace those cut within the Right of Way, planting shrubs and native plants alongside the right-of way avoid irrigative and invasive plants -slope protection as soon as clearing work completed replanting/relocate/preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments wildlife crossing that allow for safe passage roadways and provide road barriers to avoid road kills within sensitive ecosystem; bridge and culvert use of the natural – bottomed culvert habitat fragmentation through techniques (eco-viaducts etc.) provide enhancement to existing wildlife allow locally industrial by-products to be reused and recycled in highway construction either in flexible or rigid pavement such as by using steel slag, fly ash, crumb rubber, etc. usage of recycled materials for sub-grade improvement / soil stabilization, if it can be proved the process will reduce consumption of virgin materials, cost of project, and will not bring any harm / effect to the road users and environment any surface of pavement with lighter colour has higher albedo effect which indicates high reflectance of sunlight from surface pavement whereas darker colour has lower albedo effect which shows the low reflectance of sunlight from surface pavement. reuse of top soil that has been removed from grading as long as it is non-contaminated soils reuse and recycle non-hazardous materials in design or during highway construction for other base layers, shoulder, drainage, and highway furniture (signage, guardrail, etc.) balancing cut and fill quantities can reduce the need for transport of earthen materials usage of local materials in highway project depending on the location of the project site, whenever practical. allow long lasting pavement design life to avoid frequent rehabilitation, thus depending on the Average Daily Traffic, ADT and types of pavement that will be going to construct.
2
1 1
APPENDIX C2
170
Point Score Sheets
3.70
2
storm-water runoff quality and flow water control improvement
Low Impact Development (LID) storm-water controls must be considered in any highway project that construct porous pavement.
0.73
3.71
3
0.72
3.72
3
0.92
3.81
4
toll plaza
EE2
sustainable infrastructures
enhanced commissioning / recommissioning of building energy systems
3.86
4
0.84
4.06
3
0.79
3.96
3
0.91
3.75
3
3.77
3.96
1.02
0.88
4
1 0
6 8 6
0.87
3.78
3
0.85
3.85
3
0.73
3.52
0.94
3.53
3
0.66
3.80
2
0.84
3.68
0.61
3.62
3.69
reduced electrical consumption
3.94
3.64
rest & service area (RSAs)
ENERGY EFFICIENCY
EE1
enhanced commissioning / recommissioning of building energy systems
8
0.96
0.89
implement green technique to control soil erosion
0.79
soil biotechnical engineering treatments
the speed of more than 80 km/h could contribute noise disruption and noise level range is depending on types of surface pavement utilize soil biotechnical engineering treatments which is the combination of plant materials & structural elements that can protect slope and control the erosion. for examples, vegetated gabion, vegetated crib wall, etc. that implement green techniques in order to control the soil erosion, protect the slope and embankment such as turfing, planting native vegetation, hydro seeding, soil-tire vegetation, etc. updating Rest and Service Area building operation plan providing training for Rest and Service Area management staff Implement improvement to Rest and Service Area building's major energy- using system to optimize energy performance Project designs that reduce electrical consumption above and beyond typical measures. Specifically: § Solar/battery powered street lighting or warning signs. § Replace overhead sign lighting with higher type retro-reflective sign panels § Energy efficiency street lighting Project designs that include more traditional practices to reduce electrical consumption. Specifically: § Use of energy efficient warning signs/flashing beacons. § Install existing street/sign lighting with high efficiency types. provide signboard to inform drivers to switch off engine luminosity of the street light installation of lighting system with high efficiency type provide training for toll plaza management staff implement improvement to toll plaza's major energy- using system to optimize energy performance develop a commissioning or on- going commissioning plan for toll plaza's major
0.69
green scenery
MT4
reduction of noise level
3.87
0.61
0.94
Usage of Reclaimed Asphalt Pavement (RAP) and Recycled Concrete Material (RCM)
use of Reclaimed Asphalt Pavement (RAP) to produce new pavement that can minimize the dumping of RAP in landfill, reduce the consumption of virgin materials, and protecting the environment either using hot inplace recycling (HIPR) or cold in-place recycling (CIPR) methods. Application of Recycled Concrete Material (RCM) also known as crushed concrete, is a reclaimed PCC pavement material to use as coarse aggregate in aggregate surface courses, granular embankments, stabilized bases, subbase courses and aggregate in membrane waterproofing and in drainage layers as protection against erosion.
6
3
3 2
1 4
2 4
APPENDIX C2
171
Point Score Sheets
ITS (intelligent traffic system) installation any additional of IT application
provide any
0.36
3.71
1
0.92
3.64
3
3.63
0.81
3.71
3.71
0.68
0.51
2
0.92
3.74
3
0.87
3.61
3 3.69
3
0.74
3.62
8
3.73
2
0.93
3.51
3
0.93
3.51
3
0.78
3.62
3 1 2
3.57
0.84
0.44
3.63
3
the lighting for car park
0.82
3.57
3
the lighting for landscape lighting design / illumination levels
0.85 0.85
3.66 3.66
Equipment that can achieve reduction of energy consumption
0.48
3.51
apply Energy Maintenance Plan (EMP)
0.65
3.63
emission reduction
0.47
3.71
0.89
4.07
4
0.88
4.14
4
0.82
3.97
3
0.90
4.13
0.73 0.70 0.64 0.43 0.84
3.81 4.00 3.92 3.70 3.31
3.62
0.74
0.83
plan for reduced electrical consumption
variable message sign (VMS), provided before ingress/egress other traffic control and surveillance system (TCSS) vehicle detection system (VDS) (CCTV) for critical area, cover all alignment along highway automatic incident detection system (AIDS) control centre system (CCS) emergency telephone system (ETS) navigation system Workshop
9
6
0.69
6
3.59
3 3 2
5
3.67
2
3.62
sustainable highway maintenance
2 2 3 3
0.66
interchange
lighting control policy
services and facilities
EE3
energy plan for Green Performance (GPC) strategies
EE4 EE5
energy efficiency performance
energy plan for maintenance
EE6 SOCIAL AND SAFETY SS1
green energy policies
compound and car park
lighting zone
3.51 3.72 3.67 3.73
0.56
electrical submetering
0.53 0.54 0.93 0.91
0.66
toll booth (air quality for indoor environment)
energy- using system renewable energy updating toll plaza operation plan unitary air- conditioners for toll booth sensor/ automatic control devices for toll booth sensor/ automatic control devices for AirConditioning System unitary air- conditioners for Air-Conditioning System Provide separate sub-metering for 1) Lighting, AND 2) Power at each floor or tenancy Provide separate sub-metering for all energy use ≥ 100kVA. provision of auto-sensor controlled lighting in conjunction with delighting strategy for all perimeter zones and daylight areas, if any provision of motion sensors or equivalent to complement lighting zoning for at least 25% NLA all individual or enclosed spaces to be individually switched and size of individually switched lighting zones shall not exceed 100m² for 90% of the Natural Lighting Area (NLA) with switching clearly labelled and easily accessible by building occupants % utilization of renewable energy in completed works. plan for promote green energy % operational energy reduction throughout the project life cycle
2
4
4
2 5
3 3 2 2 3
1
8 6
2 2
APPENDIX C2
172
Point Score Sheets
exhaust fan for thermal comfort purposes
0.51
3.61
2
2
number of retail/biz area along highway number of retail/biz area at Rest and Service Area increase in access/interchange elements traffic volume job opportunity
0.95
3.71
4
0.90
3.73
3
0.91 0.61 0.58
3.70 3.79 3.81
3 2 2
property value
0.63
3.92
promoting tourism activity provide session to engage for public complaints regular sound level check, provide sound mitigation to maintain level of 50-60 dB all time session for public complaint corporate social responsibility
0.41
3.83
0.80
3.58
0.61
3.51
0.67 0.62
3.81 3.98
social impact assessment
0.52
3.91
provide any aesthetic initiative
0.84
3.62
0.74
3.59
0.69
3.71
SDCA EWM MT EE SS
0.71
2
3.55
5 2 3 2 7 2
3 9
provide any means of temperature control application 20%-30% from total highway length
road safety audit
conduct Road Safety Audit Report periodically (1 for 2 years)
0.68
3.74
technology
green technology
0.61
3.84
budget for R&D activities to improve sustainability level for highway
0.54
3.73
2
ASSESSMENT CRITERIA ITEM MAX POINTS SUSTAINABLE DESIGN and 72 CONSTRUCTION ACTIVITIES ENVIRONMENTAL and 86 WATER MANAGEMENT MATERIAL and TECHNOLOGY 40 ENERGY EFFICIENCY 86 SOCIAL and SAFETY 86
comments/suggestions respondent
3
3.74
0.68
3
3
3
2
4
TOTAL SCORE
ID
2
2
user thermal comfort landscaping
research and development
2
2
9
environmental friendly
1 4
3
3.90
perception
3.78
1
3.64
air and noise pollution
3 3 2
0.71
job creation new development tourism
4.14 4.13 3.70
0.60
business enhancement
0.70 0.69 0.57
0. 5 3. 77
economy environment innovation
SS3
pollution reduction public acceptance
SS4 SS5 SS6 SS7
management issue
SS2
additional facilities
Kiosk police beat base open area for emergency purposes
0.76
basic facilities
368
ILH@M CLASSIFICATION POINTS (approx.) % ILH@M RATING 219-370
>60
PLATINUM
182-218
50-59
GOLD
145-181 111-144
40-49 30-39
SILVER CERTIFIED
: :
any comments/further suggestions can be emailed to
[email protected] THANKS FOR YOUR SUPPORT! © UTM-LLM ILH@M® Team November 201
%
APPENDIX D1 Critical Chi-Square Values
173
Table D1 Critical Chi-Square Values Critical Chi-Square Values Degrees Freedom 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 11.00 12.00 13.00 14.00 15.00 16.00 17.00 18.00 19.00 20.00 21.00 22.00 23.00 24.00 25.00 26.00 27.00 28.00 29.00 30.00 50.00 100.00
0.01 0.00 0.01 0.07 0.21 0.41 0.68 0.99 1.34 1.74 2.16 2.60 3.07 3.56 4.07 4.60 5.14 5.70 6.26 6.84 7.43 8.03 8.64 9.26 9.89 10.52 11.16 11.81 12.46 13.12 13.79 27.99 67.33
0.01 0.00 0.02 0.12 0.30 0.55 0.87 1.24 1.65 2.09 2.56 3.05 3.57 4.11 4.66 5.23 5.81 6.41 7.01 7.63 8.26 8.90 9.54 10.20 10.86 11.52 12.20 12.88 13.56 14.26 14.95 29.71 70.06
Left Tail 0.03 0.00 0.05 0.22 0.48 0.83 1.24 1.69 2.18 2.70 3.25 3.82 4.40 5.01 5.63 6.26 6.91 7.56 8.23 8.91 9.59 10.28 10.98 11.69 12.40 13.12 13.84 14.57 15.31 16.05 16.79 32.36 74.22
0.05 0.00 0.10 0.35 0.71 1.15 1.64 2.17 2.73 3.32 3.94 4.58 5.23 5.89 6.57 7.26 7.96 8.67 9.39 10.12 10.85 11.59 12.34 13.09 13.85 14.61 15.38 16.15 16.93 17.71 18.49 34.76 77.93
0.10 0.02 0.21 0.58 1.06 1.61 2.20 2.83 3.49 4.17 4.86 5.58 6.30 7.04 7.79 8.55 9.31 10.08 10.86 11.65 12.44 13.24 14.04 14.85 15.66 16.47 17.29 18.11 18.94 19.77 20.60 37.69 82.36
0.90 2.71 4.60 6.25 7.78 9.24 10.64 12.02 13.36 14.68 15.99 17.28 18.55 19.81 21.06 22.31 23.54 24.77 25.99 27.20 28.41 29.62 30.81 32.01 33.20 34.38 35.56 36.74 37.92 39.09 40.26 63.17 118.50
0.95 3.84 5.99 7.82 9.49 11.07 12.59 14.07 15.51 16.92 18.31 19.68 21.03 22.36 23.68 25.00 26.30 27.59 28.87 30.14 31.41 32.67 33.92 35.17 36.42 37.65 38.88 40.11 41.34 42.56 43.77 67.50 124.34
Right Tail 0.98 5.02 7.38 9.35 11.14 12.83 14.45 16.01 17.54 19.02 20.48 21.92 23.34 24.74 26.12 27.49 28.84 30.19 31.53 32.85 34.17 35.48 36.78 38.08 39.36 40.65 41.92 43.20 44.46 45.72 46.98 71.42 129.56
0.99 6.64 9.21 11.34 13.28 15.09 16.81 18.48 20.09 21.67 23.21 24.72 26.22 27.69 29.14 30.58 32.00 33.41 34.80 36.19 37.57 38.93 40.29 41.64 42.98 44.31 45.64 46.96 48.28 49.59 50.89 76.15 135.81
1.00 7.88 10.60 12.84 14.86 16.75 18.55 20.28 21.96 23.59 25.19 26.76 28.30 29.82 31.32 32.80 34.27 35.72 37.16 38.58 40.00 41.40 42.80 44.18 45.56 46.93 48.29 49.64 50.99 52.34 53.67 79.49 140.17
APPENDIX D2 Total Variance Explained
174
Table D2 Total Variance Explained
Total 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52
12.965 11.033 9.100 6.505 4.987 4.181 3.798 3.521 3.279 2.845 2.771 2.631 2.434 2.381 2.228 2.122 2.084 2.017 1.911 1.847 1.708 1.649 1.598 1.576 1.514 1.472 1.407 1.368 1.302 1.260 1.194 1.172 1.119 1.100 .958 .881 .806 .957 .942 .889 .864 .857 .822 .795 .762 .740 .732 .702 .665 .664 .635 .615
Total Variance Explained Extraction Sums of Squared Initial Eigenvalues Loadings % of Cumulative % of Cumulative Total Variance % Variance % 9.748 9.748 12.96 9.748 9.748 8.296 18.043 11.03 8.296 18.043 6.842 24.885 9.100 6.842 24.885 4.891 29.776 6.505 4.891 29.776 3.750 33.526 4.987 3.750 33.526 3.144 36.670 4.181 3.144 36.670 2.856 39.525 3.798 2.856 39.525 2.648 42.173 3.521 2.648 42.173 2.465 44.638 3.279 2.465 44.638 2.139 46.778 2.845 2.139 46.778 2.084 48.861 2.771 2.084 48.861 1.978 50.839 2.631 1.978 50.839 1.830 52.669 2.434 1.830 52.669 1.791 54.460 2.381 1.791 54.460 1.676 56.135 2.228 1.676 56.135 1.596 57.731 2.122 1.596 57.731 1.567 59.298 2.084 1.567 59.298 1.517 60.815 2.017 1.517 60.815 1.437 62.251 1.911 1.437 62.251 1.388 63.640 1.847 1.388 63.640 1.284 64.924 1.708 1.284 64.924 1.240 66.164 1.649 1.240 66.164 1.202 67.366 1.598 1.202 67.366 1.185 68.551 1.576 1.185 68.551 1.139 69.689 1.514 1.139 69.689 1.107 70.796 1.472 1.107 70.796 1.058 71.854 1.407 1.058 71.854 1.029 72.883 1.368 1.029 72.883 .979 73.862 1.302 .979 73.862 .948 74.809 1.260 .948 74.809 .898 75.707 1.194 .898 75.707 .882 76.588 1.172 .882 76.588 .841 77.430 1.119 .841 77.430 .827 78.257 1.100 .827 78.257 .788 79.045 .767 79.812 .756 80.568 .719 81.287 .708 81.995 .668 82.664 .650 83.313 .644 83.957 .618 84.575 .597 85.173 .573 85.746 .556 86.302 .550 86.852 .528 87.379 .500 87.879 .499 88.378 .478 88.856 .462 89.318
Rotation Sums of Squared Loadingsa Total 9.221 9.541 8.642 6.571 8.428 6.004 3.807 3.854 3.930 4.831 3.403 3.937 4.160 3.450 3.958 3.171 3.012 2.868 2.903 2.888 2.661 2.450 2.841 2.620 2.701 2.107 2.447 3.167 2.850 3.211 2.833 2.222 1.925 2.102
APPENDIX D2 Total Variance Explained 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111
.608 .580 .565 .536 .513 .490 .468 .455 .430 .428 .420 .410 .390 .366 .348 .338 .329 .321 .309 .289 .279 .272 .258 .251 .242 .233 .223 .217 .205 .194 .190 .185 .180 .167 .165 .150 .142 .137 .133 .130 .121 .110 .105 .099 .095 .090 .081 .074 .073 .068 .062 .061 .058 .055 .052 .049 .043 .040 .037
.457 .436 .425 .403 .386 .369 .352 .342 .324 .322 .316 .308 .293 .275 .262 .254 .247 .242 .232 .217 .210 .205 .194 .189 .182 .175 .168 .163 .154 .146 .143 .139 .135 .126 .124 .113 .107 .103 .100 .098 .091 .083 .079 .074 .071 .067 .061 .056 .055 .051 .047 .046 .043 .041 .039 .036 .033 .030 .028
89.776 90.212 90.637 91.039 91.425 91.794 92.145 92.488 92.811 93.133 93.449 93.757 94.050 94.325 94.587 94.841 95.088 95.329 95.562 95.779 95.989 96.194 96.388 96.576 96.759 96.933 97.101 97.264 97.418 97.564 97.707 97.846 97.982 98.107 98.232 98.344 98.451 98.555 98.655 98.752 98.844 98.927 99.005 99.080 99.151 99.218 99.279 99.335 99.390 99.441 99.488 99.534 99.577 99.619 99.658 99.695 99.728 99.757 99.785
175
APPENDIX D2 Total Variance Explained 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133
.035 .032 .029 .025 .022 .021 .017 .016 .016 .014 .012 .011 .008 .007 .005 .004 .004 .003 .002 .002 .001 .000
.026 .024 .022 .019 .017 .016 .013 .012 .012 .011 .009 .008 .006 .005 .003 .003 .003 .002 .002 .001 .001 .000
99.812 99.836 99.858 99.876 99.893 99.908 99.922 99.934 99.946 99.956 99.965 99.973 99.979 99.984 99.988 99.991 99.994 99.996 99.998 99.999 100.000 100.000
176
21
-.108
-.149
.124
.138
-.183
-.117
-.123
.139
-.176 .154
.139
.155
.140
.108 .104
-.132
-.241
.113
-.191
.131
.114
-.171
-.177 .139
-.146 -.104 -.220 .133 -.178 .134
.102 -.182 -.103 .191 .106 -.181
.126
-.119 .180
.216
.116
19
.106
18
.105
17
-.110
16
.146
15
.111
.217
-.119
.102
-.141
.231
.136
14
.143
.434
.127
-.158
13
.870
.112
.124 .126
.121
.288
.128 -.127
.118
.623
.129
-.117
-.129
.121
.135
.229 .105
.261
-.227
-.224
.636
.140
-.115
.133 -.189 -.157 -.138 .124 -.151
-.103
.445
-.192 .161
.106
.116
.883
-.100
.227
.212
.897
.166
.132
.901
-.159 .214
.120
-.114 -.111 -.150 -.124 .123 -.151 .305 .149 .151 -.320 -.198 -.152
.129
.192
-.137
.689 .770 -.203
-.131 .152
-.216 .174
-.114
.666 .102
-.167 .117 .113 .182 .263 .184 -.159 -.183 .168
.125
.176
.319 .144 .104
.170 .182 -.157 .113 -.220 .115 -.153
-.198 -.138 .139 .111 .149 .138
.106
-.143
.102 -.126 .113 .112 .131
-.130
12
.168
20 .944
10
.859
11 .869
9
.841
8
.839
7
.824
6
.756
5
.755
4
.748
3
.718
2
.626 .134
.109
-.102
.982
1
.103
This table should be read together with Table D3’ Legend for Table D3. Number of Factors Elements Description 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37
APPENDIX D3 177
Pattern Matrix Tabulation
Table D3 Pattern Matrix Tabulation
44
45
-.211 .202 .142
-.113 -.132
.150 .106 -.283 -.134
.123
-.101
.111
43
.122
.139
-.213
-.143 .116
.134 -.174
-.114
.136
.214
-.147
.265 .188
-.101 .111
.226
-.136 -.629 .156
-.103 -.127
.760
.997
.110 1.02
-.122 .252 -.130 .116
.114 .195
.671 .162 .125 .103
-.105 .292 .144
.100 .262
.139 .189
.220 .106
-.100
.110
.107
.116 -.204
.105
.102 -.146
.115
.140
-.197
-.106 .187
.104
-.106
.847
-.149 -.153 -.155 .113 .106 .115 -.129 .105 .126 -.150 -.120 .115 .140 -.104 -.109 .112 .273 .281 .226 .117 .134 .165 -.142 .186 .126 -.106 -.112 -.137 -.197 -.104
.155 .225 -.103 .124 .144 -.116 -.102 .182 -.271 -.256 -.116
-.101 -.662
.142
-.135 -.142
.118 .134
.156 -.112 .232 -.227 .177 -.119 -.185 -.126 -.142
.696
-.357 .119 -.133 -.108 -.175 -.118 -.143 -.103 .293 -.102 .113 -.106 -.125 .173 -.116 -.141 -.225 .109 -.186 -.128 -.163 .159 .207 .124 -.115 -.184 -.103 .184 -.107 -.112 .107 .146 -.183 -.178
.243 .119
.147
.232
-.121 .100
.141 -.176 -.107 -.198 .237 .127 .118 -.173 -.107 .168 .135 -.110 -.128
.104 .114 .387 -.117 .134 -.131
.106 .112 .222 -.131 .110 .186 .104
.315
-.221 .232 -.220 .168 -.120 .281 -.144 .192 -.131 .134 -.163 -.115 -.110
-.254
-.160 .292
.194 -.169 .338 .140 .325
-.101 .167
-.131 .123
.110 -.100 .116 .203 .170 .135 .117 -.105 .117
-.109 .105 -.134 .148 -.113 .114
.116
-.189 .101
.164
41
.120
39 -.107 -.136
35
-.118
42 .667
32
.105
33 .642
31
.125
40 .956
34 .641
30
.633
29
.781 .806 -.112
36 .400
28
.373
27
.721
38 .357 .102
37
.307
22
-.114 .814 .892 -.155
26
-.161 -.137 .109 -.237 .707 .793 .805 .841 -.135 -.132 .105
25
.110
24
.146
23
-.120 .189
APPENDIX D3 178
Pattern Matrix Tabulation
68
69 .130
.929
-.177
.110
.355
-.116
.169
-.197
-.100
-.102
.263
.741
.131
.133
.842
.142
.925
.157
-.134
-.139
.149
.166
.111
-.131 -.144
.118 -.179 -.169
.155
.205
-.151 -.122 .148 .132
.114
.192
.930
.117
.158 .135
-.208 -.183
.125 .125 .167 .105 -.133
.159
.525
.107
.109
.218 .169 -.275 -.206
.108
.141
.132
.111
.133 .195 -.219 .116
.119
-.162 -.170 -.205 -.158
-.142
.414
.111 -.140 -.200 .175 .145 .327
-.111
-.114 -.119 .217 .229 -.105 -.101 -.130 -.228 .126
.917
.169 .174 -.106 .166 -.211 .172 -.218 .240 .109 -.182 .134 -.155
-.133
.142
-.112 .172 .103
-.139 .129
-.119 .127 .108 -.194 .349
1.02
.199 -.109 .231 -.160 .165 .132 .101 .107 .119 -.143 -.151 .162 .112 -.121 -.101 -.192 .195 .174 -.175 .258 .125 .169 .113 -.165 -.230 .153 -.125 -.127 .114 -.246 -.128 .136 -.146 -.152 .121 .287 -.216 -.325 .133 -.257 -.173 .119 .168 -.141 .216 -.127 -.121 -.110 -.105 -.105 -.121 -.121 .257
.121 .121
67
.187
66
.878
65 .844
62
.538 .214
59
.788 .843 -.113
64 .779
55
.247 .248
63 .735
53
.106 .102 -.122
61
.153
57 .107
-.102 .165
.189
-.190
.178
-.326
.132
.134
.162 -.108
.162
.111
.166
.144
.127
.136 .140
-.149 .199
-.205 .113 -.142
-.292
.115
-.101 -.108
-.123
-.179
.108 .127
.131
-.139 .114
.110
.180 .129
-.149
-.245 -.180
-.186
-.169
-.116 .130 .171
-.101 -.126 -.203 -.158 .621 .687 .612 .898 .911 .948 -.144 -.101
.121
-.111 .134 -.103 -.258 -.159 .189 .166 -.101 -.105 -.152
-.113
.105 .576
52
.191
60
-.108 .102
58
.115 .110 .140
56
-.115
54 .123
51
.260
50
.121
49
-.110
48
-.113 -.114 -.120
47
-.114
46
.162
APPENDIX D3 179
Pattern Matrix Tabulation
93
.146
.134
-.105
.167 .131 -.182 -.189
.249 -.135 .205
-.124
-.128 .151 -.199 .162 .127
-.136
.291 -.172 .189 .215 .132
-.162
.145 .933
.924 .148
.142
-.192
-.176
.107
-.121
-.169 .129 .414 .156 .163 .156 .140 .145
.108 1.23
.121 .209
-.126 .163 .877 -.143 -.111 .151 .177
.144
-.197
.207 -.117 .187 .138
.145
-.176
-.107 -.266 -.104
.159
-.136 .411 .838
-.127 -.161 -.125 .177 .177 .171 .109
.109 .165 .112 .154
.963
.123
.278
-.103 .124 -.164
.176
-.121
.317
.171 .804 .139 .164 .173
.154 -.192 .121 -.117 -.146 .227
-.142
.117
-.138
.303
-.164 .138 -.204 -.242 .113 .256 .103
.106
-.182 -.132
.232 .107
-.137
-.143 .178
.102
-.152
.889
-.153
.169
.127
-.217 .148
-.103 -.128
-.120 .112
.426 .152 -.145
-.133
.644 .206
.113
.169
.129
.635
.814
-.181
.180
.188
.186 -.183 -.163 -.132 .117
.183
-.127 .843 .159
.102
.211 -.171 -.140 -.133 .193 .226 .275 -.276 .229 -.200 -.133 -.195
.160
-.119
-.167 -.122
.100
.123 -.129 .122
-.166
-.104 .141 .100 -.165 .190 -.111
.153
1.07
-.106
.141 -.244 -.128 -.145 -.202 -.101 -.126 -.135 -.271 -.116
.387
-.223 .111
-.102
-.105
.116
.144
.909 .184
-.138 .130 .117
-.100
.144 .707 .758 .276 -.180
-.120 -.114 .110
.108 .127
.151 1.12
-.148 .109
-.107 -.103 -.140 .124 -.234 .103
.103
.122 .124 .207
-.124 1.04 .990
.118 -.127 -.106 .231
-.126 -.145
-.154 -.130 -.135 -.154
.342
.202
.236 .741
.141
81
.117 -.122 .294 .963 .283 .185
.121 .163
-.116 -.105
-.114
83
-.162 .107 .185 -.177 -.183 .107 .200 .212 -.167 .140
85 .102
-.135
78
-.101
84 .107
77
-.141
91 .153
75
-.156
74
.188 .683 .114
90 .121
.192
72
.179 -.181 -.142
92
.148
88 -.102
.117
73
.107
89 -.240
.123
76
.137 .146 -.116
87 .108
82 .109 -.102 .104
70
.140 -.115
86 .182 -.128
80
-.164
79
-.109 -.116
71
.277
APPENDIX D3 180
Pattern Matrix Tabulation
117
-.142 .210
.167
.908 -.173
-.109 -.169
-.162 .123 -.130
.388
108
-.157 -.214 .610 1.11 .261 -.198 .125 .251
.140
101 -.141
100
-.162 .190 -.242 .171 .261 .122 -.308 -.291 -.250 -.158 -.113 .326 .139 .273 -.189 .104 .202 .148 .134 .108 .160 -.102 .210 -.164 .197 .144 .134 .107
106 .103 .201
102
-.126 .138 .109
99 -.108
-.105
-.161 -.105 -.142 .112 .111
-.107 -.136 .109 .128 .204 -.168 .140 -.159 .113 .201 -.134 .174 -.191 .254 -.187 .126 .314 .182 .166 .120 -.130 -.129 -.190 .262 .147 .161 .198 .231 .124 .187 -.193 -.105 .136 -.258 -.113 -.130 -.113 -.107 .102 -.118 .234 -.160 -.101 .114 .129 -.267 -.174 .122 .283 .105 -.169 .155 -.254 .106 .187 .156 -.211 -.126 .116 -.127 -.151 .194 .212 .142 .180 .176 .188 .112 .124 .256 .244 .275 .197 .118 .414 -.205 -.109 -.102 -.165 .167 .186 -.123 .164 .614 .227 .224 .162 .102 .893 .922 -.100 .186 .188 .812 .846 .108 .113 -.124 .125 .166 .140 .126 -.181 .939 1.06 .165 .125 .137 -.194 .263 -.249 .148 -.137 .391 .620 .956 -.155 .445 .134 -.115 1.09 -.122 -.161 -.142 -.158 .166 .752 1.02 .129 .159 .122 .251 -.354 .449 .669 1.02 -.105 .282 .181 .104 -.159 .738 .846 .116 .338 .202 .131 .207 -.180 .981 -.238 -.152 .162 .242 .117 .179 .255 -.123 .134 .304 .247 .144 -.200 .261 -.204 -.103 .114 .115 .115 .186 -.102 -.277 .275 .116 -.269 -.158 -.376 -.140 .202 -.136 -.143 -.245 .126 .112 -.289 -.104 -.162 .172 .122 .121 .128 -.125 .144 -.260 .186 -.166 -.271 .158 .103 -.111 .253 -.102 -.111 .154 .107 -.200 .197 -.109 -.176 .151 -.116 -.131 -.121 .196 .104 -.170 .161 .193 -.113 .206 -.136 -.137 .172
.112
.291
-.155
98
-.101
115 .182
.126
96
.236
114 -.166
110 -.170
105 .217 .105
94
-.213
.150
107
.205
-.108
104
.122
112 .283 .139
111 -.142
103
-.119 .124
113 -.159 .109
109
.158 -.133 .153
97
.148
-.105 .123
95
.134
116
.109
APPENDIX D3 181
Pattern Matrix Tabulation
.141
132
-.136 .156
133
130
128
.111 .655
.140 .104 .100
.308
.158
-.117
-.169
.963
.920 -.101
-.138 .112 .116
.673
.107 .145
-.187 -.221 .135 -.120 .199
.163
-.162
.121
.270 -.101
.221
.134
.758
.826
.363 .440 -.204 -.244 .164 .356 .189
-.141
.114
.283
-.132
.139 .164 -.158
.138 .102 .347 .106 .129
-.128 .241
.105 .208 .897 .174 .102
.187
1.03 .163 .235 .136 .123 .292 -.121
.271 .341 .191
-.256
.550 -.107 .208 .107
-.111 -.146 -.114 -.106 -.118 .202 -.217 .184 .227 .222 .256 -.131 .241 -.209 .228 -.167 .150 -.102 -.145 -.121 -.235 .128 .141 .155 -.153 .201 .122 -.139 .129 -.113 -.194 .274 .102 -.106 -.113 -.148 .103 .310 -.143 -.202 -.141 .103 -.128 .138 -.146 -.158 -.164 -.171 .109 -.138 .123 .239 .120 .216 .140 .202 .720 -.190 1.30 .199 .935 -.165 .106
-.181
-.208
.379
-.186 -.153 -.174
.114 .225
.123
.124 -.124 .130 -.113
-.181 .207 -.108 -.132 -.143 .109 .100
-.102
-.337 -.172 -.103 .219 -.200 -.106 .109 -.132 -.106 .115 -.159 -.106 .111 -.101 .140 -.118 -.209 .194 -.186
.133 .230 -.244 .170 .323 .372
.213
.160
.112
126
-.120
129 .363
120
.115
127
.531
125
.636 .137
124
-.115 -.222 .325
123
-.139
122
-.110
121
.120 .507
119
.288 .505
.234
118
.140
131
.117 .323
APPENDIX D3 182
Pattern Matrix Tabulation
APPENDIX D3
183
Pattern Matrix Tabulation Table D3’ Legend for Table D3 Code 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44
Elements Description Variable message sign (VMS), provided before ingress/egress Other Traffic Control & Surveillance System (TCSS) Vehicle Detection System (VDS) Close circuit television system (CCTV) – for critical area, cover all alignment along highway Control Centre System (CCS) Automatic Incident Detection System (AIDS) Corporate Social Responsibility Emergency Telephone System (ETS) Social Impact Assessment Minimize the increase of impervious area due to the project Storm water control facilities (detention or retention) Reduce runoff quantity during design and construction stage ( Malaysia Urban Stormwater Management Manual & Malaysia Highway Authority Manual Conduct Lifecycle Cost Analysis (LCCA) for storm-water impact in design stage Detect and eliminate any non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources Manage water flow dissipation on the road surface during design stage Determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) Drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) Firms shall establish, document, implement, maintain and continually improve an EMS for entire duration of project Firm shall meet the requirement of ISO 14001 overpass/underpass structure should provide favourable features for animals, human ecosystem connectivity roadways and provide road barriers to avoid road kills within sensitive ecosystem; bridge and culvert, connectivity; mitigate of habitat fragmentation through techniques such as eco-viaducts Wildlife crossing that allow for safe passage of wildlife Use of the natural – bottomed culvert Enhancement to existing wildlife Replanting/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments avoid irrigative and invasive plants -slope protection as soon as clearing work completed provide CWMP method of waste minimization waste disposal site recycling plan provide erosion and sedimentation control plan use efficiency method dust control use efficient method of erosion and sedimentation control environmental training on site water tracking system GHG emission reduction Workshop Use of Low Impact Development and Best Management Practices wet or dry swales , sand filters, bio retention Design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control at stream crossing Protection from materials entering waterway on bridge demolition and construction Instrumentation to monitor and analyse pollutants in runoff and water bodies Demonstrate, through the use of models reduction of pollutant loadings to adjacent water resources by the use of Best Management Practices
APPENDIX D3
184
Pattern Matrix Tabulation 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97
Ensure entire waste water treatment (toll plaza, R&S areas, roadway landscape) to comply with the local authority Wetland restoration, reduce the total disturbed cut and fill areas off Right of Way to the minimum level provide buffer zone (Department of Wildlife and National Parks, Department of Environment ) Number of Retail/Biz Area Highway Increase In Access/Interchange Elements Number of Retail/Biz Area Rest and Service Area Traffic Volume Number of Job Creation New development Promoting tourism activity % Utilization of Renewable Energy Plan For Promote Green Energy % Operational Energy Reduction Plan For Reduced Electrical Consumption fossil fuel reduction paving emission reduction equipment emission reduction Developing a commissioning or on- going commissioning plan for toll plaza's major energyusing system Implementing improvement to toll plaza's major energy- using system to optimize energy performance Updating toll plaza operation plan Updating Rest and Service Area building operation plan Providing training for Rest and Service Area management staff Implementing improvement to Rest and Service Area building's major energy- using system to optimize energy performance Apply Energy Maintenance Plan (EMP) Innovation of Green technology that is customized to the projects Provide any aesthetic initiative % dedicated landscaping area that will provide along highway - 1 Provide any means of temperature control application use alternative construction methods noise mitigation technique operate stationary equipment Sensor/ Automatic control devices for toll booth Unitary Air- conditioners for toll booth Emission Reduction Lighting Zone(Internal Building) 2 Lighting Zone(Internal Building) 3 Reflectance of sunlight energy (ALBEDO &SRI) Reuse & Recycle of industrial by-products Recycle material for subgrade improvement/soil stabilization Kiosk Police beat base Open area for emergency purposes Green Techniques Soil biotechnical engineering treatment contractor warranty site maintenance quality management system Provide session to engage for public complaints Session for Public Complaint Regular sound level check, provide sound mitigation in order to maintain level of 50 to 60 dB for all time Reuse Top Soil Reuse & Recycle of non-hazardous material the lighting for landscape
APPENDIX D3
185
Pattern Matrix Tabulation 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133
The lighting for car park Electrical Sub-metering 2 Electrical Sub-metering 1 Usage of local material Long Lasting Pavement Design Life Usage of RAP & RCM provide 100ft buffer Reduced Electrical Consumption 2 Reduced Electrical Consumption 1 utilize visual enhancement adjust highway features reduce urban heat island Earthwork Balance avoid impact to socio-eco avoid impact to environment Reduction of noise level Storm water runoff quality & Flow water control Exhaust fan (For thermal comfort purposes) Luminosity of the street light Equipment Provide signboard to inform vehicle drivers to switch off the engine Lighting Design / Illumination levels Installation of lighting system with high efficiency type Renewable Energy at Rest and Service Area Navigation system sustainability level for highway Budget for R&D activities to improve the sustainability level for highway (%) Sensor/ Automatic control devices Lighting Zone(Internal Building) 1 Unitary Air- conditioners Limiting trees cutting within 5 meters off Right of Way each side No open burning planting trees to replace those cut within the Right of Way, planting shrubs and native plants alongside the right-of way Management Issue - Road Safety Audit (RSA) - 2 Detect non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources Providing training for toll plaza management staff
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
186
SDCA1
waste management construction management plan
air pollutants
SDCA2
innovation
noise mitigation control
technique
SDCA5
SDCA4
SDCA3
equipment equipment and machineries efficiency
quality management
context sensitive design
natural source & emission reduction
management plan and training
design flexibility
provide construction and demolition waste management plan (CWMP) during construction use efficient method of waste minimization use efficient method of water conservation provide site recycling plan as a part of CWMP during construction use appropriate approach for waste disposal on-site use construction equipment’s that reduce emissions of localized air pollutants dust control use water tracking system use alternative construction methods with low-noise or quieter machineries use proper noise mitigation techniques on-site operate stationary equipment 50 ft. from noise sensitive receptor fossil fuel reduction paving emission reduction equipment emission reduction site maintenance plan quality management system to improve construction quality contractor warranty provide environmental training on-site design to adjust highway features using design flexibility design to utilize visual enhancement design to avoid impact to socio-economic resources
4
0.73
4.10
3
0.64
3.85
2
0.70
4.01
3
0.43
4.17
2
0.60
3.77
2
0.64 0.52
3.90 3.60
2 2
0.89
3.90
3
∑FS of main criteria
4.12
∑FS of criteria
0.97
∑FS of sub criteria
ELEMENT DESCRIPTION
FL x Mean = factor score (FS)
SUBCRITERIA
mean
CRITERIA
Factor Loading (FL)
ID
Table E1 Factor Score for Element’s Description, Sub Criteria and Criteria
14
20
4
2
6 0.89
3.86
3
0.64
3.72
2
0.92 0.84
3.55 3.63
3 3
0.74
3.62
3
0.96
4.24
4
0.72
4.13
3
0.69
3.92
3
0.68
4.20
3
0.67
3.86
3
0.72
4.02
3
0.55
3.96
2
72 8
2
9
9
13
13
8
8
EWM1
SDCA7
SDCA6
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria erosion and sedimentation control
erosion and sedimentation plan
alignment selection
environmental impact reduction
environmental management system (EMS)
EMS certification
EWM2
runoff flow control (rate & quantity) storm water runoff quantity
disaster cost analysis
EWM3
drainage system (network)
storm water runoff quality
water pollution reduction
provide erosion and sedimentation control plan use efficient method of temporary erosion and sediment control design to provide >100 ft. buffer between highway and high quality area design to avoid impacts to environmental resources design to reduce urban ‘heat island’ effect firms shall meet the requirement of ISO 14001 firms shall establish, document, implement, maintain and continually improve an EMS for the entire duration of the project manage water flow dissipation on the road surface during design stage reduce runoff quantity during design and construction stage storm water control facilities (detention or retention) determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) minimize the increase of impervious area due to project conduct lifecycle cost analysis (LCCA) for storm-water impact in design stage drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) detect and eliminate any non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial detect non-storm water discharges from
0.87
4.15
4
0.83
4.16
3
0.85
3.68
3
0.55
3.93
2
0.45
4.03
2
0.94
3.75
4
0.72
3.81
3
0.76
3.62
3
0.84
3.8
3
0.87
3.79
3
187
7
7
7
7
7
7
14
0.76
3.74
3 20
0.61
3.66
2
0.84
3.60
3
3
0.75
3.62
3
3
0.82
3.67
3 9
0.77
3.49
3
24
84
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
runoff treatment and water bodies protection
unpermitted sanitary or other residential, commercial or industrial sources that enter the Right of Way or flows that ultimately discharge to the Right of Way but which cannot be eliminated ensure entire waste water treatment (toll plaza, R&S areas, roadway landscape) to comply with the local authority requirement level of water quality before discharge to natural water bodies (river, lake, bay) National Water Services Commission, Department of Environment Demonstrate; use of models reduction of pollutant loadings to adjacent water resources using Best Management Practices Instrumentation to monitor and analyse pollutants in runoff and water bodies use of Low Impact Development and Best Management Practices (wet or dry swales, sand filters, bio retention, storm water treatment systems, grass channels, buffer zone, use of highly permeable soil, etc.) to address 90% of annual rainfall event to meet regulatory requirements (Malaysia Urban Stormwater Management Manual , Public Works Department, Department of Irrigation and Drainage) erosion and sedimentation control plan: design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control at stream crossings, and staging construction to minimize soil exposure protection from materials entering waterway on bridge demolition and construction
0.72
3.79
3
0.78
3.67
3
0.81
3.76
3
0.73
3.71
3
15
0.89
3.56
3
0.81
3.59
3
188
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
habitat restoration & protection
EWM4
site vegetation
ecosystem protection and preservation tree & plants communities
ecological connectivity
MT1
reused and recycled industrial byproducts
innovation technology
recycled materials for sub-grade improvement / soil stabilization
wetland restoration, reduce the total disturbed cut and fill areas off Right of Way to minimum level provide buffer zone (Department of Wildlife and National Parks, Department of Environment) no open burning limiting trees cutting within 5 meters off Right of Way each side planting trees to replace those cut within the Right of Way, planting shrubs and native plants alongside the right-of way avoid irrigative and invasive plants -slope protection as soon as clearing work completed replanting/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments wildlife crossing that allow for safe passage roadways and provide road barriers to avoid road kills within sensitive ecosystem; bridge and culvert use of natural bottomed culvert habitat fragmentation through techniques such as eco-viaducts provide enhancement to existing wildlife allow the locally industrial by-products to be reused and recycled in highway construction either in flexible or rigid pavement such as by using steel slag, fly ash, crumb rubber, etc. allow the usage of recycled materials for sub-grade improvement / soil stabilization, if it can be proved that the process will reduce the consumption of virgin materials, cost of project, and will not bring any harm / effect to the road users and environment.
0.69
3.67
189
3
8 0.62
3.66
2
0.76
3.79
3
0.8
3.87
3
0.82
3.89
3
0.44
3.71
2
0.71
3.86
3
0.48
3.88
2
0.86
3.85
3
0.81
3.72
3
0.85
3.73
3
0.79
3.76
3
0.80
3.62
3
8
33
3
14
3
9
0.74
3.61
3
3
40
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
reflectance of sunlight energy (ALBEDO & SRI)
MT2
reuse of top soil
reduce, reuse and recycle
reused and recycled of non-hazardous materials
earthwork balance
usage of local materials
MT3
long lasting pavement design life
economical materials and pavement Usage of Reclaimed Asphalt Pavement (RAP) and Recycled Concrete Material (RCM)
any surface of pavement with lighter colour has higher albedo effect, which indicates high reflectance of sunlight from surface pavement whereas darker colour has lower albedo effect, which shows the low reflectance of sunlight from surface pavement. allow the reuse of top soil that has been removed from grading as long as it is non-contaminated soils. allow the reused and recycled of non-hazardous materials in design or during highway construction for other base layers, shoulder, drainage, and highway furniture (signage, guardrail, etc.) balancing cut and fill quantities can reduce the need for transport of earthen materials allow the usage of local materials in highway project depending on the location of the project site, whenever practical. allow long lasting pavement design life to avoid frequent rehabilitation, thus depending on the Average Daily Traffic, ADT and types of pavement that will be going to construct. use of Reclaimed Asphalt Pavement (RAP) to produce new pavement that can minimize dumping of RAP in landfill, reduce consumption of virgin materials, and protecting environment either using hot in-place recycling (HIPR) or cold in-place recycling (CIPR) methods. Application of Recycled Concrete Material (RCM) also known as crushed concrete, is a reclaimed PCC pavement material to use as coarse aggregate in aggregate surface courses, granular embankments, stabilized bases, sub-base courses and aggregate in
0.99
3.50
3
3
0.92
3.93
4
4
0.89
3.75
3
3
0.61
3.92
2
2
0.96
3.79
4
4
0.63
3.96
2
2
190
9
14
0.61
3.70
2
2
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
storm-water runoff quality and flow water control improvement
reduction of noise level
MT4
soil biotechnical engineering treatments green scenery
implement green technique to control soil erosion
EE1
enhanced commission / re-commission of building energy systems
rest & service area (RSAs)
reduced electrical consumption
membrane waterproofing and in drainage layers as protection against erosion Low Impact Development storm-water controls must be considered in any highway project that construct porous pavement the speed that more than 80 km/h could contribute noise disruption and the range of noise level is depending on the types of surface pavement any highway project that utilize soil biotechnical engineering treatments, which is the combination of plant materials and structural elements that can protect slope and control the erosion. for examples, vegetated gabion, vegetated crib wall, etc. implement green techniques in order to control the soil erosion, protect the slope and embankment such as turfing, planting native vegetation, hydro seeding, soil-tire vegetation, etc. update Rest Service Area building operation plan provide training for Rest Service Area management Implement improvement to Rest and Service Area building's major energyusing system to optimize energy performance Reduce electrical consumption beyond typical measures. Specifically: § Solar/battery powered street lighting or warning signs § Replace overhead sign lighting with higher type retro-reflective sign panels § Energy efficiency street lighting more traditional practices to reduce electrical consumption; specifically: § energy efficient warning signs/flashing beacons.
0.73
3.71
3
3
0.72
3.72
3
3
0.92
3.81
4
4
191
8
0.96
3.94
4
1.02
3.86
4
0.84
4.06
3
4
10 0.79
3.96
3
22 0.91
3.75
3 6
0.87
3.78
3
86
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
sustainable infrastructures
enhanced commission / re-commission of building energy systems
EE2
toll booth (air quality for indoor environment)
toll plaza electrical submetering
lighting zone
§ existing street/sign lighting with high efficiency types provide signboard to inform drivers to switch off engine luminosity of street light lighting system with high efficiency type providing training for toll plaza management staff improvement to toll plaza's major energy- using system to optimize energy performance develop a commissioning or on- going commission plan for toll plaza's major energy- using system renewable energy updating toll plaza operation plan unitary air- conditioners for toll booth sensor/ automatic control devices for toll booth sensor/ automatic control devices for AirConditioning System unitary air- conditioners for Air-Conditioning System Provide separate submetering for 1) Lighting, AND 2) Power at each floor or tenancy Provide separate submetering for all energy use ≥ 100kVA. provision of auto-sensor controlled lighting in conjunction with delighting strategy for all perimeter zones and daylight areas, if any provision of motion sensors or equivalent to complement lighting zoning for at least 25% NLA all individual or enclosed spaces to be individually switched; and the size of individually switched lighting zones shall not exceed 100m² for 90% of the Natural Lighting Area ( NLA); with switching clearly labelled
0.85
3.85
3
0.73
3.52
3
0.94
3.53
3
0.66
3.80
2
0.84
3.68
3
192
6
14 0.61
3.62
2
0.53
3.51
2
0.54
3.72
2
0.93
3.67
3
0.91
3.73
3
0.51
3.71
2
0.36
3.71
1
0.92
3.64
3
9
37 6 0.69
3.62
3
0.92
3.74
3
0.87
3.61
3 8
0.44
3.73
2
energy plan for Green Performance (GPC) strategies
interchange
energy plan for maintenance
SS1
EE5
compound and car park
EE6
EE4
EE3
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria
services and facilities
green energy policies
energy efficiency performance lighting control policy sustainable highway maintenance
ITS (intelligent traffic system) installation any additional of IT application
provide any basic facilities
SS2
provide additional facilities
Economy
business enhancement
job creation
and easily accessible by building occupants % utilization of renewable energy in completed works. plan for promote green energy % operational energy reduction throughout the project life cycle plan for reduced electrical consumption
0.93
3.51
3
0.93
3.51
3
0.78
3.62
3
0.74
3.63
3
the lighting for car park
0.82
3.57
3
the lighting for landscape
0.85
3.66
3
0.85
3.66
3
0.48
3.51
2
0.65
3.63
2
0.47
3.71
2
0.89
4.07
4
0.88
4.14
4
0.82
3.97
3
0.90
4.13
4
0.73
3.81
3
0.70
4.00
3
0.64
3.92
2
0.43 0.84 0.70 0.69
3.70 3.31 4.14 4.13
2 3 3 3
0.57
3.70
2
0.51
3.61
2
0.95
3.71
4
0.90
3.73
3
lighting design / illumination levels Equipment that can achieve reduction of energy consumption apply Energy Maintenance Plan (EMP) emission reduction variable message sign (VMS), provided before ingress/egress other traffic control and surveillance system (TCSS) vehicle detection system (VDS) close circuit television system (CCTV) for critical area, cover all alignment along highway automatic incident detection system (AIDS) control centre system (CCS) emergency telephone system (ETS) navigation system Workshop Kiosk police beat base open area for emergency purposes exhaust fan for thermal comfort purposes retail/biz area along highway retail/biz area at Rest and Service Area increase in access/interchange elements traffic volume job opportunity
12
12
6
6
5
5
4
4
25
38
86
11
2
12 0.91
3.70
3
0.61 0.58
3.79 3.81
2 2
193
2
18
APPENDIX D4 Factor Score for Element’s Description, Sub Criteria and Criteria new development
property value
0.63
3.92
2
194
2 2
SS4
SS3
tourism
pollution reduction
public acceptance
air and noise pollution
perception
SS5
environmental friendly environment
user thermal comfort
SS6
landscaping management issue
road safety audit (RSA)
SS7
technology
innovation
promoting tourism activity provide session to engage for public complaints regular sound level check, provide sound mitigation to maintain level of 50-60 dB all time session for public complaint corporate social responsibility social impact assessment provide any aesthetic initiative provide any means of temperature control application 20%-30% from total highway length conduct Road Safety Audit Report periodically (once every 2 years)
green technology budget for R&D activities research and to improve sustainability development level for highway TOTAL SCORE
0.41
3.83
2
0.80
3.58
3
0.61
3.51
2
0.67
3.81
3
0.62
3.98
2
0.52
3.91
2
0.84
3.62
3
3
0.74
3.59
3
3
0.69
3.71
3
3
0.68
3.74
3
3
0.61
3.84
2
2
0.54
3.73
2
2
5
5
7
7
9
3
4 368
APPENDIX E1
195
Weightage Factor for Elements Description
SDCA1
waste management construction management plan
air pollutants
SDCA2
innovation
noise mitigation control
technique
equipment and machineries efficiency
quality management
context sensitive design
natural source & emission reduction
management plan and training
design flexibility
erosion and sedimentatio n control
erosion and sedimentation plan
alignment selection
environmental impact
D C A
SDCA6
SDCA5
SDCA4
SDCA3
equipment
4.12
4
0.286
0.73
4.10
3
0.214
0.64
3.85
2
0.70
4.01
3
0.214
0.43
4.17
2
0.143
0.60
3.77
2
0.64 0.52
3.90 3.60
2 2
0.89
3.90
3
0.89
3.86
3
0.64
3.72
2
1.000
0.92 0.84
3.55 3.63
3 3
0.333 0.333
equipment emission reduction
0.74
3.62
3
0.333
provide site maintenance plan quality management system to improve construction quality contractor warranty provide environmental training on-site design to adjust highway features using design flexibility design to utilize visual enhancement design to avoid impact to socioeconomic resources provide erosion and sedimentation control plan use efficient method of temporary erosion and sediment control design to provide >100 ft. buffer between highway and high quality
0.96
4.24
4
0.308
0.72
4.13
3
provide construction and demolition waste management plan (CWMP) during construction use efficient method of waste minimization use efficient method of water conservation site recycling plan as a part of CWMP during construction use appropriate approach for waste disposal on-site construction equipment’s reduce emissions of localized air pollutants dust control use water tracking system alternative construction methods with low-noise or quieter machineries use proper noise mitigation techniques on-site operate stationary equipment 50 ft. from noise sensitive receptor fossil fuel reduction paving emission reduction
14
6 2
element weight
0.97
ELEMENT DESCRIPTION
∑FS of sub criteria
FL x Mean = Factor Score (FS)
SUBCRITERIA
mean
CRITERIA
Factor Loading (FL)
ID
Table 31 Weightage Factor for Elements Description
0.143
0.500 0.500 1.000 0.500
8
9
0.500
0.231 13
0.69
3.92
3
0.68
4.20
3
0.231
0.67
3.86
3
0.375
0.72
4.02
3
0.55
3.96
2
0.87
4.15
4
8
0.231
0.375 0.250 0.571
7 0.83
4.16
3
0.85
3.68
3
0.429 7
0.429
APPENDIX E1
196
Weightage Factor for Elements Description
EWM1
reduction
environment al management system (EMS)
EMS certification
EWM2
runoff flow control (rate & quantity) storm water runoff quantity
disaster cost analysis
EWM3
drainage system (network)
storm water runoff quality
water pollution reduction
area design to avoid impacts to environmental resources design to reduce urban ‘heat island’ effect firms shall meet the requirement of ISO 14001 firms shall establish, document, implement, maintain and continually improve an EMS for the entire duration of the project manage water flow dissipation on road surface during design stage reduce runoff quantity during design and construction stage (Malaysia Urban Stormwater Management Manual & Malaysia Highway Authority Manual) storm water control facilities (detention or retention) determine the critical volume of water to be stored by hydrograph (Malaysia Urban Stormwater Management Manual , Road Engineering Association of Malaysia, Public Works Department, Department of Irrigation and Drainage) minimize the increase of impervious area due to project (Inclusion of “permeable pavement” such as grid pavers if practical) conduct lifecycle cost analysis (LCCA) for storm-water impact in design stage drainage depth 1.2-1.5 m design for public safety (Malaysia Urban Stormwater Management Manual ) detect and eliminate any nonstorm water discharges from unpermitted sanitary or other residential, commercial or industrial sources detect non-storm water discharges from unpermitted sanitary or other residential, commercial or industrial sources that enter the Right of Way or flows that ultimately discharge to the Right of Way but which cannot be eliminated ensure entire waste water treatment (toll plaza, R&S areas, roadway landscape) to comply with the local authority requirement level of water quality before discharge to natural water bodies (river, lake, bay) - National
0.55
3.93
2
0.286
0.45
4.03
2
0.286
0.94
3.75
4
0.571
0.72
3.81
3
0.429
0.76
3.62
3
0.214
0.84
3.8
3
0.214
0.87
3.79
3
0.214
7
15 0.76
3.74
3
0.214
0.61
3.66
2
0.143
0.84
3.60
3
3
1.000
0.75
3.62
3
3
1.000
0.82
3.67
3
0.77
3.49
3
0.333
0.333 24
0.72
3.79
3
0.333
APPENDIX E1
197
Weightage Factor for Elements Description
runoff treatment and water bodies protection
EWM4
habitat restoration & protection
ecosystem protection and preservation
site vegetation
tree & plants communities
ecological connectivity
Water Services Commission, Department of Environment demonstrate, the use of models reduction of pollutant loadings to adjacent water resources using Best Management Practices Instrumentation to monitor and analyse pollutants in runoff and water bodies use of Low Impact Development and Best Management Practices (wet or dry swales, sand filters, bio retention, storm water treatment systems, grass channels, buffer zone, use of highly permeable soil, etc.) to address 90% of annual rainfall event to meet regulatory requirements (Malaysia Urban Stormwater Management Manual , Public Works Department, Department of Irrigation and Drainage) erosion and sedimentation control plan: design includes sound erosion and sediments control practices to protect highly erodible soils, special provisions for soil erosion control at stream crossings, and staging construction to minimize soil exposure protection from materials entering waterway on bridge demolition and construction wetland restoration, reduce the total disturbed cut and fill areas off Right of Way to the minimum level provide buffer zone (Department of Wildlife and National Parks , Department of Environment ) no open burning limiting trees cutting within 5 meters off Right of Way each side planting trees to replace those cut within the Right of Way, planting shrubs and native plants alongside the right-of way avoid irrigative and invasive plants -slope protection as soon as clearing work completed replanting/relocate /preserve/expand native vegetation in reclaimed work areas or in abandoned old alignments wildlife crossing that allow for safe passage roadways and provide road
0.78
3.67
3
0.200
0.81
3.76
3
0.200
0.73
3.71
3
0.200 15
0.89
3.56
3
0.200
0.81
3.59
3
0.200
0.69
3.67
3
0.375
0.62
3.66
2 11
0.250
0.76
3.79
3
0.375
0.8
3.87
3
0.375
0.82
3.89
3
0.375 5
0.44
3.71
2
0.71
3.86
3
0.48
3.88
2
0.86
3.85
3
0.250
3
15
1.000
0.143 0.214
APPENDIX E1
198
Weightage Factor for Elements Description
MT1
reused and recycled industrial byproducts
innovation technology
recycled materials for sub-grade improvement / soil stabilization
reflectance of sunlight energy (ALBEDO & SRI)
MT2
reuse of top soil
reduce, reuse and recycle
reused and recycled of non-hazardous materials earthwork balance
MT3
usage of local materials
economical materials and pavement
long lasting pavement design life Usage of Reclaimed Asphalt Pavement (RAP) and
barriers to avoid road kills within sensitive ecosystem; bridge and culvert use of the natural – bottomed culvert mitigate of habitat fragmentation through techniques such as ecoviaducts enhancement to existing wildlife allow the locally industrial byproducts to be reused and recycled in highway construction either in flexible or rigid pavement such as by using steel slag, fly ash, crumb rubber, etc. allow the usage of recycled materials for sub-grade improvement / soil stabilization, if it can be proved that the process will reduce the consumption of virgin materials, cost of project, and will not bring any harm / effect to the road users and environment. any surface of pavement with lighter colour has higher albedo effect, which indicates high reflectance of sunlight from surface pavement whereas darker colour has lower albedo effect, which shows the low reflectance of sunlight from surface pavement allow the reuse of top soil that has been removed from grading as long as it is non-contaminated soils. allow the reused and recycled of non-hazardous materials in design or during highway construction for other base layers, shoulder, drainage, and highway furniture (signage, guardrail, etc.) balancing cut and fill quantities can reduce the need for transport of earthen materials allow the usage of local materials in highway project depending on the location of the project site, whenever practical. allow long lasting pavement design life to avoid frequent rehabilitation, thus depending on the Average Daily Traffic, ADT and types of pavement that will be going to construct. use of Reclaimed Asphalt Pavement (RAP) to produce new pavement that can minimize the dumping of RAP in landfill, reduce the consumption of virgin
0.81
3.72
3
0.214
0.85
3.73
3
0.214
0.79
3.76
3
0.214
0.80
3.62
3
3
1.000
0.74
3.61
3
3
1.000
0.99
3.50
3
3
1.000
0.92
3.93
4
4
1.000
0.89
3.75
3
3
1.000
0.61
3.92
2
2
1.000
0.96
3.79
4
4
1.000
0.63
3.96
2
2
1.000
0.61
3.70
2
2
1.000
APPENDIX E1
199
Weightage Factor for Elements Description Recycled Concrete Material (RCM)
storm-water runoff quality and flow water control improvement reduction of noise level
MT4
soil biotechnical engineering treatments green scenery implement green technique to control soil erosion
EE1
enhanced commissionin g / recommissionin g of building energy systems rest & service area (RSAs) reduced electrical consumption
materials, and protecting the environment either using hot inplace recycling (HIPR) or cold inplace recycling (CIPR) methods. Application of Recycled Concrete Material (RCM) also known as crushed concrete, is a reclaimed PCC pavement material to use as coarse aggregate in aggregate surface courses, granular embankments, stabilized bases, sub-base courses and aggregate in membrane waterproofing and in drainage layers as protection against erosion. Low Impact Development stormwater controls must be considered in any highway project that construct porous pavement. the speed that more than 80 km/h could contribute noise disruption and the range of noise level is depending on the types of surface pavement any highway project that utilize soil biotechnical engineering treatments, which is the combination of plant materials and structural elements that can protect slope and control the erosion. for examples, vegetated gabion, vegetated crib wall, etc. any highway project that implement green techniques in order to control the soil erosion, protect the slope and embankment such as turfing, planting native vegetation, hydro seeding, soiltire vegetation, etc. updating Rest and Service Area building operation plan providing training for Rest and Service Area management staff Implementing improvement to Rest and Service Area building's major energy- using system to optimize energy performance for project designs that reduce electrical consumption beyond typical measures. Specifically: § Solar/battery powered street lighting or warning signs. § Replace overhead sign lighting with higher type retro-reflective sign panels. § Energy efficiency street lighting For project designs that include more traditional practices to reduce electrical consumption;
0.73
3.71
3
3
1.000
0.72
3.72
3
3
1.000
0.92
3.81
4
4
1.000
0.96
3.94
4
4
1.000
1.02
3.86
4
0.84
4.06
3
0.400 0.300 10
0.79
3.96
3
0.300
0.91
3.75
3
0.500 6
0.87
3.78
3
0.500
APPENDIX E1
200
Weightage Factor for Elements Description
sustainable infrastructures
enhanced commissionin g / recommissionin g of building energy systems
EE2
toll booth (air quality for indoor environment) toll plaza electrical submetering
EE3
lighting zone
energy plan for Green Performance (GPC) strategies
green energy policies
specifically: § Use of energy efficient warning signs/flashing beacons. § Install existing street/sign lighting with high efficiency types. provide signboard to inform drivers to switch off engine luminosity of the street light installation of lighting system with high efficiency type providing training for toll plaza management staff implementing improvement to toll plaza's major energy- using system to optimize energy performance developing a commissioning or on- going commissioning plan for toll plaza's major energy- using system renewable energy updating toll plaza operation plan unitary air- conditioners for toll booth sensor/ automatic control devices for toll booth sensor/ automatic control devices for Air-Conditioning System unitary air- conditioners for AirConditioning System Provide separate sub-metering for 1) Lighting, AND 2) Power at each floor or tenancy Provide separate sub-metering for all energy use ≥ 100kVA. provision of auto-sensor controlled lighting in conjunction with delighting strategy for all perimeter zones and daylight areas, if any provision of motion sensors or equivalent to complement lighting zoning for at least 25% NLA all individual or enclosed spaces to be individually switched; and the size of individually switched lighting zones shall not exceed 100m² for 90% of the Natural Lighting Area ( NLA); with switching clearly labelled and easily accessible by building occupants % utilization of renewable energy in completed works. plan for promote green energy % operational energy reduction throughout the project life cycle plan for reduced electrical consumption
0.85
3.85
3
0.73
3.52
3
0.500
0.94
3.53
3
0.214
0.66
3.80
2
0.143
0.84
3.68
3
6
0.500
0.214 14
0.61
3.62
2
0.143
0.53 0.54
3.51 3.72
2 2
0.143 0.143
0.93
3.67
3
0.333
0.91
3.73
3
0.333 9
0.51
3.71
2
0.222
0.36
3.71
1
0.111
0.92
3.64
3
0..5 6
0.69
3.62
3
0.500
0.92
3.74
3
0.375
0.87
3.61
3
0.375 8
0.44
3.73
2
0.250
0.93
3.51
3
0.250
0.93
3.51
3
0.78
3.62
3
0.74
3.63
3
0.250 12
0.250 0.250
APPENDIX E1
201
energy efficiency performance
EE5
interchange
lighting control policy
energy plan for maintenance
SS1
EE4
compound and car park
EE6
Weightage Factor for Elements Description
services and facilities
sustainable highway maintenance
ITS (intelligent traffic system) installation any additional of IT application
SS2
provide any basic facilities
the lighting for car park the lighting for landscape lighting design / illumination levels Equipment that can achieve reduction of energy consumption apply Energy Maintenance Plan (EMP) emission reduction variable message sign (VMS), provided before ingress/egress other traffic control and surveillance system (TCSS) vehicle detection system (VDS) close circuit television system (CCTV) for critical area, cover all alignment along highway automatic incident detection system (AIDS) control centre system (CCS) emergency telephone system (ETS) navigation system Workshop Kiosk police beat base open area for emergency purposes
3
0.85
3.66
3
0.85
3.66
3
0.500 6
0.500 0.600
5 3.51
2
0.65
3.63
2
0.47
3.71
2
0.500
0.89
4.07
4
0.160
0.88
4.14
4
0.160
0.82
3.97
3
0.120
0.90
4.13
4
0.73
3.81
3
0.120
0.70
4.00
3
0.120
0.64
3.92
2
0.080
0.43 0.84 0.70 0.69 0.57
3.70 3.31 4.14 4.13 3.70
2 3 3 11 3 2
0.080 0.273 0.273 0.273 0.182
0.51
3.61
2
1.000
0.95
3.71
4
0.90
3.73
3
0.91
3.70
3
0.250
0.61
3.79
2
0.167
job opportunity
0.58
3.81
2
2
1.000
property value
0.63
3.92
2
2
1.000
promoting tourism activity
0.41
3.83
2
2
1.000
exhaust fan for thermal comfort purposes
business enhancement
number of retail/biz area along highway number of retail/biz area at Rest and Service Area increase in access/interchange elements traffic volume
0.400 4
25
2
0.500
0.160
0.333 0.250
pollution reduction
air and noise pollution
provide session to engage for public complaints
0.80
3.58
3
5
0.600
public acceptance
session for public complaint corporate social responsibility social impact assessment
0.80 0.61 0.67
3.58 3.51 3.81
3 2 3
8
perception
0.429 0.286 0.286
provide any aesthetic initiative
0.62
3.98
2
2
1.000
0.52
3.91
2
2
1.000
0.84
3.62
3
3
1.000
SS5
SS3
14
SS4
number of job creation new development tourism
3.57
0.48
provide additional facilities
economy
0.82
environment
environmental friendly user thermal comfort landscaping
provide any means of temperature control application 20%-30% from total highway length
APPENDIX E1
202
SS6
Weightage Factor for Elements Description management issue
road safety audit (RSA)
SS7
technology innovation
research and development
conduct Road Safety Audit Report periodically (once every 2 years) green technology budget for R&D activities to improve sustainability level for highway
0.74
3.59
3
3
1.000
0.69
3.71
3
3
1.000
0.68
3.74
3
3
1.000
APPENDIX E2 Weightage Factor for Sub-Criteria
203
waste management
air pollutants
SDCA2 SDCA3
equipment and machineries efficiency
SDCA4
quality management
SDCA5
context sensitive design
SDCA6
erosion and sedimentation control alignment selection
EWM2
EWM1
noise mitigation control
SDCA7
innovation
environmental management system (EMS)
storm water runoff quantity
technique equipment natural source & emission reduction
management plan and training
design flexibility
erosion and sedimentation plan
environmental impact reduction
EMS certification
runoff flow control (rate & quantity) disaster cost analysis drainage system (network)
0.64
3.72
2
0.92 0.84
3.55 3.63
3 3
0.74
3.62
3
0.333
0.96 0.72 0.69 0.68 0.67 0.72
4.24 4.13 3.92 4.20 3.86 4.02
4 3 3 3 3 3
0.308 0.231 0.231 0.231 0.375 0.375
0.55
3.96
2
0.250
0.87
4.15
4
0.571
0.83
4.16
3
0.85 0.55
3.68 3.93
3 2
0.45
4.03
2
0.286
0.94
3.75
4
0.571
0.72
3.81
3
0.76 0.84 0.87 0.76 0.61 0.84 0.75
3.62 3.8 3.79 3.74 3.66 3.60 3.62
3 3 3 3 2 3 3
14 20 4 2 6 8 2
9
1.000
9
13
13
8
8
7
7
7
7
7
7
14 20 3 3
0.286 0.214 0.143 0.214 0.143 0.500 0.500 1.000 0.500 0.500
0.333 0.333
0.429 0.429 0.286
0.429 0.214 0.214 0.214 0.214 0.143 1.000 1.000
sub criteria weight
4 3 2 3 2 2 2 2 3 3
element weight
4.12 4.10 3.85 4.01 4.17 3.77 3.90 3.60 3.90 3.86
∑FS of criteria
0.97 0.73 0.64 0.70 0.43 0.60 0.64 0.52 0.89 0.89
∑FS of sub criteria
FL x Mean = Factor Score (FS)
construction management plan
SUB-CRITERIA
mean
CRITERIA
Factor Loading (FL)
SDCA1
ID
Table E2 Weightage Factor for Sub-Criteria
0.700
0.200 0.100 0.750 0.250
1.000
1.000
1.000
1.000
1.000
1.00 0
0.700
0.150 0.150
APPENDIX E2 Weightage Factor for Sub-Criteria
EWM3
water pollution reduction storm water runoff quality
runoff treatment and water bodies protection
EWM4
habitat restoration & protection
ecosystem protection and preservation
site vegetation tree & plants communities
EE1
MT4
MT3
MT2
MT1
ecological connectivity
innovation technology
reduce, reuse and recycle
economical materials and pavement
green scenery
rest & service area (RSAs)
reused and recycled industrial by-products recycled materials for sub-grade improvement / soil stabilization reflectance of sunlight energy (ALBEDO & SRI) reuse of top soil reused and recycled of nonhazardous materials earthwork balance usage of local materials long lasting pavement design Usage of Reclaimed Asphalt Pavement (RAP) and Recycled Concrete Material (RCM) storm-water runoff quality and flow water control improvement reduction of noise level soil biotechnical engineering treatments implement green technique to control soil erosion enhanced commissioning / recommissioning of building energy systems reduced electrical consumption
EE2
sustainable infrastructures
enhanced commissioning / recommissioning of building energy systems toll plaza toll booth (air quality for indoor environment)
204
0.82 0.77 0.72 0.78 0.81 0.73 0.89 0.81 0.69 0.62 0.76 0.8 0.82 0.44 0.71 0.48 0.86 0.81 0.85 0.79
3.67 3.49 3.79 3.67 3.76 3.71 3.56 3.59 3.67 3.66 3.79 3.87 3.89 3.71 3.86 3.88 3.85 3.72 3.73 3.76
3 3 3 3 3 3 3 3 3 2 3 3 3 2 3 2 3 3 3 3
0.80
3.62
3
3
0.74
3.61
3
3
0.99
3.50
3
0.92
3.93
0.89
9 24 15
8
8 3
33
14
0.333 0.333 0.333 0.200 0.200 0.200 0.200 0.200 0.375 0.250 0.375 0.375 0.375 0.250 1.000 0.143 0.214 0.214 0.214 0.214
0.375
0.625
0.242
0.242 0.091
0.424
1.000
0.333
1.000
0.333
3
1.000
0.333
4
4
1.000
0.444
3.75
3
3
1.000
0.333
0.61 0.96 0.63
3.92 3.79 3.96
2 4 2
2 4 2
1.000 1.000 1.000
0.222 0.286 0.143
0.61
3.70
2
2
1.000
0.143
0.73
3.71
3
3
1.000
1.000
0.72
3.72
3
3
1.000
1.000
0.92
3.81
4
4
1.000
0.500
1.000
0.500
9
9
14
8 0.96
3.94
4
1.02 0.84 0.79 0.91 0.87 0.85 0.73 0.94 0.66 0.84 0.61 0.53 0.54 0.93 0.91 0.51 0.36
3.86 4.06 3.96 3.75 3.78 3.85 3.52 3.53 3.80 3.68 3.62 3.51 3.72 3.67 3.73 3.71 3.71
4 3 3 3 3 3 3 3 2 3 2 2 2 3 3 2 1
4 10 6
22
6
14 37
9
0.400 0.300 0.300 0.500 0.500 0.500 0.500 0.214 0.143 0.214 0.143 0.143 0.143 0.333 0.333 0.222 0.111
0.455 0.273 0.273
0.378
0.243
APPENDIX E2 Weightage Factor for Sub-Criteria electrical sub-metering
EE4
green energy policies
compound and car park
EE5
energy plan for Green Performance (GPC) strategies
interchange
lighting control policy
EE6
EE3
lighting zone
energy plan for maintenance
sustainable highway maintenance
0.92 0.69 0.92 0.87 0.44 0.93 0.93 0.78
3.64 3.62 3.74 3.61 3.73 3.51 3.51 3.62
3 3 3 3 2 3 3 3
0.74
3.63
3
0.82
3.57
3
0.85
3.66
3
0.85
3.66
3
0.48
3.51
2
0.65
3.63
2
6
5
5
4
4
economy
pollution reduction public acceptance environment
environmental friendly user thermal comfort landscaping
management issue
road safety audit (RSA)
0.68
3.74
3
3
technology
0.61
3.84
2
2
innovation
SS1
services and facilities
provide any basic facilities provide additional facilities business enhancement number of job creation new development tourism air and noise pollution perception
research and development
0.54
3.73
2
1.000
0.500
1.000
0.400
1.000
0.500
0.89 0.88 0.82 0.90 0.73 0.70 0.64 0.43 0.84 0.70 0.69 0.57 0.51 0.95 0.90 0.91 0.61 0.58 0.63 0.41 0.80 0.61 0.67 0.62 0.52 0.84 0.74 0.69
ITS (intelligent traffic system) installation any additional of IT application
0.216
0.600
SS2
4 4 3 4 3 3 2 2 3 3 3 2 2 4 3 3 2 2 2 2 3 2 3 2 2 3 3 3
0.162
0.500 6
SS3
4.07 4.14 3.97 4.13 3.81 4.00 3.92 3.70 3.31 4.14 4.13 3.70 3.61 3.71 3.73 3.70 3.79 3.81 3.92 3.83 3.58 3.51 3.81 3.98 3.91 3.62 3.59 3.71
12
0..5 0.500 0.375 0.375 0.250 0.250 0.250 0.250 0.250
SS4
2
12
SS5
3.71
8
SS6
0.47
6
SS7
energy efficiency performance
205
25 38
11 2 12 18 2 2 2 5
5
7
7
3 3 3
9
3
2
4
0.500 0.160 0.160 0.120 0.160 0.120 0.120 0.080 0.080 0.273 0.273 0.273 0.182 1.000 0.333 0.250 0.250 0.167 1.000 1.000 1.000 0.600 0.400 0.429 0.286 0.286 1.000 1.000 1.000
1.000
0.678
0.290 0.053 0.667 1.000 1.000 1.000 1.000 1.000 0.333 0.333 0.333
1.000
1.000
1.000
0.500
1.000
0.500
56.00
APPENDIX E3
206
Weightage Factor for Criteria
SDCA2
construction management plan
noise mitigation control
SDCA3
equipment and machineries efficiency
SDCA4
quality management
SDCA5
context sensitive design
SDCA6
erosion and sedimentation control
SDCA7
alignment selection
EWM1
environmental management system (EMS)
EWM2
EWM3
EWM4
storm water runoff quantity
storm water runoff quality
ecosystem protection and preservation
3.81
3
0.76 0.84 0.87 0.76 0.61 0.84 0.75 0.82 0.77 0.72 0.78 0.81 0.73 0.89 0.81 0.69 0.62 0.76 0.8 0.82 0.44 0.71 0.48
3.62 3.8 3.79 3.74 3.66 3.60 3.62 3.67 3.49 3.79 3.67 3.76 3.71 3.56 3.59 3.67 3.66 3.79 3.87 3.89 3.71 3.86 3.88
3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 2 3 3 3 2 3 2
20 4 2 8
8
9
9
13
13
8
8
7
7
7
7
7
7
72
0.429
14 20 3 3 9 84 24 15
8
8 3 14
33
0.214 0.214 0.214 0.214 0.143 1.000 1.000 0.333 0.333 0.333 0.200 0.200 0.200 0.200 0.200 0.375 0.250 0.375 0.375 0.375 0.250 1.000 0.143
criteria weight
0.72
14
0.286 0.214 0.143 0.214 0.143 0.500 0.500 1.000 0.500 0.500 1.000 0.333 0.333 0.333 0.308 0.231 0.231 0.231 0.375 0.375 0.250 0.571 0.429 0.429 0.286 0.286 0.571
sub criteria weight
4 3 2 3 2 2 2 2 3 3 2 3 3 3 4 3 3 3 3 3 2 4 3 3 2 2 4
element weight
4.12 4.10 3.85 4.01 4.17 3.77 3.90 3.60 3.90 3.86 3.72 3.55 3.63 3.62 4.24 4.13 3.92 4.20 3.86 4.02 3.96 4.15 4.16 3.68 3.93 4.03 3.75
∑FS of main criteria
0.97 0.73 0.64 0.70 0.43 0.60 0.64 0.52 0.89 0.89 0.64 0.92 0.84 0.74 0.96 0.72 0.69 0.68 0.67 0.72 0.55 0.87 0.83 0.85 0.55 0.45 0.94
∑FS of criteria
FL x Mean = Factor Score (FS) ∑FS of sub criteria
mean
SDCA1
CRITERIA
Factor Loading (FL)
ID
Table E3 Weightage Factor for Criteria
0.700 0.273 0.200 0.100 0.750
0.111
0.250 1.000
0.125
1.000
0.181
1.000
0.111
1.000
0.097
1.000
0.097
1.000
0.083
0.700 0.238 0.150 0.150 0.375 0.286 0.625
0.242
0.242 0.091 0.424
0.393
APPENDIX E3
207
Weightage Factor for Criteria
MT1
innovation technology
MT2
reduce, reuse and recycle
MT3
economical materials and pavement
MT4
green scenery
EE1
EE2
rest & service area (RSAs)
toll plaza
EE3
energy plan for Green Performance (GPC) strategies
EE4
compound and car park
EE5
interchange
EE6
energy plan for maintenance
SS1
services and facilities
0.86 0.81 0.85 0.79 0.80 0.74 0.99 0.92 0.89 0.61 0.96 0.63 0.61 0.73 0.72 0.92 0.96 1.02 0.84 0.79 0.91 0.87 0.85 0.73 0.94 0.66 0.84 0.61 0.53 0.54 0.93 0.91 0.51 0.36 0.92 0.69 0.92 0.87 0.44 0.93 0.93 0.78 0.74 0.82 0.85 0.85 0.48 0.65 0.47 0.89 0.88 0.82 0.90 0.73 0.70 0.64 0.43 0.84 0.70
3.85 3.72 3.73 3.76 3.62 3.61 3.50 3.93 3.75 3.92 3.79 3.96 3.70 3.71 3.72 3.81 3.94 3.86 4.06 3.96 3.75 3.78 3.85 3.52 3.53 3.80 3.68 3.62 3.51 3.72 3.67 3.73 3.71 3.71 3.64 3.62 3.74 3.61 3.73 3.51 3.51 3.62 3.63 3.57 3.66 3.66 3.51 3.63 3.71 4.07 4.14 3.97 4.13 3.81 4.00 3.92 3.70 3.31 4.14
3 3 3 3 3 3 3 4 3 2 4 2 2 3 3 4 4 4 3 3 3 3 3 3 3 2 3 2 2 2 3 3 2 1 3 3 3 3 2 3 3 3 3 3 3 3 2 2 2 4 4 3 4 3 3 2 2 3 3
3 3 3 4 3 2 4 2 2 3 3 4 4
9
9 40 14
8
10 6
22
6
14
9
37 86
6 8
12
12
6
6
5
5
4
4
25 38
11
86
0.214 0.214 0.214 0.214 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.400 0.300 0.300 0.500 0.500 0.500 0.500 0.214 0.143 0.214 0.143 0.143 0.143 0.333 0.333 0.222 0.111 0.500 0.500 0.375 0.375 0.250 0.250 0.250 0.250 0.250 0.500 0.500 0.600 0.400 0.500 0.500 0.160 0.160 0.120 0.160 0.120 0.120 0.080 0.080 0.273 0.273
0.333 0.333 0.333 0.444 0.333 0.222 0.286 0.143 0.143 1.000 1.000 0.500 0.500
0.225
0.225
0.350
0.200
0.455 0.273
0.262
0.273
0.378
0.243
0.430
0.162 0.216
1.000
0.140
1.000
0.070
1.000
0.058
1.000
0.046
0.678 0.442
0.290
APPENDIX E3
208
Weightage Factor for Criteria
SS2
economy
SS3
pollution reduction
SS4
public acceptance
SS5
environment
SS6
management issue
SS7
innovation
0.69 0.57 0.51 0.95 0.90 0.91 0.61 0.58 0.63 0.41 0.80 0.61 0.67 0.62 0.52 0.84 0.74 0.69 0.68 0.61 0.54
4.13 3.70 3.61 3.71 3.73 3.70 3.79 3.81 3.92 3.83 3.58 3.51 3.81 3.98 3.91 3.62 3.59 3.71 3.74 3.84 3.73
3 2 2 4 3 3 2 2 2 2 3 2 3 2 2 3 3 3 3 2 2
2 14 18 2 2 2 5
5
7
7
9
9
3
3
4
4
0.273 0.182 1.000 0.333 0.250 0.250 0.167 1.000 1.000 1.000 0.600 0.400 0.429 0.286 0.286 1.000 1.000 1.000 1.000 1.000 1.000 58.50
0.053 0.667 0.209 1.000 1.000 1.000 1.000
0.058
1.000
0.081
0.333 0.333 0.333 1.000 0.500 0.500
0.105 0.035 0.046
APPENDIX E4
209
Weightage Factor for Main Criteria
construction management plan
SDCA2
noise mitigation control
SDCA3
equipment and machineries efficiency
SDCA4
quality management
SDCA5
context sensitive design
SDCA6
erosion and sedimentation control
SDCA7
alignment selection
EWM1
environmental management system (EMS)
EWM2
EWM3
EWM4
storm water runoff quantity
storm water runoff quality
ecosystem protection and preservation
3
0.85 0.55 0.45 0.94
3.68 3.93 4.03 3.75
3 2 2 4
0.72
3.81
3
0.76 0.84 0.87 0.76 0.61 0.84 0.75 0.82 0.77 0.72 0.78 0.81 0.73 0.89 0.81 0.69 0.62 0.76 0.8 0.82 0.44
3.62 3.8 3.79 3.74 3.66 3.60 3.62 3.67 3.49 3.79 3.67 3.76 3.71 3.56 3.59 3.67 3.66 3.79 3.87 3.89 3.71
3 3 3 3 2 3 3 3 3 3 3 3 3 3 3 3 2 3 3 3 2
4 2 8
8
9
9 72
13
13
8
8
7
7
7
7
7
7
0.429 0.429 0.286 0.286 0.571 0.429
15 21 3 3 24
84 39
15
9 35 8
0.200 0.200 0.200 0.200 0.133 1.000 1.000 0.125 0.125 0.125 0.200 0.200 0.200 0.200 0.200 0.333 0.222 0.333 0.375 0.375 0.250
main criteria weight
4.16
20
Criteria weight
0.83
14
0.286 0.214 0.143 0.214 0.143 0.500 0.500 1.000 0.375 0.375 0.250 0.333 0.333 0.333 0.308 0.231 0.231 0.231 0.375 0.375 0.250 0.571
Sub Criteria weight
4 3 2 3 2 2 2 2 3 3 2 3 3 3 4 3 3 3 3 3 2 4
Elements Weight
4.12 4.10 3.85 4.01 4.17 3.77 3.90 3.60 3.90 3.86 3.72 3.55 3.63 3.62 4.24 4.13 3.92 4.20 3.86 4.02 3.96 4.15
∑FS of main criteria
0.97 0.73 0.64 0.70 0.43 0.60 0.64 0.52 0.89 0.89 0.64 0.92 0.84 0.74 0.96 0.72 0.69 0.68 0.67 0.72 0.55 0.87
∑FS of criteria
FL x Mean = Factor Score (FS) ∑FS of sub criteria
mean
SDCA1
CRITERIA
Factor Loading (FL)
ID
Table E4 Weightage Factor for Main Criteria
0.700 0.278 0.200 0.100 1.000
0.111
1.000
0.125 0.186
1.000
0.181
1.000
0.111
1.000
0.097
1.000
0.097
1.000
0.069
0.714 0.206 0.143 0.143 0.615
0.230 0.382
0.385
0.257 0.343 0.226
APPENDIX E4
210
Weightage Factor for Main Criteria
MT1
innovation technology
MT2
reduce, reuse and recycle
MT3
economical materials and pavement
MT4
green scenery
EE1
EE2
EE3
EE4 EE5
rest & service area (RSAs)
toll plaza
energy plan for Green Performance (GPC) strategies compound and car park interchange
0.71 0.48 0.86 0.81 0.85 0.79 0.80 0.74 0.99 0.92 0.89 0.61 0.96 0.63 0.61 0.73 0.72 0.92 0.96 1.02 0.84 0.79 0.91 0.87 0.85 0.73 0.94 0.66 0.84 0.61 0.53 0.54 0.93 0.91 0.51 0.36 0.92 0.69 0.92 0.87 0.44 0.93 0.93 0.78 0.74 0.82 0.85 0.85
3.86 3.88 3.85 3.72 3.73 3.76 3.62 3.61 3.50 3.93 3.75 3.92 3.79 3.96 3.70 3.71 3.72 3.81 3.94 3.86 4.06 3.96 3.75 3.78 3.85 3.52 3.53 3.80 3.68 3.62 3.51 3.72 3.67 3.73 3.71 3.71 3.64 3.62 3.74 3.61 3.73 3.51 3.51 3.62 3.63 3.57 3.66 3.66
3 2 3 3 3 3 3 3 3 4 3 2 4 2 2 3 3 4 4 4 3 3 3 3 3 3 3 2 3 2 2 2 3 3 2 1 3 3 3 3 2 3 3 3 3 3 3 3
3
15
3 3 3 4 3 2 4 2 2 3 3 4 4
9
9 40 16
8
10 6
22
6
14
9
37
6 8
12
12
6
6
5
5
86
1.000 0.133 0.200 0.200 0.200 0.200 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 0.400 0.300 0.300 0.500 0.500 0.500 0.500 0.214 0.143 0.214 0.143 0.143 0.143 0.333 0.333 0.222 0.111 0.500 0.500 0.375 0.375 0.250 0.250 0.250 0.250 0.250 0.500 0.500 0.600
0.086
0.429
0.333 0.333 0.333 0.444 0.333 0.222 0.250 0.125 0.125 0.188 0.188 0.500 0.500
0.214
0.214 0.412 0.381
0.191
0.455 0.273
0.256
0.273
0.378
0.243
0.430
0.162 0.216
1.000
0.140
1.000
0.070
1.000
0.058
0.222
