Development of a Generic Methodology for ...

Development of a Generic Methodology for Assessment of Microalgae Cultivation Potential Using GIS Karabee Das, and P. Abdul Salam

Abstract-Biofuels have gained the esteem of being an important component of the renewable energy matrices in the international level. In most cases, it is the second generation biofuel which is derived from the lignocellulose agriculture and forest residue which threatens the environment like land use changes. Microalgae has been considered as an energy crop which has huge potential for biofuel production. It has the capacity for carbon dioxide fixation and detoxification of wastewater from the industries and it does not compete with the primary needs of the human being i.e. land, food and water. Many studies have been carried out to assess the technological aspects of biofuel production from the microalgae. This study reviews and develop a generic methodology for the inspection and assessment of microalgae cultivation potential in a particular site using Geographic Information System (GIS). Index terms- Biofuel, Microalgae, Geographic Information System

I. INTRODUCTION ever increasing demand for energy has led to a T hesubstantial interest in developing renewable biologically produced fuel. Burning of conventional fuel produces greenhouse gases and harmful pollutants which has led to potential threat of global warming. Due to the increasing demand of the fossil fuel, the cost of fossil fuel has risen. According to New Policies Scenario of the World Energy Outlook [1], the global energy demand increases by 40% during 2009-2035 where oil demand will increase by 18% and it is mainly driven by transport sector. The New Policies Scenario incorporates the plans and commitments given by different countries to tackle diverse problems related to energy like energy insecurity, climate change and local pollution. The annual world primary energy consumption grew by 1.8% in 2012 which was estimated to be 12477 million tonnes of oil equivalent (Mtoe), where fossil fuel consumption accounted to be 87%, with oil (33%), natural gas (24%) and Coal (30%), while other energy sources like Nuclear, hydroelectricity and renewables account for merely 4%, 7% and 2% of the total annual world energy primary consumption, respectively [2]. The carbon dioxide (CO2) emission from fossil fuel consumption in 2011 is estimated to be 33 Gtonnes [3]. The Manuscript Received K. Das was with the Energy Field of Study, Asian Institute of Technology. ([email protected]) P. Abdul Salam is with the Energy Field of Study, Asian Institute of Technology, Thailand ([email protected]; [email protected])

cause of GHG emission is mostly due to the large scale use of fossil fuels for transport, electricity and other energy generation, and thus, it has become significantly important to develop highly upgraded techniques which helps to mitigate CO2 emission [4]. Many policies has been adopted and one of its example is the Kyoto Protocol of 2012 in which participatory countries gave commitments for reduction of GHG emission by 18% below from 1990 values in the eight year period from 2013 to 2020 [5]. Thus, alternative fuels came into existence and biofuel from microalgae is considered as the most appropriate among the other existing fuels as it has a comparable quality as the fossil fuel and a minimum change is required into the existing fuel infrastructure [6]. Alternative fuels are also known as non-conventional fuels which are mainly produced from different sources of raw materials like oil-seed crops, fast-growing trees and algae. It comprises of biofuel, bio-alcohol, vegetable oil, bio-methane etc. For the production of alternative fuel, various feedstock are being considered such as the 1st generation biofuel which is derived from terrestrial crops such as sugarcane, sugar beet, maize and rapeseed which competes with the food. The 2nd generation biofuel derived from lignocellulose agriculture and forest residue threatens the environment like land use changes. Microalgae considered as the 3rd generation biofuel is the firmest contender which has the capability to produce several co-products like biofuel, bio-methane and feedstock [7]. Biofuels from microalgae has several benefits over 1 st and 2nd generation biofuels [8]. The overall objective of this study is to develop a methodology for the assessment of microalgae potential over a territory. This framework can be utilized for assessment of growth potential of microalgae as well as the analysis of the biofuel production and the quantity of carbon dioxide mitigation. II. MICROALGAE Microalgae being one of the primitive form of life is considered as planet’s most promising source of renewable biomass as it can be cultivated in large open-ponds, even in nonarable land and in brackish water [9]. They are aquatic photosynthetic micro-organisms which are happened to be thallophytic i.e., plants which lacks roots, stems and leaves. Microalgae has a very high potential for green revolution but it is essential to identify the suitable locations for growing microalgae and estimate the potential. The photosynthetic microalgae can grow in marine as well as freshwater environments and they include both unicellular and multicellular organisms. The cultivation of microalgae is

presently more expensive then the terrestrial crops, but in the coming future, more emphasis will be given on microalgae. Microalgae requires nutrients like phosphorus, carbon dioxide, nitrogen and potassium for its growth. Minimal nutritional requirements can be estimated using the approximate molecular formula of the microalgae biomass, which is CO0.48 H1.83N0.11P0.01 [10]. Other than the nutrients microalgae growth is governed by the climate controls on precipitation, solar radiation, humidity, wind, temperature land and water supply. Microalgae have the ability to fix CO2 efficiently from sources like the atmosphere, exhaust gases from industries and amounts of carbonate salts. It can also use flue gases which is exhausted by the industries, thus it works as a good sink for the carbon. Practically, microalgae growth is very fast and it can grow in most unsuitable water which cannot be consumed by human. There are numerous varieties of microalgae which grow in different environmental conditions and hence it helps in the selection of the possible species to culture in those conditions. The biofuel production from microalgae consists of several steps which determine the economic viability of the process. Although, the process of biofuel production from microalgae seems to be quite similar with other feedstock, but there are particular difference in the techniques with specific practices for example in case of cultivation, harvesting, extraction and processing techniques. In the whole process of production from microalgae it includes cultivation of cells, followed by the separation of the cells from the growing media, extraction and harvesting. There are many other different possibilities for the different processes like, recently, thermal cracking has been involved in place of transesterification for thermal decomposition or cleavage of the triglycerides and other organic compounds present in the feedstock. Microalgae has the potential to replace the existing fossil fuel as it has the capability to double its biomass within 24 hrs and while exponential growth it can grow as short as 3.5 hrs. In comparison with the other various feedstocks like agricultural crops, lignocellulose; microalgae has the capacity to give 58,700-136,900 litres oil/ha year and the average lipid content can extent up to 90% of dry weight [9, 11]. III. RESOURCES FOR SITE SELECTION Algae requires some of the basic environmental support like sufficient climatic conditions, land and water. It can be cultivated in any system including in harsh conditions with scarcity of water but it may affect the growth rate and quality of biofuel and other products [12]. There are several criteria which are to be considered for the implementation of algae cultivation unit like climate, water, land, nutrients and carbon supply, as this all factors affect the quality of the production as well as quantity [17, 7, 18, 19]. Some of the factors has been discussed below. A. Climate Solar radiation and temperature directly affects the productivity of microalgae, and the other factors like evaporation, precipitation are environmental constraints. There are many relevant factors which affect the growth of micro-

algae which includes light, temperature, pH, salinity and dissolved oxygen. Some of the factors are described below: 1) Light harvesting: Sunlight is the cheapest and the accessible source of energy for microalgae growth, but mostly it depends on the species. The microalgae activity increases with the increase in light intensity, upto 400μmolm-2s-1 [13]. But the absorption of light depends on the species of microalgae. There are many microalgal species which can switch from phototrophic to heterotrophic growth, while some other can grow mixotrophically. 2) Effect of temperature: Temperature is considered as the second most important limiting factor after light, which regulates the cellular, morphological and physiological responses of microalgae. An optimum temperature of 15-16 °C is sufficient for the cultivation of micro-algae in day-time due to the photosynthesis process but at night the temperature should be as low as 7°C. Higher temperature may result in the total culture loss and very less temperature may inhibit the cell growth. In some cases, overheating inside the bioreactors where temperature may rise upto 55°C can be observed which may result in the damage of the cell growth, so to overcome the problem evaporative water cooling systems are used which decreases the temperature to around 20-25 °C and it is economically proven. Fig. 1 shows the locations available for microalgae production under suitable temperature of 15°C or more. The zone under the rectangle shows the maximum possibility of microalgae growth.

Fig. 1. Map showing the suitable part of the world for microalgae cultivation considering the temperature [14]

B. Water resources Aquatic plants requires water for its growth, hence a sustainable source of water is essential for microalgae growth. Some of the potential sources of water resources are fresh water, seawater, brackish water, waste water and other marshes, aquifers estuaries etc. C. Land One of the most important aspect for progress to commercialization of microalgae is to find the suitable sites for economic large scale production. The generic methodology will give a basic method for site selection for microalgae cultivation and assessment of microalgae potential. Open production system or Photobioreactor system, can utilize any flat surface. Algae cultivation in one hectare

wasteland can harvest over 10-100 times of oil with respect to the other alternative fuel [15]. D. Nutrients and carbon supply 1) Carbon dioxide uptake: Higher category plants as well as microalgae can fix CO2 but latter has the higher ability to fix CO2. There are various sources through which microalgae can attain carbon dioxide such as exhausted flue gas from industrial activities, carbon dioxide from atmosphere or chemically fixed CO2 like soluble carbonates, NaHCO3 and Na2CO3. Various micro-algae species has different tolerance level for CO2 uptake, but it also depends on the pH and the CO2 concentration gradient developed by the micro-algae. In normal case, the CO2 from atmosphere (~0.0387 %( v/v)) are not sufficient for the growth of microalgae and the productivities required for full-scale biofuel production. Hence industries are also fed into the bioreactors or open pond which ranges from 5 to 15% (v/v) and can decrease the cost of separation of CO 2 in the industries. The capacity of microalgae to capture CO2 for biofuel applications almost amounts to the recycling capability of the CO2 [16]. 2) Nutrient requirements: In 1896, Molisch has observed that the mineral nutrition of the algae was not different from that of higher plants. The major nutrients required by the micro-algae include carbon, nitrogen, phosphorus, sulfur, potassium and magnesium. Carbon plays a major role in the growth of the micro-algae but there are more nutrients which are very important for the cultivation of microalgae. Nitrogen is the second most important element which is required for microalgal nutrition and then phosphorus which is mostly fed as phosphate available in the fertilizers. 3) Effect of pH: There are varieties of microalgae species where most of them are favorable to neutral pH and within them some are tolerant to higher pH (e.g. Spirulina platensis) and some are tolerant to lower pH (e.g. Chlorococcum littorale). In the microbial bioreactor system, we can observe that there is a complex relationship between CO2 concentration and pH. Higher percentage of carbon dioxide can increase the biomass productivity from the microalgae but it can have an adverse effect by decreasing the pH which will influence upon microalgal physiology. Table I gives a brief idea about the studies that has been done till date for site selection, which includes GIS. All the studies have different approach and eventually they have considered different factors for their site selection. IV. METHODOLOGY The generic methodology will give a basic method for site selection for microalgae cultivation and assessment of microalgae potential. An overall pathway for the assessment of potential of microalgae cultivation considering the factors and the required nutrients are shown in a flow diagram given in Fig. 2. The methodology has two different stages. Stage 1 comprises of examining the availability of the site considering all the factors influencing the cultivation of microalgae and stage 2 depicts the theoretical calculation of the potential of biomass from microalgae.

Stage 1 contains the methodology for site selection considering the factors for the cultivation of microalgae. All the required data and the sources from which it can be collected has been studied descriptively in this paper. The methodology, utilizes the ArcGIS software for the generation of map and Analytical Hierarchical Process (AHP) for multi-criteria evaluation of the factors. Saaty’s Analytical Hierarchical Processing model (AHP) is being used in this study to assign the priority weights to the factors which will help in identifying the best land suitability. The main purpose of AHP is to give preference to the factors relative to the other factors and their effect on the growth rate of the microalgae.

Climate

Water

30 years meteorological data of  Solar radiation  Precipitation  Relative humidity  Evaporation  Temperature

 Fresh waster  Waste water  Saline water

Land  Physical  Economic  Political  Social

Factor suitability

Nutrients  CO2 point sources  N and P sources

Geographic area selection

Multi-criteria evaluation Base map generation Map Constraints generation Select another area Suitable area

Not suitable

Stage 1 Theoretical calculation

Biomass growth model

Calculate the biomass production

Calculate the lipid production

Water calculation model

Amount of water required Land required

Carbon dioxide fixation potential

Optimum production Stage 2 Microalgae cultivation Fig. 2. A generic format to assess the microalgae potential

Not suitable

TABLE I

REVIEW OF DIFFERENT APPROACHES ON SITE SELECTION FOR ALGAE CULTIVATION Factors

Maxwell et al., 1985 [12] USDOE, 2010 [21] Lundquist et al., 2010 [22]

Wigmosta et al., 2011 [7]

Klise et al., 2011 [23]

Quinn et al., 2012 [24] Borowitzka et al. 2012 [19]

Production Type Approach

Open Pond

Open Pond

Open Pond

Open Pond

Open Pond

Open Pond

Open Pond

Subjective weighing of criteria in an additive model

Seive-Mappingbinary classification

Cost based weighting of ranked criteria in an additive model

Model oil production -Biomass Assessment tool

Model oil Production -Scenarios for 4 areas post site targeting -Incorporate costs

GIS based site target modelling

Study Area

United States United States Southwest 1:12,500,00-1:20,000,00 Unclear

California

United States-≥ 490 ha

30m×30m

30m×30m

Coastal and inland Canadian location Area of scenario location

Model oil production -Interpolation of productivity at 864 locations United States 90m×90m

90m×90m

-Urban -Agricultural -Rangelands -Lakes -Reservoirs -Wetlands -Dry salt flats -Oil and gas fields 50,000 ton/year Waste water treatment plants

10 possible sources within the study area

STAGE 1: SITE SELECTION FOR MICROALGAE CULTIVATION Below are the given methodology for the site selection and the data required with the sources from which data can be collected. A. Assessment of factors for microalgae potential 1) Factors affecting the microalgae cultivation: The major resources that pertain the growth of microalgae is the input of climate, water, land and nutrient. These factors cannot be controlled as they are nature’s gift. So, a site for potential growth of microalgae will be selected in such a way that all the factors coincide and if possible wastewater and CO2 will make it more favourable. More details about the factors affecting the microalgae cultivation has been discussed broadly under section III already. a) Climate: Climate plays a major role in the growth of microalgae as it is very sensitive for its growth condition. A flow chart has been created for the selection of data and then analysis of it, as shown in Fig. 3.

Select a site

TABLE II FACTORS AND DATA COLLECTIONS CENTERS FOR CLIMATIC CONDITIONS Factors Light

Criteria Unit Data Collection Annual average solar kWh/m2/day Meteorological radiation Stations Number of sunshine hours hours per day Agricultural Climate Temperature °C Institutes (Mountain, Humid subtropical, Tropical wet and Agricultural dry, Tropical wet, Semiresearch centers arid and Arid) Moisture Precipitation mm/year Evaporation cm Ground water level m Severe weather Hailstorm, Cyclone etc.

b) Land: Microalgae are cultivated in two different types of systems, i.e. Open pond system and Closed Photobiorectors. Open pond system is referred to the natural pond or man-made tanks and in case of Photobioreactors, it is different to that of the former is that the microalgae is grown in closed condition and the water is circulated by pumps. In the establishment of the two different systems, the minimal requirement is a flat surface land.

20-30 years of yearly meteorological data

Solar radiation

Relative Humidity

Precipitation

All land parcels

Evaporation

Air temperature

Convert all the data to Raster data Scale of each factor is given Weightage of each factor is given from AHP

Overlay all the maps Potential site Fig. 3. Flow chart for selection of potential site considering climatic conditions

The flow chart, describes that for the analysis of climatic condition, the meteorological data is required of nearly 20-30 years is required. It is very necessary to assess the climatic factors in long term basis, as the variation of the climatic conditions are happened to be in long duration. The collected data is then scrutinized and converted to RASTER data which can be feed in the ArcGIS software. Then the data is analysed by inserting the weightage from the AHP which will result in a map of the selected site. It is necessary to know about the type of data and its source of collection centres, thus, a general instruction about the data and its source has been shown in Table. II.

Social Land Use

Physical Topography Soil - Slope Geology - Elevation - Dry or shallow - Aquifer - Seismicity lake beds

Categories - Area - Industrial - Location - Wasteland - Agriculture Economic

Land value - Location - Availability of water - Proximity to transportation infrastructure - Road

Political

Land Ownership Legal - Leasing policies and cost - Acquisition of land - Public and Privately owned land - Legislation and - Area regulation - Category

ArcGIS Extraction from the map

Potential land available Fig. 4. Chart for selection of land availability

As, microalgae has the capability to grow in any degree of salinity, hence any wasteland or unwanted area can be selected for the potential site. It is necessary to search a site which can provide water for sustenance of microalgae. Microalgae being

less demanding for land and water, but for better production it is necessary to have a healthy environment for the microalgae growth. The flow chart in Fig. 4, shows the steps for data collections and selecting different factors for the selection of a particular site. The criteria for land selection has been classified into four different categories, i.e. physical, social, economic and political [21]. The four categories defines the basic classes of land with respect to its use, value and ownership. This division simplifies the difficulties related to the type of data required and its sources. Table III, gives a brief description about the different classes of land and the required data and its different possible data collection sources. The table provides a broad indication about the data that will be required for the site selection and the different sources. TABLE III INFORMATION OF DATA REQUIRED AND DATA COLLECTION

Physical

Classes of land Topography Slope 0.10, some pairwise values need to be reconsidered, the process is repeated until CR < 0.10 is reached. In the final step of the Stage 1, all the questionnaires received from the expert are used in the development of the Pair-wise comparison matrix map. And then normalization is done for the Matrix and simultaneously factor weights are estimated. Finally, from the Inconsistency Indices of Table V, Consistency ratio (CR) is calculated. It helps to measure the consistency of the judgments relative to the large number of samples of judgments. In the process of AHP, it comprises of three steps: 1. Construction of the pairwise comparison matrix 2. Computation of the factor weight 3. Estimation of the consistency ratio

STAGE 2: THEORETICAL MICROALAGE POTENTIAL

ρL

(4)

Equation 1 is used for the calculation of the Consistency Index (CI)

EMicroalgae = fL × EL +fP × EP +fC × EC

(5)

ηTransmission = ηLight distribution×ηLand Use×α×PARcomponent

(6)

ηCapture = ηPhotosynthetic × ηPhoton Utilization × (1-r)

(7)

λ max - 1 (1) CI= n-1 where λmax is the highest number of eigen value in the matrix and n is the number of factors in the matrix. TABLE V INCONSISTENCY INDICES N RI

1 0

2 3 00.58

4 5 6 7 8 9 10 11 12 13 14 15 0.9 1.12 1.241.32 1.41 1.451.49 1.51 1.48 1.56 1.57 1.59

CR =

CI RI

(2)

If the value of CR < 0.1, the judgment is said to be consistent, and if it is more than 0.1 the analysis should be repeated again as it shows inconsistency in the judgment. Suitability Maps The suitable map is formed from the weights that has been computed from the AHP analysis and then it is multiplied with the RASTER layers. As the multiplication is done the factors are reclassified for more convenience and then the final map suitable for the microalgae cultivation can be created. The weightage from the AHP is multiplied with the factors to get the final suitable map. The AHP weightage plays an important role in the suitable map as the weightage is calculated from the score has been given by the experts. The result of the AHP comes as a percentage of the different factors. All the weightage of the factors are distributed according to the opinion from the experts and all the weightage is in percentage which on calculation should sum up to 100. The most suitable factors gets the highest weightage and similarly other factors are given their weight.

CALCULATION

OF

The stage 2 gives a detailed method with mathematical model for the calculation of the potential of microalgae for the selected site in stage 1. A. Growth model The following model is simulated mainly for open raceway pond. This study will result in the theoretical production of microalgae and the lipid production from it. Some of the factors has been assumed from literature review and then sensitivity analysis has been done with respect to the solar radiation and the microalgae strain. In this generic methodology the following equations are taken into consideration for the calculation of the lipid production [26, 27]. BMproduction = MOproduction =

ηPhoton Utilization

η Transmission × ηCapture × Hs EMicroalgae

fl × BMProduction

=

Is I1

[ ln ( I )+1] I1

(3)

(8)

s

In the method of microalgae cultivation, water is required in all the processes, but before setting up a large-scale production system, it is very necessary to know the basic minimum requirement of water and the losses that might happen in the process [28]. Wr=

Bm Bc

Bm (for HR% harvesting)= Ar =

Wt Pd

(9)

MOproduction HR

(10) (11)

1) Microalgae productivity rate (BMproduction): This is the areal biomass production rate in an open raceway pond. It is the amount of algal biomass growth rate in the open pond system and it is given as mass.area-1.day-1 [29]. 2) Photon Utilization Efficiency (ηPhoton Utilization): It is also known as Bush equation. It is the fraction of captured photons utilized by microalgae [26]. It accounts for the reduction in perfect photon absorption due to different lighting conditions of the algal culture. 3) Full spectrum solar energy (Hs): This term defines the solar irradiance incident on the algal production system. The solar spectrum that falls on the Earth’s surface is a function of

many atmospheric conditions like clouds, aerosols, ozone and other gases which intervenes the spectral distribution of irradiance. Mostly the data for the full spectrum solar energy is collected from meteorological stations, agricultural research centres or from NASA maps or RET screen software [27]. 4) Photosynthetic portion of spectrum (PARComponent): It is that fraction of the solar spectrum which is essential for photosynthesis. This utilizable fraction is called Photosynthetically Active Radiation (PAR) and it is commonly between 400-700nm [26,29]. The value mostly lies between 0.43-0.46. This value doesn’t make any difference, as it vary a very small amount depending on the ratio of direct to diffusion solar irradiance. The PAR is required by the pigments to activate the electrons to produce Adenosine Triphosphate (ATP) and Nicotinamide Adenine Dinucleotide Phosphate (NADHP2). ATP and NADPH2 plays a major role in the formation of biomass, as it fixes the CO2.

is the easiest way to access data for algae. And the energy content of proteins, carbohydrates and lipid is almost the same value for most of the studies. In most of the cases, the biomass energy content i.e., EMicroalgae is 21.9 MJ.kg-1 is considered. TABLE VI BIOMASS FRACTION OF MICROALGAE Fraction Protein Carbohydrate Lipid

9) Microalgae chemical composition (fL,fP,fC): Table VII, gives the detailed information of chemical composition of different algae strains of fraction of lipid (fL), protein (fP) and carbohydrate (fC) content in percentage. TABLE VII CHEMICAL COMPOSITION OF ALGAE EXPRESSED ON A DRY MATTER BASIS (%) Strain

5) Photon energy of PAR: Photon energy is the energy which converts the PAR to the number of photons. In the PAR range, the wavelength ranges from 400-700 nm. The energy related to each wavelength is calculated by the Planck’s Law. And the weighted-average of the wavelength is taken. Considering the lowest wavelength limit, i.e., 400nm, the energy calculated by using Planck’s law. The result for 400 nm is 295 kJ/mol and for 700 nm is 171kJ/mol, hence, the weighted average for the wavelength is 217.4 kJ/mol. Planck’s law, E = hν

Anabaena cylindrical[1] Chlamydomonas rheinhardii Chlorella pyrenoidosa Chlorella vulgaris Dunaliella bioculata Dunaliella salina Euglena gracilis Porphyridium cruentum Prymnesium parvum Scenedesmus dimorphug Scenedesmus obliquus Scenedesmus quadricauda Spirogyra sp. Spirulina maxima Spirulina platensis Synechoccus sp. Tetraselmis maculate Botryococcus braunii Chlorella sp. Crypthecodinium cohnii Cylindrotheca sp.[2] Nitzschia sp. Phaeodactylum tricornutum Schizochytrium sp. Tetraselmis suecia

(12)

where, h= Planck’s constant= 6.626×10-34J.s and ν is frequency 6) Photosynthesis efficiency (ηPhotosynthetic): The photosynthesis efficiency accounts for the efficient use of PAR by the photosynthesis system. According to studies, every photosynthetic organism requires atleast eight photons to form one molecule of O2 from water. Experiments have resulted that 8-10 mol of photons are required to liberate 1 mol of O 2. In the production of one mole of O 2 by photosynthesis, it produces 3 mol ATP and 2 mol of NADPH2 [30]. Thus, the maximum efficiency for photosynthetic efficiency is 31.8%. But practically, the efficiency decreases as it is also affected by the intensity and duration of light. 7) Energy content in the biomass of microalgae (EMicroalgae): The energy content in a biomass from microalgae is the amount of light energy used for the formation of algae biomass. In general, it is calculated from the energy content of protein, lipid and carbohydrate in different strains of microalgae. In many studies, it is considered as different values ranging from 2023.75 kJg-1.

Net calorific value (MJ.kg-1) 15.5 16.7 13 15.7 38.8 37.6

[1]

Protein Carbohydrates Lipids 43-56 48

25-30 17

4-7 21

57 51-58 49 57 39-61 28-39 28-45 8-18 50-56 47 6-20 60-71 46-63 63 52

26 12-17 4 32 14-18 40-57 25-33 21-52 10-17 33-64 13-16 8-14 15 15

2 14-22 8 6 14-20 9-14 22-38 16-40 12-14 1.9 11-21 6-7 4--9 11 3 25-75 28-32 20 16-37 45-47 20-30

Nucleic acid 4-5 1-2 3-6 3-4.5 2-5 5 -

50-77 15-23

taken from [31], [2] taken from [32]

10) Annual biomass and lipid productivity: The following equation gives the theoretical annual biomass production from microalgae and the lipid productivity from the biomass. Annual biomass productivity BMannual (T/ha/yr) =BMproduction(g/m2/day) × n(days) ×10-2 (13) Annual lipid productivity

8) Energy stored in the biomass: The energy stored in the biomass describes the amount of energy captured to produce a certain amount of biomass. The energy stored mostly ranges from 20-23.75 kJ.g-1 [29]. The chemical composition of microalgae i.e., fL, fP, fc are different for different microalgae. The data can be collected from search engine oilgae.com, as it

Lipidannual(L/ha/year) = fl × BMannual(T/ha/yr)×10000/ρ(kg/L)

(14)

11) Carbon mitigation potential: Microalgae has the ability to fix carbon dioxide efficiently through photosynthesis and it is mainly converted to carbohydrates, lipids, nucleic acids and proteins. The carbon dioxide can also be provided from the flue

gas which is emitted from the industries to mitigate global warming. The CO2 fixation rate is calculated form the law of conservation of mass: Biomass molecular formula: CO0.48 H1.83N0.11P0.01 (Chisti, 2007) Mbiomass= 23.2 gram/mol: MCO2 = 44 gram/mol (Sudhakar, 2012) Table VIII gives a range of data of the factors from reviews. This data is useful for the calculation of the potential of microalgae for the biofuel production. TABLE VIII VALUES USED IN THE MODEL Name Term Unit Energy content of carbohydrates[1] EC kJ/g Energy content of lipids EL kJ/g Energy content of proteins EP kJ/g Dry mass microalgae carbohydrate fc % content fraction Dry mass microalgae lipid content fL % fraction Dry mass microalgae protein fp % content fraction[2] Solar irradiance falling on a Hs kWh/m2/day horizontal surface[3] Incident light photosynthetic I1 µmole/m2/s photon flux density (PPFD) incident on microalgae[4],[5] Saturation light photosynthetic Is µmole/m2/s photon flux density (PPFD) on microalgae[6] Photosynthetically active radiation PARComponent % of Sun Fraction of energy consumed by r respiration in microalgae Light absorption coefficient of α microalgae Land use efficiency ηLand Use % Optical light distribution ηLight distribution % Photosynthesis efficiency[7] ηPhotosynthetic %

Range 13 38.3 15.5 0.17 0.22 0.58 4.8

light falling on the cultivation system. It mainly accounts for the losses due to the construction of the system or the geometry of it. The efficiency is mostly assumed to be 90-95%. 13) Photosynthetic efficiency of microalgae: In the photosynthetic system, the algae uses light energy and CO2 to make sugars like glucose. To convert solar energy to biomass, algae absorb sunlight in the wavelength range from 400-700nm of photosynthetic efficiency of 4-6% and converting on 47% of total energy from the Sun. The biomass of algae contains energy depends on PAR, photosynthetic efficiency and transmission losses. This is the solar energy conversion into algal biomass. The photosynthesis efficiency of microalgae is given by equation 13. PEmicroalgae

=

PAR × ηphotosynthetic × Ptransmission

(15)

The theoretical maximum efficiency of solar energy conversion into biomass is approximately 11.42% by using equation 4.13, considering transmission efficiency of about 90%, PAR of about 47% and photosynthetic efficiency of 27% [27].

150-200

V. CASE STUDY 200

0.43-0.46

This study has been done on Rayong province. It is situated in the eastern part of Thailand. As shown in Fig. 6, Rayong province has many industrial estates.

0.10-0.50 1 0.98 0.96-0.98 0.27

Density of lipids usable for kg/l 0.92 𝜌L conversion to biodiesel Cell oil content fl % 15-85 Oil density Ld Kg.m-3 910-925 Depth of pond[8] Pd m 0.3-0.5 Photon Transmission Efficiency PTransmission % 90-95 [1] taken from [33], [2] taken from [34], [3] taken from [35], [4],[5] taken from [26,7], [6] taken from [27], [7] taken from [4], [8] taken from [28]

The uncertainties present in some of the term like solar radiation, energy content of carbohydrates, oil density may give some differences in result for the same site as this factors depend on the climate and the microalgae cultivated for the biofuel production. The carbon dioxide efficiency in the microalgae cultivation is given in equation 15 Total CO2 fixation = K × biomass productivity × fixation efficiency (15)

where K is rate constant and it is given by1.89 [27] Thus, the above equation will give the CO2 fixation or removal efficiency for open raceway pond or photobioreactor. Thus, it will give an idea about the category industries which can be linked up with the microalgae cultivation.

Fig. 6. Location map of Industrial Estates in Thailand [36]

12) Photon Transmission Efficiency (PTransmission): The photon transmission efficiency is the efficiency of the solar incident

Data has been collected from Thai Meteorological Department (TMD), Land Development Department (LDD) and Thailand

A. Data collection:

Institute of Scientific And Technological Research (TISTR) for Rayong district. In Fig. 7, it shows the monthly maximum and minimum temperature for Rayong area. According to TISTR, the temperature for microalgae growth in Rayong area is 28±2°C. A high temperature may also result in high evaporation and thereby water losses [22]. Thus in case of Rayong, the months from March to August is more feasible for microalgae cultivation. There are three seasons: the cool season (November to February), the hot season (April to May), and the rainy season (June to October), though monsoons rarely last for more than a couple of hours. Monthly rainfall of Rayong has been shown in Fig. 8. In the last 22 years, September and October month has the highest rainfall. Precipitation does not affect the algae production directly, but it is important while considering the siting for algae farms as it relate to the water supply [20]. Precipitation affects the water availability for a particular region like groundwater and surface water. Maximum and minimum temperatures for Rayong from 1989-2011

Temperature °C

40 30 20 10 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Months Minimum Temperature (°C)

Maximum Temperature (°C)

Fig. 7. Maximum and Minimum monthly temperatures of Rayong from 19892011[35] Rainfall (mm) in Rayong from 1989-2011

TABLE IX LIST OF DATA REQUIRED AND ITS COLLECTION SOURCES Organization 1. IEAT (Industrial Estate Authority of Thailand)

List of data 1.1 Waste water treatment plant (amount of wastewater) - whole industrial estate 1.2 Amount and name of factory in each industrial estate in Rayong province - Map Ta phut Industrial Estate - Hemaraj Eastern Industrial Estate - Padaeng Industrial Estate - Eastern Seaboard Industrial Estate - Hemaraj Eastern Seaboard Industrial Estate - Asia Industrial Estate - RIL Industrial Estate 1.3 1.3 Latitude and Longitude of each industrial estate 2. LDD (Land 2.1 Slope Development 2.3 Industrial estate location and area Department) 3. TMD (Thai 3.1 Solar radiation Meteorological 3.2 Daily sunshine hours Department) 3.3 Precipitation 3.4 Evaporation rate 3.5 Temperature (Day and Night) 3.6 Occurrence Severe weather like hailstorm, cyclone, flood etc. 4. TISTR (Thailand 4.1 Name of freshwater and marine Institute of microalgae in Rayong province Scientific and 4.2 Growth rate, lipid content Technological 4.3 Cultivation condition Research)

Location All industrial estates in Rayong province

Rayong province Map Ta Phut/ Rayong

Pathumthani

The Table X, gives the latitude and longitude of the industrial estate in the Rayong Province. It also include the waste water released from the estates. Waste water can be utilized by the researchers in the cultivation of microalgae as it detoxifies the waste water.

300 TABLE X INDUSTRIAL ESTATE OF RAYONG AND WASTE WATER IN CU.M/DAY

Rainfall (mm)

250 200

OID 0

150

1 2

100 50 0 JAN

FEB MAR APR MAY JUN

JUL AUG SEP

OCT NOV DEC

Rainfall (mm) Fig. 8. Monthly rainfall (mm) in Rayong from 1989-2011[35]

B. Data Analysis And Site Selection In the first stage of the methodology, data has been collected from different centres and processed and finally the processed data is inserted in the software ArcGIS. As a result, the final map presenting suitable sites for microalgae cultivation is produced. 1) Data Collection Centers: Table IX outlines some of the organization and list different types of data which can be acquired from that particular organization.

3 4 5 6

Industrial Estate name Eastern Seaboard Industrial Estate (Rayong) Asia Industrial estate (Ban Chang) Hemaraj Eastern Industrial Estate (Huay Pong) RIL industrial estate Map ta Phut eastern Industrial Estate Padaeng industrial estate Eastern Seaboard Industrial estate (Pluak Daeng)

Latitude LongitudeWWT 12.9285 101.4198 28000 12.7038 12.7015

101.0847 8000 101.1211 6500

12.8303 12.7040 12.6872 12.9778

101.2501 101.1439 101.1237 101.2174

16000 30000 1300 2773

2) Data Processing: Data processing, involves collection and conversion of the data so that it can be used in the ArcGIS. The collected meteorological data of last 20-30 years are interpolated between the meteorological stations present in the Rayong Province and then converted to raster data and then map is developed for individual factor. Some of the data are point factors like the waste water plants. Hence waste water data has not been interpolated by utilized as point data with considering the quantity of the waste water that has been released from the particular Industrial estate. Days with less than six hours of sunshine are considered inadequate for algae growth; thus productivity will be less during the rainy season in some area of

the country [20]. The waste water treatment (WWT) plants of the industrial estate in Rayong can be beneficial for the microalgae growth as it will supply nutrients for the microalgae growth. Solar radiation of approximately or more than 14 MJ/m2 is considered as most appropriate for algae production [37]. According to the data, Rayong has a high potential of microalgae cultivation. The number of sunshine hours is expected to affect more then the amount of the solar radiation [22]. The evaporation rate plays an important role in the open raceway pond, since in evaporation more water supply will be required which means that more evaporation will indicate a place to be selected near a water availability area. The main contribution of evaporation is water loss. While choosing a location, evaporation is a very important factor as it indirectly affects the operating costs. This is less of an issue for closed PBR’s, although evaporation help in the regulation of temperature in case of both open and closed systems [20]. Insolation and temperatures including seasonal variations are important parameters since they affect the algae productivity as well as the length of the season that could reach up to almost 300 days per year. According to TISTR, temperature about 28±2°C is favourable for microalgae growth. Temperature exceeding 40 °C or near to it, the conditions are also not optimal since the temperatures are too high for algae cultivation. Rainfall does not affect algae productivity directly, but it is important for site selection as it is related to water supply for the cultivation system. Fig. 9, is the result of the AHP and then included in the ArcGIS in which it shows the most preferable site for the microalgae cultivation. The figure shows that three industrial estates were best for the cultivation i.e., Padaeng Industrial estate, Hemaraj Eastern Industrial Estate (Huay Pong), Map ta Phut. And hence it shows that Map ta Phut is the best Industrial estate as it also has highest amount of waste water from it.

of the selected site. And then this study also includes the evaluation of carbon fixation potential of microalgae production systems and the approximate requirement of water in the cultivation system. From IEAT (2012), Map ta Phut has an overall area of 4086 acre and an unused area of 402.3 acre. Thus from the above data the water required for cultivation is calculated. Assuming the harvesting rate of 25% and algae biomass concentration of 0.25 kg/m3 and taking the value of the unused area the biomass production is 492093.36 kg/day. And thus the water required is 1968.4 ML/day for 402.3 acre. The carbon mitigation potential is 43.35 Tco2/ha/yr. VI. CONCLUSION AND DISCUSSION This study developed generic methodology for the selection of an appropriate site for microalgae cultivation considering the favourable conditions and estimation of microalgae potential at the selected site. TABLE 4.12 RESULTS FROM THE ANALYSIS Result BMproduction MOproduction Carbon fixation Water required (for 402.3 acre)

Unit g/m2/day l/ha/year TCO2/ha/yr ML

Amount 76.45 61569.62 43.35 1968.4

The validation of the model proves that the methodology can be used for approximate calculation and selection of microalgae potential. It can be seen that by sensitivity analysis, the solar radiation effects the microalgae growth to a very high extent. The carbon fixation efficiency gives an opportunity for the investors to construct large scale production near industries which can help in mitigation of carbon dioxide from the industries. The maximum possible microalgae and lipid production in Rayong is estimated to be about 76.45 g/m2/day and 61570 lt/ha/year respectively. Rayong has an about 43.35 tonne of CO2 fixation per hectare per year and high potential for biofuel production from microalgae.

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[3] Fig. 9. Final Map after AHP

C. Biomass and carbon mitigation potential The analysis of the model in equation 1-15 is done by considering the Rayong area. Equations are laid on the excel spreadsheet and then by using the values. This study is done by considering the Rayong area and the microalgae strain has been assumed to be Chlorella vulgaris. Sensitivity analysis has been done considering the solar radiation. After accomplishment of the daily microalgae productivity, it is necessary to determine the realistic productivity of oil yield

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Karabee Das received the B.Tech degree from Assam University, Assam, India, in 2011. She received the M. Eng degree in Energy from Asian Institute of Technology (AIT), Thailand, in 2013. Her research interest include biofuel, biomass and land use changes.

Dr.P. Abdul Salam is an Assistant Professor at Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology. His research interests are bioenergy (biomass, biofuel, biogas and waste to energy), rational use of energy in building, climate change mitigation and low carbon cities. He may be contacted at [email protected].