(CAAA) include a program for prevention of significant deterioration (PSD) of air quality. The ... (http://www.epa.gov/ttn/chief/net/neiwhatis.html). 1-2 ... increase in SWWY as people obtain jobs in the region's oil and gas and related service.
AIR MONITORING NETWORK ASSESSMENT PLAN FOR SOUTHWEST WYOMING Final Network Assessment Plan STI-908003.02-3329
By: Tami H. Funk Hilary R. Hafner Sonoma Technology, Inc. 1455 N. McDowell Blvd., Suite D Petaluma, CA 94954-6503
Prepared for: The State of Wyoming Department of Environmental Quality Air Quality Division 122 West 25th St., Herschler Building Cheyenne, WY 82002
June 20, 2008
TABLE OF CONTENTS Page
Section
LIST OF FIGURES .........................................................................................................................v LIST OF TABLES...........................................................................................................................v 1.
INTRODUCTION.............................................................................................................. 1-1 1.1 Background and Key Issues...................................................................................... 1-1 1.2 Study Objectives....................................................................................................... 1-4 1.3 Wyoming Air Monitoring Network.......................................................................... 1-5 1.3.1 Background .................................................................................................. 1-5 1.3.2 Southwest Wyoming Monitoring Network .................................................. 1-6 1.4 Current State of Air Quality in the Region............................................................... 1-8
2.
TECHNICAL APPROACH ............................................................................................... 2-1 2.1 Monitoring Objectives .............................................................................................. 2-2 2.2 Project Tasks and Analysis Methods........................................................................ 2-3 2.2.1 Task 1 – Acquire Data and Review Network............................................... 2-3 2.2.2 Task 2 – Perform Site-by-Site Comparison Analyses.................................. 2-6 2.2.3 Task 3 – Perform Bottom-up Analyses ...................................................... 2-10 2.2.4 Task 4 – Perform Network Optimization Analysis .................................... 2-13 2.2.5 Task 5 – Perform Meteorological Network Assessment............................ 2-15 2.2.6 Task 6 – Develop Network Assessment Report......................................... 2-17
3.
PROJECT MANAGEMENT AND STAFFING PLAN.................................................... 3-1
4.
PROJECT SCHEDULE, DELIVERABLES, AND ORGANIZATION ........................... 4-1 4.1 Schedule and Deliverables........................................................................................ 4-1 4.2 Project Organization and Structure........................................................................... 4-1
5.
GENERAL QUALITY ASSURANCE AND QUALITY CONTROL PROCEDURES .................................................................................................................. 5-1
6.
REFERENCES................................................................................................................... 6-1
iii
This PDF document contains blank pages to accommodate two-sided printing.
LIST OF FIGURES Page
Figure 1-1.
Map of the SWWY region ............................................................................................... 1-2
1-2.
Map of SWWY including mine locations, power plants, gas processing facilities, and other stationary sources............................................................................................. 1-3
1-3.
SWWY monitoring site locations and network assessment study domain...................... 1-6
2-1.
Example of other parameters monitored analysis............................................................ 2-7
2-2.
Example of an area served analysis ................................................................................. 2-8
2-3.
Example measured concentration analysis ...................................................................... 2-9
2-4.
Example of a trends impact analysis.............................................................................. 2-10
2-5.
Example emission inventory analysis for the San Francisco Bay Area......................... 2-12
2-6.
Example suitability modeling analysis .......................................................................... 2-13
2-7.
An example SPD plot for the 20% best-visibility days at Hercules Glades Wilderness Area in Missouri ......................................................................................... 2-15
2-8.
Example results of a meteorological representativeness analysis for a network of meteorological surface stations in California ................................................................ 2-16
4-1.
Project schedule by task and deliverable ......................................................................... 4-1
4-2.
Project organization and workflow diagram.................................................................... 4-2 LIST OF TABLES Page
Table 1-1.
Summary of the SWWY air monitoring network to be assessed..................................... 1-7
1-2.
Summary of 2006 ozone, PM10, PM2.5, and NO2 concentration data for the sites in SWWY................................................................................................................. 1-8
2-1.
Summary of steps involved in performing a network assessment................................... 2-1
2-2.
Summary of monitoring site objectives and preliminary discussion ............................... 2-2
2-3.
Site-by-site, bottom-up, and network optimization assessment analyses recommended for this study and the questions that each analysis method will address ...................................................................................................................... 2-4
v
1. INTRODUCTION Southwest Wyoming (SWWY) is an area of growing energy and mineral development. With the expected growth in the region’s natural gas and mineral industries, the Wyoming Department of Environmental Quality (DEQ) Air Quality Division (AQD) is interested in ensuring that its air quality and meteorological monitoring network is capable of effectively characterizing air quality and meteorology in the region. This document represents a plan for conducting an air quality and meteorological monitoring network assessment study in SWWY. 1.1
BACKGROUND AND KEY ISSUES
SWWY is a unique region characterized by dry plains and rolling hills interspersed with buttes and sand dunes. Mountain ranges bound the area in addition to the Continental Divide, which bounds the east end of the study area. Elevations in the region range from approximately 6,100 feet above mean sea level at Flaming Gorge to over 13,000 feet above mean sea level in the Wind River Range and vegetation consists primarily of sagebrush. The region is home to several wildlife species including pronghorn antelope, mule deer, elk, and moose; a variety of small animals and rodents such as rabbits, prairie dogs, ground squirrels, and mice; and several species of birds including sage grouse and migratory birds such as golden eagles, red-tailed hawks, and ferruginous hawks. Precipitation throughout the area totals approximately 8.0 inches per year (Bureau of Land Management, 2006a). The SWWY region is geologically rich and contains an abundance of natural mineral resources; consequently, it is an area of considerable mining activity for coal, oil and gas, and trona. SWWY is also unique in that it is sparsely populated and is home to many major wildlife migratory pathways and the Bridger and Fitzpatrick Wilderness Area (Class I area), northeast of Pinedale. Air pollutants have been shown to cause both foliar damage and visibility impairment in wilderness areas. As a result, legislative mandates provide special protection for wilderness areas to preserve natural ecosystems and visibility. The 1977 Clean Air Act Amendments (CAAA) include a program for prevention of significant deterioration (PSD) of air quality. The basic objective of the PSD program is to prevent substantial degradation of air quality in areas that comply with National Ambient Air Quality Standards (NAAQS), while maintaining a margin for future industrial growth (Peterson et al., 1992). Figure 1-1 shows a map of the SWWY region.
1-1
Figure 1-1. Map of the SWWY region. In addition to the mining and minerals industries, several other industrial facilities (stationary emissions sources) are located throughout the region, including power plants and gas processing plants. Figure 1-2 shows the locations of stationary sources in SWWY as reported in the U.S. Environmental Protection Agency (EPA) National Emission Inventory (NEI) (http://www.epa.gov/ttn/chief/net/neiwhatis.html).
1-2
Figure 1-2. Map of SWWY including mine locations, power plants, gas processing facilities, and other stationary sources (U.S. Environmental Protection Agency, 2002). The region is particularly rich in minerals and is home to several major oil and gas fields and coal and trona mining operations. The oil and gas sector is experiencing significant growth presently and growth is expected to continue in the future. The Jonah and Pinedale Development Area (JPDA), located immediately to the south of Pinedale, is an area of intense oil and gas development and currently has approximately 2,000 active oil and gas wells with approximately 7,000 additional wells proposed (Bureau of Land Management, 2006a, 2007a). The LaBarge gas field is an older field located south and west of Pinedale with approximately 500 active gas wells (Wyoming Oil and Gas Conservation Commission, 2008). The Moxa Arch Field west of Green River currently has approximately 1,500 active gas wells with an additional 1,800 proposed (Bureau of Land Management, 2007b). The Hiawatha Regional Energy Development project proposes adding between 1,700 and 4,400 wells to the existing 400 active gas wells in the field located south and east of Rock Springs on the Wyoming/Colorado border (Bureau of Land Management, 2006b). As a result of the planned growth in the oil and gas sector, population is expected to increase in SWWY as people obtain jobs in the region’s oil and gas and related service industries. 1-3
1.2
STUDY OBJECTIVES
The overall objectives of this network assessment are fourfold: (1) to determine if the existing air monitoring network is meeting its original objectives ( see Section 2.1 for preliminary discussion); (2) to determine if the air quality monitoring network is adequate for characterizing current air quality and impacts from future industrial and population growth; (3) to identify potential areas where new monitors can be sited or removed to support network optimization and/or to meet new monitoring objectives; and (4) to determine the spatial representativeness of the meteorological network. To meet the study objectives, Sonoma Technology, Inc. (STI) will perform a suite of analyses to address the following questions: Monitoring Objectives •
How well does the current monitoring network support current objectives? Which objectives are being met; which objectives are not being met? Are the objective(s) not being met still appropriate concerns for AQD? If so, what monitoring is necessary to meet those unaddressed objectives? What are potential future objectives for the monitoring network?
Emissions Issues •
An increase in emissions of ozone precursors is expected because of increased industrial activity. Are the existing sites collectively capable of characterizing ozone precursor emissions? Are the existing sites capable of characterizing ozone trends (spatially and temporally)? If not, what areas lack appropriate monitoring? Where should new monitors be placed, if needed? Does the existing monitoring network support future emissions assessment, reconciliation, and modeling studies? Are there parameters (at existing sites) or new sites that need to be added to support these objectives? Specifically, should AQD establish continuous, speciated volatile organic compound (VOC) measurement capabilities?
•
Is the current network capable of adequately characterizing particulate matter (both PM2.5 and PM10)? What are the major sources influencing PM concentrations in SWWY? Does the current air monitoring network produce the data to help answer these questions? If not, where should additional PM monitors be added?
•
Are there pollutants of concern, aside from criteria pollutants, that AQD should be monitoring, given the mix of emissions sources in SWWY (e.g., VOCs, hazardous air pollutants [HAPs], diesel particulate matter [DPM], black carbon [BC], or biogenics)? If so, there may not be federal reference methods (FRMs) for these pollutants; what methods would be used to measure them? Do they warrant special studies or semipermanent installations?
Monitor Siting Issues •
Is the current monitoring network sufficient to adequately assess regional air quality conditions with respect to all criteria pollutants? If not, where should monitors be relocated or added to improve the overall effectiveness of the monitoring network? How can the effectiveness of the monitoring network be maximized? Do current monitoring sites provide data to support assessment of smoke, ammonia, and ozone/precursor 1-4
transport from outside the region, including transport from Idaho and Utah? If not, what additions should be made to the network? •
The “SWWY Operator’s Agreement” provides for a sixth special purpose monitoring site. It has been determined that this site will be established in the town of Pinedale to assess ozone concentrations in the town. What other parameters should be included at this monitoring site? Can the site fulfill other objectives? Additionally, the Jonah monitoring site was shut down because of close-in high-density emissions activity (within 100 yards). Where should this monitoring station be relocated? What will be its objective and what parameters should be monitored?
•
Given the complex terrain and meteorological conditions in SWWY, is the current meteorological network capable of characterizing meteorology in the region? What is the spatial representativeness of the current network? Should other sites or parameters be added to the existing network? Are there redundancies in the current network? Should prevention of significant deterioration (PSD) sites become permanent installations?
Public Perception Issues and Questions •
Are current monitoring sites and objectives useful in addressing the public’s perception of air quality?
•
For example, –
Because current monitoring is sparse, how can AQD assume that the SWWY region is in attainment when there are so few monitors? Why are monitors not located in every town? Should there be sites at every wellhead? Should air monitors be placed on a 10-km grid?
–
Should all of AQD’s monitors be operated by the same contractor?
1.3
WYOMING AIR MONITORING NETWORK
1.3.1
Background
Since the 1970s, the AQD Monitoring Program has been working actively to evaluate monitoring requirements and use resources effectively in the State of Wyoming. In 2006, the Monitoring Program was combined with the emission inventory, regional haze, and planning staffs to create the Air Quality Resource Management Program. The Air Quality Resource Management Program will benefit the Division by looking at monitored data in conjunction with emission inventory trends and planned development to shape AQD’s air quality management policies in the future. The AQD is responsible for protecting, conserving, and enhancing the quality of Wyoming’s air resource. The AQD helps ensure that ambient air quality in Wyoming is maintained in accordance with the NAAQS and Wyoming Ambient Air Quality Standards (WAAQS) by operating and maintaining a network of ambient air quality monitors; AQD also requires industrial pollution sources to conduct source-specific ambient air monitoring when deemed necessary. The AQD currently oversees and/or operates approximately 200 monitors throughout the state. The Wyoming monitoring network is designed to meet the following six basic ambient air monitoring objectives (Wyoming Air Quality Division, 2007) to determine: 1-5
1. 2. 3. 4. 5.
the highest concentration expected to occur in the area covered by the network; representative concentrations in areas of high population density; the impact on ambient pollution levels of significant sources or source categories; general background concentration levels; the extent of regional pollutant transport among populated areas and in support of secondary standards; and 6. welfare-related impacts (such as visibility impairment and effects on vegetation).
1.3.2
Southwest Wyoming Monitoring Network
AQD’s current network in SWWY consists of seven air and meteorological monitoring sites that measure various parameters. Five sites are classified as special purpose monitoring (SPM) sites and one is classified as a state and local air monitoring site (SLAMS). The primary purpose of the AQD’s SLAMS and SPM networks is to assess compliance with the NAAQS. AQD’s SLAMS and SPMs employ reference or equivalent method technologies and are run according to SLAMS or PSD quality assurance specifications which can be compared to the NAAQS (Wyoming Air Quality Division, 2007). The SWWY network and network assessment study domain is shown in Figure 1-3 and summarized in Table 1-1.
Figure 1-3. SWWY monitoring site locations and network assessment study domain (red boundary). Note that the Wamsutter and South Pass sites are not being assessed as part of this effort but data collected at these sites will be used for regional analyses. 1-6
Table 1-1. Summary of the SWWY air monitoring network to be assessed. Site Type
Site Name AQS ID (County)
SPM
Jonah 56-035-0098 (Sublette)
Parameters Measured
Sampling Period (Frequency)a
PM10 NOx O3 Meteorology b Camera PM10 NOx O3 Meteorology b Camera Visibility NH4 PM10 NOx O3 Meteorology b Camera
(1/1) Hourly Hourly Sub-hourly Sub-hourly (1/1) Hourly Hourly Sub-hourly Sub-hourly Sub-hourly Special study (1/1) Hourly Hourly Sub-hourly Sub-hourly
SPM
Boulder 56-035-0099 (Sublette)
SPM
Daniel South 56-035-0100 (Sublette)
SPM
Pinedale 56-035-0705 (Sublette)
PM2.5
(1/3)
SPM
South Pass 56-013-0099 (Fremont)
PM10 NOx O3 SO2 Meteorology b Aerosol
(1/1) Hourly Hourly Hourly Sub-hourly Hourly
SLAMS
Rock Springs 56-037-0007 (Sweetwater)
PM10
(1/6)
Murphy Ridge 56-041-0101 (Unita)
PM10 NOx O3 SO2 CO Meteorology b
(1/1) Hourly Hourly Hourly Hourly Sub-hourly
SPM
Site Characteristics Located in the Jonah field; rural site with high oil and gas activity. This station was discontinued in April 2008. Five miles southwest of Boulder; rural site near Pinedale-Anticline fields
Rural; upwind of oil and gas fields
Regional site; population 1,800 Rural
Neighborhood site; population 19,000 Boundary, rural
(1/1) refers to sampling conducted every day, (1/3), every third day, and (1/6), every sixth day. Meteorology at each site includes wind speed, wind direction, temperature at 2 m and 10 m, solar radiation, precipitation, pressure, and humidity
a
b
1-7
1.4
CURRENT STATE OF AIR QUALITY IN THE REGION
Currently, areas represented by SLAMS and SPM sites are in attainment for PM10, PM2.5, and ozone. Table 1-2 summarizes 2006 ozone, PM10, PM2.5, and NO2 concentration data for the sites in SWWY. Because the Murphy Ridge and South Pass sites began operation in 2007, they are not included in the table. Table 1-2. Summary of 2006 ozone, PM10, PM2.5, and NO2 concentration data for the sites in SWWY. Site Name
Ozone (ppm) 4th highest 8-hr
Pollutant PM10 (μg/m ) PM2.5 (μg/m3) Annual 24-hr Annual 24-hr (98%) 3
NO2 (ppm) Annual
Boulder
0.072
10
32
–
–
0.004
Jonah
0.069
16
87
–
–
0.01
Pinedale
–
–
–
7.1
17
–
Rock Springs
–
24
67
–
–
–
South Daniel
0.074
8
30
–
–
0.003
Notes: WAAQS standards
8-hour O3 = 0.08 ppm (current); 0.075 ppm (May 2008) Annual PM10 = 50 μg/m3 24-hr PM10 = 150 μg/m3 Annual PM2.5 = 15.0 μg/m3 24-hr PM2.5 = 35 μg/m3 NO2 =100 μg/m3 (~ 0.053 ppm) Ozone values represent the 4th highest 8-hour average concentration in 2006 PM10 24-hour values represent the highest 24-hour average concentration in 2006 PM2.5 24-hour values represent the 98th percentile concentration in 2006 Annual data represent the arithmetic mean value for 2006
The SWWY region has experienced episodes of elevated ozone during the wintertime. Ozone concentrations are high when photochemistry (i.e., reaction caused by sunlight) is enhanced. Typically, photochemistry is associated with summertime when days are longer and the intensity of sunlight is greatest. Wintertime ozone is an unusual phenomenon and is currently being studied in the Upper Green River Basin. Ozone appears to be elevated in the Basin when there are strong temperature inversions, low winds, and snow cover (providing reflected sunlight).
1-8
2. TECHNICAL APPROACH The SWWY Network Assessment will be carried out in the six general steps listed in Table 2-1. Steps 1 and 2 involve understanding the history and current state of the monitoring network (see Section 1.3). These two steps have already begun as part of the network assessment planning phase (i.e., the work involved in developing this network assessment plan). Steps 3 through 6 will be performed during the network assessment following approval of this plan. Table 2-1. Summary of steps involved in performing a network assessment. Step Description 1 Prepare or update a regional description; identify important features that should be considered for network design. 2 Prepare or update a network history that explains the development of the air monitoring network over time and the motivations for network alterations, such as shifting needs or resources. 3 Perform statistical analyses of available monitoring data. These analyses can be used to identify potential redundancies or to determine the adequacy of existing monitoring sites. 4 Perform objective or subjective situational analyses. These analyses focus on the network and individual sites in more detail, taking into account research, policy, and resource needs. 5 Suggest changes to the monitoring network on the basis of statistical and situational analyses, specifically targeted to the prioritized objectives and budget of the air monitoring program. 6 Acquire the input of state and local agencies or stakeholders and revise recommendations as appropriate.
Examples Topography, climate, population, demographic trends, emissions sources, and current air quality conditions Historical network specifications (e.g., number and locations of monitors by pollutant and by year in graphical or tabular format); history of individual monitoring sites Site correlations, comparisons to the pollutant standards, trend analysis, spatial analysis, and factor analysis Risk of future exceedances, demographic shifts, density or sparseness of existing networks, scientific research or public health needs, and other circumstances (such as political factors) Reduction of number of sites for a selected pollutant, enhanced leveraging of other networks, and addition of new measurements at sites to enhance usefulness of data Workshops, conference calls, iterative reports
The technical approach that will be used to complete the SWWY network assessment, including examples of the analyses to be performed and the questions that will be addressed by each analysis, is described in the remainder of this section.
2-1
2.1
MONITORING OBJECTIVES
As part of the development of this plan, the AQD conducted a tour of SWWY for the STI network assessment team. The tour included monitoring site and emissions source facility visits to help the network assessment team better understand monitoring site characteristics, objectives, and the emissions sources in the SWWY region. The analyses performed during the network assessment will be evaluated in the context of the overall monitoring objectives. Table 2-2 summarizes the preliminary monitoring objectives for each site at the time the sites were deployed and provides a brief preliminary discussion of current site characteristics based on site visits and discussions with AQD. Table 2-2. Summary of monitoring site objectives and preliminary discussion. Site
Objective Located in the Jonah gas field – the original purpose of this site was to Jonah measure pollutant concentrations resulting from the oil and gas field emissions. It is (SPM) currently an area of high ozone precursor emissions. Located five miles southwest of Boulder – Boulder this is a rural site intended to monitor concentrations downwind of the Pinedale(SPM) Anticline oil and gas fields. Located in a rural area to the northwest of Daniel Pinedale – the purpose of this site is to measure pollutant concentrations upwind South of the Pinedale-Anticline and Jonah oil (SPM) and gas fields Located in Pinedale (population 1,800) – Pinedale the purpose of this site is to measure PM2.5 to determine NAAQS compliance in a (SPM) populated area. Located ten miles north of Evanston on Murphy the Utah border – the purpose of this site Ridge is to monitor the air masses coming from (SPM) Utah. Located on South Pass at the southern end South Pass of the Wind River Range – the purpose of this site is to monitor air quality on the (SPM) southern end of the range. Located in Rock Springs (population Rock 19,000) – the purpose of this site is to Springs measure neighborhood scale PM10 (SLAMS) concentrations.
2-2
Discussion Due to oil and gas expansion in the region, may no longer be an appropriate location to monitor ozone. Due to high ozone precursor emissions, ozone is likely being titrated by fresh NOx emissions. Likely represents downwind pollutant concentrations.
Likely represents upwind pollutant concentrations.
Likely represents regional PM concentrations.
Began operation in 2007
Began operation in 2007
Likely represents neighborhood-scale PM10 concentrations.
2.2
PROJECT TASKS AND ANALYSIS METHODS
Techniques for assessing monitoring networks may be grouped into three broad categories: site-by-site comparisons, bottom-up analyses, and network optimization analyses. Site-by-site comparisons rank individual monitors according to specific monitoring purposes; bottom-up analyses examine data other than ambient concentrations to assess optimal placement of monitors to meet monitoring purposes; and network optimization analyses evaluate proposed network design scenarios. Site-by-site analyses will be performed in Task 2, bottom-up analyses will be performed in Task 3, and network optimization analyses will be performed in Task 4. Task 5 will involve performing the meteorological network assessment analysis. Table 2-3 lists the specific network assessment analyses recommended for this network assessment and the objectives (questions) from Section 1.2 that each analysis will address. The methods listed in Table 2-3 are the same methods prescribed in the EPA’s Ambient Air Monitoring Network Assessment Guidance document (Raffuse et al., 2007). We propose to complete the network assessment in six tasks. The following section discusses each task and corresponding analysis methods when applicable. Note that the analyses build on each other and become progressively more complex. We propose to perform the site-by-site analyses (Task 2) first followed by the bottom-up (Task 3) and network optimization analyses (Task 4). We will perform the meteorological network assessment (Task 5) concurrently with Tasks 2 through 4. The results of the analyses will be viewed holistically, combined, and synthesized to develop recommendations for modifications to the air quality monitoring and meteorological networks. The recommendations will be incorporated in the network assessment final report (Task 6). 2.2.1
Task 1 – Acquire Data and Review Network
To conduct the network assessment, the Wyoming AQD will provide STI with historical data relevant to the assessment, such as ambient pollutant concentration data, site location information (i.e., longitude and latitude), and modeling results in a ready-to-use format, such as a database or documented MS Excel spreadsheets. The Wyoming AQD will work with local organizations such as the Bureau of Land Management (BLM) and Western Regional Air Partnership (WRAP) to acquire relevant data when necessary. Geographic information system (GIS) layers and emission inventory data will also be provided by the Wyoming AQD as warranted. STI has an in-house archive of Air Quality System (AQS) data which will result in a cost savings for the data acquisition task. A qualitative evaluation of the air monitoring network objectives will be performed to address the “Monitoring Objectives” questions listed in Section 1.2. STI will work with the AQD to develop an air monitoring network history. The network history will include a summary of the monitoring activities conducted in the SWWY region, their intended purpose, and resulting studies that have been produced from data collected. The network history will include a discussion of the development of the air monitoring network over time and the motivations for network alterations, such as shifting needs or resources.
2-3
Table 2-3. Site-by-site, bottom-up, and network optimization assessment analyses recommended for this study and the questions that each analysis method will address. Page 1 of 2
Measured concentrations
Emission inventory (current and future)
Suitability modeling
9
9
9
9
9
9
Is the current network capable of adequately characterizing particulate matter (both PM2.5 and PM10)? What are the major sources influencing PM concentrations in SWWY? Does the current air monitoring network produce the data to help answer these questions? If not, where do we need to add additional particulate monitors?
9
9
9
9
9
9
2-4
Are there pollutants of concern, besides criteria pollutants, that AQD should be monitoring given the mix of emissions sources in SWWY (e.g., volatile organic compounds, hazardous air pollutants, diesel particulate matter, black carbon, or biogenics)? If so, these pollutants may not have federal reference methods (FRMs); what methods would be used to measure them? Do they warrant special studies or semi-permanent installations?
9
9
9
Meteorological representative analysis
Trend impacts
There is expected to be an increase in ozone precursor concentrations due to increased oil and gas activity. Are the existing sites collectively capable of characterizing ozone precursor emissions and ozone trends (spatially and temporally)? If not, what areas are lacking ozone monitoring? Where should new monitors be placed? Does the existing monitoring network support future emissions assessment, reconciliation, and modeling studies? Are there parameters (at existing sites) or new sites that need to be added to support these objectives?
Study Questions
Network Optimization Analyses Transported Emissions Assessment Kit (TEAK) Analysis
Number of parameters monitored
Bottom-up Analyses
Area, emissions, and population served
Site-by-site Analyses
Table 2-3. Site-by-site, bottom-up, and network optimization assessment analyses recommended for this study and the questions that each analysis method will address. Page 2 of 2
The SWWY operator's agreement" has provided for a sixth special purpose monitoring site. What will be the objectives of the monitor? Where should the site be placed in the context of the existing monitors and what parameters should be measured to meet the objectives?
9
Given the complex terrain and meteorological conditions in SWWY, is the current meteorological network capable of characterizing meteorology in the region? What is the spatial representativeness of the current network? Are there sites or parameters that should be added to the existing network? Are there redundancies in the current network? Are there prevention of significant deterioration (PSD) sites that should become permanent installations?
9
9
9
9
Meteorological representative analysis
Emission inventory (current and future)
Measured concentrations
Trend impacts
9
Network Optimization Analyses Transported Emissions Assessment Kit (TEAK) Analysis
9
Bottom-up Analyses
Suitability modeling
2-5
Is the current monitoring network sufficient to adequately assess regional air quality conditions with respect to all criteria pollutants? If not, where should monitors be relocated or added to improve the overall effectiveness of the monitoring network? How can the effectiveness of the monitoring network be maximized? Do current monitoring sites provide data to support assessment of smoke, ammonia, and ozone transport from outside of the region including transport from Idaho and Utah? If not, what additions should be made to the network?
Number of parameters monitored
Study Questions
Area, emissions, and population served
Site-by-site Analyses
9
9
2.2.2
Task 2 – Perform Site-by-Site Comparison Analyses
Site-by-site comparison analyses are those that assign a ranking to individual monitors based on a particular metric. These analyses are good for assessing monitors that might be candidates for modification or removal. Site-by-site comparison analyses do not reveal the most optimized network or how good a network is as a whole. In general, the metrics at each monitor are independent of other monitors in the network. The following steps are involved in site-by-site analysis: 1. Rank monitoring purposes by importance 2. Assess the history of the monitor (including original purposes). 3. Select a list of site-by-site analysis metrics based on purposes and available resources. 4. Weight metrics based on importance of purpose. 5. Score monitors for each metric. 6. Sum scores and rank monitors. 7. Examine lowest-ranking monitors for possible reallocation of resources. Low-ranking monitors should be examined carefully on a case-by-case basis. There may be regulatory or political reasons to retain a specific monitor. Also, the site could be made potentially more useful by monitoring a different pollutant or using a different technology. Task 2.1 – Other Parameters Monitored Analysis Air quality monitoring sites hosting monitors collocated with other measurement instruments are likely more valuable than sites at which fewer parameters are measured. In addition, the operating costs can be shared among several instruments at these sites. This analysis is performed by simply counting the number of other parameters that are measured at a physical site. Sites at which many parameters are measured are ranked highest. Figure 2-1 exemplifies how the Other Parameters Monitored Analysis is performed.
2-6
Example Analysis Other Parameters Monitored
Overview This analysis is performed by counting the number of parameters that are measured at each site. Sites that measure many parameters are ranked highest. This metric addresses two aspects of monitor value. First, collocated measurements of several pollutants are valuable for many air quality analyses, such as source apportionment, model evaluation, and emission inventory reconciliation. Second, a single site With multiple measurements is more cost-effective to operate than several geographically scattered monitors.
530330080
Number of Parameters Measured 98
530110011
14
530330023
14
530330017
11
530570018
11
530090012
10
530630001
9
AIRS Code
Example analysis in the Seattle area (EPA Region 3).
Study Domain
3
3 3
Interpretation The table to the left is an extract of an analysis performed in Seattle. The monitor locations are ranked by the number of parameters measured. As shown in the table, three monitors are located within the study domain and measure numerous parameters. The site measuring 98 parameters is the most valuable for scientific analyses, such as emission inventory reconciliation and source apportionment.
Figure 2-1. Example of Other Parameters Monitored Analysis (adapted from the EPA Network Assessment Guidance Document). Task 2.2 – Area, Emissions, and Population Served Analysis STI will acquire spatially resolved emission inventory and population density data to assess each site based on its area of population coverage and potential emissions impact. A monitor’s area of coverage (area served) can be determined using a GIS-based spatial analysis approach, the Thiessen polygons technique. For this analysis, polygons are generated based on the midpoint distance between and/or among monitoring sites. Each leg of each polygon represents the midpoint line between two monitors. Figure 2-2 presents a discussion of this analysis technique and illustrates the output polygons using a study performed in Washington State as an example. 2-7
Overview Area served was one of five site-by-site criteria used in the national-scale network assessment. In the National Assessment, the “area served” metric was used as a proxy for the spatial coverage of each monitor. Theissen polygons (also called Voronoi diagrams) are applied as a standard technique in geography to assign a zone of influence or representativeness to the area around a given point. These polygons can be determined using GIS software. Calculating Theissen polygons is one of the simplest quantitative methods for determining an area of representation around sites. This method does not take into account meteorology, terrain, and other parameters that determine zone of influence. Suitability modeling should be performed to more accurately assess representativeness. However, area and emissions served analyses are a good starting point to begin to evaluate monitor represenativeness.
Thiessan polygons showing the area served by ozone monitors (dots) in and around EPA Region 10.
Interpretation Regardless of the method for determining the boundaries of influence, the interpretation is the same. Sites with a greater area served are ranked higher than sites that only cover a small area. Sites that rank highly with this metric are valuable for interpolation, background concentration, and spatial coverage.
Figure 2-2. Example of an Area Served Analysis (adapted from the EPA Network Assessment Guidance Document). Note that this example does not include emissions or population density. This technique weights rural sites and those sites on the edges of urban areas or other monitor clusters more heavily. Calculating Thiessen polygons is one of the simplest quantitative conceptual methods for determining an area of representation around sites. However, it is not a true physical representation of the area served by a site because it does not take into account meteorology (including pollutant transport), and topography. Emissions and population served can be assessed by mapping emissions and population density in the region and then overlaying the Thiessen polygons for each monitoring site. Those sites whose polygons intersect areas of high emissions and/or population density are ranked highest. This method requires spatially resolved emission inventory data (i.e., gridded) and population data (i.e., census block level). STI will work with the Wyoming AQD to acquire spatially resolved emissions data and will acquire block-level population data from the U.S. Census Bureau for this task. To investigate the expected change in emissions and population density, we will acquire available forecasted emissions and population data. We can use emissions and population forecasts to identify areas within the network where emissions and/or population are expected to 2-8
increase relative to existing monitor locations. We will evaluate the network for three time periods if emissions estimates and population forecasts are available: 2006, 2010, and 2015. We will build upon this area served analysis in subsequent suitability modeling analyses which incorporate topography and meteorology (see Task 3.2). Task 2.3 – Measured Concentration Analysis STI will rank individual monitors based on the concentrations of pollutants measured. Monitors that measure high concentrations will be ranked higher than monitors that measure low concentrations. The results of this analysis will be used to determine monitors that are less useful in meeting the selected objective. The analysis is relatively straightforward, requiring only the site design values. The greater the design value, the higher the site rank. If more than one standard exists for a pollutant (e.g., annual and 24-hr average), monitors can be assigned a score for each standard. Figure 2-3 shows an example Measured Concentration Analysis. Overview Sites that measure high concentrations are important for assessing NAAQS compliance and population exposure (AQI) and for performing model evaluations. The analysis is relatively straightforward, requiring only the site design values. The greater the design value, the higher the site rank. If more than one standard exists for a pollutant (e.g., annual and 24-hr average), monitors can be scored for each standard.. Interpretation This metric was one of five used in the 2000 National Analysis. The map above shows the results for CO monitors. Sites in red record the highest CO concentrations and are the most valuable based on this metric. Sites in blue record the lowest values and are candidates for removal or repurposing.
Figure 2-3. Example Measured Concentration Analysis (adapted from the EPA Network Assessment Guidance Document). Task 2.4 – Trends Impact Analysis Monitors that have a long historical record are valuable for tracking trends. STI will rank monitors based on the duration of their continuous measurement records. The analysis can be as simple as ranking the available monitors based on the length of the continuous sampling record. The most important monitors are those with the longest continuous trends record. Figure 2-4 provides an example Trends Impact Analysis. 2-9
Overview One approach for determining trends impact is to rank sites based on their length of continuous sampling. Sites with the longest term of operation would score higher than those with shorter terms, since they would be more useful for long-term trend analysis. Additional factors that could be used to adjust the simple ranking scale include (1) the magnitude and direction of trends observed to date at each site, (2) the suitability of a site’s location for monitoring trends after a significant event (e.g., enactment of a specific control measure), or (3) proximity of another monitor that could be used to continue the trend record. A site may be weighted as less important if changes in sampling and analysis methodology lead to a discontinuous record. Weighing these factors would require consideration of the overall goals of the monitoring network and the importance of the historical record.
City, State
AQS SiteID
Years
Stockton, CA
06-077-1002
13
Baltimore, MD
24-510-0040
12
Los Angeles, CA
06-037-1002
11
San Francisco, CA
06-001-1001
10
Fresno, CA
06-019-0008
10
Baltimore, MD
24-005-3001
10
Los Angeles, CA
06-037-1103
9
Los Angeles, CA
06-037-4002
9
San Diego, CA
06-073-0003
9
San Francisco, CA
06-075-0005
9
San Jose, CA
06-085-0004
9
Baltimore, MD
24-510-0006
9
Sacramento, CA
06-061-0006
8
San Diego, CA
06-073-0001
8
Oxnard, CA
06-111-2002
8
Chicago, IL-IN-WI
18-089-2008
8
Baltimore, MD
24-510-0035
8
Interpretation The table above shows the number of annual average values available for tetrachloroethylene at toxics trends sites from 1990 to 2003. For this analysis, sites with the longest record would be rated higher than those with shorter records.
Figure 2-4. Example of a Trends Impact Analysis (adapted from the EPA Network Assessment Guidance Document). We recognize that there may not be adequate data for performing a long-term trends analysis for the SWWY air monitoring network. However, we also realize that it will be important to have the ability to assess air quality trends in the region and will consider future objectives in the context of this analysis. 2.2.3
Task 3 – Perform Bottom-up Analyses
Bottom-up methods are used to examine the phenomena thought to cause high pollutant concentrations and/or population exposure, such as emissions, meteorology, and population density. For example, emission inventory data can be used to determine the areas of maximum expected concentrations of pollutants directly emitted (i.e., primary emissions). Emission inventory data are less useful for understanding pollutants formed in the atmosphere (i.e., 2-10
secondarily formed pollutants). Multiple data sets can be combined using spatial analysis techniques to determine optimum site locations for various objectives. Those optimum locations can then be compared to the current network. In general, bottom-up analyses indicate where monitors are best located based on specific objectives and expected pollutant behavior. However, bottom-up techniques rely on a thorough understanding of the phenomena that cause air quality problems. The most sophisticated bottom-up analysis techniques are complex and require significant resources (time, data, tools, and analytical skill). Site-by-site and bottom-up analyses are best performed in combination. Site-by-site analyses typically identify network redundancies while bottom-up analyses identify network “holes” or deficiencies. Task 3.1 – Emission Inventory Analysis Emission inventory data are used to identify areas of high emissions density for pollutants of concern. These locations can then be compared to the current monitoring network. This analysis can be scaled to various levels of complexity, depending on available resources. At the simplest level, county-level emissions patterns, such as those in the NEI, can be compared with monitor locations. For measuring maximum precursor or primary emissions, monitors should be placed in those counties with maximum emission density. More complex methods use gridded emissions and/or species-weighted emissions, depending on their importance producing secondary pollutants of concern. For our analysis, we will spatially allocate emissions to the highest resolution possible (given the data available) and assess emission densities by pollutant. As part of this analysis, we will also assess expected changes in emissions and the spatial distribution of those changes. For example, we know that emissions activities will increase for oil and gas production over the next several years. We will acquire available emissions projections and assess the current network in the context of forecasted emissions growth. Figure 2-5 shows an example of an Emission Inventory Analysis performed in the San Francisco Bay Area.
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Example Analysis Emission Inventory
Overview Gridded emission inventory data are useful for determining areas of high emissions. At the simplest level, county-level emission data, such as the National Emission Inventory, can be compared with monitor locations. For measuring maximum precursor or primary emissions, monitors should be placed in those counties with maximum emission density (tons per year per square mile). More refined site placement decisions can be considered with more refined emission inventory data and wind data to indicate up- and downwind directions. Speciated emissions inventory data can also be used. The process of disaggregating inventory pollutants into individual chemical species components or groups of species will help determine placement of monitors that have pollutant-specific monitoring objectives.
Interpretation The two blue circles on the map show areas of high emission density with no current monitors. These areas may be good candidates for future monitoring sites.
Figure 2-5. Example Emission Inventory Analysis for the San Francisco Bay Area (adapted from the EPA Network Assessment Guidance Document). Task 3.2 – Suitability Modeling Suitability modeling is a method for identifying suitable monitoring locations based on defined criteria. Geographic map layers representing important criteria, such as emissions source influence, proximity to populated places, urban or rural land use, and site accessibility, will be compiled and merged to develop a composite map representing the combination of important criteria in a defined area. Furthermore, each map layer input will be assigned a weighting factor based on the relative importance of each layer in the overall suitability model. The results identify the best locations to site monitors based on input criteria. Figure 2-6 shows an example Suitability Modeling Analysis for Phoenix, Arizona. 2-12
Overview Suitability modeling can be used to identify favorable locations for placing monitors or to assess existing monitors. The first step of a suitability analysis involves selecting criteria that can address monitoring objectives. The second step of the analysis is to acquire and process the spatial data for the suitability model within a GIS. The third and last step is to develop and run suitability model scenarios (see analysis approach figure below).
Interpretation Suitabiltiy modeling was used to assess an existing monitoring network’s ability to capture diesel particulate matter (DPM) in Arizona. It was determined that existing monitor locations, not originally located to investigate DPM, were suitable. In addition, other locations were identified as favorable for assessing DPM impacts on the population.
Suitability model conceptual diagram. Input feature data are converted to gridded surfaces, classified to a common scale, weighted, and combined to form the output model.
Figure 2-6. Example Suitability Modeling Analysis (adapted from the EPA Network Assessment Guidance Document). 2.2.4
Task 4 – Perform Network Optimization Analysis
Network optimization techniques provide a holistic approach for examining an air monitoring network. Typically, in these techniques, scores are assigned to different network scenarios; alternative network designs can be compared with the current (base-case) design. An example of a network optimization analysis process could include the following steps: 1. Select the set of scenarios (i.e., different hypothetical network designs) to be ranked. 2. Define decision criteria for scoring each network design. 3. Gather the data necessary to calculate scores for the decision criteria. 4. Index decision criteria to a common scale. 5. Weight the criteria based on relative importance. 2-13
6. Produce initial results (ranking of scenarios). 7. Iterate – adjust scenarios, decision criteria, and criteria weighting as new information and understanding are developed. 8. Obtain feedback from stakeholder deliberation. 9. Finalize network optimization scenario results. 10. Recommend changes. Network optimization analyses are more complex than site-by-site or bottom up analyses and include techniques such as principal component analysis, monitor-to-monitor correlation, and removal bias. In addition to the site-by-site and bottom-up analyses, we will use a suite of desktop tools, the Transported Emissions Assessment Kit (TEAK), to examine probable transport, source locations, and emissions impacts. TEAK was developed to assist in determining the presence of transported emissions and resulting elevated pollutant concentrations. TEAK currently contains the following three tools: 1. Spatial Probability Density (SPD) – explores and identifies where air masses originate and travel under certain conditions (e.g., days with high measured PM2.5 values). 2. Emissions Impact Potential (EIP) – combines the SPD output with emission inventory information to measure emissions impacts at a specific site. 3. Conditional Probability Impact Assessment (CoPIA) – takes the SPD analysis a step further and determines the path of air parcels to a specific site for given site conditions; that is, CoPIA shows how SPD patterns differ from normal conditions. TEAK can be used to identify whether a monitoring site is impacted by transport from other areas. In the case of SWWY, we will investigate the presence of seasonal pollutant transport from Utah and Idaho. TEAK was applied in a study to help determine if specific source types, geographic locations, or temporal patterns of emissions sources impacting Class I areas during episodes of good or poor visibility can be distinguished (Sullivan et al., 2005). This analysis is relevant to monitoring network assessment because it can help determine whether a monitoring site is achieving its intended purpose. An example output from TEAK is shown in Figure 2-7.
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Figure 2-7. An example SPD plot for the 20% best-visibility days at Hercules Glades Wilderness Area in Missouri. Darker colors represent increased transport probability. The region to the north-northwest of the site is the site’s clean air corridor, which must be protected to maintain visibility conditions at this Class I area. Note that this analysis technique is not specific to visibility analyses. 2.2.5
Task 5 – Perform Meteorological Network Assessment
An approach similar in concept to that of the air monitoring network assessment will be applied when assessing the meteorological monitoring network. In the case of meteorological measurements, it is important to understand the robustness of the measurement network to reliably record representative atmospheric phenomena and the extent (both temporally and spatially) to which a measurement network is representative of meteorological conditions as the distance away from a measurement location increases. Site-by-site analyses (similar to those described above) will be used to determine the representativeness of a meteorological measurement network. Terrain is an important consideration when assessing a meteorological measurement network. Surface and upper-air instruments provide good coverage of atmospheric phenomena, such as eddies, low-level jets, upslope/downslope flows, etc., in areas with simple terrain. However, in areas of complex terrain, meteorological measurements may not accurately represent conditions as the distance away from the monitoring sites increases. To evaluate whether a meteorological network can adequately resolve atmospheric phenomena, STI has developed a method for estimating the spatial “representativeness” of surface and aloft meteorological measurements within a monitoring network (Knoderer and Raffuse, 2004). Generally, the closer to a measurement an area of interest is, the higher the probability the measurement is representative of the actual conditions at the area of interest; however, 2-15
geographic distance is not the only important parameter. For meteorological data, factors such as elevation, slope, time of day, season, average wind speed, and predominant wind direction can render a specific measurement site’s area of representativeness larger or smaller. Figure 2-8 shows example results of the representativeness analysis for a network of meteorological surface stations in California. Meteorological conditions indicated in green are represented well by at least one measurement site, while areas in red are not represented well by any of the sites in the network. These “areas of representativeness” were determined statistically for different seasons and times of day. The examples shown are for winter morning and night hours. Areas of red suggest locations for new monitoring, while areas of green could be targeted for resource reallocation. Sites with large zones of influence are valuable to the network. Note that this analysis technique can also be applied to criteria pollutant parameters.
Figure 2-8. Example results of a meteorological representativeness analysis for a network of meteorological surface stations in California. Because the terrain in SWWY is fairly complex, this analysis will be useful for determining the representativeness of each measurement site to actual conditions, taking into account complex terrain. STI will assess the SWWY meteorological network for representativeness and identify each site’s area of representativeness. We will identify existing gaps in the meteorological network and make recommendations for changes to the network.
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2.2.6
Task 6 – Develop Network Assessment Report
STI will discuss the findings of each network assessment analysis with the Wyoming AQD and will work with the AQD to develop a set of recommendations for network modifications. These recommended modifications will be incorporated into the final network assessment report. Task 6.1 – Develop Draft Network Assessment Report STI will develop a draft Network Assessment Report that will contain the technical approach used for the network assessment, findings, and recommendations for modifications to the network. STI will craft the Network Assessment Report in the context of National Ambient Air Monitoring Strategy (NAAMS) reporting requirements set forth by the EPA and as directed by the Wyoming DEQ. A suggested outline for the draft Network Assessment Report includes the following sections: Section 1. Executive Summary of Findings Section 2. Background and Overview Section 3. Technical Approach Section 4. Findings and Results (including graphics, data summaries, etc.) Section 5. Recommendations for the Monitoring Network Section 6. References Task 6.2 – Attend Stakeholder Meeting When the draft Network Assessment Report is completed, STI personnel will travel to Rock Springs, Wyoming (tentative location), to present and discuss the report at a stakeholder meeting comprising the Wyoming AQD team and External Advisory Committee (EAC). Ms. Hilary Hafner and Ms. Tami Funk will attend the meeting. Comments and feedback provided at the stakeholder meeting will be summarized, prioritized, and incorporated into the final Network Assessment Report. Task 6.3 – Develop Final Network Assessment Report Following the stakeholder meeting, STI will revise the draft Network Assessment Report to include stakeholder comments and feedback. STI will deliver the final Network Assessment Report to Wyoming AQD in both electronic and hard-copy format. Task 6 Deliverables and Communication – Bi-weekly update calls with Wyoming AQD – Draft Network Assessment Report (electronic and hard copy) – Meeting with Wyoming AQD and EAC to discuss draft Network Assessment Report – Final Network Assessment Report, supporting data and tools, and GIS-based files.
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3. PROJECT MANAGEMENT AND STAFFING PLAN STI’s Principal Investigator (PI) for this work will be Ms. Hilary Hafner and the Project Manager (PM) for this work will be Ms. Tami Funk. Ms. Hafner and Ms. Funk will be the primary points of contact with the Wyoming AQD. The PI is responsible for providing overall technical guidance for task work and for managing budgets, resources, and quality assurance (QA) as directed by the PM. The PM is responsible for delegating task work, controlling financial and labor resource usage (which are monitored by STI’s automated accounting system), assuring the development of suitable work products, and reporting project progress and status to the Wyoming AQD PM through bi-weekly teleconferences and monthly progress letters. STI’s Chief Scientific Officer, Dr. Paul Roberts, will serve as STI’s Senior Advisor and QA/QC officer and be an additional point of contact with the Wyoming AQD PM as needed. He will independently review budget and labor resource allocations, monitor project progress according to the project schedule, and be responsible for conducting or delegating internal technical peer review of all work products before delivery to the Wyoming AQD. The project management staff are experienced at handling changes, planning for contingencies, and remaining flexible to ensure that this project, as are all projects, is given the priority needed to meet the schedule. STI proposes to complete this project with the services of the project management and technical support staff members whose short biographical paragraphs follow. Resumes and publications lists for these key staff members and all other technical support staff are available at . STI staff are uniquely and solidly qualified to perform the work, having completed similar projects for the EPA and other state, local, and international government clients. Hilary R. Hafner is Vice President and Division Manager of Air Quality Data Analysis and is the PI for this project. Ms. Hafner oversees air quality data analyses including source apportionment and monitoring network assessment. She is a nationally recognized expert on air toxics and source apportionment. Ms. Hafner has served as PI and given technical guidance on PM, air toxics, and ozone precursor data analysis and network assessment projects for the EPA, Lake Michigan Air Directors Consortium (LADCO), Arizona Department of Environmental Quality (ADEQ), Central Regional Air Planning Association (CENRAP), and U.S. tribes. Ms. Hafner’s data analysis projects have involved obtaining, processing, managing, and validating air quality data sets; developing various graphical methods to display data; performing statistical analyses including cluster, factor, and source apportionment analyses, statistical summaries, regression analyses, and trend analyses; interpreting the data relative to current chemical models; and documenting and presenting analysis results. Tami H. Funk is the Manager of the Environmental Data Analysis group and is the PM for this work. Ms. Funk’s areas of expertise include project management and the use of technology-based tools to display, develop, and analyze environmental data. Ms. Funk worked on a network assessment study for the ADEQ and helped develop some of the network assessment methods included in the EPA Network Assessment Guidance Document (Raffuse et al., 2007). Ms. Funk has extensive experience using spatial analysis techniques to quality assure, analyze, and develop applications for displaying and manipulating environmental data. Ms. Funk has used advanced statistical methods for mapping ozone and PM data to support the 3-1
EPA’s AIRNow public awareness program. She has worked with health researchers at University of California at Los Angeles, University of Southern California, and the National Institute of Health to develop state-of-the-science methods for improving spatial data for applications requiring a high degree of spatial resolution and accuracy. Her experience with emission inventories includes inventory quality assurance and reconciliation of emissions estimates with ambient data. Dr. Paul T. Roberts is Executive Vice President and Chief Scientific Officer at STI and will serve as the QA/QC officer and Senior Advisor. Dr. Roberts has designed and managed a number of air quality field, data management, and data analysis projects. Most of these projects involve the use of field data and analysis methods to understand important meteorological, air quality, and exposure phenomena. These projects have focused on a range of issues, including ozone, PM10 and PM2.5, visibility, toxics, carbon monoxide (CO), and meteorology. Dr. Roberts was the Technical Coordinator for the California Regional PM10/PM2.5 Air Quality Study (CRPAQS) Anchor Site Operations and was the project technical expert for several of the PM and gaseous instruments for CRPAQS. Dr. Roberts was the PI for the Boundary Layer Study over the Central and Western Gulf of Mexico and the Breton Aerometric Monitoring Study – Phase II, both of which were sponsored by the U.S. Department of the Interior, Minerals Management Service (MMS). He designed and managed the field measurements and data analyses for the Sacramento Area Ozone Study, the MMS-sponsored Gulf of Mexico Air Quality Study, the EPA-sponsored Paso del Norte Ozone Study, a long-term epidemiologic study in Southern California, and the exposure measurements for the Fresno Asthmatic Children’s Environment Study (FACES). Dr. Roberts co-led air quality and meteorological field measurement and data analysis efforts for the 1996-1997 Clark County CO study. Steven G. Brown is Manager of STI’s Aerometric Data Analysis group. In the past three years, Mr. Brown has managed several data analysis and source apportionment projects for LADCO, CENRAP, ADEQ, British Columbia Ministry of Water, Land and Air Protection, and the EPA. Mr. Brown led source apportionment efforts with air toxics data from multiple measurement techniques; speciated PM2.5 data from the Speciation Trends Network, IMPROVE network, and special studies; hourly VOC data from the Photochemical Assessment Monitoring Stations (PAMS) program; and continuous PM data. These efforts included validating data; developing unique and novel approaches to apply factor analysis such as PMF and PCA to different data sets; applying Conditional Probability Function (CPF) to determine wind-direction dependence of identified factors; and analyzing spatial trends in source apportionment factors from different sites within a city and region. Charley A. Knoderer is a Meteorologist II in the Meteorological Measurements and Analysis group. Mr. Knoderer has extensive experience quality-controlling radar wind profiler (RWP), sodar, and surface meteorological data and has been involved in the Central California Ozone Study (CCOS), the CRPAQS, and the 2005-2006 Texas Air Quality Study II (TexAQSII) field study for which he installed and de-installed RWPs, mini-sodars, and surface meteorological equipment. Mr. Knoderer managed the Northeast States for Coordinated Air Use Management (NESCAUM) RWP project in 2002, which involved performing quality assurance checks and setting up real-time data acquisition, quality control, and data display systems.
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Sean M. Raffuse is an Air Quality Analyst in the Environmental Data Analysis group. His efforts focus on creating and applying geospatial analysis techniques, processing and analyzing satellite data, and developing web-based and desktop GIS tools. Mr. Raffuse was the lead author on the EPA Network Assessment Guidance document (Raffuse et al., 2007). He has been involved with the design and development of several analytical tools, including the Probability of Regional Source Contribution of Haze (PORSCH) suite, which couples ensemble air mass backward trajectories with emission inventory data to help determine the causes of regional haze; an algorithm for incorporating the influence of wind direction frequency into a model of exposure to pollutants from roadways; and the AIRNow-Tech Navigator, a web-based GIS page that presents hourly pollutant, wildfire, and meteorological information collected from the EPA’s AIRNow program in an interactive geographic context.
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4. PROJECT SCHEDULE, DELIVERABLES, AND ORGANIZATION 4.1
SCHEDULE AND DELIVERABLES
We will complete the network assessment in approximately five months, assuming a project start date in mid-April 2008. A stakeholder meeting to present the results of the network assessment is tentatively scheduled for the last week of July 2008. Figure 4-1 shows the project schedule by task including deliverables. April May June July wk1 wk2 wk3 wk4 wk1 wk2 wk3 wk4 wk1 wk2 wk3 wk4 wk1 wk2 wk3 wk4 Task Network Assessment Task 1 - Data Acquisition Task 2 - Site-by-site analyses Task 3 - Bottom-up analyses Task 4 - Network optimization analyses Task 5 - Meteorological analyses Task 6 - Optional additional analyses Task 7 - Final Report & Stakeholder Meeting Bi-weekly Update Calls
Figure 4-1. Project schedule by task and deliverable. 4.2
PROJECT ORGANIZATION AND STRUCTURE
Because this project requires coordination and communication among several entities (i.e., STI, Wyoming AQD, and the EAC), it is important that the project be well-organized and that tasks be well-defined. The flowchart shown in Figure 4-2 illustrates the project organization and workflow. Note that the colors used to represent tasks in Figure 4-2 correspond to the task durations in the project schedule (Figure 4-1).
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Network Assessment Project Workflow Diagram
Task 1
Data Acquisition Network Review
Perform site-by-site analyses
Perform bottom-up analyses
Perform meteorological analyses
Perform network optimization analyses
Task 2
Task 3
Task 4
Meeting AQD
Task 5
Document findings and develop recommendations Draft Network Assessment Report
The optional visibility task will be incorporated into the overall network assessment to gain efficiency. Throughout the project duration, STI will participate in bi-weekly conference calls with Wyoming AQD to report findings and project status.
Task 6
Meeting AQD & EAC
Final Network Assessment Report
Figure 4-2. Project organization and workflow diagram.
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5. GENERAL QUALITY ASSURANCE AND QUALITY CONTROL PROCEDURES To ensure that the Network Assessment Plan and corresponding network assessment are of the highest quality and accuracy, taking into account the underlying information available, it is imperative that project activities and tasks be coordinated, reviewed, and agreed upon by both the Wyoming AQD and the STI PM. Specifically, the STI PM will engage in bi-weekly teleconferences with the Wyoming AQD PM to discuss project progress, findings, and future direction. Tasks will be performed according to plan unless changes are discussed and agreed upon by both parties. To ensure effective budget and labor allocation management, the STI PM will regularly provide project budget and schedule information to the Wyoming AQD. The EAC will have the opportunity to review and provide feedback on draft deliverables at the discretion of the Wyoming AQD. Feedback provided by the Wyoming AQD and the EAC will be addressed and incorporated into the final project deliverables as appropriate. In addition, all deliverables will be reviewed by both the PI and Quality Assurance Manager. A data quality management plan is important in any study. A data quality management plan minimizes the likelihood of faulty post-processing or computer equipment failure, maximizes the likelihood that problems will be detected, and specifies means to correct problems when they occur. QA/QC and tools for handling data include a tracking system that permits a trace back to the original data source (e.g., individual survey responses can be traced back to an individual survey, etc.); a supervisor application with password protection or a chain of custody that controls who can make changes to a data set; and periodic data backups. The STI team’s QA/QC process relies on human evaluation aided by computer graphics and statistical tools. The QA/QC review includes an assessment of data formats and values, to ensure the integrity of data files. A data administration system will be used to track possession of all data sets compiled under this contract. In general, information will flow from the source of the data to the data technician to the end user, with iterative stages of review and correction as needed. At each stage of data set compilation, review, and correction, an individual will be identified who will control any alterations to the data. This protocol will minimize the possibility of introducing errors or overwriting data.
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6. REFERENCES Bureau of Land Management (2006a) Final Environmental Impact Statement, Jonah Infill Drilling Project, Sublette County, Wyoming. Prepared by the Bureau of Land Management, U.S. Department of Interior, Cheyenne, Pinedale Field Office, WY, BLM/WY/PL-06/006-1310, January. Bureau of Land Management (2006b) Scoping Notice, Hiawatha Regional Energy Development Project, Sweetwater County, Wyoming and Moffat County, Colorado. Prepared by the Bureau of Land Management, U.S. Department of the Interior, Cheyenne, Rock Springs Field Office, WY, and Little Snake Field Office, Colorado, September. Bureau of Land Management (2007a) Supplemental Environmental Impact Statement for the Pinedale Anticline Oil and Gas Exploration and Development Project, Sublette County, Wyoming. Revised draft prepared by the Bureau of Land Management, Wyoming State Office, Cheyenne and Pinedale Field Office, Sublette County, BLM/WY/PL08/001+1310, December. Bureau of Land Management (2007b) Moxa Arch Infill Gas Development Project DRAFT Environmental Impact Statement, Lincoln, Sweetwater, and Uinta Counties, Wyoming. Prepared by the Bureau of Land Management, U.S. Department of the Interior, Cheyenne and Kemmerer Field Office, WY, BLM/WY/PL-07/034+1310, October. Knoderer C.A. and Raffuse S.M. (2004) CRPAQS surface and aloft meteorological representativeness (California Regional PM10/PM2.5 Air Quality Study Data Analysis Task 1.3). Web page prepared for the California Air Resources Board, Sacramento, CA, by Sonoma Technology, Inc., Petaluma, CA. Available on the Internet at (STI-902324-2786). Peterson D.L., Schmoldt D.L., Eilers J.M., Fisher R.W., and Doty R.D. (1992) Guidelines for evaluating air pollution impacts on class I wilderness areas in California. General technical report prepared by the Pacific Southwest Research Station, Forest Service, US. Department of Agriculture, Albany, CA, PSW-GTR-136. Raffuse S.M., Sullivan D.C., McCarthy M.C., Penfold B.M., and Hafner H.R. (2007) Ambient air monitoring network assessment guidance: Analytical techniques for technical assessments of ambient air monitoring networks. Guidance document prepared for the U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC, by Sonoma Technology, Inc., Petaluma, CA, EPA-454/D07-001 (STI-905212.02-2805-GD), February. Available on the Internet at . Sullivan D.C., Hafner H.R., Brown S.G., MacDonald C.P., Raffuse S.M., Penfold B.M., and Roberts P.T. (2005) Analyses of the causes of haze for the Central States (Phase II) summary of findings. Executive summary prepared for the Central States Regional Air Planning Association by Sonoma Technology, Inc., Petaluma, CA, STI-904780.08-2754ES, August.
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U.S. Environmental Protection Agency (2002) National Emission Inventory (NEI), air pollutant emission trends, NEI emission trends data and estimation procedures, criteria pollutant data, current emission trends summaries. Available on the Internet at . Wyoming Air Quality Division (2007) Wyoming ambient air monitoring annual network plan. Prepared by the Monitoring Section, Wyoming Air Quality Division, Department of Environmental Quality, Cheyenne, WY. Wyoming Oil and Gas Conservation Commission (2008) Field menu for the LaBarge Field. Available on the Internet at .
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