Improvements to the Spatial and Temporal Representativeness of Modeling Emission Estimates: Phase 1 Findings and Recommendations Presented by: Lyle R. Chinkin Stephen B. Reid Sonoma Technology, Inc. Petaluma, CA Presented to: The CCOS Technical Committee Sacramento, CA November 28, ?-????

2 Project Overview – Phase 1 Objective: Assess spatial and temporal allocations applied to base-year and future-year anthropogenic emission inventories (EI). Identify potential improvements. Key Benefits : Identify strengths and areas for improvement in the spatial and temporal allocations of the CCOS EIs. Rank the potential impacts of suggested improvements on the EIs. (Facilitate cost effective plan for Phase 2.)

3 Project Overview – Phase 2 Objective: Implement improvements by developing specific methods or data sets to spatially and temporally allocate anthropogenic emissions. Key Benefits : Improve photochemical modeling results by characterizing more accurately the temporal and spatial variations in ozone precursor emissions. Increase confidence in the accuracy of the EIs’ spatial and temporal variations.

4 Today’s Agenda Review and discuss the findings and recommendations produced during Phase 1. On-road mobile sources Area, off-road mobile, and point sources. Discuss potential plans for Phase 2. On-road mobile sources$215k Area, off-road mobile, and point sources$140k Final report and meetings$20k

5 On-Road Mobile Sources Findings and recommendations will be presented by Tom Kear of Dowling Associates, Inc.

Temporal Representativeness of Non-road, Area, and Point Sources Presented by: Lyle R. Chinkin Stephen B. Reid Sonoma Technology, Inc. Petaluma, CA Presented to: The CCOS Technical Committee Sacramento, CA November 28, ?-????

7 Background (1 of 5) Temporal codes are used to assign applicable temporal allocation factors (TAFs) to emission sources. TAFs allocate annualized emissions to: Months of the year Days of the week Hours of the day

8 Background (2 of 5) Statewide emissions associated with various day-of-week profiles Statewide emissions associated with various diurnal profiles

9 Background (3 of 5) Temporal variations in NO x and ROG emissions by major source type

10 Background (4 of 5) Temporal variations in NO x and ROG emissions by major source type

11 Background (5 of 5) Year-2002 annual-average emissions by major source type

12 Overview of Approach (1 of 3) Visually examined the temporal distribution of emissions Assessed existing temporal profiles and their general usage Identified and evaluated the temporal characteristics of key source categories Investigated alternatives (e.g., literature search).

13 Overview of Approach (2 of 3) Key NO x sources by region

14 Overview of Approach (3 of 3) Key ROG sources by region

15 Types of Potential Improvements 1.Corrections to temporal profile assignments for specific sources/regions 2.The incorporation of readily-available data that would increase the accuracy of temporal emission variations for specific sources/regions 3.The collection of new data that would increase the accuracy of temporal emission variations for specific sources/regions

16 Key Findings and Recommendations (1 of 7) Mis-assignments in the temporal cross-reference file need to be corrected. Day-of-week variations in emissions for the SF air basin.

17 Key Findings and Recommendations (2 of 7) Update other temporal profile assignments in the temporal cross-reference file. Diurnal profiles assigned to residential natural gas combustion.

18 Key Findings and Recommendations (3 of 7) Double-check diurnal and day-of-week temporal profiles for trains in the San Francisco Bay Area. Emissions from trains in the San Francisco Bay Area peak on the weekends.

19 Key Findings and Recommendations (4 of 7) Apply consistent temporal profiles for fuel combustion. Diurnal profiles for service and commercial fuel combustion (pictured) and for manufacturing fuel combustion vary widely between air basins and sometimes within air basins.

20 Key Findings and Recommendations (5 of 7) Apply temporal profiles recommended by STI (2001)— e.g., for architectural coatings.

21 Key Findings and Recommendations (6 of 7) Develop and apply temporal profiles for petroleum marketing. Current diurnal profiles are unlikely to represent weekend conditions. Flat monthly profiles (not pictured) can be updated based on statewide gasoline sales.

22 Key Findings and Recommendations (7 of 7) Verify the magnitude of snowmobile emissions Other (low-priority) recommendations - Develop diurnal profiles for commercial jets in the SFBA - Analyze CEM data for major point sources - Double-check seasonal patterns for planned burning

23 Phase 2 Priorities and Costs for Temporal Representativeness RecommendationLevel of Effort Reconsider temporal profiles by Chinkin et al. (2001).$5k Approximate temporal patterns for weekend light-duty vehicle activities. $15k Various and miscellaneous tasks (suggested for in-kind actions by ARB or districts). For example, Correct mis-assignments in the temporal cross-reference file. Apply monthly profiles based on statewide fuel consumption for petroleum marketing. Double-check local seasonal patterns for burning (agricultural and land management). $40k

Spatial Representativeness of Non-road, Area, and Point Sources Presented by: Lyle R. Chinkin Stephen B. Reid Sonoma Technology, Inc. Petaluma, CA Presented to: The CCOS Technical Committee Sacramento, CA November 28, ?-????

25 Background (1 of 3) For area and non-road sources, spatial allocation factors (SAFs) are used to spatially distribute county-level emissions. Current SAFs derived from spatial surrogates developed by STI in 2001 from: Land use and land cover data Demographic and socioeconomic data Location-based information 65 base-year surrogates and 26 future-year surrogates (2005, 2010, 2020) are available

26 Background (2 of 3)

27 Background (3 of 3) For point sources, location coordinates are available for individual facilities/stacks.

28 Overview of Approach Visually examined the spatial distribution of emissions Assessed existing spatial surrogate data and its general usage Identified and evaluated the spatial distribution of key source categories Investigated alternatives (e.g., literature search).

29 Key Findings and Recommendations (1 of 5) Point source locations have been reviewed by ARB and STI and no discrepancies were found. Update the spatial surrogate cross-reference file for area and non-road mobile sources. Issues include: - 49 unique EIC codes missing - Over 1,600 county/EIC code combinations unaccounted for - Current scheme makes limited use of available surrogates (14 of 65 available surrogates not utilized)

30 Key Findings and Recommendations (2 of 5) Outdated spatial surrogate data need to be updated, especially those that affect the majority of the emissions (20 of 65 available surrogates).

31 Key Findings and Recommendations (3 of 5) Future-year spatial distributions need to be prepared so that they represent future land use patterns. Future urbanization (red) overlaid on base-year agricultural lands (green) produces affected agricultural lands (blue) for future years.

32 Key Findings and Recommendations (4 of 5) The spatial distribution of recreational boats should account for popularity or restrictions on boating use at different bodies of water. Survey results (right) produce a different spatial distribution than simple surface area of water (left) in the Midwest.

33 Key Findings and Recommendations (5 of 5) The spatial distribution of construction activities should be improved for the base year and future years, potentially on the basis of construction permits and proposed developments. Residential completions in 2002 for Greater Phoenix.

34 Phase 2 Priorities and Costs for Spatial Representativeness RecommendationLevel of Effort Use a land-use allocation model, such as UPLAN, to generate future-year spatial surrogates. or Follow a low-cost approach. (Calculate differences in future- year housing or commercial building density projections.) $150k-$200k or $15k-$20k Update the SAFs by gathering the most recent versions of surrogate data. 30k Further refine SAFs by using newly available, better data.10k Conduct a statewide survey to improve spatial distribution of recreational boating activities. $80k Various and miscellaneous tasks (suggested for in-kind actions by ARB or districts). For example, Correct emissions for snowmobiles and commercial jets. Update spatial surrogate cross-references. $15k

35 Recommended Tasks for Phase 2 Funding RecommendationLevel of Effort Produce Final Report and attend final meeting.$20k Produce forecasts for on-road mobile sources: revise trip tables, run DTIM, and grid results. $80k Reconsider temporal profiles by Chinkin et al. (2001).$5k Use a land-use allocation model, such as UPLAN, to generate future-year spatial surrogates. or Follow a low-cost approach. (Calculate differences in future- year housing or commercial building density projections.) $150k-$200k or $15k-$20k Update the SAFs by gathering the most recent versions of surrogate data. 30k Further refine SAFs by using newly available, better data.10k

36 Recommended Tasks for Phase 2 Funding RecommendationLevel of Effort Identify and implement best method for speed post- processing (on-road mobile sources). $45k Model truck activity on highways and arterials, integrate w/ forecasts. $75k ($115k with counts) Conduct a statewide survey to improve spatial distribution of recreational boating activities. $80k Approximate temporal patterns for weekend light-duty vehicle activities. $15k SUBTOTAL$375k Build a weekend travel demand model. (Create weekend trip tables, validate/calibrate relative distributions.) $75k

37 Potential In-Kind Actions ($50k-$60k) Correct emissions for snowmobiles. Correct emissions for commercial jets in the South Coast Air Basin. Update spatial surrogate cross-references for un- or mis-matched emission sources. Correct temporal profile mis-assignments in the cross-reference file. Quality assure point source locations. Double-check potentially incorrect point source locations identified by STI. Apply monthly profiles based on statewide fuel consumption for petroleum marketing. Develop weekend diurnal profile for gasoline refueling (from traffic volumes). Apply diurnal profiles to gasoline refueling emissions in the SFBA air basin. Double-check diurnal and weekly patterns for trains in the SFBA air basin. Develop diurnal profiles for commercial jets in the SFBA air basin. Double-check local seasonal patterns for burning (agricultural and land management). Apply diurnal profiles for fuel combustion (manufacturing/industrial and service/commercial).

38 Additional Tasks for Consideration RecommendationLevel of Effort Improve the spatial distribution of construction activities by analyzing residential and commercial building permits. $100k Collect data to improve the spatial distribution of selected individual source categories. Varies widely Model on-road mobile sources with link-level EFs.$50k-$75k Analyze CEM data for external combustion boilers at major point sources. $15k

39 Discussion Questions or comments?