WILMINGTON AIR QUALITY STUDY Project Summary and Status

1. MWG_PRES_031604 WILMINGTON AIR QUALITY STUDYProject Summary and Status Todd Sax Vlad Isakov Planning and Technical Support Division California Air Resources Board Presentation to Modeling Working Group March 16, 2004

2. MWG_PRES_031604 Outline • Introduction and Overview • Objectives • Conceptual Plan • Preliminary Results • Emissions Inventory • Review • Status and Preliminary Results • Industrial-Commercial Facilities • Non-Port Mobile Source Inventories • Port Inventories - Status • Model Status and Evaluation • Ongoing Work

3. MWG_PRES_031604 Wilmington Air Quality Study • Barrio Logan project - first neighborhood assessment project. • Neighborhood scale inventory • Application of several local-scale and regional models • Wilmington study - next step in neighborhood assessment. • Improved local-scale emissions inventory and inventory evaluation • Larger modeling domain • Expanded model application and evaluation

4. Wilmington Domain MWG_PRES_031604 Wilmington modeling sub-domain

5. MWG_PRES_031604 WAQS Objectives • Goals • Develop and evaluate inventory/modeling methods for assessing pollutant impacts at a fine resolution • Conduct studies to assess inventory and modeling approaches for statewide assessment • Key Questions • Are existing emissions inventories adequate for neighborhood assessment? • What are the key data gaps? • What are key pollutant, source impacts in Wilmington? • Which models provide reliable results? • How do we integrate model results?

6. Wilmington Neighborhood Assessment - Conceptual Plan • Emissions • Industrial and Commercial Facilities • Industrial facilities • Non-diesel emissions from marine terminals • Gasoline stations • Dry cleaners • Autobody shops • Metal fabricators • “Magnet” Facilities like warehouses and distribution centers that attract diesel on-road sources • Dedicated, on-site off-road equipment • On-Road Sources • Automobiles and Heavy • duty trucks • Freeways, and Ramps • Major and Minor Arterials • Other Off-Road Engines • Marine, Harbor, and Dockside engines at marine terminals • Railroad activity • Health Risk • OEHHA Guidelines • - Inhalation and • multipathway risks • - Cancer and chronic • endpoints • - Comparison to health based • PM standards • Exposure • Local scale modeling • - ISCST3, AERMOD, • CALPUFF, CALINE4 • Regional modeling • - CALGRID, CMAQ, • CAMx • Combined results • Limited time-activity based exposure modeling • Model Evaluation • Tracer Study • Summer, 2003 • Release from elevated stack • Toxics Monitoring • Long term (one year), one site • - >50 pollutants • Short term study(12-15 days) • - Summer, 2003 • - Multiple sites • - Estimate diesel PM • Uncertainty Assessment • Gasoline service stations • Stationary and Mobile Diesel IC engines • Inventory Analysis • Expand quality assurance • Assess contribution of “neighborhood” sources • Evaluate uncertainty

7. MWG_PRES_031604 Outline • Introduction and Overview • Objectives • Conceptual Plan • Preliminary Results • Emissions Inventory • Review • Status and Preliminary Results • Industrial-Commercial Facilities • Non-Port Mobile Source Inventories • Port Inventories - Status • Model Status and Evaluation • Ongoing Work

8. Emissions Inventory Review MWG_PRES_031604 Emissions: Industrial and Commercial Facilities • 405 facilities-toxics / 259 -criteria • 170 surveyed facilities (118 neighborhood / 52 CEIDARS) • Compiled from multiple inventory databases • Enhanced QA/QC • Review by SCAQMD and selected facilities On-Road Emissions • Link-Based Inventory • Use Travel Demand Models and EMFAC Marine Terminals and Related Off-Road • Ports of Los Angeles and Long Beach - develop inventories for marine terminals, on-road sources, and related locomotive emissions. • Locomotives - develop link and throttle-notch specific inventories • Construction - not considered (included in regional modeling).

9. MWG_PRES_031604 Outline • Introduction and Overview • Objectives • Conceptual Plan • Preliminary Results • Emissions Inventory • Review • Status and Preliminary Results • Industrial-Commercial Facilities • Non-Port Mobile Source Inventories • Port Inventories - Status • Model Status and Evaluation • Ongoing Work

10. Industrial-Commercial Facilities MWG_PRES_031604 • Definition • Large and small point sources at non-port businesses • Method • Develop facility list • Multiple data sources: HRA, AER, CEIDARS, TRI, etc. • On-site surveys: verify and augment inventories • 118 neighborhood sources • 52 CEIDARS facilities • Choose best emissions data from hierarchy • If surveyed, include on-site area and mobile emissions categories • Compile inventory

11. Industrial-Commercial Facilities MWG_PRES_031604 Hierarchy

12. Industrial-Commercial Facilities MWG_PRES_031604

13. Industrial-Commercial Facilities • Preliminary Results: Inventory Evaluation • Designed to test inventory assumptions • Why evaluate inventories? • Existing databases designed for regional-scale analysis • Inventory update procedures designed and implemented with regional goal in mind • But NAP is local scale, not regional analysis • Asking existing databases to “do more” • Need to understand strengths and limitations • Learn how to improve and meet modeling needs

14. Industrial and Commercial Facilities MWG_PRES_031604 • Development of a community-specific industrial-commercial facility inventory improved our ability to characterize emissions in Wilmington • WAQS inventory is more recently calculated • Toxics Inventory Age • 65% of records identified by survey; year 2000 or later • Criteria Inventory Age • 55% or records in local-scale inventory updated by survey (>2000) • WAQS is more comprehensive than CEIDARS • Contains small facilities that are area sources in CEIDARS • Contains improved stack data in toxics inventory • 64% of releases are actual data; 36% defaults • Only 8% of CEIDARS records tied to stacks • Duplicate, closed CEIDARS facilities corrected.

15. Industrial-Commercial Facilities MWG_PRES_031604 • Total facility cancer scores differ substantially between inventories.

16. Industrial and Commercial Facilities MWG_PRES_031604 • On a neighborhood scale, diesel PM and CrVI from area-wide sources at facilities are significant • 80% of diesel PM and 15% of CrVI generated by facilities which are not in CEIDARS as point sources. • Other neighborhood sources have minimal impacts, but may be important near receptors.

17. Industrial and Commercial Facilities MWG_PRES_031604 • Current diesel exhaust particulate inventories representing industrial-commercial facilities need improvement for neighborhood assessments • Only ~20% of estimated diesel PM emissions at facilities generated by point sources • Remaining ~80% generated primarily by off-road sources operating within facilities. • Diesel PM from off-road sources is important at larger industrial facilities like petroleum refineries • Off-road diesel PM ~40% of total cancer potency-weighted emissions at refineries.

18. I-C Diesel Exhaust Particulate Inventory MWG_PRES_031604 • 75% generated by inventory-reporting facilities in 90744 (Wilmington community) • But 23 reporters, ~600 neighborhood sources not surveyed in 90744 • If extrapolate, inventory doubles

19. Implications of I-C DPM MWG_PRES_031604 • DPM is dominant cancer risk • Significant emissions generated by on-site off-road sources • Point source facilities generally do not report on-site mobile source inventories • However, most on-site off-road emissions were generated by facilities subject to other inventory reporting requirements • Statewide inventory based on off-road model • Top-down approach • 4 km grid cell spatial resolution

20. Industrial and Commercial Facilities MWG_PRES_031604 • Petroleum Refinery Case Study • Method • Evaluate inventory reports from 6 refineries • 3 in Wilmington, +1 in SCAQMD, +2 in BAAQMD • Analysis requires process-level inventories • Obtained best toxics data representing each facility • Must be consistently calculated, SCC process coded • Result: ability to compare facilities is limited • Different process groupings/units between facilities • Widespread inconsistencies in facility calculations • Top pollutant sources different at different facilities • Need to examine other facility categories; results may be consistent

21. MWG_PRES_031604 Case Study: Petroleum Refineries • Example: Benzene • Facility E: fugitive wastewater • Facilities B and C (AER): oil-water separators. B>C, due to activity • Some totals different in AB2588, AER • Results consistent for benzene, 1,3-B, H2S, CrVI, CHOH

22. Case Study: Petroleum Refineries MWG_PRES_031604 • Substantial differences between identical facilities, different inventories • Major differences in facility-total emissions for high risk pollutants

23. Case Study: Petroleum Refineries Process rate Emissions MWG_PRES_031604 • When emissions data reported using comparable methods, gain insights. • Example: Hexavalent Chromium (CrVI) generated by process-gas fired process heaters • On paper, majority of emissions generated by a few units at few facilities

24. MWG_PRES_031604 Outline • Introduction and Overview • Objectives • Conceptual Plan • Preliminary Results • Emissions Inventory • Review • Status and Preliminary Results • Industrial-Commercial Facilities • Non-Port Mobile Source Inventories • Port Inventories - Status • Model Status and Evaluation • Ongoing Work

25. On-Road Emissions Inventory MWG_PRES_031604 • Goal: develop and evaluate link-specific inventory • Develop and test approaches for link-specific inventory development • Assess assumptions in developing a bottom-up inventory • Compare to proposed approach for statewide modeling • Assess uncertainty and how to improve calculations • Preliminary Results • Emissions models need better resolution • Emissions estimates are uncertain due to uncertain activity estimates and uncertain emission factors

26. Mobile Emissions Inventories MWG_PRES_031604 • Emission models were never intended to provide highly spatially resolved emissions estimates • EMFAC and OFFROAD provide county-total emissions that can be allocated to 4 km grid cells • Greater inventory resolution is required for local-scale models • Allocating emissions to roadways is uncertain due to county-level assumptions • Fleet composition • Travel model limitations: link specific volumes and speeds • Operating cycle / trip-based emission factors

27. Mobile Emissions Inventory MWG_PRES_031604 • Limited test data on diesel PM emissions complicates assessment of diesel PM impacts on a local level. • Source test data are extremely limited • ~200 in-use heavy duty truck source tests • New data on-line with CRC E55-59 • <20 source tests of off-road in-use engines • Driving cycles highly variable depending on equipment • Models make key assumptions • On-road: emissions dependency with speed, driving cycles, activity, etc. • Off-road: load and deterioration, etc. • Regional or equipment specific activity / operational characteristics.

28. MWG_PRES_031604 Outline • Introduction and Overview • Objectives • Conceptual Plan • Preliminary Results • Emissions Inventory • Review • Status and Preliminary Results • Industrial-Commercial Facilities • Non-Port Mobile Source Inventories • Port Inventories - Status • Model Status and Evaluation • Ongoing Work

29. Emissions Inventory - Ports MWG_PRES_031604 • Port-wide inventories • Goal: obtain spatially resolved port-specific inventories • Work supports WAQS and SSD Port Regulatory Activities • Work conducted by Port consultants • Continuous consultation with SSD, PTSD • Improve spatial allocation - berth/terminal/rail-link specific • Improve inventory assumptions: load, stacks, etc. • Improved traffic and idling activity estimates - terminal specific • Status: Draft reports are being reviewed. • Commercial marine vessels (POLA) • Harborcraft (POLA / SSD) • Terminal on-road movement/idling (POLA and POLB) • Dockside terminal (POLA and POLB) • Locomotives (POLA and POLB)

30. MWG_PRES_031604 Outline • Introduction and Overview • Objectives • Conceptual Plan • Preliminary Results • Emissions Inventory • Review • Status and Preliminary Results • Model Status and Evaluation • Local-scale uncertainty analysis • Tracer study status • Ongoing Work

31. Modeling Status MWG_PRES_031604 • Microscale • Status: waiting on port inventories • Regional • Status: currently being planned, sensitivity studies in progress • Model Integration • Goal: combine regional and microscale models while minimizing double counting • Status: currently being planned.

32. Model Evaluation - Uncertainty Analysis MWG_PRES_031604 • Goal • Use uncertainty analysis as an objective evaluation procedure to determine the level of confidence weshould have in modeling results • Two studies • Diesel PM Study in Wilmington • Wilmington inventory sensitivity studies • What is uncertainty analysis? • An analysis method that uses assumptions about the uncertainty in model inputs to assess uncertainty in model output.

33. Model Evaluation - Uncertainty Analysis MWG_PRES_031604 • Why Uncertainty Analysis • Models are not reality • Model results are a function of assumptions • Assumptions are uncertain • We make best guess estimates to simulate reality • These estimates may be wrong • These estimates are uncertain - we pick a value from a range • What do we hope to learn? • How uncertain are our estimates? • What are the most uncertain components? • How can we reduce uncertainty? • Given uncertainty, what are model strengths and limitations?

34. Wilmington Uncertainty Analysis (1) MWG_PRES_031604 • Diesel PM - ZIP 90744 • Industrial-Commercial facilities • Surveyed and included in inventories • Extrapolated, not in I-C inventory directly • On-Road • “Major” - Freeways, Ramps, Major Arterials • “Minor” - Minor arterials, Collectors, Connectors • Approach • Assess uncertainty in emissions • Run ISC for Base Case • Assess uncertainty in model results due to meteorology, inventory release characteristics. • Develop Monte Carlo meta-model to estimate uncertainty in ISCST3 results

35. MWG_PRES_031604 (IC, on-road)

36. (point/area sources) > MWG_PRES_031604

37. (heavy duty trucks) > MWG_PRES_031604

38. (light duty trucks) > MWG_PRES_031604

39. Wilmington Uncertainty - Emissions MWG_PRES_031604 • Diesel PM emissions: mobile sources • Mobile source DPM at 4 facilities • Theoretical link • Goal: assess precision, accuracy in emissions, apply to modeling analysis • Emissions method • Estimate activity range by on-site survey • Quantify range of emission factors based upon source tests • Use Monte Carlo to propagate uncertainty

40. Case Study: Diesel Exhaust Particulate MWG_PRES_031604 • Order of magnitude uncertainty in mobile source diesel emissions estimates at facilities • Assessed on-site on-road and off-road emissions

41. Case Study: Diesel Exhaust Particulate MWG_PRES_031604 • Uncertainty is due to emission factors • Limited number of tests, all cycles considered.

42. Case Study: Theoretical Link MWG_PRES_031604 • Order of magnitude uncertainty in on-road diesel emissions estimates • Theoretical link (1-mile, 100 HD, 5 LD, 30 MPH) • Bias in Wilmington is likely (volume, fleet, EF)

43. MWG_PRES_031604 Wilmington Uncertainty Analysis Method Divide model into components • Emissions (EMS) • Spatial Allocation (SA)Assessed by emissions source category, Moved a set distance to north, south, east, west: IC +/- 25m, ZNS +/- 200m, Major onroad - fixed, Minor roadways +/- 500m. • Temporal Allocation (TA)Point sources - base scenario by survey (vary 8, 10, 12, 16, 24 hour day), Roadway sources (Vary temporal allocation +/- 2 hrs) • Release parameters (RP)Point sources base case defined by survey, uncertainty using different assumptions: 3 volume scenarios, 3 point source scenarios, Roadways - base case area sources (3 different area source options) • Meteorology (MET)Onsite data 2001 (Long Beach cloud data for stability), Assessed Long Beach - 1984-1990, 2001, Ran model, assess percent difference relative to 2001, Developed distribution for interannual variability

44. MWG_PRES_031604 Uncertainty Analysis: Conceptual Approach • Run Model • Assess model differences based on uncertainty in each model component • Assign to distribution (in our case empirical for simplicity) • Result - distribution of model results for each model component separately • Model Propagation • Assumes independence between factors in model • Spatial allocation, temporal allocation, meteorology, release parameters. • Emission rates are independent - unit emission rates • Develop Monte Carlo propagation model (EMS x C) (SA + TA + RP + MET) • Model is iterated for each source contribution to each receptor. • Receptors • Chosen to represent different types of sites

45. Wilmington Uncertainty Analysis MWG_PRES_031604 • Results: all receptors

46. Wilmington Uncertainty Analysis MWG_PRES_031604 • Receptor 1: stationary and mobile impacted

47. Wilmington Uncertainty Analysis MWG_PRES_031604 • Receptor 4: residential non-impacted

48. Wilmington Uncertainty Analysis MWG_PRES_031604 • Receptor 6: Wilmington Park Elementary

49. MWG_PRES_031604 Preliminary Conclusions • Emissions from on-road sources may be underestimated • Uncertainty in emissions appears the dominant source • Locating emissions in the domain is most important • Once located, uncertainty in calculations is dominant. • No statistical difference between sites • Due to uncertainty in magnitude and location of emissions • Model results should be verified with monitoring • Conceptual model uncertainty due to model formulation needs to be included

50. Wilmington Sensitivity Studies (2) MWG_PRES_031604 • Objective • Demonstrate the effect of different point source emissions inventories on model results using a simplified case study. • Method • Compare different level of details in point source emissions inventory • NATA 1996, CEIDARS, WAQS • Use NATA 1996 application, ASPEN modeling system for comparison.