Download ppt - 1 WILMINGTON AIR QUALITY STUDY Project Summary and Status Todd Sax Vlad Isakov Planning and Technical Support Division California Air Resources Board Presentation

1

WILMINGTON AIR QUALITY STUDY

Project Summary and Status

Todd Sax

Vlad Isakov

Planning and Technical Support DivisionCalifornia Air Resources Board

Presentation to Modeling Working Group

March 16, 2004

MWG_PRES_031604

2

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

MWG_PRES_031604

3

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

MWG_PRES_031604

4

Wilmington Domain

Wilmington modeling sub-domain

MWG_PRES_031604

5

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?

MWG_PRES_031604

6

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

Exposure

• Local scale modeling - ISCST3, AERMOD, CALPUFF, CALINE4• Regional modeling - CALGRID, CMAQ, CAMx• Combined results• Limited time-activity based exposure modeling

Health Risk

• OEHHA Guidelines - Inhalation and multipathway risks - Cancer and chronic endpoints - Comparison to health based PM standards

Model EvaluationTracer 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

Wilmington Neighborhood Assessment - Conceptual Plan

Inventory Analysis• Expand quality assurance• Assess contribution of “neighborhood” sources• Evaluate uncertainty

7







• Ongoing Work

MWG_PRES_031604

8

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).

Emissions Inventory Review

MWG_PRES_031604

9







• Ongoing Work

MWG_PRES_031604

10

Industrial-Commercial Facilities• 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

MWG_PRES_031604

11

Industrial-Commercial FacilitiesTable 1 Number of facilities in final inventories by data source.

Number of Facilities

Data Source ToxicsInventory

CriteriaInventory

CEIDARS SurveysPrimary Data Source: Health Risk Assessment 10Primary Data Source: Annual Emissions Report 28 28

Health Risk Assessments 7Air Toxic Inventory Reports (hardcopy files) 8Neighborhood Source Surveys

with no additional data 115with limited CEIDARS data 2with limited AER data 2

Limited Surveys (AQMD Annual Emission Reports) 12 13AQMD Annual Emission Reports

1998-1999 11 161999-2000 31 492001-2002 4

LAUSD Surveys 38 1ARB Emissions Inventory Database (CEIDARS)

Criteria Database 74Toxics Database 69Both 16

Energy Commission List of Emergency Generators 31 32Toxics Release Inventory, Year 2000 9AQMD Permits - ARB Emission Estimates 16 42

Total 405 259

Hie

rarc

hy

MWG_PRES_031604

12

Table 2 Industrial-Commercial Facility Emission Inventory andContribution to Potency Scores for Selected Pollutants in theWilmington Modeling Domainxy.

Pollutant Emissions(lbs/yr)

Percent of TotalCancer Score

Percent of TotalChronic Score

Ammonia 1300000 -- <1%Chlorofluorocarbons (CFCs)* 350000 -- --Toluene 300000 -- --Methanol 250000 -- --1,1,1-Trichloroethane (TCA)* 200000 -- --Ethylbenzene 200000 -- --Xylenes 120000 -- --Sulfuric Acid 95000 -- 50%Methyl Bromide 65000 -- <5%Hydrogen Sulfide 60000 -- <1%Diesel Exhaust PM 44000 70% <5%Formaldehyde 35000 <1% <5%Benzene 19000 <1% --1,3 Butadiene 6800 1% --Chlorine 6800 -- <15%Nickel 1800 <1% <15%Ethylene Oxide 1400 <1% --Cadmium 120 <1% <1%Arsenic 90 <1% --Hexavalent Chromium 14 15% --

* Reported in health risk assessments, no longer used at facilities.-- Score is negligible or pollutant has no unit risk factor/reference exposure level.x Port inventories are not included and are still in development.y This inventory reflects a combination of data sources. The methodology by which this

inventory was developed is detailed in (Sax, 2004).

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• 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.

MWG_PRES_031604

15

Industrial-Commercial Facilities• Total facility cancer scores differ substantially

between inventories.

MWG_PRES_031604

16

Industrial and Commercial Facilities• 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.

MWG_PRES_031604

Table 3 Percent contribution by facility category to top pollutant inventoriesby cancer risk score.

CATEGORY DPM CrVI 1,3-BUT BENZ Cd Ni

AB2588-TOX 0 85 100 60 70 70OR-TOX 0 15 <2 25 5 30SC-TOX 0 0 0 15 15 <1NS-TOX 0 <2 0 <1 10 0NG 10 0 0 0 0 0STAT-DPM 10 0 0 0 0 0MS-REP-DPM 70 0 0 0 0 0MS-NS-DPM 10 0 0 0 0 0

17

Industrial and Commercial Facilities• 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.

MWG_PRES_031604

18

I-C Diesel Exhaust Particulate Inventory

• 75% generated by inventory-reporting facilities in 90744 (Wilmington community)– But 23 reporters, ~600 neighborhood sources not

surveyed in 90744– If extrapolate, inventory doubles

MWG_PRES_031604

19

Implications of I-C DPM

• 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

MWG_PRES_031604

20

Industrial and Commercial Facilities• 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

MWG_PRES_031604

21

Table 4-4 Top Three Benzene Emissions Sources by

Process – Hot Spots Data. (#) = Emissions (lbs/yr) by Process.

FACILITYRank A B C D E F

1 Fugitives,Not

Classified(1000)

ProcessHeaters,Process

Gas(700)

ProcessHeaters,Process

Gas(300)

FloatingRoof Tanks

(1100)

Fugitive,Wastewater

(6000)

FugitivePipeline

Valves, etc(1300)

2 GasolineEngines

(300)

FixedRoof

Tanks(300)

Fugitives,Not

Classified(200)

Fugitives –Wastewater

(400)

Fugitive,Pipeline

Valves, etc.(3000)

Process GasExternal

Combustion(160)

3 FloatingRoof

Tanks(100)

FloatingRoof

Tanks(300)

FloatingRoof Tanks

(60)

Fugitives,Not

Classified(300)

Fugitive,Not

Classified(1400)

Fugitives,Pump Seals

(90)

Table 4-5 Top Three Benzene Emissions Sources by

Process – AER Data. (#) = Emissions (lbs/yr) by Process.

FACILITYRank A B C

1 FloatingRoof

Tanks(100)

FixedRoof

Tanks(600)

ProcessHeatersProcess

Gas(300)

2 ProcessHeater

ProcessGas(100)

Fugitive –Oil/WaterSeparator

(400)

Fugitive –Oil/WaterSeparator

(60)

3 BoilersProcess

Gas(50)

BoilersProcess

Gas(300)

Fugitive –Valves

(40)

• 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

Case Study: Petroleum Refineries

MWG_PRES_031604

22

Case Study: Petroleum Refineries• Substantial differences between identical

facilities, different inventories– Major differences in facility-total emissions for high

risk pollutants

MWG_PRES_031604

23

Case Study: Petroleum Refineries• 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

EmissionsProcess rate

MWG_PRES_031604

24







• Ongoing Work

MWG_PRES_031604

25

On-Road Emissions Inventory• 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

MWG_PRES_031604

26

• 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

Mobile Emissions Inventories

MWG_PRES_031604

27

• 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.

Mobile Emissions Inventory

MWG_PRES_031604

28

Outline

• Introduction and Overview– Objectives– Conceptual Plan




– Model Status and Evaluation• Ongoing Work

MWG_PRES_031604

29

Emissions Inventory - Ports• 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)

MWG_PRES_031604

30

Outline




– Model Status and Evaluation• Local-scale uncertainty analysis• Tracer study status

• Ongoing Work

MWG_PRES_031604

31

Modeling Status• 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.

MWG_PRES_031604

32

Model Evaluation - Uncertainty Analysis

• Goal– Use uncertainty analysis as an objective evaluation

procedure to determine the level of confidence we should 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.

MWG_PRES_031604

33

Model Evaluation - Uncertainty Analysis

• 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?

MWG_PRES_031604

34

Wilmington Uncertainty Analysis (1)• 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

MWG_PRES_031604

35

(IC, on-road)

MWG_PRES_031604

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• 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

MWG_PRES_031604

40

• Order of magnitude uncertainty in mobile source diesel emissions estimates at facilities– Assessed on-site on-road and off-road emissions

Case Study: Diesel Exhaust Particulate

MWG_PRES_031604

41

Case Study: Diesel Exhaust Particulate• Uncertainty is due to emission factors

– Limited number of tests, all cycles considered.

MWG_PRES_031604

42

• 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)

Case Study: Theoretical Link

MWG_PRES_031604

43

Wilmington Uncertainty Analysis MethodDivide 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

MWG_PRES_031604

44

• 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

Uncertainty Analysis: Conceptual Approach

MWG_PRES_031604

45

Wilmington Uncertainty Analysis• Results: all receptors

MWG_PRES_031604

46

• Receptor 1: stationary and mobile impacted

Wilmington Uncertainty Analysis

MWG_PRES_031604

47

Wilmington Uncertainty Analysis• Receptor 4: residential non-impacted

MWG_PRES_031604

48

Wilmington Uncertainty Analysis• Receptor 6: Wilmington Park Elementary

MWG_PRES_031604

49

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

MWG_PRES_031604

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.

51

Assessing Uncertainty due to Emissions

Compare multiple point source inventoriesGoal: estimate uncertainty due to different levels of detail in point source inventories (national, statewide, local-scale)

Modeling Domain:• Focus on Wilmington sub-

domain (10 x 10 km)• Outside sources treat as

background• Model all sources within

50km of domain. • Compare with observations:

Short term (~18 mo.) toxics monitor in domain.

Roadlinks

Censustractcentroids

Modelreceptors

MWG_PRES_031604

52

Analysis of emissions:

Benzene

Wilmington modeling domain10km x 10km size (blue box)

major road links - black linescensus tracts centroids - black dots

Sources of benzene emissions:Local-Scale (WAQS) - red symbolsStatewide (CEIDARS) - blue symbolsNational (1996 NTI) - yellow symbols

MWG_PRES_031604

53

Local (Wilmington) State (CEIDARS) National (NATA’96)

Benzene emissions from stationary sources(0.5 x 0.5 km gridded for visualization)

Domain total = 8.3[t/yr] Domain total = 28.6[t/yr] Domain total = 159[t/yr]804 sources: 502 sources: 280 sources: median = 0.0005 median = 0.0011 median = 0.018 95% = 0.048 95% = 0.22 95% = 0.17 max = 1.05 max = 3.57 max = 94.7

MWG_PRES_031604

54

Comparison: Local vs. Statewide Inventory Benzene Emissions

X-axis:Statewide:(CEIDARS)

Factor of 10

Factor of 2

Y-axis:Local-scale(Wilmington)

Inventory identified, not in statewide

MWG_PRES_031604

55

Model results:benzene concentrations (point sources - black, other sources - gray,background - white)

Base case: national inventory(NTI’96)

Emissions from point sourcesreplaced by statewide inventory(CEIDARS)

Emissions from point sourcesreplaced by local-scale inventory(Wilmington)

MWG_PRES_031604

56

• Emissions Inventory– Sources are more precisely located in statewide and

local-scale inventory– Large differences in inventory databases

• Model Results– Results agree with observations – Background and mobile source contributions

comparable and dominant contributors to risk– Point sources have impact when close to receptors

Benzene results

MWG_PRES_031604

57

Hexavalent Chromium

Cr (VI)

Wilmington modeling domain10km x 10km size (blue box)

major road links - black linescensus tracts centroids - black dots

Sources of Cr (VI) emissions:Local-Scale (WAQS) - red symbolsStatewide (CEIDARS) - blue trianglesNational (1996 NTI) - yellow triangles

MWG_PRES_031604

58

Cr (VI) emissions from stationary sources(0.5 x 0.5 km gridded for visualization)

Local (Wilmington) State (CEIDARS) National (NATA96)

Domain total = 12.9[lb/yr] Domain total = 162[lb/yr] Domain total = 75.9[lb/yr] 263 sources 45 sources 54 sources median = 0.0020 median = 0.0034 median = 0.0014 95% = 0.24 95% = 25.33 95% = 9.97 max = 1.76 max = 88.6 max = 27.6

( Cr6 = 0.34 * Cr )

MWG_PRES_031604

59

Comparison: Local vs. Statewide Inventory Cr (VI) Emissions

X-axis:Statewide:(CEIDARS)

Y-axis:Local-scale(Wilmington)

Factor of 10

Factor of 2

Inventory identified, not in statewide

MWG_PRES_031604

60

Model results:Cr(VI) concentrations (point sources - black, background - white)

Base case: national inventory(NTI’96)

Emissions from point sourcesreplaced by statewide inventory(CEIDARS)

Emissions from point sourcesreplaced by local-scale inventory(Wilmington)

MWG_PRES_031604

61

• Emissions Inventory– Sources are more precisely located in statewide and

local-scale inventory– Large differences in inventory databases

• Few sources account for almost all of difference, but moderate differences widespread at many sources

• Assuming 34% CrVI/Cr in NTI is simplified, conservative, has been improved in NTI’2001.

• WAQS has more sources than statewide, but fewer emissions

• Model Results– Results agree with observations– Point sources have impact when close to receptors

• Background appears consistent, low.

CrVI results

MWG_PRES_031604

62

• Key Question– What level of resolution in analysis is defensible?– What needs to be done to achieve required resolution?

• Potential Answer– Combination of inventory inputs and model sensitivity.

• Uncertainty Analysis Reports• Case Study in Regulatory Modeling Applications - Atmospheric

Environment, 2003• CRC Modeling Conference (2002)• AWMA (2003) - Framework for Uncertainty Analysis. • AWMA (2004) - DPM Uncertainty Analysis• AWMA (2004) - NATA Conceptual Uncertainty

Future Work

MWG_PRES_031604

63

Outline





• Ongoing Work

MWG_PRES_031604

64

Tracer Experiments

Why tracer studies? – existing micro-scale models (such as ISCST3 and AERMOD) have been developed and evaluated using tracer studies not specific to California (Prairie Grass study in Nebraska and Kincaid study in Illinois – flat rural conditions, and in Indianapolis, Indiana - urban conditions).

What are we doing? – We are conducting new tracer studies focused on evaluating micro-scale models (ISCST3 and AERMOD) on both near-field and local scales. Results from these studies will help us understand model performance in California under study conditions and may lead to model refinement in the future.

What needs to be done in the future? – additional tracer experiments in California are required to analyze the full range of terrain / meteorological conditions in the state.

Models need to be evaluated in complex coastal urban conditions common to the Bay area;

Models need to be evaluated on-road on a local scale.

MWG_PRES_031604

65

Databases for model evaluation:

Tracer Experiments:

1) Near field tracer experiment in San Diego, Barrio Logan

2) Field study at Dugway Proving Ground, Utah

3) Near field tracer experiment in Riverside - CE-CERT dispersion experiment: trailer wake effect in an urban area

4) Tracer experiment in urban areas - ground level release in San Diego, Barrio Logan

5) Tracer experiment in urban areas - elevated level release in Los Angeles, Wilmington

MWG_PRES_031604

66

Figure 1: The growth of the nocturnal thermal urban boundary layer (TIBL)

Stable boundary layer

Urban boundary layer

TRACER EXPERIMENTS IN WILMINGTON

MWG_PRES_031604

67

Wilmington Tracer Experiment - P.O.L.A.

68

Wilmington Tracer Experiment - P.O.L.A.

69

3 kilometers

5 kilometers

4 kilometers

Los Angeles CountySanitation Districts’ 350acre Joint Water PollutionControl Plant (JWPCP). Location of DopplerSodar, sonicanemometers at twoheights and one set ofintegrated samplers

2 kilometers

1 kilometer

LADWP HarborGeneratingStation. Locationof tracer releaseand miniSodar

Locations ofIntegrated samplers

Sonic

LADWP stack

Sodar

General map of the area

MWG_PRES_031604

70

Pilot field study - conducted in September, 2003 Meteorological measurements: sodars, sonic anemometers,

temperature, relative humidity and solar radiation sensors One daytime tracer release was performed between 8 a.m.

and 2:30 p.m. on September 22nd. Afternoon/evening releases (3 p.m. - 11 p.m.) were

performed on September 23rd, 25th and 26th. First three releases - using the 220 tall stack at the LADWP

power plant and the fourth - “surface release (~ 3 m). Tracer measurements: mobile van monitoring along several

downwind transects and “bag sampler” samplers at three locations

Performance audits were conducted on the wind sensors and tracer gas analyzer

Wilmington Tracer Pilot Study Status

MWG_PRES_031604

71

Model Evaluation - Tracer Study• Reports:

– Barrio Logan Tracer Study Final Report - under review

– Barrio Logan Tracer Study Results - accepted, Atmospheric Environment

– Wilmington Tracer Pilot Study Status Report

– 2002-2003 Presentations: CRC, EPA, Working Group

– Near-Field Modeling for Regulatory Applications - in press, Journal of the Air and Waste Management Association

MWG_PRES_031604

72

Outline





• Ongoing Work

MWG_PRES_031604

73

Model Evaluation and Planning - Regional• Goal: minimize computing resources

– Useful to determine the impact of grid cell size on model results• Conducting sensitivity 4x4 vs. 12x12.

– 12x12 results drastically lower (factor 2-10 reduction in toxics)

• Compared 2x2 MATES-II vs ARB 4x4 regional– Results comparable

• Comparing 6x6, 2x2 to 4x4 results (in progress)

– We are currently committed to 4x4 for statewide to leverage simultaneous, SIP-related work.

– Need to determine how many vertical layers are necessary to generate reliable results• Testing 7 layers vs. standard 17 (in progress)

MWG_PRES_031604

74

Toxics Monitoring• Wilmington Toxics Monitoring

– Goals: evaluate combined microscale and regional modeling results for diesel PM using monitored

concentrations of diesel indicators• Test methodology suggested in ARB meetings

• Focus on several sub-areas of Wilmington domain

– Hawaiian Ave School and I110 impacts

– Long Beach Port and I 710 impacts

– San Pedro port impacts and complex meteorology

• Integrate results with other studies

» PTSD Freeway, RD RAV4, POLA program

– Status: study in progress

MWG_PRES_031604

75

Schedule and Plan• Receive Port inventories - first quarter 04• Microscale modeling - summer 04• Research to support statewide - ongoing

– depends on peer review and working group comments• Research is focused on answering peer-review questions• Publishing ensures feedback from scientific community

– Makes peer-reviewers more confident of results

• Project report - mid-year 05– Several reports

• Public consumption - e.g. Wilmington story• Technical report

– discussing results from modeling applications and associated research– recommendations for statewide effort– geared for working group and peer-reviewers

MWG_PRES_031604