MNEQA,an emissions model for photochemical simulations

This study focuses on a new emissions model, Numerical Emissions Model for Air Quality (MNEQA), to be used in photochemical simulations and emission control strategies relating to tropospheric ozone pollutants. MNEQA processes available local information from external files and is easily adaptable to any desired spatial resolution. Top-down and bottom-up methodologies are combined to calculate emissions at the required resolution for photochemical simulations. It was used in conjunction with the MM5-CMAQ air quality modelling system and was applied to an episode of high ozone levels in June 2003. Emission results are widely analysed showing a difference of ?8.8% with EMEP NOx emissions, and ?18.7% with EMEP VOC emissions. Related to ozone simulations, comparative results between measurements and simulations indicated good behaviour of the model in reproducing diurnal ozone concentrations, as statistical values fall within the EPA and EU regulatory frameworks.     

Assessment of the emissions and air quality impacts of biomass and biogas use in California

It is estimated that there is sufficient in-state “technically” recoverable biomass to support nearly 4000 MW of bioelectricity generation capacity. This study assesses the emissions of greenhouse gases and air pollutants and resulting air quality impacts of new and existing bioenergy capacity throughout the state of California, focusing on feedstocks and advanced technologies utilizing biomass resources predominant in each region. The options for bioresources include the production of bioelectricity and renewable natural gas (NG). Emissions of criteria pollutants and greenhouse gases are quantified for a set of scenarios that span the emission factors for power generation and the use of renewable natural gas for vehicle fueling. Emissions are input to the Community Multiscale Air Quality (CMAQ) model to predict regional and statewide temporal air quality impacts from the biopower scenarios. With current technology and at the emission levels of current installations, maximum bioelectricity production could increase nitrogen oxide (NO_x) emissions by 10% in 2020, which would cause increases in ozone and particulate matter concentrations in large areas of California. Technology upgrades would achieve the lowest criteria pollutant emissions. Conversion of biomass to compressed NG (CNG) for vehicles would achieve comparable emission reductions of criteria pollutants and minimize emissions of greenhouse gases (GHG). Air quality modeling of biomass scenarios suggest that applying technological changes and emission controls would minimize the air quality impacts of bioelectricity generation. And a shift from bioelectricity production to CNG production for vehicles would reduce air quality impacts further. From a co-benefits standpoint, CNG production for vehicles appears to provide the best benefits in terms of GHG emissions and air quality.

Implications:?This investigation provides a consistent analysis of air quality impacts and greenhouse gas emissions for scenarios examining increased biomass use. Further work involving economic assessment, seasonal or annual emissions and air quality modeling, and potential exposure analysis would help inform policy makers and industry with respect to further development and direction of biomass policy and bioenergy technology alternatives needed to meet energy and environmental goals in California.     

Assessment of air quality benefits from national air pollution control policies in China. Part I: Background,emission scenarios and evaluation of meteorological predictions

Under the 11th Five Year Plan (FYP, 2006–2010) for national environmental protection by the Chinese government, the overarching goal for sulfur dioxide (SO₂) controls is to achieve a total national emissions level of SO₂ in 2010 10% lower than the level in 2005. A similar nitrogen oxides (NO_x) emissions control plan is currently under development and could be enforced during the 12th FYP (2011–2015). In this study, the U.S. Environmental Protection Agency (U.S.EPA)’s Community Multi-Scale Air Quality (Models-3/CMAQ) modeling system was applied to assess the air quality improvement that would result from the targeted SO₂ and NO_x emission controls in China. Four emission scenarios — the base year 2005, the 2010 Business-As-Usual (BAU) scenario, the 2010 SO₂ control scenario, and the 2010 NO_x control scenario—were constructed and simulated to assess the air quality change from the national control plan. The Fifth-Generation NCAR/Penn State Mesoscale Model (MM5) was applied to generate the meteorological fields for the CMAQ simulations. In this Part I paper, the model performance for the simulated meteorology was evaluated against observations for the base case in terms of temperature, wind speed, wind direction, and precipitation. It is shown that MM5 model gives an overall good performance for these meteorological variables. The generated meteorological fields are acceptable for using in the CMAQ modeling.     

Development and application of a three-dimensional aerosol chemical transport model,PMCAMx

A three-dimensional chemical transport model (PMCAMx) is used to simulate PM mass and composition in the eastern United States for a July 2001 pollution episode. The performance of the model in this region is evaluated, taking advantage of the highly time and size-resolved PM and gas-phase data collected during the Pittsburgh Air Quality Study (PAQS). PMCAMx uses the framework of CAMx and detailed aerosol modules to simulate inorganic aerosol growth, aqueous-phase chemistry, secondary organic aerosol formation, nucleation, and coagulation. The model predictions are compared to hourly measurements of PM_2.5 mass and composition at Pittsburgh, as well as to measurements from the AIRS and IMPROVE networks. The performance of the model for the major PM_2.5 components (sulfate, ammonium, and organic carbon) is encouraging (fractional errors are in general smaller than 50%). Additional improvements are possible if the rainfall measurements are used instead of the meteorological model predictions. The modest errors in ammonium predictions and the lack of bias for the total (gas and particulate) ammonium suggest that the improved ammonia inventory used is reasonable. The significant errors in aerosol nitrate predictions are mainly due to difficulties in simulating the nighttime formation of nitric acid. The concentrations of elemental carbon (EC) in the urban areas are significantly overpredicted. This is a problem related to both the emission inventory but also the different EC measurement methods that have been used in the two measurement networks (AIRS and IMPROVE) and the actual development of the inventory. While the ability of the model to reproduce OC levels is encouraging, additional work is necessary to confirm that that this is due to the right reasons and not offsetting errors in the primary emissions and the secondary formation. The model performance against the semi-continuous measurements in Pittsburgh appears to be quite similar to its performance against daily average measurements in a wide range of stations across the Eastern US. This suggests that the skill of the model to reproduce the diurnal variability of PM_2.5 and its major components is as good as its ability to reproduce the daily average values and also the significant value of high temporal resolution measurements for model evaluation.     

Preliminary evaluation of the Community Multiscale Air Quality model for 2002 over the Southeastern United States

The Visibility Improvement State and Tribal Association of the Southeast (VISTAS) is one of five Regional Planning Organizations that is charged with the management of haze, visibility, and other regional air quality issues in the United States. The VISTAS Phase I work effort modeled three episodes (January 2002, July 1999, and July 2001) to identify the optimal model configuration(s) to be used for the 2002 annual modeling in Phase II. Using model configurations recommended in the Phase I analysis, 2002 annual meteorological (Mesoscale Meterological Model [MM5]), emissions (Sparse Matrix Operator Kernal Emissions [SMOKE]), and air quality (Community Multiscale Air Quality [CMAQ]) simulations were performed on a 36-km grid covering the continental United States and a 12-km grid covering the Eastern United States. Model estimates were then compared against observations. This paper presents the results of the preliminary CMAQ model performance evaluation for the initial 2002 annual base case simulation. Model performance is presented for the Eastern United States using speciated fine particle concentration and wet deposition measurements from several monitoring networks. Initial results indicate fairly good performance for sulfate with fractional bias values generally within +/-20%. Nitrate is overestimated in the winter by approximately +50% and underestimated in the summer by more than -100%. Organic carbon exhibits a large summer underestimation bias of approximately -100% with much improved performance seen in the winter with a bias near zero. Performance for elemental carbon is reasonable with fractional bias values within +/- 40%. Other fine particulate (soil) and coarse particular matter exhibit large (80-150%) overestimation in the winter but improved performance in the summer. The preliminary 2002 CMAQ runs identified several areas of enhancements to improve model performance, including revised temporal allocation factors for ammonia emissions to improve nitrate performance and addressing missing processes in the secondary organic aerosol module to improve OC performance.     

Transport and transformation of sulfur compounds over East Asia during the TRACE-P and ACE-Asia campaigns

On the basis of the recently estimated emission inventory for East Asia with a resolution of 1×1°, the transport and chemical transformation of sulfur compounds over East Asia during the period of 22 February through 4 May 2001 was investigated by using the Models-3 Community Multi-scale Air Quality (CMAQ) modeling system with meteorological fields calculated by the regional atmospheric modeling system (RAMS). For evaluating the model performance simulated concentrations of sulfur dioxide (SO₂) and aerosol sulfate (SO₄²⁻) were compared with the observations on the ground level at four remote sites in Japan and on board aircraft and vessel during the transport and chemical evolution over the Pacific and Asian Pacific regional aerosol characterization experiment field campaigns, and it was found that the model reproduces many of the important features in the observations, including horizontal and vertical gradients. The SO₂ and SO₄²⁻ concentrations show pronounced variations in time and space, with SO₂ and SO₄²⁻ behaving differently due to the interplay of chemical conversion, removal and transport processes. Analysis of model results shows that emission was the dominant term in regulating the SO₂ spatial distribution, while conversion of SO₂ to SO₄²⁻ in the gas phase and the aqueous phase and wet removal were the primary factors that controlled SO₄²⁻ amounts. The gas phase and the aqueous phase have the same importance in oxidizing SO₂, and about 42% sulfur compounds (25% in SO₂) emitted in the model domain was transported out, while about 57% (35% by wet removal processes) was deposited in the domain during the study period.     

Models for gas/particle partitioning,transformation and air/water surface exchange of PCBs and PCDD/Fs in CMAQ

We have added the capability to simulate polychlorinated biphenyls (PCBs) and polychlorinated dibenzo [p] dioxins and polychlorinated dibenzo-furans (PCDD/Fs) to the Community Multiscale Air Quality (CMAQ) modeling system, thus taking advantage of the latter's capability to simulate atmospheric advection, diffusion, gas-phase chemistry, cloud/precipitation, and aerosol processes. The modifications reported here include the addition to the CMAQ system of two gas/particle partitioning models options: the Junge–Pankow adsorption model and the K_OA absorption model, as well as chemical transformations and atmosphere/water surface exchange processes for these semi-volatile organics. Simulations for the purpose of model testing and validation were conducted for the years 2000 and 2002 on a domain covering most of North America. Both partitioning models give reasonable results when compared with available measurements. The model predictions of deposition and air concentrations also agree well with measurements. The modeling results also indicate that the long-range transport is important and anthropogenic emissions of PCBs and PCDD/Fs are dominant although surface exchange of PCBs may be important for some clean locations.     

Influence of ship emissions on air quality and input of contaminants in southern Alaska National Parks and Wilderness Areas during the 2006 tourist season

The impact of ship emissions on air quality in Alaska National Parks and Wilderness Areas was investigated using the Weather Research and Forecasting model inline coupled with chemistry (WRF/Chem). The visibility and deposition of atmospheric contaminants was analyzed for the length of the 2006 tourist season. WRF/Chem reproduced the meteorological situation well. It seems to have captured the temporal behavior of aerosol concentrations when compared with the few data available. Air quality follows certain predetermined patterns associated with local meteorological conditions and ship emissions. Ship emissions have maximum impacts in Prince William Sound where topography and decaying lows trap pollutants. Along sea-lanes and adjacent coastal areas, NO_x, SO₂, O₃, PAN, HNO₃, and PM_2.5 increase up to 650 pptv, 325 pptv, 900 pptv, 18 pptv, 10 pptv, and 100 ng m^?3. Some of these increases are significant (95% confidence). Enhanced particulate matter concentrations from ship emissions reduce visibility up to 30% in Prince William Sound and 5–25% along sea-lanes.     

Light-Duty Motor Vehicle Exhaust Particulate Matter Measurement in the Denver,Colorado, Area

ABSTRACT

A study of particulate matter (PM) emissions from in-use, light-duty vehicles was conducted during the summer of 1996 and the winter of 1997 in the Denver, CO, region. Vehicles were tested as received on chassis dynamometers on the Federal Test Procedure Urban Dynamometer Driving Schedule (UDDS) and the IM240 driving schedule. Both PM10 and regulated emissions were measured for each phase of the UDDS. For the summer portion of the study, 92 gasoline vehicles, 10 diesel vehicles, and 9 gasoline vehicles with visible smoke emissions were tested once. For the winter, 56 gasoline vehicles, 12 diesel vehicles, and 15 gasoline vehicles with visible smoke were tested twice, once indoors at 60 °F and once outdoors at the prevailing temperature. Vehicle model year ranged from 1966 to 1996. Impactor particle size distributions were obtained on a subset of vehicles. Continuous estimates of the particle number emissions were obtained with an electrical aerosol analyzer. This data set is being provided to the Northern Front Range Air Quality Study program and to the State of Colorado and the U.S. Environmental Protection Agency for use in updating emissions inventories.     

Process analysis of a regional air pollution episode over Pearl River Delta Region,China, using the MM5-CMAQ model

This study focuses on the influences of a warm high-pressure meteorological system on aerosol pollutants, employing the simulations by the Models-3/CMAQ system and the observations collected during October 10–12, 2004, over the Pearl River Delta (PRD) region. The results show that the spatial distributions of air pollutants are generally circular near Guangzhou and Foshan, which are cities with high emissions rates. The primary pollutant is particulate matter (PM) over the PRD. MM5 shows reasonable performance for major meteorological variables (i.e., temperature, relative humidity, wind direction) with normalized mean biases (NMB) of 4.5–38.8% and for their time series. CMAQ can capture one peak of all air pollutant concentrations on October 11, but misses other peaks. The CMAQ model systematically underpredicts the mass concentrations of all air pollutants. Compared with chemical observations, SO₂ and O₃ are predicted well with a correlation coefficient of 0.70 and 0.65. PM_2.5 and NO are significantly underpredicted with an NMB of 43% and 90%, respectively. The process analysis results show that the emission, dry deposition, horizontal transport, and vertical transport are four main processes affecting air pollutants. The contributions of each physical process are different for the various pollutants. The most important process for PM₁₀ is dry deposition, and for NO_x it is transport. The contributions of horizontal and vertical transport processes vary during the period, but these two processes mostly contribute to the removal of air pollutants at Guangzhou city, whose emissions are high. For this high-pressure case, the contributions of the various processes show high correlations in cities with the similar geographical attributes. According to the statistical results, cities in the PRD region are divided into four groups with different features. The contributions from local and nonlocal emission sources are discussed in different groups.

Implications: The characteristics of aerosol pollution episodes are intensively studied in this work using the high-resolution modeling system MM5/SMOKE/CMAQ, with special efforts on examining the contributions of different physical and chemical processes to air concentrations for each city over the PRD region by a process analysis method, so as to provide a scientific basis for understanding the formation mechanism of regional aerosol pollution under the high-pressure system over PRD.     

Needed: A National R&D Effort To Develop Individual Air Pollution Monitor Instrumentation

The results from the regional air quality analysis for the Four Corners Study are discussed in this paper. This study was one of five regional studies conducted for the National Commission on Air Quality. Potential regional air quality impacts were evaluated through the year 1995 for alternative energy scenarios under current and alternative regulatory policies. The alternative regulatory policies include emission fees, technology standards, emission ceilings, and prevention of significant deterioration class elimination. The alternatives were compared in terms of their impacts on regional visibility and on the ambient concentrations of SO₂, SO₄, and primary fine particulates. The fate of the pollutants was estimated. The alternative regulatory policies were quite different with respect to their control of SO_X emissions and their impacts on regional visibility. Sources located outside of the study region were estimated to have a major impact on regional air quality within the study region.     

Development of visibility forecasting modeling framework for the Lower Fraser Valley of British Columbia using Canada’s Regional Air Quality Deterministic Prediction System

Visibility degradation, one of the most noticeable indicators of poor air quality, can occur despite relatively low levels of particulate matter when the risk to human health is low. The availability of timely and reliable visibility forecasts can provide a more comprehensive understanding of the anticipated air quality conditions to better inform local jurisdictions and the public. This paper describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System (RAQDPS) for the Lower Fraser Valley of British Columbia. A baseline model (GM-IMPROVE) was constructed using the revised IMPROVE algorithm based on unprocessed forecasts from the RAQDPS. Three additional prototypes (UMOS-HYB, GM-MLR, GM-RF) were also developed and assessed for forecast performance of up to 48 hr lead time during various air quality and meteorological conditions. Forecast performance was assessed by examining their ability to provide both numerical and categorical forecasts in the form of 1-hr total extinction and Visual Air Quality Ratings (VAQR), respectively. While GM-IMPROVE generally overestimated extinction more than twofold, it had skill in forecasting the relative species contribution to visibility impairment, including ammonium sulfate and ammonium nitrate. Both statistical prototypes, GM-MLR and GM-RF, performed well in forecasting 1-hr extinction during daylight hours, with correlation coefficients (R) ranging from 0.59 to 0.77. UMOS-HYB, a prototype based on postprocessed air quality forecasts without additional statistical modeling, provided reasonable forecasts during most daylight hours. In terms of categorical forecasts, the best prototype was approximately 75 to 87% correct, when forecasting for a condensed three-category VAQR. A case study, focusing on a poor visual air quality yet low Air Quality Health Index episode, illustrated that the statistical prototypes were able to provide timely and skillful visibility forecasts with lead time up to 48 hr.

Implications: This study describes the development of a visibility forecasting modeling framework, which leverages the existing air quality and meteorological forecasts from Canada’s operational Regional Air Quality Deterministic Prediction System. The main applications include tourism and recreation planning, input into air quality management programs, and educational outreach. Visibility forecasts, when supplemented with the existing air quality and health based forecasts, can assist jurisdictions to anticipate the visual air quality impacts as perceived by the public, which can potentially assist in formulating the appropriate air quality bulletins and recommendations.     

Modeling analyses of the effects of changes in nitrogen oxides emissions from the electric power sector on ozone levels in the eastern United States

In this paper, we examine the changes in ambient ozone concentrations simulated by the Community Multiscale Air Quality (CMAQ) model for summer 2002 under three different nitrogen oxides (NOx) emission scenarios. Two emission scenarios represent best estimates of 2002 and 2004 emissions; they allow assessment of the impact of the NOx emissions reductions imposed on the utility sector by the NOx State Implementation Plan (SIP) Call. The third scenario represents a hypothetical rendering of what NOx emissions would have been in 2002 if no emission controls had been imposed on the utility sector. Examination of the modeled median and 95th percentile daily maximum 8-hr average ozone concentrations reveals that median ozone levels estimated for the 2004 emission scenario were less than those modeled for 2002 in the region most affected by the NOx SIP Call. Comparison of the "no-control" with the "2002" scenario revealed that ozone concentrations would have been much higher in much of the eastern United States if the utility sector had not implemented NOx emission controls; exceptions occurred in the immediate vicinity of major point sources where increased NO titration tends to lower ozone levels.     

Modeling emissions for three-dimensional atmospheric chemistry transport models

Poor air quality is still a threat for human health in many parts of the world. In order to assess measures for emission reductions and improved air quality, three-dimensional atmospheric chemistry transport modeling systems are used in numerous research institutions and public authorities. These models need accurate emission data in appropriate spatial and temporal resolution as input. This paper reviews the most widely used emission inventories on global and regional scales and looks into the methods used to make the inventory data model ready. Shortcomings of using standard temporal profiles for each emission sector are discussed, and new methods to improve the spatiotemporal distribution of the emissions are presented. These methods are often neither top-down nor bottom-up approaches but can be seen as hybrid methods that use detailed information about the emission process to derive spatially varying temporal emission profiles. These profiles are subsequently used to distribute bulk emissions such as national totals on appropriate grids. The wide area of natural emissions is also summarized, and the calculation methods are described. Almost all types of natural emissions depend on meteorological information, which is why they are highly variable in time and space and frequently calculated within the chemistry transport models themselves. The paper closes with an outlook for new ways to improve model ready emission data, for example, by using external databases about road traffic flow or satellite data to determine actual land use or leaf area. In a world where emission patterns change rapidly, it seems appropriate to use new types of statistical and observational data to create detailed emission data sets and keep emission inventories up-to-date.

Implications: Emission data are probably the most important input for chemistry transport model (CTM) systems. They need to be provided in high spatial and temporal resolution and on a grid that is in agreement with the CTM grid. Simple methods to distribute the emissions in time and space need to be replaced by sophisticated emission models in order to improve the CTM results. New methods, e.g., for ammonia emissions, provide grid cell–dependent temporal profiles. In the future, large data fields from traffic observations or satellite observations could be used for more detailed emission data.     

PM10 dispersion modeling for Treasure Valley, Idaho

The recorded exceedances of the 24-hr PM10 National Ambient Air Quality Standard (NAAQS) in Treasure Valley, Idaho, have been associated with prolonged stagnation periods during the winter. A comprehensive modeling study of PM10 impact in Treasure Valley was performed to support the State Implementation Plan (SIP). The study included base-year and short-term episodic conditions. The ISCST3 (Industrial Source Complex Short Term 3) model, using the base-year meteorology and gridded emissions of mobile sources, point sources, and wood burning as input, generally agreed well with measurements in both temporal patterns and annual averages. The WYNDvalley model was evaluated using monitoring data and was used to simulate the PM10 impact for episodic exceedances during stagnant winter conditions. An emission inventory was prepared for a base year (1995) and then extrapolated to the years 2000, 2005, 2010, and 2015 in order to determine air quality planning requirements. According to the simulations using base-year emissions and meteorology, exceedances are not expected. However, exceedances at some stations could be expected using projected emissions and episodic meteorology. Results from emission control strategies we developed indicate that mobile-source emissions have the most significant impact; reduction of 25% would be needed to eliminate the simulated exceedances in all projected years.     

An environmental decision-making tool for evaluating ground-level ozone-related health effects

A computer model called the Ozone Risk Assessment Model (ORAM) was developed to evaluate the health effects caused by ground-level ozone (O3) exposure. ORAM was coupled with the U.S. Environmental Protection Agency's (EPA) Third-Generation Community Multiscale Air Quality model (Models-3/CMAQ), the state-of-the-art air quality model that predicts O3 concentration and allows the examination of various scenarios in which emission rates of O3 precursors (basically, oxides of nitrogen [NOx] and volatile organic compounds) are varied. The principal analyses in ORAM are exposure model performance evaluation, health-effects calculations (expected number of respiratory hospital admissions), economic valuation, and sensitivity and uncertainty analysis through a Monte Carlo simulation. As a demonstration of the system, ORAM was applied to the eastern Tennessee region, and the entire O3 season was simulated for a base case (typical emissions) and three different emission scenarios. The results indicated that a synergism occurs when reductions in NOx emissions from mobile and point sources were applied simultaneously. A 12.9% reduction in asthma hospital admissions is expected when both mobile and point source NOx emissions are reduced (50 and 70%, respectively) versus a 5.8% reduction caused by mobile source and a 3.5% reduction caused by point sources when these emission sources are reduced individually.     

Modeling Analyses of the Effects of Changes in Nitrogen Oxides Emissions from the Electric Power Sector on Ozone Levels in the Eastern United States

Abstract

In this paper, we examine the changes in ambient ozone concentrations simulated by the Community Multiscale Air Quality (CMAQ) model for summer 2002 under three different nitrogen oxides (NO_x) emission scenarios. Two emission scenarios represent best estimates of 2002 and 2004 emissions; they allow assessment of the impact of the NO_x emissions reductions imposed on the utility sector by the NO_x State Implementation Plan (SIP) Call. The third scenario represents a hypothetical rendering of what NO_x emissions would have been in 2002 if no emission controls had been imposed on the utility sector. Examination of the modeled median and 95th percentile daily maximum 8-hr average ozone concentrations reveals that median ozone levels estimated for the 2004 emission scenario were less than those modeled for 2002 in the region most affected by the NO_x SIP Call. Comparison of the “no-control” with the “2002” scenario revealed that ozone concentrations would have been much higher in much of the eastern United States if the utility sector had not implemented NO_x emission controls; exceptions occurred in the immediate vicinity of major point sources where increased NO titration tends to lower ozone levels.     

Projected changes in particulate matter concentrations in the South Coast Air Basin due to basin-wide reductions in nitrogen oxides,volatile organic compounds,and ammonia emissions

An ozone abatement strategy for the South Coast Air Basin (SoCAB) has been proposed by the South Coast Air Quality Management District (SCAQMD) and the California Air Resources Board (ARB). The proposed emissions reduction strategy is focused on the reduction of nitrogen oxide (NO_x) emissions by the year 2030. Two high PM_2.5 concentration episodes with high ammonium nitrate compositions occurring during September and November 2008 were simulated with the Community Multi-scale Air Quality model (CMAQ). All simulations were made with same meteorological files provided by the SCAQMD to allow them to be more directly compared with their previous modeling studies. Although there was an overall under-prediction bias, the CMAQ simulations were within an overall normalized mean error of 50%; a range that is considered acceptable performance for PM modeling. A range of simulations of these episodes were made to evaluate sensitivity to NO_x and ammonia emissions inputs for the future year 2030. It was found that the current ozone control strategy will reduce daily average PM_2.5 concentrations. However, the targeted NO_x reductions for ozone were not found to be optimal for reducing PM_2.5 concentrations. Ammonia emission reductions reduced PM_2.5 and this might be considered as part of a PM_2.5 control strategy.

Implications: The SCAQMD and the ARB have proposed an ozone abatement strategy for the SoCAB that focuses on NO_x emission reductions. Their strategy will affect both ozone and PM_2.5. Two episodes that occurred during September and November 2008 with high PM_2.5 concentrations and high ammonium nitrate composition were selected for simulation with different levels of nitrogen oxide and ammonia emissions for the future year 2030. It was found that the ozone control strategy will reduce maximum daily average PM_2.5 concentrations but its effect on PM_2.5 concentrations is not optimal.