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Each year, millions of premature deaths worldwide are caused by exposure to outdoor air pollution, especially fine particulate matter (PM2.5). Designing policies to reduce these deaths relies on air quality modeling for estimating changes in PM2.5 concentrations from many scenarios at high spatial resolution. However, air quality modeling typically has substantial requirements for computation and expertise, which limits policy design, especially in countries where most PM2.5-related deaths occur. Lower requirement reduced-complexity models exist but are generally unavailable worldwide. Here, we adapt InMAP, a reduced-complexity model originally developed for the United States, to simulate annual-average primary and secondary PM2.5 concentrations across a global-through-urban spatial domain: "Global InMAP". Global InMAP uses a variable resolution grid, with horizontal grid cell widths ranging from 500 km in remote locations to 4km in urban locations. We evaluate Global InMAP performance against both measurements and a state-of-the-science chemical transport model, GEOS-Chem. Against measurements, InMAP predicts total PM2.5 concentrations with a normalized mean error of 62%, compared to 41% for GEOS-Chem. For the emission scenarios considered, Global InMAP reproduced GEOS-Chem pollutant concentrations with a normalized mean bias of 59%–121%, which is sufficient for initial policy assessment and scoping. Global InMAP can be run on a desktop computer; simulations here took 2.6–8.4 hours. This work presents a global, open-source, reduced-complexity air quality model to facilitate policy assessment worldwide, providing a screening tool for reducing air pollution-related deaths where they occur most. [ABSTRACT FROM AUTHOR]

Agriculture is a major contributor to air pollution, the largest environmental risk factor for mortality in the United States andworldwide. It is largely unknown, however, how individual foods or entire diets affect human health via poor air quality. We show how food production negatively impacts human health by increasing atmospheric fine particulate matter (PM2.5), and we identify ways to reduce these negative impacts of agriculture. We quantify the air quality-related health damages attributable to 95 agricultural commodities and 67 final food products, which encompass >99% of agricultural production in the United States. Agricultural production in the United States results in 17,900 annual air quality-related deaths, 15,900 of which are from food production. Of those, 80% are attributable to animalbased foods, both directly fromanimal production and indirectly from growing animal feed. On-farm interventions can reduce PM2.5-related mortality by 50%, including improved livestock waste management and fertilizer application practices that reduce emissions of ammonia, a secondary PM2.5 precursor, and improved crop and animal production practices that reduce primary PM2.5 emissions from tillage, field burning, livestock dust, and machinery. Dietary shifts toward more plant-based foods that maintain protein intake and other nutritional needs could reduce agricultural air quality-related mortality by 68 to 83%. In sum, improved livestock and fertilization practices, and dietary shifts could greatly decrease the health impacts of agriculture caused by its contribution to reduced air quality. [ABSTRACT FROM AUTHOR]

Source contributions to ultrafine particle number concentrations for a summertime period in the Eastern U.S. are investigated using the chemical transport model PMCAMx-UF. New source-resolved number emissions inventories are developed for biomass burning, dust, gasoline automobiles, industrial sources, non-road and on-road diesel. According to the inventory for this summertime period in the Eastern U.S., gasoline automobiles are responsible for 40% of the ultrafine particle number emissions, followed by industrial sources (33%), non-road diesel (16%), on-road diesel (10%), and 1% from biomass burning and dust. With these emissions as input, the chemical transport model PMCAMx-UF reproduces observed ultrafine particle number concentrations (N 3-100 ) in Pittsburgh with an error of 12%. For this summertime period in the Eastern U.S., nucleation is predicted to be the source of more than 90% of the total particle number concentrations. The source contributions to primary particle number concentrations are on average similar to those of their source emissions contributions: gasoline is predicted to contribute 36% of the total particle number concentrations, followed by industrial sources (31%), non-road diesel (18%), on-road diesel (10%), biomass burning (1%), and long-range transport (4%). For this summertime period in Pittsburgh, number source apportionment predictions for particles larger than 3 nm in diameter (traffic 65%, other combustion sources 35%) are consistent with measurement-based source apportionment (traffic 60%, combustion sources 40%). [ABSTRACT FROM AUTHOR]

Abstract: The Particulate Matter Source Apportionment (PSAT) method is used to quantify the impacts of different source regions on fine particulate matter (PM) concentrations in the Eastern United States. Our analysis focuses both on how far pollutants are transported and the impacts they have in the corresponding receptor areas. Towards this goal, several quantitative measures of impact and transport distance are proposed and calculated for ten source regions for all seasons. The long range source impacts are extremely variable in space and time and are often in directions different than that of the average prevailing winds. Transport distances were usually lower during the summer than in other seasons for this region. The average transport distance (distance from the source area to the center of the pollution plume) for elemental carbon and other primary fine PM components was found to be 100–200km for most source regions. On the other hand, the secondary PM species were found to be transported the furthest with sulfate and secondary organic aerosol (SOA) traveling on average over 350km. Maximum transport distances are significant higher, with sulfate impacts reaching as far as 2000km away from the SO2 source region. The fractional contribution of a source region to fine PM ground level concentrations can be quite different (up to a factor of 3) than its emission contribution. This is mainly due to the height where the emissions are released. Regions with mainly ground level emissions contribute more while regions with elevated emissions less than the magnitude of their emissions suggests. [ABSTRACT FROM AUTHOR]

Capturing the effects of the complex processes of chemical aging of biogenic secondary organic aerosol (SOA) in chemical transport models (CTMs) has been challenging. Recent laboratory results from atmospheric simulation chambers are used in this study to develop a parameterization for biogenic SOA formation as a result of aging for use in CTMs using the Volatility Basis Set framework. This parameterization was implemented in PMCAMx which was then applied over the eastern United States to simulate summertime conditions. Using the base case parameterization of monoterpene SOA chemical aging resulted in modest increases (17–21%) in predicted domain average biogenic SOA. An alternative parameterization was developed fitting the same laboratory results, but assuming higher volatility products of chemical aging reactions. Use of this parameterization resulted in small increases (1–4%) of the predicted biogenic SOA. The PMCAMx predictions in sites where most of the SOA was biogenic were evaluated against measurements from the EPA IMPROVE network in July 2001 and during the Southern Oxidant and Aerosol Study in June 2013. The differences in the model performance were modest and mixed, a result consistent with the relatively small effect of the proposed parameterization on total organic aerosol levels. • Developed parameterization for monoterpene aging chemistry in VBS. • Modest increases (17–21%) predicted for biogenic SOA during summer in Eastern US. • Sensitivity tests suggest that the effect may be even smaller. • Modest effect on the performance of PMCAMx during 2001 and 2013 (SOAS). [ABSTRACT FROM AUTHOR]

Focuses on the sources of atmospheric carbonaceous particulate matter in Pittsburgh, Pennsylvania. Details of a stabilization method for air pollution control residues from municipal solid waste incineration; Types of air pollution control residues; Details of the leaching tests done for raw residues.

three-dimensional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions [PMCAMx]) is used to investigate changes in fine particle (PM2.5) concentrations in response to 50% emissions changes of oxides of nitrogen (NOx) and anthropogenic volatile organic compounds (VOCs) during July 2001 and January 2002 in the eastern United States. The reduction of NOx emissions by 50% during the summer results in lower average oxidant levels and lowers PM2.5 (8% on average), mainly because of reductions of sulfate (9-11%), nitrate (45-58%), and ammonium (7-11%). The organic particulate matter (PM) slightly decreases in rural areas, whereas it increases in cities by a few percent when NOx is reduced. Reduction of NOx during winter causes an increase of the oxidant levels and a rather complicated response of the PM components, leading to small net changes. Sulfate increases (8-17%), nitrate decreases (18- 42%), organic PM slightly increases, and ammonium either increases or decreases a little. The reduction of VOC emissions during the summer causes on average a small increase of the oxidant levels and a marginal increase in PM2.5. This small net change is due to increases in the inorganic components and decreases of the organic ones. Reduction of VOC emissions during winter results in a decrease of the oxidant levels and a 5-10% reduction of PM2.5 because of reductions in nitrate (4-19%), ammonium (4-10%), organic PM (12-14%), and small reductions in sulfate. Although sulfur dioxide (SO2) reduction is the single most effective approach for sulfate control, the coupled decrease of SO2 and NOx emissions in both seasons is more effective in reducing total PM2.5 mass than the SO2 reduction alone. [ABSTRACT FROM AUTHOR]

Ammonium sulfate particles were generated by atomization and introduced into a smog chamber where they were coated with secondary organic aerosol from ozonolysis of limonene or α-pinene. These mixed particles were then sampled with a humidified Tandem-DMA system where a monodisperse aerosol population was selected, humidified, and dried to observe the relative humidity (RH) at which the particles returned to the original dry diameter. The volume fraction of secondary organic aerosol (SOA) in the mixed particles ranged from 0.59 to 0.94 for limonene SOA and 0.54 to 0.72 for α-pinene SOA. Efflorescence RHs for our mixed aerosols were in the range of 28–34%, similar to our observation of 32% ERH for pure ammonium sulfate nanoparticles. These findings indicate that the effect of SOA on the ERH of inorganic salts in the atmosphere may be negligible. [ABSTRACT FROM AUTHOR]

The goal of this modeling study is to determine how concentrations of ozone respond to changes in climate over the eastern USA. The sensitivities of average ozone concentrations to temperature, wind speed, absolute humidity, mixing height, cloud liquid water content and optical depth, cloudy area, precipitation rate, and precipitating area extent are investigated individually. The simulation period consists of July 12–21, 2001, during which an ozone episode occurred over the Southeast. The ozone metrics used include daily maximum 8h average O3 concentration and number of grid cells exceeding the US EPA ambient air-quality standard. The meteorological factor that had the largest impact on both ozone metrics was temperature, which increased daily maximum 8h average O3 by 0. 34ppbK−1 on average over the simulation domain. Absolute humidity had a smaller but appreciable effect on daily maximum 8h average O3 (−0. 025ppb for each percent increase in absolute humidity). While domain-average responses to changes in wind speed, mixing height, cloud liquid water content, and optical depth were rather small, these factors did have appreciable local effects in many areas. Temperature also had the largest effect on air-quality standard exceedances; a 2. 5K temperature increase led to a 30% increase in the area exceeding the EPA standard. Wind speed and mixing height also had appreciable effects on ozone air-quality standard exceedances. [Copyright &y& Elsevier]

Reductions in airborne sulfate concentration may cause inorganic fine particulate matter (PM[sub2.5]) to respond nonlinearly, as nitric acid gas may transfer to the aerosol phase. Where this occurs, reductions in sulfur dioxide (SO[sub2]) emissions will be much less effective than expected at reducing PM[sub2.5]. As a measure of the efficacy of reductions in sulfate concentration on PM[sub2.5], we define marginal PM[sub2.5] as the local change in PM[sub2.5] resulting from a small change in sulfate concentration. Using seasonal-average conditions and assuming thermodynamic equilibrium, we find that the conditions for PM[sub2.5] to respond nonlinearly to sulfate reductions are common in the eastern United States in winter, occurring at half of the sites considered, and uncommon in summer, due primarily to the influence of temperature. Accounting for diurnal and intraseasonal variability, we find that seasonal-average conditions provide a reasonable indicator of the time-averaged PM[sub2.5] response. These results indicate that reductions in sulfate concentration may be up to 50% less effective at reducing the annual-average PM[sub2.5] than if the role of nitric acid is neglected. Further, large reductions in sulfate will also cause an increase in aerosol nitrate in many regions that are the most acidic. [ABSTRACT FROM AUTHOR]

Biogenic secondary organic aerosol (bSOA) is a major component of atmospheric particulate matter (PM 2.5) in the southeast United States especially during the summer, when emissions of biogenic volatile organic compound (VOCs) are high and emissions from anthropogenic sources enhance the formation of secondary particulate matter. In this work we test the hypothesis whether a chemical transport model (PMCAMx) that includes a detailed description of gas-phase chemistry, secondary organic aerosol (SOA) formation based on the volatility basis set (VBS), and interactions among compounds based on partitioning theory can predict organic aerosol (OA) concentrations that are consistent with the observed changes in OA in response to significant changes in anthropogenic emissions during the summers of 2001 and 2010. The model had good performance for OA for both periods and its predictions were consistent with the observed changes in both the urban and rural areas. The fractional error of OA predictions remained practically the same (0.41 and 0.44 at Chemical Speciation Network (CSN) sites and 0.40 to 0.41 at Interagency Monitoring of Protected Visual Environments (IMPROVE) sites in the summers of 2001 and 2010 respectively) in the two examined periods. The fractional bias of OA predictions increased from 0.10 to 0.22 at CSN sites and decreased from 0 to −0.09 at IMPROVE sites between the two periods. Average predicted bSOA concentrations in the southeast US did not change appreciably from the summer of 2001 to the summer of 2010, while the anthropogenic SOA decreased by 45%. As a result, the biogenic fraction of predicted total OA increased from 0.46 in 2001 to 0.63 in 2010. Partitioning effects due to reduced anthropogenic OA from 2001 resulted in 0.4 μg m−3 less biogenic OA on average in the southeast US in the summer of 2010. This was offset by biogenic SOA increases due to higher biogenic vapor emissions in the warmer 2010 summer. Removing the NO x -dependence of SOA formation yields resulted in higher fractional error and fractional bias at both CSN and IMPROVE sites in both summer periods, demonstrating the efficacy of the current formulation of SOA yields. The results of the analysis support the conclusion that a CTM that simulates NO x -dependent SOA chemistry and semivolatile partitioning of SOA material can consistently predict the observed changes in a region rich in biogenic VOCs and SOA. • PMCAMx adequately reproduced OA in the summer in the SE US in 2001 and 2010. • Anthropogenic SOA decreased by 45%. • Small change in biogenic SOA due to warmer temperatures in 2010. • Biogenic SOA increased from 46% to 63% of the total OA. • Emission changes, partitioning effects and NO x changes were the major drivers for OA. [ABSTRACT FROM AUTHOR]

Abstract: The global–regional climate–air pollution modeling system (GRE-CAPS) was applied over the eastern United States to study the impact of climate change on the concentration and deposition of atmospheric mercury. Summer and winter periods (300days for each) were simulated, and the present-day model predictions (2000s) were compared to the future ones (2050s) assuming constant emissions. Climate change affects Hg2+ concentrations in both periods. On average, atmospheric Hg2+ levels are predicted to increase in the future by 3% in summer and 5% in winter respectively due to enhanced oxidation of Hg0 under higher temperatures. The predicted concentration change of Hg2+ was found to vary significantly in space due to regional-scale changes in precipitation, ranging from −30% to 30% during summer and −20% to 40% during winter. Particulate mercury, Hg(p) has a similar spatial response to climate change as Hg2+, while Hg0 levels are not predicted to change significantly. In both periods, the response of mercury deposition to climate change varies spatially with an average predicted increase of 6% during summer and 4% during winter. During summer, deposition increases are predicted mostly in the western parts of the domain while mercury deposition is predicted to decrease in the Northeast and also in many areas in the Midwest and Southeast. During winter mercury deposition is predicted to change from −30% to 50% mainly due to the changes in rainfall and the corresponding changes in wet deposition. [Copyright &y& Elsevier]

Abstract: Scanning electron microscopy coupled to energy-dispersive x-ray spectroscopy (SEM/EDX) was used to quantify individual bioparticles in PM2.5 samples collected during the Pittsburgh Air Quality Study. Microscopy-based estimates of primary biogenic organic aerosol (PBOA) mass were compared to carbohydrate mass associated with PM2.5. Carbohydrates show substantial seasonal variations, with higher concentrations in the spring and the fall. During the summer, carbohydrates were about 30% of the estimated PBOA concentrations, but in the winter carbohydrate concentrations often greatly exceeded the PBOA mass estimate. Spores and insect detritus were the most abundant PBOA types in the summer samples, while winter samples were comprised predominantly of a mixture of microorganisms, insect and vegetative detritus. During the summer PBOA contributed on average 6.9±5.4% by mass of the PM2.5 versus 3.3±1.4% of the PM2.5 mass during the winter. [ABSTRACT FROM AUTHOR]

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 PM2. 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 PM2. 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 PM2. 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. [Copyright &y& Elsevier]

Daily ambient aerosol samples were taken in Pittsburgh, Pennsylvania from the summer 2001 to the winter 2002 as part of the Pittsburgh Air Quality Study (PAQS). The study measured PM2.5 mass by the Federal Reference Method (FRM) and the PM2.5 chemical composition by a variety of filter-based and continuous instruments. This paper examines the mass balance between the FRM-measured mass and the sum of the aerosol chemical components. For the 7-month study period, the average FRM-measured mass is 11% greater than the sum of the mass of the aerosol chemical components. This mass balance discrepancy varies seasonally, with the average FRM-measured mass 17% greater than the sum of the chemical components for the summer months, with discrepancies as large as 30% during certain periods. Meanwhile, the FRM-measured mass was at or slightly below the sum of the chemical components for the winter months.The mass balance discrepancy and its seasonal shift cannot be explained by measurement uncertainty; instead the discrepancy is due to combination of retained aerosol water on the conditioned FRM filters and volatilization losses. The relative importance of these different effects varies with aerosol composition and causes the observed seasonal variation in the mass balance. The contribution of the aerosol water to the FRM-measured mass is estimated using continuous measurements of aerosol water at the site; volatilization losses are estimated from other filter-based instruments. Water contributes 16% of the FRM mass in the summer, and 8% of the FRM mass in the winter; it also appears responsible for episodes where the FRM-measured mass is significantly greater than the sum of components. Retention of water is greatest during acidic conditions, which commonly occur during the summer months. Volatilization losses are estimated at 5% of the FRM mass during the summer, and 9% for the winter. Volatilization losses appear to be most significant on days dominated by organic aerosol, or winter days with relatively high nitrate concentration. Accounting for the effects of water and volatilization losses closes the mass balance between the FRM and the sum of the chemical components, providing insight into the FRM measurements. [Copyright &y& Elsevier]

Ambient sampling for the Pittsburgh Air Quality Study (PAQS) was conducted from July 2001 to September 2002. The study was designed (1) to characterize particulate matter (PM) by examination of size, surface area, and volume distribution, chemical composition as a function of size and on a single particle basis, morphology, and temporal and spatial variability in the Pittsburgh region; (2) to quantify the impact of the various sources (transportation, power plants, biogenic sources, etc.) on the aerosol concentrations in the area; and (3) to develop and evaluate the next generation of atmospheric aerosol monitoring and modeling techniques. The PAQS objectives, study design, site descriptions and routine and intensive measurements are presented. Special study days are highlighted, including those associated with elevated concentrations of daily average PM2.5 mass. Monthly average and diurnal patterns in aerosol number concentration, and aerosol nitrate, sulfate, elemental carbon, and organic carbon concentrations, light scattering as well as gas-phase ozone, nitrogen oxides, and carbon monoxide are discussed with emphasis on the processes affecting them. Preliminary findings reveal day-to-day variability in aerosol mass and composition, but consistencies in seasonal average diurnal profiles and concentrations. For example, the seasonal average variations in the diurnal PM2.5 mass were predominately driven by the sulfate component. [Copyright &y& Elsevier]

The secondary organic aerosol (SOA) module in PMCAMx, a three-dimensional chemical transport model, has been updated to incorporate NOx-dependent SOA yields. Under low-NOx conditions, the RO2 radicals react with other peroxy radicals to form a distribution of products with lower volatilities, resulting in higher SOA yields. At high-NOx conditions, the SOA yields are lower because aldehydes, ketones, and nitrates dominate the product distribution. Based on recent laboratory smog chamber experiments, high-NOx SOA parametrizations were created using the volatility basis-set approach.The organic aerosol (OA) concentrations in the Eastern US are simulated for a summer episode, and are compared to the available ambient measurements. Changes in NOx levels result in changes of both the oxidants (ozone, OH radical, etc.) and the SOA yields during the oxidation of the corresponding organic vapors. The NOx dependent SOA parametrization predicts a maximum average SOA concentration of 5.2 microg m(-3) and a domain average concentration of 0.6 microg m(-3). As the NOx emissions are reduced by 25%, the domain average SOA concentration does not significantly change, but the response is quite variable spatially. However, the predicted average SOA concentrations increase in northern US cities by around 3% but decrease in the rural southeast US by approximately 5%. A decrease of the average biogenic SOA by roughly 0.5 microg m(-3) is predicted for the southeast US for a 50% reduction in NOx emissions.

A three-dimensional chemical transport model (PMCAMx) was used to investigate changes in fine particle (PM2.5) concentrations in response to changes in sulfur dioxide (SO2) and ammonia (NH3) emissions during July 2001 and January 2002 in the eastern United States. A uniform 50% reduction in SO2 emissions was predicted to produce an average decrease of PM2.5 concentrations by 26% during July but only 6% during January. A 50% reduction of NH3 emissions leads to an average 4 and 9% decrease in PM2.5 in July and January, respectively. During the summer, the highest concentration of sulfate is in South Indiana (12.8 microg x m(-3)), and the 50% reduction of SO2 emissions results in a 5.7 microg x m(-3) (44%) sulfate decrease over this area. During winter, the SO2 emissions reduction results in a 1.5 microg x m(-3) (29%) decrease of the peak sulfate levels (5.2 microg x m(-3)) over Southeast Georgia. The maximum nitrate and ammonium concentrations are predicted to be over the Midwest (1.9 (-3)g x m(-3) in Ohio and 5.3 microg x m(-3) in South Indiana, respectively) in the summer whereas in the winter these concentrations are higher over the Northeast (3 microg x m(-3) of nitrate in Connecticut and 2.7 microg x m(-3) of ammonium in New York). The 50% NH3 emissions reduction is more effective for controlling nitrate, compared with SO2 reductions, producing a 1.1 microg x m(-3) nitrate decrease over Ohio in July and a 1.2 microg x m(-3) decrease over Connecticut in January. Ammonium decreases significantly when either SO2 or NH3 emissions are decreased. However, the SO2 control strategy has better results in July when ammonium decreases, up to 2 microg x m(-3) (37%), are predicted in South Indiana. The NH3 control strategy has better results in January (ammonium decreases up to 0.4 microg x m(-3) in New York). The spatial and temporal characteristics of the effectiveness of these emission control strategies during the summer and winter seasons are discussed.

Current regulation aimed at reducing inorganic atmospheric fine particulate matter (PM2.5) is focused on reductions in sulfur dioxide (SO2) and oxides of nitrogen (NO(x) = NO + NO2); however, controls on these pollutants are likely to increase in cost and decrease in effectiveness in the future. A supplementary strategy is reduction in ammonia (NH3) emissions, yet an evaluation of controls on ammonia has been limited by uncertainties in emission levels and in the cost of control technologies. We use state of the science emission inventories, an emission-based regional air quality model, and an explicit treatment of uncertainty to estimate the cost-effectiveness and uncertainty of ammonia emission reductions on inorganic particulate matter in the Eastern United States. Since a paucity of data on agricultural operations precludes a direct calculation of the costs of ammonia control, we calculate the "ammonia savings potential", defined as the minimum cost of applying SO2 and NO(x) emission controls in order to achieve the same reduction in ambient inorganic PM2.5 concentration as obtained from a 1 ton decrease in ammonia emissions. Using 250 scenarios of NH3, SO2, and NO(x) emission reductions, we calculate the least-cost SO2 and NO(x) control scenarios that achieve the same reduction in ambient inorganic PM2.5 concentration as a decrease in ammonia emissions. We find that the lower-bound ammonia savings potential in the winter is $8,000 per ton NH3; therefore, many currently available ammonia control technologies are cost-effective compared to current controls on SO2 and NO(x) sources. Larger reductions in winter inorganic particulate matter are available at lower cost through controls on ammonia emissions.