Use of stationary and mobile measurements to study power plant emissions

This paper presents a technique to study air pollution by combining high spatial resolution data obtained by a mobile platform and those measured by conventional stationary stations. Conventional stations provide time-series point data but cannot yield information that is distant from the sites. This can be complemented or supplemented by mobile measurements in the vicinity of the conventional sites. Together, the combined dataset yields a clearer and more precise picture of the dispersion and the transformation of pollutants in the atmosphere in a fixed time frame. Several experiments were conducted in the years 2002-2003 to track the impact of power plant plumes on ground receptors in the immediate vicinity (within a radius of 30 km) of the plants, using a combined mobile and stationary dataset. The mobile data allowed the identification of emissions from coal-fired and gas-fired power plants. Coal-fired power plants were the major source of sulfur dioxide (SO2), whereas nitrogen oxides (NOx) emitted from the gas-fired power plant played an important role in the formation of ozone (O3) at ground level. The mobile data showed that two particle size distribution regimes were detected: one had a dominant accumulation mode at 0.40-0.65 microm and the other at 0.65-1 microm. The existence of particles characterized by their mode at 0.65-1 microm and formed by in-cloud processes suggests that vehicular emissions were not the important source. Other local sources, such as power plants (elevated emission), were the likely sources, because Hong Kong does not have much manufacturing industry.     

Relating summer ambient particulate sulfur, sulfur dioxide, and light scattering to gaseous tracer emissions from the MOHAVE Power Project

Project MOHAVE was initiated in 1992 to examine the role of emissions from the 1580 MW coal-fired MOHAVE Power Project (MPP) on haze at the Grand Canyon National Park (GCNP), located about 130 km north-north-east of the power plant. Statistical relationships were analyzed between summertime ambient concentrations of a gaseous perfluorocarbon tracer released from MPP and ambient SO2, particulate sulfur, and light scattering to evaluate whether MPP's emissions could be transported to the GCNP and then impact haze levels there. Spatial analyses indicated that particulate sulfur levels were strongly correlated across the monitoring network, regardless of whether the monitoring stations were upwind or downwind of MPP. This indicates that particulate sulfur levels in this region were influenced by distant regional emission sources. A significant particulate sulfur contribution from a point source such as MPP would result in a non-uniform pattern downwind. There was no suggestion of this in the data. Furthermore, correlations between the MPP tracer and ambient particulate sulfur and light scattering at locations in the park were virtually zero for averaging times ranging from 24 hr to 1 hr. Hour-by-hour MPP tracer levels and light scattering were individually examined, and still no positive correlations were detected. Finally, agreement between tracer and particulate sulfur did not improve as a function of meteorological regime, implying that, even during cloudy monsoon days when more rapid conversion of SO2 to particulate sulfur would be expected, there was no evidence for downwind particulate sulfur impacts. Despite the fact that MPP was a large source of SO2 and tracer, neither time series nor correlation analyses were able to detect any meaningful relationship between MPP's SO2 and tracer emission "signals" to particulate sulfur or light scattering.     

Catalytic Cigarette Filter for Carbon Monoxide Reduction

A comparative study was performed in order to determine the relative accuracy of a gaussian dispersion model. The U.S. EPA’s RAM (Urban) model was chosen to estimate 24-hour average sulfur dioxide concentrations in the Cleveland, Ohio area. Point and area source emissions, along with a background concentration were included in the modeling effort. Projections from the model made at the ambient air stations were compared to measured sulfur dioxide concentrations. A total of 3020 comparisons were performed at 33 monitoring sites. An analysis of the results illustrates that, on a daily basis, the predictions of the model did not reflect actual air quality. The correlation coefficients of the 24-hour comparisons at the monitoring sites varied from a low of —0.121 to a high of 0.541. When the highest and second highest modeled concentrations were evaluated with respect to the highest and second highest measured concentrations, over a period of a year, a more favorable comparison was observed.     

Simulation of stack plume opacity

The visual impact of primary particles emitted from stacks is regulated according to stack opacity criteria. In-stack monitoring of the flue gas opacity allows plant operators to ensure that the plant meets U.S. Environmental Protection Agency opacity regulations. However, the emission of condensable gases such as SO3 (that hydrolyzes to H2SO4), HCl, and NH3, which may lead to particle formation after their release from the stack, makes the prediction of stack plume opacity more difficult. We present here a computer simulation model that calculates the opacity due to both primary particles emitted from the stack and secondary particles formed in the atmosphere after the release of condensable gases from the stack. A comprehensive treatment of the plume rise due to buoyancy and momentum is used to calculate the location at which the condensed water plume has evaporated (i.e., where opacity regulations apply). Conversion of H2SO4 to particulate sulfate occurs through nucleation and condensation on primary particles. A thermodynamic aerosol equilibrium model is used to calculate the amount of ammonium, chloride, and water present in the particulate phase with the condensed sulfate. The model calculates the stack plume opacity due to both primary and secondary particles. Examples of model simulations are presented for three scenarios that differ by the emission control equipment installed at the power plant: (1) electrostatic precipitators (ESP), (2) ESP and flue gas desulfurization, and (3) ESP and selective catalytic reduction. The calculated opacity is most sensitive to the primary particulate emissions. For the conditions considered here, SO3 emissions showed only a small effect, except if one assumes that most H2SO4 condenses on primary particles. Condensation of NH4Cl occurs only at high NH3 emission rates (about 25 ppm stack concentration).     

Application of the tracer-aerosol gradient interpretive technique to sulfur attribution for the big bend regional aerosol and visibility observational study

A simple data analysis method called the Tracer-Aerosol Gradient Interpretive Technique (TAGIT) is used to attribute particulate S and SO2 at Big Bend National Park in Texas and nearby areas to local and regional sources. Particulate S at Big Bend is of concern because of its effects on atmospheric visibility. The analysis used particulate S, SO2, and perfluorocarbon tracer data from six 6-hr sampling sites in and near Big Bend National Park. The data were collected in support of the Big Bend Regional Aerosol and Visibility Observational (BRAVO) Study; the field portion was conducted from July through October 1999. Perfluorocarbon tracer was released continuously from a tower at Eagle Pass, TX, approximately 25 km northeast of two large coal-fired power plants (Carbon I and II) in Coahuila, Mexico, and approximately 270 km east-southeast of Big Bend National Park. The perfluorocarbon tracer did not properly represent the location of the emissions from the Carbon power plants for individual 6-hr sampling periods and attributed only 3% of the particulate S and 27% of the SO2 at the 6-hr sites in and near Big Bend to sources represented by the tracer. An alternative approach using SO2 to tag "local" sources such as the Carbon plants attributed 10% of the particulate S and 75% of the SO2 at the 6-hr sites to local sources. Based on these two approaches, most of the regional (65-86%) and a small fraction (19-31%) of the local SO2 was converted to particulate S. The analysis implies that substantial reductions in particulate S at Big Bend National Park cannot be achieved by only reducing emissions from the Carbon power plants; reduction of emissions from many sources over a regional area would be necessary.     

Multivariate space analysis of the major precipitation ions over Europe, 1986-1997

The annual average concentrations (1986-1997) of the major ions SO4(2-), NO3-, Cl-, NH4+, Na+, Mg2+, Ca2+, and K+ in precipitation are analyzed for selected EMEP stations. The objective is to determine the ion patterns or typologies in precipitation by principal component analysis (PCA) combined with a cluster analysis. SO4(2-) and NO3- ions are predominant in central and eastern Europe. This area corresponds to high emissions of SO2 and NO2. Sea spray ions are predominant in coastal sites. The soil components show an important contribution in southern Europe, possibly due to the soil dust transported from northern Africa.     

Assessment and rationalization of water quality monitoring network: a multivariate statistical approach to the Kabbini River (India)

The establishment of an efficient surface water quality monitoring (WQM) network is a critical component in the assessment, restoration and protection of river water quality. A periodic evaluation of monitoring network is mandatory to ensure effective data collection and possible redesigning of existing network in a river catchment. In this study, the efficacy and appropriateness of existing water quality monitoring network in the Kabbini River basin of Kerala, India is presented. Significant multivariate statistical techniques like principal component analysis (PCA) and principal factor analysis (PFA) have been employed to evaluate the efficiency of the surface water quality monitoring network with monitoring stations as the evaluated variables for the interpretation of complex data matrix of the river basin. The main objective is to identify significant monitoring stations that must essentially be included in assessing annual and seasonal variations of river water quality. Moreover, the significance of seasonal redesign of the monitoring network was also investigated to capture valuable information on water quality from the network. Results identified few monitoring stations as insignificant in explaining the annual variance of the dataset. Moreover, the seasonal redesign of the monitoring network through a multivariate statistical framework was found to capture valuable information from the system, thus making the network more efficient. Cluster analysis (CA) classified the sampling sites into different groups based on similarity in water quality characteristics. The PCA/PFA identified significant latent factors standing for different pollution sources such as organic pollution, industrial pollution, diffuse pollution and faecal contamination. Thus, the present study illustrates that various multivariate statistical techniques can be effectively employed in sustainable management of water resources. Highlights ? The effectiveness of existing river water quality monitoring network is assessed ? Significance of seasonal redesign of the monitoring network is demonstrated ? Rationalization of water quality parameters is performed in a statistical framework     

Monitoring and modelling of biosphere/atmosphere exchange of gases and aerosols in Europe

Monitoring and modelling of deposition of air pollutants is essential to develop and evaluate policies to abate the effects related to air pollution and to determine the losses of pollutants from the atmosphere. Techniques for monitoring wet deposition fluxes are widely applied. A recent intercomparison experiment, however, showed that the uncertainty in wet deposition is relatively high, up to 40%, apart from the fact that most samplers are biased because of a dry deposition contribution. Wet deposition amounts to about 80% of the total deposition in Europe with a range of 10-90% and uncertainty should therefore be decreased. During recent years the monitoring of dry deposition has become possible. Three sites have been operational for 5 years. The data are useful for model development, but also for model evaluation and monitoring of progress in policy. Data show a decline in SO(2) dry deposition, whereas nitrogen deposition remained constant. Furthermore, surface affinities for pollutants changed leading to changes in deposition. Deposition models have been further developed and tested with dry deposition measurements and total deposition measurements on forests as derived from throughfall data. The comparison is reasonable given the measurement uncertainties. Progress in ozone surface exchange modelling and monitoring shows that stomatal uptake can be quantified with reasonable accuracy, but external surface uptake yields highest uncertainty.     

Industrial sources influence air concentrations of hydrogen sulfide and sulfur dioxide in rural areas of western Canada

A survey of monthly average concentrations of sulfur dioxide (SO2) and hydrogen sulfide (H2S) at rural locations in western Canada (provinces of Alberta, British Columbia, and Saskatchewan) was conducted in 2001-2002, as part of an epidemiological study of the effects of oil and gas industry emissions on the health of cattle. Repeated measurements were obtained at some months and locations. We aimed to develop statistical models of the effect of oil and gas infrastructure on air concentrations. The regulatory authorities supplied the information on location of the different oil and gas facilities during the study period and, for Alberta, provided data on H2S content of wells and flaring volumes. Linear mixed effects models were used to relate observed concentrations to proximity and type of oil and gas infrastructure. Low concentrations were recorded; the monthly geometric mean was 0.1-0.2 ppb for H2S, and 0.3-1.3 ppb for SO2. Substantial variability between repeated measurements was observed. The precision of the measurement method was 0.005 ppb for both contaminants. There were seasonal trends in the concentrations, but the spatial variability was greater. This was explained, in part, by proximity to oil/gas/bitumen wells and (for SO2) gas plants. Wells within 2 km of monitoring stations had the greatest impact on measured concentrations. For H2S, 8% of between-location variability was explained by proximity to industrial sources of emissions; for SO2 this proportion was 18%. In Alberta, proximity to sour gas wells and flares was associated with elevated H2S concentrations; however, the estimate of the effect of sour gas wells in the immediate vicinity of monitoring stations was unstable. Our study was unable to control for all possible sources of the contaminants. However, the results suggest that oil and gas extraction activities contribute to air pollution in rural areas of western Canada.     

Monitoring airborne dust in a high density coal-fired power station region in North Yorkshire

Concerns about the levels of dust deposition in the vicinity of coal-fired power stations in North Yorkshire, in particular Drax Power Station, prompted the commissioning of a detailed monitoring study in the area. This paper describes the first two years' work. The first 12-month study concentrated on the village of Barlow close to Drax Power Station, whilst in the second 12-month study, monitoring sites were spread along a transect passing through the power station belt formed by Ferrybridge, Eggborough and Drax Power Stations. Two monitoring sites were common to both 12-month studies, thus giving two years of continuous monitoring. Pairs of wet Frisbee dust deposit gauges (based on inverted Frisbees) were located at each site. Undissolved particulate matter from each gauge was weighed and characterized by microscopic examination of individual particles. The first 12-month study revealed a downward gradient in dust deposition rate and cenosphere content with distance from Drax Power Station. The high cenosphere content at Barlow, especially at the eastern end, suggested that there was a significant contribution from coal-fired power stations. In the second year, the overall pattern of dust deposition rate and cenosphere content across the power station belt suggested that power stations were contributing to higher levels. In particular, relatively high levels were again found at Barlow. Wind direction correlations point to the fly-ash tip next to Drax Power Station as being the source of cenospheres arriving at Barlow. It is concluded that in both years the fly-ash tip Drax Power Station was making a significant contribution to higher than expected dust deposition rates at Barlow, particularly its eastern end. Other villages in the area may also have been affected by dust originating from coal-fired power stations.     

Estimates of emissions of SO2, NOx, HCl and NH3 from a densely populated region of the UK

Estimates of emissions of SO2, NOx, HCl and NH3 have been made for a densely populated region of the UK, the North-West of England, using data on power generation, incinerator plant capacity, fuel usage and animal and human population statistics. The spatial distributions of SO2 and NOx emissions are quite different, reflecting their different source strengths. The emissions from motor vehicles make up 52% of the NOx emissions from the North-West of England, whilst those from fossil-fuel-fired power stations make up 20%. The emissions of fossil-fuel-fired power stations make up 58% of SO2 emissions from the North-West. A large fossil-fuel-fired power station is the largest known point source for emissions of SO2, NOx and HCl. The largest contribution to NH3 emissions in the North-West is from cattle. Humans may contribute some NH3 to overall emissions but there is considerable uncertainty as to how much is emitted and what fraction of this is deposited within buildings. The uncertainties in the methodologies used are high-lighted and, where possible, recommendations are made as to how future emissions estimates might be improved. Potential reductions in emissions of SO2, NOx and HCl are discussed under basic scenarios of planned power station closures in the area and the compliance of the electricity generation industry with the European Community Directive on Large Combustion Plants.     

The evolution of particles in the plume from a large coal-fired boiler with flue gas desulfurization

Airborne measurements were made of gaseous and particulate species in the plume of a large coal-fired power plant after flue gas desulfurization (FGD) controls were installed. These measurements were compared with measurements made before the controls were installed. The light scattering and number and volume distributions of plume excess particles were determined by nephelometry and optical particle counting techniques. The plume impact based on optical techniques was much lower than that observed in earlier measurements. Indeed, plume excess volumes as a function of particle size were of the same magnitude as the variability of the background volume distribution. In situ excess plume scattering actually decreased with distance from the source, in contrast to pre-FGD conditions. The upper limit for the dry rate of SO2-to-SO4(2-) conversion was estimated from plume excess volume measurements to be about 4% hr-1. This is slightly greater than the upper limit, 3.5% hr-1, estimated by earlier researchers, but the same as that estimated using the present technique with the earlier data. The cross-plume profile of volume suggests SO2-to-SO4(2-) conversion is highest at the plume edges. The greatest benefit of SO2 reduction on plume excess volume and visibility appears to occur far down-wind of the source.     

Air quality impact of the coal-fired power plants in the northern passageway of the China West-East Power Transmission Project

This paper analyzes the air quality impacts of coal-fired power plants in the northern passageway of the West-East Power Transmission Project in China. A three-layer Lagrangian model called ATMOS, was used to simulate the spatial distribution of incremental sulfur dioxide (SO2) and coarse particulate matter (PM10) concentrations under different emission control scenarios. In the year 2005, the emissions from planned power plants mainly affected the air quality of Shanxi, Shaanxi, the common boundary of Inner Mongolia and Shanxi, and the area around the boundary between Inner Mongolia and Ningxia. In these areas, the annually averaged incremental SO2 and PM10 concentrations exceed 2 and 2.5 microg/m3, respectively. The maximum increases of the annually averaged SO2 and PM10 concentrations are 8.3 and 7.2 microg/m3, respectively, which occur around Hancheng city, near the boundary of the Shaanxi and Shanxi provinces. After integrated control measures are considered, the maximum increases of annually averaged SO2 and PM10 concentrations fall to 4.9 and 4 microg/m3, respectively. In the year 2010, the areas affected by planned power plants are mainly North Shaanxi, North Ningxia, and Northwest Shanxi. The maximum increases of the annually averaged SO2 and PM10, concentrations are, respectively, 6.3 and 5.6 microg/m3, occurring in Northwest Shanxi, which decline to 4.4 and 4.1 microg/m3 after the control measures are implemented. The results showed that the proposed power plants mainly affect the air quality of the region where the power plants are built, with little impact on East China where the electricity will be used. The influences of planned power plants on air quality will be decreased greatly by implementing integrated control measures.     

Remote monitoring of air pollutant emissions from point sources by a mobile lidar/sodar system

This paper describes remote monitoring of air pollutant emissions by a mobile lidar (light detection and ranging)/ sodar (sound detection and ranging) system. First, measurements are carried out in the flue gas plume of a public power plant. The investigations focus mainly on quantifying SO2 emissions, but the uncertainties of such measurements are also emphasized. Furthermore, an example providing valuable data sets for the development and validation of plume dispersion models is outlined with measurements of the dilution of SO2 along the plume axis. Series of repeated determinations of SO2 emissions show a large variation in the obtained flux values, with moderate margins of error. Incomplete recording of the plume within the individual lidar scans, induced by strong looping movements of the flue gas plume, predominantly causes the variations of flux values. Therefore, the highest flux values determined are considered to be the most exact. This is verified by a comparison of measured fluxes with in situ measurements made by the plant operators. The results further indicate that lidar measurements illustrate the location and dimension of aerosol plumes better than the location and dimension of the plumes of gaseous compounds. The wind direction affecting the plume at any moment can be determined faster by lidar than by sodar because the latter requires much longer time intervals of signal averaging. Measurements show higher concentrations of SO2 compared with results from a Gaussian plume model for periods of less than 5 min after dispersion. The findings emphasize the suitability of remote sensing for detecting emissions and for investigating the propagation and dilution of air pollutant plumes.     

Site Redundancy in Urban Ozone Monitoring

This article describes two statistical methods that enable air pollution control agencies to assess the effectiveness of the spatial distribution of current stationary ozone monitoring networks by providing measures of site redundancy. These methods analyze site redundancy by determining the degree to which ozone measurements at one site can be successfully predicted from data collected at other monitoring sites. The first method, the similarity (SIM) measure, calculates redundancy based on the percentage of common operational days during which two monitoring stations report similar daily maximum ozone concentrations. The second method, a modeling technique, relates site redundancy in ozone measurement to an R-squared statistic from an autoregressive model. The model uses meteorological components recorded at a central location and ozone concentrations reported by the network’s other monitoring stations. Both techniques can assist in effective allocation of limited monitoring resources and offer a statistical approach to ambient air monitoring network design. The techniques are applied to data collected at six ozone monitoring stations in Harris County, Texas, during an eight-year period in the 1980s. The methods identified two sites in the six-site network that exhibit a high degree of redundancy.     

Seasonal aerosol sulfate trends for selected regions of the United States

Site and regional trends in seasonally averaged particle SO4(2-) concentrations were examined for a large portion of the United States using data collected by the CASTNet air monitoring network. Trends were analyzed for overlapping periods of 1988-1999 and 1992-1999. The largest absolute SO4(2-) decreases--approximately -0.4 microg/m3/yr--between 1988 and 1999 occurred in summer for sites in the Ohio River Valley and areas to the east. Generally, the largest SO4(2-) reductions were found for summer, but larger relative reductions often occurred for spring and autumn. Sulfate changes during 1992-1999 were quite different from those found for 1988-1999 and were not entirely consistent with changes in SO2 emissions. In some locations, the 1992-1999 period saw smaller declines in SO4(2-), while in other places seasonal SO4(2-) actually increased. Increases were mostly confined to summer and autumn across the southern and southwestern states. Multivariate analysis of ambient sulfur levels, by region, versus SO2 emissions reveals that annual emissions are associated with more than 80% of the variance in seasonal sulfur (SO2 and SO4(2-)) in more than three-quarters of the cases examined. The weakest associations were found for the southeastern United States.     

Air pollution modeling at road sides using the operational street pollution model--a case study in Hanoi, Vietnam

In many metropolitan areas, traffic is the main source of air pollution. The high concentrations of pollutants in streets have the potential to affect human health. Therefore, estimation of air pollution at the street level is required for health impact assessment. This task has been carried out in many developed countries by a combination of air quality measurements and modeling. This study focuses on how to apply a dispersion model to cities in the developing world, where model input data and data from air quality monitoring stations are limited or of varying quality. This research uses the operational street pollution model (OSPM) developed by the National Environmental Research Institute in Denmark for a case study in Hanoi, the capital of Vietnam. OSPM predictions from five streets were evaluated against air pollution measurements of nitrogen oxides (NO(x)), sulfur dioxide (SO2), carbon monoxide (CO), and benzene (BNZ) that were available from previous studies. Hourly measurements and passive sample measurements collected over 3-week periods were compared with model outputs, applying emission factors from previous studies. In addition, so-called "backward calculations" were performed to adapt the emission factors for Hanoi conditions. The average fleet emission factors estimated can be used for emission calculations at other streets in Hanoi and in other locations in Southeast Asia with similar vehicle types. This study also emphasizes the need to further eliminate uncertainties in input data for the street-scale air pollution modeling in Vietnam, namely by providing reliable emission factors and hourly air pollution measurements of high quality.     

模糊物元识别模型在巢湖水体富营养化评价中的应用研究

选取TN、TP、Chl-a、COD、BOD5、DO和SD等7项指标,应用模糊物元识别模型对2000~2007年巢湖的12个水质监测点的富营养化等级进行了模糊识别。通过与巢湖同期水质浓度变化及其分布区域进行对比分析,验证了模糊物元识别模型在巢湖水体富营养化评价中的适用性。巢湖富营养化评价结果表明,2000~2007年富营养化呈逐年加重的趋势,据采样点模糊物元计算结果得知西巢湖(1#~6#)的富营养化状况比东巢湖(7#~12#)更严重,西巢湖贴近度最高值为0.9974,接近极富营养状态,而东巢湖的最高值仅为0.5866。从年际变化上看,2000~2007年东巢湖富营养化状况变化不大,营养状态级处在较低的水平,而西巢湖的富营养状况变化则较大,营养状态级则处在较高水平。     

Foliar sulphur species in pine: a new indicator of a forest ecosystem under air pollution stress

An eleven-year foliar sulphur (S) monitoring program was carried out from 1976 to 1986 near a sulphur recovery-gas plant in west-central Alberta, Canada, as part of a case study designed to determine the effects of chronic, low concentration sulphur gas emissions on the forest ecosystem surrounding the gas plant. Measurements of both foliar total sulphur (ST) and foliar inorganic sulphur (SO4-S) concentration in lodgepole x jack pine trees at the end of each of the 11 growing seasons were taken to provide an indication of S loading of the forest from industrial sulphur emissions. To measure the state of the forest ecosystem, foliar ST was separated into foliar accumulated sulphur (inorganic sulphur or SO4-S) and foliar assimilated sulphur (organic sulphur or S0) and the ratio of SO4-S/S0 taken. Foliar S0 was calculated as the difference between foliar ST and foliar SO4-S. The median SO4-S/S0 ratio, with all three years of needles considered, varied from 0.29 at a reference location (AV) to 0.88 at the location with the highest stress (AI). The corresponding mean values ranged from 0.3 at the reference location to 2.2 at the location of highest stress. The mean seasonal photosynthetic rate of current year's foliage of the pine trees and soil pH were reduced at a stressed location (AI) compared to the reference location (AV), between 1976 and 1981. Over this same time period the mean foliar SO4-S/S0 ratio increased from 0.4 +/- 0.1 to 1.0 +/- 0.3 at the stressed location (AI) and remained nearly the same at the reference location (AV) at 0.3 +/- 0.1. This research suggests that the foliar SO4-S/S0 ratio is a useful indicator of the state of forest ecosystems under S air pollution stress. It is concluded that foliar S separated into various fractions has potential as an early warning environmental management tool.     

Air quality impacts of distributed energy resources implemented in the northeastern United States

Emissions from the potential installation of distributed energy resources (DER) in the place of current utility-scale power generators have been introduced into an emissions inventory of the northeastern United States. A methodology for predicting future market penetration of DER that considers economics and emission factors was used to estimate the most likely implementation of DER. The methodology results in spatially and temporally resolved emission profiles of criteria pollutants that are subsequently introduced into a detailed atmospheric chemistry and transport model of the region. The DER technology determined by the methodology includes 62% reciprocating engines, 34% gas turbines, and 4% fuel cells and other emerging technologies. The introduction of DER leads to retirement of 2625 MW of existing power plants for which emissions are removed from the inventory. The air quality model predicts maximum differences in air pollutant concentrations that are located downwind from the central power plants that were removed from the domain. Maximum decreases in hourly peak ozone concentrations due to DER use are 10 ppb and are located over the state of New Jersey. Maximum decreases in 24-hr average fine particulate matter (PM2.5) concentrations reach 3 microg/m3 and are located off the coast of New Jersey and New York. The main contribution to decreased PM2.5 is the reduction of sulfate levels due to significant reductions in direct emissions of sulfur oxides (SO(x)) from the DER compared with the central power plants removed. The scenario presented here represents an accelerated DER penetration case with aggressive emission reductions due to removal of highly emitting power plants. Such scenario provides an upper bound for air quality benefits of DER implementation scenarios.