Particulate Matter Source Apportionment Technology Research Articles

Development and Application of the SmartAQ High-Resolution Air Quality and Source Apportionment Forecasting System for European Urban Areas

Air pollution forecasting systems are useful tools for the reduction in human health risks and the eventual improvement of atmospheric quality on regional or urban scales. The SmartAQ (Smart Air Quality) forecasting system combines state-of-the-art meteorological and chemical transport models to provide detailed air pollutant concentration predictions at a resolution of 1 × 1 km2 for the urban area of interest for the next few days. The Weather Research and Forecasting (WRF) mesoscale numerical weather prediction model is used to produce meteorological fields and the PMCAMx (Particulate Matter Comprehensive Air quality Model with extensions) chemical transport model for the simulation of air pollution. SmartAQ operates automatically in real time and provides, in its current configuration, a three-day forecast of the concentration of tens of gas-phase air pollutants (NOx, SO2, CO, O3, volatile organic compounds, etc.), the complete aerosol size/composition distribution, and the source contributions for all primary and secondary pollutants. The system simulates the regional air quality in Europe at medium spatial resolution and can focus, using high resolution, on any urban area of the continent. The city of Patras in Greece is used for the first SmartAQ application, taking advantage of the available Patras’ dense low-cost sensor network for PM2.5 (particles smaller than 2.5 μm) concentration measurements. Advantages of SmartAQ include (a) a high horizontal spatial resolution of 1 × 1 km2 for the simulated urban area; (b) advanced treatment of the organic aerosol volatility and chemistry; (c) use of an updated emission inventory that includes not only the traditional sources (industry, transport, agriculture, etc.), but also biomass burning from domestic heating and cooking; (d) forecasting of not only the pollutant concentrations, but also of the sources contributions for each one of them using the Particulate matter Source Apportionment Technology (PSAT) algorithm.

Comparative Analysis of PM2.5 and O3 Source in Beijing Using a Chemical Transport Model

For many years, Beijing has suffered from severe air pollution. At present, fine particulate matter (PM2.5) pollution in the winter and ozone (O3) pollution in the summer constitute serious environmental problems. In this study, the combination of a comprehensive air quality model with particulate matter source apportionment technology (CAMx-PAST) and monitoring data was used for the high-spatial resolution source apportionment of secondary inorganic components (SNA: SO42−, NO3−, and NH4+) in PM2.5; their corresponding precursor gases (SO2, NO2, and NH3); and O3 in the winter and summer over Beijing. Emissions from residents, industry, traffic, agriculture, and power accounted for 54%, 25%, 14%, 5%, and 2% of PM2.5 in the winter, respectively. In the summer, the emissions from industry, traffic, residents, agriculture, and power accounted for 42%, 24%, 20%, 10%, and 4% of PM2.5, respectively. The monthly transport ratio of PM2.5 was 27% and 46% in the winter and summer, respectively. The regional transport of residential and industrial emissions accounted for the highest proportion of PM2.5. The regional transport of emissions had a significant effect on the SO42− and NO3− concentrations, whereas SO2 and NO2 pollution were mainly affected by local emissions, and NH4+ and NH3 were mainly attributed to agricultural emissions. Industrial and traffic sources were two major emission sectors that contributed to O3 pollution in Beijing. The monthly transport ratios of O3 were 31% and 65% in the winter and summer, respectively. The high-spatial resolution regional source apportionment results showed that emissions from Langfang, Baoding, and Tangshan had the greatest impact on Beijing’s air pollution. This work’s methods and results will provide scientific guidance to support the government in its decision-making processes to manage the PM2.5 and O3 pollution issues.

The impacts of meteorology on source contributions of air pollution in winter in Beijing, 2015–2017 changes

In this study, a combination of monitoring data and the CAMx-PAST (comprehensive air quality model with particulate matter source apportionment technology) model was used to evaluate the meteorological effect of changes in the source apportionment results of PM2.5, SO42−, NO3−, NH4+ and their precursors (SO2, NO2, and NH3) in Beijing in January 2015, January 2016 and January 2017. The meteorological conditions in 2017 were more favorable than those in the other two years in terms of air pollution accumulation and formation, with a monthly high relative humidity of 72% and a low wind speed of 2.06 m s−1. PM2.5 pollution was more serious in 2017 than in other years, with an average concentration of 116 μg m−3. Both simulation and observation data demonstrated that nitrate accounted for the largest proportion of the total secondary inorganic aerosol (SO42−, NO3− and NH4+). In the winter in Beijing, residential areas were a major source of pollution and contributed to 51%~54% of the total pollution. Meteorology has a great influence on the regional transportation of pollution. The transport ratios of PM2.5 were 22%, 26% and 33% in 2015, 2016 and 2017, respectively. Regional transport has a significant effect on both SO42− and NO3− concentration. However, primary pollution is mainly affected by local pollution sources. Local residential emissions have the greatest impact on SO2, contributing 85%, 82% and 83% of the total concentration. The local emissions contributed 88%, 84% and 84% of the total NO2 concentration.

Impact of Chinese air pollutants on a record-breaking PMs episode in the Republic of Korea for 11–15 January 2019

A record-breaking episode of highly concentrated particulate matter (PM) with diameters ≤ 2.5 μm (PM2.5) and ≤10 μm (PM10) occurred in the Republic of Korea during the period January 11–15, 2019: the hourly PM2.5 (PM10) in Seoul was 188 μg m−3 (262 μg m−3) on January 14. At the Baengnyeong and Socheongcho stations, located in the Yellow Sea between China and Korea, the hourly PM2.5 concentration reached up to 155 μg m−3 and 119.8 μg m−3, respectively, 16−19-h prior to this episode. This and the fact that the maximum PM10 concentration at Baengnyeong was 199 μg m−3 indicated a westerly transport of air pollutants. Satellite observations and 72-h back trajectory analysis clearly indicate that air pollutants from China flowed into Korea via the westerlies. According to contribution analysis using particulate matter source apportionment technology in the Comprehensive Air-quality Model with extension, air pollutants originating from northeastern China including Hebei and Shandong provinces were largely linked to the present record-breaking high concentration event in Seoul. This study will elucidate the mechanism of transboundary transport of air pollutants and help East Asian countries cooperate on air quality management.

A hybrid modeling framework to estimate pollutant concentrations and exposures in near road environments

Traffic related air pollution is one of the major local sources of pollution challenging most urban populations. Current air quality modeling approaches can estimate the concentrations of air pollutants on either regional or local scales but cannot effectively estimate concentrations from the combination of regional and local sources at both local and regional scales simultaneously. This study describes a hybrid modeling framework, HYCAMR, combining a regional model, CAMx, and a local-scale dispersion model, R-LINE, to estimate concentrations of both primary and secondary species at high temporal (hourly) and spatial (40 m) resolution. HYCAMR utilizes all the chemical and physical processes available in CAMx and the Particulate Matter Source Apportionment Technology (PSAT) tool to estimate concentrations from both onroad and nonroad emission sources. HYCAMR employs R-LINE, to estimate the normalized dispersion of pollutant mass from onroad emission sources, from primary and secondary roads, at high resolution. Applying R-LINE for one day per month using average daily meteorology yields seasonally-resolved spatial dispersion profiles at low computational cost. Combining the R-LINE spatial dispersion profile with CAMx concentration estimates yields an estimate of the combined concentrations for a range of pollutants at high spatial and temporal resolution. In three major cities in Connecticut, HYCAMR shows strong temporal and seasonal variability in NOx, PM2.5, and elemental carbon (EC) concentrations. This study evaluates HYCAMR year 2011 estimates of NO2 and PM2.5 against two sources: satellite-based estimates at coarse resolution and regression model estimates at census block group resolution. In this evaluation, HYCAMR demonstrates improved agreement with the land-use regression modeling and mixed agreement with satellite-based estimates when compared to the regional CAMx estimates.

A Hybrid Modeling Framework to Estimate Traffic-Related Exposure in Three Connecticut Cities

Traffic-related air pollution is one of the major challenges facing urban areas. As traffic-related emissions result in air pollutant concentrations that vary over spatial scales of under 100m, it is challenging to implement models to capture this behavior. In this study, we develop a hybrid modeling framework combining a regional model (CAMx) and a local scale dispersion model (RLINE) to estimate concentrations of both primary and secondary species from roadway emission sources. We use the Particulate Matter Source Apportionment Technology (PSAT) to quantify the concentrations from traffic-related emission sources. We employ RLINE to estimate pollutant distribution profiles for traffic-related emissions for typical diurnal conditions each month at a fine resolution. We use the traffic-related contributions from CAMx-PSAT alongside the profiles from RLINE to distribute the traffic-related contributions spatially and temporally. This allows us to efficiently estimate air pollutant concentrations at fine spatial (40mx40m) and hourly temporal resolution.We conduct a model evaluation of our framework for NO2 in the year 2011 using both satellite data and regression model estimates at census block resolution. We have applied this modeling framework to three cities in Connecticut (Hartford, New Haven, and Windham) and quantified human exposure to NOx, PM2.5, and elemental carbon. We also assess the health risk associated with each species for individuals of different age and genders. Finally, we quantify the environmental inequality based on income and population density. Our approach using a dispersion model is unique as it uses the mass fraction of the total dispersed pollutant at different receptor points and hence is not dependent on extensive roadway emissions data or extensive model runs. This modeling approach overcomes two major challenges facing modeling for traffic-related exposures: double counting emissions and a lack of temporal variability.

Future year ozone source attribution modeling study using CMAQ-ISAM

ABSTRACTTo achieve the current United States National Ambient Air Quality Standards (NAAQS) attainment level for ozone or particulate matter, current photochemical air quality models include tools to determine source apportionment and/or source sensitivity. Previous studies by the authors have used the Ozone and Particulate Matter Source Apportionment Technology and Higher-order Decoupled Direct Method probing tools in CAMx to investigate these source-receptor relationships for ozone. The recently available source apportionment for CMAQ, referred to as the Integrated Source Apportionment Method (ISAM), was used in this study to conduct future year (2030) source attribution modeling. The CMAQ-ISAM ozone source attribution results for selected cities across the U.S. showed boundary conditions were the dominant contributor to the future year highest July maximum daily 8-hour average (MDA8) ozone concentrations. Point sources were generally larger contributors in the eastern U.S. than in the western U.S. The contributions of on-road mobile emissions were around 5 ppb at most of the cities selected for analysis. Off-road mobile source contributions were around 20 ppb or nearly 30%. Since boundary conditions play an important role in future year ozone levels, it is important to characterize future year boundary conditions accurately. The current implementation of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, making it difficult to conduct long-term simulations for large domains. The computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM. If an efficient version of ISAM becomes available, it could be used in long-term ozone and PM2.5 studies. Implications: Ozone source attribution results provide useful information on important emission source contribution categories and provide some initial guidance on future emission reduction strategies. This study explains a new source apportionment technique, CMAQ-ISAM, and compares it to CAMx OSAT. The techniques have similar results: ozone’s highest source contributor is boundary conditions, followed by point sources, then off-road mobile sources. The current version of ISAM in CMAQ 5.0.2 requires significant computing resources for ozone source attribution, while the computing requirements for PM source attribution are even more onerous. CMAQ 5.2 was released after this study was completed, and does not include ISAM.

Source apportionment of PM2.5 pollution in the central six districts of Beijing, China

Fine particulate matter (PM2.5) has become the primary atmospheric pollutant in Beijing in recent years, causing widespread concern in society. Understanding the origin of PM2.5 is essential for developing effective strategies to reduce PM2.5. In this study, we used the Particulate Matter Source Apportionment Technology (PSAT) in Comprehensive Air Quality Model with Extensions (CAMx) to quantify the contributions of different source regions and emission categories to the PM2.5 concentration in the central six districts of Beijing in January, April, July and October, representing four seasons in 2014. The annual contribution ratios from local, suburb and the surrounding regions of Beijing as well as the outside of boundary region were 47.6, 19.3, 11.4, and 21.7%, respectively, showing significant contribution of regional transport to the PM2.5 pollution in the central six districts of Beijing. The emission category apportionment results in the central six districts showed distinct seasonal variations with important contribution of coal combustion in winter but minor contribution in the other seasons, dominant contribution of dust in spring, and dominant contribution of the vehicle related sources in the other seasons. Moreover, the detailed contribution proportion of the five emission categories showed clear spatial variation in the suburbs and the surrounding regions. Based on the sensitivity analysis of local emission reduction, the control of the vehicle related sources was the most efficient mitigation measure for the reduction of PM2.5 during the case study period in autumn, but the efficiency of the local mitigation measures was greatly reduced in the period of heavy PM2.5 pollution.

Primary and secondary particulate matter intake fraction from different height emission sources

This study uses intake fraction, the fraction of emissions that are inhaled, to compare potential particulate matter exposure among different height emission sources. We use the Particulate Matter Source Apportionment Technology (PSAT) in the Comprehensive Air Quality Model with Extensions (CAMx) to estimate intake fraction for primary and secondary particulate matter species from different height emission sources. We develop an approach to quantify intake fraction for both primary and secondary particulate matter species emitted from all types of emission sources in the contiguous United States. To compute intake fraction for secondary particulate matter species, we consider the inhalation of the precursor gas and condensed species based on the common atomic unit between the emitted gas and particulate matter product. Our calculated intake fraction varies from 1.0 to 4.9 per million for primary particulate matter, 0.4 to almost 6.0 per million for secondary species, including inhalation of both particulate matter and the relevant precursor species. Intake fraction is consistently higher in the winter than the summer for all species from all emission heights. The shortest height sources, which include area sources, display intake fractions over an order of magnitude greater than more elevated sources.

Local and regional contributions to fine particulate matter in Beijing during heavy haze episodes.

In order to alleviate extreme haze pollution, understanding the origin of fine particulate matter (PM2.5) is crucial. In this study, we applied Particulate Matter Source Apportionment Technology (PSAT) in CAMx (Comprehensive Air Quality Model with Extensions) to quantify the impacts of emissions from different regions on PM2.5 concentrations in Beijing for haze episodes during January 6-23, 2013. Emission inventory was developed by Tsinghua University. Evolution of local and Regional contributions during local and non-local dominated haze episodes were discussed, separately. In the meanwhile, average contribution of other every city in Jing-Jin-Ji region to PM2.5 concentrations larger than 75μgm-3 in Beijing urban for each range of local contribution percent was analyzed. The results indicate that local emissions contributed 83.6% of PM2.5 at the urban center of Beijing, while regional transport from surrounding cities and parts of Shandong, Henan and Anhui provinces contributed 9.4%; long-range transport contributed the remaining 7.0% mainly from areas >750km away to the south of Beijing during this study period. Compared to non-local-dominated haze episodes, local-dominated heavy haze episodes in Beijing were easily resulted from unfavorable meteorological conditions with much lower PBL and wind velocity. Furthermore, local contribution is more easily to cause a sharp increase or sharp reduction of PM2.5 concentration in central Beijing, reflecting that Beijing local has much stronger potential to form extremely heavy haze episodes. The results indicated that controlling local emissions is a much more important measure to alleviate the extreme haze episodes in Beijing, like that on the night of Jan 12, 2013. Furthermore, emission control in Jing-Jin-Ji region, especially in Tangshan, Tianjin, Baoding, Langfang, Shijiazhuang and Cangzhou, as well as Henan and Shandong province, are important to reduce the PM2.5 concentrations and the occurrence of haze episodes in Beijing.

Spatially resolved intake fraction estimates for primary and secondary particulate matter in the United States

This study uses intake fraction, the fraction of emissions that are inhaled from a given source, to quantify how emissions from different regions proportionally contribute to human exposure to both primary and secondary particulate matter species. The intake fraction for secondary species is defined using the common atomic constituents between precursor species and products, allowing estimates to include both primary and secondary species. The Particulate Matter Source Apportionment Technology (PSAT) in the Comprehensive Air Quality Model with Extensions (CAMx) regional air quality model is used to calculate the intake fraction for twenty-five source regions throughout the contiguous United States over four seasons. The calculations use spatially explicit emissions and population density to more accurately capture the variation in intake fraction between regions. The spatially explicit emissions allow for the calculation of spatial trends and variations within the intake fraction. More specifically it allows for the calculation of the amount of intake that occurs within a given distance of the emissions source or source region. Based on the results sulfate inhalation occurs over larger distances than other particulate matter species. For most regions, a substantial fraction (>75%) of the inhalation occurs within 50 km for all seasons, demonstrating that efforts to reduce emissions will have the largest health impact on the local community. Furthermore the distance over which 75% of the inhalation occurs increases by 20% for all species during the winter and a larger percentage of pollutants emitted during the winter are inhaled relative to pollutants emitted during other seasons. This demonstrates that emission reductions during the winter will have a greater impact on health than reductions during other seasons.

Long range transport of nitrate in the low atmosphere over Northeast Asia

In this study, the source-relationships were established for surface nitrate concentrations in Northeast Asia, using the Particulate Matter Source Apportionment Technology (PSAT) in the CAMx (a regional chemical transport model). Both of the local emissions and Chinese emissions were important among the sources of the particle nitrate in Japan and South Korea, accounting for 27.9–62.9% and 22.9–50.5% respectively. The local contributions of nitrate were 4–20% higher than the figures of sulfate, and this was caused by the different chemical processes and emissions involved. The seasonal variation of the nitrate concentration in East Asia led to different amounts of nitrate being attributed to long-range transport, and was higher in winter (>53%) than in summer (<41%). The interactions between ammonia/ammonium, sulfate and nitrate were also discussed. The distribution of degree of sulfate neutralization (DSN) and the adjusted gas ratio (AdjGR) in East Asia suggested that the particle nitrate concentration was most sensitive to changes in the total ammonia in most parts of Japan and some regions of South Korea. And that was different in most parts of East Asia, where there were large quantities of ammonia. The ammonia from local emissions were most likely responsible for some particulate nitrate being transformed from trans-boundary gaseous nitric, which signified that local emissions of ammonia increased the contribution of China to the nitrate concentrations in Japan and South Korea.

Estimation of the local and long-range contributions to particulate matter levels using continuous measurements in a single urban background site

The Particulate Matter Source Apportionment Technology (PSAT) algorithm is used together with PMCAMx, a regional chemical transport model, to develop a simple observation-based method (OBM) for the estimation of local and regional contributions of sources of primary and secondary pollutants in urban areas. We test the hypothesis that the minimum of the diurnal average concentration profile of the pollutant is a good estimate of the average contribution of long range transport levels. We use PMCAMx to generate “pseudo-observations” for four different European cities (Paris, London, Milan, and Dusseldorf) and PSAT to estimate the corresponding “true” local and regional contributions. The predictions of the proposed OBM are compared to the “true” values for different definitions of the source area.During winter, the estimates by the OBM for the local contributions to the concentrations of total PM2.5, primary pollutants, and sulfate are within 25% of the “true” contributions of the urban area sources. For secondary organic aerosol the OBM overestimates the importance of the local sources and it actually estimates the contributions of sources within 200 km from the receptor.During summer for primary pollutants and cities with low nearby emissions (ratio of emissions in an area extending 100 km from the city over local emissions lower than 10) the OBM estimates correspond to the city emissions within 25% or so. For cities with relatively high nearby emissions the OBM estimates correspond to emissions within 100 km from the receptor. For secondary PM2.5 components like sulfate and secondary organic aerosol the OBM's estimates correspond to sources within 200 km from the receptor. Finally, for total PM2.5 the OBM provides approximately the contribution of city emissions during the winter and the contribution of sources within 100 km from the receptor during the summer.

Source apportionment of fine particles and its chemical components over the Yangtze River Delta, China during a heavy haze pollution episode

Abstract An extremely high PM 2.5 pollution episode occurred over the eastern China in January 2013. In this paper, the particulate matter source apportionment technology (PSAT) method coupled within the Comprehensive air quality model with extensions (CAMx) is applied to study the source contributions to PM 2.5 and its major components at six receptors (Urban Shanghai, Chongming, Dianshan Lake, Urban Suzhou, Hangzhou and Zhoushan) in the Yangtze River Delta (YRD) region. Contributions from 4 source areas (including Shanghai, South Jiangsu, North Zhejiang and Super-region) and 9 emission sectors (including power plants, industrial boilers and kilns, industrial processing, mobile source, residential, volatile emissions, dust, agriculture and biogenic emissions) to PM 2.5 and its major components (sulfate, nitrate, ammonia, organic carbon and elemental carbon) at the six receptors in the YRD region are quantified. Results show that accumulation of local pollution was the largest contributor during this air pollution episode in urban Shanghai (55%) and Suzhou (46%), followed by long-range transport (37% contribution to Shanghai and 44% to Suzhou). Super-regional emissions play an important role in PM 2.5 formation at Hangzhou (48%) and Zhoushan site (68%). Among the emission sectors contributing to the high pollution episode, the major source categories include industrial processing (with contributions ranging between 12.7 and 38.7% at different receptors), combustion source (21.7–37.3%), mobile source (7.5–17.7%) and fugitive dust (8.4–27.3%). Agricultural contribution is also very significant at Zhoushan site (24.5%). In terms of the PM 2.5 major components, it is found that industrial boilers and kilns are the major source contributor to sulfate and nitrate. Volatile emission source and agriculture are the major contributors to ammonia; transport is the largest contributor to elemental carbon. Industrial processing, volatile emissions and mobile source are the most significant contributors to organic carbon. Results show that the Yangtze River Delta region should focus on the joint pollution control of industrial processing, combustion emissions, mobile source emissions, and fugitive dust. Regional transport of air pollution among the cities are prominent, and the implementation of regional joint prevention and control of air pollution will help to alleviate fine particulate matter concentrations under heavy pollution case significantly.

Contributions of local and regional sources to fine PM in the megacity of Paris

Abstract. The particulate matter source apportionment technology (PSAT) is used together with PMCAMx, a regional chemical transport model, to estimate how local emissions and pollutant transport affect primary and secondary particulate matter mass concentration levels in Paris. During the summer and the winter periods examined, only 13% of the PM2.5 is predicted to be due to local Paris emissions, with 36% coming from mid-range (50–500 km from the center of the Paris) sources and 51% from long range transport (more than 500 km from Paris). The local emissions contribution to simulated elemental carbon (EC) is significant, with almost 60% of the EC originating from local sources during both summer and winter. Approximately 50% of the simulated fresh primary organic aerosol (POA) originated from local sources and another 45% from areas 100–500 km from the receptor region during summer. Regional sources dominated the secondary PM components. During summer more than 70% of the simulated sulfate originated from SO2 emitted more than 500 km away from the center of the Paris. Also more than 45% of secondary organic aerosol (SOA) was due to the oxidation of VOC precursors that were emitted 100–500 km from the center of the Paris. The model simulates more contribution from long range secondary PM sources during winter because the timescale for its production is longer due to the slower photochemical activity. PSAT results for contributions of local and regional sources were compared with observation-based estimates from field campaigns that took place during the MEGAPOLI project. PSAT simulations are in general consistent (within 20%) with these estimates for OA and sulfate. The only exception is that PSAT simulates higher local EC contribution during the summer compared to that estimated from observations.

Use of a MM5–CAMx–PSAT Modeling System to Study SO2 Source Apportionment in the Beijing Metropolitan Region

A coupled MM5–CAMx air quality modeling system was used to simulate SO2 concentrations in Beijing, China during the heating season. Particulate matter source apportionment technology was employed to investigate the apportionment of SO2 sources in the study area. Comprehensive analysis of the industry and region revealed that the most important SO2 contributors were publicly and privately supplied heating emission sources and other industry emission sources from the urban areas of Beijing, with 66.1 % of the emission source contribution ratio. Four SO2 emission reduction scenarios based on our SO2 source apportionment research were established to assess the potential for improving the SO2 air quality in Beijing during the heating season. By weighing the desired SO2 improvement, the availability of technology, and economic considerations, a suitable SO2 reduction plan was able to be recommended for Beijing city.

Contribution of long range transport to local fine particulate matter concerns

Abstract We have utilized the Particulate Matter Source Apportionment Technology (PSAT) in PMCAMx (a regional chemical transport model) to quantify the contributions from local emissions and short range (under 100 km), mid range (100–550 km) and long range (over 550 km) pollutant transport to both primary and secondary particulate matter concentrations using the Eastern United States as a test case. We have studied these contributions for two urban (Pittsburgh, Pennsylvania and Atlanta, Georgia) and one rural area (Great Smoky Mountains National Park) during all seasons. The local emissions impacts to elemental carbon (EC) in major urban areas were found to be substantial with approximately 50% of the EC coming from local sources and 80% emitted within 200 km of the receptor. The local sources are even more important during the night contributing around 60% of the EC and then dropping to around 40% during the early afternoon. The EC in the rural Great Smoky Mountains was mainly the result of sources 100–550 km away. The seasonal variation of the EC source area contributions is small. There was also little difference between high and low EC concentration days. The contributions to secondary aerosol species were found to be more regional with more than 50% of the sulfate and secondary organic aerosol (SOA) originating from SO2 and VOC sources that were more than 200 km away from the receptor. The importance of sources further away increased during the winter because of the lower photochemical activity. While mid range transport dominated in the summer the sulfate and SOA levels in all areas, long range transport became the most important sulfate and SOA source during the winter in the colder Northeastern US and of sulfate in the warmer South.

Determination of the age distribution of primary and secondary aerosol species using a chemical transport model

A computationally efficient scheme to allow tracking of aerosol species age as a function of space and time within a three‐dimensional chemical transport model (CTM) has been developed. The aerosol age distribution is calculated by utilizing the Particulate Matter Source Apportionment Technology (PSAT) algorithm which allows the calculation of different source contributions to both primary and secondary particulate matter concentrations in the modeling domain. As an example, the aerosol age in the eastern United States, including both primary and secondary species, is examined using the regional CTM PMCAMx. The average calculated ages are on the order of a few days for particulate matter near the ground but are highly variable in space and time. Primary aerosol species had average ages of approximately 24 h over this polluted continental region while the average ages for secondary species were 48–72 h near the surface. As expected, the average age of all aerosol components increases vertically in the atmosphere. Age increases rapidly away from the sources of aerosol and its precursors, and for nonvolatile species it increases with particle size.