Spatial variability of pollution source contributions during two (2012-2013 and 2018-2019) sampling campaigns at ten sites in Los Angeles basin

This study assessed the spatial variability of PM2.5 source contributions across ten sites located in the South Coast Air Basin, California. Eight pollution sources and their contributions were obtained using positive matrix factorization (PMF) from the PM2.5 compositional data collected during the two sampling campaigns (2012/13 and 2018/19) of the Multiple Air Toxics Exposure Study (MATES). The identified sources were "gasoline vehicles", "aged sea salt", "biomass burning", "secondary nitrate", "secondary sulfate", "diesel vehicles", "soil/road dust" and "OP-rich". Among them, "gasoline vehicle" was the largest contributor to the PM2.5 mass. The spatial distributions of source contributions to PM2.5 at the sites were characterized by the Pearson correlation coefficients as well as coefficients of determination and divergence. The highest spatial variability was found for the contributions from the "OP-rich" source in both MATES campaigns suggesting varying influences of the wildfires in the Los Angeles Basin. Alternatively, the smallest spatial variabilities were observed for the contributions of the "secondary sulfate" and "aged sea salt" sources resolved for the MATES campaign in 2012/13. The "soil/road dust" contributions of the sites from the 2018/19 campaign were also highly correlated. Compared to the other sites, the source contribution patterns observed for Inland Valley and Rubidoux were the most diverse from the others likely due to their remote locations from the other sites, the major urban area, and the Pacific Ocean.

High loadings of carbonaceous aerosols from wood smoke in the atmosphere of Beijing from 2015 to 2017: Implications for energy transition policy

Recently, biomass has been regarded as a promising option for solid energy in China, which is promoted in the residential sector and firing power plants. We collected 200 PM2.5 samples (particulate matter with a aerodynamic diameter smaller than 2.5 μm) at multi-sites across Beijing from three individual sampling cases from 2015 to 2017. The levels of OC, OC fractions, EC, EC fractions, as well as K+ were measured. Then, we adopted the Positive Matrix Factorization 5.0 to apportion the sources of carbonaceous aerosols. The source apportionment results were compared with the estimates of source contribution using the bottom-up technical method with the latest emission inventories after the Action Plan was put into effect in 2013. Our results demonstrate that high pollution of carbonaceous aerosols originated from wood smoking based on the receptor modeling and bottom-up technical method in Beijing from 2015 to 2017. Future energy transition policy should focus on the technologies and regulations for reducing emissions from renewable biomass fuel combustion. This study highlights the importance of regulations that address emissions controls on fuels replacing coal combustion to meet the needs to mitigate air pollution from primary energy use.

Common and distinct pollution sources identified from ambient PM2.5 concentrations in two sites of Los Angeles Basin from 2005 to 2019

The effects of air quality control policies implemented in California from 2005 to 2019 targeting sources contributing to ambient PM2.5 concentrations, were assessed at two sampling sites in the Los Angeles Basin (N. Main Street and Rubidoux). The spatial and temporal variations of pollution source contributions obtained from dispersion-normalized positive matrix factorization, (DN-PMF) were interpreted with respect to site specific locations. Secondary nitrate and secondary sulfate were the major contributors to the ambient PM2.5 mass concentrations at both sites with substantial concentration decreases after 2008 that were likely due to the implementation of California specific programs including stricter NOx emissions control on motor vehicles. Biomass burning emissions also decreased over the study period at both sampling sites except for one event in December 2005 when strong winter storms and multiple floods led to unusually low atmospheric temperatures and likely increased residential wood burning. The large number of wildfires, trans-Pacific transport of mineral dust and regional dust transported by strong Santa Ana winds and agriculturally generated dust in Rubidoux contributed to poor air quality. Severe storms and devastating wildfires were also linked to the elevated pyrolyzed organic carbon (OP-rich) concentrations. The two distinct region-specific sources, describing fuel combustion in LA, were "residual oil" and "traffic", while separate "gasoline" and "diesel" vehicles sources were identified in Rubidoux. California emissions standards program which required replacement of conventional cars with electric or hybrid vehicles and standards for gasoline and diesel fuels, led to lower "traffic" contributions. Gasoline vehicle emissions after 2017 in Rubidoux also decreased. "Diesel" concentrations declined between 2007 and 2011 because of the recession from late 2007 to early 2009 and the Federal Heavy-Duty Diesel Rule.

Variabilities of δ13C and carbonaceous components in ambient PM2.5 in Northeast India: Insights into sources and atmospheric processes

A year-long sampling campaign of ambient PM_2.5 (particulate matter with aerodynamic diameter ≤2.5 mm) at a regional station in the North-Eastern Region (NER) of India was performed to understand the sources and formation of carbonaceous aerosols. Mass concentration, carbon fractions (organic and elemental carbon), and stable carbon isotope ratio (δ¹³C) of PM_2.5 were measured and studied along with cluster analysis and Potential Source Contribution Function (PSCF) modelling. PM_2.5 mass concentration was observed to be highest during winter and post-monsoon seasons when the meteorological conditions were relatively stable compared to other seasons. Organic carbon (OC) concentration was more than two times higher in the post-monsoon and winter seasons than in the pre-monsoon and monsoon seasons. Air mass back trajectory cluster analysis showed the dominance of local and regional air masses during winter and post-monsoon periods. In contrast, long-range transported air masses influenced the background site in pre-monsoon and monsoon. Air mass data and PSCF analysis indicated that aerosols during winter and post-monsoon are dominated by freshly generated emissions from local sources along with the influence from regional transport of polluted aerosols. On the contrary, the long-range transported air masses containing aged aerosols were dominant during pre-monsoon. No significant variability was observed in the range of δ¹³C values (-28.2‰ to -26.4‰) during the sampled seasons. The δ¹³C of aerosols indicates major sources to be combustion of biomass/biofuels (C3 plant origin), biogenic aerosols, and secondary aerosols. The δ¹³C variability and cluster/PSCF modelling suggest that aged aerosols (along with enhanced photo-oxidation derived secondary aerosols) influenced the final δ¹³C during the pre-monsoon. On the other hand, lower δ¹³C in winter and post-monsoon is attributed to the freshly emitted aerosols from biomass/biofuels.

Seasonal source analysis of nitrogen and carbon aerosols of PM2.5 in typical cities of Zhejiang, China

Fine particulate matter (PM_2.5) significantly impacts global air quality and human health due to its smaller particle size and larger specific surface area. Nitrogen and carbon aerosols, as the main components of PM_2.5, play key roles in air pollution. This study identified the sources and seasonal variation of nitrogen and carbon aerosols in PM_2.5 in typical cities of Zhejiang. The annual average PM_2.5 concentrations of Hangzhou (HZ), Ningbo (NB), and Huzhou (HUZ) were 39.8 ± 19.1 μg m^-‍3, 40.0 ± 21.5 μg m^-3, and 50.1 ± 22.6 μg m^-3, respectively, which exceeded the Chinese air quality limit of 35.0 μg m^-3. The results showed that the concentrations of nitrogen aerosols (NO₃^- and NH₄⁺) in water-soluble inorganic ions were higher at 9.6 ± 4.6 μg m^-3, 9.0 ± 4.5 μg m^-3 and 11.5 ± 5.4 μg m^-3 in HZ, NB and HUZ, respectively, especially in winter, accounting for over 60% of the total. The annual average δ¹⁵N values of PM_2.5 were 6.2 ± 1.9‰, 6.4 ± 2.2‰ and 6.7 ± 1.9‰ in HZ, NB and HZ, respectively; the δ¹⁵N values in winter were relatively low. A Bayesian isotopic mixing model was employed to analyse the sources of nitrogen aerosols in winter; the results showed that nitrogen concentration was mainly affected by NH₃ and NO_X emitted by motor vehicle exhaust, coal combustion, biomass combustion, biogenic soil emissions, animal wastes and ocean evaporation (NB). In addition, the carbon component analysis of PM_2.5 showed that the annual average mass concentration of TC accounted for 18.7%, 16.4% and 20.1% of PM_2.5 in HZ, HUZ and NB, respectively. The same isotope model was used to analyse the sources of carbon aerosols; the results showed that carbon aerosols were mainly affected by the sources of motor vehicle exhaust, coal combustion, biomass combustion and dust. In the PM_2.5 in Zhejiang, the most contributory sources of nitrogenous aerosols and carbon aerosols were motor vehicle exhaust sources.

Changing Emissions Results in Changed PM2.5 Composition and Health Impacts

In the period of 2005 to 2016, multiple air pollution control regulations have entered into effect in the United States at both the Federal and state level. In addition, economic changes have also occurred primarily in the electricity generation sector that substantially changed the emissions from this sector. This combination of policy implementations and economics has led to substantial reductions in PM2.5, its major constituents, and source specific PM2.5 concentrations across the New York State, particularly those of sulfate, nitrate, and primary organic carbon. However, secondary organic carbon and spark-ignition vehicular emission contributions have increased. Related studies of changes in health outcomes, the excess rates of emergency department visits and hospitalizations for a variety of cardiovascular and respiratory diseases and respiratory infections have increased per unit mass of PM2.5. It appears that the increased toxicity per unit mass was due to the reduction in low toxicity constituents such that the remaining mass had greater impacts on public health.

Size-resolved source apportionment of particulate matter from a megacity in northern China based on one-year measurement of inorganic and organic components

This research apportioned size-resolved particulate matter (PM) contributions in a megacity in northern China based on a full year of measurements of both inorganic and organic markers. Ions, elements, carbon fractions, n-alkanes, polycyclic aromatic hydrocarbons (PAHs), hopanes and steranes in 9 p.m. size fractions were analyzed. High molecular weight PAHs concentrated in fine PM, while most other organic compounds showed two peaks. Both two-way and three-way receptor models were used for source apportionment of PM in different size ranges. The three-way receptor model gave a clearer separation of factors than the two-way model, because it uses a combination of chemical composition and size distributions, so that factors with similar composition but distinct size distributions (like more mature and less mature coal combustion) can be resolved. The three-way model resolved six primary and three secondary factors. Gasoline vehicles and coal and biomass combustion, nitrate and high relative humidity related secondary aerosol, and resuspended dust and diesel vehicles (exhaust and non-exhaust) are the top two contributors to pseudo-ultrafine (<0.43 μm), fine (0.43-2.1 μm) and coarse mode (>2.1 μm) PM, respectively. Mass concentration of PM from coal and biomass combustion, industrial emissions, and diesel vehicle sources showed a bimodal size distribution, but gasoline vehicles and resuspended dust exhibited a peak in the fine and coarse mode, separately. Mass concentration of sulphate, nitrate and secondary organic aerosol exhibited a bimodal distribution and were correlated with temperature, indicating strong photochemical processing and repartitioning. High relative humidity related secondary aerosol was strongly associated with size shifts of PM, NO₃^- and SO₄^2- from the usual 0.43-0.65 μm to 1.1-2.1 μm. Our results demonstrated the dominance of primary combustion sources in the <0.43 μm particle mass, in contrast to that of secondary aerosol in fine particle mass, and dust in coarse particle mass in the Northern China megacity.

Mass Absorption Efficiency of Black Carbon from Residential Solid Fuel Combustion and Its Association with Carbonaceous Fractions

Black carbon (BC) emissions, derived primarily from incomplete fuel combustion, significantly affect the global and regional climate. Mass absorption efficiency (MAE) is one important parameter in evaluating the climate impacts of BC. Here, values and variabilities in the MAE of BC (MAE_BC) from real-world residential emissions were investigated from a field campaign covering 163 burning events for different fuel-stove combinations. MAE_BC (average: 12 ± 5 m²/g) was normally distributed and varied greatly by 2 orders of magnitude. Statistically significant differences in MAE_BC were found for various fuels, while no significant differences were observed among different stoves. The fuel difference explained 72 ± 7% of the MAE_BC variation. MAE_BC did not correlate with the modified combustion efficiency but positively correlated with the ratio of organic carbon (OC) to elemental carbon (EC) and negatively correlated with char-EC. The OC/EC ratio was not always lower in coal emissions in comparison to biomass burning emissions. Coal- and biomass-burning emissions had different profiles of carbon fractions. Char-EC, OC, OC/EC, and char-EC/soot-EC can explain 68.7% of the MAE_BC variation, providing the potential for predicting MAE_BC from the carbon fractions, since they are more commonly measured and available.

Characteristics, pollution patterns and risks of Perfluoroalkyl substances in drinking water sources of Taiwan

Perfluoroalkyl substances (PFASs) are found globally in the environment, but for Taiwan there is a lack of studies on PFAS occurrence, source apportionment, and health risks in drinking water sources. We collected surface water samples from the Baoshan Reservoir of Taiwan and used Positive Matrix Factorization to attribute PFAS contaminants to possible sources. The health index (HI) was used to evaluate the health risk, which was then compared to various international advisory level guidelines. PFOA and PFOS were found to be the most predominant compounds, with concentrations averaging 20.2 ng/L and 16.7 ng/L, respectively. The joint contribution of domestic and commercial waste totaled 61.2% as the predominant source of pollution, followed by urban activities as a secondary source contributing 38.8%. Using the USEPA reference dose, a health risk analysis of Baoshan Reservoir drinking water did not reflect a formal high health risk (HI < 1.0), however potential risks to human health may be present since the sum of PFOA and PFOS (130 ng/L) exceeded the USEPA Lifetime Health Advisory level (70 ng/L). This investigation provides information and reference points for further reviews of PFAS presence in public water supplies.

Assignment of PM2.5 sources in western Japan by non-negative matrix factorization of concentration-weighted trajectories of GED-ICP-MS/MS element concentrations

Rapid economic growth in Asian countries has raised concerns about the influence of air pollutants transported to Japan by westerly winds. We coupled a gas exchange device (GED) with a tandem inductively coupled plasma mass spectrometer (ICP-MS/MS) to enable direct introduction of PM_2.5 to ICP and thus provide better data than could be obtained from samples collected by conventional filter methods. We used the GED-ICP-MS/MS system in Matsue City in western Japan to monitor in real time 29 elements in PM_2.5 at 10-min intervals and to estimate the pollutant sources by non-negative matrix factorization (NMF) of concentration-weighted air-mass trajectories. The trajectory analysis identified high V, As, Sn, and Sb concentrations over the ocean from Taiwan to Tsushima Strait. NMF analysis revealed that these elements could be decomposed to multiple factors that indicated a large contribution from oceanic areas. The elemental contributions of these factors were high for metals/metalloids with low melting points as oxides, strongly suggesting that they were sourced from combustion of ship fuel. Our results demonstrate that both emissions from ships at sea and land-based emissions from Japan and continental Asia contribute to PM_2.5 in Matsue City.

Long term trends of chemical constituents and source contributions of PM2.5 in Seoul

PM_2.5 was measured and analyzed between 2014 and 2015 in Seoul, and its sources were identified with a positive matrix factorization (PMF) to characterize chemical constituents and sources of the measured PM_2.5. To verify policy interventions in reducing PM_2.5 levels in Korea, the results were compared with previously published results from 2003 to 2007 at the same study site. A total of 215 PM_2.5 samples were collected and analyzed for 24 species, i.e., carbonaceous species (OCEC), ionic species (NO3-, SO42-, and NH4+), and 19 element species in this study. The average PM_2.5 mass concentration during the sampling period was 42.6±23.3 μg m-3. The seasonal average mass concentration of PM_2.5 was the highest during winter (49.9±20.6 μg m-3), followed by spring (45.2±25.3 μg m-3), fall (34.4±19.3 μg m-3), and summer (28.4±12.5 μg m-3). Nine sources were identified and quantified using the PMF model: secondary nitrate (19.0%), secondary sulfate (20.2%), mobile (23.3%), biomass burning (12.1%), soil (8.3%), roadway emissions (3.1%), aged sea salt (1.0%), coal combustion (4.1%), and oil combustion (9.0%). The PM_2.5 levels and chemical constituents during this study were lower than those during the previous study from 2003 to 2007. Particularly, concentrations of mobile related chemicals (OC, EC, and nitrate) and mobile source contributions consistently decreased from 2003 to 2015, indicating that the mobile emission reduction policy is improving PM_2.5 levels in the region. The comparison between the two periods allows trends in chemical constituents and the sources of PM_2.5 in Seoul to be understood.

Investigating the plausibility of a PMF source apportionment solution derived using a small dataset: A case study from a receptor in a rural site in Apulia - South East Italy

Results of a methodological study on the use of Positive Matrix Factorization (PMF) with smaller datasets are being reported in this work. This study is based on 29 PM₁₀ and 33 PM_2.5 samples from a receptor in a rural setup in Apulia (Southern Italy). Running PMF on the two size fractions separately resulted in the model not functioning correctly. We therefore, augmented the size of the dataset by aggregating the PM₁₀ and PM_2.5 data. The 5-factor solution obtained for the aggregated data was fairly rotationally stable, and was further refined by the rotational tools included in USEPA PMF version 5. These refinements include the imposition of constraints on the solution, based on our knowledge of the chemical composition of the aerosol sources affecting the receptor. Additionally, the uncertainties associated with this solution were fully characterised using the improved error estimation techniques in this version of PMF. Five factors in all, were isolated by PMF: ammonium sulfate, marine aerosol, mixed carbonaceous aerosol, crustal/Saharan dust and total traffic. The results obtained by PMF were further tested inter alia, by comparing them to those obtained by two other receptor modelling techniques: Constrained Weighted Non-negative Matrix Factorization (CW - NMF) and Chemical Mass Balance (CMB). The results of these tests suggest that the solution obtained by PMF, is valid, indicating that for this particular airshed PMF managed to extract most of the information about the aerosol sources affecting the receptor - even from a dataset with a limited number of samples.

Sources of humic-like substances (HULIS) in PM2.5 in Beijing: Receptor modeling approach

Recent work has identified the presence of humic-like substances (HULIS) in ambient fine particulate matter (PM_2.5) in Beijing, China and that residential coal combustion as well as biomass burning are significant contributors to its presence. These results were based on the characterization of emissions from representative stoves and modeling of the aerosol with the Community Multiscale Air Quality (CMAQ) chemical transport model. The CMAQ source apportionment estimated that residential coal and biofuel burning and secondary aerosol formation were important annual sources of ambient HULIS, contributing 47.1%, 15.1%, and 38.9%, respectively. In this study, chemical composition data including concentrations of water-soluble organic carbon and HULIS across four seasons during 2012-2013 were analyzed with positive matrix factorization (PMF) to provide a complementary source apportionment. The PMF results indicate that the identified sources were Traffic, Biomass Burning, Nitrate/Sulfate, Incineration, Sulfate, Coal Combustion/Ammonium Chloride, Residential Coal/Biofuel Combustion, and Road Dust/Soil with mass contributions (fractions) to PM_2.5 of 12.35 (10.4%), 8.70 (8.9%), 24.51 (22.4%), 5.64 (7.2%), 25.14 (24.5%), 7.10 (6.2%), 14.18 (15.4%), and 5.33 μg/m³ (5.0%), respectively. The contributions to the observed HULIS concentrations were 0.63 (10.9%), 0.38 (6.4%), 0.07 (1.7%), 0.00 (0%), 1.12 (28.8%), 0.00 (0%), 1.50 (52.2%), and 0.01 μg/m³ (0.3%), respectively. These PMF modeling results were in reasonable agreement with the CMAQ values supporting the attribution of significant amounts of primary HULIS to residential coal and biofuel combustion. Currently, efforts are underway in China to replace solid fuel combustion for heating and cooking with natural gas and electricity by 2020. Thus, future studies should be able to see substantial reductions in both PM_2.5 and HULIS in the near term future.

Chemical characteristics of submicron aerosols observed at the King Sejong Station in the northern Antarctic Peninsula from fall to spring

The water-soluble ions and carbonaceous compounds of PM₁ were measured at the King Sejong Station (KSG) in the northern part of Antarctic Peninsula from March to November in 2009. As the sum of all measured species including organic matter [OM; organic carbon (OC)*1.9], the PM₁ mass reached a maximum of 936 ng m^-3 with the mean of 686 ± 226 ng m^-3. The most abundant constituents were OM (389 ± 109 ng m^-3) and sea-salts (Na⁺ and Cl^-, 193 ± 122 ng m^-3), which comprised 85% of the PM₁ mass. In contrast, the contribution of SO₄^2- was below 1% and its depletion relative to Na⁺ was prevalent particularly during winter, which was attributed to the frost flowers on newly formed sea-ice surface. The OC concentration was the highest in fall and its subcomponents OC2 and OC3 were moderately correlated with sea-salts (r = 0.5), indicating the marine biogenic source for OC. The elemental carbon (EC) concentration was much lower than OC, leading to the mean OC/EC ratio over 10. While the charred fraction of EC (EC1) was elevated by the long-range transport of biomass burning plume from nearby continent, the mass fraction of soot-EC (EC23) was increased concurrently with enhanced NO₃^-, suggesting EC23 as a good indicator for local influence in pristine environments like Antarctic region.

Analysis of the Characteristics and Sources of Carbonaceous Aerosols in PM2.5 in the Beijing, Tianjin, and Langfang Region, China

PM2.5 samples from Beijing, Tianjin, and Langfang were simultaneously collected from 20 November 2016 to 25 December 2016, and the organic carbon (OC) and elemental carbon (EC) content in the samples were measured and analyzed. The pollution characteristics and sources of OC and EC in atmospheric PM2.5 for three adjacent cities were discussed. The average mass concentrations of OC in PM2.5 in Beijing, Tianjin, and Langfang were 27.93 ± 23.35 μg/m³, 25.27 ± 12.43 μg/m³, and 52.75 ± 37.97 μg/m³, respectively, and the mean mass concentrations of EC were 6.61 ± 5.13 μg/m³, 6.14 ± 2.84 μg/m³, and 12.06 ± 6.81 μg/m³, respectively. The average mass concentration of total carbon (TC) accounted for 30.5%, 24.8%, and 49% of the average mass concentration of PM2.5 in the atmosphere. The total carbonaceous matter (TCA) in Beijing, Tianjin, and Langfang was 51.29, 46.57, and 96.45 μg/m³, respectively. The TCA was the main component of PM2.5 in the region. The correlation between OC and EC in the three cities showed R² values of 0.882, 0.633, and 0.784 for Beijing, Tianjin, and Langfang, respectively, indicating that the sources of urban carbonaceous aerosols had good consistency and stability. The OC/EC values of the three sampling points were 4.48 ± 1.45, 4.42 ± 1.77, and 4.22 ± 1.29, respectively, considerably greater than 2, indicating that the main sources of pollution were automobile exhaust, and the combustion of coal and biomass. The OC/EC minimum ratio method was used to estimate the secondary organic carbon (SOC) content in Beijing, Tianjin and Langfang. Their values were 10.73, 10.71, and 19.51, respectively, which accounted for 38%, 42%, and 37% of the average OC concentration in each city, respectively. The analysis of the eight carbon components showed that the main sources of pollutants in Beijing, Tianjin, and Langfang were exhaust emissions from gasoline vehicles, but the combustion of coal and biomass was relatively low. The pollution of road dust was more serious in Tianjin than in Beijing and Langfang. The contribution of biomass burning and coal-burning pollution sources to atmospheric carbon aerosols in Langfang was more prominent than that of Beijing and Tianjin.

Source-specific pollution exposure and associations with pulmonary response in the Atlanta Commuters Exposure Studies

Concentrations of traffic-related air pollutants are frequently higher within commuting vehicles than in ambient air. Pollutants found within vehicles may include those generated by tailpipe exhaust, brake wear, and road dust sources, as well as pollutants from in-cabin sources. Source-specific pollution, compared to total pollution, may represent regulation targets that can better protect human health. We estimated source-specific pollution exposures and corresponding pulmonary response in a panel study of commuters. We used constrained positive matrix factorization to estimate source-specific pollution factors and, subsequently, mixed effects models to estimate associations between source-specific pollution and pulmonary response. We identified four pollution factors that we named: crustal, primary tailpipe traffic, non-tailpipe traffic, and secondary. Among asthmatic subjects (N = 48), interquartile range increases in crustal and secondary pollution were associated with changes in lung function of -1.33% (95% confidence interval (CI): -2.45, -0.22) and -2.19% (95% CI: -3.46, -0.92) relative to baseline, respectively. Among non-asthmatic subjects (N = 51), non-tailpipe pollution was associated with pulmonary response only at 2.5 h post-commute. We found no significant associations between pulmonary response and primary tailpipe pollution. Health effects associated with traffic-related pollution may vary by source, and therefore some traffic pollution sources may require targeted interventions to protect health.

Urban Organic Aerosol Exposure: Spatial Variations in Composition and Source Impacts

We conducted a mobile sampling campaign in a historically industrialized terrain (Pittsburgh, PA) targeting spatial heterogeneity of organic aerosol. Thirty-six sampling sites were chosen based on stratification of traffic, industrial source density, and elevation. We collected organic carbon (OC) on quartz filters, quantified different OC components with thermal-optical analysis, and grouped them based on volatility in decreasing order (OC1, OC2, OC3, OC4, and pyrolyzed carbon (PC)). We compared our ambient OC concentrations (both gas and particle phase) to similar measurements from vehicle dynamometer tests, cooking emissions, biomass burning emissions, and a highway traffic tunnel. OC2 and OC3 loading on ambient filters showed a strong correlation with primary emissions while OC4 and PC were more spatially homogeneous. While we tested our hypothesis of OC2 and OC3 as markers of fresh source exposure for Pittsburgh, the relationship seemed to hold at a national level. Land use regression (LUR) models were developed for the OC fractions, and models had an average R² of 0.64 (SD = 0.09). The paper demonstrates that OC2 and OC3 can be useful markers for fresh emissions, OC4 is a secondary OC indicator, and PC represents both biomass burning and secondary aerosol. People with higher OC exposure are likely inhaling more fresh OC2 and OC3, since secondary OC4 and PC varies much less drastically in space or with local primary sources.

Source apportionments of ambient fine particulate matter in Israeli, Jordanian, and Palestinian cities

This manuscript evaluates spatial and temporal variations of source contributions to ambient fine particulate matter (PM_2.5) in Israeli, Jordanian, and Palestinian cities. Twenty-four hour integrated PM_2.5 samples were collected every six days over a 1-year period (January to December 2007) in four cities in Israel (West Jerusalem, Eilat, Tel Aviv, and Haifa), four cities in Jordan (Amman, Aqaba, Rahma, and Zarka), and three cities in Palestine (Nablus, East Jerusalem, and Hebron). The PM_2.5 samples were analyzed for major chemical components, including organic carbon and elemental carbon, ions, and metals, and the results were used in a positive matrix factorization (PMF) model to estimate source contributions to PM_2.5 mass. Nine sources, including secondary sulfate, secondary nitrate, mobile, industrial lead sources, dust, construction dust, biomass burning, fuel oil combustion and sea salt, were identified across the sampling sites. Secondary sulfate was the dominant source, contributing 35% of the total PM_2.5 mass, and it showed relatively homogeneous temporal trends of daily source contribution in the study area. Mobile sources were found to be the second greatest contributor to PM_2.5 mass in the large metropolitan cities, such as Tel Aviv, Hebron, and West and East Jerusalem. Other sources (i.e. industrial lead sources, construction dust, and fuel oil combustion) were closely related to local emissions within individual cities. This study demonstrates how international cooperation can facilitate air pollution studies that address regional air pollution issues and the incremental differences across cities in a common airshed. It also provides a model to study air pollution in regions with limited air quality monitoring capacity that have persistent and emerging air quality problems, such as Africa, South Asia and Central America.

Characteristics of carbonaceous aerosols: Impact of biomass burning and secondary formation in summertime in a rural area of the North China Plain

To determine the characteristics of carbonaceous aerosols in rural areas of the North China Plain, field measurements were conducted at Yucheng (YC) in the summers of 2013 and 2014. The concentrations of carbonaceous aerosols at YC exhibited clear diurnal variation, with higher concentrations in the early morning and at night and lower concentrations during the afternoon hours. The mass-balance method designed for particulate matter smaller than 2.5μm (PM2.5) was used to calculate the organic matter (OM)/organic carbon (OC) ratio. The value obtained, 2.07±0.05, was suggested as a reference to estimate organics in PM2.5 in rural areas of the North China Plain. Biomass burning was identified to be a significant source of carbonaceous aerosols; approximately half of the samples obtained at YC were affected by biomass burning during summer 2013. Case studies revealed that biomass burning accounted for up to 52.6% of the OC and 51.1% of the elemental carbon in PM2.5 samples. The organic coatings observed on sulphur-rich and potassium-rich particles indicated the formation of secondary organic aerosols (SOA) from the oxidation of precursor volatile organic compounds (VOCs) during the aging of smoke released from biomass burning. Based on the evolution of the VOCs, the contribution of VOCs oxidation to SOA concentration was 3.21 and 1.07μgm(-3)ppm(-1) CO under conditions of low nitrogen oxide (NOx) and high NOx, respectively. Aromatics (e.g. benzene, toluene, xylene and ethylbenzene) made the greatest contribution to SOA concentration (88.4% in low-NOx conditions and 80.6% in high-NOx conditions). The results of the study offer novel insights into the effects of biomass burning on the carbonaceous aerosols and SOA formation in polluted rural areas.

Seasonal and regional variations of source contributions for PM10 and PM2.5 in urban environment

To characterize the sources of to PM10 and PM2.5, a long-term, speciate and simultaneous dataset was sampled in a megacity in China during the period of 2006-2014. The PM concentrations and PM2.5/PM10 were higher in the winter. Higher percentages of Al, Si, Ca and Fe were observed in the summer, and higher concentrations of OC, NO3(-) and SO4(2-) occurred in the winter. Then, the sources were quantified by an advanced three-way model (defined as an ABB three-way model), which estimates different profiles for different sizes. A higher percentage of cement and crustal dust was present in the summer; higher fractions of coal combustion and nitrate+SOC were observed in the winter. Crustal and cement contributed larger portion to coarse part of PM10, whereas vehicular and secondary source categories were enriched in PM2.5. Finally, potential source contribution function (PSCF) and source regional apportionment (SRA) methods were combined with the three-way model to estimate geographical origins. During the sampling period, the southeast region (R4) was an important region for most source categories (0.6%-11.5%); the R1 (centre region) also played a vital role (0.3-6.9%).

Composition and sources of fine and coarse particles collected during 2002-2010 in Boston, MA

Identifying the sources, composition, and temporal variability of fine (PM2.5) and coarse (PM2.5-10) particles is a crucial component in understanding particulate matter (PM) toxicity and establishing proper PM regulations. In this study, a Harvard Impactor was used to collect daily integrated fine and coarse particle samples every third day for 9 years at a single site in Boston, MA. In total, 1,960 filters were analyzed for elements, black carbon (BC), and total PM mass. Positive Matrix Factorization (PMF) was used to identify source types and quantify their contributions to ambient PM2.5 and PM2.5-10. BC and 17 elements were identified as the main constituents in our samples. Results showed that BC, S, and Pb were associated exclusively with the fine particle mode, while 84% of V and 79% of Ni were associated with this mode. Elements mostly found in the coarse mode, over 80%, included Ca, Mn (road dust), and Cl (sea salt). PMF identified six source types for PM2.5 and three source types for PM2.5-10. Source types for PM2.5 included regional pollution, motor vehicles, sea salt, crustal/road dust, oil combustion, and wood burning. Regional pollution contributed the most, accounting for 48% of total PM2.5 mass, followed by motor vehicles (21%) and wood burning (19%). Source types for PM2.5-10 included crustal/road dust (62%), motor vehicles (22%), and sea salt (16%). A linear decrease in PM concentrations with time was observed for both fine (-5.2%/yr) and coarse (-3.6%/yr) particles. The fine-mode trend was mostly related to oil combustion and regional pollution contributions. Average PM2.5 concentrations peaked in summer (10.4 µg/m3), while PM2.5-10 concentrations were lower and demonstrated little seasonal variability. The findings of this study show that PM2.5 is decreasing more sharply than PM2.5-10 over time. This suggests the increasing importance of PM2.5-10 and traffic-related sources for PM exposure and future policies.

IMPLICATIONS

Although many studies have examined fine and coarse particle composition and sources, few studies have used concurrent measurements of these two fractions. Our analysis suggests that fine and coarse particles exhibit distinct compositions and sources. With better knowledge of the compositional and source differences between these two PM fractions, better decisions can be made about PM regulations. Further, such information is valuable in enabling epidemiologists to understand the ensuing health implications of PM exposure.

Chemical compositions and source identification of PM₂.₅ aerosols for estimation of a diesel source surrogate

Exposure to traffic-related pollution during childhood has been associated with asthma exacerbation, and asthma incidence. The objective of the Cincinnati Childhood Allergy and Air Pollution Study (CCAAPS) is to determine if the development of allergic and respiratory disease is associated with exposure to diesel engine exhaust particles. A detailed receptor model analyses was undertaken by applying positive matrix factorization (PMF) and UNMIX receptor models to two PM₂.₅ data sets: one consisting of two carbon fractions and the other of eight temperature-resolved carbon fractions. Based on the source profiles resolved from the analyses, markers of traffic-related air pollution were estimated: the elemental carbon attributed to traffic (ECAT) and elemental carbon attributed to diesel vehicle emission (ECAD). Application of UNMIX to the two data sets generated four source factors: combustion related sulfate, traffic, metal processing and soil/crustal. The PMF application generated six source factors derived from analyzing two carbon fractions and seven factors from temperature-resolved eight carbon fractions. The source factors (with source contribution estimates by mass concentrations in parentheses) are: combustion sulfate (46.8%), vegetative burning (15.8%), secondary sulfate (12.9%), diesel vehicle emission (10.9%), metal processing (7.5%), gasoline vehicle emission (5.6%) and soil/crustal (0.7%). Diesel and gasoline vehicle emission sources were separated using eight temperature-resolved organic and elemental carbon fractions. Application of PMF to both datasets also differentiated the sulfate rich source from the vegetative burning source, which are combined in a single factor by UNMIX modeling. Calculated ECAT and ECAD values at different locations indicated that traffic source impacts depend on factors such as traffic volumes, meteorological parameters, and the mode of vehicle operation apart from the proximity of the sites to highways. The difference in ECAT and ECAD, however, was less than one standard deviation. Thus, a cost benefit consideration should be used when deciding on the benefits of an eight or two carbon approach.

Modeling and source apportionment of diesel particulate matter

The fine and ultra fine sizes of diesel particulate matter (DPM) are of greatest health concern. The composition of these primary and secondary fine and ultra fine particles is principally elemental carbon (EC) with adsorbed organic compounds, sulfate, nitrate, ammonia, metals, and other trace elements. The purpose of this study was to use an advanced air quality modeling technique to predict and analyze the emissions and the primary and secondary aerosols concentrations that come from diesel-fueled sources (DFS). The National Emissions Inventory for 1999 and a severe southeast ozone episode that occurred between August and September 1999 were used as reference. Five urban areas and one rural area in the Southeastern US were selected to compare the main results. For urban emissions, results showed that DFS contributed (77.9%+/-8.0) of EC, (16.8%+/-8.2) of organic aerosols, (14.3%+/-6.2) of nitrate, and (8.3%+/-6.6) of sulfate during the selected episodes. For the rural site, these contributions were lower. The highest DFS contribution on EC emissions was allocated in Memphis, due mainly to diesel non-road sources (60.9%). For ambient concentrations, DFS contributed (69.5%+/-6.5) of EC and (10.8%+/-2.4) of primary anthropogenic organic aerosols, where the highest DFS contributions on EC were allocated in Nashville and Memphis on that episode. The DFS contributed (8.3%+/-1.2) of the total ambient PM(2.5) at the analyzed sites. The maximum primary DPM concentration occurred in Atlanta (1.44 microg/m(3)), which was 3.8 times higher than that from the rural site. Non-linearity issues were encountered and recommendations were made for further research. The results indicated significant geographic variability in the EC contribution from DFS, and the main DPM sources in the Southeastern U.S. were the non-road DFS. The results of this work will be helpful in addressing policy issues targeted at designing control strategies on DFS in the Southeastern U.S.

The use of source apportionment for air quality management and health assessments

Receptor modeling is the application of data analysis methods to elicit information on the sources of air pollutants. Typically, it employs methods of solving the mixture resolution problem using chemical composition data for airborne particulate matter (PM) samples. In such cases, the outcome is the identification of the pollution source types and estimates of the contribution of each source type to the observed concentrations. Receptor modeling also involves efforts to identify the locations of the sources through the use of local meteorology or ensembles of air parcel back trajectories. Compositional data were collected in a number of monitoring programs. The U.S. Environmental Protection Agency deployed a network of urban airborne PM samplers to provide PM(2.5) composition data for urban centers across the United States. In addition, advanced monitoring methods were deployed at "supersites." These data show the differences in composition in different part of the country and were also used to identify and apportion the particle sources. These results were used to (1)develop effective and efficient air quality management plans and (2) refine emission inventories for input into deterministic models to predict changes in air quality as the result of the implementation of various management plans. The apportionments also serve as exposure estimates for health effects models to identify those components of the PM that are most closely related to observed adverse health effects. Although current regulations target total airborne mass concentrations, such health effects results might result in targeting those sources that are most likely linked to adverse health effects and thus produce the maximum health benefit.

Sources of fine urban particulate matter in Detroit, MI

Data from the speciation trends network (STN) was used to evaluate the amount and temporal patterns of particulate matter originating from local industrial sources and long-range transport at two sites in Detroit, MI: Allen Park, MI, southwest of both Detroit and the areas of heavy industrial activity; Dearborn, MI, located on the south side of Detroit near the most heavily industrialized region. Using positive matrix factorization (PMF) and comparing source contributions at Allen Park to those in Dearborn, contributions made by local industrial sources (power plants, coke refineries, iron smelting, waste incineration), local area sources (automobile and diesel truck) and long range sources of PM(2.5) can be distinguished in greater Detroit. Overall, the mean mass concentration measured at Dearborn was 19% higher than that measured at Allen Park. The mass at Allen Park was apportioned as: secondary sulfate 31%, secondary nitrate 28%, soil 8%, mixed aged sea and road salts 4%, gasoline 15%, diesel 4%, and biomass burning 3%. At Dearborn the mass was apportioned as: secondary sulfate 25%, secondary nitrate 20%, soil 12%, mixed aged sea and road salts 4%, gasoline 20%, diesel 8%, iron and steel, 5%, and mixed industrial 7%. The impact of the iron and steel, soil, and mixed aged sea and road salt was much higher at the Dearborn site than at the Allen Park site, suggesting that close proximity to a local industrial complex has a direct negative impact on local air quality.

Characterization of fine particle sources in the Great Smoky Mountains area

A source apportionment study to characterize sources of fine particles in the Great Smoky Mountains area was conducted analyzing ambient PM(2.5) (particulate matter< or =2.5 microm in aerodynamic diameter) speciation data collected at a Interagency Monitoring of Protected Visual Environments (IMPROVE) monitoring site. A total of 1442 samples collected between March 1988 and December 2003 analyzed for 30 elemental species were analyzed with the application of the positive matrix factorization (PMF). Eight major sources were extracted: summer-high secondary sulfate (55%), carbon-rich secondary sulfate (16%), summer-low secondary sulfate (2%), gasoline vehicle emissions (13%), diesel emissions (1%), airborne soil (6%), industry (5%), and secondary nitrate (2%). The contributions from the carbon-rich secondary sulfate particles are likely a combination of local and regional influences of the biogenic as well as anthropogenic secondary particles. The compositional profiles for gasoline vehicle and diesel emissions are similar to those identified in other US areas. Backward trajectories indicate that the high impacts of airborne soil were likely caused by Asian and Saharan dust storms. This study would assist in the implementation plan development for attaining the air quality standards for PM(2.5), regional haze rule planning, and source-specific community epidemiology.