Atmospheric Concentrations and Potential Sources of Dioxin-Like Contaminants to Acadia National Park.

Acadia National Park (ANP) is located on Mt. Desert Island, ME on the U.S. Atlantic coast. ANP is routinely a top-ten most popular National Park with over four million visits in 2022. The overall contribution and negative effects of long-range atmospheric transport and local sources of dioxin-like contaminants endangering natural and wildlife resources is unknown. Dioxin-like (DL) contaminants polychlorinated dibenzo-p-dioxins (∑PCDD) and polychlorinated dibenzofurans (∑PCDF), non-ortho coplanar PCBs (∑CP4), and polychlorinated naphthalenes (∑PCNs) were measured at the McFarland Hill air monitoring station (44.37°N, 68.26°W). On a mass/volume basis, total PCNs averaged 90.9 % (788 fg/m3) of DL contaminants measured annually, with 92.9 % of the collected total in the vapor-phase. Alternatively, total dioxin/furans (∑PCDD/Fs) represented 71.6 % of the total toxic equivalence (∑TEQ) (1.018 fg-TEQ/m3), with 69.7 % in the particulate-phase. Maximum concentrations measured for individual sampling events for ∑PCDD/F, ∑CP4, and ∑PCN were 159 (winter), 139 (summer), and 2100 (autumn), fg/m3 respectively. Whereas the maximum ∑TEQ concentrations for individual sampling events for ∑PCDD/F, ∑CP4, and ∑PCN were 2.8 (autumn), 0.38 (summer), and 0.71 (autumn), fg-TEQ/m3 respectively. Pearson correlations were calculated for ∑PCDD/Fs and ∑PCN particulate/vapor-phase air concentrations and PM2.5 wood smoke "indicator" species. The most significant correlations were observed in autumn for particulate-phase ∑PCDD/Fs suggesting a relationship between visitation-generated combustion sources (campfires and/or waste burning) or climate-change mediated forest fires. Significant Clausius-Clapeyron (C-C) correlations observed for particulate-phase ∑PCDDs (r2=0.567) as ambient temperatures decreased suggests a connection between localized domestic heating sources or visitor-based burning of wood/trash resources. Alternatively, highly significant C-C vapor-phase ∑CP4-PCBs correlations (r2=0.815) implies that the majority of ∑CP4-PCB loading to ANP is from long-range atmospheric transport processes. Based on these findings, Acadia National Park should be classified as a remote site with minor depositional impacts from ∑PCDD/Fs, ∑CP4-PCBs, and ∑PCN atmospheric transport or local diffuse sources.

An in-depth investigation of global sea surface temperature behavior utilizing chaotic modeling.

Sea surface temperature (SST), with its complex and dynamic behavior, is a major driver of ocean-atmosphere interactions. The purpose of this study is to investigate the behavior of SST and its prediction using a chaotic approach. Average mutual information (AMI) and Cao methods were used to reconstruct the phase space. The Lyapunov exponent and correlation dimension were used to investigate chaos. The Lyapunov exponent index was used to predict SST with a 5-year average prediction horizon using the local prediction method between 2023 and 2027. The results showed a 3-month delay time for the Pacific and Antarctic Oceans, and a 2-month delay time for the Atlantic, Indian, and Arctic Oceans. The optimal embedding dimension for all oceans is between 6 and 7. Our analysis reveals that the dynamics of SST in all oceans exhibit varying degrees of chaos, as indicated by the correlation dimension. The local prediction method achieves relatively accurate short-term SST predictions due to the clustering of SST points around specific attractors in the phase space. However, in the long term, the accuracy of this method decreases as the points in the phase space of SST can spread randomly. The model performance ranking with a Percent Mean Relative Absolute Error shows that the Indian Ocean has the best performance compared to other oceans, while the Atlantic, Pacific, and Antarctic and Arctic Oceans are in the next ranks. This study contributes to understanding the dynamics of SST and has practical value for use in the development of climate models.

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.

Short- and medium-chain chlorinated paraffins in surface sediment from Lake Ontario.

Concentrations of short- and medium-chain chlorinated paraffins (SCCPs and MCCPs) were analyzed and investigated in surficial sediment collected in 2018 from ten different nearshore sites in Lake Ontario and the St. Lawrence River influenced by inputs from varying urban and historical land uses. Sites were grouped into two categories of tributary and lake according to their location. Results show that tributary sites had higher concentrations of total chlorinated paraffin (CP) than lake sites. Humber Bay, a lake site, had the highest total CP concentration (55,000 ng/gTOC) followed by Humber River, a tributary site (50,000 ng/gTOC). The lowest concentrations were found in eastern Lake Ontario and Lake St. Francis in the St. Lawrence River (540 ng/gTOC). Higher concentrations of chlorinated paraffins (CPs) were found where runoff and wastewater inputs from urban areas, current industrial activities, and population were the greatest. Levels of MCCPs were higher than SCCPs at all sites but one, Lake St. Francis. Among the SCCPs, C13 and among the MCCPs C14 were the dominant chain length alkanes, with C14 being the highest among both groups. The SCCPs and MCCPs profiles suggest that they can be used to distinguish between sites impacted by local sources vs. sites impacted by short-/long-range transport of these chemicals.

Is replacing missing values of PM2.5 constituents with estimates using machine learning better for source apportionment than exclusion or median replacement?

East Asian countries have been conducting source apportionment of fine particulate matter (PM2.5) by applying positive matrix factorization (PMF) to hourly constituent concentrations. However, some of the constituent data from the supersites in South Korea was missing due to instrument maintenance and calibration. Conventional preprocessing of missing values, such as exclusion or median replacement, causes biases in the estimated source contributions by changing the PMF input. Machine learning (ML) can estimate the missing values by training on constituent data, meteorological data, and gaseous pollutants. Complete data from the Seoul Supersite in 2018 was taken, and a random 20% was set as missing. PMF was performed by replacing missing values with estimates. Percent errors of the source contributions were calculated compared to those estimated from complete data. Missing values were estimated using a random forest analysis. Estimation accuracy (r2) was as high as 0.874 for missing carbon species and low at 0.631 when ionic species and trace elements were missing. For the seven highest contributing sources, replacing the missing values of carbon species with estimates minimized the percent errors to 2.0% on average. However, replacing the missing values of the other chemical species with estimates increased the percent errors to more than 9.7% on average. Percent errors were maximal at 37% on average when missing values of ionic species and trace elements were replaced with estimates. Missing values, except for carbon species, need to be excluded. This approach reduced the percent errors to 7.4% on average, which was lower than those due to median replacement. Our results show that reducing the biases in source apportionment is possible by replacing the missing values of carbon species with estimates. To improve the biases due to missing values of the other chemical species, the estimation accuracy of the ML needs to be improved.

Particulate black carbon mass concentrations and the episodic source identification driven by atmospheric blocking effects in Astana, Kazakhstan.

Black carbon (BC) is a component of fine particulate matter (PM2.5) that is a key contributor to adverse human health effects and climate forcing. To date, BC mass concentrations and possible sources in Kazakhstan have not been studied. Thus, understanding the temporal variations of BC for a large developing region with a complex climate is useful. In this study, measurements of fine particulate BC mass concentrations in Astana were made from June 2020 to October 2021 by measuring light absorption of PM2.5 on filters. The mean BC concentration was 2.56 ± 1.29 µg m-3 with maximum and minimum monthly mean BC concentrations being 4.56 ± 2.03 µg m-3 and 1.12 ± 0.42 µg m-3 in January 2021 and June 2020, respectively. Temporal analyses of BC, SO2, PM10, NOx, CO, meteorological and atmospheric stability parameters were performed. Aggregated pollutant 'episodic loadings' during the heating and non-heating periods were identified. Their relationships with blocking anticyclones and cyclones were investigated by examining the reversal of meridional gradients at 500 hPa geopotential height (GPH) maps and identifying Omega (Ω) and Rex blocking types. Astana has some of the highest BC concentrations of cities worldwide. Seasonal BC source location identification using Conditional Bivariate Probability Function (CBPF) analysis implicated combined heat and power (CHP) plant emissions as the major BC source in Astana. Significant increases in BC concentrations were observed during the cold season due to numerous sources, generally poorer atmospheric dispersion and blocking events. The Concentration Weighted Trajectory (CWT) analysis results showed that the distribution of the 75th percentile of BC during episodic periods actively controlled by blockings exceeding than the entire measurement period, which may reflect cross-border transport and adjacent countries.

Regulation-driven changes in PM2.5 sources in China from 2013 to 2019, a critical review and trend analysis.

Identifying changes in source-specific fine particles (PM2.5) over time is essential for evaluating the effectiveness of regulatory measures and informing future policy decisions. After the extreme haze events in China during 2013-14, more comprehensive and stringent policies were implemented to combat PM2.5 pollution. To determine the effectiveness of these policies, it is necessary to assess the changes in the specific source types to which the regulations pertain. Multiple studies have been conducted over the past decade to apportion PM2.5. The purpose of this study was to explore the available literature and conduct a critical review of the reliable results. In total, 5008 articles were screened, but only 48 studies were included for further analysis given our inclusion criteria including covering a monitoring period of ≥1 year and having enough speciation data to provide mass closure. Using these studies, we analyzed temporal and spatial trends across China from 2013 to 2019. We observed the overall decrease in the concentration contributions from all main source categories. The reductions from industry, coal and heavy oil combustion, and the related secondary sulfate were more notable, especially from 2013 to 2016-17. The contributions from biomass burning initially decreased but then increased slightly after 2016 in some locations despite new constraints on agricultural and household burning practices. Although the contributions from vehicle emissions and related secondary nitrate decreased, they gradually became the primary contributors to PM2.5 by ∼2017. Despite the substantial improvements achieved by the air pollution regulation implementations, further improvements in air quality will require additional aggressive actions, especially those targeting vehicular emissions. Ultimately, source apportionment studies based on extended duration, fixed-site sampling are recommended to provide a more thorough understanding of the sources impacting areas and transformations in PM2.5 sources prompted by regulatory actions.

Nitrate formation mechanisms causing high concentration of PM2.5 in a residential city with low anthropogenic emissions during cold season.

During the cold season in South Korea, NO3- concentrations are known to significantly increase, often causing PM2.5 to exceed air quality standards. This study investigated the formation mechanisms of NO3- in a suburban area with low anthropogenic emissions. The average PM2.5 was 25.3 µg m-3, with NO3- identified as the largest contributor. Ammonium-rich conditions prevailed throughout the study period, coupled with low atmospheric temperature facilitating the transfer of gaseous HNO3 into the particulate phase. This result indicates that the formation of HNO3 played a crucial role in determining particulate NO3- concentration. Nocturnal increases in NO3- were observed alongside increasing ozone (O3) and relative humidity (RH), emphasizing the significance of heterogeneous reactions involving N2O5. NO3- concentrations at the study site were notably higher than in Seoul, the upwind metropolitan area, during a high concentration episode. This difference could potentially attributed to lower local NO concentrations, which enhanced the reaction between O3 and NO2, to produce NO3 radicals. High concentrations of Cl- and dust were also identified as contributors to the elevated NO3- concentrations.

Application of quasi-empirical orthogonal functions to estimate wildfire impacts in northwestern Spain.

Galicia (NW Spain) is one of the most fire-prone regions in Southern Europe. In the summer of 2022, a total of thirteen wildfires each exceeding 500 ha were reported in this area, with ten of these large fires occurring in the Ourense region. To study the impacts of wildfire smoke plumes on ambient air PM2.5 concentrations, a network of 18 PurpleAir monitors was deployed across the Galicia region during July and August 2022. The PM2.5 concentration data were then used as input to test the applicability of quasi-empirical orthogonal functions (QEOFs obtained with Positive Matrix Factorization (PMF)) to characterize the spatial variability of wildfire smoke impacts on air quality. HYSPLIT back-trajectory analysis and Concentration-Weighted Trajectory (CWT) models were implemented, and the results from these tools were combined with source contributions. As a result, 19 wildfires were identified and linked with peak ambient PM2.5 concentrations (>300 µg/m3 of PM2.5; 1-h mean). Specifically, the Folgoso do Courel fire emerged as a significant contributor to these high concentrations and played an important role in influencing a significant number of the identified factors. Moreover, the results also suggested that emissions from fires in Portugal reached the study area, contributing additional impacts on air quality. These results demonstrated that this approach was useful in identifying the emission source areas contributing to observed PM2.5 concentrations during wildfire events. The PM2.5 concentration maps resulting from the CWT analysis were also valuable in understanding the short- and long-term exposures to PM2.5 from wildfire smoke.

Indoor Air Sources of Outdoor Air Pollution: Health Consequences, Policy, and Recommendations: An Official American Thoracic Society Workshop Report.

Indoor sources of air pollution worsen indoor and outdoor air quality. Thus, identifying and reducing indoor pollutant sources would decrease both indoor and outdoor air pollution, benefit public health, and help address the climate crisis. As outdoor sources come under regulatory control, unregulated indoor sources become a rising percentage of the problem. This American Thoracic Society workshop was convened in 2022 to evaluate this increasing proportion of indoor contributions to outdoor air quality. The workshop was conducted by physicians and scientists, including atmospheric and aerosol scientists, environmental engineers, toxicologists, epidemiologists, regulatory policy experts, and pediatric and adult pulmonologists. Presentations and discussion sessions were centered on 1) the generation and migration of pollutants from indoors to outdoors, 2) the sources and circumstances representing the greatest threat, and 3) effective remedies to reduce the health burden of indoor sources of air pollution. The scope of the workshop was residential and commercial sources of indoor air pollution in the United States. Topics included wood burning, natural gas, cooking, evaporative volatile organic compounds, source apportionment, and regulatory policy. The workshop concluded that indoor sources of air pollution are significant contributors to outdoor air quality and that source control and filtration are the most effective measures to reduce indoor contributions to outdoor air. Interventions should prioritize environmental justice: Households of lower socioeconomic status have higher concentrations of indoor air pollutants from both indoor and outdoor sources. We identify research priorities, potential health benefits, and mitigation actions to consider (e.g., switching from natural gas to electric stoves and transitioning to scent-free consumer products). The workshop committee emphasizes the benefits of combustion-free homes and businesses and recommends economic, legislative, and education strategies aimed at achieving this goal.

Inter-annual trends of ultrafine particles in urban Europe.

Ultrafine particles (UFP, those with diameters ≤ 100 nm), have been reported to potentially penetrate deeply into the respiratory system, translocate through the alveoli, and affect various organs, potentially correlating with increased mortality. The aim of this study is to assess long-term trends (5-11 years) in mostly urban UFP concentrations based on measurements of particle number size distributions (PNSD). Additionally, concentrations of other pollutants and meteorological variables were evaluated to support the interpretations. PNSD datasets from 12 urban background (UB), 5 traffic (TR), 3 suburban background (SUB) and 1 regional background (RB) sites in 15 European cities and 1 in the USA were evaluated. The non-parametric Theil-Sen's method was used to detect monotonic trends. Meta-analyses were carried out to assess the overall trends and those for different environments. The results showed significant decreases in NO, NO2, BC, CO, and particle concentrations in the Aitken (25-100 nm) and the Accumulation (100-800 nm) modes, suggesting a positive impact of the implementation of EURO 5/V and 6/VI vehicle standards on European air quality. The growing use of Diesel Particle Filters (DPFs) might also have clearly reduced exhaust emissions of BC, PM, and the Aitken and Accumulation mode particles. However, as reported by prior studies, there remains an issue of poor control of Nucleation mode particles (smaller than 25 nm), which are not fully reduced with current DPFs, without emission controls for semi-volatile organic compounds, and might have different origins than road traffic. Thus, contrasting trends for Nucleation mode particles were obtained across the cities studied. This mode also affected the UFP and total PNC trends because of the high proportion of Nucleation mode particles in both concentration ranges. It was also found that the urban temperature increasing trends might have also influenced those of PNC, Nucleation and Aitken modes.

Long term trends in source apportioned particle number concentrations in Rochester NY.

During the past two decades, efforts have been made to further reduce particulate air pollution across New York State through various Federal and State policy implementations. Air quality has also been affected by economic drivers like the 2007-2009 recession and changing costs for different approaches to electricity generation. Prior work has focused on particulate matter with aerodynamic diameter ≤2.5 µm. However, there is also interest in the effects of ultrafine particles on health and the environment and analyses of changes in particle number concentrations (PNCs) are also of interest to assess the impacts of changing emissions. Particle number size distributions have been measured since 2005. Prior apportionments have been limited to seasonal analyses over a limited number of years because of software limitations. Thus, it has not been possible to perform trend analyses on the source-specific PNCs. Recent development have now permitted the analysis of larger data sets using Positive Matrix Factorization (PMF) including its diagnostics. Thus, this study separated and analyzed the hourly averaged size distributions from 2005 to 2019 into two data sets; October to March and April to September. Six factors were resolved for both data sets with sources identified as nucleation, traffic 1, traffic 2, fresh secondary inorganic aerosol (SIA), aged SIA, and O3-rich aerosol. The resulting source-specific PNCs were combined to provide continuous data sets and analyzed for trends. The trends were then examined with respect to the implementation of regulations and the timing of economic drivers. Nucleation was strongly reduced by the requirement of ultralow (<15 ppm) sulfur on-road diesel fuel in 2006. Secondary inorganic particles and O3-rich PNCs show strong summer peaks. Aged SIA was constant and then declined substantially in 2015 but rose in 2019. Traffic 1 and 2 have steadily declined bur rose in 2019.

Variability of ambient air ammonia in urban Europe (Finland, France, Italy, Spain, and the UK).

This study addressed the scarcity of NH3 measurements in urban Europe and the diverse monitoring protocols, hindering direct data comparison. Sixty-nine datasets from Finland, France, Italy, Spain, and the UK across various site types, including industrial (IND, 8), traffic (TR, 12), urban (UB, 22), suburban (SUB, 12), and regional background (RB, 15), are analyzed to this study. Among these, 26 sites provided 5, or more, years of data for time series analysis. Despite varied protocols, necessitating future harmonization, the average NH3 concentration across sites reached 8.0 ± 8.9 µg/m3. Excluding farming/agricultural hotspots (FAHs), IND and TR sites had the highest concentrations (4.7 ± 3.2 and 4.5 ± 1.0 µg/m3), followed by UB, SUB, and RB sites (3.3 ± 1.5, 2.7 ± 1.3, and 1.0 ± 0.3 µg/m3, respectively) indicating that industrial, traffic, and other urban sources were primary contributors to NH3 outside FAH regions. When referring exclusively to the FAHs, concentrations ranged from 10.0 ± 2.3 to 15.6 ± 17.2 µg/m3, with the highest concentrations being reached in RB sites close to the farming and agricultural sources, and that, on average for FAHs there is a decreasing NH3 concentration gradient towards the city. Time trends showed that over half of the sites (18/26) observed statistically significant trends. Approximately 50 % of UB and TR sites showed a decreasing trend, while 30 % an increasing one. Meta-analysis revealed a small insignificant decreasing trend for non-FAH RB sites. In FAHs, there was a significant upward trend at a rate of 3.51[0.45,6.57]%/yr. Seasonal patterns of NH3 concentrations varied, with urban areas experiencing fluctuations influenced by surrounding emissions, particularly in FAHs. Diel variation showed differing patterns at urban monitoring sites, all with higher daytime concentrations, but with variations in peak times depending on major emission sources and meteorological patterns. These results offer valuable insights into the spatio-temporal patterns of gas-phase NH3 concentrations in urban Europe, contributing to future efforts in benchmarking NH3 pollution control in urban areas.

Recommendations for reporting equivalent black carbon (eBC) mass concentrations based on long-term pan-European in-situ observations.

A reliable determination of equivalent black carbon (eBC) mass concentrations derived from filter absorption photometers (FAPs) measurements depends on the appropriate quantification of the mass absorption cross-section (MAC) for converting the absorption coefficient (babs) to eBC. This study investigates the spatial-temporal variability of the MAC obtained from simultaneous elemental carbon (EC) and babs measurements performed at 22 sites. We compared different methodologies for retrieving eBC integrating different options for calculating MAC including: locally derived, median value calculated from 22 sites, and site-specific rolling MAC. The eBC concentrations that underwent correction using these methods were identified as LeBC (local MAC), MeBC (median MAC), and ReBC (Rolling MAC) respectively. Pronounced differences (up to more than 50 %) were observed between eBC as directly provided by FAPs (NeBC; Nominal instrumental MAC) and ReBC due to the differences observed between the experimental and nominal MAC values. The median MAC was 7.8 ± 3.4 m2 g-1 from 12 aethalometers at 880 nm, and 10.6 ± 4.7 m2 g-1 from 10 MAAPs at 637 nm. The experimental MAC showed significant site and seasonal dependencies, with heterogeneous patterns between summer and winter in different regions. In addition, long-term trend analysis revealed statistically significant (s.s.) decreasing trends in EC. Interestingly, we showed that the corresponding corrected eBC trends are not independent of the way eBC is calculated due to the variability of MAC. NeBC and EC decreasing trends were consistent at sites with no significant trend in experimental MAC. Conversely, where MAC showed s.s. trend, the NeBC and EC trends were not consistent while ReBC concentration followed the same pattern as EC. These results underscore the importance of accounting for MAC variations when deriving eBC measurements from FAPs and emphasize the necessity of incorporating EC observations to constrain the uncertainty associated with eBC.

Reduction of ovarian reserves and activation of necroptosis to in vivo air pollution exposures.

We investigated the association between air pollution and changes in ovarian follicles, anti-mullerian hormone (AMH) levels, the occurrence of necroptosis cell death by activation of receptor-interacting protein kinase 3 (RIPK3) and, the activation of mixed lineage kinase domain-like (MLKL) proteins. Forty-two female Wistar rats were divided into three groups of 14 each, which were exposed to real-ambient air, filtered air and purified air (control) in two periods of 3 and 5 months. The results showed that the number of ovarian follicles decreased in the group exposed to real-ambient air versus the control group (P < 0.0001). The trend of age-related AMH changes with respect to exposure to air pollutants was affected and its levels decreased after 3 months of exposure. The MLKL increased in the group exposed to the real-ambient air compared to the control group (P = 0.033). Apparently long-term exposure to air pollution can reduce ovarian reserves.

Analysis of PM2.5 inorganic and organic constituents to resolve contributing sources in Seoul, South Korea and Beijing, China and their possible associations with cytokine IL-8.

China and South Korea are the most polluted countries in East Asia due to significant urbanization and extensive industrial activities. As neighboring countries, collaborative management plans to maximize public health in both countries can be helpful in reducing transboundary air pollution. To support such planning, PM2.5 inorganic and organic species were determined in simultaneously collected PM2.5 integrated filters. The resulting data were used as inputs to positive matrix factorization, which identified nine sources at the ambient air monitoring sites in both sites. Secondary nitrate, secondary sulfate/oil combustion, soil, mobile, incinerator, biomass burning, and secondary organic carbon (SOC) were found to be sources at both sampling sites. Industry I and II were only identified in Seoul, whereas combustion and road dust sources were only identified in Beijing. A subset of samples was selected for exposure assessment. The expression levels of IL-8 were significantly higher in Beijing (167.7 pg/mL) than in Seoul (72.7 pg/mL). The associations between the PM2.5 chemical constituents and its contributing sources with PM2.5-induced inflammatory cytokine (interleukin-8, IL-8) levels in human bronchial epithelial cells were investigated. For Seoul, the soil followed by the secondary nitrate and the biomass burning showed increase with IL-8 production. However, for the Beijing, the secondary nitrate exhibited the highest association with IL-8 production and SOC and biomass burning showed modest increase with IL-8. As one of the highest contributing sources in both cities, secondary nitrate showed an association with IL-8 production. The soil source having the strongest association with IL-8 production was found only for Seoul, whereas SOC showed a modest association only for Beijing. This study can provide the scientific basis for identifying the sources to be prioritized for control to provide effective mitigation of particulate air pollution in each city and thereby improve public health.

Effect of industrialization on the differences in sources and composition of ambient PM2.5 in two Southern Ontario locations.

PM2.5 was sampled over a seven-year period (2013-2019) at two locations ∼50 km apart in Southern Ontario (concurrently for five years: 2015-2019). One is a heavily industrialized site (Hamilton), while the other was a rural site (Simcoe). To assess the impact of industrialization on the composition and sources of PM affecting air quality in these two locations, positive matrix factorization coupled with dispersion normalization (DN-PMF) was used to identify six and eight factors at Simcoe and Hamilton, respectively. The Simcoe factors in order of diminishing PM mass contribution were: particulate sulphate (pSO4), secondary organic aerosol (SOA), crustal matter, particulate nitrate (pNO3), biomass burning, and vehicular emissions. At Hamilton, the effects of industrialization were observed by the ∼36% higher average ambient PM2.5 concentration for the study period as well as the presence of factors unique to metallurgy, i.e., coking and steelmaking, compared to Simcoe. The coking and steelmaking factors contributed ∼15% to the PM mass at Hamilton. Seasonal variants of appropriate nonparametric trend tests with the associated slopes (Sen's) were used to assess statistically significant changes in the factor contributions to PM2.5 over time. Specifically at Hamilton, a significant decline in PM contributions was noted for coking (-0.03 µg/m³/yr or -4.1%/yr) while steelmaking showed no statistically significant decline over the study period. Other factors at Hamilton that showed statistically significant declines over the study period were: pSO4 (-0.27 µg/m³/yr or -12.6%/yr), biomass burning (-0.05 µg/m³/yr or -9.02%/yr), crustal matter (-0.03 µg/m³/yr or -5.28%/yr). These factors mainly accounted for the significant decline in PM2.5 over the study period (-0.35 µg/m³/yr or -4.24%/yr). This work shows the importance of long-term monitoring in assessing the unique contributions and temporal changes of industrialization on air quality in Ontario and similarly affected locations.

Heterogeneous (gas-solid) chemistry of atmospheric Cr: A case study of Astana, Kazakhstan.

Hexavalent chromium (Cr(VI)) is a known carcinogen derived from both anthropogenic and natural sources. This work reports the size-segregated concentrations of total Cr(VI) in particulate matter (PM) in Astana, the capital of Kazakhstan, and provides new insights into the gas-solid reactions of atmospheric Cr. A study of total Cr(VI) in the particulate matter, via a microwave-assisted digestion technique, was conducted using a 5-stage Sioutas Cascade impactor that captures airborne particles in size ranges: >2.5 µm, 1.0-2.5 µm, 0.50-1.0 µm, 0.25-0.50 µm, and <0.25 µm. The total Cr(VI) concentration in the size fraction <0.25 µm was the highest with a maximum value of 9.7 ng/m3. This high concentration may pose a greater risk because smaller airborne particles can penetrate deeper into the lower respiratory tract of the lungs. Total suspended particles Cr(VI) exceeded the 8.0 ng/m3 Reference Concentration (RfC) by 22 times. The overall total Cr(VI) concentration in summer was significantly higher than in fall (p < 0.05), which could be due to factors, including higher temperatures, ozone, and NO2 concentrations in summer and a higher VOC concentration in fall. The results indicate that the interaction between Cr(III) and Cr(VI) through gas-solid reaction can control the speciation of atmospheric Cr.

Generating High Spatial Resolution Exposure Estimates from Sparse Regulatory Monitoring Data.

Random Forest algorithms have extensively been used to estimate ambient air pollutant concentrations. However, the accuracy of model-predicted estimates can suffer from extrapolation problems associated with limited measurement data to train the machine learning algorithms. In this study, we developed and evaluated two approaches, incorporating low-cost sensor data, that enhanced the extrapolating ability of random-forest models in areas with sparse monitoring data. Rochester, NY is the area of a pregnancy-cohort study. Daily PM2.5 concentrations from the NAMS/SLAMS sites were obtained and used as the response variable in the model, with satellite data, meteorological, and land-use variables included as predictors. To improve the base random-forest models, we used PM2.5 measurements from a pre-existing low-cost sensors network, and then conducted a two-step backward selection to gradually eliminate variables with potential emission heterogeneity from the base models. We then introduced the regression-enhanced random forest method into the model development. Finally, contemporaneous urinary 1-hydroxypyrene was used to evaluate the PM2.5 predictions generated from the two approaches. The two-step approach increased the average external validation R2 from 0.49 to 0.65, and decreased the RMSE from 3.56 µg/m3 to 2.96 µg/m3. For the regression-enhanced random forest models, the average R2 of the external validation was 0.54, and the RMSE was 3.40 µg/m3. We also observed significant and comparable relationships between urinary 1-hydroxypyrene levels and PM2.5 predictions from both improved models. This PM2.5 model estimation strategy could improve the extrapolating ability of random forest models in areas with sparse monitoring data.