Heterogeneity of coarse particles in an urban area

Physiochemistry and sources of individual particles in response to intensified controls during the 2022 Winter Olympics in Beijing

To investigate the particle sources before, during, and after the 2022 Beijing Winter Olympic and Paralympic (WOP) in Beijing, ambient particles were passively collected from January to March 2022. The physicochemical properties including morphology, size, shape parameters, and elemental compositions were analyzed by the IntelliSEM EPAS (an advanced computer-controlled scanning electron microscopy [CCSEM] system). Using the user-defined classification rules, 37,174 individual particles were automatically classified into 27 major groups and further attributed to seven major sources based on the source-associated characteristics, including mineral dust, secondary aerosol, combustion/industry, carbonaceous particles, salt-related particles, biological particles, and fiber particles. Our results showed that mineral dust (66.5%), combustion/industry (12.6%), and secondary aerosol (6.3%) were the three major sources in a wide size range of 0.2-42.8 μm. During the Winter Olympic Games period, low emission of anthropogenic particles and favorable meteorological conditions contributed to significantly improved air quality. During the Winter Paralympic Games period, more particles sourced from the dust storm, secondary formed particles, and the adverse meteorological conditions resulted in relatively worse air quality. The secondary aerosol all decreased during the competition period, while increased during the non-competition period. Sulfate-related particles had explosive growth and further aggravate the pollution degree during the non-competition period, especially under adverse meteorological conditions. These results provide microscopic evidence revealing variations of physicochemical properties and sources in response to the control measures and meteorological conditions.

Source identification and apportionment of ambient particulate matter in Beijing using an advanced computer-controlled scanning electron microscopy (CCSEM) system

The use of electron microscopy to analyze the morphology, composition, and sources of atmospheric particles has been studied extensively worldwide. However, in China, there are few studies on single-particle source analysis based on computer-controlled scanning electron microscopy (CCSEM) technology for a large number of particles, and the related technical methods need to be established and improved. In this study, ambient particulate matter (PM) was collected simultaneously from urban, suburban, and background areas of Beijing in spring 2018 and subsequently characterized using the IntelliSEM-EPAS™ technology (an advanced CCSEM software). The deposition velocity model was used to deduce the size distribution and calculate the concentration of ambient PM. Based on the k-means algorithm and empirical rules, all particles investigated were quantitatively apportioned to nine major sources, including soil/road dust, carbonates-silicates, carbonates, irregular carbonaceous particles, irregular iron oxides, combustion/industry, calcium sulfate, secondary particles, and salt-related particles. The size-resolved contributions (mass and number) of different sources were calculated. For example, soil/road dust (65.1 %), carbonate-silicate (16.1 %), and carbonate (7.1 %) were the top three sources contributing to PM₁₀ mass. This study was the first localized application of IntelliSEM-EPAS technology in China, demonstrating its great promise in PM source apportionment. For further accurate and refined source apportionment, it is essential to build localized individual particle source profiles.

Evaluation of impact of "2+26″ regional strategies on air quality improvement of different functional districts in Beijing based on a long-term field campaign

Consecutive measurements of ambient fine particulate matter (PM_2.5) from February 2016 to April 2018 have been performed at four representative sites of Beijing to evaluate the impact of "2 + 26" regional strategies implemented in 2017 for air quality improvement in non-heating period (2017NH) and heating period (2017H). The decrease of PM_2.5 were significant both in 2017NH (20.2% on average) and 2017H (43.7% on average) compared to 2016NH and 2016H, respectively. Eight sources were resolved at each site from the PMF source apportionment including secondary nitrate, traffic, coal combustion, soil dust, road dust, sulfate, biomass/waste burning and industrial process. The results show that the reductions of industrial process, soil dust, and coal combustion were most effective among all sources at each site after the regional strategies implementation with the large reductions in potential source areas. The decrease of coal combustion in 2017NH were larger than 2017H at all sites while that of soil dust and industrial sources were the opposite. Insignificant reduction of coal combustion contribution at the suburban site in the heating period indicated that rural residential coal burning need further control. The industrial source control in the suburbs were least effective compared with other districts. Traffic was the largest contributer at each site and control of traffic emissions were more effective in 2017H than 2017NH. The local nature and increase of biomass/waste burning contributions emphasized the effect of fireworks and bio-fuel use in rural areas and incinerator emissions in urban districts. Secondary nitrate and sulfate were mainly impacted by the regional transport from southern adjacent areas and favorable meteorological conditions played an important part in the PM_2.5 abatements of 2017H. Secondary nitrate became a more major role in the air pollution process because of the larger decrease of sulfate. Finally suggestions for future control are made in this study.

Spatial-temporal variability of aerosol sources based on chemical composition and particle number size distributions in an urban settlement influenced by metallurgical industry

The Moravian-Silesian region of the Czech Republic with its capital city Ostrava is a European air pollution hot spot for airborne particulate matter (PM). Therefore, the spatiotemporal variability assessment of source contributions to aerosol particles is essential for the successful abatement strategies implementation. Positive Matrix Factorization (PMF) was applied to highly-time resolved PM_0.15-1.15 chemical composition (1 h resolution) and particle number size distribution (PNSD, 14 nm - 10 μm) data measured at the suburban (Ostrava-Plesná) and urban (Ostrava-Radvanice) residential receptor sites in parallel during an intensive winter campaign. Diel patterns, meteorological variables, inorganic and organic markers, and associations between the chemical composition factors and PNSD factors were used to identify the pollution sources and their origins (local, urban agglomeration and regional). The source apportionment analysis resolved six and four PM_0.15-1.15 sources in Plesná and Radvanice, respectively. In Plesná, local residential combustion sources (coal and biomass combustion) followed by regional combustion sources (residential heating, metallurgical industry) were the main contributors to PM_0.15-1.15. In Radvanice, local residential combustion and the metallurgical industry were the most important PM_0.15-1.15 sources. Aitken and accumulation mode particles emitted by local residential combustion sources along with common urban sources (residential heating, industry and traffic) were the main contributors to the particle number concentration (PNC) in Plesná. Additionally, accumulation mode particles from local residential combustion sources and regional pollution dominated the particle volume concentration (PVC). In Radvanice, local industrial sources were the major contributors to PNC and local coal combustion was the main contributor to PVC. The source apportionment results from the complementary datasets elucidated the relevance of highly time-resolved parallel measurements at both receptor sites given the specific meteorological conditions produced by the regional orography. These results are in agreement with our previous studies conducted at this site. Graphical abstract.

Enhancing the interpretation of in vitro bioaccessibility data by using computer controlled scanning electron microscopy (CCSEM) at the individual particle level

The adverse health effects resulting from exposure to contaminated soil on internally displaced populations in Mitrovica, Kosovo can be determined by how the potentially harmful elements are bound in the soils. Certainly this was the case for Pb, present at concentrations ranging from 624 to 46,900 mg/kg, and at bioaccessibilities ranging <5% to nearly 90%. To assess why the soil Pb might differ so markedly in terms of its bioaccessibility, computer controlled scanning electron microscopy (CCSEM) was employed to determine how the Pb was associated with other elements at the individual particle (IP) level in soils from the area. It was found that the Pb-bearing particle types were, for the most part, different in each sample. We consider these differences as the main control on Pb bioaccessibility in these soils. Pb solubility at the IP level was evaluated by examining Pb-particles from these soils in the electron microscope before and after successive immersions in a simulated gastric fluid. This analysis (differential IP analysis) confirmed the CCSEM characterization that Pb associated with other higher atomic number elements (Fe, Zn, Cu and Ni) was less soluble than when it was present as isolated phases (e.g., as carbonate) or when it was bound with lower atomic number elements (Na, Al, Si, K, Ca). The heterogeneity in solubility and composition of the Pb-particles suggested that the Pb originated from a range of different anthropogenic activities. The nature of these different anthropogenic activities created the wide differences in Pb-bioaccessibilty by producing Pb bound in many different forms in the soil particles. This type of Pb-particle characterization highlights the role CCSEM analysis, and IP acid extraction, can play in providing supporting evidence alongside bioaccessibility data for applications in human health risk assessment and management of contaminated soil.

Performance of Passive Samplers Analyzed by Computer-Controlled Scanning Electron Microscopy to Measure PM10-2.5

We report on the precision and accuracy of measuring PM10-2.5 and its components with particles collected by passive aerosol samplers and analyzed by computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy. Passive samplers were deployed for week-long intervals in triplicate and colocated with a federal reference method sampler at three sites and for 5 weeks in summer 2009 and 5 weeks in winter 2010 in Cleveland, OH. The limit of detection of the passive method for PM10-2.5 determined from blank analysis was 2.8 μg m(-3). Overall precision expressed as root-mean-square coefficient of variation (CVRMS) improved with increasing concentrations (37% for all samples, n = 30; 19% for PM10-2.5 > 10 μg m(-3), n = 9; and 10% for PM10-2.5 > 15 μg m(-3), n = 4). The linear regression of PM10-2.5 measured passively on that measured with the reference sampler exhibited an intercept not statistically different than zero (p = 0.46) and a slope not statistically different from unity (p = 0.92). Triplicates with high CVs (CV > 40%, n = 5) were attributed to low particle counts (and mass concentrations), spurious counts attributed to salt particles, and Al-rich particles. This work provides important quantitative observations that can help guide future development and use of passive samplers for measuring atmospheric particulate matter.

Elevated Concentrations of Lead in Particulate Matter on the Neighborhood-Scale in Delhi, India As Determined by Single Particle Analysis

High mass concentrations of atmospheric lead particles are frequently observed in the Delhi, India metropolitan area, although the sources of lead particles are poorly understood. In this study, particles sampled across Delhi (August - December 2008) were analyzed by computer-controlled scanning electron microscopy with energy dispersive X-ray spectroscopy (CCSEM-EDX) to improve our understanding of the spatial and physicochemical variability of lead-rich particles (>90% lead). The mean mass concentration of lead-rich particles smaller than 10 μm (PM10) was 0.7 μg/m(3) (1.5 μg/m(3) std. dev.) with high variability (range: 0-6.2 μg/m(3)). Four samples (16% of 25 samples) with PM10 lead-rich particle concentrations >1.4 μg/m(3) were defined as lead events and studied further. The temporal characteristics, heterogeneous spatial distribution, and wind patterns of events, excluded regional monsoon conditions or common anthropogenic sources from being the major causes of the lead events. Individual particle composition, size, and morphology analysis indicate informal recycling operations of used lead-acid batteries as the likely source of the lead events. This source is not typically included in emission inventories, and the observed isolated hotspots with high lead concentrations could represent an elevated exposure risk in certain neighborhoods of Delhi.

Cumulative health risk assessment of halogenated and parent polycyclic aromatic hydrocarbons associated with particulate matters in urban air

Halogenated polycyclic aromatic hydrocarbons (HPAHs) have been reported to occur widely in urban air. Nevertheless, knowledge about the human health risk associated with inhalation exposure to HPAHs is scarce so far. In the present study, nine HPAHs and 16 PAHs were determined in atmospheric particulate matter (PM) collected from Shenzhen, China to address this issue. Concentrations of Σ9HPAHs varied from 0.1 to 1.5 ng/m(3) and from 0.09 to 0.4 ng/m(3) in PM10 and PM2.5 samples, respectively. As for individuals, 9-bromoanthracene, 7-bromobenz(a)anthracene, and 9,10-dibromoanthracene were the dominant congeners. Levels of Σ16PAHs in PM10 and PM2.5 samples ranged from 3.2 to 81 ng/m(3) and from 2.8 to 85 ng/m(3), respectively. Among individual PAHs, chrysene, benzo[b]fluoranthene, and indeno[1,2,3-c,d]pyrene were the main congeners. According to the season, concentrations of HPAHs and PAHs in atmospheric PM10/PM2.5 samples show a similar decreasing trend with an order: winter>autumn>spring>summer. The daily intake (DI) of PM10/PM2.5-bound HPAHs and PAHs were estimated. Our results indicated that children have the highest DI levels via inhalation exposure. The incremental lifetime cancer risk (ILCR) induced by PM10/PM2.5-bound HPAHs and PAHs were calculated. The ILCR values showed a similar decreasing trend with an order: adults>children>seniors>adolescent. Overall, the ILCR values induced by HPAHs and PAHs were far below the priority risk level (10(-4)), indicating no obvious cancer risk. To our knowledge, this is the first study to investigate the human health risk associated with inhalation exposure to PM10/PM2.5-bound HPAHs.

Errors in coarse particulate matter mass concentrations and spatiotemporal characteristics when using subtraction estimation methods

In studies of coarse particulate matter (PM10-2.5), mass concentrations are often estimated through the subtraction of PM2.5 from collocated PM10 tapered element oscillating microbalance (TEOM) measurements. Though all field instruments have yet to be updated, the Filter Dynamic Measurement System (FDMS) was introduced to account for the loss of semivolatile material from heated TEOM filters. To assess errors in PM10-2.5 estimation when using the possible combinations of PM10 and PM2.5 TEOM units with and without FDMS, data from three monitoring sites of the Colorado Coarse Rural-Urban Sources and Health (CCRUSH) study were used to simulate four possible subtraction methods for estimating PM10-2.5 mass concentrations. Assuming all mass is accounted for using collocated TEOMs with FDMS, the three other subtraction methods were assessed for biases in absolute mass concentration, temporal variability, spatial correlation, and homogeneity. Results show collocated units without FDMS closely estimate actual PM10-2.5 mass and spatial characteristics due to the very low semivolatile PM10-2.5 concentrations in Colorado. Estimation using either a PM2.5 or PM10 monitor without FDMS introduced absolute biases of 2.4 microg/m3 (25%) to -2.3 microg/m3 (-24%), respectively. Such errors are directly related to the unmeasured semivolatile mass and alter measures of spatiotemporal variability and homogeneity, all of which have implications for the regulatory and epidemiology communities concerned about PM10-2.5. Two monitoring sites operated by the state of Colorado were considered for inclusion in the CCRUSH acute health effects study, but concentrations were biased due to sampling with an FDMS-equipped PM2.5 TEOM and PM10 TEOM not corrected for semivolatile mass loss. A regression-based model was developed for removing the error in these measurements by estimating the semivolatile concentration of PM2.5 from total PM2.5 concentrations. By estimating nonvolatile PM2.5 concentrations from this relationship, PM10-2.5 was calculated as the difference between nonvolatile PM10 and PM2.5 concentrations.

Particulate matter source apportionment in a village situated in industrial region of Central Europe

The bilinear receptor model positive matrix factorization (PMF) was used to apportion particulate matter with an aerodynamic diameter of 1-10 microm (PM1-10) sources in a village, Brezno, situated in an industrial region of northern Bohemia in Central Europe. The receptor model analyzed the data sets of 90- and 60-min integrations of PM1-10 mass concentrations and elemental composition for 27 elements. The 14-day sampling campaigns were conducted in the village in summer 2008 and winter 2010. Also, to ensure seasonal and regional representativeness of the data sets recorded in the village, the spatial-temporal variability of the 24-hr PM10 and PM1-10 within 2008-2010 in winter and summer across the multiple sites was evaluated. There were statistically significant interseasonal differences of the 24-hr PM data, but not intrasummer or intrawinter differences of the 24-hr PM1-10 data across the multiple sites. PMF resolved seven sources of PM1-10. They were high-temperature coal combustion; combustion in local heating boilers; marine aerosol; mineral dust; primary biological/wood burning; road dust, car brakes; and gypsum. The main summer factors were assigned to mineral dust (38.2%) and primary biological/wood burning (33.1%). In winter, combustion factors dominated (80%) contribution to PM1-10. The conditional probability function (CPF) helped to identified local sources of PM1-10. The source of marine aerosol from the North Sea and English Channel was indicated by the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT).

Coarse particles and respiratory emergency department visits in California

Although respiratory disease has been strongly connected to fine particulate air pollution (particulate matter <2.5 μm in diameter (PM2.5)), evidence has been mixed regarding the effects of coarse particles (particulate matter from 2.5 to 10 μm in diameter), possibly because of the greater spatial heterogeneity of coarse particles. In this study, we evaluated the relationship between coarse particles and respiratory emergency department visits, including common subdiagnoses, from 2005 to 2008 in 35 California counties. A time-stratified case-crossover design was used to help control for time-invariant confounders and seasonal influences, and the study population was limited to those residing within 20 km of pollution monitors to mitigate the influence of spatial heterogeneity. Significant associations between respiratory emergency department visits and coarse particle levels were observed. Asthma visits showed associations (for 2-day lag, excess risk per 10 μg/m³ = 3.3%, 95% confidence interval: 2.0, 4.6) that were robust to adjustment by other common air pollutants (particles <2.5 μm in diameter, ozone, nitrogen dioxide, carbon monoxide, and sulfur dioxide). Pneumonia and acute respiratory infection visits were not associated, although some suggestion of a relationship with chronic obstructive pulmonary disease visits was present. Our results indicate that coarse particle exposure may trigger asthma exacerbations requiring emergency care, and reducing exposures among asthmatic persons may provide benefits.

Single-particle SEM-EDX analysis of iron-containing coarse particulate matter in an urban environment: sources and distribution of iron within Cleveland, Ohio

The physicochemical properties of coarse-mode, iron-containing particles and their temporal and spatial distributions are poorly understood. Single-particle analysis combining X-ray elemental mapping and computer-controlled scanning electron microscopy (CCSEM-EDX) of passively collected particles was used to investigate the physicochemical properties of iron-containing particles in Cleveland, OH, in summer 2008 (Aug-Sept), summer 2009 (July-Aug), and winter 2010 (Feb-March). The most abundant classes of iron-containing particles were iron oxide fly ash, mineral dust, NaCl-containing agglomerates (likely from road salt), and Ca-S containing agglomerates (likely from slag, a byproduct of steel production, or gypsum in road salt). The mass concentrations of anthropogenic fly ash particles were highest in the Flats region (downtown) and decreased with distance away from this region. The concentrations of fly ash in the Flats region were consistent with interannual changes in steel production. These particles were observed to be highly spherical in the Flats region, but less so after transport away from downtown. This change in morphology may be attributed to atmospheric processing. Overall, this work demonstrates that the method of passive collection with single-particle analysis by electron microscopy is a powerful tool to study spatial and temporal gradients in components of coarse particles. These gradients may correlate with human health effects associated with exposure to coarse-mode particulate matter.