Composition Of Fine Particulate Matter Research Articles

Evolution of atmospheric age of particles and its implications for the formation of a severe haze event in eastern China

Abstract. Atmospheric age reflects how long particles have been suspended in the atmosphere, which is closely associated with the evolution of air pollutants. Severe regional haze events occur frequently in China, influencing air quality, human health, and regional climate. Previous studies have explored the characteristics of mass concentrations and compositions of fine particulate matter (PM2.5) during haze events, but the evolution of atmospheric age remains unclear. In this study, the age-resolved University of California, Davis/California Institute of Technology (UCD/CIT) model was developed and applied to simulate the concentration and age distribution of PM2.5 during a severe regional haze episode in eastern China. The results indicated that PM2.5 concentrations in the North China Plain (NCP) gradually accumulated due to stagnant weather conditions during the beginning stage of the haze event. Accordingly, the atmospheric age of elemental carbon (EC), primary organic aerosol (POA), sulfate (SO42-), and secondary organic aerosol (SOA) gradually increased. The subsequent PM2.5 concentration growth was driven by the local chemical formation of nitrate (NO3-) under high relative humidity. The newly formed NO3- particles led to a decrease in the mean atmospheric age of NO3- particles. During the regional transport stage, aged particles from the NCP moved to the downwind Yangtze River Delta (YRD) region, leading to a sharp increase in PM2.5 concentrations and the average age of EC, POA, SO42-, and SOA in YRD. In contrast, the average age of NO3- and ammonium remained unchanged or even slightly decreased due to continuous local formation in the YRD region. Different evolution of the atmospheric age among these components provides a unique perspective on the formation of PM2.5 components during the regional haze event. The information can also be used for designing effective control strategies for different components of PM2.5.

Associations between Fine Particulate Matter Composition and Sources with Adverse Health Effects: A Systematic Review and Meta-Analysis

Associations between Fine Particulate Matter Composition and Sources with Adverse Health Effects: A Systematic Review and Meta-Analysis

Fine particulate matter composition in American Indian vs. Non-American Indian communities

BackgroundFine particulate matter (PM2.5) exposure is a known risk factor for numerous adverse health outcomes, with varying estimates of component-specific effects. Populations with compromised health conditions such as diabetes can be more sensitive to the health impacts of air pollution exposure. Recent trends in PM2.5 in primarily American Indian- (AI-) populated areas examined in previous work declined more gradually compared to the declines observed in the rest of the US. To further investigate components contributing to these findings, we compared trends in concentrations of six PM2.5 components in AI- vs. non-AI-populated counties over time (2000–2017) in the contiguous US. MethodsWe implemented component-specific linear mixed models to estimate differences in annual county-level concentrations of sulfate, nitrate, ammonium, organic matter, black carbon, and mineral dust from well-validated surface PM2.5 models in AI- vs. non-AI-populated counties, using a multi-criteria approach to classify counties as AI- or non-AI-populated. Models adjusted for population density and median household income. We included interaction terms with calendar year to estimate whether concentration differences in AI- vs. non-AI-populated counties varied over time. ResultsOur final analysis included 3108 counties, with 199 (6.4%) classified as AI-populated. On average across the study period, adjusted concentrations of all six PM2.5 components in AI-populated counties were significantly lower than in non-AI-populated counties. However, component-specific levels in AI- vs. non-AI-populated counties varied over time: sulfate and ammonium levels were significantly lower in AI- vs. non-AI-populated counties before 2011 but higher after 2011 and nitrate levels were consistently lower in AI-populated counties. ConclusionsThis study indicates time trend differences of specific components by AI-populated county type. Notably, decreases in sulfate and ammonium may contribute to steeper declines in total PM2.5 in non-AI vs. AI-populated counties. These findings provide potential directives for additional monitoring and regulations of key emissions sources impacting tribal lands.

Elemental Composition and Sources of Fine Particulate Matter (PM2.5) in Delhi, India.

In this study we have analysed the elemental composition of fine particulate matter (PM2.5) to examine the seasonal changes and sources of the elements in Delhi, India from January, 2017 to December, 2021. During the entire sampling period, 19 elements (Al, Fe, Ti, Cu, Zn, Cr, Ni, As, Mo, Cl, P, S, K, Pb, Na, Mg, Ca, Mn, and Br) of PM2.5 were identified by Wavelength Dispersive X-ray Fluorescence Spectrometer. The higher annual mean concentrations of S (2.29µg m-3), Cl (2.26µg m-3), K (2.05µg m-3), Ca (0.96µg m-3) and Fe (0.93µg m-3) were recorded during post-monsoon season followed by Zn > Pb > Al > Na > Cu > Ti > As > Cr > Mo > Br > Mg > Ni > Mn > and P. The annual mean concentrations of elemental composition of PM2.5 accounted for 10% of PM2.5 (pooled estimate of 5 year). Principal Component Analysis (PCA) identified the five main sources [crustal/soil/road dust, combustion (BB + FFC), vehicular emissions (VE), industrial emissions (IE) and mixed source (Ti, Cr and Mo rich-source)] of PM2.5 in Delhi, India.

Characteristics and Sources of Water-Soluble Inorganic Ions in PM2.5 in Urban Nanjing, China

In this study, the water-soluble inorganic ions (WSIIs) composition of fine particulate matter (PM2.5) was measured in the northern Nanjing city from 2015 to 2021. NH4+, NO3− and SO42− concentrations dominated in total WSIIs (Na+, NH4+, K+, Mg2+, Ca2+, Cl−, NO3− and SO42−), accounting for 87.8%. The nitrate with highest average concentration among all ions was 11.0 μg·m−3. Total WSIIs concentrations were higher in winter and lower in summer, with the highest levels in December (45.6 μg·m−3) and the lowest levels in August (15.1 μg·m−3). NO3−/SO42− was higher than 1, indicating the important contribution of mobile sources. The aerosols exhibited a weak acidic by the molar ratio of water-soluble anions and cations. Positive matrix factorization (PMF) analysis results showed that secondary nitrate and sulfate were the major pollution sources in December 2016 and 2020. The contribution of secondary nitrate in 2020 increased by 47.6% compared to 2016, while that of secondary sulfate decreased by 42.4%. The potential source contribution results demonstrated that for secondary aerosol concentrations, the contribution of regional transport from north of Anhui increased, while the contribution of local emissions decreased. The results from this study could contribute to the better prevention and control of regional air pollution in the future.

Planetary Boundary Layer Height Modulates Aerosol—Water Vapor Interactions During Winter in the Megacity of Delhi

AbstractThe Indo‐Gangetic Plain (IGP) is one of the dominant sources of air pollution worldwide. During winter, the variations in planetary boundary layer (PBL) height, driven by a strong radiative thermal inversion, affect the regional air pollution dispersion. To date, measurements of aerosol‐water vapor interactions, especially cloud condensation nuclei (CCN) activity, are limited in the Indian subcontinent, causing large uncertainties in radiative forcing estimates of aerosol‐cloud interactions. We present the results of a one‐month field campaign (February‐March 2018) in the megacity, Delhi, a significant polluter in the IGP. We measured the composition of fine particulate matter (PM1) and size‐resolved CCN properties over a wide range of water vapor supersaturations. The analysis includes PBL modeling, backward trajectories, receptor models and fire spots to elucidate the influence of PBL and air mass origins on aerosols. The aerosol properties depended strongly on PBL height and a simple power‐law fit could parameterize the observed correlations of PM1 mass, aerosol particle number and CCN number with PBL height, indicating PBL induced changes in aerosol accumulation. The low inorganic mass fractions, low aerosol hygroscopicity and high externally mixed weakly CCN‐active particles under low PBL height (100 m) indicated the influence of PBL on aerosol aging processes. In contrast, aerosol properties did not depend strongly on air mass origins or wind direction, implying that the observed aerosol and CCN are from local emissions. An error function could parameterize the relationship between CCN number and supersaturation throughout the campaign.

Composition of fine particulate matter and risk of preterm birth: A nationwide birth cohort study in 336 Chinese cities

BackgroundPotential hazards of fine particulate matter (PM2.5) constituents on preterm birth (PTB) have rarely been explored in China. ObjectiveTo quantify the associations of PM2.5 constituents with PTB. MethodsThis study was based on a nationwide cohort of 3,723,169 live singleton births delivered between January 2010 and December 2015 in China. We applied satellite-based estimates of 5 PM2.5 constituents (organic carbon; black carbon; sulfate; ammonium; and nitrate). We used Cox proportional hazards regression models adjusted for individual covariates, temperature, humidity, and seasonality to evaluate the associations. ResultsDuring the entire pregnancy, each interquartile range (29 μg/m3) increase in PM2.5 concentrations was associated with a 7% increase in PTB risk [hazard ratio (HR): 1.07; 95% confidence interval (CI): 1.07–1.08). We observed the largest effect estimates on carbonaceous components (HR: 1.09; 95% CI: 1.08–1.10 for organic carbon and black carbon). Early pregnancy appeared to be the critical exposure window for most constituents. Women who were older, exposed to second-hand smoke, overweight or obese before pregnancy, conceived during winter, and living in northern China or rural areas were more susceptible. ConclusionsCarbonaceous components of PM2.5 were associated with higher PTB risk. Findings on characteristics of vulnerability underlined targeted protections on susceptible subgroups.

Evolution of size and composition of fine particulate matter in the Delhi megacity during later winter

This study presents the first multi-site evolution analysis of fine Organic Aerosols (OA) and inorganics in the Delhi megacity (National Capital Region (NCR)) using high-resolution-particle time of flight (HR-PToF) size distribution obtained from Aerodyne HR-ToF-AMS. It provides a comprehensive view of the atmospheric dynamic processes responsible for the aerosol size and composition transformation. The measurements were performed at two different sampling sites (1) Indian Institute of Technology, Delhi (IITD), and (2) Manav Rachna International University, Faridabad (MRIU) during a late winter period (February to March 2018). Among organics, primary OA (POA) showed particle growth, whereas it was absent in secondary OA proxies. IITD was observed to have a distinct growth pattern as compared to MRIU because of high vehicular density and heterogeneity, and the presence of growth-promoting factors such as acidity and RH conditions. IITD aerosols were observed to be more acidic (ANR∼ 0.75) compared to MRIU (ANR∼1) and showed a distinct diurnal bin-wise increase during the photochemically active period (PAP). Such high acidic conditions are responsible for promoting acid-catalyzed SOA productions over the broader size bins, especially during the PAPs. Primary OA (POA) such as HOA and BBOA proxies show a diurnal growth from ∼440 to 970 nm and from ∼370 to 550 nm, at IITD and from ∼270 to 400 nm and ∼430–470 nm, at MRIU respectively. Further, OA families (amines and hydrocarbons), and inorganics such as chloride and nitrate also showed distinct concurrent diurnal growth patterns at IITD (from an MMDs of ∼380–520 nm to 650–960 nm). We have also observed a positive correlation between OA and inorganics growth and the mass fraction (MF = SOA/OA) of SOA at both sites of NCR. For 0.1 (MF) increase in SOA, the sizes of HOA, chloride, primary CH family and amines (CHN family), and secondary amines (CHON family) are increased by ∼93, 80, 64, 66, and 47 nm at IITD and ∼14, 35, 8, 11, and 16 nm at MRIU respectively. The concurrent growth of these species with the increase in the SOA concentration indicates the existence of a similar size evolution mechanism at both NCR sites, further promoting the formation of internally mixed aerosols during some phase of their evolution. This suggests that condensation is significantly governing the growth mechanism in NCR. Our study indicates the inclusion of such dynamic growth patterns arising from local prevailing conditions into the models for a better understanding of atmospheric aerosol evolution and estimation of fine particulate matter budget.

Selection of metric for indoor-outdoor source apportionment of metals in PM2.5 : mg/kg versus ng/m3.

Trends in the elemental composition of fine particulate matter (PM2.5) collected from indoor, outdoor, and personal microenvironments were investigated using two metrics: ng/m3 and mg/kg. Pearson correlations that were positive using one metric commonly disappeared or flipped to become negative when the other metric was applied to the same dataset. For example, the correlation between Mo and S in the outdoor microenvironment was positive using ng/m3 (p < 0.05) but negative using mg/kg (p < 0.05). In general, elemental concentrations (mg/kg) within PM2.5 decreased significantly (p < 0.05) as PM2.5 concentrations (µg/m3) increased—a dilution effect that was observed in all microenvironments and seasons. An exception was S: in the outdoor microenvironment, the correlation between wt% S and PM2.5 flipped from negative in the winter (p < 0.01) to positive (p < 0.01) in the summer, whereas in the indoor microenvironment, this correlation was negative year‐round (p < 0.05). Correlation analyses using mg/kg indicated that elemental associations may arise from Fe‐Mn oxyhydroxide sorption processes that occur as particles age, with or without the presence of a common anthropogenic source. Application of mass‐normalized concentration metrics (mg/kg or wt%), enabled by careful gravimetric analysis, revealed new evidence of the importance of indoor sources of elements in PM2.5.

Multi-Oxygenated Organic Compounds in Fine Particulate Matter Collected in the Western Mediterranean Area

The chemical characterization of aerosols, especially fine organic fraction, is a relevant atmospheric challenge because their composition highly depends on localization. Herein, we studied the concentration of multi-oxygenated organic compounds in the western Mediterranean area, focusing on sources and the effect of air patterns. The organic aerosol fraction ranged 3–22% of the total organic mass in particulate matter (PM)2.5. Seventy multi-oxygenated organic pollutants were identified by gas chromatography–mass spectrometry, including n-alkanones, n-alcohols, anhydrosugars, monocarboxylic acids, dicarboxylic acids, and keto-derivatives. The highest concentrations were found for carboxylic acids, such as linoleic acid, tetradecanoic acid and, palmitic acid. Biomarkers for vegetation sources, such as levoglucosan and some fatty acids were detected at most locations. In addition, carboxylic acids from anthropogenic sources—mainly traffic and cooking—have been identified. The results indicate that the organic PM fraction in this region is formed mainly from biogenic pollutants, emitted directly by vegetation, and from the degradation products of anthropogenic and biogenic volatile organic pollutants. Moreover, the chemical profile suggested that this area is interesting for aerosol studies because several processes such as local costal breezes, industrial emissions, and desert intrusions affect fine PM composition.

Fine particulate matter composition and mortality: a multi-country multi-city analysis

Background/Aim: Literature suggests that inter-regional variation in short-term associations between fine particulate air pollution (PM2.5) and mortality can be attributed to differences in particulate composition. However, empirical evidence is still limited. In this contribution, we used data from a multi-country study to evaluate how the associated short-term mortality risks varied depending on the average composition of PM2.5.Methods: We collected mortality, PM2.5, and weather data for 280 cities within 19 countries in 1985-2015 from the MCC Collaborative Research Network. Average composition of the PM2.5 fractions, namely black carbon (BC); sulfate (SO42-); ammonium (NH4+); nitrate (NO3-); organic matter (OM); sea salt (SS); and mineral dust (DUST), were obtained from the Atmospheric Composition Analysis Group. We applied a two-stage time-series analytic approach. First, for each city we modelled the linear associations of two-day moving average PM2.5 with total mortality using quasi-Poisson regression and distributed lag models. Second, we used multilevel meta-regression models to pool the city-specific estimates and evaluate the effect modification of each components. Results: In preliminary analyses, the percentage excess risk for mortality associated with a 10 μg/m3 increase in PM2.5 concentration was 0.57% (95%CI:0.26% to 0.87%) on average. We found significant increases in the mortality risk for an (interquartile range) IQR increase in the components for BC (0.24% to 0.51%, p&lt;0.001) and NH4+ (0.04% to 0.43%, p=0.016), while cities with a higher percentage of sea salt have a lower percent mortality change (0.34% to 0.10%, p&lt;0.001).Conclusion: This represents the largest study assessing effect modification in short-term mortality risks by composition of PM2.5, performed by comparing different populations across the world. Preliminary findings suggest that larger PM-mortality risks are linked to anthropogenic sources of fine particulate matter. Further steps will consider multi-components models to disentangle the effect of each component.On behalf of the MCC Collaborative Research Network

Chemical Composition and Light Absorption of PM2.5 Observed at Two Sites near a Busy Road during Summer and Winter

To examine the difference in the major chemical composition of fine particulate matter (PM2.5) between two roadway sites, 24 h integrated PM2.5 samples were simultaneously collected both 15 m (Buk-Ku District Office (BKO) site) and 150 m (Chonnam National University campus (CNU) site) away from busy roads during the summer and winter periods; these samples were taken to determine the concentrations of organic and elemental carbon (OC and EC), water-soluble organic carbon (WSOC), and water-soluble inorganic species. In addition, the real-time aerosol light absorption coefficients (Abs) were measured using a dual-spot seven-wavelength aethalometer at the CNU site to evaluate the influence of traffic and biomass burning (BB) emissions on the concentrations of organic aerosol particles. The hourly NO2 concentration was also observed at an air pollution monitoring network that is about 2 km away from the CNU site. During summer, 24 h PM2.5 concentrations (PM2.5 episode) which exceeded the Korean PM2.5 standard (35 μg/m3) were linked to increases in organic matter (OM) and SO42− concentrations that accounted for on average 35–41% and 26–30%, respectively, of the PM2.5 at the two sites. The increased SO42− concentration was most likely attributable to the inflow of long-range transported aerosols, rather than local production, as demonstrated by both the MODIS (Moderate Resolution Imaging Spectroradiometer) images and transport pathways of air masses reaching the sites. On the other hand, the OM, WSOC, and EC concentrations were directly attributable to traffic emissions at the sampling sites, as supported by the tight correlation between the OC and EC. A small difference between the absorption Ångström exponent (AAE) values calculated at wavelengths of 370–950 nm (AAE370–950nm) and 370–520 nm (AAE370–520nm), and the poor correlation of absorption coefficient by brown carbon (BrC) at 370 nm (AbsBrC370nm) with K+ (R2 = 0.00) also suggest a significant contribution of traffic emissions to OM. However, the wintertime PM2.5 episode was strongly related to the enhanced OM and NO3− concentrations, which contributed 26–28% and 22–23% of the PM2.5 concentration, respectively. It is interesting to note that there were two distinct OC/EC ratios in winter: a lower OC/EC (~3.0), which indicates a significant contribution of traffic emissions to the OC and EC, and a higher OC/EC (~6.5), which suggests an additional influence of BB emissions as well as traffic emissions at the sites. Strong correlations between the OC and EC (R2 = 0.72–0.83) and the enhanced AAE370–520nm values compared to the AAE370–950nm support that BB emissions were also an important contributor to the wintertime OM concentrations as well as traffic emissions at the two sites. A good correlation between the gaseous NO2 and NO3− and meteorological conditions (e.g., low wind speed and high relative humidity) suggest that the heterogeneous oxidation of NO2 on moist particles could be an important contributor to wintertime particulate NO3− formation at the sites. The OC concentrations during summer and winter were higher at the BKO site, with a higher traffic flow and a shorter distance from the roadway than at the CNU site. However, there were slight differences in the concentrations of secondary inorganic species (NO3−, SO42−, and NH4+) between the sites during summer and winter.

Indoor Concentration and Composition of Fine Particulate Matter (PM2.5) Near an Intense Circulated Road in an Industrial City

The purpose of the present work is to present results from a measuring campaign during February-March 2020, in Galati city, Romania, aiming the concentration of fine particulate matter (PM2.5) in air and their heavy metal concentrations, then comparing the results with the air quality determined by the national monitoring system from the same city. Results show considerable differences concerning the air quality measured in this study compared with measurements of the national monitoring system that consist in four stations placed across the city. While values recorded in this study exceeded, in some situations, the maximum target from PM2.5, the reports from the national monitoring system presented a good air quality, using a colour- and number-coding (maximum level 4 out of 6 was reported). Heavy metal concentrations of the fine particulate matters collected in this study was compared with other studies across the world, high Fe and Zn values being registered in agglomerated and industrialized cities, including the city considered in the present study, while in a study conducted in Beijing, China most higher values between all analysed heavy metals were recorded.

Hygroscopic properties and cloud condensation nuclei activity of atmospheric aerosols under the influences of Asian continental outflow and new particle formation at a coastal site in eastern Asia

Abstract. The chemical composition of fine particulate matter (PM2.5), the size distribution and number concentration of aerosol particles (NCN), and the number concentration of cloud condensation nuclei (NCCN) were measured at the northern tip of Taiwan during an intensive observation experiment from April 2017 to March 2018. The parameters of aerosol hygroscopicity (i.e., activation ratio, activation diameter and kappa of CCN) were retrieved from the measurements. Significant variations were found in the hygroscopicity of aerosols (kappa – κ – of 0.18–0.56, for water vapor supersaturation – SS – of 0.12 %–0.80 %), which were subject to various pollution sources, including aged air pollutants originating in eastern and northern China and transported by the Asian continental outflows and fresh particles emitted from local sources and distributed by land–sea breeze circulations as well as produced by processes of new particle formation (NPF). Cluster analysis was applied to the back trajectories of air masses to investigate their respective source regions. The results showed that aerosols associated with Asian continental outflows were characterized by lower NCN and NCCN values and by higher kappa values of CCN, whereas higher NCN and NCCN values with lower kappa values of CCN were observed in the aerosols associated with local air masses. Besides, it was revealed that the kappa value of CCN exhibited a decrease during the early stage of an event of new particle formation, which turned to an increasing trend over the later period. The distinct features in the hygroscopicity of aerosols were found to be consistent with the characteristics in the chemical composition of PM2.5. This study has depicted a clear seasonal characteristic of hygroscopicity and CCN activity under the influence of a complex mixture of pollutants from different regional and/or local pollution sources. Nevertheless, the mixing state and chemical composition of the aerosols critically influence the aerosol hygroscopicity, and further investigations are necessary to elucidate the atmospheric processing involved in the CCN activation in coastal areas.

Computational fluid dynamics simulation of reactive fine particulate matter in a street canyon

We developed a coupled computational fluid dynamics–chemistry model to examine the transport and chemical transformation of reactive aerosols on an urban street. The model was evaluated by comparing the results of simulations with those of observational campaigns in a street canyon in Elche, Spain. The model generally captured the composition of fine particulate matter (PM1) in the street canyon in summer and winter. However, compared with the observed concentration of PM1 in summer, the simulated concentration of PM1 was overestimated by 40%, indicating that the model predicted a weaker canyon vortex. Although the model has some bias, it reasonably reproduced the observed aerosol concentration. We also investigated the diurnal variations and spatial distribution of PM1 and its composition in the street canyon. The simulated sulfate concentrations were mostly affected by boundary transport, showing weak diurnal variations. The nitrate aerosol concentrations exhibited clear sinusoidal diurnal variations following the precursor gas, HNO3, which is mainly formed by photochemical reactions. We also found that nitrate aerosol formation was suppressed by low O3 concentrations under extreme volatile organic compound-limited conditions. The concentrations of PM1, organic carbon, and black carbon followed traffic volume curves, indicating the dominant effect of vehicular emissions on aerosols. Our sensitivity model simulation showed that considering chemical reactions significantly affects the diurnal variations of secondarily produced aerosol concentrations. These results clearly demonstrate that considering chemical production and loss is essential to investigate the diurnal variations of PM1 in street canyons, especially in winter.

Regional Estimates of Chemical Composition of Fine Particulate Matter Using a Combined Geoscience-Statistical Method with Information from Satellites, Models, and Monitors.

An accurate fine-resolution surface of the chemical composition of fine particulate matter (PM2.5) would offer valuable information for epidemiological studies and health impact assessments. We develop geoscience-derived estimates of PM2.5 composition from a chemical transport model (GEOS-Chem) and satellite observations of aerosol optical depth, and statistically fuse these estimates with ground-based observations using a geographically weighted regression over North America to produce a spatially complete representation of sulfate, nitrate, ammonium, black carbon, organic matter, mineral dust, and sea-salt over 2000-2016. Significant long-term agreement is found with cross-validation sites over North America (R2 = 0.57-0.96), with the strongest agreement for sulfate (R2 = 0.96), nitrate (R2 = 0.90), and ammonium (R2 = 0.86). We find that North American decreases in population-weighted fine particulate matter (PM2.5) concentrations since 2000 have been most heavily influenced by regional changes in sulfate and organic matter. Regionally, the relative importance of several chemical components are found to change with PM2.5 concentration, such as higher PM2.5 concentrations having a larger proportion of nitrate and a smaller proportion of sulfate. This data set offers information for research into the health effects of PM2.5 chemical components.

Emission characteristics of PM2.5-bound chemicals from residential Chinese cooking

The chemical composition of fine particulate matter (PM2.5) emitted during cooking such as polycyclic aromatic hydrocarbons (PAHs), chemical elements (especially heavy metals), organic carbon (OC), and elemental carbon (EC) are of great concern to human health in China. We collected five duplicate sets of samples of cooking emissions from a Chinese residential kitchen for the five most common cooking methods based on orthogonal design. Emission rates and concentrations of PM2.5-bound chemicals, including 16 PAHs, 21 elements, OC, and EC, were determined based on the corresponding mass fraction of species in PM2.5. The chemical profile of PM2.5 varied according to the cooking method. The results indicated that OC was the dominant component of the fine emitted particles and the emission rates ranged from 27.87 μg/min to 1916.68 μg/min. In comparison, the emission rates of EC ranged from 2.02 μg/min to 29.47 μg/min. The emission rates of the elements varied between 0.01 ng/min and 9.57 μg/min and S, Ca, Na, K, Al, Mg, and Fe were the most abundant elements in cooking profiles. The total emission rates of the 16 PAHs in PM2.5 ranged between 8.83 ng/min and 241.06 ng/min and Nap, Pyr, Chr, BghiP, and Phe were the main PAHs released from residential cooking. Thereinto, Nap and Phe could be utilized as organic markers to distinguish between cooking and other non-cooking source emissions. These findings could assist in the determination of the concentrations of PM2.5-bound chemicals in regard to emission control strategies, as well as in the assessment of health risks.

Mortality and Hospitalization Linked to Fine Particulate Matter in Canada: Is There a Trend in Risk between 2001 and 2012?

Background: The Air Health Trend Indicator is designed to estimate public health risk related to short-term exposure to air pollution and to detect trends in annual national health risks. Trends in risk may reflect changes over time in population susceptibility or in composition of fine particulate matter or more generally in the air pollution mix.Design: Daily PM2.5, mortality, morbidity, and weather data for 22 cities (about 50% of the total population) were collected for 2001-2012. A Bayesian hierarchical model was employed to estimate annual national associations by season, lag of effect, sex and age group (&amp;#8804;65 vs &amp;gt;65). Circulatory (ICD_I00-I99) and respiratory (ICD_J00-J99) causes were examined for both mortality and morbidity (hospital admissions). Results: Annual population weighted PM2.5 concentrations decreased gradually by 14% from 8 to7 µg/m3 nationally over the 12 year period. While population has increased by 13%, the ratios of mortality and morbidity to the population have decreased by 6% and 14%, respectively. In relation with PM2.5 both mortality and morbidity showed higher circulatory risk for cold season, higher respiratory risk for warm season, higher risk for seniors (&amp;gt;65), and sex-specific differences. Females were at higher risk (1.9% vs 1.1% per 1 µg/m3) for circulatory mortality but males were at higher risk (0.26% vs 0.02%) for respiratory morbidity. No apparent trends were observed in PM2.5 risk over time.Discussions: Despite downward trends in PM2.5 concentrations, mortality and morbidity rates, there was no apparent trend in PM2.5 risk. The 12-year period may be not long enough to detect trends if they exist. While the age difference in risk has been consistently reported, the sex difference has been inconsistent and thus needs further investigation. These findings could differentiate adverse effects of PM2.5 on mortality and morbidity by identifying sub-populations susceptible to PM2.5 by season, age, and sex.

The impact of wildfire smoke on compositions of fine particulate matter by ecoregion in the Western US

Epidemiological studies of wildfire PM2.5 constituents are hindered by the limited information on the population exposure to ambient PM2.5 constituents during high-pollution episodes from wildfires ("smoke waves"). The chemical composition of wildfire-related PM2.5 can be affected by different ecosystems. Current literature assessing the differences in PM2.5 pollution from wildfire smoke by ecosystemsoften analyzes air samples collected from the smokenear the center of an individual fire, but the results might not represent the exposure ofthe general publicliving away from the fire center but affected by the smoke of the fire. We assessed the population-based exposure to wildfire-related PM2.5 species by integrating monitor measurements on 29 PM2.5 species and previous findings on smoke waves during 2004-2009 in 51 Western US counties across six ecoregions. We found that across all ecoregions, smoke waves were associated with an increase in the fraction of organic carbon of total PM2.5 by 20 percentage points (95% confidence interval (CI): 17, 23), an increase in the fraction of elemental carbon by 0.99 percentage points (95% CI: 0.43, 1.6), and decreases in fractions of sulfate and crustal species. While the PM2.5 mixtures were dominated by the same source (wildfires), compositions in North American Deserts and the Great Plains during smoke waves were distinct. Besides expanding the knowledge of wildfire PM2.5, our study has implications beyond wildfires and could aid future population-based epidemiological research on PM2.5 mixtures by source and region.

Accounting for uncertainty in source‐specific exposures in the evaluation of health effects of pollution sources on daily cause‐specific mortality

Assessment of source‐specific health effects has received growing attention in air pollution epidemiology over the past decade. Regardless of inherent uncertainty in the assessment of source‐specific exposures, only a handful of previous studies coped with model uncertainty in source apportionment and/or accounted for exposure measurement error in the estimation of health effects, all under normal health outcome models. We present a source‐specific health effects evaluation approach within a Bayesian framework that can handle both parameter uncertainty and model uncertainty in source apportionment under Poisson health outcome models for low daily mortality count data. While the use of a Poisson health outcome model is apparently more appropriate for low daily mortality count data for which normal approximation is not justified, it introduces additional complexity in estimating model uncertainty. We handle this complexity by introducing appropriate latent variables. The proposed method is illustrated with simulated data and daily ambient concentrations of the chemical composition of fine particulate matter (PM2.5), weather data, and counts of deaths from pneumonia in older adults (≥65 years of age) in Houston, Texas, from January 2002 to August 2005.