In the past decade, the global community has expressed growing concern over environmental microplastics, recognizing them as emerging pollutants with potential threats to human health and ecosystems. To address this concern, the development of analytical methods for quantifying airborne microplastic particles stands out as a crucial research priority. Although pyrolysis-gas chromatography-mass spectrometry (Py-GC/MS) has demonstrated its efficacy in identifying microplastics, a significant gap remains in the determination of tire-related polymers. Also, the availability of data on atmospheric conditions is scarce. This study focuses on the direct analysis of 6 polymers, polyethylene, polypropylene, polystyrene, polyethylene terephthalate, styrene-butadiene rubber, and butadiene rubber, in the matrix of atmospheric particulate matter and indoor house dust, employing off-line pyrolysis GC/MS. Comprehensive investigations into the pyrolysis products of each polymer have been conducted. The proposed method showed remarkable sensitivity, reproducibility (with a relative standard deviation of less than 16% for all polymers except PET), and recovery rates ranging from 91% to 136%. Furthermore, this method successfully identified and quantified target polymers in atmospheric particles and dust samples. Tire-related polymers and polystyrene were found to predominate in particulate matter samples, while polyethylene terephthalate dominated in indoor house dust. This off-line approach demonstrated significant consistency in pyrolysates compared to online methods documented in prior studies, offering a reliable and accurate quantification of microplastic materials.

This study provides a short-term, dry-weather multi-compartment assessment of microplastic (MP) contamination in the Choghakhor Wetland, a vital freshwater ecosystem in western Iran. We quantified MPs in air, subsurface water, the surface water microlayer (SML), and sediments and developed a first-order mass-balance framework to clarify transport and fate. The SML showed much higher MP concentrations than the subsurface water when converted to volumetric units, while method-specific SML estimates varied among approaches (4.4-13.8 MP m(-)& sup2; using a glass tube; 196-982 MP m(-)& sup2; using a sieve; and 130-1754 MP m(-)& sup2; using filter paper). Subsurface water contained 0.083-1.5 MP L-& sup1;, and the two sediment samples contained 60-400 MP kg(-)& sup1;. Atmospheric deposition during the monitored intervals reached 2363 MP m(-)& sup2; h(-)& sup1;. Flux analysis indicated that dry-weather influx exceeded observed outflux by more than three orders of magnitude. Using the conservative combined-outlet scenario, the wetland residence time was at least 168 days, whereas a water-only outlet scenario yielded similar to 344 days. FLEXPART suggested that road dust dominated modeled source contributions, with smaller agricultural and soil-related contributions, although site-specific attribution remains model-based. These findings identify wetlands as important sinks and reservoirs of MPs, while emphasizing that the present results represent a dry-weather baseline rather than seasonal or annual conditions.

We investigated how various sources contributed to observations of over 40 trace gas and particulate species in a typical Fairbanks residential neighborhood during the Alaskan Layered Pollution and Chemical Analysis campaign in January–February 2022. Aromatic volatile organic compounds (VOCs) accounted for ∼50% of measured VOCs (molar ratio), while methanol and ethanol accounted for ∼34%. The total wintertime VOC burden and contribution from aromatics were much higher than other US urban areas. Based on diel cycles and positive matrix factorization (PMF) analyses, we find traffic was the largest source of NO, CO, black carbon, and aromatic VOCs. Formic and acetic acid, hydroxyacetone, furanoids, and other VOCs were primarily attributed to residential wood combustion (RWC). Formaldehyde was one of several VOCs featuring significant contributions from multiple sources: RWC (∼35%), aging (∼30%), traffic (∼21%), and heating oil combustion (HO, ∼14%). PMF solutions assigned primary fine particulate matter to RWC (10%–30%), traffic (25%–40%), and HO (30%–60%), the latter likely reflecting high sulfur emissions from older furnaces and fast secondary chemistry. Despite cold and dark conditions, secondary processes impacted many trace gas and particle species' budget by ±10%–20% and more in some cases. Transport of O 3 ‐rich regional air into Fairbanks contributed to aging, specifically NO 3 radical formation. This work highlights a long‐term trend observed in Fairbanks: increasing traffic and decreasing RWC relative contributions as total pollution decreases. Fairbanks exports a relatively fresh pollutant mixture to the regional arctic, the fate of which warrants future study.

Accounting for exposure measurement errors has been recognized as a crucial problem in environmental epidemiology for over two decades. Bayesian hierarchical models offer a coherent probabilistic framework for evaluating associations between environmental exposures and health effects, which take into account exposure measurement errors introduced by uncertainty in the estimated exposure as well as spatial misalignment between the exposure and health outcome data. While two-stage Bayesian analyses are often regarded as a good alternative to fully Bayesian analyses when joint estimation is not feasible, there has been minimal research on how to properly propagate uncertainty from the first-stage exposure model to the second-stage health model, especially in the case of a large number of participant locations along with spatially correlated exposures. We propose a scalable two-stage Bayesian approach, called a sparse multivariate normal (sparse MVN) prior approach, based on the Vecchia approximation for assessing associations between exposure and health outcomes in environmental epidemiology. We compare its performance with existing approaches through simulation. Our sparse MVN prior approach shows comparable performance with the fully Bayesian approach, which is a gold standard but is impossible to implement in some cases. We investigate the association between source-specific exposures and pollutant (nitrogen dioxide (NO_2))-specific exposures and birth outcomes for 2012 in Harris County, Texas, using several approaches, including the newly developed method.

Water samples were collected during each of the 2012–2019 Cooperative Science and Monitoring Initiative (CSMI) cruises aboard the U.S. EPA R/V Lake Guardian as part of the Great Lakes Fish Monitoring and Surveillance Program (GLFMSP) lower food web contaminant assessment. The CSMI rotates around each of the Great Lakes in a 5-year cycle providing top-to-bottom biological, chemical, and physical environmental assessments, including dissolved-phase surface water studies at two sample locations. Average polychlorinated biphenyl (∑PCB) concentrations across the Great Lakes was 268 pg/L with a station range of 72 pg/L (Keweenaw Point-Lake Superior) to 834 pg/L (Middle Bass Island-Lake Erie). The highest average Great Lakes concentration (pg/L-sample year) were measured in Lake Erie (645 pg/L-2014) and decreased in the order of Lake Huron (378 pg/L-2012) > Lake Erie (364 pg/L-2019) > Lake Ontario (300 pg/L-2013) > Lake Michigan (125 pg/L-2015) > Lake Huron (123 pg/L-2017) > Lake Superior (74 pg/L-2016). Lake Erie registered a 44 % reduction over the 2014–2019 period, attributed to sediment remediation in the late-1990's on the Detroit River, whereas Lake Huron exhibited a 67 % decrease over the 2012–2017 sample period. Our results indicate that dissolved-phase PCB water concentrations in Lake Ontario have significantly increased, rebounding from a low-point in the late-1990's likely due to the bioenergetic diversion of dissolved- and particulate-phase PCBs into the benthic food web by invasive zebra and quagga mussel colonization. Trend analyses uncovered breakpoints in the early 1990's documenting significantly slowing rates of PCB declines for both Lakes Superior and Michigan.

Multiple regulations have been promulgated to improve air quality, and previous studies have used an accountability chain to evaluate the effects of these regulations on emission levels, air quality, and human health. However, quantifying these impacts through the accountability chain is complex due to interactions between multiple factors that can influence the efficacy of control policies and introduce uncertainties at each step. We evaluated and quantified the impact of emission controls on electricity generating units (EGU) and motor vehicle sources on emissions and air quality via Generalized Additive Models. These GAMs have minimal bias (around 10-5 to 10- 2 mu g/m3 or ppbV) and r2 values for daily concentrations ranging from 0.4 to 0.7 Counterfactual air pollutant concentrations, in the absence of EGU and mobile source regulations, were calculated using estimated counterfactual emissions for the period 2005 to 2019 in Atlanta, New York City, and California's South Coast Air Basin. Counterfactual air pollutant concentrations indicated that the effects of regulations on air pollutants varied depending on the season and location. Predicted counterfactual air pollutant concentrations were generally 2-12 times higher than the measured concentrations at these sites, except for ozone. The impact of regulations on ozone concentrations typically resulted in reduced peak ozone values in the summer, but increased concentrations in the winter. Monte Carlo modeling found small to modest uncertainties, depending on the pollutant, location and regulations assessed. Counterfactual concentrations predicted in this project will be used in the assessment of the trends of toxicity in PM2.5.

We examined the association between air pollution and neutralizing antibody responses to COVID-19 vaccination in participants enrolled in a phase 3 clinical trial. Seventy-four adults were vaccinated with two doses of the AstraZeneca ChAdOx1 vectored vaccine (AZD1222) (5 x 1010 viral particles) at baseline and day 29, between Aug 28, 2020, to Jan 15, 2021, in Monroe County, NY. SARS-CoV-2 pseudovirus neutralizing ID50 titers (NAb) and total spike protein IgG were assessed at baseline and 15, 29, 43, 57 and 90 days after vaccination. In this pilot study, each participant's dates of neutralization titers were matched to Monroe County ambient concentrations of fine particles (PM2.5; ≤ 2.5 µm), black carbon (BC; marker of traffic), among other particulate and gaseous pollutants. Using linear mixed models, we estimated the association between each interquartile range (IQR) difference in air pollutant concentrations in the 14 days prior to blood collection and antibody responses at each post vaccination timepoint. Though not statistically significant, we observed a 23% reduction in NAb titer (95% CI: -67%, 79%) measured on day 43 (i.e., 14 days after second vaccination) associated with each 0.32 µg/m3 increase in BC concentrations in the prior 14 days. We also observed a 42% increase in spike protein IgG (95% CI: -16%, 141%) measured on day 15 (i.e., 14 days after primary vaccination) associated with each 0.26 µg/m3 increase in BC concentrations in the 14 days prior. A similar pattern for total spike protein IgG was observed at day 29 (42%; 95% CI: -22%, 157%) and 90 (43%; 95% CI: -11%, 127%). Future research will need to explore the possible association between air pollution exposure and antibody response to SARS-CoV-2 vaccination given the potential for compromised vaccine efficacy.

Metal (loid)s are widely present in the environment and affect human health, especially the central nervous system. Dementia is a syndrome characterized by cognitive decline that can be caused by neurological degeneration. We aimed to review the current state of knowledge with respect to associations between various metal(loid)s in different biospecimens and dementia. We searched PubMed, Embase, and Web of Science for original research in English up to January 15th, 2025. We evaluated the synthesized using random effects and cumulative meta-analysis and assessed the risk of bias using the Newcastle-Ottawa Scale tool and the certainty of evidence by the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. Of the 7390 publications identified, 82 articles met the eligibility criteria. In the present meta-analysis, hair iron, serum zinc, cerebrospinal fluid zinc, and blood selenium showed significant negative associations with dementia. Urine iron, serum lead, and serum aluminum were significantly positively associated with dementia. It may be hypothesized that zinc/selenium/iron deficiency was the pathogenic factor for the onset or development of dementia. Increasing serum lead/aluminum may lead to dementia, especially in lower economic level countries. Because of the high heterogeneity, methodological limitations, and quality of evidence, the present findings should be interpreted with caution. The review was prospectively registered on PROSPERO CRD42024502024.

Accurately estimating aviation emissions is crucial for developing strategies to mitigate environmental impacts. However, aircraft's unique four-dimensional operation characteristics and limitations in aircraft-to-ground communication technology pose challenges for precise and dynamic emissions estimation. This study proposed a hybrid machine learning approach for realtime aviation emissions estimation based on four-dimensional flight trajectories. Using Qingdao Airport as a case study, we generated a high-resolution emission inventory and explored the emission reduction potential in flight operations. Results demonstrated that: (1) our approach achieved higher prediction accuracy for real-time fuel flow rates and emissions than conventional models, owing to a comprehensively considering the nonlinear relationships between aircraft performance and trajectories under complex operating conditions; (2) emission estimation results from our approach were 22 %-78 % higher than the ICAO reference values; (3) an emission reduction potential of 5 %-65 % was identified in flight operations. Finally, four policy recommendations were developed to reduce emissions from airport flight activities.

Background: Sex steroid hormones are critical for maintaining pregnancy and optimal fetal development. Air pollutants are potential endocrine disruptors that may disturb sex steroidogenesis during pregnancy, potentially leading to adverse health outcomes. Methods: In the Environmental influences on Child Health Outcomes Understanding Pregnancy Signals and Infant Development pregnancy cohort (Rochester, NY), sex steroid concentrations were collected at study visits in early-, mid-, and late-pregnancy in 299 participants. Since these visits varied by the gestational age at blood draw, values were imputed at 14, 22, and 30 weeks gestation. Daily NO2 and PM2.5 concentrations were estimated using random forest models, with daily concentrations from each 1-km2 grid containing the subject’s residence. Associations between gestational week mean NO2 and PM2.5 concentrations and sex steroid concentrations were examined utilizing distributed lag nonlinear models. Results: Each interquartile range (IQR = 9 ppb) increase in NO2 during weeks 0–5 was associated with higher early-pregnancy total testosterone levels (cumulative β = 0.45 ln[ng/dl]; 95% CI = 0.07, 0.83), while each IQR increase in NO2 during weeks 12–14 was associated with lower early-pregnancy total testosterone levels (cumulative β = −0.27 ln[ng/dl]; 95% CI = −0.53, −0.01). Similar NO2 increases during gestational weeks 0–14 were associated with higher late-pregnancy estradiol concentrations (cumulative β = 0.29 ln[pg/ml]; 95% CI = 0.10, 0.49), while each IQR increase in NO2 concentrations during gestational weeks 22–30 was associated with lower late-pregnancy estradiol concentrations (cumulative β = −0.18 ln[pg/ml]; 95% CI = −0.34, −0.02). No associations with PM2.5 were observed, except for an IQR increase in PM2.5 concentrations (IQR = 4 µg/m3) during gestational weeks 5–11 which was associated with lower late-pregnancy estriol levels (cumulative β = −0.16 ln[ng/ml]; 95% CI = −0.31, −0.00). Conclusions: Residential NO2 exposure was associated with altered sex steroid hormone concentrations during pregnancy with some indication of potential compensatory mechanisms.

The apportionment of equivalent black carbon (eBC) to combustion sources from liquid fuels (mainly fossil; eBC(LF)) and solid fuels (mainly non-fossil; eBC(SF)) is commonly performed using data from Aethalometer instruments (AE approach). This study evaluates the feasibility of using AE data to determine the absorption Angstrom exponents (AAEs) for liquid fuels (AAE(LF)) and solid fuels (AAE(SF)), which are fundamental parameters in the AE approach. AAEs were derived from Aethalometer data as the fit in a logarithmic space of the six absorption coefficients (470-950 nm) versus the corresponding wavelengths. The findings indicate that AAE(LF) can be robustly determined as the 1st percentile (PC1) of AAE values from fits with R-2 > 0.99. This R-2-filtering was necessary to remove extremely low and noisy-driven AAE values commonly observed under clean atmospheric conditions (i.e., low absorption coefficients). Conversely, AAE(SF) can be obtained from the 99th percentile (PC99) of unfiltered AAE values. To optimize the signal from solid fuel sources, winter data should be used to calculate PC99, whereas summer data should be employed for calculating PC1 to maximize the signal from liquid fuel sources. The derived PC1 (AAE(LF)) and PC99 (AAE(SF)) values ranged from 0.79 to 1.08, and 1.45 to 1.84, respectively. The AAE(SF) values were further compared with those constrained using the signal at mass-to-charge 60 (m/z 60), a tracer for fresh biomass combustion, measured using aerosol chemical speciation monitor (ACSM) and aerosol mass spectrometry (AMS) instruments deployed at 16 sites. Overall, the AAE(SF) values obtained from the two methods showed strong agreement, with a coefficient of determination (R-2) of 0.78. However, uncertainties in both approaches may vary due to site-specific sources, and in certain environments, such as traffic-dominated sites, neither approach may be fully applicable.

Urbanized basins are widely recognized as hotspots‌ of particulate matter (PM) pollution. Characterizing the vertical stratification of PM in these regions is essential to elucidate the influence of regional air pollutant transport, dynamics of planetary boundary layer, and pollution-meteorology feedbacks. Using Mount Emei (500-3100 m a.s.l.) as a natural observation tower, this study investigated the composition and sources of PM, ‌along with‌ the six criteria pollutants (PM2.5, PM10, O3, SO2, CO, and NO2) across three atmospheric layers within the Sichuan Basin (SCB). The monitoring sites are located in the planetary boundary layer (M-base: 550 m a.s.l.), ‌the‌ cloud/fog-active layer (M-upper: 2400 m a.s.l.), and ‌the‌ free troposphere (M-summit: 3100 m a.s.l.). The results revealed that PM at M-base exhibited typical urban pollution characteristics, with SNA (i.e., SO42-, NO3-, and NH4+) accounting for ∼60 % of total suspended particles (TSP) mass annually, ‌primarily driven‌ by anthropogenic emissions. Autumn/wintertime PM extremes at M-base resulted from the synergistic effects of increased emissions, stagnant meteorology, and enhanced aqueous-phase reactions under high relative humidity (>80 %)‌. As altitude increased, PM concentrations declined, primarily due to more effective wet scavenging and reduced anthropogenic influence. At M-upper and M-summit, the contributions of SNA reduced to ∼35 % of TSP mass annually, ‌whereas‌ contributions from biomass burning and crustal dust increased. ‌Unlike M-base‌, PM concentrations at M-summit peaked in spring, primarily due to transboundary influences, particularly the biomass burning in neighbouring countries and ‌dust from Gobi/desert in northwestern China‌. Overall, the deep-basin topography imposed three regulatory mechanisms‌ on PM pollution, including ground-level PM enhancement through chemical-meteorological interactions‌, ‌upper-altitude cloud/fog/precipitation and PM interactions, and dominance of transboundary pollutant transport in the upper/free-troposphere‌. This study provides a mechanistic basis for vertically stratified air quality management in the SCB, ‌as well as‌ other similar terrain regions worldwide.

Spatial and temporal variability of equivalent black carbon (eBC) mass concentrations were studied using Aethalometers (AE33 and AE21) at 10 sites, including 5 urban and 5 near-road across the south coast of California and New York-Rochester. Statistical methods were applied to perform intra-urban and multi-site comparisons. Given that nominal eBC values provided by the Aethalometer were significantly overestimated, eBC concentrations were corrected using an appropriate multiple-scattering enhancement correction factor (C0) to accurately calculate light absorption. Annual and seasonal variations highlighted the significant contributions of traffic emissions to eBC mass concentrations at all sites. Source apportionment using the Aethalometer approach demonstrated that fuel combustion-primarily from gasoline and diesel vehicles- accounted for up to 80% of eBC. Emission sources were found to be largely region specific. Our findings suggest that the implementation of restrictive regulations aimed at reducing gasoline and diesel vehicle emissions, such as California's Tier 3 (SULEV, 2015) and New York (2017), has led to a higher proportion of cleaner, emission-controlled vehicles in the South Coast Air Basin compared to Rochester. However, the effects of these measures may require more time to be fully observed in traffic-polluted areas across the US.

Nontargeted screening (NTS) of halogenated contaminants in biota is part of the routine monitoring of the Great Lakes ecosystem. NTS can give insight into new chemicals with possible persistent, bioaccumulative, and toxic (PBT) properties and help quantify known PBT's degradation and transformation products. The most common ionization technique for NTS is electron impact ionization (EI) due to the consistent and easily standardized fragmentation patterns. This research uses electron capture negative ionization (ECNI) as a complementary technique to broaden the range of halogenated contaminants detected in the Great Lakes. ECNI has higher sensitivity and selectivity to halogenated compounds compared to EI. GC × GC-HR-ToF MS with a multimode ion source (MMS) offers consecutive runs in EI and ECNI modes using the same chromatographic setup, facilitating retention time alignment. The exact mass measurements help in identifying compounds found only in ECNI. A total of 85 novel halogenated features were detected, 78% of which were detected only in ECNI. Only 9% of the features were detected in both modes, indicating that ECNI is a necessary complementary technique for NTS of halogenated features.

PM2.5 species, PAHs and VOCs were sampled between 2013 and 2019 once every three or six days for a period of 24 hours in an industrialized city in Ontario, Canada, and analyzed to apportion their common sources. The consequences of using these species jointly for receptor modelling were assessed via combined-phase source apportionment that used the data as is, and in an approach that considered the potential for photochemical losses of gas-phase species. Thus, initial concentrations corrected for photochemistry, called PIC were calculated. The data were then analyzed either with positive matrix factorization or its dispersion-normalized variant (DN-PMF). Comparisons of applying PMF to the originally observed input data (BASE) and DN-PMF on data with PIC corrections were made. When the combined phase input data were analyzed, nine factors were resolved for both BASE and DN-PIC PMF. These factors were: particulate sulphate, secondary organic aerosol (SOA), particulate nitrate (pNO3), biomass burning with natural gas, crustal matter, winter blend of gasoline, coking/coal combustion, steelmaking, and summer blend/light duty vehicular emissions. On comparison of the BASE and DN-PIC PMF results, the average PM mass contribution of the summer gasoline fuel factor increased from 2% in BASE case to 5%, suggesting severe underestimation of this source’s initial contributions without DN-PIC. Also, substantial increases of reactive VOCs in the SOA factor, and PAHs with ≥four rings in the pNO3 and steelmaking factors were observed with DN-PIC PMF compared to the BASE PMF case, indicating that for the SOA factor, reactive VOCs at the location of study contributed to its sources.

RI-URBANS (Research Infrastructures Services Reinforcing Air Quality (AQ) Monitoring Capacities in European Urban & Industrial AreaS) is a research project supported by the European Commission under the Horizon 2020 – Research and Innovation Framework Programme, H2020-GD-2020 (grant 10103624) that connects the atmospheric observation expertise from Aerosols, Clouds and Trace gases Research InfraStructure (ACTRIS), with the urban air quality observation capacities of the regulatory air quality monitoring networks. It is specifically connected to the new European AQ Directive (NAQD) 2024/2881/CE published on 20 November 2024.RI-URBANS focuses on the infrastructures to measure emerging pollutants for AQ and the well-being of the citizens. Particularly, service tools (STs) for novel pollutants, such as ultrafine particles (UFP), UFP-number size distribution (PNSD), black carbon (BC), as well as ammonia (NH3) and numerous volatile organic compounds (VOCs), and measurements of tracers of potential toxicity of PM (oxidative potential (OP) of particulate matter PM), are provided for urban supersites in order to support scientific understanding of their effects on health and the environment. The NAQD has been introduced in Art. 10 the measurements of these new pollutants in a new network of AQ supersites.In essence, these STs are guidance documents that RI-URBANS have reviewed, in some cases developed, tested, and recommended for advanced AQ assessment in urban areas. Two of these STs focus on the source apportionment of PM based on receptor modelling with offline and online PM speciation (ST10) and on UFP-PNSD, BC, VOCs and OP of PM. The electronic files of the guidance documents of ST10 and ST11 can be downloaded at https://riurbans.eu/project/#service-toolsPMF is used in most cases (PM, VOCs, UFP-PNSD), and it is coupled with multi-linear regression for (OP), and aethalometer source apportionment for BC.Here we present the results from the application of these source apportionment tools to datasets of PM speciation, UFP-PNSD, VOCs, BC and OP data available in urban Europe. The results have a high interest for AQ policy (identifying major sources contributing to air quality impairment, but also identifying measures needed and evaluating the impact of policy actions), evaluation of the health outcomes, and identifying the source contributions with higher toxicity potential.The creation of the European network of AQ supersites by the European NAQD will provide very valuable datasets for source apportionment receptor modelling of a number of pollutants, however the required PM speciation in the NAQD is quite limited for obtaining detailed source apportionment results. It is important to intensify the source apportionment studies to support the need of more tracers of PM to be included in the supersites in the next review of the Directive, which will take place in five years.

This study applied Positive Matrix Factorization (PMF) to PM10 speciation datasets from 24 urban sites across six European countries (France, Greece, Italy, Portugal, Spain, and Switzerland) to perform a detailed source apportionment (SA) analysis. By using a consistent source apportionment tool for all datasets, the study enhances the comparability of PM10 SA results across urban Europe. The results identified seven major PM10 sources including road traffic, biomass burning, crustal/mineral sources, secondary aerosols, industrial emissions, sea salt, and heavy oil combustion (HOC). Road traffic emerged as the predominant source of PM10 in urban areas, with contributions varying by location, but representing as much as 41

Middle Eastern sand and dust storms (SDSs) can deteriorate air quality and human health of millions of inhabitants in downwind areas such as Tehran, Iran. Limited information is available about severity, frequency, magnitude, and duration of PM10 episodes in Tehran. To identify PM10 episodes between 2015 and 2021, the Seasonal-Trend decomposition procedure based on Loess (STL) method was applied to measured PM10 concentrations at 15 sites across Tehran. The PM10 episodes were separated into 3 duration categories (PE1, PE2, and PE3). The PM10 concentrations and related meteorological characteristics of the episodes were analyzed to assess the differences. All sites had higher PM10 concentrations compared to AQG levels for daily (24-h) PM10 (45 mu g m-3). PM10 episode frequency, magnitude, and duration were 2.60/year, 35.0 percent, and 1 day/episode over the 7-years study period, respectively. The overall frequency of PM10 PE1, PE2, and PE3 events were 205, 54, and 14, respectively. Events dissipated under strong westerly winds. PM10 accumulation occurred periods of weakening of the westerly winds to stagnant conditions. Site-specific bivariate polar plots (BBPs) also supported this finding. The increase of regional dust during high wind speeds on dusty days led to lower PM2.5/PM10 ratios at most sites. Back trajectory analyses of PM10 concentrations showed that the transboundary transport from westerly directions produced the high PM10 concentrations. Understanding the PM10 pollution episode characteristics could permit planning of practical anthropogenic emissions reductions and support the joint air pollution control strategies for regional air pollution.

PM2.5 is a significant air quality concern in urban areas globally. PM2.5 in Astana exceeded the US EPA standard for annual mean PM2.5 EPA with an average PM2.5 mass concentration of 23.43 +/- 11.50 mu g/m(3) and a maximum daily value of 63.8 mu g/m(3) in January (heating season). The lowest 3.7 mu g/m(3) was observed in September (non-heating season). However, source apportionment in Kazakhstan has not been done because of a lack of PM2.5 composition measurements. This study presents the first analysis of chemical composition of PM2.5 and source apportionments in Kazakhstan. It comprehensively examined Astana's PM2.5 chemical characteristics and source apportionment over similar to two years (November 2019 to August 2021). Using elements, water-soluble inorganic ions, black carbon (BC), and estimated unmeasured mass (UMM), source apportionment was obtained using Positive Matrix Factorization (PMF) supported by conditional bivariate probability function (CBPF) analyses. Average PM2.5 contributions of the eight sources were 'Spark Ignition' (30.3%), 'Coal Flyash' (17.1%), 'Secondary Nitrate' (15.1%), 'Primary Sulfate-Fuel Combustion' (9.9%), 'Secondary Sulfate-Coal Combustion' (8.5%), 'Soil/Road Dust' (7.9%), 'Diesel' (7.1%), and 'Local Power Plant(s)' (4.2%). Local power plants burn high-ash coal and fuel oil year-round. The major contributions of heating/power plants, private residential heating systems, autonomous boilers, vehicles, asphalt pavement mixing facilities, and local construction activities. This study's source apportionment analysis provides critical insights for developing targeted air quality management strategies in Kazakhstan. Findings highlight the need for improved controls on vehicular emissions and heat/power generation sources and for the implementation of measures by local governments to effectively reduce PM2.5.

Mercury is a persistent pollutant that bioaccumulates in biota, posing ecological and health risks. This study examines the total and methylmercury (THg and MeHg, respectively) levels in the Lake Huron (LH), Ontario (LO), and Erie (LE) food webs. The MeHg levels (mean f standard deviation) in LH and LE zooplankton (18.1 f 11.8 ng/g dry weight (dw) and 31.5 f 34.1 ng/g dw, respectively) were similar, but significantly higher than observed in zooplankton from LO (0.521 f 0.219 ng/g dw). THg concentrations in lake trout (Salvelinus namaycush) from LO (103 f 31 ng/g wet weight (wwt)) were similar to those in LE (90.1 f 33 ng/g wwt), but lower than those in LH (181 f 46 ng/g wwt). The highest sediment Hg concentrations (MeHg: 1.23 f 0.14 ng/g dw; THg: 342 f 3.9 ng/g dw) were observed at the western LE site, compared to other sites across the three lakes in this study (MeHg: 0.414 f 0.331 ng/g dw; THg: 41.7 f 32.5 ng/g dw). The trophic magnification slope (TMS) using log-transformed MeHg concentrations (dw) and nitrogen stable isotopes (delta 15N) ranged from 0.15 to 0.36. Biomagnification factors (BMFs) of MeHg (dw) between prey fish and macroinvertebrates ranged from 0.246 f 0.059 to 138 f 21, whereas BMFs for apex predators and their major prey were greater than 1. The current study provides a contemporary assessment of mercury transfer in three of the Laurentian Great Lakes, illustrating the importance of trophic level on Hg bioaccumulation.