Annual Concentrations Research Articles

Estimating monthly NO2, O3, and SO2 concentrations via an ensemble three-stage procedure with downscaled satellite remote sensing data and ground measurements

The gaseous air pollutants nitrogen dioxide (NO2), ozone (O3), and sulfur dioxide (SO2), in addition to particulate matter (PM2.5), are known to be associated with many adverse health effects. However, exposure estimates may not be available in rural or mountainous areas without monitoring stations. In this study, we retrieved satellite remote sensing data for NO2, O3, and SO2 from the Ozone Monitoring Instrument (OMI) L3 products. Together with ground measurements (air monitoring stations and meteorological and land use data), we estimated the monthly NO2, O3, and SO2 concentrations with a spatial resolution of 3×3 km across Taiwan from 2005 to 2019. A three-stage estimation procedure was utilized: in Stage 1, an ensemble generalized additive model (GAM) and machine learning method were used to determine the spatiotemporal variations; in Stage 2, the remote sensing data were downscaled; and in Stage 3, the downscaled concentrations were reused in the Stage 1 procedure for fine-tuning estimations. We obtained overall leave-one-out cross-validation (LOOCV) R2 values ranging from 0.927-0.950, 0.704-0.721, and 0.601-0.716, and root-mean-square-errors (RMSEs) ranging from 1.59-2.28, 3.81-4.18, and 0.67-1.32 ppb for NO2, O3, and SO2, respectively, via the random forest procedure. The annual NO2 and SO2 concentrations greatly improved from 2005-2019, especially in the western residential area of Taiwan. However, despite these improvements in air quality, the annual O3 concentrations tended to increase from 2015–2019. This might be due to the complex mixtures of precursors (e.g., NO2), atmospheric circulation, barriers of the Central Mountain Ridge, and increasing ground temperatures over the past decade. The proposed multistage estimation procedure performed well over the whole island with complex terrain and topography. The study outcomes may provide epidemiological information for long-term ambient exposure estimates and guidance for future administrative policies.

Relationship Between Air Pollution and the Incidence of Selected Disease Among Children and Adolescents in the Years 2017-2023 in Selected Cities in Poland

The aim of this research is to examine the relationship between average annual air pollution concentrations in selected cities and the incidence of specific diseases among children and adolescents aged 0 to 18 in selected Polish cities - Gdańsk, Katowice, Poznań, and Lublin with varying levels of average annual air pollution [suspended particulate matter PM2.5 and PM10, benzo(a)pyrene, nitrogen dioxide]. The relationship between the incidence of selected diseases among children and adolescents (asthma, hypertension, food and skin allergies) from 2018 to 2023 and the quality of atmospheric air was examined. In Katowice, due to the presence of a developed industry, the permissible average annual concentrations of the analyzed air pollutants were exceeded in the initial period, unlike in Gdańsk and Lublin. However, the greatest challenge in Poland concerning air quality is the average annual concentration of benzo(a)pyrene. Nonetheless, there has been a significant decrease in recent years. Polish cities facing air pollution problems are undertaking various measures to improve air quality. Studies have shown significant connections between the concentrations of selected pollutants and the frequency of diseases such as bronchial asthma, hypertension, food and skin allergies. However, this impact varies from city to city.

Spatial–Temporal Characteristics, Source Apportionment, and Health Risks of Atmospheric Volatile Organic Compounds in China: A Comprehensive Review

Volatile organic compounds (VOCs) are ubiquitous in the atmosphere, posing significant adverse impacts on air quality and human health. However, current research on atmospheric VOCs mainly focuses on specific regions or industries, without comprehensive national-level analysis. In this study, a total of 99 articles on atmospheric VOCs in China published from 2015 to 2024 were screened, and data on their concentrations, source apportionment, and health risks were extracted and summarized. The results revealed that the annual average concentrations of TVOCs and their groups in China generally increased and then decreased between 2011 and 2022, peaking in 2018–2019. A distinct seasonal pattern was observed, with the highest concentrations occurring in winter, followed by autumn, spring, and summer. TVOC emissions were highly concentrated in northern and eastern China, mainly contributed by alkanes and alkenes. Source apportionment of VOCs indicated that vehicle sources (32.9% ± 14.3%), industrial emissions (18.0% ± 12.8%), and other combustion sources (13.0% ± 13.0%) were the primary sources of VOCs in China. There was a significant positive correlation (p < 0.05) between the annual mean VOC concentration and population size, and a notable negative correlation (p < 0.05) with GDP per capita. Atmospheric VOCs had no non-carcinogenic risk (HI = 0.5) but exhibited a probable carcinogenic risk (7.5 × 10−5), with relatively high values for 1,2-dibromoethane, 1,2-dichloroethane, and naphthalene. The health risk was predominantly driven by halocarbons. These findings are essential for a better understanding of atmospheric VOCs and for developing more targeted VOC control measures.

Spatial-temporal variations and Attribution analysis of SO2 concentration in Beijing-Tianjin-Hebei regions from 2013 to 2022

Based on the monitoring data of air pollutants in Beijing-Tianjin-Hebei regions from 2012 to 2022, the spatial-temporal distribution of SO2 concentration and main influencing factors were analyzed through multi-methods of Daniel trend test, KZ filtering and WRF/CMAQ model simulations. From 2013 to 2022, the annual averaged concentrations of SO2 in Beijing, Tianjin and Hebei regions were all in obvious downward trends, and all passed the Daniel trend test (α=0.01). The annual averaged concentration of SO2 in Beijing, Tianjin and Hebei regions decreased from 26.6~114.3μg·m-3 in 2013 to 3.0~11.0μg·m-3, with the decline rates fluctuating from 2.62~11.81μg/(m3·yr) while the decrease rate of SO2 in Beijing was the lowest. The average annual concentration of SO2 in Tangshan city decreased the most, reaching 92.3% and it changed to be the smallest, about 78.2% in Chengde City. The reduction of coal consumption in the Beijing-Tianjin-Hebei regions significantly reduced atmospheric SO2 emissions and directly reduced the regional average concentration of SO2. Meteorological factors were generally conducive to the diffusion of SO2 concentration during 2013~2022, and the meteorological factors contributed about 0.4~5.5% in 13 cities in Jingjinji area while the contribution of anthropogenic emission reduction was 94.5~99.6%. The inter-annual variation of meteorological factors in summer from 2013 to 2022 was not conducive to the diffusion of SO2 concentration on the whole, and the contribution changed to -52.6 ~ -1.0% in 13 cities. From June to August in summer under the easterly and southerly winds, the SO2 concentration in Beijing was basically twice that of the northerly and westerly winds. The contribution of southwest transport channel to SO2 concentration in Beijing was 33.5%, while it changed to 38.9% in the southeast transport channel. Therefore, strengthening the management and control of air pollutants in surrounding area of Beijing is helpful for Beijing to further reduce the levels of air pollutants and achieve targets of air quality improvement in the 14th Five-Year Plan period.

The effect of air pollution on hospitalizations with Parkinson’s disease among medicare beneficiaries nationwide

We examined the effect of annual exposure to fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ozone (O3), on the rate of first hospitalization with a PD-related diagnosis (hospitalization with PD) among Medicare Fee-for-Service beneficiaries (2001-2016). Machine learning-derived annual air pollution concentrations were linked to residential ZIP codes. For each exposure, we fitted four models: 1) traditional outcome stratification, 2) marginal structural, 3) doubly robust, and 4) generalized propensity score matching Poisson regression models, adjusted for sociodemographic and meteorological confounders and long-term trends. Among 49,121,026 beneficiaries, incidence rate ratios of 1.08 (95% CI: 1.07, 1.10), 1.07 (95% CI: 1.05, 1.08), and 1.03 (95% CI: 1.02, 1.05) for an interquartile range increase in PM2.5 (3.72 µg/m3), NO2 (13.84 ppb), and O3 (10.09 ppb), respectively, were estimated from doubly robust models. Results were similar across modeling approaches. In this nationwide study, higher air pollution exposure increased the rate of hospitalizations with PD.

Application of SWAT to assess peatland forestry impacts on water quality

ABSTRACT Peatland drainage can affect the natural state of hydrological conditions and nutrient loading but is rarely included in catchment-scale models. To understand the gap, we aimed to use the soil and water assessment tool (SWAT) model to observe drained peatlands and their properties to predict nutrients and suspended solids (SS) in the peatland-dominated Simojoki catchment. We integrated drainage networks in SWAT to (i) identify the parameters for the drainage; (ii) determine annual loads and mean concentrations of SS, organic phosphorus (Org-P), total phosphorus (TP), organic nitrogen (Org-N), and total nitrogen (TN); (iii) understand spatial variation of nutrients and SS; and (iv) investigate the uncertainty ranges for the estimates. The calibrated SWAT model showed a 9.6% PBIAS between the simulated flow and the observations with low to medium loading variations for the water quality parameters. For Org-N and TN, the highest loading per year was at the downstream outlet, whereas for SS, Org-P, and TP, it was higher at the upstream outlet of the catchment. This approach of representing the drained peatland in SWAT indicated a maximum spatial distributed load in the peat soil in the clear-cut area and it can be beneficial in future hydrological modelling efforts in identifying the status of nutrients or SS.

The impact of changing exposure to PM2.5 on mortality for US diplomats with multiple international relocations: a modelling study.

Current evidence linking long-term exposure to fine particulate matter (PM2.5) exposure and mortality is primarily based on persons that live in the same residence, city and/or country throughout the study, with few residential moves or relocations. We propose a novel method to quantify the health impacts of PM2.5 for United States (US) diplomats who regularly relocate to international cities with different PM2.5 levels. Life table methods were applied at an individual-level to US mortality statistics using the World Health Organization's database of city-specific PM2.5 annual mean concentrations. Global Burden of Disease concentration-response (C-R) functions were used to estimate cause-specific mortality and days of life lost (DLL) for a range of illustrative 20-year diplomatic assignments for three age groups. Time lags between exposure and exposure-related mortality risks were applied. Sensitivity analysis of baseline mortality, exposure level, C-R functions and lags was conducted. The effect of mitigation measures, including the addition of air purifiers, was examined. DLL due to PM2.5 exposure for a standard 20-year assignment ranged from 0.3 days for diplomats' children to 84.1 days for older diplomats. DLL decreased when assignments in high PM2.5 cities were followed by assignments in low PM2.5 cities: 162.5 DLL when spending 20 years in high PM2.5 cities compared to 62.6 DLL when spending one of every four years (5 years total) in a high PM2.5 city for older male diplomats. Use of air purifiers and improved home tightness in polluted cities may halve DLL due to PM2.5 exposure. The results were highly sensitive to lag assumptions: DLL increased by 68% without inception lags and decreased by 59% without cessation lags for older male diplomats. We developed a model to quantify health impacts of changing PM2.5 exposure for a population with frequent relocations. Our model suggests that alternating assignments in high and low PM2.5 cities may help reduce PM2.5-related mortality burdens. Adding exposure mitigation at home may help reduce PM2.5 related mortality. Further research on outcome-specific lag structures is needed to improve the model.

Extensive investigation of seasonal and spatial fluctuations of BTEX in an industrial city with a health risk assessment

There are many pollutants in the air that can be harmful to human health. Their impact varies based on factors such as the kind of pollutant, duration of exposure, and concentration levels. Volatile organic compounds are particularly significant carcinogens among the various pollutants present in the air. Consequently, people who are exposed to these harmful airborne pollutants suffer permanent consequences. This study examines the properties of BTEX compounds—benzene, toluene, ethylbenzene, and xylene—as well as their sources and risk assessments throughout a one-year period from March 21, 2019, to March 20, 2020, in Karaj, Iran’s largest industrialized city. First, utilizing a geographical information system that covered the entire city, 17 locations within Karaj were chosen for this purpose. Then, samplings were carried out in the spring, summer, autumn, and winter months with the NIOSH 1501 method. During the research period, 68 samples of BTEX compounds were collected. The adsorption of these contaminants on the activated carbon adsorbents was performed using an environmental sampling pump with a flow rate of 0.2 L/min for 1 h. The samples were subsequently prepared using a carbon disulfide solution and injected into a GC-FID for analysis. In this research, the average annual concentration of BTEX compounds in the air of Karaj city was obtained at 33.01 µg/m3. Autumn and spring had the highest and lowest average concentrations of BTEX compounds, respectively. In addition, sites 5 and 8 had the highest average annual concentrations of these pollutants. The sourcing conducted in this study showed that transportation and fuel consumption, as well as industries, were the primary sources of pollution in the city. In addition, the excess lifetime cancer risk was higher than the guideline value in some sites and lower in others. Furthermore, the Hazard Quotients were lower than 1, but in general, the citizens of Karaj were at serious risk from exposure to this group of pollutants.

Long-Term Exposure to Arsenic in Community Water Supplies and Risk of Cardiovascular Disease among Women in the California Teachers Study.

Inorganic arsenic in drinking water (wAs) is linked to atherosclerosis and cardiovascular disease. However, risk is uncertain at lower levels present in US community water supplies (CWS), currently regulated at the federal maximum contaminant level of . We evaluated the relationship between long-term wAs exposure from CWS and cardiovascular disease in the California Teachers Study cohort. Using statewide health care administrative records from enrollment through follow-up (1995-2018), we identified fatal and nonfatal cases of ischemic heart disease (IHD) and cardiovascular disease (CVD). Participants' residential addresses were linked to a network of CWS boundaries and annual wAs concentrations (1990-2020). Most participants resided in areas served by a CWS (92%). Exposure was calculated as a time-varying, 10-year moving average up to a participant's event, death, or end of follow-up. Using Cox models, we estimated hazard ratios (HRs) and 95% confidence intervals (95% CIs) for the risk of IHD or CVD. We evaluated wAs exposure categorized by concentration thresholds relevant to regulation standards (, 1.00-2.99, 3.00-4.99, 5.00-9.99, ) and continuously using a log2-transformation (i.e., per doubling). Models were adjusted for baseline age, neighborhood socioeconomic status, race/ethnicity, body mass index (BMI), and smoking status. We also stratified analyses by age, BMI, and smoking status. Our analysis included 98,250 participants, 6,119 IHD cases, and 9,936 CVD cases. The HRs for IHD at concentration thresholds (reference, ) were 1.06 (95% CI: 1.00, 1.12), 1.05 (95% CI: 0.94, 1.17), 1.20 (95% CI: 1.02, 1.41), and 1.42 (95% CI: 1.10, 1.84) for , , , and , respectively. HRs for every doubling of wAs exposure were 1.04 (95% CI: 1.02, 1.06) for IHD and 1.02 (95% CI: 1.01, 1.04) for CVD. We observed statistically stronger risk among those vs. years of age at enrollment ( and 0.012 for IHD and CVD, respectively). Long-term wAs exposure from CWS, at and below the regulatory limit, may increase cardiovascular disease risk, particularly IHD. https://doi.org/10.1289/EHP14410.

Refined prediction of SO2 concentration around Chinese coking enterprises and exposure risk assessment of different populations based on buffer Latin hypercube

Coking enterprises in China are recognized as significant sources of SO2 emissions, making them a key industry with high levels of SO2 intensity. Assessing the health risks for different populations around these coking enterprises nationwide is challenging due to the lack of clarity regarding SO2 concentrations at varying distances from these facilities. To address this issue, we developed a buffer Latin hypercube XGBoost particle swarm optimization (BLH-XGB-PSO) algorithm that combines efficient global search capabilities and accurate prediction performance. This algorithm enables effective traversal of monitoring points located at varying distances and directions around the enterprise while automatically seeking optimal model parameters. Using this model, we accurately predicted the concentration of SO2 every 0.5 km within a 10 km radius around China's coking enterprises in 2017, achieving a high prediction accuracy with an R2 value of 0.97. The prediction results indicate that the highest concentration of SO2 in the vicinity of Chinese coking enterprises is observed in the central region of Shanxi province (65.88 μg/m3). The average annual concentration of SO2 around all production enterprises amounts to 27.9 μg/m3. Furthermore, we conducted an assessment on the impact of coking enterprises on different age groups, genders, and regions regarding the number of affected individuals, health exposure risks, and control effectiveness. Our findings reveal that in 2017, around 5.5 thousand newborns (14.5% male, 85.5% female) had a hazard quotient (HQ) exceeding threshold value which poses potential human health risks. The implementation of the control policy successfully prevented 64,375 thousand people from being affected by higher concentrations of SO2. Greater attention should be devoted to the health risks faced by newborns residing in proximity to coking enterprises, with a particular emphasis on female infants.

Impact of air pollution on mortality: Geo-epidemiological study in French-speaking Africa

According to the World Health Organization, air pollution is responsible for 90 % of deaths in Africa. However, limited data on exposure to air pollution is available, and studies are rare, particularly in French-speaking Africa. This study aims to investigate the impact of air pollution on mortality in 12 French-speaking African countries (Algeria, Burkina Faso, Burundi, Cameroon, Guinea, Ivory Coast, Madagascar, Mali, Morocco, Democratic Republic of Congo, Senegal, Tunisia). Using data from the Institute for Health Metrics and Evaluation (IHME), annual concentrations of the PM2.5 pollutant from different cities were integrated into a spatial interpolation model (IDW) at the scale of each country. The interpolation was validated using cross-validation models. For each of the considered cardiorespiratory diseases (LRI, stroke, COPD, IHD), the attributable mortality fraction was estimated using literature data and population exposure calculated using demographic data from each country. Large variations in ambient PM2.5 concentration between the 12 countries are observed, with concentrations ranging from 1.76 μg/m3 in Morocco to 64.99 μg/m3 in Cameroon. Concentrations are higher in West Africa than in Central or North Africa. In 2019, 136 457 deaths attributable to air pollution were recorded in the 12 countries: 40.8 % from ischemic heart disease, 38.5 % from stroke, 13.2 % from lower respiratory infections and 7.5 % from chronic obstructive pulmonary disease. Our model allowed us to obtain a spatial distribution and the number of deaths related to air pollution. However, the estimation of the health impact from air pollution could be improved by more systematic and comprehensive local exposure assessments from a robust air quality monitoring system.

Seasonal and Distributional Changes in the Composition and Flux of Anthropogenic Microparticles in the Surface Waters of the Charles River, Massachusetts, United States

Plastic is a growing global environmental problem. While much of the focus of anthropogenic microparticles has focused on microplastics and their occurrence in marine systems, anthropogenic microparticles are found in freshwater systems. The Charles River is a highly impacted and historically important river within Massachusetts and runs for 80 miles within the state of MA through a variety of land uses. Microparticle concentrations were found to vary along the length of the river and ranged in concentrations from 1–19 pieces/L, with generally higher concentrations downstream. Microfibers were the dominant (72%) type of microparticles found, and the majority (avg 76%) of microparticles were synthetic. The highest estimated flux of microparticles occurred in May, with an estimated flux of 2 billion microparticles per day via the Charles River into the Boston Harbor. The average annual concentration of microparticles was correlated with land use, with higher concentrations occurring in regions with higher impervious coverage and in areas designated as industrial or high-density residential. Polyester, polypropylene, and polyamides were the dominant plastic polymers. However, seasonal changes in the relative importance of each polymer, along with changes in the abundance and flux rates, indicate that there would be seasonal variability in the type of microparticles exported. Changes in composition occurred between stations and between the head and mouth of the river, suggesting particle retention due to either deposition, degradation, or biological consumption.

Annual Variations of PM10, PM2.5 and PM1.0 Fraction at an Urban Site in Ansan, Korea

This study examines particulate matter (PM) concentrations, specifically PM10, PM2.5, and PM1.0, at an urban site in Ansan, South Korea. Three BAM-1020 continuous monitors measured PM10, PM2.5, and PM1.0 hourly from January to December 2021, with data acquisition rates of 97.1%, 97.3%, and 93.4%, respectively. Average annual concentrations were 45.7±48.4 µg/m³ (PM10), 26.4±22.7 µg/m³ (PM2.5), and 18.5±14.5 µg/m³ (PM1.0). PM10 was 91% of the annual air quality standard, while PM2.5 exceeded this standard by 176%, indicating severe pollution. Statistical analyses using probability density function (PDF) and cumulative distribution function (CDF) showed 98.5% of data converged at 150 µg/m³ (PM10), 75 µg/m³ (PM2.5), and 50 µg/m³ (PM1.0), with the remaining 1.5% corresponding to approximately 131 hours, annually. In 2021, all six observed yellow dust events occurred in spring (March to May). PM10, PM2.5, and PM1.0 concentrations increased from January to March, peaked in March, decreased until September, and rose again. The coarse fraction ratio increased stepwise from February to May, likely due to yellow dust and episodes of high PM concentration in the spring. The PM1.0 concentration was higher in summer and fall compared with that in spring and winter. The PM1.0/PM2.5 ratio was highest in summer and fall even though the annual PM1.0concentration was lowest, suggesting a higher secondary formation rate of fine particles during these periods. This underscores the need for further scientific investigation on PM1.0. The study provides insights into the simultaneous observation and distribution characteristics of PM10, PM2.5, and PM1.0, highlighting the mass concentration, distribution, and ratio of PM1.0. These findings are crucial for understanding PM distribution in Ansan, an industrial complex, and can serve as essential data for chemical composition comparisons, data validation, public health strategies, and cost-benefit analyses for regional PM improvement.

The mediating effect of TyG-related indicators between long-term exposure to particulate matter and cardiovascular disease: evidence from a national longitudinal cohort study

BackgroundAmbient particulate matter (PM) exposure is recognized as a risk factor for cardiovascular disease (CVD). However, the extent to which PM exposure is associated with CVD via triglyceride glucose (TyG)-related indicators remains unknown. This study examines the relationship between long-term PM exposure and CVD events, further assessing whether TyG-related indicators mediate this association.MethodsThis cohort study involved 7,532 individuals aged at least 45 years who were not diagnosed with CVD in 2011 from the China Longitudinal Study of Health and Retirement (CHARLS) and were followed up for the occurrence of CVD until 2020. The annual PM concentration data at the city level, with aerodynamic diameters ≤ 1 μm (PM1), ≤ 2.5 μm (PM2.5), and ≤ 10 μm (PM10), were obtained from the ChinaHighAirPollutants (CHAP). The average concentration of PM in the 3 years before the baseline survey in 2011 was defined as the long-term exposure level of the individual. The relationship between PM exposure and CVD incidence was examined via Cox proportional hazards models, with a focus on probing the role of TyG-related indicators through mediation analysis.ResultsA total of 1,865 individuals with CVD were diagnosed over the span of a 7.4-year follow-up period. The 3-year average concentrations before baseline were 31.29 µg/m³ for PM1, 56.03 µg/m³ for PM2.5, and 95.73 µg/m³ for PM10. In fully adjusted model, the Cox proportional hazards models revealed that an increase of 10 µg/m³ in the PM1, PM2.5, and PM10 exposure concentrations corresponded to elevated CVD risk, with HRs (95% CI) of 1.135 (1.078–1.195), 1.092 (1.062–1.123), and 1.075 (1.059–1.090), respectively. Mediation analyses further suggested that the correlation between PM exposure and CVD could be partly mediated via TyG-BMI, TyG-WC, and TyG-WHtR, with mediation proportions varying from 5.54 to 15.30%.ConclusionA significant correlation was observed between long-term PM exposure and increased CVD risk, with TyG-related indicators, such as TyG-BMI, TyG-WC, and TyG-WHtR, partially mediating this relationship.

Seasonal variation and size distribution of aromatic acids in urban aerosols in Beijing, China

Aromatic acids are an integral component of organic acids in the atmosphere, contributing to the formation of climate-altering brown carbon (BrC). To better understand the sources and formation processes of aromatic acids, we collected size-segregated particulate matter samples in urban Beijing from April 2017 to January 2018, which were analyzed using solvent-extraction followed by gas chromatography/mass spectrometry. Phthalic acid (o-PhA) had the greatest average annual concentration, followed by terephthalic acid (p-PhA), 4-hydroxybenzoic acid (4-OHBA), dehydroabietic acid (DA), syringic acid (SA), 3-hydroxybenzoic acid (3-OHBA), isophthalic acid (m-PhA), and vanillic acid (VA). We identified distinct seasonal variations in aromatic acids, with o-PhA peaking in summer due to photochemical activity, while p-PhA and 4-OHBA elevated in autumn and summer, respectively, influenced by open waste and biomass burning. Wintertime variations in all aromatic acids were driven by complex meteorology and increased anthropogenic emissions, including rural biomass burning for cooking and heating. Particle size distribution of aromatic acids was affected by seasonal agricultural activities and dust storms, multiple emission sources, and formation mechanisms. The o-PhA has predominantly bimodal distribution, with diverse sources and complex formation mechanisms including gas- and aqueous-phase chemistry. The applicability of o-PhA as a tracer for specific secondary organic aerosols has been questioned due to its potential primary sources. The 3-OHBA, 4-OHBA, VA, SA, and DA exhibited bimodal or trimodal patterns during haze and non-haze periods across different particle size ranges. The seasonal variation in VA/SA and VA/4-OHBA ratios demonstrated the complexity of biomass burning types, influenced by season, particle size, meteorological conditions, and combustion sources.

Spatial and temporal distribution of tributyltin in the coastal environment of the Croatian Adriatic (2016-2023): TBT remains a cause for concern

This work presents a spatial and temporal distribution of tributyltin (TBT) and TBT pollution assessment of the Croatian Adriatic coast in the period 2016 – 2023. The monitoring of TBT pollution was carried out within the Water Framework Directive (2000/60/EC) and the Marine Strategy Framework Directive (2008/56/EC). TBT concentrations were measured at 63 sites in coastal and transitional waters in three compartments - water, sediments and mussels. The ranges of TBT concentrations were <0.06 – 6.40 ng(TBT)/L in the water column, <1 – 2546 ng(TBT)/g(d.w.) in sediments, and <1 – 655 ng(TBT)/g(d.w.) in mussels, while transitional waters were in general more polluted than coastal waters. Monitoring of TBT concentrations in water showed that 30% of monitored sites were continuously polluted with TBT with average annual concentrations exceeding AA-EQS [0.2 ng(TBT)/L], while 20% of the sites had concentrations in sediments above the proposed EQS for sediments [1.6 ng(TBT)/g(d.w.)]. In mussels, TBT was detected at 70% of the sites with more than 60% of the sites exceeding the OSPAR criteria [12.6 ng(TBT)/g(d.w.)], indicating that the occurrence of imposex in gastropods at these sites is very likely. Only a slight decrease in TBT levels was observed over the investigated period, but concentrations at most contaminated sites did not fall below the EQS. This study shows that, despite the ban of TBT-based antifouling paints more than 15 years ago (except for public and military vessels), contamination of the Croatian Adriatic coast with TBT still exists and regular monitoring is essential. The TBT distribution was primarily determined by the vicinity of the pollution source, i.e. shipping traffic, but the role of physicochemical parameters, such as dissolved organic carbon (DOC) and transparency of the water column, should not be disregarded as well as the influence of hydrodynamics in the transitional waters. Although monitoring of TBT concentrations in water is an established approach to assess recent pollution, this long-term study has shown that mussels can be the most reliable indicator of pollution in a given area over the last several months.

Extracting regional and temporal features to improve machine learning for hourly air pollutants in urban India

India is suffering from severe particulate matter (PM, including PM2.5 and PM10) pollution, while limited ground observations are insufficient to support a comprehensive understanding of its health risks. Machine learning (ML) has the potential to improve the estimation of PM distribution and exposure efficiently. Regional transport as well as accumulation and dispersion processes of PM and its components, which have significant impacts on PM concentrations, are crucial when building ML models, especially for sparsely observed regions like India. Here, geographic and temporal-rolling weighting methods were used to separately extract regional and temporal features for improving the performance of the ML model. The incorporation of temporal and regional features into the ML model significantly improved ML model performance, with root mean square error (RMSE) reduced by 21 % and 19% for PM2.5 and PM10 estimation, as well as an improvement in model underestimation for the heavy pollution scenarios. The spatial-temporal model shows out-of-sample test CV coefficients of determination (R2) of 0.87 and 0.88 for hourly PM2.5 and PM10. The ML model predicts an annual nationwide concentration of 68.3 μg/m3 for PM2.5 with a north (high, especially in Indo-Gangetic Plain) to south (low) distribution, which is consistent with high satellite aerosol optical depth (AOD) values. Boundary layer height is identified as the main meteorological factor influencing PM2.5 concentrations in winter. Characterizing the regional transport and cumulative dispersion processes of pollutants by extracting features can help in machine learning training, and this method can be further improved and applied to other studies.

Drought reduces nitrogen supply and N2O emission in coastal bays

Severe droughts are increasingly prevalent under global climate change, disrupting watershed hydrology and coastal nitrogen cycling. However, the specific effects of drought on nitrogen transport from land to sea and subsequent nitrogen dynamics remain inadequately understood. In this study, we evaluated the consequences of the 2020–2022 drought on nitrogen supply and N2O emissions in Xiamen Bay, Southeast China. The results showed that drought significantly reduced annual NH4N, NO2N, and NO3N concentrations in Xiamen Bay by 49.4 %, 32.1 %, and 40.3 %, respectively, compared with the pre-drought year of 2019. The decline in NH4N concentration was mainly attributed to reduced surface runoff across all seasons. NO3N and NO2N concentrations declined only during spring and summer, primarily due to increased potential evapotranspiration (PET) hindering nitrogen supply via groundwater and concurrently enhancing land denitrification. Annual N2O emission from Xiamen Bay decreased by 40.0∼72.7 % during the drought, highly correlated with the decline in the concentrations of NO3N, DIN, and DTN (p < 0.001). Comparative analysis revealed that NO3N concentration exhibited consistent negative linear regressions with PET and declined as evaporative demand drought conditions worsened across Xiamen Bay, Sansha Bay, and Chesapeake Bay throughout 2010–2022. NH4N concentration showed a positive regression with river discharge in Xiamen Bay, but negative regressions in the other two bays. Our results indicates that drought reduces N2O emission primarily driven by nitrate substrate reduction in the bay. This study provides new insights for predicting coastal nitrogen dynamics and greenhouse gas emissions under global environmental change.

Trajectories of long-term exposure to PCB153 and Benzo[a]pyrene (BaP) air pollution and risk of breast cancer

BackgroundWhile genetic, hormonal, and lifestyle factors partially elucidate the incidence of breast cancer, emerging research has underscored the potential contribution of air pollution. Polychlorinated biphenyls (PCBs) and benzo[a]pyrene (BaP) are of particular concern due to endocrine-disrupting properties and their carcinogenetic effect.ObjectiveTo identify distinct long term trajectories of exposure to PCB153 and BaP, and estimate their associations with breast cancer risk.MethodsWe used data from the XENAIR case–control study, nested within the ongoing prospective French E3N cohort which enrolled 98,995 women aged 40–65 years in 1990–1991. Cases were incident cases of primary invasive breast cancer diagnosed from cohort entry to 2011. Controls were randomly selected by incidence density sampling, and individually matched to cases on delay since cohort entry, and date, age, department of residence, and menopausal status at cohort entry. Annual mean outdoor PCB153 and BaP concentrations at residential addresses from 1990 to 2011 were estimated using the CHIMERE chemistry-transport model. Latent class mixed models were used to identify profiles of exposure trajectories from cohort entry to the index date, and conditional logistic regression to estimate their association with the odds of breast cancer.Results5058 cases and 5059 controls contributed to the analysis. Five profiles of trajectories of PCB153 exposure were identified. The class with the highest PCB153 concentrations had a 69% increased odds of breast cancer compared to the class with the lowest concentrations (95% CI 1.08, 2.64), after adjustment for education and matching factors. The association between identified BaP trajectories and breast cancer was weaker and suffered from large CI.ConclusionsOur results support an association between long term exposure to PCB153 and the risk of breast cancer, and encourage further studies to account for lifetime exposure to persistent organic pollutants.

A real-time assessment of hazardous atmospheric pollutants across cities in China and India

China and India are two of the fastest-growing developing economies covering about 35 % of the world’s population. Due to the extensive prevalence of air pollution across cities in China and India, contemporary assessment of atmospheric pollution through real-time and remote sensing observations is inadequate. The study aims to determine the spatial distribution and temporal variation of hazardous atmospheric pollutants across cities in China (Shanghai, Nanjing, Jinan, Zhengzhou and Beijing) and India (Kolkata, Asansol, Patna, Kanpur and Delhi). Ground observation data on CO, O3, PM2.5, PM10, NO2 and SO2 along with remote sensing data on AOD, CO, O3, BC, NO2, SO2 and dust surface mass concentrations are used to assess atmospheric pollution. This study examines daily, zonal and longitudinal pollutant distributions using Sentinel-5 P data and surface mass concentrations over the vertical column evaluated from NASA satellite data. The Mann-Kendall test and relative change methods have been implemented to assess pollutant trends while Sen’s Slope identifies the magnitude of change. The similarity test and data validation methods including NRMSE, PC and MBias have been employed to ensure consistency in analysing annual trends for each air pollutant in the datasets. Additionally, multiple correlation matrix analysis has been used to examine the associations among different pollutants from both datasets based on their annual averages. Remote sensing data reveals that eastern China and north-eastern India have the highest aerosol, BC, CO, NO2 and SO2 while western China and southern India lowest. Dust peaks in the west while O3 levels are highest in the northern part of China and India. Ground observation data indicates that Chinese cities have higher annual mean SO2 and O3 concentrations with yearly declines in PM2.5, PM10, NO2, SO2 and CO notably SO2. Indian cities witnessed overall increases in PM2.5, PM10, NO2 and SO2 from 2012 to 2019 with a slight decline in 2020 followed by a resurgence in 2023. The findings provide insights for implementing regional policy measures to reduce air pollution based on changes in pollutant behaviour. The study suggests that addressing atmospheric pollutants, particularly NO2, CO, PM2.5, PM10, and SO2 requires a comprehensive environmental policy framework involving central and state governments and enforcing stringent environmental protection laws.