In this study, the contamination levels and seasonal variation of 22 PFASs were investigated in coastal reef-building corals (n = 68) from the northern South China Sea (SCS) during wet and dry seasons. Perfluorohexane sulfonate (PFHxS) was the predominant PFASs in all coral samples, representing 43% of the total PFAS. Long-chain PFASs, as well as PFAS alternatives, were frequently detected above the MQL (>88%) but showed relatively low concentrations compared to short-chain PFASs in most species and seasons. Seasonal variation of PFAS concentrations were observed in branching corals, indicating that the accumulation of PFASs may be associated with coral morphological structures. Interspecies differences in PFAS levels agree well with different bioaccumulation potentials among coral species. Redundancy analysis (RDA) showed that seasonal factor and coral genus could partly influence PFAS concentrations in coral tissues. In summary, our study firstly reported the occurrence of PFASs in coral communities from the SCS and highlights the necessity for future investigations on more toxicity data for coral communities.

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R² and root mean squared error (RMSE) were 0.80 and 20.93 μg/m³ at daily level in 2013–2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 μg/m³ in mainland China in 2013, and reached 100.96 μg/m³ in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April–September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 μg/m³ have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future.

South Korea has experienced a rapid increase in ozone concentrations in surface air together with China for decades. Here we use a 3-D global chemical transport model, GEOS-Chem nested over East Asia (110 E - 140 E, 20 N–50 N) at 0.25° × 0.3125° resolution, to examine locally controllable (domestic anthropogenic) versus uncontrollable (background) contributions to ozone air quality at the national scale for 2016. We conducted model simulations for representative months of each season: January, April, July, and October for winter, spring, summer, and fall and performed extensive model evaluation by comparing simulated ozone with observations from satellite and surface networks. The model appears to reproduce observed spatial and temporal ozone variations, showing correlation coefficients (0.40–0.87) against each observation dataset. Seasonal mean ozone concentrations in the model are the highest in spring (39.3 ± 10.3 ppb), followed by summer (38.3 ± 14.4 ppb), fall (31.2 ± 9.8 ppb), and winter (24.5 ± 7.9 ppb), which is consistent with that of surface observations. Background ozone concentrations obtained from a sensitivity model simulation with no domestic anthropogenic emissions show a different seasonal variation in South Korea, showing the highest value in spring (46.9 ± 3.4 ppb) followed by fall (38.2 ± 3.7 ppb), winter (33.0 ± 1.9 ppb), and summer (32.1 ± 6.7 ppb). Except for summer, when the photochemical formation is dominant, the background ozone concentrations are higher than the seasonal ozone concentrations in the model, indicating that the domestic anthropogenic emissions play a role as ozone loss via NOₓ titration throughout the year. Ozone air quality in South Korea is determined mainly by year-round regional background contributions (peak in spring) with summertime domestic ozone formation by increased biogenic VOCs emissions with persistent NOₓ emissions throughout the year. The domestic NOₓ emissions reduce MDA8 ozone around large cities (Seoul and Busan) and hardly increase MDA8 in other regions in spring, but it increases MDA8 across the country in summer. Therefore, NOₓ reduction can be effective in control of MDA8 ozone in summer, but it can have rather countereffect in spring.

The health effects of potentially toxic elements (PTEs) in airborne particulate matter (PM) are strongly dependent on their size distribution and dissolution. This study examined PTEs within nine distinct sizes of PM in a Chinese megacity, with a focus on their deposited and dissolved bioaccessibility in the human pulmonary region. A Multiple Path Particle Dosimetry (MPPD) model was used to estimate the deposited bioaccessibility, and an in-vitro experiment with simulated lung fluid was conducted for dissolved bioaccessibility. During the non-heating season, the dissolved bioaccessible fraction (DBF) of As, Cd, Co, Cr, Mn, Pb and V were greater in fine PM (aerodynamics less than 2.1 μm) than in coarse PM (aerodynamics between 2.1 and 10 μm), and vice versa for Ni. With the increased demand of heating, the DBF of Pb and As decreased in fine particle sizes, probably due to the presence of oxide/silicate compounds from coal combustion. Inhalation health risks based on the bioaccessible concentrations of PTEs displayed the peaks in <0.43 μm and 2.1–3.3 μm particulate sizes. The non-cancer risk was at an acceptable level (95th percentiles of hazard index (HI) was 0.49), but the cancer risk exceeded the threshold value (95th percentiles of total incremental lifetime cancer risk (TCR) was 8.91 × 10⁻⁵). Based on the results of uncertainty analysis, except for the exposure frequency, the total concentrations and DBF of As and Cr in <0.43 μm particle size segment have a greater influence on the uncertainty of probabilistic risk.

Litter is an ecological, economic, and social problem that impacts marine environments around the world. To create prevention and mitigation measures to solve this issue, it is necessary to understand the amounts and sources of this type of pollution. Cassino Beach is an extensive sandy beach located in South Brazil (∼220 km in length) that presents multiple uses, such as touristic, portuary and fishery activities. In order to evaluate the spatial and seasonal variation of litter amounts, types and sources at Cassino Beach, litter (>2.5 cm) was collected over 27 months at two urban and two non-urban sites. At each site, the litter present in three 200 m² areas was sampled and evaluated. A total of 19,457 items were collected, mostly composed by plastic (∼88%). Paper, metal, and cloth items were also present, but in low amounts. Fragments and cigarette butts were the major types of plastic litter, with abundances of 28.4% and 17.0%, respectively. Urban sites presented higher amounts of litter, with those related to beach use being more common, emphasizing the contribution of beachgoers to litter input at these sites. During the summer season, when beach use increases, the highest total litter concentration was found. Undefined and/or beach use-related sources were dominant in all sites and seasons. Mapping the predominant materials, types and potential sources of litter creates important baseline data that can contribute not only to beach monitoring, but also to the development of litter reduction strategies.

The atmosphere as a temporary habitat for airborne microbial communities is a valuable topic to explore, and it is through aerobiological studies that the diversity of biological particles and their release, emission, transport, deposition, and impact are assessed. Specific microorganisms are involved in meteorological processes, and phytosanitary and public health concerns. Airborne microbial composition is related to factors such as geographic region and weather conditions.In this study a metagenomic approach was used to determine the composition of bacterial and fungal communities in the air of two different land-use areas (urban area and semi-rural area), during dry and rainy seasons in Mexico City. Air sampling was carried out with a Hirst-type spore trap, collecting the samples simultaneously in both study areas. Forty-two bioaerosol samples were collected, and the DNA obtained was sequenced using Next-Generation Sequencing. The results indicated that the bacterial communities were represented mainly by the phyla Actinobacteria, Proteobacteria, Firmicutes, Bacteroidetes, Cyanobacteria, and the fungal communities by the phyla Ascomycota followed by Basidiomycota. The evident changes in microbial composition were related more to seasonality than to locality, since both UA and SRA showed a high degree of urbanization, despite some differences in land use. Continuous monitoring of atmospheric bioaerosols is essential to determine the influence of meteorological factors on the composition of the aerial microbiota.

The strict environmental management has been implemented in Taihu Basin to reduce the surface water contamination; however, the effectiveness of the management actions has not been comprehensively evaluated. In the present study, 364 samples were collected during four campaigns over a span of one year from surface water, municipal wastewater treatment plants (MWWTPs), industrial wastewater treatment plants (IWWTPs), industrial enterprises, and aquaculture in a typical region in the Upper Taihu Basin. Overall concentration, temporal variation and spatial distribution of 16 PAHs in surface water and various pollution sources were evaluated and the potential pollution sources were identified. Results showed that concentrations of individual PAHs in the surface water ranged from less than the limit of quantification (LOQ) to 949 ng L⁻¹, indicating a reduction of PAH contamination level after the implementation of environmental management actions. Influent of MWWTPs and wastewater from industrial enterprises exhibited relatively high ∑PAHs concentrations (mean: 880 ng L⁻¹ and 642 ng L⁻¹, respectively); these samples also exhibited a similar seasonal variation as well as composition of PAH congeners to those found in surface water, and therefore were designated as the main emission sources of PAHs in the studied region. Additional source apportionment using principal component analysis was also conducted to verify the proposed sources and diagnose other pollution sources. The findings provided a thorough understanding of PAH pollution, especially its major emission sources, in a typical region with pollution-intensive industries after the implementation of strict environmental management.

This study employs the grain size distributions and the concentrations and isotopic compositions of Sr, Nd, and Pb in the precipitation samples collected from the Laohugou Glacier (LHG) in northeastern Tibetan Plateau (TP) during August 2014–2015 to investigate seasonal variability in the insoluble precipitation particle sources. Fine dust particle (0.57–27 μm) depositions dominated in autumn and winter, whereas both fine and coarse dust particle (27–100 μm) depositions were found in spring and summer. Furthermore, the concentrations of Sr, Nd, and Pb also varied seasonally—the highest and lowest Sr and Nd concentrations were recorded in spring and autumn, respectively, whereas the highest and lowest Pb concentrations were recorded in winter and summer, respectively. The Sr and Nd isotopes revealed that the dust in the winter precipitation originated predominately from the Taklimakan Desert and that in spring originated from the Badain Jaran and Qaidam deserts. The precipitation residues in summer were derived from a complex mixture of dust sources from the Gobi and other large deserts in northwest China. Autumn residues were predominately sourced from local soil near the LHG as well as from the Qaidam Basin and the northern TP surface soil. The Taklimakan, long suspected as a major source of long-range transported dust, was an insignificant contributor to the precipitation over LHG during spring, summer, and autumn. Further, the Pb isotopic ratios indicated a primary impact of anthropogenic pollutants for most part of the year (except spring). Meteorological data and the MODIS AOD model are in good agreement with the results from the analyses of the Sr, Nd, and Pb isotopes for the LHG particle source, and further clarify the source regions. Thus, this study thus provides new evidence on the seasonal variability of the sources of the residual particles in remote glaciers in Central Asia.

We used the Weather Research and Forecasting Model coupled with Chemistry (WRF-Chem) to simulate elemental carbon (EC) concentrations in Thailand in 2017. The goals were to quantify the respective contributions of local emissions and regional transport outside Thailand to EC pollution in Thailand, and to identify the most effective emission control strategy for decreasing EC pollution. The simulated EC concentrations in Chiang Mai, Bangkok, and Phuket were comparable with the observation data. The correlation coefficient between the simulated and observed EC concentrations was 0.84, providing a good basis for evaluating EC sources in Thailand. The simulated mean EC concentration over the whole country was the highest (1.38 μg m⁻³) in spring, and the lowest (0.51 μg m⁻³) in summer. We conducted several sensitivity simulations to evaluate EC sources. Local emissions (including anthropogenic and biomass burning emissions) and regional transport outside Thailand contributed 81.2% and 18.8% to the annual mean EC concentrations, respectively, indicating that local sources played the dominant role for EC pollution in Thailand. Among the local sources, anthropogenic emissions (including the industry, power plant, residential, and transportation sectors) and biomass burning contributed 75.1% and 6.1% to the annual mean EC concentrations, respectively. As the anthropogenic emissions dominated the EC pollution, we performed four sensitivity simulations by reducing 30% of the emissions from each of the industry, power plant, residential, and transportation sectors in Thailand. The results indicated that controlling transportation emissions in Thailand was the most effective way in reducing the EC pollution. The 30% reduction of transportation emissions decreased the annual mean EC concentrations by 12.1%. In contrast, 30% reductions of the residential, industry, and power plant emissions caused 8.4%, 6.4%, and 4.0% decreases in the annual mean EC concentrations, respectively. The model results could potentially provide useful information for air pollution control strategies in Thailand.