The relation between pesticides exposure and metabolic syndrome (MetS) has not been clearly identified. Performing a systematic review and meta-analysis, PubMed, Cochrane Library, Embase, and ScienceDirect were searched for studies reporting the risk of MetS following pesticides exposure and their contaminants. We included 12 studies for a total of 6789 participants, in which 1981 (29.1%) had a MetS. Overall exposure to pesticides and their contaminants increased the risk of MetS by 30% (95CI 22%–37%). Overall organochlorine increased the risk of MetS by 23% (14–32%), as well as for most types of organochlorines: hexachlorocyclohexane increased the risk by 53% (28–78%), hexachlorobenzene by 40% (0.01–80%), dichlorodiphenyldichloroethylene by 22% (9–34%), dichlorodiphenyltrichloroethane by 28% (5–50%), oxychlordane by 24% (1–47%), and transnonchlor by 35% (19–52%). Sensitivity analyses confirmed that overall exposure to pesticides and their contaminants increased the risk by 46% (35–56%) using crude data or by 19% (10–29%) using fully-adjusted model. The risk for overall pesticides and types of pesticides was also significant with crude data but only for hexachlorocyclohexane (36% risk increase, 17–55%) and transnonchlor (25% risk increase, 3–48%) with fully-adjusted models. Metaregressions demonstrated that hexachlorocyclohexane increased the risk of MetS in comparison to most other pesticides. The risk increased for more recent periods (Coefficient = 0.28, 95CI 0.20 to 0.37, by year). We demonstrated an inverse relationship with body mass index and male gender. In conclusion, pesticides exposure is a major risk factor for MetS. Besides organochlorine exposure, data are lacking for other types of pesticides. The risk increased with time, reflecting a probable increase of the use of pesticides worldwide. The inverse relationship with body mass index may signify a stockage of pesticides and contaminants in fat tissue.

Ground-based Multi-Axis Differential Optical Absorption Spectroscopy (Max-DOAS) measurements of nitrogen dioxide (NO₂) were continuously obtained from January to November 2019 in northeastern China (NEC). Seasonal variations in the mean NO₂ vertical column densities (VCDs) were apparent, with a maximum of 2.9 × 10¹⁶ molecules cm⁻² in the winter due to enhanced NO₂ emissions from coal-fired winter heating, a longer photochemical lifetime and atmospheric transport. Daily maximum and minimum NO₂ VCDs were observed, independent of the season, at around 11:00 and 13:00 local time, respectively, and the most obvious increases and decreases occurred in the winter and autumn, respectively. The mean diurnal NO₂ VCDs at 11:00 increased to at 08:00 by 1.6, 5.8, and 6.7 × 10¹⁵ molecules cm⁻² in the summer, autumn and winter, respectively, due to increased NO₂ emissions, and then decreased by 2.8, 4.2, and 5.1 × 10¹⁵ molecules cm⁻² at 13:00 in the spring, summer, and autumn, respectively. This was due to strong solar radiation and increased planetary boundary layer height. There was no obvious weekend effect, and the NO₂ VCDs only decreased by about 10% on the weekends. We evaluated the contributions of emissions and transport in the different seasons to the NO₂ VCDs using a generalized additive model, where the contributions of local emissions to the total in the spring, summer, autumn, and winter were 89 ± 12%, 92 ± 11%, 86 ± 12%, and 72 ± 16%, respectively. The contribution of regional transport reached 26% in the winter, and this high contribution value was mainly correlated with the northeast wind, which was due to the transport channel of air pollutants along the Changbai Mountains in NEC. The NO₂/SO₂ ratio was used to identify NO₂ from industrial sources and vehicle exhaust. The contribution of industrial NO₂ VCD sources was >66.3 ± 16% in Shenyang due to the large amount of coal combustion from heavy industrial activity, which emitted large amounts of NO₂. Our results suggest that air quality management in Shenyang should consider reductions in local NO₂ emissions from industrial sources along with regional cooperative control.

Many cities across the world face the challenge of severe fine particulate matter (PM₂.₅) pollution. Among the many factors that affect PM₂.₅ pollution, there is an increasing interest in the impacts of urban structure. However, quantifying these impacts in China has been difficult due to differences of study area and scale in existing research, as well as limited sample sizes. Here, we conducted a continental study focusing on 301 prefectural cities in mainland China to investigate the effects of urban structure, including urban size and urban compactness, on PM₂.₅ concentrations. Based on PM₂.₅ raster and land cover data, we used quantile regression and a general multilinear model to estimate the effects and relative contributions of urban size and urban compactness on urban PM₂.₅ pollution, with explicit consideration for pollution level, urban size and geographical location. We found: (1) nationwide, the larger and more compact that cities were, the heavier the PM₂.₅ pollution tended to be. Additionally, this relationship became stronger with increasing levels of pollution. (2) In general, urban size played a more important role than urban form, and there were no significant interactive effects between the two metrics on urban PM₂.₅ concentrations at the national scale. (3) The impacts of urban size and form varied by city size and geographical location. The impacts of urban size were only significant for small or medium-large cities but not for large cities. Among large cities, only urban form had a significantly positive effect on urban PM₂.₅ concentrations. The further north and west that cities were, the more dependent PM₂.₅ pollution was on urban form, whereas the further south and east that cities were, the greater the impact of urban size. These results provide insights into how urban design and planning can be used to alleviate air pollution.

The concentration of persistent organic pollutants (POPs) makes remarkable difference to environmental fate. In the field of passive sampling, the partition coefficients between polystyrene-divinylbenzene resin (XAD) and air (i.e., KXAD₋A) are indispensable to obtain POPs concentration, and the KXAD₋A is generally thought to be governed by temperature and molecular structure of POPs. However, experimental determination of KXAD₋A is unrealistic for countless and novel chemicals. Herein, the Abraham solute descriptors of poly parameter linear free energy relationship (pp-LFER) and temperature were utilized to develop models, namely pp-LFER-T, for predicting KXAD₋A values. Two linear (MLR and LASSO) and four nonlinear (ANN, SVM, kNN and RF) machine learning algorithms were employed to develop models based on a data set of 307 sample points. For the aforementioned six models, R²ₐdⱼ and Q²ₑₓₜ were both beyond 0.90, indicating distinguished goodness-of-fit and robust generalization ability. By comparing the established models, the best model was observed as the RF model with R²ₐdⱼ = 0.991, Q²ₑₓₜ = 0.935, RMSEₜᵣₐ = 0.271 and RMSEₑₓₜ = 0.868. The mechanism interpretation revealed that the temperature, size of molecules and dipole-type interactions were the predominant factors affecting KXAD₋A values. Concurrently, the developed models with the broad applicability domain provide available tools to fill the experimental data gap for untested chemicals. In addition, the developed models were helpful to preliminarily evaluate the environmental ecological risk and understand the adsorption behavior of POPs between XAD membrane and air.

Recently, with the rapid development of China's economy, the pollution of trace metal(loid)s (TMs) in soils has become increasingly severe and attracted widespread attention. Based on 1,402 published papers from 2000 to 2021, this study aimed to analyze the pollution intensity, ecological risk and driving factors for eight TMs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) in Chinese soils. Results showed that the average concentrations of eight TMs in Chinese soils all exceeded background values, and the pollution of Cd and Hg was the most serious. Based on Principal component analysis of pollution intensity and ecological risk, the priority control TMs were identified for the heavily polluted provinces. The results of Geo-detector model suggested that Urban development factors contributed most to the TM accumulation in Chinese soils. Further, spatial analysis using bivariate Moran's I indicated that industrial activities contributed most to soil TM accumulation in the middle and lower reaches of the Yangtze River, while soil TM pollution in the southwest and northwest provinces was mainly caused by mining and metal smelting. This study investigated the relationship between soil TM pollution and anthropogenic activities, thus providing a scientific basis for controlling soil TM pollution at a large-scale level.

DO₃SE (Deposition of Ozone for Stomatal Exchange), is a dry deposition model, designed to assess tropospheric ozone risk to vegetation, and is based on two alternative algorithms to estimate stomatal conductance: multiplicative and photosynthetic. The multiplicative model has been argued to perform better for leaf-level and regional-level application. In this study, we demonstrate that the photosynthetic model is superior to the multiplicative model even for leaf-level studies using measurements performed on Mangifera indica. We find that the multiplicative model overestimates the daytime stomatal conductance, when compared with measured stomatal conductance and prescribes zero conductance at night while measurements show an average conductance of 100 mmol(H₂O)m⁻²s⁻¹ between 9 p.m. and 4 a.m. The daytime overestimation of the multiplicative model can be significantly reduced when the model is modified to include a response function for ozone-induced stomatal closure. However, nighttime pollutant uptake fluxes can only be accurately assessed with the photosynthetic model which includes the stomatal opening at night during respiration and is capable of reproducing the measured nighttime stomatal conductance. At our site, the nocturnal flux contributes 64%, 39%, 46%, and 88% of the total for NO₂ uptake in winter, summer, monsoon, and post-monsoon, respectively. For SO₂, nocturnal uptake amounts to 35%, 28%, 28%, and 44% in winter, summer, monsoon, and post-monsoon, respectively while for ozone the nighttime uptake contributes 30%, 17%, 18%, and 29% of the total stomatal uptake in winter, summer, monsoon, and post-monsoon respectively.

Mangroves play a vital role in protecting the coastal community from the climate change effect and in the restoration of the coastal ecosystem. This research has been designed to determine the spatial and seasonal changes of potentially toxic elements’ (PTEs) concentration in sediments and their potential source contribution among the different human-driven processes in Sundarbans, Bangladesh. Different pollution evaluation indices, random forest (RF) model, conditional inference tree (CIT), self-organizing map (SOM), geographical information system (GIS), and principal component analysis (PCA) were used for the interpretation of sources and risk assessment of PTEs. The mean concentration of PTEs both in winter and monsoon seasons has fallen below the threshold effect level but exceeded the rare effect level of marine sediments quality standards. Results showed that the PTEs were significantly enriched (EF > 1.00 < 70.00) in sediments, whereas the Cd enrichment (7.00% samples) was very alarming (EF = 60–70). Except for Zn and Cd, other PTEs were enriched in 30–60% samples. The highest geoaccumulation and contamination factors for Cd were observed in 46–72% of samples. The ecological risk (ER) factors showed similar results where Cd showed strong to very strong factors (ER = 110–2218) in 80% of samples. The CIT explained the natural/geogenic and anthropogenic sources of pollution, where the higher CIT values for Cd indicated industrial, aquaculture, and coal-based thermal powerplant. The RF model provided that shrimp firms, power plants, industry, and seaport were recognized as the influential sources for Zn, Pb, Cr, Cd, and As in sediments. Though Pb and As were found as the most significant pollutants, Cd was identified as a severe threat to ecology and public health. Based on CIT, RF, SOM and PCA the order of PTEs in mangroves sediment were:industrial/urban > aquaculture/shrimpfirm > powerplant > seaportoperation > tourism > geogenic/natural. The present study will help the policymakers for effective and sustainable management of the mangrove ecosystem.

The increased frequency and intensity of short-term extreme warming phenomena have been associated to harsh biological and ecosystem outcomes (i.e., mass mortalities in marine organisms). Marine heatwaves (MHWs), occurring when seasonal temperature threshold is exceeded for at least 5 consecutive days, may reduce the tolerance of coastal species toward additional pressures, but interactions between such multiple stressors are virtually unexplored. The present study aimed to characterize in Mytilus galloprovincialis the influence of a simulated MHW scenario on the toxicological effects of the pharmaceutical carbamazepine (CBZ), ubiquitously detected in the marine environment and chosen as model compound for this relevant class of emerging contaminants. The bioaccumulation of CBZ and responsiveness of various biological parameters, including immune system, antioxidant status, lipid metabolism and cellular integrity, were analyzed in exposed mussels both during and after the end of the heatwave. MHW appeared to strongly modulate accumulation of CBZ, paralleled by weakened immunocompetence and onset of oxidative disturbance that finally evolved to cellular damages and lipid metabolism disorders. Elaboration of the overall results through a quantitative Weight of Evidence model, revealed the highest hazard in organisms exposed to both the stressors 10 days after the end of the heatwave, suggesting that MHWs could leave a footprint on the capability of mussels to counteract CBZ toxicity, thus affecting their vulnerability and predisposition to adverse effects toward multiple stressors.

Tetrabromobisphenol A (TBBPA) and its substitutes and derivatives have been widely used as halogenated flame retardants (HFRs), in the past few decades. As a consequence, these compounds are frequently detected in the environment, as well as human bodily fluids, especially umbilical cord blood and breast milk. This has raised awareness of their potential risks to fetuses and infants. In this study, we employed human embryonic stem cell differentiation models to assess the potential developmental toxicity of six TBBPA-like compounds, at human relevant nanomolar concentrations. To mimic early embryonic development, we utilized embryoid body-based 3D differentiation in presence of the six HFRs. Transcriptomics data showed that HFR exposure over 16 days of differentiation only interfered with the expression of a few genes, indicating those six HFRs may not have specific tissue/organ targets during embryonic development. Nevertheless, further analyses revealed that some cardiac-related genes were dysregulated. Since the heart is also the first organ to develop, we employed a cardiac differentiation model to analyze the six HFRs’ potential developmental toxicity in more depth. Overall, HFRs of interest did not significantly disturb the canonical WNT pathway, which is an essential signal transduction pathway for cardiac development. In addition, the six HFRs showed only mild changes in gene expression levels for cardiomyocyte markers, such as NKX2.5, MYH7, and MYL4, as well as a significant down-regulation of some but not all the epicardial and smooth muscle cell markers selected. Taken together, our results show that the six studied HFRs, at human relevant concentrations, may impose negligible effects on embryogenesis and heart development. Nevertheless, higher exposure doses might affect the early stages of heart development.

Carbonaceous aerosols pose significant climatic impact, however, their sources and respective contribution to light absorption vary and remain poorly understood. In this work, filter-based PM₂.₅ samples were collected in winter of 2021 at three urban sites in Yibin, a fast-growing city in the south of Sichuan Basin, China. The composition characteristics of PM₂.₅, light absorption and source of carbonaceous aerosol were analyzed. The city-wide average concentration of PM₂.₅ was 87.4 ± 31.0 μg/m³ in winter. Carbonaceous aerosol was the most abundant species, accounting for 42.5% of the total PM₂.₅. Source apportionment results showed that vehicular emission was the main source of PM₂.₅ during winter, contributing 34.6% to PM₂.₅. The light absorption of black carbon (BC) and brown carbon (BrC) were derived from a simplified two-component model. We apportioned the light absorption of carbonaceous aerosols to BC and BrC using the Least Squares Linear Regression with optimal angstrom absorption exponent of BC (AAEBC). The average absorption of BC and BrC at 405 nm were 51.6 ± 21.5 Mm⁻¹ and 17.7 ± 8.0 Mm⁻¹, respectively, with mean AAEBC = 0.82 ± 0.02. The contribution of BrC to the absorption of carbonaceous reached 26.1% at 405 nm. Based on the PM₂.₅ source apportionment and the mass absorption cross-section (MAC) value of BrC at 405 nm, vehicle emission was found to be the dominant source of BrC in winter, contributing up to 56.4%. Therefore, vehicle emissions mitigation should be the primary and an effective way to improve atmospheric visibility in this fast-developing city.