The fetus is prenatally exposed to a mixture of organochlorine pesticides (OCPs), mercury (Hg), docosahexaenoic acid (DHA), eicosapentaenoic acid (EPA) and selenium (Se) through maternal seafood consumption in real-life scenario. Prenatal exposure to these contaminants and nutrients has been suggested to affect thyroid hormone (TH) status in newborns, but the potential relationships between them are unclear and the joint effects of the mixture are seldom analyzed. The aim of the study is to investigate the associations of prenatal exposure to a mixture of OCPs, Hg, DHA, EPA and Se with TH parameters in newborns. 228 mother-infant pairs in Shanghai, China were included. We measured 20 OCPs, total Hg, DHA, EPA and Se in cord blood samples as exposure variables. The total thyroxine (TT4), free thyroxine (FT4), total triiodothyronine (TT3), free triiodothyronine (FT3), and thyroid-stimulating hormone (TSH) levels and the FT3/FT4 ratio in cord serum were determined as outcomes. Using linear regression models, generalized additive models and Bayesian kernel machine regression, we found dose-response relationships of the mixture component with outcomes: among the contaminants, p,p'-DDE was the most important positive predictor of TT3, while HCB was predominantly positively associated with FT3 and the FT3/FT4 ratio, indicating different mechanisms underlying these relationships; among the nutrients, EPA was first found to be positively related to the FT3/FT4 ratio. Additionally, we found suggestive evidence of interactions between p,p'-DDE and HCB on both TT3 and FT3, and EPA by HCB interactions for TT3, FT3 and FT3/FT4 ratio. However, the overall effects of the mixture on thyroid hormone parameters were not significant. Our result suggests that prenatal exposure to p,p’-DDE, HCB and EPA as part of a mixture might affect thyroid function of newborns in independent and interactive ways. The potential biological mechanisms merit further investigation.

Around the world, green tides are happening with increasing frequency because of the dual effects of increasingly intense human activity and climate change; this leads to significant impacts on marine ecology and economies. In the last decade, the world's largest green tide, which is formed by Ulva/Enteromorpha porifera, has become a recurrent phenomenon every year in the southern Yellow Sea (China), and it has been getting worse. To alleviate the impacts of such green tide outbreaks, multiple measures need to be developed. Among these approaches, biotechnology plays important roles in revealing the outbreak mechanism (e.g., molecular identification technology for algal genotypes), controlling and preventing outbreaks at the origin sites (e.g., technology to inhibit propagation), and utilizing valuable algal biomass. This review focuses on the various previously used biotechnological approaches that may be applicable to worldwide seaweed blooms that result from global climate change and environmental degradation.

There has been an increasing interest in the pollution caused by meso- and microplastics (MMPs) in terrestrial ecosystems. Mulch film was once considered to be the most important source of MMPs in the mulching cultivated soil. However, the academic community has not given sufficient scientific evidence. In this study, stratified random sampling method was used to selectively interview households in Hebei province, China (400 households, 20 villages, 5 counties). Finally, household characteristics and mulch film use behavior of 41 households were collected, and corresponding soil samples were sampled. The results showed that 1) the abundance of MMPs was 29.3 ± 33.1 items·kg⁻¹ (DW) and the particle size of MMPs was 2.95 × 10³±1.75 × 10³ μm, and the proportion of MMPs derived from Polyethylene (PE) was only 18.8%; 2) the mass of MMPs was 2.90 ± 3.72 mg kg⁻¹ (DW) and the proportion of PE MMPs was 43.75%, which has the highest mass percentage; 3) After controlling the endogenous and dummy variables, the use history of mulch film (HistMF) was found to be positively correlated to the abundance of MMPs and inversely correlated to the particle size, but nor with the mass of MMPs; 4) Regarding the heterogeneous characteristics of MMPs, including particle size, color, shape, and type, the findings found the absence of a significant correlation between HistMF and the abundance and mass of PE. In summary, mulch-derived MMPs are not the primary source of MMPs in the mulching cultivated soil in terms of abundance but probably be in terms of mass.

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.

Rice consumption is the major pathway for human methylmercury (MeHg) exposure in inland China, especially in mercury (Hg) contaminated regions. MeHg production, a microbially driven process, depends on both the chemical speciation of inorganic divalent mercury, Hg(II), that determines Hg bioavailability for methylation. Studies have shown that Hg(II) speciation in contaminated paddy soils is mostly controlled by natural organic matter and sulfide levels, which are typically thought to limit Hg mobility and bioavailability. Yet, high levels of MeHg are found in rice, calling for reconsideration of the nature of Hg species bioavailable to methylators in paddy soils. Here, we conducted incubation experiments using a multi-isotope tracer technique including ¹⁹⁸Hg(NO₃)₂, natural organic matter bond Hg(II) (NOM-¹⁹⁹Hg(II)), ferrous sulfide sorbed Hg(II) (≡FeS-²⁰⁰Hg(II)), and nanoparticulate mercuric sulfide (nano-²⁰²HgS), to investigate the relative importance of geochemically diverse yet relevant Hg(II) species on Hg methylation in paddy soils across a Hg concentration gradient. We show that methylation rates for all Hg(II) species tested decreased with increasing Hg concentrations, and that methylation rates using NOM-¹⁹⁹Hg(II) and nano-²⁰²HgS as substrates were similar or greater than rates obtained using the labile ¹⁹⁸Hg(NO₃)₂ substrate. ≡FeS-²⁰⁰Hg(II) yielded the lowest methylation rate in all sites, and thus the formation of FeS is likely a sink for labile ¹⁹⁸Hg(NO₃)₂ in sulfide-rich paddy soils. Moreover, the variability in the methylation data for a given site (1 to 5-fold variation depending on the Hg species) was smaller than what was observed across the Hg concentration gradient (10³–10⁴ fold variation between sites). These findings emphasize that at broad spatial scales, site-specific characteristics, such as microbial community structure, need to be taken into consideration, alongside the nature of the Hg substrate available for methylation, to determine net MeHg production. This study highlights the importance of developing site-specific strategies for remediating Hg pollution.

The health risk induced by metal(loid)s in crops are becoming increasingly serious. In this study, eight major vegetables and rhizosphere soils were collected in a peri-urban area with intense electronic information manufacturing activities. The source, distribution and bioaccumulation of six typical metal(loid)s in different vegetable species were analyzed, and exposure risk through vegetable ingestion was estimated. Results showed that vegetables and agricultural soils in the study area suffered from serious metal(loid)s pollution, especially for Cd and Pb. The bioaccumulation capacity differed greatly among individual metal(loid)s and vegetable categories. In general, the highest transfer factors (TF) for Cd, Pb, and As were found in leafy vegetables, while leguminous vegetables had the highest TF of Cu and Zn and root vegetables had the highest TF for Cr. Significant correlations were found between concentrations in vegetables and rhizosphere soils for most metal(loid)s, the exceptions being Pb and Zn. The enrichment of Pb, Cd, Cr and As was mainly attributed to electronic information manufacturing activities, while the enrichment of Zn, Cu and Cd was associated with the application of commercial fertilizers and pesticides. The health risk associated with vegetable intake decreased in the order of leafy > fruit > leguminous > root vegetables. Leafy vegetables were identified as the category with the highest risk, with the mean risk value of 1.26. Cd was the major risk element for leafy vegetables. The non-carcinogenic risks estimated for leguminous and root vegetables were under the acceptable level. In conclusion, special attention should be paid to the health risks of toxic metal(loid)s in leafy vegetables in peri-urban areas with intense electronic information manufacturing activities. In order to minimize health risk, it is necessary to identify low-risk crops based on a comprehensive consideration of the metal(loid)s’ pollution characteristics, transfer factors and local people's consumption behaviors.

The Wang Lake Wetland is a highly valued area that is protected due to its high biodiversity. The wetland has a complicated hydrological regime and is subject to frequent human disturbance. We hypothesize that fluctuating hydrology and human activities have varied contributions to the temporal and spatial variations of polycyclic aromatic hydrocarbons (PAHs) in the wetland. Soil (SS), sediment (SD), and water, to acquire dissolved phase (DP) and suspended particulate matter (SPM), samples were collected from eight locations during low- and high-flow periods to elucidate multimedia phase distribution and transport of PAHs. Following the onset of the rainy season, the concentration of SPM-associated PAHs increased significantly, while the DP PAHs remained stable. Individual PAH ratios showed that, although pyrogenic sources are common, petrogenic derived compounds are the main source of PAHs in the Wang Lake Wetland. During the high-flow period, the empirical values for logarithms of the organic carbon-normalized partition coefficients (log KOC) of individual PAH-congeners were lower than the corresponding field-observed log KOC values from the SPM-DP and SD-DP systems, reflecting the complexity in evaluating multi-phase PAH partitioning. During the high-flow period, temperature-driven changes may have changed the sediment from a sink to a source for some high molecular weight PAHs. It was determined that human activities governed the PAH loading in the low-flow period, whereas during high-flow conditions, increased rainfall, higher temperatures, and fishery activity are the main factors controlling PAH input to the Wang Lake Wetland.

The most prominent source of Cu contamination in soils is metal mining and processing, partly since the Middle Age. However, coal mining and combustion can also cause (some) Cu contamination. We studied the distribution of Cu concentrations and isotope ratios in soils of the Huaibei coal mining area. The contribution of the coal mining and combustion to total Cu concentrations in soil was determined with a two-end-member mixing model based on the distinct δ⁶⁵Cu values of the Cu emitted from coal mining and combustion and in native soil. The mean Cu concentration of 75 mg kg⁻¹ exceeded the local soil background value (round to 22.13 mg kg⁻¹). The similar δ⁶⁵Cu value of grass near the coal mining and combustion operation as in gangue and flying ash indicated a superficial Cu contamination. Mining input was the dominant source of Cu in the contaminated soils, contributing up to 95% and on average 72% of the total Cu in the topsoils. The mining-derived Cu was leached to a depth of 65 cm, where still 29% of the Cu could be attributed to the mining emissions. Grasses showed lower δ⁶⁵Cu values than the topsoils, because of the preferential uptake of light Cu isotopes. However, the Δ⁶⁵Cugᵣₐₛₛ₋ₛₒᵢₗ was lower in the contaminated than the uncontaminated area because of superficial adsorption of isotopically heavy Cu from the mining emissions. Overall, in this study the distinct δ⁶⁵Cu values of the mining-derived Cu emissions and the native soil allowed for the quantification of the mining-derived Cu and had already reached the subsoil and contaminated the grass by superficial adsorption in only 60 years of mining operation.

China is the largest CO₂ emitting country on Earth. During the COVID-19 pandemic, China implemented strict government control measures on both outdoor activity and industrial production. These control measures, therefore, were expected to significantly reduce anthropogenic CO₂ emissions. However, large discrepancies still exist in the estimated anthropogenic CO₂ emission reduction rate caused by COVID-19 restrictions, with values ranging from 10% to 40% among different approaches. Here, we selected Nanchang city, located in eastern China, to examine the impact of COVID-19 on CO₂ emissions. Continuous atmospheric CO₂ and ground-level CO observations from January 1st to April 30th, 2019 to 2021 were used with the WRF-STILT atmospheric transport model and a priori emissions. And a multiplicative scaling factor and Bayesian inversion method were applied to constrain anthropogenic CO₂ emissions before, during, and after the COVID-19 pandemic. We found a 37.1–40.2% emission reduction when compared to the COVID-19 pandemic in 2020 with the same period in 2019. Carbon dioxide emissions from the power industry and manufacturing industry decreased by 54.5% and 18.9% during the pandemic period. The power industry accounted for 73.9% of total CO₂ reductions during COVID-19. Further, emissions in 2021 were 14.3–14.9% larger than in 2019, indicating that economic activity quickly recovered to pre-pandemic conditions.

Dyslipidemia may be a potential mechanism linking air pollution to adverse cardiovascular outcomes and this may differ among obese and normal-weight populations. However, the joint effect of multiple air pollutants on lipid profiles and the role of each pollutant are still unclear. This panel study aims to investigate and compare the overall associations of major air pollutants with lipid parameters in obese and normal-weight adults, and assess the relative importance of each pollutant for lipid parameters. Forty-four obese and 53 normal-weight young adults were recruited from December 2017 to June 2018 in Beijing, China. Their fasting blood was collected and serum lipid levels were measured in three visits. Six major air pollutants were included in this study, which were PM₂.₅, PM₁₀, NO₂, SO₂, O₃ and CO. Bayesian kernel machine regression (BKMR) was implemented to estimate the joint effect of the six air pollutants on various lipid parameters. We found that decreased high-density lipoprotein cholesterol (HDL-C) in the obese group and increased low-density lipoprotein cholesterol (LDL-C) and non-HDL-C in the normal-weight group were associated with the exposure to the mixture of six air pollutants above. Significant increases in total cholesterol (TC)/HDL-C and non-HDL-C/HDL-C were observed in both groups, and the effect was stronger in obese group. Of the six air pollutants above, O₃ had the largest posterior inclusion probability in above lipid indices, ranging from 0.75 to 1.00. In the obese group, approximately linear exposure-response relationships were observed over the whole range of logarithmic O₃-8 h max concentration, while in the normal-weight group, these relationships existed when the logarithmic concentration exceeded about 2.8. Therefore, lipid profiles of obese adults may be more sensitive to air pollution and this study highlights the importance of strengthening emissions control efforts for O₃ in the future.