Although huge interspecies differences in the response to dioxins have been acknowledged, toxic equivalency factors derived from rodent studies are often used to assess human health risk. To determine interspecies differences, we first developed a toxicokinetic model in humans by measuring dioxin concentrations in environmental and biomonitoring samples from Southern China. Significant positive correlations between dioxin concentrations in blood and age were observed for seven dioxin congeners, indicating an age-dependent elimination rate. Based on toxicokinetic models in humans, the half-lives of 15 dioxin congeners were estimated to be 1.60–28.55 years. In consideration that the highest contribution to total toxic equivalency in blood samples was by 12378-polychlorinated dibenzo-p-dioxin (P₅CDD), this study developed a physiologically based pharmacokinetic (PBPK) model of 12378-P₅CDD levels in the liver, kidney, and fat of C57/6J mice exposed to a single oral dose, and the half-life was estimated to be 26.1 days. Based on estimated half-lives in humans and mice, we determined that the interspecies difference of 12378-P₅CDD was 71, much higher than the default usually used in risk assessment. These results could reduce the uncertainty human risk assessment of 12378-P₅CDD, and our approach could be used to estimate the interspecies differences of other dioxin congeners.

In recent years, with the expansion of the Weining county in the northeast of Caohai wetland, the construction of a new port in the north, and the large-scale development of cultivated land in the east, land use patterns in lakeshore areas have changed. These changes have affected the state of lake shores water bodies in complex ways, resulting in varying degrees of local water pollution. To explore the distribution and transformation characteristics of water chemistry and heavy metals in different areas of a water body under the influence of different land uses, especially the interactions between water chemical factors and heavy metals in different areas of a water body, this study used Circos diagrams, originally used in biological genetic analysis, to visualize these interactions. This is the first time that the Circos diagram has been applied to the analysis of environmental interactions. The results showed that there are significant differences in the distribution of water chemical factors and heavy metals in different areas of the Caohai wetland. In particular, Cd is affected by anthropogenic sources. The Cd content is higher in the NCL and UL areas, which are at greater risk from pollution. The factors controlling heavy metal levels in water bodies were different in the different regions. The NCL region was mainly affected by construction excavation ore, UL was mainly affected by man-made industrial inputs, CL was mainly affected by pesticide and fertilizer inputs, and ML and FL were mainly affected by Eh and DO. The PCA results showed that the sources of heavy metals in different types of water bodies in the lakeshore zone were both natural and anthropogenic. Therefore, controlling pollutants, reducing environmental pollution inputs to the lakeshore zone, and strengthening supervision and management near wetlands may be of great significance for handling heavy metal pollution.

Microplastic pollution in estuarine and coastal environments has recently been characterised in several countries but few researchers have addressed the influence of different forms of coastal zone use on the distribution of microplastic. Here, microplastic particles were sampled in Hangzhou Bay, which is heavily influenced by a range of human activities, and their abundance, size, and polymer type characterised. The abundance of microplastics was 0.14 ± 0.12 items/m³ in water, 84.3 ± 56.6 items/kg dry weight of sediment, and between 0.25 ± 0.14 and 1.4 ± 0.37 items/individual in biota. These results show that Hangzhou Bay has a low level of microplastic contamination compared to other coastal systems in China, although abundance was spatially variable within the bay; relatively higher microplastic abundances were found in the southern area of the bay, which has adjacent industrial and urban land-use zones, while lower abundances were observed in the central and northern bay areas where mariculture, fisheries, and mineral and energy industries are most common. The relatively low microplastic abundance observed in the biota samples is consistent with the generally low values for the seawater and sediment samples. Pellets were the most common of four particle-shape classes (fibres, fragments, films, and pellets) in surface seawater, while fibres were most abundant in sediment and biota. Smaller-sized microplastics (<1.0 mm) were dominant in all samples. Microplastics in the surface seawater were dominated by low-density polypropylene and polyethylene particles, while rayon was dominant in the sediment and biota samples. Our results demonstrate that regional variability in anthropogenic activity and land-use are important controls on the spatial pattern of microplastic pollution in Hangzhou Bay.

To accurately visualize the spatial distribution of heavy metal pollution and provide basic information on soil remediation in dairy farm, Geographic Information System (GIS) is used for optimization of sample collection and data analysis. Based on GIS technology, dairy manure, 10 cm-depth surface soil, 50 cm-depth sub soil, and surface water samples were collected from dairy farm in Dulbert Mongolian Autonomous County, Daqing City, Heilongjiang Province in China. The spatial distribution and assessment of heavy metals were performed by using GIS inverse distance weighted interpolation and pollution index method. The single factor pollution index value of As element in the soil was found to indicate the class of extreme contamination, whereas Ni in both surface water inside and outside the farm, and Sb in the cow drinking water were assigned to the level of moderate contamination. The comprehensive pollution index implied serious contamination for soil samples, slight contamination for water samples and safety for manure samples, respectively. Comprehensive score for heavy metal elements followed the orders of As>Zn>Cr>Ni>Cu>Pb>Cd>Hg. The horizontal pollution that mainly occurred in the middle and east regions was increased from north to south, and west to east district. Historically, the dairy farm belonged to heavily polluted saline-alkali soil, where the heavy metals might enter the food chain through transportation from soil to water, the cows, and eventually to the milk and human body. Visualizing spatial distribution of heavy metal contamination by using GIS technology will be of significance to provide useful information for soil remediation of dairy farm.

In recent years, implementation of aggressive and strict clean air policies has resulted in significant decline in observed PM₂.₅ concentration in the Beijing–Tianjin–Hebei (BTH) region and its surrounding areas (i.e., the “2 + 26” region). To eliminate the effects of interannual and seasonal meteorological variation, and to evaluate the effectiveness of emission abatement policies, we applied a boosted regression tree model to remove confounding meteorological factors. Results showed that the annual average PM2.5 concentration normalized by meteorology for the “2 + 26” region declined by 38% during 2014–2019 (i.e., from 96 to 60 μg/m³); however, the BTH region exhibited the most remarkable decrease in PM₂.₅ concentration (i.e., a 60% reduction). Certain seasonal trend in normalized PM₂.₅ level remained for four target subregions owing to the effects of anthropogenic emissions in autumn and winter. Although strong interannual variations of meteorological conditions were unfavorable for pollutant dispersion during the heating seasons of 2016–2018, the aggressive abatement policies were estimated to have contributed to reductions in normalized PM₂.₅ concentration of 19%, 10%, 19%, and 17% in the BTH, Henan, Shandong, and Shanxi subregions, respectively. Our study eliminated the meteorological contribution to concentration variation and confirmed the effectiveness of the implemented clean air policies.

Over three different seasons, seawater, porewater and sediment samples were collected from Jinzhou Bay, a previously heavily contaminated bay, to quantitatively assess the benthic flux of trace metals after a reduction in fluvial/sewage discharge for almost three decades. The spatial distribution patterns of trace metals in seawater, surface sediment, as well as the vertical distribution patterns of metals in porewater and solid phases in short sediment cores were reported. Metal concentrations in seawater and sediment all showed much higher Cd and Zn concentrations inside the Jinzhou Bay compared to the rest of Bohai Sea area. Zn, Ni, Pb and Co all had average benthic fluxes coming out of the sediments to the water column, contributing about 0.5%, 0.3%, 1.4% and 14% to their current standing stock in Jinzhou Bay. Seasonal difference was also identified in seawater and porewater, as well as in the benthic fluxes. In general, benthic fluxes and porewater concentrations all tended to be higher in summer, implying a close relationship between benthic flux and the temperature-dependent organic matter degradation process at the sediment-water interface.Currently, there are clearly still other sources, possibly fluvial/sewage discharge, as the main source of trace metals in Jinzhou Bay waters. For Cd and Cu, concentrations in the water column remain high on an annual basis indicating that sediment still acts as a sink. Conversely, for Pb, Zn, Co, and Ni, the sediment is beginning to act as a source to the water column. Although this may not yet be significant, it will become more and more important with time, and can last for hundreds to thousands of years.

Quantifying methane (CH₄) emissions from paddy fields is essential for evaluating the environmental risks of the paddy rice production system, and improving the accuracy of CH₄ modeling is a key issue that needs to be addressed. Based on a database containing 835 field measurements, both single national and region-specific models were established to estimate CH₄ emissions from paddy fields considering different environmental factors and management patterns using 70% of the measurements. The remaining 30% of the measurements were then used for model evaluation. The performance of the region-specific model was better than that of the single national model. The region-specific model could simulate CH₄ emissions in an unbiased manner with R² values of 0.15–0.70 and efficiency values of 11–60%. The paddy rice type, water regime, organic amendment, latitude, and soil characteristics (pH and bulk density) were identified as the main drivers in the models. By inputting the high-resolution spatial data of these drivers into the established model, the CH₄ emissions from China’s paddy fields were estimated to be 4.75 Tg in 2015, with a 95% confidence interval of 4.19–5.61 Tg. The results indicated that establishing and driving a region-specific model with high-resolution data can improve the estimation accuracy of CH₄ emissions from paddy fields.

Both air pollution and dyslipidemias contributed to large number of deaths and disability-adjusted life lost years. Long-term air pollution exposure was related to changed blood lipids and risk of dyslipidemias. This study was designed to evaluate relationships between air pollutants, blood lipids and prevalence of dyslipidemias in a Chinese rural population exposed to high-level air pollution based on baseline data of The Henan Rural Cohort study. An amount of 39,057 participants from rural areas in China were included. The 3-year average exposure of air pollutants (PM2.5, PM10, NO2) was estimated by a spatiotemporal model. Logistic and linear regression models were employed to explore relationships between air pollutants, blood lipids (TC, TG, HDL-C and LDL-C) and prevalence of dyslipidemias. The three-year concentration of PM2.5, PM10 and NO2 was 72.8 ± 2.3 μg/m3, 131.5 ± 5.7 μg/m3and 39.1 ± 3.1 μg/m3, respectively. Overall, increased air pollution exposure was related to increased TC and LDL-C, while decreased TG and HDL-C. Each 1-μg/m3 increment of PM2.5 was related to 0.10% (0.07%–0.19%) increase in TC, 0.63% (0.50%–0.77%) increase in LDL-C, 2.93% (2.70%–3.16%) decrease in TG, 0.49% (0.38%–0.60%) decrease in HDL-C; and 5.7% (95%CI: 3.7%–7.6%), 4.0% (95%CI: 2.1%–6.0%) and 3.8% (95%CI: 2.5%–5.1%) increase in odds for hypercholesterolemia, hyperbetalipoproteinemia and hypoalphalipoproteinemia, respectively. Stronger associations were found in male and older participants. Findings suggest that air pollutants were associated with changed blood lipid levels and higher risk of dyslipidemias among rural population. Male and elder people should pay more attention to personal safety protection.

Northern China is a significant source of dust source in Central Asia. Thus, high-resolution analysis of dust storms and comparison of dust sources in different regions of northern China are important to clarify the formation mechanism of East Asian dust storms and predict or even prevent such storms. Here, we analyzed spatiotemporal trends in dust storms that occurred in three main dust source regions during 1960–2007: Taklimakan Desert (western region [WR]), Badain Jaran and Tengger Deserts (middle region [MR]), and Otindag Sandy Land (eastern region [ER]). We analyzed daily dust storm frequency (DSF) at the 10-day scale (first [FTDM], middle [MTDM], and last [LTDM] 10 days of a month), and investigated the association of dust storm occurrences with meteorological factors. The 10-day DSF was greatest in the FTDM (accounting for 77.14% of monthly occurrences) in the WR, MTDM (45.85%) in the MR, and LTDM (72.12%) in the ER, showing a clear trend of movement from the WR to the ER. Temporal analysis of DSF revealed trend changes over time at annual and 10-day scales, with mutation points at 1985 and 2000. We applied single-factor and multiple-factor analyses to explore the driving mechanisms of DSF at the 10-day scale. Among single factors, a low wind-speed threshold, high solar radiation, and high evaporation were correlated with a high DSF, effectively explaining the variations in DSF at the 10-day scale; however, temperature, relative humidity, and precipitation poorly explained variations in DSF. Similarly, multiple-factor analysis using a classification and regression tree revealed that maximum wind speed was a major influencing factor of dust storm occurrence at the 10-day scale, followed by relative humidity, evaporation, and solar radiation; temperature and precipitation had weak influences. These findings help clarify the mechanisms of dust storm occurrence in East Asia.

Large amounts of wastewater discharge have emerged as a burden in the process of industrialization and urbanization. In this study, a dynamic wastewater-induced input-output model is developed to systematically analyze the related situation. The developed model is applied to Guangdong Province, China to analyze its prominent characteristics from 2002 to 2015. Combining input-output analysis, ecological network analysis and structural decomposition analysis, the developed model reveals issues of direct and indirect discharges, relationships among various discharges, and driving forces of wastewater discharges. It is uncovered that Primary Manufacturing and Advanced Manufacturing dominate the system because of significant temporal and spatial variations in wastewater discharge. In addition, Manufacturing of paper, computer and machinery and Services are the key industries responsible for large amounts of wastewater discharge and unhealthy source-discharge relationships. The largest wastewater discharge occurred in 2005 and indirect wastewater discharge is the main form. Furthermore, final demand is found to be the biggest driving force of wastewater discharge. Finally, a three-phase policy implementation system implemented in stages proposes solutions to wastewater problems.