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.

The biogeochemical cycling of sulfur in soil is closely associated with the mobility and bioavailability of heavy metals; however the influence of sulfur on the behavior of metal-based nanoparticles has not yet been studied. The influence of S fertilizer (S⁰ and Na₂SO₄) applied in paddy soils on CuO NPs behavior in soil pore water was explored in the present study. Synchrotron-based techniques were applied to investigate the migration and speciation transformation of CuO NPs in soil pore water colloids. The application of sulfur fertilizer increased the zeta potential of soil colloids from the rice rhizosphere region and reduced the size of the colloids. Sulfur fertilization decreased the concentration of Cu in soil pore water in the rice rhizosphere region. S⁰ fertilizer reduced the Cu concentration in soil colloids (by 55.8%–73.5%), while Na₂SO₄ increased the Cu concentration in soil colloids (by 173.8%–265.1%). Sulfur fertilization changed the spatial distribution of Fe³⁺ and Cu²⁺ in colloids, making these ions more likely to be aggregated on the edges of soil colloids. Speciation transformation of CuO NPs happened during the process of migration. The main Cu speciation in the soil colloids were CuO NPs, Cu-Cysteine, Cu₂S and Cu-Citrate. Sulfur fertilization increased the proportion of Cu₂S (by 40.5%) in soil pore water colloids from the rice rhizosphere region, while the proportion of CuO NPs was reduced (by 18.4%). Sulfur fertilization changed the morphology and elementary composition of colloids in soil pore water, thus influencing the migration of CuO NPs in the soil column through soil colloids.

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.

Potassium (K⁺) is the most abundant cation in phytoplankton cells, but its impact on Microcystis aeruginosa (M. aeruginosa) has not been fully documented. This study presents evidence of how K⁺ availability affects the growth, oxidative stress and microcystin (MC) production of M. aeruginosa. The iTRAQ-based proteomic analysis revealed that during K⁺ deficiency, serious oxidative damage occurred and the photosynthesis-associated and ABC transporter-related proteins in M. aeruginosa were substantially downregulated. In the absence of K⁺, a 69.26% reduction in cell density was shown, and both the photosynthesis and iron uptake were depressed, which triggered a declined production of ATP and expression of MC synthetases genes (mcyA, B and D), and MC exporters (mcyH). Through the impairment of both the MC biosynthesis and MC transportation out of cells, K⁺ depletion caused an 85.89% reduction of extracellular MC content at the end of the study. However, with increasing in the available K⁺ concentrations, photosynthesis efficiency, the expression of ABC-transporter proteins, and the transcription of mcy genes displayed slight differences compared with those in the control group. This work represents evidence that K⁺ availability can regulate the physiological metabolic activity of M. aeruginosa and K⁺ deficiency leads to depressed growth and MC production in M. aeruginosa.

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.

Anti-sea lice pesticides, used in the salmonid aquaculture industry, are a growing environmental concern due to their potential to adversely affect non-target crustaceans. Azamethiphos and deltamethrin are two bath treatment pesticides used on salmon farms in Norway, however, limited information is available on their impact on European lobster (Homarus gammarus) larvae in the Norwegian marine environment. Here, we firstly report the lethal (LC₅₀) and effective (EC₅₀) concentrations of azamethiphos and deltamethrin for stage I and stage II larvae, following 1-h exposures. Using a hydrodynamic model, we also modelled the dispersal of both compounds into the marine environment around selected Norwegian farms and mapped the potential impact zones (areas that experience LC₅₀ and EC₅₀ concentrations) around each farm. Our data shows that azamethiphos and deltamethrin are acutely toxic to both larval stages, with LC₅₀ and EC₅₀ values below the recommended treatment concentrations. We also show that the azamethiphos impact zones around farms were relatively small (mean area of 0.04–0.2 km²), however deltamethrin impact zones covered much larger areas (mean area of 21.1–39.0 km²). These findings suggest that deltamethrin poses a significant risk to European lobster in the Norwegian marine environment while the impact of azamethiphos may be less severe.

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.

Microplastics have attracted much attention in recent years because they are able to interact with other pollutants including pesticides, with implications for the potential risks to biota. However, the sorption behavior of pesticides on microplastics, especially on biodegradable microplastics which are promising alternatives to conventional polymers, has been insufficiently studied. In this study, triadimefon and difenoconazole were selected as model triazole fungicides, and their sorption behavior on a typical biodegradable microplastics (PBS: polybutylene succinate) and two conventional polyethylene (PE) and polyvinyl chloride (PVC) microplastics was investigated with batch experiments in an aqueous solution. PBS presented the highest sorption capacity for triadimefon (104.2 ± 4.8 μg g⁻¹) and difenoconazole (192.8 ± 2.3 μg g⁻¹), which was 1.8- and 1.3-fold that on PE and 4.4- and 7.4-fold that of PVC, respectively. The results of sorption kinetic and isotherm modeling were better fit by a pseudo-second order model and linear model, respectively. More importantly, the effects of environmental factors (pH, salinity and dissolved organic matter) on the sorption behavior were investigated. Fungicide sorption on PBS was generally not affected by salinity, pH or dissolved organic matter. However, in contrast, salinity and dissolved organic matter both significantly decreased sorption on PE and PVC. The results showed that not only the sorption capacities of biodegradable microplastics but also their responses to environmental factors are quite different from those of conventional microplastics. This finding highlights the importance of the role played by biodegradable microplastics in the accumulation and transportation of organic pollutants.

In predicting palm oil mill effluent (POME) degradation efficiency, previous developed quadratic model quantitatively evaluated the effects of O2 flowrate, TiO2 loadings and initial concentration of POME in labscale photocatalytic system, which however suffered from low generalization due to the overfitting behaviour. Evidently, high RMSE (131.61) and low R₂ (−630.49) obtained indicates its insufficiency in describing POME degradation at unseen factor ranges, hence verified the fact of poor generalization. To overcome this issue, several models were developed via machine learning-assisted techniques, namely Gaussian Process Regression (GPR), Linear Regression (LR), Decision Tree (DT), Supported Vector Machine (SVM) and Regression Tree Ensemble (RTE), subsequently being assessed systematically. To achieve high generalization, all models were subjected to ‘train-all-test-all’ strategy, 5-fold and 10-fold cross validation. Specifically, GPR model was furnished with high accuracy in ‘train-all-test-all’ strategy, judging from its low RMSE (1.0394) and high R₂ (0.9962), which however menaced by the risk of overfitting. In contrast, despite relatively poorer RMSE and R₂ (1.7964 and 0.9886) obtained in 5-fold cross validation, GPR model was rendered with highest generalization, while sufficiently preserving its accuracy in development process. Besides, SVM and RTE models were also demonstrated promising R₂ (0.9372 and 0.9208), which however shadowed by their high RMSEs (4.2174 and 4.7366). Furthermore, the extraordinary generalization of GPR model was coincidentally verified in 10-fold cross validation. The lowest RMSE (2.1624) and highest R₂ (0.9835) obtained with feature number of 36 asserted its sufficiency in both generalization and accuracy prospect. Other models were all rendered with slight lower R₂ (> 0.9), plausibly due to the higher RMSE (> 4.0). According to GPR model, optimized POME degradation (52.52%) can be obtained at 70 mL/min of O₂, 70.0 g/L of TiO₂ and 250 ppm of POME concentration, with only ∼3% error as compared to the actual data.

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.