In this study, a novel approach was employed for the remediation of cationic and anionic metals/metalloids co-contaminated soil by tetrapolyphosphate enhanced soil washing coupled with ferrous sulfide treatment. Tetrapolyphosphate could simultaneously enhance the desorption of cationic metals (Pb and Zn) and anionic metal/metalloid (Cr and As) from the contaminated soil in the whole tested pH range of 2–10. With addition of 0.15 mol/L tetrapolyphosphate at pH 7.0, the removal ratio of Pb, Zn, As and Cr could achieve 83.1%, 70.4%, 75.7% and 66.4% respectively. The fractionation analysis of heavy metals/metalloids demonstrated the release of exchangeable and Fe/Mn bound forms contributed to most desorption of Pb and Zn. The decreases of non-specifically sorbed form and amorphous and poorly-crystalline hydrous oxides of Fe and Al bound form were responsible for most removal of As. The comparison with other common washing agents (EDTA, oxalate and phosphate) under their respective optimal dosage could confirm that tetrapolyphosphate was superior to simultaneously desorb the cationic and anionic metals/metalloids with higher efficiency. After 12 h, applying 150 mg/L FeS at pH 3.5 could totally remove Pb, Zn, As and Cr from the washing effluent by sulfide precipitation, reduction and adsorption processes. Higher pH would inhibit the removal of As and Cr by FeS. Meanwhile, the residual of tetrapolyphosphate could be totally recovered from the washing effluent by employing anion exchange resin. This study suggests tetrapolyphosphate enhanced soil washing coupled with ferrous sulfide treatment is a promising approach for remediation of cationic and anionic metals/metalloids co-contaminated soil in view of its high efficiency and simple operation.

The aquaculture industry is considered a key sector for the supply of high quality, nutritious food. However, growth of the aquaculture sector has been slow, particularly in Europe, and this is amongst others linked to concerns about environmental impacts of this industry. Integrated Multitrophic Aquaculture (IMTA) has been identified as an important technology to sustainably improve freshwater fish production. In IMTA, economically valuable extractive species feed on waste produced by other species, remediating wastewater, and minimising the environmental impact of aquaculture. This study presents quantitative information on the nitrogen and phosphorus removal efficiency of a duckweed-based, pilot, semi-commercial IMTA system. Duckweed species are free-floating freshwater species belonging to the family of Lemnaceae. The aim of this study was to test the potential of duckweed-based IMTA under realistic environmental conditions. Three different approaches were used to assess remediation capacity; 1) assessment of water quality pre and post treatment with duckweed showed that the system can remove 0.78 and 0.38 T y⁻¹ of Total Nitrogen (TN) and Total Phosphorus (TP), respectively 2) based on nitrogen and phosphorus content of newly grown duckweed biomass, it was shown that 1.71 and 0.22 T y⁻¹ of TN and TP can be removed, respectively 3) extrapolation based on laboratory established nitrogen and phosphorus uptake rates determined that 0.88 and 0.08 T y⁻¹ of TN and TP can be removed by the system. There is substantive agreement between the three assessments, and the study confirms that duckweed can maintain good quality water in an IMTA system, while yielding high protein content (21.84 ± 2.45%) biomass. The quantitative data on nitrogen and phosphorus removal inform the design of further IMTA systems, and especially create a scientific basis to determine the balance between aquaculture and extractive species.

Micro and nanoplastics are new generation contaminants of global concern. It is important to evaluate the effects on edible products due to the presence of micro- and nano-sized plastics in the treated wastewater. A hydroponic experiment was carried out to explore the effect of polsytrene nanoplastics (PS-NPs; 20 nm) at different concentrations (0, 12.5, 25, and 50 mg L⁻¹) on Glycine max L. (soybean) seedlings for 7-days. In the current study, firstly the uptake of PS-NPs by Glycine max L. (soybean) roots were confirmed by laser confocal scanning microscope. Exposure to PS-NPs, negatively affected growth parameters and increased Fe, Zn and Mn contents in roots and leaves of soybean seedlings. PS-NPs treatments caused oxidative stress in soybean seedlings. The hydrogen peroxide and malondialdehyde contents, showed similar increase pattern in seedlings exposed to PS-NPs. Response to PS-NPs, the level of antioxidant enzymes (superoxide dismutase, catalase, ascorbate peroxidase, and guaiacol peroxidase) and proline content were generally enhanced in roots and leaves of soybean. The expression level of stress-related genes examined in the study included CSD5, FSD3, APX1, and POD up-regulated in PS-NPs treated-soybean seedlings in a tissue specific manner. The results of the present study showed the adverse effects of PS-NPs on soybean seedlings, which may have important implications for the risk assessment of NPs on crop production and environmental safety.

Phytoplankton contribute approximately 50% to the global photosynthetic carbon (C) fixation. However, our understanding of the corresponding C sequestration capacity and driving mechanisms associated with each individual phytoplankton taxonomic group is limited. Particularly in the hydrologically dynamic system with highly complex surface hydrological processes (floodplain lake systems). Through investigating seasonal monitoring data in a typical floodplain lake system and estimation of primary productivity of each phytoplankton taxonomic group individually using novel equations, this study proposed a phytoplankton C fixation model. Results showed that dominant phytoplankton communities had a higher gross carbon sequestration potential (CSP) (9.50 ± 5.06 Gg C each stage) and gross primary productivity (GPP) (65.46 ± 25.32 mg C m⁻² d⁻¹), but a lower net CSP (−1.04 ± 0.79 Gg C each stage) and net primary productivity (NPP) (−5.62 ± 4.93 mg C m⁻³ d⁻¹) than rare phytoplankton communities in a floodplain lake system. Phytoplanktonic GPP was high (317.94 ± 73.28 mg C m⁻² d⁻¹) during the rainy season and low (63.02 ± 9.65 mg C m⁻² d⁻¹) during the dry season. However, their NPP reached the highest during the rising-water stage and the lowest during the receding-water stage. Findings also revealed that during the rainy season, high water levels (p = 0.56**) and temperatures (p = 0.37*) as well as strong solar radiation (p = 0.36*) will increase photosynthesis and accelerate metabolism and respiration of dominant phytoplankton communities, then affect primary productivity and CSP. Additionally, water level fluctuations drive changes in nutrients (p = −0.57*) and metals (p = −0.68*) concentrations, resulting in excessive nutrients and metals slowing down phytoplankton growth and reducing GPP. Compared with the static water lake system, the floodplain lake system with a lower net CSP became a heterotrophic C source.

Air pollution is becoming serious in developing country, and how to quantify the role of local emission and/or meteorological factors is very important for government to implement policy to control pollution. Here, we use a random forest model, a machine learning (ML) approach, combined with a de-weather method to analyze the PM₂.₅ level during the COVID-19 outbreak in Hubei Province. The results show that changes in anthropogenic emissions have reduced PM₂.₅ concentrations in February and March 2020 by about 33.3% compared to the same period in 2019, while changes in meteorological conditions have increased PM₂.₅ concentrations by about 8.8%. Moreover, the impact of meteorological conditions is more significant in the central region, which is likely to be related to regional transport. After excluding the contribution of meteorological conditions, the PM₂.₅ concentration in Hubei Province in February and March 2020 is lower than the secondary standard of China (35 μ g/m³). Our estimates also indicate that under similar meteorological conditions as in February and March 2019, an emission reduction intensity equivalent to about 48% of the emission reduction intensity during the lockdown may bring the annual average PM₂.₅ concentration to the standard (35 μ g/m³). Our study shows that machine learning is a powerful tool to quantify the influencing factors of PM₂.₅, and the results further emphasize the need for scientific emission reduction as well as joint regional control measures in future.

The formation of tailings ponds depends on the long-term accumulation of tailing and high terrain. Its seepage pollution characteristics may have gradient variations on spatiotemporal scales. Used three nearby metal tailings ponds with different service times, we aimed to reveal seepage pollution trends on spatiotemporal scales and the response of soil microbial community. The results showed that the degree of seepage pollution was negatively correlated with the distance from the tailings pond on the spatial scale, while the seepage pollution showed higher levels in tailings ponds with longer service times on the temporal scale (RI = 248.04–2109.85). The pollution effect of seepage persisted after the tailings pond was discontinued (RI = 226.72). Soil microbial diversity increased with spatial scale expansion. The proportion of Actinomyces gradually increased and Proteobacteria decreased. Cr (r = 0.21) and Fe (r = 0.22) contributed more to the microbial community changes. Functional predictions showed that pathways related to signal transduction and energy metabolism were more abundant in the tailings pond. In contaminated areas, the proportion of nitrate respiration and cellulolysis functional communities had decreased, and some potentially pathogenic human taxa had accumulated. These results emphasized that there was pollution accumulation on temporal scale and pollution dispersion on spatial scale around tailings ponds, and the response of the microbial community further illustrated these trends.

The environmental behavior of microplastics (MPs) in estuaries with saline and freshwater intersections is extremely complex. This increases the chance of MP ingestion by fishery resources, posing potentially tremendous health risks for humans. Herein, a total of 105 fishes from 14 different species, and 86 crustaceans (including shrimps and crabs) from five different species were sampled in the Yangtze River estuary and offshore, and MP bioaccumulation, accumulative organ, and the influencing factors were comprehensively studied. The results elucidated that MP accumulation in benthos was significantly higher than that in pelagic animals due to the lower acceptance threshold, assimilation efficiency and egestion rate for benthos. The MP content in crustaceans with the burrowing favoring the MP retention was significantly higher than that in fishes. MPs ingested by fish can accumulate in skin, gills and viscera rather than muscles. Most MPs accumulated in fishery resources were cellulose and polyethylene terephthalate characterized by black and gray fibrous and lengths ranging from 0.1 mm to 1 mm. The gill retention capacity of pelagic fish to smaller-size (<0.1 mm) MPs was pronouncedly stronger than that of benthic fish. It was more accurate to assess the ecological risk of MPs in terms of the maximum size of MPs accumulated in organisms. Compared with the offshore area, the incidence of MP uptake was higher in the estuary owing to anthropogenic impacts. This study helps understand the transfer of MPs in aquatic food webs and offers a foundation for assessing the risk of human exposure to MPs.

In arid inland irrigated areas, the role of human activities on fluoride enrichment in groundwater is not fully understood. There is an extremely arid climate, high-intensity irrigation, and severe soil salinization in the Hotan Oasis within the Tarim Basin, Northwestern China. In this study, hydrogeochemistry and environmental isotope methods were combined to explore the distribution characteristics and controlling processes of fluoride enrichment in groundwater. The F⁻ concentration in groundwater had a range of 1.12–9.4 mg/L. F⁻ concentrations of all the groundwater samples were higher than 1.0 mg/L (Chinese Standards for Drinking Water Quality), and about 89% were higher than 1.5 mg/L (WHO Guidelines for Drinking Water Quality). High fluoride groundwater was mainly distributed downstream of the river and in the middle of the interfluvial zone. Vertically, the fluoride concentration was higher when the sampling depth was less than 15 m. There was a significant positive correlation between F⁻ concentration and salinity in groundwater. F⁻ in groundwater was mainly derived from river water fluoride, which could be imported to groundwater with infiltration of rivers and irrigation canals as well as irrigation return flow. Anthropogenic inputs may be partly responsible for fluoride enrichment in groundwater. Fluoride accumulated in the vadose zone by strong evapotranspiration and then leached into groundwater with irrigation return flow was the main mechanism of F⁻ enrichment in groundwater in the study area. This work is a clear example of how human activities together with natural processes can affect the chemical quality of groundwater, which is essential to safeguard the sustainable management of water and soil resources inland arid oasis areas.

Traditional soil heavy metal (HM) investigation usually costs a lot of human and material resources. In-situ portable X-ray fluorescence spectrometry (PXRF) is a cheap and rapid HM analysis method, but its analysis accuracy is usually affected by spatially non-stationary field environment factors. In this study, residual sequential Gaussian co-simulation (RCoSGS) was first proposed to incorporate both continuous and categorical auxiliary variables for spatial simulation of soil Cu. Next, additional in-situ PXRF sampling sites (n = 300) were allocated in the subareas with high, medium, and low conditional variances in the proportions of 50%, 33.33%, and 16.67%, respectively. Then, robust geographically weighted regression (RGWR) was established to correct the spatially non-stationary effects of field environmental factors on in-situ PXRF and further compared with the traditionally-used multiple linear regression (MLR) and basic GWR in correction accuracy. Finally, RCoSGS with the RGWR-corrected in-situ PXRF as part of hard data (RCoSGS-PXRF) was established and further compared with the model with one or multiple auxiliary variables in the spatial simulation accuracy. Results showed that (i) RCoSGS effectively incorporated both SOM and land-use types and obtained higher spatial simulation accuracy (RI = 37.52%) than residual sequential Gaussian simulation with land-use types (RI = 19.44%) and sequential Gaussian co-simulation with SOM (RI = 20.92%); (ii) RGWR significantly weakened the spatially non-stationary effects of field environmental factors on in-situ PXRF, and RGWR (RI = 58.96%) and GWR (RI = 39.61%) obtained higher correction accuracy than MLR; (iii) the RGWR-corrected in-situ PXRF (RI = 66.57%) brought higher spatial simulation accuracy than both land-use types and SOM (RI = 37.52%); (iv) RCoSGS-PXRF obtained the highest spatial simulation accuracies (RI = 83.74%). Therefore, the proposed method is cost-effective for the rapid and high-precision investigation of soil HMs at a regional scale.

Effects of human activities on atmospheric nitrate (NO₃⁻) formation remain unclear, though the knowledge is critical for improving atmospheric chemistry models and nitrogen deposition reduction strategies. A potentially useful way to explore this is to compare NO₃⁻ oxidation processes in urban and rural atmospheres based upon the oxygen stable isotope composition of NO₃⁻ (Δ¹⁷O–NO₃⁻). Here we compared the Δ¹⁷O–NO₃⁻ from three-years of daily-based bulk deposition in urban (Shenyang) and forested rural sites (Qingyuan) in northeast China and quantified the relative contributions of different formation pathways based on the SIAR model. Our results showed that the Δ¹⁷O in Qiangyuan (26.2 ± 3.3‰) is significantly higher (p < 0.001) than in Shenyang (24.0 ± 4.0‰), and significantly higher in winter (Shenyang: 26.1 ± 6.7‰, Qingyuan: 29.6 ± 2.5‰) than in summer (Shenyang: 22.7 ± 2.9‰, Qingyuan: 23.8 ± 2.4‰) in both sites. The lower values in the urban site are linked with conditions that favored a higher relative contribution of nitrogen dioxide reaction with OH pathway (0.76-0.91) than in rural site (0.47-0.62), which should be induced by different levels of human activities in the two sites. The seasonal variations of Δ¹⁷O–NO₃⁻ in both sites are explained by a higher relative contribution of ozone-mediated oxidation chemistry and unfavorable conditions for the OH pathway during winter relative to summer, which is affected by human activities and seasonal meteorological condition change. Based on Δ¹⁷O, wintertime conditions led to a contribution of O₃ related pathways (NO₃ + DMS/HC and N₂O₅ hydrolysis) of 0.63 in Qingyuan and 0.42 in Shenyang, while summertime conditions led to 0.15 in Qingyuan and 0.05 in Shenyang. Our comparative study on Δ¹⁷O–NO₃⁻ between urban and rural sites reveals different anthropogenic effects on nitrate formation processes on spatial and temporal scales, illustrating different responses of reactive nitrogen chemistry to changes in human activities.