Spatial characteristics and influencing factors of river pollution in China

Decomposition of metal-organic complexes and metal recovery in wastewater: A systematic review and meta-synthesis

Metals are rarely found as free ions in natural and anthropogenic environments, but they are often associated with organic matter and minerals. Under the context of circular economy, metals should be recycled, yet they are difficult to extract for their complex forms in real situations. Based on the protocols of review methodology and the analysis of VOS viewer, there are few reviews on the properties of metal-organic complexes, decomplexation methods, the effect of coexisting ions, the pH influence, and metal recovery methods for the increasingly complicated metal-organic complexes wastewater. Conventional treatment methods such as flocculation, adsorption, biological degradation, and ion exchange fail to decompose metal-organic complexes completely without causing secondary pollution in wastewater. To enhance comprehension of the behavior and morphology exhibited by metal-organic complexes within aqueous solutions, we presented the molecular structure and properties of metal-organic complexes, the decomplexation mechanisms that encompassed both radical and non-radical oxidizing species, including hydroxyl radical (OH), sulfate radical (SO˙4-), superoxide radical (O˙2-), hydrogen peroxide (H2O2), ozone (O3), and singlet oxygen (1O2). More importantly, we reviewed novel aspects that have not been covered by previous reviews considering the impact of operational parameters and coexisting ions. Finally, the potential avenues and challenges were proposed for future research.

Data fusion strategy based on ultraviolet-visible spectra and near-infrared spectra for simultaneous and accurate determination of key parameters in surface water

Chemical oxygen demand (COD), ammonia nitrogen (AN) and total nitrogen (TN) are the key parameters to reflect the degree of surface water pollution. Ultraviolet - visible (UV-Vis) spectroscopy and near - infrared (NIR) spectroscopy are ideal techniques for rapid monitoring of these indicators. In this study, a strategy based on the fusion of UV-Vis and NIR spectral data (UV-Vis-NIR) for water quality detection was proposed to further improve the quantitative analysis accuracy of spectroscopic methods. Seventy river samples with different levels of pollution were used for spectroscopic analysis. The UV-Vis-NIR fusion spectrum of each water sample was obtained by directly splicing sample's UV-Vis spectrum and NIR diffuse transmission spectrum. The UV-Vis-NIR fusion models were optimized through using different variable selection algorithms. The results show that the UV-Vis-NIR fusion models for surface water COD, AN and TN achieves better prediction results (the root mean square errors of prediction are 6.95, 0.195, and 0.466, respectively) than single-spectroscopic based models. Since better prediction performances were shown under different optimization conditions, the robustness of fusion models were also better than the single-spectroscopic based models. Therefore, the data fusion strategy proposed in this study has a promising application prospect for further accurate and rapid monitoring of surface water quality.

Potential linkage between WWTPs-river-integrated area pollution risk assessment and dissolved organic matter spectral index

The direct discharge of wastewater can cause severe damage to the water environment of the surface water. However, the influence of dissolved organic matter (DOM) present in wastewater on the allocation of DOM, nitrogen (N), and phosphorus (P) in rivers remains largely unexplored. Addressing the urgent need to monitor areas affected by direct wastewater discharge in a long-term and systematic manner is crucial. In this paper, the DOM of overlying water and sediment in the WWTPs-river-integrated area was characterized by ultraviolet-visible absorption spectroscopy (UV-vis), three-dimensional excitation-emission matrix combined with parallel factor (PARAFAC) method. The effects of WWTPs on receiving waters were investigated, and the potential link between DOM and N, P pollution was explored. The pollution risk was fitted and predicted using a spectral index. The results indicate that the improved water quality index (IWQI) is more suitable for the WWTPs-river integration zone. The DOM fraction in this region is dominated by humic-like matter, which is mainly influenced by WWTPs drainage as well as microbial activities. The DOM fractions in sediment and overlying water were extremely similar, but fluorescence intensity possessed more significant spatial differences. The increase in humic-like matter facilitates the production and preservation of P and also inhibits nitrification, thus affecting the N cycle. There is a significant correlation between DOM fraction, fluorescence index, and N, P. Fluorescence index (FI) fitting of overlying water DOM predicted IWQI and trophic level index, and a(254) fitting of sediment DOM predicted nitrogen and phosphorus pollution risk (FF) with good results. These results contribute to a better understanding of the impact of WWTPs on receiving waters and the potential link between DOM and N and P pollution and provide new ideas for monitoring the water environment in highly polluted areas.

Abundant bacteria shaped by deterministic processes have a high abundance of potential antibiotic resistance genes in a plateau river sediment

Recent research on abundant and rare bacteria has expanded our understanding of bacterial community assembly. However, the relationships of abundant and rare bacteria with antibiotic resistance genes (ARGs) remain largely unclear. Here, we investigated the biogeographical patterns and assembly processes of the abundant and rare bacteria from river sediment at high altitudes (Lhasa River, China) and their potential association with the ARGs. The results showed that the abundant bacteria were dominated by Proteobacteria (55.4%) and Cyanobacteria (13.9%), while the Proteobacteria (33.6%) and Bacteroidetes (18.8%) were the main components of rare bacteria. Rare bacteria with a large taxonomic pool can provide function insurance in bacterial communities. Spatial distribution of persistent abundant and rare bacteria also exhibited striking differences. Strong selection of environmental heterogeneity may lead to deterministic processes, which were the main assembly processes of abundant bacteria. In contrast, the assembly processes of rare bacteria affected by latitude were dominated by stochastic processes. Abundant bacteria had the highest abundance of metabolic pathways of potential drug resistance in all predicted functional genes and a high abundance of potential ARGs. There was a strong potential connection between these ARGs and mobile genetic elements, which could increase the ecological risk of abundant taxa and human disease. These results provide insights into sedimental bacterial communities and ARGs in river ecosystems.

Comparison of epiphytic and intestinal bacterial communities in freshwater snails (Bellamya aeruginosa) living on submerged plants

The combination of submerged plants and snails can combat eutrophication of freshwater systems by suppressing algal growth and assimilating nutrients. By consuming epiphytes, snails can benefit the growth of submerged plants. However, the efficiency of this phytoremediation strategy may depend on the microbes associated with the plants and snails. In this study, we compared the epiphytic bacterial communities on submerged plants (Vallisneria natans and Cabomba caroliniana) and intestinal bacterial communities of a snail, Bellamya aeruginosa, found on these plants using 16S rRNA gene sequencing. Epiphytic bacterial communities were similar between the two plant species and snails shared a high proportion of snail intestinal bacterial OTUs (75%) and genera (85%) with plants they grazed on. However, significant variations of Bray-Curtis distances differentiated epiphytic and intestinal bacterial communities. In addition, between the top 50 genera shared by intestinal and epiphytic bacterial communities, more Spearman correlations were detected within bacterial communities associated with snails than between communities associated with plants (190 vs. 143), and the correlations in epiphytic bacterial networks were more concentrated on certain genera, indicating they possessed distinct bacterial networks. This suggests the bacterial communities associated with snails do not depend strongly on the plant they graze on, which may be important for better understanding the role of snails in aquatic eco-restoration.

Comparing spatial patterns of 11 common cancers in Mainland China

Background

A stronger spatial clustering of cancer burden indicates stronger environmental and human behavioral effects. However, which common cancers in China have stronger spatial clustering and knowledge gaps regarding the environmental and human behavioral effects have yet to be investigated. This study aimed to compare the spatial clustering degree and hotspot patterns of 11 common cancers in mainland China and discuss the potential environmental and behavioral risks underlying the patterns.

Methods

Cancer incidence data recorded at 339 registries in 2014 was obtained from the “China Cancer Registry Annual Report 2017”. We calculated the spatial clustering degree of the common cancers using the global Moran’s Index and identified the hotspot patterns using the hotspot analysis.

Results

We found that esophagus, stomach and liver cancer have a significantly higher spatial clustering degree (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<0.05$$\end{document}p<0.05) than others. When by sex, female esophagus, male stomach, male esophagus, male liver and female lung cancer had significantly higher spatial clustering degree (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<0.001$$\end{document}p<0.001). The spatial clustering degree of male liver was significantly higher than that of female liver cancer (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<0.001$$\end{document}p<0.001), whereas the spatial clustering degree of female lung was significantly higher than that of male lung cancer (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$p<0.001$$\end{document}p<0.001). The high-risk areas of esophagus and stomach cancer were mainly in North China, Huai River Basin, Yangtze River Delta and Shaanxi Province. The hotspots for liver and male liver cancer were mainly in Southeast China and south Hunan. Hotspots of female lung cancer were mainly located in the Pearl River Delta, Shandong, North and Northeast China. The Yangtze River Delta and the Pearl River Delta were high-risk areas for multiple cancers.

Conclusions

The top highly clustered cancer types in mainland China included esophagus, stomach and liver cancer and, by sex, female esophagus, male stomach, male esophagus, male liver and female lung cancer. Among them, knowledge of their spatial patterns and environmental and behavioral risk factors is generally limited. Potential factors such as unhealthy diets, water pollution and climate factors have been suggested, and further investigation and validation are urgently needed, particularly for male liver cancer. This study identified the knowledge gap in understanding the spatial pattern of cancer burdens in China and offered insights into targeted cancer monitoring and control.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-022-13926-y.

Twenty years of China's water pollution control: Experiences and challenges

Water pollution is a major environmental problem worldwide, especially in developing countries. China's environmental protection strategies have been pushed to the highest priority in history, driving remarkable achievements in water pollution control, but were also coupled with new challenges. In this study, we analyzed diverse long-term data (i.e. water quality, WWTPs, pollutant discharge etc.) to systematically understand the process of water pollution control in China in the last twenty years. The results highlighted that the collection and treatment capacity of wastewater in China approached the developed country level, with the treatment rates exceeding 90% both in urban and country areas. The environmental quality of surface water was continuously improved, but water pollution problems remained in the river basins of eastern China, with remarkable economic progress. Rapid economic growth rather than population growth was the limiting factor for water pollution control in China. Therefore, more efforts should be made to further improve wastewater collection and treatment capacity and address the gap between effluent discharge limits for wastewater treatment plants and environmental quality standards for surface water. China's progress toward water pollution control provided important insights for other developing countries.

Research on SVR Water Quality Prediction Model Based on Improved Sparrow Search Algorithm

Multiparameter water quality trend prediction technique is one of the important tools for water environment management and regulation. This study proposes a new water quality prediction model with better prediction performance, which is combined with improved sparrow search algorithm (ISSA) and support vector regression (SVR) machine. For the problems of low population diversity and easily falling into local optimum of sparrow search algorithm (SSA), ISSA is proposed to increase the initial population diversity by introducing Skew-Tent mapping and to help the algorithm jump out of local optimum by using the adaptive elimination mechanism. The optimal values of the penalty factor C and kernel function parameter g of the SVR model are selected using ISSA to make the model have better prediction accuracy and generalization performance. The performance of the ISSA-SVR water quality prediction model is compared with BP neural network, SVR model, and other hybrid models by conducting water quality prediction experiments with actual breeding-water quality data. The experimental results showed that the prediction accuracy of the ISSA-SVR model was significantly higher than that of other models, reaching 99.2%; the mean square deviation (MSE) was 0.013, which was 79.37% lower than that of the SVR model and 75% lower than that of SSA-SVR model, and the coefficient of determination (R²) was 0.98, which was 5.38% higher than that of the SVR model and 7.57% higher than that of the SSA-SVR model, indicating that the ISSA-SVR water quality prediction model has some engineering application value in the field of water body management.

Exploration of the driving factors and distribution of fecal coliform in rivers under a traditional agro-pastoral economy in Kyrgyzstan, Central Asia

Fecal coliform (FC) in river water is one of the threats to human health. To explore the pollution status of FC in rivers of Kyrgyzstan, a mountainous country with traditional agro-pastoral economy, 184 water samples from the rivers of Kyrgyzstan in low and high river flow period were analyzed. Spatial autocorrelation and classical statistical methods were used to analyze the spatiotemporal distribution and driving factors of FC. The results showed that the surface water quality of Kyrgyz rivers was good, and the concentration range of FC was 0-23 MPN/100 mL. Temporally, the maximum FC concentration was 4 MPN/100 mL in low river flow period, while in the period of high river flow, the highest value reached to 23 MPN/100 mL. Spatially, the concentration of FC in high altitude areas was low, while that in the lowland areas was relatively high, which indicated that animal husbandry in high altitude areas contributed little to FC in rivers, and urban domestic sewage and agricultural activities in lowlands were the main pollution sources of FC in rivers. There was no correlation between FC and hardness, electrical conductivity (EC), pH and total organic carbon (TOC) in river water of Kyrgyzstan, and the distribution of FC in high river flow period was mainly driven by population and human modification of terrestrial systems. The results can provide a basis for the prevention and control of surface water FC pollution and related diseases in Kyrgyzstan.

Spatiotemporal variation patterns of water pollution drivers: The case of China's south-north water transfer project

Water pollution is subject to the effects of various drivers and exhibits significant spatiotemporal effects. This paper reviews the spatiotemporal variation pattern of water pollution drivers within the extended framework of the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) that considers spatiotemporal effects. Taking China's South-North Water Transfer Project (SNWTP) as an example, this paper examines the spatial spillover and spatiotemporal heterogeneity of water pollution drivers in the SNWTP's water receiving cities by constructing spatial autocorrelation regression and geographical and temporal weighted regression models. The findings demonstrate that water pollution drivers have interactions between adjacent economic cities, making it more challenging to assess water pollution in specific cities accurately. Moreover, there are significant spatiotemporal heterogeneities in the drivers'impact on water pollution. First, the spatial effect of the population driver is more prominent than the temporal effect. Second, the economic driver is positively correlated with pollution and fluctuates with time. Finally, the technology driver also presents significant spatiotemporal heterogeneity. These spatiotemporal heterogeneities make water pollution control more complicated.

Effective Strategies, Mechanisms, and Photocatalytic Efficiency of Semiconductor Nanomaterials Incorporating rGO for Environmental Contaminant Degradation

The water pollution problems severely affect the natural water resources due to the large disposal of dyes, heavy metals, antibiotics, and pesticides. Advanced oxidation processes (AOP) have been developed using semiconductor nanomaterials as photocatalysts for water treatment as an essential strategy to minimize environmental pollution. Significant research efforts have been dedicated over the past few years to enhancing the photocatalytic efficiencies of semiconductor nanomaterials. Graphene-based composites created by integrating reduced graphene oxide (rGO) into various semiconductor nanomaterials enable the unique characteristics of graphene, such as the extended range of light absorption, the separation of charges, and the high capacity of adsorption of pollutants. Therefore, rGO-based composites improve the overall visible-light photocatalytic efficiency and lead to a new pathway for high-performance photocatalysts’ potential applications. This brief review illustrates the strategies of combining rGO with various semiconductor nanomaterials and focuses primarily on modification and efficiency towards environmental contaminants.