Although machine learning methods have enabled considerable progress in air quality assessment, challenges persist regarding data privacy, cross-regional data processing, and model generalization. To address these issues, we introduce an advanced federated Bayesian network (FBN) approach. By integrating federated learning, adaptive optimization algorithms, and homomorphic encryption technologies, we substantially enhanced the efficiency and security of cross-regional air quality data processing. The novelty of this research lies in the improvements implemented in federated learning for air quality data analysis, particularly in distributed model training optimization and data consistency. Through the integration of adaptive structural modification strategies and simulated annealing immune optimization algorithms, we markedly enhanced the structural learning accuracy of the Bayesian network, resulting in a 20% improvement in prediction accuracy. Moreover, employing homomorphic encryption ensured data transmission security and confidentiality. In our Beijing-Tianjin-Hebei case study, our method demonstrated a 15% improvement in air quality classification accuracy compared to conventional methods and exhibited superior interpretability in analyzing environmental factor interactions. We quantified complex air pollution patterns across regions and found that a 30% fluctuation in the air quality index correlated with NO2 concentrations. We also observed a moderate positive correlation between specific pollutant indicators in Hebei Province and Tianjin and changes in air quality. Additionally, the FBN exhibited better operational efficiency and data confidentiality than other machine learning models in handling large-scale and multisource environmental data. Our FBN approach presents a novel perspective for environmental monitoring and assessment, vital for understanding complex air pollution patterns and formulating future ecological protection policies.

Out of 5 million Indian spring water systems, a few were characterised for hydrochemistry and freshwater potential. The present study focuses on analysing the hydrochemistry, discharge, and drinking/irrigation water quality of both cold and thermal spring clusters namely Southern Kerala Springs (SKS) and Dakshina Kannada Springs (DKS) of Southern Western Ghats, India. Currently, eleven springs from SKS and ten from DKS including one thermal spring (TS) with temperature ranges from 34 to 37 °C were considered. The study revealed that cold springs (CS) of SKS are Na-Cl type, while the thermal and cold-water springs in DKS are Na-HCO3 and mixing water type, respectively. Two distinct mechanisms predominantly define the hydro-chemical composition of the springs-SKS are influenced by precipitation, whereas DKS is likely by chemical weathering processes. While comparing the major ions and saturation indices of thermal springs (TS), it is evident that silicate minerals predominantly affect the chemical composition of water. CaCO3- is oversaturated in TS water and tends to precipitate as a scale layer. PCA showed that both geogenic and anthropogenic factors influence water chemistry. WQI categorized the CS in both the clusters are in the \"Excellent\" rank as compared to TS. Irrigation water quality signifies that the cold springs are only suitable for irrigation. Moreover, it is evident from the discharge that both SKS and DKS were rainfed in nature. Discharge monitoring designated that the CS could augment drinking water supplies in the nearby regions indicating the necessity of conservation and sustainable use considering future freshwater scarcity.

Over two decades, the area with sugarcane has more than doubled, from 4.8 million hectares in 2000 to 10 million in 2018, in Brazil. São Paulo State is mostly responsible for the sugarcane production in the country, accounting for 51% of the national production. In 2008, a study was conducted analysing the relationship between sugarcane cultivation and the aquatic macroinvertebrate community, showing the impacts of sugarcane on the macroinvertebrate aquatic fauna. The present study aims to gather actual information on the aquatic macroinvertebrate community in the same streams studied in 2008, to make a historical comparison with studies previously carried out. Eight streams were selected; four located in areas of sugarcane cultivation and four located in preserved areas. Three samples were carried out between 2018 and 2020. The aquatic macroinvertebrates were collected using a D-frame aquatic net (250 μm) including riffle and pools areas and identified using specific identification keys. The results of the historical assessment showed better ecological conditions of the streams in 2008 when compared to 2018 in areas of sugarcane cultivation, suggesting that the environmental impact was maintained and increased after ten years.

Previous research on pesticides in green tea mainly focused on detection technology but lacked insights into pesticide use during cultivation. To address this gap, a survey was conducted among Rizhao green tea farmers. The survey results showed that most tea farmers were approximately 60 years old and managed small, scattered tea gardens (< 0.067 ha). Notably, tea farmers who had received agricultural training executed more standardized pesticide application practices. Matrine and thiazinone are the most used pesticides. A total of 16 types of pesticides were detected in the tested green tea samples, with 65% of the samples containing residues of at least one pesticide. Notably, higher levels of residues were observed for bifenthrin, cyfluthrin, and acetamiprid. The presence of pesticide residues varied significantly between seasons and regions. The risk assessment results indicated that the hazard quotient (HQ) values for all 16 pesticides detected in green tea were < 1, suggesting that these residue levels do not pose a significant public health concern.

Based on ozone (O3) monitoring data for Xiangtan and meteorological observation data for 2020-2022, we examined ozone pollution characteristics and the effects of meteorological factors on daily maximum 8-h average ozone (O3-8h) concentrations in Xiangtan. Thus, we observed significant increases as well as notable seasonal variations in O3-8h concentrations in Xiangtan during the period considered. The ozone and temperature change response slope (KO3-T) indicated that local emissions had no significant effect on O3-8h generation. Further, average O3-8h concentration and maximum temperature (Tmax) values showed a polynomial distribution. Specifically, at Tmax < 27 °C, it increased almost linearly with increasing temperature, and at Tmax between 27 and 37 °C, it showed an upward curvilinear trend as temperature increased, but at a much lower rate. Then, at Tmax > 37 °C, it decreased with increasing temperature. With respect to relative humidity (RH), the average O3-8h concentration primarily exceeded the standard value when RH varied in the range of 45-65%, which is the key humidity range for O3 pollution, and the inflection point for the correlation curve between O3-8h concentration and RH appeared at ~55%. Furthermore, at wind speeds (WSs) below 1.5 m∙s-1, O3-8h concentration increased rapidly, and at WSs in the 1.5-2 m∙s-1 range, it increased at a much faster rate. However, at WSs > 2 m∙s-1, it decreased slowly with increasing WS. O3-8h concentration also showed the tendency to exceed the standard value when the dominant wind directions in Xiangtan were easterly or southeasterly.

Demonstrating the temporal changes in PM2.5 pollution risk in regions facing serious PM2.5 pollution problems can provide scientific evidence for the air pollution control of the region. However, research on the variation of PM2.5 pollution risk on a fine temporal scale is very limited. Therefore, we developed a method for quantitative characterizing PM2.5 pollution risk based on the supply and demand of PM2.5 removal services, analyzed the time series characteristics of PM2.5 pollution risk, and explored the reasons for the temporal changes using the urban areas of Beijing as the case study area. The results show that the PM2.5 pollution risk in the urban areas of Beijing was close between 2008 and 2012, decreased by approximately 16.3% in 2016 compared to 2012, and further decreased by approximately 13.2% in 2021 compared to 2016. The temporal variation pattern of the PM2.5 pollution risk in 2016 and 2021 showed significant differences, including an increase in the number of risk-free days, a decrease in the number of heavily polluted days, and an increase in the stability of the risk day sequence. The significant reduction in risk level was mainly attributed to Beijing\'s air pollution control measures, supplemented by the impact of COVID-19 control measures in 2021. The results of PM2.5 pollution risk decomposition indicate that compared to the previous 2 years, the stability and predictability of the risk variation in 2016 increased, but the overall characteristics of high risk from November to February and low risk from April to September did not change. The high risk from November to February was mainly due to the demand for coal heating during this period, a decrease in PM2.5 removal service supply caused by plant leaf fall, and the common occurrence of temperature inversions in winter, which hinders the diffusion of air pollutants. This study provides a method for the analysis of PM2.5 pollution risk on fine temporal scales and may provide a reference for the PM2.5 pollution control in the urban areas of Beijing.

The intensive global use of pesticides presents an escalating threat to human health, ecosystems, and water quality. To develop national and local environmental management strategies for mitigating pollution caused by pesticides, it is essential to understand the quantities, timing, and location of their application. This study aims to estimate the spatial distribution of pesticide use in an agricultural region of La Plata River basin in Uruguay. Estimates of pesticide use were made by surveying doses applied to each crop. This information was spatialized through identifying agricultural rotations using remote sensing techniques. The study identified the 60 major agricultural rotations in the region and mapped the use and application amount of the nine most significant active ingredients (glyphosate, 2,4-dichlorophenoxyacetic acid, flumioxazin, S-metolachlor, clethodim, flumetsulam, triflumuron, chlorantraniliprole, and fipronil). The results reveal that glyphosate is the most extensively used pesticide (53.5% of the area) and highest amount of use (> 1.44 kg/ha). Moreover, in 19% of the area, at least seven active ingredients are applied in crop rotations. This study marks the initial step in identifying rotations and estimating pesticide applications with high spatial resolution at a regional scale in agricultural regions of La Plata River basin. The results improve the understanding of pesticide spatial distribution based on data obtained from agronomists, technicians, and producers and provide a replicable methodological approach for other geographic and productive contexts. Generating baseline information is key to environmental management and decision making, towards the design of more robust monitoring systems and human exposure assessment.

Rivers are important reservoirs of antibiotic resistance genes (ARGs). However, most current studies have focused on the temporal and spatial distribution, and data on the differences in the species and abundance of ARGs between urban and rural rivers is still lacking for certain areas. In view of this, two rural rivers and three urban rivers were selected in Shijiazhuang City. In both December 2020 and April 2021, sediments were collected at 15 sampling sites. Metagenomic sequencing technology was used to compare the differences in temporal-spatial variation for ARGs in sediments. The results showed that:① 162 and 79 ARGs were detected in urban (4 776 ±4 452) and rural rivers (1 043 ±632), respectively. The abundance and species of ARGs in urban rivers were higher than those in rural rivers. ② The relative abundances of sulfonamide (SAs,27 %), aminoglycoside (AGs,26 %), and multidrug (MDs,15 %) ARGs had the highest abundance in urban rivers, whereas the relative abundance of MDs ARGs was highest in rural rivers (65 %). On the whole, the complexity of ARGs in urban rivers was higher than that in rural rivers. ③ There was a significant positive correlation between SAs, AGs, MDs, tetracycline, phenicol, macrolides-lincosamids-streptogramins (MLS), β-lactams, and diaminopyrimidine ARGs in urban rivers (P < 0.01); however, there was a significant negative correlation between glycopeptide ARGs and all types of ARGs (P < 0.05 and P < 0.01). There was a significant positive correlation between MDs and SAs ARGs in rural rivers (P < 0.05), but there was a significant negative correlation between amino aminocoumarin, peptide, rifamycin, and fosfomycin ARGs (P < 0.05 and P < 0.01). ④ For the temporal variation in urban rivers, 162 ARGs (4 776 ±4 452) and 148 ARGs (5 673 ±5 626) were detected in December and April, respectively. For the temporal variation in rural rivers, 79 species (1 043 ±632) and 46 species (467 ±183) were detected in December and April, respectively. ⑤ RDA analysis results showed that the spatial-temporal distributions of ARGs in urban and rural rivers were different. Correlation analysis showed that the ARGs in urban rivers were significantly correlated with the number of industrial enterprises, whereas the ARGs in rural rivers were significantly correlated with the output value of animal husbandry. In general, this study identified the main influencing factors for ARGs in different rivers and provided data support for ARGs risk management in different rivers.

River water quality is influenced by natural processes and human activities. Multi-scale landscape patterns can affect river water quality by altering the generation and transport processes of pollutants at different spatial scales. Taking Taizi River Basin in Northeast China as an example, we analyzed the relationship between landscape patterns and non-point source pollution in rivers based on water quality monitoring data and land use data by using correlation analysis and redundancy analysis methods. We aimed to determine the key spatial scales for the responses of landscape patterns to non-point source pollution and identify the key landscape indices influencing river non-point source pollution. The results showed that water quality of Taizi River Basin had seasonal differences, with better water quality during the flood season than non-flood season. Spatially, total nitrogen (TN) and total phosphorus (TP) were higher at the confluence points of tributaries and downstream areas. The impact of landscape patterns on non-point source pollution was stronger during the non-flood season than the flood season, while the influence on TN was stronger than on TP. At the spatial scale of within 500 m buffer zone during the flood season and at the sub-watershed scale during the non-flood season, landscape patterns showed the highest explanatory power for the variations of TN and TP. At the type level, built-up land, cropland, and bare land were positively correlated with TN and TP, while forest was negatively correlated with TN and TP, which were the key types influencing non-point source pollution. At the landscape level, patch density, percentage of like adjacencies, and contagion index were key indicators affecting watershed water quality. Lower patch density was associated with better connectivity and aggregation of \"sink\" landscapes, leading to better purification effects on TN, but more pronounced retention effects on TP. Conversely, higher landscape diversity and denser pattern of multiple types would cause the deterioration of water quality. Our results suggested that rational allocation of landscape types within the watershed and riparian buffer zones, appropriately enriching landscape diversity, and optimizing landscape aggregation and connectivity would be effective measures for improving water quality and achieving sustainable ecological management.
河流水质是自然与人类活动综合影响的结果,多尺度景观格局通过改变不同空间尺度污染物的产生和运移过程对河流水质产生不同程度的影响。本研究以中国北方太子河流域为例,基于水质监测数据和土地利用数据,运用相关性分析、冗余分析方法,分析景观格局与河流非点源污染的关系,确定非点源污染对景观格局响应的最佳空间尺度,识别影响河流非点源污染的关键景观指标。结果表明: 太子河流域水质在时间上具有季节差异,汛期水质优于非汛期;在空间上,污染物全氮(TN)和全磷(TP)的高值出现在支流汇入点和下游地区;景观格局对非点源污染的影响在非汛期强于汛期,且TN强于TP。在汛期500 m以内河岸带缓冲区、非汛期集水区尺度下,景观格局对太子河TN和TP的解释率最高;类型水平上,建设用地、耕地和裸地与TN和TP呈正相关,林地与TN和TP呈负相关,是影响非点源污染的关键类型;景观水平上,斑块密度、相似邻近比例和蔓延度指数是影响流域水质的关键指标。斑块密度越低,“汇”型景观连通性越好,对TN的净化效果越好,但对TP的截留效应更明显。反之,景观多样性增加并构成多种类型的密集格局,越易导致水质恶化。合理配置流域内及河岸带缓冲区景观类型、适当丰富景观多样性、优化景观聚集性和连通性,是流域水质改善及可持续生态管理的有效措施。.

The rapid development of the social economy and the influence of human activities can lead to aggravated groundwater pollution. Groundwater safety is the premise of residents\' health. Therefore, studying the sustainable utilization and health risks of groundwater quality is important. The groundwater quality and potential health risks were evaluated in the Shijiazhuang area, which is located in the North China Plain in this paper. Based on 159 groundwater samples collected in the study area, the potential health risks of As, Cr6+, Ni, Pb, F-, and NO3 - to humans were evaluated from oral and skin contact. Results of the human health risk assessment showed that the average carcinogenic risk and non-carcinogenic risk of children are higher than those of adults. According to the spatial distribution of the total risk value, adults and children in the southwest of the study area face higher risks. Because of the uncertainty of USEPA, Monte Carlo simulation was used to calculate the probability of health risk assessment and prioritization of contaminant treatment. The results of the Monte Carlo simulation showed that the acceptable range for children is 6.82%, and the acceptable range for adults is 18.07%. According to the HRWM model, carcinogenic pollutants mainly include As, Cr6+, and Ni. The most important chemical species of As is HAsO4 2-, followed by H2AsO4 -. Similarly, CrO4 2- and Ni2+ are the main forms of Cr6+ and Ni. The results of this study can provide data support for the protection and management of groundwater quality in the North China Plain. PRACTITIONER POINTS: Children are more susceptible to carcinogenic risk than adults. After calculation, the main influencing elements are Ni and Cr. Metal morphology analysis was carried out, and the results showed that HAsO4 2-, CrO4 2-, and Ni2+ were the main types.