Huanjing Kexue/Environmental Science最新文献

{"title":"[Variation Characteristics and Source Analysis of Atmospheric Ozone Pollution in Guanzhong Region].","authors":"Xing Wang, Ai-di Huo, Ji-Qiang Lü, Zhi-Xin Zhao, Jian Chen, Fang-Qian Zhong, Lu-Ying Yang, Lei Yang","doi":"10.13227/j.hjkx.202305229","DOIUrl":"https://doi.org/10.13227/j.hjkx.202305229","url":null,"abstract":"<p><p>Guanzhong urban agglomeration has a good development foundation and great development potential, and it has a unique strategic position in the national all-round opening up pattern. In recent years, the problem of near-surface ozone （O₃） in the Guanzhong Region has become increasingly prominent, which has become a bottleneck affecting the continuous improvement of air quality. In order to effectively prevent and control O₃ pollution, this study analyzed the characteristics of annual, monthly, and daily changes in O₃ concentration in the Guanzhong Region based on the environmental monitoring data from 2018 to 2021. A geo-detector was used to study the driving factors of the spatial differentiation of O₃ concentration, and the sources of O₃ were analyzed using a backward trajectory model and emission inventory construction. The results showed that the daily and monthly variation in O₃ concentration in the Guanzhong Region were unimodal. The daily maximum value appeared at 15：00, the minimum value appeared at 07：00, the peak value of the monthly average appeared in June, and the valley value appeared in December. The O₃ concentration was highest in summer, followed by that in spring, and the lowest in winter. The days of O₃ exceeding the standard showed mainly mild pollution, and moderate and above pollution showed a trend of decreasing first and then increasing. The O₃ concentration in the Guanzhong Region was mainly closely related to precursors and meteorological factors, and the explanatory power of the interaction of each factor was significantly greater than that of any single factor. The regional transport of O₃ concentration in the Guanzhong Region was mainly affected by easterly airflow, followed by the northwest direction, with the potential source areas located mainly in Henan Province and Hubei Province. The main local sources of volatile organic compounds （VOCs） were solvent use sources, process sources, and mobile sources, and the main emission sources of nitrogen oxides （NO<i>_x</i>） were mobile sources and industrial production combustion sources. The research results have a guiding significance for O₃ joint prevention and control in the Guanzhong Region.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Effects of Straw and Biochar Amendments on Characteristics of Soil Fungal Community and Organic Carbon Pool in <i>Jasminum sambac</i> Garden].","authors":"Jia-Hao Peng, Shao-Ying Lin, Wei-Qi Wang, Yu Zeng, Mei-Chun Chen, Wen-Wen Yang, Si-Cong Chen","doi":"10.13227/j.hjkx.202306194","DOIUrl":"https://doi.org/10.13227/j.hjkx.202306194","url":null,"abstract":"<p><p>In order to elucidate the changes in the soil fungal community and soil organic carbon components of a <i>Jasminum sambac</i> garden after straw and biochar application, we measured the organic carbon components and soil fungal community of the 0-15 cm soil layer in a <i>J. sambac</i> garden, which was divided into a control group, straw treatment group, and biochar treatment group. The carbon pool management index （CPMI） was also calculated. The results showed that the diversity of the soil fungal community was decreased after straw and biochar application, and the structure of dominant fungal genera was changed in each treatment. The soil fungal community structure in the biochar treatment was significantly different from that in the straw treatment and control groups. Redundancy analysis （RDA） showed that soil fungal community structure was mainly affected by soil bulk density, C∶N, salinity, and TN. Secondly, compared with that in the control group, soil labile organic carbon （LOC） in the straw treatment group was significantly increased by 87.44% （<i>P</i><0.05）, whereas soil dissolved organic carbon （DOC） and microbial biomass carbon （MBC） in the biochar treatment group were significantly increased by 22.27% and 23.17% （<i>P</i><0.05）, respectively. Further, compared with that in the control group, the carbon pool activity （<i>L</i>） under straw treatment was significantly increased （<i>P</i><0.05）, and the carbon pool index （CPI） under biochar treatment was significantly increased （<i>P</i><0.05）. Spearman correlation analysis showed that the distribution characteristics of soil organic carbon active components were regulated by the dominant fungi. FUNGuild functional prediction results showed that saprophytic and its facultative nutritional fungi had an important impact on soil organic carbon active components and carbon pool management index after straw and biochar application.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634803","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatial Prediction and Influencing Factors Analysis of Soil Salinization in Coastal Area Based on MGWR].","authors":"Ying Song, Ming-Xiu Gao, Jia-Fan Wang, Ze-Xin Xu","doi":"10.13227/j.hjkx.202307195","DOIUrl":"https://doi.org/10.13227/j.hjkx.202307195","url":null,"abstract":"<p><p>Quantitative analysis of the spatial non-stationary characteristics of soil salinization influencing factors and the prediction of its spatial distribution are of great significance for the rational use of coastal saline soil resources and the formulation of local prevention and control measures. In this study, the Hekou District of Dongying City, Shandong Province, was used as the study area, and the descriptive statistics of soil salinization status were conducted using classical statistical methods. Spatial autocorrelation theory was used to explore the characteristics of global and local spatial structure of soil salinization in the study area. Influential factors related to soil salinity were selected, and multivariate linear regression （MLR）, geographically weighted regression （GWR）, and multi-scale geographically weighted regression （MGWR） methods were used to model and predict the spatial distribution of soil salinity in the study area and to analyze the spatial heterogeneity of the effects of different influencing factors on soil salinity. The results showed that： ① The mean value of soil salinity in the study area was 5.84 g·kg^-1, indicating severe salinization, with a global Moran's <i>I</i> index of 0.19 （<i>P</i><0.00） and obvious spatial aggregation characteristics. ② Among the three models, the MGWR model had the highest modeling accuracy. Compared with that of the MLR model, the <i>R</i>_adj² of GWR and MGWR improved by 0.05 and 0.07, respectively, and the RSS decreased by 210.13 and 179.95, respectively. ③ The results of MGWR regression showed that the spatial distribution of soil salinity appeared to be mainly affected by the middle soil salinity, soil clay content, and vegetation cover from the mean values of standardized regression coefficients of different influencing factors. Different influencing factors had significant spatial non-stationary characteristics on soil salinization. ④ The results of the spatial distribution prediction of soil salinity in MGWR showed that the areas of high soil salinity （≥6 g·kg^-1） were mainly distributed in the northern part of the study area, with an overall spatial trend of decreasing from the coast to the interior. The results of the study can be used as a reference for the analysis and predictive mapping of factors affecting soil salinization in the county and on a larger scale using MGWR.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634808","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatiotemporal Coupling Analysis of Urbanization and Ecosystem Services in Southeastern Fujian].","authors":"Feng-Yi Du, Song-Lin Chen, Jia-Hao Pu","doi":"10.13227/j.hjkx.202308118","DOIUrl":"https://doi.org/10.13227/j.hjkx.202308118","url":null,"abstract":"<p><p>Revealing the spatiotemporal coupling relationship between urbanization and ecosystem services can help to clarify regional development differences, optimize the implementation path of urbanization, and improve the quality of ecosystem services. Taking southeastern Fujian, a region with a good ecological foundation and strong urbanization potential, as a case study, the levels of multidimensional urbanization systems and typical ecosystem services of this region in the years 2000, 2010, and 2020 were quantified using the index comprehensive evaluation method and the InVEST model. The Pearson correlation coefficient and the coupling coordination degree model were used to analyze the spatiotemporal coupling relationship between urbanization and ecosystem services, and suggestions for improving regional coordinated development were proposed. The results showed that： ① The comprehensive urbanization level in southeastern Fujian increased continuously, with an average annual growth rate of 7.3%, of which social urbanization was the fastest, followed by economic urbanization and population urbanization, and spatial urbanization was relatively backward. Ecosystem services tended to decline, especially food and water provision services, which decreased by 61.9% and 46.9%, respectively. The spatial distribution showed a mismatch pattern of \"high urbanization level and weak ecosystem services\" in the southeast coastal area and \"low urbanization level and strong ecosystem services\" in the northwest inland area. ② The correlation between urbanization and ecosystem services was mainly negative. The negative effect of economic and social urbanization on ecosystem services was weaker than that of population and spatial urbanization, with a clear weakening tendency. As population and spatial urbanization slowed down sharply and economic and social urbanization accelerated, the driving force of urbanization development gradually shifted from \"quantitative increase\" to \"qualitative improvement.\" Thus, the decline of ecosystem services was alleviated. ③ Comprehensive urbanization and various ecosystem services experienced three stages of \"imbalance-transition-reconciliation,\" with an average increase of 60.5% to 120.6% in the coupling coordination degree. However, highly coordinated regions remained scarce, indicating that there is still significant room for improvement. The relative relationship between urbanization and ecosystem services evolved from urbanization lag to ecosystem services lag. The fluctuation problem of backward coupling coordination level caused by excessive urbanization had initially appeared in the southeastern coastal area. Therefore, in future construction, southeastern Fujian should improve economic quality and social benefits； strengthen the overall management, protection, and restoration of ecological space； and enhance the order and stability of the coordinated development of urbanization and ecosystem services.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Analysis of Ozone and VOCs Pollution Characteristics, Sources, and Abatement Control Strategies in Hebi].","authors":"Yu-Ting Liu, Zhan-Xia Du, Xin-Min Zhang, Sha Chen, Ying-Ying Liu, Lan-Tian Zhang","doi":"10.13227/j.hjkx.202307102","DOIUrl":"https://doi.org/10.13227/j.hjkx.202307102","url":null,"abstract":"<p><p>In order to control the increasing ozone （O₃） pollution in Hebi, Henan Province, clarifying the pollution characteristics of ozone and its precursors is vital. Therefore, we conducted a comprehensive analysis of O₃ pollution utilizing the OFP-PMF-EKMA method combined with online hourly resolution monitoring data of conventional pollutants and volatile organic compounds （VOCs） in the summer of 2022 （June-September）. Ozone formation potential （OFP） was used to identify the key VOCs species, and the PMF model was used to identify the VOCs emission sources, whereas EKMA curves and scenario analysis were used to identify the main ozone control area in Hebi and to determine the reduction ratio of VOCs and NO<i>_x</i> in a scientifically refined way. In 2022, Hebi had persistent O₃ pollution, with the highest concentration in June. Conditions of high temperature, low humidity, and low atmospheric pressure contributed to the O₃ accumulation. Aromatic and oxygenated volatile organic compounds （OVOCs） contributed significantly to the OFP and VOCs fraction, which were the dominant active substance and concentration dominant species. The results of the VOCs source analysis indicated that vehicle exhaust sources （25.3%） were the main source of atmospheric VOCs, followed by process sources （17.7%） and biomass combustion sources （17.6%）. Thus, emission sources associated with the combustion of fossil fuels and industrial production emissions were the most urgent sources of atmospheric VOCs to be controlled in Hebi. The O₃ generation in Hebi occurred in the VOCs-sensitive zones, and the emission reduction results showed that a synergistic emission reduction of VOCs and nitrogen oxide （NO<i>_x</i>） could effectively control O₃ pollution with a 75% reduction in VOCs and a 10% reduction in NO<i>_x</i>.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Estimation of Near-surface Ozone Concentration in the Beijing-Tianjin-Hebei Region Based on XGBoost-LME Model].","authors":"De-Cai Gong, Ning Du, Li Wang, Xian-Yun Zhang, Long Li, Hong-Fei Zhang","doi":"10.13227/j.hjkx.202307110","DOIUrl":"https://doi.org/10.13227/j.hjkx.202307110","url":null,"abstract":"<p><p>High spatiotemporal resolution data on near-surface ozone concentration distribution is of great significance for monitoring and controlling atmospheric ozone pollution and improving the living environment. Using TROPOMI-L3 NO₂, HCHO products, and ERA5-land high-resolution data as estimation variables, an XGBoost-LME model was constructed to estimate the near-surface ozone concentration in the Beijing-Tianjin-Hebei Region. The results showed that： ① Through correlation analysis, surface 2 m temperature （T2M）, 2 m dewpoint temperature （D2M）, surface solar radiation downwards （SSRD）, tropospheric formaldehyde （HCHO）, and tropospheric nitrogen dioxide （NO₂） were important factors affecting the near-surface ozone concentration in the Beijing-Tianjin-Hebei Region. Among them, T2M, SSRD, and D2M had strong correlations, with correlation coefficients of 0.82, 0.75, and 0.71, respectively. ② Compared with that of other models, the XGBoost-LME model had the best performance in terms of various indicators. The ten-fold cross-validation evaluation indicators <i>R</i>², MAE, and RMSE were 0.951, 9.27 μg·m^-3, and 13.49 μg·m^-3, respectively. At the same time, the model performed well at different time scales. ③ In terms of time, there was a significant seasonal difference in near-surface ozone concentration in the Beijing-Tianjin-Hebei Region in 2019, with the concentration changing in the order of summer &gt; spring &gt; autumn &gt; winter. The monthly average ozone concentration in the region showed an inverted \"V\" trend, with a slight increase in September. The highest value occurred in July, whereas the lowest value occurred in December. In terms of spatial distribution, the near-surface ozone concentrations in the Beijing-Tianjin-Hebei Region during the months of February and March were generally at the same levels. In January, November, and December, there was a relatively insignificant trend of higher concentrations in the north and lower concentrations in the south. For the remaining months, the spatial distribution of near-surface ozone concentrations in this area predominantly exhibited a pattern of higher concentrations in the south and lower concentrations in the north. High-value areas were predominantly found in the plain regions of the southern part with lower altitudes, dense population, and higher industrial emissions； low-value areas, on the other hand, were primarily located in mountainous areas of the northern part with higher altitudes, sparse population, higher vegetation coverage, and lower industrial emissions.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Spatiotemporal Trends and Driving Factors of PM_2.5-related Health Burden in Gansu Province, China from 2013 to 2020].","authors":"Qin Liao, Yong Li, Yan Tao","doi":"10.13227/j.hjkx.202308073","DOIUrl":"https://doi.org/10.13227/j.hjkx.202308073","url":null,"abstract":"<p><p>To evaluate the spatiotemporal trends and drivers of PM_2.5-related health effects in Gansu Province since the implementation of the Air Pollution Prevention and Control Action Plan, the latest global exposure mortality model （GEMM） was adopted to estimate the health burden attributable to PM_2.5 in Gansu Province from 2013 to 2020. The factor decomposition method was used to further quantify the main causes of the long-term changes in deaths attributable to PM_2.5 pollution. The results showed that from 2013 to 2020, the population-weighted PM_2.5 concentration in Gansu Province decreased by 34.57%, and the proportion of people exposed to areas with an annual average PM_2.5 concentration exceeding 35 μg·m^-3 decreased significantly from 72.89% to 11.61%. Moreover, the number of attributable deaths in Gansu Province declined from 12 826 （95%CI： 7 840-17 408） in 2 013 to 9 814 （95%CI： 6 407-13 036） in 2020, indicating a decrease of 23.48%. Attributable deaths from stroke, chronic obstructive pulmonary disease, lung cancer, and lower respiratory infection declined, whereas deaths from ischemic heart disease increased by 12.11%. Notably, individuals aged 60 years and older accounted for more than 80% of all age-related deaths. The number of deaths attributable to PM_2.5 in central and eastern Gansu Province was significantly higher than that in the Hexi region, and most regions showed a downward trend. The contribution of the total population, age structure, baseline mortality rate, and PM_2.5 concentration to the change in PM_2.5-related deaths was -1.26%, 16.16%, -9.84%, and -28.55%, respectively. Overall, population aging and a decrease in PM_2.5 concentration were the main factors contributing to the increase and decrease in PM_2.5-related deaths, respectively. The active clean air policies in Gansu Province have reduced the health burden caused by PM_2.5 pollution, but with the trend of population aging, a significant reduction in PM_2.5 concentration will be needed in the future to avoid more attributable deaths.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Evolution Trend of Water Quality in the Inner Mongolia Section of the Yellow River from 2003 to 2020].","authors":"Yuan-Song Hou, Zhi-Lei Xie, Yong-Li Tian, Jia-Wei Jiang, Yun-Qing Liang, Qian Wang, Qiang Fang, Tao Xu, Ying-Fang Zhang, Hao Li, Li-Han Ce","doi":"10.13227/j.hjkx.202305068","DOIUrl":"https://doi.org/10.13227/j.hjkx.202305068","url":null,"abstract":"<p><p>The aim of this study was to comprehensively understand the water environment quality status and its change trend in the Inner Mongolia section of the Yellow River Basin. To analyze the water quality in recent years,the water quality data in the Yellow River basin from 2003 to 2020 were firstly collected from five typical monitoring stations．Various data analysis methods, including principal component analysis, cluster analysis, and a long short-term memory model, were used along with an improved comprehensive water quality identification index to explore the spatiotemporal characteristics of water quality in the Yellow River Basin. The results showed that the overall water quality in the basin has improved and stabilized over time. In terms of temporal variation, there was a distinction between the wet season and dry season, with a better status observed during the wet season due to increased agricultural irrigation and higher water volume. Spatially, the five monitoring sections could be divided into three categories based on strong natural factors that maintained their temporal characteristics during the wet season； however, significant differences were observed during the dry season due to urban water usage patterns. Analysis using LSTM models revealed that ammonia nitrogen will continue to decline and have a decreasing impact on the comprehensive water quality. These findings provide valuable insights for the comprehensive management of water quality in Inner Mongolia's Yellow River Basin.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Identification and Derivation of Emerging Contaminants in the Roof Rainwater Confluence].","authors":"Xin-Yue Ju, Zan Gao, Wen-Hao Zheng, Qiong-Hua Zhang","doi":"10.13227/j.hjkx.202307236","DOIUrl":"https://doi.org/10.13227/j.hjkx.202307236","url":null,"abstract":"<p><p>To identify emerging contaminants （ECs） in rainwater is a topic that has gradually received widespread attention. Rainwater resources, specifically urban roofs, play a crucial role in utilizing rainwater efficiently by understanding the occurrence and migration characteristics of pollutants in precipitation. This study selected a typical roof and studied the differences in rainwater quality and pollution occurrence at different collection stages during six rainfall events from March to May in 2023. Principal component analysis （PCA） and correlation analysis were used to explore the distribution, migration, and transformation of ECs in the collection process of roof rainwater. The findings revealed the presence of 44/54 ECs in wet deposition, dry and wet deposition, and roof runoff processes, with a total concentration range of 63.0 to 432.4 ng·L^-1 and an average concentration of 166.8 ng·L^-1. Notably, bisphenol A （BPA） exhibited the highest concentration, ranging from 14.7 to 265.6 ng·L^-1, with an average concentration of 62.5 ng·L^-1, followed by ofloxacin （OFX） and ethylhexyl methoxycinnamate （EHMC）, with detected concentrations up to 45.5 ng·L^-1 and 44.8 ng·L^-1. Dissolved organic matter （DOM）, nitrogen pollutants, and particulate matter were important factors affecting the occurrence characteristics of ECs, with a mantel correlation coefficient of up to 0.98 （<i>P</i><0.01）. Based on the analysis of different rainfall events and collection stages, variations were observed in the accumulation pathways and contribution ratios of different pollutants. The wet deposition exhibited the highest content of ECs in the initial stage, whereas the dry and wet deposition and roof runoff processes displayed higher ECs content in the later stages. Additionally, the average ECs contribution rates of dry and wet deposition to roof runoff were 21.48% and 78.52%, respectively. Due to the influence of roof material and surface roughness retention performance, over 30% of ECs, including pharmaceuticals and personal care products （PPCPs）, endocrine-disrupting compounds （EDCs）, and pesticides, were deposited on the roof during the runoff collection. The results of this research can provide the theoretical foundation and technical support for the identification and control of ECs in urban roof runoff and for the safe storage of rainwater.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634776","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"[Structure and Function of Fungal Community in Channel Sediments of Different Sections of Jialing River].","authors":"Yu Wang, Fei Xu, Lan-Ping Zhu, Tuo Zhang, Si-Yao Liu, Lei Jian, Shu-Cong Lü","doi":"10.13227/j.hjkx.202307209","DOIUrl":"https://doi.org/10.13227/j.hjkx.202307209","url":null,"abstract":"<p><p>This study aimed to explore the effects of different disturbances on the fungal communities in the sediments of the Jialing River in order to provide scientific basis for the protection of the river ecosystem. The fungal community in the sediments of the main stream of the Jialing River was taken as the research object, and high-throughput sequencing and bioinformatics techniques were used to analyze the differences in the composition and function of fungal communities in river sediment of different types of disturbance （project disturbance, tributary disturbance, sand mining disturbance, and reclamation disturbance） and non-disturbance sections. The results showed that： ① The reclamation and project disturbances significantly inhibited the diversity and richness of fungal communities （<i>P</i><0.05）. The tributary disturbance increased the richness of fungal communities, whereas the impact of sand mining disturbance on sediment fungal communities was not significant. ② The diversity and composition of fungal communities tended to be similar at the different sampling sites in the section with low input of exogenous substances （non-disturbance and sand mining disturbance）, whereas there were obvious differences in the diversity of fungal communities at the different sampling sites of high input of external substances （tributary disturbance, project disturbance, and reclamation disturbance） sections. ③ Ascomycota, Rozellomycota, and Basidiomycota were the main dominant fungal phyla in the sediments of the Jialing River. The relative abundance of Rozellomycota was the highest in the sand mining interference section, and the relative abundance of Basidiomycota was the highest in the tributary interference section. Project disturbance significantly increased the relative abundance of saprotrophs, animal pathogens, plant pathogens, and dung saprotrophs, whereas other disturbances inhibited the relative abundance of fungal parasitic fungi, plant pathogens, and plant saprophytes. In conclusion, human disturbance has caused changes in fungal diversity, community structure, and function in the sediment of the Jialing River, and xenobiotic input was a key factor contributing to this phenomenon. The results can provide a reference for predicting and evaluating the ecological quality of river sediments.</p>","PeriodicalId":35937,"journal":{"name":"Huanjing Kexue/Environmental Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141634783","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}