环境科学最新文献

{"title":"[Immobilization of Heavy Metals in Municipal Sludge by Co-pyrolysis of Shaddock Peel and Sludge].","authors":"Xiao-Fang Shen, Xin-Yan Gong, Xian Yuan, Qing-Hua Li","doi":"10.13227/j.hjkx.202312034","DOIUrl":"https://doi.org/10.13227/j.hjkx.202312034","url":null,"abstract":"<p><p>Co-pyrolysis with other biomass is a promising method for municipal sludge treatment and has attracted great attention. However, the dominant mechanism by which the heavy metals in municipal sludge are immobilized during the co-pyrolysis remains unknown. In this study, municipal-sludge biochar was prepared by pyrolysis and co-pyrolysis, and the effects of pyrolysis temperature （400-800 ℃） and the addition of shaddock peel on the properties of biochar, the contents of heavy metals （Cu, Zn, Pb, Cd, Ni, and Cr）, and their environmental risks were investigated. Based on the analysis of characterization results and heavy metal contents in the biochar, it was observed that co-pyrolysis promoted the formation of stabilized crystalline minerals （e.g., CdPbO₃, Pb₅（PO₄）₃OH, CuCl, and ZnS）, which reduced the potential risk of heavy metals in biochar. Furthermore, aromatic groups were detected and could interact with heavy metals through cation-π interaction. Further analysis revealed that the immobilization was enhanced by the complexation between heavy metals and the functional groups in biochar, such as -OH and -CO-NH-, which played the main role in the stabilization of Cu and Ni at low pyrolysis temperatures. However, surface sorption and pore filling, due to the increase in specific surface area and porosity, dominated the immobilization of Cd, Cr, Pb, and Zn. The leaching concentrations of heavy metals in co-pyrolysis biochar were much lower than the limit values of \"Identification Standards for Hazardous Wastes-Identification for Extraction Toxicity\" （GB 5085.2-2007） and those by US EPA 1311, 1990. Additionally, the potential ecological risk index （RI value） of heavy metals in biochar was significantly reduced by co-pyrolysis compared to that of sludge or biochar without the co-pyrolysis. This study reveals the dominant immobilization mechanism for specific heavy metals during co-pyrolysis of municipal sludge with shaddock peel and provides an alternative practical strategy for the safe disposal of municipal sludge and biomass wastes.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"944-955"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441430","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":"[Distribution, Source Apportionment, and Health Risk Assessment of Inorganic Components in Groundwater in the Plain Area of Manas River Basin in Xinjiang].","authors":"Wen-Hui Kang, Yin-Zhu Zhou, Jin-Long Zhou, Feng Jiang, Shuang-Bao Han, Mi Lei, Jin-Wei Liu","doi":"10.13227/j.hjkx.202401204","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401204","url":null,"abstract":"<p><p>Groundwater is the main source of water for daily life, agricultural irrigation, and industrial production in the Manas River Basin （MRB） in Xinjiang. To explore the spatial distribution and sources of inorganic components in groundwater and their negative effects on human health, 37 groundwater samples were collected in the plain area of MRB. The spatial distribution, sources, and potential health risks of inorganic components in groundwater were analyzed using Kriging interpolation, PMF source analysis, Pearson correlation analysis, and a health risk assessment model. The results showed that all of the groundwater in the area was weakly alkaline. Groundwater TDS and Cl^- had similar distribution characteristics, being higher in the eastern part of the plain area. The high SO₄^2- area was mainly distributed in the periphery of Manas County and the edge of the Gurbantonggut desert. The distribution of groundwater NO₃^--N, which was greatly affected by human activities, showed spatial heterogeneity, and the high-value areas were mainly distributed in urban areas. Arsenic （As）, fluoride （F）, and iodine （I） were important inorganic components affecting groundwater quality, with over-limit rates of 51.35%, 45.95%, and 51.35% according to the Standard for Groundwater Quality （GB/T 14848-2017）. High As, F, and I groundwater was distributed in the low plain area north of the West Bank Canal, which had a small topographic slope, hydraulic gradient, and aquifer particles with weak groundwater runoff intensity and was conducive to the enrichment of groundwater As, F, and I. Source apportionment showed that groundwater in different aquifers had similar sources or evolution processes. The concentration of inorganic components was controlled by leaching concentration, point source pollution under the geological environment-domestic sewage-agricultural irrigation, agricultural activities, point source pollution caused by domestic sewage, an alkaline-reducing environment, and ion exchange. Health risk assessment showed that As in groundwater was the main inorganic component threatening human health. The non-carcinogenic risk for children and adults could be ignored, whereas the carcinogenic risk cannot be ignored, and children were more sensitive to the risk of cancer caused by inorganic substances in the groundwater. Therefore, more attention should be paid to As exposure to drinking water safety, especially for children.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"843-853"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442082","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":"[Environmental Screening Drives the Assembly Process of Periphytic Algae Community in the Lower Reaches of Yarlung Zangbo River].","authors":"Hui-Qiu Liu, Sheng-Xian Yang, Xin Chao, Bing-Jie Yan, Pei-Pei Wei, Xiang-Jun Wu, Sang Ba","doi":"10.13227/j.hjkx.202402145","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402145","url":null,"abstract":"<p><p>Periphytic algae is an important primary producer in the river ecosystem, and it is one of the important indicators for the monitoring and evaluation of river water ecology. As a typical plateau river, the assembly process of the algae community in the Yarlung Zangbo River is still unclear. In May 2022 and July and September 2023, algae samples were collected, and water environmental factors were determined in the lower reaches of the Yarlung Zangbo River. The algal species were identified, and cell abundance and biomass were calculated using in vivo observation and fixed staining techniques to explore the diversity pattern of algae communities in the lower reaches of the Yarlung Zangbo River, to clarify the relative importance of deterministic and random processes in the assembly of algal communities, and to reveal the influencing factors driving the assembly process. The results showed that there were significant differences in the time of water environmental factors, mainly concentrated between spring, summer, summer, and autumn. A total of 274 species of algae were identified in the three seasons, belonging to 7 phyla, 9 classes, 18 orders, 31 families, and 63 genera, and the community differences between seasons were significant （<i>P</i>=0.001）. They all showed Bacillariophyta-Chlorophyta-Cyanophyta, and the community assembly process of algae was affected by both a deterministic process and random process but was dominated by the deterministic process. The interspecific relationship was mainly cooperative, and the co-occurrence network in autumn showed stronger network complexity and connectivity. The pH and turbidity were important water environmental factors affecting the community structure of algae, which could indirectly affect the community assembly process of algae by driving the metabolic rate and ecological adaptability of algae species.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"889-899"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442122","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 Spatiotemporal Changes and Driving Factors of Ecological Environment Quality in the Yellow River Basin].","authors":"Jing-Xin Zhang, Yu-Xin Gu, Jia-Qi Shen, Ming-Qi Zhang, Ming Cong, Yan Sun, Jiao-Jie He, Li-Wei Yang","doi":"10.13227/j.hjkx.202401141","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401141","url":null,"abstract":"<p><p>The Yellow River Basin plays an important role in China's economic development and ecological protection. Based on remote sensing ecological index （RSEI） data, climate data, digital elevation data, and night-time remote sensing data, the RSEI index was used as the ecological environment quality evaluation index. such as Theil Sen slope estimation, Hurst index, and Mann-Kendall test were used to evaluate the spatiotemporal changes in the ecological environment quality of the Yellow River Basin from 2001 to 2021. Geodetectors were used to quantitatively detect and analyze the key factors and their interactions in the ecological environment of the basin. The results showed that： Firstly, the overall ecological environment quality in the Yellow River Basin was slightly lower than the moderate level and gradually improved from the northwest to the southeast. The areas with moderate and lower grades accounted for 83.12% of the total area in the basin. The ecological environment quality has shown an upward trend in the past 21 years, which was confirmed by a significance test with a confidence level of 95%. Secondly, the ecological quality within the region showed a phased change of rising decreasing rising, with frequent area transfer between adjacent ecological levels and migration of ecological positions at different levels. The proportion of ecological improvement areas in the past 21 years reached 58.09%, but 51.75% of the regional improvement trend did not pass the significance test. Thirdly, the future ecological environment quality in the basin is expected to deteriorate, with the proportion of continuously deteriorating areas accounting for 24.39% and the proportion of areas transitioning from improvement to deterioration accounting for 5.08%. Attention should be paid to the ecological deterioration risks in Qinghai and Gansu, and the trend of ecological degradation in Inner Mongolia should be curbed. Fourthly, the results of the geographical detector indicated that the ecological environment in the Yellow River Basin was mainly influenced by population density, and the influence of climate factors represented by rainfall has been continuously increasing. The interaction between the two factors enhanced the explanatory power of the factors, with the main interaction type being mutual enhancement, accounting for 70.2%. In the future, efforts should be made to strengthen the ecosystem governance in the Yellow River Basin and carry out comprehensive ecological restoration work considering both human activities and climate change. The evaluation of the ecological environment in the Yellow River Basin can provide a theoretical basis and data support for implementing targeted measures and promoting ecological protection and high-quality development in the basin.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"956-971"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441939","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-temporal Relationships Between Urbanization Levels and Air Pollution Across Various Stages of Urbanization Nationwide].","authors":"Chen-Hao Xue, Bin Zou, Yong Xu, Shen-Xin Li, Sha Li","doi":"10.13227/j.hjkx.202402046","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402046","url":null,"abstract":"&lt;p&gt;&lt;p&gt;This research investigates the spatial and temporal relationship between urbanization levels and air pollution in cities at different stages of urbanization in China, highlighting its significance for guiding cities towards green development with reduced pollution and carbon emissions. The study uses a range of datasets from 2005 to 2020, including per capita GDP raster data, land use type data, remotely sensed PM&lt;sub&gt;2.5&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt; concentration data, and meteorological raster data. The urbanization stages for the years 2005, 2010, 2015, and 2020 were classified using the Chenery standard, facilitating a nuanced analysis of urban growth patterns. A one-way analysis of variance（ANOVA）was employed to examine the significance of differences in PM&lt;sub&gt;2.5&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt; concentrations across urbanization stages, revealing distinct pollution profiles. Furthermore, multi-scale geographically weighted regression（MGWR）was applied to quantitatively analyze the spatial and temporal correlations between urbanization levels and the concentrations of PM&lt;sub&gt;2.5&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt;, offering insights into the complex dynamics at play. The findings indicate a progression through six urbanization stages from 2005 to 2020. In 2005, 110 cities were in the primary product stage （PPS）, and 118 were in the primary industrialization stage （PIS）. By 2010, the urbanization phase had shifted predominantly towards industrialization, with 139 cities in the medium-term industrialization stage （MIS） and 88 in the late industrialization stage （LIS）. The trend continued towards advanced stages, with the majority of cities in 2015 and 2020 being in the middle to late industrialization and developed stages. The number of cities in the primary developed stage （PDS）and the developed stage （DS）reached 80 and 91, respectively. The spatial distribution of PM&lt;sub&gt;2.5&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt; concentration trends and their average values at different urbanization stages showed significant variance. From PPS to DS, the average PM&lt;sub&gt;2.5&lt;/sub&gt; concentration initially rose and then declined, with concentrations during the industrialization stage higher than in the primary and developed stages. In contrast, the average O&lt;sub&gt;3&lt;/sub&gt; concentration trended upward across all stages, reaching its peak in the developed stage. The MGWR results identified significant regional variations in the impact of urban built-up area proportions on PM&lt;sub&gt;2.5&lt;/sub&gt; and O&lt;sub&gt;3&lt;/sub&gt; concentrations. High-value areas for PM&lt;sub&gt;2.5&lt;/sub&gt; regression coefficients in 2005 and 2010 were predominantly found in the Yunnan-Guizhou-Sichuan urban cluster, extending northeast by 2015 and 2020 to cover most of China. Conversely, high-value areas for O&lt;sub&gt;3&lt;/sub&gt; regression coefficients from 2005 to 2020 were mainly in western and central China, with eastern regions, particularly in the south, showing significantly lower coefficients, indicating a negative correlation overall. Synergisti","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"705-714"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442301","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":"[Carbon Emission Performance of Chinese Cities Under the Background of Economic Transformation： Characteristics and Effects].","authors":"Zheng-de Fan, Zhi-Ji Huang, Cheng-Dong Yi, Jia-Rong Liao, Ming-Yue Song","doi":"10.13227/j.hjkx.202401096","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401096","url":null,"abstract":"<p><p>This study calculates the carbon emission performance of 277 Chinese cities from 2006 to 2020 with the help of an SBM-DEA model, displays its evolution characteristics using the ArcGIS platform, and empirically tests and analyzes the local and spatial spillover effects of economic transformation on carbon emission performance using the spatial Durbin model. The results showed that： ① The carbon emission performance level of Chinese cities was generally high, but the trend of decline was obvious, and the distribution showed the characteristics of low-level agglomeration from equilibrium distribution to U-shaped transformation. ② At the current stage, the local promoting effect of economic transformation on the improvement of carbon emission performance has not been fully revealed. The marketization, globalization, and fiscal decentralization of local urban economic transformation significantly improved the carbon emission performance of local cities, but the decentralization of administrative categories, the intensity of environmental regulation, and the level of green technology innovation inhibited the improvement of carbon emission performance. ③ Carbon emission performance was spatially dependent. The globalization level of economic transformation, environmental regulation intensity, green technology innovation level, and improvement of carbon emission performance of neighboring cities had a positive spillover effect on local carbon emission performance, while the decentralization level of administrative categories had a negative spillover effect. Clarifying the level and distribution of urban carbon emission performance and explaining it from the perspective of economic transformation is of great practical significance for promoting the realization of the \"double carbon\" goal in China and other countries.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"660-668"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441945","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":"[Niche and Interspecific Association of Phytoplankton Dominant Species at Different Hydrological Periods in Xiaoche River, Guizhou Province].","authors":"Shuang-Yan Wang, Jing Xiao, Chun-Chun Chen, Jia-Xiang Pan, Shu-Chan Peng, Qiu-Hua Li","doi":"10.13227/j.hjkx.202401178","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401178","url":null,"abstract":"<p><p>To understand the niche and interspecific association of phytoplankton in different hydrological periods of the Xiaoche River in Guizhou Province, phytoplankton samples were collected in two different hydrological periods （dry period and wet period） from 2020 to 2022. The niche width （<i>B_i</i>），niche overlap（<i>O_ik</i>），variance ratio method（VR），chisquare test（<i>χ</i>²）, AC test, and Jaccard index （JI） were used to analyze the niche and interspecific association of phytoplankton dominant species. The results showed that a total of 7 phyla and 50 species of phytoplankton were identified in the Xiaoche River, with 4 phyla and 12 species being the dominant species. The combination analysis of niche width and FG functional group showed that the water environment of the Xiaoche River in a medium eutrophic state. The dominant species could be divided into broad niche species, medium niche species, and narrow niche species, and the niche width of the dominant species varied between 1.278 and 4.849. No significant difference exists in the three years of niche overlap value, with the proportion of <i>O_ik</i>&gt;0.6 being 50.00% （2020）, 42.86% （2021）, and 53.49% （2022）, respectively, indicating that there were close to the same or more common species occupying environmental resources in a highly similar way. The dominant species showed a significant positive correlation overall, and the community was relatively stable. The chi-square test showed that only four pairs of 66 dominant species had significant associations； the AC test showed that 33 pairs had significant associations； and the Jaccard index showed that 41 pairs had significant associations, all of which showed more negative than positive associations, indicating that the phytoplankton community in the Xiaoche River was in the early stage of succession.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"900-909"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442215","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 Evolution Characteristics and Influencing Factors of China's Industrial Carbon Emissions at the \"City-industry\" Scale： From the Perspective of Industrial Correlation].","authors":"Zhi-Ji Huang, Ming-Yue Song, Zheng-de Fan, Ke-Ying Xiang","doi":"10.13227/j.hjkx.202401095","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401095","url":null,"abstract":"<p><p>In the context of the deepening of the \"dual carbon\" strategy, based on the customs database and the energy consumption database, starting from the \"city-industry\" scale, this study characterizes and analyzes the spatiotemporal distribution characteristics of carbon emissions from double-digit industrial industries in prefecture-level cities in China. We constructed a fixed effects model using panel data and studied the impact and transmission mechanism of industrial correlation, empowering industrial carbon reduction. Moreover, it was revealed that： ① The carbon emission intensity of various industries in the eastern and central western regions had decreased, and the difference in industry carbon emissions between the two regions had been significantly reduced. The carbon emission intensity of the same industry category in the central and western regions decreased more significantly, and the effectiveness of industrial carbon reduction measures was significant. ② Improving the level of industry correlation within cities was an alternative path to reducing carbon emissions. For every 1% increase in industrial correlation, the average carbon emission intensity decreased by 0.234%, a result that still held after a series of robustness tests. ③ This effect was more significant in capital-intensive industries, middle- and low-end technology industries, western regions, and cities with stronger government intervention. ④ The quality of technological innovation and the vitality of the digital economy played an important intermediary role in the carbon emission reduction effect of industrial linkage. Industrial linkage promoted the reduction in industrial carbon emission intensity by improving the quality of technological innovation and economic innovation vitality. The research results uncovered the \"black box\" of the effectiveness of industry correlation in promoting industry carbon reduction at the \"city-industry\" scale, which can provide new decision-making references for achieving coordinated and unified regional industrial development and low-carbon transformation.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"647-659"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442307","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 Soil Property Factors Restricting the Remediation Effect of Passivators on Arsenic and Cadmium Pollution in Purple Soil].","authors":"De-Cai Jiang, Zhen-Mao Jiang, Shi-Qiang Wei","doi":"10.13227/j.hjkx.202402102","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402102","url":null,"abstract":"<p><p>The effect of passivating agents on Cd and As is closely related to soil properties. Optimizing passivating agents that adapt to soil properties is the key basis for the application of passivation technology. This study uses eight types of purple soils with widely different properties as test soils, uses indoor culture experiments, sets different pollution conditions, and simultaneously compares the passivation rates of cadmium （Cd） and arsenic （As） by seven common passivators. Additionally, combined with the measurement of soil physical and chemical properties, the relationship between passivation efficiency and soil properties was explored. The results showed that among the seven common passivators tested, calcium oxide, organic fertilizer, silicon calcium magnesium fertilizer, humic acid, and hydroxyapatite had a significant passivation effect on purple soil Cd, and iron oxide, silicon calcium magnesium fertilizer, hydroxyapatite, and humic acid had a passivating effect on As. Only three passivating agents, calcium silicon magnesium fertilizer, hydroxyapatite, and humic acid, had a passivating effect on both Cd and As. Great differences exist in the key soil property factors that determined the passivation efficiency of specific passivators： soil organic matter, clay content, and total potassium were significantly positively correlated with the passivation rate of soil Cd by the tested passivators； soil pH, free iron oxide, free manganese oxide, and total phosphorus were significantly negatively correlated with them； soil CEC, free manganese oxide, and soil total As were significantly positively correlated with the As passivation rate of the tested passivators； and the content of soil clay particles was significantly negatively correlated with it. The study established the optimal multiple linear regression model between the passivation efficiency of passivating agents Cd and As and the soil properties and pollution characteristics of purple soil. The model quantitatively reflects the relationship between the passivation efficiency of heavy metals and soil properties and can be used to predict and optimize adaptation accordingly. Highly efficient passivators with different soil properties provide a scientific basis for the safe use of regionally contaminated farmland.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1130-1144"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441934","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":"[Influences of Acidification on the Allocation and Availability of Lead and Cadmium within Soil Aggregates].","authors":"Shu-Ting Tang, Sheng-Bai Xiao, Hao Cui, Shi-Qiang Wei","doi":"10.13227/j.hjkx.202401288","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401288","url":null,"abstract":"<p><p>Soil aggregates, the fundamental units of soil structure, crucially regulate soil physicochemical properties. Acidification alters soil aggregation, impacting heavy metal distribution and availability within aggregates. This study explores aggregate composition in differently acidified yellow and purple soils, along with the variation in the distribution and availability of cadmium （Cd） and lead （Pb） in different-sized aggregates. Acidification reduced the mass fraction of large aggregates （&gt;2 mm）, with non-acidified soil being 5%-15% higher. In both soils, large aggregates contributed most to the total amount of Cd and Pb （contribution factors 0.31-0.47）. Yellow soil showed the highest Cd and Pb contents in small （1-0.25 mm） and micro-aggregates （&lt;0.25 mm）, while the highest contents were observed in large aggregates in acidified purple soil. The mass fractions determined the distribution of external Pb and Cd in aggregates when entered into soils. In highly acidified soil, smaller aggregates posed a higher heavy metal release risk, while in non-acidified soil, the large aggregates showed higher Cd and Pb contents and thus a higher release risk. The alterations in the transformation and availability of Cd and Pb were attributed to the variations in soil aggregate composition and their properties driven by acidification, including mineral weathering, iron oxide leaching, organic matter loss, etc. These results provide the basis for the co-remediation of soil acidification and heavy metal pollution.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1107-1117"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442032","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}