环境科学最新文献

{"title":"[Photochemical Causes of Localized Ozone Pollution under Static and Stable Weather in Nanjing Area].","authors":"Jie He, Jun-Lin An, Yue-Zheng Feng, Jia-Ying Zhu, Ling-Xia Wu","doi":"10.13227/j.hjkx.202401123","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401123","url":null,"abstract":"<p><p>Based on the observational data of volatile organic compounds （VOCs）, conventional air pollutants, and ERA5 meteorological reanalysis data at three sites, namely, Caochangmen （CCM）, Pukou （PK）, and Xianlin University Town （XL）, in Nanjing from 2015 to 2021, the ozone generation and depletion mechanisms in ozone-polluted days under stable weather conditions were investigated using the observation-based model （OBM-MCM）. The results showed that ① Significant year-by-year differences exist in the frequency of stable weather on ozone-polluted days for the three sites. The maximum number of stable days occurred in 2019, with 46 d （66.7%）, 50 d （64.9%）, and 54 d （69.2%） at the CCM, PK, and XL sites, respectively. ② Significant differences exist between the net O₃ production rates for the CCM, PK, and XL sites during the polluted period, with the highest rate of 2.5×10^-9 h^-1 at the CCM site and the lowest rate of 1.4×10^-9 h^-1 at the XL site. Additionally, the O₃ production and depletion rate at the XL site were lower compared to those at the other two sites. ③ The reactions of HO₂·+NO and ·OH+NO₂, respectively, contributed the most to O₃ production and depletion. The HO₂·+NO reaction contributed to O₃ production by 69% （CCM）, 68% （PK）, and 71% （XL）, and the ·OH+NO₂ reaction contributed to O₃ depletion by 67% （CCM）, 63% （PK）, and 62% （XL）. ④ The modeling study observed that ozone pollution under stable weather conditions was mainly affected by local photochemistry processes； therefore, local emission reduction is very important for O₃ pollution mitigation.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"755-763"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442225","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":"[PM_2.5 Prediction Based on EOF Decomposition and CNN-LSTM Neural Network].","authors":"Ming-Ming Li, Xiao-Lan Wang, Jiang Yue, Ling Chen, Wen-Ya Wang, Ai-Qin Yang","doi":"10.13227/j.hjkx.202401023","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401023","url":null,"abstract":"<p><p>Based on the surface meteorological data and ambient air quality data of Taiyuan from 2016 to 2020, the temporal and spatial variation characteristics of PM_2.5 concentration in Taiyuan were analyzed. The temporal and spatial variation characteristics of PM_2.5 concentration in Taiyuan were studied using the EOF decomposition diagnostic analysis method. At the same time, the importance of meteorological factors was analyzed using a random forest model, and a PM_2.5 concentration prediction model based on the CNN-LSTM neural network was established. The results showed that from 2016 to 2020, the annual mean PM_2.5 concentration in the urban area of Taiyuan generally exhibited a decreasing trend from year to year, and the high value mainly appeared in November, December, January, and February. From 18：00 to 02：00 of the next day, the peak value of PM_2.5 concentration was easily reached, and the annual average value of PM_2.5 concentration gradually increased from northwest to southeast. The EOF decomposition of PM_2.5 concentration was as follows： the variance contribution rate of modal 1 eigenvector was 49.4%, and the variance contribution rate of modal 2 eigenvector was 30.8%. Considering Nanzhai-Julun-Jinyuan as the boundary, it was a positive area to the northwest and a negative area to the southeast. The positive center appeared in Jinsheng district, and the negative center appeared in Xiaodian in the southeast. PM_2.5 concentration was positively correlated with relative humidity and dew point temperature. Moreover, it was mainly negatively correlated with wind speed, precipitation, and mixing layer height and generally negatively correlated with ventilation and self-purification capacity, with no significant correlations involving temperature. Relative humidity, dew point temperature, air pressure, humidity, and mixing layer height all played an important role in the ranking of the four seasonal characteristics, followed by wind speed, wind direction, ventilation volume, and self-purification capacity. Using the CNN-LSTM model for modeling, the <i>R</i>² of PM_2.5 concentration prediction was 0.805, 0.826, 0.897, and 0.901 in spring, summer, autumn, and winter, respectively. <i>R</i>² was above 0.8 in all four seasons. The predicted residuals of the CNN-LSTM model in all four seasons were approximately normally distributed, and the absolute error of the model was controlled within 10 μg·m^-3. The prediction results below 10 μg·m^-3 reached a maximum of 81.2% in summer, followed by 75.9% and 62.9% in autumn and spring, respectively. The performance in winter was average, with 51.5% of the prediction results having an absolute error below 10 μg·m^-3.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"715-726"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442227","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":"[Impact of Differences in Vegetation Cover on Soil Organic Carbon Composition and Stability in Caohai].","authors":"He-Feng Wan, Juan Jiang, Gui-Ting Mu, Yun-Chuan Long, Rong-Xiang Su","doi":"10.13227/j.hjkx.202402096","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402096","url":null,"abstract":"<p><p>Soil organic carbon （SOC） stability and carbon sequestration potential can be affected by vegetation cover. The Caohai in Guizhou is a typical plateau freshwater wetland ecosystem at the same latitude as other regions worldwide. The study focused on the soils from Caohai and selected five types of vegetation cover, including forest land, cultivated land, grassland, reeds, and tidal flats. Soil samples were collected vertically at depths of 0-20, 20-40, and 40-60 cm, and the activity and stability of SOC were tested to explore the impact of different vegetation covers on the composition and stability of SOC, finally providing basic data for soil carbon sequestration and ecological protection in the Caohai. The results indicated that cover variability led to differences in SOC content on the vertical distribution scale （<i>P</i>&lt;0.05）. Comparing SOC content in various covers with tidal flats （14.75 g·kg^-1） on a horizontal scale, reductions were observed in forests （19.32%）, reeds （15.05%）, cropland （12.47%）, and grassland （1.58%）. The proportions of stable and labile organic carbon （SAOC and LOC） accounted for 52.51% and 45.00% of the total SOC content, respectively. The <i>ω</i>（ROC） （g·kg^-1） values were 7.89 （forests）, 7.47 （tidal flats）, 6.67 （reeds）, 6.36 （cropland）, and 5.67 （grassland）, with N/P and TN being the main physicochemical factors influencing ROC （<i>r</i>≥0.72）. ROCI ranged from 0.16 to 0.34, with the highest in forest land and relatively lower values in cropland and grassland, mainly affected by N/P （<i>P</i>&lt;0.01）, negatively correlated with BD （<i>P</i>&lt;0.05）, and influenced by cover type （<i>P</i>&lt;0.001） and soil depth （<i>P</i>&lt;0.01）. Both cover type and soil depth interacted significantly with ROCI （<i>P</i>&lt;0.01）. The research indicated that vegetation cover variability altered organic matter decomposition and accumulation, leading to a differential distribution of organic carbon components. Agricultural activities affected the stability and accumulation status of organic carbon, contributing to the higher levels of unstable carbon components SAOC and LOC and exhibiting significant potential for soil carbon sequestration enhancement. Moreover, it is recommended to implement scientific management practices to transition towards a more stable state, thereby enhancing regional ROCI levels and carbon sequestration potential.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1046-1055"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441839","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":"[Impact of Meteorological Factors on Ozone Concentration in Four Typical Cities of Guangdong Based on Generalized Additive Model].","authors":"Ting-Yuan Li, Jing Tang, Jin Shen, Jing-Yang Chen, Yu Gong","doi":"10.13227/j.hjkx.202402121","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402121","url":null,"abstract":"<p><p>Based on the observation and reanalysis data in Guangdong from 2015 to 2020, the variation characteristics of ozone （O₃） concentration in Guangdong and four typical cities were analyzed, and the effects of meteorological factors on O₃ concentration in different cities and different seasons were revealed based on the generalized additive model （GAM）. The daily maximum 8-hour average O₃ concentration （O₃_8h） increased significantly from 2015 to 2019, with a trend of 5.0 μg·m^-3·a^-1, and decreased slightly in 2020 in Guangdong. The O₃_8h concentration and the total number of polluted days were substantially higher in autumn than those in other seasons in Guangdong and showed different variation characteristics in four typical cities. The highest values in Guangzhou, Heyuan, Jieyang, and Maoming occurred in summer and autumn, spring and summer, spring and autumn, and autumn, respectively. The regression model had a good fit for the variation in O₃_8h concentration, and the seasonal models were generally better than the annual models. As for the seasonal models, the average <i>R</i>² values were 0.78, 0.69, 0.70, and 0.65, and the mean interpretation rate of variance （IRV） values were 79%, 71%, 73%, and 67% in Guangzhou, Heyuan, Jieyang, and Maoming, respectively. The equation fitting degrees of the optimal models varied considerably in different cities and different seasons, with the <i>R</i>² values ranging from 0.52 to 0.83 and the IRV values ranging from 55.5% to 86.9%. The O₃_8h concentration showed a nonlinear relationship with meteorological factors. The meteorological factors that had a significant impact on the variation of O₃_8h concentration in different cities and seasons differed considerably, and all of the meteorological factors were in the top three lists of importance. Relative humidity was the most important meteorological factor affecting the variation in O₃_8h concentration in different cities, followed by the V-component of wind. When the relative humidity was below 45%, the O₃_8h concentration was relatively higher. When the relative humidity was above 45%, the O₃_8h concentration decreased with the increase in relative humidity. Higher O₃ concentrations appeared when the wind speed was greater than 2 m·s^-1, indicating the regional transport of pollutants and emphasizing the importance of regional joint prevention and control.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"746-754"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441960","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 Biochar Application Amount and Frequency on Yellow Soil Nutrients and Key Enzyme Activities].","authors":"Kai-Yu Li, Li-Hong Song, Yan Zhang, Yi Liu, Qin-Yao Ran, San-Wei Yang, Zu-Yong Chen, Guan-di He","doi":"10.13227/j.hjkx.202402127","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402127","url":null,"abstract":"&lt;p&gt;&lt;p&gt;Yellow soil, predominant in the southern regions of China, constitutes 28% of the nation's cultivated land. Exploring the regulatory mechanisms of biochar on nutrient levels and key enzyme activities in yellow soil holds significance for soil health restoration and food security. This study investigated the effects of different amounts and frequencies of biochar application on yellow soil nutrients and enzyme activities. The experiment involved two biochar application frequencies： ① a once'application amount of biochar at rates of 5 （B5）, 10 （B10）, 20 （B20）, and 50 （B50） t·hm&lt;sup&gt;-2&lt;/sup&gt;, and ② a consistent application of an equivalent total amount of biochar over three years at rates of 5 （B5-3）, 10 （B10-3）, 20 （B20-3）, and 50 （B50-3） t·hm&lt;sup&gt;-2&lt;/sup&gt;. A control treatment （CK） without biochar application （0 t·hm&lt;sup&gt;-2&lt;/sup&gt;） was included. The results of the study showed that the application of biochar in the yellow soil agriculture ecosystem significantly increased soil pH and electrical conductivity （EC）. Moreover, it improved the contents of alkaline hydrolysis nitrogen （AN）, available phosphorus （AP）, and organic carbon （SOC）. Furthermore, the activities of urease, phosphatase, sucrase, and catalase in the soil were increased by the application of biochar. A comparison between the two application modes showed that the continuous application of biochar resulted in higher soil nutrient levels and enzyme activities. No significant interactive effects of different biochar amounts and frequencies exist on soil pH, EC, AN, SOC, phosphatase, sucrase, and catalase activities. However, interactive effects were observed on AP, available potassium （AK）, and urease activity. The structural equation model elucidated that biochar had a direct negative effect on the activities of soil urease, catalase, phosphatase, and sucrase. Nevertheless, it indirectly promoted enzyme activity by enhancing soil nutrient levels. The application of biochar in yellow soil agriculture ecosystems consistently enhanced the soil's comprehensive fertility under both application modes. Among the once-application models, B10 emerged as the most effective treatment, exhibiting a higher comprehensive fertility score than that of other treatments. Specifically, compared to those in the control （CK）, soil pH, EC, AN, AP, AK, SOC, urease, phosphatase, sucrase, and catalase activities in B10 increased by 8.31%, 13.28%, 22.18%, 10.68%, 21.49%, 15.40%, 44.79%, 16.62%, 35.68%, and 16.62%, respectively. In contrast, for the continuous three-year application of biochar, treatment B50-3 had the highest comprehensive fertility score. Compared to that in CK, soil pH in B50-3 increased by 15.11%, EC by 26.26%, AN by 11.02%, AP by 43.30%, AK by 17.29%, SOC by 36.68%, urease by 20.44%, phosphatase by 3.71%, sucrase by 18.38%, and catalase activities by 16.62%. In summary, the application of biochar in yellow soil farmland could effectively enhance soil fertility by increasing soil nutrien","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1065-1075"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442090","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":"[Hydrochemical Characteristics of Shallow Groundwater and Identification of Water Quality Types in the Dawen River Basin].","authors":"Ya-Xin Zhang, Zi-Zhao Cai, Xiao-Bo Tan, Guang-Chao Wen, Xu Guo","doi":"10.13227/j.hjkx.202403023","DOIUrl":"https://doi.org/10.13227/j.hjkx.202403023","url":null,"abstract":"<p><p>Groundwater chemical characteristics and water quality are affected by both natural geological conditions and human activities. Taking the Dawen River Basin as the research object, we analyzed the hydrochemical characteristics and their influencing factors through field investigation and sampling, evaluated the water quality by applying the entropy-weighted water quality index （EWQI）, distinguished the degree of influence of human activities on the groundwater quality by applying the method of identifying hydrochemical anomalies, and then coupled the two evaluating methods to identify the types of groundwater water quality. The results showed that the anions and cations of groundwater in the Dawen River Basin were dominated by HCO₃^- and Ca²⁺, respectively, and the exceedance rates of TH, TDS, SO₄^2-, and NO₃^- concentrations in the groundwater were high； the groundwater chemistry types were dominated by HCO₃·SO₄-Ca, HCO₃·Cl-Ca, and HCO₃·SO₄·Cl-Ca types； and the chemical components of the groundwater were affected by the interaction between the water and rocks. The chemical components of groundwater were affected by water-rock interactions and human activities. The EWQI results showed that the proportions of groundwater quality classes I and II were 10.71% and 36.91%, respectively； the proportion of groundwater quality class III was 41.67%； and the proportions of class IV and V water were 5.95% and 4.76%, respectively. The water quality condition from the upstream to the downstream of the basin was getting worse, and the quality of fissure water and karst water was better than that of pore water. The areas where water chemistry identified a greater degree of anthropogenic influence were mainly located in the downstream Dongping County and Dongping Lake, in the middle reaches of the river in Ningyang County and Wenyang Town, and in the upper reaches of the river in Quangou and Yucun Towns, where human activities were mainly concentrated in the watershed's low-lying terrain. The above two evaluation results had a strong positive correlation, with a correlation coefficient of 0.588. Combining the two evaluation methods of EWQI and the degree of influence of human activities, the state of groundwater protection and management was classified into three categories： protection, prevention, control and management, which could make up for the fact that the single evaluation method was incomplete in identifying the type of water quality. Moreover, it is useful to differentiate between poor-quality water under natural geological conditions and poor-quality water caused by human activities.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"821-832"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442091","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":"[Impact of Different Vegetation Restoration Types on Soil Microbial Community Structure in the Restoration Area of Quarries in Northern Hebei Province].","authors":"Feng Yan, Xin Zhao, Li-Jun Shao, Xing-Yu Wang, Yue-Bing Liang, Ya-Heng Chen","doi":"10.13227/j.hjkx.202402063","DOIUrl":"https://doi.org/10.13227/j.hjkx.202402063","url":null,"abstract":"<p><p>Soil microorganisms have a strong influence on the soil environment of mining sites and the effectiveness of vegetation restoration. To investigate the response of soil microbial diversity in quarries in northern Jibei, China, to different types of vegetation restoration, we considered the common restoration vegetation in the area （YS, SJ, MX, MH, and CH） as the object of study and analyzed inter-root soil physicochemical factors and vegetation microbial community structure using the techniques of soil nutrient determination, high-throughput sequencing, and other methods. The results showed that： ① The type of vegetation restoration had a significant effect on the inter-root soil environment, and the alkaline dissolved nitrogen content of the inter-root soil of sea buckthorn and oil pine； the organic matter content of the soil of cotton acacia； and the microbial carbon content of lucerne, cotton acacia, and acacia were significantly higher than that of the control group （<i>P</i>&lt;0.05）. ② The community composition and diversity of bacteria and fungi differed significantly among the different vegetation types. Proteobacteria and Ascomycota were the main dominant populations of bacteria and fungi, respectively. The relative abundance of Anabaena was higher than that of other plants in oil pine and sea buckthorn, and the ACE and Chao1 indices of lucerne and acacia differed significantly （<i>P</i>&lt;0.05）, and the intergroup differences between different treatment groups were obvious （stress&lt;0.1）. ③ The microbial communities of different restoration types were significantly correlated with soil factors, and the structure of bacterial and fungal communities showed highly significant correlations with SOM, TN, and MBC （<i>P</i>&lt;0.01）. Among the bacterial communities, Acidobacteriota was positively correlated with microbial nitrogen content, alkaline dissolved nitrogen content, etc. Among the fungal communities； Olpidiomycota was positively correlated with TK and pH； the individual effects of nutrient factors were greatest in the bacterial phylum-level communities, and the synergistic effects of nutrient factors and enzyme activity factors were greatest in the fungal phylum-level communities. The conclusions of the study have theoretical implications for subsequent ecological restoration work in the mining area.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1213-1224"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441959","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 of Priority Sources for Heavy Metals in Soils of Typical Coal Gangue Accumulation Areas Based on Source-specific Health Risk Assessment].","authors":"Ji-Yang Zhao, Xing Chen, Liu-Gen Zheng, Yong-Chun Chen, Peng-Fei Tao","doi":"10.13227/j.hjkx.202403056","DOIUrl":"https://doi.org/10.13227/j.hjkx.202403056","url":null,"abstract":"<p><p>Heavy metals contained in coal gangue can be released into the surrounding environment through various pathways during long-term accumulation, posing potential threats to human health. To effectively control and mitigate the health risks of heavy metals in the soil of coal gangue accumulation areas, this study focused on the Panyi coal gangue accumulation area in Huainan. The study involved collecting soil samples to determine the concentrations of Cd, Zn, Cu, Fe, Mn, Cr, Ni, and Pb and employed the positive matrix factorization model for quantitative analysis of the contributions from different pollution sources of soil heavy metals. This approach, coupled with the results of the source analysis and a health risk assessment model, evaluates the risks posed by specific sources and further identifies the spatial distribution characteristics of health risk contributions from these sources. The results showed that the average concentrations of soil heavy metals Cd and Zn were 4.65 and 2.16 times their background values, respectively, with the average values of other heavy metals all below background levels. Among them, Zn was the most influenced by human activities. Source analysis indicated that the sources of soil heavy metals in the study area were influenced by coal gangue accumulation pollution, traffic activity pollution, natural parent material soil formation, and agricultural activity pollution sources, with contribution rates of 27.5%, 16.4%, 30.4%, and 25.6%, respectively. The non-carcinogenic risk of soil heavy metals to children requires special attention. Based on the specific source-health risk assessment model analysis, agricultural activities contributed the most to the non-carcinogenic risk to children （59.3%）, identifying them as a priority source for control measures. Given the spatial distribution of health risks from various sources, recommendations include enhancing the resourceful use of coal gangue, collecting and treating leachate from coal gangue, and implementing environmental management strategies to reduce pesticide and fertilizer use.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1098-1106"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442097","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":"[Evaluation of Annual Straw Return Based on Soil Carbon Pool and Crop Yield in Wheat-maize Cropping System].","authors":"Qun-Wen Wu, Pei-Hong Song, Jian-Hua Huang, Xin Qian, Ying-Bo Gao, Hui Zhang, Kai-Chang Liu, Liang Wang, Zong-Xin Li","doi":"10.13227/j.hjkx.202401267","DOIUrl":"https://doi.org/10.13227/j.hjkx.202401267","url":null,"abstract":"<p><p>The treatment and recycling of crop straws has become a hot spot in the field of agricultural research, with the need to optimize the management of wheat-maize annual straws, improve the carbon efficiency of cropping systems, and promote the sustainable production of wheat-maize annual straw. Based on an 8-year long-term field trial, two treatments, wheat-maize double cropping （WS-MS） and wheat-maize single cropping （WS-MN）, were set up, and the effects of straw returning on soil organic carbon （TOC） content, oxidizable organic carbon （EOOC） content, soil carbon storage, carbon pool management index （CPMI）, carbon use efficiency, and crop yield were compared between WS-MS and WS-MN treatments. The results showed that the content of TOC in WS-MS and WS-MN increased by 8.1% and 5.5%, respectively, and the content of EOOC in WS-MS and WS-MN increased by 50.4% and 45.5%, respectively. The WS-MS and WS-MN treatments increased organic carbon storage by 20.5% and 18.3%, respectively, but the WS-MS treatment did not significantly increase organic carbon storage compared with that in the WS-MN treatment. The carbon pool index （CPI）, carbon pool activity （CPA）, carbon pool activity index （CPAI）, and CPMI of WS-MS were 3.7%, 20.5%, 2.2%, and 7.9% higher than those of WS-MN, respectively. The annual yield of WS-MN was 0.2% higher than that of WS-MS. The annual production efficiency and ecological efficiency of WS-MN were 136.1% and 64.2% higher than those of WS-MS, respectively. The carbon benefit of the WS-MN treatment was significantly higher than that of the WS-MS treatment. Therefore, considering the straw return method, straw carbon utilization efficiency, and crop yield, the single season return of wheat straw is more suitable for the efficient utilization of annual straw resources in the intensive wheat-maize double cropping system in the Huang-Huai-Hai Region, without significantly affecting the annual grain yield of wheat-miaze and its soil carbon pool.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1016-1024"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143442126","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":"[Bacterial Community Structure and Functional Characteristics of Soil in <i>Carex</i> Tussock Marsh Wetland with Different Degradation Levels].","authors":"Miao-Miao Zhang, Man-Yin Zhang, Jing Li, Li-Juan Cui, Zi-Liang Guo, Wei-Wei Liu, He-Nian Wang, Da-An Wang","doi":"10.13227/j.hjkx.202403046","DOIUrl":"https://doi.org/10.13227/j.hjkx.202403046","url":null,"abstract":"<p><p>To explore the characteristics and influencing factors of soil bacterial communities in degraded marsh wetlands, we divided the <i>Carex</i> tussock marsh wetland in northeast China into three degradation degrees： non-degraded （ND）, mildly degraded （LD）, and heavily degraded （HD）. High-throughput sequencing technology and PICRUSt bacterial function prediction tools were used. We analyzed the soil environmental characteristics and soil microbial community structure characteristics of degraded wetlands and explored the influencing factors of microbial changes in degraded wetlands. The results showed that： ① The soil pH value was generally neutral to alkaline in general. With increasing degrees of degradation, the contents of soil organic carbon, total nitrogen, total carbon, and zinc decreased significantly （<i>P&lt;</i>0.05）, while the content of total potassium increased significantly （<i>P&lt;</i>0.05）. ② The dominant bacterial groups included Proteobacteria, Acidobacteriota, and Gemmatimonadota in the degraded wetlands. ③ The Alpha diversity of soil bacterial communities increased significantly with the increases in wetland degradation degree （<i>P&lt;</i>0.05）, and there was a significant difference between degraded （LD and HD） and non-degraded （ND） wetlands in bacterial community composition.④ From the perspective of bacterial community functions, the primary metabolic functions, such as metabolism, genetic information processing, cellular processes, and environmental information processing, were significantly weakened with the increasing degree of degradation （<i>P&lt;</i>0.05）. The main secondary functions such as amino acid metabolism, carbohydrate metabolism, biodegradation, and metabolism of exogenous substances were significantly weakened （<i>P&lt;</i>0.05）. ⑤ Pearson correlation analysis showed that the change in soil bacterial Alpha diversity was significantly correlated with the contents of soil total nitrogen, total carbon, and organic carbon and the physical characteristics （diameter, height, and number） of <i>Carex</i> hummocks （<i>P&lt;</i>0.05）. RDA results showed that pH value was a key factor affecting soil bacterial community structure in the degraded wetland （<i>P&lt;</i>0.05）. The functional differences of bacterial communities were mainly affected by the contents of soil total iron and zinc （<i>P&lt;</i>0.05）. In conclusion, soil physical and chemical properties, bacterial community diversity and structure, and bacterial community function changed regularly with the degree of degradation. Soil pH； contents of total nitrogen, total carbon, and organic carbon； and physical characteristics of <i>Carex</i> tussock were the key factors affecting the microbial community in the degraded wetland, which can provide the scientific basis for understanding the degradation and restoration processes of <i>Carex</i> marsh ecosystems.</p>","PeriodicalId":35937,"journal":{"name":"环境科学","volume":"46 2","pages":"1203-1212"},"PeriodicalIF":0.0,"publicationDate":"2025-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143441944","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}