Soil Environmental Quality Research Articles

How does the biochar-supported sulfidized nanoscale zero-valent iron affect the soil environment and microorganisms while remediating cadmium contaminated paddy soil?

In previous studies, iron-based nanomaterials, especially biochar (BC)-supported sulfidized nanoscale zero-valent iron (S-nZVI/BC), have been widely used for the remediation of soil contaminants. However, its potential risks to the soil ecological environment are still unknown. This study aims to explore the effects of 3% added S-nZVI/BC on soil environment and microorganisms during the remediation of Cd contaminated yellow-brown soil of paddy field. The results showed that after 49 d of incubation, S-nZVI/BC significantly reduced physiologically based extraction test (PBET) extractable Cd concentration (P < 0.05), and increased the immobilization efficiency of Cd by 16.51% and 17.43% compared with S-nZVI and nZVI/BC alone, respectively. Meanwhile, the application of S-nZVI/BC significantly increased soil urease and sucrase activities by 0.153 and 0.446 times, respectively (P < 0.05), improving the soil environmental quality and promoting the soil nitrogen cycle and carbon cycle. The results from the analysis of the 16S rRNA genes indicated that S-nZVI/BC treatment had a minimal effect on the bacterial community and did not appreciably alter the species of the original dominant bacterial phylum. Importantly, compared to other iron-based nanomaterials, incorporating S-nZVI/BC significantly increased the soil organic carbon (OC) content and decreased the excessive release of iron (P < 0.05). This study also found a significant negative correlation between OC content and Fe(II) content (P < 0.05). It might originate from the reducing effect of Fe-reducing bacteria, which consumed OC to promote the reduction of Fe(III). Accompanying this process, the redistribution of Cd and Fe mineral phases in the soil as well as the generation of secondary Fe(II) minerals facilitated Cd immobilization. Overall, S-nZVI/BC could effectively reduce the bioavailability of Cd, increase soil nutrients and enzyme activities, with less toxic impacts on the soil microorganisms.

Đánh giá hiện trạng môi trường đất khu vực đất ngập nước xã Đồng Rui, huyện Tiên Yên, tỉnh Quảng Ninh

Wetland ecosystems play the most important role but are also vulnerable under economic evelopment activities in estuarine and coastal areas. The quality of the soil environment is an important parameter to assess human impacts on this ecosystem environment. In this study, 28 soil and sediment samples of different types of land use were collected and analyzed with physical indicators (mechanized action, pH, salinity), nutrient indicators (N total, P total, OC, Ca2+, Mg2+) to assess the current state of the soil environment in Dong Rui commune. The results showed a large difference in land indicator groups between 2 groups of land use types distributed inside and outside the levee. For the quality of soil environment in the group of types outside dikes such as river sediments and mangrove soils, the pH value is at a less acidic level, the composition is mainly sand, organic content, high exchange cations. For the group of land use types located inside the dike, the pH value is at the acidity level, the grain level composition is more balanced, the organic content and the ability to exchange cations is low. This difference shows the extent of human impact on these wetlands as well as their natural resilience, particularly in restored forest areas in abandoned shrimp lagoons. This is an important solution in the management and restoration of wetlands in Dong Rui commune.

Temporal and Spatial Variation of Toxic Metal Concentrations in Cultivated Soil in Jiaxing, Zhejiang Province, China: Characteristics and Mechanisms.

The toxic metal (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn) pollution in 250 agricultural soil samples representing the urban area of Jiaxing was studied to investigate the temporal and spatial variations. Compared to the early 1990s, the pollution level has increased. Industry and urbanization were the main factors causing toxic metal pollution on temporal variation, especially the use of feed containing toxic metals. The soil types and crop cultivation methods are the main factors causing toxic metal pollution on spatial variation. Although the single-factor pollution indices of all the toxic metals were within the safe limits, as per the National Soil Environmental Quality Standard (risk screening value), if the background values of soil elements in Jiaxing City are used as the standard, the pollution index of all the elements surveyed exceeds 1.0, reaching a level of mild pollution. The soil samples investigated were heavily contaminated with toxic metal compounds, and their levels increased over time. This situation poses potential ecological and health risks.

Heavy Metal Concentration Estimation for Different Farmland Soils Based on Projection Pursuit and LightGBM with Hyperspectral Images.

Heavy metal pollution in farmland soil threatens soil environmental quality. It is an important task to quickly grasp the status of heavy metal pollution in farmland soil in a region. Hyperspectral remote sensing technology has been widely used in soil heavy metal concentration monitoring. How to improve the accuracy and reliability of its estimation model is a hot topic. This study analyzed 440 soil samples from Sihe Town and the surrounding agricultural areas in Yushu City, Jilin Province. Considering the differences between different types of soils, a local regression model of heavy metal concentrations (As and Cu) was established based on projection pursuit (PP) and light gradient boosting machine (LightGBM) algorithms. Based on the estimations, a spatial distribution map of soil heavy metals in the region was drawn. The findings of this study showed that considering the differences between different soils to construct a local regression estimation model of soil heavy metal concentration improved the estimation accuracy. Specifically, the relative percent difference (RPD) of As and Cu element estimations in black soil increased the most, by 0.30 and 0.26, respectively. The regional spatial distribution map of heavy metal concentration derived from local regression showed high spatial variability. The number of characteristic bands screened by the PP method accounted for 10-13% of the total spectral bands, effectively reducing the model complexity. Compared with the traditional machine model, the LightGBM model showed better estimation ability, and the highest determination coefficients (R2) of different soil validation sets reached 0.73 (As) and 0.75 (Cu), respectively. In this study, the constructed PP-LightGBM estimation model takes into account the differences in soil types, which effectively improves the accuracy and reliability of hyperspectral image estimation of soil heavy metal concentration and provides a reference for drawing large-scale spatial distributions of heavy metals from hyperspectral images and mastering soil environmental quality.

Assessment of Heavy Metal Contamination and Ecological Risk in Soil within the Zheng–Bian–Luo Urban Agglomeration

As urbanization accelerates, the contamination of urban soil and the consequent health implications stemming from urban expansion are increasingly salient. In recent years, a plethora of cities and regions nationwide have embarked on rigorous soil geological surveys with a focus on environmental quality, yielding invaluable foundational data. This research aims to develop scientifically robust and rational land-use planning strategies while assessing the levels of heavy metal pollution and associated risks. The urban agglomeration encompassing Zhengzhou, Luoyang, and Kaifeng (referred to as Zheng–Bian–Luo Urban Agglomeration) in Henan Province was designated as the study area. Leveraging the Nemerow comprehensive index method alongside the Hakanson potential ecological risk assessment method, this study delved into the pollution levels and potential ecological ramifications of nine heavy metals, namely Cr, Mn, Ni, Cu, Zn, As, Cd, Pb, and Co. Research indicates that the hierarchy of individual potential ecological risks ranges from most to least significant as follows: Cd &gt; Pb &gt; Cr &gt; Ni &gt; Cu &gt; Zn &gt; As &gt; Mn &gt; Co. The concentrations of Cd in both Zhengzhou and Kaifeng surpassed the established background levels. Furthermore, the mean single-factor pollution index values for the heavy metals Cd and Zn exceeded 1, signifying a state of minor pollution. The Nemerow comprehensive index P of Cd and Zn is between 1 &lt; Pcomp ≤ 2, which is considered mild pollution. The comprehensive P values of the other seven metal elements are all less than 0.7, reaching a clean (alert) level. Predominantly, the primary potential risk factor in the superficial soil of the Zheng–Bian–Luo urban agglomeration is Cd, while the ecological risk implications associated with other heavy metal elements are comparatively minimal. The soil environmental quality within the designated study area remains secure, although certain localized areas pose potential risks of heavy metal pollution. A comprehensive assessment of the current state of soil heavy metal pollution is essential to establish a theoretical foundation and provide technical support for soil environmental protection, pollution mitigation, and sustainable utilization.

Earthworms improve the rhizosphere micro-environment to mitigate the toxicity of microplastics to tomato (Solanum lycopersicum)

Microplastics (MPs) are widespread in agricultural soil, potentially threatening soil environmental quality and plant growth. However, toxicological research on MPs has mainly been limited to individual components (such as plants, microbes, and animals), without considering their interactions. Here, we examined earthworm-mediated effects on tomato growth and the rhizosphere micro-environment under MPs contamination. Earthworms (Eisenia fetida) mitigated the growth-inhibiting effect of MPs on tomato plant. Particularly, when exposed to environmentally relevant concentrations (ERC, 0.02% w/w) of MPs, the addition of earthworms significantly (p < 0.05) increased shoot and root dry weight by 12–13% and 13–14%, respectively. MPs significantly reduced (p < 0.05) soil ammonium (NH4+-N) (0.55–0.69 mg/kg), nitrate nitrogen (NO3−-N) (7.02–8.65 mg/kg) contents, and N cycle related enzyme activities (33.47–42.39 μg/h/g) by 37.7–50.9%, 22.6–37.2%, and 34.2–48.0%, respectively, while earthworms significantly enhanced (p < 0.05) inorganic N mineralization and bioavailability. Furthermore, earthworms increased bacterial network complexity, thereby enhancing the robustness of the bacterial system to resist soil MPs stress. Meanwhile, partial least squares modelling showed that earthworms significantly influenced (p < 0.01) soil nutrients, which in turn significantly affected (p < 0.01) plant growth. Therefore, the comprehensive consideration of soil ecological composition is important for assessing MPs ecological risk.

Review of soil environment quality in India near coal mining regions: current and future predictions.

Production and utilization of coal are one of the primary routes of accumulation of Toxic Elements (TEs) in the soil. The exploration of trends in the accumulation of TEs is essential to establishing a soil pollution strategy, implementing cost-effective remediation, and early warnings of ecological risks. This study provides a comprehensive review of soil concentrations and future accumulation trends of various TEs (Cr, Ni, Pb, Co, Cu, Cd, Zn, Fe, Mn, and As) in Indian coal mines. The findings revealed that average concentrations of Cr, Mn, Ni, Cu, Zn, Pb, and Co surpass India's natural background soil levels by factors of 2, 4.05, 5.32, 1.77, 9.6, and 6.15, respectively. Geo-accumulation index values revealed that 27.3%, 14.3%, and 7.7% of coal mines are heavily polluted by Ni, Co, and Cu, respectively. Also, the Potential Ecological Risk Index indicates that Cd and Ni are primary contaminants in coal mines. Besides, the health risk assessment reveals oral ingestion as the main exposure route for soil TMs. Children exhibit a higher hazard index than adults, with Pb and Cr being major contributors to their non-carcinogenic risk. In addition, carcinogenic risks exist for females and children, with Cr and Cu as primary contributors. Multivariate statistical analysis revealed that TEs (except Cd) accumulated in the soil from anthropogenic sources. The assessment of future accumulation trends in soil TE concentrations reveals dynamic increases that significantly impact both the ecology and humans at elevated levels. This study signifies a substantial improvement in soil quality and risk management in mining regions.

Chemical Technology and Development Trend of Contaminated Land Remediation

In recent years, the rapid development of industry and agriculture in China has led to the destruction of soil environmental quality caused by pesticides, heavy metals and other pollutants entering the soil, and the decline of crop yield and quality. Therefore, soil pollution remediation is urgent, and it is urgent to explore the remediation technologies of polluted land with good remediation effect, low cost and popularization. This paper summarizes the relevant technologies in the literature, expounds several practical measures of chemical remediation technology of polluted land in detail, and discusses the development trend of contaminated land remediation technology in the future, in order to provide theoretical support for promoting the remediation technology of polluted land in China.

The Distribution Characteristics and Risk Assessments of Organochlorine Pesticides in the Sediments of Sanshan Lake, China

ABSTRACT Situated in the middle reaches of the Yangtze River, Sanshan Lake represents a typical rural-urban junction lake. In May 2019, sediment core samples were gathered from five distinct sites within the lake to assess contamination levels and potential health hazards stemming from organochlorine pesticides (OCPs). The OCPs scrutinized included p,p’-DDE, α-HCH, γ-HCH, β-HCH, and δ-HCH, with concentrations of ∑DDTs and ∑HCHs ranging from 0.03 to 1.49 mg/kg and from 0.03 to 1.42 mg/kg, respectively. Average DDT and HCH residues stood at 0.04 ± 0.03 and 0.51 ± 0.41 mg/kg, respectively. This study unveiled substantial OCP contamination in Sanshan Lake, notably with remarkably elevated HCH residue levels compared to other analyzed compounds. The predominant OCP detected was β-HCH, prevalent across all samples. Moreover, the average HCH residue concentrations were an order of magnitude higher than those found in soils of the United States and Italy. At some sampling points, DDT residue levels surpassed both the ecological screening benchmark for soil DDT established by the U.S. Environmental Protection Agency (0.0025 mg/kg) and China’s primary standard as per soil environmental quality regulations (GB15618–2008, 0.05 mg/kg). Source analysis indicated that historical agricultural practices primarily contributed to DDT contamination, while technical blends accounted for HCH pollution. Carcinogenic risk assessments conducted on HCH exposure through ingestion, inhalation, and dermal contact revealed higher non-carcinogenic risks for children, with α-HCH posing the most significant carcinogenic risk among the various homologues studied. Conversely, the associated carcinogenic and non-carcinogenic risks linked with DDT residue exposure were minimal or negligible.

Life-like evolutionary tree of regional soil environmental quality: An innovative theory and method

Life-like evolutionary tree of regional soil environmental quality: An innovative theory and method

Evaluation and Source Apportionment on Potentially Toxic Elements Pollution of Agricultural Soil in Mango Planting Areas in Panzhihua City, China

ABSTRACT Heavy metal pollution in agricultural soil has a wide range of sources and an enormous scope of influence, bringing about severe environmental risk. In this study, we used Pearson correlation analysis, combined with principal component and cluster analysis (PCA/CA) to comprehensively analyze the sources of soil heavy metal contamination in a mango plantation area in Panzhihua City. We performed a spatial distribution of heavy metal contamination levels via ArcGIS for single factor and Nemerow Contamination Index. The results showed that PTEs exceeded background values of soil pollution in Sichuan Province. The enrichment of Cr, Ni and Zn were caused by the development of local industry. Cu is mainly from atmospheric dust. Various pollution sources controlled the accumulation of Cd, whereas that of As and Pb were related to agricultural activities and transportation. The spatial distribution of the pollution indices indicated that the soil in the study area was mild to severe pollution with compound PTEs. Chemical speciation analysis showed that the ecological risk of PTEs enrichment in the study area was slight. This study highlights the geographic distribution of heavy metal contamination levels and source resolution, providing targeting for local regulatory authorities to improve soil environmental quality.

Geostatistical modelling of physico-chemical properties of soils impacted by artisanal gold mining and farming: implications for soil environmental quality assessment

Geostatistical modelling of physico-chemical properties of soils impacted by artisanal gold mining and farming: implications for soil environmental quality assessment

Ensemble intelligence algorithms and soil environmental quality to model economic quantity of land resource allocation and spatial inequality

With the increasing concern on soil pollution in context of land market reform, it’s an emerging topic to discuss whether soil pollution can cause land economic value substantially depreciated at geospatial scale. This study proposed a data science approach by synthesizing machine learning and deep learning algorithms to establish the land economic equivalent model (LEEM) with best prediction ability. The results indicated that Light Gradient Boosting Machine (LightGBM) and Random Forest (RF) performed well in estimating residential/commercial and industrial land value, respectively. Spatial variation of soil environment quality indeed largely affected economic productivity of residential/commercial land with contribution of 13.82%. For industrial land, population density was strongly related to the land price (11.77%), of which importance score was much higher than other 10 variables except distance to center business district (CBD, 28.75%) and transaction time (28.61%). Another important finding was that soil protection measures could generate extra benefits equivalent with a mean of 22.46% and 28.92% for residential/commercial and industrial land value in current status, respectively, and high-value areas could also be predicted for effective decisions on land allocation and trading. In terms of sustainable land management, the regression tree-based LEEM is an effective tool in assisting decision makers with urban land reclamation, planning and pricing.

Effects of Different Mulching Practices on Soil Environment and Fruit Quality in Peach Orchards

Effects of Different Mulching Practices on Soil Environment and Fruit Quality in Peach Orchards

Traceability Analysis and Environmental Quality Assessment of Soil Heavy Metal Pollution in West Hunan Province

In order to explore the status of soil heavy metal pollution and environmental quality in west Hunan, relevant areas of Phoenix County were selected as the study area. Using data from 440 soil samples collected in the study area from June to August 2022, the pH value of the soil and contents of eight heavy metal elements, namely, As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, were analyzed. The PMF model was used for traceability analysis and geochemical evaluation of soil environmental quality. The results showed that the average values of soil heavy metals ω(Zn), ω(Cr), ω(Pb), ω(Ni), ω(Cu), ω(As), ω(Cd), and ω(Hg) were 81.02, 64.67, 31.63, 29.27, 25.52, 9.93, 0.28, and 0.13 mg·kg-1, respectively. The soil in the study area was mainly weakly acidic, and the contents of the Cd and Hg elements were relatively high compared to the national soil background values and were highly variable. The contents of the Hg and Cd elements in forest land were higher than that in other land uses. The PMF model results showed that the contribution rates of heavy metal pollution sources in the study area were mining sources (37.4%), atmospheric sedimentation sources (7.7%), natural sources (41.1%), and agricultural activity sources (13.8%) and provided suggestions on pollution control measures according to the spatial distribution of the four types of pollution sources. Through the comprehensive assessment of soil environmental geochemistry, the study area was divided into three types of plots, namely, non-risk areas (94.27 km2), accounting for 76.38%; risk-controllable areas (27.45 km2), accounting for 22.24%; and high-risk areas (1.7 km2), accounting for 1.38%. This study provided data support for the prevention and control measures of land pollution in the research area, as well as the delineation of the prevention and control scope.

Characteristics and Identification Priority Source of Heavy Metals Pollution in Farmland Soils in the Yellow River Basin

Assessments of the soil environmental quality of farmland and pollution source apportionment are the foundation for ensuring national food security and agricultural sustainable development, as well as an important prerequisite for the pursuit to keep our lands clean. This study evaluated the characteristics of heavy metal pollution in farmland soils in the Yellow River Basin from 2000 to 2023, based on the data of heavy metal contents including As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn, using the geo-accumulation index method. Source apportionment was conducted by employing a positive matrix factorization (PMF) model. The probabilistic health risks were evaluated by coupling Monte Carlo simulation with a human health risk assessment model, and priority pollution sources and elements were identified. The results showed that:① the average content of all heavy metals in farmland soils within the study area was lower than the screening values specified in the soil environment quality risk control standard for soil contamination of agriculture land (GB 15618-2018) (pH>7.5). However, the contents of Cd, As, and Zn in the samples exceeded their screening values, with percentages of 21.69%, 5.56%, and 1.23%, respectively, with Cd having the highest rate of exceedance. ② Hg and Cd were moderately polluted, Cu and Pb were slightly polluted, and the other elements were not polluted. ③ The main sources of heavy metals in farmland soil were traffic-industrial sources, natural-agricultural sources, industrial-natural sources, and agricultural-industrial sources, with contribution rates of 37.04%, 26.69%, 21.72%, and 14.55%, respectively. ④ Heavy metals in farmland soil posed carcinogenic health risks to adults and children but did not have non-carcinogenic risks; As and Cd were priority control elements for human health risks, and industrial-natural sources and agricultural-industrial sources were priority control sources in the study area.

Harnessing the potential of sugarcane-based liquid byproducts—molasses and spentwash (vinasse) for enhanced soil health and environmental quality. A systematic review

Farming practices reliant solely on synthetic agrochemicals face unreliability in the current era marked by unpredictable climate changes and rapid soil health deterioration. Consequently, a shift towards sustainable approaches is imperative to ensure both food security and environmental quality. Molasses and vinasse, abundant organic liquid by-products from sugar processing and distillery industries respectively, have historically served as soil conditioners and biofertilizers. Despite their potential, their effectiveness as organic amendments remain relatively unknown globally. In response, we conducted a systematic literature review to unveil the benefits of molasses and vinasse as organic amendments. Our findings reveal that these by-products consist of both inorganic and organic compounds that enhance soil and aquatic ecosystem performance. These compounds include essential plant nutrients as mineral elements and organic matter, contributing to improved soil physico-chemical and biological properties. Notably, the application of molasses and vinasse in crop production has demonstrated superiority over chemical fertilizers, particularly when combined with other inorganic amendments. Molasses and vinasse have been reported to significantly increase yield in several crops including sugarcane (Saccharum officinarum), tomatoes (Solanum lycopersicum), soybean (Glycine max), maize (Zea mays) and rice (Oryza sativa). Strategic utilization of vinasse has the potential to enhance environmental quality by reducing soil heavy metal loads and mitigating negative impacts associated with synthetic fertilizers. However, it is crucial to note that irregular disposal or misuse of these by-products can result in detrimental effects on the environment and human health. To encourage sustainable utilization on a global scale, it is essential to establish appropriate dosages, raise awareness among farmers and stakeholders regarding judicious use, and develop effective methods for handling and application of molasses and vinasse. This approach ensures cost-effective and environmentally friendly organic amendments, fostering a harmonious balance between agricutural productivity and ecological well-being.

Distribution, Source, and Ecological Risk of Heavy Metals in Sewage Irrigation of Taiyuan, Shanxi Province, China.

The pollution of agricultural soil by heavy metals is a significant environmental issue that has a serious impact on human health and food security. This study focused on investigating the presence of heavy metal pollution in sewage-irrigated soils in Taiyuan city. A total of 110 soil samples were analyzed for the presence of As, Hg, Cd, Pb, Cr, Cu and Zn. The results showed that the concentrations of these metals ranged from 0.06 to 26.74 mg/kg for As, 0.00 to 0.84 mg/kg for Hg, 0.03 to 0.69 mg/kg for Cd, 44.32 to 100.09 mg/kg for Pb, 9.85 to 42.19 mg/kg for Cr, 13.38 to 53.72 mg/kg for Cu, and 42.77 to 145.47 mg/kg for Zn. The average concentrations of these metals were found to be below the risk values specified in the "Soil environmental quality (GB15618-2018)", except for As and Cd in three sampling points in Xiaodian District. The heavy metal pollution in these areas can be attributed to various sources, such as industrial activities, the use of fertilizers and pesticides, and the irrigation process. According to the geo-accumulation index, the agricultural soil in the Taiyuan irrigation area was found to be uncontaminated by Zn, Cr, Cu, and As, and lightly contaminated by Cd, Hg, and Pb. The Nemerow Pollution Index indicated that the soil at all sampling points exhibited a slight level of pollution. Moreover, the ecological risk assessment indicated that all heavy metals posed a slight level of pollution. The findings of this study provide a scientific basis for the development of effective policies and measures for soil environmental protection and pollution control.

Spatial Analysis Using Geographically Weighted Ordinary Logistic Regression (GWOLR) Method for Prediction of Particle-Size Fraction in Soil Surface

Spatial analysis is a method used to understand the spatial variation of geospatial data. In this study, the Geographically Weighted Ordinary Logistic Regression (GWOLR) method was used in spatial analysis to predict the particle size fraction of the surface soil. The particle size fraction of the surface soil is an important parameter in determining soil productivity and environmental quality. However, the particle size fraction in surface soils can vary spatially and is influenced by geographical factors such as elevation, rainfall, and soil texture. This study will be carried out by collecting particle size fraction data and geospatial data at randomly selected locations. Accurate modelling of soil texture is necessary because it‘s a crucial factor in determining how soil management will go. However, because soil texture is a compositional data set, it is one of the soil attributes that is more challenging to model. The challenge presented by this compositional data set is the imposition of constant quantities, specifically the requirement that the total of the fractions of clay, silt, and sand be 100%. Topographical variability can be derived from DEM data, making it an independent variable or predictor for soil texture prediction. The data will then be analyzed using the GWOLR method to predict the particle size fraction at locations that have not been observed before. The resulting prediction model will then be evaluated using cross-validation to check the accuracy of the model. This study will provide benefits for land management and natural resource management and can improve understanding of the spatial variation of particle size fractions in surface soils and the spatial and geographical factors that influence them. The GWOLR model for predicting particle size fractions in surface soils was carried out with a fixed bi-square weight and a bandwidth of 0.28895. The GWOLR model classification accuracy value is 94 percent, this shows that the GWOLR model for predicting soil particle size is more suitable than the ordinal logistic regression model with a classification accuracy of 90 percent. The aims of this study are to: (1) Establish a soil texture prediction model using the GWOLR method; and (2) Test the reliability of the model in predicting surface soil texture.

Leguminous green manure intercropping changes the soil microbial community and increases soil nutrients and key quality components of tea leaves.

Intercropping, a green and sustainable planting pattern, has demonstrated positive effects on plant growth and the soil environment. However, there is currently little research on the influence of intercropping leguminous plants and using them as green manure on the soil environment and tea quality. During the profuse flowering period of Chinese milkvetch, the contents of tea amino acids and soluble sugar in intercropping tea plants with soybean increased by 6.89 and 54.58%. Moreover, there was 27.42% increase in soil ammonium nitrogen and 21.63% increase in available nitrogen. When Chinese milkvetch was returned to soil for 1month during its profuse flowering period, the soybean and Chinese milkvetch as green manure enhanced tea amino acids and soluble sugar by 9.11 and 33.96%, and soil ammonium nitrogen, nitrate nitrogen and available nitrogen increased by 25.04, 77.84, and 48.90%. Intercropping systems also have positive effects on tea quality components, soil fertility, and soil microbial communities during the profuse flowering period of soybeans and when soybeans with this period were returned to the field for 1month. Furthermore, the soil fertility index was significantly increased, especially in the intercropping system of tea-soybean-Chinese milkvetch. The soil bacterial community complexity and fungal community interactions were significantly increased. Soil pH, nitrate nitrogen, and available phosphorus were found to be crucial influencing factors on soil microbial communities, specifically bacterial communities. These results highlight the significance of optimizing intercropping systems to improve the soil environment and tea quality components. They also provide a theoretical foundation for promoting the sustainable development of tea plantations.