Search Results (404)

Agricultural non-point source (NPS) pollution is an important contributor to nitrogen enrichment in many northern Chinese watersheds. Using monthly water quality data collected at nine national monitoring sections along the main stem of the Liao River during 2021–2025, we estimated total nitrogen (TN) emissions from crop cultivation, livestock and poultry farming, and aquaculture using an emission coefficient method. We also used the maximum information coefficient (MIC) to examine nonlinear associations between monthly discharge and TN concentration, and described the spatial and temporal patterns of TN. TN concentrations were lower at the upstream inflow section than at the downstream estuarine section, a pattern consistent with additional inputs within Liaoning Province. The MIC analysis identified a lagged statistical association between terminal discharge and TN concentration; however, it does not establish a transport time or causal mechanism. TN concentrations declined in 2025 while pollution control measures were being implemented, although the observational record cannot attribute that decline to the measures. These results provide a basis for prioritizing monitoring and agricultural NPS control in the Liao River Basin. Full article

Agricultural nonpoint source pollution mainly causes lake eutrophication in China, largely affected by variations in crop distribution. To analyze the multiscale relationships between the long-term evolution of cropping patterns and lake water quality at the macro scale, this study analyzed nationwide datasets for 2000 and 2020 covering 420 relatively large lakes. We systematically examined the spatial restructuring of six major food and cash crops—wheat, rice, maize, soybean, peanut, and rapeseed—and evaluated their multiscale associations with lake total nitrogen (TN) and total phosphorus (TP) concentrations and how these associations changed over time. The results showed the following: (1) From 2000 to 2020, the spatial distributions of the six major crops underwent substantial restructuring. The dominant production areas of rice, wheat, and maize were maintained or further reinforced, whereas soybean, rapeseed, and peanut exhibited varying degrees of regional redistribution and localized concentration. (2) Lake water quality differed between the flood and non-flood seasons. TN exhibited pronounced seasonal differences between the two study periods, whereas temporal changes in TP were generally limited; both nutrients nevertheless showed marked regional heterogeneity among the five major lake regions. (3) The crop–water quality relationship exhibits significant scale dependence and crop-specific variations. The XGBoost model demonstrated a certain degree of out-of-field (OOF) predictive capability for both TN and TP, with OOF R² values of 0.448 and 0.447, respectively. For TN, the highest OOF R² values were observed in the 1000–2000 m buffer zone in both 2000 and 2020; the optimal prediction scale for TP shifted from 1000–2000 m in 2000 to 2000–5000 m in 2020. SHAP results showed that corn maintained a high and relatively stable predictive importance in the TN model, followed by wheat, peanuts, and rice; in the TP model, corn and rapeseed were the crop predictors with the highest relative SHAP importance. PDP results further indicate that there are generally nonlinear or non-monotonic relationships between different crop coverage proportions and TN and TP. (4) Pronounced spatial heterogeneity was observed across the five lake regions. The Eastern Plain Lake Region was characterized by associations involving multiple crops, whereas maize was the most prominent crop in the Northeast Plain and Mountain Lake Region. In the Inner Mongolia–Xinjiang Plateau Lake Region, maize predominated, with wheat and rapeseed also showing notable importance. In the Tibetan Plateau Lake Region, TN was associated with multiple crops, whereas TP was primarily related to maize and rapeseed. The Yunnan–Guizhou Plateau Lake Region exhibited particularly strong scale-dependent differences. This study provides a nationwide analytical framework for comparing the scale differences and regional variations in the statistical associations between the spatial distribution of crops and lake water quality at the specific crop level. The findings can provide a scientific basis for formulating differentiated agricultural nonpoint source pollution control strategies that are adapted to the evolving characteristics of crop planting structures. Full article

Improving cropland carbon performance while maintaining food security is central to China’s agricultural transition and climate goals This study examines low-carbon cropland use performance (PCLU) and its model-implied interprovincial association network across 31 Chinese provinces from 2010 to 2023. A global super-efficiency slacks-based measure model estimated PCLU by incorporating agricultural output, carbon emissions, nonpoint-source pollution, and crop sequestration; annual directed networks were constructed with a modified gravity model and analyzed using social network analysis, a temporal exponential random graph model (TERGM), and complementary quadratic-assignment analyses. Mean PCLU increased from 0.524 to 0.861, while the interquartile range widened from 0.146 to 0.310; network density declined before partially recovering as hierarchy increased, indicating improvement without provincial convergence and reconnection within a more differentiated multi-hub structure. Persistence (β = 4.510) and reciprocity (β = 2.376) dominated network evolution, whereas shared partners produced neither additional triadic closure nor expanding open chains; similarities in urbanization and planting structure favored ties, while rural-income differences reflected socioeconomic complementarity. External validation showed moderate overall correspondence with green-technology patent collaboration (mean annual QAP r = 0.335) but limited overlap among the strongest dyads. Overall, China’s low-carbon cropland transition combined rising but increasingly uneven performance with a path-dependent and selective interprovincial structure, providing an empirical basis for differentiated coordination based on provincial performance and network position. Full article

Advanced treatment of plant effluent (tailwater) is critical for mitigating agricultural non-point source pollution; however, plant–substrate synergy in vertical-flow constructed wetlands (VFCWs) remains poorly understood under subtropical conditions. This one-year pilot study evaluated the effects of substrate type (zeolite vs. gravel) and P. australis presence on nutrient removal, seasonal performance stability, and microbial community assembly in tailwater treatment. Methodologically, twelve VFCWs were operated across seasons, and their performance was assessed via water quality monitoring and high-throughput sequencing. The results indicate that all configurations consistently met stringent discharge standards. Planted treatments significantly outperformed unplanted controls in removing TN, COD, and TP (p < 0.05), while no significant difference emerged between zeolite- and gravel-planted systems, confirming vegetation’s dominance over substrate selection under low-concentration loads. Seasonal analysis revealed temperature-dependent TN removal (p < 0.01), whereas TP, COD, and NH₄⁺-N removal remained stable. Microbial analysis showed P. australis selectively enriched functional taxa driving N and organic matter mineralization despite a shared core microbiome at the genus level. Gravel-planted VFCWs exhibited superior long-term resilience compared to the transient sorption of zeolites. We considered that vegetation-driven biological pathways offer a resilient design for polishing nutrients in tailwater, showing potential for agricultural irrigation and nutrient interception. Full article

The Yellow River Basin is an important ecological security barrier and agricultural production area in China. Using panel data for nine sprovincial-level regions from 2010 to 2022, this study constructs a multidimensional development index of rural industrial integration and examines its association with regional environmental pollution. Regional pollution pressure is measured from total wastewater discharge, sulfur dioxide emissions, and general industrial solid-waste generation; the measure therefore captures broad regional pollution linked to agricultural and related industrial chains rather than agricultural non-point-source pollution alone. Two-way fixed-effects estimates show that higher integration scores are significantly associated with lower pollution levels. This association is statistically evident in the upper reaches, whereas the middle- and lower-reach estimates are not statistically significant and are interpreted as exploratory because each subsample contains only two provinces. Exploratory channel regressions suggest that agricultural technological progress, rural labor mobility, and agricultural industrial scale may help explain the observed association, but the regressions do not establish causal mediation. The findings indicate potential synergies between rural industrial integration and environmental governance, while also requiring caution regarding causal interpretation, composite-index boundaries, and small-sample regional comparisons. Full article

The hilly terrain at the western foot of the Wanda Mountains boasts intricate geological conditions, compounded by long-term mineral extraction and farming activities. The multi-sourced heavy metals stored within stream sediments create substantial obstacles to accurate source apportionment and targeted risk mitigation. In this work, stream sediment samples were collected across the study watershed to test concentrations of eight heavy metals: As, Cd, Cr, Ni, Cu, Pb, Hg and Zn. Pollution and ecological risk assessments were implemented via the pollution load index (PLI), geo-accumulation index (I_geo) and potential ecological risk index (RI). Kriging interpolation was utilized to visualize and interpret the spatial variation patterns of heavy metals. Combined correlation analysis, principal component analysis (PCA) and the Absolute Principal Component Scores–Multiple Linear Regression (APCS-MLR) receptor model were adopted to qualitatively and quantitatively distinguish pollution endmembers of heavy metals. The main results are as follows: Cr, Cd, Pb and As show significant enrichment, whereas Ni, Cu, Zn and Hg appear depleted; all measured heavy metals present strong spatial variability. Weathering of basic bedrocks governs the widespread high-value zones of Cr, Ni, Cu and Zn. Patchy enrichment of Pb, As and Cd is concentrated in river valley farmlands, with no continuous anomalous zones detected for Hg. The watershed as a whole suffers mild contamination and low potential ecological risk, with only sampling points surrounding mines and agricultural lands experiencing moderate-to-severe pollution and medium ecological hazards. Three source endmembers are identified in the region: a natural geogenic endmember (Cr, Ni, Co, etc.), a mixed mining-associated anthropogenic endmember (Zn, Hg, Cu, Cd), and an agricultural non-point endmember (Pb, As, Sb). Quantitative APCS-MLR calculations confirm that mining disturbances serve as the predominant anthropogenic input for Zn, Hg, Cu and Cd; agricultural practices dominate the accumulation of As and Pb; and geogenic contributions stay marginal for all elements. This study corroborates that regional lithology sets the natural geochemical baseline of heavy metals, while anthropogenic interferences function as the primary driver of localized pollution anomalies. The conclusions can deliver theoretical support for heavy metal pollution remediation in similar hilly watersheds throughout Northeast China. Full article

This study presents the first integrated multi-compartment assessment linking soil heavy- metal contamination and satellite-derived tropospheric air pollution in Lebanon’s Bekaa Valley. Six metals (Cd, Cr, Cu, Ni, Pb, Zn) were measured in 295 agricultural topsoils using DTPA extraction—which targets the labile, bioavailable pool most relevant to food-chain transfer in calcareous soils—and were compared with Sentinel-5P TROPOMI vertical columns of SO₂, NO₂ and HCHO extracted at point, 1000 m and 5000 m scales. Chromium was the dominant element, and composite pollution indices indicated overall good but transitional soil quality, with a majority of sites at warning level. Principal component analysis, spatial autocorrelation and land-use analysis converged on three plausible source groupings—predominantly geogenic (Cr, Ni), localized anthropogenic (Cd, Pb) and agricultural (Cu)—although, in the absence of isotopic or other direct source tracing, these assignments remain indicative rather than confirmed. Soil metals and atmospheric columns were largely uncorrelated (|r| < 0.3 for 17 of 18 pairs); this decoupling is consistent with the contrasting temporal integration and spatial support of the two compartments rather than with a single shared pathway. Multi-scale analysis supported a parsimonious dual-scale (point + 5000 m) sampling framework. The study offers a transferable assessment framework for other Mediterranean regions and underscores the need for locally calibrated, total-metal soil background values. Because these indices and threshold comparisons are computed from DTPA-extractable concentrations, they serve here as one-directional, bioavailability-based screening tools rather than regulatory determinations: an exceedance conservatively flags a site for confirmatory total-metal analysis, whereas a non-exceedance does not establish compliance. Full article

The Hetao Irrigation District in arid northwestern China presents a significant challenge in balancing agricultural intensification and water conservation, particularly in its terminal lake, Wuliangsu Lake. This study examined how changes in Land Use/Land Cover (LULC) and cropping structures influenced the lake’s water quality. By using remote sensing data for LULC classification and agricultural statistics for crop composition, we analyzed the spatio-temporal variation in LULC and cropping structure in the irrigation district and quantified the associated agricultural non-point source pollution loads (total nitrogen, total phosphorus, and chemical oxygen demand) entering the lake. A calibrated Environmental Fluid Dynamics Code model was applied to evaluate water quality responses to cropping structure optimization. Our findings revealed significant shifts in LULC and cropping structure during the study period, driven by agricultural intensification, ecological restoration policies, urbanization, market forces, and national food security strategies. Concurrently, agricultural non-point source pollution loads into the lake showed a steady declining trend from 2018 to 2023, with total nitrogen (TN) decreasing by 15%, total phosphorus (TP) by 16.9%, and chemical oxygen demand (COD) by 19.4%. Model simulations demonstrated that optimizing the cropping structure, specifically by reducing the area of high-fertilizer crops (sunflower) and expanding low-fertilizer crops (spring wheat) and forage crops for ecological purposes, could further improve lake water quality. Under the intensive adjustment scenario, the inflow loads of TN, TP, and COD decreased by 10%, 11.7%, and 10.9%, respectively, while the corresponding in-lake concentrations decreased by 22.1%, 19.8%, and 18.7%, respectively. TP exhibited the highest sensitivity to such adjustments. By linking cropping structure adjustments with hydrodynamic-water quality modeling, this study provides a quantitative framework for assessing water quality responses in arid irrigated systems, offering a scientific basis for balancing agricultural production and water ecosystem protection in the Hetao district and similar regions. Full article

Agricultural nonpoint-source phosphorus (NPS-P) losses threaten receiving waters, but regional control is complicated by differences in source intensity, erosion sensitivity, and hydrologic connectivity. This study jointly applied an improved export coefficient model (IECM), the Revised Universal Soil Loss Equation (RUSLE), Global and Local Moran statistics, and Getis-Ord Gi* analysis to six contrasting basins. The outputs were cross-interpreted without a formal composite index. Average annual soil erosion ranged from 1.96 to 18.47 t ha⁻¹ yr⁻¹, with very slight and slight erosion dominating all basins. Annual NPS-P export ranged from 2169.55 to 12,028.32 t yr⁻¹ (1.26–2.74 kg ha⁻¹ yr⁻¹), and cultivated land contributed 48.60–69.32% of modeled export. Under 999 random permutations, Global Moran’s I ranged from 0.615 to 0.834 (pseudo p = 0.001), and Gi* hot spots occupied 26.18–33.59% of valid cells. The basin-level perturbation analysis indicated greater ranking robustness for clearly high- and low-load basins than for intermediate basins, while the cultivated-land sensitivity analysis quantified the influence of the dominant coefficient. The framework supports regional screening, monitoring prioritization, and subsequent field verification rather than calibrated event-scale prediction. Full article

Agricultural green total factor productivity (AGTFP) is a key indicator for evaluating the level of green development in agriculture. However, conventional approaches to AGTFP measurement often treat intermediate agricultural production processes as a “black box”, overlooking internal system mechanisms and thus leading to biased identification of efficiency bottlenecks. To address this limitation, this study introduces an analysis using a network slack-based measure (NSBM) model to move beyond the traditional single “input–output” transmission framework. By integrating soil sample data from 2017 to 2024, the agricultural production process is decomposed into three sequential stages—material inputs, nutrient transformation, and crop production—to evaluate AGTFP in Baoding, China. The results reveal that AGTFP in Baoding remains at a relatively low level overall, although a steady upward trend is observed over time. Specifically, overall efficiency increased by 18.18%, while the efficiency of converting agricultural inputs into soil nutrients (the input subsystem) improved by 36.13%. The input subsystem serves as the primary driver of AGTFP improvement, with a marginal contribution coefficient of 0.61% to overall efficiency (p < 0.01). Although the efficiency of transforming soil nutrients into agricultural output (the output subsystem) remains relatively high, its growth potential is constrained by biological limits. It is highly sensitive to external factors such as topography and natural disasters. At present, the key bottleneck to enhancing regional AGTFP is the low efficiency with which external inputs are converted into soil nutrients. These findings suggest that policy priorities should shift from simple input reduction to process-oriented management, with an emphasis on improving the conversion efficiency of external inputs into effective soil nutrients, thereby facilitating agricultural green transformation while mitigating non-point source pollution. Based on existing research frameworks, this study supplements and refines the original analytical framework by incorporating soil data from the agricultural production process, providing new empirical evidence for uncovering the “black box” of agricultural production. Full article

Shallow aquifers in intensively managed alluvial plains worldwide are increasingly impacted by inorganic nitrogen, yet the simultaneous occurrence and interconversion of nitrate (NO₃⁻–N), nitrite (NO₂⁻–N) and ammonium (NH₄⁺–N) often confound source attribution when single indicators are used. Here, we present a transferable, process-linked framework for diagnosing “tri-nitrogen” (tri-N) pollution that integrates hydrogeochemical evolution, data-driven pattern discovery and receptor-model apportionment. We analyzed 409 shallow-groundwater samples from Shijiazhuang City (central North China Plain) for major ions and tri-N species, interpreted within Piper facies and salinization gradients, and then applied a Gaussian mixture model (GMM) to resolve multivariate hydrochemical–nitrogen end-members. Six clusters (I–VI) depict an interpretable progression from background Ca–HCO₃/Ca·Mg–HCO₃ waters to agricultural NO₃⁻–N enrichment under oxic conditions and a distinct NH₄⁺–N-rich point-source end-member under reducing conditions. An attention-based attribution model indicates that total tri-N, Na⁺, NO₃⁻–N, the NO₂⁻ fraction and SO₄²⁻ are the primary discriminators of cluster structure. Species-resolved positive matrix factorization (US EPA PMF 5.0) quantifies dominant controls, with agricultural leaching–nitrification explaining most NO₃⁻–N (Factor 6, 87.9%) and sewage/manure inputs dominating NH₄⁺–N (Factor 3, 95.3%), while NO₂⁻–N reflects mixed contributions consistent with redox-interface transitions. Beyond this case study, the combined GMM–interpretability–PMF workflow provides a general template for separating non-point versus point tri-N inputs and for prioritizing management actions in shallow aquifers where isotope or tracer data are limited. Full article

This study investigated the contamination characteristics, sources, and ecological risks of organochlorine pesticides (OCPs) in surface sediments from three plateau lakes in southwestern China (Qilu Lake, Dianchi Lake, and Yangzonghai Lake). Significant differences in OCP pollution levels were observed among the three lakes. Hexachlorocyclohexanes (HCHs) were identified as the dominant contaminants, reflecting historical technical HCH input and subsequent long-term aging, whereas dichlorodiphenyltrichloroethanes (DDTs) exhibited generally low concentrations and originated primarily from historical technical use, with predominantly aerobic degradation. Principal component analysis (PCA) revealed that agricultural non-point source pollution was the main contributor to OCP residues. Ecological risk assessment demonstrated that most OCPs posed low or negligible risk; however, γ-HCH (lindane) ubiquitously presented moderate risk across all lakes, with one site exceeding the high-risk threshold. Endrin derivatives and methoxychlor further elevated combined risks at specific sites. Notably, the unique hydrological characteristics of plateau lakes may enhance OCP retention and accumulation in sediments. These findings provide a scientific basis for ecological risk management and pollution control in plateau lakes. Full article

The present study aims to address critical research gaps in duckweed–microbe symbiotic systems specifically applied to high-load livestock and poultry breeding wastewater. These gaps include the insufficient development of well-characterized, multi-functional, complex microbial consortia adapted to complex livestock wastewater matrices, and the technical challenge of achieving simultaneous efficient wastewater purification and duckweed feed quality enhancement. This study is motivated by the pressing issue of agricultural non-point source pollution, which is caused by large-scale livestock and poultry breeding wastewater discharge, and the high external dependence of the feed industry on protein raw materials. The present study utilised Spirodela as the fundamental material, and a functionally complementary complex symbiotic bacterial consortium consisting of Bacillus subtilis, Bacillus tequilensis and Pseudomonas fluorescens was screened and constructed. An experiment was conducted over a 14-day period in which a range of inoculation ratios were systematically explored. The aim of this experiment was to ascertain the purification efficiency of the duckweed–bacteria symbiotic system on high-load livestock and poultry breeding wastewater. Furthermore, the experiment sought to determine the effect of this purification process on the feed value of duckweed. The results demonstrated that complex bacterial inoculation significantly enhanced wastewater purification efficiency. The final removal rate of ammonia nitrogen in all treatment groups exceeded 90% after 14 days, and the maximum removal rates of total nitrogen and total phosphorus reached 67.0% and 58.9%, respectively, thereby demonstrating superior purification performance in comparison to the control group. The inoculation ratio of 10:1 was identified as the optimal parameter for wastewater purification, while the 5:1 ratio was found to be the maximum for crude protein accumulation in duckweed. The maximum dry-based crude protein content recorded was 38.9% on day 14, representing an increase of 26.3% in comparison with the control group. The established duckweed–bacteria symbiotic system has the capacity to simultaneously achieve the efficient purification of livestock and poultry breeding wastewater and the high-value utilisation of duckweed. The optimal process parameters for a range of application scenarios have been determined. This study contributes to the theoretical framework of aquatic plant–microbe symbiotic remediation and provides technical support for the recycling of wastewater resources and the sustainable development of the livestock and poultry breeding industry. Full article

The sources of potentially toxic elements (PTEs) in the lower reaches of the Yellow River (LYR) remain poorly understood due to intensive human activities in this region. To elucidate the spatiotemporal distribution characteristics and sources of PTEs, water samples were collected from both mainstream and tributary sites during the dry season (DS) and flood season (FS). Concentrations of eight PTEs (Fe, Mn, Cu, Zn, Pb, As, Cr, and Hg) were determined. The single-factor pollution index, Nemerow comprehensive pollution index, statistical techniques, and the positive matrix factorization (PMF) receptor model were jointly employed to evaluate PTEs pollution levels and quantitatively apportion its sources. The results showed that PTEs concentrations in the mainstream were significantly higher than those in the tributaries, with Fe and Mn being the primary contaminants exceeding standards. During the DS, the mean concentrations of Fe and Mn were 1.33 mg/L and 0.34 mg/L, with exceedance rates of 100% and 84.2%, respectively. In contrast, both concentrations declined markedly in the FS (Fe: 0.27 mg/L; Mn: 0.112 mg/L). The PMF model identified three sources in the DS, with contribution rates of 42.1% (geogenic background and domestic sewage), 32.4% (industrial wastewater), and 25.5% (agricultural sources). In the FS, two sources were resolved, namely a mixture of non-point source pollution and domestic sewage (64.3%) and a mixture of geogenic background and industrial wastewater (35.7%). The pronounced increase in non-point source contribution during the FS highlights the role of rainfall runoff in driving pollutant input. This study provides a scientific basis for PTEs pollution control in the LYR. Full article

Rapid urbanization and industrialization have profoundly affected aquatic ecosystems in urban rivers, with phytoplankton taxa and functional group composition being particularly sensitive to environmental changes. Field surveys were conducted in the Nanming River, Guiyang, in October 2018 and July 2019, with 33 sampling sites evenly distributed across the upstream, midstream, and downstream reaches. The results revealed that: (1) The phytoplankton community comprised 6 phyla, 53 genera, and 61 species, dominated by Bacillariophyta, Chlorophyta, and Cyanobacteria. The community was classified into 20 functional groups, among which B, D, MP, P, and S1 were dominant and exhibited clear spatial heterogeneity along the longitudinal gradient. (2) Analysis of variance indicated that physicochemical parameters were the dominant factors explaining the variation in phytoplankton taxonomic and functional groups, with their independent contribution significantly higher than that of anthropogenic disturbance indicators and geographical factors. Redundancy analysis further identified NH₄-N, TP, and TN as key environmental factors. Spearman’s correlation analysis further indicated that human activities alter ambient environmental conditions, which are significantly correlated with dissolved oxygen and chlorophyll a levels, thereby driving the differentiation of phytoplankton niches. (3) Functional group succession followed a distinct spatial pattern: upstream areas were dominated by groups P, SN, and Y, reflecting agricultural non-point source inputs; midstream areas were dominated by groups W1, H1, and S1, characteristic of urban complex pollution; and downstream areas were dominated by groups C and X1, indicating cumulative nutrient loading. Collectively, this study elucidates the driving mechanisms of phytoplankton dynamics in karst urban rivers and provides a scientific foundation for water quality monitoring, eutrophication risk pre-warning, and aquatic ecological restoration. Full article