Agricultural Non-point Source Research Articles

Impact of new maize variety adoption on yield and fertilizer input in China: Implications for sustainable food and agriculture

CONTEXTCrop variety adoption is considered as one of the main strategies for farmers to enhance productivity under stress brought by the climate change, with less environment impacts. It holds an upstream position in the whole life cycle of agricultural clean production, compared to the field management and agricultural non-point source pollution treatment. OBJECTIVEThis paper aims to (i) assess the impact of new maize variety adoption on maize yield and fertilizer input; (ii) analyze the main determinants of farmers' new maize variety choice in the context of climate change, and (iii) identify the heterogeneity of small-scale and large-scale farmers in maize variety choice and its impacts. METHODSBased on plot-level data collected from three major grain producing provinces in China, we employ a treatment effects model to correct the potential bias resulting from the farmers' self-selection and estimate the direct impacts of farmers' new maize variety adoption and the main determinants of such adoption. RESULTS AND CONCLUSIONSThe empirical results indicate that the adoption of new maize varieties significantly increases maize yield by 9.4% but fertilizer use by 16.6 kg/mu (1 mu = 1/15 ha) as well, and this trade-off between economic impacts and environmental impacts is more pronounced among small-scale farmers. However, in the face of natural disasters, adopting new maize varieties results in a significant reduction in yield losses by 1.4% and a decrease in fertilizer input for natural disaster management by 2.45 kg/mu, as compared to the adoption of old varieties. What's more, our findings suggest that a higher frequency of pest and disease disasters significantly increases the probability of new maize variety adoption by farmers, while a higher frequency of climate disasters significantly decreases the probability. SIGNIFICANCEThe estimated impacts of new maize varieties point out the need of synergistically optimized resistance and nutrient use efficiency for crop breeding, which have important policy implications for sustainable food and agriculture. Also, the significant factor analysis contributes to the proposal of feasible ways to promote the farmers' adoption behavior.

Navigating agricultural nonpoint source pollution governance: A social network analysis of best management practices in central Pennsylvania.

The Chesapeake Bay watershed is representative of governance challenges relating to agricultural nonpoint source pollution and, more generally, of sustainable resources governance in complex multi-actor settings. We assess information flows around Best Management Practices (BMPs) undertaken by dairy farmers in central Pennsylvania, a subregion of the watershed. We apply a mixed-method approach, combining Social Network Analysis, the analysis of BMP-messaging (i.e. information source, flow, and their influences), and qualitative content analysis of stakeholders' interviews. Key strategic actors were identified through network centrality measures such as degree of node, betweenness centrality, and clustering coefficient. The perceived influence/credibility (by farmers) of BMP-messages and their source, allowed for the identification of strategic entry points for BMP-messages diffusion. Finally, the inductive coding process of stakeholders' interviews revealed major hindrances and opportunities for BMPs adoption. We demonstrate how improved targeting of policy interventions for BMPs uptake may be achieved, by better distributing entry-points across stakeholders. Our results reveal governance gaps and opportunities, on which we draw to provide insights for better tailored policy interventions. We propose strategies to optimize the coverage of policy mixes and the dissemination of BMP-messages by building on network diversity and actors' complementarities, and by targeting intervention towards specific BMPs and actors. We suggest that (i) conservation incentives could target supply chain actors as conservation intermediaries; (ii) compliance-control of manure management planning could be conducted by accredited private certifiers; (iii) policy should focus on incentivizing inter-farmers interaction (e.g. farmers' mobility, training, knowledge-exchange, and engagement in multi-stakeholders collaboration) via financial or non-pecuniary compensation; (iv) collective incentives could help better coordinate conservation efforts at the landscape or (sub-)watershed scale; (v) all relevant stakeholders (including farmers) should be concerted and included in the discussion, proposition, co-design and decision process of policy, in order to take their respective interests and responsibilities into account.

Study of Steroid Estrogen Loss in Soil after the Application of Composted Manure as a Fertilizer

Steroid estrogens (SEs) play a significant role as endocrine-disrupting substances, and one of their major sources is animal manure. However, there is limited information available regarding the loss of SEs in farmland soil after the application of commercial composted animal manure or fertilizers. To address this gap, our study aimed to simulate rainfall and flood irrigation scenarios and investigate the loss characteristics of SEs, as well as Chemical Oxygen Demand (COD), Total Nitrogen (TN), and Total Phosphorus (TP) in runoff from soil–manure mixtures. The results demonstrated that the loss concentrations of SEs (73.1 ng/L of the mean E2β active equivalent factor) presented a potential environmental risk. Additionally, substituting composted manure with commercial organic fertilizers lead to a significant reduction in TP (maximum 56%) and TN (maximum 24%) loss. Consequently, the application of commercial organic fertilizers offers considerable advantages in maintaining nitrogen and phosphorus fertilization efficiency while controlling SEs loss. Furthermore, our study explored the synergistic pollution mechanism among these pollutants and observed significant correlations between SEs and TN, TP, and COD loss concentrations, indicating the simultaneous occurrence and migration of these pollutants in agricultural non-point source pollution. These results provide valuable insights into the environmental risk associated with SEs from agricultural non-point sources.

Classification of Pollution Sources and Their Contributions to Surface Water Quality Using APCS-MLR and PMF Model in a Drinking Water Source Area in Southeastern China

Identifying the potential pollution sources of surface water pollutants is essential for the management and protection of regional water environments in drinking water source areas. In this study, absolute principal component score-multiple linear regression (APCS-MLR) and positive matrix factorization (PMF) models were applied to assess water quality and identify the potential pollution sources affecting the surface water quality of Xin’an River Basin. For this purpose, a 10-year (2011–2020) dataset of eight water quality indicators (including pH, EC, DO, COD, NH3-N, TN, TP, and FC) covering eight monitoring stations and 7248 monthly observations was used. The results indicated that Pukou section had the worst water quality among the eight monitoring stations, and TN was the most serious water quality index. Both the APCS-MLR and PMF models identified agricultural nonpoint source pollution, urban nonpoint source pollution and rural domestic pollution, and meteorological factors. The sum of these three sources was very close, accounting for 60% and 58%, respectively. The APCS-MLR results demonstrated that for EC, COD, and NH3-N, the major pollution sources were urban nonpoint sources and rural domestic pollution. The major contamination source of TN was agricultural nonpoint source pollution (30.4%). Meanwhile, the major pollution sources of pH, DO, TP, and FC were unidentified factors. The PMF model identified five potential sources, and pH and DO were affected by meteorological factors. NH3-N and TP were influenced mainly by agricultural nonpoint source pollution. Atmospheric deposition was the major pollution source (87.9%) of TN. FC was mostly derived from livestock and poultry breeding (88.3%). EC and COD were mostly affected by urban nonpoint sources and rural domestic pollution. Therefore, receptor models can help managers identify the major sources of pollution in watersheds, but the major factors affecting different pollutants need to be supplemented by other methods.

Effects of Pesticides Use on Pesticides Residues and Its Environmental Risk Assessment in Xingkai Lake（China）

Xingkai Lake, located in Heilongjiang Province, is an important fishery and agricultural base and is seriously polluted by agricultural non-point sources. To clarify the residual status of many pesticides in the surface water of Xingkai Lake, 27 types of pesticides, herbicides, and their degradation products were analyzed in rice paddy, drainage, and surface water around Xingkai Lake (China) during the rice heading and maturity periods. The results showed that all 27 types of pesticides, herbicides, and their degradation products were detected during the rice heading period, and the total concentration ranged from 247.97 to 6 094.49 ng·L-1. Additionally, 25 species were detected during the rice maturity period, and the total concentration ranged from 485.36 to 796.23 ng·L-1. In comparison, more pesticides, herbicides, and derived degradation products were detected during the heading period, and their total concentration was higher as well. During the rice heading period, atrazine, simetryn, and paclobutrazol were the main detected pesticides, atrazine and isoprothiolane were the main pesticides detected during the maturity period. The distribution characteristics of pesticides and herbicides in the surface water around Xingkai Lake (China) was similar to that in drainage, so they were probably imported from the drainage and rice paddy. The average risk quotient (RQ) values of atrazine, simetryn, prometryn, butachlor, isoprothiolane, and oxadiazon were higher than 0.1 in drainage and Xingkai Lake (China), which showed a potential risk to aquatic organisms.

Big Data Analysis: The Impact of Agricultural Non-point Source Pollution on Household Decision-making

Big Data Analysis: The Impact of Agricultural Non-point Source Pollution on Household Decision-making

Sponge iron-coupled biochar solution can achieve the synergistic augmentation of carbon sequestration, carbon sink capacity, and denitrification in ecological ditches

Carbon dioxide (CO2) is a more powerful greenhouse gas due to its enhanced instantaneous radiative forcing. Since agricultural ecological ditches (eco-ditches) controlling agricultural non-point source pollution are potential CO2 hotspots, carbon capture technologies must be deployed immediately to sequester carbon and combat climate change. Zero-waste biochar, a negative-carbon technology, remains contentious regarding C sequestration. Iron (Fe) enhances long-term organic carbon (OC) preservation, but the cascading effects of Fe-biochar interactions on the promotion of C accumulation are unclear in eco-ditches. In this paper, we fill these research gaps and employ sponge iron (s-ZVI) and biochar coupling (Fe-C) to enhance the iron gate C protection in eco-ditches. The results reveal that Myriophyllum aquaticum(M.A.)-derived biochar prepared by low-temperature pyrolysis (Biochar_M.A.) enjoys the highest FI, the lowest SUVA254 and SUVA280 and moderate dissolution stability. The coupling of s-ZVI and environmentally compatible Biochar_M.A. achieve a triple benefit situation of C sequestration, C sink, and pollutant removal. Overall carbon gain is jointly determined by abiotic controls and biotic controls. The carbon burial effects of biochar-amended eco-ditches are mainly controlled by the trade-offs between Fe-bound OC mineralization via the biochar-induced prime effect and preservation of OC derived from microbial biomass. The unique Fe-C boosts the rusty sink and yields a negative priming as a result of the dominance of Fe-OC. The upregulated β-glucosidase activity and new-formed Fe-OC indirectly and directly contribute to overall C gain in Fe-C-filled eco-ditches, respectively. These findings provide novel insights into the coupled biotic-abiotic contribution mechanisms underlying the iron gate and reverse enzyme latch phenomenon and advance more robust and prospective theoretical knowledge of C dynamics that are not restricted to eco-ditches, soil, constructed wetlands C storage.

Research on a Biofilter for a Typical Application Scenario in China: Treatment of Pesticide Residue Wastewater in Orchards

To reduce pesticide pollution and promote sustainable agricultural development in China, we designed a pilot-scale biofilter system to treat residual imidacloprid wastewater in an orchard. The biofilter system demonstrated a high rate of removal of imidacloprid from the biodegradation wastewater, with removal rates from the outlet exceeding 99% at different concentrations of pesticides. Among environmental factors, imidacloprid concentration at the inlet and biomixture significantly affected the activity of imidacloprid-degrading bacteria. The dominant microbial communities during the stable operation of the biofilter system included Firmicutes, Actinobacteria, Proteobacteria, and Bacteroidetes at the phylum level and Bacillus, Methylobacter, and unclassified_f__Microbacteriaceae at the genus level. In future initiatives to improve biofilter performance and applicability, increasing attention should be paid to the dominant microbial communities, the number of biofilter units, and important environmental factors. Orchard workers in China should improve the existing treatment of residual pesticide wastewater to mitigate agricultural non-point source pollution.

Evaluating Best Management Practice Efficacy Based on Seasonal Variability and Spatial Scales

Implementing best management practices (BMPs) has proven to be an efficient method for reducing non-point source (NPS) pollutants. Agricultural NPS pollution is considered to be a major contributor to water quality impairment. This study aims to assess the variation in hydrologic and water quality outputs at field and watershed scales when BMPs are implemented using modeling approaches. The Yazoo River Watershed (YRW) is the largest watershed basin in the state of Mississippi with approximately 50% agricultural land. Runoff generated from agricultural areas carries sediments and nutrients. The Merigold watershed (MW) is a sub-basin of the YRW and a field-scale watershed with most of the land use being agriculture. It is essential to quantify the streamflow, sediment, total nitrogen (TN), and total phosphorus (TP) when BMPs are implemented. BMPs such as vegetative filter strips (VFS) and cover crops (CC) were tested in this study. The Soil and Water Assessment Tool (SWAT) model was applied to quantify the watershed’s hydrologic and water quality outputs. SWAT model accuracy assessment was performed by calibration and validation process using the Nash and Sutcliffe Efficiency Index (NSE). Model performance was satisfactory for monthly streamflow, with NSE values in the range of 0.62 to 0.81, and for daily sediments, TN, and TP load estimation, with NSE values of 0.21, 0.20, and 0.47, respectively. CC was planted after harvesting the main crop. Therefore, it is essential to quantify the seasonal reduction in pollutants. Water quality was improved after BMP implementation, and an overall decrease in streamflow, sediment, TN, and TP loads was observed for both MW and YRW during dry and wet seasons. Previous studies regarding seasonal assessments with CC implementation in the MW and YRW were limited. Therefore, the results from this study could be a unique addition to the scientific literature.

Assessment of Agricultural Non-point Source Pollution Loads Applying Improved Export Coefficient Model (IECM) : A Case Study in Taihu Lake Basin

Accurate and comprehensive estimation of agricultural non-point source pollution (ANPSP) is of vital importance in watershed pollution control, while data inaccessibility and complexity of process-based models may be main restrictions in practice. An estimation methodology framework for ANPSP was established based on improved export coefficient model (IECM) in this research. A series of updated, regional coefficients were collected and/or calculated with multiple pollution sources considered (i.e., animal husbandry, farming and forestry, fishery, and rural domestic sewage) to provide a comprehensive estimation of TN and TP pollution loads in Taihu Lake Basin. According to this model, pollution loads of TN and TP in Taihu Lake Basin were 65791.28 and 11400.38 t in 2016, respectively. Animal husbandry was main source of ANPSP, accounting for 31.05% and 66.70% for TN and TP, respectively, which requires more efficient and clean agricultural production modes and strict pollution control measures. IECM-based estimation framework may provide a reference for ANPSP management practice in large scale watershed.

Identification of agricultural surface source pollution in plain river network areas based on 3D-EEMs and convolutional neural networks.

Agricultural non-point sources, as major sources of organic pollution, continue to flow into the river network area of the Jiangnan Plain, posing a serious threat to the quality of water bodies, the ecological environment, and human health. Therefore, there is an urgent need for a method that can accurately identify various types of agricultural organic pollution to prevent the water ecosystems in the region from significant organic pollution. In this study, a network model called RA-GoogLeNet is proposed for accurately identifying agricultural organic pollution in the river network area of the Jiangnan Plain. RA-GoogLeNet uses fluorescence spectral data of agricultural non-point source water quality in Changzhou Changdang Lake Basin, based on GoogLeNet architecture, and adds an efficient channel attention (ECA) mechanism to its A-Inception module, which enables the model to automatically learn the importance of independent channel features. ResNet are used to connect each A-Reception module. The experimental results show that RA-GoogLeNet performs well in fluorescence spectral classification of water quality, with an accuracy of 96.3%, which is 1.2% higher than the baseline model, and has good recall and F1 score. This study provides powerful technical support for the traceability of agricultural organic pollution.

“Period-area-source” hierarchical management for agricultural non-point source pollution in typical watershed with integrated planting and breeding

Agricultural non-point source (NPS) pollution threatens the aquatic environments significantly. Insufficient attention to the migration characteristics of multiple sources of pollution as well as the variability of anthropogenic interference hinders effective pollution control, particularly in watersheds with integrated planting and breeding (IPB). In this study, we proposed a distributed dual-structure empirical export model for IPB (DSEEM-IPB) that optimizes hydrological processes in pollutant transport and refines NPS load estimation from animal breeding sources to simulate agricultural NPS pollution in a typical IPB watershed. Based on the estimated NPS load, a “period-area-source” management approach for NPS pollution is proposed with a co-analysis of critical periods (CPs), critical source areas (CSAs), and critical source types (CSTs). The results show that (1) the CPs of only two months (June and July) contributed 62.9% and 56.2% of the total nitrogen (TN) and total phosphorus (TP) load respectively; (2) the CSAs in the CPs contributed 17.6% of the TN load within 14.0% of the area and 16.2% of the TP load within 13.4% of the area; (3) planting (74.4%) is the primary source of nitrogen loss while breeding (58.3%) is the primary source of phosphorus loss; and (4) optimal control measures should target planting sources in CSAs and sub-CSAs within CPs (yielding 32.4% of annual TN loads) and breeding sources in CSAs within non-CPs (yielding 22.1% of annual TP loads). This study indicates that prioritizing pollution management of critical sources from critical areas or periods can achieve efficient and targeted control of agricultural NPS pollution.

Evolutionary Trend Analysis of Agricultural Non-Point Source Pollution Load in Chongqing Based on Land Use Simulation

Analysis of the relationship between future land use change and agricultural non-point source pollution (ANPSP) evolution is vital to promoting sustainable regional development. By simulating future land use types, we can identify and analyze the evolution trend of ANPSP. This study takes Chongqing as a case study to establish an integrated solution based on the PLUS model, output coefficient model, and GIS technology. The solution can simulate data, identify trends, and identify key control areas under future development scenarios. The results show that the PLUS model can simulate land use types at the provincial scale with high accuracy, with a Kappa coefficient of around 0.9. The land use type changes show that urban expansion has occupied a large amount of cultivated land. From 2000 to 2020, the proportion of high-load areas with TN pollution load levels was 4.93%, 5.02%, and 4.73%, respectively. Under the two scenarios in 2030–2050, the number of high-load areas decreased, and the average load level decreased from west to east. Sensitivity analysis found that risk changes are more sensitive to the increase in fertilizer application. When the TN and TP output coefficients are increased, the number of towns with increased levels is greater than those with decreased levels when the output coefficients are decreased. Sensitivity analysis can better identify key pollution control areas. The areas sensitive to changes in farmers’ behavior are mainly the Hechuan District, Nanchuan District, Qijiang District, Jiangjin District, and Bishan District. This study provides data and decision-making support for rural green development and water environment improvement.

Nutrient runoff and leaching under various fertilizer treatments and pedogeographic conditions: A case study in tobacco (Nicotiana tabacum L.) fields of the Erhai Lake basin, China

To ensure water security, it is crucial to understand the characteristics of nitrogen (N) and phosphorus (P) in water and to reduce their inputs. We conducted a 2-year trial (2021–2022) in tobacco fields across three sites in the Erhai Lake basin, China, to comprehensively measure and summarize N and P loss through runoff and leaching for four fertilizer treatments: no fertilizer (CK); farmers' traditional organic fertilizer (FP); chemical fertilizer (CF); and a combination of organic and inorganic fertilizer (OIC). The highest N concentrations were detected in leachate in the early tobacco growth stage, whereas the highest P concentrations occurred in runoff in the middle growth stage. Compared to FP, the OIC treatment improved nutrient uptake in flue-cured tobacco, while also reducing N loss through runoff and leaching by 45.37% and 19.34%, and reducing P loss by 7.22% and 8.26%, respectively. Correlation analyses revealed positive relationships of nutrient loss with soil organic matter content and nutrient inputs; elevation and soil water content exhibited varying correlations with different nutrients. These findings provide a theoretical foundation for the effective management of agricultural non-point source pollution in the Erhai Lake basin and shed light on water pollution pressures worldwide.

Yield, Quality, and Nitrogen Leaching of Open-Field Tomato in Response to Different Nitrogen Application Measures in Northwestern China.

The overuse of fertilizers in open-field tomato leads to soil deterioration through nutrient leaching and increases the risk of agricultural non-point source contamination. Currently, the combined effects of different fertilization methods on soil nitrogen leaching and tomato production are still unclear. Therefore, the most effective fertilization method for open-field tomato should be discovered by examining how different fertilization methods affected tomato yield and quality, nitrogen use efficiency (NUE), and soil nitrogen leaching. Compared with CK (no fertilization), fertilization significantly increased the yield, total sugar (TS), total soluble solids (TSS), and vitamin C (vC) contents of fruits (p < 0.05), and OPT (optimal fertilization, controlled release nitrogen application, 240 kg ha-1) had the largest effect on increasing yield, quality, and net profit. However, when the fertilizer application rate reached 375 kg ha-1, these indices decreased. Nitrogen leaching concentrations, leaching amount, and titratable acids (TAs) increased with increased nitrogen application rates. Compared with other treatments, OPT reduced the total leaching amounts of total nitrogen (TN), nitrate nitrogen (NO3--N), and ammonia nitrogen (NH4+-N) by 30.09-51.79%, 24.89-50.03%, and 30-65%, respectively. Principal component analysis (PCA) showed that OPT achieved the highest overall score in terms of yield, quality, and nitrogen leaching conditions. The partial least squares path modeling (PLS-PM) further reveals that applications of high amounts of nitorigen have a positive effect on soil nitrogen leaching. The amount of nitrogen leaching vegetatively affects tomato yield and quality, while plant uptake of nitrogen positively affects tomato production. These findings confirm the importance of using controlled-release fertilizers and reducing nitrogen inputs to control nitrogen leaching and enhance open-field tomato yields.

Assessing the Influence of Agricultural Nonpoint Source Pollution on Water Quality in Central Kentucky’s Headwater Streams

This study addresses the pressing issue of nonpoint source water pollution in Kentucky, particularly associated with large-scale agriculture. Centered on the outer bluegrass region of Central Kentucky, the research examines the water quality of headwater streams during the agricultural season. The approach involves geospatial land cover classification using aerial imagery. Water quality data were collected during the agricultural growing season from May to October 2018. Land cover classification utilized ERDAS Imagine 2016 and ESRI ArcGIS 10.6 GIS software, while conventional water quality parameters were measured with a YSI ProDSS® multiparameter water probe and a Marsh-McBirney Flo-Mate 2000 flow meter. Statistical analyses show significant differences in stream water chemistry, suggesting the impact of agricultural nonpoint source pollution. Forested streams exhibited more varied conditions, indicating a potentially better environment. As agricultural land percentage increased, water chemistry variation suggested a measurable threshold for changes. Significant differences in water quality between agricultural and forested streams highlight the potential benefits of expanding riparian zones beyond regulations. Enlarging these zones is proposed as a strategy to mitigate nonpoint source pollution in Kentucky’s waterways.

Managing the water-agriculture-environment-energy nexus: Trade-offs and synergies in an arid area of Northwest China

Water is a stabilizer for production and life in the arid areas. According to research shared by the Pacific Institute and The Guardian, there were 228 incidents of water conflict globally in 2022. Therefore, comprehensive measures are necessary to achieve regional water security. This objective can be achieved by the application of interdisciplinary and professional approaches through establishing a dynamic equilibrium of the different water consumers, and trade-offs and synergies for water allocation between them. A multi-objective optimization model is proposed for managing the water-agriculture-energy-environment (WAEE) nexus in water-scarce areas. Real and integer-encoded multi-objective evolutionary algorithms (EMCMO) were applied to solving management models. Multiple objectives, such as the maximization of economic benefits from agriculture and hydropower generation, the minimization of ecological water shortages for local plants, and the minimization of environmental risks influenced by land use and food supply, were defined in the model. The model was applied to the Yanqi Basin, an important agriculture and energy producer in Xinjiang province, Northwest China. The results indicated that (1) the four-dimensional Pareto solution set has the advantage of presenting the WAEE nexus, highlighting the trade-offs and synergies between high-value crops, surface water, and groundwater, ecological water demand, hydropower generation and total nitrogen and phosphorus loading (TNP); (2) An excessive increase in the agricultural economy will increase TNP loading and agricultural non-point source pollution; (3) Optimization of WAFE for local ecosystem restoration. Optimization in a wet year, reduced agricultural economic benefits by 0.20%, and agricultural TNP loading by 13.19% while increasing ecological water by 58.33%, and hydropower generation by 3.98%; in a normal year, reduced agricultural economic benefits by 6.62%, agricultural TNP loading by 13.19% while increasing ecological water by 46.43%, and hydropower generation by 0.79%; in a dry year, reduced agricultural economic benefits by 17.19%, agricultural TNP loading by 9.72%, and hydropower generation by 16.18% while increasing ecological water by 42.86%. The trade-offs and synergies of the WAEE nexus also apply to other similar water-scarce areas.

A Comprehensive Analysis of Agricultural Non-Point Source Pollution in China: Current Status, Risk Assessment and Management Strategies

With the expansion of the scope and diversity of agricultural non-point source (AGNPS) pollution, environmental pollution in water bodies and soils has intensified, seriously affecting the quality of life of urban and rural residents. This paper presents a comprehensive analysis of the current status of AGNPS pollution from five aspects: fertilizers, pesticides, agricultural films, livestock and crop residues. The study also includes a comprehensive risk assessment of the nitrogen and phosphorus pollution, microplastic pollution, and heavy metal contamination attributed to the current AGNPS pollution in China. The findings reveal widespread nitrogen and phosphorus pollution across provinces in China, a low risk of microplastic pollution, and acute contamination with heavy metals such as As, Cd and Hg, notably in Hubei, Gansu, Liaoning, Guizhou, and Hunan. Additionally, the study reveals that in Chinese provinces currently facing severe heavy metal pollution, heavy metal contamination constitutes a significant carcinogenic risk to adult health and a serious non-carcinogenic risk to child health. Consequently, guided by the ‘3R theory’ principles of source reduction, interception, and remediation, this paper suggests an array of expanded strategies for AGNPS pollution management. These strategies are proposed to aid in the sustainable advancement of AGNPS pollution control.

Does digital village construction contribute to improving food security?

&lt;p class="MsoNormal" style="margin-top: 12pt; text-align: justify;"&gt;&lt;span lang="EN-US" style="font-family: 'times new roman', times, serif; font-size: 14pt;"&gt;The issue of food security has become a global challenge, and it is therefore crucial to seek measures to ensure food security. As an emerging economic model, the digital economy is regarded as the most effective tool for the modernization of agricultural development. As a large food-producing country, China faces serious problems of agricultural non-point source pollution and food loss and waste. The purpose of this study is to explore the impact of digital village construction on food security. We measure the level of digital village construction and food security by entropy method and use the spatial Durbin model to analyze them. In this paper, we found that digital village construction facilitates food security not only in the region but also in neighboring regions. In addition, we found that the promotion effect is significant in main grain producing regions, while the opposite result is found in non-main grain producing regions. We hold that the application of the digital economy in the countryside has played an obvious role in promoting food security in main grain producing provinces, and provides important experimental evidence for reference to ensure food security in the future.&lt;/span&gt;&lt;/p&gt;

Prediction of agricultural nonpoint source pollution in highly urbanised areas based on shared socioeconomic pathways: a case study of Taihu Lake Basin

Prediction of agricultural nonpoint source pollution in highly urbanised areas based on shared socioeconomic pathways: a case study of Taihu Lake Basin