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Environmental regulation (ER) is essential to preventing agricultural non-point source pollution (ANSP). Prior research has focused on the effect of ER on agricultural pollution (AP), but little is known about the impact of ER following digitization on preventing AP, particularly ANSP. Based on the spatial heterogeneity, the effect of ER was examined using a geographic detector tool with provincial panel data from 2010 to 2020 in rural China. The results show that ER is a driver in preventing ANSP, primarily because of the constraint on farmers' behavior. Digitization positively affects the prevention of ANSP, as the new impetus for the infrastructure, technology, and capital is supported. The interaction between ER and digitalization forms a driving effect on the prevention of ANSP, indicating that digitalization constitutes the path dependence of farmers' rule acquisition and perception and addresses the \"free riding\" dilemma of farmers' participation, thereby enabling the incentive of ER to make agricultural production green and efficient. These findings indicate that the endogenous factor of digitization allowing ER is essential to preventing ANSP.

Non-point source (NPS) pollution, including fertilizer and manure application, sediment erosion, and haphazard discharge of wastewater, has led to a wide range of water pollution problems in the Miyun Reservoir, the most important drinking water source in Beijing. In this study, the Soil and Water Assessment Tool (SWAT) model was used to evaluate NPS pollution loads and the effectiveness of best management practices (BMPs) in the two subwatersheds within the Miyun Reservoir Watershed (MRW). Spatial distributions of soil types and land uses, and changes in precipitation and fertilizer application, were analysed to elucidate the distribution of pollution in this watershed from 1990 to 2010. The results demonstrated that the nutrient losses were significantly affected by soil properties and higher in both agricultural land and barren land. The temporal distribution of pollutant loads was consistent with that of precipitation. Soil erosion and nutrient losses would increase risks of water eutrophication and ecosystem degradation in the Miyun Reservoir. The well-calibrated SWAT model was used to assess the effects of several Best Management Practices (BMPs), including filter strips, grassed waterways, constructed wetlands, detention basins, converting farmland to forest, soil nutrient management, conservation tillage, contour farming, and strip cropping. The removal rates of those BMPs ranged from 1.03 to 38.40% and from 1.36 to 39.34% for total nitrogen (TN) and total phosphorus (TP) loads, respectively. The efficiency of BMPs was dependent on design parameters and local factors and varied in different sub-basins. This study revealed that no single BMP could achieve the water quality improvement targets and highlighted the importance of optimal configuration of BMP combinations at sub-basin scale. The findings presented here provide valuable information for developing the sustainable watershed management strategies.

Road-deposited sediments (RDS) on an expressway, residual RDS collected after sweeping, and RDS removed by means of sweeping were analyzed to evaluate the degree to which sweeping removed various non-point source contaminants. The total RDS load was 393.1 ± 80.3 kg/km and the RDS, residual RDS, and swept RDS were all highly polluted with organics, nutrients, and metals. Among the metals studied, Cu, Zn, Pb, Ni, Ca, and Fe were significantly enriched, and most of the contaminants were associated with particles within the size range from 63 μm to 2 mm. Sweeping reduced RDS and its associated contaminants by 33.3–49.1% on average. We also measured the biological oxygen demand (BOD) of RDS in the present work, representing to our knowledge the first time that this has been done; we found that RDS contains a significant amount of biodegradable organics and that the reduction of BOD by sweeping was higher than that of other contaminants. Significant correlations were found between the contaminants measured, indicating that the organics and the metals originated from both exhaust and non-exhaust particles. Meanwhile, the concentrations of Cu and Ni were higher in 63 μm–2 mm particles than in smaller particles, suggesting that some metals in RDS likely exist intrinsically in particles, rather than only as adsorbates on particle surfaces. Overall, the results in this study showed that sweeping to collect RDS can be a good alternative for reduction of contaminants in runoff.

It is the key point to reveal the effect of irrigation water and fertilization conditions on the agriculture non-point pollution in the paddy field. In this study, the estimation model of agricultural non-point source pollution loads at field scale was established on the basis of agricultural drainage irrigation model and combined with pollutant concentration predication model. Based on the estimation model of agricultural non-point source pollution in the field and experimental data, the load of agricultural non-point source pollution in different irrigate amount and fertilization schedule in paddy field was calculated. The results showed that the variation of field drainage varies greatly under different irrigation conditions, and there is an “inflection point” between the irrigation water amount and field drainage amount. The non-point pollution load increased with the increase of irrigation water and showed a significant power correlation. Under the different irrigation condition, the increase amplitude of non-point pollution load with the increase of irrigation water was different. When the irrigation water is smaller, the non-point pollution load increase relatively less, and when the irrigation water increased to inflection point, the non-point pollution load will increase considerably. In addition, there was a positive correlation between the fertilization and non-point pollution load. The non-point pollution load had obvious difference in different fertilization schedule even with same fertilization level, in which the fertilizer pollution load increased the most in the period of turning green to tillering. The results provide some basis for the field control and management of agricultural non-point source pollution.

Agricultural non-point source pollution causes global warming and the deterioration of air and water quality. It is difficult to identify and monitor the emission sources of agricultural pollution due to the large number of farms in China. Many studies focus on the technological aspect of achieving agricultural sustainability, but its socioeconomic aspect is poorly understood. Here, we report how group size (number of farms in a certain region) affects agricultural pollution governance through conducting a social science experiment. We found that when communication was allowed among group members, a small group size facilitated cooperation. Although deviations from the cooperation equilibrium occurred with time in all groups, the smaller the group size, the slower the cooperation equilibrium became frangible. These findings suggest that reducing number of farms and extending the length of farm property rights can benefit the mitigation of agricultural non-point pollution in China. Social science experiments can be a useful tool to understand the socioeconomic aspect of agricultural sustainability.

Agricultural non-point source pollution is threatening water environmental health of the Three Gorges reservoir. However, current studies for precision management of the agricultural non-point source pollution within this area are still limited. The objective of this study was identifying the critical areas and primary sources of agricultural non-point source pollution for precision management. Firstly, the inventory analysis approach was used to estimate the discharge amount of total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD) from farmland fertilizer, crop residues, livestock breeding, and daily activities. Afterwards, the deviation standardization method was applied to evaluate the emission intensity of TN, TP, and COD, as well as calculating the comprehensive pollution index (CPI) of each village, based on which the critical areas for agricultural non-point source pollution management could be distinguished. Moreover, the equivalence pollution load method was conducted to identify the primary pollution sources within each critical zone. The above methods were implemented to an emigrant town within the Three Gorges reservoir area named Gufu. Results showed that agricultural non-point source pollution in Gufu town has been alleviated to a certain extent since 2016. Nevertheless, in four areas of the town (i.e., Longzhu, Fuzi, Shendu, and Maicang), the agricultural non-point source pollution still deserved attention and improvement. For the mentioned critical areas, farmland fertilizer and livestock breeding were the primary sources causing agricultural non-point source pollution. The emission amount of TN and TP from farmland fertilizer accounted for 60% and 48% of the total, respectively. And those from livestock breeding were 29% and 46%. Our research could provide definite targets to relieve agricultural non-point source pollution, which had great significance to protect water environment while coordinating regional economic growth after emigrant resettlement.

The concerns about the contradiction between agricultural production and Agricultural Non-Point (ANPS) pollution has become increased with economic development in China. Government interventions are key to controlling ANPS pollution through the establishment of laws and policies. This paper uses the entropy method to calculate the emissions amount of ANPS pollution and policy strength of 31 provinces from 2010 to 2019 in China. The dynamic panel data model with system generalized moment is used to estimate the impacts of policies with different measures on ANPS pollution emission. According to our findings, China's policies have been helpful in controlling ANPS pollution though there are important regional differences. Moreover, four types of policy measures all contribute to the reduction in ANPS pollution. These findings improve our understanding of the relationship between policies and ANPS pollution in the analyzed period, thus providing support for the formulation of pollution management strategies in the next stage.

Solving the contradiction between agricultural economic growth and agricultural environmental problems is a difficult problem in regional environmental governance. Based on the panel data of 31 provinces, municipalities, and autonomous regions in China from 2000 to 2019, spatial Dubin model (SDM) is used to analyze the influence of agricultural economic growth and other factors on planting non-point source pollution. Innovate from the perspective of research objects and research methods, and the research results show (1) In the past 20 years, the amount of fertilizer applied and crop straw yield increased continuously. Through the fertilizer and farmland solid waste discharge of ammonia nitrogen (NH 3 –N), total nitrogen (TN), total phosphorus (TP), and chemical oxygen demand (COD), calculation of the equal-standard discharges of planting non-point source pollution shows that China’s planting non-point source pollution is serious. Among the investigated areas in 2019, the equal-standard discharges of planting non-point source pollution in Heilongjiang Province were the highest and have reached 24.35 × 10 10 m 3 . (2) The global Moran index of 20 years in the study area shows obvious spatial aggregation and diffusion characteristics, and has a significant positive global spatial autocorrelation, indicating that planting non-point source pollution discharges of the study area have potential interdependence in space. (3) SDM time-fixed effect model showed that the equal-standard discharges of planting non-point source pollution had a significant negative spatial spillover effect, and the spatial lag coefficient was − 0.11. Among the influencing factors, agricultural economic growth, technological progress, financial support to agriculture level, consumption capacity, industrial structure, and risk perception have significant spatial spillover effects on planting non-point source pollution. The results of effect decomposition show that the positive spatial spillover effect of agricultural economic growth on adjacent areas is greater than the negative effect on the local area. Based on the analysis of significant influencing factors, the paper provides direction guidance for the formulation of planting non-point source pollution control policy.

To promote sustainable agricultural development in small town areas during rapid industrialization, it is important to study the evolution of agricultural non-point source pollution (ANSP) and its influencing factors in small town areas in the context of rapid industrialization. The non-point source inventory method was used to study the characteristics of ANSP evolution in 14 small town areas in Gongyi City from 2002 to 2019. Using the spatial Durbin model and geographical detectors, the factors influencing ANSP in small town areas were analyzed in terms of spatial spillover effects and the spatial stratified heterogeneity. The results showed a zigzagging downward trend of ANSP equivalent emissions over time. Spatially, the equivalent emissions of ANSP showed a distribution pattern of being high in the west and low in the east. There was a significant positive global spatial autocorrelation feature and there was an inverted \"U-shaped\" Environmental Kuznets Curve relationship between industrialization and ANSP. Affluence, population size, and cropping structure positively contributed to the reduction of ANSP. Population size, land size, and industrialization were highly influential factors affecting the spatial variation of ANSP and the interaction of these factors was bivariate or nonlinearly enhanced. This study provides a feasible reference for policymakers and managers to develop reasonable management measures to mitigate ANSP in small town areas during rapid industrialization.

1. Adult coho salmon Oncorhynchus kisutch return each autumn to freshwater spawning habitats throughout western North America. The migration coincides with increasing seasonal rainfall, which in turn increases storm water run-off, particularly in urban watersheds with extensive impervious land cover. Previous field assessments in urban stream networks have shown that adult coho are dying prematurely at high rates (> 50%). Despite significant management concerns for the long-term conservation of threatened wild coho populations, a causal role for toxic run-off in the mortality syndrome has not been demonstrated. 2. We exposed otherwise healthy coho spawners to: (i) artificial storm water containing mixtures of metals and petroleum hydrocarbons, at or above concentrations previously measured in urban run-off; (ii) undiluted storm water collected from a high traffic volume urban arterial road (i.e. highway run-off); and (iii) highway run-off that was first pre-treated via bioinfiltration through experimental soil columns to remove pollutants. 3. We find that mixtures of metals and petroleum hydrocarbons - conventional toxic constituents in urban storm water - are not sufficient to cause the spawner mortality syndrome. By contrast, untreated highway run-off collected during nine distinct storm events was universally lethal to adult coho relative to unexposed controls. Lastly, the mortality syndrome was prevented when highway run-off was pretreated by soil infiltration, a conventional green storm water infrastructure technology. 4. Our results are the first direct evidence that: (i) toxic run-off is killing adult coho in urban watersheds, and (ii) inexpensive mitigation measures can improve water quality and promote salmon survival. 5. Synthesis and applications. Coho salmon, an iconic species with exceptional economic and cultural significance, are an ecological sentinel for the harmful effects of untreated urban runoff. Wild coho populations cannot withstand the high rates of mortality that are now regularly occurring in urban spawning habitats. Green storm water infrastructure or similar pollution prevention methods should be incorporated to the maximal extent practicable, at the watershed scale, for all future development and redevelopment projects, particularly those involving transportation infrastructure.