Intensive Agricultural Regions Research Articles

Effects of the organochlorine pesticide metabolite p,p’-DDE on the gastrointestinal lipidome in fish: A novel toxicity pathway for a legacy pollutant

Though phased out from use in the United States, environmental contamination by organochlorine pesticides (OCPs) remains a widespread issue, especially around intensive agricultural regions. OCPs, such as dichlorodiphenyltrichloroethane (DDT) and its primary metabolite, dichlorodiphenyldichloroethylene (DDE), have been detected in soils, sediments, surface waters, and biota decades after their discontinued use. As OCPs are persistent and can bioaccumulate in fats, these compounds can transfer and magnify across food webs. Freshwater predatory fish and birds can accumulate high OCP concentrations, leading to a myriad of deleterious impacts on organismal health. Studies have found evidence of reproductive disruption in predatory fish, such as the largemouth bass (LMB; Micropterus salmoides), associated with DDT and DDE exposure. DDE can act through estrogenic pathways and induce the expression of estrogenic signals in male animals; however, the molecular mechanism of disruption is unclear. Recently, metabolomics research has revealed corollary relationships between lipid signals and organic pollutant toxicity. Here, a two-month feeding experiment on LMB was conducted to assess the interactions of DDE (as p,p'-DDE) in food with gut and liver lipid signaling. Targeted lipidomic analysis revealed global alterations in the abundance of tissue lipids, especially cholesteryl esters and phospholipids, in LMB exposed to low levels of p,p'-DDE. Results from these studies indicate that p,p'-DDE may act through disruption of normal lipid homeostasis to cause toxicity in freshwater fish.

Shallow Groundwater Around Plateau Lakes： Spatiotemporal Distributions of Dissolved Carbon and Its Driving Factors

Dissolved carbon in groundwater plays an important role in carbon cycling and ecological function maintenance, and its concentration level affects the migration and transformation of pollutants in groundwater. To understand the spatiotemporal variation characteristics of dissolved carbon and its driving factors in shallow groundwater around plateau lakes, variations in the concentrations of dissolved organic carbon （DOC）, inorganic carbon （DIC）, and total carbon （DTC） and their driving factors in shallow groundwater （n = 404） around eight plateau lakes were analyzed. The results indicated that the average values of ρ（DOC）, ρ（DIC）, and ρ（DTC） in shallow groundwater around plateau lakes were 8.23, 49.01, and 57.84 mg·L-1, respectively, with the ρ（DOC） in 79.0% of shallow groundwater samples exceeding 5 mg·L-1. There were no significant differences in the DOC, DIC, and DTC concentrations between rainy and dry seasons, whereas the change in dissolved carbon concentrations in shallow groundwater were strongly affected by the intensity of agricultural intensification and the depth of groundwater table； the DOC, DIC, and DTC concentrations in shallow groundwater from facility agricultural regions （SFAR）, cropland fallow agricultural regions （CFAR）, and intensive agricultural regions with deeper groundwater tables （DIAR） were significantly reduced by 25.8% - 56.6%, 14.0% - 32.9%, and 16.6% - 36.7%, respectively, compared with those in intensive agricultural regions with shallower groundwater tables （SIAR）. Additionally, the dissolved carbon concentrations in shallow groundwater from DIAR were significantly lower than those of SFAR and CFAR. RDA revealed that physicochemical factors in water and soil significantly explained the changes in the dissolved carbon concentrations. Moreover, the dissolved carbon concentrations in shallow groundwater around Yilong Lake were significantly higher than those of other lakes, whereas that of Chenghai Lake was significantly lower than that of other lakes. Our study highlights that agricultural intensification intensity and groundwater table depth jointly drove the variations in dissolved carbon concentrations in shallow groundwater around plateau lakes. The study results are expected to provide a scientific basis for understanding the carbon cycle in plateau lake areas with underground runoff flowing into lakes and evaluating the attenuation of pollutants by dissolved carbon in shallow groundwater.

Shallow groundwater table fluctuations weaken nitrogen accumulation in the thin layer vadose zone of cropland around plateau lakes, Southwest China

Excessive accumulation of nitrogen (N) in the soil profile in the intensive agricultural region will seriously threaten groundwater quality and safety. However, the impact of shallow groundwater table (SGWT) fluctuations driven by seasonal variations on the N accumulation characterizations in the soil profiles has not been well quantified, particularly in the regions with thin layer vadose zone. Through in-situ monitoring and simulation experiments, the changes in the SGWT and N accumulation of soil profile in intensive cropland around 7 plateau lakes in Yunnan were studied during the rainy season (RS) and dry season (DS), and the N loss in soil profile of cropland driven by SGWT fluctuations was estimated. The results showed that the SGWT and N accumulation in soil profile of cropland around the plateau lakes had obvious seasonal variation characteristics. The proportion of N storage in different forms in 60–100 cm soil layer in the RS was greater than that in the DS, particularly the proportion of NH4+-N storage was as high as 55 %, while N accumulation in surface soil was obvious in the DS. Compared with the DS, due to the rising SGWT in the RS, the maximum storages of TN and NO3−-N in the 0–100 cm soil layer decreased by17% and 36 %, respectively. The TN loss intensities from the 0–100 cm soil profiles of cropland around Fuxian Lake, Yilong Lake, Qilu Lake, Dianchi Lake, Yangzong Lake, Erhai Lake, and Xingyun Lake were 74, 54, 127, 105, 93, 72 and 207 kg/ha, respectively. Moreover, if the SGWT was <30 cm, the average TN loss intensity and amount could reach 177 kg/ha and 1250 t, respectively. Therefore, the SGWT regulation was one of the key measures to reducing soil N loss from the thin layer vadose zone of cropland around plateau lakes and improving groundwater quality.

Tracing groundwater nitrate sources in an intensive agricultural region integrated of a self-organizing map and end-member mixing model tool

The traceability of groundwater nitrate pollution is crucial for controlling and managing polluted groundwater. This study integrates hydrochemistry, nitrate isotope (δ15N-NO3− and δ18O-NO3−), and self-organizing map (SOM) and end-member mixing (EMMTE) models to identify the sources and quantify the contributions of nitrate pollution to groundwater in an intensive agricultural region in the Sha River Basin in southwestern Henan Province. The results indicate that the NO3−-N concentration in 74% (n = 39) of the groundwater samples exceeded the WHO standard of 10 mg/L. According to the results of EMMTE modeling, soil nitrogen (68.4%) was the main source of nitrate in Cluster-1, followed by manure and sewage (16.5%), chemical fertilizer (11.9%) and atmospheric deposition (3.3%). In Cluster-2, soil nitrogen (60.1%) was the main source of nitrate, with a significant increase in the contribution of manure and sewage (35.5%). The considerable contributions of soil nitrogen may be attributed to the high nitrogen fertilizer usage that accumulated in the soil in this traditional agricultural area. Moreover, it is apparent that most Cluster-2 sampling sites with high contributions of manure and sewage are located around residential land. Therefore, the arbitrary discharge and leaching of domestic sewage may be responsible for these results. Therefore, this study provides useful assistance for the continuous management and pollution control of groundwater in the Sha River Basin.

Processing of Legume Green Manures Slowdowns C Release, Reduces N Losses and Increases N Synchronisation Index for Two Years

The number of livestock farms decreased by 40% in Europe over the last 10-year period. Stockless organic cropping systems started to dominate in many intensive agricultural regions in Europe. Developing the sustainable management of an organic stockless agroecosystem is related to guaranteeing self-sufficiency in nitrogen (N) supply, maintaining high grain yields, and promoting carbon (C) sequestration in the soil. The aim of this study was to investigate if the processed legume green manures can be an alternative to granulated cattle manure and direct ploughing of legume biomass in order to develop the sustainability of the stockless organic cropping system. The decomposition rate and C and N release were observed for green manures made of fermented red clover and composted red clover with wheat straw. Fresh red clover biomass and granulated cattle manure were used for the comparison. Results of the 3-year field experiment showed that technologically processed legume biomass had a positive effect on the productivity of crops at least two years in rotation. Fermented red clover and red clover compost increased N use efficiency by 15% and biomass output efficiency by 16% compared with fresh red clover biomass. Processed legume green manures significantly increased the synchronisation index between crop N demand and N supply. In autumn, incorporated fresh red clover biomass lost 65.6% of its initial C and 37.6 kg ha−1 (50.1%) of its initial N under decomposition in the first non-growing season. It also increased mineral N losses deeper into the subsoil by 52.7%. Meanwhile, fermented red clover and red clover compost released 43% of its N during the first crop growing season, sustained at least one year slower C release to the soil, promoted ecosystem productivity, prevented mineral N losses to subsoil and gained high N synchrony indexes. The best N synchrony was achieved using fermented red clover, with a higher decomposition rate positively significantly correlated (r = 0.47–0.78, p &lt; 0.05) with grain yield, total biomass, protein content and total N accumulated in the plant of spring wheat and spring barley.

Extreme precipitation accelerates nitrate leaching in the intensive agricultural region with thick unsaturated zones

Nitrate accumulation in the soil profile in the intensive agricultural region has been widely concerned in the world. However, the changes in nitrate accumulation characteristics caused by climate change, such as extremely high precipitation, are not well quantified, particularly for the regions with thick unsaturated zones. Here, we resampled the soil profiles taken in normal year (2020) after extreme precipitation year (2021) (>800 cm) in three regions in the southern Loess Plateau (LP) with three different water managements including rainfed orchards (n = 10), well-irrigated orchards (n = 4) and canal-irrigated orchards (n = 8). The accumulation amounts, peak depths, and accumulation depths of nitrate soil profiles of the different regions of two years were compared. The results showed that average nitrate accumulation in normal year at the rainfed region (800-cm depth), well-irrigated region (800-cm depth) and canal-irrigated region (1400-cm depth) were 5995 kg N ha−1, 9765 kg N ha−1, and 19,608 kg N ha−1, respectively. Compared with 2020, extreme precipitation in 2021 led to 56–91% reductions (2060–3702 kg N ha−1) in nitrate accumulation in 0–200 cm soil layer, and average nitrate leaching into the aquifer was >1390 kg N ha−1 in the canal-irrigated region. Average migration depths of nitrate peak in rainfed, well-irrigated and canal-irrigated regions were 92 cm, 115 cm, and 188 cm, respectively; as for nitrate accumulation depths, they were 10 cm, 80 cm and 108 cm, respectively. Vertically, the dried soil layer and paleosol layer (high clay content) in the canal-irrigated region significantly hindered nitrate deep migration caused by the extreme precipitation. The result highlights that extreme precipitation significantly accelerated nitrate leaching in the deep soil profiles, and future vulnerability and risk assessment studies must account for the impacts of extreme precipitation on nitrate leaching.

Dissolved organic carbon and dissolved oxygen determine the nitrogen removal rate constant in small water bodies of intensive agricultural region

Small water bodies are extensively distributed and play critical roles in nitrogen (N) removal, primarily through sediment denitrification. However, our comprehension understanding of the N removal rate constant in these systems, particularly within the first-order kinetics model, remains limited. To address this gap, a one-year field study was conducted to investigate the N removal rate and N removal rate constant in various small water bodies within a typical intensive agricultural area. We observed a decrease in N removal rates in the downstream direction, from ditches to downstream ponds and streams, potentially due to upstream water bodies receiving higher nutrient inputs. Moreover, our findings revealed that the N removal process in small water bodies generally follows a first-order kinetics reaction model, with the N removal rate constant varying from 0.22 d1 in streams and 0.48 d1 in vegetated ditches. Both water dissolved organic carbon (DOC) and dissolved oxygen (DO) concentrations collectively influenced the N removal rate constants. By leveraging the relationship between the N removal rate constant and these environmental factors, we further estimated that, on average, small water bodies remove 68% of the N loading in the Dongting Lake Basin. We recommend implementing artificial management measures, such as vegetation, to enhance the N removal capacity of water bodies. However, the caution must be exercised in measures like concrete linings in ditches, as they can hinder N removal. These findings not only offer methods for estimating N removal in small water bodies, but also provide an insight into enhancing the N removal capacity of these systems to effectively mitigate non-point N pollution.

Exploring recharge mechanisms of soil water in the thick unsaturated zone using water isotopes in the North China Plain

Exploring the groundwater recharge mechanisms in regions with thick unsaturated zones can enhance our understanding of intricate groundwater processes, especially in intensive agricultural regions such as the North China Plain (NCP). For example, to better answer the question of how deep soil water can be recharged, it is of utmost importance to illustrate the recharge mechanisms of groundwater under different land use types in the NCP. This study collected soil samples from four boreholes up to 18 m deep covering farmland and orchards with different stand ages and measured soil water content (SWC), stable and radioactive isotopes (δ18O, δ2H and 3H) of both soil water and groundwater. Results indicated that the movement of water through the deep vadose zone of soils was primarily piston flow based on a soil tritium profile. The infiltration rate was estimated to be 32.2 mm yr−1 based on the tritium peak method. The variations of soil water δ18O and line control excess (lc-excess) indicated that the orchards had lower evaporation effects and a higher precipitation offset than those in farmland soils. Furthermore, the deep soil water was replenished by intensive precipitation events (from July to September). The great soil water deficit and decreased deep drainage under pear orchards is usually closely related to huge water consumption by evapotranspiration (ET) via root uptake, which explains the increase of ET in pear orchards with increasing stand age. These findings have provided substantial insights into groundwater resource management in similar regions with limited water resources and recharge modeling for regions covered with thick unsaturated zones.

Volatile organic compound fluxes in the agricultural San Joaquin Valley – spatial distribution, source attribution, and inventory comparison

Abstract. The San Joaquin Valley is an agricultural region in California that suffers from poor air quality. Since traffic emissions are decreasing, other sources of volatile organic compounds (VOCs) are gaining importance in the formation of secondary air pollutants. Using airborne eddy covariance, we conducted direct, spatially resolved flux observations of a wide range of VOCs in the San Joaquin Valley during June 2021 at 23–36 ∘C. Through land-cover-informed footprint disaggregation, we were able to attribute emissions to sources and identify tracers for distinct source types. VOC mass fluxes were dominated by alcohols, mainly from dairy farms, while oak isoprene and citrus monoterpenes were important sources of reactivity. Comparisons with two commonly used inventories showed that isoprene emissions in the croplands were overestimated, while dairy and highway VOC emissions were generally underestimated in the inventories, and important citrus and biofuel VOC point sources were missing from the inventories. This study thus presents unprecedented insights into the VOC sources in an intensive agricultural region and provides much needed information for the improvement of inventories, air quality predictions, and regulations.

Landscape-scale floral resource discontinuity decreases bumble bee occurrence and alters community composition.

Agricultural practices and intensification during the past two centuries have dramatically altered the abundance and temporal continuity of floral resources that support pollinating insects such as bumble bees. Long-term trends among bumble bees within agricultural regions suggest that intensive agricultural conditions have created inhospitable conditions for some species, while other species have maintained their relative abundances despite landscape-level changes in flower availability. Bumble bee responses to spatiotemporal resource heterogeneity have been explored at the colony and behavioral level, but we have yet to understand whether these conditions drive community structure and ultimately explain the diverging patterns in long-term species trends. To explore the relationship between landscape-level floral resource continuity and the likelihood of bumble bee occurrence, we mapped the relative spatial and temporal availability of floral resources within an intensive agricultural region in the US Upper Midwest and related this resource availability with bumble bee species relative abundance. Across the bee community, we found that relative bumble bee occurrence increases in landscapes containing more abundant and more temporally continuous floral resources. Declining species, such as Bombus terricola, exhibited the strongest, positive responses to resource abundance and continuity whereas common, stable species, such as Bombus impatiens, showed no statistical relationship to either. Together with existing experimental evidence, this work suggests that efforts to increase spatiotemporal flower availability, along with overall flower abundance at landscape scales may have positive effects on bumble bee communities in the US Upper Midwest.

Distribution, sources and main controlling factors of nitrate in a typical intensive agricultural region, northwestern China: Vertical profile perspectives

Nitrate (NO3−) pollution of groundwater is a global concern in agricultural areas. To gain a comprehensive understanding of the sources and destiny of nitrate in soil and groundwater within intensive agricultural areas, this study employed a combination of chemical indicators, dual isotopes of nitrate (δ15N–NO3− and δ18O–NO3−), random forest model, and Bayesian stable isotope mixing model (MixSIAR). These approaches were utilized to examine the spatial distribution of NO3− in soil profiles and groundwater, identify key variables influencing groundwater nitrate concentration, and quantify the sources contribution at various depths of the vadose zone and groundwater with different nitrate concentrations. The results showed that the nitrate accumulation in the cropland and kiwifruit orchard at depths of 0–400 cm increased, leading to subsequent leaching of nitrate into deeper vadose zones and ultimately groundwater. The mean concentration of nitrate in groundwater was 91.89 mg/L, and 52.94% of the samples exceeded the recommended grade III value (88.57 mg/L) according to national standards. The results of the random forest model suggested that the main variables affecting the nitrate concentration in groundwater were well depth (16.6%), dissolved oxygen (11.6%), and soil nitrate (10.4%). The MixSIAR results revealed that nitrate sources vary at different soil depths, which was caused by the biogeochemical process of nitrate. In addition, the highest contribution of nitrate in groundwater, both with high and low concentrations, was found to be soil nitrogen (SN), accounting for 56.0% and 63.0%, respectively, followed by chemical fertilizer (CF) and manure and sewage (M&S). Through the identification of NO3− pollution sources, this study can take targeted measures to ensure the safety of groundwater in intensive agricultural areas.

Nutrient retention of newly restored wetlands receiving agricultural runoff in a temperate region of North America

Globally, eutrophication is deemed to be the greatest threat to freshwater resources and is particularly problematic for large shallow lakes where the prevalence of cyanobacterial blooms has increased in recent decades. Restored wetlands have been identified as natural infrastructure that can reduce nutrient loads from agricultural landscapes, thereby reducing eutrophication in downstream freshwater systems. While restored wetlands are generally accepted as efficient nutrient transformers and processors, there are relatively few studies that examine nutrient retention based on detailed hydrological budgets across seasons. We determined the nutrient retention capacity for phosphorus and nitrogen species of newly restored wetlands (<8 years old) receiving nonpoint source agricultural runoff over two water years. These restored wetlands are located in an intensive agricultural region that contributes to the central and western basin of Lake Erie. Two-year mean TP and TN wetland retention capacities were 11.7 ± 5.9 and 261.2 ± 112.3 kg ha−1 yr−1, respectively. Two-year mean TP and TN wetland retention efficiencies were 46 ± 13 and 47 ± 8%, respectively. The mean SRP retention capacity and reduction efficiency over the two-year monitoring period were 4.8 ± 1.7 kg ha−1 yr−1 and 60 ± 11%, respectively. Investigating data over two water years revealed that nutrient retention was noticeably different across seasons for both TP and TN, with the highest retention occurring in summer for TP (5.7 ± 2.7 kg P ha−1) and in the spring for TN (99.9 ± 50.0 kg N ha−1). Our findings demonstrate that restored wetlands in agriculturally intensive temperate regions designed primarily for wildlife habitat can effectively reduce nonpoint source nutrients under a range of hydrological conditions. However, further research is needed to investigate the long-term effectiveness of restored wetlands as natural infrastructure for nutrient reduction, and to evaluate the potential environmental trade-offs and economic benefits of their implementation.

Spatial Characteristics and Obstacle Factors of Cultivated Land Quality in an Intensive Agricultural Region of the North China Plain

Cultivated land quality (CLQ) is at the core of the trinity protection of cultivated land in China. Scientific evaluation of CLQ and identification of its obstacle factors are the foundation for the construction and improvement of the quality of cultivated land. The main objective of this study was to evaluate CLQ and identify its obstacle factors, and Quzhou County, an intensive agricultural region in the North China Plain (NCP), was selected as a case study. The evaluation index system of CLQ was constructed based on five dimensions, including climate condition, topographic characteristic, soil property, farming status, and environmental condition, by analyzing the logical evolution of elements, processes, functions, and quality of cultivated land. A methodological system based on the Weighted Summation Method (WSM) and the “1 + X” model was developed to evaluate the CLQ. Then, the obstacle diagnosis model constructed based on the Cask Law and relevant academic studies was used to identify the obstacle factors of CLQ. The results showed that the proportion of high-, medium-, and low-quality cultivated land in Quzhou County was 36.19%, 33.60%, and 30.21%, respectively, and the average grade of CLQ was 2.97, which was considered to be at a medium level. Moran’s I of global spatial autocorrelation in Quzhou County was 0.8782, indicating a significant positive autocorrelation of the cultivated land quality index (CLQI). The main obstacle factors of CLQ in Quzhou County were soil profile constitution, irrigation guarantee rate, groundwater depth, and soil microbial biomass carbon. Therefore, based on the stable and dynamic characteristics of the obstacle factors, suggestions were provided to improve the quality of cultivated land in terms of strengthening the consolidation of cultivated land, transforming the concept of agricultural fertilization, and carrying out cultivated land recuperation. This study provides a new perspective on the cognition, evaluation, and identification of obstacle factors of CLQ, and the findings of this study can provide a reference for the consolidation and improvement of CLQ in the NCP.

Combining spectral analysis and geochemical tracers to investigate surface water–groundwater interactions: A case study in an intensive agricultural setting (southern Guatemala)

An increase in the frequency of severe hydrological events has highlighted the importance of sustainable water management in intensive agricultural regions. In a warming climate, improved understanding and stewardship of water resources are needed to guarantee water supply, ensure food security, and build resilience against extreme events. In this study, we evaluate a framework that combines spectral analysis and geochemical tracers as a potential tool for (1) gaining valuable insights into surface water (SW)–groundwater (GW) interactions, and (2) providing guidance for improved water management in an intensive agricultural basin in southern Guatemala. The framework proves to be useful in revealing important water dynamics, exposing key feedback mechanisms for water availability and quality. With the use of power density functions and hydrochemistry (T, pH, EC, and major ions), two specific interaction regimes (influent and effluent) were identified and delimited for the main watercourse. These segments are estimated to interact at high rates with the shallow aquifer in the river channel proximities and would lose influence towards the basin flanks. Furthermore, the δ2H and δ18O values indicate that regional groundwater flow systems play an essential role in the basin groundwater recharge. Lastly, we established three influence zones that depict the spatial extent of the SW-GW interactions within the basin. With these zones, we provide recommendations that will allow for further investigation and application into better water management strategies regulating groundwater development and land use activities within the agricultural context of the area.

Spatio-temporal variations of nitrate pollution of groundwater in the intensive agricultural region: Hotspots and driving forces

Nitrate (NO3−) pollution of groundwater is a persistent and widespread problem worldwide, particularly in intensive agricultural regions with high nitrogen (N) surplus. Identifying spatio-seasonal variations, drivers and sources of NO3− in groundwater is key to controlling this pollution. In this study, we monitored 175 wells in areas with different irrigation practices (dryland, well irrigation and canal irrigation) in an intensive apple-planting region over a year (September 2020–October 2021) in the southern Loess Plateau, China. The integration of hydrochemical analysis, deep soil profiles, NO3− isotopic composition and a Bayesian isotope mixing model (SIAR) was used to identify the hotspots and hot moments of groundwater NO3− pollution, and main NO3− sources. The results showed that average NO3− concentrations of three regions gradually decreased from north to south, following the order of dryland region (9 mg NO3 L−1) < well irrigation region (23 mg NO3 L−1) < canal irrigation region (94 mg NO3 L−1), and orchard > residential area ≈ cereal land. In the study region, 44% of groundwater exceeded the drinking standard of the World Health Organization (50 mg NO3 L−1). The intensive apple planting in the canal irrigation regions has caused groundwater NO3− pollution, and changed hydrochemical types from HCO3−Ca‧Mg to SO4‧Cl‧NO3-Ca‧Mg. In the canal irrigation region, NO3− in the vadose zone has migrated to groundwater. The hotspots of groundwater NO3− pollution (NO3− vulnerable zones) were identified at low-altitude loess tableland and alluvial plains with canal irrigation. Irrigation and precipitation accelerated soil NO3− deep migration. The hot moments of NO3− pollution in the irrigated region was the period from the wet season to the dry season; and the “hidden reactive N pool” in the deep vadose zone (>2 m) caused a time lag of NO3− reaching into groundwater. Chemical N fertilizer and manure N applied in apple orchards were the main contributing sources of groundwater NO3− pollution in the apple-planting region. Our study highlights the significant effect of apple-planting industry development on groundwater quality.

Identify nitrogen transport paths and sources contribution in karst valley depression area using isotopic approach

Karst groundwater provides drinking water for a quarter of Earth's population. However, in intensive agricultural regions worldwide, karst water is commonly polluted by nitrate (NO3−), particularly in the valley depression areas with well hydrological connectivity. The valley depression aquifers are particularly vulnerable to anthropogenic pollution because their pipes and sinkholes respond quickly to rainfall events and anthropogenic inputs. Identifying nitrate sources and transport paths in the valley depression areas is key to understanding the nitrogen cycle and effectively preventing and controlling NO3− pollution. This study collected high-resolution samples at four sites including one surface stream–SS, two sinkholes–SH and reservoir–Re, during the wet season in the headwater sub-catchment. The chemical component concentrations and stable isotopes (δ15N–NO3– and δ18O–NO3–) were analyzed. The stable isotope analysis model in R language (SIAR) was used to quantitatively analyze the contribution rate of NO3− sources. The results showed that the down section site (Re) has the highest [NO3−–N], followed by SH and the lowest SS. The sources calculation of SIAR demonstrated that, during the non-rainfall period, soil organic nitrogen was the primary source of the down section site, followed by fertilizer and the upper reaches sinkholes. During the rainfall period, fertilizer was the primary source of the down section site, followed by soil organic nitrogen and from upper reaches sinkholes. Rainfall events accelerated fertilizer–leaching into the groundwater. Slight denitrification may have occurred at the sampling sites but the assimilation of Re and SH could not occur. In conclusion, agricultural activities were still the primary influencing factor of [NO3−–N] in the study area. Therefore, the focus of NO3− prevention and control in the valley depression areas should consider the methods and timing of fertilization and the spatial distribution of sinkholes. To reduce nitrogen flux in the valley depression area, effective management policy should consider, e.g., prolongation of water residence time by wetland, and blocking nitrogen loss paths by sinkholes.

Hydrochemical evolution characteristics, controlling factors, and high nitrate hazards of shallow groundwater in a typical agricultural area of Nansi Lake Basin, North China

Anthropogenic nitrate contamination in groundwater could not be neglected, which has been a global issue threatening public health, especially in agricultural fields where fertilizers were used intensively. The present study focused on evaluating the groundwater evolution process, quality, and associated health risks from nitrate pollution in Nansi Lake Basin (NLB), a typical intensive agricultural region of North China. For this purpose, fifty-two shallow groundwater samples were collected and analyzed major chemical parameters in June 2022. The groundwater samples are found to be mainly dominated by HCO3–Ca·Mg and SO4·Cl–Ca·Mg types. Water-rock interactions like minerals dissolution/precipitation and ion exchange were found to be the important processes influencing hydrochemistry. Nitrate content in groundwater fluctuated from 1.9 to 750.0 mg/L (average:148.7 mg/L), with about 75% of samples surprisingly exceeding the permissible limit (50 mg/L) set by the World Health Organization (WHO). Anthropogenic activities can be classified as excessive nitrogen fertilizer application, livestock manure, and industrial/domestic sewage, coupled with irrigation return flow, which brought significant hazards to human health. The calculation results of entropy weighted water quality index (EWQI) showed that about half of groundwater samples are unfit for drinking purposes. Most importantly, 88.5%, 88.5%, 73.1%, and 71.2% of the water samples had considerable NO3− health risks (HQ > 1) for infants, children, females, and males, respectively. It is suggested that the groundwater should be chemical and biological denitrification for nitrate removal before being used for drinking purposes. The findings of this work can help policymakers to solve groundwater pollution problems and ensure healthy drinking water in such intensive agricultural basins and other similar regions worldwide.

Do differentially charged nanoplastics affect imidacloprid uptake, translocation, and metabolism in Chinese flowering cabbage?

Micro(nano)plastics are ubiquitous in the environment. Among the microplastics, imidacloprid (IMI) concentration has been increasing in some intensive agricultural regions, thus receiving increased attention. However, only a few studies have investigated the interaction of nanoplastics (polystyrene (PS)) and IMI in vegetable crops. We studied the effects of positively (PS-NH2) and negatively (PS-COOH) charged nanoplastics on the uptake, translocation, and degradation of IMI in Chinese flowering cabbage grown in Hoagland solution for 28 days. PS-NH2 co-exposure with IMI inhibited plant growth, resulting in decreased plant weight, height, and root length. Translocation of IMI from the roots to the shoots was significantly lower in the presence of PS-NH2, whereas PS-COOH accelerated the accumulation and translocation of IMI in plants, thus potentially affecting IMI metabolism in plants. Notably, IMI-NTG and 5-OH-IMI were the two dominant metabolites. PS-NH2 co-exposure with IMI induced significant oxidation stress and considerably affected the activities of superoxide dismutase (SOD) and peroxidase (POD), indicating that the antioxidant defense system was the main mechanism for reducing oxidative damage. Notably, both positively and negatively charged nanoplastics can accumulate in Chinese flowering cabbage. Plants in the PS-COOH alone treatment group had the highest concentration of nanoplastics in both roots and shoots. The accumulation of nanoplastics, IMI, and its metabolites in plants raises concerns about their combined potential toxicity because it compromises food safety.

Shifts in the sources and fates of nitrate in shallow groundwater caused by agricultural intensification intensity: Revealed by hydrochemistry, stable isotopic composition and source contribution

Groundwater nitrogen (N) pollution in intensive agricultural regions is increasing globally, and understanding the effects of increasing agricultural intensity on the sources and fates of N is critical for the effective control of groundwater pollution. Using multiple stable isotopes (δ15N-NO3—, δ18O-NO3—, δ18O-H2O, δD-H2O), hydrochemistry and the Bayesian stable isotope mixing model, the sources and fates of N were expounded, and their contributions were quantified in shallow groundwater (SG, n = 325) from an intensive agricultural region, a facility agricultural region and a cropland fallow region. We found that NO3— accounted for 60% of total N, and 52% of SG samples exceeded the WHO NO3— drinking water threshold (10 mg N L−1). Each N form concentrations and NO3— exceeding the standard rate in the intensive and facility agricultural regions were significantly higher than those in the cropland fallow region. Soil N, N fertilizer and manure and sewage were the dominant NO3— contributors in the SG of intensive agricultural regions, contributing to 66%, 21% and 10% of NO3—, respectively. The highest contributions of manure and sewage occurred in the cropland fallow region (46%), followed by the soil N (33%) and N fertilizer (13%), while the N sources in the SG from the facility agricultural region were dominated by manure and sewage (35%), soil N (31%) and N fertilizer (25%). Denitrification was the primary N biogeochemical cycle process in SG from the intensive and facility agricultural regions, whereas nitrification mainly occurred in the cropland fallow region. These results indicated that the shifts in the sources and fates of N in SG were controlled by agricultural intensification intensity, and soil N and manure and sewage, rather than N fertilizer, may become the most dominant N sources in SG in intensive agricultural regions. The N contamination control in SG should pay attention to improving septic tanks and sewage pipelines, the scientific and reasonable stacking of manure, and reducing the soil N pool in intensive agricultural regions.

Prediction of phosphorus concentrations in shallow groundwater in intensive agricultural regions based on machine learning

Excessive accumulation of phosphorus in soil profiles has become the main source of phosphorus in groundwater due to the application of phosphorus fertilizers in intensive agricultural regions (IARs). Elevated phosphorus concentrations in groundwater have become a global phenomenon, which places enormous pressure on the safe use of water resources and the safety of the aquatic environment. Currently, the prediction of pollutant concentrations in groundwater mainly focuses on nitrate nitrogen, while research on phosphorus prediction is limited. Taking the IARs approximately 8 plateau lakes in the Yunnan-Guizhou Plateau as an example, 570 shallow groundwater samples and 28 predictor variables were collected and measured, and a machine learning approach was used to predict phosphorus concentrations in groundwater. The performance of three machine learning algorithms and different sets of variables for predicting phosphorus concentrations in shallow groundwater was evaluated. The results showed that after all variables were introduced into the model, the R2, RMSE and MAE of support vector machine (SVM), random forest (RF) and neural network (NN) were 0.52–0.60, 0.101–0.108 and 0.074–0.081, respectively. Among them, the SVM model had the best prediction effect. The clay content and water-soluble phosphorus in soil and soluble organic carbon in groundwater had a high contribution to the prediction accuracy of the model. The prediction accuracy of the model with reduced number of variables showed that when the number of variables was equal to 6, the RF model had R2, RMSE and MAE values of 0.53, 0.108 and 0.074, respectively, and the number of variables increased again; there were small changes in R2, RMSE and MAE. Compared with the SVM and NN models, the RF model can achieve higher accuracy by inputting fewer variables.