Farmland Microhabitat Mediated by a Residual Microplastic Film: Microbial Communities and Function.

How the plastisphere mediated by the residual microplastic film in farmlands affects microhabitat systems is unclear. Here, microbial structure, assembly, and biogeochemical cycling in the plastisphere and soil in 33 typical farmland sites were analyzed by amplicon sequencing of 16S rRNA genes and ITS and metagenome analysis. The results indicated that residual microplastic film was colonized by microbes, forming a unique niche called the plastisphere. Notable differences in the microbial community structure and function were observed between soil and plastisphere. Residual microplastic film altered the microbial symbiosis and assembly processes. Stochastic processes significantly dominated the assembly of the bacterial community in the plastisphere and soil but only in the plastisphere for the fungal community. Deterministic processes significantly dominated the assembly of fungal communities only in soil. Moreover, the plastisphere mediated by the residual microplastic film acted as a preferred vector for pathogens and microorganisms associated with plastic degradation and the nitrogen and sulfur cycle. The abundance of genes associated with denitrification and sulfate reduction activity in the plastisphere was pronouncedly higher than that of soil, which increase the potential risk of nitrogen and sulfur loss. The results will offer a scientific understanding of the harm caused by the residual microplastic film in farmlands.

Uncertainty analysis and economic value prediction of water environmental capacity based on Copula and Bayesian model: A case study of Yitong River, China.

Water environmental capacity (WEC) is an indicator of environment management. The uncertainty analysis of WEC is more closely aligned with the actual conditions of the water body. It is crucial for accurately formulating pollution total emissions control schemes. However, the current WEC uncertainty analysis method ignored the connection between water quality and discharge, and required a large amount of monitoring data. This study analyzed the uncertainty of the WEC and predicted its economic value based on Copula and Bayesian model for the Yitong River in China. The Copula model was employed to calculate joint probabilities of water quality and discharge. And the posterior distribution of WEC with limited data was obtained by the Bayesian formula. The results showed that the WEC-COD in the Yitong River was 9009.67 t/a, while NH3-N had no residual WEC. Wanjinta Highway Bridge-Kaoshan Town reach had the most serious pollution. In order to make it have WEC, the reduction of COD and NH3-N was 5330.47 t and 3017.87 t. The economic value of WEC-COD was 5.97 × 107 CNY, and the treatment cost was 2.04 × 108 CNY to make NH3-N have residual WEC. The economic value distribution of WEC was extremely uneven, which could be utilized by adjusting the sewage outlet. In addition, since the treated water was discharged into the Sihua Bridge-Wanjinta Highway Bridge reach, the WEC-COD and the economic value were 19,488.51 t/a and 8.24 × 107 CNY. Increasing the flow of rivers could effectively improve WEC and economic value. This study provided an evaluation tool for guiding river water environment management.

Evaluation of the water quality monitoring network layout based on driving-pressure-state-response framework and entropy weight TOPSIS model: A case study of Liao River, China.

The establishment of river water quality monitoring network is crucial for watershed protection. However, the evaluation process of monitoring network layout involves significant subjectivity and has not yet to form a complete indicator system. This study constructed an indicator system based on the DPSR (Driving-Pressure-State-Response) framework in the Liao River Basin, China. SWAT model and ArcGIS were used to quantify the indicators. And the entropy weight-TOPSIS method was employed to rank monitoring points. The results showed that pressure and state indicators had a greater impact on the network layout, with the indicator for proportion of land use in residential areas carrying the largest weight of 0.136. It suggested that the risk of river pollution remained high, and the governance strategies needed to be improved. Priority monitoring points were mainly located in the east and middle of the basin, consistent with the distribution of human activities such as urban areas and farmland. In addition, the redundancy of points should be avoided, and evaluation results should be adjusted based on the actual situation. The study provided an evaluation method for the layout of monitoring points.

From field soil sampling to watershed model: Upscaling by integrating information entropy and interpolation method.

Soil property data plays a crucial role in watershed hydrology and non-point source (H/NPS) modeling, but how to improve modeling accuracy with affordable soil samplings and the effects of sampling information on H/NPS modeling remains to be further explored. In this study, the number of sampling points and soil properties were optimized by the information entropy and the spatial interpolation method. Then the sampled properties were parameterized and the effects of different parameterization schemes on H/NPS modeling were tested using the Soil and Water Assessment Tool (SWAT). The results indicated that the required sampling points increased successively for soil bulk density (SOL_BD), soil saturated hydraulic conductivity (SOL_K) and soil available water capacity (SOL_AWC). Compared to the traditional database (Harmonized world soil database), the NSE and R2 performance by new scheme increased by 22.8% and 10.5%, respectively. The entropy-based optimization reduced the sampling points by 13.2%, indicating a more cost-effective scheme. Compared to hydrological simulation, sampled properties showed greater effects on NPS modeling, especially for nitrogen. This proposed method/framework can be generalized to other watersheds by upscaling field soil sampling information to the watershed scale, thus improving H/NPS simulation.

Integrating source apportionment and landscape patterns to capture nutrient variability across a typical urbanized watershed.

Effective integrated watershed management requires models that can characterize the sources and transport processes of pollutants at the watershed with multiple landscape patterns. However, few studies have investigated the influence of landscape spatial configuration on pollutant transport processes. In this study, the SPARROW_TN and SPARROW_TP models were constructed by combining direct pollution source data and landscape pattern data to investigate the source composition and nutrient transport processes and to reveal the influence of landscape patterns on nutrient transport in the urbanized Beiyun River Watershed. The introduction of landscape metrics significantly improved the simulation results of both models, with R2 increasing from 0.89 to 0.85 to 0.93 and 0.91, respectively. Spatial variations existed in TN and TP loads and yields, as well as the source compositions. Pollution hotspots were effectively identified. Source apportionment showed that for the entire watershed, TN came from atmospheric nitrogen deposition (35.25%), untreated sewage (28.23%), agricultural sources (22.60%), and treated sewage (13.92%). In comparison, TP came from untreated sewage (44.94%), agricultural sources (40.22%), and treated sewage (11.51%). In addition, the largest patch index of grassland correlated positively with both TN and TP, whereas the largest shape index of buildup land and interspersion and juxtaposition index of forest were negatively correlated with TN and TP, respectively. The results of this study will provide insight into effective nutrient control measures that consider spatially varying nutrient sources and associated nutrient transport processes.

Influence of landscape patterns on nitrate and particulate organic nitrogen inputs to urban stormwater runoff.

This study investigated the effect of the landscape pattern of permeable/impermeable patches on NO3--N and particulate organic nitrogen (PON) concentrations during stormwater runoff transport and their source contributions. Six landscape pattern indices, namely, mean proximity index (MPI), largest patch index (LPI), mean shape index (MSI), landscape shape index (LSI), connect index (CONNECT), and splitting index (SPLIT), were selected to reflect the fragmentation, complexity, and connectivity of permeable patches in urban catchments. The results show that lower fragmentation, higher complexity, and greater connectivity can reduce NO3--N concentrations in road runoff and drainage flow (i.e., the flow in the stormwater drainage network), as well as PON concentrations in road runoff. Further, the above landscape pattern is effective for mitigating the contributions of NO3--N and PON from road runoff. Low impact development (LID) can be incorporated with the landscape pattern of permeable/impermeable patches to mitigate nitrogen pollution in urban stormwater at the catchment scale by optimizing the spatial arrangement.

New method for scaling nonpoint source pollution by integrating the SWAT model and IHA-based indicators.

Nonpoint source (NPS) pollution shows spatial scaling effects because it is affected by topography, river networks, and many other factors. Currently, the lack of an integrated methodology for quantifying the scaling effect has become a crucial barrier in evaluating NPS pollution. In this study, a new method was proposed for scaling NPS pollution by integrating hydrological model and hydrological alteration indicators. Nested catchments were delineated by eight-direction algorithm, and a semidistributed hydrological model was used to simulate the interannual process within the drainage area and to obtain data series of runoff, sediment, and total phosphorus (TP) at different spatial scales. In addition, the average, the extrema, the change rate and feature variables of each type of indicators were proposed to quantitatively describe the pattern of NPS pollution at different spatial scales. The results show the coefficients of variation (CVs) of most runoff and TP indicators are 0.6-0.8, while those of sediment vary greatly from 0.4 to 1.6 with the threshold of those indicators being 0.33. With the increase in drainage area, the NPS load-related indicators show an increasing trend, while load intensity indicators show a decreasing trend and their changing patterns are affected by the heterogeneity of topographic or hydrological information included. Based on logarithmic variance of the change rate, 825 km2 was identified as the turning point for scaling transformation where the slope changes dramatically. The proposed methodology comprehensively describes features of the NPS scaling effect that could be utilized for targeted monitoring and control of NPS pollution in other watersheds.

Source appointment at large-scale and ungauged catchment using physically-based model and dynamic export coefficient.

Data scarcity has caused enormous problems in non-point pollution predictions and the related source apportionment. In this study, a new framework was developed to undertake the source apportionment at a large-scale and ungauged catchment, by integrating the physically-based model and a surrogate model. The improvements were made, in terms of the application of a physically-based model in an ungauged area for the transfer process and the parametric transplantation process. The new framework was then tested in the Chaohu Lake basin, China. The result suggested that there has been a good match between simulated and observed data. Although the planting industry was the largest emission source with 48.16% of nitrogen (N), itonly contributed 12.61% of N flux to the Chaohu Lake. The ungauged catchments surrounding the Chaohu Lake were identified as non-negligible sources with 8.46% of phosphorus (P) contribution. The rainfall conditions could have great impacts on source apportionment results; e.g., the planting industry contributed from 68.17t of P in dry year to 436.02t in wet year. The new framework could be extended to other large-scale watersheds for source apportionment with data limitations.

Pesticide fate at watershed scale: A new framework integrating multimedia behavior with hydrological processes.

Pesticide pollution has been one serious ecological and environmental issue due to its wide application, high toxicity, and complex environmental behavior. The fugacity model has been widely used to quantify biogeochemical cycles of pesticides due to its clear compartments, simple structure, and easy-accessible data. However, the lack of detailed hydrological processes limits its application for large and heterogeneous watershed. In present study, a new framework was proposed through integration of hydrological processes of SWAT and pesticide fate of fugacity model, and was applied into a typical watershed in the Three Gorges Reservoir Area, China. The results showed that surface runoff, soil erosion, and percolation varied spatiotemporally, which highlighted the importance of considering regional and seasonal heterogeneity of pesticide transport variables in the fugacity model. The amount of dichlorvos (DDV) and chlorpyrifos (CHP) in air, water, soil, and sediment phase were estimated as 0.26 kg, 19.77 kg, 1.06 × 104 kg, and 0.55 kg, respectively. Spatiotemporally, pesticide concentrations in water phase peaked in summer, while the middle and southwest regions of the watershed were identified as the hotspots for pesticide pollution. Compared with the classical model, the new framework provided technical support for the pesticide assessment at watershed scale with heterogeneous hydrological conditions, which can be easily extended to other watersheds, and integrated with other models for comprehensive agricultural management.

Impacts of rapid urbanization on characteristics, sources and variation of fecal coliform at watershed scale.

Microbial pollution is an environmental problem of growing concern for threatening human health. However, the impacts of rapid urbanization on characteristics, sources and variation of fecal coliform (FC) at watershed scale have not been fully explored. In this study, FC characteristics were monitored monthly for 2 years at 21 river sections in an urbanizing watershed, while the sources and continuously annual variation were quantified by integrating two commonly-used models. The results showed that FC varied from 103 to 106 MPN/L, indicating a great spatiotemporal variation at watershed scale. Peak FC occurred in summer and autumn among upstream and downstream areas, respectively. Besides, 65% impermeable surface was identified as the threshold of urban level, beyond which the key FC source would shift from agriculture to urban. It was also found that the changes of urban landscape patterns had poor correlation with annual variation of FC. In comparison, urbanization speed was identified as the major driver with the threshold of 30% for deteriorating FC pollution. The Low Impact Development could result in a 5.13%-97.59% reduction of FC at watershed scale.

Water quality variability affected by landscape patterns and the associated temporal observation scales in the rapidly urbanizing watershed.

Landscape patterns are a major factor affecting river water quality variations. However, the related temporal scaling effects of water quality variations and associated responses to landscape have not been fully explored in rapidly urbanizing watersheds. In this study, we explored the event and seasonal water quality variations by multi-section monitoring, and annual water quality variations using model simulation. Results showed that spatial heterogeneity of river water quality varied from event to annual scales. Rainfall showed greater impacts on event water quality variations (changed by 155.20%-183.70% after the rainfall) than seasonal variations (changed by 35.32%-92.25% from dry to wet season). Nutrients varied more significantly than other pollutants, such as chemical oxygen demand and suspended solids. Compared to annual scale, landscape pattern showed a more significant correlation with event and seasonal variations of water quality. Besides, grassland and forest might change from sink to source landscapes as observation scales changed from season and annum to event. Fragmentation (diversity) metrics showed negative (positive) relationships with event and seasonal water quality variations. However, the impacts of these landscape metrics would become heterogeneous for annual water quality variations. These results highlighted the consideration of multi-temporal studies and provided useful suggestions for urban water quality protection.

Iron-Catalyzed Tertiary Alkylation of Terminal Alkynes with 1,3-Diesters via a Functionalized Alkyl Radical.

Direct oxidative C(sp)-H/C(sp3 )-H cross-coupling offers an ideal and environmentally benign protocol for C(sp)-C(sp3 ) bond formations. As such, reactivity and site-selectivity with respect to C(sp3 )-H bond cleavage have remained a persistent challenge. Herein is reported a simple method for iron-catalyzed/silver-mediated tertiary alkylation of terminal alkynes with readily available and versatile 1,3-dicarbonyl compounds. The reaction is suitable for an array of substrates and proceeds in a highly selective manner even employing alkanes containing other tertiary, benzylic, and C(sp3 )-H bonds alpha to heteroatoms. Elaboration of the products enables the synthesis of a series of versatile building blocks. Control experiments implicate the in situ generation of a tertiary carbon-centered radical species.

Applying copulas to predict the multivariate reduction effect of best management practices.

Best management practices (BMPs) have been widely applied to mitigate non-point source (NPS) pollution in agricultural watersheds. However, a prediction of the multivariate reduction effect of NPS pollutants by BMPs considering its stochastic nature has not been conducted. A new modeling approach combining a hydrological model and copulas was proposed to predict the multivariate effect of BMPs fully considering the stochastic characteristics of BMPs effects and the dependence structure between them. Two levels of reduction effect, i.e., the multi-indicator effect of a single BMP and the combined effect of multiple BMPs, were simulated. The approach was demonstrated in Zhangjiachong watershed, a typical small watershed in the Three Gorges Reservoir area, China. Results show that copulas can effectively simulate the dependence between the univariate effects of BMPs. The approach can accurately predict the probability to achieve the reduction objective for multiple pollutants and multiple BMPs in a watershed. It provides a stochastic way to predict the multivariate effect of BMPs and has great potential to be widely applied in BMPs related decision making.

Tracking faecal microorganisms using the qPCR method in a typical urban catchment in China.

Faecal microorganisms represent a key threat to human health. Potential origins of faecal microbial contamination in a typical urban-representative micro-scale were evaluated. The quantitative polymerase chain reaction (qPCR) method was used in this study. The Bacteroidetes is selected as the indicative microorganism in runoff samples that are collected during four representative stormwater events in north China. The principal component analysis (PCA) method indicated the distribution feature of the environmental factors. The largest contributor is dog, followed by bird and human to the faecal pollution in stormwater runoff. The output of human and dog faecal pollutants in response to the first flush effect of nonpoint source pollution while the transmit time of bird faecal pollutant is relatively longer. In addition, the number of antecedent drying days represents the key factor for dog faecal pollution, while human faecal pollution is impacted by more factors. The results of this study will provide sound evidence for the tracking and management of nonpoint source faecal pollution in urban catchment areas.

Risk assessment of soil heavy metals associated with land use variations in the riparian zones of a typical urban river gradient.

Urbanization-induced land use changes in riparian area alter soil and water regimes in complex ways, which may also affect the migration and transformation of soil heavy metals and increase the risk of release. In this study, soil samples from the riparian zone of Beiyun River, which located in the rapidly urbanized Beijing metropolis, were collected and analyzed for heavy metals (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn). Then their zoning distribution pattern along river (section 1 to section 4 from upper to low reaches) and the correlation of heavy metals between riparian soils and riverine sediments were investigated. Results showed that the average soil heavy metal concentrations of Cd, Cr, Cu and Zn in riparian zone were approximately 2.2, 1.7, 1.9 and 2.0 times higher than the background values. Sectionally, the concentrations of Cd, Ni, Pb and Zn displayed a decreasing order with section 2 > section 3 > section 4 > section 1, while the highest values of Cr and Cu were found in section 3. The concentrations of all heavy metals except Cr in artificial garden land were higher than those in other land use types, and the concentrations of Cr among five land use types were in the order of grass land > farmland > artificial garden land > forest land > forest-grass land. Generally, most of the heavy metals in the riverine sediments had higher contents than those in riparian zones, especially Cu and Zn. There was a decreasing order for the average geo-accumulation index (Igeo) of measured heavy metals in the soils of riparian zone: Zn (0.15) > Cr (0.08) > Cu (0.07) > Cd (-0.08) > As (-0.57) > Pb (-0.67) > Mn (-0.75) > Ni (-0.86), whereas they had different "high-low" orders in different land use types. The Igeo index indicated most regions of riparian zone were moderately polluted with Cd, Cr, Cu and Zn, especially in grass land and forest land. Also, Cd, Cr and Zn in riparian zone have positive relationships with the concentrations in riverine sediments. Health risk assessment showed that the contribution of ingestion HQ to HI was the highest among the three exposure pathways (ingestion, inhalation and dermal contact), and children had higher non-carcinogenic risk and carcinogenic risk index than adult. Our findings suggest that land use and soil in riparian zone should be protected and managed scientifically to control the riverine pollution and ensure human health.

Is returning farmland to forest an effective measure to reduce phosphorus delivery across distinct spatial scales?

As one typical land use change, the mechanism of returning farmland to forests (RFF) on nonpoint source pollution (NPS) is not clear, especially at multiple spatial scales. In this study, by using the Soil and Water Assessment Tool (SWAT), the changes in several flow-related and NPS-related indicators across several nested catchments were quantified and compared in the Three Gorges Reservoir Region, China. The results indicated that RFF could reduce the total flow and total phosphorus (TP), which are higher in the dry season (41% and 79%, respectively) than in the wet season (21% and 47%, respectively) at the watershed with a total area of 2423.74 km2. In comparison, RFF has a larger impact on the baseflow index during the wet season (367.02%) than during the dry season (166.54%). The results also indicated that a spatial scaling effect did exist, while the reduction in TP increased from 24.57% to 48.46% as the drainage area increased from 65.92 km2 to 2104.35 km2. Specific thresholds of RFF efficiency were also observed (approximately 2000 km2 for the study area). It is suggested that other source control measures could supplement RFF by stabilizing the efficiency of RFF across different spatial scales. The results of this study could provide valuable suggestions for land use development and water quality protection, especially for large, complex watersheds.

Quantifying effects of conservation practices on non-point source pollution in the Miyun Reservoir Watershed, China.

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.

Scaling Effects of Elevation Data on Urban Nonpoint Source Pollution Simulations.

The scale effects of digital elevation models (DEM) on hydrology and nonpoint source (NPS) pollution simulations have been widely reported for natural watersheds but seldom studied for urban catchments. In this study, the scale effect of DEM data on the rainfall-runoff and NPS pollution was studied in a typical urban catchment in China. Models were constructed based on the DEM data of nine different resolutions. The conventional model performance indicators and the information entropy method were applied together to evaluate the scale effects. Based on the results, scaling effects and a resolution threshold of DEM data exist for urban NPS pollution simulations. Compared with natural watersheds, the urban NPS pollution simulations were primarily affected by the local terrain due to the overall flat terrain and dense sewer inlet distribution. The overland process simulation responded more sensitively than the catchment outlet, showing prolonged times of concentration for impervious areas with decreasing DEM resolution. The diverse spatial distributions and accumulation magnitudes of pollutants could lead to different simulation responses to scaling effects. This paper provides information about the specific characteristics of the scale effects of DEM data in a typical urban catchment, and these results can be extrapolated to other similar catchments as a reference for data collection.

Spatial Distribution of Metals and Associated Risks in Surface Sediments Along a Typical Urban River Gradient in the Beijing Region.

Surface sediments from Beiyun River located in the rapidly urbanized Beijing metropolis were collected and analyzed for heavy metals (As, Cd, Cr, Cu, Mn, Ni, Pb, and Zn) to investigate their spatial distribution pattern, ecotoxicology and source identification. Results indicated the average heavy metal concentrations of Cd, Cr, Cu, Pb, and Zn were approximately 4, 2, 3, 2, and 4 times higher than their background values. Spatially, we found the concentrations of heavy metals made significant change in four sections along urbanized river gradients. The contents in midstream of urban region and farmland region (section 2 and section 3) were greater than those in upstream (section 1) and downstream (section 4). However, one-way analysis of variance for spatial analysis suggested there were no significant differences between mainstream and tributaries. The geo-accumulation index (I geo) used to assess the sediment quality exhibited there was a decreasing order for the average I geo of measured heavy metals: Zn (0.82) > Cd (0.53) > Cu (0.50) > Cr (- 0.08) > Pb (- 0.45) > Ni (- 0.96) > Mn (- 0.97) > As (- 1.01), whereas they had different "high-low" orders at different sampling transects. Ecological risk index values showed that section 2 and section 3 revealed a high and moderate ecological risk, respectively. Furthermore, principal component analysis indicated the first principle component explained 64.73% of total variance with the main pollutants of As, Cr, Ni, Zn, and Cu which were probably controlled by the mixed sources covering natural factors and anthropogenic input.

Biological nitrogen removal using soil columns for the reuse of reclaimed water: Performance and microbial community analysis.

The main aim of this study was to remove nitrogen compounds from reclaimed water and reuse the water in semi-arid riverine lake systems. In order to assess the nitrogen removal efficiencies in different natural environments, laboratory scale column experiments were performed using sterilized soil (SS), silty clay (SC), soil with submerged plant (SSP) and biochar amendment soil (BCS). The initial concentration of NO3--N and the flow rate was maintained constant at 15 mg L-1 and 0.6 ±â€¯0.1 m d-1, respectively. Among the tested columns, both SSP and BCS were able to achieve NO3--N levels <0.2 mg L-1 in the treated reclaimed water. The results from bacterial community structure analysis, using 454 pyrosequencing of 16s rRNA genes, showed that the dominant denitrifier was Bacillus at the genera level.