Special Issue "Point-Source and Diffuse Water Pollution"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".

Deadline for manuscript submissions: 31 August 2022 | Viewed by 3401

Special Issue Editors

Dr. Lei Chen
E-Mail Website
Guest Editor
State Key Laboratory of Water Environment, School of Environment, Beijing Normal University, Beijing 100875, China
Interests: simulation and control of non-point-source pollution; water environment simulation and repair
Special Issues, Collections and Topics in MDPI journals
Dr. Hui Xie
E-Mail Website
Guest Editor
Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Interests: catchment hydrology; nonpoint source pollution modeling; water quality target management
Prof. Dr. Lei Wu
E-Mail Website
Guest Editor
College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
Interests: hydrological modeling; agricultural nonpoint source pollution; best management practices; watershed hydrology; ecohydrology; watershed management; soil erosion; soil and water conservation; nutrient loss; sediment transport; water quality; model; surface hydrology; water resources management; environmental impact assessment
Prof. Dr. Liang Zhang
E-Mail Website
Guest Editor
Department of Environment and Disaster, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China
Interests: watershed/non-point source pollution control; environmental monitoring and assessment

Special Issue Information

Dear Colleagues,

With the continuous improvement of point source pollution control, non-point-source pollution has become the main cause of water pollution. Non-point-source pollution has the characteristics of wide distribution, randomness, latency and lag, which leads to difficulties in pollution monitoring, evaluation, and management control. In view of the current problems such as lack of technology for the real-time monitoring of non-point-source pollution, the lag of data collection, and low priority placed on pollution control, a Special Issue on “Point-Source and Diffuse Water Pollution” is being set up to promote the sharing of technology and methods, the discussion of problems, and encourage cooperative scientific research in this field through exchanges.

Dr. Lei Chen
Dr. Hui Xie
Dr. Lei Wu
Prof. Dr. Liang Zhang
Guest Editors

Biography

Dr. Lei Chen has participated in the national 973 Program project, innovative research group projects, and has received support from the National Science Fund for Distinguished Young Scholars, National Natural Science Foundation of China. He has conducted a research project on the public welfare of the environmental protection industry, as well as national water special projects and national or provincial scientific research projects.

 

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • non-point-source pollution
  • diffuse pollution
  • best management practices

Published Papers (5 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Assessment of Diffuse Pollution Loads in Peri-Urban Rivers—Analysis of the Accuracy of Estimation Based on Monthly Monitoring Data
Water 2022, 14(15), 2354; https://doi.org/10.3390/w14152354 - 30 Jul 2022
Viewed by 424
Abstract
Diffuse pollution loads are crucial information for water resource management, and yet field data are often scarce, implying questionable accuracy in load estimates made from low-frequency water quality monitoring. This paper aimed to characterize diffuse pollution in a stream of a mixed-land-cover watershed [...] Read more.
Diffuse pollution loads are crucial information for water resource management, and yet field data are often scarce, implying questionable accuracy in load estimates made from low-frequency water quality monitoring. This paper aimed to characterize diffuse pollution in a stream of a mixed-land-cover watershed with a significant portion of urbanized areas through intensive monitoring and to perform a comparative analysis between the loads estimated by pollutant rating curves obtained by regression and the estimates using monthly water quality data, which is the method currently used. Continuous rainfall and flow monitoring was conducted between 2019 and 2021, and samples were collected during flood events and the dry period for water quality analysis. Flood events were found to induce an increase in suspended solids (TSS) and COD concentrations, while inorganic nitrogen (Inorg-N) concentrations were higher in the dry season. Flood characteristics showed a positive correlation with solids and COD event mean concentrations (EMCs) and negative with Inorg-N EMCs, while rainfall characteristics, such as antecedent dry days and intensity, correlate positively with all these pollutants. The rating curves performed well for total load estimation in low discharge events (R2 and NSE > 0.8), except for total phosphorus (TP) loads. Estimated annual unit loads found for the watershed were 2 ton TSS/ha.year, 300 kg COD/ha.year, 5 kg Inorg-N/ha.year, and 0.5 kg TP/ha.year, showing high pollution generated in the watershed. Finally, a comparison with estimates based on monthly monitoring data indicated that this method is sufficient for accurate nutrient loads, but not for TSS and COD loads, which require continuous monitoring to improve the accuracy of estimation. Full article
(This article belongs to the Special Issue Point-Source and Diffuse Water Pollution)
Show Figures

Figure 1

Article
Cephalexin Adsorption by Acidic Pretreated Jackfruit Adsorbent: A Deep Learning Prediction Model Study
Water 2022, 14(14), 2243; https://doi.org/10.3390/w14142243 - 17 Jul 2022
Viewed by 453
Abstract
Cephalexin (CFX) residues in the environment represent a major threat to human health worldwide. Herein we investigate the use of novel approaches in deep learning in order to understand the mechanisms and optimal conditions for the sorption of cephalexin in water onto an [...] Read more.
Cephalexin (CFX) residues in the environment represent a major threat to human health worldwide. Herein we investigate the use of novel approaches in deep learning in order to understand the mechanisms and optimal conditions for the sorption of cephalexin in water onto an acidic pretreated jackfruit peel adsorbent (APJPA). The interaction between the initial concentration of CFX (10–50 mg/100 mL), APJAP dosage (3–10 mg/100 mL), time (10–60 min), and the pH (4–9), was simulated using the one-factor-at-a-time method. APJPA was characterized by FESEM images showing that APJPA exhibits a smooth surface devoid of pores. FTIR spectra confirmed the presence of -C-O, C–H, C=C, and -COOH bonds within the APJPA. Maximum removal was recorded with 6.5 mg/100 mL of APJAP dosage, pH 6.5, after 35 min and with 25 mg/100 mL of CFX, at which the predicted and actual adsorption were 96.08 and 98.25%, respectively. The simulation results show that the dosage of APJAP exhibits a high degree of influence on the maximum adsorption of CFX removal (100%) between 2 and 8 mg dose/100 mL. The highest adsorption capacity of APJAP was 384.62 mg CFX/g. The simulation for the effect of pH determined that the best pH for the CFX adsorption lies between pH 5 and 8. Full article
(This article belongs to the Special Issue Point-Source and Diffuse Water Pollution)
Show Figures

Figure 1

Article
Enrichment Evaluation of Heavy Metals from Stormwater Runoff to Soil and Shrubs in Bioretention Facilities
Water 2022, 14(4), 638; https://doi.org/10.3390/w14040638 - 18 Feb 2022
Viewed by 606
Abstract
Bioretention facilities with different inflow concentrations, growing media and plants were examined to determine whether the soil in these facilities was polluted with heavy metals and whether runoff had obvious toxic effects on plants. Using Beijing soil background value as the standard, the [...] Read more.
Bioretention facilities with different inflow concentrations, growing media and plants were examined to determine whether the soil in these facilities was polluted with heavy metals and whether runoff had obvious toxic effects on plants. Using Beijing soil background value as the standard, the soils were evaluated by bioaccumulation index and single factor index. The results show that stormwater runoff containing Cu caused slight pollution in soils, and stormwater runoff containing Zn and Pb was not polluted. Nemerow comprehensive index evaluation revealed that the heavy metals content in the facilities containing vermiculite (a yellow or brown mineral found as an alteration product of mica and other minerals, used for insulation or as a moisture-retentive medium for growing plants) and perlite (a form of obsidian characterized by spherulites formed by cracking of the volcanic glass during cooling, used as insulation or in plant growth media) were higher than the standard. High influent concentration caused significantly higher heavy metals content in plants. While Pb accumulation in the two studied plants was the highest, Cu and Zn accumulation, which are essential for plant growth, was relatively low. The contents of the three heavy metals in the studied plants also exceeded their corresponding critical values. Full article
(This article belongs to the Special Issue Point-Source and Diffuse Water Pollution)
Show Figures

Graphical abstract

Article
Nitrogen Transport/Deposition from Paddy Ecosystem and Potential Pollution Risk Period in Southwest China
Water 2022, 14(4), 539; https://doi.org/10.3390/w14040539 - 11 Feb 2022
Cited by 1 | Viewed by 516
Abstract
Nitrogen (N) losses through runoff from cropland and atmospheric deposition contributed by agricultural NH3 volatilization are important contributors to lake eutrophication and receive wide attention. Studies on the N runoff and atmospheric N deposition from the paddy ecosystem and how the agriculture-derived [...] Read more.
Nitrogen (N) losses through runoff from cropland and atmospheric deposition contributed by agricultural NH3 volatilization are important contributors to lake eutrophication and receive wide attention. Studies on the N runoff and atmospheric N deposition from the paddy ecosystem and how the agriculture-derived N deposition was related to NH3 volatilization were conducted in the paddy ecosystem in the Erhai Lake Watershed in southwest China. The critical period (CP) with a relatively high total N (TN) and NH4+-N deposition occurred in the fertilization period and continued one week after the completion of fertilizer application, and the CP period for N loss through surface runoff was one week longer than that for deposition. Especially, the mean depositions of NH4+-N in the CP period were substantially higher than those in the subsequent period (p < 0.01). Moreover, agriculture-derived NH4+ contributed more than 54% of the total NH4+-N deposition in the CP period, being positively related to NH3 volatilization from cropland soil (p < 0.05). The N concentrations were higher in the outlet water of ditches and runoff in May than in other months due to fertilization and irrigation. Therefore, to reduce the agricultural N losses and improve lake water quality, it is important to both reduce agricultural NH4+-N deposition from NH3 volatilization and intercept water flow from the paddy fields into drainage ditches during the CP. Full article
(This article belongs to the Special Issue Point-Source and Diffuse Water Pollution)
Show Figures

Graphical abstract

Article
Development and Assessment of a New Framework for Agricultural Nonpoint Source Pollution Control
Water 2021, 13(22), 3156; https://doi.org/10.3390/w13223156 - 09 Nov 2021
Cited by 1 | Viewed by 573
Abstract
The transport of agricultural nonpoint source (NPS) pollutants in water pathways is affected by various factors such as precipitation, terrain, soil erosion, surface and subsurface flows, soil texture, land management, and vegetation coverage. In this study, based on the transmission mechanism of NPS [...] Read more.
The transport of agricultural nonpoint source (NPS) pollutants in water pathways is affected by various factors such as precipitation, terrain, soil erosion, surface and subsurface flows, soil texture, land management, and vegetation coverage. In this study, based on the transmission mechanism of NPS pollutants, we constructed a five-factor model for predicting the path-through rate of NPS pollutants. The five indices of the hydrological processes, namely the precipitation index (α), terrain index (β), runoff index (TI), subsurface runoff index (LI), and buffer strip retention index (RI), are integrated with the pollution source data, including the rural living, livestock and farmland data, obtained from the national pollution source census. The proposed model was applied to the headwater of the Miyun Reservoir watershed for identifying the areas with high path-through rates of agricultural NPS pollutants. The results demonstrated the following. (1) The simulation accuracy of the model is acceptable in mesoscale watersheds. The total nitrogen (TN) and total phosphorus (TP) agriculture loads were determined as 705.11 t and 3.16 t in 2014, with the relative errors of the simulations being 19.62% and 24.45%, respectively. (2) From the spatial distribution of the agricultural NPS, the TN and TP resource loads were mainly distributed among the upstream of Dage and downstream of Taishitun, as well as the towns of Bakshiying and Gaoling. The major source of TN was found to be farmland, accounting for 47.6%, followed by livestock, accounting for 37.4%. However, the path-through rates of TP were different from those of TN; rural living was the main TP source (65%). (3) The path-through rates of agricultural NPS were the highest for the towns of Wudaoying, Dage, Tuchengzi, Anchungoumen, and Huodoushan, where the path-through rate of TN ranged from 0.17 to 0.26. As for TP, it was highest in Wudaoying, Kulongshan, Dage, and Tuchengzi, with values ranging from 0.012 to 0.019. (4) A comprehensive analysis of the distribution of the NPS pollution load and the path-through rate revealed the towns of Dage, Wudaoying, and Tuchengzi as the critical source areas of agricultural NPS pollutants. Therefore, these towns should be seriously considered for effective watershed management. In addition, compared with field monitoring, the export coefficient model, and the physical-based model, the proposed five-factor model, which is based on the path-through rate and the mechanism of agricultural NPS pollutant transfer, cannot only obtain the spatial distribution characteristics of the path-through rate on a field scale but also be applicable to large-scale watersheds for estimating the path-through rates of NPS pollutants. Full article
(This article belongs to the Special Issue Point-Source and Diffuse Water Pollution)
Show Figures

Figure 1

Back to TopTop