Spatial and temporal variations of nitrogen pollution in Wen-Rui Tang River watershed, Zhejiang, China

New insights into pollution source analysis using receptor models in the upper Yangtze river basin: Effects of land use on source identification and apportionment

To effectively control pollution and improve water quality, it is essential to accurately analyze the potential pollution sources in rivers. The study proposes a hypothesis that land use can influence the identification and apportionment of pollution sources and tested it in two areas with different types of water pollution and land use. The redundancy analysis (RDA) results showed that the response mechanisms of water quality to land use differed among regions. In both regions, the results indicated that the water quality response relationship to land use provided important objective evidence for pollution source identification, and the RDA tool optimized the procedure of source analysis for receptor models. Positive matrix decomposition (PMF) and absolute principal component score-multiple linear regression (APCS-MLR) receptor models identified five and four pollution sources along with their corresponding characteristic parameters. PMF attributed agricultural nonpoint sources (23.8%) and domestic wastewater (32.7%) as the major sources in regions 1 and 2, respectively, while APCS-MLR identified mixed sources in both regions. In terms of model performance parameters, PMF demonstrated better-fit coefficients (R²) than APCS-MLR and had a lower error rate and proportion of unidentified sources. The results show that considering the effect of land use in the source analysis can overcome the subjectivity of the receptor model and improve the accuracy of pollution source identification and apportionment. The results of the study can help managers clarify the priorities of pollution prevention and control, and provide a new methodology for water environment management in similar watersheds.

Influence of a biofilm bioreactor on water quality and microbial communities in a hypereutrophic urban river

Biofilms play an important role in degradation, transformation and assimilation of anthropogenic pollutants in aquatic ecosystems. In this study, we assembled a tubular bioreactor containing a biofilm substrate and aeration device, which was introduced into mesocosms to explore the effects of bioreactor on physicochemical and microbial characteristics of a hypereutrophic urban river. The biofilm bioreactor greatly improved water quality, especially by decreasing dissolved inorganic nitrogen (DIN) concentrations, suggesting that biofilms were the major sites of nitrification and denitrification with an oxygen concentration gradient. The biofilm bioreactor increased the abundance of planktonic bacteria, whereas diversity of the planktonic microbial community decreased. Sequencing revealed that Proteobacteria, Bacteroidetes, Planctomycetes, and Actinobacteria were the four predominant phyla in the planktonic microbial community, and the presence of the biofilm bioreactor increased the relative abundance of Proteobacteria. Variations in microbial communities were most strongly affected by the presence of the biofilm bioreactor, as indicated by principal component analysis (PCA) and redundancy analysis (RDA). This study provides valuable insights into changes in ecological characteristics associated with self-purification processes in hypereutrophic urban rivers, and may be of important for the application of biofilm bioreactor in natural urban river.

Shallow Groundwater Quality and Its Controlling Factors in the Su-Xi-Chang Region, Eastern China

Understanding factors influencing groundwater quality is critical to the development of best management practices at the large watershed scale. In this study, the shallow groundwater (10–20 m depth) in the Su-Xi-Chang region, eastern China, was investigated as part of a monitoring program from 2007 to 2008 to analyze the regional groundwater quality as well as the hydrogeochemical processes and their controlling factors. Conventional physicochemical water parameters (pH, turbidity, electrical conductivity, dissolved oxygen, total phosphorus), major cations (Na⁺, Ca²⁺, Mg²⁺ and NH₄⁺) and anions (Cl⁻, NO₃⁻ and SO₄²⁻) were measured. Hydrochemical methods and multivariate statistical methods were applied to analyze the hydrogeochemical signatures, origins, the similarities among the variables and to identify the main pollution sources in the groundwater. The results showed that (1) the concentrations of TDS (224.89–1086.70 mg/L) and turbidity (0.1–18.60 NTU) were higher than the class II groundwater quality standards in China and the WHO drinking water standards, (2) there were extremely high concentrations of ammonia (0.01–32.90 mg/L), with a mean value of 0.72 mg/L and (3) the nitrate concentrations (average value of 22.07 mg/L) exceeded the class III groundwater quality standards. The study also provided evidence that weathering, dissolution of carbonate, halite and silicate and cation exchange were the possible primary hydrogeochemical control mechanisms in the groundwater. The sources of ammonia, total phosphorus, sulfates and nitrates included rock–water interactions and anthropogenic activities. The groundwater administration of pollution sinks and sources, long-term legal frameworks and economic incentives should be improved to optimize watershed scale management in the context of rapid development in China.

Drivers of water pollution and evaluating its ecological stress with special reference to macrovertebrates (fish community structure): a case of Churni River, India

The focus of this study is to measure ecological stress of Churni River based on the estimates of dissolved oxygen (DO), pH, biological oxygen demand (BOD), chemical oxygen demand (COD), nutrients imbalances of dissolved inorganic nitrogen or DIN (NO₃^- N and NO₂^- N) and dissolved inorganic phosphate or DIP (PO₄^3-). The present water quality measured in terms of overall index of pollution (OIP), eutrophication index (EI), organic pollution (OPI) and water pollution indexes for ecological status (WPI) portrays that the river is polluted having a high concentration of BOD, COD, nutrients (DIP and DIN) and a very low concentration of DO. Fish community structure taken as most sensitive indicator of ecological stress of water pollution depicts that out of 44 species, 28 fish species (63.63%) comprising 20.0% planktivore (PL), 9.09% benthic feeder (BE), 18.18% omnivorous (OM) and 15.90% carnivorous (CA) at Majhdia and 21 fish species (47.72%) comprising 18.18% PL, 4.59% BE, 13.63% OM and 11.36% CA at Ranaghat have been disappeared. The present investigation has found that anthropogenic interventions like disposal of industrial effluents and agricultural run-off from on-bed and off bed land use are the main drivers of the pollution. Furthermore, natural forcing in the form of neotectonic movements and monsoon regimes has intensified the problem.

Particle-attached microorganism oxidation of ammonia in a hypereutrophic urban river

To elucidate the importance and mechanisms of particle-attached microorganisms on ammonia oxidation, we conducted a controlled simulation experiment with samples collected from the Shunao River, an ammonia-rich hypereutrophic urban river in eastern China. The effects of particle concentration, ammonia concentration, organic carbon source and concentration, dissolved oxygen concentration, and pH were investigated on ammonia transformation rate (ammonia removal rate and NO₂ ^-  + NO₃ ^- accumulation rate) and abundance of particle-attached ammonia-oxidizing bacteria (AOB) and archaea (AOA). All these factors significantly influenced ammonia transformation rates. Our results provided direct evidence that microorganisms attached on riverine suspended particles were associated with ammonia oxidation. Sequencing revealed that the AOA genus Nitrososphaera, and the AOB genus Nitrosomonas were the most dominant in particle-attached ammonia-oxidizing microbial communities. Further analysis showed that AOB communities had higher species richness and diversity compared with AOA communities. Additionally, AOB amoA genes were ~10-100 times more abundant than AOA amoA genes, and AOB abundance was more strongly correlated with ammonia transformation rates than AOA abundance in most experiments, indicating that particle-attached AOB were more important than AOA in the hypereutrophic urban river. This study adds to our knowledge of particle-attached microorganism oxidation of ammonia.

Spatial Patterns of Urban Wastewater Discharge and Treatment Plants Efficiency in China

With the rapid economic development, water pollution has become a major concern in China. Understanding the spatial variation of urban wastewater discharge and measuring the efficiency of wastewater treatment plants are prerequisites for rationally designing schemes and infrastructures to control water pollution. Based on the input and output urban wastewater treatment data of the 31 provinces of mainland China for the period 2011–2015, the spatial variation of urban water pollution and the efficiency of wastewater treatment plants were measured and mapped. The exploratory spatial data analysis (ESDA) model and super-efficiency data envelopment analysis (DEA) combined Malmquist index were used to achieve this goal. The following insight was obtained from the results. (1) The intensity of urban wastewater discharge increased, and the urban wastewater discharge showed a spatial agglomeration trend for the period 2011 to 2015. (2) The average inefficiency of wastewater treatment plants (WWTPs) for the study period was 39.2%. The plants’ efficiencies worsened from the eastern to western parts of the country. (3) The main reasons for the low efficiency were the lack of technological upgrade and scale-up. The technological upgrade rate was −4.8%, while the scale efficiency increases as a result of scaling up was −0.2%. Therefore, to improve the wastewater treatment efficiency of the country, the provinces should work together to increase capital investment and technological advancement.

Properties of bacterial communities attached to artificial substrates in a hypereutrophic urban river

Bacterial communities of biofilms growing on artificial substrates were examined at two time periods (7 and 14 days) and two locations (lentic and lotic areas) in a hypereutrophic urban river of eastern China. Previous studies in this river network indicated that variations of microbial communities were the major factor affecting the distribution of antibiotic resistant genes highlighting the importance of understanding controls of microbial communities. Bacterial communities associated with biofilms were determined using epifluorescence microscopy and high-throughput sequencing. Results showed that sampling time and site had significant effects on the abundances of surface-associated bacteria. No significant differences were found in the number of surface-associated bacteria between two substrate types (filament vs. slide). Sequencing revealed microbial communities attached to artificial substrates in a hypereutrophic urban river were composed of 80,375 OTUs, and distributed in 47 phyla. Proteobacteria and Cyanobacteria/Chloroplast were the two dominant phyla, followed by Planctomycetes, Actinobacteria, Verrucomicrobia, Firmicutes and Bacteroidetes. Taxonomic composition showed ammonia-oxidizing microorganisms, fecal indicator bacteria and pathogens enriched in attached microbial communities, especially the ammonia-oxidizing Nitrosomonas bacteria. These results indicated that there were significant temporal and intra-river heterogeneity of attached microbial community structure, but no significant difference in community composition was detected between the two substrate types.

Spatiotemporal variability of drinking water quality and the associated health risks in southwestern towns of Ethiopia

The failure to provide safe drinking water services to all people is the greatest development setback of the twenty-first century including Ethiopia. Potential pollutants from various sources are deteriorating drinking water quality in different seasons, and associated health risks were not clearly known. We determined seasonal and spatial variations of urban drinking water characteristics and associated health risks in Agaro, Jimma, and Metu towns, Southwest Ethiopia. Seventy-two samples were collected during dry and rainy seasons of 2014 and 2015. The majority (87.4%) of physicochemical parameters was found within the recommended limits. However, free residual chlorine in Jimma and Agaro town water sources was lower than the recommended limit and negatively correlated with total and fecal coliform counts (r = - 0.585 and - 0.638). Statistically significant differences were observed at pH, turbidity, and total coliform between dry and rainy seasons (p < 0.05). A Kruskal-Wallis H test revealed a statistically significant difference in electrical conductivity, total hardness, fluoride, iron, and fecal coliform across the study towns (p < 0.05). The Agaro town water source was the highest in fluoride concentration (3.15 mg/l). The daily exposure level for high fluoride concentration in Agaro town was estimated between 0.19 and 0.41 mg/kg day, and the average cumulative hazard index of fluoride was > 3.13 for all age groups. Water quality variations were observed in all conventional water treatment systems in the rainy season, and further research should focus on its optimization to safeguard the public.

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R² values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R² ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations.

Integrated Application of Multivariate Statistical Methods to Source Apportionment of Watercourses in the Liao River Basin, Northeast China

Source apportionment of river water pollution is critical in water resource management and aquatic conservation. Comprehensive application of various GIS-based multivariate statistical methods was performed to analyze datasets (2009–2011) on water quality in the Liao River system (China). Cluster analysis (CA) classified the 12 months of the year into three groups (May–October, February–April and November–January) and the 66 sampling sites into three groups (groups A, B and C) based on similarities in water quality characteristics. Discriminant analysis (DA) determined that temperature, dissolved oxygen (DO), pH, chemical oxygen demand (COD_Mn)_, 5-day biochemical oxygen demand (BOD₅), NH₄⁺–N, total phosphorus (TP) and volatile phenols were significant variables affecting temporal variations, with 81.2% correct assignments. Principal component analysis (PCA) and positive matrix factorization (PMF) identified eight potential pollution factors for each part of the data structure, explaining more than 61% of the total variance. Oxygen-consuming organics from cropland and woodland runoff were the main latent pollution factor for group A. For group B, the main pollutants were oxygen-consuming organics, oil, nutrients and fecal matter. For group C, the evaluated pollutants primarily included oxygen-consuming organics, oil and toxic organics.

Comparison of seven water quality assessment methods for the characterization and management of highly impaired river systems

In the context of water resource management and pollution control, the characterization of water quality impairments and identification of dominant pollutants are of critical importance. In this study, water quality impairment was assessed on the basis of 7 hydrochemical variables that were monitored bimonthly at 17 sites in 2010 along the rural-suburban-urban portion of the Wen-Rui Tang River in eastern China. Seven methods were used to assess water quality in the river system. These methods included single-factor assessment, water quality grading, comprehensive pollution index, the Nemerow pollution index, principle component analysis, fuzzy comprehensive evaluation, and comprehensive water quality identification index. Our analysis showed that the comprehensive water quality identification index was the best method for assessing water quality in the Wen-Rui Tang River due to its ability to effectively characterize highly polluted waters with multiple impairments. Furthermore, a guideline for the applications of these methods was presented based on their characteristics and efficacy. Results indicated that the dominant pollutant impairing water quality was total nitrogen comprised mainly of ammonium. The temporal variation of water quality was closely related to precipitation as a result of dilution. The spatial variation of water quality was associated with anthropogenic influences (urban, industrial, and agriculture activities) and water flow direction (downstream segments experiencing cumulative effects of upstream inputs). These findings provide valuable information and guidance for water pollution control and water resource management in highly polluted surface waters with multiple water quality impairments in areas with rapid industrial growth and urbanization.

Evaluation of spatial-temporal variations and trends in surface water quality across a rural-suburban-urban interface

Water quality degradation is often a severe consequence of rapid economic expansion in developing countries. Methods to assess spatial-temporal patterns and trends in water quality are essential for guiding adaptive management efforts aimed at water quality remediation. Temporal and spatial patterns of surface water quality were investigated for 54 monitoring sites in the Wen-Rui Tang River watershed of eastern China to identify such patterns in water quality occurring across a rural-suburban-urban interface. Twenty physical and chemical water quality parameters were analyzed in surface waters collected once every 4-8 weeks from 2000 to 2010. Temporal and spatial variations among water quality parameters were assessed between seasons (wet/dry) and among major land use zones (urban/suburban/rural). Factor analysis was used to identify parameters that were important in assessing seasonal and spatial variations in water quality. Results revealed that parameters related to organic pollutants (dissolved oxygen (DO), chemical oxygen demand (manganese) (COD(Mn)), and 5-day biochemical oxygen demand (BOD₅)), nutrients (ammonia nitrogen (NH₄ ⁺-N), total nitrogen (TN), total phosphorus (TP)), and salt concentration (electrical conductivity (EC)) were the most important parameters contributing to water quality variation. Collectively, they explained 70.9 % of the total variance. A trend study using the seasonal Kendall test revealed reductions in COD(Mn), BOD₅, NH₄ ⁺-N, petrol, V-phen, and EC concentrations over the 11-year study period. Cluster analysis was employed to evaluate variation among 14 sampling sites representative of dominant land use categories and indicated three, three, and four clusters based on organic, nutrient, and salt water quality characteristics, respectively. Factors that are typically responsible for water quality degradation (including population, topography, and land use) showed no strong correlation with water quality trends implying considerable point source inputs in the watershed. The results of this study help inform ongoing water quality remediation efforts by documenting trends in water quality across various land use zones.

Spatial distribution and source apportionment of water pollution in different administrative zones of Wen-Rui-Tang (WRT) river watershed, China

Water quality degradation in river systems has caused great concerns all over the world. Identifying the spatial distribution and sources of water pollutants is the very first step for efficient water quality management. A set of water samples collected bimonthly at 12 monitoring sites in 2009 and 2010 were analyzed to determine the spatial distribution of critical parameters and to apportion the sources of pollutants in Wen-Rui-Tang (WRT) river watershed, near the East China Sea. The 12 monitoring sites were divided into three administrative zones of urban, suburban, and rural zones considering differences in land use and population density. Multivariate statistical methods [one-way analysis of variance, principal component analysis (PCA), and absolute principal component score-multiple linear regression (APCS-MLR) methods] were used to investigate the spatial distribution of water quality and to apportion the pollution sources. Results showed that most water quality parameters had no significant difference between the urban and suburban zones, whereas these two zones showed worse water quality than the rural zone. Based on PCA and APCS-MLR analysis, urban domestic sewage and commercial/service pollution, suburban domestic sewage along with fluorine point source pollution, and agricultural nonpoint source pollution with rural domestic sewage pollution were identified to the main pollution sources in urban, suburban, and rural zones, respectively. Understanding the water pollution characteristics of different administrative zones could put insights into effective water management policy-making especially in the area across various administrative zones.

Centennial-scale analysis of the creation and fate of reactive nitrogen in China (1910-2010)

Human mobilization and use of reactive nitrogen (Nr) has been one of the major aspects of global change over the past century. Nowhere has that change been more dramatic than in China, where annual net Nr creation increased from 9.2 to 56 Tg from 1910 to 2010. Since 1956, anthropogenic Nr creation exceeded natural Nr creation, contributing over 80% of total Nr until 2010. There is great interest and uncertainty in the fate and effects of this Nr in China. Here, a comprehensive inventory of Nr in China shows that Nr (including recycled Nr) has continuously and increasingly accumulated on land (from 17 to 45 Tg), accompanied by increasing transfers to the atmosphere (before deposition; from 7.6 to 20 Tg), inland waters (from 2.7 to 9.6 Tg), and coastal waters (from 4.5 to 7.7 Tg) over the past 30 y. If current trends continue, Nr creation from human activities will increase to 63 Tg by 2050, raising concerns about deleterious environmental consequences for land, air, and water at regional and global scales. Tremendous amounts of Nr have accumulated in plants, soils, and waters in China over the past 30 y, but the retention capacity of the terrestrial landscape seems to be declining. There is a possibility that the negative environmental effects of excessive Nr may accelerate in coming decades, increasing the urgency to alter the trajectory of increasing Nr imbalance. Here, a conceptual framework of the relationships between human drivers and Nr cycling in China is oriented and well-targeted to Chinese abatement strategies for Nr environmental impact.

Optimizing water quality monitoring networks using continuous longitudinal monitoring data: a case study of Wen-Rui Tang River, Wenzhou, China

Identification of representative sampling sites is a critical issue in establishing an effective water quality monitoring program. This is especially important at the urban-agriculture interface where water quality conditions can change rapidly over short distances. The objective of this research was to optimize the spatial allocation of discrete monitoring sites for synoptic water quality monitoring through analysis of continuous longitudinal monitoring data collected by attaching a water quality sonde and GPS to a boat. Sampling was conducted six times from March to October 2009 along a 6.5 km segment of the Wen-Rui Tang River in eastern China that represented an urban-agricultural interface. When travelling at a velocity of ∼2.4 km h(-1), this resulted in water quality measurements at ∼20 m interval. Ammonia nitrogen (NH(4)(+)-N), electrical conductivity (EC), dissolved oxygen (DO), and turbidity data were collected and analyzed using Cluster Analysis (CA) to identify optimal locations for establishment of long-term monitoring sites. The analysis identified two distinct water quality segments for NH(4)(+)-N and EC and three distinct segments for DO and turbidity. According to our research results, the current fixed-location sampling sites should be adjusted to more effectively capture the distinct differences in the spatial distribution of water quality conditions. In addition, this methodology identified river reaches that require more comprehensive study of the factors leading to the changes in water quality within the identified river segment. The study demonstrates that continuous longitudinal monitoring can be a highly effective method for optimizing monitoring site locations for water quality studies.