Influence of rapid rural-urban population migration on riverine nitrogen pollution: perspective from ammonia-nitrogen

Temporal and spatial changes of water quality in intensively developed urban rivers and water environment improvement: a case study of the Longgang River in Shenzhen, China

The water quality status, spatial and temporal change processes, and water environment improvement process of urban rivers are valuable lessons to be learned under the sustainable development strategy. This study aims to reveal the water environment improvement process of intensively developed urban rivers, elucidate the spatial and temporal distribution characteristics of major pollutants, and provide recommendations for their water environment management. Water quality data from eight monitoring sites (2007-2020) in the Longgang River basin in Shenzhen, China, and comprehensive pollution index method (CPI), modified comprehensive pollution index method (M-CPI), and Pearson correlation analysis method were used for comprehensive analysis. The study shows that TN, TP, NH3-N, and COD have the greatest influence on the water quality of Longgang River, with the average pollution contribution of 53.39%, 14.49%, 11.66%, and 4.92%, in order. In 2015-2020, the water quality of the main stream of the Longgang River in the wet season was worse than that in the dry season, while the water quality of the tributaries Dingshan River and the Huangsha River in the dry season was worse than the wet season. The spatial distribution characteristics based on M-CPI indicate that the water quality of the lower reaches of Longgang River, the tributaries Dingshan River and Huangsha River, is relatively poor. In addition, the water environment improvement process of Longgang River can be divided into 3 stages: engineering stage (2007-2013, rating changed from heavily polluted to basically qualified), bottleneck stage (2013-2017, rating fluctuated slightly above and below basically qualified), and ecological restoration stage (2017-2020, rating reached qualified in 2019).

Identifying surface water and groundwater interactions using multiple experimental methods in the riparian zone of the polluted and disturbed Shaying River, China

Identifying groundwater (GW)-surface water (SW) interactions in riparian zones is important for assessing the transport pathways of pollutants and all potential biochemical processes, particularly in rivers with artificially controlled water levels. In this study, we constructed two monitoring transects along the nitrogen-polluted Shaying River, China. The GW-SW interactions were qualitatively and quantitatively characterized through an intensive 2-y monitoring program. The monitoring indices included water level, hydrochemical parameters, isotopes (δ¹⁸O, δD, and ²²²Rn) and microbial community structures. The results showed that the sluice altered the GW-SW interactions in the riparian zone. A decrease in river level occurs during the flood season owing to sluice regulation, resulting in discharge of riparian GW into the river. The water level, hydrochemistry, isotopes, and microbial community structures in near-river wells were similar to those in the river, indicating mixing of the river water with the riparian GW. As the distance from the river increased, the percentage of river water in the riparian GW decreased, whereas the GW residence time increased. We found that nitrogen may be easily transported through the GW-SW interactions, acting as a sluice regulator. Nitrogen stored in river water may be removed or diluted by mixing GW and rainwater during the flood season. As the residence time of the infiltrated river in the riparian aquifer increased, nitrate removal increased. Identifying the GW-SW interactions is crucial for water resource regulation and for further tracing the transport of contaminants such as nitrogen in the historically polluted Shaying River.

Metagenomic insights into comparative study of nitrogen metabolic potential and microbial community between primitive and urban river sediments

As a result of anthropogenic pollution, the nitrogen nutrients load in urban rivers has increased, potentially raising the risk of river eutrophication. Here, we studied how anthropogenic impacts alter nitrogen metabolism in river sediments by comparing the metagenomic function of microbial communities between relatively primitive and human-disturbed sediments. The contents of organic matter (OM), total nitrogen (TN), NO₃^--N and NO₂^--N were higher in primitive site than in polluted sites, which might be due to vegetation density, sediment type, hydrology, etc. Whereas, NH₄⁺-N content was higher in midstream and downstream, indicating that nitrogen loading increased in the anthropogenic regions and subsequently leading higher NH₄⁺-N. Hierarchical cluster analyses revealed significant changes in the community structure and functional potential between the primitive and human-affected sites. Metagenomic analysis demonstrated that Demequina, Streptomyces, Rubrobacter and Dechloromonas were the predominant denitrifiers. Ardenticatena and Dechloromonas species were the most important contributors to dissimilatory nitrate reduction. Furthermore, anthropogenic pollution significantly increased their abundance, and resulting in a decrease in NO₃^-, NO₂^--N and an increase in NH₄⁺-N contents. Additionally, the SOX metabolism of Dechloromonas and Sulfuritalea may involve in the sulfur-dependent autotrophic denitrification process by coupling the conversion of thiosulfate to sulfate with the reduction of NO₃^--N to N₂. From pristine to anthropogenic pollution sediments, the major nitrifying bacteria harboring Hao transitioned from Nitrospira to Nitrosomonas. This study sheds light on the consequences of anthropogenic activities on nitrogen metabolism in river sediments, allowing for better management of nitrogen pollution and eutrophication in river.

How Do Non-Agricultural Employment and Regional Selection Affect Farmers' Domestic Sewage Discharge Behavior? Empirical Evidence from Rural China

In many countries, along with rising rural labor transfer, the problem of rural domestic sewage discharge is becoming increasingly serious due to labor shortages in the villages. It is urgent to solve the environment pollution and health problems of residents which is caused by the massive discharge of domestic sewage in rural areas. Based on the survey data collected from Nanjing Agricultural University in 2020, this paper employs the ordered probit model and the CMP method, to empirically test the impact of non-agricultural employment and regional choice on farmers' domestic sewage discharge behavior and the moderating effect of environmental cognition and the social network. The results show that: (1) There is a significantly positive correlation between non-agricultural employment and farmers' sewage treatment behavior. (2) Environmental cognition significantly improves the participation of urban non-agricultural employment farmers in sewage treatment, and the social network has a significant role in promoting the adoption of sewage treatment behavior of local non-agricultural employment farmers. (3) Further heterogeneity analysis results show that the inhibitory effect of urban non-agricultural employment on random sewage discharge is more pronounced than that of local non-agricultural employment. Therefore, in order to effectively solve the problem of rural domestic sewage discharge, it is necessary to actively guide the sewage discharge behavior of non-agricultural employment households, strengthen the social network interaction within the village, and increase the publicity for sewage discharge knowledge.

Machine learning-based estimation of riverine nutrient concentrations and associated uncertainties caused by sampling frequencies

Accurate and sufficient water quality data is essential for watershed management and sustainability. Machine learning models have shown great potentials for estimating water quality with the development of online sensors. However, accurate estimation is challenging because of uncertainties related to models used and data input. In this study, random forest (RF), support vector machine (SVM), and back-propagation neural network (BPNN) models are developed with three sampling frequency datasets (i.e., 4-hourly, daily, and weekly) and five conventional indicators (i.e., water temperature (WT), hydrogen ion concentration (pH), electrical conductivity (EC), dissolved oxygen (DO), and turbidity (TUR)) as surrogates to individually estimate riverine total phosphorus (TP), total nitrogen (TN), and ammonia nitrogen (NH₄⁺-N) in a small-scale coastal watershed. The results show that the RF model outperforms the SVM and BPNN machine learning models in terms of estimative performance, which explains much of the variation in TP (79 ± 1.3%), TN (84 ± 0.9%), and NH₄⁺-N (75 ± 1.3%), when using the 4-hourly sampling frequency dataset. The higher sampling frequency would help the RF obtain a significantly better performance for the three nutrient estimation measures (4-hourly > daily > weekly) for R² and NSE values. WT, EC, and TUR were the three key input indicators for nutrient estimations in RF. Our study highlights the importance of high-frequency data as input to machine learning model development. The RF model is shown to be viable for riverine nutrient estimation in small-scale watersheds of important local water security.

Management implications of spatial-temporal variations of net anthropogenic nitrogen inputs (NANI) in the Yellow River Basin

It is an important content of environment management to accurately identify the time change and spatial distribution of net anthropogenic nitrogen inputs (NANI) in the river basin. In order to develop a unified management and diverse control strategy that fits the characteristics of the basin, this study establishes the NANI-S model combining the NANI model with the spatial autocorrelation analysis method, which is a quantification-analysis-control process, and takes the 70 prefecture-cities in the Yellow River Basin (YRB) as the study area. The result shows that (1) the NANI of YRB increased first and then decreased with an average NANI value of 6787.59 kg/(km²·a), showing that the overall N pollution situation of the YRB shows a trend of improvement in nitrogen (N) fertilizer input as the main source, and the average contribution rate was 47.45%. (2) There were obvious spatial differences in the NANI in the YRB because the global Moran's I fluctuated between 0.67 and 0.78. Cities with high NANI clustered in the middle and lower reaches, while low NANI clustered in the upper reaches. (3) Improving fertilizer utilization rate and industrial and domestic sewage treatment capacity was the key point of N control. Based on the results, practical policy recommendations for water pollution management were constructed, which provides a scientific basis for pollution prevention and high-quality development in the basin. In addition, this analysis method can also be applied to other basin N management studies.

Behavioral Variables to Assess the Toxicity of Unionized Ammonia in Aquatic Snails: Integrating Movement and Feeding Parameters

Behavioral endpoints are important parameters to assess the effects of toxicants on aquatic animals. These endpoints are useful in ecotoxicology because several toxicants modify the animal behavior, which may cause adverse effects at higher levels of ecological organization. However, for the development of new bioassays and for including the behavior in ecotoxicological risk assessment, the comparison of sensitivity between different behavioral endpoints is necessary. Additionally, some toxicants remain in aquatic environments for a few hours or days, which may lead to animal recovery after toxicant exposure. Our study aimed to assess the effect of unionized ammonia on the movement and feeding behaviors of the aquatic gastropod Potamopyrgus antipodarum (Tateidae, Mollusca) and its recovery after exposure. Four treatments were used: a control and three nominal concentrations of unionized ammonia (0.25, 0.5 and 1 mg N-NH₃/L). Each treatment was replicated eight times, with six animals in each replicate. Animals were exposed to unionized ammonia for 48 h (exposure period) and, subsequently, to control water for 144 h (post-exposure period). Two movement variables were monitored without food and five feeding behavioral variables were monitored in the presence of food. Some of the feeding behavioral variables showed higher sensitivity (LOEC = 0.25-0.5 mg N-NH₃/L) than the movement behavior variables monitored without food (LOEC = 1 mg N-NH₃/L). After exposure to unionized ammonia, animals showed a recovery of most behavioral endpoints. The inclusion of post-exposure period and feeding behaviors in bioassays may make studies more realistic, which is crucial for a proper ecotoxicological risk assessment.

Influence of Nitrogen Fertilization Rate on Soil Respiration: A Study Using a Rapid Soil Respiration Assay

Efficient nitrogen (N) management is one of the primary objectives of agronomic research as N is expensive and a major environmental pollutant. Soil microbes regulate N cycling and soil respiration (SR) measures soil microbial activity. The Comprehensive Assessment of Soil Health (CASH) soil respiration protocol is a rapid test, and a study was designed to approve this test as a potential tool for corn (Zea mays L.) N management. Five locations were selected around South Dakota (SD) where corn received 0, 45, 90, and 180 kg N ha−1 during summer of 2019. Soil samples were collected before planting and at the V6 corn growth stage to measure SR. We found that N fertilization increased SR and the highest SR was recorded at Ipswich (1.94 mg CO2 g−1) while SR was lowest at Bushnell (1.45 mg CO2 g−1). Higher SR was recorded at the sites where no-till farming was practiced, and soil had higher initial nitrate and organic matter content. SR was weakly correlated with corn grain yield, which indicated a potential area for future research. We concluded that split N application or an additional N application at a later growth stage might boost corn productivity in soil with higher microbial activity.

What Factors Influence Rural-To-Urban Migrant Peasants to Rent out Their Household Farmland? Evidence from China’s Pearl River Delta

With the accommodative policy and rapid urbanization in China, large-scale migration of rural-to-urban peasants seeking nonagricultural employment has occurred. This has led to farmland rental, which is considered an effective means of land arrangement. Multiple variables were selected to examine the influencing factors of land rental for rural–urban peasants in China by using survey data collected in six core cities of the Pearl River Delta and a logistic regression model. This study revealed that benefits, household members, and urban living conditions and urban integration are factors that affect land rental. According to the results, improvements in working conditions, urban social insurance and urban integration, annual gross household income, and secure land ownership can promote land rental, whereas stronger hometown connections and parenting inhibit land rental. Women and youth excluded from China’s previous land allocation hold complex attitudes toward land rental, with age and sex statistically significant variables affecting land rental. We underscore the influence of family members and urban living conditions for land rental, which were ignored in earlier studies, to provide suggestions for future policy development, with an emphasis on the land rental market and redistribution of idle land.

Impact of human activities on phosphorus flows on an early eutrophic plateau: A case study in Southwest China

The net anthropogenic phosphorus inputs (NAPI) model has been used extensively to assess changes in phosphorus (P) inputs and cycling in the environment. However, temporary populations have generally been unconsidered in these assessments. In this study, the NAPI model was used to estimate P loads from the 16 towns and villages in the Erhai Lake Basin (ELB), Southwest China and to evaluate the potential impact from temporary residents (tourism). The results showed that the average value P inputs in the basin (estimated at 2384 kg P km^-2 year^-1) were 5 times the national average level, and that temporary residents contributed 1%. Agriculture accounted for most of the net P, with chemical fertilizers (55% of the inputs) as the main source, followed by food and animal feed. Only 9.54% of the P inputs to the basin were exported. River water quality and NAPI were significantly correlated (P < 0.01). Tourism industry contributes significantly to regional economic growth and prosperity, but its beneficial effects on the economy does not equate with the adverse impact on environment. This study illustrates what is happening in Southwest China and provides scientific evidence that shows we need to find novel ways to reduce nutrients.

Scenario-based pollution discharge simulations and mapping using integrated QUAL2K-GIS

Malaysia is a tropical country that is highly dependent on surface water for its raw water supply. Unfortunately, surface water is vulnerable to pollution, especially in developed and dense urban catchments. Therefore, in this study, a methodology was developed for an extensive temporal water quality index (WQI) and classification analysis, simulations of various pollutant discharge scenarios using QUAL2K software, and maps with NH₃-N as the core pollutant using an integrated QUAL2K-GIS. It was found that most of the water quality stations are categorized as Class III (slightly polluted to polluted). These stations are surrounded by residential areas, industries, workshops, restaurants and wet markets that contribute to the poor water quality levels. Additionally, low WQI values were reported in 2010 owing to development and agricultural activities. However, the WQI values improved during the wet season. High concentrations of NH₃-N were found in the basin, especially during dry weather conditions. Three scenarios were simulated, i.e. 10%, 50% and 70% of pollution discharge into Skudai river using a calibrated and validated QUAL2K model. Model performance was evaluated using the relative percentage difference. An inclusive graph showing the current conditions and pollution reduction scenarios with respect to the distance of Skudai river and its tributaries is developed to determine the WQI classification. Comprehensive water quality maps based on NH₃-N as the core pollutant are developed using integrated QUAL2K-GIS to illustrate the overall condition of the Skudai river. High NH₃-N in the Skudai River affects water treatment plant operations. Pollution control of more than 90% is required to improve the water quality classification to Class II. The methodology and analysis developed in this study can assist various stakeholders and authorities in identifying problematic areas and determining the required percentage of pollution reduction to improve the Skudai River water quality.

The isotopomer ratios of N2O in the Shaying River, the upper Huai River network, Eastern China: The significances of mechanisms and productions of N2O in the heavy ammonia polluted rivers

In order to figure out the effects of nitrogen pollution and dams on N₂O production paths in the river systems, the isotopomer ratios in N₂O, NH₄⁺ and NO₃^-, as well as N₂ concentrations and physico-chemical characteristics of water and sediments from the Shaying River system, which is the biggest tributary and major NH₄⁺ contributor of the Huai River, were analyzed in the years 2015 and 2016. The results showed that the net productions of N₂O (△N₂O) in the river were pretty high, ranging from 12.9 to 440 nmol/L. N₂O exhibited a narrow range in δ¹⁵N^bulk (-0.04 to 13.51‰), nevertheless a wide range in δ¹⁸O (22.54 to 59.90‰). Isotopocule diagram and Pearson correlation analysis indicated that isotopomer ratios of N₂O were significantly affected by the mixing of N₂O from difference production paths, not by N₂O reduction. Relative contributions of nitrification and denitrification to N₂O in the Shaying river system were deduced from the two end-members model. The contribution of nitrification to gross N₂O was 58.5% on average, almost equal to the contribution of denitrification in summer, although denitrification was the dominant N₂O source with average contribution of 75.6% in winter. No significant relationship was found either between △N₂O and NH₄⁺ or between △N₂O and NO₃^- in the Shaying River. Heavy NO₃^- and COD loading reduced nitrification and increased the relative contribution of denitrification to N₂O in winter. Heavy ammonia pollution caused pH values to decrease apparently, from 7.5 ± 0.3 in July to 6.3 ± 0.1 in December, resulting in denitrification being the dominant source to N₂O in winter. Assimilation enhanced by the construction of dams had weakened the contribution of nitrification to N₂O in summer in the Shaying River.

Spatial and temporal risk quotient based river assessment for water resources management

Malaysia depends heavily on rivers as a source for water supply, irrigation, and sustaining the livelihood of local communities. The evolution of land use in urban areas due to rapid development and the continuous problem of illegal discharge have had a serious adverse impact on the health of the country's waterways. Klang River requires extensive rehabilitation and remediation before its water could be utilised for a variety of purposes. A reliable and rigorous remediation work plan is needed to identify the sources and locations of streams that are constantly polluted. This study attempts to investigate the feasibility of utilising a temporal and spatial risk quotient (RQ) based analysis to make an accurate assessment of the current condition of the tributaries in the Klang River catchment area. The study relies on existing data sets on Biochemical Oxygen Demand (BOD), Chemical Oxygen Demand (COD), Total Suspended Solids (TSS), and Ammonia (NH₃) to evaluate the water quality at thirty strategic locations. Analysis of ammonia pollution is not only based on the limit established for river health but was expanded to include the feasibility of using the water for water intake, recreational activities, and sustaining fish population. The temporal health of Klang River was evaluated using the Risk Matrix Approach (RMA) based on the frequency of RQ > 1 and associated colour-coded hazard impacts. By using the developed RMA, the hazard level for each parameter at each location was assessed and individually mapped using Geographic Information System (GIS). The developed risk hazard mapping has high potential as one of the essential tools in making decisions for a cost-effective river restoration and rehabilitation.

Sources and transformations of anthropogenic nitrogen in the highly disturbed Huai River Basin, Eastern China

Due to serious nitrogen pollution in the Huai River, Eastern China, nitrogenous concentrations and dual stable isotopes (δ¹⁵N and δ¹⁸O) were measured to ascertain the sources and transformation of nitrogen in the Shaying River, the largest and most polluted tributary of the Huai River during the summer and winter seasons. Total nitrogen (TN), NO₃^-, and NH₄⁺ were significantly higher in winter, with values of 7.84 ± 3.44 mg L^-1, 2.31 ± 0.81 mg L^-1, and 3.00 ± 2.24 mg L^-1, respectively, while the highest nitrogen compounds occurred in the Jialu River, one of the tributaries of the Shaying River, in both summer and winter. Isotope characteristics of nitrate reveal that manure and sewage were the principal nitrate sources in both summer (62.44 ± 19.66%) and winter (67.33 ± 15.45%), followed by soil organic nitrogen, with 24.94 ± 15.52% in summer and 26.33 ± 9.45% in winter. Values of δ¹⁵N-suspended particulate nitrogen (SPN) ranged from 0.78 to 13.51%, revealing that point source from industrial and domestic sewage accounted for the largest input to SPN at most sites, whereas soil organic nitrogen and agricultural fertilizers were found in the Jialu River in both sampling periods. Point sources from septic/manure and household waste were the main contributors to ammonium in most river water samples in both summer and winter; most wastewater discharged into the river was untreated, which was one of the main reasons for the high level of ammonium in winter. Nitrogen pollution and the dams had an effect on N transformation in the river. Significant assimilation of NH₄⁺ and aerobic denitrification competed for NH₄⁺, resulting in the weakness of nitrification in the summer. Denitrification was also an important process of nitrate removal during the summer, whereas nitrification was a key N transformation process in the river in the winter time. To reduce nitrogen pollution and improve water quality, greater effort should be focused on the management of sources from urban input as well as on the improvement in sewage treatment.