Soil nitrogen and phosphorous dynamics by in situ soil experiments along an urban-rural gradient in Shanghai, China

Identifying critical source areas of non-point source pollution to enhance water quality: Integrated SWAT modeling and multi-variable statistical analysis to reveal key variables and thresholds

By integrating soil and water assessment tool (SWAT) modeling and land use and land cover (LULC) based multi-variable statistical analysis, this study aimed to identify driving factors, potential thresholds, and critical source areas (CSAs) to enhance water quality in southern Alabama and northwest Florida's Choctawhatchee Watershed. The results revealed the significance of forest cover and of the lumped developed areas and cultivated crops ("Source Areas") in influencing water quality. The stepwise linear regression analysis based on self-organizing maps (SOMs) showed that a negative correlation between forest percent cover and total nitrogen (TN), organic nitrogen (ORGN), and organic phosphorus (ORGP), highlighting the importance of forests in reducing nutrient loads. Conversely, Source Area percentage was positively correlated with total phosphorus (TP) loads, indicating the influence of human activities on TP levels. The receiver operating characteristic (ROC) curve analysis determined thresholds for forest percentage and Source Area percentage as 37.47 % and 20.26 %, respectively. These thresholds serve as important reference points for identifying CSAs. The CSAs identified based on these thresholds covered a relatively small portion (28 %) but contributed 47 % of TN and 50 % of TP of the whole watershed. The study underscores the importance of considering both physical process-based modeling and multi-variable statistical analysis for a comprehensive understanding of watershed management, i.e., the identification of CSAs and the associated variables and their tipping points to maintain water quality.

Mapping the Spatial Heterogeneity of Anthropogenic Soil Nitrogen Net Replenishment Based on Soil Loss: A Coastal Case in the Yellow River Delta, China

To explore the spatial heterogeneity of nitrogen supply from human activities to soil in coastal areas, we established a soil nitrogen net replenishment index (A-SNNRI). We applied the Revised Universal Soil Loss Equation (RUSLE) model for soil loss risk calculation and geostatistical analysis for process simulation. A case study in the Yellow River Delta (YRD) showed that the A-SNNRI worked well. During the summer crop-growing season, population and land use presented significant influences on the soil total nitrogen (STN) status. Urban villages and arable land both had the largest summary STN and variety. There was a negative correlation between STN change and soil loss. The east coast held both the largest A-SNNRIs and soil loss risks. There were significant positive correlations between A-SNNRIs and population and GDP. Therefore, to control and reduce soil-source nitrogen exports in the YRD, we need to reduce nitrogen emissions from urban villages, agriculture, industry, and aquaculture and determine the main risk locations along the east coast and in the main city.

Urban Metabolism of Food-Sourced Nitrogen among Different Income Households: A Case Study Based on Large Sample Survey in Xiamen City, China

Food consumption is fundamental for urban households if they are to sustain production and daily life. Nitrogen resulting from food consumption has significantly contributed to pollutant emissions in urban ecosystems. Taking Xiamen city, a rapid urbanizing area of southeast China as a case study, we evaluated the food-sourced nitrogen consumption of households based on a large simple onsite questionnaire survey, as well as differences between households in the consumption of plant-based and animal-based foods. A material flow analysis (MFA) was conducted to simulate the urban metabolism of food-sourced nitrogen and environmental emissions among different income groups. The impacts of household attributes, plant-based food consumption, and animal-based food consumption on environmental nitrogen emissions were examined with a structural equation model (SEM). Our results show that the surveyed households' diets were more plant-based and less animal-based. Aquatic products and livestock were the source of 43.7% of food-sourced nitrogen, and 84.5% of the food-sourced nitrogen was discharge into the environment through direct discharge and waste treatment. Soil, water, and air emissions accounted for 62.8%, 30.1%, and 7.1% of the food-sourced nitrogen, respectively. Household income, household size, and household area are all associated with accelerating increases of nitrogen emissions released into the environment, though middle-income group households have the highest food-sourced environmental nitrogen emissions. On this basis, we discuss how to better manage the urban metabolism of food-sourced nitrogen, so as to improve urban household consumption, lower nitrogen emissions, and improve food security.