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Assessment and driving factor analysis of total nitrogen loads: a case study of counties from 2000 to 2020 in Henan Province, China.
- Source :
-
Stochastic Environmental Research & Risk Assessment . Sep2024, Vol. 38 Issue 9, p3377-3392. 16p. - Publication Year :
- 2024
-
Abstract
- China's unsustainable agricultural production activities have caused severe agricultural non-point source pollution (ANPSP), particularly nitrogen source pollution (NSP), which impacts farmland ecological environments. Understanding NSP is important for managing ANPSP and improving environmental water quality. Thus, inventory analysis methods were used to assess county-level total nitrogen (TN) loads in large-scale agricultural areas, analyze spatial and temporal variations in TN loads, examine the major sources of TN loads and identify the driving factors of DITN using Pearson correlation and random forest (RF) methods. The results showed that (1) TN loads and discharge intensity decreased by 4.59% and 12.7%, respectively, increasing and then decreasing via market regulations, policy incentives, and policy constraints. The eastern and northern Henan Province plain areas were highly discharged. (2) The major pollution sources varied, with the total contributions of mineral fertilizers and livestock and poultry breeding to TN being 73.53% and 81.78%, respectively. Farmland solid waste contributed minimally but increased yearly from 10.84 to 19.74%. (3) The discharge intensity of TN was highly significantly negatively correlated with the urbanization rate, economic development and slope; neither was significantly correlated with arable land. The RF results showed that total mineral fertilizer consumption and total livestock and poultry production were the major factors controlling the NSP in Henan Province. China's agricultural policies have slightly reduced pollutant discharge intensities, but the situation remains grim. This study provides a scientific basis for the development of differentiated TN control measures in Henan Province, which is important for improving pollution prevention and control capabilities. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14363240
- Volume :
- 38
- Issue :
- 9
- Database :
- Academic Search Index
- Journal :
- Stochastic Environmental Research & Risk Assessment
- Publication Type :
- Academic Journal
- Accession number :
- 179357113
- Full Text :
- https://doi.org/10.1007/s00477-024-02752-w