China’s agricultural non-point source pollution control: Policy logic, spatiotemporal characteristics and trend prediction DOI Creative Commons
Lilin Zou, Yun‐Kuan Liang, Yuanyuan Yang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 23, 2024

Abstract Agricultural non-point source pollution (ANPSP) control is essential for advancing sustainable, low-carbon agricultural development and accelerating the establishment of a robust economy. However, existing research has paid limited attention to policy rationale underlying ANPSP mitigation efforts, with insufficient exploration spatiotemporal characteristics various pollutants across provinces nationwide their projected future trends. This paper comprehensively analyzed aforesaid aspects through theoretical deductions, quantitative assessments, predictive trend modeling. The findings revealed that formulation logic behind China’s followed framework “legislating first, adjusting next, implementing subsequently.” Across different stages, implementation manifested distinct operational modes determining factors, while deviations arose from inducements within political incentives, promotion-based fiscal incentives. From 1978 2022, loads chemical oxygen demand, total nitrogen, phosphorus in China production sector increased overall, though emission intensity gradually decreased; livestock fertilizer application persisted as primary sources ANPSP. status regions demonstrated considerable stability, significant spatial spillover effects wherein adjacent units influenced state units, direction degree these vary. Projections indicate evolutionary trends pollutants. Consequently, direct recommendations include establishing comprehensive framework, regionally differentiated strategies, enhancing dynamic monitoring ANPSP, coordinated measures regions.

Language: Английский

Regional disparities in carbon tax effectiveness: A multi-regional CGE analysis of provincial production and freight emissions in China DOI
Xian Wang,

Junfeng Liu,

Ying Liu

et al.

Environmental Impact Assessment Review, Journal Year: 2025, Volume and Issue: 114, P. 107943 - 107943

Published: April 14, 2025

Language: Английский

Citations

0
China’s agricultural non-point source pollution control: Policy logic, spatiotemporal characteristics and trend prediction DOI Creative Commons
Lilin Zou, Yun‐Kuan Liang, Yuanyuan Yang

et al.

Research Square (Research Square), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 23, 2024

Abstract Agricultural non-point source pollution (ANPSP) control is essential for advancing sustainable, low-carbon agricultural development and accelerating the establishment of a robust economy. However, existing research has paid limited attention to policy rationale underlying ANPSP mitigation efforts, with insufficient exploration spatiotemporal characteristics various pollutants across provinces nationwide their projected future trends. This paper comprehensively analyzed aforesaid aspects through theoretical deductions, quantitative assessments, predictive trend modeling. The findings revealed that formulation logic behind China’s followed framework “legislating first, adjusting next, implementing subsequently.” Across different stages, implementation manifested distinct operational modes determining factors, while deviations arose from inducements within political incentives, promotion-based fiscal incentives. From 1978 2022, loads chemical oxygen demand, total nitrogen, phosphorus in China production sector increased overall, though emission intensity gradually decreased; livestock fertilizer application persisted as primary sources ANPSP. status regions demonstrated considerable stability, significant spatial spillover effects wherein adjacent units influenced state units, direction degree these vary. Projections indicate evolutionary trends pollutants. Consequently, direct recommendations include establishing comprehensive framework, regionally differentiated strategies, enhancing dynamic monitoring ANPSP, coordinated measures regions.

Language: Английский

Citations

0