Preprint Article Version 1 This version is not peer-reviewed

Scenario-Based Modeling of Agricultural Nitrous Oxide Emissions in China

Version 1 : Received: 14 October 2024 / Approved: 15 October 2024 / Online: 15 October 2024 (12:13:57 CEST)

How to cite: Bu, M.; Xi, W.; Wang, Y.; Wang, G. Scenario-Based Modeling of Agricultural Nitrous Oxide Emissions in China. Preprints 2024, 2024101157. https://doi.org/10.20944/preprints202410.1157.v1 Bu, M.; Xi, W.; Wang, Y.; Wang, G. Scenario-Based Modeling of Agricultural Nitrous Oxide Emissions in China. Preprints 2024, 2024101157. https://doi.org/10.20944/preprints202410.1157.v1

Abstract

Agricultural land in China represents a major source of nitrous oxide emissions, and as population growth and technological advancements drive agricultural intensification, these emissions are projected to increase. A thorough understanding of historical trends and future dynamics of these emissions is critical for formulating effective mitigation strategies and advancing progress toward the Sustainable Development Goals. This study quantifies nitrous oxide emissions across 31 provinces in China from 2000 to 2021, employing the IPCC coefficient method alongside China’s provincial greenhouse gas inventory guidelines. The spatiotemporal evolution of emission intensities is examined, with the STIRPAT model employed to assess the influence of population, technological development, economic growth, and energy structure. The findings confirm that agricultural land remains the primary source of nitrous oxide emissions, with significantly higher levels observed in eastern coastal regions compared to western inland areas. Implementing targeted mitigation strategies, such as enhanced agricultural and manure management practices and region-specific interventions, is imperative to effectively curb the rising emission trends.

Keywords

Nitrous oxide from agricultural sources; IPCC coefficient method; Spatiotemporal evolution; Scenario forecasting

Subject

Environmental and Earth Sciences, Environmental Science

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