基于现象学数据,改进了中国三大主要作物的肥料应用的氨排放清单
Yongqi Zhao1, Baojie Li1, Jinyan Dong1
1Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, Nanjing 210044, China.
The Science of the total environment
|July 1, 2023
概括
这项研究引入了一种使用卫星数据的新方法,用于准确地绘制中国肥料应用中氨 (NH3) 排放的地图. 这有助于更好地了解雾污染源和时间排放模式.
科学领域:
- 大气化学和空气污染.
- 农业排放和环境科学.
- 遥感和地理空间分析.
背景情况:
- 氨 (NH3) 显著影响大气化学,并导致雾污染.
- 现有的NH3排放库存缺乏精确的时间分布数据,导致不确定性.
- 准确的NH3排放清单对于制定有效的污染控制策略至关重要.
研究的目的:
- 开发一种新的方法,用于中国的肥料应用所产生的NH3排放的时间分配.
- 使用综合数据源建立主要作物的高分辨率NH3排放清单.
- 确定与农业实践相关的NH3排放的关键区域和时间模式.
主要方法:
- 综合卫星遥感和地面站现象数据用于时间分配.
- 开发了一套高分辨率 (1/12° × 1/12°) 的数据集,用于中国的肥料应用.
- 根据肥料应用数据,为三个主要作物创建了NH3排放库存.
主要成果:
- 观察到肥料应用的时间变化很大,集中在6月,7月和8月.
- 2019年,中国三大农作物的NH3总排放量为2.73 Tg.
- 北中国平原和中下长江平原被确定为主要的高排放地区;夏季排放在7月达到峰值.
结论:
- 该研究成功地使用遥感现象学数据建立了高分辨率的NH3排放清单,这是一种新的方法.
- 这些发现强调了NH3排放清单的时间和空间准确性对污染控制的重要性.
- 这种方法显著提高了NH3排放库存的准确性,有助于缓解雾污染的努力.
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