Development of a high-resolution emission inventory of agricultural machinery with a novel methodology: A case study for Yangtze River Delta region

Recent increased use of agricultural machines elevated the atmospheric pollutant emissions in the Yangtze River Delta (YRD) region in eastern China. Given the potentially large environmental and health impacts in busy seasons with enhanced machinery usage, it is important to accurately estimate the magnitude, spatial and temporal distributions of the emissions. We developed a novel method to estimate the real-world in-use agricultural machinery emissions, by combining satellite data, land and soil information, and in-house investigation. The machinery usage was determined based on the spatial distribution, growing and rotation pattern of the crops. The varied requirement of machinery power by heterogeneous soil texture, which was ignored in the previous studies, was considered in our methodology. The spatiotemporal pattern of machinery usage was determined based on the explored quantitative correlation between the local agricultural activity duration and the geographic location of the activity. A grid-based (30 x 30 m) inventory with daily emissions was then obtained, achieving significant improvement on spatial and temporal resolution. It substantially diminished the bias of previous inventories based on the machinery population or power installation census data. The emissions of NOX, PM2.5, CO and THC were estimated at 36300, 2000, 36900 and 8430 metric tons in YRD, with the majority contribution from Anhui and Jiangsu. Ten cities locating in northern and central Anhui and Jiangsu contributed the largest machinery emissions, accounting for 60% of the total emissions in YRD. Harvesting was found to have the largest emissions, followed by tilling and planting. Regarding the crops, the emissions from wheat and rice related machinery usage were the largest. In the busy seasons (spring and autumn), larger daily NOx and PM2.5 emissions were found from machinery than on-road vehicles in 42% of counties in Anhui and Jiangsu, highlighting the necessity of careful strategy making on controls of priority emission source. (C) 2020 Elsevier Ltd. All rights reserved.