High-resolution measurement of ammonia emissions from fertilization of vegetable and rice crops in the Pearl River Delta Region, China

Abstract

Loss of ammonia (NH3) as a result of intensive N fertilization, especially due to agronomic practices in South China, is not well characterized. To investigate mechanisms and characteristics of NH3 volatilization after urea application, an on-line monitoring system, with 30-min data resolution, was used to study vegetable and rice fields from January 2009 to September 2010. Ammonia emissions and concurrent meteorological conditions were monitored for up to 20 days after fertilization in 12 experiments. Standard recovery test results indicated that the on-line measurement system was both stable and accurate. The NH3 emission factors (EFs) related to broadcast (soil surface) basal dressing and top dressing to Brassica rapa L. were 23.6% and 21.3%, respectively. The NH3 EFs from holing basal dressing and broadcasting top dressing for lettuce were 17.6% and 24.0%, respectively. The NH3 EFs for early rice in parallel broadcast basal dressing process were 10.7% and 14.2%, while in parallel top dressing process were 24.0% and 22.6%, respectively. The NH3 EFs for late rice were 15.4% and 21.0% in parallel broadcasting basal dressing process, while 13.2% and 17.6% in parallel top dressing process. Emission of NH3 from vegetable and rice fields occurred mainly in the first 2–3 weeks after fertilization. Ammonia emission flux was positively correlated with air temperature and soil temperature in the majority of the experiments. Relationships between NH3 emissions and humidity, soil moisture or wind speed were explored, which were not consistent among all tests. Ammonia emission in vegetable and rice fields was primarily associated with temperature. High-resolution data, such as those gathered in the current investigation, will contribute to a more thorough quantitative understanding of the relationship between fertilizer application, environmental conditions, and NH3 volatilization which, in turn, will improve the accuracy of atmospheric modeling on local, regional and global scales.