Abstract

Ammonia emission is one of the dominant pathways of nitrogen fertilizer loss from rice fields in China. It is difficult to measure ammonia emissions by high-frequency sampling with the chamber methods widely used in China, which is of great significance for investigating the environmental effects on the ammonia emissions. The chamber methods also can not accurately determine the ammonia emissions. In this study, the backward Lagrangian stochastic dispersion model, with ammonia concentrations continuously measured by the open-path tunable diode laser absorption spectroscopy technique, was used to determine ammonia emissions from a rice field after fertilizer application at excessive (270 kg N ha−1) and appropriate (210 kg N ha−1) rates in the Taihu Lake Region of China. High temporal resolution measurements of ammonia emissions revealed that high intraday fluctuations of ammonia emissions were significantly affected by the meteorological conditions. Multiple regression analysis showed a dominant solar radiation dependence of intraday ammonia emission cycles, especially during the rice panicle formation stage. The NH4+-N concentrations of the surface water of the rice field were found to be the decisive factor that influenced interday dynamics of ammonia emissions. Accurate quantifications of ammonia emissions indicated that the total ammonia losses under appropriate nitrogen application rate were 27.4 kg N ha−1 during the rice tillering stage and 11.2 kg N ha−1 during the panicle formation stage, which were 29.4% and 17.0% less than those under traditional excessive nitrogen application rate used by the local farmers, respectively. The ammonia loss proportions during the rice panicle formation stage were significantly lower than those of the tillering stage, which might be due to different nitrogen application rates and environmental effects during the two stages. This study indicated that the open-path tunable diode laser absorption spectroscopy technique could facilitate the investigation of high temporal resolution dynamic of ammonia emissions from farmland and the environmental influence on the ammonia emissions.

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