A dynamic ammonia emission model and the online coupling with WRF–Chem (WRF–SoilN–Chem v1.0): development and regional evaluation in China

Abstract

Abstract. The volatilization of ammonia (NH3) from fertilizer application and livestock wastes is an overwhelmingly important pathway of nitrogen losses in agricultural ecosystems and constitutes the largest source of atmospheric NH3. The volatilization of NH3 highly depends on environmental and meteorological conditions, however, this phenomenon is poorly described in current emission inventory and atmospheric models. Here, we develop a dynamic NH3 emission model capable of calculating the NH3 emission rate interactively with temporal- and spatial-varying meteorological and soil conditions. The NH3 flux parameterization relies on several meteorological factors and anthropogenic activity including fertilizer application, livestock waste, traffic, residential, and industrial sectors. The model is then embedded into a regional WRF–Chem model and is evaluated against field measurements of NH3 concentrations, emission flux, and satellite retrievals of column loading. The evaluation shows a substantial improvement in the model performance of NH3 flux and ambient concentration in China. The model represents the spatial and temporal variations of ambient NH3 concentration well, indicating the highest emission in the North China Plain (NCP) and Sichuan Basin, especially during summertime. Compared with normal simulations using fixed emission inventory input, this model features superior capability in simulating NH3 emission flux and concentration during drastic weather changes like frontal activities and precipitation. Such advances in emission quantification also improve the model performance of secondary inorganic aerosol on synoptic scales. While more laboratory and field measurements are still needed for better parameterization of NH3 volatilization, the seamless coupling of soil emission with meteorology provides a better understanding of NH3 emission evolution and its contribution to atmospheric chemistry.

Ammonia Emissions from Cattle Manure under Variable Moisture Exchange between the Manure and the Environment

“…Ammonia (NH 3 ) volatilization from fertilization and animal waste is an extremely important mode of nitrogen loss in agricultural ecosystems and is the largest source of atmospheric NH 3 . The volatilization of NH 3 is highly dependent on environmental and meteorological conditions [43].…”

Safety Assessment of the Ammonia Bunkering Process in the Maritime Sector: A Review

“…Figure 6 presents a computational algorithm and procedure of risk assessment. According to typical studies on the modeling of ammonia leakage and release [64][65][66][67][68][69][70][71][72][73][74][75][76][77], the common algorithmic diagram for the computational analysis of ammonia leakage is shown in Figure 5, and the computational algorithm and procedure are presented in Figure 6. The six steps required to use computational fluid dynamics (CFD) for the modeling and consequence analysis of ammonia leakage or accidents include the following:…”

“…The algorithm in Figure 7 below describes a procedure for risk analysis using riskbased methods similar to those seen in [78][79][80][81][82][83]. According to typical studies on the modeling of ammonia leakage and release [64][65][66][67][68][69][70][71][72][73][74][75][76][77], the common algorithmic diagram for the computational analysis of ammonia leakage is shown in Figure 5, and the computational algorithm and procedure are presented in Figure 6. The six steps required to use computational fluid dynamics (CFD) for the modeling and consequence analysis of ammonia leakage or accidents include the following: (i) Identify the simulation case: This step is to clarify the purpose of the simulation and which leakage/release case will be addressed.…”

Summertime Urban Ammonia Emissions May Be Substantially Underestimated in Beijing, China

“…Research indicates that urban NH 3 concentrations in eastern China are also underestimated, but the magnitude is smaller than in Beijing. 37,38 Research methodologies in this study can be applied to unveil mechanisms of underestimation in other cities. Dense and regular NH 3 monitoring is the basis for comprehensive model evaluation, improved air quality modeling, and subsequent science-informed policymaking with respect to clean air.…”

“…Even for a larger region such as the NCP, studies using different methods disagree on whether NH 3 emissions in the NCP are underestimated or overestimated. 35,36 In addition, previous research reported that model-simulated gaseous NH 3 concentrations were biased low against groundbased or satellite observations in Nanjing and Beijing, 37,38 in California 39−41 and near large source regions across the United States, 42 and in Paris, Mexico City, and Toronto 43 during the warm season. However, few studies have attributed such biases to uncertainties in emissions, chemistry, meteorology, or regional transport quantitatively, especially for China.…”