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Accurate estimations of ammonia (NH 3 ) emissions due to nitrogen (N) fertilization are required to identify efficient mitigation techniques and improve agricultural practices. Process-based models such as Volt'Air can be used for this purpose because they incorporate the effects of several key factors influencing NH 3 volatilization at fine spatio-temporal resolutions. However, these models require a large number of input variables and their implementation on a large scale requires long computation times that may restrict their use by public environmental agencies. In this study, we assess the capabilities of various types of meta-models to emulate the complex process-based Volt'Air for estimating NH 3 emission rates from N fertilizer and manure applications. Meta-models were developed for three types of fertilizer (N solution, cattle farmyard manure, and pig slurry) for four major agricultural French regions (Bretagne, Champagne-Ardenne, Ile-de-France, and Rhône-Alpes) and at the national (France) scale. The meta-models were developed from 106,092 NH 3 emissions simulated by Volt'Air in France. Their performances were evaluated by cross-validation, and the meta-models providing the best approximation of the original model were selected. The results showed that random forest and ordinary linear regression models were more accurate than generalized additive models, partial least squares regressions, and least absolute shrinkage and selection operator regressions. Better approximations of Volt'Air simulations were obtained for cattle farmyard manure (3% < relative root mean square error of prediction (RRMSEP) < 8%) than for pig slurry (17% < RRMSEP < 19%) and N solution (21% < RRMSEP < 40%). The selected meta-models included between 6 and 15 input variables related to weather conditions, soil properties and cultural practices. Because of their simplicity and their short computation time, our meta-models offer a promising alternative to process-based models for NH 3 emission inventories at both regional and national scales. Our approach could be implemented to emulate other process-based models in other countries., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

A need exists to improve the utilization of manure nutrients by minimizing NH(3) emissions from land application of manure. Management strategies to reduce NH(3) emissions are available; however, few have been validated under Canadian conditions. A well tested and accurate simulation model, however, can help overcome this challenge by determining appropriate management strategies for a given set of field conditions. The Volt'Air simulation model was utilized to estimate NH(3) volatilization from manure spreading for various manure spreading considerations under a range of atmospheric conditions typically encountered in eastern Canada. Considerations included: (i) soil liming, (ii) time of day of manure spreading, (iii) rainfall (timing and amount) and (iv) manure incorporation (timing, depth and manure coverage). Results demonstrated that liming to increase soil pH, increased NH(3) emissions by 3.3 kg ha(-1) for each increment of 0.1 pH (up to a 1.5 total increase), over no liming at 34.6 kg ha(-1). For each hour delay in manure spreading past 0800 h, NH(3) losses were reduced by 1.5 kg ha(-1). Rainfall (10mm) at least 20 h after manure application reduced losses, with increased reductions at higher rainfall amounts. Incorporation soon (1h) after application was best for NH(3) mitigation. Increasing the depth of incorporation by 5c m reduced NH(3) emissions by 4.4 kg ha(-1); also increasing manure coverage by incorporation reduced losses by 2 kg ha(-1) for each 10% increase in coverage, compared to surface application at 34.6 kg ha(-1). This investigation using Volt'Air yielded valuable information about simulating manure management strategies and the magnitude of their effects on NH(3) emissions.