Open AccessA Decreasing Trend of Nitrous Oxide Emissions From California Cropland From 2000 to 2015
Author(s) -
Deng Jia,
Guo Lei,
Salas William,
Ingraham Pete,
CharrierKlobas Jessica G.,
Frolking Steve,
Li Changsheng
Publication year - 2022
Publication title -
earth's future
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.641
H-Index - 39
ISSN - 2328-4277
DOI - 10.1029/2021ef002526
Subject(s) - nitrous oxide , environmental science , greenhouse gas , atmospheric sciences , geology , chemistry , oceanography , organic chemistry
Mitigation of greenhouse gas emissions from agriculture requires an understanding of spatial‐temporal dynamics of nitrous oxide (N 2 O) emissions. Process‐based models can quantify N 2 O emissions from agricultural soils but have rarely been applied to regions with highly diverse agriculture. In this study, a process‐based biogeochemical model, DeNitrification‐DeComposition (DNDC), was applied to quantify spatial‐temporal dynamics of direct N 2 O emissions from California cropland employing a wide range of cropping systems. DNDC simulated direct N 2 O emissions from nitrogen (N) inputs through applications of synthetic fertilizers and crop residues during 2000–2015 by linking the model with a spatial‐temporal differentiated database containing data on weather, crop areas, soil properties, and management. Simulated direct N 2 O emissions ranged from 3,830 to 7,875 tonnes N 2 O‐N yr −1 , representing 0.73%–1.21% of the N inputs. N 2 O emission rates were higher for hay and field crops and lower for orchard and vineyard. State cropland total N 2 O emissions showed a decreasing trend primarily driven by reductions of cropland area and N inputs, the trend toward growing more orchard, and changes in irrigation. Annual direct N 2 O emissions declined by 47% from 2000 to 2015. Simulations showed N 2 O emission variations could be explained not only by cropland area and N fertilizer inputs but also climate, soil properties, and management besides N fertilization. The detailed spatial‐temporal emission dynamics and driving factors provide knowledge toward effective N 2 O mitigation and highlight the importance of coupling process‐based models with high‐resolution data for characterizing the spatial‐temporal variability of N 2 O emissions in regions with diverse croplands.