Dataset Information

A Decreasing Trend of Nitrous Oxide Emissions From California Cropland From 2000 to 2015.

ABSTRACT: Mitigation of greenhouse gas emissions from agriculture requires an understanding of spatial-temporal dynamics of nitrous oxide (N₂O) emissions. Process-based models can quantify N₂O 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 N₂O emissions from California cropland employing a wide range of cropping systems. DNDC simulated direct N₂O 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 N₂O emissions ranged from 3,830 to 7,875 tonnes N₂O-N yr^-1, representing 0.73%-1.21% of the N inputs. N₂O emission rates were higher for hay and field crops and lower for orchard and vineyard. State cropland total N₂O 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 N₂O emissions declined by 47% from 2000 to 2015. Simulations showed N₂O 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 N₂O mitigation and highlight the importance of coupling process-based models with high-resolution data for characterizing the spatial-temporal variability of N₂O emissions in regions with diverse croplands.

SUBMITTER: Deng J

PROVIDER: S-EPMC9285611 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Streams and river networks are increasingly recognized as significant sources for the greenhouse gas nitrous oxide (N2 O). N2 O is a transformation product of nitrogenous compounds in soil, sediment and water. Agricultural areas are considered a particular hotspot for emissions because of the large input of nitrogen (N) fertilizers applied on arable land. However, there is little information on N2 O emissions from forest streams although they constitute a major part of the total stream network globally. Here, we compiled N2 O concentration data from low-order streams (~1,000 observations from 172 stream sites) covering a large geographical gradient in Sweden from the temperate to the boreal zone and representing catchments with various degrees of agriculture and forest coverage. Our results showed that agricultural and forest streams had comparable N2 O concentrations of 1.6 ± 2.1 and 1.3 ± 1.8 µg N/L, respectively (mean ± SD) despite higher total N (TN) concentrations in agricultural streams (1,520 ± 1,640 vs. 780 ± 600 µg N/L). Although clear patterns linking N2 O concentrations and environmental variables were difficult to discern, the percent saturation of N2 O in the streams was positively correlated with stream concentration of TN and negatively correlated with pH. We speculate that the apparent contradiction between lower TN concentration but similar N2 O concentrations in forest streams than in agricultural streams is due to the low pH (<6) in forest soils and streams which affects denitrification and yields higher N2 O emissions. An estimate of the N2 O emission from low-order streams at the national scale revealed that ~1.8 × 109 g N2 O-N are emitted annually in Sweden, with forest streams contributing about 80% of the total stream emission. Hence, our results provide evidence that forest streams can act as substantial N2 O sources in the landscape with 800 × 109 g CO2 -eq emitted annually in Sweden, equivalent to 25% of the total N2 O emissions from the Swedish agricultural sector.

Project description:China is the largest CO2 emitter in the world and announced that carbon peak and neutral targets will be achieved before 2030 and 2060, respectively. A retrospective analysis of past CO2 emissions and their drivers is important for the actions of peaking CO2 emissions before 2030 in China. CO2 emissions from energy use (coal, oil, and natural gas) and cement production from 2000 to 2020 were calculated first, and their drivers were decomposed into economic and population growth, energy intensity, and emission coefficient by logarithmic mean Divisa index (LMDI) analysis in this study. China’s CO2 emissions increased nearly threefold from 3385 in 2000 to 10,788 million tonnes (Mt) in 2020, with a decline from 2013 to 2016. Coal was the major emission sector contributing more than 70% in most years, while natural gas emissions increased nearly 13 times from 53 to 723 Mt in the two decades, although its contribution only accounted for 6.7% in 2020. Economic growth was the major positive driver, while energy intensity reduction was the major negative driver of the emission increments by year and by the Five Year Plan (FYP). Emission coefficient reduction gradually became important due to its negative effect, especially in the 13th FYP, which offset ~ 30% of the emissions induced by economic growth. The projections of CO2 emissions in 2025, 2030, and 2035 could be 11,596 ± 582, 11,774 ± 621, and 11,401 ± 672 Mt, respectively, suggesting that China’s carbon emissions could peak around 2030 with an increment of ~ 1000 Mt on the 2020 levels. Under the sustainable growth of the economy and population, it is possible to reduce the carbon peak value or achieve peak time earlier through the additional reduction of energy intensity and emission coefficient by technological progress and energy alternatives such as non-fossil fuels. Graphical Abstract Supplementary Information The online version contains supplementary material available at 10.1007/s10668-022-02811-8.

Dataset Information

A Decreasing Trend of Nitrous Oxide Emissions From California Cropland From 2000 to 2015.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets