• Energy Research

Abstract Reliable quantification of nitrous oxide emission is a key to assessing efficiency of use and environmental impacts of N fertilizers in crop production. In this study, N2O emission and yield were quantified with a database of 853 field measurements in 104 reported studies and a regression model was fitted to the associated environmental attributes and management practices from China’s croplands. The fitted emission model explained 48% of the variance in N2O emissions as a function of fertilizer rate, crop type, temperature, soil clay content, and the interaction between N rate and fertilizer type. With all other variables fixed, N2O emissions were lower with rice than with legumes and then other upland crops, lower with organic fertilizers than with mineral fertilizers. We used the subset of the dataset for rice - covering a full range of different typical water regimes, and estimated emissions from China’s rice cultivation to be 31.1 Gg N2O-N per year. The fitted yield model explained 35% of the variance in crop yield as a function of fertilizer rate, temperature, crop type, and soil clay content. Finally, the empirical models for N2O emission and crop yield were coupled to explore the optimum N rates (N rate with minimum N2O emission per unit yield) for combinations of crop and fertilizer types. Consequently, the optimum N application rate ranged between 100 kg N ha−1 and 190 kg N ha−1 respectively with organic and mineral fertilizers, and different crop types. This study therefore improved on existing empirical methods to estimate N2O emissions from China’s croplands and suggests how N rate may be optimized for different crops, fertilizers and site conditions.

Abstract Reliable quantification of nitrous oxide emission is a key to assessing efficiency of use and environmental impacts of N fertilizers in crop production. In this study, N2O emission and yield were quantified with a database of 853 field measurements in 104 reported studies and a regression model was fitted to the associated environmental attributes and management practices from China’s croplands. The fitted emission model explained 48% of the variance in N2O emissions as a function of fertilizer rate, crop type, temperature, soil clay content, and the interaction between N rate and fertilizer type. With all other variables fixed, N2O emissions were lower with rice than with legumes and then other upland crops, lower with organic fertilizers than with mineral fertilizers. We used the subset of the dataset for rice - covering a full range of different typical water regimes, and estimated emissions from China’s rice cultivation to be 31.1 Gg N2O-N per year. The fitted yield model explained 35% of the variance in crop yield as a function of fertilizer rate, temperature, crop type, and soil clay content. Finally, the empirical models for N2O emission and crop yield were coupled to explore the optimum N rates (N rate with minimum N2O emission per unit yield) for combinations of crop and fertilizer types. Consequently, the optimum N application rate ranged between 100 kg N ha−1 and 190 kg N ha−1 respectively with organic and mineral fertilizers, and different crop types. This study therefore improved on existing empirical methods to estimate N2O emissions from China’s croplands and suggests how N rate may be optimized for different crops, fertilizers and site conditions.

AbstractThe regulation of soil water retention by biochar amendment has been concerned especially in cropland ecosystem. However, the quantification of biochar's effects on soil hydrological properties and crop water use efficiency (WUE) is still limited, and the factors driving the biochar effect need to be investigated. Based on a database with 681 observations, meta‐analysis and structural equation model (SEM) were employed to reveal how biochar amendment affects water supply capacity and WUE. The results showed that biochar application increased available water content (AWC) and WUE by 26.8% and 4.7% on average, respectively. According to the SEM of AWC (R2 = 0.70–0.96), the increase of soil organic carbon (+36.1%) by biochar application can not only directly improve AWC but also indirectly improve AWC by affecting permanent wilting point (−1.0%) and mean weight diameter (+11.1%). The SEM of WUE (R2 = 0.74) indicated that soil moisture and porosity were increased by 10.8% and 7.0% under biochar amendment, which was the reason why biochar improved WUE. This study emphasized that biochar can improve soil hydrology and crop yield by increasing soil water supply conditions. And a rational rate of biochar is the precondition to obtaining the benefits of soil hydrology, otherwise, the excessive use of biochar may lead to the decline of WUE.

AbstractThe regulation of soil water retention by biochar amendment has been concerned especially in cropland ecosystem. However, the quantification of biochar's effects on soil hydrological properties and crop water use efficiency (WUE) is still limited, and the factors driving the biochar effect need to be investigated. Based on a database with 681 observations, meta‐analysis and structural equation model (SEM) were employed to reveal how biochar amendment affects water supply capacity and WUE. The results showed that biochar application increased available water content (AWC) and WUE by 26.8% and 4.7% on average, respectively. According to the SEM of AWC (R2 = 0.70–0.96), the increase of soil organic carbon (+36.1%) by biochar application can not only directly improve AWC but also indirectly improve AWC by affecting permanent wilting point (−1.0%) and mean weight diameter (+11.1%). The SEM of WUE (R2 = 0.74) indicated that soil moisture and porosity were increased by 10.8% and 7.0% under biochar amendment, which was the reason why biochar improved WUE. This study emphasized that biochar can improve soil hydrology and crop yield by increasing soil water supply conditions. And a rational rate of biochar is the precondition to obtaining the benefits of soil hydrology, otherwise, the excessive use of biochar may lead to the decline of WUE.

AbstractDespite research into the response of ammonia (NH3) volatilization in farmland to various meteorological factors, the potential impact of future climate change on NH3 volatilization is not fully understood. Based on a database consisting of 1063 observations across China, nonlinear NH3 models considering crop type, meteorological, soil and management variables were established via four machine learning methods, including support vector machine, multi‐layer perceptron, gradient boosting machine and random forest (RF). The RF model had the highest R2 of 0.76 and the lowest RMSE of 0.82 kg NH3‐N ha−1, showing the best simulation capability. Results of model importance indicated that NH3 volatilization was mainly controlled by total input of N fertilizer, followed by meteorological factors, human managements and soil characteristics. The NH3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH3‐N. By 2050, NH3 volatilization will increase by 23.1−32.0% under different climate change scenarios (Representative Concentration Pathways, RCPs), and climate change will have the greatest impact on NH3 volatilization in the Yangtze river agro‐region of China due to high warming effects. However, the potential increase in NH3 volatilization under future climate change can be mitigated by 26.1−47.5% through various N fertilizer management optimization options.

AbstractDespite research into the response of ammonia (NH3) volatilization in farmland to various meteorological factors, the potential impact of future climate change on NH3 volatilization is not fully understood. Based on a database consisting of 1063 observations across China, nonlinear NH3 models considering crop type, meteorological, soil and management variables were established via four machine learning methods, including support vector machine, multi‐layer perceptron, gradient boosting machine and random forest (RF). The RF model had the highest R2 of 0.76 and the lowest RMSE of 0.82 kg NH3‐N ha−1, showing the best simulation capability. Results of model importance indicated that NH3 volatilization was mainly controlled by total input of N fertilizer, followed by meteorological factors, human managements and soil characteristics. The NH3 emissions of China's cereal production (paddy rice, wheat and maize) in 2018 was estimated to be 3.3 Mt NH3‐N. By 2050, NH3 volatilization will increase by 23.1−32.0% under different climate change scenarios (Representative Concentration Pathways, RCPs), and climate change will have the greatest impact on NH3 volatilization in the Yangtze river agro‐region of China due to high warming effects. However, the potential increase in NH3 volatilization under future climate change can be mitigated by 26.1−47.5% through various N fertilizer management optimization options.

Abstract Emissions of greenhouse gases (GHG) from paddy rice are significant, so reducing these emissions has significant potential for climate change mitigation. We investigated alternate wetting and drying (AWD) as part of an integrated management approach to enhance mitigation, together with combinations of mineral nitrogen (N), reduced tillage, a suitable combination of plant residues and well decomposed manure. To quantify GHG emissions, and the potential for mitigation without yield decline, a process-based model, DayCent was used to simulate methane (CH4) and nitrous oxide (N2O) emissions from paddy rice (Oryza sativa L.) in Bangladesh. The four test sites selected were amended with mineral N fertilizer or an organic amendment (rice straw). A good agreement (p

Abstract Emissions of greenhouse gases (GHG) from paddy rice are significant, so reducing these emissions has significant potential for climate change mitigation. We investigated alternate wetting and drying (AWD) as part of an integrated management approach to enhance mitigation, together with combinations of mineral nitrogen (N), reduced tillage, a suitable combination of plant residues and well decomposed manure. To quantify GHG emissions, and the potential for mitigation without yield decline, a process-based model, DayCent was used to simulate methane (CH4) and nitrous oxide (N2O) emissions from paddy rice (Oryza sativa L.) in Bangladesh. The four test sites selected were amended with mineral N fertilizer or an organic amendment (rice straw). A good agreement (p