Coupling of crop and livestock production can reduce the agricultural GHG emission from smallholder farms

Crop-specific embodied greenhouse gas emissions inventory for 28 staple crops in China from 2007 to 2017

Rapid economic development and population growth have driven significant greenhouse gas (GHG) emissions from China's crop farming. Understanding specific features of these emissions is crucial for developing effective mitigation strategies. While existing studies primarily focused on accounting for GHG emissions at the entire crop farming system level, a critical gap exists in systematic measurements at individual crop level. This study addresses this gap by constructing a high-resolution China's provincial crop-specific embodied GHG emission inventory for years 2007, 2010, 2012, 2015, and 2017. The inventory quantifies embodied GHG emissions per unit yield and per unit area for 28 staple crops across 30 Chinese provinces, providing insights into status and structure of emissions across diverse crops and regions. The results demonstrate significant disparities in crop-specific embodied GHG emissions, with grain crops exhibiting higher emissions than cash crops-1.51 times greater per unit area and 0.86 times greater per unit yield on average. This dataset offers information for formulating effective emission mitigation strategies for crop farming in China.

Inequality in agricultural greenhouse gas emissions intensity has risen in rural China from 1993 to 2020

Reducing greenhouse gas (GHG) emissions in crop production while ensuring emission equity is crucial for sustainable agriculture in China, yet long-term large-scale data on GHG emissions intensity (GEI) are limited. Using an extensive dataset based on surveyed farm households (n > 430,000 households) from 1993 to 2020, we reveal that 2015 was a turning point for GEI levels, which dropped 16% in 2020, while inequality-measured as average GHG emissions per unit planted area-increased 13%. The key driving forces behind such trends included farmland input, all other inputs, agricultural labour input and total factor productivity but not capital input. Notably, farmland input and all other inputs contributed to 80% of the inequality, while contribution of total factor productivity gradually declined and was replaced by migration-induced agricultural labour input differences. Reducing GEI levels and guarding against widening inequality require optimizing production factor inputs.

Assessing agricultural greenhouse gas emission mitigation by scaling up farm size: An empirical analysis based on rural household survey data

Agriculture is a major contributor to greenhouse gas (GHG) emissions. Farm size affects agricultural production inputs and thus has impacts on agricultural GHG emissions. However, the effects and mechanisms behind this are still unclear. In this paper, we identified the effects and mechanisms of farm size on agricultural GHG emissions, based on survey data about over 20,000 rural households in China from 2009 to 2016. Firstly, we calculated the agricultural CO2, CH4, and N2O emissions using the life-cycle analysis (LCA). Secondly, the impacts of farm size on GHG emissions intensity were explored with a fixed effect model, based on the long-term rural household survey data. Finally, the mechanisms were tested by the mediation effect model. The results showed that a 1 % increase in farm size, on average, could reduce the GHG emissions intensity of rural households by 0.245 % from 2009 to 2016. The mechanism analysis showed that the larger farm size reduced GHG emissions intensity mainly by reducing the non-fixed input intensity and raising fixed input investment. By identifying the impacts and mechanisms of farm size on agricultural GHG emissions, this paper aims to provide insights for policymakers to achieve China's goal of reaching carbon neutrality by 2060.

Soil amendments reduce CH4 and CO2 but increase N2O and NH3 emissions in saline-alkali paddy fields

Limited research has been conducted on ammonia (NH3) volatilization and greenhouse gases (GHGs) emissions in saline-alkali paddy fields, along with complex interaction involving various genes (16sRNA, amoA, narG, nirK, nosZ, and nifH). This study employed mesocosm-scale experiment to investigate NH3 volatilization and GHGs emissions, focusing on bacterial communities and genic abundance, in saline-alkali paddy fields with desulfurized gypsum (DG) and organic fertilizer (OF) amendments. Compared to the control (CK) treatment, DG and OF treatments reduced methane (CH4) and carbon dioxide (CO2) emissions by 78.05 % and 26.18 %, and 65.84 % and 11.62 %, respectively. However, these treatments increased NH3 volatilization by 26.26 % and 45.23 %, and nitrous oxide (N2O) emission by 41.00 % and 12.31 %. Notably, NH3 volatilization primarily stemmed from ammonia nitrogen (NH4+-N), rather than total nitrogen (TN) in soil and water. N2O was mainly produced from nitrate nitrogen (NO3--N) in soil and water, as well as NH4+-N in water. The increase in NH3 volatilization and N2O emission in DG and OF treatments, was attributed to the reduced competition among bacterial communities, rather than the increased bacterial activity and genic copies. These findings offer valuable insights for managing nutrient loss and gaseous emissions in saline-alkali paddy fields.

Optimization of coupling crop and livestock production system's eco-efficiency in northern China based on a life cycle assessment and data envelopment analysis method

Under the twin pressures of global food security and dual‑carbon strategies, improving farm eco-efficiency is critical for achieving China's goal of a 50 Pg increase in grain production, meeting the ambitious climate mitigation targets set by the Paris Agreement, and meeting seven of the seventeen Sustainable Development Goals (SDGs) set by the United Nations. However, there is limited research on eco-efficiency measures supported by localised fine-scale data and coupling mechanisms for the structure, production process, efficiency improvement, and carbon reduction synergies of integrated farming systems in China. This study used the Life Cycle Assessment (LCA) and Data Envelopment Analysis (DEA) methods to assess eco-efficiency at the farm level in northern China, included in the National Coupling Crop and Livestock Production Pilot Programs, to improve the eco-efficiency of farms to achieve increased production and emission reductions. The results showed that the overall eco-efficiency of farms was in the lower-middle range, with only 20.18 % of the farms having a technical efficiency exceeding 1. Problems included a backward level of pure technical efficiency and a return to scale. Non-integrated farms have the lowest profitability (41.33 %) and the highest carbon emission intensity of 3.03 kg CO2eq/USD. The global warming potential impact of non-integrated farms optimization could be reduced by 25 Pg CO2eq. Implementing the integrated farming mode has a significant advantage in reducing carbon emissions and improving productivity. Overall, farm fodder optimization can be increased by up to 42.41 %. Simultaneously, farms with sufficient farmland are more likely to realise a highly integrated business mode for crop cultivation and livestock breeding. Therefore, constructing a new type of green integrated farming system will help farms achieve increased production and emission reductions, promote the development of sustainable agriculture, and provide a Chinese model for the realisation of global SDGs.