Agricultural Greenhouse Gas Research Articles

Engineered microbial consortia for next-generation feedstocks

Addressing urgent environmental challenges, this commentary emphasizes the need for green, bio-based solutions in chemical production from renewable feedstocks. It highlights advanced metabolic engineering of microbial strains and the use of microbial consortia as innovative approaches for efficient resource recovery. These strategies aim to enhance the conversion of diverse renewable feedstocks, including agricultural residues, industrial by-products, and greenhouse gases, into value-added chemicals. This article discusses cutting-edge techniques in renewable feedstock upcycling, utilizing both engineered unicellular and multicellular systems. It advocates a paradigm shift in sustainable biomanufacturing, focusing on transforming renewable resources into value-added products. This approach is crucial for developing a circular bioeconomy, aligning with global efforts to mitigate environmental impacts.

Determinants of greenhouse gas emissions by Brazilian agricultural sector.

The agricultural sector is one of the most polluting economic activities, contributing significantly to greenhouse gas (GHGs) emissions. Brazil is one of the largest agricultural producers worldwide and plays a major role in reducing the environmental impact of this sector. Here, we aimed to determine the impact of the agricultural sector, with special attention to production, prices, and trade openness, on the short- and long-term GHGs emissions of Brazilian agriculture. Employing data from 1974 to 2019, we tested the cointegration of variables and compared the determinants of GHG emissions using Autoregressive Distributed Lag (ARDL) and Vector Error Correction Model (VECM) methods. Our results show a long-term equilibrium trend for Brazilian agricultural GHGs emissions, a result that correlates with emerging environmental compliance, and society demands the adoption of sustainable technologies, processes, and policies. In the short run, both cattle herds and Agricultural Added Value to GDP per capita showed an expected positive and significant contribution to GHGs emissions, while agricultural crop area demonstrated an inverse relationship. The trade openness index confirmed that foreign trade plays an important role in reducing GHGs emissions. The price index is not significant in our models. Both the private and public sectors have important roles in sustainable agriculture, especially in increasing system efficiency through the adoption of management and technologies that reduce GHG emissions levels.

Estimating Nitrous Oxide (N2O) emissions from managed soils at higher spatial resolution in the Republic of Ireland

This paper aims to define a high spatial resolution model for estimating nitrous oxide (N2O) emissions from agricultural soils in Ireland. In 2020, N2O emissions from the management of agricultural soils represented 10% of the total national agricultural Greenhouse Gas (GHG) emissions. The high spatial resolution model employed here takes account of environmental factors that influence N2O emissions at a more disaggregated spatial scale than the Intergovernmental Panel on Climate Change (IPCC) national inventory-reporting framework. Activity data from the EU Farm Accountancy Data Network (for Ireland) is used in conjunction with biophysical and climatic data in a geographic information system (GIS) framework to estimate N2O emissions at a sub-national level. Results indicate that N2O emissions are 5% lower by applying this high spatial resolution modelling approach at the farm level compared to the baseline model (Tier 2). Nevertheless, 25% of the farms in the sample analysed had an overestimation in their N2O emissions of 20%, and another 25% of the farm sample had an average underestimation in their N2O emissions by 19%, a consequence of the variation of environmental factors among farms. Using a data panel regression, results confirm that the environmental factors examined are statistically significant within the model proposed, and with a simulation, we assessed the switching of 20% of CAN fertiliser for protected urea. According to the high spatial model, this mitigation measure can reduce N2O emissions from inorganic fertilisers by up to 15%. However, the reduction is conditioned by local factors and environmental conditions.

Greenhouse Gas Emissions Efficiency in Polish Agriculture

Analysis of the efficiency of greenhouse gas emissions in agriculture is an important part of agricultural and environmental economics research. The theme is extremely important due to the deepening problem of climate change and the simultaneous need to ensure food security. However, counteracting climate change cannot be achieved at the expense of reducing agricultural productivity. Due to the need to study the economic-environmental relationship in agriculture, the main purpose of this study was to assess the changes in the level and structure of agricultural greenhouse gas emissions and to examine the changes in efficiency of agricultural greenhouse gas emissions. The authors also estimated the relative efficiency of emissions, which allowed for comparing the efficiency of emissions between agriculture and other sectors of the national economy. Analyzing the changes in agricultural emissions efficiency, as well as changes in relative efficiency of emissions, is an indirect way of assessing whether the ongoing trends are consistent with the sustainable development concept and if the country is effective enough in mitigating climate change in relation to its economic performance. The research conducted showed that agriculture has a significant share of greenhouse gas emissions among all sectors of the Polish economy. However, greenhouse gas emissions from agriculture decreased by a total of 23.5% in the years studied. The most significant changes occurred in the context of greenhouse gas emissions from intestinal fermentation. The research also shows that the efficiency of emissions from agriculture more than doubled in the years examined. However, it decreased compared to other sectors of the economy in the country. This study was based on emissions data retrieved from National Inventory Reports prepared by the National Center for Emissions Management and on the Agricultural Statistical Yearbooks of the Central Statistical Office. This paper also proposes some examples of measures that could be taken to reduce agricultural emissions. Some of them include reducing food losses, sustainable use of fertilizers, increasing energy efficiency, and greater use of renewable energy.

Grain Production in Turkey and Its Environmental Drivers Using ARDL in the Age of Climate Change

This study aims to evaluate the long-run and causality relationships between the annual grain production (kg per hectare) in Turkey, fertilizer used in agriculture, the number of tractors, agricultural greenhouse gas emissions, and grain production area from 1988 to 2018. The study’s data for the years 1988–2018 were taken from the World Bank and Turkish Statistical Institute (Turkstat) databases. The autoregressive distributed lag bounds (ARDL) test was applied to estimate the cointegration between the variables. The cointegration test results confirmed a long-run relationship between the variables. The short-run estimation revealed that the error correction coefficient was negative and statistically significant. The result obtained for the error correction term estimated that the deviations from the short-run equilibrium would be corrected, and the system would converge to the long-run equilibrium within 1.05 years. Further, the long-run estimation showed that all variables included in the model had a statistically significant effect on the dependent variable. While this relationship was negative for grain production amount and carbon emission, it was positive for fertilizer use and the number of tractors. The grain areas estimated as the dependent variable in the ARDL model were in a feedback relationship with the current production and number of tractors variables, while the fertilizer and carbon emission variables were in a unidirectional causality relationship towards the grain production area. There is a negative relationship between grain production (kg per hectare) and grain production areas (hectares). A 1% increase in grain production leads to a decrease of approximately 0.30% in grain production areas. Agricultural greenhouse gas emissions, another variable that stands out with its negative impact in ARDL long-run estimation results, indicate that product groups produced as an alternative to grain have a higher emission-generating power. The other long-run estimation results reveal that the tractor variable positively affects grain production areas.

Slow-release fertilizer deep placement increased rice yield and reduced the ecological and environmental impact in Southeast China: A life-cycle perspective

An unreasonable application of nitrogen fertilizer leads to increased agricultural greenhouse gas (GHG) emissions and carbon footprint (CF). To solve this issue, slow-release fertilizer and deep placement of nitrogen fertilizer are recommended, and have been proven effective in improving nitrogen utilization efficiency and reducing nitrogen loss. However, the deep placement of fertilizer increases the cost of mechanical fuel and labor, especially in the hilly and mountainous areas of southeast China and the comprehensive effects throughout the life cycle of crop production, including economic benefits, energy flow, and environmental and ecological advantages, resulting from different application strategies for nitrogen fertilizer, are still largely unknown. In this work, a two-year field trial was conducted in Fujian Province, China, from 2021 to 2022. The main objectives of the study were to investigate the yield and GHG emissions resulting from the deep placement of slow-release fertilizer (DSK) and to assess the carbon footprint, energy use efficiency, and net economic and ecological benefits from a life-cycle perspective. The results showed that compared with deep placement of urea (DCK), slow-release fertilizer broadcasting (SK), and the traditional fertilization mode practiced by farmers (CK), the average annual yield of rice under DSK treatment significantly increased by 8.78%, 15.18%, and 23.54% respectively. Compared with CK, the contents of indole-3-acetic acid (IAA) and trans-Zeatin Riboside (t-ZR) under DSK were significantly increased and the dry matter translocation amount, Non-Structural Carbohydrates (NSC) translocation amount and Nitrogen translocation amount were significantly increased by 22.79%, 49.60% and 41.47% respectively. GHG emissions were indirectly reduced by the transport of above-ground substances to grains. The average cumulative CH4 emissions were significantly reduced by 25.34% in the DSK treatment, compared to the CK treatment, primarily as a result of decreased methanogenic gene abundance of mcra gene. Additionally, N2O emissions decreased significantly by 48.97%, compared to the CK, mainly due to a decrease in nirK gene abundance and an increase in nosZ gene abundance in denitrifying bacteria. Furthermore, the carbon footprint of the DSK treatment significantly decreased by 38.74% compared to the CK treatment, while net energy income and net ecological and economic benefits increased by 43.83% and 76.43%, respectively. Comprehensive analysis showed that deep placement of slow-release fertilizer is a sustainable nitrogen fertilizer management mode that helps to balance grain yield, environmental footprint, and economic benefits in southeast China.

Carbon dynamics in agricultural greenhouse gas emissions and removals: a comprehensive review

Carbon dynamics in agricultural greenhouse gas emissions and removals: a comprehensive review

Decomposition of agriculture-related non-CO2 greenhouse gas emissions in Chengdu: 1995–2020

Methane (CH4) and nitrous oxide (N2O) emissions originating from agricultural systems exert a significant influence on climate change. The exploration of potential driving factors and emission trends based on a city is important for policy-makers and land managers, however has been rarely known. We aim to investigate the potential driving factors behind five non-CO2 sources within Chengdu's agricultural sector spanning 1995 to 2020, including rice cultivation (CH4), agricultural land (N2O), manure management (CH4 and N2O), and enteric fermentation (CH4), and project non-carbon dioxide (CO2) greenhouse gas (GHG) emissions in Chengdu's agricultural sector for the period from 2021 to 2035. The logarithmic mean Divisia index (LMDI) decomposition model was adopted to figure out the influencing factors, while Monte Carlo simulation and scenario analysis were applied to predict the agricultural non-CO2 GHG emissions from 2021 to 2035. Results reveal that non-CO2 GHG emissions from Chengdu's agriculture exhibit fluctuations and declines, with N2O emissions from agricultural land being the most substantial source. Driving actors such as emission intensity (EI), agricultural industrial structure (IS), and rural population (RP) contribute to carbon emission reductions, resulting in reductions of 8.10, 4.25, and 0.91 million tons (Mt), respectively. Conversely, the regional economic development level (EDL), and urbanization rate (URB) are the primary drivers behind increased agricultural non-CO2 GHG emissions, leading to emissions of 8.91 and 2.35 Mt, respectively. Ultimately, the predictive analysis demonstrates that, under the technological breakthrough scenario, Chengdu's agricultural non-CO2 GHG emissions are projected to peak in 2025, with an expected value of only 2.28 Mt. This study offered practical guidance for mitigating non-CO2 GHG emissions in city-level agriculture.

The impact of oil palm and paddy production on greenhouse gas (GHG) emissions in Indonesia’s agricultural sector

The most widely produced agricultural commodities in Indonesia are oil palm and paddy crops, which contribute the most to national income in the agricultural sector. On the other hand, in 2020, the agricultural sector contributed 9% to national greenhouse gas (GHG) emissions. This study aims to determine the effect of agricultural crop production, namely oil palm and paddy on GHG emissions in Indonesia’s agricultural sector from 2000-2020. Data for the study were obtained from the Directorate General of Climate Change, the Ministry of Environment and Forestry and BPS-Statistics Indonesia. The GHG effect of agricultural crop production were analyzed using multiple linear regression. The findings showed that the production of oil palm and paddy crops significantly affects the agricultural sector’s GHG emissions. Oil palm and paddy production have a significant level of 5% with a regression coefficients of 0.4958 and 0.0003, respectively. From the findings, it can be implied that an increase in oil palm and paddy production will raise Indonesia’s agricultural sector GHG emissions. The government can draw up regulations related to (1) protecting forest areas and peatlands close to community residential areas so that land conversion does not occur in oil palm plantations and (2) a sustainable agricultural system to increase paddy productivity, hoping that the agricultural sector’s GHG emissions will decrease.

Analyzing long-term dynamics of agricultural greenhouse gas emissions in Austria, 1830–2018

Agriculture is an important contributor to greenhouse gas (GHG) emissions. While the development of agricultural GHG emissions on national and global scales is well studied for the last three to six decades, little is known about their trajectory and drivers over longer periods. In this article, we address this research gap by calculating and analyzing GHG emissions related to agriculture in Austria from 1830 to 2018. We calculate territorial emissions on an annual basis and include all GHG emissions from the processes directly involved in agricultural production. Based on this time series, we quantify the relative importance of major drivers of changes in GHG emissions across time and agricultural product categories, applying a structural decomposition analysis. We find that agricultural GHG emissions in Austria increased by 69 % over the total study period, from 4.6 Mt. CO2e/yr in 1830 to 7.7 Mt. CO2e/yr in 2018. While emissions increased only moderately from 1830 to 1945 (+22 % overall), with strong fluctuations between 1914 and 1945, they doubled from 1945 to 1985. In the most recent period from 1985 to 2018, emissions fell by one third, with decreases leveling off over time. Our decomposition analysis reveals that increases in agricultural production per capita most importantly contributed to the high growth in GHG emissions from 1945 to 1985. Conversely, decreasing emission intensities of products and a more climate friendly product mix were key drivers in the emissions reduction observed after 1985. We also contribute to the discussion around the global warming potential star (GWP*), by calculating GHG emissions based on this alternative metric, and contextualize our data within total socio-economic GHG emission trends. By providing insights into the historical trends and drivers of agricultural GHG emissions, our findings enhance the understanding of their long-term historical dynamics and adds to the knowledge base for future mitigation efforts.

Quantifying the effect of agricultural greenhouse gas emissions, food production index, and land use on cereal production in South Asia

Cereal grains are widely used as staple foods, therefore ensuring a steady supply of food globally requires cereal production, and South Asia contributes significantly to this endeavor. However, the global food system is thought to be responsible for around one-fourth of all greenhouse gas (GHG) emissions, with grain production being a major contributor to this system. With the increasing need for food, especially cereal grains, it is difficult to reduce GHG emissions from food production on limited land. However, the cereal production - land use - agricultural GHG emissions nexus has been disregarded in earlier studies which needs to be identified for the sustainable food production system. Therefore, this research aims to assess the interactions between agricultural GHG emissions, food production index, and land usage on cereal production in South Asia. This study employs the Fully Modified Ordinary Least Square (FMOLS) model as a baseline model for a panel data set of 1990–2020 and further checks the validity via Dynamic Ordinary Least Square (DOLS) and robust least square procedure to tackle the endogeneity, serial correlation, and outlier issues. Findings confirm that growing the food production index and land usage boosts cereal grain production in South Asia, whereas rising agricultural CO2 emissions lessen output in the long run. In this paper, we also deploy Dumitrescu and Hurlin's (2012) panel causality test to prove a dual causal connection between the food production index, land use, and cereal food production. From a policy perspective, the findings indicate the necessity of integrating green agro-technology into land cultivation practices in order to achieve increased grain production and mitigate GHG emissions originating from the agricultural sector.

Agricultural support policies and GHG emissions from agriculture in Latin America: relationships and policy implications for climate change

Domestic support policies for farmers and agriculture, through their price effect, have been deemed potentially environmentally harmful; for example, in developing countries, agricultural prices have been set- below the world market prices, aiming to secure low retail prices for urban consumers. This practice has lowered producer prices, and thereby prevented farmers from adopting ecofriendly production techniques. This study uses policy data —market price support (MPS) and general service support estimates (GSSE) as shares of total support estimate (TSE)— and greenhouse gases (GHG) data for main crops and livestock sectors in 18 Latin-American countries and it applies cluster analysis to construct a typology that highlights patterns between policy incentives for agricultural crops and activities and GHG emissions. The results suggest that an increase in the TSE and/or MPS comprising a large share of the TSE leads to an increase in GHGs. Conversely, GHGs fall when GSSE comprise a larger share of the TSE.

Decarbonization of Agriculture: The Greenhouse Gas Impacts and Economics of Existing and Emerging Climate-Smart Practices.

The worldwide emphasis on reducing greenhouse gas (GHG) emissions has increased focus on the potential to mitigate emissions through climate-smart agricultural practices, including regenerative, digital, and controlled environment farming systems. The effectiveness of these solutions largely depends on their ability to address environmental concerns, generate economic returns, and meet supply chain needs. In this Review, we summarize the state of knowledge on the GHG impacts and profitability of these three existing and emerging farming systems. Although we find potential for CO2 mitigation in all three approaches (depending on site-specific and climatic factors), we point to the greater level of research covering the efficacy of regenerative and digital agriculture in tackling non-CO2 emissions (i.e., N2O and CH4), which account for the majority of agriculture's GHG footprint. Despite this greater research coverage, we still find significant methodological and data limitations in accounting for the major GHG fluxes of these practices, especially the lifetime CH4 footprint of more nascent climate-smart regenerative agriculture practices. Across the approaches explored, uncertainties remain about the overall efficacy and persistence of mitigation-particularly with respect to the offsetting of soil carbon sequestration gains by N2O emissions and the lifecycle emissions of controlled environment agriculture systems compared to traditional systems. We find that the economic feasibility of these practices is also system-specific, although regenerative agriculture is generally the most accessible climate-smart approach. Robust incentives (including carbon credit considerations), investments, and policy changes would make these practices more financially accessible to farmers.

Development of an assessment-based planting structure optimization model for mitigating agricultural greenhouse gas emissions

Optimization of crop structure is an efficient way to reduce greenhouse gas (GHGs) from agriculture production. However, carbon footprint have rarely been incorporated into previous planting structure optimization models due to the challenges of assessing the spatial and temporal distribution of agricultural carbon footprint for multiple crops in irrigated districts. In addition, previous planting structure models suffered from strong subjectivity in objective function determination, and the obtained non-dominated solution set offered difficulties to decision-makers in selecting specific implementation options. To fill such gaps, an integrated accounting-assessment-optimization-decision making (AAODM) approach was proposed, which remedies the shortcomings of previous crop planting structure optimization models in carbon footprint mitigation, and overcomes the subjectivity of objective function determination and the difficulty in selecting specific implementation options. Firstly, life cycle assessment (LCA) method was used to account for the multi-year agricultural carbon footprints of multiple crops in the irrigation district. The optimization objective functions of planting structure optimization models can then be determined based on the assessment method of carbon footprint influencing factors. Next, the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) was used to generate a non-dominated solution set of the optimization model. The optimal planting structure can be finally obtained based on decision making methods by determining the maximum harmonic mean (HM) and knee points (KPs) of the non-dominated solution set. The developed AAODM approach was then applied to a case study of agricultural crop management in Bayan Nur City, China. The results showed that the level of economic development was a key factor influencing the increase in carbon footprint in Bayan Nur City over the past 20 years. The regulation of the level of economic development would significantly influence the agricultural carbon footprint in Bayan Nur City. Moreover, two optimal crop cultivation patterns were provided for decision-makers by selecting solutions from the Pareto front with decision making methods. The comparison results with other methods showed that the solutions obtained by NSGA-II were superior to MOPSO in terms of carbon reduction. The developed AAODM approach for agricultural GHG mitigation could help agricultural production systems in achieving low carbon emissions and high efficiency.

Waterlogging increases greenhouse gas release and decreases yield in winter rapeseed (Brassica napus L.) seedlings

A sustainable future depends on increasing agricultural carbon (C) and nitrogen (N) sequestration. Winter rapeseeds are facing severe yield loss after waterlogging due to the effects of extreme rainfall, especially in the seedling stage, where rainfall is most sensitive. Uncertainty exists over the farming greenhouse gas (GHG) release of rapeseed seedlings following the onset of waterlogging. The effect of waterlogging on GHG release and leaf gas exchange in winter rapeseed was examined in a pot experiment. The experiment included waterlogging treatments lasting 7-day and 21-day and normal irrigation as a control treatment. According to our findings, (1) The ecosystem of rapeseed seedlings released methane (CH4) and nitrous oxide (N2O) in a clear up change that was impacted by ongoing waterlogging. Among them, N2O release had a transient rise during the early stages under the effect of seedling fertilizer. (2) The net photosynthetic rate, transpiration rate, stomatal conductance, plant height, soil moisture, and soil oxidation–reduction potential of rapeseed all significantly decreased due to the ongoing waterlogging. However, rapeseed leaves showed a significant increase in intercellular carbon dioxide (CO2) concentration and leaf chlorophyll content values after waterlogging. Additionally, the findings demonstrated an extremely significant increase in the sustained-flux global warming potential of the sum CO2-eq of CH4 and N2O throughout the entire waterlogging stress period. Therefore, continuous waterlogging can increase C and N release from rapeseed seedlings ecosystem and decrease yield. Therefore, we suggest increasing drainage techniques to decrease the release of agricultural GHGs and promote sustainable crop production.

The potential for mitigating greenhouse gas emissions and minimizing yield losses using the negative pressure irrigation system

Efficient strategies for reducing agricultural greenhouse gas (GHG) emissions without yield penalties are crucial for sustainable agricultural development in the context of population increases and global warming. This study investigates the efficacy of negative pressure irrigation (NPI) in mitigating GHG emissions, as well as its impact on crop yield, global warming potential (GWP), and GHG emission intensity (GHGI), using surface irrigation (CK) as the control. The NPI system operated at three water pressure levels: NPI1 (-2 kPa), NPI2 (-4 kPa), and NPI3 (-6 kPa). The results revealed a notable pattern under NPI: a single peak in GHG emissions that remained consistently, and much lower than CK for the majority of the vegetable season, directly results in the lower cumulative GHG emissions and GWP from NPI than those from CK. Notably, the central region, located near the emitter, exhibited significantly lower GWP compared to the edge region, accompanied by higher yields, leading to a lower GHGI. Based on the findings, the -2 kPa water pressure level demonstrated the optimal performance in sustaining crop yields for Chinese chives while effectively reducing GWP and GHGI. Additionally, regions situated 20 cm on both sides of the emitter under -2 kPa NPI were identified as suitable areas for crop cultivation, offering higher yields and lower GWP and GHGI compared to CK. These results emphasize the win-win situation by balancing vegetable yield while reduced GHG emissions.

The potential for bioenergy generated on marginal land to offset agricultural greenhouse gas emissions in China

Rational use of marginal land for cultivation of bioenergy crops is an effective means to solve land use competition and is an important way to reduce greenhouse gas (GHG) emissions and improve energy supply. This study conducted an evaluation of the suitability of marginal land for growing energy crops in China during 1990–2020 using the GIS and multi-factor analysis method and revealed the quantitative relationship between bioenergy produced by marginal land energy crops and carbon reduction potential. The Intergovernmental Panel on Climate Change (IPCC) coefficient method and life cycle method were applied to measure the biofuel yield of the Jatropha curcas and assessed its potential to offset agricultural greenhouse gas emissions. The findings are: (1) The marginal land area available for energy crops in 2020 is 1.63 × 106 km2, which is 8.35 % lower than the area planted in 1990. (2) When the reclamation index is 60 %, all suitable marginal land can be used to grow energy crops, and biofuels can replace 3.31 × 1011 tons of conventional energy. (3) In 2020, agricultural greenhouse gas emissions will be 9.02 × 108 tons, and the potential of bioenergy crop cultivation to offset agricultural greenhouse gas emissions amounts to 4.31 × 108 tons, or 47.88 %. In the future, the pressure of agricultural GHG emission reduction will be further exacerbated by population growth and agricultural land supply, etc. Rational use of marginal land and development of bioenergy crops are effective ways for China to cope with climate change and realize its renewable energy strategy.

Trade-induced land-use transitions and greenhouse gas emissions: The case of the EU-Mercosur free-trade agreement

Currently, land use change (LUC) accounts for approximately 18.8% of all greenhouse gas (GHG) emissions globally, and up to 66% and 70% in Brazil and Paraguay respectively. However, owing to measurement difficulties, examining the effects of changing trade patterns is often overlooked in studies. This study aims to investigate the induced effects of LUC and their consequences concerning GHG emissions for the EU-Mercosur free trade agreement. A multi-regional computable general equilibrium (CGE) model with an explicit land module is used to simulate the effects of the free trade agreement. GHG emissions are calculated for LUC, fossil energy CO2, and non-CO2 emissions to capture a wide range of sources and reveal their relative contributions. The study finds that as a more extensive liberalization scheme is implemented, the majority of global GHG emissions change are driven by LUC, consisting up to 89.9% of the total increase. These findings align with previous studies. Nonetheless, we argue that for Latin America, where LUC and deforestation are historical problems, careful consideration of LUC and agriculture GHG sources is necessary to address the potential environmental impacts of trade agreements.

A global dataset for the production and usage of cereal residues in the period 1997–2021

Crop residue management plays an important role in determining agricultural greenhouse gas emissions and related changes in soil carbon stocks. However, no publicly-available global dataset currently exists for how crop residues are managed. Here we present such a dataset, covering the period 1997–2021, on a 0.5° resolution grid. For each grid cell we estimate the total production of residues from cereal crops, and determine the fraction of residues (i) used for livestock feed/bedding, (ii) burnt on the field, (iii) used for other off-field purposes (e.g. domestic fuel, construction or industry), and (iv) left on the field. This dataset is the first of its kind, and can be used for multiple purposes, such as global crop modelling, including the calculation of greenhouse gas inventories, estimating crop-residue availability for biofuel production or modelling livestock feed availability.

Estimation of Agricultural Greenhouse Gas Emissions and Emission Reduction Potential of Beijing During the 14th Five-Year Plan Period Under the Background of "Carbon Peak and Neutrality"

To achieve the goal of "carbon peak and neutrality," the strict requirements for greenhouse gas (GHG) emissions control in the agricultural sector were recommended in relevant plans for Beijing during the 14th Five-Year Plan period. Through collecting agricultural activity data and calculating and screening the emission factors, the amount and emission characteristics of agricultural GHG emissions in Beijing in 2020 were estimated and set as the baseline condition. On this basis, the GHG emissions in 2025 with optimized measurements implemented, which were selected in combination with the natural conditions and planting-breeding mode of Beijing, were set as the reduction condition. The emission reduction potential and its distribution during the 14th Five-Year Plan Period were predicted simultaneously. Meanwhile, the reduction effects on the GHG emissions of optimized measurements were evaluated. In addition, relevant policy recommendations on GHG reduction were proposed accordingly. The results revealed that the total agricultural GHG emissions in Beijing were estimated to be 456000 t (CO2-eq) in 2020, primarily from sources of animal intestinal fermentation and manure management, with contribution rates of 50.7% and 26.7%, respectively. Spatially, it was mainly distributed in districts with large livestock and poultry breeding scales, such as Shunyi District, Miyun District, and Yanqing District, etc. It was predicted that in 2025, the total agricultural GHG emissions would be 349000 t (CO2-eq), and the emission reduction potential in the 14th Five-Year Plan period would be 107000 t (CO2-eq). Animal intestinal fermentation would be the emission source with the largest reduction potential (60000 tons, CO2-eq), followed by the emission source of animal manure management (37000 tons, CO2-eq). Adjusting fodder composition and optimizing manure management were analyzed to be the most effective optimized measurements for agricultural GHG emission reduction. Moreover, the emission reduction potential of CH4 would be greater than that of N2O. The emission reduction potential would be mainly distributed in Miyun District, Shunyi District, Yanqing District, Fangshan District, Tongzhou District, and other suburbs with large livestock and poultry breeding scales, accounting for more than 10% of the total emission reduction potential for each. These regions with large emission reduction potential should be prioritized and then the assessments should be extended to the whole city. The measurements were recommended as follows:① the research and promotion of technologies such as fodder optimization and the efficient treatment of manure should be strengthened, ② the scope of the combination of planting and breeding model should be expanded to promote the development of circular agriculture, and ③ relevant standards, guidelines, and specifications for green and low-carbon agriculture should be formulated, and the regulatory and policy system for synergy reduction of agricultural pollution and GHG should be developed.