Agricultural Greenhouse Gas Emissions Research Articles

Flower strips as a carbon sequestration measure in temperate croplands

PurposeFlower strips have been shown to increase insect biodiversity and improve agricultural yields through increased pollination and pest predation. Less is known about their potential to increase soil organic carbon (SOC). We aimed to investigate the biomass production and SOC sequestration potential of flower strips as a sustainable management option of temperate agricultural soils.Methods23 flower strips across varying soil types and climatic regions in Germany were sampled for aboveground and belowground peak biomass in order to estimate the annual carbon input to the soil. Those were used as 23 scenarios to model the potential SOC sequestration of the flower strips compared to a business-as-usual scenario for 1533 sites of the German Agricultural Soil Inventory using the RothC model.ResultsOn average, flower strips sequestered 0.48 ± 0.36 Mg C ha−1 year−1 in the initial 20-year period after establishment. Converting 1 % of the total German cropland area into flower strips would thus lead to a mitigation of 0.24 Tg CO2 year−1, which equals 0.4 % of current agricultural greenhouse gas emissions in Germany.We found a negative correlation between C sequestration rate and the number of plant species in the flower strips, mainly related to grasses outcompeting herbaceous species.ConclusionFlower strips are one overlooked option for increasing SOC stocks of croplands that has multiple benefits for agro-ecosystems. However, within a flower strip it might not be possible to maximise both plant biodiversity and SOC sequestration.

Energy productivity and greenhouse gas emission intensity in Dutch dairy farms: A Hicks–Moorsteen by‐production approach under non‐convexity and convexity with equivalence results

AbstractThe agricultural sector is currently confronted with the challenge to reduce greenhouse gas (GHG) emissions, whilst maintaining or increasing production. Energy‐saving technologies are often proposed as a partial solution, but the evidence on their ability to reduce GHG emissions remains mixed. Production economics provides methodological tools to analyse the nexus of agricultural production, energy use and GHG emissions. Convexity is predominantly maintained in agricultural production economics, despite various theoretical and empirical reasons to question it. Employing non‐convex and convex frontier frameworks, this contribution evaluates energy productivity change (the ratio of aggregate output change to energy use change) and GHG emission intensity change (the ratio of GHG emission change to polluting input change) using Hicks‐Moorsteen productivity formulations. We consider GHG emissions as by‐products of the production process by using a multi‐equation model. Given our empirical specification, non‐convex and convex Hicks‐Moorsteen indices can coincide under certain circumstances, which leads to a series of theoretical equivalence results. The empirical application focuses on 1,510 observations of Dutch dairy farms for the period of 2010–2019. The results show a positive association between energy productivity change and GHG emission intensity change, which calls into question the potential of on‐farm, energy‐efficiency‐increasing measures to reduce GHG emission intensity.

Agricultural greenhouse gas emissions of an Indian village - Who's to blame: crops or livestock?

A carbon footprint assessment, combining various scales of analysis and including a territorial assessment, is proposed to estimate the greenhouse gas (GHG) emissions from crops and livestock in an Indian village impacted by both Green (for crops) and White (for milk) revolutions. It is based on the GHG assessment of 10 cropping systems, 8 livestock farming systems and 9 production systems using the comparative agriculture and Life Cycle Assessment (LCA) approaches. Results show that mineral fertilisation, irrigation and methane from paddy fields are the main drivers of emissions at plot level. Livestock farming systems emit from 4.7 tCO2eq/female to 8.6 tCO2eq/female, enteric fermentation being the first source of emission. Disparities at farm level are huge, ranging from 9 to 733 tCO2eq. At village level, emissions yield 37 tCO2eq/ha and livestock contributes to 60 % of GHG emissions. The high GHG emissions are a legacy of the Green and White Revolutions: the livestock population is high, fed on highly emissive fodder and concentrates and produces little milk. The results enhance our understanding of the share of carbon emissions from crops and livestock at farm and territorial level. They pinpoint the environmental and socio-economic downsides of livestock farming intensification.

Use of Winery and Animal Waste as Fertilizers to Achieve Climate Neutrality in Non-Irrigated Viticulture

There is a growing interest globally in reducing the environmental impacts of farming by reusing agricultural waste and reducing agricultural greenhouse gas (GHG) emissions. In this work, the potential of Mediterranean viticulture for GHG emissions mitigation and Carbon (C) storage in biomass and soil is examined. In a field experiment, synthetic fertilizer use was reduced by 50 and 100% after applying a winery waste-based biofertilizer, and the C balance was determined at the vineyard level. The Vineyard Carbon Tool (VCT) for GHG emissions estimation in vineyards was developed by tailoring to vineyards the widely used Cool Farm Tool (CFT). Our results show that existing conventional viticulture could be easily transformed into zero-emissions by reducing nitrogen (N) fertilizers, lowering tillage frequency, using less fuel, and maintaining field margin vegetation at the farm level. Use of Life Cycle Analysis (LCA) showed that farm input reductions lead to a vineyard lifetime C storage equal to 25,124 kg CO2-eq ha−1 or 837 kg CO2-eq ha−1 year−1. This approach could be used for the design of eco-schemes related to C farming under the new Common Agricultural Policy (CAP).

Sustainable Agro-Food Systems for Addressing Climate Change and Food Security

Despite world food production keeping pace with population growth because of the Green Revolution, the United Nations (UN) State of Food Security and Nutrition in the World 2022 Report indicates that the number of people affected by hunger has increased to 828 million with 29.3% of the global population food insecure, and 22% of children under five years of age stunted. Many more have low-quality, unhealthy diets and micronutrient deficiencies leading to obesity, diabetes, and other diet-related non-communicable diseases. Additionally, current agro-food systems significantly impact the environment and the climate, including soil and water resources. Frequent natural disasters resulting from climate change, pandemics, and conflicts weaken food systems and exacerbate food insecurity worldwide. In this review, we outline the current knowledge in alternative agricultural practices for achieving sustainability as well as policies and practices that need to be implemented for an equitable distribution of resources and food for achieving several goals in the UN 2030 Agenda for Sustainable Development. According to the UN Intergovernmental Panel on Climate Change, animal husbandry, particularly ruminant meat and dairy, accounts for a significant proportion of agricultural greenhouse gas (GHG) emissions and land use but contributes only 18% of food energy. In contrast, plant-based foods, particularly perennial crops, have the lowest environmental impacts. Therefore, expanding the cultivation of perennials, particularly herbaceous perennials, to replace annual crops, fostering climate-smart food choices, implementing policies and subsidies favoring efficient production systems with low environmental impact, empowering women, and adopting modern biotechnological and digital solutions can help to transform global agro-food systems toward sustainability. There is growing evidence that food security and adequate nutrition for the global population can be achieved using climate-smart, sustainable agricultural practices, while reducing negative environmental impacts of agriculture, including GHG emissions.

Will Biochar Suppress or Stimulate Greenhouse Gas Emissions in Agricultural Fields? Unveiling the Dice Game through Data Syntheses

With the increasing popularity of biochar as a soil amendment worldwide in recent years, a question of concern arises as to whether the application of biochar would suppress or stimulate greenhouse gas (GHG) emissions. In this study, published data extracted from independent individual studies were systematically selected, statistically processed, graphically presented and critically analyzed to understand biochar’s influences on the emissions of CO2, CH4 and N2O—the three major GHGs emitted in agricultural fields. The results revealed not only the significant importance of biochar’s pyrolysis temperature for its impacts on GHG emissions, but also the dissimilar influences on the generations of different GHGs. The application of biochar, in general, stimulated the emissions of CO2 and CH4 to various extents. With biochar pyrolyzed under relatively lower temperatures (e.g., <500 °C), higher application rates generally resulted in more stimulated CO2 and CH4 emissions; whereas those pyrolyzed under relatively higher temperatures (e.g., >550 °C) became less stimulative (and sometimes even suppressive) for CO2 and CH4 emissions, especially when applied at higher rates. Nevertheless, the response of N2O emission to biochar application contrasted with those of CO2 and CH4. The results may contribute to better regulations for biochar application in combating GHG emissions in agriculture.

Reducing Carbon Footprint of Agriculture—Can Organic Farming Help to Mitigate Climate Change?

In the face of a changing climate, intensive efforts are needed for limiting the global temperature increase to 1.5 °C. Agricultural production has the potential to play an important role in mitigating climate change. It is necessary to optimize all of the agricultural practices that have high levels of greenhouse gas (GHG) emissions. Among the plant production processes, mineral fertilization is of the greatest importance in the formation of the carbon footprint (CF) of crops. There are many possibilities for reducing GHG emissions from the application of fertilizers. Further benefits in reducing the CF can be obtained through combining tillage treatments, reduced and no-till technologies, and the cultivation of catch crops and leguminous plants. Organic farming has the potential for reducing GHG emissions and improving organic carbon sequestration. This system eliminates synthetic nitrogen fertilizers and thus could lower global agricultural GHG emissions. Organic farming could result in a higher soil organic carbon content compared to non-organic systems. When used together with other environmentally friendly farming practices, significant reductions of GHG emissions can be achieved.

Productivity and global warming potential of direct seeding and transplanting in double-season rice of central China.

Labor and water scarcity requires crop establishment of double-season rice to be shifted from traditional transplanting to direct seeding. Owing to the limited thermal time, only ultrashort-duration cultivars of about 95 d can be used for direct-seeded, double-season rice (DDR) in central China. However, whether the shift in crop establishment of double-season rice can reduce greenhouse gas emissions without yield penalty remains unclear. Field experiments were conducted in Hubei province, central China with three treatments of crop establishment in the early and late seasons of 2017 and 2018. Treatments included DDR with ultrashort-duration cultivars (DDRU), transplanted double-season rice with ultrashort-duration cultivars (TDRU), or with widely grown cultivars which have short duration of about 110 d (TDRS). It was found that crop growth duration of DDRU was 6-20 days shorter than that of TDRU and TDRS, respectively. Ultrashort-duration cultivars under DDRU achieved 15.1t ha-1 of annual yield that was 9.4% higher than TDRU, and only 3.2% lower than TDRS. DDRU reduced the annual cumulative CH4 emission by 32.0-46.1%, but had no difference in N2O emission in comparison with TDRU and TDRS. The highest CO2 emission was TDRS followed by DDRU, and then TDRU. As a result, shifting from TDRU and TDRS to DDRU decreased global warming potential and yield-scaled greenhouse gas intensity by 28.9-53.2% and 20.7-63.8%, respectively. These findings suggest that DDR can be a promising alternative to labor- and water-intensive TDR in central China that offers important advantages in mitigating agricultural greenhouse gas emissions without sacrificing grain yield.

Drainage in paddy systems maintains rice yield and reduces total greenhouse gas emissions on the global scale

Rice sustains the survival of nearly half of humanity, meanwhile, paddy systems are also a significant source of greenhouse gas (GHG) emissions in agriculture. Drainage is widely accepted as a key agricultural management practice (AMP) to reduce CH4 emissions in paddy systems, however, its impact on rice yield and global warming potential (GWP) under different soil and APM conditions remains uncertain. Here, we performed a global meta-analysis of 519 samples from 74 fields in 64 peer-reviewed publications, including measurements of rice yield and at least one of GHG emissions (N2O, CH4, and CO2). Overall, the effects of implementing drainage in paddy systems on yield, N2O emissions, CH4 emissions, CO2 emissions, GWP, and GWP intensity (GWPI) were +0.3% (p = 0.85), +149.9% (p< 0.0001), −57.8% (p< 0.0001), +27.7% (p = 0.12), −44.9% (p< 0.0001), and 57.7% (p< 0.0001), respectively. Drainage in lower total N soils was more capable of maintaining yield (+0.9% vs. −1.4%), and drainage in higher pH and organic carbon soils resulted in greater reductions in CH4 emissions (−46.73% vs. −37.3%, −46.36% vs. −38.12%). Mid-season drainage was superior to early-season and fallow season drainage in CH4 emissions reduction. Extending the duration and increasing the events of drainage would increase N2O emissions but contribute to a better CH4 emissions reduction effect. Implementing drainage in paddy systems with organic amendment can achieve greater GHG emissions reduction (both N2O and CH4) than in that without organic amendment. The GWPI decreased by the installation of drainage system might disappear when the nitrogen fertilizer application rate (N rate) reached over 530 kg ha−1. As for different N rates, single drainage is more suitable for the N rate below 115 kg ha−1, while multi-drainage has more advantages on reducing GWPI in the high N rate (≥ 115 kg ha−1).

Agricultural carbon footprint and food security: an assessment of multiple carbon mitigation strategies in China

PurposeTo achieve the dual goals of decarbonization and food security, this paper examines China's carbon footprint reduction in 2050 based on current mitigation strategies.Design/methodology/approachConsidering publications as featured evidence, this study develops an investigation of agricultural decarbonization in China. First, the authors summarize the mitigation strategies for agricultural greenhouse gas (GHG) emissions in the existing literature. Second, the authors demonstrate the domestic food production target in 2050 and the projection target's projected life-cycle-based GHG emissions at the commodity level. Lastly, the authors forecast China's emission removal in the agri-food sector in 2050 concerning current mitigation strategies and commodity productions. The authors highlight the extent to which each mitigation strategy contributes to decarbonization in China.FindingsPractices promoting sustainable development in the agri-food sector significantly contribute to GHG emission removal. The authors find mitigation strategies inhibiting future GHG emissions in the agri-food sector comprise improving nitrogen use efficiency in fertilizers, changing food consumption structure, manure management, cover crops, food waste reduction, dietary change of livestock and covered manure. A 10% improvement in nitrogen use efficiency contributes to 5.03% of GHG emission removal in the agri-food sector by 2050. Reducing food waste and food processing from 30% to 20% would inhibit 1.59% of the total GHG emissions in the agri-food sector.Originality/valueThis study contributes to policy discussions by accounting for agricultural direct and indirect emission components and assessing the dynamic changes in those related components. This study also extends existing research by forecasting to which extent the decarbonization effects implemented by current mitigation strategies can be achieved while meeting 2050 food security in China.

Greenhouse Gas Emissions from Beef Cattle Breeding Based on the Ecological Cycle Model.

Over the past few decades, the supply of beef has increasingly become available with the great improvement of the quality of life, especially in developing countries. However, along with the demand for meat products of high quality and the transformation of dietary structure, the impact of massive agricultural greenhouse gas emissions on the environmental load cannot be ignored. Therefore, the objective of this study is to predict the annual greenhouse gas emissions of 10 million heads of beef cattle under both the ecological cycle model (EC model) and the non-ecological cycle model (non-EC model), respectively, in order to compare the differences between these two production models in each process, and thus explore which one is more sustainable and environmentally friendly. To this end, through the life cycle assessment (LCA), this paper performs relevant calculations according to the methodology of 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories (2019 IPCC Inventories). The results have shown that the total GHG emissions of the non-EC model were almost 4 times higher than those of the EC model, and feed-grain cultivation and manure management were main emission sources in both models. The non-EC model produced significantly more emissions than the EC model in each kind of GHG, especially the largest gap between these two was in CO2 emissions that accounted for 68.01% and 56.17% of the respective planting and breeding systems. This study demonstrates that the transformation of a beef cattle breeding model has a significant direct impact on cutting agricultural GHG emissions, and persuades other countries in the similar situation to vigorously advocate ecological cycling breeding model instead of the traditional ones so that promotes coordinated development between planting industry and beef cattle breeding industry.

Blue revolution for food security under carbon neutrality: A case from the water-saving and drought-resistance rice

Blue revolution for food security under carbon neutrality: A case from the water-saving and drought-resistance rice

The potential impacts of an EU-wide agricultural mitigation target on the Irish agriculture sector

ABSTRACT The Irish Climate Action Plan published in 2019 outlines the significant role that agriculture will have to take to achieve a national reduction in greenhouse gas emissions in Ireland. Recent growth in the agricultural sector, especially of the bovine population, however, has led to a continuous increase of agricultural greenhouse gas emissions. For the agricultural sector to meet its potential, greenhouse gas emission targets could be challenging. The agricultural sector model CAPRI is used to investigate the impact of a 20 per cent EU-wide agricultural greenhouse gas mitigation target on the Irish agriculture sector. Three scenarios, allowing the endogenous implementation of mitigation technologies, show the possible impact range of such a policy target. The research indicates that the Irish agriculture sector can achieve the set mitigation target by adapting livestock production systems, resulting in agricultural efficiency gains, and by implementing specific mitigation technologies. Without a mandatory mitigation target but with subsidies granted, changes in the level of agricultural greenhouse gas emissions are marginal, and voluntary adoption is limited. Subsidising the implementation of mitigation technologies can buffer the impact that a mitigation target will have on the agriculture sector in Ireland while achieving the set greenhouse gas emissions reduction. Total agricultural income increases if a mandatory target is set due to strong structural changes. As the analysis shows, the emission reduction is partly achieved through a reduction in total production and strong competitors outside of the EU appear to fill the occurring supply gap. This could potentially lead to a carbon leakage effect with production and emissions shifting towards strong ruminant-based producing countries.

A new index on agricultural land greenhouse gas emissions in Africa.

Africa emits the lowest amounts of greenhouse gases (GHGs) into the global GHG budget. However, the continent remains the most vulnerable continent to the effects of climate change. The agricultural sector in Africa is among the most vulnerable sectors to climate change. Also, as a dominant agricultural sector, African agriculture is increasingly contributing to climate change through GHG emissions. Research has so far focused on the effects of GHG emissions on the agricultural and other sectors with very little emphasis on monitoring and quantifying the spatial distribution of GHG emissions from agricultural land in Africa. This study develops a new index: African Agricultural Land Greenhouse Gas Index (AALGGI) that uses scores and specific scale ranges for carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O) to map the spatial variations in regional GHG emissions across Africa. The data for the three main GHGs (CO2, CH4, and N20) were downloaded from FAOSTAT. The data were analyzed through the newly developed African Agricultural Land Greenhouse Gas Index (AALGGI). This is an empirical index with scores ranging from 0 to 10, with higher scores indicating higher levels of emissions. The results show that Southern and North African regions have the lowest amounts of agricultural land GHG emissions, with AALGGIs of 3.5 and 4.5, respectively. East Africa records the highest levels of GHG emissions, with an AALGGI of 8 followed by West Africa with an AALGGI of 7.5. With the continental mean or baseline AALGGI being 5.8, East and Middle Africa are above the mean AALGGI. These results underscore the fact that though Africa, in general, is not a heavy emitter of GHGs, African agricultural lands are increasingly emitting more GHGs into the global GHG budget. The low AALGGIs in the more developed parts of Africa such as Southern and North Africa are explained by their domination in other GHG emitting sectors such as industrialization and energy. The high rates of emissions in East Africa and Middle Africa are mainly linked to intensive traditional farming practices/processes and deforestation. These findings underscore the need to further leverage climate change mitigation actions and policy in Africa and most importantly the co-benefits of mitigation and adaptations in the most vulnerable regions.

Analysis of agricultural greenhouse gas emissions using the STIRPAT model: a case study of Bangladesh.

The agriculture sector is one of the leading emitters of greenhouse gases in Bangladesh, owing to increasing mechanization, changing population patterns and increasing cultivation of irrigation intensive crops like rice. The objective of this research is to analyze how population trends, energy use and land use practices impact the emissions of three greenhouse gases from the agriculture sector in Bangladesh. The gases studied are carbon dioxide, methane and nitrous oxide. The Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model and ridge regression are used to analyze the drivers of emissions covering the period from 1990 to 2014. Explanatory factors of emissions are the total and rural population, affluence, urbanization, fertilizer intensity and quantity, carbon and energy intensity, irrigation, rice cultivation, cultivated land and crop yield. The findings reveal that the country’s total population has a negative effect, and the rural population has a negative, nonlinear impact on the emissions of methane. Affluence affects emissions of all the gases. The energy intensity and carbon intensity of agriculture increase carbon dioxide emissions. The cultivated land area, rice cultivation quantity and crop yield increase methane emissions, while irrigated land area decreases it. Rural population, total population and urbanization have a positive linear effect on carbon dioxide and nitrous oxide emissions. Fertilizer quantity and intensity increase nitrous oxide emissions. The findings imply that increasing agricultural mechanization should be based on clean energy, and land management should be regulated to enable the country to meet its Nationally Determined Contribution (NDC) targets as well as the targets of Sustainable Development Goal (SDG) 7 of increasing the share of clean energy.Graphic abstract

Toward carbon neutrality before 2060: Trajectory and technical mitigation potential of non-CO2 greenhouse gas emissions from Chinese agriculture

In 2020, China announced that it aims to achieve carbon neutrality before 2060. Despite the recognition of agriculture's importance in emission mitigation strategies, assessing the non-CO2 greenhouse gas (GHG) mitigation potentials from this sector remains technically and conceptually challenging. This study developed a bottom-up inventory-based model (the Agriculture-induced non-CO2GreenHouse Gases INVentory model) to provide region-specific long-term projections (to 2060) of non-CO2 GHG emissions (including methane and nitrous oxide) from the Chinese agricultural sector. Seventeen production-side technologies were identified that could reduce on-farm emissions, and their mitigation potentials by 2060 were evaluated. Results showed that agricultural non-CO2 GHG emissions rose by 34% from 1980 to 2018, and they are projected to increase further by 33% to reach 1153 MtCO2-eq yr−1 by 2060. Implementing selected technological adaptations could lead to peak agricultural emissions before 2030 and then reduce them by 32%–50% by 2060. The most effective mitigation measures include feed supplements, feed quality improvements, slow-release fertilizers, and improved water management for paddy fields and uplands. All six regions of China will see a gradual increase in agricultural emissions. South Central China and Southwest China have the largest shares of total national emissions and the greatest mitigation potentials. However, technology adoption faces a series of socio-economic obstacles such as the high cost of technology promotion, smaller farm sizes, farmers' aversion to risk, and a complex set of objectives for agriculture.

Identifying Farming Strategies Associated With Achieving Global Agricultural Sustainability

Sustainable agroecosystems provide adequate food while supporting environmental and human wellbeing and are a key part of the United Nations Sustainable Development Goals (SDGs). Some strategies to promote sustainability include reducing inputs, substituting conventional crops with genetically modified (GM) alternatives, and using organic production. Here, we leveraged global databases covering 121 countries to determine which farming strategies—the amount of inputs per area (fertilizers, pesticides, and irrigation), GM crops, and percent agriculture in organic production—are most correlated with 12 sustainability metrics recognized by the United Nations Food and Agriculture Organization. Using quantile regression, we found that countries with higher Human Development Indices (HDI) (including education, income, and lifespan), higher-income equality, lower food insecurity, and higher cereal yields had the most organic production and inputs. However, input-intensive strategies were associated with greater agricultural greenhouse gas emissions. In contrast, countries with more GM crops were last on track to meeting the SDG of reduced inequalities. Using a longitudinal analysis spanning 2004–2018, we found that countries were generally decreasing inputs and increasing their share of agriculture in organic production. Also, in disentangling correlation vs. causation, we hypothesize that a country's development is more likely to drive changes in agricultural strategies than vice versa. Altogether, our correlative analyses suggest that countries with greater progress toward the SDGs of no poverty, zero hunger, good health and wellbeing, quality education, decent work, economic growth, and reduced inequalities had the highest production of organic agriculture and, to a lesser extent, intensive use of inputs.

Prediction of greenhouse gas emissions from agricultural fields with and without cover crops

AbstractThe significant contribution of greenhouse gas (GHG) emissions to global climate change and stratospheric ozone depletion has been calling the attention to assess the effect of agricultural management on them. Although machine learning (ML) methods have been widely used for the quantification of various inherent and dynamic soil properties, the accuracy of these techniques in the prediction of agricultural soil GHG emissions remains unclear. Therefore, this study aims at evaluating the performance of six different ML methods including simple linear regression, Cubist, support vector machines (SVM) with three different kernel functions, and random forest (RF) for the prediction of CO2 and N2O fluxes from plots managed with and without cover cropping. The input parameters include typical meteorological data as well as soil temperature and soil water content. Results show that the daily flux of CO2 is positively correlated with soil temperature and solar radiation and negatively with soil water content, whereas daily N2O flux is positively correlated with soil water content. For plots without cover cropping, Cubist and SVM with polynomial kernel function outperformed in the prediction of the testing dataset with RMSE of 14.18 kg ha–1 d–1 and 11.52 g ha–1 d–1 for daily CO2 and N2O emissions, respectively. Where cover cropping was considered, SVM with radial basis function and Cubist were the best models in the prediction of daily CO2 and N2O fluxes with respective RMSE values of 15.71 kg ha–1 d–1 and 14.12 g ha–1 d–1. Considering the ranking of the models for all scenarios and both GHGs, SVM with nonlinear kernel functions and Cubist method surpassed other ML techniques.

Genetically modified crops support climate change mitigation.

Genetically modified (GM) crops can help reduce agricultural greenhouse gas (GHG) emissions. In addition to possible decreases in production emissions, GM yield gains also mitigate land-use change and related emissions. Wider adoption of already-existing GM crops in Europe could result in a reduction equivalent to 7.5% of the total agricultural GHG emissions of Europe.

The cost-effectiveness of agricultural greenhouse gas reduction under diverse carbon policies in China

PurposeMitigating agricultural greenhouse gas (GHG) emissions is an essential part of China's effort to achieve net-zero emissions. This study assesses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies.Design/methodology/approachThe study employs a parametric non-radial distance function approach and estimates the technical abatement potential and marginal abatement cost (MAC) of GHG in China's agricultural sector for the 2008–2017 period.FindingsAgriculture is expected to make a great contribution to China's net-zero emissions progress. This study empirically analyses the cost-effectiveness of China's agricultural GHG reduction under diverse carbon policies. A parametric non-radial distance function approach is used to derive technical abatement potential and MAC of GHG for the 2008–2017 period. The results indicate that no significant improvement had been achieved in terms of agricultural GHG reduction in China during 2008–2017. The country's agricultural sector could reduce 20–40% GHG emissions with a mean value of 31%. In general, western provinces have larger reduction potential than eastern ones. The average MAC for the whole country is 4,656 yuan/ton CO2e during 2008–2017. For most western provinces, their MAC values are considerably higher than those for most eastern provinces. Compared with previous sectoral estimates of GHG mitigation cost, this study’s estimates indicate that reducing agricultural GHG emissions in some provinces is likely to be cost-effective. The Chinese government should consider expanding its national carbon market to cover agricultural sector.Practical implicationsThe Chinese government should consider expanding its national carbon market to cover agricultural sector.Originality/valueExisting studies in the field mostly ignore input constraints, which is inconsistent with carbon mitigation policy practice, especially in the agricultural sector. This study’s approach integrates both input and output constraints reflecting differing policy practice.