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Long-term changes in average temperatures, precipitation, and climate variability threaten agricultural production, food security, and the livelihoods of farming communities globally. Whilst adaptation to climate change is necessary to ensure food security and protect livelihoods of poor farmers, mitigation of greenhouse gas (GHG) emissions can lessen the extent of climate change and future needs for adaptation. Many agricultural practices can potentially mitigate GHG emissions without compromising food production. India is the third largest GHG emitter in the world where agriculture is responsible for 18% of total national emissions. India has identified agriculture as one of the priority sectors for GHG emission reduction in its Nationally Determined Contributions (NDCs). Identification of emission hotspots and cost-effective mitigation options in agriculture can inform the prioritisation of efforts to reduce emissions without compromising food and nutrition security.We adopted a bottom-up approach to analyse GHG emissions using large datasets of India's ‘cost of cultivation survey’ and the ‘19th livestock census’ together with soil, climate and management data for each location. Mitigation measures and associated costs and benefits of adoption, derived from a variety of sources including the literature, stakeholder meetings and expert opinion, were presented in the form of Marginal Abatement Cost Curves (MACC). We estimated that by 2030, business-as-usual GHG emissions from the agricultural sector in India would be 515 Megatonne CO2 equivalent (MtCO2e) per year with a technical mitigation potential of 85.5 MtCO2e per year through adoption of various mitigation practices. About 80% of the technical mitigation potential could be achieved by adopting only cost-saving measures. Three mitigation options, i.e. efficient use of fertilizer, zero-tillage and rice-water management, could deliver more than 50% of the total technical abatement potential.

This study evaluates the dynamics of soil organic carbon (SOC) underperennial crops across the globe. It quantifies the effect of change fromannual to perennial crops and the subsequent temporal changes in SOCstocks during the perennial crop cycle. It also presents an empiricalmodel to estimate changes in the SOC content under crops as a functionof time, land use, and site characteristics. We used a harmonised globaldataset containing paired-comparison empirical values of SOC andincluding different types of perennial crops (perennial grasses, palms,and woody plants) with different end-uses: bioenergy, food, other bioproducts, and short rotation coppice crops. Salient outcomes include: a20-year period encompassing a change from annual to perennial cropsled to an average 20% increase in SOC at 0-30 cm (6.0 ± 4.6 Mg ha-1gain) and a total of 10% increase over the 0-100 cm soil profile (5.7 ±10.9 Mg ha-1). A change from natural pasture to perennial cropdecreased SOC stocks by 1% over 0-30 cm (-2.5 ± 4.2 Mg ha-1) and10% over 0-100 cm (-13.6 ± 8.9 Mg ha-1). The effect of a land usechange from forest to perennial crops did not have significant impacts,probably due to the limited number of plots; but the data indicated thatwhile a 2% increase in SOC was observed at 0-30 cm (16.81 ± 55.1 Mgha-1), a decrease of 24% was observed at 30-100 cm (-40.1 ± 16.8 Mgha-1); perennial crops generally accumulate SOC through time,especially woody crops; and temperature was the main driver explainingdifferences in SOC dynamics, followed by crop age, soil bulk density, claycontent and depth. We present empirical evidence showing that the FAOperennialization strategy is reasonable, underscoring the role ofperennial crops as a useful component of climate change mitigationstrategies.

To limit warming to well below 2°C, most scenario projections rely on greenhouse gas removal technologies (GGRTs); one such GGRT uses soil carbon sequestration (SCS) in agricultural land. In addition to their role in mitigating climate change, SCS practices play a role in delivering agroecosystem resilience, climate change adaptability and food security. Environmental heterogeneity and differences in agricultural practices challenge the practical implementation of SCS, and our analysis addresses the associated knowledge gap. Previous assessments have focused on global potentials, but there is a need among policymakers to operationalise SCS. Here, we assess a range of practices already proposed to deliver SCS, and distil these into a subset of specific measures. We provide a multidisciplinary summary of the barriers and potential incentives towards practical implementation of these measures. First, we identify specific practices with potential for both a positive impact on SCS at farm level and an uptake rate compatible with global impact. These focus on: (a) optimising crop primary productivity (e.g. nutrient optimisation, pH management, irrigation); (b) reducing soil disturbance and managing soil physical properties (e.g. improved rotations, minimum till); (c) minimising deliberate removal of C or lateral transport via erosion processes (e.g. support measures, bare fallow reduction); (d) addition of C produced outside the system (e.g. organic manure amendments, biochar addition); (e) provision of additional C inputs within the cropping system (e.g. agroforestry, cover cropping). We then consider economic and non‐cost barriers and incentives for land managers implementing these measures, along with the potential externalised impacts of implementation. This offers a framework and reference point for holistic assessment of the impacts of SCS. Finally, we summarise and discuss the ability of extant scientific approaches to quantify the technical potential and externalities of SCS measures, and the barriers and incentives to their implementation in global agricultural systems., To limit warming to well below 2°C, many scenario projections rely on greenhouse gas removal by soil carbon sequestration (SCS) in agricultural land. Here, we provide a multidisciplinary summary of the barriers and potential incentives towards practical implementation SCS. First, we identify specific practices with potential for both a positive impact on SCS and an uptake rate compatible with global impact. Then, we then consider economic and non‐cost barriers and incentives for implementing SCS, and potential externalised impacts of implementation. Finally, we discuss the ability of existing methods to model the potential of SCS in global agricultural systems.

Updating and refining the N2O emission factors (N2O-EFs) are vital to reduce the uncertainty in estimates of direct N2O emissions. Based on a database with 1151 field measurements across China, the N2O-EFs were established via three approaches including the maximum likelihood method, a linear regression with an intercept and a linear regression with the intercept set to 0 using 70% of the observations. The remaining 30% of the observations were then used to evaluate the predicted N2O-EFs. The third method had the highest R2 of 0.39 and the best model efficiency of 0.38 with no significant bias, showing the best calculation efficiency. The results showed that the N2O-EFs varied with agroregions, crops, and management patterns. The agroregions of Huang-Huai-Hai and Yangtze River had the higher N2O-EFs in maize and wheat seasons than other regions, and the highest N2O-EFs of 0.66-0.92% in the rice season was found in the South and Southwest agroregions. Both fertilizer types and water regimes had the remarkable effects on N2O-EFs. Based on the best estimation by the selected method, direct N2O emissions from China's crop cultivation were estimated to be 194 Gg N2O-N with a 95% confidence interval of 180-208 Gg N2O-N in the year 2016.

Food production is estimated to emit between 20–30 % of global anthropogenic carbon emissions. The need to achieve net zero emissions requires a transition to low carbon, sustainable food sources. Of the total greenhouse gas (GHG) emissions for food production, only 4 % are attributed to wild capture fisheries. However, within seafood GHG studies a wide range of estimates can be found across different species, fishing methods and regions. This study assesses the environmental impact of fish capture, including the carbon footprint (CF), by the Scottish pelagic fleet, a highly modernised fleet targeting herring, mackerel and blue whiting in the North Sea and Atlantic Ocean. A life cycle assessment (LCA) was undertaken to provide a standardised comparison of pelagic fish with other seafood studies. One kg of whole round fish caught by the Scottish pelagic trawl fleet had a CF of 0.452 kg CO2 eq. Fuel burned during fishing operations was the largest contributing factor, accounting for approximately 96% of a CF. This figure was consistent with the expected results for a fishery for small pelagics, which are typically under 1 kg CO2 eq. per kg of whole fish landed. When contrasted with other seafood LCAs, the results were found to be lower than most other seafood. Our results demonstrate that Scottish-caught pelagic fish are a low carbon food source that could contribute to minimising food-related GHG emissions.

Agriculture is a major contributor to India's environmental footprint, particularly through greenhouse gas (GHG) emissions from livestock and fresh water used for irrigation. These impacts are likely to increase in future as agriculture attempts to keep pace with India's growing population and changing dietary preferences. Within India there is considerable dietary variation, and this study therefore aimed to quantify the GHG emissions and water usage associated with distinct dietary patterns. Five distinct diets were identified from the Indian Migration Study – a large adult population sample in India – using finite mixture modelling. These were defined as: Rice & low diversity, Rice & fruit, Wheat & pulses, Wheat, rice & oils, Rice & meat. The GHG emissions of each dietary pattern were quantified based on a Life Cycle Assessment (LCA) approach, and water use was quantified using Water Footprint (WF) data. Mixed-effects regression models quantified differences in the environmental impacts of the dietary patterns. There was substantial variability between diets: the rice-based patterns had higher associated GHG emissions and green WFs, but the wheat-based patterns had higher blue WFs. Regression modelling showed that the Rice & meat pattern had the highest environmental impacts overall, with 0.77 (95% CI 0.64–0.89) kg CO2e/capita/day (31%) higher emissions, 536 (95% CI 449–623) L/capita/day (24%) higher green WF and 109 (95% CI 85.9–133) L/capita/day (19%) higher blue WF than the reference Rice & low diversity pattern. Diets in India are likely to become more diverse with rising incomes, moving away from patterns such as the Rice & low diversity diet. Patterns such as the Rice & meat diet may become more common, and the environmental consequences of such changes could be substantial given the size of India's population. As global environmental stress increases, agricultural and nutrition policies must recognise the environmental impacts of potential future dietary changes., Graphical abstract Unlabelled Image, Highlights • India's food system produces large environmental impacts but these vary by diets. • We explored differences in GHG emissions and water use of Indian dietary patterns. • Rice-based diets had higher emissions but wheat-based diets used more water. • Diets with more animal products had the highest environmental impacts overall. • Diversifying diets in India may have severe consequences for environmental impacts.

CCAFS-MOT is a tool to support farmers, policy advisors and agricultural extension services on the choice of management practices that reduce greenhouse gas emissions (GHG) without risking food security. It is an Excel-based tool which brings together several empirical models to estimate GHG emissions in rice, cropland and livestock systems, and provides information about the most effective mitigation options. Greenhouse gas emissions are estimated in terms of carbon dioxide equivalent per hectare (kg CO2eq ha− 1) and carbon dioxide equivalent per unit of product (kg CO2eq kg− 1). Baseline management practices are chosen by the user and a set of mitigation options are ranked according to their mitigation potential. The tool allows different levels of input to be specified from an introductory to detailed level, depending on objectives and issues like to accommodate users with different backgrounds and details concerning input data. As such it allows for product and region specific assessments of GHGs and mitigation potentials to be made without the need for expert knowledge or for lengthy model set-up and calibration.

There has been much debate about the uncertainties associated with the estimation of direct and indirect agricultural nitrous oxide (N2O) emissions in developing countries and in particular from tropical regions. In this study, we report an up-to-date review of the information published in peer-review journals on direct N2O emissions from agricultural systems in tropical and sub-tropical regions. We statistically analyze net-N2O-N emissions to estimate tropic-specific annual N2O emission factors (N2O-EFs) using a Generalized Additive Mixed Model (GAMM) which allowed the effects of multiple covariates to be modelled as linear or smooth non-linear continuous functions. Overall the mean N2O-EF was 1.2% for the tropics and sub-tropics, thus within the uncertainty range of IPCC-EF. On a regional basis, mean N2O-EFs were 1.4% for Africa, 1.1%, for Asia, 0.9% for Australia and 1.3% for Central & South America. Our annual N2O-EFs, estimated for a range of fertiliser rates using the available data, do not support recent studies hypothesising non-linear increase N2O-EFs as a function of applied N. Our findings highlight that in reporting annual N2O emissions and estimating N2O-EFs, particular attention should be paid in modelling the effect of study length on response of N2O.

Increasing concerns about global environmental change and food security have focused attention on the need for environmentally sustainable agriculture. This is agriculture that makes efficient use of natural resources and does not degrade the environmental systems that underpin it, or deplete natural capital stocks. We convened a group of 29 ‘practitioners' and 17 environmental scientists with direct involvement or expertise in the environmental sustainability of agriculture. The practitioners included representatives from UK industry, non-government organizations and government agencies. We collaboratively developed a long list of 264 knowledge needs to help enhance the environmental sustainability of agriculture within the UK or for the UK market. We refined and selected the most important knowledge needs through a three-stage process of voting, discussion and scoring. Scientists and practitioners identified similar priorities. We present the 26 highest priority knowledge needs. Many of them demand integration of knowledge from different disciplines to inform policy and practice. The top five are about sustainability of livestock feed, trade-offs between ecosystem services at farm or landscape scale, phosphorus recycling and metrics to measure sustainability. The outcomes will be used to guide ongoing knowledge exchange work, future science policy and funding.