Evaluating the potential and eligibility of conservation agriculture practices for carbon credits

Carbon credits, a voluntary market mechanism to reduce greenhouse gas (GHG) emissions, can incentivize climate action. We evaluate the potential and eligibility of Conservation Agriculture (CA) practices for carbon credit generation in India under Verra's VM0042 methodology. Using farmer surveys and remote sensing data, we assess the eligibility based on the following conditions: Additionality Condition (GHG emission reductions to exceed legal requirements and the weighted mean adoption rate to be < 20% of area in the baseline), Yield Penalty Condition (no > 5% decrease in crop yields), and Quantitative Adjustment Condition (reduction in chemical fertilizer use by > 5%). Our analysis shows that CA has the potential to increase farmers' carbon credit earnings by USD 18/ha and USD 30/ha in Bihar and Punjab, respectively. Punjab's ban on crop residue burning and the fact that > 20% of the area unburned limits the full economic realization of CA through carbon markets, decreasing potential income to USD 16/ha. A 60% increase in carbon prices from the current norm (USD 25) is required to encourage wider adoption of CA. Zero tillage of wheat in both Punjab and Bihar and reduction of nitrogen fertilizer overuse in Punjab fulfil all the conditions and are eligible for carbon farming projects.

Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh

Climate change is and will continue to have significant implications for agricultural systems. While adaptation to climate change should be the priority for smallholder production systems, adoption of cost-effective mitigation options in agriculture not only contributes to food security but also reduces the extent of climate change and future adaptation needs. Utilizing management data from 16,413 and 12,548 crop and livestock farmers and associated soil and climatic data, we estimated GHG emissions generated from crop and livestock production using crop and livestock models, respectively. Mitigation measures in crop and livestock production, their mitigation potential and cost/benefit of adoption were then obtained from literature review, stakeholder consultations and expert opinion. We applied the identified mitigation measures to a realistic scale of adoption scenario in the short- (2030) and long-term (2050). Our results were then validated through stakeholders consultations. Here, we present identified mitigation options, their mitigation potentials and cost or benefit of adoption in the form of Marginal Abatement Cost Curves (MACC). Based on our analysis, total GHG emissions from agricultural sector in Bangladesh for the year 2014-15 is 76.79 million tonne (Mt) carbon-dioxide equivalent (CO₂e). Business-as-usual GHG emissions from the agricultural sector in Bangladesh are approximately 86.87 and 100.44 Mt CO₂e year^-1 by 2030 and 2050, respectively. Adoption of climate-smart crop and livestock management options to reduce emissions considering a realistic adoption scenario would offer GHG mitigation opportunities of 9.51 and 14.21 Mt CO₂e year^-1 by 2030 and 2050, respectively. Of this mitigation potential, 70-75% can be achieved through cost-saving options that could benefit smallholder farmers. Realization of this potential mitigation benefit, however, largely depends on the degree to which supportive policies and measures can encourage farmers' adoption of the identified climate smart agricultural techniques. Therefore, government should focus on facilitating uptake of these options through appropriate policy interventions, incentive mechanisms and strengthening agricultural extension programs.

Model comparison and quantification of nitrous oxide emission and mitigation potential from maize and wheat fields at a global scale

Maize and wheat are major cereals that contribute two-thirds of the food energy intake globally. The two crops consume about 35% of the nitrogen (N) fertilizer used in agriculture and thereby contribute to fertilizer-induced nitrous oxide (N₂O) emissions. Thus, estimation of spatially disaggregated N₂O emissions from maize and wheat fields on a global scale could be useful for identifying emission and mitigation hotspots. It could also be needed for prioritizing mitigation options consistent with location-specific production and environmental goals. N₂O emission from four models (CCAFS-MOT, IPCC Tier-I, IPCC Tier-II and Tropical N₂O) using a standard gridded dataset from global maize and wheat fields were compared and their performance evaluated using measured N₂O emission data points (777 globally distributed datapoints). The models were used to quantify spatially disaggregated N₂O emission and mitigation potential from maize and wheat fields globally and the values were compared. Although the models differed in their performance of capturing the level of measured N₂O emissions, they produced similar spatial patterns of annual N₂O emissions from maize and wheat fields. Irrespective of the models, predicted N₂O emissions per hectare were higher in some countries in East and South Asia, North America, and Western Europe, driven mainly by higher N application rates. The study indicated a substantial N₂O abatement potential if application of excess N in the maize and wheat systems is reduced without compromising the yield of the crops through technological and crop management innovations. N₂O mitigation potential is higher in those countries and regions where N application rates and current N₂O emissions are already high. The estimated mitigation potentials are useful for hotspot countries to target fertilizer and crop management as one of the mitigation options in their Nationally Determined Contributions (NDCs) to the United Nations Framework Convention on Climate Change (UNFCCC).

Spatially explicit database on crop-livestock management, soil, climate, greenhouse gas emissions and mitigation potential for all of Bangladesh

This data article provides spatially explicit data on greenhouse gas (GHG) emissions and mitigation potential at various administrative levels for the whole of Bangladesh. The results arising from analysis of this database are presented in research article "Quantifying opportunities for greenhouse gas emissions mitigation using big data from smallholder crop and livestock farmers across Bangladesh" [1]. We collected crop and livestock management data and associated soil and climatic data from variety of primary and secondary sources outlined below in our methodology. The datafiles on crops and livestock contain model outputs for three greenhouse gases (CO2, CH4 and N2O) and their global warming potential, which are linked, to the information on crop/livestock management, soil and climatic conditions presented in the supplementary data of the associated manuscript. The datafiles on mitigation potential contain district-level annual GHG mitigation potential by 2030 and 2050 segregated by different crops/livestock types and mitigation options. This dataset is useful for Bangladesh's GHG accounting from the agricultural sector, and can be used to update its nationally determined contributions. Administrative level emissions and mitigation potential estimates segregated by crop-livestock types and mitigation options are useful to prioritize agricultural research and development interventions consistent with food security and environmental goals and to organize agricultural extension and support services to better inform farmers on food production and move towards GHG mitigation goals.

Global high-resolution gridded dataset of N2O Emission and mitigation potential from maize and wheat fields

This data article provides a high-resolution raw data on Nitrous Oxide (N₂O) emission and its mitigation potential from global maize and wheat fields. The analytical results, discussion and conclusion thereof is presented in the related manuscript “Model Comparison and Quantification of Nitrous Oxide Emission and Mitigation Potential from Maize and Wheat Fields at a Global Scale” [1]. This raw dataset has a spatial resolution of 0.0833° × 0.0833°, and comprises pixel level baseline emissions estimated using four empirical N₂O emission models (CCAFS-MOT, IPCC Tier-I, IPCC Tier-II and Tropical-N2O) and the model results were validated using experimental data extracted from the literature. Spatially explicit soil, climate and crop management data were obtained from various sources detailed in “Experimental Design, Materials and Methods” section below. N₂O mitigation potential were then quantified under four scenarios of excess nitrogen reduction (i.e. 25%, 50%, 75% and 100% reduction of excess nitrogen). We believe that the dataset is a valuable source of information to assess N₂O emissions and mitigation measures from maize and wheat fields and to make informed decision. Countries can use this dataset to determine emissions reduction targets in their nationally determined contributions (NDCs) from agricultural sector.

Meta-analysis of yield and nitrous oxide outcomes for nitrogen management in agriculture

Improved nitrogen (N) use is key to future food security and environmental sustainability. While many regions still experience N shortages, agriculture is the leading global emitter of N₂ O due to losses exacerbated by N surpluses in other regions. In order to sustainably maintain or increase food production, farmers and their advisors need a comprehensive and actionable understanding of how nutrient management affects both yield and N₂ O emissions, particularly in tropical and subtropical agroecosystems. We performed a meta-analysis to determine the effect of N management and other factors on N₂ O emissions, plant N uptake, and yield. Our analysis demonstrates that performance indicators-partial N balance and partial factor productivity-predicted N₂ O emissions as well as or better than N rate. While we observed consistent production and environmental benefits with enhanced-efficiency fertilizers, we noted potential trade-offs between yield and N₂ O emissions for fertilizer placement. Furthermore, we observed confounding effects due to management dynamics that co-vary with nutrient application practices, thus challenging the interpretation of the effect of specific practices such as fertilization frequency. Therefore, rather than providing universally prescriptive management for N₂ O emission reduction, our evidence supports mitigation strategies based upon tailored nutrient management approaches that keep N balances within safe limits, so as to minimize N₂ O emissions while still achieving high crop yields. The limited evidence available suggests that these relationships hold for temperate, tropical, and subtropical regions, but given the potential for expansion of N use in crop production, further N₂ O data collection should be prioritized in under-represented regions such as Sub-Saharan Africa.

Cost-effective opportunities for climate change mitigation in Indian agriculture

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.

Long-term impact of conservation agriculture and diversified maize rotations on carbon pools and stocks, mineral nitrogen fractions and nitrous oxide fluxes in inceptisol of India

Given the increasing scarcity of production resources such as water, energy and labour coupled with growing climatic risks, maize-based production systems could be potential alternatives to intensive rice-wheat (RW) rotation in western Indo-Gangetic Plains (IGP). Conservation agriculture (CA) in maize systems has been widely promoted for minimizing soil degradation and ensuring sustainability under emerging climate change scenario. Such practices are also believed to provide mitigation co-benefits through reduced GHG emission and increased soil carbon sequestration. However, the combined effects of diversified crop rotations and CA-based management on GHG mitigation potential and other co-benefits are generally over looked and hence warrant greater attention. A field trial was conducted for 5-years to assess the changes in soil organic carbon fractions, mineral-N, N₂O emission and global warming potential (GWP) of maize-based production systems under different tillage & crop establishment methods. Four diversified cropping systems i.e. maize-wheat-mungbean (MWMb), maize-chickpea-Sesbania (MCS), maize-mustard-mungbean (MMuMb) and maize-maize-Sesbania (MMS) were factorially combined with three tillage & crop establishment methods i.e. zero tilled permanent beds (PB), zero-tillage flat (ZT) and conventional tillage (CT) in a split-plot design. After 5-years of continued experimentation, we recorded that across the soil depths, SOC content, its pools and mineral-N fractions were greatly affected by tillage & crop establishment methods and cropping systems. ZT and PB increased SOC stock (0-30 cm depth) by 7.22-7.23 Mg C ha^-1 whereas CT system increased it only by 0.88 Mg C ha^-1as compared to initial value. Several researchers reported that SOC & mineral-N fraction contents in the top 30 cm soil depth are correlated with N₂O-N emission. In our study, global warming potential (GWP) under CT system was higher by 18.1 and 17.4%, compared to CA-based ZT and PB, respectively. Among various maize systems, GWP of MMS were higher by 11.2, 6.7 and 6.6%, compared that of MWMb (1212 kg CO₂-eq. ha^-1), MCS (1274 kg CO₂-eq. ha^-1) and MMuMb (1275 kg CO₂-eq. ha^-1), respectively. The results of our study suggest that CA and diversified crop rotations should be promoted in north-western IGP and other similar agro-ecologies across the globe for ensuring food security, restoration of soil health and climate change mitigation, the key sustainable development goals (SDGs).

Identifying high-yield low-emission pathways for the cereal production in South Asia

Increasing agricultural production to meet the growing demand for food whilst reducing agricultural greenhouse gas (GHG) emissions is the major challenge under the changing climate. To develop long-term policies that address these challenges, strategies are needed to identify high-yield low-emission pathways for particular agricultural production systems. In this paper, we used bio-physical and socio-economic models to analyze the impact of different management practices on crop yield and emissions in two contrasting agricultural production systems of the Indo-Gangetic Plain (IGP) of India. The result revealed the importance of considering both management and socio-economic factors in the development of high-yield low-emission pathways for cereal production systems. Nitrogen use rate and frequency of application, tillage and residue management and manure application significantly affected GHG emissions from the cereal systems. In addition, various socio-economic factors such as gender, level of education, training on climate change adaptation and mitigation and access to information significantly influenced the adoption of technologies contributing to high-yield low-emission pathways. We discussed the policy implications of these findings in the context of food security and climate change.

Direct Nitrous Oxide Emissions From Tropical And Sub-Tropical Agricultural Systems - A Review And Modelling Of Emission Factors

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.

Greenhouse gas emissions from agricultural food production to supply Indian diets: Implications for climate change mitigation

Agriculture is a major source of greenhouse gas (GHG) emissions globally. The growing global population is putting pressure on agricultural production systems that aim to secure food production while minimising GHG emissions. In this study, the GHG emissions associated with the production of major food commodities in India are calculated using the Cool Farm Tool. GHG emissions, based on farm management for major crops (including cereals like wheat and rice, pulses, potatoes, fruits and vegetables) and livestock-based products (milk, eggs, chicken and mutton meat), are quantified and compared. Livestock and rice production were found to be the main sources of GHG emissions in Indian agriculture with a country average of 5.65 kg CO₂eq kg^-1 rice, 45.54 kg CO₂eq kg^-1 mutton meat and 2.4 kg CO₂eq kg^-1 milk. Production of cereals (except rice), fruits and vegetables in India emits comparatively less GHGs with <1 kg CO₂eq kg^-1 product. These findings suggest that a shift towards dietary patterns with greater consumption of animal source foods could greatly increase GHG emissions from Indian agriculture. A range of mitigation options are available that could reduce emissions from current levels and may be compatible with increased future food production and consumption demands in India.