Alternate wetting and drying in irrigated rice

Alternate wetting and drying (AWD) is a rice management practice that reduces water use by up to 30% and can save farmers money on irrigation and pumping costs. AWD reduces methane emissions by 48% without reducing yield. Efficient nitrogen use and application of organic inputs to dry soil can further reduce emissions. Incentives for adoption of AWD are higher when farmers pay for pump irrigation

Measure The Chain: Tools For Assessing GHG Emissions In Agricultural Supply Chains

Climate change poses a number of risks to food and agricultural companies that impact their corporate performance and long-term value creation. Land use change (LUC) from commodity crop and subsistence agriculture, particularly in Latin America and Southeast Asia, where the production of beef, soy, palm oil and cocoa have led to 87 percent of all tree cover loss between 2001 and 2015, have an outsized impact on greenhouse gas emissions (FAO, 2016). Of the emissions generated by food systems, most—over 80 percent—stem directly from agricultural production and its associated land-use change (Vermeulen et al., 2012). For most food and agricultural companies, these emissions are considered “scope 3” emissions: upstream or downstream emissions not under direct control of the company (i.e. indirect emissions) (Figure 1). While many companies have for some time estimated and reported greenhouse gas emissions (GHG) from company facilities, company vehicles and purchased electricity (i.e. scope 1 and scope 2 emissions), companies are increasingly recognizing the importance of also measuring and disclosing their scope 3 emissions. Measuring emissions from agricultural production and LUC within corporate value chains is both essential and difficult. Agricultural emissions are driven by complex interactions between natural and human processes, and estimating these emissions with any accuracy requires data on agricultural management, soil, and climatic factors at the site of production. For a company producing multiple products and sourcing from potentially thousands of producers, collecting such data can be daunting. This report provides an overview of available resources (i.e. standards, methodologies, tools, and calculators) for assessing emissions from agricultural production and agriculturally-driven LUC. Resources were assessed in terms of how they could help companies track progress on reduction targets for agricultural emissions. The collection of tools and approaches included in this report was assembled from: company reports to CDP; conversations with companies attending a March 2018 workshop on metrics for climate-smart agriculture hosted by the World Business Council for Sustainable Development (WBCSD) and the CGIAR Research Program on Climate Change, Agriculture and Food Security (CCAFS); conversations with service providers in the GHG accounting field; published reviews of agricultural GHG accounting tools; and the authors’ previous knowledge. The report is limited to tools and approaches specific to agricultural commodities, with a limited discussion on the most widely used frameworks for corporate GHG inventories generally

National contributions to climate change mitigation from agriculture: allocating a global target

Globally, agriculture and related land use change contributed about 17% of the world’s anthropogenic GHG emissions in 2010 (8.4 GtCO2e yr−1), making GHG mitigation in the agriculture sector critical to meeting the Paris Agreement’s 2°C goal. This article proposes a range of country-level targets for mitigation of agricultural emissions by allocating a global target according to five approaches to effort-sharing for climate change mitigation: responsibility, capability, equality, responsibility-capability-need and equal cumulative per capita emissions. Allocating mitigation targets according to responsibility for total historical emissions or capability to mitigate assigned large targets for agricultural emission reductions to North America, Europe and China. Targets based on responsibility for historical agricultural emissions resulted in a relatively even distribution of targets among countries and regions. Meanwhile, targets based on equal future agricultural emissions per capita or equal per capita cumulative emissions assigned very large mitigation targets to countries with large agricultural economies, while allowing some densely populated countries to increase agricultural emissions. There is no single ‘correct’ framework for allocating a global mitigation goal. Instead, using these approaches as a set provides a transparent, scientific basis for countries to inform and help assess the significance of their commitments to reducing emissions from the agriculture sector. Key policy insights Meeting the Paris Agreement 2°C goal will require global mitigation of agricultural non-CO2 emissions of approximately 1 GtCO2e yr−1 by 2030. Allocating this 1 GtCO2e yr−1 according to various effort-sharing approaches, it is found that countries will need to mitigate agricultural business-as-usual emissions in 2030 by a median of 10%. Targets vary widely with criteria used for allocation. The targets calculated here are in line with the ambition of the few countries (primarily in Africa) that included mitigation targets for the agriculture sector in their (Intended) Nationally Determined Contributions. For agriculture to contribute to meeting the 2°C or 1.5°C targets, countries will need to be ambitious in pursuing emission reductions. Technology development and transfer will be particularly important

Agriculture's contribution to national emissions

This info note offers an overview of the distribution of agricultural emissions among countries and the relative contribution of agriculture to national emissions. It is based on three data sources: the FAOSTAT database of greenhouse gas emissions from agriculture, United States Environmental Protection Agency (EPA) global emission estimates for 2010 and national reports to the United Nations Framework Convention on Climate Change (UNFCCC).

What is the scientific basis for climate-smart agriculture?

Climate-smart agriculture (CSA) is a systematic approach to agricultural development. It intends to address climate change and food security challenges simultaneously across levels, from field management to national policy, with goals to 1) improve food security and agricultural productivity, 2) increase the resilience of farming systems to climate change, and 3) mitigate greenhouse gas (GHG) emissions or sequester carbon. After the introduction of the CSA concept in 2010, development organizations, national governments, and donors have quickly adopted a “climate-smart” agenda

10 best bet innovations for adaptation in agriculture: A supplement to the UNFCCC NAP Technical Guidelines

Faced with the triple challenges of achieving food security, adapting to the impacts of climate change, and reducing emissions, agriculture has been prioritized by countries as a sector for climate action. The national process of formulating and implementing National Adaptation Plans, which gives effect to the ambitions set out in the Intended Nationally Determined Contributions of countries, is a key instrument that will not only facilitate access to resources, but also advance best practice and implementation of proven and effective adaptation actions. In order to support countries in the elaboration of their National Adaptation Plans, this paper aims to tap into agricultural research for development conducted by CGIAR Centers and research programs, to identify best bet innovations for adaptation in agriculture, which can help achieve food security under a changing climate, while also delivering co-benefits for environmental sustainability, nutrition and livelihoods

Improved ruminant genetics: Implementation guidance for policymakers and investors

Genetics makes use of natural variation among animals. Selecting preferred animals as parents can yield permanent and cumulative improvements in the population. More efficient animals can greatly reduce greenhouse gas emissions and feed costs. Breeding, including cross-breeding between indigenous and imported species, can also improve resilience to diseases and heat stress and increase reproductive performance

Reusing Distance Courseware to Enable Blended Delivery: A New Zealand Case Study

Digital distance course materials can be used across different forms of education delivery. In particular, courseware designed for asynchronous digital distance education can serve as the basis for blended learning, which features a different teaching role and fuller interpersonal experience. Blended learning can be used to extend programme opportunities across population regions where a full, lecture-based model might not be viable. This case study explores the experiences of three regional polytechnics in New Zealand that adopted and modified courseware created for digital distance learners studying asynchronously. The courseware was used to provide local students with more flexible study options, drawing on high quality courseware that had been centrally created by a team of experienced courseware designers and Subject Matter Experts (SMEs)

Agriculture's prominence in the INDCs

Analysis of agriculture in countries’ climate change mitigation and adaptation strategies finds: Most Parties to the UNFCCC include agriculture in their mitigation targets (80%) and adaptation strategies (64%); Non-annex 1 Parties note the need for international financial support to implement their INDCs and raise the ambition of their contributions; For countries to meet their targets, climate finance will need to address agriculture

Reducing the costs of GHG estimates in agriculture to inform low emissions development: Report from an international workshop

Sixty practitioners, policy makers and scientists reviewed and shared knowledge on the available robust and low-cost methods and data for GHG emission estimation in agriculture in a CCAFS/FAO workshop in Rome, October 2014. The participants emphasized that iterative interaction between data collection, data quality assurance and modelling is needed as well as protocol development for GHG estimation in agriculture. Emission factor development is also key, including in regional, national and sub-national levels. Easily accessible platforms where to store data and models would enhance sharing and better coordination. The country level coordination is also important in order to harmonize data collection practices, tools and methods. As countries are at different level in terms of GHG inventories and access to data, capacity need assessment will help providing right type, targeted support for capacity development. It is also important to ensure the policy level awareness raising, engagement and commitment. Linking adaptation and mitigation will reduce data needs and provide incentives for action. New tools for estimation are being developed, including remote sensing and crowd-sourcing, modeling and utilizing the national surveys and agriculture censuses that can help reduce data costs