Exploring greenhouse gas mitigation strategies for agriculture in Africa: The case of Nigeria.
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ABSTRACT:
SUBMITTER: Dioha MO
PROVIDER: S-EPMC7320083 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundPolicy decisions regarding climate change mitigation are increasingly incorporating the beneficial and adverse health impacts of greenhouse gas emission reduction strategies. Studies of such co-benefits and co-harms involve modeling approaches requiring a range of analytic decisions that affect the model output.ObjectiveOur objective was to assess analytic decisions regarding model framework, structure, choice of parameters, and handling of uncertainty when modeling health co-benefits, and to make recommendations for improvements that could increase policy uptake.MethodsWe describe the assumptions and analytic decisions underlying models of mitigation co-benefits, examining their effects on modeling outputs, and consider tools for quantifying uncertainty.DiscussionThere is considerable variation in approaches to valuation metrics, discounting methods, uncertainty characterization and propagation, and assessment of low-probability/high-impact events. There is also variable inclusion of adverse impacts of mitigation policies, and limited extension of modeling domains to include implementation considerations. Going forward, co-benefits modeling efforts should be carried out in collaboration with policy makers; these efforts should include the full range of positive and negative impacts and critical uncertainties, as well as a range of discount rates, and should explicitly characterize uncertainty. We make recommendations to improve the rigor and consistency of modeling of health co-benefits.ConclusionModeling health co-benefits requires systematic consideration of the suitability of model assumptions, of what should be included and excluded from the model framework, and how uncertainty should be treated. Increased attention to these and other analytic decisions has the potential to increase the policy relevance and application of co-benefits modeling studies, potentially helping policy makers to maximize mitigation potential while simultaneously improving health.
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Project description:This is the first structured review to identify and summarize research on lifestyle choices that improve health and have the greatest potential to mitigate climate change. Two literature searches were conducted on: (1) active transport health co-benefits, and (2) dietary health co-benefits. Articles needed to quantify both greenhouse gas emissions and health or nutrition outcomes resulting from active transport or diet changes. A data extraction tool (PRISMA) was created for article selection and evaluation. A rubric was devised to assess the biases, limitations and uncertainties of included articles. For active transport 790 articles were retrieved, nine meeting the inclusion criteria. For diet 2524 articles were retrieved, 23 meeting the inclusion criteria. A total of 31 articles were reviewed and assessed using the rubric, as one article met the inclusion criteria for both active transport and diet co-benefits. Methods used to estimate the effect of diet or active transport modification vary greatly precluding meta-analysis. The scale of impact on health and greenhouse gas emissions (GHGE) outcomes depends predominately on the aggressiveness of the diet or active transport scenario modelled, versus the modelling technique. Effective mitigation policies, infrastructure that supports active transport and low GHGE food delivery, plus community engagement are integral in achieving optimal health and GHGE outcomes. Variation in culture, nutritional and health status, plus geographic density will determine which mitigation scenario(s) best suit individual communities.
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Project description:As a major contributor to agricultural greenhouse gas (GHG) emissions, it has been suggested that reducing animal agriculture or consumption of animal-derived foods may reduce GHGs and enhance food security. Because the total removal of animals provides the extreme boundary to potential mitigation options and requires the fewest assumptions to model, the yearly nutritional and GHG impacts of eliminating animals from US agriculture were quantified. Animal-derived foods currently provide energy (24% of total), protein (48%), essential fatty acids (23-100%), and essential amino acids (34-67%) available for human consumption in the United States. The US livestock industry employs 1.6 × 106 people and accounts for $31.8 billion in exports. Livestock recycle more than 43.2 × 109 kg of human-inedible food and fiber processing byproducts, converting them into human-edible food, pet food, industrial products, and 4 × 109 kg of N fertilizer. Although modeled plants-only agriculture produced 23% more food, it met fewer of the US population's requirements for essential nutrients. When nutritional adequacy was evaluated by using least-cost diets produced from foods available, more nutrient deficiencies, a greater excess of energy, and a need to consume a greater amount of food solids were encountered in plants-only diets. In the simulated system with no animals, estimated agricultural GHG decreased (28%), but did not fully counterbalance the animal contribution of GHG (49% in this model). This assessment suggests that removing animals from US agriculture would reduce agricultural GHG emissions, but would also create a food supply incapable of supporting the US population's nutritional requirements.
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