Dataset Information

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

ABSTRACT: 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

SUBMITTER: Aziz S

PROVIDER: S-EPMC9301621 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Organic fertilizers have been shown to stimulate CH4 uptake from agricultural soils. Managing fertilizer application to maximize this effect and to minimize emission of other greenhouse gasses offers possibilities to increase sustainability of agriculture. To tackle this challenge, we incubated an agricultural soil with different organic amendments (compost, sewage sludge, digestate, cover crop residues mixture), either as single application or in a mixture and subjected it to different soil moisture concentrations using different amounts of organic amendments. GHG fluxes and in vitro CH4 oxidation rates were measured repeatedly, while changes in organic matter and abundance of GHG relevant microbial groups (nitrifiers, denitrifiers, methanotrophs, methanogens) were measured at the end of the incubation. Overall the dynamics of the analyzed GHGs differed significantly. While CO2 and N2O differed considerably between the treatments, CH4 fluxes remained stable. In contrast, in vitro CH4 oxidation showed a clear increase for all amendments over time. CO2 fluxes were mostly dependent on the amount of organic residue that was used, while N2O fluxes were affected more by soil moisture. Several combinations of amendments led to reductions of CO2, CH4, and/or N2O emissions compared to un-amended soil. Most optimal GHG balance was obtained by compost amendments, which resulted in a similar overall GHG balance as compared to the un-amended soil. However, compost is not very nutrient rich potentially leading to lower crop yield when applied as single fertilizer. Hence, the combination of compost with one of the more nutrient rich organic amendments (sewage sludge, digestate) provides a trade-off between maintaining crop yield and minimizing GHG emissions. Additionally, we could observe a strong increase in microbial communities involved in GHG consumption in all amendments, with the strongest increase associated with cover crop residue mixtures. Future research should focus on the interrelation of plants, soil, and microbes and their impact on the global warming potential in relation to applied organic amendments.

Project description:Agricultural production in Minqin Oasis, China, is commonly categorized as intensive crop production (ICP), integrated crop-livestock production (ICLP), intensive livestock production (confined feeding) (IFLP), and extensive livestock production (grazing) (EGLP). The objectives of the present study were to use a life cycle assessment technique to evaluate on-farm energy balances and greenhouse gas (GHG) emissions of agricultural production, and to compare the differences among the four systems. Data used in the present study were collected from published literature and face-to face questionnaires from 529 farms in eight towns (two towns per production system) within Minqin county. The ANOVA of averaged data from 2014 to 2015 indicated that the net energy ratio (Output/Input) for the EGLP system was significantly higher than that for any other system (P < 0.01), whereas the difference among other three systems were not significant. The EGLP system generated lower CO2-eq emissions per hectare of farmland than other systems (P < 0.01). Relating carbon economic efficiency to market values (US$) of agricultural products, indicated that the carbon economic efficiency (US$/kg CO2-eq) of the IFLP system was significantly greater than that of other systems (P < 0.01). The major GHG emission sources varied across the systems, that is, soil respiration is the dominant source in EGLP, while the main sources in IFLP are enteric methane and manure management; in ICLP major sources are enteric methane, soil respiration and fertilizer; and in ICP are soil respiration and fertilizer. The structural equation modelling analysis showed that livestock category was strongly linked to net income. The direct effects and total effects of water use efficiency, via its positive influence on energy balances and GHG emissions were much stronger than those of other dependent variables. The study provides important benchmark information to help develop sustainable agricultural production systems on energy balances and GHG emissions in northwestern China.

Project description:BackgroundFood production accounts for 30% of global greenhouse gas (GHG) emissions. Less environmentally sustainable diets are also often more processed, energy-dense and nutrient-poor. To date, the environmental impact of diets have mostly been based on a limited number of broad food groups.ObjectivesWe link GHG emissions to over 3000 foods, assessing associations between individuals' GHG emissions, their nutrient requirements and their demographic characteristics. We also identify additional information required in dietary assessment to generate more accurate environmental impact data for individual-level diets.MethodsGHG emissions of individual foods, including process stages prior to retail, were added to the UK Composition Of Foods Integrated Dataset (COFID) composition tables and linked to automated online dietary assessment for 212 adults over three 24-hour periods. Variations in GHG emissions were explored by dietary pattern, demographic characteristics and World Health Organization Recommended Nutrient Intakes (RNIs).ResultsGHG emissions estimates were linked to 98% (n = 3233) of food items. Meat explained 32% of diet-related GHG emissions; 15% from drinks; 14% from dairy; and 8% from cakes, biscuits and confectionery. Non-vegetarian diets had GHG emissions 59% (95% CI 18%, 115%) higher than vegetarian. Men had 41% (20%, 64%) higher GHG emissions than women. Individuals meeting RNIs for saturated fats, carbohydrates and sodium had lower GHG emissions compared to those exceeding the RNI.DiscussionPolicies encouraging sustainable diets should focus on plant-based diets. Substituting tea, coffee and alcohol with more sustainable alternatives, whilst reducing less nutritious sweet snacks, presents further opportunities. Healthier diets had lower GHG emissions, demonstrating consistency between planetary and personal health. Further detail could be gained from incorporating brand, production methods, post-retail emissions, country of origin, and additional environmental impact indicators.

Dataset Information

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

Graphic abstract

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets