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Over the years, the household sector has become an important energy consumer and the main source of greenhouse gas (GHG) emissions. The rural household sector has significant potential for emission reduction due to its heavy reliance on traditional fuels and technologies. A great number of academic studies have been undertaken to analyze patterns of household energy and their determinants around the globe, particularly in developing countries. However, little is known about the association between household dynamics and patterns of energy (biomass vs. non-renewable) use. This study aims to analyze the relationship between different household dynamics, such as household size, income, climate, availability of resources, markets, awareness, consumption of energy, and carbon emissions. The study uses the STIRPAT model to investigate the impact of income, household size, housing dimensions, clean energy, and market accessibility on energy consumption. The findings of the study reveal that biomass energy accounts for the majority of household energy consumption and dung has the highest share in total household energy consumption (39.11%) The consumption of biomass increased with the size of the household and decreased with the level of income. A 1 kgoe increase in biomass consumption resulted in a 15.355 kg increase in CO2 emissions; on the other hand, a 1 kgoe increase in non-renewable-energy consumption resulted in just a 0.8675 kg increase in CO2 emissions. The coefficients of housing unit size, distance from the LPG market, and livestock were the primary determinants for choosing any fuel. Having knowledge of modern cookstoves, clean energy, and the environmental impact of fuels reduced the consumption of both energy sources. Furthermore, it was found that households with a greater reliance on biomass emitted higher quantities of carbon compared to those with a low reliance on biomass. Based on the results of the study, it can be stated that a reduction in the use of biomass and non-renewable energy is possible with adequate interventions and knowledge.

Human capital is the most important strategic factor for development; as new technologies emerge, the market demand for better and healthier products and consumer demand in terms of quality and delivery time are changing. In today's world, it becomes increasingly important to know how information can be accessed, how it is adopted, and how it can be assimilated. In this respect, each country allocates budget for training, education, and extension according to its own conditions. This budget may be intended for rural community-based social assistance, but the economic and welfare effect is essential. In this way, it is aimed to increase the living standards of the families living in the rural areas. This will naturally contribute to national income and to the prosperity of society. The subject has been discussed generally in the world, especially in the case of Turkey. According to this, all over the world, particularly in developing countries, research and extension (R&E) is very important and should be considered at least as much as research and development (R&D). However, it will be ensured that societies meet with the technology produced. For this, the development of human resources should be emphasized and a suitable atmosphere should be prepared for this widespread prosperity.

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This study aimed to model energy use, energy efficiency, and greenhouse gas emissions in rain-fed wheat production by using a nonparametric data envelopment analysis (DEA) method. Data were collected through face-to-face interviews with 140 wheat farmers in 4 districts of Antalya Province. The energy inputs (independent variables) were human labor, seeds, chemical fertilizers, herbicides, and diesel fuel, and the energy output was the dependent variable. The results showed that the average energy consumption and the output energy for the studied wheat production system were 21. 07GJ ha−1 and 50. 99 GJ ha−1, respectively, and the total GHG emissions were calculated to be 592.12 kg CO2eq ha−1. Chemical fertilizer has the highest share of energy consumption and total GHG emissions. Based on the results from DEA, the technical efficiency of the farmers was found to be 0.81, while pure technical and scale efficiencies were 0.65 and 0.76, respectively. The results also highlighted that there is a potential opportunity to save approximately 14% (2.93 GJ ha−1) of the total energy consumption and consequently a 17% reduction in GHG emissions by following the optimal amounts of energy consumption while keeping the wheat yield constant. Efficient use of energy and reduction in GHG emissions will lead to resource efficiency and sustainable production, which is the main aim of the green economy.

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