Relationship between Household Dynamics, Biomass Consumption, and Carbon Emissions in Pakistan

Abstract

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.

Impact of Indoor Air Pollution in Pakistan—Causes and Management

“…Pakistan is a predominantly rural country having an average family size of five to seven members [84]. As per an estimate, about 90% of the rural and 50% of the urban population rely on biomass fuels in Pakistan [85][86][87]. However, this consumption was decreased for the population with improved income and economic conditions [88].…”

Towards Achieving 100% Renewable Energy Supply for Sustainable Climate Change in Pakistan

“…Sixty-two percent of Pakistan's population lives in villages and rural areas, making it an agricultural nation. These regions have employment opportunities in agriculture and vocations that are directly or indirectly related to agriculture [52]. The main source of energy generation in villages is traditional biomass, such as cow dung, fuel woods, and crop wastes [52].…”

“…These regions have employment opportunities in agriculture and vocations that are directly or indirectly related to agriculture [52]. The main source of energy generation in villages is traditional biomass, such as cow dung, fuel woods, and crop wastes [52]. According to [53], there are around 160 million animals in Pakistan, with a 9% yearly growth rate.…”

Supply-demand bilateral energy structure optimization and carbon emission reduction in Shandong rural areas based on long-range energy alternatives planning model

“…Many studies in literature have focused on demand-side or supply-side optimization of energy for rural residents using different models. As for the rural energy demand side, the researches mainly concentrated on energy consumption characteristics (Wu et al, 2019;Zou and Luo, 2019;Yang et al, 2021) and optimization of consumption structure (Jin et al, 2019;Hong, 2020;Wang et al, 2021;Imran et al, 2022). Zou et al (Zou and Luo, 2019) and Wu et al (Wu et al, 2019) proved that the current energy consumption of rural residents was dominated by biomass energy, and could be transformed to clean energy in the future.…”

“…Yang et al (Yang et al, 2021) believed that heating in winter was a key factor affecting the total energy consumption of rural residents, and there existed significant differences in biomass energy consumption among different users. Aiming at optimizing consumption structure, GM (1, 1) and MARKAL model (Hong, 2020), LMDI model (Wang et al, 2021) and STIRPAT model (Imran et al, 2022) were used to evaluate the factors affecting rural energy consumption.…”