Household Energy Consumption And Related Emissions From Biomass And Non-renewable Energy Sources: A Case Study From Bangladesh

In developing countries, access to clean and equal energy is often hindered due to lack of understanding of households’ energy consumption pattern and socioeconomic factors. In Bangladesh, only 61% of the population has access to electricity, with a per capita consumption of 293.03 kWh a⁻¹ (kilowatt hour per year) (REN21, 2017). About 91% of the country’s total electricity generation depends on non-renewable energy sources (natural gas, furnace oil, diesel, coal), with natural gas being the largest contributor (69%) (BPDB, 2015). However, within the next few decades, Bangladesh will be aiming to confront the serious energy crisis owing to declining reserves of natural gas and coal.

Renewable energy sources represented only about 1% of the total electricity generation in 2015 (BPDB, 2015), which the GOB has envisioned to reach up to 10% by 2020. However, locally available traditional forms of biomass in terms of leaves and forest residues, agricultural residues, manure etc are used via direct combustion mostly in rural and remote areas. This study explores household-level energy consumption patterns, relevant socioeconomic factors across the three income groups (rich, medium-income, poor households) and carbon-emissions from various energy sources.

This explorative study revealed that households greatly depended on biomass energy that accounts for 87% of their monthly energy consumption. The major fuels, including firewood, leaves, and twigs, were used mainly for cooking, and these were collected mainly from households’ homestead forests. This over-dependence on the homestead forest, however, may lead to deforestation and degradation of the resources, thus causing a shortage of source of fuels in future. Other sources, such as forest plantation and the market can reduce the over-dependence on a homestead forest. In addition, poor households inhabiting nearby public forests also collected biomass from forests.

Total monthly energy expenditure was 23.96 US$ per household, of which biomass energy contributed more than double as much as for non-renewables. Households spent 10% of their monthly income for biomass energy and 4% for non-renewable energy. Poor households had to spend much more of their income and energy budget on biomass, while the financially solvent households invested in non-renewables.

Rich households spent significantly more money on energy, especially for firewood, electricity, liquid petroleum gas (LPG), and candles than the relatively lower income groups. These fuels were unaffordable for the poor households due to their high prices. Oppositely, leaves and twigs as well as manure, on which the poor households spent more money than the households with higher incomes. This was because higher prices of firewood forced the poor households to buy leaves and twigs, a lower-grade biomass fuel, for which they spent most of their energy budget and income. However, the collection of leaves and manure may lower the soil fertility, resulting in environmental degradation.

Income, education, and landholdings of households were the key drivers in the consumption of fuels. This indicates that households with higher incomes, literacy rate, and large landholdings are more likely to shift from less convenient and dirty fuels (e.g., kerosene, and leaves and twigs) to more convenient fuels (firewood, electricity, candles, and LPG), as was also found in other Asian countries, including Nepal, Bhutan, and India.

The households’ consumption of biomass was 555% higher in comparison with that of non-renewables. However, the burning of firewood for cooking caused the highest carbon emissions, accounting for 192 kg carbon dioxide equivalent per household per month. This might be due to the fact that the use of traditional cooking stoves released higher emissions because of incomplete combustion compared to improved cooking stoves (ICS). Therefore, the efficient use of biomass is essential to reduce emissions and avoid fossil fuels. For example, in Bangladesh, meeting total energy demand and concurrently avoiding fossil fuels would be possible by using merely one-third of the overall biomass available (Hossen et al. 2017).

The finding of this study is in line with the aims of the Renewable Energy Policy 2008 of Bangladesh: to harness the potential and dissemination of renewable energy resources and their technologies, for example, biomass gasification and clean energy promotion for clean development mechanism (CDM), while substituting the non-renewable energy resources (GOB PD, 2011).

Biomass-based power plants and gasification at small scale, and introducing ICS under the CDM would result in both less dependency on the non-renewables and carbon emissions reductions while fulfilling the local demand of electricity and heat for lighting, heating, and cooking. The CDM forestry programs, by implementing it in homestead and cropland agroforestry, would be a sustainable source of biomass fuels for clean energy, while preventing overexploitation of public and homestead forests, and simultaneously generating income supports for poor households through carbon trading. These findings offer insights to enhance household-level clean energy access in Bangladesh and countries alike.

These findings are described in the article entitled A comparative study on household level energy consumption and related emissions from renewable (biomass) and non-renewable energy sources in Bangladesh, recently published in the journal Energy Policy. This work was conducted by Baul T. K. (University of Chittagong; University of Eastern Finland) and Datta D. (University of Chittagong) and Alam A. (University of Eastern Finland).

References:

1. BPDB, 2015. Annual report 2014–2015. Bangladesh Power Development Board, Dhaka, Bangladesh.
2. Hossen, M.M., Rahman, A.H.M.S., Kabir, A.S., Hasan, M.M.F., Ahmed, S., 2017. Systematic assessment of the availability and utilization potential of biomass in Bangladesh. Renew. Sustain. Energy Rev. 67, 94–105. http://dx.doi.org/10.1016/j.rser.2016.09.008.
3. REN21, 2017. Renewables 2017 Global status report. 〈http://www.map.ren21.net/GSR/GSR2017.pdf〉. (accessed 26 April 2018).