Every person consumes a different amount of energy based on daily behaviours influenced by their location and income. People in rural village presumably use less electricity compared to urban residents. Some working groups seemed to consume more than others. In this “research for fun” project, I would like to explore the association between electricity consumption and people’s lifestyle.
A number of papers have discussed the correlation between lifestyle and energy consumption. For example, a study examines the human life schedule in the energy-intensive residential sector in Japan, including heating, cooling, lighting, and media/entertainment (Fong, et al., 2007). By collecting data about employment status, employment sector, family size, age, and city size to represent the life schedule, they found that retirees and housewives generally consume more household energy than working groups.
Another study in China also investigates the residents’ lifestyle factors on energy use and related CO2 emission, comparing between the urban and rural (Wei, et al., 2007). The energy use being considered by the authors is divided into 2 categories: (1) a lifestyle with the direct impact towards CO2 emissions, such as personal travel; and (2) indirect impact of lifestyles such as the expenditure of food, clothing, and other miscellaneous commodities.
In addition, a research project in the US analysed the residential electricity consumption in terms of social and behavioural patterns associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use (Sanquist, et al., 2012). They argued that this kind of lifestyle factors is better in projecting energy usage than income. In contrast, another researcher in Denmark suggested that lifestyle is not the most useful aspect in analysing household’s energy consumption (Gram-Hanssen, 2014).
While the above-mentioned studies provide a deep method in analysing a specific country, I would like to try performing a holistic approach by inspecting people’s lifestyles in many countries. The lifestyle aspects chosen in this study include employment status and the population living in urban areas. Additionally, I also want to take into account the number of people with internet access which represents a technological lifestyle.
Datasets
After looking through the list of indicators in the Gapminder codebook to collect my datasets, I have decided that I am particularly interested in electricity consumption per person, hence the variable electricperperson. The lifestyle aspects can be found in variables incomeperperson, employrate, and urbanrate. Additionally, I include variables femaleemployrate and internetuserate, to check any gender and digital gaps respectively. Furthermore, I think it would be interesting too to see the effect of the human lifestyle on the environment. The increase in energy consumption will lead to the rise of greenhouse gas (GHG) emissions. Therefore, I also add one variable co2emissions, as the primary GHG emitted from human activities.
In that regard, please find below my final personal codebook for this study.
| Variable | Description of Indicator | Main Source | |
| electricperperson | Electric power consumption measures the production of power plants and combined heat and power plants less transmission, distribution, and transformation losses and own use by heat and power plants (kWh per capita) | World Bank | |
| co2emissions | Carbon dioxide emissions from the burning of fossil fuels (metric tonnes of CO2 per person) | CDIAC (Carbon Dioxide Information Analysis Center) | |
| incomeperperson | Gross domestic product per person adjusted for differences in purchasing power (in international dollars, fixed 2011 prices, PPP based on 2011 ICP) | World Bank Work Development Indicators | |
| employrate | Total employees age 15+ (% of population). Percentage of total population, age above 15, that has been employed during the given year | International Labour Organization | |
| urbanrate | Urban population (% of total). Urban population refers to people living in urban areas as defined by national statistical offices (calculated using World Bank population estimates and urban ratios from the United Nations World Urbanization Prospects) | World Bank | |
| femaleemployrate | Percentage of female population, age above 15, that has been employed during the given year | International Labour Organization | |
| internetuserate | Internet users (per 100 people). Internet users are people with access to the worldwide network | World Bank |
Research Objectives
What is the impact of human lifestyle on electricity consumption and CO2 emissions?
References
- Fong, W.-K., Matsumoto, H., Lun, Y.-F., Kimura, R., 2007. Influences of Indirect Lifestyle Aspects and Climate on Household Energy Consumption. Journal of Asian Architecture and Building Engineering 6, 395–402. https://doi.org/10.3130/jaabe.6.395
- Gram-Hanssen, K., 2014. New needs for better understanding of household’s energy consumption – behaviour, lifestyle or practices? Architectural Engineering and Design Management 10, 91–107. https://doi.org/10.1080/17452007.2013.837251
- Sanquist, T.F., Orr, H., Shui, B., Bittner, A.C., 2012. Lifestyle factors in U.S. residential electricity consumption. Energy Policy 42, 354–364. https://doi.org/10.1016/j.enpol.2011.11.092
- Wei, Y.-M., Liu, L.-C., Fan, Y., Wu, G., 2007. The impact of lifestyle on energy use and CO2 emission: An empirical analysis of China’s residents. Energy Policy 35, 247–257. https://doi.org/10.1016/j.enpol.2005.11.020