Back to Search Start Over

Electricity consumption patterns within cities: application of a data-driven settlement characterization method.

Authors :
Roy Chowdhury, Pranab K.
Weaver, Jeanette E.
Weber, Eric M.
Lunga, Dalton
LeDoux, St. Thomas M.
Rose, Amy N.
Bhaduri, Budhendra L.
Source :
International Journal of Digital Earth; Jan2020, Vol. 13 Issue 1, p119-135, 17p
Publication Year :
2020

Abstract

Urban areas presently consume around 75% of global primary energy supply, which is expected to significantly increase in the future due to urban growth. Having sustainable, universal energy access is a pressing challenge for most parts of the globe. Understanding urban energy consumption patterns may help to address the challenges to urban sustainability and energy security. However, urban energy analyses are severely limited by the lack of urban energy data. Such datasets are virtually non-existent for the developing countries. As per current projections, most of the new urban growth is bound to occur in these data-starved regions. Hence, there is an urgent need of research methods for monitoring and quantifying urban energy utilization patterns. Here, we apply a data-driven approach to characterize urban settlements based on their formality, which is then used to assess intra-urban urban energy consumption in Johannesburg, South Africa; Sana'a, Yemen; and Ndola, Zambia. Electricity is the fastest growing energy fuel. By analyzing the relationship between the settlement types and the corresponding nighttime light emission, a proxy of electricity consumption, we assess the differential electricity consumption patterns. Our study presents a simple and scalable solution to fill the present data void to understand intra-city electricity consumption patterns. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
17538947
Volume :
13
Issue :
1
Database :
Complementary Index
Journal :
International Journal of Digital Earth
Publication Type :
Academic Journal
Accession number :
140852168
Full Text :
https://doi.org/10.1080/17538947.2018.1556355