Electricity consumption patterns within cities: application of a data-driven settlement characterization method
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 ma...
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Published in | International journal of digital earth Vol. 13; no. 1 |
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Main Authors | , , , , , , |
Format | Journal Article |
Language | English |
Published |
United States
Taylor & Francis
21.01.2019
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Subjects | |
Online Access | Get full text |
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Summary: | 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. |
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Bibliography: | USDOE AC05-00OR22725 |
ISSN: | 1753-8947 1753-8955 |