Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar
This study investigates the water – electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors. Due to inadequate research on spatial modelling of water – electricity consumption in the context of the COVID-19 pandemic, this study investigated geographical block...
محفوظ في:
| المؤلف الرئيسي: | |
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| التنسيق: | article |
| منشور في: |
2021
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| الموضوعات: | |
| الوصول للمادة أونلاين: | http://dx.doi.org/10.1016/j.apenergy.2021.117864 https://www.sciencedirect.com/science/article/pii/S0306261921011867 http://hdl.handle.net/10576/55731 |
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| _version_ | 1857415085228556288 |
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| author | Ammar, Abulibdeh |
| author_facet | Ammar, Abulibdeh |
| author_role | author |
| dc.creator.none.fl_str_mv | Ammar, Abulibdeh |
| dc.date.none.fl_str_mv | 2021-09-17 2024-06-02T10:37:37Z |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | http://dx.doi.org/10.1016/j.apenergy.2021.117864 Abulibdeh, A. (2021). Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar. Applied Energy, 304, 117864. 0306-2619 https://www.sciencedirect.com/science/article/pii/S0306261921011867 http://hdl.handle.net/10576/55731 304 1872-9118 |
| dc.language.none.fl_str_mv | en |
| dc.publisher.none.fl_str_mv | Elsevier |
| dc.rights.none.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Water-electricity consumption Socioeconomic sectors Spatial modeling Statistical modeling Qatar |
| dc.title.none.fl_str_mv | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| dc.type.none.fl_str_mv | Article info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article |
| description | This study investigates the water – electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors. Due to inadequate research on spatial modelling of water – electricity consumption in the context of the COVID-19 pandemic, this study investigated geographical block-level variation in water and electricity consumption in Doha city of Qatar. Spatial analyses were performed to investigate the spatial differences in each sector. Five geospatial techniques in a Geographical Information System (GIS) context were used in the study. Moran’s I, Anselin Local Moran's I, and Getis-Ord Gi∗ statistics tools were used to identify the hot spots and cold spots of water and electricity consumption in each sector. Furthermore, Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) models were employed to investigate the spatial relationship between water and electricity consumption during the pandemic year. The findings show that there is a distinction in water and electricity consumption at the block level across all sectors and over time. Hot spot and spatial regression analysis reveal spatial and temporal heterogeneities in the study area across the six socioeconomic sectors. The intensity of hot spots of water and electricity consumption are found in the southern and western parts of the city due to high population density and the concentration of the commercial and industrial areas. Furthermore, analyzing the spatiotemporal correlation between the water and electricity consumption across the six sectors shows variation within and between these sectors over space and time. The results show a positive relationship between water and electricity consumption in some blocks and over time of each sector. During the lockdown phase, strong positive correlation between water and electricity consumption have exist in the residential sector due to extra water and electricity footprints in this sector. Conversely, the water and electricity consumption were positively correlated but declined in the industrial and commercial sector due to the curtailment in production, economic activities, and reduction in people’s mobility. Mapping the hot spot blocks and the blocks with high relationship between water and electricity consumption could provide useful insight to decision-makers for targeted interventions. |
| eu_rights_str_mv | openAccess |
| format | article |
| id | qu_4d190d0403d6fa30854623d053a1dfa3 |
| identifier_str_mv | Abulibdeh, A. (2021). Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar. Applied Energy, 304, 117864. 0306-2619 304 1872-9118 |
| language_invalid_str_mv | en |
| network_acronym_str | qu |
| network_name_str | Qatar University repository |
| oai_identifier_str | oai:qspace.qu.edu.qa:10576/55731 |
| publishDate | 2021 |
| publisher.none.fl_str_mv | Elsevier |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| spelling | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, QatarAmmar, AbulibdehWater-electricity consumptionSocioeconomic sectorsSpatial modelingStatistical modelingQatarThis study investigates the water – electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors. Due to inadequate research on spatial modelling of water – electricity consumption in the context of the COVID-19 pandemic, this study investigated geographical block-level variation in water and electricity consumption in Doha city of Qatar. Spatial analyses were performed to investigate the spatial differences in each sector. Five geospatial techniques in a Geographical Information System (GIS) context were used in the study. Moran’s I, Anselin Local Moran's I, and Getis-Ord Gi∗ statistics tools were used to identify the hot spots and cold spots of water and electricity consumption in each sector. Furthermore, Ordinary Least Square (OLS) and Geographically Weighted Regression (GWR) models were employed to investigate the spatial relationship between water and electricity consumption during the pandemic year. The findings show that there is a distinction in water and electricity consumption at the block level across all sectors and over time. Hot spot and spatial regression analysis reveal spatial and temporal heterogeneities in the study area across the six socioeconomic sectors. The intensity of hot spots of water and electricity consumption are found in the southern and western parts of the city due to high population density and the concentration of the commercial and industrial areas. Furthermore, analyzing the spatiotemporal correlation between the water and electricity consumption across the six sectors shows variation within and between these sectors over space and time. The results show a positive relationship between water and electricity consumption in some blocks and over time of each sector. During the lockdown phase, strong positive correlation between water and electricity consumption have exist in the residential sector due to extra water and electricity footprints in this sector. Conversely, the water and electricity consumption were positively correlated but declined in the industrial and commercial sector due to the curtailment in production, economic activities, and reduction in people’s mobility. Mapping the hot spot blocks and the blocks with high relationship between water and electricity consumption could provide useful insight to decision-makers for targeted interventions.This publication was made possible by an NPRP award [ NPRP13S-0206-200272 ] from the Qatar National Research Fund (a member of Qatar Foundation). The open access publication of this article was funded by the Qatar National Library (QNL) .Elsevier2024-06-02T10:37:37Z2021-09-17Articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://dx.doi.org/10.1016/j.apenergy.2021.117864Abulibdeh, A. (2021). Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar. Applied Energy, 304, 117864.0306-2619https://www.sciencedirect.com/science/article/pii/S0306261921011867http://hdl.handle.net/10576/557313041872-9118enhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:qspace.qu.edu.qa:10576/557312024-07-23T15:53:53Z |
| spellingShingle | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar Ammar, Abulibdeh Water-electricity consumption Socioeconomic sectors Spatial modeling Statistical modeling Qatar |
| status_str | publishedVersion |
| title | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| title_full | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| title_fullStr | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| title_full_unstemmed | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| title_short | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| title_sort | Spatiotemporal analysis of water-electricity consumption in the context of the COVID-19 pandemic across six socioeconomic sectors in Doha City, Qatar |
| topic | Water-electricity consumption Socioeconomic sectors Spatial modeling Statistical modeling Qatar |
| url | http://dx.doi.org/10.1016/j.apenergy.2021.117864 https://www.sciencedirect.com/science/article/pii/S0306261921011867 http://hdl.handle.net/10576/55731 |