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- W4386899008 abstract "This research paper explores the complex relationship between energy consumption and greenhouse gas emissions in different sectors and boroughs of London, with a focus on the impact of population density on energy consumption patterns and emissions. A quantitative approach is used to analyze data from the London Energy and Greenhouse Gas Inventory (LEGGI) dataset, employing a multiple linear regression method to develop a prediction model for greenhouse gas emissions based on energy consumption data. The accuracy and usefulness of this model are evaluated using statistical measures such as RMSE (Root Mean Square Error) and R2 (R-squared). Additionally, this study also examines the impact of the COVID-19 pandemic on energy consumption patterns in London boroughs and analyzes population growth trends and their corresponding changes in greenhouse gas emissions levels. The findings highlight the need for continued efforts to reduce greenhouse gas emissions across all sectors to mitigate the effects of climate change effectively." @default.
- W4386899008 created "2023-09-21" @default.
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- W4386899008 date "2023-08-25" @default.
- W4386899008 modified "2023-09-27" @default.
- W4386899008 title "A Comprehensive Analysis of The Correlation Between Electricity Usage and Greenhouse Gas Emissions in London Boroughs" @default.
- W4386899008 doi "https://doi.org/10.1109/iciis58898.2023.10253494" @default.
- W4386899008 hasPublicationYear "2023" @default.
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