Promoting Energy Efficiency and Emissions Reduction in Urban Areas with Key Performance Indicators and Data Analytics

Angel A. Juan (), Majsa Ammouriova, Veronika Tsertsvadze, Celia Osorio, Noelia Fuster and Yusef Ahsini
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Angel A. Juan: Research Center on Production Management and Engineering, Universitat Politècnica de València, 03801 Alcoy, Spain
Majsa Ammouriova: Computer Science Department, Universitat Oberta de Catalunya, 08018 Barcelona, Spain
Veronika Tsertsvadze: Research Center on Production Management and Engineering, Universitat Politècnica de València, 03801 Alcoy, Spain
Celia Osorio: Research Center on Production Management and Engineering, Universitat Politècnica de València, 03801 Alcoy, Spain
Noelia Fuster: Research Center on Production Management and Engineering, Universitat Politècnica de València, 03801 Alcoy, Spain
Yusef Ahsini: Research Center on Production Management and Engineering, Universitat Politècnica de València, 03801 Alcoy, Spain

Energies, 2023, vol. 16, issue 20, 1-19

Abstract: With the increasing demand for sustainable urban development, smart cities have emerged as a promising solution for optimizing energy usage, reducing emissions, and enhancing the quality of life for citizens. In this context, the combined use of key performance indicators (KPIs) and data analytics has gained significant attention as a powerful tool for promoting energy efficiency and emissions reduction in urban areas. This paper presents a comprehensive conceptual framework in which a series of KPIs are proposed to serve as essential metrics for guiding, monitoring, and assessing energy efficiency and emissions reduction levels in smart cities. Some of the included KPIs in the analysis are 'annual energy consumption per person', 'reduction in greenhouse gas emissions', 'public transport use', and 'adoption of renewable energy'. By incorporating these KPIs, city planners and policymakers can gain valuable insights into the effectiveness of sustainability initiatives. Furthermore, the paper explores how the integration of KPIs with data analytics can be used for monitoring and assessing the overall performance of the city in terms of energy efficiency, emissions reduction, and the enhancement of urban living conditions. Visualization tools, such as radar plots, and time series analysis forecasting methods allow data to be processed and patterns to be identified, enabling informed decision-making and efficient resource allocation. Real-life case studies of ongoing smart city projects are presented in the paper, which also provides a KPI comparison among different European cities, as well as models to forecast the evolution of KPIs related to energy usage and emissions reduction in different European cities.

Keywords: urban areas; energy efficiency; emissions reduction; key performance indicators; data analytics (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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