Identifying urban, transportation, and socioeconomic characteristics across US zip codes affecting CO2 emissions: A decision tree analysis
Understanding the factors contributing to CO2 emissions is pivotal for informed policy-making and sustainable urban development. This study probes the interconnections between urban attributes, transportation patterns, and socioeconomic factors concerning CO2 emissions using Decision Tree analysis a...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
KeAi Communications Co., Ltd.
2025-06-01
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| Series: | Energy and Built Environment |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666123324000102 |
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| Summary: | Understanding the factors contributing to CO2 emissions is pivotal for informed policy-making and sustainable urban development. This study probes the interconnections between urban attributes, transportation patterns, and socioeconomic factors concerning CO2 emissions using Decision Tree analysis across a substantial dataset of US zip codes. The dataset was carefully prepared to ensure accuracy and relevance, considering temporal, geographical, and socioeconomic heterogeneity. The Decision Tree algorithm was applied iteratively to evaluate variable interactions and identify critical thresholds that influence carbon emissions. The findings of this study shed light on the key drivers of CO2 emissions across US zip codes. The analysis reveals significant variations in the relative importance of different factors in different regions, emphasizing the need for localized and tailored strategies to address carbon reduction targets effectively. The research provides a more holistic understanding that can drive effective urban planning and energy policies, ultimately contributing to the global effort to reduce carbon emissions and combat climate change. The findings from this research underscore the importance of multidisciplinary approaches in addressing environmental challenges and highlight the necessity for continuous innovation in analytical methodologies to keep pace with the evolving urban landscapes. |
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| ISSN: | 2666-1233 |