量化和预测城市移动中的排放减少:一个物联网驱动的共享单车分析
Manuel Uche-Soria1, Bernardo Tabuenca2, Gonzalo Halcón-Gibert1
1Department of Engineering Organization, Business Administration and Statistics, Universidad Politécnica de Madrid, 28006 Madrid, Spain.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
自行车共享系统 (BSS) 在城市地区显著减少二氧化碳和氧化物排放. 这项研究提供了一个预测模型来量化这些环境效益,帮助可持续的城市规划.
科学领域:
- 环境科学 环境科学
- 城市规划 城市规划
- 运输工程 运输工程
背景情况:
- 解决城市空气质量和气候变化的紧迫性越来越大.
- 需要可持续的移动解决方案来减轻车辆的排放.
- 对共享自行车系统 (BSS) 的确切环境影响的有限探索.
研究的目的:
- 量化和预测来自马德里BSS使用的CO2和NOx排放量的减少.
- 开发和验证一个集成物联网传感器数据的先进预测模型.
- 为城市规划者和政策制定者提供一个工具,以评估和复制BSS环境效益.
主要方法:
- 实时物联网传感器数据与先进的预测模型的整合.
- 分析非线性和季节性流动性和排放模式.
- 预测因BSS使用而减少的CO2和NOx排放量.
主要成果:
- 预测模型在捕捉移动性和排放模式方面取得了高准确性.
- 通过实施框架,显著的能源节约得到了证明.
- 在马德里使用BSS导致的二氧化碳和氧化物排放量的量化减少.
结论:
- BSS为城市地区提供了证实的环境效益.
- 开发的框架是评估可持续城市流动性的强有力的工具.
- 这些发现支持在其他城市扩展和复制BSS分析,以改善空气质量.
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