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ORIGINAL RESEARCH article

Front. Public Health
Sec. Environmental Health and Exposome
Volume 12 - 2024 | doi: 10.3389/fpubh.2024.1469578
This article is part of the Research Topic Multi-scale Urban Built Environment and Human Health View all 4 articles

How to improve public environmental health by facilitating metro usage on weekend: Exploring the non-linear and threshold impacts of the built environment

Provisionally accepted
Bozhezi Peng Bozhezi Peng Tao Wang Tao Wang Yi Zhang Yi Zhang *Chaoyang Li Chaoyang Li
  • Shanghai Jiao Tong University, Shanghai, China

The final, formatted version of the article will be published soon.

    The accelerated motorization has brought a series of environmental concerns and damaged public environmental health by causing severe air and noise pollution. The advocate of urban rail transit system such as metro is effective to reduce the private car dependence and alleviate associated environmental outcomes. Meanwhile, the increased metro usage can also benefit public and individual health by facilitating physical activities such as walking or cycling to the metro station. Therefore, promoting metro usage by discovering the nonlinear associations between the built environment and metro ridership is critical for the government to benefit public health, while most studies ignored the non-linear and threshold effects of built environment on weekend metro usage.Method: Using multi-source datasets in Shanghai, this study applies Gradient Boosting Decision Trees (GBDT), a nonlinear machine learning approach to estimate the non-linear and threshold effects of the built environment on weekend metro ridership.Results: Results show that land use mixture, distance to CBD, number of bus line, employment density and rooftop density are top five most important variables by both relative importance analysis and SHapley Additive exPlanations (SHAP) values. Employment density and distance to city center are top five important variables by feature importance. According to the Partial Dependence Plots (PDPs), every built environment variable shows non-linear impacts on weekend metro ridership, while most of them have certain effective ranges to facilitate the metro usage. Maximum weekend ridership occurs when land use mixture entropy index is less than 0.7, number of bus lines reaches 35, rooftop den-sity reaches 0.25, and number of bus stops reaches 10. Implication: Research findings can not only help government the non-linear and threshold effects of the built environment in planning practice, but also benefit public health by providing practical guidance for policymakers to increase weekend metro usage with station-level built environment optimization.

    Keywords: built environment, Metro ridership, machine learning, nonlinearity, Public Environmental health

    Received: 24 Jul 2024; Accepted: 17 Oct 2024.

    Copyright: © 2024 Peng, Wang, Zhang and Li. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Yi Zhang, Shanghai Jiao Tong University, Shanghai, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.