Quantifying spatially varying impacts of public transport on $N{O}_2$ concentrations with big geo-data

Abstract

Anthropogenic $N{O}_2$ concentrations cause climate change and human health issues. Previous studies have focused on the contribution of traffic factors to $N{O}_2$ emissions but have ignored the spatially varying impact of public transport supply and demand on high-resolution $N{O}_2$ concentrations. This study first applies a two-stage interpolation model to generate a high-resolution urban $N{O}_2$ concentration map originating from satellite measurement products. Then, we formulate 12 explanatory indicators derived from a fusion of massive big geo-data including smart card data and point of interest information, to represent the specific degree of public transport supply and citizens’ demand. Furthermore, a geographically weighted regression is applied to quantify the spatial variation in the effect of these indicators on the urban $N{O}_2$ concentrations. The result shows that public transportation coverage, frequency, and capabilities as public transport supply indicators in metropolitan and suburban areas have a two-way influence on the $N{O}_2$ emissions. However, among public transport demand indicators, the economic level has a significant positive impact in most areas. Our findings can provide policy implications for public transportation system optimization and air quality improvement.

Han Wang

Grad Student
2020 - 2023

Interested in all things cool.

Xiao Zhou

Postdoctoral Researcher
2021 - 2023

My research interests include sustainable development, marine spatial planning, and environmental policy analysis

Hao Guo

Grad Student
2020 - present

My research interests lie in the general area of spatial analysis theory and methods, including spatial statistics, GeoAI, and spatial optimization.

Zhou Huang

Associate professor

Associate professor of GIScience