Spatial and Socio-Classification of Traffic Pollutant Emissions and Associated Mortality Rates in High-Density Hong Kong via Improved Data Analytic Approaches

Abstract

Excessive traffic pollutant emissions in high-density cities result in thermal discomfort and are associated with devastating health impacts. In this study, an improved data analytic framework that combines geo-processing techniques, social habits of local citizens like traffic patterns and working schedule and district-wise building morphologies was established to retrieve street-level traffic NOx and PM2.5 emissions in all 18 districts of Hong Kong. The identification of possible human activity regions further visualizes the intersection between emission sources and human mobility. The updated spatial distribution of traffic emission could serve as good indicators for better air quality management, as well as the planning of social infrastructures in the neighborhood environment. Further, geo-processed traffic emission figures can systematically be distributed to respective districts via mathematical means, while the correlations of NOx and mortality within different case studies range from 0.371 to 0.783, while varying from 0.509 to 0.754 for PM2.5, with some assumptions imposed in our study. Outlying districts and good practices of maintaining an environmentally friendly transportation network were also identified and analyzed via statistical means. This newly developed data-driven framework of allocating and quantifying traffic emission could possibly be extended to other dense and heavily polluted cities, with the aim of enhancing health monitoring campaigns and relevant policy implementations.

Dynamic Differential Game Strategy of the Energy Big Data Ecosystem Considering Technological Innovation

“…In addition, this study only considers the two-stage supply chain, including one technology supplier and one power grid enterprise. However, the energy big data ecosystem is a complex system, including multiple stakeholders such as power grid enterprises, technology suppliers, governments, energy suppliers, and energy consumers, and there are data sharing barriers among stakeholders [65]. Therefore, in future research, the game strategy of a multi-level supply chain considering data openness can be further explored.…”

From Comparative and Statistical Assessments of Liveability and Health Conditions of Districts in Hong Kong towards Future City Development

“…Moreover, research in the United Kingdom has shown that people who can gain access to green space will generally encounter less depression, while exposure to traffic noise and pollution will result in respiratory diseases like asthma, chronic, and heart diseases [19]. The latter conclusion has already been verified within Hong Kong context, via the advanced data analytic framework for assessing street-level traffic emission variabilities and evaluating its connection with undesirable health effects [53]. Due to dense morphologies and complex urban structures, vehicular pollutants are usually being trapped in between the tall buildings situated on two sides of a road, which result in street canyon effect and the lack of proper air ventilation [34].…”

“…In addition, the overall architectural design of buildings was to facilitate airflow, enhance ventilation, reduce the trapping of pollutants within street canyons, and to provide more open space to citizens. All these reduce the NO x emissions and pollutant concentrations of Sai Kung [53], with an average NO 2 concentration of only 29 µg/m 3 detected in roadside monitoring stations [85]. Further, the government is promoting cycling as an alternative to private vehicles for short distance travel, which can also serve as the transport mode to connect with public transport, offices, and residential flats.…”

“…Further, 21.86% of the working population of Hong Kong reside in Kwun Tong, which causes high demand for traffic. However, the limited provision of roads has exacerbated traffic congestions in road junctions during peak hours, thus leading to devastating air pollution and environmental problems [95], as reviewed by the extraordinarily high roadside PM 2.5 and NO 2 concentrations observed in different parts of the district [53,85]. Moreover, kerbside activities like loading and unloading take place in different major roads of the district (e.g., Hing Yip Street and Wai Yip Street), and the associated illegal parking problems have influenced normal traffic flow and road capacity [96], because existing road network is ineffective to manage the transformation of district from an industrial to a commercial one.…”

Retrieval of Land-Use/Land Cover Change (LUCC) Maps and Urban Expansion Dynamics of Hyderabad, Pakistan via Landsat Datasets and Support Vector Machine Framework

“…Thus, corresponding assessments of temperature change caused by urbanization processes are important, because associated climatic variations could easily reduce thermal comfort, and trap pollutants within street canyons, especially in metropolitan cities, as a result causing devastating health impacts to residents. Therefore, on top of monitoring temperature changes within urbanized areas, one should also focus on evaluating how changing land-use patterns, local traffic and mobility conditions, and meteorological conditions could affect pollutant distributions at fine spatial resolutions, via satellite remote sensing techniques and modelling approaches [130][131][132].…”