Characterizing Spatial and Temporal Patterns of Thermal Environment and Air Quality in Taipei Metropolitan Area
Abstract
The urban heat island effect (UHI) caused by the regional-to-global environmental changes, dramatic urbanization, and shifting in land-use compositions has becoming an important environmental issue in recent years. In the past century, the coverage of urban area in Taipei Basin has dramatically increasing by ten folds. The strengthen of UHI effect significantly enhances the frequency of warm-night effect, and strongly influences the thermal environment of the residents in the Greater Taipei Metropolitan. In addition, the urban expansions due to dramatic increasing in urban populations and traffic loading significantly impacts the air quality and causes health issue in Taipei. In this study, the main objective is to quantify and characterize the temporal and spatial distributions of thermal environmental and air quality in the Greater Taipei Metropolitan Area by using monitoring data from Central Weather Bureau, Environmental Protection Administration. In addition, in this study, we conduct the analysis on the distribution of physiological equivalent temperature in the micro scale in the metropolitan area by using the observation data and quantitative simulation to investigate how the thermal environment is influenced under different conditions. Furthermore, we establish a real-time mobile monitoring system by using wireless sensor network to investigate the correlation between the thermal environment, air quality and other environmental factors, and propose to develop the early warning system for heat stress and air quality in the metropolitan area. The results from this study can be integrated into the management and planning system, and provide sufficient and important background information for the development of smart city in the metropolitan area in the future.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFMPA21A0337J
- Keywords:
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- 0493 Urban systems;
- BIOGEOSCIENCES;
- 1640 Remote sensing;
- GLOBAL CHANGE;
- 1942 Machine learning;
- INFORMATICS;
- 4330 Vulnerability;
- NATURAL HAZARDS