Mahsa Ashouri, Frederick Kin Hing Phoa, Chun-Hhouh Chen, Galit Shmueli
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引用次数: 0
Abstract
Examining PM2.5 (atmospheric particulate matter with a maximum diameter of 2.5 micrometers), seasonal patterns is an important research area for environmental scientists. An improved understanding of PM2.5 seasonal patterns can help environmental protection agencies (EPAs) make decisions and develop complex models for controlling the concentration of PM2.5 in different regions. This work proposes an R Shiny App web-based interactive tool, namely a “model-based time series clustering” (MTSC) tool, for clustering PM2.5 time series using spatial and population variables and their temporal features, like seasonality. Our tool allows stakeholders to visualize important characteristics of PM2.5 time series, including temporal patterns and missing values, and cluster series by attribute groupings. We apply the MTSC tool to cluster Taiwan’s PM2.5 time series based on air quality zones and types of monitoring stations. The tool clusters the series into four clusters that reveal several phenomena, including an improvement in Taiwan's air quality since 2017 in all regions, although at varying rates, an increasing pattern of PM2.5 concentration when moving from northern towards southern regions, winter/summer seasonal patterns that are more pronounced in certain types of areas (e.g., industrial), and unusual behavior in the southernmost region. The tool provides cluster-specific quantitative figures, like seasonal variations in PM2.5 concentration in different air quality zones of Taiwan, and identifies, for example, an annual peak in early January and February (maximum value around 120 μg m-3). Our analysis identifies a region in southernmost Taiwan as different from other zones that are currently grouped together with it by Taiwan EPA (TEPA), and a northern region that behaves differently from its TEPA grouping. All these cluster-based insights help EPA experts implement short-term zone-specific air quality policies (e.g., fireworks and traffic regulations, school closures) as well as longer-term decision-making (e.g., transport control stations, fuel permits, old vehicle replacement, fuel type).
期刊介绍:
The international journal of Aerosol and Air Quality Research (AAQR) covers all aspects of aerosol science and technology, atmospheric science and air quality related issues. It encompasses a multi-disciplinary field, including:
- Aerosol, air quality, atmospheric chemistry and global change;
- Air toxics (hazardous air pollutants (HAPs), persistent organic pollutants (POPs)) - Sources, control, transport and fate, human exposure;
- Nanoparticle and nanotechnology;
- Sources, combustion, thermal decomposition, emission, properties, behavior, formation, transport, deposition, measurement and analysis;
- Effects on the environments;
- Air quality and human health;
- Bioaerosols;
- Indoor air quality;
- Energy and air pollution;
- Pollution control technologies;
- Invention and improvement of sampling instruments and technologies;
- Optical/radiative properties and remote sensing;
- Carbon dioxide emission, capture, storage and utilization; novel methods for the reduction of carbon dioxide emission;
- Other topics related to aerosol and air quality.