Pollution zone identification research during ozone pollution processes
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Pollution zone identification research during ozone pollution processes Dongyue Li
&
Yilan Liao
Received: 4 March 2020 / Accepted: 13 August 2020 # Springer Nature Switzerland AG 2020
Abstract Identifying an ozone pollution zone during the pollution processes is significant for ozone pollution management and environmental health risk assessment. However, few studies have focused on ozone pollution zone identification during pollution processes. A spatial-temporal clustering framework for identifying pollution zones during ozone pollution processes was initially proposed in this study, and an ozone pollution process in China in May 2017 was selected as a case. The results showed that the framework can help selecting one more accurate method to identify the pollution zone according to the pollution characteristics of air pollution process. In addition, different ozone pollution zone identification methods work well in different scenarios: The self-organizing map (SOM) method was suitable for identifying the zone with the duration of pollution between 24 and 48 h, the image fusion Dongyue Li and Yilan Liao contributed equally to this work. D. Li : Y. Liao The State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China D. Li College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China Y. Liao (*) Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China e-mail: [email protected]
based on wavelet transform (IFbWT) method for the zone with the duration of pollution over 48 h and the Apriori method for the zone with obvious boundaries between high-value and low-value ozone concentrations. The proposed procedure can also be applied to identify the pollution zone of the pollution process of other pollutants. Keywords Pollution zone . Pollution process . Spatiotemporal clustering . Image fusion . Frequency pattern
Introduction With the development of large-scale industrialization and urbanization, many developing countries have experienced rapid economic growth in the previous two decades. However, this growth has led to a decline in air quality (Ji et al. 2014; Shao et al. 2006). Ground-level ozone (replace with “ozone” in the following description) is one of the most significant pollutants (Feng et al. 2015; Ramos et al. 2018; Zhan et al. 2017) that can cause harm to the human body at high concentrations (Chen et al. 2017; Sheffield et al. 2011; Tao et al. 2012; Turner et al. 2016). Ozone concentration has significantly increased in recent years, especially in the Northeast Asian Pacific rim region (Akimoto et al. 2015; Brauer et al. 2016; Feng et al. 2015). Generally, the concentration of ozone in a region is stable (Cheng et al. 2016; Gorai et al. 2017). If the ozone concentration is suddenly affected by precursors, or the diffusion of ozone from other areas, the ozone
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