Abstract
Air quality is crucial for the environment and the life quality of citizens. Therefore, in the present study a software application is developed to predict air quality on the basis of 2.5 particulate matter (〖PM〗_(2.5)) and 10particulate matter (〖PM〗_10), in the city of Upper Hunter, Australia, as it is considered to be one of the cities with the lowest air quality levels worldwide. For this purpose, it has been decided to use the methodology of long-short term memory (LSTM) from data collected by NSW department of planning industry and environment during the period of 30 September 2012 to 30 September 2019, to predict the behavior of the mentioned particulate matter during the month of October 2019. A comparison between the average and maximum values suggested by the software and the actual values has been made and it is shown that the predicted results of the study are quite close to reality. Finally, the results obtained in this study may serve as a basis for local authorities to proceed with the necessary protocols and measures in case an alarming prediction occurs.
Highlights
The effects of air pollution on health have been the focus of study in the past decades [1]
Air quality prediction is of great importance for environmental protection
Considering the multivariate data in terms of PM2.5 and PM10 values of the information collected by the Upper Hunter station during the years 2012 to 2019 it was possible to verify that the long-short term memory (LSTM) method is valid for predicting behavior of the mentioned parameters in the future, allowing the development of protocols or procedures in case of an alarming prediction
Summary
The effects of air pollution on health have been the focus of study in the past decades [1]. In the late eighties approximately, epidemiological studies have proved a relationship among air pollution levels and cardiovascular mortality, as well as hospital admissions and emergency room visits [2] in both developed and developing countries [3]; which leads to the recognition of air pollution as an influential and changeable determinant of cardiovascular disease in urban communities [4]. It has been estimated, according to the World Health Organization, that environmental air pollution is responsible for about 4.2 million premature deaths worldwide annually by 2018 [5]. As Xiang et al [7], quoted by [6], pointed out, high-resolution air quality data in the urban context are essential for the management of cities.
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