A Novel Framework for Forecasting, Evaluation and Early-Warning for the Influence of PM10 on Public Health

Wendong Yang,Yan Hao,Jianzhou Wang,Guolin Tang

doi:10.3390/atmos12081020

Abstract

PM2.5 has attracted widespread attention since the public has become aware of it, while attention to PM10 has started to wane. Considering the significance of PM10, this study takes PM10 as the research object and raises a significant question: when will the influence of PM10 on public health end? To answer the abovementioned question, two promising research areas, i.e., air pollution forecasting and health effects analysis, are employed, and a novel hybrid framework is developed in this study, which consists of one effective model and one evaluation model. More specifically, this study first introduces one advanced optimization algorithm and cycle prediction theory into the grey forecasting model to develop an effective model for multistep forecasting of PM10, which can achieve reasonable forecasting of PM10. Then, an evaluation model is designed to evaluate the health effects and economic losses caused by PM10. Considering the significance of providing the future impact of PM10 on public health, we extend our forecasting results to evaluate future changes in health effects and economic losses based on our proposed health economic losses evaluation model. Accordingly, policymakers can adjust current air pollution prevention plans and formulate new plans according to the results of forecasting, evaluation and early-warning. Empirical research shows that the developed framework is applicable in China and may become a promising technique to enrich the current research and meet the requirements of air quality management and haze governance.

Highlights

The development of China’s economy has brought about serious environmental problems, especially smog pollution, which is common in many cities in China, has a pernicious influence on public health and causes great economic losses and confusion in society
In this paper, by combining the newly proposed forecasting model and evaluation model, a novel hybrid framework is developed for forecasting, evaluation, and early-warning for the influence of PM10 on public health
To provide effective forecasting results of PM10 in the future, this study developed a forecasting model based on the GM (1, 1), manta ray foraging optimization (MRFO) algorithm, and cycle prediction strategy

Summary

Introduction

The development of China’s economy has brought about serious environmental problems, especially smog pollution, which is common in many cities in China, has a pernicious influence on public health and causes great economic losses and confusion in society. One particular question remains to be answered: When will the influence of air pollution on public health end? PM10 , which is considered as one of the most dangerous air pollutants, is defined as particulate matter with an effective aerodynamic diameter of less than 10 μm [1]. What is more serious is that existing research shows that even if the concentration of PM10 in the air is small, it will harm human health [4]. In this context, to fill this research gap, this study takes

Results

Discussion

Conclusion