A Machine-Learning-Based Classification Method for Meteorological Conditions of Ozone Pollution

IF 2.5 4区 环境科学与生态学 Q3 ENVIRONMENTAL SCIENCES Aerosol and Air Quality Research Pub Date : 2023-01-01 DOI:10.4209/aaqr.220239
Yang Cao, Xiaoli Zhao, Debin Su, Xiang Cheng, Hong Ren
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引用次数: 2

Abstract

Ozone pollution is harmful to human health and ecosystem, which occurs in ecosystems and has occurred frequently in China in recent years, especially during the warm seasons. Meteorological conditions are among the important factors affecting the occurrence of ozone pollution. In this study, a classification method for meteorological conditions of ozone pollution levels based on a back propagation (BP) neural network was proposed to reflect the impact of meteorological conditions on the occurrence of ozone pollution. Ozone pollution was divided into three levels according to surface hourly ozone (O 3 ) concentrations and thus into three groups of meteorological conditions. The input physical parameters for the BP neural network were determined by evaluating the relationship between surface O 3 concentrations and meteorological parameters and precursors, including relative humidity, temperature, mixing layer height, precipitation
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基于机器学习的臭氧污染气象条件分类方法
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来源期刊
Aerosol and Air Quality Research
Aerosol and Air Quality Research ENVIRONMENTAL SCIENCES-
CiteScore
8.30
自引率
10.00%
发文量
163
审稿时长
3 months
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.
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