Since COVID-19 pneumonia broke out, the Chinese government has taken a series of measures to control the spread of the epidemic, which has made the air quality of Taiyuan in February 2020 significantly better than during the same period in previous y...
The air quality index (AQI) depends on the concentrations of six pollutants (PM2.5, PM10, SO2, NO2, O3, and CO). We propose a hybrid Prophet–LSTM forecasting framework with an improved particle swarm optimization (PSO) algorithm to tune the fus...
Makkah draws millions of visitors during Hajj and Ramadan, establishing itself as one of Saudi Arabia’s most bustling cities. The imperative lies in maintaining pristine air quality and comprehending diverse air pollutants to effectively manage...
The WRF-CMAQ (Weather research and forecast-community multiscale air quality) simulation system is commonly used as the first prediction model of air pollutant concentration, but its prediction accuracy is not ideal. Considering the complexity of air...
The air quality index (AQI) forecast in big cities is an exciting study area in smart cities and healthcare on the Internet of Things. In recent years, a large number of empirical, academic, and review papers using machine learning (ML) for air quali...
Air pollution episodes in Metropolitan Lima pose persistent challenges for urban health protection and timely environmental decision-making. However, many machine learning approaches for air-quality prediction remain difficult to operationalize due t...
In the context of carbon neutrality and air pollution prevention, it is of great research significance to achieve high-accuracy prediction of the air quality index. In this paper, Beijing is used as the study area; data from January 2014 to December...
Accurate prediction of the air quality index (AQI) is crucial for understanding urban pollution dynamics and protecting public health. This study proposes a dual-branch fusion framework (CL-XGB-Season) to address seasonal heterogeneity in AQI predict...
Air pollution poses a pressing global challenge, particularly in rapidly industrializing nations like China where deteriorating air quality critically endangers public health and sustainable development. To address the heterogeneous patterns of air p...
Unprecedented levels of air pollution in our cities due to rapid urbanization have caused major health concerns, severely affecting the population, especially children and the elderly. A steady loss of ecological balance, without remedial measures li...
Effective air quality prediction models are crucial for the timely prevention and control of air pollution. However, previous models often fail to fully consider air quality’s temporal and spatial distribution characteristics. In this study, Xi...
Air pollution poses a significant global challenge, impacting human health and environmental sustainability worldwide. Accurate air quality forecasting is essential for effective mitigation strategies, particularly in rapidly urbanizing regions. This...
The air-quality index (AQI) is an important comprehensive evaluation index to measure the quality of air, with its value reflecting the degree of air pollution. However, it is difficult to predict the AQI accurately by the commonly used WRF-CMAQ mode...
PM2.5 pollution is increasing, causing health problems. The objective of this study was to model the behavior of PM2.5AQI (air quality index) using machine learning (ML) predictive models of linear regression, lasso, ridge, and elastic net. A total o...
Air-quality monitoring and forecasting are crucial for atmosphere pollution control and management. We propose an innovative data-driven framework for air quality index (AQI) prediction by integrating GNSS radio occultation (GNSS-RO) observation and...
A linear regression model of particle pollution and an ordered logistic regression model of the relevant index were selected for observations in the US city of Los Angeles, California. Models were used to forecast Air Quality Index (AQI) from a sampl...
Accurate Air Quality Index (AQI) forecasting is crucial for environmental pollution control. However, the strong nonlinearity and pronounced non-stationarity of AQI time series limit the precision of single-model predictions. This paper therefore pro...
4 December 2019
Poor air quality has a negative impact on social life and economic production activities. Using financial derivatives to hedge risks is one of the important methods. Air quality index (AQI) options are designed to help enterprises cope with the opera...
Accurate, timely air quality index (AQI) forecasting helps industries in selecting the most suitable air pollution control measures and the public in reducing harmful exposure to pollution. This article proposes a comprehensive method to forecast AQI...
Under the global warming trend, the diffusion of air pollutants has intensified, causing extremely serious environmental problems. In order to improve the air quality–meteorology correlation model’s prediction accuracy, this work focuses...
The growing concern about air quality and its influence on human health has prompted the development of sophisticated monitoring and forecast systems. This article gives a thorough investigation into forecasting the air quality index (AQI) with an In...
Accurately forecasting air pollutants concentration can reduce health risks and provide an important reference for environmental governance. This study proposes a new deep learning model, GLA-Net, which aims to achieve high-precision prediction of th...
Accurate AQI forecasting is essential for public health and environmental management. However, existing network models for AQI forecasting still exhibit limited predictive accuracy, with insufficient consideration of key influencing factors in curren...
The Environmental Protection Administration of Taiwan’s Executive Yuan has set up many air quality monitoring stations to monitor air pollution in the environment. The current weather forecast also includes information used to predict air pollution....
Air pollution has become an essential issue in environmental protection. The Air Quality Index (AQI) is often used to determine the severity of air pollution. When the AQI reaches the red level, the proportion of asthma patients seeking medical treat...
This paper discusses air quality index (AQI) representation using a fuzzy logic framework to cover the blurry areas of AQI where indices are in between ranges of values. After studying several standards for air quality prediction (AQP), this research...
To analyze the dynamic characteristics of air quality for enforcing effective measures to prevent and evade air pollution harm, air quality index (AQI) time series data was selected and transformed into a symbol sequence consisting of characters (H,...
To better inform the public about ambient air quality and associated health risks and prevent cardiovascular and chronic respiratory diseases in Macau, the local government authorities apply the Air Quality Index (AQI) for air quality management with...
The Beijing–Tianjin–Hebei (BTH) region faces complex air pollution driven by alternating particulate matter (PM) and ozone (O3) dominance, regional transport, topography, and meteorology. This study develops a hybrid framework integrating...
This study applies a Long Short-Term Memory (LSTM) model to predict key air pollutants, i.e., sulphur dioxide (SO2), nitrogen dioxide (NO2), and particulate matter (PM2.5), as well as the Air Quality Index (AQI) across South Africa using satellite-de...
Air pollution places a considerable disease burden on the public. Compared with the widely applied air quality index (AQI), the air quality health index (AQHI) provides a more comprehensive measure of multiple pollutants. In this study, AQHI was cons...
With the rapid development of industrialization and urbanization, atmospheric pollution research is vital for regional sustainable development and related policies formulated by the government. Previous studies have mainly studied a single evaluation...
With the continuous deterioration of air quality and the increasingly serious environmental problem of air pollution, accurate air quality prediction is of great significance for environmental governance. Air quality index (AQI) prediction based on d...
An accurate, reliable and stable air quality prediction system is conducive to the public health and management of atmospheric ecological environment; therefore, many models, individual or hybrid, have been implemented widely to deal with the predict...
Accurate air quality prediction (AQP) is crucial for safeguarding public health and guiding smart city management. However, reliable assessment remains challenging due to complex emission patterns, meteorological variability, and chemical interaction...
24 November 2019
With the development of industrialization and urbanization, air pollution in many countries has become more serious and has affected people’s health. The air quality has been continuously concerned by environmental managers and the public. Ther...
25 June 2021
This study investigates changes in fine particulate matter (PM2.5) concentration and air-quality index (AQI) in Asia using nine different Coupled Model Inter-Comparison Project 6 (CMIP6) climate model ensembles from historical and future scenarios un...
Accurate Air Quality Index (AQI) forecasting is essential for public health protection and sustainable urban planning. Existing data-driven forecasting models often provide limited interpretability of pollutant interactions, while conventional Fuzzy...
This study uses data from Taichung Fengyuan Station in Taiwan’s Civil IoT to conduct short-term forecasting of the Air Quality Index (AQI). We compile multiple pollutant and meteorological features and develop three models—Long Short-Term...
This research models and forecasts daily AQI (air quality index) levels in 16 cities/counties of Taiwan, examines their AQI level forecast performance via a rolling window approach over a one-year validation period, including multi-level forecast cla...
Rapid urbanization has exacerbated traffic congestion and associated vehicle emissions, making real-time air quality index (AQI) prediction crucial for urban environmental management. Transportation emissions, including exhaust gases and particulate...
Air pollution has become an important environmental issue in recent decades. Forecasts of air quality play an important role in warning people about and controlling air pollution. We used support vector regression (SVR) and random forest regression (...
Air pollution in cities is a severe and worrying problem because it causes threats to economic development and health. Furthermore, with the development of industry and technology, rapid population growth, and the massive expansion of cities, the tot...
Accurate prediction of the Air Quality Index (AQI) is crucial for protecting public health; however, the inherent instability and high volatility of AQI present significant challenges. To address this, the present study introduces a novel hybrid deep...
Addressing the constraints inherent in traditional primary Air Quality Index (AQI) forecasting models and the shortcomings in the exploitation of meteorological data, this research introduces a novel air quality prediction methodology leveraging mach...
Accurate prediction of Air Quality Index (AQI) is of significant importance for environmental governance. In this paper, the CNN-LSTM prediction model based on Pelican Optimization Algorithm (POA) was proposed to study the air quality index (AQI) and...
With the rapid development of the economy and continuous improvement in people’s living standards, the predictions of the air quality index have attracted wide attention. In this paper, a new feature selection method (Pearson-MI) and a combined...
Air pollution primarily originates from substances that are directly emitted from natural or anthropogenic processes, such as carbon monoxide (CO) gas emitted in vehicle exhaust or sulfur dioxide (SO2) released from factories. However, a major air po...
The Air Quality Index (AQI) dataset contains information on measurements of pollutants and ambient air quality conditions at certain location that can be used to predict air quality. Unfortunately, this dataset often has many missing observations and...
Air pollution has been a looming issue of the 21st century that has also significantly impacted the surrounding environment and societal health. Recently, previous studies have conducted extensive research on air pollution and air quality monitoring....
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