5,503 Results Found

PM_2.5 in the atmosphere causes severe air pollution and dramatically affects the normal production and lives of residents. The real-time monitoring of PM_2.5 concentrations has important practical significance for the construction of ecological civili...

Although much research is being conducted on the characteristics of PM2.5 and PM10 at subway stations, there is no research focusing on a complex subway transfer station. In this paper, the characteristics of PM2.5 and PM10 at transfer stations are s...

Long-term prediction of hour-concentration of PM2.5 (particles in atmospheric suspension with effective dimensions equal or lower than 2.5 microns) is of great significance for environmental protection and people’s health. At present, the predi...

The Plain Forestation Project is an important measure designed to alleviate air pollution in Beijing, the capital of China. Ten commonly cultivated forest types of the Plain Forestation Project were studied at three growth stages of leaves. The parti...

For a better environment and sustainable development of China, it is indispensable to unravel how urban forms (UF) affect the fine particulate matter (PM_2.5) concentration. However, research in this area have not been updated consider multiscale and...

Urban particulate matter forecasting is regarded as an essential issue for early warning and control management of air pollution, especially fine particulate matter (PM_2.5). However, existing methods for PM_2.5 concentration prediction neglect the eff...

Complex topography has nonnegligible effects on local meteorological conditions as well as the transportation of atmospheric pollutants, which deserves more extensive study. In this study, the impacts of complex terrain features (mountains and river...

In recent years, green, low carbon and sustainable development has become a common topic of concern. Aiming at solving the drawback of low accuracy of PM2.5 concentration prediction, this paper proposes a method based on deep learning to predict PM2....

Fine aerosols with a diameter of less than 2.5 microns (PM_2.5) have a significant negative impact on human health. However, their measurement devices or instruments are usually expensive and complicated operations are required, so a simple and effect...

The air quality prediction is a very important and challenging task, especially PM${}_{2.5}$ (particles with diameter less than 2.5 μm) concentration prediction. To improve the accuracy of the PM${}_{2.5}$ concentration prediction, an improved integrated deep neur...

The concentration of PM2.5 is an important index to measure the degree of air pollution. When it exceeds the standard value, it is considered to cause pollution and lower the air quality, which is harmful to human health and can cause a variety of di...

As industrialization and economic growth accelerate, PM_2.5 pollution has become a critical environmental concern. Predicting PM_2.5 concentration is challenging due to its nonlinear and complex temporal dynamics, limiting the accuracy and robustness o...

This article explores the effects of outdoor PM_2.5 concentration, venue airtightness and the distribution of indoor PM_2.5 concentration on the curling venue of the National Aquatics Center. Research has found that when the filtration efficiency of th...

The particulate matter 2.5 (PM_2.5) is a serious air-pollutant emission in China, which has caused serious risks to public health. To reduce the pollution and corresponding public mortality, this paper proposes a method by incorporating slacks-based d...

With the development of urbanization, the hourly PM_2.5 concentration in the air is constantly changing. In order to improve the accuracy of PM_2.5 prediction, a prediction model based on the Classification and Regression Tree (CART) and Broad Learning...

PM_2.5 is a main source of China’s frequent air pollution. Using real-time monitoring of PM_2.5 data in 338 Chinese cities during 2014–2017, this study employed multi-temporal and multi-spatial scale statistical analysis to reveal the tempo...

The PM2.5 index is an important basis for measuring the degree of air pollution. The accurate prediction of PM2.5 concentration has an important guiding role in air pollution prevention and control. The Pearson Correlation Coefficient (PCC) is a comm...

As a key indicator of air quality, effective forecasting of ${\mathrm{PM}}_{2.5}$ concentration can provide key technical support for the scientific and precise implementation of air pollution prevention and control. However, predicting ${\mathrm{PM}}_{2.5}$ concentrations faces ch...

In this article, a robust statistical analysis of particulate matter (PM_2.5) concentration measurements is carried out. Here, the region chosen for the study was the urban park La Carolina, which is one of the most important in Quito, Ecuador, and is...

The novel coronavirus disease (COVID-19) has become a public health problem at a global scale because of its high infection and mortality rate. It has affected most countries in the world, and the number of confirmed cases and death toll is still gro...

PM_2.5 is one of the main pollutants that cause air pollution, and high concentrations of PM_2.5 seriously threaten human health. Therefore, an accurate prediction of PM_2.5 concentration has great practical significance for air quality detection, air p...

Discharging fireworks during the Chinese Lunar New Year celebrations is a deep-rooted custom in China. In this paper, we analyze the effect of this cultural activity on PM_2.5 concentration using both ground observations and satellite data. By combini...

As an extension of the traditional Land Use Regression (LUR) modelling, the generalized additive model (GAM) was developed in recent years to explore the non-linear relationships between PM_2.5 concentrations and the factors impacting it. However, the...

As air pollution becomes more and more serious, PM2.5 is the primary pollutant, inevitably attracts wide public attention. Therefore, a novel PM2.5 concentration forecasting method based on linear fuzzy information granule_dynamic time warping_hierar...

Air pollution in cities has a massive impact on human health, and an increase in fine particulate matter (PM${}_{2.5}$) concentrations is the main reason for air pollution. Due to the chaotic and intrinsic complexities of PM${}_{2.5}$ concentration time series, it...

In this article, robust confidence intervals for PM_2.5 (particles with size less than or equal to $2.5 \mu m$ ) concentration measurements performed in La Carolina Park, Quito, Ecuador, have been built. Different techniques have been app...

Atmospheric PM_2.5 pollution has become a prominent environmental problem in China, posing considerable threat to sustainable development. The primary driver of PM_2.5 pollution in China is urbanization, and its relationship with PM_2.5 concentration ha...

Accurate prediction of fine particulate matter (PM2.5) concentration is crucial for improving environmental conditions and effectively controlling air pollution. However, some existing studies could ignore the nonlinearity and spatial correlation of...

The purpose of this study was to use principal component analysis to determine the effect of meteorological elements on the concentration of PM_2.5 particulate matter in Krakow, the capital of the Lesser Poland Voivodeship in southern Poland. Daily va...

Fine particulate matter (PM_2.5) threatens human health and the natural environment. Estimating the near-ground PM_2.5 concentrations accurately is of great significance in air quality research. Statistical and deep-learning models are widely used for...

Severe air pollution problems continue to increase because of accelerated industrialization and urbanization. Specifically, fine particulate matter (${\mathrm{PM}}_{2.5}$) causes respiratory and cardiovascular diseases, and according to the World Health Organization...

Air pollution has become a critical factor affecting the health of human beings. Forecasting the trend of air pollutants will be of considerable help to public health, including improving early-warning systems. The article designs a novel hybrid deep...

PM${}_{2.5}$ concentration prediction is an important task in atmospheric environment research, so many prediction models have been established, such as machine learning algorithm, which shows remarkable generalization ability. The time series data composed...

Street trees are crucial for air pollutant reduction in urban areas. Herein, we used computational fluid dynamics (CFD) simulation to identify changes in airborne particulate matter (PM_2.5) concentration based on wind characteristics (direction and v...

Industrial heat source (IHS) radiation areas are key accumulation zones for fine particulate matter with an aerodynamic diameter of 2.5 μm or less (PM_2.5) in heavily industrialized regions, but PM_2.5 concentration reduction rates by vegetation typ...

We investigated the effects of wall- and tree-type fences on the airflow and fine particular matter (PM_2.5) concentration around a school using a computational fluid dynamics (CFD) model. First, we validated the simulated wind speeds and PM_2.5 concen...

Particulate matter (PM) concentration, especially PM_2.5, is a major culprit of environmental pollution from unreasonable energy system emissions that significantly affects visibility, climate, and public health. The prediction of PM_2.5 concentration...

Abstract: Exposure to outdoor air pollution has been shown to increase asthma symptoms. We assessed the potential role of particulate matter with aerodynamic diameter <2.5 μm (PM_2.5) on respiratory condition in schoolchildren in the south Mediterr...

Determining accurate PM2.5 pollution concentrations and understanding their dynamic patterns are crucial for scientifically informed air pollution control strategies. Traditional reliance on linear correlation coefficients for ascertaining PM2.5-rela...

Accurate prediction of PM_2.5 concentration is one of the key tasks of air pollution assessment, early warning, and treatment. In this paper, four monitoring sites were arranged in Jiangbei New District of Nanjing City, China. The environmental parame...

Near-surface PM_2.5 concentrations have been greatly exacerbated by urban land expansion and dense urban traffic. This study aims to clarify the effects of multiple factors on near-surface PM_2.5 concentrations from three perspectives of background cli...

The atmospheric environment is of great importance to human health. However, its influencing factors are complex and variable. An efficient technique is required to more precisely estimate PM_2.5 concentration values. In this paper, an enhanced Sparro...

Precise PM_2.5 concentration forecasting is significant to environmental management and human health. Researchers currently add various parameters to deep learning models for PM_2.5 concentration forecasting, but most of them ignore the problem of PM_2....

Particulate matter (PM) in the air can cause various health problems and diseases in humans. In particular, the smaller size of PM${}_{2.5}$ enable them to penetrate deep into the lungs, causing severe health impacts. Exposure to PM${}_{2.5}$ can result in respira...

Accurate PM2.5 concentration prediction is crucial for protecting public health and improving air quality. As a popular deep learning model, deep belief network (DBN) for PM2.5 concentration prediction has received increasing attention due to its eff...

At present, fine particulate matter (PM_2.5) has become an important pollutant in regard to air pollution and has seriously harmed the ecological environment and human health. In the face of increasingly serious PM_2.5 air pollution problems, feasible...

The issue of urban air quality in China has become increasingly significant due to industrialization and rapid urbanization. Although PM_2.5 is the major air pollutant in most cities of northern China and has a direct negative impact on human health,...

With the rapid development of China’s economy, the environmental problems are becoming increasingly prominent, especially the PM_2.5 (particulate matter with diameter smaller than 2.5 μm) concentrations that have exerted adverse influences on...

Particulate matter with a diameter less than 2.5 µm (PM_2.5), one of the main sources of air pollution, has increasingly become a concern of the people and governments in China. Examining the socioeconomic factors influencing on PM_2.5 concentrat...

Exploring the spatial differentiation of PM_2.5 concentrations in typical urban agglomerations and analyzing their atmospheric health patterns are necessary for building high-quality urban agglomerations. Taking the Xiamen-Zhangzhou-Quanzhou urban agg...