With increasing ozone pollution and deeper understanding of its harm to humans and climate, it is important to accurately forecast ozone. In this study, training and testing data sets were constructed with hourly numerical models forecasts and monitoring station observation for the year 2018 for Sichuan-Chongqing region, China. Three machine learning methods including Lasso, random forest and long

Cold-start emissions from road vehicles are an important source of air pollution. However, how to evaluate them in the real driving emission (RDE) test is controversial. Although the Commission Regulation (EU) 2017/1154 and 2018/1832 successively adopt the moving averaging window (MAW) method and the cumulative averaging (CA) method to calculate the emission factors that include the cold-start emissions

This study was conducted to evaluate the performance of the support vector regression (SVR) model with and without applying wavelet transformation for predicting the PM10, PM2.5, SO2, NO2, CO, and O3 in Isfahan metropolis, central Iran. Ground-based data, TerraClimate, and MODIS products were used to predict air pollution parameters. These factors were first trained using the SVR and Wavelet-SVR models

Brown haze, observed over some cities during the winter months, has been found to be associated with poor surface air quality and negative health outcomes. While the link between the atmospheric boundary layer (ABL) structure and surface air quality is well-established, the degree to which boundary layer structure influences local brown haze formation is unknown. Using continuous ceilometer data from

This study sought to analyze the particulate matter (PM) deposited on the surface of pine needles (Pinus densiflora) and pollutants within the needles and to investigate their utility as bioindicators. First-year needles of pines native to South Korea were collected at least 2 m above the ground. A total of four sampling points were selected: two parks around an industrial complex and two urban parks

As one of the largest agglomerations of cities in the world, the infrastructure and living conditions of the residents in the Pearl River Delta (PRD) have significantly improved since the late 1970s. However, as a two-sided sword, the boosting of economic growth has inevitably exerted adverse effects on the environment in this region. To further understand the current fine particulate matter (PM2.5)

During the COVID-19 lockdown, only the most basic and necessary production activities were retained in China. Such strict measures have caused many inconveniences to the people and the economy, but also provided the research community with a rare opportunity to compare the effects of weather conditions and human activities on air quality in the region. Here, a comparative analysis of the impact of

Silt loading (sL) is an important parameter used to calculate fugitive road dust emission inventories and to reflect emission characteristics. The AP-42 method is commonly used to obtain sL values, but is time consuming, unsafe and can only be used on a limited number of roads. We propose a method combining the AP-42 and Testing Re-entrained Aerosol Kinetic Emissions from Roads (TRAKER) methods to

The gas-particle partitioning, source, and lung cancer risk of atmospheric polycyclic aromatic hydrocarbons (PAHs) in different seasons were investigated in a megacity of China with coal dominating the energy structure over one year period. The total concentrations of 16 U.S. EPA priority PAHs (Σ16PAHs) were highest in winter (gaseous: 36.6 ± 1.89 ng m−3; PM phase: 16.9 ± 10.2 ng m−3) and lowest in

Beijing has achieved significant air quality improvement over the past decade. In this study, we applied a simulation technique on pollutant monitoring data to investigate the contribution of emission reduction (ERE) and meteorological effects (ME) to the improvement of air quality. We measured the daily PM2.5 concentrations during four months (representing the four seasons) in 2013 and 2018. We found

Atomospheric particulate matter (PM) has been accepted as a risk to human health worldwide. PM contains a variety of components, but it is not clear which components are harmful to human health. For example, there have been many reports on metals, but there have been only a few studies on proteins. Based on an analysis of serum antibodies in a mouse model of PM-induced asthma reported previously, we

In recent years, low-cost air sensors designed to measure ambient particulate matters and trace gases have been changing the world of air quality monitoring. Although low-cost sensors have the capability of gathering high temporally and spatially-resolved air quality information, they tend to have more severe data quality issues compared to the conventional monitoring instruments. To enhance the data

As air pollution becomes increasingly serious, accurate forecasting of air quality has become an important issue. Many studies related to machine learning and deep learning methods have been proposed to predict air quality. These studies have also confirmed that deep learning has better predictive performance than traditional machine learning. Ensemble Learning has also been proven that can improve

Near-roadway air quality modelling requires detailed inputs about traffic, vehicle emissions, and atmospheric dispersion in order to capture microscopic features of each phenomena. However, these inputs are often a major source of uncertainty in resultant air quality estimates. We aim to evaluate the impact of different traffic behavior patterns on vehicle emissions and the subsequent effect of these

To comprehensively evaluate the transport pathways and regional sources of PM2.5 in the “2 + 26” cities, air quality simulations using WRF-Chem were pursued over January, April, July, October 2015. The seasonal characteristics, vertical distributions of PM2.5 fluxes, and transport pathways were investigated. The model reasonably predicted the meteorological parameters (e.g., T2, Q2, WS10, and WD10)

This study proposes an approach to improve the spatial resolution of ground-level concentrations of PM2.5 that is required to assess health risks associated with exposure to pollutants released during wildfires. We use this approach to analyze the impact on air quality of the wildfire complex consisting of the Atlas, Nuns, Tubbs, Pocket, and Redwood Valley fires in northern California that started

Air quality is a vital concern globally, especially in China. To improve fine particulate matter (PM2.5) forecasts, a nonlinear least squares four-dimensional variational (NLS-4DVar) data assimilation system was established and applied into the Weather Research and Forecasting model coupled with the “offline” Community Multiscale Air Quality (WRF-CMAQ) model. By assimilating hourly surface PM2.5 observations

Light absorbing carbon (LAC), also referred to as black carbon (BC) or more colloquially as soot; is generated from the partial combustion of fossil fuels and biomass. The significant research interest in BC is largely due to its aerodynamic diameter well within the 2.5 μm size fraction (known as PM2.5), as well as its abundance being a major constituent of atmospheric particulate matter, particularly

Previous studies have intensively studied the atmospheric conditions associated with high- and low-PM10 (particulate matter < 10 μm) episodes according to air quality standards. However, the association with the sudden changes in PM10 concentrations has not been clearly understood. Here we defined a PM10 change of above one standard deviation as a sudden change and divided these changes into PM10-increasing

PM2.5 and its main chemical components have been investigated during six air pollution period across four seasons from Jun. 16, 2016 to Jun. 15, 2017 at a suburban site in Beijing, China. Daily PM2.5 mass concentrations were measured with associated ions, OC, EC, 16 PAHs and seven heavy metals. Mass closure analyses were conducted using measured and reconstructed chemical components. Chemical ratios

There are limited source apportionment studies conducted to assess vertical distributions of fine particulate matter (PM2.5) and its contributing sources in urban regions. Additionally, none of these vertical studies used inorganic and organic tracers simultaneously. The present study aimed to explore the vertical variation of source-specific contributions to PM2.5 by modeling with both inorganic and

This study aims to predict land susceptibility (a term that indicates the degree of sensitivity of land to detachment of soil particles by wind) to dust emissions in Yazd province, central Iran, by combining a new integrated data mining (DM) model and the RegCM4 climatic model. The study further determines the relative importance of key factors controlling dust emissions by applying 12 individual DM

Industrial enterprises are one of the main causes of air pollution in eastern China. How to monitor them efficiently is directly related to the result of air pollution control in China. However, the monitoring of enterprises now mainly relies on the ground online monitoring technology, and only for some large enterprises, some small and medium-sized enterprises will be missed which also contribute

Fulfilling the Paris Climate Agreement requires reducing rapidly the new emissions of greenhouse gases (GHGs) to reach net zero by 2050. As some anthropogenic emissions cannot be zero, to compensate them it will be necessary to remove GHGs from the atmosphere. Among possible methods, the Iron Salt Aerosol (ISA) offers new possibilities, including removal of methane and several other GHGs, as well as

This study evaluated toxicological effects owing to fine particulate matter (PM2.5) exposure in cardioblast cells (H9c2 lineage). The cells were treated with different particulate matter extract solutions for 24 h, F100% (1g of filter containing PM2.5 per 100 mL culture medium, used as stock), F50% (1/2 F100) and F10% (10% of stock). Cell viability, the production of reactive oxygen species (ROS),

Assessment of pedestrian exposure and lung deposition is critical to better understanding the health risks resulting from exposure to ambient particles, and to develop site-specific risk control countermeasures. In this study, real-time mobile-monitoring campaigns of three different PM size fractions (PM10, PM2.5 and UFP) were performed during morning and evening peak hours in two seasons (summer and

PM2.5 pollution in India increases severely during the winter season due to adverse meteorological conditions and shows comparatively higher pollution loading in Indo-Gangetic Plain (IGP). However, investigation of the role of major sources and different states of IGP in local and regional higher PM2.5 pollution for effective formulation of mitigation policies has been limited. In this study, the Weather

This study analyses the influence of synoptic weather conditions on atmospheric particulate matter concentration and composition during an intensive measurement campaign, performed in the urban area of Rome (Italy) in winter 2017. To evaluate the effect of local particulate sources, data from several urban and rural ground-based air quality stations were considered. The analysis involved the following

Coronary heart disease (CHD) is a common noncommunicable disease. This study aimed to explore the association between long-term sulfur dioxide (SO2) exposure and CHD morbidity. We conducted a retrospective cohort study in four northern Chinese cities (Tianjin, Taiyuan, Shenyang and Rizhao). This retrospective cohort study was based on the household registration information of each community in 1998

This study was to investigate the association between trimester-specific exposure to air pollutants and the risk of Birth defects (BDs) among Chinese births. A time-dependent Cox proportional hazards model was used to explore the associations between trimester-specific and entire pregnancy concentrations of the pollutants and BDs at Changsha, China from 2014 to 2018. Each increment in ambient particles

The prevention and control measures in place during the coronavirus disease 2019 (COVID-19) pandemic served as perfect conditions for a natural experiment, which has provided an opportunity to investigate the extent to which environmental regulations can improve air quality in the short term. This article examines the relationship between anti-epidemic measures and air quality via a regression discontinuity

Particulate matter with an aerodynamic diameter less than 2.5 μm (PM2.5) has drawn considerable concern due to its significant air quality and public health effects. Aerosol optical depth (AOD) from polar-orbiting satellites has been widely used for estimating ground-level PM2.5 concentration. However, the PM2.5 estimation from the polar-orbiting satellites AOD are limited in spatio-temporal coverage

Size-segregated aerosols (six stages with a diameter from <0.49 to >7.2 μm) were collected during daytime and nighttime in the summer of 2020 and were analyzed for dicarboxylic acids, isoprene, α/β-pinene and β-caryophyllene secondary organic aerosol (SOA) tracers, aromatic acids, hydroxy-polyacids, monocarboxylic acids and levoglucosan. The vast majority of the detected compounds presented significantly

Arsine (AsH3) and phosphine (PH3) in industrial emissions in the purification of liquefied petroleum gas (LPG) in two petrochemical plants, one in Colombia, the other in Spain—were the focus of this research. The study shows the challenges and contributions to environmental sciences in quantifying the magnitude of the environmental impact of these pollutants. AsH3 and PH3 were determined and quantified

Smoke aerosols emitted by wildfires can ascend to the free troposphere, travel over long distances and descend to affect local air quality (AQ) in downwind areas. This study investigates the AQ impact of long-range transported (LRT) smoke aerosols from western North America during summer 2017 in New York State (NYS) using observations and numerical products. Analysis of total fine particulate matter

In the present study, we seek to conduct a real-world assessment of the driving behavior, emission performance, and fuel consumption of urban buses in a medium-sized city in the Middle East, i.e. Isfahan, Iran. A comprehensive data collection was conducted within the main routes of the city and then the ISFahan Bus Driving Cycle (ISFBDC) was developed using a micro-trips random selection approach.

Carbon dioxide (CO2) and Methane (CH4) are considered the most crucial climate forcing greenhouse gases due to their significant impacts on climate systems. The present study is aimed at analyzing the long-term (2004–2016) concentration patterns of CO2 and CH4 over Malawi located in Southeast Africa using the observations from Atmospheric Infrared Sounding (AIRS). The study found an annual increase

Lockdowns implemented in response to COVID-19 have caused an unprecedented reduction in global economic and transport activity. In this study, variation in the concentration of health-threatening air pollutants (PM2.5, NO2, and O3) pre- and post-lockdown was investigated at global, continental, and national scales. We analyzed ground-based data from >10,000 monitoring stations in 380 cities across

Owing to rapid economic development and urbanization, environmental problems caused by PM2.5 and O3 have been occurring frequently. Volatile organic compounds (VOCs) are significant precursors of O3 and secondary organic aerosols that contribute to PM2.5. The study of VOC pollution characteristics is of great significance for providing a reference to guide its reduction policy formulation. Proton transfer

In this study, the effects of high-rise building on the flow and pollutant dispersion under different temperature stratification conditions were simulated using the Reynolds Averaged Navier Stokes (RANS) method and standard k-ε turbulence model. The results showed the following: Both the height of central building and temperature stratification significantly affect the airflow around building arrays

Owing to rapid urbanization and industrialization over decades, nitrogen dioxide (NO2) has become a serious air pollutant in China. The Chinese government has proposed a series of strict strategies for the reduction of nitrogen oxides (NOx) emissions. This research studies the spatio-temporal characteristics of NO2 pollution over China from October 2004 to June 2020 based on satellite observations

Delhi National Capital Region (NCR) of India is one of the most polluted regions in the world, yet only two ground-based monitoring sites under the AEROsol RObotic NETwork (AERONET) measuring Aerosol Optical Depth (AOD) are operational in this region. Here, we assessed the performance of Terra and Aqua MODIS collection 6.1 AOD product to understand their applicability for studying seasonal and spatial

Fine particulate matter (PM2.5) in New York State declined significantly between 2005 and 2016. Fewer hospitalizations and emergency department (ED) visits for cardiovascular diseases (CVD), respiratory diseases (RD), and respiratory infections (RI) were also observed. However, increased per unit mass toxicity of the remaining PM2.5 was observed. In this study, the changes in hospitalizations and ED

Few studies have quantified the effects of particulate air pollution reductions on electronic toll collection (ETC) and manual toll collection (MTC). Our study evaluated the levels of particulate pollutants, including particulate polycyclic aromatic hydrocarbons (p-PAHs), PM1.0, PM2.5, and PM10, from MTC and ETC systems in booths at a manual/electric hybrid toll station on a highway in Taiwan. A two-week