Sources, Characterization and Control of Particulate Matter

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".

Deadline for manuscript submissions: closed (15 September 2022) | Viewed by 15962

Special Issue Editors


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Guest Editor
Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
Interests: aerosol chemistry; atmospheric heterogeneous chemistry; fog and cloud chemistry; air quality; secondary aerosol formation

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Guest Editor
Department of Research in Geoscience, KaruSphère, Les Abymes, Guadeloupe (F.W.I.), France
Interests: air pollution; atmospheric sciences; air quality; multifractal analysis; stochastics methods; machine learning, deep learning; urban climatology; climate change
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Special Issue Information

Dear Colleagues,

Particulate matter is one of the most studied air pollutants in the literature due to its adverse health effects. Several epidemiological studies have already associated it with cardiovascular and respiratory diseases, prematurity, general mortality and a series of infectious diseases. This particulate matter can come from natural or anthropogenic sources. The impacts of climate change in desert regions and increasing industrialization and urbanization are some of the causes of increasing concentrations of particulate matter in the atmosphere in the last few decades. Therefore, it is crucial to improve knowledge about the behavior of particulate matter in order to develop strategies and build tools to predict its concentration.

Given the scientific community’s keen interest in this pollutant, the open-access journal Atmosphere is hosting a Special Issue to showcase the most recent findings related to the sources, characterization and control of particulate matter. Whatever the origin and size of the particles, all papers using field measurements, remote sensing, soundings and models are welcome. These articles can cover areas ranging from local to synoptic scale. With the recent increase in the number of volcanic eruptions around the world, this Special Issue is also a suitable place for articles that discuss particulate matter in ash and its impact on human health.

Prof. Dr. Jianmin Chen
Dr. Thomas Plocoste
Guest Editors

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Keywords

  • particulate matter
  • mineral dust
  • ash
  • biomass burning
  • anthropogenic activity
  • ground measurements
  • remote sensing
  • modeling
  • health impact

Published Papers (6 papers)

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Research

13 pages, 632 KiB  
Article
Forecasting PM10 Concentrations in the Caribbean Area Using Machine Learning Models
by Thomas Plocoste and Sylvio Laventure
Atmosphere 2023, 14(1), 134; https://doi.org/10.3390/atmos14010134 - 07 Jan 2023
Cited by 12 | Viewed by 2034
Abstract
In the Caribbean basin, particulate matter lower or equal to 10 μm in diameter (PM10) has a huge impact on human mortality and morbidity due to the African dust. For the first time in this geographical area, the theoretical framework [...] Read more.
In the Caribbean basin, particulate matter lower or equal to 10 μm in diameter (PM10) has a huge impact on human mortality and morbidity due to the African dust. For the first time in this geographical area, the theoretical framework of artificial intelligence is applied to forecast PM10 concentrations. The aim of this study is to forecast PM10 concentrations using six machine learning (ML) models: support vector regression (SVR), k-nearest neighbor regression (kNN), random forest regression (RFR), gradient boosting regression (GBR), Tweedie regression (TR), and Bayesian ridge regression (BRR). Overall, with MBEmax = −2.8139, the results showed that all the models tend to slightly underestimate PM10 empirical data. GBR is the model that gives the best performance (r = 0.7831, R2 = 0.6132, MAE = 6.8479, RMSE = 10.4400, and IOA = 0.7368). By comparing our results to other PM10 ML studies in megacities, we found similar performance using only three input variables, whereas previous studies use many input variables with Artificial Neural Network (ANN) models. All these results showed the features of PM10 concentrations in the Caribbean area. Full article
(This article belongs to the Special Issue Sources, Characterization and Control of Particulate Matter)
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12 pages, 8652 KiB  
Article
Modeling of Atmospheric Dispersion of Jarosite Particles from Tailing Waste in Mitrovica, Kosovo
by Mihone Kerolli Mustafa, Jelena Djokic and Lidija Ćurković
Atmosphere 2022, 13(10), 1690; https://doi.org/10.3390/atmos13101690 - 15 Oct 2022
Viewed by 1232
Abstract
Most of the zinc producers in the world use the jarosite process to improve zinc recovery and to remove iron as an undesirable constituent of zinc ores. Jarosite waste released from the zinc extraction process in Mitrovica, Kosovo has led to severe environmental [...] Read more.
Most of the zinc producers in the world use the jarosite process to improve zinc recovery and to remove iron as an undesirable constituent of zinc ores. Jarosite waste released from the zinc extraction process in Mitrovica, Kosovo has led to severe environmental problems due to toxic heavy metals. This industrial waste from the Zn hydrometallurgy process was abandoned on an open field, being exposed to meteorological conditions and aging. The chemical composition and grain size distribution of the jarosite waste deposit was determined. Microwave digestion procedures were used on whole jarosite samples for use in inductively coupled plasma optical emission spectrometry trace metal analysis (ICP-OES). In addition, different weathering conditions were considered for testing the emission rate of the particles in the laboratory, including relative humidity, wind speed, and temperature. Terrain properties, urban infrastructure, source formation, and location were used for modeling with the AERMOD View-Gaussian air dispersion model. The modeling results showed a range of pollution exceeding the maximum limits in an area of 3 km in the conditions of southeast wind direction and wind speed exceeding 10 m s−1, heavily polluting the city of Mitrovica. Full article
(This article belongs to the Special Issue Sources, Characterization and Control of Particulate Matter)
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28 pages, 14219 KiB  
Article
Applying Wind Erosion and Air Dispersion Models to Characterize Dust Hazard to Highway Safety at Lordsburg Playa, New Mexico, USA
by Iyasu G. Eibedingil, Thomas E. Gill, R. Scott Van Pelt, John Tatarko, Junran Li and Wen-Whai Li
Atmosphere 2022, 13(10), 1646; https://doi.org/10.3390/atmos13101646 - 09 Oct 2022
Cited by 2 | Viewed by 1742
Abstract
Lordsburg Playa, a dry lakebed in the Chihuahuan Desert of southwestern New Mexico (USA), is crossed by Interstate Highway 10 (I-10). Dust from the playa threatens highway safety and has caused dozens of fatal accidents. Two numerical models—the U.S. Department of Agriculture’s Single-Event [...] Read more.
Lordsburg Playa, a dry lakebed in the Chihuahuan Desert of southwestern New Mexico (USA), is crossed by Interstate Highway 10 (I-10). Dust from the playa threatens highway safety and has caused dozens of fatal accidents. Two numerical models—the U.S. Department of Agriculture’s Single-Event Wind Erosion Evaluation Program (SWEEP) and the American Meteorological Society and U.S. Environmental Protection Agency Regulatory Model (AERMOD)—were used to simulate and predict the generation and dispersion of windblown soil, dust, and PM10 from playa hotspots and estimate PM10 concentrations downwind. SWEEP simulates soil loss and particulate matter emissions from the playa surface, and AERMOD predicts the concentration of transported dust. The modeling was informed by field and laboratory data on Lordsburg Playa’s properties, soil and land use/land cover databases, and weather data from meteorological stations. The integrated models predicted that dust plumes originating on the playa—including a large, highly emissive area away from the highway and a smaller, less emissive site directly upwind of the interstate—can lead to hourly average PM10 concentrations of tens, to hundreds of thousands, of micrograms per cubic meter. Modeling results were consistent with observations from webcam photos and visibility records from the meteorological sites. Lordsburg Playa sediment contains metals, as will its dust, but human exposures will be short-term and infrequent. This study was the first to successfully combine the SWEEP wind erosion model and the AERMOD air dispersion model to evaluate PM10 dispersion by wind erosion in a playa environment. With this information, land managers will be able to understand the potential levels of dust and PM10 exposure along the highway, and better manage human health and safety during conditions of blowing dust and sand at Lordsburg Playa. Full article
(This article belongs to the Special Issue Sources, Characterization and Control of Particulate Matter)
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12 pages, 3085 KiB  
Article
Exploring the Mass Concentration of Particulate Matter and Its Relationship with Meteorological Parameters in the Hindu-Kush Range
by Farooq Usman, Bahadar Zeb, Khan Alam, Mohammad Valipour, Allah Ditta, Armin Sorooshian, Rana Roy, Iftikhar Ahmad and Rashid Iqbal
Atmosphere 2022, 13(10), 1628; https://doi.org/10.3390/atmos13101628 - 06 Oct 2022
Cited by 8 | Viewed by 2041
Abstract
Particulate matter (PM) is among the deadliest air pollutants due to its negative health impacts and environmental harm. This study reports on monthly and seasonal concentrations of PM10, PM2.5, and PM1, along with their ratios. Twelve-day samples [...] Read more.
Particulate matter (PM) is among the deadliest air pollutants due to its negative health impacts and environmental harm. This study reports on monthly and seasonal concentrations of PM10, PM2.5, and PM1, along with their ratios. Twelve-day samples were collected once a month in Mingora city (Swat, Pakistan) from January to December 2019 using a low volume sampler. Maximum average mass concentrations of PM10, PM2.5, and PM1 were recorded in December having values of 78, 56, and 32 μg m−3, respectively. Minimum average values for PM10 (44 μg m−3) and PM2.5 (25.1 μg m−3) were recorded in April, while the lowest PM1 (11 μg m−3) was recorded in August. In comparison to other months, the maximum average mass concentrations were 1.77 times (PM10), 2.23 times (PM2.5), and 2.9 times (PM1) higher in December. During the winter season, average mass concentrations remained high. Substantial correlation coefficients of 0.92, 0.79, and 0.75 were recorded between PM10 and PM2.5, PM2.5 and PM1, and PM2.5 and PM1, respectively. The overall average ratios PM2.5: PM10, PM1: PM2.5, and PM1: PM10 were 68.3, 52.6, and 35.4%, respectively. A moderate negative correlation of PM10, PM2.5, and PM1 with wind speed (−0.34, −0.39, and −0.41), a strong negative correlation with temperature (−0.69, −0.71, and −0.74) and rainfall (−0.63, −0.61, and −0.59), and a weak relationship with relative humidity (−0.32, −0.1, and −0.02) were recorded. Full article
(This article belongs to the Special Issue Sources, Characterization and Control of Particulate Matter)
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22 pages, 9753 KiB  
Article
Air Pollution Dispersion over Durban, South Africa
by Mark R. Jury and Mandisa S. Buthelezi
Atmosphere 2022, 13(5), 811; https://doi.org/10.3390/atmos13050811 - 16 May 2022
Cited by 7 | Viewed by 5234
Abstract
Air pollution dispersion over Durban is studied using satellite, reanalysis and in situ measurements. This coastal city of 4 million people located on the east coast of South Africa contributes 29 million T/yr of trace gases, mostly from transport and industry. Terrestrial and [...] Read more.
Air pollution dispersion over Durban is studied using satellite, reanalysis and in situ measurements. This coastal city of 4 million people located on the east coast of South Africa contributes 29 million T/yr of trace gases, mostly from transport and industry. Terrestrial and agricultural particulates derive from the Kalahari Desert, Zambezi Valley and Mozambique. Surface air pollutants accumulate during winter (May–August) and provide a focus for statistical analysis of monthly, daily and hourly time series since 2001. The mean diurnal cycle has wind speed minima during the land−sea breeze transitions that follow morning and evening traffic emissions. Daily air pollution concentrations (CO, NO2, O3, PM2.5 and SO2) vary inversely with dewpoint temperature and tend to peak during winter prefrontal weather conditions. Descending airflow from the interior highlands induces warming, drying and poor air quality, bringing dust and smoke plumes from distant sources. Spatial regression patterns indicate that winters with less dispersion are preceded by warm sea surface temperatures in the tropical West Indian Ocean that promote a standing trough near Durban. Statistical outcomes enable the short- and long-range prediction of atmospheric dispersion and risk of exposure to unhealthy trace gases and particulates. The rapid inland decrease of mean wind speed from 8 to 2 m/s suggests that emissions near the coast will disperse readily compared with in interior valleys. Full article
(This article belongs to the Special Issue Sources, Characterization and Control of Particulate Matter)
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10 pages, 4955 KiB  
Article
Characteristics of PM10 Levels Monitored in Bangkok and Its Vicinity Areas, Thailand
by Navaporn Kanjanasiranont, Teera Butburee and Piangjai Peerakiatkhajohn
Atmosphere 2022, 13(2), 239; https://doi.org/10.3390/atmos13020239 - 30 Jan 2022
Cited by 8 | Viewed by 2584
Abstract
The ambient air concentrations of PM10 were observed in Bangkok and its vicinity areas including Nonthaburi and Nakhon Pathom, Thailand. The selected study areas are located near heavy-traffic roads with a high concentration of traffic-related air pollution. The ambient air samples were collected [...] Read more.
The ambient air concentrations of PM10 were observed in Bangkok and its vicinity areas including Nonthaburi and Nakhon Pathom, Thailand. The selected study areas are located near heavy-traffic roads with a high concentration of traffic-related air pollution. The ambient air samples were collected in the winter season (October 2019 to February 2020). The highest average level of PM10 was found in Nonthaburi (66.63 µg/m3), followed by Bangkok (56.79 µg/m3) and Nakhon Pathom (40.18 µg/m3), respectively. The morphology of these particles is typically spherical and irregular shape particles. At the sampling site in Bangkok, these particles are primarily composed of C, O, and Si, and a certain amount of metals such as Fe, Cu, and Cr. Some trace amount of other elements such as Ca, Na, and S are present in minor concentration. The particles collected from Nakhon Pathom and Nonthaburi sampling sites contain the main abundant elements C, O, and Si, followed by Cu, Cr, S, Fe, Ca, and Na, respectively. These particles are an agglomeration of carbon particles resulting from the incomplete combustion of organic matter. Their origin may be associated with road dust, vehicle emission, and the erosion of building products. It can be noted that the levels and characteristics of PM10 are key factors in understanding the behavior of the particles in not only atmospheric visibility but also human health risks. Full article
(This article belongs to the Special Issue Sources, Characterization and Control of Particulate Matter)
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