Composition Analysis and Health Effects of Atmospheric Particulate Matter (2nd Edition)
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality and Health".
Deadline for manuscript submissions: 26 February 2025 | Viewed by 1445
Special Issue Editor
Interests: aerosol
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
This Special Issue is a follow-up of the first Special Issue, entitled “Composition Analysis and Health Effects of Atmospheric Particulate Matter” (https://www.mdpi.com/journal/atmosphere/special_issues/F13HARCL6U) published in Atmosphere.
The multifaceted health effects of atmospheric particulate matter (e.g., PM2.5 or PM10) have raised broader, stronger concerns in recent years, calling for comprehensive environmental health risk assessments to provide new insights into their relations to composition analysis. Atmospheric particulate matter are a mixture of solid and liquid particles suspended in the air. Their major chemical constituents include mineral dust, water-soluble ions (e.g., NO3−, SO42−, Cl−, NH4+, Na+, Ca2+, and Mg2+), organic carbon (OC), elemental carbon (EC), and metals. These particles can be directly emitted from sources such as deserts, oceans, and forests, or they can be chemically produced in the air through reactions involving precursor gasses, such as NOx, SO2, and NH3, emitted from both anthropogenic and natural sources. Specific components of atmospheric particulate matter or different toxic substances adsorbed in them often lead to un-agreeable results of epidemiological and toxicological health risk assessments. This raises an urgent necessity to rapidly and accurately determine the components of atmospheric particulate matter and identify their contributions to relevant toxicological effects. Understanding the quantitative contribution of different components is crucial for correctly assessing their toxicities and exposure risks on human health. Based on various monitoring and detection methods, a clear observation of the particle size, shape, mixing state, and element or group constituents and specific identification of particulate species such as mineral dust, sea-spray aerosols, different types of organic carbon (particularly microplastics and biogenic aerosols), carbon-rich particles (such as soot, tar balls, and char) and heavy metal-containing particles can be performed and their corresponding toxicities in vivo and in vitro can be determined and assessed. With the promising development of machine-learning and artificial intelligence techniques, predictive toxicology through the investigation of their quantitative structure–activity relationships (QSAR) using model calculation has become more and more popular. In this Special Issue, we aim to promote the publication of papers focusing on the characterization and determination of atmospheric particulate matter and estimating, modeling, and forecasting their toxicities and health effects. These include laboratory studies and measurement protocols, methodological approaches, a comparison of acellular and in vitro or in vivo approaches, the influence of chemical composition and indoor/outdoor sources on health impacts, the correlation of health indicators with source apportionment results, and an assessment of health effects related to oxidative stress and population exposure. In particular, whether original research papers or review articles, the Special Issue invites, but it is not limited to, studies with the following focuses:
- Proposing new measurement techniques and analysis approaches on particulate matter’s components;
- Estimating particle toxicities and health impacts using physical, chemical, statistical, and artificial intelligence methods;
- Emphasizing the impacts of atmospheric particulate matter on human health in both indoor and outdoor environments;
- Proposing new tools and indicators for assessing toxicological effects and adverse health impacts of atmospheric particulate matter;
- Assessing the exposure risk to human health relating to compositions of airborne particulate matter;
- Modeling the dynamics of the different compositions of particles to predict their toxicities and health effects.
Prof. Dr. Hong Geng
Guest Editor
Manuscript Submission Information
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Keywords
- atmospheric particulate matter
- bulk and single-particle analysis
- chemical composition
- toxicity
- predictive toxicology
- health impacts
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