According to World Health Origination (WHO), almost 92% of the world’s population lives in places where air pollution levels exceed WHO limits. More than half the world’s population resides in cities that tend to be densely populated, and residents are therefore disproportionately affected by ambient air pollution. However, the causes of environmental problems due to air pollution in different countries and regions are becoming increasingly complex due to the complex sources of particulate matter (PM). Therefore, an understanding of the present state and the spatio-temporal distribution of air pollutants, exposure of the population, and evaluation of the adverse health effects caused by air pollution is important for protecting human and environmental health and establishing pollution control policies.
Changes in emissions over recent decades have prompted urban pollution patterns to be considered in new policy developments and health impact studies. In addition, urban PM contributions have seen a decreasing trend relative to non-urban sources in some regions in the last decade (e.g., Beijing, New Delhi, Hanoi), and numerous studies, however, have shown that regional and continental PM is contributing more significantly to urban PM in many cities.
This Research Topic will focus on papers characterizing aerosols and air quality in cities, and their potential environmental health risks. We aim to collect research on PM composition, the source contributors of PM, nanoparticles, and gaseous precursors, as well as spatially resolved exposure maps of urban pollutants, with the aim to enhance air quality policy assessment and the evaluation of health effects in urban cities.
The following subtopics will be included in the Research Topic but are not limited to:
1. The spatio-temporal distribution of air pollutants and personal exposure assessment in urban environments.
2. The potential environmental health risks and impacts of urban ambient air pollution and factors determining susceptibility in urban populations.
3. The application of Artificial Intelligence and Big Data for atmospheric pollution monitoring and prediction models
Original research and review article submissions are welcomed from all researchers working on the themes listed above, including participants of the RI-URABNS project.
We wish to acknowledge the contributions of our Topic Coordinators, Xiansheng Liu and Hadiatullah Hadiatullah who provided valuable support in the realization of this project.
According to World Health Origination (WHO), almost 92% of the world’s population lives in places where air pollution levels exceed WHO limits. More than half the world’s population resides in cities that tend to be densely populated, and residents are therefore disproportionately affected by ambient air pollution. However, the causes of environmental problems due to air pollution in different countries and regions are becoming increasingly complex due to the complex sources of particulate matter (PM). Therefore, an understanding of the present state and the spatio-temporal distribution of air pollutants, exposure of the population, and evaluation of the adverse health effects caused by air pollution is important for protecting human and environmental health and establishing pollution control policies.
Changes in emissions over recent decades have prompted urban pollution patterns to be considered in new policy developments and health impact studies. In addition, urban PM contributions have seen a decreasing trend relative to non-urban sources in some regions in the last decade (e.g., Beijing, New Delhi, Hanoi), and numerous studies, however, have shown that regional and continental PM is contributing more significantly to urban PM in many cities.
This Research Topic will focus on papers characterizing aerosols and air quality in cities, and their potential environmental health risks. We aim to collect research on PM composition, the source contributors of PM, nanoparticles, and gaseous precursors, as well as spatially resolved exposure maps of urban pollutants, with the aim to enhance air quality policy assessment and the evaluation of health effects in urban cities.
The following subtopics will be included in the Research Topic but are not limited to:
1. The spatio-temporal distribution of air pollutants and personal exposure assessment in urban environments.
2. The potential environmental health risks and impacts of urban ambient air pollution and factors determining susceptibility in urban populations.
3. The application of Artificial Intelligence and Big Data for atmospheric pollution monitoring and prediction models
Original research and review article submissions are welcomed from all researchers working on the themes listed above, including participants of the RI-URABNS project.
We wish to acknowledge the contributions of our Topic Coordinators, Xiansheng Liu and Hadiatullah Hadiatullah who provided valuable support in the realization of this project.