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Air Quality Characterisation and Modelling
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Air Quality Characterisation and Modelling

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Environmental Sustainability and Applications".

Deadline for manuscript submissions: closed (15 January 2023) | Viewed by 41515

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. José Carlos Magalhães Pires

E-Mail Website
Guest Editor
LEPABE - Laboratory for Process Engineering, Environment, Biotechnology and Energy, Faculty of Engineering, University of Porto, Rua Dr. Roberto Frias, 4200-465 Porto, Portugal
Interests: CO2 capture; wastewater treatment; microalgal biofuels; process modelling
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Álvaro Gómez-Losada

E-Mail Website
Guest Editor
Department of Quantitative Methods, Loyola University Andalusia, 41704 Sevilla, Spain
Interests: air pollution; environmental data science; knowledge discovery from databases; spatial and temporal forecasting; statistics data mining methods; machine learning

Special Issue Information

Dear Colleagues,

Air pollution is a mixture of particles and gases, which can reach unsafe concentrations for human health, the environment, vegetation and materials. It has become one of the main sustainability issues and a concerning topic in atmospheric science. According to the World Health Organization (WHO), 90% of the world’s population lives in highly polluted environments, and about 7 million premature deaths are caused every year by outdoor and indoor air pollution. The combination of fast-growing populations, transport, fossil fuels, and biomass burning is leading to pollution levels being especially high in some urban areas. Agriculture and natural phenomena are also an important source of pollution, underscoring the multi-faceted and transboundary nature of air pollution. The monitoring and understanding of the temporal and spatial behaviours of air pollutant concentrations are essential for both the implementation of air quality policies and the definition of effective measures to mitigate air pollution and its effects. Quantifying and monitoring exposure to air pollution in terms of public health is also a critical component in policy discussion.

This Special Issue will present recent research activities concerning the characterization of air pollution and the applied modelling approaches.

Dr. José Carlos Magalhães Pires
Prof. Dr. Álvaro Gómez-Losada
Guest Editors

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • particulate matter
  • African dust
  • nitrogen oxides
  • ground-level ozone
  • development, evaluation and application of models
  • statistical models
  • data mining and machine-learning-based models
  • integrated modelling and assessment

Published Papers (16 papers)

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Research

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14 pages, 3731 KiB  
Article
Air Quality Modeling of Cooking Stove Emissions and Exposure Assessment in Rural Areas
by Yucheng He, Sanika Ravindra Nishandar, Rufus David Edwards and Marko Princevac
Sustainability 2023, 15(7), 5676; https://doi.org/10.3390/su15075676 - 24 Mar 2023
Viewed by 1529
Abstract
Cooking stoves produce significant emissions of PM2.5 in homes, causing major health impacts in rural communities. The installation of chimneys in cooking stoves has been documented to substantially reduce indoor emissions compared to those of traditional open fires. Majority of the emissions [...] Read more.
Cooking stoves produce significant emissions of PM2.5 in homes, causing major health impacts in rural communities. The installation of chimneys in cooking stoves has been documented to substantially reduce indoor emissions compared to those of traditional open fires. Majority of the emissions pass through chimneys to the outdoors, while some fraction of the emissions leak directly into the indoor air, which is defined as fugitive emission. Indoor PM2.5 concentrations are then the result of such fugitive emissions and the infiltration of outdoor neighborhood pollutants. This study uses a combination of the one-contaminant box model and dispersion models to estimate the indoor PM2.5 household concentration. The results show that the contributions of outdoor infiltration to indoor PM2.5 concentrations increase with higher packing densities and ventilation rates. For a case study, under WHO recommended ventilation conditions, the 24 h average mass concentration is ~21 μg/m3, with fugitive concentration accounting for ~90% of the total exposure for highly packed communities. These results help to identify the potential benefits of intervention strategies in regions that use chimney stoves. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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17 pages, 3193 KiB  
Article
Investigating the Relationship between Landscape Design Types and Human Thermal Comfort: Case Study of Beijing Olympic Forest Park
by Lin Zhang, Haiyun Xu and Jianbin Pan
Sustainability 2023, 15(4), 2969; https://doi.org/10.3390/su15042969 - 06 Feb 2023
Viewed by 1827
Abstract
Urban green space can improve the local thermal environment and thus the quality of the urban residential environment. Taking the green space of Beijing Olympic Forest Park (BOFP) as an example, this study analysed sample points representing different plant community structures, plant community [...] Read more.
Urban green space can improve the local thermal environment and thus the quality of the urban residential environment. Taking the green space of Beijing Olympic Forest Park (BOFP) as an example, this study analysed sample points representing different plant community structures, plant community types, and landscape environments based on 15 years of continuous dynamic measurement and selected typical annual data (from 2020). The study analysed and explained the spatial differentiation characteristics of human thermal comfort (HTC) in green space areas of BOFP using the predicted mean vote (PMV)–predicted percentage dissatisfied (PPD) physical comfort index model, which comprehensively considers both the objective environment and people’s subjective feelings and psychological states. The results showed that the level of HTC in the park’s green space, across community types and across typical landscape environments, differed between areas with different community structures. PMV–PPD mathematical model fitting further verified the above results. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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23 pages, 6990 KiB  
Article
Spatiotemporal Variations of Air Pollution during the COVID-19 Pandemic across Tehran, Iran: Commonalities with and Differences from Global Trends
by Mohsen Maghrebi, Ali Danandeh Mehr, Seyed Mohsen Karrabi, Mojtaba Sadegh, Sadegh Partani, Behzad Ghiasi and Vahid Nourani
Sustainability 2022, 14(23), 16313; https://doi.org/10.3390/su142316313 - 06 Dec 2022
Viewed by 1822
Abstract
The COVID-19 pandemic has induced changes in global air quality, mostly short-term improvements, through worldwide lockdowns and restrictions on human mobility and industrial enterprises. In this study, we explored the air pollution status in Tehran metropolitan, the capital city of Iran, during the [...] Read more.
The COVID-19 pandemic has induced changes in global air quality, mostly short-term improvements, through worldwide lockdowns and restrictions on human mobility and industrial enterprises. In this study, we explored the air pollution status in Tehran metropolitan, the capital city of Iran, during the COVID-19 outbreak. To this end, ambient air quality data (CO, NO2, O3, PM10, SO2, and AQI) from 14 monitoring stations across the city, together with global COVID-19-related records, were utilized. The results showed that only the annual mean concentration of SO2 increased during the COVID-19 pandemic, mainly due to burning fuel oil in power plants. The findings also demonstrated that the number of days with a good AQI has significantly decreased during the pandemic, despite the positive trend in the global AQI. Based on the spatial variation of the air quality data across the city, the results revealed that increasing pollution levels were more pronounced in low-income regions. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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24 pages, 1881 KiB  
Article
Analysis of Atmospheric Pollutant Data Using Self-Organizing Maps
by Emanoel L. R. Costa, Taiane Braga, Leonardo A. Dias, Édler L. de Albuquerque and Marcelo A. C. Fernandes
Sustainability 2022, 14(16), 10369; https://doi.org/10.3390/su141610369 - 20 Aug 2022
Viewed by 1133
Abstract
Atmospheric pollution is a critical issue in our society due to the continuous development of countries. Therefore, studies concerning atmospheric pollutants using multivariate statistical methods are widely available in the literature. Furthermore, machine learning has proved a good alternative, providing techniques capable of [...] Read more.
Atmospheric pollution is a critical issue in our society due to the continuous development of countries. Therefore, studies concerning atmospheric pollutants using multivariate statistical methods are widely available in the literature. Furthermore, machine learning has proved a good alternative, providing techniques capable of dealing with problems of great complexity, such as pollution. Therefore, this work used the Self-Organizing Map (SOM) algorithm to explore and analyze atmospheric pollutants data from four air quality monitoring stations in Salvador-Bahia. The maps generated by the SOM allow identifying patterns between the air quality pollutants (CO, NO, NO2, SO2, PM10 and O3) and meteorological parameters (environment temperature, relative humidity, wind velocity and standard deviation of wind direction) and also observing the correlations among them. For example, the clusters obtained with the SOM pointed to characteristics of the monitoring stations’ data samples, such as the quantity and distribution of pollution concentration. Therefore, by analyzing the correlations presented by the SOM, it was possible to estimate the effect of the pollutants and their possible emission sources. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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20 pages, 2098 KiB  
Article
Regional Differences, Distribution Dynamics, and Convergence of Air Quality in Urban Agglomerations in China
by Yuting Xue and Kai Liu
Sustainability 2022, 14(12), 7330; https://doi.org/10.3390/su14127330 - 15 Jun 2022
Cited by 5 | Viewed by 1346
Abstract
The urban agglomeration (UA), with a high concentration of population and economy, represents an area with grievous air pollution. It is vital to examine the regional differences, distribution dynamics, and air quality convergence in UAs for sustainable development. In this study, we measured [...] Read more.
The urban agglomeration (UA), with a high concentration of population and economy, represents an area with grievous air pollution. It is vital to examine the regional differences, distribution dynamics, and air quality convergence in UAs for sustainable development. In this study, we measured the air quality of ten UAs in China through the Air Quality Index (AQI). We analyzed regional differences, distribution dynamics, and convergence using Dagum’s decomposition of the Gini coefficient, kernel density estimation, and the convergence model. We found that: the AQI of China’s UAs shows a downward trend, and the index is higher in northern UAs than in southern UAs; the differences in air quality within UAs are not significant, but there is a gap between them; the overall difference in air quality tends to decrease, and regional differences in air quality are the primary contributor to the overall difference; the overall distribution and the distribution of each UA move rightward; the distribution pattern, ductility, and polarization characteristics are different, indicating that the air quality has improved and is differentiated between UAs; except for the Guanzhong Plain, the overall UA and each UA have obvious σ convergence characteristics, and each UA presents prominent absolute β convergence, conditional β convergence, and club convergence. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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18 pages, 2458 KiB  
Article
Do Lawsuits by ENGOs Improve Environmental Quality? Results from the Field of Air Pollution Policy in Germany
by Fabio Bothner, Annette Elisabeth Töller and Paul Philipp Schnase
Sustainability 2022, 14(11), 6592; https://doi.org/10.3390/su14116592 - 27 May 2022
Cited by 3 | Viewed by 2015
Abstract
It is generally assumed that in EU Member States the right of recognized environmental organizations (ENGOs) to file lawsuits under the Aarhus Convention contributes not only to a better enforcement of environmental law, but also to an improvement of environmental quality. However, this [...] Read more.
It is generally assumed that in EU Member States the right of recognized environmental organizations (ENGOs) to file lawsuits under the Aarhus Convention contributes not only to a better enforcement of environmental law, but also to an improvement of environmental quality. However, this has not yet been investigated. Hence, this paper examines whether 49 lawsuits that environmental associations filed against air quality plans of German cities between 2011 and 2019 had a positive effect on air quality by reducing NO2 emissions in the respective cities. Using a staggered difference-in-differences regression model, we show that, on average, lawsuits against cities’ clean air plans have a negative effect on NO2 concentration in these cities. In fact, the NO2 concentration in cities sued by ENGOs decreased by about 1.31 to 3.30 µg/m3 relative to their counterfactual level. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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14 pages, 2180 KiB  
Article
Assessing the Impact of Local Policies on PM2.5 Concentration Levels: Application to 10 European Cities
by Enrico Pisoni, Philippe Thunis, Alexander De Meij and Bertrand Bessagnet
Sustainability 2022, 14(11), 6384; https://doi.org/10.3390/su14116384 - 24 May 2022
Cited by 4 | Viewed by 1667
Abstract
In this paper, we propose a methodology to evaluate the effectiveness of local emission reduction policies on PM2.5 concentration levels. In particular, we look at the impact of emission reduction policies at different scales (from urban to EU scale) on different PM2.5 baseline [...] Read more.
In this paper, we propose a methodology to evaluate the effectiveness of local emission reduction policies on PM2.5 concentration levels. In particular, we look at the impact of emission reduction policies at different scales (from urban to EU scale) on different PM2.5 baseline concentration levels. The methodology, based on a post-processing of air quality model simulations, is applied to 10 cities in Europe to understand on which sources local actions are effective to improve air quality, and over which concentration ranges. The results show that local actions are effective on low-level concentrations in some cities (e.g., Rome), whereas in other cases, policies are more effective on high-level concentrations (e.g., Krakow). This means that, in specific geographical areas, a coordinated approach (among cities or even at different administration levels) would be needed to significantly improve air quality. At last, we show that the effectiveness of local actions on urban air pollution is highly city-dependent. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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16 pages, 2421 KiB  
Article
A Real-Time Comparison of Four Particulate Matter Size Fractions in the Personal Breathing Zone of Paris Subway Workers: A Six-Week Prospective Study
by Rémy Pétremand, Guillaume Suárez, Sophie Besançon, J. Hugo Dil and Irina Guseva Canu
Sustainability 2022, 14(10), 5999; https://doi.org/10.3390/su14105999 - 15 May 2022
Cited by 6 | Viewed by 1949
Abstract
We developed a Bayesian spline model for real-time mass concentrations of particulate matter (PM10, PM2.5, PM1, and PM0.3) measured simultaneously in the personal breathing zone of Parisian subway workers. The measurements were performed by GRIMM, a gravimetric method, and DiSCmini during the workers’ [...] Read more.
We developed a Bayesian spline model for real-time mass concentrations of particulate matter (PM10, PM2.5, PM1, and PM0.3) measured simultaneously in the personal breathing zone of Parisian subway workers. The measurements were performed by GRIMM, a gravimetric method, and DiSCmini during the workers’ work shifts over two consecutive weeks. The measured PM concentrations were analyzed with respect to the working environment, the underground station, and any specific events that occurred during the work shift. Overall, PM0.3 concentrations were more than an order of magnitude lower compared to the other PM concentrations and showed the highest temporal variation. The PM2.5 levels raised the highest exposure concern: 15 stations out of 37 had higher mass concentrations compared to the reference. Station PM levels were not correlated with the annual number of passengers entering the station, the year of station opening or renovation, or the number of platforms and tracks. The correlation with the number of station entrances was consistently negative for all PM sizes, whereas the number of correspondence concourses was negatively correlated with PM0.3 and PM10 levels and positively correlated with PM1 and PM2.5 levels. The highest PM10 exposure was observed for the station platform, followed by the subway cabin and train, while ticket counters had the highest PM0.3, PM1, and PM2.5 mass concentrations. We further found that compared to gravimetric and DiSCmini measurements, GRIMM results showed some discrepancies, with an underestimation of exposure levels. Therefore, we suggest using GRIMM, calibrated by gravimetric methods, for PM sizes above 1μm, and DiSCmini for sizes below 700 nm. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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16 pages, 3663 KiB  
Article
Investigating the Emission of Hazardous Chemical Substances from Mashrabiya Used for Indoor Air Quality in Hot Desert Climate
by Chuloh Jung and Nahla Al Qassimi
Sustainability 2022, 14(5), 2842; https://doi.org/10.3390/su14052842 - 28 Feb 2022
Cited by 16 | Viewed by 1706
Abstract
Dubai has the reputation of a continuously growing city, with skyscrapers and mega residential projects. Many new residential projects with poor choices of material and ventilation have led to a faster rise in sick building syndrome (SBS) in Dubai than in any other [...] Read more.
Dubai has the reputation of a continuously growing city, with skyscrapers and mega residential projects. Many new residential projects with poor choices of material and ventilation have led to a faster rise in sick building syndrome (SBS) in Dubai than in any other country, and the IAQ (indoor air quality) has become more critical. Volatile organic compounds (VOCs) and formaldehyde (HCHO) affect the health of residents, producing the phenomenon known as SBS (sick building syndrome). It has been reported that wood materials used for furniture and wooden windows and doors are a significant source of indoor air pollution in new houses. This paper aims to identify the factor elements emitting harmful chemical substances, such as VOCs and HCHO, from wooden mashrabiya (traditional Arabic window) by examining the characteristics of the raw and surface materials through test pieces. As a methodology, a small chamber system was used to test the amount of hazardous chemicals generated for each test piece. For Total volatile organic compounds (TVOC) and HCHO, the blank concentration before the injection and the generation after seven days were measured. The results showed that to reduce TVOC, it is necessary to secure six months or more as a retention period for raw materials and surface materials. The longer the retention period, the smaller the TVOC emission amount. In the case of mashrabiya, an HCHO low-emitting adhesive and maintenance for one month or more are essential influencing factors. It was proven that using raw materials with a three-month or more retention period and surface materials with a one-month or more retention period is safe for indoor mashrabiya. This study is the first study in the Middle East to identify factors and characteristics that affect the emission of hazardous chemicals from wood composite materials, such as wood mashrabiya, that affect indoor air quality in residential projects in Dubai. It analyzes the correlation between emission levels and the retention period of raw and surface materials, in order to provide a new standard for indoor air pollutants. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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17 pages, 4760 KiB  
Article
Surface Ozone Pollution: Trends, Meteorological Influences, and Chemical Precursors in Portugal
by Rafaela C. V. Silva and José C. M. Pires
Sustainability 2022, 14(4), 2383; https://doi.org/10.3390/su14042383 - 19 Feb 2022
Cited by 4 | Viewed by 1602
Abstract
Surface ozone (O3) is a secondary air pollutant, harmful to human health and vegetation. To provide a long-term study of O3 concentrations in Portugal (study period: 2009–2019), a statistical analysis of ozone trends in rural stations (where the highest concentrations [...] Read more.
Surface ozone (O3) is a secondary air pollutant, harmful to human health and vegetation. To provide a long-term study of O3 concentrations in Portugal (study period: 2009–2019), a statistical analysis of ozone trends in rural stations (where the highest concentrations can be found) was first performed. Additionally, the effect of nitrogen oxides (NOx) and meteorological variables on O3 concentrations were evaluated in different environments in northern Portugal. A decreasing trend of O3 concentrations was observed in almost all monitoring stations. However, several exceedances to the standard values legislated for human health and vegetation protection were recorded. Daily and seasonal O3 profiles showed high concentrations in the afternoon and summer (for all inland rural stations) or spring (for Portuguese islands). The high number of groups obtained from the cluster analysis showed the difference of ozone behaviour amongst the existent rural stations, highlighting the effectiveness of the current geographical distribution of monitoring stations. Stronger correlations between O3, NO, and NO2 were detected at the urban site, indicating that the O3 concentration was more NOx-sensitive in urban environments. Solar radiation showed a higher correlation with O3 concentration regarding the meteorological influence. The wind and pollutants transport must also be considered in air quality studies. The presented results enable the definition of air quality policies to prevent and/or mitigate unfavourable outcomes from O3 pollution. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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18 pages, 10035 KiB  
Article
Impact of Ventilation Strategy on the Transmission of Outdoor Pollutants into Indoor Environment Using CFD
by Murtaza Mohammadi and John Calautit
Sustainability 2021, 13(18), 10343; https://doi.org/10.3390/su131810343 - 16 Sep 2021
Cited by 11 | Viewed by 2452
Abstract
The transition to remote working due to the pandemic has accentuated the importance of clean indoor air, as people spend a significant portion of their time indoors. Amongst the various determinants of indoor air quality, outdoor pollution is a significant source. While conventional [...] Read more.
The transition to remote working due to the pandemic has accentuated the importance of clean indoor air, as people spend a significant portion of their time indoors. Amongst the various determinants of indoor air quality, outdoor pollution is a significant source. While conventional studies have certainly helped to quantify the long-term personal exposure to pollutants and assess their health impact, they have not paid special attention to the mechanism of transmission of pollutants between the two environments. Nevertheless, the quantification of infiltration is essential to determine the contribution of ambient pollutants in indoor air quality and its determinants. This study evaluates the transmission of outdoor pollutants into the indoor environment using 3D computational fluid dynamics modelling with a pollution dispersion model. Naturally ventilated buildings next to an urban canyon were modelled and simulated using Ansys Fluent and validated against wind tunnel results from the Concentration Data of Street Canyons database. The model consisted of two buildings of three storeys each, located on either side of a road. Two line-source pollutants were placed in the street, representing traffic emissions. Three internal rooms were selected and modelled on each floor and implemented with various ventilation strategies. Results indicate that for a canyon with an aspect ratio of 1, indoor spaces in upstream buildings are usually less polluted than downstream ones. Although within the canyon, pollution is 2–3 times higher near the upstream building. Cross ventilation can minimise or prevent infiltration of road-side pollutants into indoor spaces, while also assisting in the dispersion of ambient pollutants. The critical configuration, in terms of air quality, is single-sided ventilation from the canyon. This significantly increases indoor pollutant concentration regardless of the building location. The study reveals that multiple factors determine the indoor–outdoor links, and thorough indexing and understanding of the processes can help designers and urban planners in regulating urban configuration and geometries for improved indoor air quality. Future works should look at investigating the influence of indoor emissions and the effects of different seasons. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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16 pages, 2762 KiB  
Article
Mitigation of Suspendable Road Dust in a Subpolar, Oceanic Climate
by Brian Charles Barr, Hrund Ólöf Andradóttir, Throstur Thorsteinsson and Sigurður Erlingsson
Sustainability 2021, 13(17), 9607; https://doi.org/10.3390/su13179607 - 26 Aug 2021
Cited by 11 | Viewed by 2906
Abstract
Tire and road wear particles (TRWP) are a significant source of atmospheric particulate matter and microplastic loading to waterways. Road wear is exacerbated in cold climate by the widespread use of studded tires. The goal of this research was to assess the anthropogenic [...] Read more.
Tire and road wear particles (TRWP) are a significant source of atmospheric particulate matter and microplastic loading to waterways. Road wear is exacerbated in cold climate by the widespread use of studded tires. The goal of this research was to assess the anthropogenic levers for suspendable road dust generation and climatic conditions governing the environmental fate of non-exhaust particles in a wet maritime winter climate. Sensitivity analyses were performed using the NORTRIP model for the Capital region of Reykjavík, Iceland (64.1° N). Precipitation frequency (secondarily atmospheric relative humidity) governed the partitioning between atmospheric and waterborne PM10 particles (55% and 45%, respectively). Precipitation intensity, however, increased proportionally most the drainage to waterways via stormwater collection systems, albeit it only represented 5% of the total mass of dust generated in winter. A drastic reduction in the use of studded tires, from 46% to 15% during peak season, would be required to alleviate the number of ambient air quality exceedances. In order to achieve multifaceted goals of a climate resilient, resource efficient city, the most important mitigation action is to reduce overall traffic volume. Reducing traffic speed may help speed environmental outcomes. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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10 pages, 2026 KiB  
Article
Considering Condensable Particulate Matter Emissions Improves the Accuracy of Air Quality Modeling for Environmental Impact Assessment
by Doo Sung Choi, Jong-Sang Youn, Im Hack Lee, Byung Jin Choi and Ki-Joon Jeon
Sustainability 2021, 13(8), 4470; https://doi.org/10.3390/su13084470 - 16 Apr 2021
Cited by 7 | Viewed by 1840
Abstract
This study examines environmental impact assessment considering filterable particulate matter (FPM) and condensable particulate matter (CPM) to improve the accuracy of the air quality model. Air pollutants and meteorological data were acquired from Korea’s national monitoring station near a residential development area in [...] Read more.
This study examines environmental impact assessment considering filterable particulate matter (FPM) and condensable particulate matter (CPM) to improve the accuracy of the air quality model. Air pollutants and meteorological data were acquired from Korea’s national monitoring station near a residential development area in the target district and background site. Seasonal emissions of PM2.5, including CPM, were estimated using the California puff (CALPUFF) model, based on Korea’s national emissions inventory. These results were compared with the traditional environmental impact assessment results. For the residential development area, the seasonal PM2.5 concentration was predicted by considering FPM and CPM emissions in the target area as well as the surrounding areas. In winter and spring, air quality standards were not breached because only FPM was considered. However, when CPM was included in the analysis, the results exceeded the air quality standards. Furthermore, it was predicted that air quality standards would not be breached in summer and autumn, even when CPM is included. In other words, conducting an environmental impact assessment on air pollution including CPM affects the final environmental decision. Therefore, it is concluded that PM2.5 should include CPM for greater accuracy of the CALPUFF model for environmental impact assessment. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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15 pages, 5642 KiB  
Article
Use of Simulated and Observed Meteorology for Air Quality Modeling and Source Ranking for an Industrial Region
by Awkash Kumar, Anil Kumar Dikshit and Rashmi S. Patil
Sustainability 2021, 13(8), 4276; https://doi.org/10.3390/su13084276 - 12 Apr 2021
Cited by 4 | Viewed by 2525
Abstract
The Gaussian-based dispersion model American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) is being used to predict concentration for air quality management in several countries. A study was conducted for an industrial area, Chembur of Mumbai city in India, to assess the agreement [...] Read more.
The Gaussian-based dispersion model American Meteorological Society/Environmental Protection Agency Regulatory Model (AERMOD) is being used to predict concentration for air quality management in several countries. A study was conducted for an industrial area, Chembur of Mumbai city in India, to assess the agreement of observed surface meteorology and weather research and forecasting (WRF) output through AERMOD with ground-level NOx and PM10 concentrations. The model was run with both meteorology and emission inventory. When results were compared, it was observed that the air quality predictions were better with the use of WRF output data for a model run than with the observed meteorological data. This study showed that the onsite meteorological data can be generated by WRF which saves resources and time, and it could be a good option in low-middle income countries (LIMC) where meteorological stations are not available. Also, this study quantifies the source contribution in the ambient air quality for the region. NOx and PM10 emission loads were always observed to be high from the industries but NOx concentration was high from vehicular sources and PM10 concentration was high from industrial sources in ambient concentration. This methodology can help the regulatory authorities to develop control strategies for air quality management in LIMC. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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15 pages, 401 KiB  
Article
Can Carbon Trading Policies Promote Regional Green Innovation Efficiency? Empirical Data from Pilot Regions in China
by Baoliu Liu, Zhenqing Sun and Huanhuan Li
Sustainability 2021, 13(5), 2891; https://doi.org/10.3390/su13052891 - 07 Mar 2021
Cited by 34 | Viewed by 5050
Abstract
Although the emission reduction and innovation effects of carbon emissions trading have attracted considerable interest among academics and policy makers, there is a lack of empirical research on how carbon trading pilots in China promote regional green innovation. Therefore, we measured the green [...] Read more.
Although the emission reduction and innovation effects of carbon emissions trading have attracted considerable interest among academics and policy makers, there is a lack of empirical research on how carbon trading pilots in China promote regional green innovation. Therefore, we measured the green innovation efficiency of 30 provinces and cities in mainland China from 2005 to 2018, using selected panel data within a super-efficient SBM model that incorporated undesirable outputs. We used a double differential model to evaluate the impacts of carbon trading policies on the green innovation efficiency of seven carbon trading pilot regions. These impacts were confirmed using the double differential propensity score matching method. Our findings were as follows. (1) The implementation of carbon trading policies has a significant and continuous effect of promoting and improving green innovation efficiency in the pilot areas. (2) Carbon trading induces technological innovation effects, enabling green innovation potential to be realized. Regional green innovation efficiency is further improved through energy substitution and structural upgrading effects and subsequently through all three of the above effects. (3) The synergy between the three major effects of carbon trading policies amplifies regional green innovation efficiency. Therefore, the Chinese government should accelerate its efforts to develop and improve carbon markets, promote carbon trading policies, and actively foster synergy among the three effects to achieve green and sustainable regional development. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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Review

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26 pages, 13058 KiB  
Review
The History of Air Quality in Utah: A Narrative Review
by Logan E. Mitchell and Chris A. B. Zajchowski
Sustainability 2022, 14(15), 9653; https://doi.org/10.3390/su14159653 - 05 Aug 2022
Cited by 5 | Viewed by 7062
Abstract
Utah has a rich history related to air pollution; however, it is not widely known or documented. This is despite air quality being a top issue of public concern for the state’s urban residents and acute episodes that feature some of the world’s [...] Read more.
Utah has a rich history related to air pollution; however, it is not widely known or documented. This is despite air quality being a top issue of public concern for the state’s urban residents and acute episodes that feature some of the world’s worst short-term particulate matter exposure. As we discuss in this narrative review, the relationship between air pollution and the state’s residents has changed over time, as fuel sources shifted from wood to coal to petroleum and natural gas. Air pollution rose in prominence as a public issue in the 1880s as Utah’s urban areas grew. Since then, scientific advances have increased the understanding of air quality impacts on human health, groups of concerned citizens worked to raise public awareness, policy makers enacted legislation to improve air quality, and courts upheld rights to clean air. Utah’s air quality future holds challenges and opportunities and can serve as useful case for other urbanizing regions struggling with air quality concerns. Population growth and changing climate will exacerbate current air quality trends, but economically viable clean energy technologies can be deployed to reduce air pollution, bringing substantial public health and economic benefits to the state’s residents and other settings with similar public health concerns. Full article
(This article belongs to the Special Issue Air Quality Characterisation and Modelling)
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