Special Issue "Air Quality in the UK"

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

Deadline for manuscript submissions: closed (15 November 2021).

Special Issue Editors

Dr. Fabio Galatioto
E-Mail Website
Guest Editor
Connected Places Catapult, Milton Keynes MK9 1BP, UK
Interests: monitoring; modelling and predictions; indoor/outdoor air quality; pollutants emissions; transport strategies and planning; sustainable transport; transport modes
Prof. Dr. Prashant Kumar
E-Mail Website
Guest Editor
Global Centre for Clean Air Research (GCARE), University of Surrey, Guildford GU2 7XH, UK
Interests: urban air quality; public health; atmospheric aerosols and nanoparticles
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Francis Pope
E-Mail Website
Guest Editor
Professor of Atmospheric Science, University of Birmingham, Birmingham B15 2TT, UK
Interests: atmospheric sciences; human health; sustainable cities; air pollution; climate change; fundamental aerosol chemistry and microphysics; city resilience
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cities, urban areas and large indoor spaces are the places where people and the economy of a Country grow, however those same places are known to be subject to the highest level of air pollution. According to World Health Organization 90% of people are exposed to unsafe air, and breathing it in is killing nearly 9 million people a year and harming billions more. The number of early deaths caused by air pollution has doubled previous estimates, meaning toxic air is now killing more people than tobacco, making air pollution the third highest cause of death globally. In the UK, according to a 2016 report from the Royal College of Physicians, up to 40,000 additional deaths and a cut in lifespan of up to 2 years were linked to air pollution exposure.

This is why research, applications, technology and innovation in the Air Quality subject, spanning from monitoring to modelling, from impact assessment to exposure quantification are more than ever needed to mitigate and solve in the long-term this global issue and enable clean and sustainable economic growth.

Over recent years, the UK has implemented more stringent policies (e.g. Clean Air Strategy and related Clean Air Zones, and recently The Environment Bill) as well as funded several research and innovation projects across the Country, but also applied research through EU and International initiatives in UK Demonstration Cities. For that, this Special Issue wants to give the opportunity to Academia, SMEs, Industry, Local Authorities and relevant Agencies to publish their original research or review on the subject of Air Quality in the UK and identify new technologies which can be used to address the problem.

Dr. Fabio Galatioto
Prof. Dr. Prashant Kumar
Prof. Francis Pope
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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

  • Air quality/emissions monitoring, low-cost sensing, modelling and mapping;
  • Applications of innovative technologies to reduce emissions and/or pollutants concentration and citizen science to limit exposure of public;
  • Implementation of urban strategies/policies to improve outdoor air quality;
  • Indoor air quality (residential, business, measurements, modelling, impacts, in-out flow, …);
  • Road, rail, maritime and aviation pollution sources and their individual or cumulative air quality impacts;
  • Non-transport related air quality (e.g. major urban sources, innovation in industrial air pollution abatement, …);
  • Clean growth and economic implication of poor air quality (indoor and outdoor, implications on productivity, ….);
  • Air quality human exposure (epidemiology, biomonitoring technologies, impacts of ultra-fine particles on human health, short- and long-term implications, ….)

Published Papers (9 papers)

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Research

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Article
A Gaussian Process Method with Uncertainty Quantification for Air Quality Monitoring
Atmosphere 2021, 12(10), 1344; https://doi.org/10.3390/atmos12101344 - 14 Oct 2021
Viewed by 343
Abstract
The monitoring and forecasting of particulate matter (e.g., PM2.5) and gaseous pollutants (e.g., NO, NO2, and SO2) is of significant importance, as they have adverse impacts on human health. However, model performance can easily degrade due to [...] Read more.
The monitoring and forecasting of particulate matter (e.g., PM2.5) and gaseous pollutants (e.g., NO, NO2, and SO2) is of significant importance, as they have adverse impacts on human health. However, model performance can easily degrade due to data noises, environmental and other factors. This paper proposes a general solution to analyse how the noise level of measurements and hyperparameters of a Gaussian process model affect the prediction accuracy and uncertainty, with a comparative case study of atmospheric pollutant concentrations prediction in Sheffield, UK, and Peshawar, Pakistan. The Neumann series is exploited to approximate the matrix inverse involved in the Gaussian process approach. This enables us to derive a theoretical relationship between any independent variable (e.g., measurement noise level, hyperparameters of Gaussian process methods), and the uncertainty and accuracy prediction. In addition, it helps us to discover insights on how these independent variables affect the algorithm evidence lower bound. The theoretical results are verified by applying a Gaussian processes approach and its sparse variants to air quality data forecasting. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
Air Flow Experiments on a Train Carriage—Towards Understanding the Risk of Airborne Transmission
Atmosphere 2021, 12(10), 1267; https://doi.org/10.3390/atmos12101267 - 29 Sep 2021
Viewed by 730
Abstract
A series of experiments was undertaken on an intercity train carriage aimed at providing a “proof of concept” for three methods in improving our understanding of airflow behaviour and the accompanied dispersion of exhaled droplets. The methods used included the following: measuring CO [...] Read more.
A series of experiments was undertaken on an intercity train carriage aimed at providing a “proof of concept” for three methods in improving our understanding of airflow behaviour and the accompanied dispersion of exhaled droplets. The methods used included the following: measuring CO2 concentrations as a proxy for exhaled breath, measuring the concentrations of different size fractions of aerosol particles released from a nebuliser, and visualising the flow patterns at cross-sections of the carriage by using a fog machine and lasers. Each experiment succeeded in providing practical insights into the risk of airborne transmission. For example, it was shown that the carriage is not well mixed over its length, however, it is likely to be well mixed along its height and width. A discussion of the suitability of the fresh air supply rates on UK train carriages is also provided, drawing on the CO2 concentrations measured during these experiments. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
Real-World Contribution of Electrification and Replacement Scenarios to the Fleet Emissions in West Midland Boroughs, UK
Atmosphere 2021, 12(3), 332; https://doi.org/10.3390/atmos12030332 - 04 Mar 2021
Cited by 5 | Viewed by 704
Abstract
This study reports the likely real-world effects of fleet replacement with electric vehicles (EVs) and higher efficiency EURO 6 vehicles on the exhaustive emissions of NOx, PM, and CO2 in the seven boroughs of the West Midlands (WM) region, UK. [...] Read more.
This study reports the likely real-world effects of fleet replacement with electric vehicles (EVs) and higher efficiency EURO 6 vehicles on the exhaustive emissions of NOx, PM, and CO2 in the seven boroughs of the West Midlands (WM) region, UK. National fleet composition data, local EURO distributions, and traffic compositions were used to project vehicle fleet compositions for different roads in each borough. A large dataset of real-world emission factors including over 90,000 remote-sensing measurements, obtained from remote sensing campaigns in five UK cities, was used to parameterize the emission profiles of the studied scenarios. Results show that adoption of the fleet electrification approach would have the highest emission reduction potential on urban roads in WM boroughs. It would result in maximum reductions ranging from 35.0 to 37.9%, 44.3 to 48.3%, and 46.9 to 50.3% for NOx, PM, and CO2, respectively. In comparison, the EURO 6 replacement fleet scenario would lead to reductions ranging from 10.0 to 10.4%, 4.0 to 4.2%, and 6.0 to 6.4% for NOx, PM, and CO2, respectively. The studied mitigation scenarios have higher efficacies on motorways compared to rural and urban roads because of the differences in traffic fleet composition. The findings presented will help policymakers choose climate and air quality mitigation strategies. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
Road Emissions in London: Insights from Geographically Detailed Classification and Regression Modelling
Atmosphere 2021, 12(2), 188; https://doi.org/10.3390/atmos12020188 - 30 Jan 2021
Cited by 2 | Viewed by 965
Abstract
Greenhouse gases and air pollutant emissions originating from road transport continues to rise in the UK, indicating a significant contribution to climate change and negative impacts on human health and ecosystems. However, emissions are usually estimated at aggregated levels, and on many occasions [...] Read more.
Greenhouse gases and air pollutant emissions originating from road transport continues to rise in the UK, indicating a significant contribution to climate change and negative impacts on human health and ecosystems. However, emissions are usually estimated at aggregated levels, and on many occasions roads of minor importance are not taken into account, normally due to lack of traffic counts. This paper presents a methodology enabling estimation of air pollutants and CO2 for each street segment in the Greater London area. This is achieved by applying a hybrid probabilistic classification–regression approach on a set of variables believed to affect traffic volumes and utilizing emission factors. The output reveals pollution hot spots and the effects of open spaces in a spatially rich dataset. Considering the disaggregated approach, the methodology can be used to facilitate policy making for both local and national aggregated levels. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
Understanding Spatial Variability of NO2 in Urban Areas Using Spatial Modelling and Data Fusion Approaches
Atmosphere 2021, 12(2), 179; https://doi.org/10.3390/atmos12020179 - 29 Jan 2021
Cited by 2 | Viewed by 514
Abstract
Small-scale spatial variability in NO2 concentrations is analysed with the help of pollution maps. Maps of NO2 estimated by the Airviro dispersion model and land use regression (LUR) model are fused with measured NO2 concentrations from low-cost sensors (LCS), reference [...] Read more.
Small-scale spatial variability in NO2 concentrations is analysed with the help of pollution maps. Maps of NO2 estimated by the Airviro dispersion model and land use regression (LUR) model are fused with measured NO2 concentrations from low-cost sensors (LCS), reference sensors and diffusion tubes. In this study, geostatistical universal kriging was employed for fusing (integrating) model estimations with measured NO2 concentrations. The results showed that the data fusion approach was capable of estimating realistic NO2 concentration maps that inherited spatial patterns of the pollutant from the model estimations and adjusted the modelled values using the measured concentrations. Maps produced by the fusion of NO2-LCS with NO2-LUR produced better results, with r-value 0.96 and RMSE 9.09. Data fusion adds value to both measured and estimated concentrations: the measured data are improved by predicting spatiotemporal gaps, whereas the modelled data are improved by constraining them with observed data. Hotspots of NO2 were shown in the city centre, eastern parts of the city towards the motorway (M1) and on some major roads. Air quality standards were exceeded at several locations in Sheffield, where annual mean NO2 levels were higher than 40 µg/m3. Road traffic was considered to be the dominant emission source of NO2 in Sheffield. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
Mobile Monitoring for the Spatial and Temporal Assessment of Local Air Quality (NO2) in the City of London
Atmosphere 2021, 12(1), 106; https://doi.org/10.3390/atmos12010106 - 13 Jan 2021
Viewed by 901
Abstract
This paper reports on the analysis and findings of the data collected during a mobile air quality campaign commissioned by the City of London Corporation (CoL). This was done using an equipped vehicle capable of taking continuous precision measurements of local air quality [...] Read more.
This paper reports on the analysis and findings of the data collected during a mobile air quality campaign commissioned by the City of London Corporation (CoL). This was done using an equipped vehicle capable of taking continuous precision measurements of local air quality while travelling within the City. Several comparative analyses on measured Nitrogen Dioxide (NO2) data have been performed between Smogmobile data and those available from CoL precision systems as well as with indicative systems, namely Diffusion Tubes, distributed across the City. Key findings highlight that data collected from the Smogmobile, in terms of average concentration of NO2 across the City (62 µg/m3), are very similar to those obtained by averaging the values from the 48 indicative systems (59.5 µg/m3), with an error of just 4%. Overall, this study demonstrates significant potential and value in using mobile air quality measurements to support assessment of air quality over large areas by Local authorities. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
Indoor Air Pollution from Residential Stoves: Examining the Flooding of Particulate Matter into Homes during Real-World Use
Atmosphere 2020, 11(12), 1326; https://doi.org/10.3390/atmos11121326 - 07 Dec 2020
Cited by 3 | Viewed by 14860
Abstract
This study concerns the levels of particulate matter (PM2.5 and PM1) released by residential stoves inside the home during ‘real world’ use. Focusing on stoves that were certified by the UK’s Department of Environment, Food, and Rural Affairs (DEFRA), [...] Read more.
This study concerns the levels of particulate matter (PM2.5 and PM1) released by residential stoves inside the home during ‘real world’ use. Focusing on stoves that were certified by the UK’s Department of Environment, Food, and Rural Affairs (DEFRA), PM sensors were placed in the vicinity of 20 different stoves over four weeks, recording 260 uses. The participants completed a research diary in order to provide information on time lit, amount and type of fuel used, and duration of use, among other details. Multivariate statistical tools were used in order to analyse indoor PM concentrations, averages, intensities, and their relationship to aspects of stove management. The study has four core findings. First, the daily average indoor PM concentrations when a stove was used were higher for PM2.5 by 196.23% and PM1 by 227.80% than those of the non-use control group. Second, hourly peak averages are higher for PM2.5 by 123.91% and for PM1 by 133.09% than daily averages, showing that PM is ‘flooding’ into indoor areas through normal use. Third, the peaks that are derived from these ’flooding’ incidents are associated with the number of fuel pieces used and length of the burn period. This points to the opening of the stove door as a primary mechanism for introducing PM into the home. Finally, it demonstrates that the indoor air pollution being witnessed is not originating from outside the home. Taken together, the study demonstrates that people inside homes with a residential stove are at risk of exposure to high intensities of PM2.5 and PM1 within a short period of time through normal use. It is recommended that this risk be reflected in the testing and regulation of residential stoves. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Article
A Nonlinear Land Use Regression Approach for Modelling NO2 Concentrations in Urban Areas—Using Data from Low-Cost Sensors and Diffusion Tubes
Atmosphere 2020, 11(7), 736; https://doi.org/10.3390/atmos11070736 - 11 Jul 2020
Cited by 3 | Viewed by 1492
Abstract
Land Use Regression (LUR) based on multiple linear regression model is one of the techniques used most frequently for modelling the spatial variability of air pollution and assessing exposure in urban areas. In this paper, a nonlinear generalised additive model is proposed for [...] Read more.
Land Use Regression (LUR) based on multiple linear regression model is one of the techniques used most frequently for modelling the spatial variability of air pollution and assessing exposure in urban areas. In this paper, a nonlinear generalised additive model is proposed for LUR and its performance is compared to a linear model in Sheffield, UK for the year 2019. Pollution models were estimated using NO2 measurements obtained from 188 diffusion tubes and 40 low-cost sensors. Performance of the models was assessed by calculating several statistical metrics including correlation coefficient (R) and root mean square error (RMSE). High resolution (100 m × 100 m) maps demonstrated higher levels of NO2 in the city centre, eastern side of the city and on major roads. The results showed that the nonlinear model outperformed the linear counterpart and that the model estimated using NO2 data from diffusion tubes outperformed the models using data from low-cost sensors or both low-cost sensors and diffusion tubes. The proposed method provides a basis for further application of advanced nonlinear modelling approaches to constructing LUR models in urban areas which enable quantifying small scale variability in pollution levels. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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Review

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Review
Current State of Indoor Air Phytoremediation Using Potted Plants and Green Walls
Atmosphere 2021, 12(4), 473; https://doi.org/10.3390/atmos12040473 - 09 Apr 2021
Cited by 4 | Viewed by 1322
Abstract
Urban civilization has a high impact on the environment and human health. The pollution level of indoor air can be 2–5 times higher than the outdoor air pollution, and sometimes it reaches up to 100 times or more in natural/mechanical ventilated buildings. Even [...] Read more.
Urban civilization has a high impact on the environment and human health. The pollution level of indoor air can be 2–5 times higher than the outdoor air pollution, and sometimes it reaches up to 100 times or more in natural/mechanical ventilated buildings. Even though people spend about 90% of their time indoors, the importance of indoor air quality is less noticed. Indoor air pollution can be treated with techniques such as chemical purification, ventilation, isolation, and removing pollutions by plants (phytoremediation). Among these techniques, phytoremediation is not given proper attention and, therefore, is the focus of our review paper. Phytoremediation is an affordable and more environmentally friendly means to purify polluted indoor air. Furthermore, studies show that indoor plants can be used to regulate building temperature, decrease noise levels, and alleviate social stress. Sources of indoor air pollutants and their impact on human health are briefly discussed in this paper. The available literature on phytoremediation, including experimental works for removing volatile organic compound (VOC) and particulate matter from the indoor air and associated challenges and opportunities, are reviewed. Phytoremediation of indoor air depends on the physical properties of plants such as interfacial areas, the moisture content, and the type (hydrophobicity) as well as pollutant characteristics such as the size of particulate matter (PM). A comprehensive summary of plant species that can remove pollutants such as VOCs and PM is provided. Sources of indoor air pollutants, as well as their impact on human health, are described. Phytoremediation and its mechanism of cleaning indoor air are discussed. The potential role of green walls and potted-plants for improving indoor air quality is examined. A list of plant species suitable for indoor air phytoremediation is proposed. This review will help in making informed decisions about integrating plants into the interior building design. Full article
(This article belongs to the Special Issue Air Quality in the UK)
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