A comprehensive modelling approach has been developed to predict population exposure to the ambient air PM2.5 concentrations in different microenvironments in London. The modelling approach ...integrates air pollution dispersion and exposure assessment, including treatment of the locations and time activity of the population in three microenvironments, namely, residential, work and transport, based on national demographic information. The approach also includes differences between urban centre and suburban areas of London by taking account of the population movements and the infiltration of PM2.5 from outdoor to indoor. The approach is tested comprehensively by modelling ambient air concentrations of PM2.5 at street scale for the year 2008, including both regional and urban contributions. Model analysis of the exposure in the three microenvironments shows that most of the total exposure, 85%, occurred at home and work microenvironments and 15% in the transport microenvironment. However, the annual population weighted mean (PWM) concentrations of PM2.5 for London in transport microenvironments were almost twice as high (corresponding to 13–20 μg/m3) as those for home and work environments (7–12 μg/m3). Analysis has shown that the PWM PM2.5 concentrations in central London were almost 20% higher than in the surrounding suburban areas. Moreover, the population exposure in the central London per unit area was almost three times higher than that in suburban regions. The exposure resulting from all activities, including outdoor to indoor infiltration, was about 20% higher, when compared with the corresponding value obtained assuming inside home exposure for all times. The exposure assessment methodology used in this study predicted approximately over one quarter (−28%) lower population exposure, compared with using simply outdoor concentrations at residential locations. An important implication of this study is that for estimating population exposure, one needs to consider the population movements, and the infiltration of pollution from outdoors to indoors.
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•Most of exposure to ambient PM2.5 occurred in home and work microenvironments (ME).•PM2.5 concentrations in transport ME were twice as high as those at home and work MEs.•Exposure per unit area in central London is three times higher than in outer London.•This study estimates 28% lower exposure as compared to the traditional approach.•It is important to consider the population movements, and the infiltration of pollution.
This review provides a community's perspective on air quality
research focusing mainly on developments over the past decade. The article
provides perspectives on current and future challenges as well ...as research
needs for selected key topics. While this paper is not an exhaustive review
of all research areas in the field of air quality, we have selected key
topics that we feel are important from air quality research and policy
perspectives. After providing a short historical overview, this review
focuses on improvements in characterizing sources and emissions of air
pollution, new air quality observations and instrumentation, advances in air
quality prediction and forecasting, understanding interactions of air
quality with meteorology and climate, exposure and health assessment, and
air quality management and policy. In conducting the review, specific
objectives were (i) to address current developments that push the boundaries
of air quality research forward, (ii) to highlight the emerging prominent
gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider
community. This review also identifies areas of particular importance for
air quality policy. The original concept of this review was borne at the
International Conference on Air Quality 2020 (held online due to the COVID
19 restrictions during 18–26 May 2020), but the article incorporates a wider
landscape of research literature within the field of air quality science. On
air pollution emissions the review highlights, in particular, the need to
reduce uncertainties in emissions from diffuse sources, particulate matter
chemical components, shipping emissions, and the importance of considering
both indoor and outdoor sources. There is a growing need to have integrated
air pollution and related observations from both ground-based and remote
sensing instruments, including in particular those on satellites. The research
should also capitalize on the growing area of low-cost sensors, while
ensuring a quality of the measurements which are regulated by guidelines.
Connecting various physical scales in air quality modelling is still a
continual issue, with cities being affected by air pollution gradients at
local scales and by long-range transport. At the same time, one should allow
for the impacts from climate change on a longer timescale. Earth system
modelling offers considerable potential by providing a consistent framework
for treating scales and processes, especially where there are significant
feedbacks, such as those related to aerosols, chemistry, and meteorology.
Assessment of exposure to air pollution should consider the impacts of
both indoor and outdoor emissions, as well as application of more sophisticated,
dynamic modelling approaches to predict concentrations of air pollutants in
both environments. With particulate matter being one of the most important
pollutants for health, research is indicating the urgent need to understand,
in particular, the role of particle number and chemical components in terms
of health impact, which in turn requires improved emission inventories and
models for predicting high-resolution distributions of these metrics over
cities. The review also examines how air pollution management needs to
adapt to the above-mentioned new challenges and briefly considers the
implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.
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•A global observational analysis of air quality changes due to COVID-19 is presented.•NO2 decreased with heterogeneous changes in O3 and PM2.5 showing complex signals.•Urban oxidant ...was driven by primary NO2 and by regional inputs at background sites.•Meteorology, chemistry, emissions, climate and socioeconomics all affect air quality.•More ambitious regional regulation is needed to meet WHO air quality guidelines.
This global study, which has been coordinated by the World Meteorological Organization Global Atmospheric Watch (WMO/GAW) programme, aims to understand the behaviour of key air pollutant species during the COVID-19 pandemic period of exceptionally low emissions across the globe. We investigated the effects of the differences in both emissions and regional and local meteorology in 2020 compared with the period 2015–2019. By adopting a globally consistent approach, this comprehensive observational analysis focuses on changes in air quality in and around cities across the globe for the following air pollutants PM2.5, PM10, PMC (coarse fraction of PM), NO2, SO2, NOx, CO, O3 and the total gaseous oxidant (OX = NO2 + O3) during the pre-lockdown, partial lockdown, full lockdown and two relaxation periods spanning from January to September 2020. The analysis is based on in situ ground-based air quality observations at over 540 traffic, background and rural stations, from 63 cities and covering 25 countries over seven geographical regions of the world. Anomalies in the air pollutant concentrations (increases or decreases during 2020 periods compared to equivalent 2015–2019 periods) were calculated and the possible effects of meteorological conditions were analysed by computing anomalies from ERA5 reanalyses and local observations for these periods. We observed a positive correlation between the reductions in NO2 and NOx concentrations and peoples’ mobility for most cities. A correlation between PMC and mobility changes was also seen for some Asian and South American cities. A clear signal was not observed for other pollutants, suggesting that sources besides vehicular emissions also substantially contributed to the change in air quality.
As a global and regional overview of the changes in ambient concentrations of key air quality species, we observed decreases of up to about 70% in mean NO2 and between 30% and 40% in mean PM2.5 concentrations over 2020 full lockdown compared to the same period in 2015–2019. However, PM2.5 exhibited complex signals, even within the same region, with increases in some Spanish cities, attributed mainly to the long-range transport of African dust and/or biomass burning (corroborated with the analysis of NO2/CO ratio). Some Chinese cities showed similar increases in PM2.5 during the lockdown periods, but in this case, it was likely due to secondary PM formation. Changes in O3 concentrations were highly heterogeneous, with no overall change or small increases (as in the case of Europe), and positive anomalies of 25% and 30% in East Asia and South America, respectively, with Colombia showing the largest positive anomaly of ~70%. The SO2 anomalies were negative for 2020 compared to 2015–2019 (between ~25 to 60%) for all regions. For CO, negative anomalies were observed for all regions with the largest decrease for South America of up to ~40%. The NO2/CO ratio indicated that specific sites (such as those in Spanish cities) were affected by biomass burning plumes, which outweighed the NO2 decrease due to the general reduction in mobility (ratio of ~60%). Analysis of the total oxidant (OX = NO2 + O3) showed that primary NO2 emissions at urban locations were greater than the O3 production, whereas at background sites, OX was mostly driven by the regional contributions rather than local NO2 and O3 concentrations. The present study clearly highlights the importance of meteorology and episodic contributions (e.g., from dust, domestic, agricultural biomass burning and crop fertilizing) when analysing air quality in and around cities even during large emissions reductions. There is still the need to better understand how the chemical responses of secondary pollutants to emission change under complex meteorological conditions, along with climate change and socio-economic drivers may affect future air quality. The implications for regional and global policies are also significant, as our study clearly indicates that PM2.5 concentrations would not likely meet the World Health Organization guidelines in many parts of the world, despite the drastic reductions in mobility. Consequently, revisions of air quality regulation (e.g., the Gothenburg Protocol) with more ambitious targets that are specific to the different regions of the world may well be required.
This study aims to quantify exhaust/non-exhaust emissions and the uncertainties associated with them by combining innovative motorway tunnel sampling and source apportionment modelling. Analytical ...techniques ICP-AES and GC–MS were used to identify the metallic and organic composition of PM10, respectively. Good correlation was observed between Fe, Cu, Mn, Ni, Pb and Sb and change in traffic volume. The concentration of polycyclic aromatic hydrocarbons and other organics varies significantly at the entrance and exit site of the tunnel, with fluoranthene, pyrene, benzoapyrene, chrysene and benzothiazole having the highest incremented concentrations. The application of Principal Component Analysis and Multiple Linear Regression Analysis helped to identify the emission sources for 82% of the total PM10 mass inside the tunnel. Identified sources include resuspension (27%), diesel exhaust emissions (21%), petrol exhaust emissions (12%), brake wear emissions (11%) and road surface wear (11%). This study shows that major health related chemical species of PM10 originate from non-exhaust sources, further signifying the need for legislation to reduce these emissions.
•Identifies major sources of traffic emissions by using a real world motorway tunnel.•Major non-exhaust sources include resuspension, brake wear and road surface wear.•Several toxic metals (e.g. Fe, Cu, Mn, Ni, Pb, Sb) and PAHs show high incremented levels.•Diesel (21%) & petrol (12%) exhaust emissions also contribute as major sources of PM10.•A number of toxic chemical species of PM10 originate from non-exhaust sources.
Fine particulate matter (PM2.5) and surface ozone (O3) are major air pollutants in megacities such as Delhi, but the design of suitable mitigation strategies is challenging. Some strategies for ...reducing PM2.5 may have the notable side effect of increasing O3. Here, we demonstrate a numerical framework for investigating the impacts of mitigation strategies on both PM2.5 and O3 in Delhi. We use Gaussian process emulation to generate a computationally efficient surrogate for a regional air quality model (WRF-Chem). This allows us to perform global sensitivity analysis to identify the major sources of air pollution and to generate emission-sector-based pollutant response surfaces to inform mitigation policy development. Based on more than 100 000 emulation runs during the pre-monsoon period (peak O3 season), our global sensitivity analysis shows that local traffic emissions from the Delhi city region and regional transport of pollution emitted from the National Capital Region (NCR) surrounding Delhi are dominant factors influencing PM2.5 and O3 in Delhi. They together govern the O3 peak and PM2.5 concentration during daytime. Regional transport contributes about 80% of the PM2.5 variation during the night. Reducing traffic emissions in Delhi alone (e.g. by 50 %) would reduce PM2.5 by 15 %–20 % but lead to a 20 %–25 % increase in O3. However, we show that reducing NCR regional emissions by 25 %–30 % at the same time would further reduce PM2.5 by 5 %–10 % in Delhi and avoid the O3 increase. This study provides scientific evidence to support the need for joint coordination of controls on local and regional scales to achieve effective reduction in PM2.5 whilst minimising the risk of O3 increase in Delhi.
We have estimated the spatial changes in NO2 levels over different regions of India during the COVID-19 lockdown (25 March–3 May 2020) using the satellite-based tropospheric column NO2 observed by ...the Ozone Monitoring Instrument (OMI) and the Tropospheric Monitoring Instrument (TROPOMI), as well as surface NO2 concentrations obtained from the Central Pollution Control Board (CPCB) monitoring network. A substantial reduction in NO2 levels was observed across India during the lockdown compared to the same period during previous business-as-usual years, except for some regions that were influenced by anomalous fires in 2020. The reduction (negative change) over the urban agglomerations was substantial (∼ 20 %–40 %) and directly proportional to the urban size and population density. Rural regions across India also experienced lower NO2 values by ∼ 15 %–25 %. Localised enhancements in NO2 associated with isolated emission increase scattered across India were also detected. Observed percentage changes in satellite and surface observations were consistent across most regions and cities, but the surface observations were subject to larger variability depending on their proximity to the local emission sources. Observations also indicate NO2 enhancements of up to ∼ 25 % during the lockdown associated with fire emissions over the north-east of India and some parts of the central regions. In addition, the cities located near the large fire emission sources show much smaller NO2 reduction than other urban areas as the decrease at the surface was masked by enhancement in NO2 due to the transport of the fire emissions.
We report on the analysis of contributions from road traffic emissions to fine particulate matter (PM
2.5
) concentrations within London for 2008 with the OSCAR Air Quality Assessment System. A ...spatiotemporal evaluation of the OSCAR system has been conducted with measurements from the London air quality network (LAQN). For the predicted and measured hourly time series of concentrations at 18 sites in London, the medians of correlation, mean absolute error, index of agreement, and factor of two (FAC2) of all stations were 0.80, 4.1 μg/m
3
, 0.86, and 74%, respectively. Spatial evaluation of modeled and observed annual mean concentrations also showed a fairly good agreement, with all the values falling within the FAC2 range. According to model predictions, the urban increment (including the contributions from urban traffic and other urban sources) was evaluated to be on the average 18%, 33%, 39%, and 43% of the total PM
2.5
in suburban environments, in the urban background, near roads, and near busy roads, respectively. However, the highest values of the urban traffic increment can be around 50% of the total PM
2.5
concentrations near motorways and major roads. The total concentrations (including regional background, and the contributions from urban traffic and other urban sources) can therefore be almost three times the regional background. The total urban increment close to busy roads was around 7-8 μg/m
3
, in which the estimated traffic contribution is more than 2 μg/m
3
. On the average, urban traffic contributes approximately 1 μg/m
3
of PM
2.5
to the urban background across London. According to modeling, approximately two-thirds of the traffic increment originated from exhaust emissions and most of the rest was due to brake and tire wear.
Implications:
The urban increment and traffic contribution to the total PM
2.5
are significant and spatially heterogeneous across London. The highly heterogeneous distribution of PM
2.5
hence requires detailed modeling studies to be carried out at high spatial resolution, which can be particularly important for exposure and health impact assessment. This type of information can be used to quantify health impacts resulting from specific sources of PM
2.5
such as traffic emissions, to aid city and national decision makers when formulating pollution control strategies.
Gamma glutamyl transferase (GGT) is related to oxidative stress and an indicator for liver damage. We investigated the association between air pollution and GGT in a large Austrian cohort ...(N = 116,109) to better understand how air pollution affects human health.
Data come from voluntary prevention visits that were routinely collected within the Vorarlberg Health Monitoring and Prevention Program (VHM&PP). Recruitment was ongoing from 1985 to 2005. Blood was drawn and GGT measured centralized in two laboratories. Land use regression models were applied to estimate individuals' exposure at their home address for particulate matter (PM) with a diameter of <2.5 μm (PM2.5), <10 μm (PM10), fraction between 10 μm and 2.5 μm (PMcoarse), as well as PM2.5 absorbance (PM2.5abs), NO2, NOx and eight components of PM. Linear regression models, adjusting for relevant individual and community-level confounders were calculated.
The study population was 56 % female with a mean age of 42 years and mean GGT was 19.0 units. Individual PM2.5 and NO2 exposures were essentially below European limit values of 25 and 40 μg/m3, respectively, with means of 13.58 μg/m3 for PM2.5 and 19.93 μg/m3 for NO2. Positive associations were observed for PM2.5, PM10, PM2.5abs, NO2, NOx, and Cu, K, S in PM2.5 and PM10 fractions and Zn mainly in PM2.5 fraction. The strongest association per interquartile range observed was an increase of serum GGT concentration by 1.40 % (95 %-CI: 0.85 %; 1.95 %) per 45.7 ng/m3 S in PM2.5. Associations were robust to adjustments for other biomarkers, in two-pollutant models and the subset with a stable residential history.
We found that long-term exposure to air pollution (PM2.5, PM10, PM2.5abs, NO2, NOx) as well as certain elements, were positively associated with baseline GGT levels. The elements associated suggest a role of traffic emissions, long range transport and wood burning.
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•Air pollution is affecting GGT, a marker of oxidative stress and liver disease.•Relevant sources appear to be traffic, wood burning and long range transported PM.•Associations with sulfur seem to be independent of metals (Cu, Fe, Ni, Zn).•Associations below EU limits stress importance of revising air quality regulation.
Numerical simulations are conducted using the Weather Research and Forecast numerical model to examine the effects of a marine air intrusion (including a sea-breeze front), in an easterly wind regime ...on 7 May 2008, on the structure of London’s urban heat island (UHI). A sensitivity study is undertaken to assess how the representation of the urban area of London in the model, with a horizontal grid resolution of 1 km, affects its performance characteristics for the near-surface air temperature, dewpoint depression, and wind fields. No single simulation is found to provide the overall best or worst performance for all the near-surface fields considered. Using a multilayer (rather than single layer or bulk) urban canopy model does not clearly improve the prediction of the intensity of the UHI but it does improve the prediction of its spatial pattern. Providing surface-cover fractions leads to improved predictions of the UHI intensity. The advection of cooler air from the North Sea reduces the intensity of the UHI in the windward suburbs and displaces it several kilometres to the west, in good agreement with observations. Frontal advection across London effectively replaces the air in the urban area. Results indicate that there is a delicate balance between the effects of thermal advection and urbanization on near-surface fields, which depend, inter alia, on the parametrization of the urban canopy and the urban land-cover distribution.
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