Regional impact assessment of air quality improvement: The air quality lifecourse assessment tool (AQ-LAT) for the West Midlands combined authority (WMCA) area.

Poor air quality is the largest environmental health risk in England. In the West Midlands, UK, ∼2.9 million people are affected by air pollution with an average loss in life expectancy of up to 6 months. The 2021 Environment Act established a legal framework for local authorities in England to develop regional air quality plans, generating a policy need for predictive environmental impact assessment tools. In this context, we developed a novel Air Quality Lifecourse Assessment Tool (AQ-LAT) to estimate electoral ward-level impacts of PM2.5 and NO2 exposure on outcomes of interest to local authorities, namely morbidity (asthma, coronary heart disease (CHD), stroke, lung cancer), mortality, and associated healthcare costs. We apply the Tool to assess the health economic burden of air pollutant exposure and estimate benefits that would be generated by meeting WHO 2021 Global Air Quality Guidelines (AQGs) (annual average concentrations) for NO2 (10 µg/m3) and PM2.5 (5 µg/m3) in the West Midlands Combined Authority Area. All West Midlands residents live in areas which exceed WHO AQGs, with 2070 deaths, 2070 asthma diagnoses, 770 CHD diagnoses, 170 lung cancers and 650 strokes attributable to air pollution exposure annually. Reducing PM2.5 and NO2 concentrations to WHO AQGs would save 10,700 lives reducing regional mortality by 1.8%, gaining 92,000 quality-adjusted life years (QALYs), and preventing 20,500 asthma, 7400 CHD, 1400 lung cancer, and 5700 stroke diagnoses, with economic benefits of £3.2 billion over 20 years. Significantly, we estimate 30% of QALY gains relate to reduced disease burden. The AQ-LAT has major potential to be replicated across local authorities in England and applied to inform regional investment decisions.

Modelling the dispersion of particle number concentrations in the West Midlands, UK using the ADMS-Urban model.

Ultrafine particles (UFPs) are respirable particles with a diameter less than 100 nm, which some studies have associated with adverse effects upon health. UFPs are currently not regulated as the health evidence is insufficient and very few observational data are available in most cities. The 2021 WHO Global Air Quality Guidelines highlighted the pressing issue of UFPs and provided a good practice statement for UFPs, which recommends that more measurement and modelling studies are implemented in future. Particle number concentrations (PNC) are the most common metric for UFPs as this fraction normally dominates the total ambient PNC in urban environments. This study simulates the dispersion of particle number concentrations in the West Midlands (a metropolitan area), UK using the local scale ADMS-Urban model, which is an advanced quasi-Gaussian plume dispersion modelling system. ADMS-Urban implements a physics-based approach to represent the characteristics of the atmospheric boundary layer and has been widely used in the dispersion modelling of air pollutants. It can represent a variety of source types (such as road and grid emissions) occurring in urban environments and requires a range of input data. Particle number was used as a passive scalar, with no inclusion of aerosol microphysics within the model, as a first implementation in the ADMS-Urban model for the West Midlands, UK. Evaluation was conducted by comparing the modelled (from a receptor run) and measured data at the Birmingham Air Quality Supersite. Overall, the model performed well although there was a slight underestimation for PNC. Based on the modelling output from a contour run, PNC maps at a variety of spatial scales (i.e. street scale, ward level and local authority level) and temporal resolutions (i.e. annual, 24-hour, and 1-hour) were generated. PNC mapping could be linked to local population and health data for potential epidemiological studies.

Impacts of net zero policies on air quality in a metropolitan area of the United Kingdom: Towards world health organization air quality guidelines.

Climate change and air pollution are closely interlinked since carbon dioxide and air pollutants are co-emitted from fossil fuel combustion. Net Zero (NZ) policies aiming to reduce carbon emissions will likely bring co-benefits in air quality and associated health. However, it is unknown whether regional NZ policies alone will be sufficient to reduce air pollutant levels to meet the latest 2021 World Health Organisation (WHO) guidelines. Here, we carried out high resolution air quality modelling for in the West Midlands region, a typical metropolitan area in the UK, to quantify the effects of different NZ policies on air quality. Results show that NZ policies will significantly improve air quality in the West Midlands, with up to 6 µg m-3 (21%) reduction in annual mean NO2 (mostly through the electrification of vehicle fleet, EV) and up to 1.4 µg m-3 (12%) reduction in annual mean PM2.5 projected for 2030 relative to levels under a "business as usual" (BAU) scenario. Under BAU, 2030 PM2.5 concentrations in most wards would be below 10 µg m-3 whilst under the Net Zero scenario, those in all wards would be below 10 µg m-3. This means that the ward averages in the West Midlands would meet the UK PM2.5 of 10 µg m-3target a decade early under the Net Zero scenario. However, no ward-level-averaged annual mean PM2.concentrations meet the 2021 WHO Air Quality guideline level of 5 µg m-3 under any scenario. Similarly for NO2 only 18 wards (8% of the region's population) are predicted to have NO2 concentrations below the 2021 WHO guideline level (10 µg m-3). Decarbonisation policies linked to Net Zero deliver substantial regional air quality benefits, but are not in isolation sufficient to deliver clean air with air pollutant levels low enough to meet the 2021 WHO guidelines.

In-vehicle exposure to NO2 and PM2.5: A comprehensive assessment of controlling parameters and reduction strategies to minimise personal exposure.

Vehicles are the third most occupied microenvironment, other than home and workplace, in developed urban areas. Vehicle cabins are confined spaces where occupants can mitigate their exposure to on-road nitrogen dioxide (NO2) and fine particulate matter (PM2.5) concentrations. Understanding which parameters exert the greatest influence on in-vehicle exposure underpins advice to drivers and vehicle occupants in general. This study assessed the in-vehicle NO2 and PM2.5 levels and developed stepwise general additive mixed models (sGAMM) to investigate comprehensively the combined and individual influences of factors that influence the in-vehicle exposures. The mean in-vehicle levels were 19 ± 18 and 6.4 ± 2.7 µg/m3 for NO2 and PM2.5, respectively. sGAMM model identified significant factors explaining a large fraction of in-vehicle NO2 and PM2.5 variability, R2 = 0.645 and 0.723, respectively. From the model's explained variability on-road air pollution was the most important predictor accounting for 22.3 and 30 % of NO2 and PM2.5 variability, respectively. Vehicle-based predictors included manufacturing year, cabin size, odometer reading, type of cabin filter, ventilation fan speed power, window setting, and use of air recirculation, and together explained 48.7 % and 61.3 % of NO2 and PM2.5 variability, respectively, with 41.4 % and 51.9 %, related to ventilation preference and type of filtration media, respectively. Driving-based parameters included driving speed, traffic conditions, traffic lights, roundabouts, and following high emitters and accounted for 22 and 7.4 % of in-vehicle NO2 and PM2.5 exposure variability, respectively. Vehicle occupants can significantly reduce their in-vehicle exposure by moderating vehicle ventilation settings and by choosing an appropriate cabin air filter.

Extreme Concentrations of Nitric Oxide Control Daytime Oxidation and Quench Nocturnal Oxidation Chemistry in Delhi during Highly Polluted Episodes.

Delhi, India, suffers from periods of very poor air quality, but little is known about the chemical production of secondary pollutants in this highly polluted environment. During the postmonsoon period in 2018, extremely high nighttime concentrations of NOx (NO and NO2) and volatile organic compounds (VOCs) were observed, with median NOx mixing ratios of ∼200 ppbV (maximum of ∼700 ppbV). A detailed chemical box model constrained to a comprehensive suite of speciated VOC and NOx measurements revealed very low nighttime concentrations of oxidants, NO3, O3, and OH, driven by high nighttime NO concentrations. This results in an atypical NO3 diel profile, not previously reported in other highly polluted urban environments, significantly perturbing nighttime radical oxidation chemistry. Low concentrations of oxidants and high nocturnal primary emissions coupled with a shallow boundary layer led to enhanced early morning photo-oxidation chemistry. This results in a temporal shift in peak O3 concentrations when compared to the premonsoon period (12:00 and 15:00 local time, respectively). This shift will likely have important implications on local air quality, and effective urban air quality management should consider the impacts of nighttime emission sources during the postmonsoon period.

Extensive field evidence for the release of HONO from the photolysis of nitrate aerosols.

Particulate nitrate ([Formula: see text]) has long been considered a permanent sink for NOx (NO and NO2), removing a gaseous pollutant that is central to air quality and that influences the global self-cleansing capacity of the atmosphere. Evidence is emerging that photolysis of [Formula: see text] can recycle HONO and NOx back to the gas phase with potentially important implications for tropospheric ozone and OH budgets; however, there are substantial discrepancies in "renoxification" photolysis rate constants. Using aircraft and ground-based HONO observations in the remote Atlantic troposphere, we show evidence for renoxification occurring on mixed marine aerosols with an efficiency that increases with relative humidity and decreases with the concentration of [Formula: see text], thus largely reconciling the very large discrepancies in renoxification photolysis rate constants found across multiple laboratory and field studies. Active release of HONO from aerosol has important implications for atmospheric oxidants such as OH and O3 in both polluted and clean environments.

NO2 levels inside vehicle cabins with pollen and activated carbon filters: A real world targeted intervention to estimate NO2 exposure reduction potential.

Traffic related nitrogen dioxide (NO2) poses a serious environmental and health risk factor in the urban environment. Drivers and vehicle occupants in general may have acute exposure to NO2 levels. In order to identify key controllable measures to reduce vehicle occupant's exposure, this study measures NO2 exposure inside ten different vehicles under real world driving conditions and applies a targeted intervention by replacing previously used filters with new standard pollen and new activated carbon cabin filters. The study also evaluates the efficiency of the latter as a function of duration of use. The mean in-vehicle NO2 exposure across the tested vehicles, driving the same route under comparable traffic and ambient air quality conditions, was 50.8 ± 32.7 µg/m3 for the new standard pollen filter tests and 9.2 ± 8.6 µg/m3 for the new activated carbon filter tests. When implementing the new activated carbon filters, overall we observed significant (p < 0.05) reductions by 87 % on average (range 80 - 94.2 %) in the in-vehicle NO2 levels compared to the on-road concentrations. We further found that the activated carbon filter NO2 removal efficiency drops by 6.8 ± 0.6 % per month; showing a faster decay in removal efficiency after the first 6 months of use. These results offer novel insights into how the general population can control and reduce their exposure to traffic related NO2. The use and regular replacement of activated carbon cabin air filters represents a relatively inexpensive method to significantly reduce in-vehicle NO2 exposure.

The impact of the first United Kingdom COVID-19 lockdown on environmental air pollution, digital display device use and ocular surface disease symptomatology amongst shielding patients.

Worldwide lockdown reduced air pollution during the first phase of the COVID-19 pandemic. The relationship between exposure to ambient air pollution, digital display device use and dry eye symptoms amongst patients with severe ocular surface disease (OSD) were considered. Symptoms and air pollutant concentrations for three different time periods (pre, during and post COVID-19 lockdown) were analysed in 35 OSD patients who achieved an immunosuppression risk-stratification score > 3 fulfilling the UK Government criteria for 12-week shielding. OSDI symptoms questionnaire, residential postcode air pollution data obtained from the Defra Automated Urban and Rural monitoring network for concentrations of nitrogen dioxide (NO2), nitrogen oxides (NOx), particulate matter (PM) with diameters below 10 µm and 2.5 µm, and English Indices of Deprivation were analysed. Significant reductions in NO2 and NOx concentrations were observed between pre- and during-lockdown periods, followed by a reversal in the post-lockdown period. Changes were linked to the Living Environment outdoor decile. A 12% increase (p = 0.381) in symptomatology during-lockdown was observed that reversed post-lockdown by 19% (p = 0.144). OSDI scores were significantly correlated with hours spent on digital devices (r2 = 0.243) but not with air pollutant concentrations. Lockdown measures reduced ambient air pollutants whilst OSD symptomatology persisted. Environmental factors such as increased time indoors and use of bluescreen digital devices may have partly played a role.

Evaluating the real changes of air quality due to clean air actions using a machine learning technique: Results from 12 Chinese mega-cities during 2013-2020.

China has implemented two national clean air actions in 2013-2017 and 2018-2020, respectively, with the aim of reducing primary emissions and hence improving air quality at a national level. It is important to examine the effectiveness of such emission reductions and assess the resulting changes in air quality. However, such evaluation is difficult as meteorological factors can amplify, or obscure the changes of air pollutants, in addition to the emission reduction. In this study, we applied the random forest machine learning technique to decouple meteorological influences from emissions changes, and examined the deweathered trends of air pollutants in 12 Chinese mega-cities during 2013-2020. The observed concentrations of all criteria pollutants except O3 showed significant declines from 2013 to 2020, with PM2.5 annual decline rates of 6-9% in most cities. In contrast, O3 concentrations increased with annual growth rates of 1-9%. Compared with the observed results, all the pollutants showed smoothed but similar variation in trend and annual rate-of-change after weather normalization. The response of O3 to NO2 concentrations indicated significant regional differences in photochemical regimes, and the differences between observed and deweathered results provided implications for volatile organic compound emission reductions in O3 pollution mitigation. We further evaluated the effectiveness of first and second clean air actions by removing the meteorological influence. We found that the meteorology can make negative or positive contribution in reducing pollutant concentrations from emission reduction, depending on type of pollutants, locations, and time period. Among the 12 mega-cities, only Beijing showed a positive meteorological contribution in amplifying reductions in main pollutants except O3 during both clean air action periods. Considering the large and variable impact of meteorological effects in changing air quality, we suggest that similar deweathered analysis is needed as a routine policy evaluation tool on a regional basis.

Rapid rise in premature mortality due to anthropogenic air pollution in fast-growing tropical cities from 2005 to 2018.

Tropical cities are experiencing rapid growth but lack routine air pollution monitoring to develop prescient air quality policies. Here, we conduct targeted sampling of recent (2000s to 2010s) observations of air pollutants from space-based instruments over 46 fast-growing tropical cities. We quantify significant annual increases in nitrogen dioxide (NO2) (1 to 14%), ammonia (2 to 12%), and reactive volatile organic compounds (1 to 11%) in most cities, driven almost exclusively by emerging anthropogenic sources rather than traditional biomass burning. We estimate annual increases in urban population exposure to air pollutants of 1 to 18% for fine particles (PM2.5) and 2 to 23% for NO2 from 2005 to 2018 and attribute 180,000 (95% confidence interval: -230,000 to 590,000) additional premature deaths in 2018 (62% increase relative to 2005) to this increase in exposure. These cities are predicted to reach populations of up to 80 million people by 2100, so regulatory action targeting emerging anthropogenic sources is urgently needed.

Impacts of emergency health protection measures upon air quality, traffic and public health: evidence from Oxford, UK.

Emergency responses to the COVID-19 pandemic led to major changes in travel behaviours and economic activities in 2020. Machine learning provides a reliable approach for assessing the contribution of these changes to air quality. This study investigates impacts of health protection measures upon air pollution and traffic emissions and estimates health and economic impacts arising from these changes during two national 'lockdown' periods in Oxford, UK. Air quality improvements were most marked during the first lockdown with reductions in observed NO2 concentrations of 38% (SD ± 24.0%) at roadside and 17% (SD ± 5.4%) at urban background locations. Observed changes in PM2.5, PM10 and O3 concentrations were not significant during first or second lockdown. Deweathering and detrending analyses revealed a 22% (SD ± 4.4%) reduction in roadside NO2 and 2% (SD ± 7.1%) at urban background with no significant changes in the second lockdown. Deweathered-detrended PM2.5 and O3 concentration changes were not significant, but PM10 increased in the second lockdown only. City centre traffic volume reduced by 69% and 38% in the first and second lockdown periods. Buses and passenger cars were the major contributors to NO2 emissions, with relative reductions of 56% and 77% respectively during the first lockdown, and less pronounced changes in the second lockdown. While car and bus NO2 emissions decreased during both lockdown periods, the overall contribution from buses increased relative to cars in the second lockdown. Sustained NO2 emissions reduction consistent with the first lockdown could prevent 48 lost life-years among the city population, with economic benefits of up to £2.5 million. Our findings highlight the critical importance of decoupling emissions changes from meteorological influences to avoid overestimation of lockdown impacts and indicate targeted emissions control measures will be the most effective strategy for achieving air quality and public health benefits in this setting.

Atmospheric conditions and composition that influence PM2.5 oxidative potential in Beijing, China.

Epidemiological studies have consistently linked exposure to PM2.5 with adverse health effects. The oxidative potential (OP) of aerosol particles has been widely suggested as a measure of their potential toxicity. Several acellular chemical assays are now readily employed to measure OP; however, uncertainty remains regarding the atmospheric conditions and specific chemical components of PM2.5 that drive OP. A limited number of studies have simultaneously utilised multiple OP assays with a wide range of concurrent measurements and investigated the seasonality of PM2.5 OP. In this work, filter samples were collected in winter 2016 and summer 2017 during the atmospheric pollution and human health in a Chinese megacity campaign (APHH-Beijing), and PM2.5 OP was analysed using four acellular methods: ascorbic acid (AA), dithiothreitol (DTT), 2,7-dichlorofluorescin/hydrogen peroxidase (DCFH) and electron paramagnetic resonance spectroscopy (EPR). Each assay reflects different oxidising properties of PM2.5, including particle-bound reactive oxygen species (DCFH), superoxide radical production (EPR) and catalytic redox chemistry (DTT/AA), and a combination of these four assays provided a detailed overall picture of the oxidising properties of PM2.5 at a central site in Beijing. Positive correlations of OP (normalised per volume of air) of all four assays with overall PM2.5 mass were observed, with stronger correlations in winter compared to summer. In contrast, when OP assay values were normalised for particle mass, days with higher PM2.5 mass concentrations (µgm-3) were found to have lower mass-normalised OP values as measured by AA and DTT. This finding supports that total PM2.5 mass concentrations alone may not always be the best indicator for particle toxicity. Univariate analysis of OP values and an extensive range of additional measurements, 107 in total, including PM2.5 composition, gas-phase composition and meteorological data, provided detailed insight into the chemical components and atmospheric processes that determine PM2.5 OP variability. Multivariate statistical analyses highlighted associations of OP assay responses with varying chemical components in PM2.5 for both mass- and volume-normalised data. AA and DTT assays were well predicted by a small set of measurements in multiple linear regression (MLR) models and indicated fossil fuel combustion, vehicle emissions and biogenic secondary organic aerosol (SOA) as influential particle sources in the assay response. Mass MLR models of OP associated with compositional source profiles predicted OP almost as well as volume MLR models, illustrating the influence of mass composition on both particle-level OP and total volume OP. Univariate and multivariate analysis showed that different assays cover different chemical spaces, and through comparison of mass- and volume-normalised data we demonstrate that mass-normalised OP provides a more nuanced picture of compositional drivers and sources of OP compared to volume-normalised analysis. This study constitutes one of the most extensive and comprehensive composition datasets currently available and provides a unique opportunity to explore chemical variations in PM2.5 and how they affect both PM2.5 OP and the concentrations of particle-bound reactive oxygen species.

Chemical source profiles of fine particles for five different sources in Delhi.

Increasing emissions from sources such as construction and burning of biomass from crop residues, roadside and municipal solid waste have led to a rapid increase in the atmospheric concentrations of fine particulate matter (≤2.5 µm; PM2.5) over many Indian cities. Analyses of their chemical profiles are important for receptor models to accurately estimate the contributions from different sources. We have developed chemical source profiles for five important pollutant sources - construction (CON), paved road dust (PRD), roadside biomass burning (RBB), solid waste burning (SWB), and crop residue burning (CPB) - during three intensive campaigns (winter, summer and post-monsoon) in and around Delhi. We obtained chemical characterisations of source profiles incorporating carbonaceous material such as organic carbon (OC) and elemental carbon (EC), water-soluble ions (F-, Cl-, NO2-, NO3-, SO42-, PO43-, Na+ and NH4+), and elements (Mg, Al, Si, P, S, Cl, K, Ca, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, As, Br, Rb, Sr, Ba, and Pb). CON was dominated by the most abundant elements, K, Si, Fe, Al, and Ca. PRD was also dominated by crustal elements, accounting for 91% of the total analysed elements. RBB, SWB and CPB profiles were dominated by organic matter, which accounted for 94%, 86.2% and 86% of the total PM2.5, respectively. The database of PM emission profiles developed from the sources investigated can be used to assist source apportionment studies for accurate quantification of the causes of air pollution and hence assist governmental bodies in formulating relevant countermeasures.

Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns.

The COVID-19 lockdowns led to major reductions in air pollutant emissions. Here, we quantitatively evaluate changes in ambient NO2, O3, and PM2.5 concentrations arising from these emission changes in 11 cities globally by applying a deweathering machine learning technique. Sudden decreases in deweathered NO2 concentrations and increases in O3 were observed in almost all cities. However, the decline in NO2 concentrations attributable to the lockdowns was not as large as expected, at reductions of 10 to 50%. Accordingly, O3 increased by 2 to 30% (except for London), the total gaseous oxidant (O x = NO2 + O3) showed limited change, and PM2.5 concentrations decreased in most cities studied but increased in London and Paris. Our results demonstrate the need for a sophisticated analysis to quantify air quality impacts of interventions and indicate that true air quality improvements were notably more limited than some earlier reports or observational data suggested.

Enhanced wintertime oxidation of VOCs via sustained radical sources in the urban atmosphere.

Daytime atmospheric oxidation chemistry is conventionally considered to be driven primarily by the OH radical, formed via photolytic sources. In this paper we examine how, during winter when photolytic processes are slow, chlorine chemistry can have a significant impact on oxidative processes in the urban boundary layer. Photolysis of nitryl chloride (ClNO2) provides a significant source of chlorine atoms, which enhances the oxidation of volatile organic compounds (VOCs) and the production of atmospheric pollutants. We present a set of observations of ClNO2 and HONO made at urban locations in central England in December 2014 and February 2016. While direct emissions and in-situ chemical formation of HONO continue throughout the day, ClNO2 is only formed at night and is usually completely photolyzed by midday. Our data show that, during winter, ClNO2 often persists through the daylight hours at mixing ratios above 10-20 ppt (on average). In addition, relatively high mixing ratios of daytime HONO (>65 ppt) provide a strong source of OH radicals throughout the day. The combined effects of ClNO2 and HONO result in sustained sources of Cl and OH radicals from sunrise to sunset, which form additional ozone, PAN, oxygenated VOCs, and secondary organic aerosol. We show that radical sources such as ClNO2 and HONO can lead to a surprisingly photoactive urban atmosphere during winter and should therefore be included in atmospheric chemical models.