Publications
114 results found
Piggin M, Alvarado Cruz L, Hargreaves D, et al., 2024, Online public involvement session on early life respiratory infections and their impact on lung age
Zapata R, Douglas P, Chan KLA, et al., 2024, Microplastic emissions via air and compost from an industrial composting facility in England, Environmental Pollutants and Bioavailability, Vol: 36, ISSN: 2639-5932
Composting provides a sustainable method of processing biodegradable waste but is often contaminated with plastic. We quantified and characterised microplastics in air and compost samples from an industrial aerobic green waste composting facility in England. Compost samples were taken at different stages of the process; air samples were taken onsite, upwind, and downwind. Microplastics were found in compost from all stages of the process at levels comparable to those reported for marine sediments; higher concentrations were found in the screening stages of the composting process (mean 9.0 (IQR: 7.1) and 9.0 (IQR: 7.4) MPs 5 g-1 (dw), for 30 mm and 10 mm screened material, respectively). Airborne microplastics were found onsite (32–49 MP m−3), upwind (1 MP m−3) and downwind (3 MP m−3). Composting facilities represent a potential source of microplastics and point of entry to the wider environment. Further investigation into other sites and processes is warranted.
Lim S, Said B, Zurba L, et al., 2024, Characterising sources of PM2·5 exposure for school children with asthma: a personal exposure study across six cities in sub-Saharan Africa., Lancet Child Adolesc Health, Vol: 8, Pages: 17-27
BACKGROUND: Air pollution is the second largest risk to health in Africa, and children with asthma are particularly susceptible to its effects. Yet, there is a scarcity of air pollution exposure data from cities in sub-Saharan Africa. We aimed to identify potential exposure reduction strategies for school children with asthma living in urban areas in sub-Saharan Africa. METHODS: This personal exposure study was part of the Achieving Control of Asthma in Children in Africa (ACACIA) project. Personal exposure to particulate matter (PM) was monitored in school children in six cities in sub-Saharan Africa (Blantyre, Malawi; Durban, South Africa; Harare, Zimbabwe; Kumasi, Ghana; Lagos, Nigeria; and Moshi, Tanzania). Participants were selected if they were aged 12-16 years and had symptoms of asthma. Monitoring was conducted between June 21, and Nov 26, 2021, from Monday morning (approximately 1000 h) to Friday morning (approximately 1000 h), by use of a bespoke backpack with a small air pollution monitoring unit with an inbuilt Global Positioning System (GPS) data logger. Children filled in a questionnaire detailing potential sources of air pollution during monitoring and exposures were tagged into three different microenvironments (school, commute, and home) with GPS coordinates. Mixed-effects models were used to identify the most important determinants of children's PM2·5 (PM <2·5 μm in diameter) exposure. FINDINGS: 330 children were recruited across 43 schools; of these, 297 had valid monitoring data, and 1109 days of valid data were analysed. Only 227 (20%) of 1109 days monitored were lower than the current WHO 24 h PM2·5 exposure health guideline of 15 μg/m3. Children in Blantyre had the highest PM2·5 exposure (median 41·8 μg/m3), whereas children in Durban (16·0 μg/m3) and Kumasi (17·9 μg/m3) recorded the lowest exposures. Children had significantly higher PM2·5 exposures at school than at ho
Kolozali S, Chatzidiakou L, Jones R, et al., 2023, Early detection of COPD patients’ symptoms with personal environmental sensors: a remote sensing framework using probabilistic latent component analysis with linear dynamic systems, Neural Computing and Applications, Vol: 35, Pages: 17247-17265, ISSN: 0941-0643
In this study, we present a cohort study involving 106 COPD patients using portable environmental sensor nodes with attached air pollution sensors and activity-related sensors, as well as daily symptom records and peak flow measurements to monitor patients’ activity and personal exposure to air pollution. This is the first study which attempts to predict COPD symptoms based on personal air pollution exposure. We developed a system that can detect COPD patients’ symptoms one day in advance of symptoms appearing. We proposed using the Probabilistic Latent Component Analysis (PLCA) model based on 3-dimensional and 4-dimensional spectral dictionary tensors for personalised and population monitoring, respectively. The model is combined with Linear Dynamic Systems (LDS) to track the patients’ symptoms. We compared the performance of PLCA and PLCA-LDS models against Random Forest models in the identification of COPD patients’ symptoms, since tree-based classifiers were used for remote monitoring of COPD patients in the literature. We found that there was a significant difference between the classifiers, symptoms and the personalised versus population factors. Our results show that the proposed PLCA-LDS-3D model outperformed the PLCA and the RF models between 4 and 20% on average. When we used only air pollutants as input, the PLCA-LDS-3D forecasting results in personalised and population models were 48.67 and 36.33% accuracy for worsening of lung capacity and 38.67 and 19% accuracy for exacerbation of COPD patients’ symptoms, respectively. We have shown that indicators of the quality of an individual’s environment, specifically air pollutants, are as good predictors of the worsening of respiratory symptoms in COPD patients as a direct measurement.
Bos B, Barratt B, Batalle D, et al., 2023, Prenatal exposure to air pollution is associated with structural changes in the neonatal brain, Environment International, Vol: 174, ISSN: 0160-4120
BackgroundPrenatal exposure to air pollution is associated with adverse neurologic consequences in childhood. However, the relationship between in utero exposure to air pollution and neonatal brain development is unclear.MethodsWe modelled maternal exposure to nitrogen dioxide (NO2) and particulate matter (PM2.5 and PM10) at postcode level between date of conception to date of birth and studied the effect of prenatal air pollution exposure on neonatal brain morphology in 469 (207 male) healthy neonates, with gestational age of ≥36 weeks. Infants underwent MR neuroimaging at 3 Tesla at 41.29 (36.71–45.14) weeks post-menstrual age (PMA) as part of the developing human connectome project (dHCP). Single pollutant linear regression and canonical correlation analysis (CCA) were performed to assess the relationship between air pollution and brain morphology, adjusting for confounders and correcting for false discovery rate.ResultsHigher exposure to PM10 and lower exposure to NO2 was strongly canonically correlated to a larger relative ventricular volume, and moderately associated with larger relative size of the cerebellum. Modest associations were detected with higher exposure to PM10 and lower exposure to NO2 and smaller relative cortical grey matter and amygdala and hippocampus, and larger relaive brainstem and extracerebral CSF volume. No associations were found with white matter or deep grey nuclei volume.ConclusionsOur findings show that prenatal exposure to air pollution is associated with altered brain morphometry in the neonatal period, albeit with opposing results for NO2 and PM10. This finding provides further evidence that reducing levels of maternal exposure to particulate matter during pregnancy should be a public health priority and highlights the importance of understanding the impacts of air pollution on this critical development window.
Chatzidiakou L, Krause A, Kellaway M, et al., 2022, Automated classification of time-activity-location patterns for improved estimation of personal exposure to air pollution, Environmental Health, Vol: 21, ISSN: 1476-069X
BackgroundAir pollution epidemiology has primarily relied on measurements from fixed outdoor air quality monitoring stations to derive population-scale exposure. Characterisation of individual time-activity-location patterns is critical for accurate estimations of personal exposure and dose because pollutant concentrations and inhalation rates vary significantly by location and activity.MethodsWe developed and evaluated an automated model to classify major exposure-related microenvironments (home, work, other static, in-transit) and separated them into indoor and outdoor locations, sleeping activity and five modes of transport (walking, cycling, car, bus, metro/train) with multidisciplinary methods from the fields of movement ecology and artificial intelligence. As input parameters, we used GPS coordinates, accelerometry, and noise, collected at 1 min intervals with a validated Personal Air quality Monitor (PAM) carried by 35 volunteers for one week each. The model classifications were then evaluated against manual time-activity logs kept by participants.ResultsOverall, the model performed reliably in classifying home, work, and other indoor microenvironments (F1-score>0.70) but only moderately well for sleeping and visits to outdoor microenvironments (F1-score=0.57 and 0.3 respectively). Random forest approaches performed very well in classifying modes of transport (F1-score>0.91). We found that the performance of the automated methods significantly surpassed those of manual logs.ConclusionsAutomated models for time-activity classification can markedly improve exposure metrics. Such models can be developed in many programming languages, and if well formulated can have general applicability in large-scale health studies, providing a comprehensive picture of environmental health risks during daily life with readily gathered parameters from smartphone technologies.
Zhang H, Fan Y, Han Y, et al., 2022, Partitioning indoor-generated and outdoor-generated PM2.5 from real-time residential measurements in urban and peri-urban Beijing, Science of the Total Environment, Vol: 845, ISSN: 0048-9697
Limited number of projects have attempted to partition and quantify indoor- and outdoor-generated PM2.5 (PM2.5ig and PM2.5og) where strong indoor sources (e.g., solid fuel, tobacco smoke, or kerosene) exist. This study aimed to apply and refine a previous recursive model used to derive infiltration efficiency (Finf) to additionally partition pollution concentrations into indoor and outdoor origins within residences challenged by elevated ambient and indoor combustion-related sources. During the winter of 2016 and summer of 2017 we collected residential measurements in 72 homes in urban and peri-urban Beijing, 12 of which had additional paired residential outdoor measurements during the summer season. Local ambient measurements were collected throughout. We then compared the calculated PM2.5ig and using (i) outdoor and (ii) ambient measurements as model inputs. The results from outdoor and ambient measurements were not significantly different, which suggests that ambient measurements can be used as a model input for pollution origin partitioning when paired outdoor measurements are not available. From the results calculated using ambient measurements, the mean percentage contribution of indoor-generated PM2.5 was 19 % (σ = 22 %), and 7 % (11 %) of the total indoor PM2.5 for peri-urban and urban homes respectively during the winter; and 18 % (18 %) and 6 % (10 %) of the total indoor PM2.5 during the summer. Partitioning pollution into PM2.5ig and PM2.5og is important to allow investigation of distinct associations between health outcomes and particulate mixes, often with different physiochemical composition and toxicity. It will also inform targeted interventions that impact indoor and outdoor sources of pollution (e.g., domestic fuel switching vs. power generation), which are typically radically different in design and implementation.
Delgado-Saborit JM, Lim S, Hickman A, et al., 2022, Factors affecting occupational black carbon exposure in enclosed railway stations, Atmospheric Environment, Vol: 289, Pages: 1-14, ISSN: 1352-2310
Many rail services around the world continue to use diesel as the primary fuel source and enclosed railway stations have been identified as a possible hotspot for exposure to harmful diesel exhaust exposures. Little is known about the occupational exposure to air pollution for railway station workers due to their mobility around the station and variations in station design. A detailed understanding of the concentration of black carbon (BC), a diesel exhaust tracer, inside railway stations and the factors driving occupational exposures is required to minimize occupational exposure. Real-time personal exposure to BC was measured during 60 work-shifts encompassing different roles at three large enclosed railway stations of different design in London, Birmingham and Edinburgh (UK). Sampling was conducted by the train station workers over a period of 27 days between January 2017 to October 2018. Worker shift-mean BC exposures ranged 0.6–20.8 μg m−3 but 1-min peak exposures reached 773 μg m−3, with train dispatchers experiencing the highest BC exposures. Station design, job role, and frequency of diesel trains were the main drivers of occupational BC exposure. Elevated exposures for some station workers indicate that mitigation measures to reduce their exposure should be implemented to lower the risk of occupational health impacts. These could include improving ventilation and reducing engine emissions.
Vu TV, Stewart GB, Kitwiroon N, et al., 2022, Assessing the contributions of outdoor and indoor sources to air quality in London homes of the SCAMP cohort, Building and Environment, Vol: 222, Pages: 1-8, ISSN: 0360-1323
Given that many people typically spend the majority of their time at home, accurate measurement and modelling of the home environment is critical in estimating their exposure to air pollution. This study investigates the fate and impact on human exposure of outdoor and indoor pollutants in London homes, using a combination of sensor measurements, outdoor air pollution estimated from the CMAQ-urban model and indoor mass balance models. Averaged indoor concentrations of PM2.5, PM10 and NO2 were 14.6, 24.7 and 14.2 μg m−3 while the outdoor concentrations were 14.4, 22.6 and 21.4 μg m−3, respectively. Mean infiltration factors of particles (0.6–0.7) were higher than those of NO2 (0.4). In contrast, higher loss rates were found for NO2 (0.5–0.8 h−1) compared to those for particles (0.1–0.3 h−1). The average concentrations of PM2.5, PM10 and NO2 in kitchen environments were 22.0, 33.7 and 20.8 μg m−3, with highest hourly concentrations (437, 644 and 136 μg m−3, respectively) during cooking times (6–7 pm). Indoor sources increased the indoor concentrations of particles and NO2 by an average of 26–37% in comparison to the indoor background level without indoor sources. Outdoor and indoor air exchange plays an important role in reducing air pollution indoors by 65–86% for particles and 42–65% for NO2.
Lim S, Bassey E, Bos B, et al., 2022, Comparing human exposure to fine particulate matter in low and high-income countries: a systematic review of studies measuring personal PM2.5 exposure, Science of the Total Environment, Vol: 833, ISSN: 0048-9697
BackgroundDue to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.ObjectivesThe aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.MethodsThis review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).ResultsFrom the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.ConclusionThis review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and seve
Suel E, Sorek-Hamer M, Moise I, et al., 2022, What you see is what you breathe? Estimating air pollution spatial variation using street level imagery, Remote Sensing, Vol: 14, ISSN: 2072-4292
High spatial resolution information on urban air pollution levels is unavailable in many areas globally, partially due to high input data needs of existing estimation approaches. Here we introduce a computer vision method to estimate annual means for air pollution levels from street level images. We used annual mean estimates of NO2 and PM2.5 concentrations from locally calibrated models as labels from London, New York, and Vancouver to allow for compilation of a sufficiently large dataset (~250k images for each city). Our experimental setup is designed to quantify intra and intercity transferability of image-based model estimates. Performances were high and comparable to traditional land-use regression (LUR) and dispersion models when training and testing on images from the same city (R2 values between 0.51 and 0.95 when validated on data from ground monitoring stations). Like LUR models, transferability of models between cities in different geographies is more difficult. Specifically, transferability between the three cities i.e., London, New York, and Vancouver, which have similar pollution source profiles were moderately successful (R2 values between zero and 0.67). Comparatively, performances when transferring models trained on these cities with very different source profiles i.e., Accra in Ghana and Hong Kong were lower (R2 between zero and 0.21) suggesting the need for local calibration with local calibration using additional measurement data from cities that share similar source profiles.
Dimakopoulou K, Samoli E, Analitis A, et al., 2022, Development and Evaluation of Spatio-Temporal Air Pollution Exposure Models and Their Combinations in the Greater London Area, UK, INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, Vol: 19
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- Citations: 2
Kenis A, Barratt B, 2022, The role of the media in staging air pollution: The controversy on extreme air pollution along Oxford Street and other debates on poor air quality in London, ENVIRONMENT AND PLANNING C-POLITICS AND SPACE, Vol: 40, Pages: 611-628, ISSN: 2399-6544
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- Citations: 4
Lim S, Mudway I, Molden N, et al., 2022, Identifying trends in ultrafine particle infiltration and carbon dioxide ventilation in 92 vehicle models, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 812, ISSN: 0048-9697
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- Citations: 1
Wang J, Alli AS, Clark S, et al., 2022, Nitrogen oxides (NO and NO2) pollution in the Accra metropolis: spatiotemporal patterns and the role of meteorology, Science of the Total Environment, Vol: 803, ISSN: 0048-9697
Economic and urban development in sub-Saharan Africa (SSA) may be shifting the dominant air pollution sources in cities from biomass to road traffic. Considered as a marker for traffic-related air pollution in cities, we conducted a city-wide measurement of NOx levels in the Accra Metropolis and examined their spatiotemporal patterns in relation to land use and meteorological factors. Between April 2019 to June 2020, we collected weekly integrated NOx (n = 428) and NO2 (n = 472) samples at 10 fixed (year-long) and 124 rotating (week-long) sites. Data from the same time of year were compared to a previous study (2006) to assess changes in NO2 concentrations. NO and NO2 concentrations were highest in commercial/business/industrial (66 and 76 μg/m3, respectively) and high-density residential areas (47 and 59 μg/m3, respectively), compared with peri-urban locations. We observed annual means of 68 and 70 μg/m3 for NO and NO2, and a clear seasonal variation, with the mean NO2 of 63 μg/m3 (non-Harmattan) increased by 25–56% to 87 μg/m3 (Harmattan) across different site types. The NO2/NOx ratio was also elevated by 19–28%. Both NO and NO2 levels were associated with indicators of road traffic emissions (e.g. distance to major roads), but not with community biomass use (e.g. wood and charcoal). We found strong correlations between both NO2 and NO2/NOx and mixing layer depth, incident solar radiation and water vapor mixing ratio. These findings represent an increase of 25–180% when compared to a small study conducted in two high-density residential neighborhoods in Accra in 2006. Road traffic may be replacing community biomass use (major source of fine particulate matter) as the prominent source of air pollution in Accra, with policy implication for growing cities in SSA.
Morawska L, Zhu T, Liu N, et al., 2021, The state of science on severe air pollution episodes: quantitative and qualitative analysis, Environment International, Vol: 156, ISSN: 0160-4120
Severe episodic air pollution blankets entire cities and regions and have a profound impact on humans and their activities. We compiled daily fine particle (PM2.5) data from 100 cities in five continents, investigated the trends of number, frequency, and duration of pollution episodes, and compared these with the baseline trend in air pollution. We showed that the factors contributing to these events are complex; however, long-term measures to abate emissions from all anthropogenic sources at all times is also the most efficient way to reduce the occurrence of severe air pollution events. In the short term, accurate forecasting systems of such events based on the meteorological conditions favouring their occurrence, together with effective emergency mitigation of anthropogenic sources, may lessen their magnitude and/or duration. However, there is no clear way of preventing events caused by natural sources affected by climate change, such as wildfires and desert dust outbreaks.
Lim S, Holliday L, Barratt B, et al., 2021, Assessing the exposure and hazard of diesel exhaust in professional drivers: a review of the current state of knowledge, Air Quality, Atmosphere and Health, Vol: 14, Pages: 1681-1695, ISSN: 1873-9318
It is well-established that traffic-related air pollution has a detrimental impact on health. Much of the focus has been on diesel exhaust emissions due to a rapid increase in vehicle numbers and studies finding that this pollutant is carcinogenic. Unsurprisingly, the highest diesel exposures that the general population experiences are during urban daily commutes; however, few studies have considered professional drivers who are chronically exposed to the pollutant due to their work in transport microenvironments. In this narrative review, we address the literature on professional drivers’ exposure to diesel exhaust and advocate that a modern exposure science approach utilised in commuter personal exposure studies is needed. This type of evaluation will provide a more detailed understanding of the time-activity of professional drivers’ exposures which is required to identify specific interventions to reduce their risk to diesel exhaust emissions.
Varaden D, Leidland E, Lim S, et al., 2021, "I am an air quality scientist"- Using citizen science to characterise school children's exposure to air pollution, ENVIRONMENTAL RESEARCH, Vol: 201, ISSN: 0013-9351
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Lim S, Barratt B, Holliday L, et al., 2021, Characterising professional drivers’ exposure to traffic-related air pollution: Evidence for reduction strategies from in-vehicle personal exposure monitoring, Environment International, Vol: 153, ISSN: 0160-4120
Professional drivers working in congested urban areas are required to work near harmful traffic related pollutants for extended periods, representing a significant, but understudied occupational risk. This study collected personal black carbon (BC) exposures for 141 drivers across seven sectors in London. The aim of the study was to assess the magnitude and the primary determinants of their exposure, leading to the formulation of targeted exposure reduction strategies for the occupation. Each participant’s personal BC exposures were continuously measured using real-time monitors for 96 h, incorporating four shifts per participant. ‘At work’ BC exposures (3.1 ± 3.5 µg/m3) were 2.6 times higher compared to when ‘not at work’ (1.2 ± 0.7 µg/m3). Workers spent 19% of their time ‘at work driving’, however this activity contributed 36% of total BC exposure, highlighting the disproportionate effect driving had on their daily exposure. Taxi drivers experienced the highest BC exposures due to the time they spent working in congested central London, while emergency services had the lowest. Spikes in exposure were observed while driving and were at times greater than 100 µg/m3. The most significant determinants of drivers’ exposures were driving in tunnels, congestion, location, day of week and time of shift. Driving with closed windows significantly reduced exposures and is a simple behaviour change drivers could implement. Our results highlight strategies by which employers and local policy makers can reduce professional drivers’ exposure to traffic-related air pollution.
Evangelopoulos D, Chatzidiakou L, Walton H, et al., 2021, Personal exposure to air pollution and respiratory health of COPD patients in London, European Respiratory Journal, Vol: 58, ISSN: 0903-1936
Previous studies have investigated the effects of air pollution on chronic obstructive pulmonary disease (COPD) patients using either fixed site measurements or a limited number of personal measurements, usually for one pollutant and a short time period. These limitations may introduce bias and distort the epidemiological associations as they do not account for all the potential sources or the temporal variability of pollution.We used detailed information on individuals' exposure to various pollutants measured at fine spatio-temporal scale to obtain more reliable effect estimates. A panel of 115 patients was followed up for an average continuous period of 128 days carrying a personal monitor specifically designed for this project that measured temperature, PM10, PM2.5, NO2, NO, CO and O3 at one-minute time resolution. Each patient recorded daily information on respiratory symptoms and measured peak expiratory flow (PEF). A pulmonologist combined related data to define a binary variable denoting an "exacerbation". The exposure-response associations were assessed with mixed-effects models.We found that gaseous pollutants were associated with a deterioration in patients' health. We observed an increase of 16.4% (95% confidence interval: 8.6-24.6%), 9.4% (5.4-13.6%) and 7.6% (3.0-12.4%) in the odds of exacerbation for an interquartile range increase in NO2, NO and CO respectively. Similar results were obtained for cough and sputum. O3 was found to have adverse associations with PEF and breathlessness. No association was observed between particles and any outcome.Our findings suggest that, when considering total personal exposure to air pollutants, mainly the gaseous pollutants affect COPD patients' health.
Liu NM, Miyashita L, Sanak M, et al., 2021, Prostaglandin E<sub>2</sub> and phagocytosis of inhaled particulate matter by airway macrophages in cystic fibrosis, JOURNAL OF CYSTIC FIBROSIS, Vol: 20, Pages: 673-677, ISSN: 1569-1993
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Alli AS, Clark S, Hughes AF, et al., 2021, Spatial-temporal patterns of ambient fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra, Environmental Research Letters, Vol: 16, Pages: 1-12, ISSN: 1748-9326
Background: Sub-Saharan Africa (SSA) is rapidly urbanizing, and ambient air pollution has emerged as a major environmental health concern in SSA cities. Yet, effective air quality management is hindered by limited data. We deployed robust, low-cost and low-power devices in a large-scale measurement campaign and characterized within-city variations in fine particulate matter (PM2.5) and black carbon (BC) pollution in Accra, Ghana. Methods: Between April 2019 and June 2020, we measured weekly gravimetric (filter-based) and minute-by-minute PM2.5 concentrations at 146 unique locations, comprising of 10 fixed (~1-year) and 136 rotating (7-day) sites covering a range of land-use and source influences. Filters were weighed for mass, and light absorbance (10−5m−1) of the filters was used as proxy for BC concentration. Year-long data at four fixed sites that were monitored in a previous study (2006-2007) were compared to assess change in PM2.5 concentrations. Results: The mean annual PM2.5 across the fixed sites ranged from 26 μg/m3 at a peri-urban site to 40 μg/m3 at commercial, business, and industrial (CBI) areas. CBI areas had the highest PM2.5 levels (mean: 37 μg/m3), followed by high-density residential neighborhoods (mean: 36 μg/m3), while peri-urban areas recorded the lowest (mean: 26 μg/m3). Both PM2.5 and BC levels were highest during the dry dusty Harmattan period (mean PM2.5: 89 μg/m3) compared to non-Harmattan season (mean PM2.5: 23 μg/m3). PM2.5 at all sites peaked at dawn and dusk, coinciding with morning and evening heavy traffic. We found about a ~50% reduction (71 vs 37 μg/m3) in mean annual PM2.5 concentrations when compared to measurements in 2006-2007 in Accra. Conclusion: Ambient PM2.5 concentrations in Accra may have plateaued at levels lower than those seen in large Asian megacities. However, levels are still 2- to 4-fold higher than the WHO guideline. Effective and equitable policies are needed to reduce pollution
Varaden D, Barratt B, Heather K, et al., 2021, Engaging primary students with the issue of air pollution through citizen science: lessons to be learnt, Journal of Emergent Science
Bos B, Lim S, Hedges M, et al., 2021, Taxi drivers' exposure to black carbon and nitrogen dioxide in electric and diesel vehicles: A case study in London, ENVIRONMENTAL RESEARCH, Vol: 195, ISSN: 0013-9351
Zongbo S, Barratt B, Bloss W, et al., 2021, Atmospheric pollution and human health in a Chinese megacity (APHH-Beijing) programme, Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) Programme
In 2016, over 150 UK and Chinese scientists joined forces to understand the causes and impacts - emission sources, atmospheric processes and health effects - of air pollution in Beijing, with the ultimate aim of informing air pollution solutions and thus improving public health. The Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-Beijing) research programme succeeded in delivering its ambitious objectives and significant additional science, through a large-scale, coordinated multidisciplinary collaboration. APHH-Beijing conducted the largest international air pollution field campaigns to date in Beijing in 2016 and 2017, generating new insight into air pollution characteristics using novel observational and modelling tools. The multi-faceted capabilities of the APHH-Beijing team addressed key policy-relevant air pollution challenges, such as the role of road traffic and long-range transport in influencing air quality, by combining approaches across disciplines, institutions and countries. To date, the APHH Beijing team has contributed to over 400 international peer-reviewed scientific journal papers including in multidisciplinary journals and 47 in the APHH-Beijing Atmospheric Chemistry & Physics / Atmospheric Measurement Techniques special Issue. More importantly, APHH-Beijing generated a range of scientific insights which can support the development of mitigation strategies to improve air quality and public health and reduce air quality inequality. In this report, we highlight some of the research outcomes that have potential implications for policymaking:
Han Y, Chatzidiakou L, Yan L, et al., 2021, Difference in ambient-personal exposure to PM2.5 and its inflammatory effect in local residents in urban and peri-urban Beijing, China: results of the AIRLESS project, Faraday Discussions, Vol: 226, Pages: 569-583, ISSN: 1359-6640
Measurement of ambient fine particulate matter (PM2.5) is often used as a proxy of personal exposure in epidemiological studies. However, the difference between personal and ambient exposure, and whether it biases the estimates of health effects remain unknown. Based on an epidemiological study (AIRLESS) and simultaneously launched intensive monitoring campaigns (APHH), we quantified and compared the personal and ambient exposure to PM2.5 and the related health impact among residents in Beijing, China. In total, 123 urban and 128 peri-urban non-smoking participants were recruited from two well-established cohorts in Beijing. During winter 2016 and summer 2017, each participant was instructed to carry a validated personal air monitor (PAM) to measure PM2.5 concentration at high spatiotemporal resolution for seven consecutive days in each season. Multiple inflammatory biomarkers were measured, including exhaled NO, blood monocytes counts and C-reactive protein. Linear mixed-effect models were used for the associations between exposure and health outcomes with adjustment for confounders. The average level of daily personal exposure to PM2.5 was consistently lower than using corresponding ambient concentration, and the difference is greater during the winter. The personal to ambient (P/A) ratio of exposure to PM2.5 exhibited an exponentially declining trend, and showed larger variations when ambient PM2.5 levels < 25 μg m−3. Personal exposure to PM2.5 was significantly associated with the increase in respiratory and systemic inflammatory biomarkers; however, the associations were weaker or became insignificant when ambient concentrations were used. Exposure to ambient PM2.5 might not be a good proxy to estimate the health effect of exposure to personal PM2.5.
Liu NM, Miyashita L, Maher BA, et al., 2021, Evidence for the presence of air pollution nanoparticles in placental tissue cells, SCIENCE OF THE TOTAL ENVIRONMENT, Vol: 751, ISSN: 0048-9697
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- Citations: 57
Han Y, Chen W, Chatzidiakou L, et al., 2020, Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing: protocol for the AIRLESS study, Atmospheric Chemistry and Physics, Vol: 20, Pages: 15775-15792, ISSN: 1680-7316
Beijing, as a representative megacity in China, is experiencing some of the most severe air pollution episodes in the world, and its fast urbanization has led to substantial urban and peri-urban disparities in both health status and air quality. Uncertainties remain regarding the possible causal links between individual air pollutants and health outcomes, with spatial comparative investigations of these links lacking, particularly in developing megacities. In light of this challenge, Effects of AIR pollution on cardiopuLmonary disEaSe in urban and peri-urban reSidents in Beijing (AIRLESS) was initiated, with the aim of addressing the complex issue of relating multi-pollutant exposure to cardiopulmonary outcomes. This paper presents the novel methodological framework employed in the project, namely (1) the deployment of two panel studies from established cohorts in urban and peri-urban Beijing, with different exposure settings regarding pollution levels and diverse sources; (2) the collection of detailed measurements and biomarkers of participants from a nested case (hypertensive) and control (healthy) study setting; (3) the assessment of indoor and personal exposure to multiple gaseous pollutants and particulate matter at unprecedented spatial and temporal resolution with validated novel sensor technologies; (4) the assessment of ambient air pollution levels in a large-scale field campaign, particularly the chemical composition of particulate matter. Preliminary results showed that there is a large difference between ambient and personal air pollution levels, and the differences varied between seasons and locations. These large differences were reflected on the different health responses between the two panels.
Analitis A, Barratt B, Green D, et al., 2020, Prediction of PM<sub>2.5</sub> concentrations at the locations of monitoring sites measuring PM<sub>10</sub> and NO<sub>x</sub>, using generalized additive models and machine learning methods: A case study in London, ATMOSPHERIC ENVIRONMENT, Vol: 240, ISSN: 1352-2310
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- Citations: 17
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