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Li J, Deng Z, Soerensen SJC, Kachuri L, Cardenas A, Graff RE, Leppert JT, Langston ME, Chung BI. Ambient air pollution and urological cancer risk: A systematic review and meta-analysis of epidemiological evidence. Nat Commun 2024; 15:5116. [PMID: 38879581 PMCID: PMC11180144 DOI: 10.1038/s41467-024-48857-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 05/13/2024] [Indexed: 06/19/2024] Open
Abstract
Exposure to ambient air pollution has significant adverse health effects; however, whether air pollution is associated with urological cancer is largely unknown. We conduct a systematic review and meta-analysis with epidemiological studies, showing that a 5 μg/m3 increase in PM2.5 exposure is associated with a 6%, 7%, and 9%, increased risk of overall urological, bladder, and kidney cancer, respectively; and a 10 μg/m3 increase in NO2 is linked to a 3%, 4%, and 4% higher risk of overall urological, bladder, and prostate cancer, respectively. Were these associations to reflect causal relationships, lowering PM2.5 levels to 5.8 μg/m3 could reduce the age-standardized rate of urological cancer by 1.5 ~ 27/100,000 across the 15 countries with the highest PM2.5 level from the top 30 countries with the highest urological cancer burden. Implementing global health policies that can improve air quality could potentially reduce the risk of urologic cancer and alleviate its burden.
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Affiliation(s)
- Jinhui Li
- Department of Urology, Stanford University Medical Center, Stanford, CA, USA.
| | - Zhengyi Deng
- Department of Urology, Stanford University Medical Center, Stanford, CA, USA
| | - Simon John Christoph Soerensen
- Department of Urology, Stanford University Medical Center, Stanford, CA, USA
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Linda Kachuri
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Andres Cardenas
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Rebecca E Graff
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - John T Leppert
- Department of Urology, Stanford University Medical Center, Stanford, CA, USA
- Division of Nephrology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Division of Urology, Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - Marvin E Langston
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Benjamin I Chung
- Department of Urology, Stanford University Medical Center, Stanford, CA, USA
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2
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Wang J, Alli AS, Clark SN, Ezzati M, Brauer M, Hughes AF, Nimo J, Moses JB, Baah S, Nathvani R, D V, Agyei-Mensah S, Baumgartner J, Bennett JE, Arku RE. Inequalities in urban air pollution in sub-Saharan Africa: an empirical modeling of ambient NO and NO 2 concentrations in Accra, Ghana. ENVIRONMENTAL RESEARCH LETTERS : ERL [WEB SITE] 2024; 19:034036. [PMID: 38419692 PMCID: PMC10897512 DOI: 10.1088/1748-9326/ad2892] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 02/04/2024] [Accepted: 02/12/2024] [Indexed: 03/02/2024]
Abstract
Road traffic has become the leading source of air pollution in fast-growing sub-Saharan African cities. Yet, there is a dearth of robust city-wide data for understanding space-time variations and inequalities in combustion related emissions and exposures. We combined nitrogen dioxide (NO2) and nitric oxide (NO) measurement data from 134 locations in the Greater Accra Metropolitan Area (GAMA), with geographical, meteorological, and population factors in spatio-temporal mixed effects models to predict NO2 and NO concentrations at fine spatial (50 m) and temporal (weekly) resolution over the entire GAMA. Model performance was evaluated with 10-fold cross-validation (CV), and predictions were summarized as annual and seasonal (dusty [Harmattan] and rainy [non-Harmattan]) mean concentrations. The predictions were used to examine population distributions of, and socioeconomic inequalities in, exposure at the census enumeration area (EA) level. The models explained 88% and 79% of the spatiotemporal variability in NO2 and NO concentrations, respectively. The mean predicted annual, non-Harmattan and Harmattan NO2 levels were 37 (range: 1-189), 28 (range: 1-170) and 50 (range: 1-195) µg m-3, respectively. Unlike NO2, NO concentrations were highest in the non-Harmattan season (41 [range: 31-521] µg m-3). Road traffic was the dominant factor for both pollutants, but NO2 had higher spatial heterogeneity than NO. For both pollutants, the levels were substantially higher in the city core, where the entire population (100%) was exposed to annual NO2 levels exceeding the World Health Organization (WHO) guideline of 10 µg m-3. Significant disparities in NO2 concentrations existed across socioeconomic gradients, with residents in the poorest communities exposed to levels about 15 µg m-3 higher compared with the wealthiest (p < 0.001). The results showed the important role of road traffic emissions in air pollution concentrations in the GAMA, which has major implications for the health of the city's poorest residents. These data could support climate and health impact assessments as well as policy evaluations in the city.
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Affiliation(s)
- Jiayuan Wang
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, United States of America
| | - Abosede S Alli
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, United States of America
| | - Sierra N Clark
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
- Regional Institute for Population Studies, University of Ghana, Accra, Ghana
- Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, United Kingdom
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, Canada
| | | | - James Nimo
- Department of Physics, University of Ghana, Accra, Ghana
| | | | - Solomon Baah
- Department of Physics, University of Ghana, Accra, Ghana
| | - Ricky Nathvani
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Vishwanath D
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Samuel Agyei-Mensah
- Department of Geography and Resource Development, University of Ghana, Accra, Ghana
- Department of Civil and Environmental Engineering, Imperial College London, London, United Kingdom
| | - Jill Baumgartner
- Institute for Health and Social Policy, McGill University, Montreal, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada
| | - James E Bennett
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
| | - Raphael E Arku
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA, United States of America
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3
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Ghosh B, Barman HC, Ghosh S, Habib MM, Mahato J, Dayal L, Mahato S, Sao P, Murmu AC, Chowdhury AD, Pramanik S, Biswas R, Kumar S, Padhy PK. Air pollution status and attributable health effects across the state of West Bengal, India, during 2016-2021. ENVIRONMENTAL MONITORING AND ASSESSMENT 2024; 196:165. [PMID: 38233613 DOI: 10.1007/s10661-024-12333-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2023] [Accepted: 01/08/2024] [Indexed: 01/19/2024]
Abstract
Air pollution is one of the most significant threats to human safety due to its detrimental health consequences worldwide. This study examines the air pollution levels in 22 districts of West Bengal from 2016 to 2021, using data from 81 stations operated by the West Bengal Pollution Control Board (WBPCB). The study assesses the short- and long-term impacts of particulate matter (PM) on human health. The highest annual variation of PM10 was noted in 2016 (106.99 ± 34.17 μg/m3), and the lowest was reported in 2020 (88.02 ± 13.61 μg/m3), whereas the highest annual variations of NO2 (μg/m3) were found in 2016 (35.17 ± 13.55 μg/m3), and lowest in 2019 (29.72 ± 13.08 μg/m3). Similarly, the SO2 level was lower (5.35 μg/m3) in 2017 and higher in 2020 (7.78 μg/m3). In the state, Bardhaman, Bankura, Kolkata, and Howrah recorded the highest PM10 concentrations. The monthly and seasonal variations of pollution showed higher in December, January, and February (winter season) and lowest observed in June, July, and August (rainy season). The southern part of West Bengal state has recorded higher pollution levels than the northern part. The short- and long-term health impact assessment due to particulate matter shows that the estimated number of attributable cases (ENACs) for incidence of chronic bronchitis in adults and prevalence of bronchitis in children were 305,234 and 14,652 respectively. The long-term impact of PM2.5 on human health ENACs for mortality due to chronic obstructive pulmonary disease for adults, acute lower respiratory infections in children aged 0-5, lung cancer, and stroke for adults were 21,303, 12,477, 25,064, 94,406, and 86,272 respectively. This outcome assists decision-makers and stakeholders in effectively addressing the air pollution and health risk concerns within the specified area.
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Affiliation(s)
- Buddhadev Ghosh
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Harish Chandra Barman
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Sayoni Ghosh
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Md Maimun Habib
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Jayashree Mahato
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Lovely Dayal
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Susmita Mahato
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Priti Sao
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Atul Chandra Murmu
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Ayontika Deb Chowdhury
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Sourina Pramanik
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Rupsa Biswas
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Sushil Kumar
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India
| | - Pratap Kumar Padhy
- Department of Environmental Studies, Visva-Bharati, Siksha Bhavana (Institute of Science), Santiniketan, Birbhum, West Bengal, 731235, India.
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4
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Ayejoto DA, Agbasi JC, Nwazelibe VE, Egbueri JC, Alao JO. Understanding the connections between climate change, air pollution, and human health in Africa: Insights from a literature review. JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART C, TOXICOLOGY AND CARCINOGENESIS 2023; 41:77-120. [PMID: 37880976 DOI: 10.1080/26896583.2023.2267332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/27/2023]
Abstract
Climate change and air pollution are two interconnected global challenges that have profound impacts on human health. In Africa, a continent known for its rich biodiversity and diverse ecosystems, the adverse effects of climate change and air pollution are particularly concerning. This review study examines the implications of air pollution and climate change for human health and well-being in Africa. It explores the intersection of these two factors and their impact on various health outcomes, including cardiovascular disease, respiratory disorders, mental health, and vulnerable populations such as children and the elderly. The study highlights the disproportionate effects of air pollution on vulnerable groups and emphasizes the need for targeted interventions and policies to protect their health. Furthermore, it discusses the role of climate change in exacerbating air pollution and the potential long-term consequences for public health in Africa. The review also addresses the importance of considering temperature and precipitation changes as modifiers of the health effects of air pollution. By synthesizing existing research, this study aims to shed light on complex relationships and highlight the key findings, knowledge gaps, and potential solutions for mitigating the impacts of climate change and air pollution on human health in the region. The insights gained from this review can inform evidence-based policies and interventions to mitigate the adverse effects on human health and promote sustainable development in Africa.
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Affiliation(s)
- Daniel A Ayejoto
- Department of Environmental and Sustainability Sciences, Texas Christian University, Fort Worth, Texas, USA
| | - Johnson C Agbasi
- Department of Geology, Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State, Nigeria
| | - Vincent E Nwazelibe
- Department of Earth Sciences, Albert Ludwig University of Freiburg, Freiburg, Germany
| | - Johnbosco C Egbueri
- Department of Geology, Chukwuemeka Odumegwu Ojukwu University, Uli, Anambra State, Nigeria
| | - Joseph O Alao
- Department of Physics, Air Force Institute of Technology, Kaduna, Nigeria
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5
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Metzler AB, Nathvani R, Sharmanska V, Bai W, Muller E, Moulds S, Agyei-Asabere C, Adjei-Boadi D, Kyere-Gyeabour E, Tetteh JD, Owusu G, Agyei-Mensah S, Baumgartner J, Robinson BE, Arku RE, Ezzati M. Phenotyping urban built and natural environments with high-resolution satellite images and unsupervised deep learning. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 893:164794. [PMID: 37315611 PMCID: PMC7615085 DOI: 10.1016/j.scitotenv.2023.164794] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 05/05/2023] [Accepted: 06/08/2023] [Indexed: 06/16/2023]
Abstract
Cities in the developing world are expanding rapidly, and undergoing changes to their roads, buildings, vegetation, and other land use characteristics. Timely data are needed to ensure that urban change enhances health, wellbeing and sustainability. We present and evaluate a novel unsupervised deep clustering method to classify and characterise the complex and multidimensional built and natural environments of cities into interpretable clusters using high-resolution satellite images. We applied our approach to a high-resolution (0.3 m/pixel) satellite image of Accra, Ghana, one of the fastest growing cities in sub-Saharan Africa, and contextualised the results with demographic and environmental data that were not used for clustering. We show that clusters obtained solely from images capture distinct interpretable phenotypes of the urban natural (vegetation and water) and built (building count, size, density, and orientation; length and arrangement of roads) environment, and population, either as a unique defining characteristic (e.g., bodies of water or dense vegetation) or in combination (e.g., buildings surrounded by vegetation or sparsely populated areas intermixed with roads). Clusters that were based on a single defining characteristic were robust to the spatial scale of analysis and the choice of cluster number, whereas those based on a combination of characteristics changed based on scale and number of clusters. The results demonstrate that satellite data and unsupervised deep learning provide a cost-effective, interpretable and scalable approach for real-time tracking of sustainable urban development, especially where traditional environmental and demographic data are limited and infrequent.
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Affiliation(s)
- A Barbara Metzler
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Ricky Nathvani
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Viktoriia Sharmanska
- Department of Informatics, University of Sussex, UK; Department of Computing, Imperial College London, London, UK
| | - Wenjia Bai
- Department of Computing, Imperial College London, London, UK; Department of Brain Sciences, Imperial College London, London, UK
| | - Emily Muller
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK
| | - Simon Moulds
- School of Geography and the Environment, University of Oxford, UK
| | | | - Dina Adjei-Boadi
- Department of Geography and Resource Development, University of Ghana, Legon, Accra, Ghana
| | - Elvis Kyere-Gyeabour
- Department of Geography and Resource Development, University of Ghana, Legon, Accra, Ghana
| | - Jacob Doku Tetteh
- Department of Geography and Resource Development, University of Ghana, Legon, Accra, Ghana
| | - George Owusu
- Institute of Statistical, Social & Economic Research, University of Ghana, Accra, Ghana
| | - Samuel Agyei-Mensah
- Department of Geography and Resource Development, University of Ghana, Legon, Accra, Ghana
| | - Jill Baumgartner
- Department of Epidemiology and Biostatistics, McGill University, Montreal, Québec, Canada; Department of Equity, Ethics and Policy, McGill University, Montreal, Québec, Canada
| | - Brian E Robinson
- Department of Geography, McGill University, Montreal, Québec, Canada
| | - Raphael E Arku
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, USA
| | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, Imperial College London, London, UK; Regional Institute for Population Studies, University of Ghana, Accra, Ghana; Abdul Latif Jameel Institute for Disease and Emergency Analytics, Imperial College London, London, UK.
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6
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Li X, Abdullah LC, Sobri S, Syazarudin Md Said M, Aslina Hussain S, Poh Aun T, Hu J. Long-term spatiotemporal evolution and coordinated control of air pollutants in a typical mega-mountain city of Cheng-Yu region under the "dual carbon" goal. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION (1995) 2023; 73:649-678. [PMID: 37449903 DOI: 10.1080/10962247.2023.2232744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/19/2022] [Revised: 05/31/2023] [Accepted: 06/20/2023] [Indexed: 07/18/2023]
Abstract
Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for megacities to formulate relevant air pollution prevention and control measures and achieve carbon neutrality goals. Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain-city in China, environmental problems are complex and sensitive. This research aims to investigate the exceeding standard levels and spatio-temporal evolution of criteria pollutants between 2014 and 2020. The results indicated that PM10, PM2.5, CO and SO2 were decreased significantly by 45.91%, 52.86%, 38.89% and 66.67%, respectively. Conversely, the concentration of pollutant O3 present a fluctuating growth and found a "seesaw" phenomenon between it and PM. Furthermore, PM and O3 are highest in winter and summer, respectively. SO2, NO2, CO, and PM showed a "U-shaped", and O3 showed an inverted "U-shaped" seasonal variation. PM and O3 concentrations are still far behind the WHO, 2021AQGs standards. Significant spatial heterogeneity was observed in air pollution distribution. These results are of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, and formulate a regional carbon peaking roadmap under climate coordination. Besides, it can provide an important platform for exploring air pollution in typical terrain around the world and provide references for related epidemiological research.Implications: Chongqing is one of the dual-core key megacities in Cheng-Yu region and as a typical mountain city, environmental problems are complex and sensitive. Under the background of the "14th Five-Year Plan", the construction of the "Cheng-Yu Dual-City Economic Circle" and the "Dual-Carbon" goal, this article comprehensively discussed the annual and seasonal excess levels and spatiotemporal evolution of pollutants under the multiple policy and the newest international standards (WHO,2021AQG) backgrounds from 2014 to 2020 in Chongqing. Furthermore, suggestions and measures related to the collaborative management of pollutants were discussed. Finally, limitations and recommendations were also put forward.Clarifying the spatiotemporal distribution and impact mechanism of pollution is the prerequisite for cities to formulate relevant air pollution control measures and achieve carbon neutrality goals. This study is of great significance for Chongqing to achieve "double control and double reduction" of PM2.5 and O3 pollution, study and formulate a regional carbon peaking roadmap under climate coordination and an action plan for sustained improvement of air quality.In addition, this research can advanced our understanding of air pollution in complex terrain. Furthermore, it also promote the construction of the China national strategic Cheng-Yu economic circle and build a beautiful west. Moreover, it provides scientific insights for local policymakers to guide smart urban planning, industrial layout, energy structure, and transportation planning to improve air quality throughout the Cheng-Yu region. Finally, this is also conducive to future scientific research in other regions of China, and even megacities with complex terrain in the world.
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Affiliation(s)
- Xiaoju Li
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
| | - Luqman Chuah Abdullah
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Shafreeza Sobri
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Mohamad Syazarudin Md Said
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Siti Aslina Hussain
- Department of Chemical and Environmental Engineering, Faculty of Engineering, University Putra Malaysia, Serdang, Malaysia
| | - Tan Poh Aun
- SOx NOx Asia Sdn Bhd, Subang Jaya, Selangor, Malaysia
| | - Jinzhao Hu
- Department of Resource and Environment, Xichang University, Xichang City, Sichuan Province, China
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7
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Alli AS, Clark SN, Wang J, Bennett J, Hughes AF, Ezzati M, Brauer M, Nimo J, Bedford-Moses J, Baah S, Cavanaugh A, Agyei-Mensah S, Owusu G, Baumgartner J, Arku RE. High-resolution patterns and inequalities in ambient fine particle mass (PM 2.5) and black carbon (BC) in the Greater Accra Metropolis, Ghana. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 875:162582. [PMID: 36870487 PMCID: PMC10131145 DOI: 10.1016/j.scitotenv.2023.162582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 02/06/2023] [Accepted: 02/27/2023] [Indexed: 06/02/2023]
Abstract
Growing cities in sub-Saharan Africa (SSA) experience high levels of ambient air pollution. However, sparse long-term city-wide air pollution exposure data limits policy mitigation efforts and assessment of the health and climate effects. In the first study of its kind in West Africa, we developed high resolution spatiotemporal land use regression (LUR) models to map fine particulate matter (PM2.5) and black carbon (BC) concentrations in the Greater Accra Metropolitan Area (GAMA), one of the fastest sprawling metropolises in SSA. We conducted a one-year measurement campaign covering 146 sites and combined these data with geospatial and meteorological predictors to develop separate Harmattan and non-Harmattan season PM2.5 and BC models at 100 m resolution. The final models were selected with a forward stepwise procedure and performance was evaluated with 10-fold cross-validation. Model predictions were overlayed with the most recent census data to estimate the population distribution of exposure and socioeconomic inequalities in exposure at the census enumeration area level. The fixed effects components of the models explained 48-69 % and 63-71 % of the variance in PM2.5 and BC concentrations, respectively. Spatial variables related to road traffic and vegetation explained the most variability in the non-Harmattan models, while temporal variables were dominant in the Harmattan models. The entire GAMA population is exposed to PM2.5 levels above the World Health Organization guideline, including even the Interim Target 3 (15 μg/m3), with the highest exposures in poorer neighborhoods. The models can be used to support air pollution mitigation policies, health, and climate impact assessments. The measurement and modelling approach used in this study can be adapted to other African cities to bridge the air pollution data gap in the region.
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Affiliation(s)
- Abosede S Alli
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, USA
| | - Sierra N Clark
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Jiayuan Wang
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, USA
| | - James Bennett
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | | | - Majid Ezzati
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Regional Institute for Population Studies, University of Ghana, Accra, Ghana
| | - Michael Brauer
- School of Population and Public Health, The University of British Columbia, Vancouver, Canada
| | - James Nimo
- Department of Physics, University of Ghana, Accra, Ghana
| | | | - Solomon Baah
- Department of Physics, University of Ghana, Accra, Ghana
| | | | - Samuel Agyei-Mensah
- Department of Geography and Resource Development, University of Ghana, Accra, Ghana
| | - George Owusu
- Institute of Statistical, Social & Economic Research, University of Ghana, Accra, Ghana
| | - Jill Baumgartner
- Institute for Health and Social Policy, McGill University, Montreal, Canada; Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Canada
| | - Raphael E Arku
- Department of Environmental Health Sciences, School of Public Health and Health Sciences, University of Massachusetts, Amherst, USA.
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8
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Wang Y, Liu P, Schwartz J, Castro E, Wang W, Chang H, Scovronick N, Shi L. Disparities in ambient nitrogen dioxide pollution in the United States. Proc Natl Acad Sci U S A 2023; 120:e2208450120. [PMID: 37036985 PMCID: PMC10120073 DOI: 10.1073/pnas.2208450120] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 03/08/2023] [Indexed: 04/12/2023] Open
Abstract
Average ambient concentrations of nitrogen dioxide (NO2), an important air pollutant, have declined in the United States since the enactment of the Clean Air Act. Despite evidence that NO2 disproportionately affects racial/ethnic minority groups, it remains unclear what drives the exposure disparities and how they have changed over time. Here, we provide evidence by integrating high-resolution (1 km × 1 km) ground-level NO2 estimates, sociodemographic information, and source-specific emission intensity and location for 217,740 block groups across the contiguous United States from 2000 to 2016. We show that racial/ethnic minorities are disproportionately exposed to higher levels of NO2 pollution compared with Whites across the United States and within major metropolitan areas. These inequities persisted over time and have worsened in many cases, despite a significant decrease in the national average NO2 concentration over the 17-y study period. Overall, traffic contributes the largest fraction of NO2 disparity. Contributions of other emission sources to exposure disparities vary by location. Our analyses offer insights into policies aimed at reducing air pollution exposure disparities among races/ethnicities and locations.
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Affiliation(s)
- Yifan Wang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA30322
| | - Pengfei Liu
- School of Earth and Atmospheric Sciences, Georgia Institute of Technology, Atlanta, GA30322
| | - Joel Schwartz
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA02115
| | - Edgar Castro
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA02115
| | - Wenhao Wang
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA30322
| | - Howard Chang
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA30322
| | - Noah Scovronick
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA30322
| | - Liuhua Shi
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA30322
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9
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Agyei-Mensah S, Kyere-Gyeabour E, Mwaura A, Mudu P. Between Policy and Risk Communication: Coverage of Air Pollution in Ghanaian Newspapers. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:13246. [PMID: 36293823 PMCID: PMC9603739 DOI: 10.3390/ijerph192013246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 10/06/2022] [Accepted: 10/07/2022] [Indexed: 06/16/2023]
Abstract
Mass media plays an increasingly persuasive role in orienting political decisions, shaping social agendas, influencing individuals' actions, and interpreting scientific evidence for the public. With growing scientific understanding of the health, social and environmental consequences of air pollution, there is an urgent need to understand how media coverage frames these links, particularly in Low- and Middle-Income Countries. This paper examines how the Ghanaian print and electronic media houses are covering air pollution issues given increased efforts at reducing air pollution within the country. The main goal of this work is to track the progress of policies to reduce air pollution. We used a qualitative content analysis of selected newspapers (both traditional and online) between the periods 2016 and 2021 and we found that articles on air pollution have been increasing, with more reportage on impact and policy issues compared to causes of air pollution. A focus group with six members of the media confirmed an interest in covering health and environmental issues, particularly coverage of specific diseases and human-interest pieces. This increasing attention is likely associated with intensifying local, national, and international action to improve air quality in Ghana, and growing awareness of the health impacts of air pollution.
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Affiliation(s)
- Samuel Agyei-Mensah
- Department of Geography and Resource Development, University of Ghana, Legon, Accra P.O. Box LG 59, Ghana
| | - Elvis Kyere-Gyeabour
- Department of Geography and Resource Development, University of Ghana, Legon, Accra P.O. Box LG 59, Ghana
| | - Abraham Mwaura
- Environment, Climate Change and Health, World Health Organization, 1211 Geneva, Switzerland
| | - Pierpaolo Mudu
- Environment, Climate Change and Health, World Health Organization, 1211 Geneva, Switzerland
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10
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Suel E, Sorek-Hamer M, Moise I, von Pohle M, Sahasrabhojanee A, Asanjan AA, Arku RE, Alli AS, Barratt B, Clark SN, Middel A, Deardorff E, Lingenfelter V, Oza N, Yadav N, Ezzati M, Brauer M. What you see is what you breathe? Estimating air pollution spatial variation using street level imagery. REMOTE SENSING 2022; 14:3429. [PMID: 37719470 PMCID: PMC7615101 DOI: 10.3390/rs14143429] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
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.
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Affiliation(s)
| | | | | | - Michael von Pohle
- Universities Space Research Association (USRA)
- NASA Ames Research Center
| | | | | | | | | | | | | | | | - Emily Deardorff
- Universities Space Research Association (USRA)
- NASA Ames Research Center
- San Diego State University
| | - Violet Lingenfelter
- Universities Space Research Association (USRA)
- NASA Ames Research Center
- UC Berkeley
| | | | - Nishant Yadav
- Universities Space Research Association (USRA)
- NASA Ames Research Center
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11
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Rehan M, Munir S. Analysis and Modeling of Air Pollution in Extreme Meteorological Conditions: A Case Study of Jeddah, the Kingdom of Saudi Arabia. TOXICS 2022; 10:toxics10070376. [PMID: 35878281 PMCID: PMC9320433 DOI: 10.3390/toxics10070376] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 06/26/2022] [Accepted: 07/01/2022] [Indexed: 02/01/2023]
Abstract
Air pollution has serious environmental and human health-related consequences; however, little work seems to be undertaken to address the harms in Middle Eastern countries, including Saudi Arabia. We installed a continuous air quality monitoring station in Jeddah, Saudi Arabia and monitored several air pollutants and meteorological parameters over a 2-year period (2018–2019). Here, we developed two supervised machine learning models, known as quantile regression models, to analyze the whole distribution of the modeled pollutants, not only the mean values. Two pollutants, namely NO2 and O3, were modeled by dividing their concentrations into several quantiles (0.05, 0.25, 0.50, 0.75, and 0.95) and the effect of several pollutants and meteorological variables was analyzed on each quantile. The effect of the explanatory variables changed at different segments of the distribution of NO2 and O3 concentrations. For instance, for the modeling of O3, the coefficients of wind speed at quantiles 0.05, 0.25, 0.5, 0.75, and 0.95 were 1.40, 2.15, 2.34, 2.31, and 1.56, respectively. Correlation coefficients of 0.91 and 0.92 and RMSE values of 14.41 and 8.96, which are calculated for the cross-validated models of NO2 and O3, showed an acceptable model performance. Quantile analysis aids in better understanding the behavior of air pollution and how it interacts with the influencing factors.
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Affiliation(s)
- Mohammad Rehan
- Center of Excellence in Environmental Studies (CEES), King Abdulaziz University, Jeddah 21589, Saudi Arabia
- Correspondence: ; Tel.: +966-583047435
| | - Said Munir
- Institute for Transport Studies, Faculty of Environment, University of Leeds, Leeds LS2 9JT, UK;
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