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Kadelbach P, Weinmayr G, Chen J, Jaensch Dipl-Dok A, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Cesaroni G, Fecht D, Forastiere PF, Gulliver PJ, Hertel O, Hoffmann B, Hvidtfeldt UA, Katsouyanni PK, Ketzel M, Leander K, Ljungman P, Magnusson PKE, Pershagen G, Rizzuto D, Samoli E, Severi G, Stafoggia M, Tjønneland PA, Vermeulen R, Peters A, Wolf K, Raaschou-Nielsen PO, Brunekreef B, Hoek G, Zitt E, Nage PG. Long-term exposure to air pollution and chronic kidney disease-associated mortality - results from the pooled cohort of the European multicentre ELAPSE-study. Environ Res 2024:118942. [PMID: 38649012 DOI: 10.1016/j.envres.2024.118942] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2024] [Revised: 04/12/2024] [Accepted: 04/13/2024] [Indexed: 04/25/2024]
Abstract
Despite the known link between air pollution and cause-specific mortality, its relation to chronic kidney disease (CKD)-associated mortality is understudied. Therefore, we investigated the association between long-term exposure to air pollution and CKD-related mortality in a large multicentre population-based European cohort. Cohort data were linked to local mortality registry data. CKD-death was defined as ICD10 codes N18-N19 or corresponding ICD9 codes. Mean annual exposure at participant's home address was determined with fine spatial resolution exposure models for nitrogen dioxide (NO2), black carbon (BC), ozone (O3), particulate matter ≤2.5μm (PM2.5) and several elemental constituents of PM2.5. Cox regression models were adjusted for age, sex, cohort, calendar year of recruitment, smoking status, marital status, employment status and neighbourhood mean income. Over a mean follow-up time of 20.4 years, 313 of 289 564 persons died from CKD. Associations were positive for PM2.5 (hazard ratio (HR) with 95% confidence interval (CI) of 1.31 (1.03-1.66) per 5μg/m3, BC (1.26 (1.03-1.53) per 0.5×10- 5/m), NO2 (1.13 (0.93-1.38) per 10μg/m3) and inverse for O3 (0.71 (0.54-0.93) per 10μg/m3). Results were robust to further covariate adjustment. Exclusion of the largest sub-cohort contributing 226 cases, led to null associations. Among the elemental constituents, Cu, Fe, K, Ni, S and Zn, representing different sources including traffic, biomass and oil burning and secondary pollutants, were associated with CKD-related mortality. In conclusion, our results suggest an association between air pollution from different sources and CKD-related mortality.
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Affiliation(s)
- Pauline Kadelbach
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Gudrun Weinmayr
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
| | - Jie Chen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | | | - Sophia Rodopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Maciej Strak
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Zorana J Andersen
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Tom Bellander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jørgen Brandt
- Department of Environmental Science, Aarhus University, Roskilde, Denmark; iClimate - interdisciplinary Centre for Climate Change, Aarhus University, Roskilde, Denmark
| | - Giulia Cesaroni
- Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy
| | - Daniela Fecht
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Prof Francesco Forastiere
- Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy; Environmental Research Group, School of Public Health, Faculty of Medicine, Imperial College, London, UK
| | - Prof John Gulliver
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, UK
| | - Ole Hertel
- Faculty of Technical Sciences, Aarhus University, Roskilde, Denmark
| | - Barbara Hoffmann
- Institute for Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Prof Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece; Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy
| | - Matthias Ketzel
- Department of Environmental Science, Aarhus University, Roskilde, Denmark; Global Centre for Clean Air Research (GCARE), University of Surrey, Guildford GU2 7XH, United Kingdom
| | - Karin Leander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Petter Ljungman
- Institute of Environmental Medicine, Karolinska Institutet, SE-171 77 Stockholm, Sweden; Department of Cardiology, Danderyd University Hospital, 182 88 Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Debora Rizzuto
- Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Gianluca Severi
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP UMR1018, 94805, Villejuif, France
| | - Massimo Stafoggia
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy
| | - Prof Anne Tjønneland
- The Danish Cancer Institute, Copenhagen, Denmark; Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Prof Ole Raaschou-Nielsen
- The Danish Cancer Institute, Copenhagen, Denmark; Department of Environmental Science, Aarhus University, Roskilde, Denmark
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Emanuel Zitt
- Agency for Preventive and Social Medicine (aks), Bregenz, Austria; Department of Internal Medicine 3, LKH Feldkirch, Feldkirch, Austria; Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT), Feldkirch, Austria
| | - Prof Gabriele Nage
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
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Weinmayr G, Chen J, Jaensch A, Skodda L, Rodopoulou S, Strak M, de Hoogh K, Andersen ZJ, Bellander T, Brandt J, Fecht D, Forastiere F, Gulliver J, Hertel O, Hoffmann B, Hvidtfeldt UA, Katsouyanni K, Ketzel M, Leander K, Magnusson PKE, Pershagen G, Rizzuto D, Samoli E, Severi G, Stafoggia M, Tjønneland A, Vermeulen R, Wolf K, Zitt E, Brunekreef B, Thurston G, Hoek G, Raaschou-Nielsen O, Nagel G. Long-term exposure to several constituents and sources of PM 2.5 is associated with incidence of upper aerodigestive tract cancers but not gastric cancer: Results from the large pooled European cohort of the ELAPSE project. Sci Total Environ 2024; 912:168789. [PMID: 37996018 DOI: 10.1016/j.scitotenv.2023.168789] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 11/17/2023] [Accepted: 11/20/2023] [Indexed: 11/25/2023]
Abstract
It is unclear whether cancers of the upper aerodigestive tract (UADT) and gastric cancer are related to air pollution, due to few studies with inconsistent results. The effects of particulate matter (PM) may vary across locations due to different source contributions and related PM compositions, and it is not clear which PM constituents/sources are most relevant from a consideration of overall mass concentration alone. We therefore investigated the association of UADT and gastric cancers with PM2.5 elemental constituents and sources components indicative of different sources within a large multicentre population based epidemiological study. Cohorts with at least 10 cases per cohort led to ten and eight cohorts from five countries contributing to UADT- and gastric cancer analysis, respectively. Outcome ascertainment was based on cancer registry data or data of comparable quality. We assigned home address exposure to eight elemental constituents (Cu, Fe, K, Ni, S, Si, V and Zn) estimated from Europe-wide exposure models, and five source components identified by absolute principal component analysis (APCA). Cox regression models were run with age as time scale, stratified for sex and cohort and adjusted for relevant individual and neighbourhood level confounders. We observed 1139 UADT and 872 gastric cancer cases during a mean follow-up of 18.3 and 18.5 years, respectively. UADT cancer incidence was associated with all constituents except K in single element analyses. After adjustment for NO2, only Ni and V remained associated with UADT. Residual oil combustion and traffic source components were associated with UADT cancer persisting in the multiple source model. No associations were found for any of the elements or source components and gastric cancer incidence. Our results indicate an association of several PM constituents indicative of different sources with UADT but not gastric cancer incidence with the most robust evidence for traffic and residual oil combustion.
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Affiliation(s)
- Gudrun Weinmayr
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
| | - Jie Chen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Andrea Jaensch
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Lea Skodda
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
| | - Sophia Rodopoulou
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Maciej Strak
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands; National Institute for Public Health and the Environment, Bilthoven, the Netherlands
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Basel, Switzerland; University of Basel, Basel, Switzerland
| | - Zorana J Andersen
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Tom Bellander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Jørgen Brandt
- Department of Environmental Science, Aarhus University, Roskilde, Denmark; iClimate - interdisciplinary Centre for Climate Change, Aarhus University, Roskilde, Denmark
| | - Daniela Fecht
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Francesco Forastiere
- Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy; Environmental Research Group, School of Public Health, Faculty of Medicine, Imperial College, London, UK
| | - John Gulliver
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK; Centre for Environmental Health and Sustainability & School of Geography, Geology and the Environment, University of Leicester, Leicester, UK
| | - Ole Hertel
- Faculty of Technical Sciences, Aarhus University, Roskilde, Denmark
| | - Barbara Hoffmann
- Institute for Occupational, Social and Environmental Medicine, Centre for Health and Society, Medical Faculty, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | | | - Klea Katsouyanni
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece; MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Matthias Ketzel
- Department of Environmental Science, Aarhus University, Roskilde, Denmark; Global Centre for Clean Air Research (GCARE), University of Surrey, Guildford GU2 7XH, UK
| | - Karin Leander
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Patrik K E Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Göran Pershagen
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Debora Rizzuto
- Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden; Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Evangelia Samoli
- Department of Hygiene, Epidemiology and Medical Statistics, Medical School, National and Kapodistrian University of Athens, Athens, Greece
| | - Gianluca Severi
- University Paris-Saclay, UVSQ, Inserm, Gustave Roussy, "Exposome and Heredity" team, CESP UMR1018, 94805, Villejuif, France
| | - Massimo Stafoggia
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Epidemiology, Lazio Region Health Service/ASL Roma 1, Rome, Italy
| | - Anne Tjønneland
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark; The Danish Cancer Institute, Copenhagen, Denmark
| | - Roel Vermeulen
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Kathrin Wolf
- Institute of Epidemiology, Helmholtz Zentrum München, Neuherberg, Germany
| | - Emanuel Zitt
- Agency for Preventive and Social Medicine (aks), Bregenz, Austria; Department of Internal Medicine 3, LKH Feldkirch, Feldkirch, Austria
| | - Bert Brunekreef
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - George Thurston
- Division of Environmental Medicine, Depts of Medicine and Population Health, New York University Grossman School of Medicine, New York, USA
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Ole Raaschou-Nielsen
- Department of Environmental Science, Aarhus University, Roskilde, Denmark; The Danish Cancer Institute, Copenhagen, Denmark
| | - Gabriele Nagel
- Institute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany
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von Mikecz A. Elegant Nematodes Improve Our Understanding of Human Neuronal Diseases, the Role of Pollutants and Strategies of Resilience. Environ Sci Technol 2023; 57:16755-16763. [PMID: 37874738 PMCID: PMC10634345 DOI: 10.1021/acs.est.3c04580] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2023] [Revised: 10/05/2023] [Accepted: 10/06/2023] [Indexed: 10/26/2023]
Abstract
The prevalence of neurodegenerative disorders such as Alzheimer's and Parkinson's disease are rising globally. The role of environmental pollution in neurodegeneration is largely unknown. Thus, this perspective advocates exposome research in C. elegans models of human diseases. The models express amyloid proteins such as Aβ, recapitulate the degeneration of specifically vulnerable neurons and allow for correlated neurobehavioral phenotyping throughout the entire life span of the nematode. Neurobehavioral traits like locomotion gaits, rigidity, or cognitive decline are quantifiable and carefully mimic key aspects of the human diseases. Underlying molecular pathways of neurodegeneration are elucidated in pollutant-exposed C. elegans Alzheimer's or Parkinson's models by transcriptomics (RNA-seq), mass spectrometry-based proteomics and omics addressing other biochemical traits. Validation of the identified disease pathways can be achieved by genome-wide association studies in matching human cohorts. A consistent One Health approach includes isolation of nematodes from contaminated sites and their comparative investigation by imaging, neurobehavioral profiling and single worm proteomics. C. elegans models of neurodegenerative diseases are likewise well-suited for high throughput methods that provide a promising strategy to identify resilience pathways of neurosafety and keep up with the number of pollutants, nonchemical exposome factors, and their interactions.
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Affiliation(s)
- Anna von Mikecz
- IUF − Leibniz Research Institute
of Environmental Medicine GmbH, Auf’m Hennekamp 50, 40225 Duesseldorf, Germany
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Jones JS, Nedkoff L, Heyworth JS, Almeida OP, Flicker L, Golledge J, Hankey GJ, Lim EH, Nieuwenhuijsen M, Yeap BB, Trevenen ML. Long-term exposure to low-concentration PM 2.5 and heart disease in older men in Perth, Australia: The Health in Men Study. Environ Epidemiol 2023; 7:e255. [PMID: 37545811 PMCID: PMC10402964 DOI: 10.1097/ee9.0000000000000255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2023] [Accepted: 05/31/2023] [Indexed: 08/08/2023] Open
Abstract
Exposure to particulate matter with an aerodynamic diameter less than or equal to 2.5 μm (PM2.5) is associated with increased risk of heart disease, but less is known about the relationship at low concentrations. This study aimed to determine the dose-response relationship between long-term PM2.5 exposure and risk of incident ischemic heart disease (IHD), incident heart failure (HF), and incident atrial fibrillation (AF) in older men living in a region with relatively low ambient air pollution. Methods PM2.5 exposure was estimated for 11,249 older adult males who resided in Perth, Western Australia and were recruited from 1996 to 1999. Participants were followed until 2018 for the HF and AF outcomes, and until 2017 for IHD. Cox-proportional hazards models, using age as the analysis time, and adjusting for demographic and lifestyle factors were used. PM2.5 was entered as a restricted cubic spline to model nonlinearity. Results We observed a mean PM2.5 concentration of 4.95 μg/m3 (SD 1.68 μg/m3) in the first year of recruitment. After excluding participants with preexisting disease and adjusting for demographic and lifestyle factors, PM2.5 exposure was associated with a trend toward increased incidence of IHD, HF, and AF, but none were statistically significant. At a PM2.5 concentration of 7 μg/m3 the hazard ratio for incident IHD was 1.04 (95% confidence interval [CI] = 0.86, 1.25) compared with the reference category of 1 μg/m3. Conclusions We did not observe a significant association between long-term exposure to low-concentration PM2.5 air pollution and IHD, HF, or AF.
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Affiliation(s)
- Joshua S. Jones
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Lee Nedkoff
- School of Population and Global Health, The University of Western Australia, Crawley, Western Australia, Australia
- Victor Chang Cardiac Research Institute, Sydney, New South Wales, Australia
| | - Jane S. Heyworth
- School of Population and Global Health, The University of Western Australia, Crawley, Western Australia, Australia
- Centre for Air Pollution, Energy and Health, Glebe, New South Wales, Australia
| | - Osvaldo P. Almeida
- Western Australian Centre for Health and Ageing, Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Leon Flicker
- Western Australian Centre for Health and Ageing, Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Jonathan Golledge
- Queensland Research Centre for Peripheral Vascular Disease, College of Medicine and Dentistry, James Cook University, Townsville, Queensland, Australia
- The Department of Vascular and Endovascular Surgery, Townsville University Hospital, Townsville, Queensland, Australia
- The Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Queensland, Australia
| | - Graeme J. Hankey
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
- Perron Institute for Neurological and Translational Science, Perth, Western Australia, Australia
| | - Elizabeth H. Lim
- School of Population and Global Health, The University of Western Australia, Crawley, Western Australia, Australia
| | - Mark Nieuwenhuijsen
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Bu B. Yeap
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth, Western Australia, Australia
- Harry Perkins Institute of Medical Research, Robin Warren Drive, Murdoch, Western Australia, Australia
| | - Michelle L. Trevenen
- Western Australian Centre for Health and Ageing, Medical School, The University of Western Australia, Perth, Western Australia, Australia
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Khomenko S, Pisoni E, Thunis P, Bessagnet B, Cirach M, Iungman T, Barboza EP, Khreis H, Mueller N, Tonne C, de Hoogh K, Hoek G, Chowdhury S, Lelieveld J, Nieuwenhuijsen M. Spatial and sector-specific contributions of emissions to ambient air pollution and mortality in European cities: a health impact assessment. Lancet Public Health 2023; 8:e546-e558. [PMID: 37393093 DOI: 10.1016/s2468-2667(23)00106-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2023] [Revised: 05/11/2023] [Accepted: 05/16/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND Ambient air pollution is a major risk to health and wellbeing in European cities. We aimed to estimate spatial and sector-specific contributions of emissions to ambient air pollution and evaluate the effects of source-specific reductions in pollutants on mortality in European cities to support targeted source-specific actions to address air pollution and promote population health. METHODS We conducted a health impact assessment of data from 2015 for 857 European cities to estimate source contributions to annual PM2·5 and NO2 concentrations using the Screening for High Emission Reduction Potentials for Air quality tool. We evaluated contributions from transport, industry, energy, residential, agriculture, shipping, and aviation, other, natural, and external sources. For each city and sector, three spatial levels were considered: contributions from the same city, the rest of the country, and transboundary. Mortality effects were estimated for adult populations (ie, ≥20 years) following standard comparative risk assessment methods to calculate the annual mortality preventable on spatial and sector-specific reductions in PM2·5 and NO2. FINDINGS We observed strong variability in spatial and sectoral contributions among European cities. For PM2·5, the main contributors to mortality were the residential (mean contribution of 22·7% [SD 10·2]) and agricultural (18·0% [7·7]) sectors, followed by industry (13·8% [6·0]), transport (13·5% [5·8]), energy (10·0% [6·4]), and shipping (5·5% [5·7]). For NO2, the main contributor to mortality was transport (48·5% [SD 15·2]), with additional contributions from industry (15·0% [10·8]), energy (14·7% [12·9]), residential (10·3% [5·0]), and shipping (9·7% [12·7]). The mean city contribution to its own air pollution mortality was 13·5% (SD 9·9) for PM2·5 and 34·4% (19·6) for NO2, and contribution increased among cities of largest area (22·3% [12·2] for PM2·5 and 52·2% [19·4] for NO2) and among European capitals (29·9% [12·5] for PM2·5 and 62·7% [14·7] for NO2). INTERPRETATION We estimated source-specific air pollution health effects at the city level. Our results show strong variability, emphasising the need for local policies and coordinated actions that consider city-level specificities in source contributions. FUNDING Spanish Ministry of Science and Innovation, State Research Agency, Generalitat de Catalunya, Centro de Investigación Biomédica en red Epidemiología y Salud Pública, and Urban Burden of Disease Estimation for Policy Making 2023-2026 Horizon Europe project.
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Affiliation(s)
- Sasha Khomenko
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Enrico Pisoni
- European Commission, Joint Research Centre, Ispra, Italy
| | | | | | - Marta Cirach
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Tamara Iungman
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Evelise Pereira Barboza
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Haneen Khreis
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Natalie Mueller
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Cathryn Tonne
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Kees de Hoogh
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland
| | - Gerard Hoek
- Institute for Risk Assessment Sciences, Utrecht University, Utrecht, Netherlands
| | | | | | - Mark Nieuwenhuijsen
- Institute for Global Health, Barcelona, Spain; Department of Experimental and Health Sciences, Universitat Pompeu Fabra, Barcelona, Spain; CIBER Epidemiología y Salud Pública, Madrid, Spain.
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6
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Li P, Wu J, Wang R, Liu H, Zhu T, Xue T. Source sectors underlying PM 2.5-related deaths among children under 5 years of age in 17 low- and middle-income countries. Environ Int 2023; 172:107756. [PMID: 36669285 DOI: 10.1016/j.envint.2023.107756] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 01/11/2023] [Accepted: 01/14/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND Fine particulate matter (PM2.5) from different source sectors might differ in toxicity. However, data from large-scale studies on vulnerable children in low- and middle-income countries (LMICs) are insufficient. OBJECTIVE To analyze the association of under-five death (U5D) with long-term exposure to PM2.5 from different sources. METHOD We evaluated demographic and health survey data for 79,995 babies born in 2017 in 16 Asian and African LMICs (AA-LMICs) and a Latin America low-income country (i.e., Haiti). Long-term exposure to PM2.5 was assessed by a well-established product that attributed the annual concentration to 20 source sectors in 2017. The associations of survival during < 5-year periods with each source-specific concentration of PM2.5 were analyzed by Cox regression with multiple adjustments. We derived a multiple-pollutant ridge regression model to estimate the joint exposure-response function (JERF) between U5D and PM2.5 mixtures. To evaluate how sources affected PM2.5 toxicity, we evaluated the number of U5Ds attributable to PM2.5 based on the source profiles for 88 AA-LMICs. RESULTS According to the single-pollutant model, the risk of U5D increased by 7% (95% confidence interval [CI]: 5%, 9%) for each 10 μg/m3 increment in total PM2.5 concentration. The model performance was lower than that of the multiple-pollutant ridge regression model. For each 10 μg/m3 increment in PM2.5, the excess risk of U5D ranged from 6% (95% CI: 4%, 9%) in Nepal to 10% (95% CI: 6%, 14%) in Mauritania. Based on the JERF, PM2.5 contributed to 817,647 (95% CI: 585,729, 1,050,439), i.e., 28.0% (95% CI: 20.1%, 35.8%), of all U5Ds across the 88 AA-LMICs. The PM2.5-related U5Ds were mostly attributable to PM2.5 produced by desert dust, followed by solid biofuel combustion and open fires. CONCLUSION The average toxicity of PM2.5 varied by source profile, which should be taken into consideration when planning public health interventions. For some AA LMICs, natural sources of PM2.5 had the most significant health effects, and should not be ignored to ensure the protection of child health.
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Affiliation(s)
- Pengfei Li
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China; Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China; National Institute of Health Data Science, Peking University, Beijing 100191, China
| | - Jingyi Wu
- Advanced Institute of Information Technology, Peking University, Hangzhou 311215, China.
| | - Ruohan Wang
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China.
| | - Hengyi Liu
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China.
| | - Tong Zhu
- College of Environmental Sciences and Engineering, Peking University, Beijing 100086, China; Center for Environment and Health, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
| | - Tao Xue
- Institute of Reproductive and Child Health / National Health Commission Key Laboratory of Reproductive Health and Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Centre, Beijing 100191, China; Center for Environment and Health, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
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7
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Xie M, Lu X, Ding F, Cui W, Zhang Y, Feng W. Evaluating the influence of constant source profile presumption on PMF analysis of PM 2.5 by comparing long- and short-term hourly observation-based modeling. Environ Pollut 2022; 314:120273. [PMID: 36170893 DOI: 10.1016/j.envpol.2022.120273] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 08/31/2022] [Accepted: 09/21/2022] [Indexed: 06/16/2023]
Abstract
Hourly PM2.5 speciation data have been widely used as an input of positive matrix factorization (PMF) model to apportion PM2.5 components to specific source-related factors. However, the influence of constant source profile presumption during the observation period is less investigated. In the current work, hourly concentrations of PM2.5 water-soluble inorganic ions, bulk organic and elemental carbon, and elements were obtained at an urban site in Nanjing, China from 2017 to 2020. PMF analysis based on observation data during specific pollution (firework combustion, sandstorm, and winter haze) and emission-reduction (COVID-19 pandemic) periods was compared with that using the whole 4-year data set (PMFwhole). Due to the lack of data variability, event-based PMF solutions did not separate secondary sulfate and nitrate. But they showed better performance in simulating average concentrations and temporal variations of input species, particularly for primary source markers, than the PMFwhole solution. After removing event data, PMF modeling was conducted for individual months (PMFmonth) and the 4-year period (PMF4-year), respectively. PMFmonth solutions reflected varied source profiles and contributions and reproduced monthly variations of input species better than the PMF4-year solution, but failed to capture seasonal patterns of secondary salts. Additionally, four winter pollution days were selected for hour-by-hour PMF simulations, and three sample sizes (500, 1000, and 2000) were tested using a moving window method. The results showed that using short-term observation data performed better in reflecting immediate changes in primary sources, which will benefit future air quality control when primary PM emissions begin to increase.
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Affiliation(s)
- Mingjie Xie
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China.
| | - Xinyu Lu
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Feng Ding
- Nanjing Environmental Monitoring Center of Jiangsu Province, 175 Huju Road, Nanjing, 210013, China
| | - Wangnan Cui
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Yuanyuan Zhang
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
| | - Wei Feng
- Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, School of Environmental Science and Engineering, Nanjing University of Information Science & Technology, 219 Ningliu Road, Nanjing, 210044, China
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8
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Wang Z, Hu B, Zhang C, Atkinson PM, Wang Z, Xu K, Chang J, Fang X, Jiang Y, Shi Z. How the Air Clean Plan and carbon mitigation measures co-benefited China in PM 2.5 reduction and health from 2014 to 2020. Environ Int 2022; 169:107510. [PMID: 36099757 DOI: 10.1016/j.envint.2022.107510] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 08/18/2022] [Accepted: 09/06/2022] [Indexed: 06/15/2023]
Abstract
China implemented a stringent Air Clean Plan (ACP) since 2013 to address environmental and health risks caused by ambient fine particulate matter (PM2.5). However, the policy effectiveness of ACP and co-benefits of carbon mitigation measures to environment and health are still largely unknown. Using satellite-based PM2.5 products produced in our previous study, concentration-response functions, and the logarithmic mean Divisia index (LMDI) method, we analyzed the spatiotemporal dynamics of premature deaths attributable to PM2.5 exposure, and quantitatively estimated the policy benefits of ACP and carbon mitigation measures. We found the annual PM2.5 concentrations in China decreased by 33.65 % (13.41 μg m-3) from 2014 to 2020, accompanied by a decrease in PM2.5-attributable premature deaths of 0.23 million (95 % confidence interval (CI): 0.22-0.27), indicating the huge benefits of China ACP for human health and environment. However, there were still 1.12 million (95 % CI: 0.79-1.56) premature deaths caused by the exposure of PM2.5 in mainland China in 2020. Among all ACP measures, clean production (contributed 55.98 % and 51.14 % to decrease in PM2.5 and premature deaths attributable to PM2.5) and energy consumption control (contributed 32.58 % and 29.54 % to decrease in PM2.5 and premature deaths attributable to PM2.5) made the largest contribution during the past seven years. Nevertheless, the environmental and health benefits of ACP are not fully synergistic in different regions, and the effectiveness of ACP measures reduced from 2018 to 2020. The co-effects of CO2 and PM2.5 has become one of the major drivers for PM2.5 and premature deaths reduction since 2018, confirming the clear environment and health co-benefits of carbon mitigation measures. Our study suggests, with the saturation of clean production and source control, more targeted region-specific strategies and synergistic air pollution-carbon mitigation measures are critical to achieving the WHO's Air Quality Guideline target and the UN's Sustainable Development Goal Target in China.
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Affiliation(s)
- Zhige Wang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Bifeng Hu
- Department of Land Resource Management, School of Tourism and Urban Management, Jiangxi University of Finance and Economics, Nanchang 330013, China
| | - Ce Zhang
- Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK; UK Centre for Ecology & Hydrology, Library Avenue, Bailrigg, Lancaster LA1 4AP, UK
| | - Peter M Atkinson
- Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK; Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A Datun Road, Beijing 100101, China
| | - Zifa Wang
- LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Kang Xu
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Jinfeng Chang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Biodiversity and Natural Resources (BNR), International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
| | - Xuekun Fang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Center for Global Change Science, Massachusetts Institute of Technology, Cambridge, MA 02139, United States
| | - Yefeng Jiang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Zhou Shi
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China; Key Laboratory of Environment Remediation and Ecological Health, Ministry of Education, College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China.
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