1
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Liu X, Zhang X, Wang T, Jin B, Wu L, Lara R, Monge M, Reche C, Jaffrezo JL, Uzu G, Dominutti P, Darfeuil S, Favez O, Conil S, Marchand N, Castillo S, de la Rosa JD, Stuart G, Eleftheriadis K, Diapouli E, Gini MI, Nava S, Alves C, Wang X, Xu Y, Green DC, Beddows DCS, Harrison RM, Alastuey A, Querol X. PM 10-bound trace elements in pan-European urban atmosphere. ENVIRONMENTAL RESEARCH 2024; 260:119630. [PMID: 39019137 DOI: 10.1016/j.envres.2024.119630] [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: 05/14/2024] [Revised: 07/08/2024] [Accepted: 07/15/2024] [Indexed: 07/19/2024]
Abstract
Although many studies have discussed the impact of Europe's air quality, very limited research focused on the detailed phenomenology of ambient trace elements (TEs) in PM10 in urban atmosphere. This study compiled long-term (2013-2022) measurements of speciation of ambient urban PM10 from 55 sites of 7 countries (Switzerland, Spain, France, Greece, Italy, Portugal, UK), aiming to elucidate the phenomenology of 20 TEs in PM10 in urban Europe. The monitoring sites comprised urban background (UB, n = 26), traffic (TR, n = 10), industrial (IN, n = 5), suburban background (SUB, n = 7), and rural background (RB, n = 7) types. The sampling campaigns were conducted using standardized protocols to ensure data comparability. In each country, PM10 samples were collected over a fixed period using high-volume air samplers. The analysis encompassed the spatio-temporal distribution of TEs, and relationships between TEs at each site. Results indicated an annual average for the sum of 20 TEs of 90 ± 65 ng/m3, with TR and IN sites exhibiting the highest concentrations (130 ± 66 and 131 ± 80 ng/m3, respectively). Seasonal variability in TEs concentrations, influenced by emission sources and meteorology, revealed significant differences (p < 0.05) across all monitoring sites. Estimation of TE concentrations highlighted distinct ratios between non-carcinogenic and carcinogenic metals, with Zn (40 ± 49 ng/m3), Ti (21 ± 29 ng/m3), and Cu (23 ± 35 ng/m3) dominating non-carcinogenic TEs, while Cr (5 ± 7 ng/m3), and Ni (2 ± 6 ng/m3) were prominent among carcinogenic ones. Correlations between TEs across diverse locations and seasons varied, in agreement with differences in emission sources and meteorological conditions. This study provides valuable insights into TEs in pan-European urban atmosphere, contributing to a comprehensive dataset for future environmental protection policies.
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Affiliation(s)
- Xiansheng Liu
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
| | - Xun Zhang
- Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, 100048, China; State Key Laboratory of Resources and Environmental Information System, Beijing, China.
| | - Tao Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science & Engineering, Fudan University, Shanghai, 200433, China.
| | - Bowen Jin
- Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, 100048, China
| | - Lijie Wu
- Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer and Artificial Intelligence, Beijing Technology and Business University, Beijing, 100048, China
| | - Rosa Lara
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
| | - Marta Monge
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
| | - Jean-Luc Jaffrezo
- Univ. Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP, IGE, UMR 5001, 38000, Grenoble, France
| | - Gaelle Uzu
- Univ. Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP, IGE, UMR 5001, 38000, Grenoble, France
| | - Pamela Dominutti
- Univ. Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP, IGE, UMR 5001, 38000, Grenoble, France
| | - Sophie Darfeuil
- Univ. Grenoble Alpes, IRD, CNRS, INRAE, Grenoble INP, IGE, UMR 5001, 38000, Grenoble, France
| | - Olivier Favez
- INERIS, Parc Technologique Alata, BP 2, 60550, Verneuil-en-Halatte, France; Laboratoire central de surveillance de la qualité de l'air (LCSQA), 60550, Verneuil-en-Halatte, France
| | - Sébastien Conil
- ANDRA DISTEC/EES Observatoire Pérenne de l'Environnement, F-55290, Bure, France
| | | | - Sonia Castillo
- Department of Applied Physics, University of Granada, 18011, Granada, Spain; Andalusian Institute of Earth System Research, IISTA-CEAMA, University of Granada, 18006, Granada, Spain
| | - Jesús D de la Rosa
- Associate Unit CSIC-UHU Atmospheric Pollution, University of Huelva, 21071, Huelva, Spain
| | - Grange Stuart
- Swiss Federal Laboratories for Materials Science and Technology, Dübendorf, CH, Switzerland
| | - Konstantinos Eleftheriadis
- ENRACT, Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Ag. Paraskevi, Athens, Greece
| | - Evangelia Diapouli
- ENRACT, Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Ag. Paraskevi, Athens, Greece
| | - Maria I Gini
- ENRACT, Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310, Ag. Paraskevi, Athens, Greece
| | - Silvia Nava
- INFN Division of Florence and Department of Physics and Astronomy, University of Florence, via G.Sansone 1, 50019, Sesto Fiorentino, Italy
| | - Célia Alves
- Department of Environment and Planning, Centre for Environmental and Marine Studies (CESAM), University of Aveiro, 3810-193, Aveiro, Portugal
| | - Xianxia Wang
- School of Management, Minzu University of China, Beijing, 100081, China
| | - Yiming Xu
- School of Grassland Science, Beijing Forestry University, Beijing, 100083, China
| | - David C Green
- MRC Centre for Environment and Health, Environmental Research Group, Imperial College London, United Kingdom
| | - David C S Beddows
- School of Geography Earth and Environmental Sciences, University of Birmingham, B15 2TT, Birmingham, United Kingdom
| | - Roy M Harrison
- School of Geography Earth and Environmental Sciences, University of Birmingham, B15 2TT, Birmingham, United Kingdom
| | - Andrés Alastuey
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), 08034, Barcelona, Spain
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2
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Azimi F, Hafezi F, Ghaderpoori M, Kamarehie B, Karami MA, Sorooshian A, Baghani AN. Temporal characteristics and health effects related to NO 2, O 3, and SO 2 in an urban area of Iran. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 349:123975. [PMID: 38615834 DOI: 10.1016/j.envpol.2024.123975] [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: 02/07/2024] [Revised: 03/22/2024] [Accepted: 04/11/2024] [Indexed: 04/16/2024]
Abstract
This study reports on temporal variations of NO2, O3, and SO2 pollutants and their related health effects in urban air of Khorramabad, Iran using AirQ 2.2.3 software. Based on data between 2015 and 2021, hourly NO2, O3, and SO2 concentrations increase starting at 6:00 a.m. local time until 9:00 p.m., 3:00 p.m., and 7:00 p.m. local time, respectively, before gradually decreasing. The highest monthly NO2, O3, and SO2 concentrations are observed in October, August, and September, respectively. Annual median NO2, O3, and SO2 concentrations range between 17 ppb and 38.8 ppb, 17.5 ppb-36.6 ppb, and ∼14 ppb-30.8 ppb, respectively. Two to 93 days and 17-156 days between 2015 and 2021 exhibit daily concentrations of NO2 and SO2 ≤ WHO AQGs, respectively, while 187-294 days have 8-h maximum O3 concentrations ≤ WHO AQGs. The mean excess mortality ascribed to respiratory mortality, cardiovascular mortality, hospital admissions for COPD, and acute myocardial infraction are 121, 603, 39, and 145 during 2015-2021, respectively. O3 is found to exert more significant health effects compared to SO2 and NO2, resulting in higher cardiovascular mortality. The gradual increase in NO2 and possibly O3 over the study period is suspected to be due to economic sanctions, while SO2 decreased due to regulatory activity. Sustainable control strategies such as improving fuel quality, promoting public transportation and vehicle retirement, applying subsidies for purchase of electric vehicles, and application of European emission standards on automobiles can help decrease target pollutant levels in ambient air of cities in developing countries.
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Affiliation(s)
- Faramarz Azimi
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Fariba Hafezi
- Department of Environmental Health Engineering, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Mansour Ghaderpoori
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Bahram Kamarehie
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Mohammad Amin Karami
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, University of Arizona, Tucson, AZ, USA; Department of Hydrology and Atmospheric Sciences, University of Arizona, Tucson, AZ, USA
| | - Abbas Norouzian Baghani
- Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran.
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3
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Wu S, Yan X, Yao J, Zhao W. Quantifying the scale-dependent relationships of PM 2.5 and O 3 on meteorological factors and their influencing factors in the Beijing-Tianjin-Hebei region and surrounding areas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 337:122517. [PMID: 37678736 DOI: 10.1016/j.envpol.2023.122517] [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: 06/13/2023] [Revised: 08/28/2023] [Accepted: 09/03/2023] [Indexed: 09/09/2023]
Abstract
To investigate the variations of PM2.5 and O3 and their synergistic effects with influencing factors at different time scales, we employed Bayesian estimator of abrupt seasonal and trend change to analyze the nonlinear variation process of PM2.5 and O3. Wavelet coherence and multiple wavelet coherence were utilized to quantify the coupling oscillation relationships of PM2.5 and O3 on single/multiple meteorological factors in the time-frequency domain. Furthermore, we combined this analysis with the partial wavelet coherence to quantitatively evaluate the influence of atmospheric teleconnection factors on the response relationships. The results obtained from this comprehensive analysis are as follows: (1) The seasonal component of PM2.5 exhibited a change point, which was most likely to occur in January 2017. The trend component showed a discontinuous decline and had a change point, which was most likely to appear in February 2017. The seasonal component of O3 did not exhibit a change point, while the trend component showed a discontinuous rise with two change points, which were most likely to occur in July 2018 and May 2017. (2) The phase and coherence relationships of PM2.5 and O3 on meteorological factors varied across different time scales. Stable phase relationships were observed on both small- and large-time scales, whereas no stable phase relationship was formed on medium scales. On all-time scales, sunshine duration was the best single variable for explaining PM2.5 variations and precipitation was the best single variable explaining O3 variations. When compared to single meteorological factors, the combination of multiple meteorological factors significantly improved the ability to explain variations in PM2.5 and O3 on small-time scales. (3) Atmospheric teleconnection factors were important driving factors affecting the response relationships of PM2.5 and O3 on meteorological factors and they had greater impact on the relationship at medium-time scales compared to small- and large-time scales.
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Affiliation(s)
- Shuqi Wu
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048, China.
| | - Xing Yan
- State Key Laboratory of Remote Sensing Science, College of Global Change and Earth System Science, Beijing Normal University, Beijing, 100875, China.
| | - Jiaqi Yao
- Academy of Eco-civilization Development for Jing-Jin-Ji Megalopolis, Tianjin Normal University, Tianjin, 300382, China.
| | - Wenji Zhao
- School of Resource, Environment and Tourism, Capital Normal University, Beijing, 100048, China.
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4
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Liu X, Hadiatullah H, Zhang X, Trechera P, Savadkoohi M, Garcia-Marlès M, Reche C, Pérez N, Beddows DCS, Salma I, Thén W, Kalkavouras P, Mihalopoulos N, Hueglin C, Green DC, Tremper AH, Chazeau B, Gille G, Marchand N, Niemi JV, Manninen HE, Portin H, Zikova N, Ondracek J, Norman M, Gerwig H, Bastian S, Merkel M, Weinhold K, Casans A, Casquero-Vera JA, Gómez-Moreno FJ, Artíñano B, Gini M, Diapouli E, Crumeyrolle S, Riffault V, Petit JE, Favez O, Putaud JP, Santos SMD, Timonen H, Aalto PP, Hussein T, Lampilahti J, Hopke PK, Wiedensohler A, Harrison RM, Petäjä T, Pandolfi M, Alastuey A, Querol X. Ambient air particulate total lung deposited surface area (LDSA) levels in urban Europe. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 898:165466. [PMID: 37451445 DOI: 10.1016/j.scitotenv.2023.165466] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 06/16/2023] [Accepted: 07/09/2023] [Indexed: 07/18/2023]
Abstract
This study aims to picture the phenomenology of urban ambient total lung deposited surface area (LDSA) (including head/throat (HA), tracheobronchial (TB), and alveolar (ALV) regions) based on multiple path particle dosimetry (MPPD) model during 2017-2019 period collected from urban background (UB, n = 15), traffic (TR, n = 6), suburban background (SUB, n = 4), and regional background (RB, n = 1) monitoring sites in Europe (25) and USA (1). Briefly, the spatial-temporal distribution characteristics of the deposition of LDSA, including diel, weekly, and seasonal patterns, were analyzed. Then, the relationship between LDSA and other air quality metrics at each monitoring site was investigated. The result showed that the peak concentrations of LDSA at UB and TR sites are commonly observed in the morning (06:00-8:00 UTC) and late evening (19:00-22:00 UTC), coinciding with traffic rush hours, biomass burning, and atmospheric stagnation periods. The only LDSA night-time peaks are observed on weekends. Due to the variability of emission sources and meteorology, the seasonal variability of the LDSA concentration revealed significant differences (p = 0.01) between the four seasons at all monitoring sites. Meanwhile, the correlations of LDSA with other pollutant metrics suggested that Aitken and accumulation mode particles play a significant role in the total LDSA concentration. The results also indicated that the main proportion of total LDSA is attributed to the ALV fraction (50 %), followed by the TB (34 %) and HA (16 %). Overall, this study provides valuable information of LDSA as a predictor in epidemiological studies and for the first time presenting total LDSA in a variety of European urban environments.
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Affiliation(s)
- Xiansheng Liu
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain.
| | | | - Xun Zhang
- Beijing Key Laboratory of Big Data Technology for Food Safety, School of Computer Science and Engineering, Beijing Technology and Business University, Beijing, China; Hotan Normal College. Hotan 848000, Xinjiang, China.
| | - Pedro Trechera
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Marjan Savadkoohi
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain; Department of Mining, Industrial and ICT Engineering (EMIT), Manresa School of Engineering (EPSEM), Universitat Politècnica de Catalunya (UPC), 08242 Manresa, Spain
| | - Meritxell Garcia-Marlès
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain; Department of Applied Physics-Meteorology, University of Barcelona, Barcelona, Spain
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Noemí Pérez
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | | | - Imre Salma
- Institute of Chemistry, Eötvös Loránd University, Budapest, Hungary
| | - Wanda Thén
- Hevesy György Ph.D. School of Chemistry, Eötvös Loránd University, Budapest, Hungary
| | - Panayiotis Kalkavouras
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, Greece; Institute for Environmental Research & Sustainable Development, National Observatory of Athens, Athens, Greece
| | - Nikos Mihalopoulos
- Environmental Chemical Processes Laboratory, Department of Chemistry, University of Crete, Heraklion, Greece; Institute for Environmental Research & Sustainable Development, National Observatory of Athens, Athens, Greece
| | - Christoph Hueglin
- Laboratory for Air Pollution and Environmental Technology, Swiss Federal Laboratories for Materials Science and Technology (EMPA), Duebendorf, Switzerland
| | - David C Green
- MRC Centre for Environment and Health, Environmental Research Group, Imperial College London, UK; NIHR HPRU in Environmental Exposures and Health, Imperial College London, UK
| | - Anja H Tremper
- MRC Centre for Environment and Health, Environmental Research Group, Imperial College London, UK
| | - Benjamin Chazeau
- Aix Marseille Univ., CNRS, LCE, Marseille, France; Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen, Switzerland
| | - Grégory Gille
- AtmoSud, Regional Network for Air Quality Monitoring of Provence-Alpes-Côte-d'Azur, Marseille, France
| | | | - Jarkko V Niemi
- Helsinki Region Environmental Services Authority (HSY), Helsinki, Finland
| | - Hanna E Manninen
- Helsinki Region Environmental Services Authority (HSY), Helsinki, Finland
| | - Harri Portin
- Helsinki Region Environmental Services Authority (HSY), Helsinki, Finland
| | - Nadezda Zikova
- Institute of Chemical Process Fundamentals, v.v.i. Academy of Sciences of the Czech Republic Rozvojova, Prague, Czech Republic
| | - Jakub Ondracek
- Institute of Chemical Process Fundamentals, v.v.i. Academy of Sciences of the Czech Republic Rozvojova, Prague, Czech Republic
| | - Michael Norman
- Environment and Health Administration, SLB-analys, Stockholm, Sweden
| | - Holger Gerwig
- German Environment Agency (UBA), Dessau-Roßlau, Germany
| | - Susanne Bastian
- Saxon State Office for Environment, Agriculture and Geology (LfULG), Dresden, Germany
| | - Maik Merkel
- Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
| | - Kay Weinhold
- Leibniz Institute for Tropospheric Research (TROPOS), Leipzig, Germany
| | - Andrea Casans
- Andalusian Institute for Earth System Research (IISTA-CEAMA), University of Granada, Granada, Spain
| | - Juan Andrés Casquero-Vera
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain; Andalusian Institute for Earth System Research (IISTA-CEAMA), University of Granada, Granada, Spain
| | | | | | - Maria Gini
- ENRACT, Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310 Ag. Paraskevi, Athens, Greece
| | - Evangelia Diapouli
- ENRACT, Institute of Nuclear and Radiological Science & Technology, Energy & Safety, NCSR Demokritos, 15310 Ag. Paraskevi, Athens, Greece
| | - Suzanne Crumeyrolle
- Univ. Lille, CNRS, UMR 8518 Laboratoire d'Optique Atmosphérique (LOA), Lille, France
| | - Véronique Riffault
- IMT Nord Europe, Institut Mines-Télécom, Université de Lille, Centre for Energy and Environment, 59000, Lille, France
| | - Jean-Eudes Petit
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/Orme des Merisiers, Gif-sur-Yvette, France
| | - Olivier Favez
- Institut national de l'environnement industriel et des risques (INERIS), Parc Technologique Alata BP2, Verneuil-en-Halatte, France
| | | | | | - Hilkka Timonen
- Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland
| | - Pasi P Aalto
- Institute for Atmospheric and Earth System Research (INAR), Faculty of Science, University of Helsinki, Finland
| | - Tareq Hussein
- Institute for Atmospheric and Earth System Research (INAR), Faculty of Science, University of Helsinki, Finland; Environmental and Atmospheric Research Laboratory, Department of Physics, School of Science, The University of Jordan, Amman 11942, Jordan
| | - Janne Lampilahti
- Institute for Atmospheric and Earth System Research (INAR), Faculty of Science, University of Helsinki, Finland
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | | | - Roy M Harrison
- Division of Environmental Health and Risk Management, School of Geography, Earth and Environmental Sciences University of Birmingham, Edgbaston, Birmingham, United Kingdom; Department of Environmental Sciences, Faculty of Meteorology, Environment and Arid Land Agriculture, King Abdulaziz University, Jeddah, Saudi Arabia
| | - Tuukka Petäjä
- Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA
| | - Marco Pandolfi
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Andrés Alastuey
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
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5
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Khajehpour H, Taksibi F, Hassanvand MS. Comparative review of ambient air PM 2.5 source apportioning studies in Tehran. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2023; 21:21-34. [PMID: 37159743 PMCID: PMC10163186 DOI: 10.1007/s40201-023-00855-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/19/2023] [Indexed: 05/11/2023]
Abstract
Rapid urbanization and consuming lifestyles have intensified air pollution in urban areas. Air pollution in megacities has imposed severe environmental damages to human health. Proper management of the issue necessitates identification of the share of emission sources. Therefore, numerous research works have studied the apportionment of the total emissions and observed concentrations among different emissions sources. In this research, a comprehensive review is conducted to compare the source apportioning results for ambient air PM2.5 in the megacity of Tehran, the capital of Iran. One hundred seventy-seven pieces of scientific literatures, published between 2005 and 2021, were reviewed. The reviewed research are categorized according to the source apportioning methods: emission inventory (EI), source apportionment (SA), and sensitivity analysis of the concentration to the emission sources (SNA). The possible reasons for inconsistency among the results are discussed according to the scope of the studies and the implemented methods. Although 85% of the reviewed original estimates identify that mobile sources contribute to more thant 60% of Tehran air pollution, the distribution of vehicle types and modes are clearly inconsistent among the EI studies. Our review suggests that consistent results in the SA studies in different locations in central Tehran may indicate the reliability of this method for the identification of the type and share of the emission sources. In contrast, differences among the geographical and sectoral coverage of the EI studies and the disparities among the emission factors and activity data have caused significant deviations among the reviewed EI studies. Also, it is shown that the results of the SNA studies are highly dependent on the categorization type, model capabilities and EI presumptions and data input to the pollutant dispersion modelings. As a result, integrated source apportioning in which the three methods complement each other's results is necessary for consistent air pollution management in megacities. Supplementary information The online version contains supplementary material available at 10.1007/s40201-023-00855-0.
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Affiliation(s)
- Hossein Khajehpour
- Department of Energy Engineering, Sharif University of Technology, Tehran, Iran
| | - Farzaneh Taksibi
- Institute for the Environment, University of North Carolina at Chapel Hill, Chapel Hill, NC USA
| | - Mohammad Sadegh Hassanvand
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, 8th Floor, No. 1547, North Kargar Avenue, Tehran, Iran
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6
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Faridi S, Krzyzanowski M, Cohen AJ, Malkawi M, Moh'd Safi HA, Yousefian F, Azimi F, Naddafi K, Momeniha F, Niazi S, Amini H, Künzli N, Shamsipour M, Mokammel A, Roostaei V, Hassanvand MS. Ambient Air Quality Standards and Policies in Eastern Mediterranean Countries: A Review. Int J Public Health 2023; 68:1605352. [PMID: 36891223 PMCID: PMC9986936 DOI: 10.3389/ijph.2023.1605352] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2022] [Accepted: 01/23/2023] [Indexed: 02/22/2023] Open
Abstract
Objectives: National ambient air quality standards (NAAQS) are critical tools for controlling air pollution and protecting public health. We designed this study to 1) gather the NAAQS for six classical air pollutants: PM2.5, PM10, O3, NO2, SO2, and CO in the Eastern Mediterranean Region (EMR) countries, 2) compare those with the updated World Health Organizations Air Quality Guidelines (WHO AQGs 2021), 3) estimate the potential health benefits of achieving annual PM2.5 NAAQS and WHO AQGs per country, and 4) gather the information on air quality policies and action plans in the EMR countries. Methods: To gather information on the NAAQS, we searched several bibliographic databases, hand-searched the relevant papers and reports, and analysed unpublished data on NAAQS in the EMR countries reported from these countries to the WHO/Regional office of the Eastern Mediterranean/Climate Change, Health and Environment Unit (WHO/EMR/CHE). To estimate the potential health benefits of reaching the NAAQS and AQG levels for PM2.5, we used the average of ambient PM2.5 exposures in the 22 EMR countries in 2019 from the Global Burden of Disease (GBD) dataset and AirQ+ software. Results: Almost all of the EMR countries have national ambient air quality standards for the critical air pollutants except Djibouti, Somalia, and Yemen. However, the current standards for PM2.5 are up to 10 times higher than the current health-based WHO AQGs. The standards for other considered pollutants exceed AQGs as well. We estimated that the reduction of annual mean PM2.5 exposure level to the AQG level (5 μg m-3) would be associated with a decrease of all natural-cause mortality in adults (age 30+) by 16.9%-42.1% in various EMR countries. All countries would even benefit from the achievement of the Interim Target-2 (25 μg m-3) for annual mean PM2.5: it would reduce all-cause mortality by 3%-37.5%. Less than half of the countries in the Region reported having policies relevant to air quality management, in particular addressing pollution related to sand and desert storms (SDS) such as enhancing the implementation of sustainable land management practices, taking measures to prevent and control the main factors of SDS, and developing early warning systems as tools to combat SDS. Few countries conduct studies on the health effects of air pollution or on a contribution of SDS to pollution levels. Information from air quality monitoring is available for 13 out of the 22 EMR countries. Conclusion: Improvement of air quality management, including international collaboration and prioritization of SDS, supported by an update (or establishment) of NAAQSs and enhanced air quality monitoring are essential elements for reduction of air pollution and its health effects in the EMR.
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Affiliation(s)
- Sasan Faridi
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.,Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Michal Krzyzanowski
- Environmental Research Group, School of Public Health, Imperial College London, London, United Kingdom
| | - Aaron J Cohen
- Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, United States.,Boston University School of Public Health, Boston, MA, United States.,Health Effects Institute, Boston, MA, United States
| | - Mazen Malkawi
- World Health Organization/Regional Office of the Eastern Mediterranean/Climate Change, Health and Environment Unit (WHO/EMR/CHE), Amman, Jordan
| | - Heba Adel Moh'd Safi
- World Health Organization/Regional Office of the Eastern Mediterranean/Climate Change, Health and Environment Unit (WHO/EMR/CHE), Amman, Jordan
| | - Fatemeh Yousefian
- Department of Environmental Health Engineering, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Faramarz Azimi
- Environmental Health Research Center, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Kazem Naddafi
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.,Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Momeniha
- Center for Solid Waste Research, Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Sadegh Niazi
- International Laboratory for Air Quality and Health, Faculty of Science, School of Earth and Atmospheric Sciences, Queensland University of Technology (QUT), Brisbane, QLD, Australia
| | - Heresh Amini
- Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Nino Künzli
- Swiss Tropical and Public Health Institute, Allschwil, Switzerland.,University of Basel, Basel, Switzerland
| | - Mansour Shamsipour
- Department of Research Methodology and Data Analysis, Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Adel Mokammel
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Vahid Roostaei
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadegh Hassanvand
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.,Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
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7
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Liu Z, Liu C, Cui Y, Liu J, Zhang H, Feng Y, Wang N, Jiao M, Kang Z, Xu X, Zhao J, Wang C, Zou D, Liang L, Wu Q, Hao Y. Air pollution and refraining from visiting health facilities: a cross-sectional study of domestic migrants in China. BMC Public Health 2022; 22:2007. [PMID: 36324110 PMCID: PMC9628112 DOI: 10.1186/s12889-022-14401-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2022] [Accepted: 10/19/2022] [Indexed: 11/07/2022] Open
Abstract
BACKGROUND Local environmental factors are associated with health and healthcare-seeking behaviors. However, there is a paucity in the literature documenting the link between air pollution and healthcare-seeking behaviors. This study aimed to address the gap in the literature through a cross-sectional study of domestic migrants in China. METHODS Data were extracted from the 2017 China Migrants Dynamic Survey (n = 10,051) and linked to the official air pollution indicators measured by particulate matter (PM2.5 and PM10) and air quality index (AQI) in the residential municipalities (n = 310) of the study participants over the survey period. Probit regression models were established to determine the association between air pollution and refraining from visiting health facilities after adjustment for variations in the predisposing, enabling and needs factors. Thermal inversion intensity was adopted as an instrumental variable to overcome potential endogeneity. RESULTS One unit (µg/m3) increase in monthly average PM2.5 was associated with 1.8% increase in the probability of refraining from visiting health facilities. The direction and significance of the link remained unchanged when PM2.5 was replaced by AQI or PM10. Higher probability of refraining from visiting health facilities was also associated with overwork (β = 0.066, p = 0.041) and good self-related health (β = 0.171, p = 0.006); whereas, lower probability of refraining from visiting health facilities was associated with short-distance (inter-county) migration (β=-0.085, p = 0.048), exposure to health education (β=-0.142, p < 0.001), a high sense of local belonging (β=-0.082, p = 0.018), and having hypertension/diabetes (β=-0.169, p = 0.005). CONCLUSION Air pollution is a significant predictor of refraining from visiting health facilities in domestic migrants in China.
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Affiliation(s)
- Zhixin Liu
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Chaojie Liu
- grid.1018.80000 0001 2342 0938Department of Public Health, School of Psychology and Public Health, La Trobe University, 3086 Melbourne, VIC Australia
| | - Yu Cui
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Junping Liu
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Huanyu Zhang
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Yajie Feng
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Nan Wang
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Mingli Jiao
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Zheng Kang
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Xiaoxue Xu
- grid.410736.70000 0001 2204 9268Department of Health Economics, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Juan Zhao
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China ,grid.416208.90000 0004 1757 2259Southwest Hospital, Third Military Medical University (Army Medical University), 400000 Chongqing, China
| | - Chen Wang
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China ,grid.417298.10000 0004 1762 4928Xinqiao Hospital, Third Military Medical University (Army Medical University), 400037 Chongqing, China
| | - Dandan Zou
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Libo Liang
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Qunhong Wu
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
| | - Yanhua Hao
- grid.410736.70000 0001 2204 9268Department of Social Medicine, School of Health Management, Harbin Medical University, 150081 Harbin, China
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8
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Xu R, Li Z, Zhu X, Guo C, Su Q, Peng J, Wang Z, Qian Y, Li X, Xu Q, Wei Y. Acute effects of exposure to fine particulate matter and ozone on lung function, inflammation and oxidative stress in healthy adults. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 243:114013. [PMID: 36037633 DOI: 10.1016/j.ecoenv.2022.114013] [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: 06/17/2022] [Revised: 08/12/2022] [Accepted: 08/21/2022] [Indexed: 06/15/2023]
Abstract
Both fine particulate matter (PM2.5) and ozone (O3) may have adverse effects on human health. However, previous studies on the effects of air pollutants mainly have focused on susceptible population, and evidence on healthy young adults is limited. We aimed to examine the associations of the two main air pollutants (PM2.5 and O3) with lung function, inflammation and oxidative stress in healthy young adults. We recruited 30 healthy young adults for a longitudinal panel study in Beijing and implemented health examination seven times, including lung function (FEV1 and PEF) and biomarkers of inflammation and oxidative stress (i.e. C-reactive protein, CRP; interleukin-6, IL-6; malondialdehyde, MDA) from December 2019 to May 2021. Hourly ambient air pollutants data were obtained from the closest air quality monitoring station. Linear mixed-effect model was applied to explore the associations between air pollutants and lung function, inflammation and oxidative stress. We observed higher PM2.5 exposure was associated with decrement in lung function and increment in CRP and MDA. Each 10 μg/m3 increase in PM2.5 (lag 2 day) is associated with a 17.06 ml (95% CI: -31.53, -2.58) decrease in FEV1, 46.34 ml/s (95% CI: -76.41, -16.27) decrease in PEF and increments of 2.86% (95% CI: 1.47%, 4.27%) in CRP, 1.63% (95% CI: 0.14%, 3.14%) in MDA respectively. However, there is no significant association between ozone exposure and health indicators. The study suggested that short-term exposure to PM2.5 may decrease lung function and induce inflammation and oxidative stress in healthy adults, but there is no association between O3 and each outcome.
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Affiliation(s)
- Rongrong Xu
- Center for Global Health, School of Public Health, Nanjing Medical University, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Zhigang Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Xiaojing Zhu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Chen Guo
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Qiaoqiao Su
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Jianhao Peng
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Zhanshan Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Yan Qian
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Xiaoqian Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Qiujin Xu
- Center for Global Health, School of Public Health, Nanjing Medical University, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China.
| | - Yongjie Wei
- Center for Global Health, School of Public Health, Nanjing Medical University, China; State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, China.
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9
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Chen Q, Chen Q, Wang Q, Xu R, Liu T, Liu Y, Ding Z, Sun H. Particulate matter and ozone might trigger deaths from chronic ischemic heart disease. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 242:113931. [PMID: 35914398 DOI: 10.1016/j.ecoenv.2022.113931] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 07/26/2022] [Accepted: 07/27/2022] [Indexed: 06/15/2023]
Abstract
AIMS To study the association between short-term exposure to air pollutants and mortality of Chronic Ischemic Heart Disease (CIHD). METHODS Using a case-crossover design, we investigated 148,443 CIHD deaths from 2015 to 2020 in Jiangsu Province, China. Exposure to six ambient pollutants, including PM10, PM2.5, NO2, CO, SO2, and O3, was assessed by extracting daily concentrations from validated 10 km × 10 km pollutant grids at each subject's residential address. A conditional logistic regression approach was used to explore the exposure-response relationship with adjustment for temperature and relative humidity. We calculated the Population Attributable Fractions (PAFs) and the attributable deaths number of CIHD. RESULTS An increase of 10 μg/m3 in PM10 and PM2.5 exposure was associated with a 1.16% (95% CI: 0.85-1.48%) and 1.80% (1.36-2.24%) increase in CIHD mortality, respectively. A threshold value of 123 µg/m3 was identified for the association between O3 exposure and CIHD mortality. Controlling for PM2.5, each increase of 10 µg/m3 in O3 (>threshold) was statistically significantly associated with a 0.94% (0.19-1.71%) increase in CIHD mortality, however there was no association between NO2, SO2, CO exposure and CIHD mortality. Reducing PM2.5, PM10 and O3 to the WHO air quality guidelines would prevent 6.16% (95% CI: 4.70-7.58%), 4.30% (3.18-5.43%) and 1.29% (0.48-4.20%) of CIHD deaths, respectively. During the warm season, mortality and PAFs of CIHD associated with PM2.5, PM10, and O3 were significantly higher. CONCLUSIONS Short-term exposure to ambient PM2.5, PM10, and O3 might trigger deaths from CIHD. These findings indicate that the premature deaths of CIHD patients can be alleviated by reducing exposure to polluted air.
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Affiliation(s)
- Qing Chen
- Department of Planning and Finance, First People's Hospital of Lianyungang City 6, Zhenhua East Road, Lianyungang, Jiangsu, 222000, China
| | - Qi Chen
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, Jiangsu, 210009, China
| | - Qingqing Wang
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, Jiangsu, 210009, China
| | - Ruijun Xu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 74 Zhongshan Second Road, Guangzhou, Guangdong 510080, China
| | - Tingting Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 74 Zhongshan Second Road, Guangzhou, Guangdong 510080, China
| | - Yuewei Liu
- Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, 74 Zhongshan Second Road, Guangzhou, Guangdong 510080, China
| | - Zhen Ding
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, Jiangsu, 210009, China
| | - Hong Sun
- Department of Environment and Health, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, Jiangsu, 210009, China.
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10
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Health burden and economic loss attributable to ambient PM 2.5 in Iran based on the ground and satellite data. Sci Rep 2022; 12:14386. [PMID: 35999246 PMCID: PMC9399101 DOI: 10.1038/s41598-022-18613-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Accepted: 08/16/2022] [Indexed: 01/02/2023] Open
Abstract
We estimated mortality and economic loss attributable to PM2·5 air pollution exposure in 429 counties of Iran in 2018. Ambient PM2.5-related deaths were estimated using the Global Exposure Mortality Model (GEMM). According to the ground-monitored and satellite-based PM2.5 data, the annual mean population-weighted PM2·5 concentrations for Iran were 30.1 and 38.6 μg m-3, respectively. We estimated that long-term exposure to ambient PM2.5 contributed to 49,303 (95% confidence interval (CI) 40,914-57,379) deaths in adults ≥ 25 yr. from all-natural causes based on ground monitored data and 58,873 (95% CI 49,024-68,287) deaths using satellite-based models for PM2.5. The crude death rate and the age-standardized death rate per 100,000 population for age group ≥ 25 year due to ground-monitored PM2.5 data versus satellite-based exposure estimates was 97 (95% CI 81-113) versus 116 (95% CI 97-135) and 125 (95% CI 104-145) versus 149 (95% CI 124-173), respectively. For ground-monitored and satellite-based PM2.5 data, the economic loss attributable to ambient PM2.5-total mortality was approximately 10,713 (95% CI 8890-12,467) and 12,792.1 (95% CI 10,652.0-14,837.6) million USD, equivalent to nearly 3.7% (95% CI 3.06-4.29) and 4.3% (95% CI 3.6-4.5.0) of the total gross domestic product in Iran in 2018.
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11
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Fazlzadeh M, Hassanvand MS, Nabizadeh R, Shamsipour M, Salarifar M, Naddafi K. Effect of portable air purifier on indoor air quality: reduced exposure to particulate matter and health risk assessment. ENVIRONMENTAL MONITORING AND ASSESSMENT 2022; 194:638. [PMID: 35925421 DOI: 10.1007/s10661-022-10255-w] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 06/28/2022] [Indexed: 06/15/2023]
Abstract
We sought to investigate the impact of air purifiers in the removal of particular matter (PM)10, PM2.5, PM1, and particle number concentration (PNC) in the indoor air of dormitories located at Iran's largest medical university, Tehran University of Medical Sciences. Twelve rooms were selected and randomly assigned to two rooms: sham air purifier system deployed room (SR) and true air purifier system deployed room (TR). All study samples were drawn simultaneously from assigned rooms using portable GRIMM dust monitors for 24 h. The PM monitors of air were positioned in the middle of each room next to the air purifier at the height of the breathing zone (1.5 m in height). The mean PM10, PM2.5, PM1, and PNC removal efficiency in rooms with and without a smoker were measured to be 40.7 vs 83.8%, 31.2 vs 78.4%, 29.9 vs 72.3%, and 44.3 vs 75.6%, respectively. The results showed that smoking is an important influencing factor on the indoor air quality; smoking lowered the removal efficiency of PM10, PM2.5, PM1, and PNC by 43%, 47%, 43%, and 31%, respectively. An air purifier could decline the PM10 and PM2.5 even lower than the WHO 24-h guideline level in non-smoker rooms. This study revealed that using household air purifiers in rooms with smokers and non-smokers significantly reduces the non-carcinogenic risks of exposure to PM10 and PM2.5.
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Affiliation(s)
- Mehdi Fazlzadeh
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadegh Hassanvand
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Ramin Nabizadeh
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Mansour Shamsipour
- Department of Research Methodology and Data Analysis, Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Mojtaba Salarifar
- Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Kazem Naddafi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.
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12
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Song J, Ding Z, Zheng H, Xu Z, Cheng J, Pan R, Yi W, Wei J, Su H. Short-term PM 1 and PM 2.5 exposure and asthma mortality in Jiangsu Province, China: What's the role of neighborhood characteristics? ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 241:113765. [PMID: 35753271 DOI: 10.1016/j.ecoenv.2022.113765] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2022] [Revised: 06/07/2022] [Accepted: 06/09/2022] [Indexed: 06/15/2023]
Abstract
BACKGROUND Evidence suggests that particulate matter (PM) with smaller particle sizes (such as PM1, PM with an aerodynamic diameter≤1 µm) may have more toxic health effects. However, the short-term association between PM1 and asthma mortality remains largely unknown. OBJECTIVE This study aimed to examine the short-term effects of PM1 and PM2.5 on asthma mortality, as well as to investigate how neighborhood characteristics modified this association. METHODS Daily data on asthma mortality were collected from 13 cities in Jiangsu Province, China, between 2016 and 2017. A time-stratified case-crossover design was attempted to examine the short-term effects of PM1 and PM2.5 on asthma mortality. Individual exposure levels of PM1 and PM2.5 on case and control days were determined based on individual's residential addresses. Stratified analyses by neighborhood characteristics (including green space, tree canopy, blue space, population density, nighttime light and street connectivity) were conducted to identify vulnerable living environments. RESULTS Mean daily concentrations of PM1 and PM2.5 on case days were 33.8 μg/m3 and 54.3 μg/m3. Each 10 μg/m3 increase in three-day-averaged (lag02) PM1 and PM2.5 concentrations were associated with an increase of 6.66% (95%CI:1.18%,12.44%) and 2.39% (95%CI: 0.05%-4.78%) asthma mortality, respectively. Concentration-response curves showed a consistent increase in daily asthma mortality with increasing PM1 and PM2.5 concentrations. Subgroup analyses indicated that the effect of PM1 appeared to be evident in neighborhood characteristics with high green space, low urbanization level and poor street connectivity. CONCLUSION This study suggested an association between short-term PM1 and PM2.5 exposures and asthma mortality. Several neighborhood characteristics (such as green space and physical supportive environment) that could modify the effect of PM1 on asthma mortality should be further explored.
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Affiliation(s)
- Jian Song
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Zhen Ding
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Hao Zheng
- Department of Environmental Health, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Zhiwei Xu
- School of Public Health, University of Queensland, Queensland, Australia
| | - Jian Cheng
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Rubing Pan
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Weizhuo Yi
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China
| | - Jing Wei
- Department of Atmospheric and Oceanic Science, Earth System Science Interdisciplinary Center, University of Maryland, College Park, MD, USA.
| | - Hong Su
- Department of Epidemiology and Health Statistics, School of Public Health, Anhui,Medical University, Hefei, Anhui 230032, China; Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, China.
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13
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Eslami B, Alipour S, Omranipour R, Naddafi K, Naghizadeh MM, Shamsipour M, Aryan A, Abedi M, Bayani L, Hassanvand MS. Air pollution exposure and mammographic breast density in Tehran, Iran: a cross-sectional study. Environ Health Prev Med 2022; 27:28. [PMID: 35786683 PMCID: PMC9283909 DOI: 10.1265/ehpm.22-00027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022] Open
Abstract
BACKGROUND Air pollution is one of the major public health challenges in many parts of the world possibly has an association with breast cancer. However, the mechanism is still unclear. This study aimed to find an association between exposure to six criteria ambient air pollutants (PM2.5, PM10, SO2, NO2, O3, and CO) and mammographic breast density (MBD), as one of the strongest predictors for developing breast cancer, in women living in Tehran, Iran. METHODS Participants were selected from women attending two university hospitals for screening mammography from 2019 to 2021. Breast density was rated by two expert radiologists. Individual exposures to 3-year ambient air pollution levels at the residence were estimated. RESULTS The final analysis in 791 eligible women showed that low and high breast density was detected in 34.8 and 62.2 of participants, respectively. Logistic regression analysis after considering all possible confounding factors represented that an increase in each unit of NO2 (ppb) exposure was associated with an increased risk of breast density with an OR equal to 1.04 (95CI: 1.01 to 1.07). Furthermore, CO level was associated with a decreasing breast density (OR = 0.40, 95CI = 0.19 to 0.86). None of the other pollutants were associated with breast density. CONCLUSION Higher MBD was associated with an increased level of NO2, as a marker of traffic-related air pollution. Furthermore, CO concentration was associated with a lower MBD, while other criteria air pollutants were not related to MBD. Further studies are needed to evaluate the association between ambient air pollutants with MBD.
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Affiliation(s)
- Bita Eslami
- Breast Diseases Research Center, Cancer Institute, Tehran University of Medical Science
| | - Sadaf Alipour
- Breast Diseases Research Center, Cancer Institute, Tehran University of Medical Science.,Department of Surgery, Arash Women's Hospital, Tehran University of Medical Sciences
| | - Ramesh Omranipour
- Breast Diseases Research Center, Cancer Institute, Tehran University of Medical Science.,Department of Surgical Oncology, Cancer Institute, Tehran University of Medical Sciences
| | - Kazem Naddafi
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences.,Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences
| | | | - Mansour Shamsipour
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences.,Department of Research Methodology and Data Analysis, Institute for Environmental Research (IER), Tehran University of Medical Sciences
| | - Arvin Aryan
- Department of Radiology, Advanced Diagnostic and Interventional Radiology Research Center, Imam Khomeini Hospital, Tehran University of Medical Sciences
| | - Mahboubeh Abedi
- Department of Radiology, Arash Women's Hospital, Tehran University of Medical Sciences
| | - Leila Bayani
- Department of Radiology, Arash Women's Hospital, Tehran University of Medical Sciences
| | - Mohammad Sadegh Hassanvand
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences.,Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences
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14
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Leo Hohenberger T, Che W, Sun Y, Fung JCH, Lau AKH. Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants. ENVIRONMENT INTERNATIONAL 2022; 165:107329. [PMID: 35660952 DOI: 10.1016/j.envint.2022.107329] [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: 01/20/2022] [Revised: 05/09/2022] [Accepted: 05/27/2022] [Indexed: 06/15/2023]
Abstract
For the monitoring of urban air pollution, smart sensors are often seen as a welcome addition to fixed-site monitoring (FSM) networks. Due to price and simple installation, increases in spatial representation are thought to be achieved by large numbers of these sensors, however, a number of sensor errors have been identified. Based on a high-resolution modelling system, up to 400 pseudo smart sensors were perturbated with the aim of simulating common sensor errors and added to the existing FSM network in Hong Kong, resulting in 1200 pseudo networks for PM2.5 and 1040 pseudo networks for NO2. For each pseudo network, population-weighted area representativeness (PWAR) was calculated based on similarity frequency. For PM2.5, improvements (up to 16%) to the high baseline representativeness (PWAR = 0.74) were achievable only by the addition of high-quality sensors and favourable environmental conditions. The baseline FSM network represents NO2 less well (PWAR = 0.52), as local emissions in the study domain resulted in high spatial pollution variation. Due to higher levels of pollution (population-weighted average 37.3 ppb) in comparison to sensor error ranges, smart sensors of a wider quality range were able to improve network representativeness (up to 42%). Marginal representativeness increases were found to exponentially decrease with existing sensor number. The quality and maintenance of added sensors had a stronger effect on overall network representativeness than the number of sensors added. Often, a small number of added sensors of a higher quality class led to larger improvements than hundreds of lower-class sensors. Whereas smart sensor performance and maintenance are important prerequisites particularly for developed cities where pollutant concentration is low and there is an existing FSM network, our study shows that for places with high pollutant variability and concentration such as encountered in some developing countries, smart sensors will provide benefits for understanding population exposure.
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Affiliation(s)
- Tilman Leo Hohenberger
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Wenwei Che
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China.
| | - Yuxi Sun
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China
| | - Jimmy C H Fung
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China; Department of Mathematics, The Hong Kong University of Science & Technology, Clear Water Bay, Hong Kong, China
| | - Alexis K H Lau
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China; Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong, China; Institute for the Environment, The Hong Kong University of Science & Technology, Clear Water Bay, Hong Kong, China
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15
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Faridi S, Brook RD, Yousefian F, Hassanvand MS, Nodehi RN, Shamsipour M, Rajagopalan S, Naddafi K. Effects of respirators to reduce fine particulate matter exposures on blood pressure and heart rate variability: A systematic review and meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2022; 303:119109. [PMID: 35271952 PMCID: PMC10411486 DOI: 10.1016/j.envpol.2022.119109] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2021] [Revised: 03/01/2022] [Accepted: 03/04/2022] [Indexed: 06/14/2023]
Abstract
Particulate-filtering respirators (PFRs) have been recommended as a practical personal-level intervention to protect individuals from the health effects of particulate matter exposure. However, the cardiovascular benefits of PFRs including improvements in key surrogate endpoints remain unclear. We performed a systematic review and meta-analysis of randomized studies (wearing versus not wearing PFRs) reporting the effects on blood pressure (BP) and heart rate variability (HRV). The search was performed on January 3, 2022 to identify published papers until this date. We queried three English databases, including PubMed, Web of Science Core Collection and Scopus. Of 527 articles identified, eight trials enrolling 312 participants (mean age ± standard deviation: 36 ± 19.8; 132 female) met our inclusion criteria for analyses. Study participants wore PFRs from 2 to 48 h during intervention periods. Wearing PFRs was associated with a non-significant pooled mean difference of -0.78 mmHg (95% confidence interval [CI]: -2.06, 0.50) and -0.49 mmHg (95%CI: -1.37, 0.38) in systolic and diastolic BP (SBP and DBP). There was a marginally significant reduction of mean arterial pressure (MAP) by nearly 1.1 mmHg (95%CI: -2.13, 0.01). The use of PFRs was associated with a significant increase of 38.92 ms2 (95%CI: 1.07, 76.77) in pooled mean high frequency (power in the high frequency band (0.15-0.4 Hz)) and a reduction in the low (power in the low frequency band (0.04-0.15Hz))-to-high frequency ratio [-0.14 (95%CI: -0.27, 0.00)]. Other HRV indices were not significantly changed. Our meta-analysis demonstrates modest or non-significant improvements in BP and many HRV parameters from wearing PFRs over brief periods. However, these findings are limited by the small number of trials as well as variations in experimental designs and durations. Given the mounting global public health threat posed by air pollution, larger-scale trials are warranted to elucidate more conclusively the potential health benefits of PFRs.
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Affiliation(s)
- Sasan Faridi
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | | | - Fatemeh Yousefian
- Department of Environmental Health Engineering, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Mohammad Sadegh Hassanvand
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Ramin Nabizadeh Nodehi
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mansour Shamsipour
- Department of Research Methodology and Data Analysis, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Kazem Naddafi
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran; Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
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16
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Maio S, Baldacci S, Tagliaferro S, Angino A, Parmes E, Pärkkä J, Pesce G, Maesano CN, Annesi-Maesano I, Viegi G. Urban grey spaces are associated with increased allergy in the general population. ENVIRONMENTAL RESEARCH 2022; 206:112428. [PMID: 34838570 DOI: 10.1016/j.envres.2021.112428] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 10/27/2021] [Accepted: 11/21/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND the built environment in urban areas may have side effects on children's respiratory health, whilst less is known for adulthood. AIM to assess the association between increasing exposure to grey spaces and allergic status in an adult general population sample. METHODS 2070 subjects (age range 15-84 yrs), living in Pisa/Cascina, Italy, were investigated in 1991-93 through a questionnaire on health status and risk factors, skin prick test (SPT), serum Immunoglobulins E (IgE), and serum antibodies to benzo(a)pyrene diol epoxide (BPDE)-DNA adducts. Land-cover exposure within a 1000 m buffer from each subject's home address was assessed through the CORINE Land Cover program (CLC 1990) within the FP7/HEALS project (2013-2018). Participants' residential addresses were geocoded and the proportion of surrounding grey spaces was calculated. Through logistic regression models, adjusting for potential confounding factors, the effect of a 10% increase in grey spaces exposure on allergic biomarkers/conditions was assessed; the relationship with serum antibodies to BPDE-DNA adducts positivity was also analyzed. RESULTS A 10% increase in grey spaces coverage was associated with a higher probability of having SPT positivity (OR 1.07, 95% CI 1.02-1.13), seasonal SPT positivity (OR 1.12, 1.05-1.19), polysensitization (OR 1.11, 1.04-1.19), allergic rhinitis (OR 1.10, 1.04-1.17), co-presence of SPT positivity and asthma/allergic rhinitis (OR 1.16, 1.08-1.25), asthma/allergic rhinitis (OR 1.06, 1.00-1.12), presence of serum antibodies to BPDE-DNA adducts positivity (OR 1.07, 1.01-1.14). CONCLUSIONS grey spaces have adverse effects on allergic status and are related to a biomarker of polycyclic aromatic hydrocarbons exposure in adulthood. Thus, they may be used as a proxy of urban environmental exposure.
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Affiliation(s)
- S Maio
- Pulmonary Environmental Epidemiology Unit, CNR Institute of Clinical Physiology, Pisa, Italy.
| | - S Baldacci
- Pulmonary Environmental Epidemiology Unit, CNR Institute of Clinical Physiology, Pisa, Italy
| | - S Tagliaferro
- Pulmonary Environmental Epidemiology Unit, CNR Institute of Clinical Physiology, Pisa, Italy
| | - A Angino
- Pulmonary Environmental Epidemiology Unit, CNR Institute of Clinical Physiology, Pisa, Italy
| | - E Parmes
- VTT Technical Research Centre of Finland Ltd, Espoo, Finland
| | - J Pärkkä
- VTT Technical Research Centre of Finland Ltd, Espoo, Finland
| | - G Pesce
- INSERM, Paris-Saclay University, UVSQ, Center for Research in Epidemiology and Population Health (CESP), Villejuif, France
| | - C N Maesano
- INSERM, Montpellier University, Institut Desbrest d'Épidémiologie et de Santé Publique, Montpellier, France
| | - I Annesi-Maesano
- INSERM, Montpellier University, Institut Desbrest d'Épidémiologie et de Santé Publique, Montpellier, France
| | - G Viegi
- Pulmonary Environmental Epidemiology Unit, CNR Institute of Clinical Physiology, Pisa, Italy; CNR Institute for Research and Biomedical Innovation, Palermo, Italy
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17
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Naghan DJ, Neisi A, Goudarzi G, Dastoorpoor M, Fadaei A, Angali KA. Estimation of the effects PM2.5, NO2, O3 pollutants on the health of Shahrekord residents based on AirQ + software during (2012-2018). Toxicol Rep 2022; 9:842-847. [PMID: 36561960 PMCID: PMC9764246 DOI: 10.1016/j.toxrep.2022.03.045] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2022] [Revised: 03/26/2022] [Accepted: 03/29/2022] [Indexed: 12/25/2022] Open
Abstract
Research objectives Intertwined with modern life, air pollution is not a new phenomenon. Air pollution imposes a significant number of deaths and disease complications on society, and therefore it is very important to determine the extent of its effects on health in any society. This study sought to evaluate the concentration and short-term and long-term excess mortality attributed to PM2.5, NO2 and O3 observed in Shahrekord. Procedure Hourly concentrations of PM2.5, O3, and NO2 measured at different stations of the Shahrekord Monitoring Network were obtained from the Shahrekord Department of Environment (DOE). Then, for different air quality monitoring stations, the average 24-hour PM2.5 concentration, the one-hour average NO2 concentration and the maximum 8-hour daily O3 concentration were calculated using Excel 2010. When the maximum 8-hour daily ozone level exceeds 35, it drops below 35 to calculate the SOMO35 index for modeling. Results The death rates of IHD, COPD, lung cancer and ALRI and stroke related to PM2.5 were 176, 7, 0, 10, 105, respectively. The effect of ozone on respiratory mortality was zero. During the study period in Shahrekord, no respiratory mortality was determined due to ozone and acute lower respiratory tract infection (ALRI). this study is first ever study on health effects of air pollution in shahrekord city. Conclusion A significant number of deaths due to air pollutants in Shahrekord have been reported. It can be concluded that by designing and implementing strategies and measures to control air pollution, both health effects and economic losses are prevented.
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Affiliation(s)
- Davood Jalili Naghan
- Department of Environmental Health Engineering, School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran,Corresponding author.
| | - Abdolkazem Neisi
- Environmental Health Department, Air pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Gholamreza Goudarzi
- Environmental Health Department, Air pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Maryam Dastoorpoor
- Department of Biostatistics and Epidemiology, Air pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Abdolmajid Fadaei
- Department of Environmental Health Engineering, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran
| | - Kambiz Ahmadi Angali
- Department of Biostatistics and Epidemiology, Air pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
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18
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Tao T, Shi Y, Gilbert KM, Liu X. Spatiotemporal variations of air pollutants based on ground observation and emission sources over 19 Chinese urban agglomerations during 2015-2019. Sci Rep 2022; 12:4293. [PMID: 35277593 PMCID: PMC8915768 DOI: 10.1038/s41598-022-08377-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Accepted: 03/07/2022] [Indexed: 12/03/2022] Open
Abstract
The "comparative attitude" of urban agglomerations involves multidimensional perspectives such as infrastructure, ecological protection, and air pollution. Based on monitoring station data, comparative studies of multispatial, multitimescale and multiemission pollution sources of air quality on 19 urban agglomerations during the 13th Five-Year Plan period in China were explored by mathematical statistics. The comparison results are all visualized and show that clean air days gradually increased and occurred mainly in summer, especially in South and Southwest China. PM2.5, PM10 and O3 were still the main primary pollutants. PM2.5 is mainly concentrated in December, January and February, and PM10 is mainly concentrated in October-November and March-April. The O3 pollution in the Pearl River Delta and Beibu Gulf urban agglomerations located in the south is mainly concentrated from August to November, which is different from others from May to September. Second, from 2015 to 2019, the increasing rate of O3 concentration in any hour is higher than that of particulate matter (PM). Diurnal trends in O3 concentration in all directions also showed a single peak, with the largest increments that appeared between 13:00 and 16:00, while the spatial distribution of this peak was significantly regional, earlier in the east but later in the west. Third, this analysis indicated that the annual average air quality index (AQI) showed a gradually decreasing trend outward, taking the Central Plain urban agglomeration as the center. The ambient air pollutants are gradually moving southward and mainly concentrated in the Central Plains urban agglomeration from 2015 to 2019. Furthermore, in each urban agglomeration, the cumulative emission of PM2.5 is consisted of the four average emissions, which is approximately 2.5 times of that of PM10, and industries are the main sources of PM2.5, PM10 and VOCs (volatile organic compounds). VOCs and NOX increased in half of the urban agglomerations, which are the reasons for the increase in ozone pollution. The outcomes of this study will provide targeted insights on pollution prevention in urban agglomerations in the future.
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Affiliation(s)
- Tianhui Tao
- College of Surveying and Geo-Informatics, Tongji University, Shanghai, 200092, China
| | - Yishao Shi
- College of Surveying and Geo-Informatics, Tongji University, Shanghai, 200092, China.
| | | | - Xinyi Liu
- Zhejiang Zhipu Engineering Technology Limited Company, Huzhou, 313000, Zhejiang, China
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19
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Tong Y, Gao J, Wang K, Jing H, Wang C, Zhang X, Liu J, Yue T, Wang X, Xing Y. Highly-resolved spatial-temporal variations of air pollutants from Chinese industrial boilers. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 289:117931. [PMID: 34426180 DOI: 10.1016/j.envpol.2021.117931] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Revised: 05/20/2021] [Accepted: 08/05/2021] [Indexed: 06/13/2023]
Abstract
Industrial boilers are a significant anthropogenic source of air pollutant emissions. In this study, a county-based atmospheric emission inventory of particulate matter (PM), PM10, PM2.5, SO2, NOx, organic carbon (OC) and elemental carbon (EC) from industrial boilers over mainland China in 2017 was developed for the first time, based on county-level activity data from ~61,000 coal-fired industrial boilers (CFIBs), ~44,000 biomass-fired industrial boilers (BFIBs), ~71,000 gas-fired industrial boilers (GFIBs) and ~9300 oil-fired industrial boilers (OFIBs), updated emission factors (EFs) and air pollution control device (APCD) efficiencies. The total national PM, PM2.5, PM10, SO2, NOx, OC and EC emissions from industrial boilers in 2017 were estimated to be 1,240, 347, 761, 1,648, 1,340, 13.1 and 15.8 kilotons (kt), respectively. Intensive air pollutant emissions from industrial boilers of more than 1000 kg/km2 were predominantly in north-eastern, northern and eastern China. CFIBs contributed the most (77.6-94.0 %) to air pollutant emissions because of their high air pollutant EFs and the large amounts of coal consumed. BFIBs were the second-highest contributor to national air pollutant emissions, with the contribution of BFIBs to PM2.5, OC and EC emissions in central and southern China reaching up to 42.1 %, 61.7 % and 45.5 %, respectively. There were seasonal peaks in monthly air pollutant emissions in heating regions. The overall uncertainty realting to the new emission inventory was estimated as -25.9 %-22.7 %. Significant air pollutant emission reductions were obtained from 2017 to 2030, and by 2030 the PM, PM10, PM2.5, SO2 and NOx emissions were forecast to decrease by 40.1-84.0 %, 41.6-84.3 %, 44.5-75.2 %, 44.5-75.2 % and 19.5-46.8 % compared to 2017, respectively, under four proposed scenarios. The results of this study showed that differentiated industrial boiler management measures should be developed according to the actual emission characteristics. This work developed a county-based atmospheric emission inventory of PM, PM10, PM2.5, SO2, NOx, OC and EC from Chinese industrial boilers in 2017 for the first time.
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Affiliation(s)
- Yali Tong
- Department of Air Pollution Control, Beijing Municipal Institute of Labour Protection, Beijing, 100054, China; Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, College of Environmental Science and Engineering, Ocean University of China, Qingdao, 266100, China; Key Laboratory of Land Surface Pattern and Simulation, Chinese Academy of Sciences, Beijing, 100101, China
| | - Jiajia Gao
- Department of Air Pollution Control, Beijing Municipal Institute of Labour Protection, Beijing, 100054, China
| | - Kun Wang
- Department of Air Pollution Control, Beijing Municipal Institute of Labour Protection, Beijing, 100054, China; Key Laboratory of Marine Environmental Science and Ecology, Ministry of Education, College of Environmental Science and Engineering, Ocean University of China, Qingdao, 266100, China
| | - Hong Jing
- China National Environmental Monitoring Centre, Beijing, 100012, China
| | - Chenlong Wang
- Department of Air Pollution Control, Beijing Municipal Institute of Labour Protection, Beijing, 100054, China
| | - Xiaoxi Zhang
- Department of Air Pollution Control, Beijing Municipal Institute of Labour Protection, Beijing, 100054, China
| | - Jieyu Liu
- Department of Air Pollution Control, Beijing Municipal Institute of Labour Protection, Beijing, 100054, China
| | - Tao Yue
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China.
| | - Xin Wang
- China National Environmental Monitoring Centre, Beijing, 100012, China
| | - Yi Xing
- School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing, 100083, China
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20
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Faridi S, Yousefian F, Janjani H, Niazi S, Azimi F, Naddafi K, Hassanvand MS. The effect of COVID-19 pandemic on human mobility and ambient air quality around the world: A systematic review. URBAN CLIMATE 2021; 38:100888. [PMID: 36536793 PMCID: PMC9750834 DOI: 10.1016/j.uclim.2021.100888] [Citation(s) in RCA: 24] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Revised: 05/18/2021] [Accepted: 06/13/2021] [Indexed: 05/19/2023]
Abstract
We conducted this systematic review to identify and appraise studies investigating the coronavirus disease 2019 (COVID-19) effect on ambient air pollution status worldwide. The review of studies was conducted using determined search terms via three major electronic databases (PubMed, Web of Science, and Scopus) according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. A total of 26 full-text studies were included in our analysis. The lockdown measures related to COVID-19 pandemic caused significant decreases in the concentrations of PM2.5, NO2, PM10, SO2 and CO globally in the range of 2.9%-76.5%, 18.0%-96.0%, 6.0%-75.0%, 6.8%-49.0% and 6.2%-64.8%, respectively. However, O3 concentration increased in the range of 2.4%-252.3%. The highest decrease of PM2.5 was found in 16 states of Malaysia (76.5%), followed by Zaragoza (Spain) with 58.0% and Delhi (India) with 53.1%. The highest reduction of NO2 was found in Salé city (Morocco) with 96.0%, followed by Mumbai (India) with 75.0%, India with 70.0%, Valencia (Spain) with 69.0%, and São Paulo (Brazil) with 68.0%, respectively. The highest increase of O3 was recorded for Milan (Italy) with 252.3% and 169.9% during the first and third phases of lockdown measures, and for Kolkata (India) with 87% at the second phase of lockdown measures. Owing to the lockdown restrictions in the studied countries and cities, driving and public transit as a proxy of human mobilities and the factors affecting emission sources of ambient air pollution decreased in the ranges of 30-88% and 45-94%, respectively. There was a considerable variation in the reduction of ambient air pollutants in the countries and cities as the degree of lockdown measures had varied there. Our results illustrated that the COVID-19 pandemic had provided lessons and extra motivations for comprehensive implementing policies to reduce air pollution and its health effects in the future.
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Affiliation(s)
- Sasan Faridi
- Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Yousefian
- Department of Environmental Health Engineering, Faculty of Health, Kashan University of Medical Sciences, Kashan, Iran
| | - Hosna Janjani
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Sadegh Niazi
- Queensland University of Technology (QUT), Faculty of Science, School of Earth and Atmospheric Siences, Brisbane 4001, Australia
| | - Faramarz Azimi
- Department of Environment Health Engineering, Environmental Health Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Kazem Naddafi
- Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadegh Hassanvand
- Centre for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
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21
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Seifi M, Rastkari N, Hassanvand MS, Naddafi K, Nabizadeh R, Nazmara S, Kashani H, Zare A, Pourpak Z, Hashemi SY, Yunesian M. Investigating the relationship between particulate matter and inflammatory biomarkers of exhaled breath condensate and blood in healthy young adults. Sci Rep 2021; 11:12922. [PMID: 34155256 PMCID: PMC8217428 DOI: 10.1038/s41598-021-92333-6] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2020] [Accepted: 06/08/2021] [Indexed: 12/15/2022] Open
Abstract
Inflammatory biomarkers in exhaled breath condensate (EBC) are measured to estimate the effects of air pollution on humans. The present study was conducted to investigate the relationship between particulate matter and inflammatory biomarkers in blood plasma and exhaled air in young adults. The obtained results were compared in two periods; i.e., winter and summer. GRIMM Dust Monitors were used to measure PM10, PM2.5, and PM1 in indoor and outdoor air. A total of 40 healthy young adults exhaling air condensate were collected. Then, biomarkers of interleukin-6 (IL-6), Nitrosothiols (RS-NOs), and Tumor necrosis factor-soluble receptor-II (sTNFRII) were measured by 96 wells method ELISA and commercial kits (HS600B R&D Kit and ALX-850–037-KI01) in EBC while interleukin-6 (IL-6), sTNFRII and White Blood Cell (WBC) were measured in blood plasma in two periods of February 2013 (winter) and May 2013 (summer). Significant association was found between particulate matter and the white blood cell count (p < 0.001), as well as plasma sTNFRII levels (p-value = 0.001). No significant relationship was found between particulate matter with RS-NOs (p = 0.128), EBC RSNOs (p-value = 0.128), and plasma IL-6 (p-value = 0.167). In addition, there was no significant relationship between interleukin-6 of exhaled air with interleukin-6 of plasma (p-value < 0.792 in the first period and < 0.890 in the second period). sTNFRII was not detected in EBC. Considering the direct effect between increasing some biomarkers in blood and EBC and particulate matter, it is concluded that air pollution causes this increasing.
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Affiliation(s)
- Morteza Seifi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Noushin Rastkari
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadegh Hassanvand
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Kazem Naddafi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Ramin Nabizadeh
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Shahrokh Nazmara
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Homa Kashani
- Department of Research Methodology and Data Analysis, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahad Zare
- Immunology, Asthma and Allergy Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Zahra Pourpak
- Immunology, Asthma and Allergy Research Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Seyed Yaser Hashemi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Masud Yunesian
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran. .,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.
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22
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Cardiovascular health effects of wearing a particulate-filtering respirator to reduce particulate matter exposure: a randomized crossover trial. J Hum Hypertens 2021; 36:659-669. [PMID: 34031547 DOI: 10.1038/s41371-021-00552-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Revised: 04/23/2021] [Accepted: 05/13/2021] [Indexed: 12/07/2022]
Abstract
This randomized crossover trial sought to determine whether wearing a high-efficiency particulate-filtering respirator (PFR) improves cardiovascular function over 48 h among healthy college students in Tehran. This trial was conducted from February 14th to 23rd, 2019 and twenty-six participants completed two 48-h intervention periods. Brachial blood pressure (BP) measured by 24-h ambulatory monitoring was the primary health outcome. Secondary outcomes included 48-h heart rate variability (HRV) indices, high-sensitive cardiac troponin (hs-TnT) and other biomarkers. The participants wore the PFR between 10.2 and 11.1 h while awake during the interventions. More than 80% of participants reported increased respiratory resistance while wearing the PFR due to a lack of an exhalation valve. There were no significant differences in brachial BP levels between subjects who wore PFR respirator and those did not. Except for high frequency (HF) power and heart rate (HR), no significant differences between interventions were observed for other HRV metrics. Wearing the PFR led to an increase of 66.0 ms2 (95% confidence interval [CI], 9.6-110.5) and 79.6 ms2 (95% CI, 19.0-140.1) in HF power during the first day when the two groups of participants wore the PFR. Night-time HR was significantly increased during the PFR intervention period. Other secondary outcomes were not significantly different between interventions. It is plausible that incomplete exposure reduction due to wearing the PFR less than half of the time or increased respiratory resistance mitigated potential health benefits. Additional trials are warranted to validate the CV protection of wearing PFRs in heavily-polluted cities.
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Abstract
Lung cancer is the most rapidly increasing malignancy worldwide with an estimated 2.1 million cancer cases in the latest, 2018 World Health Organization (WHO) report. The objective of this study was to investigate the association of air pollution and lung cancer, in Tehran, Iran. Residential area information of the latest registered lung cancer cases that were diagnosed between 2014 and 2016 (N = 1,850) were inquired from the population-based cancer registry of Tehran. Long-term average exposure to PM10, SO2, NO, NO2, NOX, benzene, toluene, ethylbenzene, m-xylene, p-xylene, o-xylene (BTEX), and BTEX in 22 districts of Tehran were estimated using land use regression models. Latent profile analysis (LPA) was used to generate multi-pollutant exposure profiles. Negative binomial regression analysis was used to examine the association between air pollutants and lung cancer incidence. The districts with higher concentrations for all pollutants were mostly in downtown and around the railway station. Districts with a higher concentration for NOx (IRR = 1.05, for each 10 unit increase in air pollutant), benzene (IRR = 3.86), toluene (IRR = 1.50), ethylbenzene (IRR = 5.16), p-xylene (IRR = 9.41), o-xylene (IRR = 7.93), m-xylene (IRR = 2.63) and TBTEX (IRR = 1.21) were significantly associated with higher lung cancer incidence. Districts with a higher multiple air-pollution profile were also associated with more lung cancer incidence (IRR = 1.01). Our study shows a positive association between air pollution and lung cancer incidence. This association was stronger for, respectively, p-xylene, o-xylene, ethylbenzene, benzene, m-xylene and toluene.
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Eskandari Z, Maleki H, Neisi A, Riahi A, Hamid V, Goudarzi G. Temporal fluctuations of PM 2.5 and PM 10, population exposure, and their health impacts in Dezful city, Iran. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2020; 18:723-731. [PMID: 33312597 PMCID: PMC7721840 DOI: 10.1007/s40201-020-00498-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Accepted: 06/09/2020] [Indexed: 05/28/2023]
Abstract
Morbidity and mortality impacts of particulate matter (PM) are globally important health critical parameters. In this ecological-descriptive study, the health impact of PM10 and PM2.5 associated with there temporal variations in Dezful city were assessed from 2013 to 2015. AirQ+ software handles the PM air pollutants by addressing impact evaluation and life table evaluation. We used a new method to analysis fine particles feature by using regular daily observations of PM10. In this method, relationship between PM2.5 and PM10 mass concentrations were analyzed and calculated. The annual average concentrations of PM10 were 147.1, 114.3 and 158.8 μg/m3, and the annual average concentration of PM2.5 were 57.8, 50.7 and 58.2 μg/m3 in 2013, 2014 and 2015, respectively. PM10 also had obvious diurnal variations with highest hourly concentrations in 13:00 and 22:00 but the lowest concentrations often occurred in 05:00 and 16:00. Unexpectedly, in weekends the concentration of PM pollutants appeared to have increased from 18:00 to midnight. The daily based analysis showed that there are 147 dusty days in the study period during which the most severe dusty day occurred in 2014. Over the study period, mean levels of PM10 and PM2.5 in both conditions were higher in 2015 compare to 2013 and 2014, which probably is due to higher frequency of dust storms in 2015. Hence, during 2015 and 2013 they're were higher morbidity and mortality compare to 2014 due to exposure to higher polluted air with PMs in all cases except lung cancer (LC).
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Affiliation(s)
- Zahra Eskandari
- Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Heidar Maleki
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- MS of Environmental Engineering, Faculty of Water Sciences Engineering, Shahid Chamran University of Ahvaz, Ahvaz, Iran
| | - Abdolkazem Neisi
- Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Atefeh Riahi
- Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Vafa Hamid
- Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Gholamreza Goudarzi
- Department of Environmental Health Engineering, School of Public Health, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
- Air Pollution and Respiratory Diseases Research Center, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
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Faridi S, Akbari H, Faridi H, Keshmiri S, Adibzadeh A. Human, Forest and vegetation health metrics of ground-level ozone (SOMO35, AOT40f and AOT40v) in Tehran. JOURNAL OF ENVIRONMENTAL HEALTH SCIENCE & ENGINEERING 2020; 18:1351-1358. [PMID: 33312647 PMCID: PMC7721827 DOI: 10.1007/s40201-020-00552-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/07/2020] [Accepted: 09/28/2020] [Indexed: 06/12/2023]
Abstract
PURPOSE We aimed to investigate the spatial O3 indices (SOMO35: annual sum of maximum daily 8-h ozone means over 35 ppb, AOT40: the accumulated exposure over an hourly threshold of 40 ppb during daylight hours between 8:00 and 20:00 in the growing seasons of plants) in Tehran (2019-2020). METHODS The data of ambient O3 concentrations, measured at twenty-three regulatory ambient air quality monitoring stations (AQMSs) in Tehran, were obtained. RESULTS The annual mean O3 concentrations were found to be 15.8-25.7 ppb; the highest and lowest annual mean concentration of ambient O3 were observed in Shahrdari 22 and Shahr-e-Rey stations, respectively. Spatial distribution of exposure to O3 across Tehran was in the range of 1.36-1.64; the highest O3 concentrations were observed in the northern, west and south-western parts of Tehran, while the central and south areas of Tehran city experienced low to moderate concentrations. The indices of SOMO35, AOT40f and AOT40v across AQMSs in Tehran was in the range of 1830-6437 ppb. Days, 10,613-39,505 ppb.h and 4979-16,804 ppb.h, respectively. For Tehran city, the indices of SOMO35 and AOT40f were 4138 ppb. days and 27,556 ppb.h respectively. Our results revealed that the value of SOMO35 across AQMSs of Tehran was higher than the recommended target value of 3000 ppb. days. CONCLUSIONS To reduce O3 pollution and its effects on both human and plants health, the governmental organizations should take appropriate sustainable control policies.
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Affiliation(s)
- Sasan Faridi
- Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Hesam Akbari
- Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Hamed Faridi
- Department of Public Health, School of Nursing and Midwifery Iranshahr University of Medical Sciences, Iranshahr, Iran
| | - Saeed Keshmiri
- Systems Environmental Health and Energy Research Center, The Persian Gulf Biomedical Sciences Research Institute, Bushehr University of Medical Sciences, Bushehr, Iran
- Faculty of Medicine, Bushehr University of Medical Sciences, Bushehr, Iran
| | - Amir Adibzadeh
- Health Research Center, Lifestyle Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
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Faridi S, Nodehi RN, Sadeghian S, Tajdini M, Hoseini M, Yunesian M, Nazmara S, Hassanvand MS, Naddafi K. Can respirator face masks in a developing country reduce exposure to ambient particulate matter? JOURNAL OF EXPOSURE SCIENCE & ENVIRONMENTAL EPIDEMIOLOGY 2020; 30:606-617. [PMID: 32317771 DOI: 10.1038/s41370-020-0222-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/31/2019] [Revised: 03/14/2020] [Accepted: 03/27/2020] [Indexed: 05/16/2023]
Abstract
Respirator face masks (RFMs) as a personal-level intervention is increasingly being utilized to reduce ambient particulate matter (PM) exposure, globally. We tested the effectiveness of 50 commercially available ones in reducing the exposure of ambient particle number concentrations (PNC), PM10, PM2.5, and PM1 (PM ≤ 10, 2.5, and 1 μm in diameter, respectively) in a traffic-affected urban site in Tehran. To examine the efficiency of RFMs, we applied a specific experimental setup including vacuum pumps, dummy heads, connecting tubes, glass chambers, and GRIMM Aerosol Spectrometer to measure all metrics after dummy heads. The average effectiveness of RFMs was in the range of 0.7-83.5%, 3.5-68.1%, 0.8-46.1%, and 0.4-32.2% in reducing ambient PNC, PM10, PM2.5, and PM1, respectively. Considering all metrics, the highest effectiveness was observed always for Biomask, followed by 3 M 9332, due to their well-designed physical characteristics (e.g., adjustable nose clip for any face/nose shape, and size, soft inner material in the nose panel to provide a secure seal against leakage, adjustable or elasticated straps/ear loops to better adjust on any face). Biomask reduced ambient PM10 with a mean value of 94.6 μg m-3 (minimum-maximum: 51.7-100.3 μg m-3), whereas it filtered on average just 29.0 μg m-3 (25.7-43.5 μg m-3) of ambient PM2.5 and 18.2 μg m-3 (14.7-21.8 μg m-3) of PM1. A fuzzy analytical hierarchy process to find the most important design-related factors of RFMs affecting their effectiveness, which showed the exhalation valve and its diaphragm (20.4%), nose clip (19.7%), and cheek flaps (18.6%) are ranked as the main design-related variables. The fuzzy technique for order preference by similarity to ideal solution indicated that Biomask and 3M 9332 had scores of 1 and 0.97, the highest scores compared with other RFMs. This study provides crucial evidence-based results to elucidate the effectiveness and design-related factors of RFMs in real-environmental circumstances.
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Affiliation(s)
- Sasan Faridi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Ramin Nabizadeh Nodehi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Saeed Sadeghian
- Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Masih Tajdini
- Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Hoseini
- Research Center for Health Sciences, Institute of Health, Department of Environmental Health, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran
| | - Masud Yunesian
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
- Center for Research Methodology and Data Analysis (CRMDA), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Shahrokh Nazmara
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohammad Sadegh Hassanvand
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.
| | - Kazem Naddafi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.
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Yousefian F, Faridi S, Azimi F, Aghaei M, Shamsipour M, Yaghmaeian K, Hassanvand MS. Temporal variations of ambient air pollutants and meteorological influences on their concentrations in Tehran during 2012-2017. Sci Rep 2020; 10:292. [PMID: 31941892 PMCID: PMC6962207 DOI: 10.1038/s41598-019-56578-6] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2019] [Accepted: 11/17/2019] [Indexed: 01/18/2023] Open
Abstract
We investigated temporal variations of ambient air pollutants and the influences of meteorological parameters on their concentrations using a robust method; convergent cross mapping; in Tehran (2012–2017). Tehran citizens were consistently exposed to annual PM2.5, PM10 and NO2 approximately 3.0–4.5, 3.5–4.5 and 1.5–2.5 times higher than the World Health Organization air quality guideline levels during the period. Except for O3, all air pollutants demonstrated the lowest and highest concentrations in summertime and wintertime, respectively. The highest O3 concentrations were found on weekend (weekend effect), whereas other ambient air pollutants had statistically significant (P < 0.05) daily variations in which higher concentrations were observed on weekdays compared to weekend (holiday effect). Hourly O3 concentration reached its peak at 3.00 p.m., though other air pollutants displayed two peaks; morning and late night. Approximately 45% to 65% of AQI values were in the subcategory of unhealthy for sensitive groups and PM2.5 was the responsible air pollutant in Tehran. Amongst meteorological factors, temperature was the key influencing factor for PM2.5 and PM10 concentrations, while nebulosity and solar radiation exerted major influences on ambient SO2 and O3 concentrations. Additionally, there is a moderate coupling between wind speed and NO2 and CO concentrations.
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Affiliation(s)
- Fatemeh Yousefian
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Sasan Faridi
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.,Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran
| | - Faramarz Azimi
- Nutrition Health Research Centre, Department of Environment Health, School of Health and Nutrition, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Mina Aghaei
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran
| | - Mansour Shamsipour
- Department of Research Methodology and Data Analysis, Institute for Environmental Research, Tehran University of Medical Sciences, Tehran, Iran
| | - Kamyar Yaghmaeian
- Department of Environmental Health Engineering, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.
| | - Mohammad Sadegh Hassanvand
- Center for Air Pollution Research (CAPR), Institute for Environmental Research (IER), Tehran University of Medical Sciences, Tehran, Iran.
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