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Schleicher NJ, Weiss DJ. Identification of atmospheric particulate matter derived from coal and biomass burning and from non-exhaust traffic emissions using zinc isotope signatures. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 329:121664. [PMID: 37085103 DOI: 10.1016/j.envpol.2023.121664] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2023] [Revised: 03/30/2023] [Accepted: 04/17/2023] [Indexed: 05/03/2023]
Abstract
Improving urban air quality is a global challenge. To implement successful abatement measures that reduce atmospheric particulate matter (APM) and associated metal concentrations, precise source apportionment is needed. For this, apportioning contributions from coal and biomass burning and differentiating these from non-exhaust traffic emissions in urban APM is critical. Recent studies characterising the metal isotope composition of urban APM, and potential source materials suggested that non-traditional isotope systems could prove unique fingerprinting tools. Zinc isotopes should be able to separate APM derived from uncontrolled combustion (fly ash, isotopically heavy) from non-exhaust traffic sources (tyre and brake wear, intermediate) and from controlled industrial emissions (flue gas, light). To test this hypothesis, we determined zinc isotope ratios of APM (TSP, PM2.5, PM1) in Beijing (coal combustion for residential heating) and Varanasi (biomass burning in pre-monsoon periods). In Beijing, δ66ZnLyon values of PM2.5 ranged from -0.41 to +1.01‰ in 2015 (avg = +0.25 ± 0.50‰, n = 19). Aerosols (including TSP, PM2.5 and PM1 samples) from the heating period were significantly (t-test, p < 0.001) heavier (avg = +0.90 ± 0.12‰, n = 7) than those from the non-heating period (avg = +0.14 ± 0.36‰, n = 23). Average δ66ZnLyon values of PM2.5 in Varanasi in spring 2015 were +0.82 ± 0.11‰ (n = 4). Extent and direction of isotope fractionation is in line with that expected from theoretical models and the isotope signatures observed agree with previously determined ratios of source materials. Our study links for the first time comprehensively the heavy zinc isotope compositions in APM to coal and biomass burning and shows that zinc isotope compositions of aerosols can discriminate between non-exhaust traffic and combustion sources.
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Affiliation(s)
- Nina J Schleicher
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, Prince Consort Road, SW7 2AZ, London, United Kingdom.
| | - Dominik J Weiss
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, Prince Consort Road, SW7 2AZ, London, United Kingdom
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2
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Morgan JLL, Shauchuk A, Meyers JL, Altemeier A, Qiao X, Jones M, Smith ED, Jiang J. Quantifying the Deposition of Airborne Particulate Matter Pollution on Skin Using Elemental Markers. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2020; 54:15958-15967. [PMID: 33210540 DOI: 10.1021/acs.est.0c03901] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Airborne particulate matter (PM) pollution is an environmental and health concern. The health impact of PM pollution has typically focused on the respiratory system. The impact of PM pollution on skin has been largely understudied due to the lack of a quantitative method to measure the deposition on skin. This manuscript presents a method to quantify PM pollution on skin using elemental markers as a proxy for PM. Skin tape strips were collected from forehead and buttock of 100 outdoor workers in Beijing, China. Skin samples were analyzed for 19 elemental markers using inductively coupled plasma mass spectrometry. To determine the specific elemental signature of PM for the region, air samples were collected over 7 days for PM < 2.5 μm (PM2.5) and analyzed for the same 19 elements as the skin samples. An enrichment factor was calculated for each element and the potential source was evaluated. Using the elemental markers unique to PM pollution for the region, the PM concentration deposited on skin was determined to be 0.621-2.53 μg PM2.5 /cm2. This method can be re-applied in different regions and the PM concentration on skin can inform future studies on the health impact of air pollution on skin.
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Affiliation(s)
- Jennifer L L Morgan
- Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, Ohio 45040, United States
| | - Andrei Shauchuk
- Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, Ohio 45040, United States
| | - Jessa L Meyers
- Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, Ohio 45040, United States
| | - Amy Altemeier
- Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, Ohio 45040, United States
| | - Xiaohui Qiao
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
| | - Maiysha Jones
- Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, Ohio 45040, United States
| | - Edward D Smith
- Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, Ohio 45040, United States
| | - Jingkun Jiang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing, 100084, China
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Difference of Airborne Particulate Matter Concentration in Urban Space with Different Green Coverage Rates in Baoji, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2019; 16:ijerph16081465. [PMID: 31027177 PMCID: PMC6517868 DOI: 10.3390/ijerph16081465] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/18/2019] [Revised: 04/18/2019] [Accepted: 04/23/2019] [Indexed: 11/17/2022]
Abstract
With the acceleration of urbanization and industrialization, the problem of airborne particulate pollution has become more and more serious. Green areas in urban spaces with different green coverage rates in Baoji City were selected to quantitatively compare the effects and differences of month, time, temperature, humidity, wind velocity, vegetation structure, and area of site on PM2.5 and PM10 concentration. The results showed that increasing the urban green coverage rate will help to improve the green area's reduction of airborne particulate matter concentration and the selected factors affecting the green area's reduction ability were discrepant in urban spaces with different green coverage rates. With the decrease of the green coverage rate, the purification effect of green area itself on air particles was weakened, and other factors, such as meteorological conditions and human activities, became the dominant influencing factors. Vegetation structure only had significant effects on the concentration of PM2.5 and PM10 in green areas of urban space with a green coverage rate greater than 75%. The concentration of PM2.5 and PM10 were lowest in the partly closed green area of one-layered coniferous trees and the closed green area of one-layered mixed trees. The research shows that green areas in urban spaces with different green coverage rates have different reduction effects on the concentration of airborne particles, which provides a theoretical basis and reference for the optimization of green area structures and to improve air quality effectively in the future.
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Zhao Z, Lv S, Zhang Y, Zhao Q, Shen L, Xu S, Yu J, Hou J, Jin C. Characteristics and source apportionment of PM 2.5 in Jiaxing, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2019; 26:7497-7511. [PMID: 30659487 DOI: 10.1007/s11356-019-04205-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/24/2018] [Accepted: 01/08/2019] [Indexed: 05/16/2023]
Abstract
Herein we investigated the morphology, chemical characteristics, and source apportionment of fine particulate matter (PM2.5) samples collected from five sites in Jiaxing. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that soot aggregates and coal-fired fly ash were generally the most abundant components in the samples. All the samples were analyzed gravimetrically for mass concentrations and their various compositions were determined. Our results revealed that the PM2.5 concentrations in the samples were in the following order: winter > spring > autumn > summer. The PM2.5 concentrations in winter and spring were higher than those in autumn and summer, except for inorganic elements. Carbonaceous species and water-soluble inorganic ions were the most abundant components in the samples, accounting for 26.17-50.44% and 34.27-49.6%, respectively. The high secondary organic carbon/organic carbon ratio indicated that secondary organic pollution in Jiaxing was severe. The average ratios of NO3-/SO42-, ranging from 1.01 to 1.25 at the five sites, indicated that mobile pollution sources contributed more to the formation of PM2.5 than stationary sources. The BeP/(BeP + BaP) ratio (0.52-0.71) in samples reflected the influence of transportation from outside of Jiaxing. The positive matrix factorization (PMF) model identified eight main pollution sources: secondary nitrates (26.95%), secondary sulfates (15.49%), secondary organic aerosol (SOA) (19.64%), vehicle exhaust (15.67%), coal combustion (8.6%), fugitive dust (7.7%), ships and heavy oil (5.23%), biomass burning, and other sources (0.91%). Therefore, PM2.5 pollution in Jiaxing during the winter and spring seasons was more severe than that in the summer and autumn. Secondary aerosols were the most important source of PM2.5 pollution; therefore, focus should be placed on controlling gaseous precursors.
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Affiliation(s)
- Zhipeng Zhao
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Sheng Lv
- Jiaxing Environmental Monitoring Station, Jiaxing, 314000, China
| | - Yihua Zhang
- Shanghai Environmental Monitoring Center, Shanghai, 200235, China
| | - Qianbiao Zhao
- Shanghai Environmental Monitoring Center, Shanghai, 200235, China
| | - Lin Shen
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Shi Xu
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jianqiang Yu
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jingwen Hou
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Chengyu Jin
- Instrumental Analysis Center, Shanghai Jiao Tong University, Shanghai, 200240, China.
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Abstract
Exposure to fine particulate matter (PM) results in adverse health outcomes. Although this is a global concern, residents of China may be particularly vulnerable due to frequent severe air pollution episodes associated with economic growth, industrialization, and urbanization. Until 2012, PM2.5 was not regulated and monitored in China and annual average concentrations far exceeded the World Health Organizations guidelines of 10 μg/m3. Since the establishment of PM2.5 Ambient Air Quality Criteria in 2012, concentrations have decreased, but still pose significant health risks. A review of ambient PM2.5 health effect studies is warranted to evaluate the current state of knowledge and to prioritize future research efforts. Our review found that recent literature has confirmed associations between PM2.5 exposure and total mortality, cardiovascular mortality, respiratory mortality, hypertension, lung cancer, influenza and other adverse health outcomes. Future studies should take a long-term approach to verify associations between exposure to PM2.5 and health effects. In order to obtain adequate exposure assessment at finer spatial resolutions, high density sampling, satellite remote sensing, or models should be employed. Personal monitoring should also be conducted to validate the use of outdoor concentrations as proxies for exposure. More research efforts should be devoted to seasonal patterns, sub-population susceptibility, and the mechanism by which exposure causes health effects. Submicron and ultrafine PM should also be monitored and regulated.
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The Reducing Effect of Green Spaces with Different Vegetation Structure on Atmospheric Particulate Matter Concentration in BaoJi City, China. ATMOSPHERE 2018. [DOI: 10.3390/atmos9090332] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
With the acceleration of urbanisation and industrialisation, atmospheric particulate pollution has become one of the most serious environmental problems in China. In this study, green spaces in Baoji city were classified into different patterns on the basis of vegetation structural parameters, i.e., horizontal structure, vertical structure and vegetation type. Eleven types of green space with different structures were selected for investigating the relationships between atmospheric particulate matter (PM) concentration and green spaces with different vegetation structure, based on the “matrix effect” of environmental factors, i.e., location, time, wind velocity, temperature, humidity and area to the concentration of PM2.5 and PM10 in the green spaces. The results showed that: (1) Location, time, wind velocity, temperature and humidity had highly significant effects on the concentration of PM2.5 and PM10. In sunny and breeze weather conditions, PM2.5 and PM10 concentration increased with the wind velocity and humidity, and decreased with the temperature. The range of PM10 concentration was greater than the range of PM2.5 concentration. (2) Less than 2 hectares of the green space had no significant influence on the concentration of PM2.5 and PM10. (3) The concentration of PM2.5 and PM10 showed no significant difference between all the green spaces and the control group. There was no significant difference in the reduction of PM2.5 concentration between different structural green spaces, but there was a significant difference in the reduction of PM10 concentration. The above results will provide a theoretical basis and practical methods for the optimisation of urban green space structures for improving urban air quality effectively in the future.
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Cai M, Xin Z, Yu X. Spatio-temporal variations in PM leaf deposition: A meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2017; 231:207-218. [PMID: 28802990 DOI: 10.1016/j.envpol.2017.07.105] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Revised: 06/21/2017] [Accepted: 07/31/2017] [Indexed: 06/07/2023]
Abstract
Particulate matter (PM) pollution in urban cities is of great concern for public health due to its global and adverse effect of human health while ecosystems function and vegetation control is an effective and eco-friendly way to alleviate PM pollution. We reviewed 150 studies conducted in 15 countries that were published between 1960 and 2016 and used a meta-analysis to examine the time trends and regional differences in leaf deposited PM of urban greening plants. The results suggested that the weekly PM leaf deposition varied markedly with both plant species and space-time and the average value was 1.71 ± 0.05 g m-2·wk-1, and the variations occurred because of vegetation factors, characteristics of the PM source and meteorological factors. Moreover, fine particulate matter accounts for the minimum proportion of the total PM mass but its number ratio is maximum, more than 90% of the total number of particles. This meta-analysis illustrated the spatio-temporal trends and variations in PM leaf deposition and the influencing factors, which provides a scientific basis for the mechanism of PM deposition on leaf surface as well as plant selection and configuration in urban greening.
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Affiliation(s)
- Mengfan Cai
- College of Soil and Water Conservation, Beijing Forestry University, 35 Tsinghua Road, Haidian District, Beijing 100083, PR China
| | - Zhongbao Xin
- College of Soil and Water Conservation, Beijing Forestry University, 35 Tsinghua Road, Haidian District, Beijing 100083, PR China.
| | - Xinxiao Yu
- College of Soil and Water Conservation, Beijing Forestry University, 35 Tsinghua Road, Haidian District, Beijing 100083, PR China
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Li L, Tan Q, Zhang Y, Feng M, Qu Y, An J, Liu X. Characteristics and source apportionment of PM 2.5 during persistent extreme haze events in Chengdu, southwest China. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2017; 230:718-729. [PMID: 28732335 DOI: 10.1016/j.envpol.2017.07.029] [Citation(s) in RCA: 60] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Revised: 06/03/2017] [Accepted: 07/10/2017] [Indexed: 06/07/2023]
Abstract
Based on detailed data from Chengdu Plain (CP) from 6 January to 16 January, two typical haze episodes were analyzed to clarify the haze formation mechanism in winter. Weather conditions, chemical compositions, secondary pollutant transformation, optical properties of aerosols, the potential source contribution function (PSCF) and source apportionment were studied. The planetary boundary layer (PBL) height decreased distinctly during the haze episodes and restrained air pollutant vertical dispersion. As the haze worsened, the value of PBL × PM2.5 increased notably. The [NO3-]/[SO42-] ratio was 0.61, 0.76 and 0.88 during a non-haze period, episode 1 and episode 2, respectively, indicating that the mobile source of the air pollution is increasingly predominant in Chengdu. Water vapor also played a vital role in the formation of haze by accelerating the chemical transformation of secondary pollutants, leading to the hygroscopic growth of aerosols. The PSCF and backward trajectories of the air masses indicated that the pollution mainly came from the south. The secondary inorganic aerosols, vehicle emissions, coal combustion, biomass burning, industry, and dust contributed 34.1%, 24.1%, 12.7%, 12.3%, 7.6%, and 7.2% to PM2.5 masses in episode 1 and 28.9%, 23.1%, 9.4%, 9.5%, 20.3% and 7.5% in episode 2.
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Affiliation(s)
- Lulu Li
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China
| | - Qinwen Tan
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Yuanhang Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
| | - Miao Feng
- Chengdu Academy of Environmental Sciences, Chengdu 610072, China
| | - Yu Qu
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Junling An
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Xingang Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing 100875, China.
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Zhang Y, Cai J, Wang S, He K, Zheng M. Review of receptor-based source apportionment research of fine particulate matter and its challenges in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2017; 586:917-929. [PMID: 28237464 DOI: 10.1016/j.scitotenv.2017.02.071] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/23/2016] [Revised: 01/17/2017] [Accepted: 02/08/2017] [Indexed: 05/10/2023]
Abstract
As the key for haze control, atmospheric fine particulate matter with aerodynamic diameter <2.5μm (or PM2.5) is of great concern lately in China. It is closely linked to fast pace of urbanization, industrialization and economic development, especially in eastern China. A good understanding of its sources is required for effective pollution abatement. Receptor models are one of the major methods for source apportionment used in China. The major objective of this study is to understand sources that contribute to fine particulate matter in China and key challenges in this area. Spatial distribution of fine particulate matter concentration, chemical composition and dominant sources in North and South China are summarized. Based on chemical speciation results from 31 cities and source apportionment results from 21 cities, it is found that secondary sources and traffic emission have higher contribution in South China while the percentage of coal combustion, dust and biomass burning to total PM2.5 are higher in North China. Source profiles established in China from 44 cities and areas are also summarized as references for future source apportionment studies. Suggestions for future research are also provided including methods for evaluating source apportionment results, ways for integrating multiple source apportionment methods, the need for standardizing protocols and developing tools for high-time resolution source apportionment.
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Affiliation(s)
- Yanjun Zhang
- SKL-ESPC and BIC-ESAT, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Jing Cai
- SKL-ESPC and BIC-ESAT, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Shuxiao Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Mei Zheng
- SKL-ESPC and BIC-ESAT, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China.
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Zegarska B, Pietkun K, Zegarski W, Bolibok P, Wiśniewski M, Roszek K, Czarnecka J, Nowacki M. Air pollution, UV irradiation and skin carcinogenesis: what we know, where we stand and what is likely to happen in the future? Postepy Dermatol Alergol 2017; 34:6-14. [PMID: 28261026 PMCID: PMC5329103 DOI: 10.5114/ada.2017.65616] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2016] [Accepted: 05/17/2016] [Indexed: 02/08/2023] Open
Abstract
The link between air pollution, UV irradiation and skin carcinogenesis has been demonstrated within a large number of epidemiological studies. Many have shown the detrimental effect that UV irradiation can have on human health as well as the long-term damage which can result from air pollution, the European ESCAPE project being a notable example. In total, at present around 2800 different chemical substances are systematically released into the air. This paper looks at the hazardous impact of air pollution and UV and discusses: 1) what we know; 2) where we stand; and 3) what is likely to happen in the future. Thereafter, we will argue that there is still insufficient evidence of how great direct air pollution and UV irradiation are as factors in the development of skin carcinogenesis. However, future prospects of progress are bright due to a number of encouraging diagnostic and preventive projects in progress at the moment.
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Affiliation(s)
- Barbara Zegarska
- Chair of Cosmetology and Aesthetic Dermatology, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
| | - Katarzyna Pietkun
- Chair of Cosmetology and Aesthetic Dermatology, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
- Chair and Department of Rehabilitation, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Poland
| | - Wojciech Zegarski
- Chair and Department of Surgical Oncology, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Oncology Centre – Professor Franciszek Łukaszczyk Memorial Hospital in Bydgoszcz, Poland
| | - Paulina Bolibok
- Physicochemistry of Carbon Materials Research Group, Faculty of Chemistry, Nicolaus Copernicus University, Torun, Poland
| | - Marek Wiśniewski
- Physicochemistry of Carbon Materials Research Group, Faculty of Chemistry, Nicolaus Copernicus University, Torun, Poland
| | - Katarzyna Roszek
- Department of Biochemistry, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Torun, Poland
| | - Joanna Czarnecka
- Department of Biochemistry, Faculty of Biology and Environment Protection, Nicolaus Copernicus University, Torun, Poland
| | - Maciej Nowacki
- Chair and Department of Surgical Oncology, Ludwik Rydygier’s Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Torun, Oncology Centre – Professor Franciszek Łukaszczyk Memorial Hospital in Bydgoszcz, Poland
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Zhang T, Liu G, Zhu Z, Gong W, Ji Y, Huang Y. Real-Time Estimation of Satellite-Derived PM 2.5 Based on a Semi-Physical Geographically Weighted Regression Model. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2016; 13:E974. [PMID: 27706054 PMCID: PMC5086713 DOI: 10.3390/ijerph13100974] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2016] [Revised: 09/26/2016] [Accepted: 09/26/2016] [Indexed: 11/16/2022]
Abstract
The real-time estimation of ambient particulate matter with diameter no greater than 2.5 μm (PM2.5) is currently quite limited in China. A semi-physical geographically weighted regression (GWR) model was adopted to estimate PM2.5 mass concentrations at national scale using the Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) Aerosol Optical Depth product fused by the Dark Target (DT) and Deep Blue (DB) algorithms, combined with meteorological parameters. The fitting results could explain over 80% of the variability in the corresponding PM2.5 mass concentrations, and the estimation tends to overestimate when measurement is low and tends to underestimate when measurement is high. Based on World Health Organization standards, results indicate that most regions in China suffered severe PM2.5 pollution during winter. Seasonal average mass concentrations of PM2.5 predicted by the model indicate that residential regions, namely Jing-Jin-Ji Region and Central China, were faced with challenge from fine particles. Moreover, estimation deviation caused primarily by the spatially uneven distribution of monitoring sites and the changes of elevation in a relatively small region has been discussed. In summary, real-time PM2.5 was estimated effectively by the satellite-based semi-physical GWR model, and the results could provide reasonable references for assessing health impacts and offer guidance on air quality management in China.
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Affiliation(s)
- Tianhao Zhang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
| | - Gang Liu
- Shanghai Institute of Satellite Engineering, Shanghai 201100, China.
| | - Zhongmin Zhu
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
- College of Information Science and Engineering, Wuchang Shouyi University, Wuhan 430064, China.
| | - Wei Gong
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
- Collaborative Innovation Center for Geospatial Technology, Wuhan 430079, China.
| | - Yuxi Ji
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
| | - Yusi Huang
- State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China.
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12
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Network Analysis of Fine Particulate Matter (PM2.5) Emissions in China. Sci Rep 2016; 6:33227. [PMID: 27608625 PMCID: PMC5016853 DOI: 10.1038/srep33227] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2016] [Accepted: 08/23/2016] [Indexed: 11/30/2022] Open
Abstract
Specification of PM2.5 spatial and temporal characteristics is important for understanding PM2.5 adverse effects and policymaking. We applied network analysis to studying the dataset MIX, which contains PM2.5 emissions recorded from 2168 monitoring stations in China in 2008 and 2010. The results showed that for PM2.5 emissions from industrial sector 8 clusters were found in 2008 but they merged together into a huge cluster in 2010, suggesting that industrial sector underwent an integrating process. For PM2.5 emissions from electricity generation sector, strong locality of clusters was revealed, implying that each region had its own electricity generation system. For PM2.5 emissions from residential sector, the same pattern of 10 clusters was uncovered in both years, implicating the household energy consumption unchanged from 2008 to 2010. For PM2.5 emissions from transportation sector, the same pattern of 5 clusters with many connections in-between was unraveled, indicating the high-speed development of transportation nationalwidely. Except for the known elements, mercury (Hg) surfaced as an element for particle nucleation. To our knowledge, this is the first network study in this field.
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13
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Chen Y, Schleicher N, Fricker M, Cen K, Liu XL, Kaminski U, Yu Y, Wu XF, Norra S. Long-term variation of black carbon and PM2.5 in Beijing, China with respect to meteorological conditions and governmental measures. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2016; 212:269-278. [PMID: 26854696 DOI: 10.1016/j.envpol.2016.01.008] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/04/2015] [Revised: 12/29/2015] [Accepted: 01/05/2016] [Indexed: 06/05/2023]
Abstract
Black carbon (BC) and PM2.5 were studied for nine years from 2005 to 2013 in the Beijing urban area. The overall weekly average mass concentrations of BC and PM2.5 were 4.3 and 66.8 μg/m³. PM2.5 annual means of the nine years are around 2 times of the standard (GB3095-2012) in China, and are 5-7 times higher than the WHO standard. The Beijing Olympic Games in 2008 was a milestone to mitigate aerosol pollution. Temporal distribution of BC shows a distinct declining trend, and annual mean mass concentrations of PM2.5 after 2008 were lower than those before 2008 but increased from 2011 to 2013. Wind rose plots show that high BC concentrations are usually associated with low wind speed of northeastern or southwestern winds, generally causing poor visibility. Governmental mitigation measures such as traffic restriction despite increased motor vehicle numbers and gasoline consumption and industry relocation with declining consumption of coal and coke were successful in reducing BC emissions. Annual mean of BC was reduced by 38% in 2013 compared to 2005. However, BC contamination in Beijing is still severe when compared to other urban areas around the world.
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Affiliation(s)
- Yuan Chen
- Institute of Applied Geosciences, Working Group for Environmental Mineralogy and Environmental System Analysis, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany.
| | - Nina Schleicher
- Institute of Applied Geosciences, Working Group for Environmental Mineralogy and Environmental System Analysis, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany
| | - Mathieu Fricker
- Air Quality Department, Research Center Human Biometeorology, German Meteorological Service, 79104, Freiburg i. Br., Germany
| | - Kuang Cen
- School of the Earth Sciences and Resources, China University of Geosciences, 100083, Beijing, China
| | - Xiu-Li Liu
- School of the Earth Sciences and Resources, China University of Geosciences, 100083, Beijing, China
| | - Uwe Kaminski
- Air Quality Department, Research Center Human Biometeorology, German Meteorological Service, 79104, Freiburg i. Br., Germany
| | - Yang Yu
- School of the Earth Sciences and Resources, China University of Geosciences, 100083, Beijing, China
| | - Xue-Fang Wu
- School of the Earth Sciences and Resources, China University of Geosciences, 100083, Beijing, China
| | - Stefan Norra
- Institute of Applied Geosciences, Working Group for Environmental Mineralogy and Environmental System Analysis, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany; Institute of Geography and Geoecology, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany; Institute of Mineralogy, Technische Universität Bergakademie Freiberg, Brennhausgasse 14, 09596, Freiberg, Germany
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14
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You W, Zang Z, Zhang L, Li Y, Wang W. Estimating national-scale ground-level PM25 concentration in China using geographically weighted regression based on MODIS and MISR AOD. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2016; 23:8327-38. [PMID: 26780051 DOI: 10.1007/s11356-015-6027-9] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 12/28/2015] [Indexed: 05/06/2023]
Abstract
Taking advantage of the continuous spatial coverage, satellite-derived aerosol optical depth (AOD) products have been widely used to assess the spatial and temporal characteristics of fine particulate matter (PM2.5) on the ground and their effects on human health. However, the national-scale ground-level PM2.5 estimation is still very limited because the lack of ground PM2.5 measurements to calibrate the model in China. In this study, a national-scale geographically weighted regression (GWR) model was developed to estimate ground-level PM2.5 concentration based on satellite AODs, newly released national-wide hourly PM2.5 concentrations, and meteorological parameters. The results showed good agreements between satellite-retrieved and ground-observed PM2.5 concentration at 943 stations in China. The overall cross-validation (CV) R (2) is 0.76 and root mean squared prediction error (RMSE) is 22.26 μg/m(3) for MODIS-derived AOD. The MISR-derived AOD also exhibits comparable performance with a CV R (2) and RMSE are 0.81 and 27.46 μg/m(3), respectively. Annual PM2.5 concentrations retrieved either by MODIS or MISR AOD indicated that most of the residential community areas exceeded the new annual Chinese PM2.5 National Standard level 2. These results suggest that this approach is useful for estimating large-scale ground-level PM2.5 distributions especially for the regions without PMs monitoring sites.
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Affiliation(s)
- Wei You
- Institute of Meteorology and Oceanography, PLA University of Science and Technology, No.60, Shuanglong Street, Nanjing, 211101, China
| | - Zengliang Zang
- Institute of Meteorology and Oceanography, PLA University of Science and Technology, No.60, Shuanglong Street, Nanjing, 211101, China.
| | - Lifeng Zhang
- Institute of Meteorology and Oceanography, PLA University of Science and Technology, No.60, Shuanglong Street, Nanjing, 211101, China
| | - Yi Li
- Institute of Meteorology and Oceanography, PLA University of Science and Technology, No.60, Shuanglong Street, Nanjing, 211101, China
| | - Weiqi Wang
- Institute of Meteorology and Oceanography, PLA University of Science and Technology, No.60, Shuanglong Street, Nanjing, 211101, China
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15
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Devi G, Devi A, Bhattacharyya KG. Hydrocarbons and heavy metals in fine particulates in oil field air: possible impacts on production of natural silk. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2016; 23:3310-3321. [PMID: 26490906 DOI: 10.1007/s11356-015-5533-0] [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: 05/08/2015] [Accepted: 10/05/2015] [Indexed: 06/05/2023]
Abstract
Analyses of fine particulates (PM2.5) from the upper Assam oil fields of India indicated considerable presence of higher hydrocarbons (C22-C35) and heavy metals, Cd, Co, Cr, Cu, Ni, Pb, and Zn. This has raised serious concern for the sustainability of the exotic Muga (Antheraea assama) silk production, which has been a prime activity of a large number of people living in the area. The Muga worm feeds on the leaves of Machilus bombycina plant, and the impacts of air quality on its survival were further investigated by analyzing the leaves of the plant, the plantation soil, and the Muga cocoons. PM2.5 content in the air was much more during the winter due to near calm conditions and high humidity. Fourier transform infrared (FTIR), thermogravimetric analysis (TGA), and gas chromatography-mass spectrometer (GC-MS) analysis of PM2.5 showed the presence of higher alkanes (C22-C35) that could be traced to crude oil. Cr, Ni, and Zn were found in higher concentrations in PM2.5, M. bombycina leaves, and the plantation soil indicating a common origin. The winter has been the best period for production of the silk cocoons, and the unhealthy air during this period is likely to affect the production, which is already reflected in the declining yield of Muga cocoons from the area. SEM and protein analyses of the Muga silk fiber produced in the oil field area have exhibited the deteriorating quality of the silk. This is the first report from India on hydrocarbons and associated metals in PM2.5 collected from an oil field and on their possible effects on production of silk by A. assama.
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Affiliation(s)
- Gitumani Devi
- Environmental Chemistry Laboratory, Life Sciences Division (LSD), Institute of Advanced Study in Science and Technology (IASST), Paschim Boragaon, Guwahati, Assam, 781 035, India
| | - Arundhuti Devi
- Environmental Chemistry Laboratory, Life Sciences Division (LSD), Institute of Advanced Study in Science and Technology (IASST), Paschim Boragaon, Guwahati, Assam, 781 035, India.
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16
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Xu W, Wu Q, Liu X, Tang A, Dore AJ, Heal MR. Characteristics of ammonia, acid gases, and PM2.5 for three typical land-use types in the North China Plain. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2016; 23:1158-72. [PMID: 26507724 PMCID: PMC4713460 DOI: 10.1007/s11356-015-5648-3] [Citation(s) in RCA: 35] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/18/2015] [Accepted: 10/19/2015] [Indexed: 05/22/2023]
Abstract
Air pollution is one of the most serious environmental problems in China due to its rapid economic development alongside a very large consumption of fossil fuel, particularly in the North China Plain (NCP). During the period 2011-2014, we integrated active and passive sampling methods to perform continuous measurements of NH3, HNO3, NO2, and PM2.5 at two urban, one suburban, and two rural sites in the NCP. The annual average concentrations of NH3, NO2, and HNO3 across the five sites were in the ranges 8.5-23.0, 22.2-50.5, and 5.5-9.7 μg m(-3), respectively, showing no significant spatial differences for NH3 and HNO3 but significantly higher NO2 concentration at the urban sites. At each site, annual average concentrations of NH3 and NO2 showed increasing and decreasing trends, respectively, while there was no obvious trend in annual HNO3 concentrations. Daily PM2.5 concentrations ranged from 11.8 to 621.0 μg m(-3) at the urban site, from 19.8 to 692.9 μg m(-3) at the suburban site, and from 23.9 to 754.5 μg m(-3) at the two rural sites, with more than 70% of sampling days exceeding 75 μg m(-3). Concentrations of water-soluble ions in PM2.5 ranked differently between the non-rural and rural sites. The three dominant ions were NH4(+), NO3(-), and SO4(2-) and mainly existed as (NH4)2SO4, NH4HSO4, and NH4NO3, and their concentrations averaged 48.6 ± 44.9, 41.2 ± 40.8, and 49.6 ± 35.9 μg m(-3) at the urban, suburban, and rural sites, respectively. Ion balance calculations indicated that PM2.5 was neutral at the non-rural sites but acidic at the rural sites. Seasonal variations of the gases and aerosols exhibited different patterns, depending on source emission strength and meteorological conditions. Our results suggest that a feasible pathway to control PM2.5 pollution in the NCP should target ammonia and acid gases together.
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Affiliation(s)
- Wen Xu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Qinghua Wu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Xuejun Liu
- College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China.
| | - Aohan Tang
- College of Resources and Environmental Sciences, China Agricultural University, Beijing, 100193, China
| | - Anthony J Dore
- Centre for Ecology and Hydrology, Edinburgh, Bush Estate, Penicuik, Midlothian, EH26 0QB, UK
| | - Mathew R Heal
- School of Chemistry, The University of Edinburgh, David Brewster Road, Edinburgh, EH9 3FJ, UK
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17
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Zhang H, Qian J, Zhao H, Wang J, Zhu H, Zhou Y, Wang J, Guo J, Gehendra M, Qiu H, Sun Z, He D. A study of the association between atmospheric particulate matter and blood pressure in the population. Blood Press 2015; 25:169-76. [PMID: 26634767 DOI: 10.3109/08037051.2015.1111019] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Affiliation(s)
- Huawei Zhang
- Department of Cardiology, Chinese PLA General Hospital, Beijing, PR China
| | - Jin Qian
- Department of Aged Cadres, Beijing Shijitan Hospital, Capital Medical University, Beijing, PR China
| | - Haiping Zhao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China
| | - Jinda Wang
- Department of Cardiology, Chinese PLA General Hospital, Beijing, PR China
| | - Hang Zhu
- Department of Cardiology, Chinese PLA General Hospital, Beijing, PR China
| | - Ying Zhou
- Department of Cardiology, Chinese PLA General Hospital, Beijing, PR China
| | - Juan Wang
- Department of Cardiology, Chinese PLA General Hospital, Beijing, PR China
| | - Jin Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China
| | - Mahara Gehendra
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China
| | - Hongyan Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Ningxia Medical University, Yinchuan, PR China
| | - Zhijun Sun
- Department of Cardiology, Chinese PLA General Hospital, Beijing, PR China
| | - Dian He
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, PR China
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18
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Huang F, Li X, Wang C, Xu Q, Wang W, Luo Y, Tao L, Gao Q, Guo J, Chen S, Cao K, Liu L, Gao N, Liu X, Yang K, Yan A, Guo X. PM2.5 Spatiotemporal Variations and the Relationship with Meteorological Factors during 2013-2014 in Beijing, China. PLoS One 2015; 10:e0141642. [PMID: 26528542 PMCID: PMC4631325 DOI: 10.1371/journal.pone.0141642] [Citation(s) in RCA: 43] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2015] [Accepted: 10/12/2015] [Indexed: 02/06/2023] Open
Abstract
Objective Limited information is available regarding spatiotemporal variations of particles with median aerodynamic diameter < 2.5 μm (PM2.5) at high resolutions, and their relationships with meteorological factors in Beijing, China. This study aimed to detect spatiotemporal change patterns of PM2.5 from August 2013 to July 2014 in Beijing, and to assess the relationship between PM2.5 and meteorological factors. Methods Daily and hourly PM2.5 data from the Beijing Environmental Protection Bureau (BJEPB) were analyzed separately. Ordinary kriging (OK) interpolation, time-series graphs, Spearman correlation coefficient and coefficient of divergence (COD) were used to describe the spatiotemporal variations of PM2.5. The Kruskal-Wallis H test, Bonferroni correction, and Mann-Whitney U test were used to assess differences in PM2.5 levels associated with spatial and temporal factors including season, region, daytime and day of week. Relationships between daily PM2.5 and meteorological variables were analyzed using the generalized additive mixed model (GAMM). Results Annual mean and median of PM2.5 concentrations were 88.07 μg/m3 and 71.00 μg/m3, respectively, from August 2013 to July 2014. PM2.5 concentration was significantly higher in winter (P < 0.0083) and in the southern part of the city (P < 0.0167). Day to day variation of PM2.5 showed a long-term trend of fluctuations, with 2–6 peaks each month. PM2.5 concentration was significantly higher in the night than day (P < 0.0167). Meteorological factors were associated with daily PM2.5 concentration using the GAMM model (R2 = 0.59, AIC = 7373.84). Conclusion PM2.5 pollution in Beijing shows strong spatiotemporal variations. Meteorological factors influence the PM2.5 concentration with certain patterns. Generally, prior day wind speed, sunlight hours and precipitation are negatively correlated with PM2.5, whereas relative humidity and air pressure three days earlier are positively correlated with PM2.5.
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Affiliation(s)
- Fangfang Huang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xia Li
- Graduate Entry Medical School, University of Limerick, Limerick, Ireland
| | - Chao Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Qin Xu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Wei Wang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
- School of Medical Sciences, Edith Cowan University, Perth, Australia
| | - Yanxia Luo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Lixin Tao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Qi Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Jin Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Sipeng Chen
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Kai Cao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Long Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Ni Gao
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xiangtong Liu
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Kun Yang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Aoshuang Yan
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Science and Technology Commission, Beijing, China
- * E-mail: (ASY); (XHG)
| | - Xiuhua Guo
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
- * E-mail: (ASY); (XHG)
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19
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Yang J, Fu Q, Guo X, Chu B, Yao Y, Teng Y, Wang Y. Concentrations and seasonal variation of ambient PM(2.5) and associated metals at a typical residential area in Beijing, China. BULLETIN OF ENVIRONMENTAL CONTAMINATION AND TOXICOLOGY 2015; 94:232-9. [PMID: 25528273 DOI: 10.1007/s00128-014-1443-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Accepted: 12/13/2014] [Indexed: 05/24/2023]
Abstract
In this study, continuous monitoring of PM2.5 was carried out for 1 year period at one of the largest residential areas in Beijing. Annual mean of PM2.5 during sampling period was 100.4 µg/m(3). The seasonal variation trend of PM2.5 was winter > spring > autumn and summer. The total mass concentrations of metals in PM2.5 ranged from 0.4 to 13.2 μg/m(3). There were significant (p < 0.05) seasonal variations for concentrations of Ca, Al, Mn, As, Rb, Cr, Ni, Cd and Co, seasonal variations in PM-associated metals were not necessarily the same as the seasonal variation in PM2.5, related to differing seasonal trends in source types. The impact of meteorological factors (e.g., wind speed) on metals levels of PM2.5 was found to be significant by regression models. The EFs value of Ag, Ca, Cd, Pb, Zn, As, Cu, and Cr were higher than ten, suggesting that those elements were primarily contributed by anthropogenic sources. Seasonal characteristic of EFs were found for As, Cr, Ca and Ag, which indicating the seasonal pollution sources types for those metals. Overall, these findings indicated that the pollution control of ambient PM2.5 should not be negligible in residential area in Beijing and the local government should pertinent and accurate prevent and control of air pollution as well as protect human health.
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Affiliation(s)
- Jing Yang
- College of Water Sciences, Beijing Normal University, No. 19, XinJieKouWai St., HaiDian District, Beijing, 100875, People's Republic of China
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20
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Xiao Q, Ma Z, Li S, Liu Y. The impact of winter heating on air pollution in China. PLoS One 2015; 10:e0117311. [PMID: 25629878 PMCID: PMC4309400 DOI: 10.1371/journal.pone.0117311] [Citation(s) in RCA: 47] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Accepted: 12/20/2014] [Indexed: 11/24/2022] Open
Abstract
Fossil-fuel combustion related winter heating has become a major air quality and public health concern in northern China recently. We analyzed the impact of winter heating on aerosol loadings over China using the MODIS-Aqua Collection 6 aerosol product from 2004–2012. Absolute humidity (AH) and planetary boundary layer height (PBL) -adjusted aerosol optical depth (AOD*) was constructed to reflect ground-level PM2.5 concentrations. GIS analysis, standard statistical tests, and statistical modeling indicate that winter heating is an important factor causing increased PM2.5 levels in more than three-quarters of central and eastern China. The heating season AOD* was more than five times higher as the non-heating season AOD*, and the increase in AOD* in the heating areas was greater than in the non-heating areas. Finally, central heating tend to contribute less to air pollution relative to other means of household heating.
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Affiliation(s)
- Qingyang Xiao
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
| | - Zongwei Ma
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing, China
| | - Shenshen Li
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing, China
| | - Yang Liu
- Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, United States of America
- * E-mail:
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21
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Baccarelli AA, Zheng Y, Zhang X, Chang D, Liu L, Wolf KR, Zhang Z, McCracken JP, Díaz A, Bertazzi PA, Schwartz J, Wang S, Kang CM, Koutrakis P, Hou L. Air pollution exposure and lung function in highly exposed subjects in Beijing, China: a repeated-measure study. Part Fibre Toxicol 2014; 11:51. [PMID: 25272992 PMCID: PMC4192276 DOI: 10.1186/s12989-014-0051-7] [Citation(s) in RCA: 55] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2014] [Accepted: 09/15/2014] [Indexed: 11/10/2022] Open
Abstract
Background Exposure to ambient particulate matter (PM) has been associated with reduced lung function. Elemental components of PM have been suggested to have critical roles in PM toxicity, but their contribution to respiratory effects remains under-investigated. We evaluated the effects of traffic-related PM2.5 and its elemental components on lung function in two highly exposed groups of healthy adults in Beijing, China. Methods The Beijing Truck Driver Air Pollution Study (BTDAS) included 60 truck drivers and 60 office workers evaluated in 2008. On two days separated by 1-2 weeks, we measured lung function at the end of the work day, personal PM2.5, and nine elemental components of PM2.5 during eight hours of work, i.e., elemental carbon (EC), potassium (K), sulfur (S), iron (Fe), silicon (Si), aluminum (Al), zinc (Zn), calcium (Ca), and titanium (Ti). We used covariate-adjusted mixed-effects models including PM2.5 as a covariate to estimate the percentage change in lung function associated with an inter-quartile range (IQR) exposure increase. Results The two groups had high and overlapping exposure distributions with mean personal PM2.5 of 94.6 μg/m3 (IQR: 48.5-126.6) in office workers and 126.8 μg/m3 (IQR: 73.9-160.5) in truck drivers. The distributions of the nine elements showed group-specific profiles and generally higher levels in truck drivers. In all subjects combined, forced expiratory volume in 1 second (FEV1) and forced vital capacity (FVC) did not significantly correlate with PM2.5. However, FEV1 showed negative associations with concentrations of four elements: Si (-3.07%, 95% CI: -5.00; -1.11, IQR: 1.54), Al (-2.88%, 95% CI: -4.91; -0.81, IQR: 0.86), Ca (-1.86%, 95% CI: -2.95; -0.76, IQR: 1.33), and Ti (-2.58%, 95% CI: -4.44; -0.68, IQR: 0.03), and FVC showed negative associations with concentrations of three elements: Si (-3.23%, 95% CI: -5.61; -0.79), Al (-3.26%, 95% CI: -5.73; -0.72), and Ca (-1.86%, 95% CI: -3.23; -0.47). In stratified analysis, Si, Al, Ca, and Ti showed associations with lung function only among truck drivers, and no significant association among office workers. Conclusion Selected elemental components of PM2.5 showed effects on lung function that were not found in analyses of particle levels alone. Electronic supplementary material The online version of this article (doi:10.1186/s12989-014-0051-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Andrea A Baccarelli
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.
| | - Yinan Zheng
- Institute for Public Health and Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Xiao Zhang
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Dou Chang
- Department of Safety Engineering, China Institute of Industrial Health, Beijing, China.
| | - Lei Liu
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Katherine Rose Wolf
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - Zhou Zhang
- Driskill Graduate Program in Life Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
| | - John P McCracken
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.
| | - Anaité Díaz
- Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala.
| | - Pier Alberto Bertazzi
- Center of Molecular and Genetic Epidemiology, Department of Clinical Sciences and Community Health, University of Milan and IRCCS Foundation Ca' Granda, Ospedale Maggiore Policlinico, Italy.
| | - Joel Schwartz
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.
| | - Sheng Wang
- Department of Occupational and Environmental Health, Peking University Health Science Center, No. 38 Xueyuan Road, Haidian District, Beijing, 100191, China.
| | - Choong-Min Kang
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.
| | - Petros Koutrakis
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA.
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA. .,Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA.
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22
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Chen Y, Schleicher N, Chen Y, Chai F, Norra S. The influence of governmental mitigation measures on contamination characteristics of PM(2.5) in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2014; 490:647-658. [PMID: 24887192 DOI: 10.1016/j.scitotenv.2014.05.049] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2014] [Revised: 05/08/2014] [Accepted: 05/13/2014] [Indexed: 06/03/2023]
Abstract
Beijing, the capital of China, has become one of the most air-polluted cities due to its rapid economic growth. Weekly PM2.5 samples-collected continuously from 2007 to 2010-were used to study the contamination characteristics of atmospheric particles and effects of governmental mitigation measures especially since the 2008 Summer Olympic Games. PM2.5 mass concentrations during the sampling period were reduced compared to the previous studies before 2005, although they were still too high in comparison with environmental standards of China and many other countries as well as WHO standards. Results of principle component analysis show that elements of primary anthropogenic origin had an obvious decline while elements mainly from the natural environment kept a relatively stable course. The governmental macro-control measures influenced both anthropogenic and geogenic sources, but they also led to some pollution peaks prior to implementation of the respective measures. Some element concentrations correlated to the restrictiveness of relative measures, especially during different traffic restrictions. The comparison with other countries and international standards shows that there is a long way to go in order to improve air quality in Beijing, and that governmental mitigation measures need to be continued and reinforced.
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Affiliation(s)
- Yuan Chen
- Institute of Mineralogy and Geochemistry, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany.
| | - Nina Schleicher
- Institute of Mineralogy and Geochemistry, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany
| | - Yizhen Chen
- Institute of Urban and Regional Atmospheric Sciences, Chinese Research Academy of Environmental Sciences, 100012, Beijing, China
| | - Fahe Chai
- Institute of Urban and Regional Atmospheric Sciences, Chinese Research Academy of Environmental Sciences, 100012, Beijing, China
| | - Stefan Norra
- Institute of Mineralogy and Geochemistry, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany; Institute of Geography and Geoecology, Karlsruhe Institute of Technology, 76131, Karlsruhe, Germany
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Ma Z, Hu X, Huang L, Bi J, Liu Y. Estimating ground-level PM2.5 in China using satellite remote sensing. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2014; 48:7436-44. [PMID: 24901806 DOI: 10.1021/es5009399] [Citation(s) in RCA: 122] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/25/2023]
Abstract
Estimating ground-level PM2.5 from satellite-derived aerosol optical depth (AOD) using a spatial statistical model is a promising new method to evaluate the spatial and temporal characteristics of PM2.5 exposure in a large geographic region. However, studies outside North America have been limited due to the lack of ground PM2.5 measurements to calibrate the model. Taking advantage of the newly established national monitoring network, we developed a national-scale geographically weighted regression (GWR) model to estimate daily PM2.5 concentrations in China with fused satellite AOD as the primary predictor. The results showed that the meteorological and land use information can greatly improve model performance. The overall cross-validation (CV) R(2) is 0.64 and root mean squared prediction error (RMSE) is 32.98 μg/m(3). The mean prediction error (MPE) of the predicted annual PM2.5 is 8.28 μg/m(3). Our predicted annual PM2.5 concentrations indicated that over 96% of the Chinese population lives in areas that exceed the Chinese National Ambient Air Quality Standard (CNAAQS) Level 2 standard. Our results also confirmed satellite-derived AOD in conjunction with meteorological fields and land use information can be successfully applied to extend the ground PM2.5 monitoring network in China.
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Affiliation(s)
- Zongwei Ma
- State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Xianlin Campus , Box 624, 163 Xianlin Avenue, Nanjing 210023, China
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Guo L, Byun HM, Zhong J, Motta V, Barupal J, Zheng Y, Dou C, Zhang F, McCracken JP, Diaz A, Marco SG, Colicino S, Schwartz J, Wang S, Hou L, Baccarelli AA. Effects of short-term exposure to inhalable particulate matter on DNA methylation of tandem repeats. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2014; 55:322-35. [PMID: 24436168 PMCID: PMC4426495 DOI: 10.1002/em.21838] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/04/2013] [Revised: 01/06/2013] [Accepted: 01/06/2014] [Indexed: 05/21/2023]
Abstract
There is compelling evidence that particulate matter (PM) increases lung cancer risk by triggering systemic inflammation, and leukocyte DNA hypomethylation. However, previous investigations focused on repeated element sequences from LINE-1 and Alu families. Tandem repeats, which display a greater propensity to mutate, and are often hypomethylated in cancer patients, have never been investigated in individuals exposed to PM. We measured methylation of three tandem repeats (SATα, NBL2, and D4Z4) by polymerase chain reaction-pyrosequencing on blood samples from truck drivers and office workers (60 per group) in Beijing, China. We used lightweight monitors to measure personal PM2.5 (PM with aerodynamic diameter ≤2.5 µm) and elemental carbon (a tracer of PM from vehicular traffic). Ambient PM10 data were obtained from air quality measuring stations. Overall, an interquartile increase in personal PM2.5 and ambient PM10 levels was associated with a significant covariate-adjusted decrease in SATα methylation (-1.35% 5-methyl cytosine [5mC], P = 0.01; and -1.33%5mC; P = 0.01, respectively). Effects from personal PM2.5 and ambient PM10 on SATα methylation were stronger in truck drivers (-2.34%5mC, P = 0.02; -1.44%5mC, P = 0.06) than office workers (-0.95%5mC, P = 0.26; -1.25%5mC, P = 0.12, respectively). Ambient PM10 was negatively correlated with NBL2 methylation in truck drivers (-1.38%5mC, P = 0.03) but not in office workers (1.04%5mC, P = 0.13). Our result suggests that PM exposure is associated with hypomethylation of selected tandem repeats. Measuring tandem-repeat hypomethylation in easy-to-obtain blood specimens might identify individuals with biological effects and potential cancer risk from PM exposure.
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Affiliation(s)
- Liqiong Guo
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), College of Environmental Sciences and Engineering, Nankai University, Tianjin, China
- Correspondence to: Liqiong Guo, Nankai University, College of Environmental Sciences and Engineering, Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin 300071, Tel. +86(186)-9804-6908,
| | - Hyang-Min Byun
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Jia Zhong
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Valeria Motta
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
- Center for Molecular and Genetic Epidemiology, Department of Environmental and Occupational Health, Ca’Granda Ospedale Maggiore Policlinico IRCCS Foundation, Universita degli Studi di Milano, Milan, Italy
| | - Jitendra Barupal
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Yinan Zheng
- Driskill Graduate Program (DGP) in Life Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Chang Dou
- Department of Safety Engineering, China Institute of Industrial Health, Beijing, China
| | - Feiruo Zhang
- Department of Occupational and Environmental Health, Peking University Health Science Center, Beijing, China
| | - John P. McCracken
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Anaité Diaz
- Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Sanchez-Guerra Marco
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Silvia Colicino
- Center for Molecular and Genetic Epidemiology, Department of Environmental and Occupational Health, Ca’Granda Ospedale Maggiore Policlinico IRCCS Foundation, Universita degli Studi di Milano, Milan, Italy
| | - Joel Schwartz
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Sheng Wang
- Department of Occupational and Environmental Health, Peking University Health Science Center, Beijing, China
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
- The Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Andrea A. Baccarelli
- Laboratory of Environmental Epigenetics, Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
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Hou L, Zhang X, Zheng Y, Wang S, Dou C, Guo L, Byun HM, Motta V, McCracken J, Díaz A, Kang CM, Koutrakis P, Bertazzi PA, Li J, Schwartz J, Baccarelli AA. Altered methylation in tandem repeat element and elemental component levels in inhalable air particles. ENVIRONMENTAL AND MOLECULAR MUTAGENESIS 2014; 55:256-65. [PMID: 24273195 PMCID: PMC4001244 DOI: 10.1002/em.21829] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/06/2013] [Accepted: 10/31/2013] [Indexed: 05/20/2023]
Abstract
Exposure to particulate matter (PM) has been associated with lung cancer risk in epidemiology investigations. Elemental components of PM have been suggested to have critical roles in PM toxicity, but the molecular mechanisms underlying their association with cancer risks remain poorly understood. DNA methylation has emerged as a promising biomarker for environmental-related diseases, including lung cancer. In this study, we evaluated the effects of PM elemental components on methylation of three tandem repeats in a highly exposed population in Beijing, China. The Beijing Truck Driver Air Pollution Study was conducted shortly before the 2008 Beijing Olympic Games (June 15-July 27, 2008) and included 60 truck drivers and 60 office workers. On two days separated by 1-2 weeks, we measured blood DNA methylation of SATα, NBL2, D4Z4, and personal exposure to eight elemental components in PM2.5 , including aluminum (Al), silicon (Si), sulfur (S), potassium (K), calcium (Ca) titanium (Ti), iron (Fe), and zinc (Zn). We estimated the associations of individual elemental component with each tandem-repeat methylation in generalized estimating equations (GEE) models adjusted for PM2.5 mass and other covariates. Out of the eight examined elements, NBL2 methylation was positively associated with concentrations of Si [0.121, 95% confidence interval (CI): 0.030; 0.212, False Discovery Rate (FDR) = 0.047] and Ca (0.065, 95%CI: 0.014; 0.115, FDR = 0.047) in truck drivers. In office workers, SATα methylation was positively associated with concentrations of S (0.115, 95% CI: 0.034; 0.196, FDR = 0.042). PM-associated differences in blood tandem-repeat methylation may help detect biological effects of the exposure and identify individuals who may eventually experience higher lung cancer risk.
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Affiliation(s)
- Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
- The Robert H. Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Xiao Zhang
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Yinan Zheng
- Driskill Graduate Program (DGP) in Life Sciences, Feinberg School of Medicine, Northwestern University, Evanston, Illinois, USA
| | - Sheng Wang
- Department of Occupational and Environmental Health, Peking University Health Science Center, Beijing, China
| | - Chang Dou
- Department of Safety Engineering, China Institute of Industrial Health, Beijing, China
| | - Liqiong Guo
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
- Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), College of Environmental Sciences and Engineering, Nankai University, Tianjin, China
| | - Hyang-Min Byun
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Valeria Motta
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - John McCracken
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Anaité Díaz
- Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Choong-Min Kang
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Petros Koutrakis
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Pier Alberto Bertazzi
- Department of Clinical Sciences and Community Health - DISCCO, Università degli Studi di Milano and Fondazione IRCCS Ca' Granda Maggiore Policlinico Hospital, Milan, Italy
| | - Jingyun Li
- Beijing Institute of Occupational Medicine for Chemical Industry, Beijing, China
| | - Joel Schwartz
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health, Harvard School of Public Health, Boston, MA, USA
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Schleicher N, Norra S, Chen Y, Chai F, Wang S. Efficiency of mitigation measures to reduce particulate air pollution--a case study during the Olympic Summer Games 2008 in Beijing, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2012; 427-428:146-158. [PMID: 22560243 DOI: 10.1016/j.scitotenv.2012.04.004] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/27/2012] [Revised: 04/01/2012] [Accepted: 04/02/2012] [Indexed: 05/31/2023]
Abstract
Atmospheric particles were studied before, during, and after the period of the Olympic Summer Games in Beijing, China, in August 2008 in order to investigate the efficiency of the mitigation measures implemented by the Chinese Government. Total suspended particles (TSP) and fine particles (PM(2.5) and PM(1)) were collected continuously from October 2007 to February 2009 and were analyzed in detail with regard to mass and element concentrations, water-soluble ions, and black carbon (BC). Mass as well as element concentrations during the Olympic air quality control period were lower than the respective concentrations during the time directly before and after the Olympic Games. The results showed that the applied aerosol source control measures, such as shutting down industries and reducing traffic, had a huge impact on the reduction of aerosol pollution in Beijing. However, the meteorological conditions, especially rainfall, certainly also contributed to the successful reduction of particulate air pollution. Coarse particles were reduced more efficiently than finer particles, which indicates that long-range transport of atmospheric particles is difficult to control and that presumably the established mitigation area was not large enough. The study further showed that elements from predominantly anthropogenic sources, such as S, Cu, As, Cd, and Pb, as well as BC, were reduced more efficiently during the Olympic Games than elements for which geogenic sources are more significant, such as Al, Fe, Rb or Sr. Furthermore, the mentioned anthropogenic element concentrations were reduced more in the finer PM(2.5) samples whereas geogenic ones were reduced stronger in TSP samples including the coarser fraction. Consequently, it can be assumed that the mitigation measures, as intended, were successful in reducing more toxic and health-relevant particles from anthropogenic sources. Firework displays, especially at the Opening Ceremony, could be identified as a special short-time source for atmospheric particles during the Olympic Games.
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Affiliation(s)
- Nina Schleicher
- Institute of Mineralogy and Geochemistry, Karlsruhe Institute of Technology, Adenauerring 20b, 76131, Karlsruhe, Germany.
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Baccarelli A, Barretta F, Dou C, Zhang X, McCracken JP, Díaz A, Bertazzi PA, Schwartz J, Wang S, Hou L. Effects of particulate air pollution on blood pressure in a highly exposed population in Beijing, China: a repeated-measure study. Environ Health 2011; 10:108. [PMID: 22188661 PMCID: PMC3273442 DOI: 10.1186/1476-069x-10-108] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2011] [Accepted: 12/21/2011] [Indexed: 05/20/2023]
Abstract
BACKGROUND Particulate Matter (PM) exposure is critical in Beijing due to high population density and rapid increase in vehicular traffic. PM effects on blood pressure (BP) have been investigated as a mechanism mediating cardiovascular risks, but results are still inconsistent. The purpose of our study is to determine the effects of ambient and personal PM exposure on BP. METHODS Before the 2008 Olympic Games (June 15-July 27), we examined 60 truck drivers and 60 office workers on two days, 1-2 weeks apart (n = 240). We obtained standardized measures of post-work BP. Exposure assessment included personal PM(2.5) and Elemental Carbon (EC, a tracer of traffic particles) measured using portable monitors during work hours; and ambient PM(10) averaged over 1-8 days pre-examination. We examined associations of exposures (exposure group, personal PM(2.5)/EC, ambient PM(10)) with BP controlling for multiple covariates. RESULTS Mean personal PM(2.5) was 94.6 μg/m(3) (SD = 64.9) in office workers and 126.8 (SD = 68.8) in truck drivers (p-value < 0.001). In all participants combined, a 10 μg/m(3) increase in 8-day ambient PM(10) was associated with BP increments of 0.98 (95%CI 0.34; 1.61; p-value = 0.003), 0.71 (95%CI 0.18; 1.24; p-value = 0.01), and 0.81 (95%CI 0.31; 1.30; p-value = 0.002) mmHg for systolic, diastolic, and mean BP, respectively. BP was not significantly different between the two groups (p-value > 0.14). Personal PM(2.5) and EC during work hours were not associated with increased BP. CONCLUSIONS Our results indicate delayed effects of ambient PM(10) on BP. Lack of associations with exposure groups and personal PM(2.5)/EC indicates that PM effects are related to background levels of pollution in Beijing, and not specifically to work-related exposure.
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Affiliation(s)
- Andrea Baccarelli
- Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Francesco Barretta
- Department of Occupational and Environmental Health, University of Milan and Fondazione IRCCS Ca' Granda Policlinico, Milan, Italy
| | - Chang Dou
- Deptartment of Safety Engineering, China Institute of Industrial Health No.45 Zengguang Rd., Haidian District, Beijing 100048, China
| | - Xiao Zhang
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - John P McCracken
- Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Anaité Díaz
- Center for Health Studies, Universidad del Valle de Guatemala, Guatemala City, Guatemala
| | - Pier Alberto Bertazzi
- Department of Occupational and Environmental Health, University of Milan and Fondazione IRCCS Ca' Granda Policlinico, Milan, Italy
| | - Joel Schwartz
- Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA
| | - Sheng Wang
- Department of Occupational and Environmental Health, Peking University Health Science Center, Beijing, China
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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Schleicher N, Norra S, Dietze V, Yu Y, Fricker M, Kaminski U, Chen Y, Cen K. The effect of mitigation measures on size distributed mass concentrations of atmospheric particles and black carbon concentrations during the Olympic Summer Games 2008 in Beijing. THE SCIENCE OF THE TOTAL ENVIRONMENT 2011; 412-413:185-193. [PMID: 22035559 DOI: 10.1016/j.scitotenv.2011.09.084] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/25/2011] [Revised: 09/28/2011] [Accepted: 09/29/2011] [Indexed: 05/31/2023]
Abstract
The period of the 2008 Olympic Summer Games in Beijing can be considered as a unique opportunity to study the influences of emission reduction measures on air quality improvement. Within this study atmospheric particles of different size classes (2.5 to 80 μm) were investigated before, during, and after the Olympic Games period in order to observe and assess the success of short-term measures to mitigate extreme urban aerosol pollution and also to investigate, which particle size classes were reduced most effectively. Furthermore, black carbon (BC) concentrations in fine particles (PM(2.5)) during the source control period were compared to those of the previous years in order to investigate the decrease of combustion-derived aerosols. It is shown that besides the implemented mitigation measures precipitation decisively contributed to a considerable decrease of particulate air pollution in Beijing compared to the respective concentrations during the time directly before and after the Olympic Games, and also compared to average August concentrations during the previous years and the following year 2009. Particles of the fine fraction of the coarse mode (2.5 to 5 μm), which have a residence time in the order of several days and which, therefore, are typically transported over long distances from outside of Beijing, were less efficiently reduced than coarser particles. This indicates that long-range transport of atmospheric particles is difficult to control and that presumably the established mitigation area was not large enough to also reduce the fine fraction of the coarse mode more efficiently. Furthermore, the study showed that coarse geogenic particles, which originated to a high percentage from construction sites and resuspension processes due to traffic seemed to be reduced most efficiently during the Olympic Games period.
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Affiliation(s)
- Nina Schleicher
- Institute of Mineralogy and Geochemistry, Karlsruhe Institute of Technology, Adenauerring 20b, 76131, Karlsruhe, Germany.
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Impact of energy structure adjustment on air quality: a case study in Beijing, China. ACTA ACUST UNITED AC 2011. [DOI: 10.1007/s11783-011-0357-8] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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