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Abstract
The major organic compositions from biomass burning emissions are monosaccharide derivatives from the breakdown of cellulose, generally accompanied by small amounts of straight-chain, aliphatic, oxygenated compounds, and terpenoids from vegetation waxes, resins/gums, and other biopolymers. Levoglucosan from cellulose can be utilized as a specific or general indicator for biomass combustion emissions in aerosol samples. There are other important compounds, such as dehydroabietic acid, syringaldehyde, syringic acid, vanillic acid, vanillin, homovanillic acid, 4-hydroxybenzoic acid, and p-coumaric acid, which are additional key indicators of biomass burning. In this review, we will address these tracers from different types of biomass burning and the methods used to identify the sources in ambient aerosols. First, the methods of inferring biomass burning types by the ratio method are summarized, including levoglucosan/mannose, syringic acid/vanillic acid, levolgucosan/K+, vanillic acid/4-hydroxybenzoic acid, levoglucosan/OC, and levoglucosan/EC to infer the sources of biomass burning, such as crop residual burning, wheat burning, leaf burning, peatland fire, and forest fire in Asia. Second, we present the source tracer ratio methods that determine the biomass combustion types and their contributions. Finally, we introduce the PCA (Principal component analysis) and PMF (Positive matrix factor) methods to identify the type of biomass burning and its contributions according to emission factors of different species in various plants such as softwood, hardwood, and grass.
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Compositional Characteristics of Atmospheric Aerosols during a Consecutive High Concentration Episode in Seoul, Korea. ATMOSPHERE 2020. [DOI: 10.3390/atmos11030310] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
This study focuses on the temporal variation in the compositional characteristics of atmospheric aerosols in Seoul, South Korea, during the consecutive high aerosol concentration episode from 30 December 2013 to 2 January 2014. The temporal variations in the observed physical, optical, and chemical properties show that there were three distinct episodes during the period: haze, mixed haze/Asian dust, and Asian dust episodes. For the haze period, the concentration of secondary inorganic aerosols increased and both secondary inorganic aerosols and calcium species exhibited simultaneously high concentrations during the mixed haze/Asian dust period. The neutralization factors by ammonia in the haze periods were higher as 1.03 than the other periods, meanwhile the neutralization contribution by calcium carbonate was relatively higher as 1.39 during the Asian dust episode. The backward trajectory analysis showed that concentrations of SO42−, NO3−, and NH4+ were relatively high when air masses moved over East China. Principal component analysis showed that water-soluble components originated from soil dust/incineration, secondary aerosols/biomass burning, and road dust from the haze aerosol. For the mixed haze/Asian dust episode, the major source of aerosols was estimated to have originated from soil dust, pollutants from fossil fuel combustion, biomass burning, and sea-salt emissions. Furthermore, the main sources of ionic species in the Asian dust aerosols were estimated to be sea-salt/soil dust, secondary aerosols/coal combustion, and road dust.
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Fu W, Chen Z, Zhu Z, Liu Q, van den Bosch CCK, Qi J, Wang M, Dang E, Dong J. Spatial and Temporal Variations of Six Criteria Air Pollutants in Fujian Province, China. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:ijerph15122846. [PMID: 30551634 PMCID: PMC6313486 DOI: 10.3390/ijerph15122846] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/06/2018] [Revised: 12/02/2018] [Accepted: 12/11/2018] [Indexed: 12/23/2022]
Abstract
Air pollution has become a critical issue in the urban areas of southeastern China in recent years. A complete understanding of the tempo-spatial characteristics of air pollution can help the public and governmental bodies manage their lives and work better. In this study, data for six criteria air pollutants (including particulate matter (PM2.5, PM10), carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2) and ozone (O3)) from 37 sites in nine major cities within Fujian Province, China were collected between January 2015 to December 2016, and analyzed. We analyzed the spatial and temporal variations of these six criteria pollutants, as well as the attainment rates, and identified what were the major pollutants. Our results show that: (1) the two-year mean values of PM2.5 and PM10 exceeded the Chinese National Ambient Air Quality Standard (CAAQS) standard I levels, whereas other air pollutants were below the CAAQS standard I; (2) the six criteria air pollutants show spatial variations (i.e. most air pollutants were higher in the city center areas, followed by suburban areas and exurban areas, except for O3; and the concentrations of PM10, PM2.5, NO2, O3 were higher in coastal cities than in inland cities); (3) seasonal variations and the no attainment rates of air pollutants were found to be higher in cold seasons and lower in warm seasons, except for O3; (4) the most frequently present air pollutant was PM10, with PM2.5 and O3 being the second and third most frequent, respectively; (5) all the air pollutants, except O3, showed positive correlations with each other. These results provide additional information for the effective control of air pollution in the province of Fujian.
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Affiliation(s)
- Weicong Fu
- College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China.
- Urban Forestry Research in Action, Department of Forest Resources Management, The University of British Columbia, Vancouver V6T 1Z4, BC Canada.
- Collaborative for Advanced Landscape Planning, Faculty of Forestry, The University of British Columbia, Vancouver V6T 1Z4, BC, Canada.
- Faculty of Forestry, The University of British Columbia, Vancouver V6T 1Z4, BC, Canada.
| | - Ziru Chen
- College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China.
- Urban Forestry Research in Action, Department of Forest Resources Management, The University of British Columbia, Vancouver V6T 1Z4, BC Canada.
- Collaborative for Advanced Landscape Planning, Faculty of Forestry, The University of British Columbia, Vancouver V6T 1Z4, BC, Canada.
| | - Zhipeng Zhu
- College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China.
- Faculty of Forestry, The University of British Columbia, Vancouver V6T 1Z4, BC, Canada.
| | - Qunyue Liu
- College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China.
- Urban Forestry Research in Action, Department of Forest Resources Management, The University of British Columbia, Vancouver V6T 1Z4, BC Canada.
| | - Cecil C Konijnendijk van den Bosch
- Urban Forestry Research in Action, Department of Forest Resources Management, The University of British Columbia, Vancouver V6T 1Z4, BC Canada.
- Faculty of Forestry, The University of British Columbia, Vancouver V6T 1Z4, BC, Canada.
| | - Jinda Qi
- Faculty of built environment, University of New South Wales, Sydney 2052, Australia.
| | - Mo Wang
- College of Architecture & Urban Planning, Guangzhou University, Guangzhou 510006, Guangdong, China.
| | - Emily Dang
- Faculty of Forestry, The University of British Columbia, Vancouver V6T 1Z4, BC, Canada.
| | - Jianwen Dong
- College of Landscape Architecture, Fujian Agriculture and Forestry University, Fuzhou 350002, Fujian, China.
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Statistical Analysis of Spatiotemporal Heterogeneity of the Distribution of Air Quality and Dominant Air Pollutants and the Effect Factors in Qingdao Urban Zones. ATMOSPHERE 2018. [DOI: 10.3390/atmos9040135] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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Ramírez O, Sánchez de la Campa AM, Amato F, Catacolí RA, Rojas NY, de la Rosa J. Chemical composition and source apportionment of PM 10 at an urban background site in a high-altitude Latin American megacity (Bogota, Colombia). ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2018; 233:142-155. [PMID: 29059629 DOI: 10.1016/j.envpol.2017.10.045] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/17/2017] [Revised: 10/10/2017] [Accepted: 10/12/2017] [Indexed: 05/23/2023]
Abstract
Bogota registers frequent episodes of poor air quality from high PM10 concentrations. It is one of the main Latin American megacities, located at 2600 m in the tropical Andes, but there is insufficient data on PM10 source contribution. A characterization of the chemical composition and the source apportionment of PM10 at an urban background site in Bogota was carried out in this study. Daily samples were collected from June 2015 to May 2016 (a total of 311 samples). Organic carbon (OC), elemental carbon (EC), water soluble compounds (SO42-, Cl-, NO3-, NH4+), major elements (Al, Fe, Mg, Ca, Na, K, P) and trace metals (V, Cd, Pb, Sr, Ba, among others) were analyzed. The results were interpreted in terms of their variability during the rainy season (RS) and the dry season (DS). The data obtained revealed that the carbonaceous fraction (∼51%) and mineral dust (23%) were the main PM10 components, followed by others (15%), Secondary Inorganic Compounds (SIC) (11%) and sea salt (0.4%). The average concentrations of soil, SIC and OC were higher during RS than DS. However, peak values were observed during the DS due to photochemical activity and forest fires. Although trace metals represented <1% of PM10, high concentrations of toxic elements such as Pb and Sb on RS, and Cu on DS, were obtained. By using a PMF model, six factors were identified (∼96% PM10) including fugitive dust, road dust, metal processing, secondary PM, vehicles exhaust and industrial emissions. Traffic (exhaust emissions + road dust) was the major PM10 source, accounting for ∼50% of the PM10. The results provided novel data about PM10 chemical composition, its sources and its seasonal variability during the year, which can help the local government to define control strategies for the main emission sources during the most critical periods.
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Affiliation(s)
- Omar Ramírez
- Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen s/n, 21071, Huelva, Spain; Environmental Engineering Program, Group of Applied Environmental Studies-GEAA, Universidad Nacional Abierta y a Distancia-UNAD, Tv 31 #12-38 sur, Bogota, Colombia.
| | - A M Sánchez de la Campa
- Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen s/n, 21071, Huelva, Spain
| | - Fulvio Amato
- Institute for Environmental Assessment and Water Research (IDÆA), Spanish National Research Council (CSIC), C/Jordi Girona 18-26, Barcelona, Spain
| | - Ruth A Catacolí
- Environmental Engineering Program, Universidad Libre, Cr. 70A # 53-40, Bogota, Colombia
| | - Néstor Y Rojas
- Department of Chemical and Environmental Engineering, Universidad Nacional de Colombia, Cr. 30 # 45-03, Edif. 412, Of. 206. Bogota, Colombia
| | - Jesús de la Rosa
- Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen s/n, 21071, Huelva, Spain
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Yotova GI, Tsitouridou R, Tsakovski SL, Simeonov VD. Urban air quality assessment using monitoring data of fractionized aerosol samples, chemometrics and meteorological conditions. JOURNAL OF ENVIRONMENTAL SCIENCE AND HEALTH. PART A, TOXIC/HAZARDOUS SUBSTANCES & ENVIRONMENTAL ENGINEERING 2016; 51:544-552. [PMID: 26942452 DOI: 10.1080/10934529.2016.1141620] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
The present article deals with assessment of urban air by using monitoring data for 10 different aerosol fractions (0.015-16 μm) collected at a typical urban site in City of Thessaloniki, Greece. The data set was subject to multivariate statistical analysis (cluster analysis and principal components analysis) and, additionally, to HYSPLIT back trajectory modeling in order to assess in a better way the impact of the weather conditions on the pollution sources identified. A specific element of the study is the effort to clarify the role of outliers in the data set. The reason for the appearance of outliers is strongly related to the atmospheric condition on the particular sampling days leading to enhanced concentration of pollutants (secondary emissions, sea sprays, road and soil dust, combustion processes) especially for ultra fine and coarse particles. It is also shown that three major sources affect the urban air quality of the location studied-sea sprays, mineral dust and anthropogenic influences (agricultural activity, combustion processes, and industrial sources). The level of impact is related to certain extent to the aerosol fraction size. The assessment of the meteorological conditions leads to defining of four downwind patterns affecting the air quality (Pelagic, Western and Central Europe, Eastern and Northeastern Europe and Africa and Southern Europe). Thus, the present study offers a complete urban air assessment taking into account the weather conditions, pollution sources and aerosol fractioning.
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Affiliation(s)
- Galina I Yotova
- a Analytical Chemistry, Faculty of Chemistry and Pharmacy, University of Sofia "St. Kl. Okhridski" , Sofia , Bulgaria
| | - Roxani Tsitouridou
- b Laboratory of Analytical Chemistry, Chemical Engineering Department, Aristotle University of Thessaloniki , Thessaloniki , Greece
| | - Stefan L Tsakovski
- a Analytical Chemistry, Faculty of Chemistry and Pharmacy, University of Sofia "St. Kl. Okhridski" , Sofia , Bulgaria
| | - Vasil D Simeonov
- a Analytical Chemistry, Faculty of Chemistry and Pharmacy, University of Sofia "St. Kl. Okhridski" , Sofia , Bulgaria
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Wang L, Zhou X, Ma Y, Cao Z, Wu R, Wang W. Carbonaceous aerosols over China--review of observations, emissions, and climate forcing. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2016; 23:1671-1680. [PMID: 26385857 DOI: 10.1007/s11356-015-5398-2] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/14/2015] [Accepted: 09/08/2015] [Indexed: 06/05/2023]
Abstract
Carbonaceous aerosols have been attracting attention due to the influence on visibility, air quality, and regional climate. Statistical analyses based on concentration levels, spatial-temporal variations, correlations, and organic carbon (OC) to element carbon (EC) ratios from published data of OC and EC in particulate matter (PM2.5 and PM10) were carried out in order to give a carbonaceous aerosol profile in China. The results showed maxima for OC of 29.5 ± 18.2 μg C m(-3) and for EC of 8.4 ± 6.3 μg C m(-3) in winter and minima for OC of 12.9 ± 7.7 μg C m(-3) in summer and for EC of 4.6 ± 2.8 μg C m(-3) in spring. In addition, OC and EC both had higher concentrations in urban than those in rural sites. Carbonaceous aerosol levels in China are about three to seven times higher compared to those in the USA and Europe. OC and EC occupied 20 ± 6 and 7 ± 3% of PM2.5 mass and 17 ± 7 and 5 ± 3% of PM10 mass, respectively, implying that carbonaceous aerosols are the main component of PM, especially OC. Secondary organic carbon (SOC) was a significant portion of PM and contributed 41 ± 26% to OC and 8 ± 6% to PM2.5 mass. The OC/EC ratio was 3.63 ± 1.73, which, along with the good correlation between OC and EC and the OC to EC slope of 2.29, signifies that coal combustion and/or vehicular exhaust is the dominated carbonaceous aerosol source in China. These provide a primary observation-based understanding of carbonaceous aerosol pollution in China and have a great significance in improving the emission inventory and climate forcing evaluation.
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Affiliation(s)
- Linpeng Wang
- Environment Research Institute, Shandong University, Shanda South Road 27, Ji'nan, 250100, Shandong, China
| | - Xuehua Zhou
- Environment Research Institute, Shandong University, Shanda South Road 27, Ji'nan, 250100, Shandong, China.
| | - Yujie Ma
- Environment Research Institute, Shandong University, Shanda South Road 27, Ji'nan, 250100, Shandong, China
| | - Zhaoyu Cao
- Environment Research Institute, Shandong University, Shanda South Road 27, Ji'nan, 250100, Shandong, China
| | - Ruidong Wu
- Environment Research Institute, Shandong University, Shanda South Road 27, Ji'nan, 250100, Shandong, China
| | - Wenxing Wang
- Environment Research Institute, Shandong University, Shanda South Road 27, Ji'nan, 250100, Shandong, China
- Chinese Research Academy of Environmental Sciences, Beijing, 100012, China
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An J, Duan Q, Wang H, Miao Q, Shao P, Wang J, Zou J. Fine particulate pollution in the Nanjing northern suburb during summer: composition and sources. ENVIRONMENTAL MONITORING AND ASSESSMENT 2015; 187:561. [PMID: 26255270 DOI: 10.1007/s10661-015-4765-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/11/2015] [Accepted: 07/20/2015] [Indexed: 06/04/2023]
Abstract
To understand the chemical composition characteristic of pollution in a northern suburb of Nanjing, particle samples were collected by two Andersen cascade impactors from May to July 2013. The positive matrix factorization version 3 (EPA-PMF 3.0) was applied to identify the source contribution of PM2.1 concentrations in the study area. Source categories were determined based on the chemical component abundances in the source profiles. Overall, results indicated that seven factors were obtained. The factors are identified as follows: (I) secondary aerosol, characterized by high concentrations of NH4 (+), NO3 (-), and SO4 (2-), accounting for 20.22 %; (II) metallurgical aerosol, characterized by high concentrations of Pb, Cd, and Zn, accounting for 6.71 %; (III) road dust, characterized by high concentrations of Mg, Ca, Na, Al, and Ba, accounting for 11.85 %; (IV) biomass burning, characterized by high concentrations of K(+), Na(+), Cl(-), and K, accounting for 10.17 %; (V) residual oil, characterized by high concentrations of V and Cr, accounting for 16.63 %; (VI) iron and steel industry, characterized by high concentrations of Mn and Fe, accounting for 9.48 %; and (VII) vehicle exhaust, characterized by high concentrations of organic carbon (OC), Mo, elemental carbon (EC) and K, accounting for 24.94 %.
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Affiliation(s)
- Junlin An
- Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Key Laboratory for Aerosol-Cloud-Precipitation of China Meteorological Administration, Nanjing University of Information Science and Technology, Nanjing, 210044, China,
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