1
|
Nizamani MM, Zhang HL, Bolan N, Zhang Q, Guo L, Lou Y, Zhang HY, Wang Y, Wang H. Understanding the drivers of PM 2.5 concentrations in Chinese cities: A comprehensive study of anthropogenic and environmental factors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 361:124783. [PMID: 39173864 DOI: 10.1016/j.envpol.2024.124783] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/15/2024] [Revised: 06/27/2024] [Accepted: 08/19/2024] [Indexed: 08/24/2024]
Abstract
Understanding the factors that drive PM2.5 concentrations in cities with varying population and land areas is crucial for promoting sustainable urban population health. This knowledge is particularly important for countries where air pollution is a significant challenge. Most existing studies have investigated either anthropogenic or environmental factors in isolation, often in limited geographic contexts; however, this study fills this knowledge gap. We employed a multimethodological approach, using both multiple linear regression models and geographically weighted regression (GWR), to assess the combined and individual effects of these factors across different cities in China. The variables considered were urban built-up area, land consumption rate (LCR), population size, population growth rate (PGR), longitude, and latitude. Compared with other studies, this study provides a more comprehensive understanding of PM2.5 drivers. The findings of this study showed that PGR and population size are key factors affecting PM2.5 concentrations in smaller cities. In addition, the extent of urban built-up areas exerts significant influence in medium and large cities. Latitude was found to be a positive predictor for PM2.5 concentrations across all city sizes. Interestingly, the northeast, south, and southwest regions demonstrated lower PM2.5 levels than the central, east, north, and northwest regions. The GWR model underscored the importance of considering spatial heterogeneity in policy interventions. However, this research is not without limitations. For instance, international pollution transfers were not considered. Despite the limitation, this study advances the existing literature by providing an understanding of how both anthropogenic and environmental factors, in conjunction with city scale, shape PM2.5 concentrations. This integrated approach offers invaluable insights for tailoring more effective air pollution management strategies across cities of different sizes and characteristics.
Collapse
Affiliation(s)
- Mir Muhammad Nizamani
- Department of Plant Pathology, Agricultural College, Guizhou University, Guiyang, 550025, China
| | - Hai-Li Zhang
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresources, School of Life Sciences, Hainan University, Haikou, 570228, China
| | - Nanthi Bolan
- UWA School of Agriculture and Environment, The University of Western Australia, Perth, Western Australia, 6009, Australia; The UWA Institute of Agriculture, The University of Western Australia, Perth, Western Australia, 6009, Australia
| | - Qian Zhang
- Department of Plant Pathology, Agricultural College, Guizhou University, Guiyang, 550025, China
| | - Lingyuan Guo
- Hainan Key Laboratory for Sustainable Utilization of Tropical Bioresources, School of Life Sciences, Hainan University, Haikou, 570228, China
| | - YaHui Lou
- Zhongtie Electrical Railway Operation Management Co., Ltd, China
| | - Hai-Yang Zhang
- College of International Studies, Sichuan University, Chengdu, 610065, China
| | - Yong Wang
- Department of Plant Pathology, Agricultural College, Guizhou University, Guiyang, 550025, China.
| | - Hailong Wang
- School of Environmental and Chemical Engineering, Foshan University, Foshan, 528000, China; Guangdong Provincial Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Institute of Eco-environmental and Soil Sciences, Guangdong Academy of Sciences, Guangzhou, 510650, China.
| |
Collapse
|
2
|
Bendl J, Saraji-Bozorgzad MR, Käfer U, Padoan S, Mudan A, Etzien U, Giocastro B, Schade J, Jeong S, Kuhn E, Sklorz M, Grimmer C, Streibel T, Buchholz B, Zimmermann R, Adam T. How do different marine engine fuels and wet scrubbing affect gaseous air pollutants and ozone formation potential from ship emissions? ENVIRONMENTAL RESEARCH 2024; 260:119609. [PMID: 39002626 DOI: 10.1016/j.envres.2024.119609] [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: 03/25/2024] [Revised: 07/09/2024] [Accepted: 07/10/2024] [Indexed: 07/15/2024]
Abstract
Sulphur Emission Control Areas (SECAs), mandated by the International Maritime Organization (IMO), regulate fuel sulphur content (FSC) to mitigate the environmental and health impact of shipping emissions in coastal areas. Currently, FSC is limited to 0.1% (w/w) within and 0.5% (w/w) outside SECAs, with exceptions for ships employing wet sulphur scrubbers. These scrubbers enable vessels using non-compliant fuels such as high-sulphur heavy fuel oils (HFOs) to enter SECAs. However, while sulphur reduction via scrubbers is effective, their efficiency in capturing other potentially harmful gases remains uncertain. Moreover, emerging compliant fuels like highly aromatic fuels or low-sulphur blends lack characterisation and may pose risks. Over three years, we assessed emissions from an experimental marine engine at 25% and 75% load, representative of manoeuvring and cruising, respectively. First, characterizing emissions from five different compliant and non-compliant fuels (marine gas oil MGO, hydro-treated vegetable oil HVO, high-, low- and ultra-low sulphur HFOs), we calculated emission factors (EF). Then, the wet scrubber gas-phase capture efficiency was measured using compliant and non-compliant HFOs. NOx EF varied among fuels (5200-19700 mg/kWh), with limited scrubber reduction. CO (EF 750-13700 mg/kWh) and hydrocarbons (HC; EF 122-1851 mg/kWh) showed also insufficient abatement. Carcinogenic benzene was notably higher at 25% load and about an order of magnitude higher with HFOs compared to MGO and HVO, with no observed scrubber reduction. In contrast, carbonyls such as carcinogenic formaldehyde and acetaldehyde, acting as ozone precursors, were effectively scrubbed due to their polarity and water solubility. The ozone formation potential (OFP) of all fuels was examined. Significant EF differences between fuels and engine loads were observed, with the wet scrubber providing limited or no reduction of gaseous emissions. We suggest enhanced regulations and emission abatements in the marine sector to mitigate gaseous pollutants harmful to human health and the environment.
Collapse
Affiliation(s)
- Jan Bendl
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany.
| | - Mohammad Reza Saraji-Bozorgzad
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany.
| | - Uwe Käfer
- Joint Mass Spectrometry Center (JMSC) at Comprehensive Molecular Analytics (CMA), Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
| | - Sara Padoan
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany.
| | - Ajit Mudan
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany.
| | - Uwe Etzien
- Chair of Piston Machines and Internal Combustion Engines, Faculty of Mechanical Engineering and Marine Technology, University of Rostock, Albert-Einstein-Strasse 2, 18059 Rostock, Germany.
| | - Barbara Giocastro
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany; Joint Mass Spectrometry Center (JMSC) at Comprehensive Molecular Analytics (CMA), Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
| | - Julian Schade
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany.
| | - Seongho Jeong
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany; Joint Mass Spectrometry Center (JMSC) at Analytical Chemistry, Institute of Chemistry, University of Rostock, Albert-Einstein-Strasse 27, 18059 Rostock, Germany.
| | - Evelyn Kuhn
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany; Joint Mass Spectrometry Center (JMSC) at Comprehensive Molecular Analytics (CMA), Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
| | - Martin Sklorz
- Joint Mass Spectrometry Center (JMSC) at Comprehensive Molecular Analytics (CMA), Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
| | - Christoph Grimmer
- Joint Mass Spectrometry Center (JMSC) at Analytical Chemistry, Institute of Chemistry, University of Rostock, Albert-Einstein-Strasse 27, 18059 Rostock, Germany.
| | - Thorsten Streibel
- Joint Mass Spectrometry Center (JMSC) at Analytical Chemistry, Institute of Chemistry, University of Rostock, Albert-Einstein-Strasse 27, 18059 Rostock, Germany.
| | - Bert Buchholz
- Chair of Piston Machines and Internal Combustion Engines, Faculty of Mechanical Engineering and Marine Technology, University of Rostock, Albert-Einstein-Strasse 2, 18059 Rostock, Germany.
| | - Ralf Zimmermann
- Joint Mass Spectrometry Center (JMSC) at Comprehensive Molecular Analytics (CMA), Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany; Joint Mass Spectrometry Center (JMSC) at Analytical Chemistry, Institute of Chemistry, University of Rostock, Albert-Einstein-Strasse 27, 18059 Rostock, Germany.
| | - Thomas Adam
- University of the Bundeswehr Munich, Faculty for Mechanical Engineering, Institute of Chemistry and Environmental Engineering, Werner-Heisenberg-Weg 39, 85577 Neubiberg, Germany; Joint Mass Spectrometry Center (JMSC) at Comprehensive Molecular Analytics (CMA), Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764 Neuherberg, Germany.
| |
Collapse
|
3
|
Zeng L, Xiao S, Dai Y, Chen T, Wang H, Yang P, Huang G, Yan M, You Y, Zheng X, Zhang S, Wu Y. Characterization of on-road nitrogen oxides and black carbon emissions from high emitters of heavy-duty diesel vehicles in China. JOURNAL OF HAZARDOUS MATERIALS 2024; 477:135225. [PMID: 39059297 DOI: 10.1016/j.jhazmat.2024.135225] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2024] [Revised: 06/12/2024] [Accepted: 07/14/2024] [Indexed: 07/28/2024]
Abstract
Heavy-duty diesel vehicles (HDDVs) significantly contribute to atmospheric nitrogen oxides (NOX) and black carbon (BC), with high emitters within the HDDV fleet impacting the total emissions. However, emission patterns and contributions of high emitters are rarely explored from a fleet-perspective. We investigated NOX and BC emission factors (EFs) from 1925 HDDVs in Shenzhen by the plume-chasing method, and found that the fleet-average EFs decreased with stricter emission standards. Unexpectedly, the average NOX EF for the China IV fleet was comparable with that for the China III fleet due to possible ineffective aftertreatment in high-emitter sectors of China IV HDDVs. Decreasing trend in average NOX EF since 2017 reflected the effective emission controls by the implementation of China V standard. Besides, semi-trailer tractors exhibited a higher incidence of NOX over-emissions, whereas BC high emitters were more pronounced in box trucks. Total NOX and BC emissions from HDDVs in Shenzhen were revisited, reaching 54.0 and 1.1 Gg·yr-1, with updated NOX EF correcting a 26.2 % underestimation in national guidelines. Notably, eliminating high emitters yields greater emission reduction benefits than merely retiring old HDDVs, with BC reduction outpacing NOX. This study provides new insights into the implementation of targeted emission reduction measures for HDDVs.
Collapse
Affiliation(s)
- Lewei Zeng
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, PR China
| | - Shupei Xiao
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, PR China
| | - Yifei Dai
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, PR China
| | - Ting Chen
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, PR China; State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China
| | - Hui Wang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China
| | - Pan Yang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China
| | - Guancong Huang
- Shenzhen Academy of Environmental Sciences, Shenzhen, Guangdong 518022, PR China
| | - Min Yan
- Shenzhen Academy of Environmental Sciences, Shenzhen, Guangdong 518022, PR China
| | - Yan You
- National Observation and Research Station of Coastal Ecological Environments in Macao, Macao Environmental Research Insititute, Macau University of Science and Technology, 999078, Macao Special Administrative Regions of China
| | - Xuan Zheng
- College of Chemistry and Environmental Engineering, Shenzhen University, Shenzhen, Guangdong 518060, PR China.
| | - Shaojun Zhang
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China
| | - Ye Wu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, Tsinghua University, Beijing 100084, PR China
| |
Collapse
|
4
|
Mueller N, Cirach M, Ambros A, Daher C, Nieuwenhuijsen M, Basagaña X. Health impact assessment of port-sourced air pollution in Barcelona. PLoS One 2024; 19:e0305236. [PMID: 39213287 PMCID: PMC11364232 DOI: 10.1371/journal.pone.0305236] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/28/2024] [Indexed: 09/04/2024] Open
Abstract
INTRODUCTION Air pollution is a major health risk factor. Ports might be an understudied source of air pollution. METHODS We conducted a spatial health impact assessment (HIA) of port-sourced air pollution for Barcelona for 2017 at the neighbourhood level. Total NO2 and PM10 and port-sourced NO2, PM10 and PM2.5 concentrations were available through the ADMS-Urban model. Population data, mortality and morbidity data, and risk estimates were obtained. We followed standard HIA methodologies and calculated relative risks and impact fractions for 1.35 million adults living in 73 neighbourhoods. RESULTS The city-wide mean total NO2 and PM10 concentrations were 37.88 μg/m3 (range: 19.61-52.17 μg/m3) and 21.68 μg/m3 (range: 17.33-26.69 μg/m3), respectively, of which 7% (range: 2-36%) and 1% (range: 0-7%) were port-sourced, respectively. The mean port-sourced PM2.5 concentration was 0.19 μg/m3 (range: 0.06-1.38 μg/m3). We estimated that 1,123 (PI: 0-3,060) and 1,230 (95% CI: 0-2,566) premature deaths were attributable to total NO2 and PM10, respectively, of which 8.1% (91; PI: 0-264) and 1.1% (13; 95% CI 0-29) were attributable to port-sourced NO2 and PM10, respectively. 20 (95% CI: 15-26) premature deaths were attributable to port-sourced PM2.5. Additionally, a considerable morbidity burden and losses in life expectancy were attributable to port-sourced air pollution. Neighbourhoods closest to the port in the south-east were most adversely affected, gradually decreasing towards the north-west. CONCLUSIONS The port is an understudied air pollution source in Barcelona with strong health impacts. Cities need local insight into health risk factors, their sources, attributable burdens and distributions for defining targeted policies.
Collapse
Affiliation(s)
- Natalie Mueller
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Marta Cirach
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Albert Ambros
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Carolyn Daher
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Mark Nieuwenhuijsen
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Xavier Basagaña
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| |
Collapse
|
5
|
Belachsen I, Broday DM. Decomposing PM 2.5 concentrations in urban environments into meaningful factors: 1. Separating the contribution of local anthropogenic activities from background and long-range transport. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 940:173749. [PMID: 38844234 DOI: 10.1016/j.scitotenv.2024.173749] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 06/02/2024] [Accepted: 06/02/2024] [Indexed: 06/10/2024]
Abstract
Fine particulate matter (PM2.5) is a complex mixture of aerosol particles with varying properties and sources, both local and distant. In areas lacking detailed monitoring of PM2.5 speciation, the common source-apportionment analyses are not applicable. This study demonstrates an alternative framework for estimating sources and processes that affect observed PM2.5 concentrations when information on the particle composition is unavailable. Eight years (2012-2019) of half-hourly PM2.5 observations from 10 air quality monitoring (AQM) stations, clustered according to their airmass transport sector were analyzed, using Non-negative Matrix Factorization (NMF). Factors were determined based on their variation in time, space, and between airmass sectors. Employing a supervised machine-learning model provided insights into the relationships between the extracted factors, meteorological parameters and co-measured airborne pollutants. Factor interpretations were evaluated through comparisons with measurements of PM2.5 species from a nearby Surface PARTiculate mAtter Network (SPARTAN) station. The NMF successfully separated background factors from an urban anthropogenic-activity factor, with the latter accounting for approximately 60 % of the observed PM2.5 levels in Tel Aviv (∼10±6μg/m3). Positive monotonic relationships were observed between the PM2.5 urban anthropogenic-activity factor and measurements of nitrogen oxides (NOx) and absolute humidity (AH), representing the impact of traffic emissions and hygroscopic growth, respectively. The summer background factor was found to represent long-range transport (LRT) from Europe, showing a good agreement (R2 = 0.81) with ammonium sulphate concentrations. Our results demonstrate that a spatial NMF analysis can reliably estimate contributions of different sources with distinct compositions and properties to the total observed PM2.5. Using such an analysis, future environmental health studies could assess health risks associated with exposure to distinct PM2.5 fractions. This information may assist decision makers to set environmental targets for abating PM2.5 with specific compositions and properties.
Collapse
Affiliation(s)
- Idit Belachsen
- Faculty of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, Israel
| | - David M Broday
- Faculty of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, Israel.
| |
Collapse
|
6
|
Belachsen I, Broday DM. Decomposing PM 2.5 concentrations in urban environments into meaningful factors 2. Extracting the contribution of traffic-related exhaust emissions. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 940:173715. [PMID: 38852869 DOI: 10.1016/j.scitotenv.2024.173715] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 05/13/2024] [Accepted: 05/31/2024] [Indexed: 06/11/2024]
Abstract
Vehicle-emitted fine particulate matter (PM2.5) has been associated with significant health outcomes and environmental risks. This study estimates the contribution of traffic-related exhaust emissions (TREE) to observed PM2.5 using a novel factorization framework. Specifically, co-measured nitrogen oxides (NOx) concentrations served as a marker of vehicle-tailpipe emissions and were integrated into the optimization of a Non-negative Matrix Factorization (NMF) analysis to guide the factor extraction. The novel TREE-NMF approach was applied to long-term (2012-2019) PM2.5 observations from air quality monitoring (AQM) stations in two urban areas. The extracted TREE factor was evaluated against co-measured black carbon (BC) and PM2.5 species to which the TREE-NMF optimization was blind. The contribution of the TREE factor to the observed PM2.5 concentrations at an AQM station from the first location showed close agreement (R2=0.79) with monitored BC data. In the second location, a comparison of the extracted TREE factor with measurements at a nearby Surface PARTiculate mAtter Network (SPARTAN) station revealed moderate correlations with PM2.5 species commonly associated with fuel combustion, and a good linear regression fit with measured equivalent BC concentrations. The estimated concentrations of the TREE factor at the second location accounted for 7-11 % of the observed PM2.5 in the AQM stations. Moreover, analysis of specific days known to be characterized by little traffic emissions suggested that approximately 60-78 % of the traffic-related PM2.5 concentrations could be attributed to particulate traffic-exhaust emissions. The methodology applied in this study holds great potential in areas with limited monitoring of PM2.5 speciation, in particular BC, and its results could be valuable for both future environmental health research, regional radiative forcing estimates, and promulgation of tailored regulations for traffic-related air pollution abatement.
Collapse
Affiliation(s)
- Idit Belachsen
- Faculty of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, Israel
| | - David M Broday
- Faculty of Civil and Environmental Engineering, Technion, Israel Institute of Technology, Haifa, Israel.
| |
Collapse
|
7
|
Attri P, Mani D, Satyanarayanan M, Reddy D, Kumar D, Sarkar S, Kumar S, Hegde P. Atmospheric aerosol chemistry and source apportionment of PM10 using stable carbon isotopes and PMF modelling during fireworks over Hyderabad, southern India. Heliyon 2024; 10:e26746. [PMID: 38495155 PMCID: PMC10943357 DOI: 10.1016/j.heliyon.2024.e26746] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 02/11/2024] [Accepted: 02/19/2024] [Indexed: 03/19/2024] Open
Abstract
This study examined the influence of fireworks on atmospheric aerosols over the Southern Indian city of Hyderabad during festival of Diwali using mass closure, stable carbon isotopes and the EPA-PMF model. Identification of chemical species in day and night time aerosol samples for 2019 and 2020 Diwali weeks showed increased concentrations of NH4+, NO3-, SO42-, K+, organic carbon (OC), Ba, Pb and Li, which were considered as tracers for fireworks. PM10 source apportionment was done using inorganic (trace elements, major ions) and carbonaceous (organic and elemental carbon; OC & EC) constituents, along with stable isotopic compositions of TC and EC. K+/Na+ ∼1 and K+nss/OC > 0.5 indicated contribution from fireworks. High NO3-, NH4+, Na+, Cl- and SO42- suggested the presence of deliquescent salts NaCl, NH4NO3 and (NH4)2SO4. TAE/TCE >1 suggested H+ exclusion, indicating possible presence of H2SO4 and NH4HSO4 in the aerosols. Ba, Pb, Sb, Sr and Fe increased by 305 (87), 12 (11), 12 (3), 3 (2) and 3 (4) times on Diwali nights, compared to pre-Diwali of 2019 (2020), and are considered as metallic tracers of fireworks. δ13CTC and δ13CEC in aerosols closely resembled that of diesel and C3 plant burning emissions, with meagre contribution from firecrackers during Diwali period. The δ13CEC was relatively depleted than δ13CTC and δ13COC. For both years, δ13COC-EC (δ13COC - δ13CEC) were positive, suggesting photochemical aging of aerosols during long-range transport, while for pre-Diwali 2019 and post-Diwali 2020, δ13COC-EC were negative with high OC/EC ratio, implying secondary organic aerosols formation. High toluene during Diwali week contributed to fresh SOA formation, which reacted with precursor 12C, leading to 13C depletions. Eight-factored EPA-PMF source apportionment indicated highest contribution from residue/waste burning, followed by marine/dust soil and fireworks, while least was contributed from solid fuel/coal combustion.
Collapse
Affiliation(s)
- Pradeep Attri
- Centre for Earth, Ocean and Atmospheric Sciences, University of Hyderabad, Telangana 500046, India
| | - Devleena Mani
- Centre for Earth, Ocean and Atmospheric Sciences, University of Hyderabad, Telangana 500046, India
| | - M. Satyanarayanan
- CSIR-National Geophysical Research Institute, Hyderabad, Telangana 500007, India
| | - D.V. Reddy
- CSIR-National Geophysical Research Institute, Hyderabad, Telangana 500007, India
| | - Devender Kumar
- CSIR-National Geophysical Research Institute, Hyderabad, Telangana 500007, India
| | | | - Sanjeev Kumar
- Physical Research Laboratory, Ahmedabad, Gujarat 380009, India
| | - Prashant Hegde
- Space Physics Laboratory, Vikram Sarabhai Space Centre, Thiruvananthapuram, Kerala 695021, India
| |
Collapse
|
8
|
In 't Veld M, Seco R, Reche C, Pérez N, Alastuey A, Portillo-Estrada M, Janssens IA, Peñuelas J, Fernandez-Martinez M, Marchand N, Temime-Roussel B, Querol X, Yáñez-Serrano AM. Identification of volatile organic compounds and their sources driving ozone and secondary organic aerosol formation in NE Spain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 906:167159. [PMID: 37758152 DOI: 10.1016/j.scitotenv.2023.167159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 08/30/2023] [Accepted: 09/15/2023] [Indexed: 10/03/2023]
Abstract
Volatile organic compounds (VOCs) play a crucial role in the formation of ozone (O3) and secondary organic aerosol (SOA). We conducted measurements of VOC ambient mixing ratios during both summer and winter at two stations: a Barcelona urban background station (BCN) and the Montseny rural background station (MSY). Subsequently, we employed positive matrix factorization (PMF) to analyze the VOC mixing ratios and identify their sources. Our analysis revealed five common sources: anthropogenic I (traffic & industries); anthropogenic II (traffic & biomass burning); isoprene oxidation; monoterpenes; long-lifetime VOCs. To assess the impact of these VOCs on the formation of secondary pollutants, we calculated the ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAP) associated with each VOC. In conclusion, our study provides insights into the sources of VOCs and their contributions to the formation of ozone and SOA in NE Spain. The OFP was primarily influenced by anthropogenic aromatic compounds from the traffic & industries source at BCN (38-49 %) and during winter at MSY (34 %). In contrast, the summer OFP at MSY was primarily driven by biogenic contributions from monoterpenes and isoprene oxidation products (45 %). Acetaldehyde (10-35 %) and methanol (13-14 %) also made significant OFP contributions at both stations. Anthropogenic aromatic compounds originating from traffic, industries, and biomass burning played a dominant role (88-93 %) in SOA formation at both stations during both seasons. The only exception was during the summer at MSY, where monoterpenes became the primary driver of SOA formation (41 %). These findings emphasize the importance of considering both anthropogenic and biogenic VOCs in air quality management strategies.
Collapse
Affiliation(s)
- Marten In 't Veld
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain; Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya, 08034 Barcelona, Spain.
| | - Roger Seco
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain
| | - Noemi Pérez
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain
| | - Andres Alastuey
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain
| | - Miguel Portillo-Estrada
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium
| | - Ivan A Janssens
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium
| | - Josep Peñuelas
- CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; CSIC, Global Ecology Unit, CREAF-CSIC-UAB, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain
| | - Marcos Fernandez-Martinez
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium; CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; CSIC, Global Ecology Unit, CREAF-CSIC-UAB, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain
| | | | | | - Xavier Querol
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain
| | - Ana Maria Yáñez-Serrano
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, 08034 Barcelona, Spain; CREAF, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain; CSIC, Global Ecology Unit, CREAF-CSIC-UAB, E08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain
| |
Collapse
|
9
|
Anastasopolos AT, Hopke PK, Sofowote UM, Mooibroek D, Zhang JJY, Rouleau M, Peng H, Sundar N. Evaluating the effectiveness of low-sulphur marine fuel regulations at improving urban ambient PM 2.5 air quality: Source apportionment of PM 2.5 at Canadian Atlantic and Pacific coast cities with implementation of the North American Emissions Control Area. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 904:166965. [PMID: 37699485 DOI: 10.1016/j.scitotenv.2023.166965] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 09/07/2023] [Accepted: 09/08/2023] [Indexed: 09/14/2023]
Abstract
Ambient fine size fraction particulate matter (PM2.5) sources were resolved by positive matrix factorization at two Canadian cities on the Atlantic and Pacific coast over the 2010-2016 period, corresponding to implementation of the North American Emissions Control Area (NA ECA) low-sulphur marine fuel regulations. Source types contributing to local PM2.5 concentrations were: ECA regulation-related (residual oil, anthropogenic sulphate), urban transportation and residential (gasoline, diesel, secondary nitrate, biomass burning, road dust/soil), industry (refinery, Pb-enriched), and largely natural (biogenic sulphate, sea salt). Anthropogenic sources accounted for approximately 80 % of PM2.5 mass over 2010-2016. Anthropogenic and biogenic sources of PM2.5-sulphate were separated and apportioned. Anthropogenic PM2.5-sulphate was approximately 2-3 times higher than biogenic PM2.5-sulphate prior to implementation of the NA ECA low-S marine fuel regulations, decreasing to 1-2 times higher after regulation implementation. Non-marine anthropogenic sources (gasoline, road dust, local industry factors) were shown to together contribute 38 % - 45 % of urban PM2.5. At both coastal cities, the residual oil and anthropogenic sulphate factors clearly reflected the effects of the low-S fuel regulations at reducing primary and secondary sulphur-related PM2.5 emissions. Comparing a pre-regulation and post-regulation period, residual oil combustion PM2.5 decreased by 0.24-0.25 μg/m3 (94%-95 % decrease) in both cities and anthropogenic sulphate PM2.5 decreased by 0.78 μg/m3 in Halifax (47 % decrease) and 0.71 μg/m3 in Burnaby (58 % decrease). Regulation-related PM2.5 across these factors decreased by approximately 1 μg/m3 after regulation implementation, providing a quantified lower estimate of the beneficial influence of the regulations on urban ambient PM2.5 concentrations. Further reductions in coastal city ambient PM2.5 may best consider air quality strategies that include multiple sources, including marine shipping and non-marine anthropogenic source types given this analysis found that marine vessel emissions remain an important source of urban ambient PM2.5.
Collapse
Affiliation(s)
| | - Philip K Hopke
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
| | - Uwayemi M Sofowote
- Environmental Monitoring and Reporting Branch, Ontario Ministry of the Environment, Conservation and Parks, Toronto, Ontario, Canada
| | - Dennis Mooibroek
- National Institute for Public Health and the Environment, Bilthoven, Netherlands
| | - Joyce J Y Zhang
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Mathieu Rouleau
- Healthy Environments and Consumer Safety Branch, Health Canada, Ottawa, Ontario, Canada
| | - Hui Peng
- Environmental Protection Branch, Environment and Climate Change Canada, Ottawa, Ontario, Canada
| | - Navin Sundar
- Environmental Protection Branch, Environment and Climate Change Canada, Vancouver, British Columbia, Canada
| |
Collapse
|
10
|
Bai Z, Shao J, Xu W, Zhu K, Zhao L, Wang L, Chen J. An unneglected source to ambient brown carbon and VOCs at harbor area: LNG tractor truck. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 900:165575. [PMID: 37499815 DOI: 10.1016/j.scitotenv.2023.165575] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 06/23/2023] [Accepted: 07/14/2023] [Indexed: 07/29/2023]
Abstract
The ambient air quality of harbors area in Asia is commonly more polluted compared to other continents. The airborne pollutant is directly or indirectly related to a significant impact of traffic emissions. This study for the first time assessed the impacts on brown carbon (BrC) and volatile organic compounds (VOCs) from in-port liquid natural gas (LNG) tractor truck at harbor areas, via conducting real-time monitoring of VOCs characteristic and sampling for ambient air at a harbor (named as W harbor) in Shanghai, China, collecting emissions of in-port LNG tractor truck and miniCast in laboratory, as well as statistics of external container diesel trucks in the port for further validation. HPLC/DAD/Q-Tof MS was adopted for sample analysis. Results showed that many CHO compounds were associated with vehicle exhausts. Among of them, aliphatic CHO compounds with low degree of unsaturation were identified as fatty acids and fatty acid methyl esters extensively existing in fuel combustion emissions. And non-aliphatic CHO compounds characterized by low O/C ratios (<0.17) identified for the harbor air came from the emissions of in-port LNG power trucks with low-speed driving and idling. The ambient average non-methane total hydrocarbons (NMHC) concentration (0.59 ppm) at W harbor was much greater than that for other areas in Shanghai. The higher ratios of toluene/benzene (3.30) and m/p-xylene/ethylbenzene (3.11) observed at W harbor implied instead of external container diesel trucks, the dominating contributing of internal LNG tractor trucks to ambient VOCs cannot be neglected. This study concluded that LNG is not as clean as it was expected. The LNG-fueled vehicles can produce strong light-absorption chromophores as well as high concentration of VOCs.
Collapse
Affiliation(s)
- Zhe Bai
- School of Ecology and Environment, Inner Mongolia University, China; Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China
| | - Jiantao Shao
- China Construction Eighth Engineering Division Corp., Ltd., Shanghai 200112, China
| | - Wei Xu
- Shanghai Jianke Environmental Techonology Co., Ltd, China
| | - Ke Zhu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China
| | - Ling Zhao
- School of Ecology and Environment, Inner Mongolia University, China
| | - Lina Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China.
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Institute of Eco-Chongming (IEC), Shanghai, China
| |
Collapse
|
11
|
Fang T, Wang T, Zou C, Guo Q, Lv J, Zhang Y, Wu L, Peng J, Mao H. Heavy vehicles' non-exhaust exhibits competitive contribution to PM 2.5 compared with exhaust in port and nearby areas. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 333:122124. [PMID: 37390912 DOI: 10.1016/j.envpol.2023.122124] [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: 03/05/2023] [Revised: 06/09/2023] [Accepted: 06/27/2023] [Indexed: 07/02/2023]
Abstract
Heavy port transportation networks are increasingly considered as significant contributors of PM2.5 pollution compared to vessels in recent decades. In addition, evidence points to the non-exhaust emission of port traffic as the real driver. This study linked PM2.5 concentrations to varied locations and traffic fleet characteristics in port area through filter sampling. The coupled emission ratio-positive matrix factorisation (ER-PMF) method resolves source factors by avoiding direct overlap from collinear sources. In the port central and entrance areas, freight delivery activity emissions including vehicle exhaust and non-exhaust particles, as well as induced road dust resuspension, accounted for nearly half of the total contribution (42.5%-49.9%). In particular, the contribution of non-exhaust from denser traffic with high proportion of trucks was competitive and equivalent to 52.3% of that from exhaust. Backward trajectory statistical models further interpreted the notably larger-scale coverage of non-exhaust emissions in the port's central area. The distribution of PM2.5 were interpolated within the scope of the port and nearby urban areas, displaying the potential contribution of non-exhaust within 1.15 μg/m3-4.68 μg/m3, slightly higher than the urban detections reported nearby. This study may provide useful insights into the increasing percentage of non-exhaust from trucks in ports and nearby urban areas and facilitate supplementary data collection on Euro-VII type-approval limit settings.
Collapse
Affiliation(s)
- Tiange Fang
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Ting Wang
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.
| | - Chao Zou
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Quanyou Guo
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Jianhua Lv
- Qingdao Research Academy of Environmental Sciences, Qingdao, 266003, China
| | - Yanjie Zhang
- Tianjin Youmei Environmental Protection Technology Co., LTD, Tianjin, 300393, China
| | - Lin Wu
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Jianfei Peng
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China
| | - Hongjun Mao
- Tianjin Key Laboratory of Urban Transport Emission Research & State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300071, China.
| |
Collapse
|
12
|
Via M, Yus-Díez J, Canonaco F, Petit JE, Hopke P, Reche C, Pandolfi M, Ivančič M, Rigler M, Prevôt ASH, Querol X, Alastuey A, Minguillón MC. Towards a better understanding of fine PM sources: Online and offline datasets combination in a single PMF. ENVIRONMENT INTERNATIONAL 2023; 177:108006. [PMID: 37285710 DOI: 10.1016/j.envint.2023.108006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 05/09/2023] [Accepted: 05/29/2023] [Indexed: 06/09/2023]
Abstract
Source apportionment (SA) techniques allocate the measured ambient pollutants with their potential source origin; thus, they are a powerful tool for designing air pollution mitigation strategies. Positive Matrix Factorization (PMF) is one of the most widely used SA approaches, and its multi-time resolution (MTR) methodology, which enables mixing different instrument data in their original time resolution, was the focus of this study. One year of co-located measurements in Barcelona, Spain, of non-refractory submicronic particulate matter (NR-PM1), black carbon (BC) and metals were obtained by a Q-ACSM (Aerodyne Research Inc.), an aethalometer (Aerosol d.o.o.) and fine offline quartz-fibre filters, respectively. These data were combined in a MTR PMF analysis preserving the high time resolution (30 min for the NR-PM1 and BC, and 24 h every 4th day for the offline samples). The MTR-PMF outcomes were assessed varying the time resolution of the high-resolution data subset and exploring the error weightings of both subsets. The time resolution assessment revealed that averaging the high-resolution data was disadvantageous in terms of model residuals and environmental interpretability. The MTR-PMF resolved eight PM1 sources: ammonium sulphate + heavy oil combustion (25%), ammonium nitrate + ammonium chloride (17%), aged secondary organic aerosol (SOA) (16%), traffic (14%), biomass burning (9%), fresh SOA (8%), cooking-like organic aerosol (5%), and industry (4%). The MTR-PMF technique identified two more sources relative to the 24 h base case data subset using the same species and four more with respect to the pseudo-conventional approach mimicking offline PMF, indicating that the combination of both high and low TR data is significantly beneficial for SA. Besides the higher number of sources, the MTR-PMF technique has enabled some sources disentanglement compared to the pseudo-conventional and base case PMF as well as the characterisation of their intra-day patterns.
Collapse
Affiliation(s)
- Marta Via
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain; Department of applied physics, Faculty of Physics, University of Barcelona, Barcelona 08028, Spain.
| | - Jesús Yus-Díez
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain; Department of applied physics, Faculty of Physics, University of Barcelona, Barcelona 08028, Spain
| | - Francesco Canonaco
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland; Datalystica Ltd., Park innovAARE, 5234 Villigen, Switzerland
| | - Jean-Eudes Petit
- Laboratoire des Sciences du Climat et de l'Environnement (CNRS-CEA-UVSQ), Gif-sur-Yvette, France
| | - Philip Hopke
- Institute for a Sustainable Environment, Clarkson University, Potsdam NY13699, USA; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester NY14642, USA
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - Marco Pandolfi
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - Matic Ivančič
- Aerosol d.o.o., Kamniška 39a, 1000 Ljubljana, Slovenia
| | - Martin Rigler
- Aerosol d.o.o., Kamniška 39a, 1000 Ljubljana, Slovenia
| | - André S H Prevôt
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, 5232 Villigen PSI, Switzerland
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - Andrés Alastuey
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| | - María Cruz Minguillón
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona 08034, Spain
| |
Collapse
|
13
|
Tseng YL, Yuan CS, Wong KW, Lin C. Chemical fingerprints and source resolution of atmospheric fine particles in an industrial harbor based on one-year intermittent field sampling data. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 868:161335. [PMID: 36603635 DOI: 10.1016/j.scitotenv.2022.161335] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Revised: 12/25/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
This study investigated the spatiotemporal variation, chemical characteristics, and source resolution of PM2.5 in an East Asian seaport adjacent to industrial complex and urban area. Three representative harbor sites were selected to simultaneously sample 24-h PM2.5 once every 13 days in four seasons. A significant seasonal variation was observed with the highest and the lowest PM2.5 concentration in February (winter) and May (summer), respectively. High contribution of secondary inorganic aerosols (SIAs) showed that SO2 and NOx emitted from neighboring combustion sources burning coal and heavy fuel oil (HFO) were the major precursors forming secondary inorganic PM2.5. High ratios of V/Ni and V/Cu were observed in summer (June~August) since the prevailing west and southwest winds from outer port carried ship emissions to inter port. The correlation of chemical fingerprints (V, Ni, V/Ni, Zn, nss-SO42-, OC) and the number of ships were high at the Zhung-He Site and moderate at the Qi-Ho Site. The Cl-, Na+, V, Ni, nss-SO42-, OC, and V/Ni of PM2.5 were co-influenced by ship missions and oceanic spray in the Kaohsiung Harbor. The influences were relatively higher for winds blown from the harbor areas than those blown from the industrial areas. Oppositely, the Fe, Mn, Cr, Cu, Ca, Zn, and Al in PM2.5 were higher for winds blown from the industrial areas than those from the harbor areas. The CMB receptor modelling resolved that the major sources of PM2.5 were industrial missions, secondary aerosols, mobile sources, ship emissions, oceanic spray, fugitive dust, biomass burning, and organic carbon. Similar to Busan (South Korea), Brindisi (Italy), Lampedusa (Italy), and Barcelona (Spain), the contributions of ship emissions in the Kaohsiung Harbor were in the range of 7.4-7.8 %. Meanwhile, Kaohsiung Harbor was highly influenced by emissions from industrial areas and urban areas.
Collapse
Affiliation(s)
- Yu-Lun Tseng
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC
| | - Chung-Shin Yuan
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC; Aeroaol Science Research Center, National Sun Yat-sen University, Kaohsiung City, Taiwan, ROC.
| | - Kwok-Wai Wong
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC
| | - Chitsan Lin
- Department of Marine Environmental Engineering, National Kaohsiung University of Science and Technology, Kaohsiung City, Taiwan, ROC
| |
Collapse
|
14
|
In 't Veld M, Pandolfi M, Amato F, Pérez N, Reche C, Dominutti P, Jaffrezo J, Alastuey A, Querol X, Uzu G. Discovering oxidative potential (OP) drivers of atmospheric PM 10, PM 2.5, and PM 1 simultaneously in North-Eastern Spain. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 857:159386. [PMID: 36240941 DOI: 10.1016/j.scitotenv.2022.159386] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Revised: 09/23/2022] [Accepted: 10/08/2022] [Indexed: 06/16/2023]
Abstract
Ambient particulate matter (PM) is a major contributor to air pollution, leading to adverse health effects on the human population. It has been suggested that the oxidative potential (OP, as a tracer of oxidative stress) of PM is a possible determinant of its health impact. In this study, samples of PM10, PM2.5, and PM1 were collected roughly every four days from January 2018 until March 2019 at a Barcelona urban background site and Montseny rural background site in northeastern Spain. We determined the chemical composition of samples, allowing us to perform source apportionment using positive matrix factorization. The OP of PM was determined by measuring reactive oxygen species using dithiothreitol and ascorbic acid assays. Finally, to link the sources with the measured OP, both a Pearson's correlation and a multiple linear regression model were applied to the dataset. The results showed that in Barcelona, the OP of PM10 was much higher than those of PM2.5 and PM1, whereas in Montseny results for all PM sizes were in the same range, but significantly lower than in Barcelona. In Barcelona, several anthropogenic sources were the main drivers of OP in PM10 (Combustion + Road Dust + Heavy Oil + OC-rich) and PM2.5 (Road Dust + Combustion). In contrast, PM1 -associated OP was driven by Industry, with a much lower contribution to PM10 and PM2.5 mass. Meanwhile, Montseny exhibited no clear drivers for OP evolution, likely explaining the lack of a significant difference in OP between PM10, PM2.5, and PM1. Overall, this study indicates that size fraction matters for OP, as a function of the environment typology. In an urban context, OP is driven by the PM10 and PM1 size fractions, whereas only the PM1 fraction is involved in rural environments.
Collapse
Affiliation(s)
- Marten In 't Veld
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain; Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona 08034, Spain.
| | - M Pandolfi
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - F Amato
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - N Pérez
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - C Reche
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - P Dominutti
- University Grenoble Alpes, CNRS, IRD, INP-G, IGE (UMR 5001), 38000 Grenoble, France
| | - J Jaffrezo
- University Grenoble Alpes, CNRS, IRD, INP-G, IGE (UMR 5001), 38000 Grenoble, France
| | - A Alastuey
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - X Querol
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - G Uzu
- University Grenoble Alpes, CNRS, IRD, INP-G, IGE (UMR 5001), 38000 Grenoble, France
| |
Collapse
|
15
|
Wang G, Huang K, Fu Q, Chen J, Huo J, Zhao Q, Duan Y, Lin Y, Yang F, Zhang W, Li H, Xu J, Qin X, Zhao N, Deng C. Response of PM 2.5-bound elemental species to emission variations and associated health risk assessment during the COVID-19 pandemic in a coastal megacity. J Environ Sci (China) 2022; 122:115-127. [PMID: 35717077 PMCID: PMC8520875 DOI: 10.1016/j.jes.2021.10.005] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2021] [Revised: 09/19/2021] [Accepted: 10/06/2021] [Indexed: 06/15/2023]
Abstract
The coronavirus (COVID-19) pandemic is disrupting the world from many aspects. In this study, the impact of emission variations on PM2.5-bound elemental species and health risks associated to inhalation exposure has been analyzed based on real-time measurements at a remote coastal site in Shanghai during the pandemic. Most trace elemental species decreased significantly and displayed almost no diel peaks during the lockdown. After the lockdown, they rebounded rapidly, of which V and Ni even exceeded the levels before the lockdown, suggesting the recovery of both inland and shipping activities. Five sources were identified based on receptor modeling. Coal combustion accounted for more than 70% of the measured elemental concentrations before and during the lockdown. Shipping emissions, fugitive/mineral dust, and waste incineration all showed elevated contributions after the lockdown. The total non-carcinogenic risk (HQ) for the target elements exceeded the risk threshold for both children and adults with chloride as the predominant species contributing to HQ. Whereas, the total carcinogenic risk (TR) for adults was above the acceptable level and much higher than that for children. Waste incineration was the largest contributor to HQ, while manufacture processing and coal combustion were the main sources of TR. Lockdown control measures were beneficial for lowering the carcinogenic risk while unexpectedly increased the non-carcinogenic risk. From the perspective of health effects, priorities of control measures should be given to waste incineration, manufacture processing, and coal combustion. A balanced way should be reached between both lowering the levels of air pollutants and their health risks.
Collapse
Affiliation(s)
- Guochen Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Kan Huang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China; IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200433, China; Institute of Eco-Chongming (IEC), Shanghai 202162, China.
| | - Qingyan Fu
- Shanghai Environmental Monitoring Center, Shanghai 200030, China.
| | - Jia Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Juntao Huo
- Shanghai Environmental Monitoring Center, Shanghai 200030, China
| | - Qianbiao Zhao
- Shanghai Environmental Monitoring Center, Shanghai 200030, China
| | - Yusen Duan
- Shanghai Environmental Monitoring Center, Shanghai 200030, China
| | - Yanfen Lin
- Shanghai Environmental Monitoring Center, Shanghai 200030, China
| | - Fan Yang
- Pudong New District Environmental Monitoring Station, Shanghai 200122, China
| | - Wenjie Zhang
- Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Hao Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Jian Xu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xiaofei Qin
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Na Zhao
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Congrui Deng
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| |
Collapse
|
16
|
Navarro-Selma B, Clemente A, Nicolás JF, Crespo J, Carratalá A, Lucarelli F, Giardi F, Galindo N, Yubero E. Size segregated ionic species collected in a harbour area. CHEMOSPHERE 2022; 294:133693. [PMID: 35063561 DOI: 10.1016/j.chemosphere.2022.133693] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 11/22/2021] [Accepted: 01/17/2022] [Indexed: 06/14/2023]
Abstract
Water-soluble ions were analysed in size segregated aerosol samples collected in the port of Alicante (Southeastern Spain) during summer and winter using a multistage cascade impactor. Seasonal variations in the size distributions of the analysed components and the influence of bulk materials handling (loading/unloading and stockpiling) at the docks were investigated. The size distributions of SO42-, NH4+ and K+ were characterized by prominent peaks in the condensation and droplet modes, both in summer and winter, while those of Ca2+, Na+, Mg2+ and Cl- had a main peak centred at ∼4 μm. Although oxalate size distributions were similar during both seasons, the fraction of coarse-mode oxalate increased in summer most likely as a result of volatilization and repartition processes or reactions of oxalic acid with coarse alkaline particles. Nitrate size distributions were dominated by a coarse mode; however, during winter, modal peaks in the submicron size range were also observed due to favourable conditions for the formation of fine-mode NH4NO3. Harbour activities had a significant impact only on the concentrations of calcium, particularly in the coarse fraction, during both summer and winter.
Collapse
Affiliation(s)
- B Navarro-Selma
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - A Clemente
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - J F Nicolás
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - J Crespo
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - A Carratalá
- Department of Chemical Engineering, University of Alicante, P. O. Box 99, 03080, Alicante, Spain
| | - F Lucarelli
- Department of Physics and Astronomy, University of Florence and INFN, 50019, Florence, Italy
| | - F Giardi
- Department of Physics and Astronomy, University of Florence and INFN, 50019, Florence, Italy
| | - N Galindo
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - E Yubero
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain.
| |
Collapse
|
17
|
Chianese E, Tirimberio G, Appolloni L, Dinoi A, Contini D, Di Gilio A, Palmisani J, Cotugno P, Miniero DV, Dusek U, Cammino G, Riccio A. Chemical characterisation of PM 10 from ship emissions: a study on samples from hydrofoil exhaust stacks. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:17723-17736. [PMID: 34676477 PMCID: PMC8530373 DOI: 10.1007/s11356-021-17035-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Accepted: 10/11/2021] [Indexed: 06/13/2023]
Abstract
A chemical characterization of PM10 collected at hydrofoil exhaust stacks was performed conducting two on-board measuring campaigns, with the aim of assessing the ship emission impact on PM10 collected in the coastal area of Naples (Southern Italy) and providing information about the characteristics of this important PM emission source.Samples were analysed determining the contribution of different chemical parameters to PM10's mass, which consisted of polycyclic aromatic hydrocarbons (PAHs) (0.10 ± 0.12%), total carbon (61.9% ± 20.0%, with 40.4% of organic carbon, OC, and 21.5% of elemental carbon, EC) and elemental fraction (0.44% ± 1.00%). Differences in terms of composition and chemical parameter profiles were observed between samples collected during offshore navigation (Off) and samples collected during shunting operations (SO), the latter of higher concern on a local scale. For SO samples, lower contributions of OC and EC were observed (39.7% and 19.6% respectively) compared to Off samples (41.5% and 24.2%), and an increase in terms of elements (from 0.32 to 0.51%) and PAHs (from 0.06 to 0.12%) concentrations was observed. In addition, enrichment factors (EFs) for some elements such as V, Zn, Cd, Cu, Ag and Hg as well as PAHs profile varied significantly between SO and Off. Data presented here were compared with data on chemical composition of PM10 sampled in a tunnel, in a background site and in an urban site in the city of Naples. Results indicated that shipping activities contributed significantly to the emission of V and, in some extent, Zn and Cd; in addition, PAH profiles indicated a greater contribution to urban PM10 from vehicular traffic than shipping emissions. These results can significantly contribute to the correct evaluation of the influence of shipping emission on PM10 generation in urban coastal areas and can be a useful reference for similar studies. The coastal area of Naples is an important example of the coexistence of residential, touristic and natural areas with pollutants emission sources including, among the others, shipping emissions. In this and similar contexts, it is important to distinguish the contribution of each emission source to clearly define environmental control policies.
Collapse
Affiliation(s)
- Elena Chianese
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy.
| | - Giuseppina Tirimberio
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy
| | - Luca Appolloni
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy
| | - Adelaide Dinoi
- Istituto Di Scienze Dell'Atmosfera E del Clima, ISAC-CNR, 73100, Lecce, Italy
| | - Daniele Contini
- Istituto Di Scienze Dell'Atmosfera E del Clima, ISAC-CNR, 73100, Lecce, Italy
| | - Alessia Di Gilio
- Department of Biology, University of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Jolanda Palmisani
- Department of Biology, University of Bari, Via Orabona 4, 70126, Bari, Italy
| | - Pietro Cotugno
- Department of Biology, University of Bari, Via Orabona 4, 70126, Bari, Italy
| | | | - Ulrike Dusek
- Centre for Isotope Research (CIO) Energy and Sustainability Research Institute Groningen (ESRIG), University of Groningen, 9747 AG, Groningen, Netherlands
| | - Gennaro Cammino
- Autorità Di Sistema Portuale del Mar Tirreno Centrale, Piazzale Pisacane 80133, Napoli, Italy
| | - Angelo Riccio
- Department of Science and Technology, University of Naples 'Parthenope', Centro Direzionale Isola C4, 80143, Napoli, Italy
| |
Collapse
|
18
|
What Are the Sectors Contributing to the Exceedance of European Air Quality Standards over the Iberian Peninsula? A Source Contribution Analysis. SUSTAINABILITY 2022. [DOI: 10.3390/su14052759] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The Iberian Peninsula, located in southwestern Europe, is exposed to frequent exceedances of different threshold and limit values of air pollution, mainly related to particulate matter, ozone, and nitrous oxide. Source apportionment modeling represents a useful modeling tool for evaluating the contribution of different emission sources or sectors and for designing useful mitigation strategies. In this sense, this work assesses the impact of various emission sectors on air pollution levels over the Iberian Peninsula using a source contribution analysis (zero-out method). The methodology includes the use of the regional WRF + CHIMERE modeling system (coupled to EMEP emissions). In order to represent the sensitivity of the chemistry and transport of gas-phase pollutants and aerosols, several emission sectors have been zeroed-out to quantify the influence of different sources in the area, such as on-road traffic or other mobile sources, combustion in energy generation, industrial emissions or agriculture, among others. The sensitivity analysis indicates that large reductions of precursor emissions (coming mainly from energy generation, road traffic, and maritime-harbor emissions) are needed for improving air quality and attaining the thresholds set in the European Directive 2008/50/EC over the Iberian Peninsula.
Collapse
|
19
|
Veld MI', Alastuey A, Pandolfi M, Amato F, Pérez N, Reche C, Via M, Minguillón MC, Escudero M, Querol X. Compositional changes of PM 2.5 in NE Spain during 2009-2018: A trend analysis of the chemical composition and source apportionment. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 795:148728. [PMID: 34328931 DOI: 10.1016/j.scitotenv.2021.148728] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/11/2021] [Accepted: 06/24/2021] [Indexed: 06/13/2023]
Abstract
In this work, time-series analyses of the chemical composition and source contributions of PM2.5 from an urban background station in Barcelona (BCN) and a rural background station in Montseny (MSY) in northeastern Spain from 2009 to 2018 were investigated and compared. A multisite positive matrix factorization analysis was used to compare the source contributions between the two stations, while the trends for both the chemical species and source contributions were studied using the Theil-Sen trend estimator. Between 2009 and 2018, both stations showed a statistically significant decrease in PM2.5 concentrations, which was driven by the downward trends of levels of chemical species and anthropogenic source contributions, mainly from heavy oil combustion, mixed combustion, industry, and secondary sulfate. These source contributions showed a continuous decrease over the study period, signifying the continuing success of mitigation strategies, although the trends of heavy oil combustion and secondary sulfate have flattened since 2016. Secondary nitrate also followed a significant decreasing trend in BCN, while secondary organic aerosols (SOA) very slightly decreased in MSY. The observed decreasing trends, in combination with the absence of a trend for the organic aerosols (OA) at both stations, resulted in an increase in the relative proportion of OA in PM2.5 by 12% in BCN and 9% in MSY, mostly from SOA, which increased by 7% in BCN and 4% in MSY. Thus, at the end of the study period, OA accounted for 40% and 50% of the annual mean PM2.5 at BCN and MSY, respectively. This might have relevant implications for air quality policies aiming at abating PM2.5 in the study region and for possible changes in toxicity of PM2.5 due to marked changes in composition and source apportionment.
Collapse
Affiliation(s)
- Marten In 't Veld
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain; Department of Civil and Environmental Engineering, Universitat Politècnica de Catalunya, Barcelona 08034, Spain.
| | - Andres Alastuey
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - Marco Pandolfi
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - Fulvio Amato
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - Noemi Pérez
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - Marta Via
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain; Department of Applied Physics, University of Barcelona, Barcelona 08028, Spain
| | - María Cruz Minguillón
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| | - Miguel Escudero
- Centro Universitario de la Defensa, Academia General Militar, Zaragoza 50090, Spain
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research, IDAEA-CSIC, Barcelona 08034, Spain
| |
Collapse
|
20
|
Tseng YL, Wu CH, Yuan CS, Bagtasa G, Yen PH, Cheng PH. Inter-comparison of chemical characteristics and source apportionment of PM 2.5 at two harbors in the Philippines and Taiwan. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 793:148574. [PMID: 34328987 DOI: 10.1016/j.scitotenv.2021.148574] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/15/2021] [Revised: 06/07/2021] [Accepted: 06/16/2021] [Indexed: 06/13/2023]
Abstract
This study inter-compared the concentration and chemical characteristics of PM2.5 at two harbors in East Asia, and identified the potential sources of PM2.5 and their contribution. Two sites located at the Kaohsiung (Taiwan) and Manila (the Philippines) Harbors were selected for simultaneous sampling of PM2.5 in four seasons. The sampling of 24-h PM2.5 was conducted for continuous seven days in each season. Water-soluble ions, metallic elements, carbonaceous content, anhydrosugars, and organic acids in PM2.5 were analyzed to characterize their chemical fingerprints. Receptor modeling and trajectory simulation were further applied to resolve the source apportionment of PM2.5. The results indicated that the Kaohsiung Harbor was highly influenced by long-range transport (LRT) of polluted air masses from Northeast Asia, while the Manila Harbor was mainly influenced by local emissions. Secondary inorganic aerosols were the most abundant ions in PM2.5. Crustal elements dominated the metallic content of PM2.5, but trace elements were mainly originated from anthropogenic sources. Higher concentrations of organic carbon (OC) than elemental carbon (EC) was found in PM2.5, with secondary OC (SOC) dominant to the former. Levoglucosan in PM2.5 at the Manila Harbor were superior to those at the Kaohsiung Harbor due to biomass burning surrounding the Manila Harbor. Additionally, high mass ratios of malonic and succinic acids (M/S) in PM2.5 indicated the formation of SOAs. Overall, the ambient air quality of Manila Harbor was more polluted than Kaohsiung Harbor. The Kaohsiung Harbor was more severely affected by LRT of polluted air masses from Northeast Asia, while those toward the Manila Harbor came from the oceans. The major sources resolved by CMB and PMF models at the Kaohsiung Harbor were secondary aerosols, ironworks, incinerators, oceanic spray, and ship emissions, while those at the Manila Harbor were secondary aerosols, soil dust, biomass burning, ship emissions, and oceanic spray.
Collapse
Affiliation(s)
- Yu-Lun Tseng
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC
| | - Chien-Hsing Wu
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC
| | - Chung-Shin Yuan
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC; Aeroaol Science Research Center, National Sun Yat-sen University, Kaohsiung City, Taiwan, ROC.
| | - Gerry Bagtasa
- Institute of Environmental Science & Meteorology, University of the Philippines at Diliman, Quezon City, Manila, the Philippines
| | - Po-Hsuan Yen
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC
| | - Po-Hung Cheng
- Institute of Environmental Engineering, National Sun-Yat Sen University, Kaohsiung City, Taiwan, ROC
| |
Collapse
|
21
|
Mineralogical and Chemical Tracing of Dust Variation in an Underground Historic Salt Mine. MINERALS 2021. [DOI: 10.3390/min11070686] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
The aim of this study was to investigate the causes of the evolution of atmospheric dust composition in an open-to-public subterranean site (UNESCO-recognized historic mine) at increasing distances from the air intake. The role of the components imported with atmospheric air from the surface was compared with natural and anthropogenic sources of dust from inside the mine. Samples of deposited dust were directly collected from flat surfaces at 11 carefully selected sites. The morphological, mineralogical, and chemical characteristics were obtained using scanning electron microscopy (SEM), X-ray diffraction (XRD), and inductively coupled plasma spectroscopy (ICP). The study showed that the air in the underground salt mine was free of pollutants present in the ambient air on the surface. Most of the components sucked into the mine by the ventilation system from the surface (regular dust, particulate matter, gaseous pollutants, biogenic particles, etc.) underwent quick and instantaneous sedimentation in the close vicinity of the air inlet to the mine. The dust settled in the mine interior primarily consisted of natural geogenic particles, locally derived from the weathering of the host rock (halite, anhydrite, and aluminosilicates). This was confirmed by low values of enrichment factors (EF) calculated for minor and trace elements. Only one site, due to the tourist railroad and the associated local intensive tourist traffic, represented the anthropogenic sources of elevated concentrations of ferruginous particles and accompanied metals (P, Cr, Mn, Co, Ni, Cu, As, Mo, Cd, Sn, Sb, Pb, and W). The gravitational deposition of pollutants from these sources limits the effects of the emissions to the local range. The used methodology and the results are universal and might also apply to other mines, caves, or underground installations used for museums, tourists, or speleotherapeutic purposes.
Collapse
|
22
|
Iungman T, Khomenko S, Nieuwenhuijsen M, Barboza EP, Ambròs A, Padilla C, Mueller N. The impact of urban and transport planning on health: Assessment of the attributable mortality burden in Madrid and Barcelona and its distribution by socioeconomic status. ENVIRONMENTAL RESEARCH 2021; 196:110988. [PMID: 33689819 DOI: 10.1016/j.envres.2021.110988] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 02/15/2021] [Accepted: 03/04/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND The population living in urban areas is growing rapidly. The level of exposure to adverse environmental factors is detrimental to human health and is directly related to urban and transport planning practices. OBJECTIVE To estimate the premature mortality burden of non-compliance with international exposure guidelines for air pollution, noise, access to green space and heat for Barcelona and Madrid (Spain), and its distribution among the population by the socioeconomic status (SES). METHODS The Urban and TranspOrt planning Health Impact Assessment (UTOPHIA) tool was applied and the attributable premature mortality due to non-compliance with recommended exposure levels was estimated. The distribution of the attributable mortality burden among the population by SES was investigated through Generalized Additive Models (GAMs) adjusting for spatial autocorrelation and a cluster analysis was performed to identify attributable mortality hot spots. RESULTS Annually, 7.1% and 3.4% of premature mortality in Barcelona and Madrid, respectively, could be attributed to non-compliance with the international exposure recommendations for air pollution, noise, heat and access to green space. In addition, analysis by SES showed that in Barcelona lower SES areas had an overall greater attributable mortality rate, while in Madrid, the distribution of the attributable mortality burden by SES varied by exposure. CONCLUSION This study shows the impact of environmental exposures on mortality and highlights the importance of taking integrated actions when designing cities considering the health impacts, but also the specificities of each city such as the socio-demographic context. Moreover, the high precision scale of the analysis enables the identification of environmental hazards and mortality hot spots providing a powerful tool to support priority-setting and guide policymakers towards a healthy, sustainable and just city for all of their residents.
Collapse
Affiliation(s)
- Tamara Iungman
- Institute for Global Health (ISGlobal), Barcelona, Spain; École des Hautes Études en Santé Publique (EHESP), Paris, France
| | - Sasha Khomenko
- Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Mark Nieuwenhuijsen
- Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.
| | - Evelise Pereira Barboza
- Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Albert Ambròs
- Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - CindyM Padilla
- École des Hautes Études en Santé Publique (EHESP), Paris, France
| | - Natalie Mueller
- Institute for Global Health (ISGlobal), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| |
Collapse
|
23
|
Shipping and Air Quality in Italian Port Cities: State-of-the-Art Analysis of Available Results of Estimated Impacts. ATMOSPHERE 2021. [DOI: 10.3390/atmos12050536] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
Populated coastal areas are exposed to emissions from harbour-related activities (ship traffic, loading/unloading, and internal vehicular traffic), posing public health issues and environmental pressures on climate. Due to the strategic geographical position of Italy and the high number of ports along coastlines, an increasing concern about maritime emissions from Italian harbours has been made explicit in the EU and IMO (International Maritime Organization, London, UK) agenda, also supporting the inclusion in a potential Mediterranean emission control area (MedECA). This work reviews the main available outcomes concerning shipping (and harbours’) contributions to local air quality, particularly in terms of concentration of particulate matter (PM) and gaseous pollutants (mainly nitrogen and sulphur oxides), in the main Italian hubs. Maritime emissions from literature and disaggregated emission inventories are discussed. Furthermore, estimated impacts to air quality, obtained with dispersion and receptor modeling approaches, which are the most commonly applied methodologies, are discussed. Results show a certain variability that suggests the necessity of harmonization among methods and input data in order to compare results. The analysis gives a picture of the effects of this pollution source, which could be useful for implementing effective mitigation strategies at a national level.
Collapse
|
24
|
Clemente Á, Yubero E, Galindo N, Crespo J, Nicolás JF, Santacatalina M, Carratala A. Quantification of the impact of port activities on PM 10 levels at the port-city boundary of a mediterranean city. JOURNAL OF ENVIRONMENTAL MANAGEMENT 2021; 281:111842. [PMID: 33370677 DOI: 10.1016/j.jenvman.2020.111842] [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: 04/22/2020] [Revised: 10/13/2020] [Accepted: 12/10/2020] [Indexed: 06/12/2023]
Abstract
The main objective of this work was to quantify the impact of handling of bulk materials on PM10 levels measured at the port-city border of Alicante (Spain), located on the western Mediterranean coast. To achieve that goal, 355 PM10 samples were collected at the perimeter of the harbor of Alicante from March 2017 to February 2018. A 181 sample subgroup was chemically characterized in order to perform a source apportionment study with the EPA PMF 5.0 model. Eight factors were identified, two of them directly related to the handling of bulk materials (Limestone + gypsum and Clinker), accounting jointly for 35% of the average PM10 concentration. A Road traffic factor was the second highest contributor to PM10 levels (17%) while the Shipping emissions factor accounted for only 6% of the average PM10 mass. Other factors such as Biomass burning+ secondary nitrate and Aged sea salt represented a joint contribution of 25% of the PM10 mass. Results indicate that emission abatement strategies should primarily focus on the reduction of fugitive emissions caused by the handling of bulk materials at the docks. Moreover, scenarios including reductions of more than 50% in bulk handling sources and 10% in other anthropogenic sources would help to reduce anthropogenic exceedances of the daily PM10 limit (50 μg·m-3) and to approach to WHO daily PM10 standard (20 μg m-3).
Collapse
Affiliation(s)
- Á Clemente
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain.
| | - E Yubero
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - N Galindo
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - J Crespo
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - J F Nicolás
- Atmospheric Pollution Laboratory (LCA), Department of Applied Physics, Miguel Hernández University, Avenida de la Universidad S/N, 03202, Elche, Spain
| | - M Santacatalina
- Department of Chemical Engineering, University of Alicante, P. O. Box 99, 03080, Alicante, Spain
| | - A Carratala
- Department of Chemical Engineering, University of Alicante, P. O. Box 99, 03080, Alicante, Spain
| |
Collapse
|
25
|
Saraga D, Maggos T, Degrendele C, Klánová J, Horvat M, Kocman D, Kanduč T, Garcia Dos Santos S, Franco R, Gómez PM, Manousakas M, Bairachtari K, Eleftheriadis K, Kermenidou M, Karakitsios S, Gotti A, Sarigiannis D. Multi-city comparative PM 2.5 source apportionment for fifteen sites in Europe: The ICARUS project. THE SCIENCE OF THE TOTAL ENVIRONMENT 2021; 751:141855. [PMID: 32889477 DOI: 10.1016/j.scitotenv.2020.141855] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 08/01/2020] [Accepted: 08/19/2020] [Indexed: 06/11/2023]
Abstract
PM2.5 is an air pollution metric widely used to assess air quality, with the European Union having set targets for reduction in PM2.5 levels and population exposure. A major challenge for the scientific community is to identify, quantify and characterize the sources of atmospheric particles in the aspect of proposing effective control strategies. In the frame of ICARUS EU2020 project, a comprehensive database including PM2.5 concentration and chemical composition (ions, metals, organic/elemental carbon, Polycyclic Aromatic Hydrocarbons) from three sites (traffic, urban background, rural) of five European cities (Athens, Brno, Ljubljana, Madrid, Thessaloniki) was created. The common and synchronous sampling (two seasons involved) and analysis procedure offered the prospect of a harmonized Positive Matrix Factorization model approach, with the scope of identifying the similarities and differences of PM2.5 key-source chemical fingerprints across the sampling sites. The results indicated that the average contribution of traffic exhausts to PM2.5 concentration was 23.3% (traffic sites), 13.3% (urban background sites) and 8.8% (rural sites). The average contribution of traffic non-exhausts was 12.6% (traffic), 13.5% (urban background) and 6.1% (rural sites). The contribution of fuel oil combustion was 3.8% at traffic, 11.6% at urban background and 18.7% at rural sites. Biomass burning contribution was 22% at traffic sites, 30% at urban background sites and 28% at rural sites. Regarding soil dust, the average contribution was 5% and 8% at traffic and urban background sites respectively and 16% at rural sites. Sea salt contribution was low (1-4%) while secondary aerosols corresponded to the 16-34% of PM2.5. The homogeneity of the chemical profiles as well as their relationship with prevailing meteorological parameters were investigated. The results showed that fuel oil combustion, traffic non-exhausts and soil dust profiles are considered as dissimilar while biomass burning, sea salt and traffic exhaust can be characterized as relatively homogenous among the sites.
Collapse
Affiliation(s)
- D Saraga
- National Centre for Scientific Research 'Demokritos', Atmospheric Chemistry & Innovative Technologies Laboratory, 15310 Aghia Paraskevi, Athens, Greece.
| | - T Maggos
- National Centre for Scientific Research 'Demokritos', Atmospheric Chemistry & Innovative Technologies Laboratory, 15310 Aghia Paraskevi, Athens, Greece
| | - C Degrendele
- Masaryk University, RECETOX Centre, Kamenice 5, 625 00 Brno, Czech Republic
| | - J Klánová
- Masaryk University, RECETOX Centre, Kamenice 5, 625 00 Brno, Czech Republic
| | - M Horvat
- Department of Environmental Sciences, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
| | - D Kocman
- Department of Environmental Sciences, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
| | - T Kanduč
- Department of Environmental Sciences, Jožef Stefan Institute, Jamova 39, 1000 Ljubljana, Slovenia
| | - S Garcia Dos Santos
- Instituto de salud Carlos III, Área de Contaminación Atmosférica, Centro Nacional de Sanidad Ambiental, Ctra. Majadahonda a Pozuelo, 28220 Majadahonda, Madrid, Spain
| | - R Franco
- Instituto de salud Carlos III, Área de Contaminación Atmosférica, Centro Nacional de Sanidad Ambiental, Ctra. Majadahonda a Pozuelo, 28220 Majadahonda, Madrid, Spain
| | - P Morillo Gómez
- Instituto de salud Carlos III, Área de Contaminación Atmosférica, Centro Nacional de Sanidad Ambiental, Ctra. Majadahonda a Pozuelo, 28220 Majadahonda, Madrid, Spain
| | - M Manousakas
- National Centre for Scientific Research 'Demokritos', Environmental Radioactivity Laboratory, 15310 Aghia Paraskevi, Athens, Greece
| | - K Bairachtari
- National Centre for Scientific Research 'Demokritos', Atmospheric Chemistry & Innovative Technologies Laboratory, 15310 Aghia Paraskevi, Athens, Greece
| | - K Eleftheriadis
- National Centre for Scientific Research 'Demokritos', Environmental Radioactivity Laboratory, 15310 Aghia Paraskevi, Athens, Greece
| | - M Kermenidou
- Department of Chemical Engineering, Aristotle University of Thessaloniki (AUTH), Environmental Engineering Laboratory, 54124 Thessaloniki, Greece
| | - S Karakitsios
- Department of Chemical Engineering, Aristotle University of Thessaloniki (AUTH), Environmental Engineering Laboratory, 54124 Thessaloniki, Greece
| | - A Gotti
- Department of Chemical Engineering, Aristotle University of Thessaloniki (AUTH), Environmental Engineering Laboratory, 54124 Thessaloniki, Greece
| | - D Sarigiannis
- Department of Chemical Engineering, Aristotle University of Thessaloniki (AUTH), Environmental Engineering Laboratory, 54124 Thessaloniki, Greece
| |
Collapse
|
26
|
Khan JZ, Sun L, Tian Y, Shi G, Feng Y. Chemical characterization and source apportionment of PM 1 and PM 2.5 in Tianjin, China: Impacts of biomass burning and primary biogenic sources. J Environ Sci (China) 2021; 99:196-209. [PMID: 33183697 DOI: 10.1016/j.jes.2020.06.027] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 06/03/2020] [Accepted: 06/20/2020] [Indexed: 05/12/2023]
Abstract
The submicron particulate matter (PM1) and fine particulate matter (PM2.5) are very important due to their greater adverse impacts on the natural environment and human health. In this study, the daily PM1 and PM2.5 samples were collected during early summer 2018 at a sub-urban site in the urban-industrial port city of Tianjin, China. The collected samples were analyzed for the carbonaceous fractions, inorganic ions, elemental species, and specific marker sugar species. The chemical characterization of PM1 and PM2.5 was based on their concentrations, compositions, and characteristic ratios (PM1/PM2.5, AE/CE, NO3-/SO42-, OC/EC, SOC/OC, OM/TCA, K+/EC, levoglucosan/K+, V/Cu, and V/Ni). The average concentrations of PM1 and PM2.5 were 32.4 µg/m3 and 53.3 µg/m3, and PM1 constituted 63% of PM2.5 on average. The source apportionment of PM1 and PM2.5 by positive matrix factorization (PMF) model indicated the main sources of secondary aerosols (25% and 34%), biomass burning (17% and 20%), traffic emission (20% and 14%), and coal combustion (17% and 14%). The biomass burning factor involved agricultural fertilization and waste incineration. The biomass burning and primary biogenic contributions were determined by specific marker sugar species. The anthropogenic sources (combustion, secondary particle formation, etc) contributed significantly to PM1 and PM2.5, and the natural sources were more evident in PM2.5. This work significantly contributes to the chemical characterization and source apportionment of PM1 and PM2.5 in near-port cities influenced by the diverse sources.
Collapse
Affiliation(s)
- Jahan Zeb Khan
- Center for Ecological Research & Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin, 150040, China; State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Long Sun
- Center for Ecological Research & Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, College of Forestry, Northeast Forestry University, Harbin, 150040, China
| | - Yingze Tian
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Guoliang Shi
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| |
Collapse
|
27
|
Liu B, Wu J, Wang J, Shi L, Meng H, Dai Q, Wang J, Song C, Zhang Y, Feng Y, Hopke PK. Chemical characteristics and sources of ambient PM 2.5 in a harbor area: Quantification of health risks to workers from source-specific selected toxic elements. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 268:115926. [PMID: 33153802 DOI: 10.1016/j.envpol.2020.115926] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2020] [Revised: 10/21/2020] [Accepted: 10/22/2020] [Indexed: 06/11/2023]
Abstract
Samples of ambient PM2.5 were collected in the Qingdao harbor area between 21 March and May 25, 2016, and analyzed to investigate the compositions and sources of PM2.5 and to assess source-specific selected toxic element health risks to workers via a combination of positive matrix factorization (PMF) and health risk (HR) assessment models. The mean concentration of PM2.5 in harbor area was 48 μg m-3 with organic matter (OM) dominating its mass. Zn and V concentrations were significantly higher than the other selected toxic elements. The hazard index (HI) and cancer risk (Ri) of all selected toxic elements were lower than the United States Environmental Protection Agency (USEPA) limits. There were no non-cancer and cancer risks for workers in harbor area. The contributions from industrial emissions (IE), ship emissions (SE), vehicle emissions (VE), and crustal dust and coal combustion (CDCC) to selected toxic elements were 39.0%, 12.8%, 24.0%, and 23.0%, respectively. The HI values of selected toxic elements from IE, CDCC, SE, and VE were 1.85 × 10-1, 7.08 × 10-2, 6.36 × 10-2, and 3.37 × 10-2, respectively; these are lower than the USEPA limits. The total cancer risk (Rt) value from selected toxic elements in CDCC was 2.04 × 10-7, followed by IE (6.40 × 10-8), SE (2.26 × 10-8), and VE (2.18 × 10-8). CDCC and IE were the likely sources of cancer risk in harbor area. The Bo Sea and coast were identified as the likely source areas for health risks from IE via potential source contribution function (PSCF) analysis based on the results of PMF-HR modelling. Although the source-specific health risks were below the recommended limit values, this work illustrates how toxic species in PM2.5 health risks can be associated with sources such that control measures could be undertaken if the risks warranted it.
Collapse
Affiliation(s)
- Baoshuang Liu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Jianhui Wu
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China.
| | - Jing Wang
- Qingdao Ecological and Environmental Monitoring Centre of Shandong Province, Qingdao, 266003, China
| | - Laiyuan Shi
- Qingdao Ecological and Environmental Monitoring Centre of Shandong Province, Qingdao, 266003, China
| | - He Meng
- Qingdao Ecological and Environmental Monitoring Centre of Shandong Province, Qingdao, 266003, China
| | - Qili Dai
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Jiao Wang
- College of Environmental Science and Engineering, Key Laboratory of Marine Environmental Science and Ecology (Ministry of Education), Ocean University of China, Qingdao, Shandong, 266100, China
| | - Congbo Song
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham, B15 2TT, UK
| | - Yufen Zhang
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Yinchang Feng
- State Environmental Protection Key Laboratory of Urban Ambient Air Particulate Matter Pollution Prevention and Control & Tianjin Key Laboratory of Urban Transport Emission Research, College of Environmental Science and Engineering, Nankai University, Tianjin, 300350, China
| | - Philip K Hopke
- Center for Air Resources Engineering and Science, Clarkson University, Potsdam, NY, 13699, USA; Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, NY, 14642, USA
| |
Collapse
|
28
|
Corral AF, Dadashazar H, Stahl C, Edwards EL, Zuidema P, Sorooshian A. Source Apportionment of Aerosol at a Coastal Site and Relationships with Precipitation Chemistry: A Case Study over the Southeast United States. ATMOSPHERE 2020; 11:1212. [PMID: 34211764 PMCID: PMC8243544 DOI: 10.3390/atmos11111212] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
This study focuses on the long-term aerosol and precipitation chemistry measurements from colocated monitoring sites in Southern Florida between 2013 and 2018. A positive matrix factorization (PMF) model identified six potential emission sources impacting the study area. The PMF model solution yielded the following source concentration profiles: (i) combustion; (ii) fresh sea salt; (iii) aged sea salt; (iv) secondary sulfate; (v) shipping emissions; and (vi) dust. Based on these results, concentration-weighted trajectory maps were developed to identify sources contributing to the PMF factors. Monthly mean precipitation pH values ranged from 4.98 to 5.58, being positively related to crustal species and negatively related to SO4 2-. Sea salt dominated wet deposition volume-weighted concentrations year-round without much variability in its mass fraction in contrast to stronger seasonal changes in PM2.5 composition where fresh sea salt was far less influential. The highest mean annual deposition fluxes were attributed to Cl-, NO3 -, SO4 2-, and Na+ between April and October. Nitrate is strongly correlated with dust constituents (unlike sea salt) in precipitation samples, indicative of efficient partitioning to dust. Interrelationships between precipitation chemistry and aerosol species based on long-term surface data provide insight into aerosol-cloud-precipitation interactions.
Collapse
Affiliation(s)
- Andrea F. Corral
- Department of Chemical and Environmental Engineering, The University of Arizona, Tucson, AZ 85721, USA
| | - Hossein Dadashazar
- Department of Chemical and Environmental Engineering, The University of Arizona, Tucson, AZ 85721, USA
| | - Connor Stahl
- Department of Chemical and Environmental Engineering, The University of Arizona, Tucson, AZ 85721, USA
| | - Eva-Lou Edwards
- Department of Chemical and Environmental Engineering, The University of Arizona, Tucson, AZ 85721, USA
| | - Paquita Zuidema
- Rosenstiel School of Marine and Atmospheric Science, University of Miami, Miami, FL 33149, USA
| | - Armin Sorooshian
- Department of Chemical and Environmental Engineering, The University of Arizona, Tucson, AZ 85721, USA
- Department of Hydrology and Atmospheric Sciences, The University of Arizona, Tucson, AZ 85721, USA
| |
Collapse
|
29
|
Feng X, Shen J, Yang H, Wang K, Wang Q, Zhou Z. Time-Frequency Analysis of Particulate Matter (PM 10) Concentration in Dry Bulk Ports Using the Hilbert-Huang Transform. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2020; 17:ijerph17165754. [PMID: 32784870 PMCID: PMC7460512 DOI: 10.3390/ijerph17165754] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/27/2020] [Accepted: 08/05/2020] [Indexed: 01/29/2023]
Abstract
To analyze the time–frequency characteristics of the particulate matter (PM10) concentration, data series measured at dry bulk ports were used to determine the contribution of various factors during different periods to the PM10 concentration level so as to support the formulation of air quality improvement plans around port areas. In this study, the Hilbert–Huang transform (HHT) method was used to analyze the time–frequency characteristics of the PM10 concentration data series measured at three different sites at the Xinglong Port of Zhenjiang, China, over three months. The HHT method consists of two main stages, namely, empirical mode decomposition (EMD) and Hilbert spectrum analysis (HSA), where the EMD technique is used to pre-process the HSA in order to determine the intrinsic mode function (IMF) components of the raw data series. The results show that the periods of the IMF components exhibit significant differences, and the short-period IMF component provides a modest contribution to all IMF components. Using HSA technology for these IMF components, we discovered that the variations in the amplitude of the PM10 concentration over time and frequency are discrete, and the range of this variation is mainly concentrated in the low-frequency band. We inferred that long-term influencing factors determine the PM10 concentration level in the port, and short-term influencing factors determine the difference in concentration data at different sites. Therefore, when formulating PM10 emission mitigation strategies, targeted measures must be implemented according to the period of the different influencing factors. The results of this study can help guide recommendations for port authorities when formulating the optimal layout of measurement devices.
Collapse
Affiliation(s)
- Xuejun Feng
- College of Habour, Coastal and Offshore Engineering, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (X.F.); (K.W.)
| | - Jinxing Shen
- College of Civil and Transportation Engineering, Hohai University, No.1, Xikang Road, Nanjing 210098, China
- Correspondence:
| | - Haoming Yang
- Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution Control, Nanjing University of Information Science and Technology, No.219, Ningliu Road, Nanjing 210044, China;
| | - Kang Wang
- College of Habour, Coastal and Offshore Engineering, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (X.F.); (K.W.)
| | - Qiming Wang
- College of Science, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (Q.W.); (Z.Z.)
| | - Zhongguo Zhou
- College of Science, Hohai University, No.1, Xikang Road, Nanjing 210098, China; (Q.W.); (Z.Z.)
| |
Collapse
|
30
|
Sánchez Lasheras F, García Nieto PJ, García Gonzalo E, Bonavera L, de Cos Juez FJ. Evolution and forecasting of PM10 concentration at the Port of Gijon (Spain). Sci Rep 2020; 10:11716. [PMID: 32678178 PMCID: PMC7366928 DOI: 10.1038/s41598-020-68636-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 06/30/2020] [Indexed: 11/30/2022] Open
Abstract
The name PM10 refers to small particles with a diameter of less than 10 microns. The present research analyses different models capable of predicting PM10 concentration using the previous values of PM10, SO2, NO, NO2, CO and O3 as input variables. The information for model training uses data from January 2010 to December 2017. The models trained were autoregressive integrated moving average (ARIMA), vector autoregressive moving average (VARMA), multilayer perceptron neural networks (MLP), support vector machines as regressor (SVMR) and multivariate adaptive regression splines. Predictions were performed from 1 to 6 months in advance. The performance of the different models was measured in terms of root mean squared errors (RMSE). For forecasting 1 month ahead, the best results were obtained with the help of a SVMR model of six variables that gave a RMSE of 4.2649, but MLP results were very close, with a RMSE value of 4.3402. In the case of forecasts 6 months in advance, the best results correspond to an MLP model of six variables with a RMSE of 6.0873 followed by a SVMR also with six variables that gave an RMSE result of 6.1010. For forecasts both 1 and 6 months ahead, ARIMA outperformed VARMA models.
Collapse
Affiliation(s)
- Fernando Sánchez Lasheras
- Department of Mathematics, Faculty of Sciences, University of Oviedo, c/ Federico García Lorca 18, 33007, Oviedo, Spain.
| | - Paulino José García Nieto
- Department of Mathematics, Faculty of Sciences, University of Oviedo, c/ Federico García Lorca 18, 33007, Oviedo, Spain
| | - Esperanza García Gonzalo
- Department of Mathematics, Faculty of Sciences, University of Oviedo, c/ Federico García Lorca 18, 33007, Oviedo, Spain
| | - Laura Bonavera
- Department of Physics, Faculty of Sciences, University of Oviedo, c/ Federico García Lorca 18, 33007, Oviedo, Spain
| | - Francisco Javier de Cos Juez
- Department of Mining Exploitation and Prospecting, University of Oviedo, c/ Independencia 13, 33004, Oviedo, Spain
| |
Collapse
|
31
|
Gobbi GP, Di Liberto L, Barnaba F. Impact of port emissions on EU-regulated and non-regulated air quality indicators: The case of Civitavecchia (Italy). THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 719:134984. [PMID: 31837859 DOI: 10.1016/j.scitotenv.2019.134984] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 09/23/2019] [Accepted: 10/13/2019] [Indexed: 06/10/2023]
Abstract
Current shipping activities employ about 3% of the world-delivered energy. Most of this energy is conveyed by diesel engines. In Europe, release of NOx and particulate matter (PM) from shipping is expected to equal the road-transport one by the year 2020. This paper addresses a typical central Mediterranean city-port condition to evaluate the relative contribution of shipping activities to the local air quality. A 3-year long air quality dataset collected at the boundary between the port of Civitavecchia (the major port in central Italy) and the city itself was analyzed to evaluate the long-term, relative contribution of the port and of the city at determining the loads of EU-regulated pollutants (NO2, PM10 and SO2). In addition, black carbon and ultrafine-to-coarse particles data collected along a short-term, intensive campaign were used to assess the port's role at emitting these unregulated pollutants. Cross-analysis of the measurements, allowed to assess which shipping-related activities and port's sectors represent the principal emitters. At the city-port boundary, the annual share of regulated pollutants originating in the port area by shipping and ground movements is of 33% for PM10, 43% for NO2, and 60% for SO2. Analysis of non-regulated pollutants shows the in-port, high polluting potential of some ship categories, in particular those employing low-sulfur but poorly refined oils. These conditions appear to be more often associated with Ro-Ro passenger ships. Piers closest to the Civitavecchia urban settlements are also observed to host the largest emissions. Meteorology and location of the piers with respect to residential areas are confirmed to govern the port's share at impacting the city air quality. Even though air quality thresholds for regulated pollutants are not exceeded in Civitavecchia, constant consideration of an enlarged set of environmental variables should drive actions implemented to mitigate the port's impact onto the nearby city's air quality.
Collapse
Affiliation(s)
- Gian Paolo Gobbi
- Institute of Atmospheric Sciences and Climate, ISAC-CNR, Via Fosso del Cavaliere, 100, 00133 Rome, Italy.
| | - Luca Di Liberto
- Institute of Atmospheric Sciences and Climate, ISAC-CNR, Via Fosso del Cavaliere, 100, 00133 Rome, Italy
| | - Francesca Barnaba
- Institute of Atmospheric Sciences and Climate, ISAC-CNR, Via Fosso del Cavaliere, 100, 00133 Rome, Italy
| |
Collapse
|
32
|
Viana M, Rizza V, Tobías A, Carr E, Corbett J, Sofiev M, Karanasiou A, Buonanno G, Fann N. Estimated health impacts from maritime transport in the Mediterranean region and benefits from the use of cleaner fuels. ENVIRONMENT INTERNATIONAL 2020; 138:105670. [PMID: 32203802 PMCID: PMC8314305 DOI: 10.1016/j.envint.2020.105670] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/25/2019] [Revised: 03/05/2020] [Accepted: 03/16/2020] [Indexed: 05/19/2023]
Abstract
Ship traffic emissions degrade air quality in coastal areas and contribute to climate impacts globally. The estimated health burden of exposure to shipping emissions in coastal areas may inform policy makers as they seek to reduce exposure and associated potential health impacts. This work estimates the PM2.5-attributable impacts in the form of premature mortality and cardiovascular and respiratory hospital admissions, from long-term exposure to shipping emissions. Health impact assessment (HIA) was performed in 8 Mediterranean coastal cities, using a baseline conditions from the literature and a policy case accounting for the MARPOL Annex VI rules requiring cleaner fuels in 2020. Input data were (a) shipping contributions to ambient PM2.5 concentrations based on receptor modelling studies found in the literature, (b) population and health incidence data from national statistical registries, and (c) geographically-relevant concentration-response functions from the literature. Long-term exposure to ship-sourced PM2.5 accounted for 430 (95% CI: 220-650) premature deaths per year, in the 8 cities, distributed between groups of cities: Barcelona and Athens, with >100 premature deaths/year, and Nicosia, Brindisi, Genoa, Venice, Msida and Melilla, with tens of premature deaths/year. The more stringent standards in 2020 would reduce the number of PM2.5-attributable premature deaths by 15% on average. HIA provided a comparative assessment of the health burden of shipping emissions across Mediterranean coastal cities, which may provide decision support for urban planning with a special focus on harbour areas, and in view of the reduction in sulphur content of marine fuels due to MARPOL Annex VI in 2020.
Collapse
Affiliation(s)
- M Viana
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain.
| | - V Rizza
- Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino (FR), Italy
| | - A Tobías
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - E Carr
- Energy and Environmental Research Associates, LLC, Pittsford, NY, United States
| | - J Corbett
- College of Earth, Ocean, and Environment, University of Delaware, Newark, DE, United States
| | - M Sofiev
- Finnish Meteorological Institute (FMI), Helsinki, Finland
| | - A Karanasiou
- Institute of Environmental Assessment and Water Research (IDAEA-CSIC), Barcelona, Spain
| | - G Buonanno
- Department of Civil and Mechanical Engineering, University of Cassino and Southern Lazio, Cassino (FR), Italy; Queensland University of Technology, Brisbane, Australia
| | - N Fann
- Office of Air Quality Planning and Standards, U.S. Environmental Protection Agency, Washington, DC, United States
| |
Collapse
|
33
|
Comparison Study between Indoor and Outdoor Chemical Composition of PM2.5 in Two Italian Areas. ATMOSPHERE 2020. [DOI: 10.3390/atmos11040368] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Outdoor air quality guidelines have been constantly implemented during the last decades. Nonetheless, no international regulations have been put into action in terms of indoor air quality standards and standardized procedures for indoor pollution measurements. In this study, we investigated the chemical composition of PM2.5 collected outdoors and indoors at six dwellings located in two Italian areas. The selected sites concerned inland/central and southern Italy, including urban, peri-urban, rural and coastal settings. The seasonal and site-specific particulate matter (PM) variations were analyzed outdoors and indoors, by estimating the impact of the main macro-sources and the contribution of the macro- and micro-components. Outdoors, organic matter represented the main contribution at inland and coastal sites, respectively during winter and summer. A clear, seasonal variation was also observed for secondary inorganic species. A site-specific dependence was exhibited by traffic-related components. Indoors, organic and soil-related species were influenced by the presence of the inhabitants. Some specific tracers allowed to identify additional local source contributions and indoor activities. Although the sampling season and site location defined the outdoor air quality, the higher PM concentrations and the chemical composition indoors were influenced by the infiltration of outdoor air and by the indoor activities carried out by its inhabitants.
Collapse
|
34
|
Ramírez O, Sánchez de la Campa AM, Sánchez-Rodas D, de la Rosa JD. Hazardous trace elements in thoracic fraction of airborne particulate matter: Assessment of temporal variations, sources, and health risks in a megacity. THE SCIENCE OF THE TOTAL ENVIRONMENT 2020; 710:136344. [PMID: 31923687 DOI: 10.1016/j.scitotenv.2019.136344] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/05/2019] [Revised: 12/24/2019] [Accepted: 12/24/2019] [Indexed: 06/10/2023]
Abstract
The deleterious health effects of thoracic fractions seem to be more related to the chemical composition of the particles than to their mass concentration. The presence of hazardous materials in PM10 (e.g., heavy metals and metalloids) causes risks to human health. In this study, twelve trace elements (Cd, Cr, Pb, Zn, Cu, Ni, Sn, Ba, Co, As, V, and Sb) in 315 samples of ambient PM10 were analyzed. The samples were collected at an urban background site in a Latin American megacity (Bogota, Colombia) for one year. The concentrations and temporal variabilities of these elements were examined. According to the results, Cu (52 ng/m3), Zn (44 ng/m3), Pb (25 ng/m3), and Ba (20 ng/m3) were the traces with the highest concentrations, particularly during the dry season (January to March), which was characterized by barbecue (BBQ) charcoal combustion and forest fires. In addition, the differences between the results of weekdays and weekends were identified. The determined enrichment factor (EF) indicated that Zn, Pb, Sn, Cu, Cd, and Sb mainly originated from anthropogenic sources. Moreover, a speciation analysis of inorganic Sb (EF > 300) was conducted, which revealed that Sb(V) was the main Sb species in the PM10 samples (>80%). Six causes for the hazardous elements were identified based on the positive matrix factorization (PMF) model: fossil fuel combustion and forest fires (60%), road dust (19%), traffic-related emissions (9%), copper smelting (8%), the iron and steel industry (2%), and an unidentified industrial sector (2%). Furthermore, a health risk assessment of the carcinogenic elements was performed. Accordingly, the cancer risk of inhalation exposure to Co, Ni, As, Cd, Sb(III), and Pb was negligible for children and adults at the sampling site. For adults, the adjusted Cr(VI) level was slightly higher than the minimal acceptable risk level during the study period (1.4 × 10-6).
Collapse
Affiliation(s)
- Omar Ramírez
- Faculty of Engineering, Environmental Engineering, Universidad Militar Nueva Granada, Km 2, Cajicá-Zipaquirá 250247, Colombia; Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen, 21071 Huelva, Spain.
| | - Ana M Sánchez de la Campa
- Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen, 21071 Huelva, Spain; Department of Mining, Mechanic, Energetic and Construction Engineering, ETSI, University of Huelva, Campus de El Carmen, 21071 Huelva, Spain
| | - Daniel Sánchez-Rodas
- Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen, 21071 Huelva, Spain; Department of Chemistry, University of Huelva, Campus de El Carmen, 21071 Huelva, Spain
| | - Jesús D de la Rosa
- Associate Unit CSIC-University of Huelva "Atmospheric Pollution", Centre for Research in Sustainable Chemistry-CIQSO, Campus de El Carmen, 21071 Huelva, Spain; Department of Earth Sciences, University of Huelva, Campus de El Carmen, 21071 Huelva, Spain
| |
Collapse
|
35
|
Sorte S, Rodrigues V, Borrego C, Monteiro A. Impact of harbour activities on local air quality: A review. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 257:113542. [PMID: 31733971 DOI: 10.1016/j.envpol.2019.113542] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2019] [Revised: 10/29/2019] [Accepted: 10/29/2019] [Indexed: 06/10/2023]
Abstract
Several harbour activities cause negative environmental impacts in the harbours' surrounding areas, namely the degradation of air quality. This paper intends to comprehensively review the status of the air quality measured in harbour areas. The published studies show a limited number of available air quality monitoring data in harbours areas, mostly located in Europe (71%). Measured concentrations of the main air pollutants were compiled and intercompared, for different countries worldwide allowing a large spatial representativeness. The higher NO2 and PM10 concentrations were found in Europe - ranging between 12 and 107 μg/m3 and 2-50 μg/m3, respectively, while the higher concentrations of PM2.5 were found in Asia (25-70 μg/m3). In addition, the lower levels of SO2 monitored in recent years suggest that current mitigation strategies adopted across Europe were very efficient in promoting the reduction of SO2 concentrations. Part of the reviewed studies also estimated the contributions from ship emissions to PM concentration through the application of source apportionment methods, with an average of 5-15%. In some specific harbour areas in Asia, ships can contribute up to 7-26% to the local fine particulate matter concentrations. This review confirms that emissions from the maritime transport sector should be considered as a significant source of particulate matter in harbour areas, since this pollutant concentrations are frequently exceeding the established standard legal limit values. Therefore, the results from this review boost the implementation of mitigation measures, aiming to reduce, in particular, particulate matter emissions.
Collapse
Affiliation(s)
- Sandra Sorte
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal.
| | - Vera Rodrigues
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal
| | - Carlos Borrego
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal
| | - Alexandra Monteiro
- CESAM, Department of Environment and Planning, University of Aveiro, 3810-193, Aveiro, Portugal
| |
Collapse
|
36
|
Fameli KM, Kotrikla AM, Psanis C, Biskos G, Polydoropoulou A. Estimation of the emissions by transport in two port cities of the northeastern Mediterranean, Greece. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2020; 257:113598. [PMID: 31753631 DOI: 10.1016/j.envpol.2019.113598] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2019] [Revised: 11/07/2019] [Accepted: 11/08/2019] [Indexed: 06/10/2023]
Abstract
Air pollution is one of the most important branches of environmental science as it affects human health, climate and ecosystems. Emissions of air pollutants from transport (vehicles and ships) in port cities strongly affect air quality at local scales, warranting for a combination of theoretical and experimental studies to identify pollution hotspots. The purpose of this paper is to provide a methodology for developing a hybrid emission inventory from transport sector for two port cities located respectively on the Northern Aegean islands of Chios and Lesvos. Emission inventories were constructed for the year 2014 based on top-down and bottom-up approaches. Official data from local authorities and survey results were used for the calculation of emissions. Traffic emissions were spatially allocated to the road network based on population data and hourly traffic counts, and distributed over time (on an hourly basis) with the use of local temporal coefficients. Regarding carbon monoxide road emissions, the highest quantities are mainly emitted by Passenger Cars (43%,32% in Chios and Lesvos respectively) while for PM10 emissions, trucks have the largest share (66% in Chios and 86% in Lesvos). The pollutants that are emitted in greater quantities from the ships at the ports of Mytilene and Chios are NOx, followed by SO2 and CO. Most of the ship emissions in the ports occur by the ships at berth, as they remain berthed for hours whereas maneuvering lasts 15-20 min. As for the daily contribution of the two transport sources to the pollution profile of Mytilene, road emissions are higher for almost all pollutants. However, the contribution of ship emissions is not negligible, especially during the touristic period when marine traffic increases and emissions close to the port area become more important than those from road transport.
Collapse
Affiliation(s)
- K M Fameli
- Institute for Environmental Research and Sustainable Development, National Observatory of Athens, V.Pavlou and I. Metaxa str., 152 36 Athens, Greece.
| | - A M Kotrikla
- Department of Shipping, Transport and Trade, University of the Aegean, Chios, 82100 Greece
| | - C Psanis
- Department of Environment, University of the Aegean, Mytilene, 81100 Greece
| | - G Biskos
- Energy Environment and Water Research Centre, The Cyprus Institute, Nicosia, 2121, Cyprus; Faculty of Civil Engineering and Geosciences, Delft University of Technology, Delft, 2628CN, the Netherlands
| | - A Polydoropoulou
- Department of Shipping, Transport and Trade, University of the Aegean, Chios, 82100 Greece
| |
Collapse
|
37
|
PM10 and PM2.5 Qualitative Source Apportionment Using Selective Wind Direction Sampling in a Port-Industrial Area in Civitavecchia, Italy. ATMOSPHERE 2020. [DOI: 10.3390/atmos11010094] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The possibility to discriminate between different emission sources and between natural and anthropogenic contributions is a key issue for planning efficient air pollution reduction and mitigation strategies. Moreover, the knowledge of the particulate matter (PM) chemical composition for the different size fractions is recognized as increasingly important, in particular with respect to health effects of exposed population. This study is focused on the characterization of PM10 and PM2.5 main sources located in the Civitavecchia harbor-industrial area (Central Italy), namely a large coal-fired power plant, a natural gas power plant, the harbor area, the vehicular traffic (due to both the local traffic and the highway crossing the area) and small industrial activities. The approach was based on PM10/PM2.5 samples monthly collected for one year and a further relative chemical characterization of organic and inorganic fractions. Wind-select sensors, allowing a selective PM10 and PM2.5 sampling downwind to specific emission sources, were used for the overall sampling. This methodology manages to explain specific emission patterns and to assess the concentration levels of the micro pollutants emitted by local sources and particularly toxic for health. A descriptive statistical analysis of data was performed, also verifying the occurrence of legislative threshold exceedances. Moreover, in order to highlight the contribution of specific sources, the differences in the measured micro pollutants concentrations between wind directions, PM size fractions and sampling sites have been investigated, as well as the seasonal trends of pollutants concentrations. These results allow to highlight that the applied methodology represents a valid support in source apportionment studies.
Collapse
|
38
|
Vertical Distribution of Particulates within the Near-Surface Layer of Dry Bulk Port and Influence Mechanism: A Case Study in China. SUSTAINABILITY 2019. [DOI: 10.3390/su11247135] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Knowing the vertical distribution of ambient particulate matter (PM) will help port authorities choose the optimal dust-suppression measures to reduce PM concentrations. In this study, we used an unmanned aerial vehicle (UAV) to assess the vertical distribution (0–120 m altitude) of PM in a dry bulk port along the Yangtze River, China. Total suspended particulates (TSP), PM10, and PM2.5 concentrations at different altitudes were measured at seven sites representing different cargo-handling sites and a background site. Variations in results across sites make it not suitable to characterize the vertical distribution of PM concentration at this port using simple representative distributions. Bulk cargo particle size, fog cannon use, and porous fence all affected the vertical distribution of TSP concentrations but had only minor impacts on PM10 and PM2.5 concentrations. Optimizing porous fence layout according to weather conditions and cargo demand at port have the most potential for mitigating PM pollution related to port operation. As ground-based stations cannot fully measure vertical PM distributions, our methods and results represent an advance in assessing the impact of port activities on air quality and can be used to determine optimal dust-suppression measures for dry bulk ports.
Collapse
|
39
|
de Jesus AL, Rahman MM, Mazaheri M, Thompson H, Knibbs LD, Jeong C, Evans G, Nei W, Ding A, Qiao L, Li L, Portin H, Niemi JV, Timonen H, Luoma K, Petäjä T, Kulmala M, Kowalski M, Peters A, Cyrys J, Ferrero L, Manigrasso M, Avino P, Buonano G, Reche C, Querol X, Beddows D, Harrison RM, Sowlat MH, Sioutas C, Morawska L. Ultrafine particles and PM 2.5 in the air of cities around the world: Are they representative of each other? ENVIRONMENT INTERNATIONAL 2019; 129:118-135. [PMID: 31125731 DOI: 10.1016/j.envint.2019.05.021] [Citation(s) in RCA: 80] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/03/2019] [Accepted: 05/08/2019] [Indexed: 05/06/2023]
Abstract
Can mitigating only particle mass, as the existing air quality measures do, ultimately lead to reduction in ultrafine particles (UFP)? The aim of this study was to provide a broader urban perspective on the relationship between UFP, measured in terms of particle number concentration (PNC) and PM2.5 (mass concentration of particles with aerodynamic diameter < 2.5 μm) and factors that influence their concentrations. Hourly average PNC and PM2.5 were acquired from 10 cities located in North America, Europe, Asia, and Australia over a 12-month period. A pairwise comparison of the mean difference and the Kolmogorov-Smirnov test with the application of bootstrapping were performed for each city. Diurnal and seasonal trends were obtained using a generalized additive model (GAM). The particle number to mass concentration ratios and the Pearson's correlation coefficient were calculated to elucidate the nature of the relationship between these two metrics. Results show that the annual mean concentrations ranged from 8.0 × 103 to 19.5 × 103 particles·cm-3 and from 7.0 to 65.8 μg·m-3 for PNC and PM2.5, respectively, with the data distributions generally skewed to the right, and with a wider spread for PNC. PNC showed a more distinct diurnal trend compared with PM2.5, attributed to the high contributions of UFP from vehicular emissions to PNC. The variation in both PNC and PM2.5 due to seasonality is linked to the cities' geographical location and features. Clustering the cities based on annual median concentrations of both PNC and PM2.5 demonstrated that a high PNC level does not lead to a high PM2.5, and vice versa. The particle number-to-mass ratio (in units of 109 particles·μg-1) ranged from 0.14 to 2.2, >1 for roadside sites and <1 for urban background sites with lower values for more polluted cities. The Pearson's r ranged from 0.09 to 0.64 for the log-transformed data, indicating generally poor linear correlation between PNC and PM2.5. Therefore, PNC and PM2.5 measurements are not representative of each other; and regulating PM2.5 does little to reduce PNC. This highlights the need to establish regulatory approaches and control measures to address the impacts of elevated UFP concentrations, especially in urban areas, considering their potential health risks.
Collapse
Affiliation(s)
- Alma Lorelei de Jesus
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Md Mahmudur Rahman
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Mandana Mazaheri
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Helen Thompson
- School of Mathematical Sciences, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, QLD 4006, Australia
| | - Cheol Jeong
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, Toronto, ON M5S 3ES, Canada
| | - Greg Evans
- Southern Ontario Centre for Atmospheric Aerosol Research, University of Toronto, Toronto, ON M5S 3ES, Canada
| | - Wei Nei
- Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Qixia, Nanjing 210023, China
| | - Aijun Ding
- Institute for Climate and Global Change Research, School of Atmospheric Sciences, Nanjing University, Qixia, Nanjing 210023, China
| | - Liping Qiao
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Li Li
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Harri Portin
- Helsinki Region Environmental Services Authority, HSY, FI-00066 Helsinki, Finland
| | - Jarkko V Niemi
- Helsinki Region Environmental Services Authority, HSY, FI-00066 Helsinki, Finland
| | - Hilkka Timonen
- Atmospheric Composition Research, Finnish Meteorological Institute, P.O. Box 503, FI-00101 Helsinki, Finland
| | - Krista Luoma
- Department of Physics, University of Helsinki, FI-00014 Helsinki, Finland
| | - Tuukka Petäjä
- Department of Physics, University of Helsinki, FI-00014 Helsinki, Finland
| | - Markku Kulmala
- Department of Physics, University of Helsinki, FI-00014 Helsinki, Finland
| | - Michal Kowalski
- Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany
| | - Annette Peters
- Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany
| | - Josef Cyrys
- Helmholtz Zentrum München, German Research Centre for Environmental Health, Institute of Epidemiology II, Neuherberg, Germany
| | - Luca Ferrero
- GEMMA and POLARIS Research Centres, Department of Earth and Environmental Sciences, University of Milano-Bicocca, 20126 Milano, Italy
| | - Maurizio Manigrasso
- Department of Technological Innovations, National Institute for Insurance against Accidents at Work, Research Area, Rome, Italy
| | - Pasquale Avino
- Department of Agricultural, Environmental and Food Sciences, University of Molise, via F. De Sanctis, I-86100 Campobasso, Italy
| | - Giorgio Buonano
- Department of Engineering, University of Naples "Parthenope", Via Ammiraglio Ferdinando Acton, 38, 80233 Napoli, Italy
| | - Cristina Reche
- Institute of Environmental Assessment and Water Research, IDAEA, Spanish Research Council (CSIC), C/Jordi Girona 18-26, 08034 Barcelona, Spain
| | - Xavier Querol
- Institute of Environmental Assessment and Water Research, IDAEA, Spanish Research Council (CSIC), C/Jordi Girona 18-26, 08034 Barcelona, Spain
| | - David Beddows
- National Centre of Atmospheric Science, School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Roy M Harrison
- Division of Environmental Health and Risk Management, School of Geography, Earth and Environmental Sciences, University of Birmingham, Edgbaston, Birmingham B15 2TT, United Kingdom
| | - Mohammad H Sowlat
- Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Constantinos Sioutas
- Department of Civil and Environmental Engineering, University of Southern California, Los Angeles, CA 90089, USA
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, Brisbane, QLD 4000, Australia.
| |
Collapse
|
40
|
Liang D, Wang YQ, Wang YJ, Ma C. National air pollution distribution in China and related geographic, gaseous pollutant, and socio-economic factors. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2019; 250:998-1009. [PMID: 31085487 DOI: 10.1016/j.envpol.2019.03.075] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Revised: 03/12/2019] [Accepted: 03/18/2019] [Indexed: 06/09/2023]
Abstract
Regional specification of PM2.5 pollution characteristics is crucial for pollution control and policymaking. Spatiotemporal variations of six criteria air pollutants and influencing factors in China were studied using hourly concentrations of PM2.5, PM10, SO2, NO2, CO, and O3 from 2015 to 2016. China was categorized into eight regions: north-east, northern coastland, eastern coastland, southern coastland, Yellow River middle reaches, Yangtze River middle reaches, south-west, and north-west. The 29 exemplary cities in China were also researched. It was found that the PM2.5 concentration in the northern coastland (Beijing-Tianjin-Hebei-Shandong) was the highest (72.28 μg.m-3) among the eight regions, particularly in the city of Baoding, Hebei, which had an annual average PM2.5 concentration of 98.53 μg.m-3. Average PM2.5 concentrations in 2015 and 2016 of China were 50.16 μg.m-3 and 46.61 μg.m-3, respectively. Compared with 2015, the PM2.5 concentration decreased by 8.41% in 2016, the decline of PM2.5 in summer was the largest, followed by autumn, spring and winter. The average mean PM2.5 concentrations of the 29 exemplary cities in 2015 and 2016 were 54.66 μg.m-3 and 48.37 μg.m-3, respectively, exceeding the limit for grade 2 of the national standards (35 μg.m-3). National air pollution distribution has exploded geographically with influence of regional economic factors. Gaseous pollutant as well as geographical and socio-economic conditions influenced PM2.5 emissions. Effects of these factors on PM2.5 emissions varied across regions and decreased continuously from the northern region to the south-west and eastern coastland regions. This paper clearly identifies the regional characteristics and distribution of PM2.5, focusing on the effects of gaseous pollutant, geography and socio-economic development. Secondary transformation and vehicle exhaust across regions should be further studied.
Collapse
Affiliation(s)
- Dan Liang
- Jinyun Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China; Beijing Engineering Research Center of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China
| | - Yun-Qi Wang
- Jinyun Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China; Beijing Engineering Research Center of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China.
| | - Yu-Jie Wang
- Jinyun Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China; Beijing Engineering Research Center of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China
| | - Chao Ma
- Jinyun Forest Ecosystem Research Station, School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China; Beijing Engineering Research Center of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China
| |
Collapse
|
41
|
Sorte S, Arunachalam S, Naess B, Seppanen C, Rodrigues V, Valencia A, Borrego C, Monteiro A. Assessment of source contribution to air quality in an urban area close to a harbor: Case-study in Porto, Portugal. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 662:347-360. [PMID: 30690369 DOI: 10.1016/j.scitotenv.2019.01.185] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 01/14/2019] [Accepted: 01/15/2019] [Indexed: 06/09/2023]
Abstract
Several harbors, like the Port of Leixões (Porto, Portugal), are located near urban and industrial areas, places where residential urban areas, highways and the refinery industry coexist. The need for assessing the contribution of the port to the air quality in its vicinity around the port is the motivation for the present study. This contribution was investigated using a numerical modelling approach based on the web-based research screening tool C-PORT. The impact of the meteorological conditions (namely atmospheric stability and wind direction) was first evaluated, and the most critical conditions for pollutants dispersion were identified. The dominant wind direction, from WSW, was responsible for the transport of pollutants over the surrounding urban area, which was potentiated by the diurnal sea breeze circulation. Multiple scenario runs were then performed to quantify the contribution of each emission sector/activity (namely maritime emissions; port activities; road traffic and refinery) to the ambient air quality. The multiple scenario runs indicated that land-based emission sources at the Port (including trucks, railways, cargo handling equipment and bulk material stored) were the major contributors (approximately 80%) for the levels of surface PM10 concentrations over the study area. Whereas, the main drivers of NOX concentrations were docked ships, responsible for 55-73% of the total NOX concentrations.
Collapse
Affiliation(s)
- Sandra Sorte
- CESAM, Department of Environment and Planning, University of Aveiro, Portugal.
| | - Saravanan Arunachalam
- Institute for the Environment, The University of North Carolina at Chapel Hill, NC, USA
| | - Brian Naess
- Institute for the Environment, The University of North Carolina at Chapel Hill, NC, USA
| | - Catherine Seppanen
- Institute for the Environment, The University of North Carolina at Chapel Hill, NC, USA
| | - Vera Rodrigues
- CESAM, Department of Environment and Planning, University of Aveiro, Portugal
| | - Alejandro Valencia
- Institute for the Environment, The University of North Carolina at Chapel Hill, NC, USA
| | - Carlos Borrego
- CESAM, Department of Environment and Planning, University of Aveiro, Portugal
| | - Alexandra Monteiro
- CESAM, Department of Environment and Planning, University of Aveiro, Portugal
| |
Collapse
|
42
|
Saraga DE, Tolis EI, Maggos T, Vasilakos C, Bartzis JG. PM2.5 source apportionment for the port city of Thessaloniki, Greece. THE SCIENCE OF THE TOTAL ENVIRONMENT 2019; 650:2337-2354. [PMID: 30292125 DOI: 10.1016/j.scitotenv.2018.09.250] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/24/2018] [Revised: 09/04/2018] [Accepted: 09/19/2018] [Indexed: 06/08/2023]
Abstract
This paper aims to identify the chemical fingerprints of potential PM2.5 sources and estimate their contribution to Thessaloniki port-city's air quality. For this scope, Positive Matrix Factorization model was applied on a comprehensive PM2.5 dataset collected over a one-year period, at two sampling sites: the port and the city center. The model indicated six and five (groups of) sources contributing to particle concentration at the two sites, respectively. Traffic and biomass burning (winter months) comprise the major local PM sources for Thessaloniki (their combined contribution can exceed 70%), revealing two of the major control-demanding problems of the city. Shipping and in-port emissions have a non-negligible impact (average contribution to PM2.5: 9-13%) on both primary and secondary particles. Road dust factor presents different profile and contribution at the two sites (19.7% at the port; 7.4% at the city center). The secondary-particle factor represents not only the aerosol transportation over relatively long distances, but also a part of traffic-related pollution (14% at the port; 34% at the city center). The study aims to contribute to the principal role of quantitative information on emission sources (source apportionment) in port-cities for the implementation of the air quality directives and guidelines for public health.
Collapse
Affiliation(s)
- Dikaia E Saraga
- Environmental Research Laboratory, Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, National Centre for Scientific Research "Demokritos", 15310 Ag. Paraskevi, Attiki, Greece; University of Western Macedonia, Department of Mechanical Engineering, Environmental Technology Laboratory, Sialvera & Bakola Street, 50100 Kozani, Greece.
| | - Evangelos I Tolis
- University of Western Macedonia, Department of Mechanical Engineering, Environmental Technology Laboratory, Sialvera & Bakola Street, 50100 Kozani, Greece
| | - Thomas Maggos
- Environmental Research Laboratory, Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, National Centre for Scientific Research "Demokritos", 15310 Ag. Paraskevi, Attiki, Greece
| | - Christos Vasilakos
- Environmental Research Laboratory, Institute of Nuclear & Radiological Sciences & Technology, Energy & Safety, National Centre for Scientific Research "Demokritos", 15310 Ag. Paraskevi, Attiki, Greece
| | - John G Bartzis
- University of Western Macedonia, Department of Mechanical Engineering, Environmental Technology Laboratory, Sialvera & Bakola Street, 50100 Kozani, Greece
| |
Collapse
|
43
|
Lopes M, Russo A, Gouveia C, Ferreira F. Monitoring of Ultrafine Particles in the Surrounding Urban Area of In-Land Passenger Ferries. ACTA ACUST UNITED AC 2019. [DOI: 10.4236/jep.2019.106050] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
|
44
|
Scerri MM, Kandler K, Weinbruch S, Yubero E, Galindo N, Prati P, Caponi L, Massabò D. Estimation of the contributions of the sources driving PM 2.5 levels in a Central Mediterranean coastal town. CHEMOSPHERE 2018; 211:465-481. [PMID: 30081219 DOI: 10.1016/j.chemosphere.2018.07.104] [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: 05/08/2018] [Revised: 07/11/2018] [Accepted: 07/18/2018] [Indexed: 06/08/2023]
Abstract
Receptor modelling techniques are widely used in order to identify the main natural and anthropogenic processes driving aerosol levels at a receptor. In this work, Positive Matrix Factorization (PMF) was used to apportion PM2.5 levels at a traffic site (Msida) located in a coastal town. 180 filters collected throughout a yearly sampling campaign conducted in 2016, were chemically characterized by light absorbance analysis, x-ray fluorescence and ion chromatography in order to determine the concentrations of black carbon, 17 elements and 5 ions, respectively. The resulting chemical data base was used in conjunction with PMF in order to identify the 7 components affecting the PM2.5 levels at the receptor site. Six of these sources are considered to be typical of the atmospheric composition of coastal traffic sites: traffic (27.3%), ammonium sulfate (23.6%), Saharan dust (15%), aged sea salt (12.7%), shipping (5%) and fresh sea salt (4.6%). This is the first time that such a study was carried out in Malta and helps in understanding the aerosol pollution climate of the Central Mediterranean, which is still relatively understudied when compared to the Eastern and Western Mediterranean. Furthermore, we have isolated a factor exclusive to Malta: the fireworks component, which is responsible for 2.9% of the PM2.5 and which has health implications due to its chemical composition. The results of this work should also serve to guide the policy makers in achieving the necessary emission reductions in order to achieve the WHO guideline for PM2.5 by 2020.
Collapse
Affiliation(s)
- Mark M Scerri
- Ambient Quality & Waste Unit, Environment and Resources Authority, Malta; Institute of Applied Geosciences, Technical University Darmstadt, Darmstadt, Germany; Institute of Earth Systems, University of Malta, Msida, Malta.
| | - Konrad Kandler
- Institute of Applied Geosciences, Technical University Darmstadt, Darmstadt, Germany
| | - Stephan Weinbruch
- Institute of Applied Geosciences, Technical University Darmstadt, Darmstadt, Germany
| | - Eduardo Yubero
- Atmospheric Pollution Laboratory, Universidad Miguel Hernández, Avenida de la Universidad s/n, Edificio Alcudia, 03202, Elche, Spain
| | - Nuria Galindo
- Atmospheric Pollution Laboratory, Universidad Miguel Hernández, Avenida de la Universidad s/n, Edificio Alcudia, 03202, Elche, Spain
| | - Paolo Prati
- Physics Department & INFN, Università degli studi di Genova, via Dodecaneso 33, 16146, Genova, Italy
| | | | - Dario Massabò
- Physics Department & INFN, Università degli studi di Genova, via Dodecaneso 33, 16146, Genova, Italy
| |
Collapse
|
45
|
Characterization of In Situ Aerosol Optical Properties at Three Observatories in the Central Mediterranean. ATMOSPHERE 2018. [DOI: 10.3390/atmos9100369] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
In this work, results of scattering and backscattering coefficients, scattering Ångström exponent (SAE), single scattering albedo (SSA), and asymmetry parameter (g) of atmospheric aerosols are presented. All these parameters were measured during the month of April 2016 in Southern Italy on three different Global Atmosphere Watch observatories in the Central Mediterranean. This is the first time, to our knowledge, that optical aerosol properties were studied at the same time, even if in a brief intensive measurement campaign, at three sites in the South of Italy. In order to obtain a characteristic value for aerosol optical properties, different kinds of particle sources (i.e., dust, marine, and anthropic) have been identified and studied. In the measurement period, one event of a long-range transport of Saharan dust from Northern Africa was observed at all observatories. During the Saharan dust transport event, a minimum value of the SAE (0.69 ± 0.34) and a relatively higher values of SSA were observed. During the dust event, g increased up to 0.69. Marine aerosol contribution and anthropic/urban aerosol intrusion were analysed. From this analysis, SAE average values were 0.70, 0.84, and 1.22, respectively, for dust, marine, and anthropic particles. On the other hand, the SSA minimum value was 0.86 for anthropic particles, and it increased for dust (0.88) and marine (0.93) aerosols. The asymmetry parameter had a limited variability for the three types of aerosol from 0.62 to 0.58, as reported also in literature.
Collapse
|
46
|
Xu L, Jiao L, Hong Z, Zhang Y, Du W, Wu X, Chen Y, Deng J, Hong Y, Chen J. Source identification of PM 2.5 at a port and an adjacent urban site in a coastal city of China: Impact of ship emissions and port activities. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 634:1205-1213. [PMID: 29710626 DOI: 10.1016/j.scitotenv.2018.04.087] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2018] [Revised: 04/03/2018] [Accepted: 04/06/2018] [Indexed: 06/08/2023]
Abstract
Daily PM2.5 samples were collected simultaneously at an urban site (UB) and a nearby port-industrial site (PI) on the coast of southeastern China from April 2015 to January 2016. The PM2.5 mass concentration at the PI (51.9μgm-3) was significantly higher than that at the UB. The V concentration at the PI was also significantly higher and well-correlated to the urban value, which suggests that shipping emissions had a significant impact on the PI and, to a lesser extent, on the urban area. A positive matrix factorization (PMF) analysis showed that secondary aerosols were the dominant contribution of PM2.5 at both sites (36.4% at the PI and 27.2% at the UB), while the contribution of industry and ship emissions identified by V, Mn, and Ba at the PI (26.1%) were double those at the UB. The difference in each source contribution among the trajectory clusters that included significant differences and insignificant differences from the UB to the PI provided insight into the role of local impacts. With regards to the UB, local potential sources play important roles in industry and ship emissions, traffic emissions, fugitive dust, and in their contributions to secondary aerosols. A conditional probability function further revealed that the ship emissions and port activities distributed in the NE, E, and SSE wind sectors were responsible for the source contributions of industry and ship emissions and secondary aerosols at the UB. This study provides an example of investigating the impact of ship emissions and port activities on the surrounding air environment using land-based measurements.
Collapse
Affiliation(s)
- Lingling Xu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Ling Jiao
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Academy of resource and environment, Fujian Agriculture and Forestry University, Fuzhou 350002, China
| | - Zhenyu Hong
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Graduate School of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanru Zhang
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Graduate School of Chinese Academy of Sciences, Beijing 100049, China
| | - Wenjiao Du
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Graduate School of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Wu
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Graduate School of Chinese Academy of Sciences, Beijing 100049, China
| | - Yanting Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Junjun Deng
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Youwei Hong
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
| | - Jinsheng Chen
- Center for Excellence in Regional Atmospheric Environment, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China; Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China.
| |
Collapse
|
47
|
Liu H, Jin X, Wu L, Wang X, Fu M, Lv Z, Morawska L, Huang F, He K. The impact of marine shipping and its DECA control on air quality in the Pearl River Delta, China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2018; 625:1476-1485. [PMID: 29996444 DOI: 10.1016/j.scitotenv.2018.01.033] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 01/04/2018] [Accepted: 01/04/2018] [Indexed: 06/08/2023]
Abstract
Marine trade has significantly expanded over the past decades aiding to the economic development of the maritime countries, yet, this has been associated with a considerable increase in pollution emission from shipping operation. This study aims at considering both sides of the spectrum at the same time, which is including both public and shipping business. Of the key significance would be to optimize the operation of the shipping industry, such that its impact on air pollution is minimized, without, however, significant escalation of its cost, and therefore to protect the whole seaborne trade. To do this, we considered the impacts of three control strategies, including the current emission control area (ECA) design, as well two additional ones. Thus the first scenario (DECA1) was based on the China's domestic emission control area (DECA), which was set up in 2016. The DECA1 scale was only 12 nautical miles, which was much smaller than the emission control areas in US or Europe. We defined the second scenario (DECA2), by stretching the zone to 200 nautical miles towards the ocean, modeling it on the ECA in North America. The third scenario (DECA3), on the other hand, expanded the 12 nautical miles control zone along the whole coastline. To investigate the impact of shipping emissions on air quality, a shipping emission calculation model and an air quality simulation model were used, and Pearl River Delta (PRD), China was chosen to serve as a case study. The study demonstrated that in 2013 marine shipping emissions contributed on average 0.33 and 0.60μg·m-3, respectively to the land SO2 and PM2.5 concentrations in the PRD, and that the concentrations were high along the coastline. The DECA1 policy could effectively reduce SO2 and PM2.5 concentrations in the port regions, and the average reduction in the land area were 9.54% and 2.7%, respectively. Compared with DECA1, DECA2 would not measurably improve the air quality, while DECA3 would effectively decrease the pollution in the entire coast area. Thus, instead of expanding emission control area far to the ocean, it is more effective to control emissions along the coastline to secure the best air quality and lower the health impacts. By doing this, 19 million dollars of fuel cost could be saved per year. The saved cost could help the ship owners to endure, considering the current low profits of the seaborne trade, and thus to protect the overall growth of the economy.
Collapse
Affiliation(s)
- Huan Liu
- State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China.
| | - Xinxin Jin
- State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
| | - Luolin Wu
- School of Atmospheric Sciences, Sun Yat-Sen University, Guangzhou 510275, China
| | - Xuemei Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 511443, China.
| | - Mingliang Fu
- State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
| | - Zhaofeng Lv
- State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology, 2 George Street, Brisbane, QLD 4001, Australia
| | - Feifan Huang
- State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Key Joint Laboratory of ESPC, School of Environment, Tsinghua University, Beijing 100084, China
| |
Collapse
|
48
|
A Computational Fluid Dynamic (CFD) Simulation of PM 10 Dispersion Caused by Rail Transit Construction Activity: A Real Urban Street Canyon Model. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018. [PMID: 29522495 PMCID: PMC5877027 DOI: 10.3390/ijerph15030482] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Particle emissions derived from construction activities have a significant impact on the local air quality, while the canyon effect with reduced natural ventilation contributes to the highest particulate pollution in urban environments. This study attempted to examine the effect of PM10 emissions derived from the construction of a rail transit system in an urban street canyon. Using a 3D computational fluid dynamic (CFD) model based on a real street canyon with different height ratios, this study formulates the impact of height ratio and wind directions on the dispersion and concentration of PM10. The results indicate that parallel flow would cause the concentration of PM10 at the end of the street canyons in all height ratios, and the trends in horizontal, vertical and lateral planes in all street canyons are similar. While in the condition of perpendicular flow, double-eddy circulations occur and lead to the concentration of PM10 in the middle part of the street canyon and leeward of backwind buildings in all height ratios. Furthermore, perpendicular flow will cause the concentration of PM10 to increase if the upwind buildings are higher than the backwind ones. This study also shows that the dispersion of PM10 is strongly associated with wind direction in and the height ratios of the street canyons. Certain measures could, therefore, be taken to prevent the impact on people in terms of the PM10 concentration and the heights of street canyons identified in this research. Potential mitigation strategies are suggested, include measurements below 4 m according to governmental regulations, dust shields, and atomized water.
Collapse
|
49
|
Dimitriou K, Kassomenos P. The influence of specific atmospheric circulation types on PM 10-bound benzo(a)pyrene inhalation related lung cancer risk in Barcelona, Spain. ENVIRONMENT INTERNATIONAL 2018; 112:107-114. [PMID: 29268158 DOI: 10.1016/j.envint.2017.12.022] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 12/01/2017] [Accepted: 12/15/2017] [Indexed: 06/07/2023]
Abstract
Benzo(a)pyrene (BaP) is a Polycyclic Aromatic Hydrocarbon (PAH) well known for its carcinogenic effects. In this study, BaP levels in daily PM10 samples collected at 8 stations in Barcelona (Spain), during the years 2013-2015, were analyzed in relation to distinct atmospheric circulation patterns. Our objective was to estimate the BaP inhalation related Lung Cancer Risk (LCR) in connection with the prevailing synoptic conditions. Air masses were also analyzed in order to examine the possibility of transboundary BaP contributions. The influence of high pressure anticyclonic systems caused a sharp increase of PM10-bound BaP concentrations in all stations due to recirculation and accumulation of polluted air, whilst the calculated BaP inhalation related LCR values implied a potential health risk from BaP exposure and were not recommendable primarily at central heavily trafficked sites. However the LCR remained below the upper limit posed by United States Environmental Protection Agency (US EPA), even under the most stagnant atmospheric conditions. The elaboration of backward air mass trajectories with Concentration Weighted Trajectory (CWT) algorithm indicated that combustion emissions in Spain, France and the industrialized Northern coast of Algeria are potential contributors to the PM10-bound BaP concentrations measured in Barcelona.
Collapse
Affiliation(s)
| | - Pavlos Kassomenos
- Laboratory of Meteorology, Department of Physics, University of Ioannina, Greece
| |
Collapse
|
50
|
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.
Collapse
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
| |
Collapse
|