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Zhang Z, Man H, Zhao J, Huang W, Huang C, Jing S, Luo Z, Zhao X, Chen D, He K, Liu H. VOC and IVOC emission features and inventory of motorcycles in China. J Hazard Mater 2024; 469:133928. [PMID: 38447368 DOI: 10.1016/j.jhazmat.2024.133928] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Revised: 02/09/2024] [Accepted: 02/28/2024] [Indexed: 03/08/2024]
Abstract
How did the motorcycle emissions evolve during the economic development in China? To address data gaps, this study firstly measured the volatile organic compound (VOC) and intermediate-volatility organic compound (IVOC) emissions from motorcycles. The results confirmed that the emission control of motorcycles, especially small-displacement motorcycles, significantly lagged behind other gasoline-powered vehicles. For the China IV motorcycles, the average VOC and IVOC emission factors (EFs) were 2.74 and 7.78 times higher than the China V-VI light-duty gasoline vehicles, respectively. The notable high IVOC emissions were attributed to a dual influence from gasoline and lubricating oil. Furthermore, based on the complete EF dataset and economy-related activity data, a county-level emission inventory was developed in China. Motorcycle VOC and IVOC emissions changed from 2536.48 Gg and 197.19 Gg in 2006 to 594.21 Gg and 12.66 Gg in 2020, respectively. The absence of motorcycle IVOC emissions in the existed vehicular inventories led to an underestimation of up to 20%. Across the 15 years, the motorcycle VOC and IVOC emission hotspots were concentrated in the undeveloped regions, with the rural emissions reaching 5.81-10.14 times those of the urban emissions. This study provides the first-hand and close-to-realistic data to support motorcycle emission management and accurate air quality simulations.
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Affiliation(s)
- Zhining Zhang
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Hanyang Man
- Fujian Key Laboratory of Pollution Control & Resource Reuse, College of Environmental and Resource Sciences, Fujian Normal University, Fuzhou, 350007, China
| | - Junchao Zhao
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Wendong Huang
- Shanghai Motor Vehicle Inspection Certification & Tech Innovation Center Co., Ltd, Shanghai 201805, China
| | - Cheng Huang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Shengao Jing
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environmental Sciences, Shanghai 200233, China
| | - Zhenyu Luo
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Xinyue Zhao
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Dawei Chen
- State Environmental Protection Key Laboratory of Vehicle Emission Control and Simulation, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Kebin He
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China
| | - Huan Liu
- State Key Joint Laboratory of ESPC, State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, School of Environment, Tsinghua University, Beijing 100084, China.
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2
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Tang R, Guo S, Song K, Yu Y, Tan R, Wang H, Liu K, Shen R, Chen S, Zeng L, Zhang Z, Zhang W, Shuai S, Hu M. Emission characteristics of intermediate volatility organic compounds from a Chinese gasoline engine under varied operating conditions: Influence of fuel, velocity, torque, rotational speed, and after-treatment device. Sci Total Environ 2024; 906:167761. [PMID: 37832675 DOI: 10.1016/j.scitotenv.2023.167761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2023] [Revised: 09/14/2023] [Accepted: 10/10/2023] [Indexed: 10/15/2023]
Abstract
Improved measurement of new pollutants, particularly intermediate volatility organic compounds (IVOCs), is urgently needed due to the lack of emission data under various operating conditions and potential fuel switching for gasoline engines. This study focused on examining the emission characteristics of IVOCs and the formation of secondary organic aerosols (SOA) in a commercial gasoline direct injection (GDI) engine, considering different fuels and operating conditions. The key findings are as follows: (1) The emission factor (EF) of IVOCs ranged from 2.0 to 357.8 mg kg-fuel-1, with a median value of 87.9 mg kg-fuel-1. (2) IVOCs emission characteristics were influenced by the fuel type and engine operating conditions. The addition of ethanol resulted in a significant decrease in IVOCs emissions, while lower velocities and torques led to higher IVOCs emissions. (3) Ethanol-blended fuel scenarios (E10, E25) and CGPF (Pd/Rh catalytically coated gasoline particle filter)-equipped scenarios exhibited high proportions of oxygen-containing compounds like aliphatic alcohols, ethers, and carboxylic acids. (4) IVOCs exhibited a high potential for the formation of SOA, underscoring the importance of controlling IVOCs in future strategies to mitigate particulate matter pollution in China. These findings highlight the significance of smooth traffic flow and advancements in fuel types, engine technologies, and after-treatment designs to effectively control IVOC emissions and contribute to the realization of a carbon-neutral society.
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Affiliation(s)
- Rongzhi Tang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, PR China; School of Energy and Environment, City University of Hong Kong, Kowloon 999077, Hong Kong, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China; Collaborative Innovation Center of Atmospheric Environment and Equipment Technology, Nanjing University of Information Science & Technology, Nanjing 210044, PR China.
| | - Kai Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Ying Yu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Rui Tan
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Hui Wang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Kefan Liu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Ruizhe Shen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Shiyi Chen
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Limin Zeng
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
| | - Zhou Zhang
- State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, PR China
| | - Wenbin Zhang
- State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, PR China
| | - Shijin Shuai
- State Key Laboratory of Automotive Safety and Energy, School of Vehicle and Mobility, Tsinghua University, Beijing 100084, PR China
| | - Min Hu
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Peking University, Beijing 100871, PR China
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3
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Cui M, Xu Y, Liu Z, Zhang Y, Zhang F, Yan C, Chen Y. Characteristics of intermediate volatility organic compounds emitted from inland vessels with different influential factors and implication of reduction emissions. Sci Total Environ 2023; 904:166868. [PMID: 37678527 DOI: 10.1016/j.scitotenv.2023.166868] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 08/23/2023] [Accepted: 09/04/2023] [Indexed: 09/09/2023]
Abstract
Ships could emit an abundance intermediate volatility organic compounds (IVOCs). In recent years, many studies on the emission characteristics of IVOCs have focused on the burning of heavy fuel oil by ocean-going ships; however, few have focused on inland vessels which have a more significant impact on air quality and human health owing to their closer proximity to cities than ocean-going ships. In this study, the IVOC emission factors (EFIVOCs) of three inland vessels were determined using a dilution sampling system considering different influencing factors (ship age and operating conditions). The results showed that the EFIVOCs values ranged from 869.9 to 7607 mg/kg fuel, with an average of 4128 ± 2703 mg/kg fuel. In addition, the age of the vessel was found to have a dramatic effect on emissions with the average EFIVOCs of inland vessels aged >10 years was 4300 ± 4319, 5769, and 6484 ± 1586 mg/kg fuel under cruising, idling, and maneuvering conditions, respectively, while that of vessels <10 years old was 1180 ± 328.3 mg/kg fuel when maneuvering. The percentages of emission factors for unresolved complex mixture (UCM), normal alkanes (n-alkanes), branched alkanes (b-alkanes), and polycyclic aromatic hydrocarbons (PAHs) from inland vessels were 82.1 ± 2.6 %, 5.2 ± 0.9 %, 10.6 ± 2.0 % and 2.0 ± 0.6 % of the total IVOCs, respectively. The secondary organic aerosols (SOA) production of inland vessels was estimated to be 1212 ± 801.7 mg/kg fuel, which was substantially higher than those of diesel vehicles, non-road construction machinery, and gasoline vehicles reported by other researches. Moreover, based on the ship movement and measured EFIVOCs data, the IVOCs emission inventory of inland vessels in Jiangsu Province and China in 2016 was 4.2 ± 2.8 and 32.0 ± 21.0 Gg respectively, which was comparable to those from diesel vehicle emissions.
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Affiliation(s)
- Min Cui
- College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225009, PR China.
| | - Yuanyuan Xu
- College of Environmental Science and Engineering, Yangzhou University, Yangzhou 225009, PR China
| | - Zeyu Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, PR China
| | - Yishun Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, PR China
| | - Fan Zhang
- School of Geographic Sciences, East China Normal University, Shanghai 200241, PR China
| | - Caiqing Yan
- Environment Research Institute, Shandong University, Qingdao 266237, PR China
| | - Yingjun Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP(3)), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, PR China.
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Zhang Z, Zhang Y, Zou L, Ou Z, Luo D, Liu Z, Huang Z, Fei L, Wang X. Intermediate-volatility aromatic hydrocarbons from the rubber products industry in China. Sci Total Environ 2023; 898:165583. [PMID: 37467984 DOI: 10.1016/j.scitotenv.2023.165583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Revised: 07/14/2023] [Accepted: 07/15/2023] [Indexed: 07/21/2023]
Abstract
As key components of intermediate-volatility organic compounds (IVOCs), intermediate-volatility aromatic hydrocarbons (IAHs) are important precursors of ozone and secondary organic aerosol (SOA). Rubber products (RP) industry has significant influence on ozone and SOA formation, yet few studies are available to characterize their emissions of IAHs. Here we conducted measurements of IAHs emitted from rubber products (RP) factories in China. Tens of C10-C12 IAH species were identified with C10H14-AH (such as tetramethyl benzene) and naphthalene (C10H8) as the dominant species, accounting for 57.0 % - 100.0 % of total IAHs emissions. On average, IAHs showed higher concentrations (1.1 × 102-1.2 × 103 μg m-3) in mixing, extrusion, painting, crushing, and grinding processes than those (8.2-14 μg m-3) in vulcanization and gumming processes as well as warehouse. Moreover, IAHs concentrations were 1.3-1.7 times of volatile aromatic hydrocarbons (VAHs; C6-C9 aromatics) in the emissions from mixing, extrusion, crushing and grinding processes. The average IAHs to volatile organic compounds (VOCs) ratios also showed relatively higher values (0.1-0.7) in these processes, which were significantly higher than those of 0.01-0.03 observed in other industries, and even comparable to the IVOCs to VOCs ratio of 0.2 used for estimating solvent-related emission. The ozone and SOA formation potential values of IAHs were 1.1-2.6 times and 0.9-3.9 times those of VAHs, respectively, and were 0.5-1.0 times and 0.9-1.9 times those of total VOCs in emissions of mixing, extrusion, crushing, and grinding processes of the RP industry. The total emission of IAHs was estimated to be 115.8 Gg from the RP industry in China, which could account for 64.5 % of total IAH emissions from all industrial sectors. This study further suggests that the RP industry might be an important emission source of IAHs with substantially higher ozone and SOA formation potentials.
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Affiliation(s)
- Zhou Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; Changsha Center for Mineral Resources Exploration, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Changsha 410013, China
| | - Yanli Zhang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China.
| | - Lilin Zou
- Changsha Center for Mineral Resources Exploration, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Changsha 410013, China
| | - Zhongxiangyu Ou
- Changsha Center for Mineral Resources Exploration, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Changsha 410013, China
| | - Datong Luo
- Hunan Research Academy of Environmental Sciences, Changsha 410004, China
| | - Zhan Liu
- Hunan Research Academy of Environmental Sciences, Changsha 410004, China
| | - Zhonghui Huang
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Leilei Fei
- South China Institute of Environmental Sciences, Ministry of Ecology and Environment, Guangzhou 510655, China
| | - Xinming Wang
- State Key Laboratory of Organic Geochemistry and Guangdong Key Laboratory of Environmental Protection and Resources Utilization, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, China; University of Chinese Academy of Sciences, Beijing 100049, China
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5
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Shen X, Che H, Yao Z, Wu B, Lv T, Yu W, Cao X, Hao X, Li X, Zhang H, Yao X. Real-World Emission Characteristics of Full-Volatility Organics Originating from Nonroad Agricultural Machinery during Agricultural Activities. Environ Sci Technol 2023. [PMID: 37419883 DOI: 10.1021/acs.est.3c02619] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/09/2023]
Abstract
Nonroad agricultural machinery (NRAM) emissions constitute a significant source of air pollution in China. Full-volatility organics originating from 19 machines under 6 agricultural activities were measured synchronously. The diesel-based emission factors (EFs) for full-volatility organics were 4.71 ± 2.78 g/kg fuel (average ± standard deviation), including 91.58 ± 8.42% volatile organic compounds (VOCs), 7.94 ± 8.16% intermediate-volatility organic compounds (IVOCs), 0.28 ± 0.20% semivolatile organic compounds (SVOCs), and 0.20 ± 0.16% low-volatility organic compounds (LVOCs). Full-volatility organic EFs were significantly reduced by stricter emission standards and were the highest under pesticide spraying activity. Our results also demonstrated that combustion efficiency was a potential factor influencing full-volatility organic emissions. Gas-particle partitioning in full-volatility organics could be affected by multiple factors. Furthermore, the estimated secondary organic aerosol formation potential based on measured full-volatility organics was 143.79 ± 216.80 mg/kg fuel and could be primarily attributed to higher-volatility-interval IVOCs (bin12-bin16 contributed 52.81 ± 11.58%). Finally, the estimated emissions of full-volatility organics from NRAM in China (2021) were 94.23 Gg. This study provides first-hand data on full-volatility organic EFs originating from NRAM to facilitate the improvement of emission inventories and atmospheric chemistry models.
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Affiliation(s)
- Xianbao Shen
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hongqian Che
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Zhiliang Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Bobo Wu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Tiantian Lv
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Wenhan Yu
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
| | - Xinyue Cao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xuewei Hao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xin Li
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Hanyu Zhang
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
| | - Xiaolong Yao
- School of Ecology and Environment, Beijing Technology and Business University, Beijing 100048, China
- State Environmental Protection Key Laboratory of Food Chain Pollution Control, Beijing Technology and Business University, Beijing 100048, China
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Tang R, Song K, Gong Y, Sheng D, Zhang Y, Li A, Yan S, Yan S, Zhang J, Tan Y, Guo S. Detailed Speciation of Semi-Volatile and Intermediate-Volatility Organic Compounds (S/IVOCs) in Marine Fuel Oils Using GC × GC-MS. Int J Environ Res Public Health 2023; 20:2508. [PMID: 36767874 PMCID: PMC9916049 DOI: 10.3390/ijerph20032508] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 01/16/2023] [Accepted: 01/28/2023] [Indexed: 06/18/2023]
Abstract
Ship emissions contribute substantial air pollutants when at berth. However, the complexity and diversity of the marine fuels utilized hinder our understanding and mapping of the characteristics of ship emissions. Herein, we applied GC × GC-MS to analyze the components of marine fuel oils. Owing to the high separation capacity of GC × GC-MS, 11 classes of organic compounds, including b-alkanes, alkenes, and cyclo-alkanes, which can hardly be resolved by traditional one-dimensional GC-MS, were detected. Significant differences are observed between light (-10# and 0#) and heavy (120# and 180#) fuels. Notably, -10# and 0# diesel fuels are more abundant in b-alkanes (44~49%), while in 120# and 180#, heavy fuels b-alkanes only account for 8%. Significant enhancement of naphthalene proportions is observed in heavy fuels (20%) compared to diesel fuels (2~3%). Hopanes are detected in all marine fuels and are especially abundant in heavy marine fuels. The volatility bins, one-dimensional volatility-based set (VBS), and two-dimensional VBS (volatility-polarity distributions) of marine fuel oils are investigated. Although IVOCs still take dominance (62-66%), the proportion of SVOCs in heavy marine fuels is largely enhanced, accounting for ~30% compared to 6~12% in diesel fuels. Furthermore, the SVOC/IVOC ratio could be applied to distinguish light and heavy marine fuel oils. The SVOC/IVOC ratios for -10# diesel fuel, 0# diesel fuel, 120# heavy marine fuel, and 180# heavy marine fuel are 0.085 ± 0.046, 0.168 ± 0.159, 0.504, and 0.439 ± 0.021, respectively. Our work provides detailed information on marine fuel compositions and could be further implemented in estimating organic emissions and secondary organic aerosol (SOA) formation from marine fuel storage and evaporation processes.
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Affiliation(s)
- Rongzhi Tang
- School of Energy and Environment, City University of Hong Kong, Kowloon 999077, Hong Kong, China
- Shenzhen Research Institute, City University of Hong Kong, Shenzhen 518057, China
- School of Environment and Materials Engineering, Yantai University, Yantai 264003, China
| | - Kai Song
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Beijing 100871, China
| | - Yuanzheng Gong
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Beijing 100871, China
| | - Dezun Sheng
- School of Environment and Materials Engineering, Yantai University, Yantai 264003, China
| | - Yuan Zhang
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Beijing 100871, China
| | - Ang Li
- China Automotive Technology and Research Center (CATARC), Beijing 100176, China
| | - Shuyuan Yan
- China Automotive Technology and Research Center (CATARC), Beijing 100176, China
| | - Shichao Yan
- China Automotive Technology and Research Center (CATARC), Beijing 100176, China
| | - Jingshun Zhang
- Department of Investigation Shanghai Police College, Shanghai 200137, China
| | - Yu Tan
- School of Chemical Engineering and Technology, Sun Yat-sen University, Zhuhai 519082, China
| | - Song Guo
- State Key Joint Laboratory of Environmental Simulation and Pollution Control, International Joint Laboratory for Regional Pollution Control, Ministry of Education (IJRC), College of Environmental Sciences and Engineering, Beijing 100871, China
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Liu Z, Chen Y, Zhang Y, Zhang F, Feng Y, Zheng M, Li Q, Chen J. Emission Characteristics and Formation Pathways of Intermediate Volatile Organic Compounds from Ocean-Going Vessels: Comparison of Engine Conditions and Fuel Types. Environ Sci Technol 2022; 56:12917-12925. [PMID: 36070884 DOI: 10.1021/acs.est.2c03589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The lack of emission data for ocean-going vessels (OGVs) and the recent fuel switching make it urgent to enhance the onboard measurement of ship emissions, especially for intermediate volatile organic compounds (IVOCs). This study focused on the IVOC emission characteristics and formation pathways of three OGVs under various engine conditions (power and load) and fuel oils (heavy fuel oil (HFO) versus marine gas oil (MGO)). The results showed that the (1) IVOC emission factors (EFIVOC) of the three OGVs increased with engine power and were higher for MGO (1494.4 ± 421.7 mg/kg) than HFO (1830.5 ± 534.5 mg/kg) and engine load is an important parameter. (2) Engine load and oil type affect the composition and volatility distribution of IVOCs. The proportion of polycyclic aromatic hydrocarbons in IVOCs increased with a higher load, and using MGO shifted IVOC components to a higher volatility in contrast to HFO. (3) The compositions of IVOCs were more like those in fuel oils under low loads than under high loads, indicating that different formation pathways of IVOCs exist for different engine loads. (4) A higher EFIVOC was observed nearshore than in open sea owing to the lower and transient engine load, which indicates the necessity of paying attention to the IVOC emissions for ships.
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Affiliation(s)
- Zeyu Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Yingjun Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai 200092, China
| | - Yan Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Fan Zhang
- Key Laboratory of Geographic Information Science, Ministry of Education, East China Normal University, Shanghai 200241, China
- School of Geographic Sciences, East China Normal University, Shanghai 200241, China
- Key Laboratory of Spatial-Temporal Big Data Analysis and Application of Natural Resources in Megacities, Ministry of Natural Resources, Shanghai 200241, China
| | - Yanli Feng
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Mei Zheng
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Qing Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
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Ling Z, Wu L, Wang Y, Shao M, Wang X, Huang W. Roles of semivolatile and intermediate-volatility organic compounds in secondary organic aerosol formation and its implication: A review. J Environ Sci (China) 2022; 114:259-285. [PMID: 35459491 DOI: 10.1016/j.jes.2021.08.055] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Revised: 08/31/2021] [Accepted: 08/31/2021] [Indexed: 06/14/2023]
Abstract
Secondary organic aerosol (SOA) is a very important component of fine particulate matter (PM2.5) in the atmosphere. However, the simulations of SOA, which could help to elucidate the detailed mechanism of SOA formation and quantify the roles of various precursors, remains unsatisfactory, as SOA levels are frequently underestimated. It has been found that the performance of SOA formation models can be significantly improved by incorporating the emission and evolution of semivolatile and intermediate-volatility organic compounds (S/IVOCs). In order to explore the roles of S/IVOCs in SOA formation, this study reviews some simulation models which could consider S/IVOCs for SOA formation as well as the development of emission inventories of S/IVOCs and S/IVOC modules for SOA formation. In addition, the future research directions for simulations of the effect of S/IVOCs on SOA formation are suggested.
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Affiliation(s)
- Zhenhao Ling
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Liqing Wu
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Yonghong Wang
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Min Shao
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
| | - Xuemei Wang
- Guangdong-Hongkong-Macau Joint Laboratory of Collaborative Innovation for Environmental Quality, Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China.
| | - Weiwen Huang
- School of Atmospheric Sciences, Sun Yat-sen University, Key Laboratory of Tropical Atmosphere-Ocean System, Ministry of Education, and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
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Li J, Li K, Li H, Wang X, Wang W, Wang K, Ge M. Long-chain alkanes in the atmosphere: A review. J Environ Sci (China) 2022; 114:37-52. [PMID: 35459500 DOI: 10.1016/j.jes.2021.07.021] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Revised: 07/15/2021] [Accepted: 07/20/2021] [Indexed: 06/14/2023]
Abstract
As a representative species of intermediate volatile organic compounds (IVOCs), long-chain alkanes are considered to be important precursors of secondary organic aerosols (SOA) in the atmosphere. This work reviews the previous studies on long-chain alkanes in the atmosphere: (1) the detection methods and filed observations of long-chain alkanes in both gas and particle phases are summarized briefly; (2) the laboratory studies of long chain alkanes are reviewed, the kinetic data, reaction mechanism, SOA yields, and physicochemical properties of SOA are included in detail; (3) the research progress related to model simulations of long-chain alkanes are also discussed. In addition, based on available research results, several perspective contents are proposed that can be used as a guideline for future research plans.
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Affiliation(s)
- Junling Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Kun Li
- Laboratory of Atmospheric Chemistry, Paul Scherrer Institute, Villigen 5232, Switzerland
| | - Hong Li
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Xuezhong Wang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Weigang Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China.
| | - Ke Wang
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
| | - Maofa Ge
- State Key Laboratory for Structural Chemistry of Unstable and Stable Species, Beijing National Laboratory for Molecular Sciences, CAS Research/Education Center for Excellence in Molecular Sciences, Institute of Chemistry, Chinese Academy of Sciences, Beijing 100190, China
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Feng X, Zhao J, Feng Y, Cai J, Yan C, Chen Y. Chemical Characterization, Source, and SOA Production of Intermediate Volatile Organic Compounds during Haze Episodes in North China. Atmosphere 2021; 12:1484. [DOI: 10.3390/atmos12111484] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
The growth of secondary organic aerosols (SOA) is a vital cause of the outbreaks of winter haze in North China. Intermediate volatile organic compounds (IVOCs) are important precursors of SOA. Therefore, the chemical characteristics, source, and SOA production of IVOCs during haze episodes have attracted much attention. Hourly time resolution IVOC samples during two haze episodes collected in Hebei Province in North China were analyzed in this study. Results showed that: (1) the concentration of IVOCs measured was within the range of 11.3~85.1 μg·cm−3 during haze episodes, with normal alkanes (n-alkanes), polycyclic aromatic hydrocarbons (PAHs), branched alkanes (b-alkanes), and the residue unresolved complex mixture (R-UCM) accounting for 8.6 ± 2.3%, 6.8 ± 2.2%, 24.1 ± 3.8%, and 60.5 ± 6.5% of IVOCs, respectively. NC12-nC15 in n-alkanes, naphthalene and its alkyl substitutes in PAHs, b-alkanes in B12–B16 bins, and R-UCM in B12–B16 bins are the main components, accounting for 87.0 ± 0.2%, 87.6 ± 2.9%, 85.9 ± 5.4%, 74.0 ± 8.3%, respectively. (2) Based on the component characteristics of IVOCs and the ratios of n-alkanes/b-alkanes in emission sources and the hourly variation of IVOCs during haze episodes, coal combustion (CC), biomass burning (BB), gasoline vehicles (GV), and diesel vehicles (DV)were identified as important emission sources of IVOCs in Hebei Province. (3) During haze episodes, temporal variation of the estimated SOA production based on different methods (such as IVOCs concentration, OC/ECmin tracer, and the PMF model) were similar; however, the absolute values were different. This difference may be due to the transformation of IVOCs to SOA affected by various factors such as SOA production from different IVOC components, meteorological conditions, atmospheric oxidation, etc.
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Abstract
In recent decades, maritime transport demand has increased along with world population and global trades. This is associated with higher pollution levels, including the emissions of GHG and other polluting gases. Ports are important elements within maritime transport and contribute themselves to pollutant emissions. This paper aims to offer a comprehensive yet technical review of the latest related technologies, explaining and covering aspects that link ports with emissions, i.e., analyzing, monitoring, assessing, and mitigating emissions in ports. This has been achieved through a robust scientific analysis of very recent and significant research studies, to offer an up-to-date and reliable overview. Results show the correlation between emissions and port infrastructures, and demonstrate how proper interventions can help with reducing pollutant emissions and financial costs as well, in ports and for maritime transportation in general. Besides, this review also wishes to propose new ideas for future research: new future experimental studies might spin-off from it, and perhaps port Authorities might be inspired to experiment and implement dedicated technologies to improve their impact on environment and sustainability.
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12
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Qian Z, Chen Y, Liu Z, Han Y, Zhang Y, Feng Y, Shang Y, Guo H, Li Q, Shen G, Chen J, Tao S. Intermediate Volatile Organic Compound Emissions from Residential Solid Fuel Combustion Based on Field Measurements in Rural China. Environ Sci Technol 2021; 55:5689-5700. [PMID: 33797233 DOI: 10.1021/acs.est.0c07908] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Residential solid fuel combustion (RSFC) is a key cause of air pollution in China. In these serial studies, field measurements of RSFC from 166 rural households in eastern China were conducted to update the database of emission factors (EFs) and chemical profiles of gaseous and particulate organic pollutants, and the present study focuses on the intermediate volatile organic compounds (IVOCs), which are precursors of secondary organic aerosol (SOA). The results show that the averaged EFs of IVOCs (EFIVOC) for crop straw, fuelwood, and coal are 550.7 ± 397.9, 416.1 ± 249.5, and 361.9 ± 308.0 mg/kg, respectively, which are among the EFIVOC of gasoline vehicle, diesel vehicle, non-road machinery, and heavy fuel oil vessel, and are significantly affected by fuel, stove, and combustion efficiency. The percentages of normal alkanes (n-alkanes), branched alkanes (b-alkanes), polycyclic aromatic hydrocarbons (PAHs), and unresolved complex mixture from RSFC are 3.5 ± 1.6, 8.0 ± 3.7, 17.6 ± 6.7, and 70.9 ± 8.1%, respectively, and the compositions are featured by lower b-alkanes and higher PAHs than those of vehicle sources. The proportions of some individual n-alkanes and PAHs (such as n-C12-n-C15, naphthalene, and its alkyl substituents) can be used as indicators to differentiate RSFC from vehicle sources, while methoxyphenols can be used to distinguish biomass burning from coal combustion. Based on China's energy statistics, the total IVOC emissions from RSFC in 2014 were 175.9 Gg. These data will help to update the IVOC emission inventory and improve the estimates of SOA production in China.
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Affiliation(s)
- Zhe Qian
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Yingjun Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Zeyu Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Yong Han
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Yishun Zhang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Yanli Feng
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Yu Shang
- Institute of Environmental Pollution and Health, School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Hai Guo
- Air Quality Studies, Department of Civil and Environmental Engineering, The Hong Kong Polytechnic University, Hong Kong 999077, China
| | - Qing Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Guofeng Shen
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200438, China
| | - Shu Tao
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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Wu L, Ling Z, Liu H, Shao M, Lu S, Wu L, Wang X. A gridded emission inventory of semi-volatile and intermediate volatility organic compounds in China. Sci Total Environ 2021; 761:143295. [PMID: 33183811 DOI: 10.1016/j.scitotenv.2020.143295] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2020] [Revised: 09/22/2020] [Accepted: 10/16/2020] [Indexed: 06/11/2023]
Abstract
An emission inventory of precursors is a prerequisite for the simulation of secondary organic aerosol (SOA), which could provide valuable information on the evolution of precursors, formation of SOA, and its influence on fine particle (PM2.5) abundance, oxidative capacity, and climate change. However, an emission inventory of semi-volatile and intermediate volatility organic compounds (S/IVOCs), the key precursor of SOA, particularly the gridded inventory that is appropriate for input into regional air quality models, remains limited in China, leading to an incomplete understanding of S/IVOCs sources and roles in SOA formation and the atmospheric environment. Therefore, a gridded emission inventory of S/IVOCs in China for 2016 was developed based on ample source-specific measured data on emission ratios of S/IVOCs to primary organic aerosols (POA) from literatures. The total emission of S/IVOCs was estimated to be 9.6 Tg, and industry and residential sectors were major sources of S/IVOCs, with contributions of 48.0% and 30.2%, respectively. The spatial variations suggested that S/IVOC emissions were mainly distributed in the highly industrialized and urbanized regions in China, such as Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), the Pearl River Delta (PRD), and the Sichuan-Chongqing (SC) regions, though the contributions and temporal patterns varied between different regions. Furthermore, uncertainty of the emission inventory was estimated to be within the range of -66%-153%, which was mainly attributed to emission ratios of IVOCs/POA for industry, transportation, and power plants. The gridded emission inventory developed in this study can be used to estimate the emissions of S/IVOCs in different regions, and can be applied to different models for a better understanding of the environmental effects of S/IVOCs.
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Affiliation(s)
- Liqing Wu
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Zhenhao Ling
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China.
| | - Huan Liu
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Min Shao
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China
| | - Sihua Lu
- College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Luolin Wu
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Sun Yat-sen University and Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Zhuhai 519082, China
| | - Xuemei Wang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510632, China.
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Wang R, Yuan Z, Zheng J, Li C, Huang Z, Li W, Xie Y, Wang Y, Yu K, Duan L. Characterization of VOC emissions from construction machinery and river ships in the Pearl River Delta of China. J Environ Sci (China) 2020; 96:138-150. [PMID: 32819688 DOI: 10.1016/j.jes.2020.03.013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 03/17/2020] [Accepted: 03/17/2020] [Indexed: 06/11/2023]
Abstract
Speciated characterization of Volatile Organic Compounds (VOCs), including oxygenated VOCs (OVOCs), from construction machinery and river ships in China is currently lacking. In this regard, we conducted field measurement on speciated VOC (including OVOC) emissions from six construction machinery and five river ships in the Pearl River Delta (PRD) region to identify VOC emission characteristics. We noticed that OVOC emissions from construction machinery and ships accounted for more than 50% of the total VOC emissions, followed by alkenes, aromatics and alkanes. Formaldehyde and acetaldehyde were the most emission species, accounting for 61.8%-83.2% of OVOCs. For construction machinery, the fuel-based emission factors of roller, grader and pile driver were 3.12, 3.12 and 7.36 g/kg, respectively. With the rigorous restraint by the national emission standards, VOC emissions of construction machinery had decreased considerably, especially during stage Ⅲ. Ozone formation potential was also significantly reduced due to the significant decrease in emissions of OVOCs and alkenes with higher reactivity. For river ships, the fuel-based emission factors of cargo ships and speedboat were 1.46 and 0.44 g/kg, respectively. VOC emissions from construction machinery and river ships in Guangdong Province in 2017 were 8851.0 and 4361.0 ton, respectively. This study filled the knowledge gaps of reactive gas emissions from different kinds of non-road mobile sources over the PRD, and more importantly, highlighted the necessity in adding OVOC measurement to give a complete and accurate depiction of reactive gas emissions from non-road mobile sources.
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Affiliation(s)
- Richao Wang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Zibing Yuan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China.
| | - Junyu Zheng
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510000, China
| | - Cheng Li
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510000, China
| | - Zhijiong Huang
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510000, China
| | - Wenshi Li
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yan Xie
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Yiran Wang
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
| | - Kaiyang Yu
- Institute for Environmental and Climate Research, Jinan University, Guangzhou 510000, China
| | - Lejun Duan
- School of Environment and Energy, South China University of Technology, Guangzhou 510006, China
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15
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Su P, Hao Y, Qian Z, Zhang W, Chen J, Zhang F, Yin F, Feng D, Chen Y, Li Y. Emissions of intermediate volatility organic compound from waste cooking oil biodiesel and marine gas oil on a ship auxiliary engine. J Environ Sci (China) 2020; 91:262-270. [PMID: 32172975 DOI: 10.1016/j.jes.2020.01.008] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2019] [Revised: 01/02/2020] [Accepted: 01/06/2020] [Indexed: 06/10/2023]
Abstract
Ship auxiliary engines contribute large amounts of air pollutants when at berth. Biodiesel, including that from waste cooking oil (WCO), can favor a reduction in the emission of primary pollutant when used with internal combustion engines. This study investigated the emissions of gaseous intermediate-volatile organic compounds (IVOCs) between WCO biodiesel and marine gas oil (MGO) to further understand the differences in secondary organic aerosol (SOA) production of exhausts. Results revealed that WCO exhaust exhibited similar IVOC composition and volatility distribution to MGO exhaust, despite the differences between fuel contents. While WCO biodiesel could reduce IVOC emissions by 50% as compared to MGO, and thus reduced the SOA production from IVOCs. The compositions and volatility distributions of exhaust IVOCs varied to those of their fuels, implying that fuel-component-based SOA predicting model should be used with more cautions when assessing SOA production of WCO and MGO exhausts. WCO biodiesel is a cleaner fuel comparing to conventional MGO on ship auxiliary engines with regard to the reductions in gaseous IVOC emissions and corresponding SOA productions. Although the tests were conducted on test bench, the results could be considered as representative due to the widely applications of the test engine and MGO fuel on real-world ships.
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Affiliation(s)
- Penghao Su
- Department of Environmental Engineering, Shanghai Maritime University, Shanghai 201306, China; International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), Shanghai Maritime University, Shanghai 200135, China.
| | - Yuejiao Hao
- Department of Environmental Engineering, Shanghai Maritime University, Shanghai 201306, China; International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), Shanghai Maritime University, Shanghai 200135, China
| | - Zhe Qian
- College of Environmental Science and Engineering, Tongji University, Shanghai 200092, China
| | - Weiwei Zhang
- Department of Environmental Engineering, Shanghai Maritime University, Shanghai 201306, China; International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), Shanghai Maritime University, Shanghai 200135, China
| | - Jing Chen
- Department of Environmental Engineering, Shanghai Maritime University, Shanghai 201306, China; International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), Shanghai Maritime University, Shanghai 200135, China
| | - Fan Zhang
- Key Lab of Geographic Information Science of Ministry of Education of China, School of Geographic Sciences, East China Normal University, Shanghai 200142, China
| | - Fang Yin
- Department of Environmental Engineering, Shanghai Maritime University, Shanghai 201306, China; International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), Shanghai Maritime University, Shanghai 200135, China
| | - Daolun Feng
- Department of Environmental Engineering, Shanghai Maritime University, Shanghai 201306, China; International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), Shanghai Maritime University, Shanghai 200135, China.
| | - Yingjun Chen
- School of Environmental Engineering, Fudan University, Shanghai 200433, China
| | - Yifan Li
- International Joint Research Center for Persistent Toxic Substances (IJRC-PTS), State Key Laboratory of Urban Water Resource and Environment, School of Municipal and Environmental Engineering, Harbin Institute of Technology, Harbin 150090, China
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