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Wu L, Shen Y, Che F, Zhang Y, Gao J, Wang C. Evaluating the performance and influencing factors of three portable black carbon monitors for field measurement. J Environ Sci (China) 2024; 139:320-333. [PMID: 38105058 DOI: 10.1016/j.jes.2023.05.044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 05/26/2023] [Accepted: 05/30/2023] [Indexed: 12/19/2023]
Abstract
Black carbon (BC) is associated with adverse human health and climate change. Mapping BC spatial distribution imperatively requires low-cost and portable devices. Several portable BC monitors are commercially available, but their accuracy and reliability are not always satisfactory during continuous field observation. This study evaluated three models of portable black carbon monitors, C12, MA350 and DST, and investigates the factors that affect their performance. The monitors were tested in urban Beijing, where portable devices running for one month alongside a regular-size reference aethalometer AE33. The study considers several factors that could influence the monitors' performance, including ambient weather, aerosol composition, loading artifacts, and built-in algorithms. The results show that MA350 and DST present considerable discrepancies to the reference instrument, mainly occurring at lower concentrations (0-500 ng/m3) and higher concentrations (2500-8000 ng/m3), respectively. These discrepancies were likely caused by the anomalous noise of MA350 and the loading artifacts of DST. The study also suggests that the ambient environment has limited influence on the monitors' performance, but loading artifacts and accompanying compensation algorithms can result in unrealistic data. Based on the evaluation, the study suggests that C12 is the best choice for unsupervised field measurement, DST should be used in scenarios where frequent maintenance is available, and MA350 is suitable for research purposes with post-processing applicable. The study highlights the importance of assigning portable BC monitors to appropriate applications and the need for optimized real-time compensation algorithms.
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Affiliation(s)
- Liqing Wu
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yicheng Shen
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Fei Che
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Yuzhe Zhang
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
| | - Jian Gao
- State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
| | - Chong Wang
- Jinan Ecological Environmental Protection Grid-Based Supervision Center, Jinan 250013, China
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Cao N, Chen L, Liu Y, Wang J, Yang S, Su D, Mi K, Gao S, Zhang H. Spatiotemporal distribution, light absorption characteristics, and source apportionments of black and brown carbon in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 919:170796. [PMID: 38336053 DOI: 10.1016/j.scitotenv.2024.170796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/20/2023] [Revised: 01/30/2024] [Accepted: 02/06/2024] [Indexed: 02/12/2024]
Abstract
Black carbon (BC) and brown carbon (BrC) are aerosols that absorb light and thereby contribute to climate change. In this study, the light absorption properties and spatiotemporal distributions of equivalent BC (eBC) and BrC aerosols were determined based on continuous measurements of aerosol light absorption from January to August 2017, using a seven-channel aethalometer at 49 sampling sites in China. The source apportionments of BC and BrC were identified using the BC/PM2.5, absorption Ångström exponent, the concentration-weighted trajectory method, and the random forest model. Based on the results, BC was the dominant light absorber, whereas BrC was responsible for a higher proportion of the light absorption in northern compared to southern China. The light absorption of BrC was highest in winter (34.3 Mm-1), followed by spring (19.0 Mm-1) and summer (3.6 Mm-1). The combustion of liquid fuels accounted for over 50 % of the light absorption coefficient of BC in most cities and the importance of carbon monoxide (CO) and nitrogen dioxide (NO2) was over 10 % for BC emitted by liquid fuel combustion, based on the random forest model. The contribution of solid fuel combustion to BC in the north was larger than that in the southern regions as coal combustion and crop residue burning are important emission sources of BC in most northern cities. The contribution of primary BrC to light absorption was high in some northern cities, whereas that of secondary BrC was prevalent in some southern cities. The diurnal variations in secondary BrC were affected by changes in odd oxygen and relative humidity, which promoted the photobleaching of the chromophores and aqueous-phase reactions of secondary BrC.
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Affiliation(s)
- Nan Cao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Li Chen
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China.
| | - Yusi Liu
- State Key Laboratory of Severe Weather, Key Laboratory for Atmospheric Chemistry of China Meteorology Administration, Chinese Academy of Meteorological Sciences, Beijing 100081, China.
| | - Jing Wang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Shuangqin Yang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Die Su
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Ke Mi
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Shuang Gao
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
| | - Hu Zhang
- School of Geographic and Environmental Sciences, Tianjin Normal University, Tianjin 300387, China
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Liao K, Wang Q, Wang S, Yu JZ. Bayesian Inference Approach to Quantify Primary and Secondary Organic Carbon in Fine Particulate Matter Using Major Species Measurements. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2023; 57:5169-5179. [PMID: 36940370 DOI: 10.1021/acs.est.2c09412] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The determination of primary organic carbon (POC) and secondary organic carbon (SOC) in fine particulate matter using ambient measurements is essential in atmospheric chemistry. A novel Bayesian inference (BI) approach is proposed to achieve such quantification using only major component measurement data and tested in two case studies. One case study composes of filter-based daily compositional data made in the Pearl River Delta region, China, during 2012, while the other uses online measurement data recorded at the Dianshan Lake monitoring site in Shanghai in wintertime 2019. Source-specific organic trace measurement data are available in both the cases so that positive matrix factorization (PMF) analysis is performed, where PMF-resolved POC and SOC are used as the best available reference values for model evaluation. Meanwhile, traditional techniques, i.e., minimum ratio value, minimum R squared, and multiple linear regression, are also employed and evaluated. For both the cases, the BI models have shown significant advantages in accurately estimating POC and SOC amounts over conventional methods. Further analysis suggests that using sulfate as the SOC tracer in BI model gives the best model performance. This methodological advance provides an improved and practical tool to derive POC and SOC levels for addressing PM-related environmental impacts.
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Affiliation(s)
- Kezheng Liao
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
| | - Qiongqiong Wang
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
| | - Shan Wang
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
| | - Jian Zhen Yu
- Department of Chemistry, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
- Division of Environment and Sustainability, The Hong Kong University of Science and Technology, Kowloon 999077, Hong Kong, China
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Shang Y, Xue W, Kong J, Chen Y, Qiu X, An X, Li Y, Wang H, An J. Ultrafine black carbon caused mitochondrial oxidative stress, mitochondrial dysfunction and mitophagy in SH-SY5Y cells. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 813:151899. [PMID: 34838543 DOI: 10.1016/j.scitotenv.2021.151899] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2021] [Revised: 09/02/2021] [Accepted: 11/19/2021] [Indexed: 06/13/2023]
Abstract
Exposure to ambient ultrafine black carbon (uBC, with aerodynamic diameter less than 100 nm) is associated with many neurodegenerative diseases. Oxidative stress is the predominantly reported neurotoxic effects caused by uBC exposure. Mitochondrion is responsible for production of majority of ROS in cells and mitochondrial dysfunction is closely related to adverse nervous outcomes. Mitophagy is an important cellular process to eliminate dysfunctional or damaged mitochondria. However, the mechanisms that modulate mitophagy and mitochondrial dysfunction initiated by uBC remain to be elucidated. The purpose of this study was to investigate how mitochondrial oxidative stress regulated mitochondrial dysfunction and mitophagy in human neuroblastoma cell line (SH-SY5Y) after uBC treatment. RNA interference was further applied to explore the roles of mitophagy in mitochondrial dysfunction. We found uBC triggered cell apoptosis via ROS-mitochondrial apoptotic pathway. The uBC also caused serious mitochondrial damage and respiratory dysfunction, indicated by the abnormalities in mitochondrial division and fusion related proteins, decreased mitochondria number and ATP level. Increased PTEN induced putative kinase 1 (PINK1) and Parkin protein levels and the autolysosome numbers suggested uBC could promote Pink1/Parkin-dependent mitophagy process in SH-SY5Y cells. Mitophagy inhibition could reserve mitochondria number and ATP activity, but not fusion and division related protein levels in SH-SY5Y cells exposed to uBC. Administration of a mitochondria-targeted antioxidant (mitoquinone) significantly eliminated uBC caused apoptosis, mitochondrial dysfunction and mitophagy. Our data suggested mitochondrial oxidative stress regulated uBC induced mitochondrial dysfunction and PINK1/Parkin-dependent mitophagy. PINK1/Parkin-dependent mitophagy probably participated in regulating uBC caused mitochondrial dysfunction but not by controlling mitochondrial fusion and division related proteins. Our results may provide some new insights and evidences to understand the mechanisms of neurotoxicity induced by uBC.
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Affiliation(s)
- Yu Shang
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China; State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Wanlei Xue
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Jiexing Kong
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China
| | - Yingjun Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai 200433, China
| | - Xinghua Qiu
- BIC-ESAT and SKL-ESPC, College of Environmental Sciences and Engineering, Peking University, Beijing 100871, China
| | - Xingqin An
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Yi Li
- State Key Laboratory of Severe Weather & Key Laboratory of Atmospheric Chemistry of CMA, Chinese Academy of Meteorological Sciences, Beijing 100081, China
| | - Hongli Wang
- State Environmental Protection Key Laboratory of Formation and Prevention of Urban Air Pollution Complex, Shanghai Academy of Environment Sciences, Shanghai 200233, China
| | - Jing An
- School of Environmental and Chemical Engineering, Shanghai University, Shanghai 200444, China.
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