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54. The Characteristics of Heavy Ozone Pollution Episodes and Identification of the Primary Driving Factors Using a Generalized Additive Model (GAM) in an Industrial Megacity of Northern China

Author

Diao, Liuli, primary, Bi, Xiaohui, additional, Zhang, Wenhui, additional, Liu, Baoshuang, additional, Wang, Xuehan, additional, Li, Linxuan, additional, Dai, Qili, additional, Zhang, Yufen, additional, Wu, Jianhui, additional, and Feng, Yinchang, additional

Published
2021
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63. The underappreciated impact of emission source profiles on the simulation of PM2.5 components: New evidence from sensitivity analysis.

Author

Luo, Zhongwei, Han, Yan, Hua, Kun, Zhang, Yufen, Wu, Jianhui, Bi, Xiaohui, Dai, Qili, Liu, Baoshuang, Chen, Yang, Long, Xin, and Feng, Yinchang

Subjects
AIR quality, AIR pollution, HEALTH risk assessment, COMPUTER simulation, POLLUTANTS
Abstract

The chemical transport model (CTM) is an essential tool for air quality prediction and management, widely used in air pollution control and health risk assessment. However, the current models do not perform very well in simulating PM2.5 components. Studies suggested that the uncertainties of model chemical mechanism, source emission inventory and meteorological field can cause inaccurate simulation results. Still, the emission source profile of PM2.5 has not been fully taken into account in current numerical simulation. This study aims to answer (1) Whether the variation of source profile adopted in chemical transport models (CTMs) has an impact on the simulation of PM2.5 chemical components? (2) How much does it impact? (3) How does the impact work? Based on the characteristics and variation rules of chemical components in typical PM2.5 sources, different simulation scenarios were designed and the sensitivity of components simulation results to PM2.5 sources profile was explored. Our findings showed that the influence of source profile changes on simulated PM2.5 concentration was insignificant, but its impact on PM2.5 components could not be ignored. The variations of simulated components ranged from 8 % to 167 % under selected different source profiles, and simulation results of some components were sensitive to the adopted PM2.5 source profile in CTMs. These influences are connected to the chemical mechanisms of the model since the variation of species allocations in emission sources directly affected the thermodynamic equilibrium system. We also found that the perturbation of the PM2.5 source profile caused the variation of simulated gaseous pollutants, which indirectly indicated that the perturbation of the source profile affected the simulation of secondary PM2.5 components. Given the vital role of air quality simulation in environment management and health risk assessment, the representativeness and timeliness of source profile should be considered. [ABSTRACT FROM AUTHOR]

Published
2022
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66. Global air quality and COVID-19 pandemic

Author

Torkmahalleh, Mehdi Amouei, Akhmetvaliyeva, Zarina, Omran, Ali Darvishi, Omran, Faezeh Darvish, Kazemitabar, Mohadeseh, Naseri, Mahtab, Naseri, Motahareh, Sharifi, Hamed, Malekipirbazari, Milad, Adotey, Enoch Kwasi, Gorjinezhad, Soudabeh, Eghtesadi, Neda, Sabanov, Sergei, Alastuey, Andrés, Andrade, María de Fátima, Buonanno, Giorgio, Carbone, Samara, Cárdenas-Fuentes, Diego Ernesto, Cassee, Flemming R., Dai, Qili, Henríquez, Andrés, Hopke, Philip K., Keronen, Petri, Khwaja, Haider Abbas, Kim, Jong, Kulmala, Markku, Kumar, Prashant, Kushta, Jonilda, Kuula, Joel, Massagué, Jordi, Mitchell, Tamsin, Mooibroek, Dennis, Morawska, Lidia, Niemi, Jarkko V., Ngagine, Soulemane Halif, Norman, Michael, Oyama, Beatríz, Oyola, Pedro, Öztürk, Fatma, Petäjä, Tuukka, Querol, Xavier, Rashidi, Yousef, Reyes, Felipe, Ross-Jones, Matthew, Salthammer, Tunga, Savvides, Chrysanthos, Stabile, Luca, Sjöberg, Karin, Söderlund, Karin, Raman, Ramya Sunder, Timonen, Hilkka, Umezawa, Masakazu, Viana, Mar, Xie, Shanju, and Publica

Subjects
SARS-CoV-2, global air quality, O3, COVID-19 pandemic, PM2.5, NO2
Abstract

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has challenged most countries worldwide. It was quickly recognized that reduced activities (lockdowns) during the Coronavirus Disease of 2019 (COVID-19) pandemic produced major changes in air quality. Our objective was to assess the impacts of COVID-19 lockdowns on ground-level PM2.5, NO2, and O3 concentrations on a global scale. We obtained data from 34 countries, 141 cities, and 458 air monitoring stations on 5 continents (few data from Africa). On a global average basis, a 34.0% reduction in NO2 concentration and a 15.0% reduction in PM2.5 were estimated during the strict lockdown period (until April 30, 2020). Global average O3 concentration increased by 86.0% during this same period. Individual country and continent-wise comparisons have been made between lockdown and business-as-usual periods. Universally, NO2 was the pollutant most affected by the COVID-19 pandemic. These effects were likely because its emissions were from sources that were typically restricted (i.e., surface traffic and non-essential industries) by the lockdowns and its short lifetime in the atmosphere. Our results indicate that lockdown measures and resulting reduced emissions reduced exposure to most harmful pollutants and could provide global-scale health benefits. However, the increased O3 may have substantially reduced those benefits and more detailed health assessments are required to accurately quantify the health gains. At the same, these restrictions were obtained at substantial economic costs and with other health issues (depression, suicide, spousal abuse, drug overdoses, etc.). Thus, any similar reductions in air pollution would need to be obtained without these extensive economic and other consequences produced by the imposed activity reductions.

Published
2021

67. Global Air Quality and COVID-19 Pandemic: Do We Breathe Cleaner Air?

Author

Amouei Torkmahalleh, Mehdi, Akhmetvaliyeva, Zarina, Omran, Ali Darvishi, Faezeh Darvish Omran, Faezeh, Kazemitabar, Mohadeseh, Naseri, Mahtab, Naseri, Motahareh, Sharifi, Hamed, Malekipirbazari, Milad, Kwasi Adotey, Enoch, Gorjinezhad, Soudabeh, Eghtesadi, Neda, Sabanov, Sergei, Alastuey, Andrés, De Fátima Andrade, María, Buonanno, Giorgio, Carbone, Samara, Cárdenas-fuentes, Diego Ernesto, Cassee, Flemming R., Dai, Qili, Henríquez, Andrés, Hopke, Philip K., Keronen, Petri, Khwaja, Haider Abbas, Kim, Jong, Kulmala, Markku, Kumar, Prashant, Kushta, Jonilda, Kuula, Joel, Massagué, Jordi, Mitchell, Tamsin, Mooibroek, Dennis, Morawska, Lidia, Niemi, Jarkko V., Ngagine, Soulemane Halif, Norman, Michael, Oyama, Beatríz, Oyola, Pedro, Öztürk, Fatma, Petäjä, Tuukka, Querol, Xavier, Rashidi, Yousef, Reyes, Felipe, Ross-jones, Matthew, Salthammer, Tunga, Savvides, Chrysanthos, Stabile, Luca, Sjöberg, Karin, Söderlund, Karin, Sunder Raman, Ramya, Timonen, Hilkka, Umezawa, Masakazu, Viana, Mar, Xie, Shanju, Amouei Torkmahalleh, Mehdi, Akhmetvaliyeva, Zarina, Omran, Ali Darvishi, Faezeh Darvish Omran, Faezeh, Kazemitabar, Mohadeseh, Naseri, Mahtab, Naseri, Motahareh, Sharifi, Hamed, Malekipirbazari, Milad, Kwasi Adotey, Enoch, Gorjinezhad, Soudabeh, Eghtesadi, Neda, Sabanov, Sergei, Alastuey, Andrés, De Fátima Andrade, María, Buonanno, Giorgio, Carbone, Samara, Cárdenas-fuentes, Diego Ernesto, Cassee, Flemming R., Dai, Qili, Henríquez, Andrés, Hopke, Philip K., Keronen, Petri, Khwaja, Haider Abbas, Kim, Jong, Kulmala, Markku, Kumar, Prashant, Kushta, Jonilda, Kuula, Joel, Massagué, Jordi, Mitchell, Tamsin, Mooibroek, Dennis, Morawska, Lidia, Niemi, Jarkko V., Ngagine, Soulemane Halif, Norman, Michael, Oyama, Beatríz, Oyola, Pedro, Öztürk, Fatma, Petäjä, Tuukka, Querol, Xavier, Rashidi, Yousef, Reyes, Felipe, Ross-jones, Matthew, Salthammer, Tunga, Savvides, Chrysanthos, Stabile, Luca, Sjöberg, Karin, Söderlund, Karin, Sunder Raman, Ramya, Timonen, Hilkka, Umezawa, Masakazu, Viana, Mar, and Xie, Shanju

Abstract

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has challenged most countries worldwide. It was quickly recognized that reduced activities (lockdowns) during the Coronavirus Disease of 2019 (COVID-19) pandemic produced major changes in air quality. Our objective was to assess the impacts of COVID-19 lockdowns on ground-level PM2.5, NO2, and O3 concentrations on a global scale. We obtained data from 34 countries, 141 cities, and 458 air monitoring stations on 5 continents (few data from Africa). On a global average basis, a 34.0% reduction in NO2 concentration and a 15.0% reduction in PM2.5 were estimated during the strict lockdown period (until April 30, 2020). Global average O3 concentration increased by 86.0% during this same period. Individual country and continent-wise comparisons have been made between lockdown and business-as-usual periods. Universally, NO2 was the pollutant most affected by the COVID-19 pandemic. These effects were likely because its emissions were from sources that were typically restricted (i.e., surface traffic and non-essential industries) by the lockdowns and its short lifetime in the atmosphere. Our results indicate that lockdown measures and resulting reduced emissions reduced exposure to most harmful pollutants and could provide global-scale health benefits. However, the increased O3 may have substantially reduced those benefits and more detailed health assessments are required to accurately quantify the health gains. At the same, these restrictions were obtained at substantial economic costs and with other health issues (depression, suicide, spousal abuse, drug overdoses, etc.). Thus, any similar reductions in air pollution would need to be obtained without these extensive economic and other consequences produced by the imposed activity reductions.

Published
2021

68. Global Air Quality and COVID-19 Pandemic: Do We Breathe Cleaner Air?

Author

Alastuey, Andrés [0000-0002-5453-5495], Querol, Xavier [0000-0002-6549-9899], Viana, Mar [0000-0002-4073-3802], Torkmahalleh, Mehdi Amouei, Akhmetvaliyeva, Zarina, Darvishi Omran, Ali, Darvish Omran, Faezeh, Kazemitabar, Mohadeseh, Naseri, Mahtab, Naseri, Motahareh, Sharifi, Hamed, Malekipirbazari, Milad, Kwasi Adotey, Enoch, Gorjinezhad, Soudabeh, Eghtesadi, Neda, Sabanov, Sergei, Alastuey, Andrés, Andrade, María de Fátima, Buonanno, Giorgio, Carbone, Samara, Cárdenas-Fuentes, Diego Ernesto, Cassee, Flemming R., Dai, Qili, Henríquez, Andrés, Hopke, Philip K., Keronen, Petri, Khwaja, Haider Abbas, Kim, Jong, Kulmala, Markku, Kumar, Prashant, Kushta, Jonilda, Kuula, Joel, Massagué, Jordi, Mitchell, Tamsin, Mooibroek, Dennis, Morawska, Lidia, Niemi, Jarkko V., Ngagine, Soulemane Halif, Norman, Michael, Oyama, Beatriz, Oyola, Pedro, Öztürk, Fatma, Petäjä, Tuukka, Querol, Xavier, Rashidi, Yousef, Reyes, Felipe, Ross-Jones, Matthew, Salthammer, Tunga, Savvides, Chrysanthos, Stabile, Luca, Sjöberg, Karin, Söderlund, Karin, Sunder Raman, Ramya, Timonen, Hilkka, Umezawa, Masakazu, Viana, Mar, Xie, Shanju, Alastuey, Andrés [0000-0002-5453-5495], Querol, Xavier [0000-0002-6549-9899], Viana, Mar [0000-0002-4073-3802], Torkmahalleh, Mehdi Amouei, Akhmetvaliyeva, Zarina, Darvishi Omran, Ali, Darvish Omran, Faezeh, Kazemitabar, Mohadeseh, Naseri, Mahtab, Naseri, Motahareh, Sharifi, Hamed, Malekipirbazari, Milad, Kwasi Adotey, Enoch, Gorjinezhad, Soudabeh, Eghtesadi, Neda, Sabanov, Sergei, Alastuey, Andrés, Andrade, María de Fátima, Buonanno, Giorgio, Carbone, Samara, Cárdenas-Fuentes, Diego Ernesto, Cassee, Flemming R., Dai, Qili, Henríquez, Andrés, Hopke, Philip K., Keronen, Petri, Khwaja, Haider Abbas, Kim, Jong, Kulmala, Markku, Kumar, Prashant, Kushta, Jonilda, Kuula, Joel, Massagué, Jordi, Mitchell, Tamsin, Mooibroek, Dennis, Morawska, Lidia, Niemi, Jarkko V., Ngagine, Soulemane Halif, Norman, Michael, Oyama, Beatriz, Oyola, Pedro, Öztürk, Fatma, Petäjä, Tuukka, Querol, Xavier, Rashidi, Yousef, Reyes, Felipe, Ross-Jones, Matthew, Salthammer, Tunga, Savvides, Chrysanthos, Stabile, Luca, Sjöberg, Karin, Söderlund, Karin, Sunder Raman, Ramya, Timonen, Hilkka, Umezawa, Masakazu, Viana, Mar, and Xie, Shanju

Abstract

The global spread of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has challenged most countries worldwide. It was quickly recognized that reduced activities (lockdowns) during the Coronavirus Disease of 2019 (COVID-19) pandemic produced major changes in air quality. Our objective was to assess the impacts of COVID-19 lockdowns on ground-level PM2.5, NO2, and O3 concentrations on a global scale. We obtained data from 34 countries, 141 cities, and 458 air monitoring stations on 5 continents (few data from Africa). On a global average basis, a 34.0% reduction in NO2 concentration and a 15.0% reduction in PM2.5 were estimated during the strict lockdown period (until April 30, 2020). Global average O3 concentration increased by 86.0% during this same period. Individual country and continent-wise comparisons have been made between lockdown and business-as-usual periods. Universally, NO2 was the pollutant most affected by the COVID-19 pandemic. These effects were likely because its emissions were from sources that were typically restricted (i.e., surface traffic and non-essential industries) by the lockdowns and its short lifetime in the atmosphere. Our results indicate that lockdown measures and resulting reduced emissions reduced exposure to most harmful pollutants and could provide global-scale health benefits. However, the increased O3 may have substantially reduced those benefits and more detailed health assessments are required to accurately quantify the health gains. At the same, these restrictions were obtained at substantial economic costs and with other health issues (depression, suicide, spousal abuse, drug overdoses, etc.). Thus, any similar reductions in air pollution would need to be obtained without these extensive economic and other consequences produced by the imposed activity reductions.

Published
2021

69. Co‐Occurrence of Surface O3, PM2.5 Pollution, and Tropical Cyclones in China.

Author

Shao, Min, Yang, Jianbo, Wang, Jinmei, Chen, Pulong, Liu, Baoshuang, and Dai, Qili

Subjects
TROPICAL cyclones, AIR pollutants, POLLUTION, AIR pollution, TROPICAL storms, EXTREME weather, PARTICULATE matter
Abstract

Extreme weather events are on the rise against the backdrop of climate change. Impact of tropical cyclone (TC) system, one of the extreme weather events, on air pollution remain poorly understood. A total of 103 recorded TCs (tropical storms and stronger) together with the surface air quality data collected from over 2000 observational sites in mainland China in 2014–2020 were utilized to examine the co‐occurrence of TC with continental ozone (O3) and fine particulate matters (PM2.5) pollution. TCs exhibit cleaning effects on PM2.5 within its coverage (typically ∼650 km), but enhance the co‐occurrence of O3 and PM2.5 in an extended region. The co‐occurrence frequencies are greater than 30% for any two co‐occurring events, and ∼8% for TC + PM2.5 + O3. We observed superregional trans‐boundary transportation of air pollutants driven by TC, led to ubiquitous spatial offsets and temporal lags of O3, PM2.5 pollution and TC, which are often inconsistent with traditional mechanisms such as accelerated chemical reactions for O3 formation. O3 pollution tends to occur 1∼2 days after PM2.5 pollution moved west. In contrast, PM2.5 pollution usually occur 4–12 hr following O3 pollution within a day over most regions except the southeast of China. Such spatial and temporal offsets vary with the paths of TCs. Composite analysis shows that temperature, wind field and large pressure systems are the key factors for air pollution formation and transportation over TC periphery. Our results have implications for understanding the interactions between TCs and air pollution, particularly for coastal areas where there are recurring TCs. Key Points: Tropical cyclones driving superregional trans‐boundary transportation of air pollutantsTropical cyclone (e.g., super typhoon In‐Fa) structure could induce unique distribution of O3 in both horizontal and vertical directionsComposite analysis shows that tropical cyclone associated temperature, wind field and large pressure systems are the key factors forming air pollution [ABSTRACT FROM AUTHOR]

Published
2022
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74. Global Air Quality and COVID-19 Pandemic: Do We Breathe Cleaner Air?

Author

Amouei Torkmahalleh, Mehdi, primary, Akhmetvaliyeva, Zarina, additional, Omran, Ali Darvishi, additional, Faezeh Darvish Omran, Faezeh, additional, Kazemitabar, Mohadeseh, additional, Naseri, Mahtab, additional, Naseri, Motahareh, additional, Sharifi, Hamed, additional, Malekipirbazari, Milad, additional, Kwasi Adotey, Enoch, additional, Gorjinezhad, Soudabeh, additional, Eghtesadi, Neda, additional, Sabanov, Sergei, additional, Alastuey, Andrés, additional, de Fátima Andrade, María, additional, Buonanno, Giorgio, additional, Carbone, Samara, additional, Cárdenas-Fuentes, Diego Ernesto, additional, Cassee, Flemming R., additional, Dai, Qili, additional, Henríquez, Andrés, additional, Hopke, Philip K., additional, Keronen, Petri, additional, Khwaja, Haider Abbas, additional, Kim, Jong, additional, Kulmala, Markku, additional, Kumar, Prashant, additional, Kushta, Jonilda, additional, Kuula, Joel, additional, Massagué, Jordi, additional, Mitchell, Tamsin, additional, Mooibroek, Dennis, additional, Morawska, Lidia, additional, Niemi, Jarkko V., additional, Ngagine, Soulemane Halif, additional, Norman, Michael, additional, Oyama, Beatríz, additional, Oyola, Pedro, additional, Öztürk, Fatma, additional, Petäjä, Tuukka, additional, Querol, Xavier, additional, Rashidi, Yousef, additional, Reyes, Felipe, additional, Ross-Jones, Matthew, additional, Salthammer, Tunga, additional, Savvides, Chrysanthos, additional, Stabile, Luca, additional, Sjöberg, Karin, additional, Söderlund, Karin, additional, Sunder Raman, Ramya, additional, Timonen, Hilkka, additional, Umezawa, Masakazu, additional, Viana, Mar, additional, and Xie, Shanju, additional

Published
2021
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78. Chemical characteristics and source apportionment of PM2.5 using PMF modelling coupled with 1-hr resolution online air pollutant dataset for Linfen, China

Author

Li, Yafei, primary, Liu, Baoshuang, additional, Xue, Zhigang, additional, Zhang, Yufen, additional, Sun, Xiaoyun, additional, Song, Congbo, additional, Dai, Qili, additional, Fu, Ruichen, additional, Tai, Yonggang, additional, Gao, Jinyu, additional, Zheng, Yajun, additional, and Feng, Yinchang, additional

Published
2020
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85. Supplementary material to "Seasonal differences in formation processes of oxidized organic aerosol near Houston, TX"

Author

Dai, Qili, primary, Schulze, Benjamin C., additional, Bi, Xiaohui, additional, Bui, Alexander A. T., additional, Guo, Fangzhou, additional, Wallance, Henry W., additional, Sanchez, Nancy P., additional, Flynn, James H., additional, Lefer, Barry L., additional, Feng, Yinchang, additional, and Griffin, Robert J., additional

Published
2018
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91. Chemical nature of PM2.5 and PM10 in Xi'an, China: Insights into primary emissions and secondary particle formation

Author

Dai, Qili, primary, Bi, Xiaohui, additional, Liu, Baoshuang, additional, Li, Liwei, additional, Ding, Jing, additional, Song, Wenbin, additional, Bi, Shiyang, additional, Schulze, Benjamin C., additional, Song, Congbo, additional, Wu, Jianhui, additional, Zhang, Yufen, additional, Feng, Yinchang, additional, and Hopke, Philip K., additional

Published
2018
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92. Supplementary material to "The impacts of regional shipping emissions on the chemical characteristics of coastal submicron aerosols near Houston, TX"

Author

Schulze, Benjamin C., primary, Wallace, Henry W., additional, Bui, Alexander T., additional, Flynn, James H., additional, Erickson, Matt H., additional, Alvarez, Sergio, additional, Dai, Qili, additional, Usenko, Sascha, additional, Sheesley, Rebecca J., additional, and Griffin, Robert J., additional

Published
2018
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93. Vehicular volatile organic compounds (VOCs)-NOx-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment

Author

Song, Congbo, primary, Liu, Yan, additional, Sun, Shida, additional, Sun, Luna, additional, Zhang, Yanjie, additional, Ma, Chao, additional, Peng, Jianfei, additional, Li, Qian, additional, Zhang, Jinsheng, additional, Dai, Qili, additional, Liu, Baoshuang, additional, Wang, Peng, additional, Zhang, Yi, additional, Wang, Ting, additional, Wu, Lin, additional, Hu, Min, additional, and Mao, Hongjun, additional

Published
2018
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94. Supplementary material to "Vehicular volatile organic compounds (VOCs)-NO<sub><i>x</i></sub>-CO emissions in a tunnel study in northern China: emission factors, profiles, and source apportionment"

Author

Song, Congbo, primary, Liu, Yan, additional, Sun, Shida, additional, Sun, Luna, additional, Zhang, Yanjie, additional, Ma, Chao, additional, Peng, Jianfei, additional, Li, Qian, additional, Zhang, Jinsheng, additional, Dai, Qili, additional, Liu, Baoshuang, additional, Wang, Peng, additional, Zhang, Yi, additional, Wang, Ting, additional, Wu, Lin, additional, Hu, Min, additional, and Mao, Hongjun, additional

Published
2018
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95. Effectiveness evaluation of temporary emission control action in 2016 in winter in Shijiazhuang, China

Author

Liu, Baoshuang, primary, Cheng, Yuan, additional, Zhou, Ming, additional, Liang, Danni, additional, Dai, Qili, additional, Wang, Lu, additional, Jin, Wei, additional, Zhang, Lingzhi, additional, Ren, Yibin, additional, Zhou, Jingbo, additional, Dai, Chunling, additional, Xu, Jiao, additional, Wang, Jiao, additional, Feng, Yinchang, additional, and Zhang, Yufen, additional

Published
2018
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96. Effectiveness evaluation of temporary emission control action in 2016 winter in Shijiazhuang, China

Author

Liu, Baoshuang, primary, Cheng, Yuan, additional, Zhou, Ming, additional, Liang, Danni, additional, Dai, Qili, additional, Wang, Lu, additional, Jin, Wei, additional, Zhang, Lingzhi, additional, Ren, Yibin, additional, Zhou, Jingbo, additional, Dai, Chunling, additional, Xu, Jiao, additional, Wang, Jiao, additional, Feng, Yinchang, additional, and Zhang, Yufen, additional

Published
2017
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97. Supplementary material to "Effectiveness evaluation of temporary emission control action in 2016 winter in Shijiazhuang, China"

Author

Liu, Baoshuang, primary, Cheng, Yuan, additional, Zhou, Ming, additional, Liang, Danni, additional, Dai, Qili, additional, Wang, Lu, additional, Jin, Wei, additional, Zhang, Lingzhi, additional, Ren, Yibin, additional, Zhou, Jingbo, additional, Dai, Chunling, additional, Xu, Jiao, additional, Wang, Jiao, additional, Feng, Yinchang, additional, and Zhang, Yufen, additional

Published
2017
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98. Air pollution in China: Status and spatiotemporal variations

Author

Song, Congbo, primary, Wu, Lin, additional, Xie, Yaochen, additional, He, Jianjun, additional, Chen, Xi, additional, Wang, Ting, additional, Lin, Yingchao, additional, Jin, Taosheng, additional, Wang, Anxu, additional, Liu, Yan, additional, Dai, Qili, additional, Liu, Baoshuang, additional, Wang, Ya-nan, additional, and Mao, Hongjun, additional

Published
2017
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