Update: 2023/02/08 Full list see Google Scholar.
Working papers (# co-first author, * corresponding author)
Song, C.*, Zhang, J., Tong, H., Xu, J., Shi, Z., Coe, H., and Mao, H.* (2022). Two-step Machine Learning Reveals Near-road Polycyclic Aromatic Hydrocarbons (PAHs) in Individual Particles from Biomass Burning, Coal Combustion and Vehicle Emissions. (In preparation)
Published papers (# co-first author, * corresponding author)
| 2017 | 2018 | 2019 | 2020 | 2021 | 2022 | 2023 |
2023
Song, C., Liu, B., Cheng K., Cole, M., Dai, Q.*, Elliott, R., Shi, Z.*. (2023). Attribution of Air Quality Benefits to Clean Winter Heating Polices in China: Combining Machine Learning with Causal Inference. Environmental Science & Technology. ASAP. https://doi.org/10.1021/acs.est.2c06800 [pdf]
Brean, J.*, Beddows, D. C. S., Harrison, R. M., Song, C., Tunved, P., Ström, J., Krejci, R., Freud, E., Massling, A., Skov, H., Asmi, E., Lupi, A., and Dall’Osto, M.*. (2023). Collective geographical ecoregions and precursor sources driving Arctic new particle formation, Atmos. Chem. Phys., 23, 2183–2198, https://doi.org/10.5194/acp-23-2183-2023
Zhang, Q., Liu, J., Wei, N., Song, C., Peng, J., Wu, L., Mao, H. (2023). Identify the contribution of vehicle non-exhaust emissions: a single particle aerosol mass spectrometer test case at typical road environment. Front. Environ. Sci. Eng. 17(5): 62. https://doi.org/10.1007/s11783-023-1662-8 [pdf]
2022
Song, C.*, Becagli, S., Beddows, D., Brean, j., Browse, J., Dai, Q., Dall’Osto, M., Ferracci, V., Harrison, R., Harris, N., Li, W., Jones, A., Kirchgäßner, A., Kramawijaya, A., Kurganskiy, A., Lupi, A., Mazzola M., Severi, M., Traversi, R., and Shi, S.*. (2022). Understanding Sources and Drivers of Size-Resolved Aerosol in the High Arctic Islands of Svalbard Using a Receptor Model Coupled with Machine Learning. Environmental Science & Technology, 56 (16), 11189-11198. https://doi.org/10.1021/acs.est.1c07796[pdf]
Hou, L., Dai, Q.*, Song, C., Liu, B., Guo, F., Dai, T., Li, L., Liu, B., Bi, X., Zhang, Y. and Feng, Y. (2022). Revealing Drivers of Haze Pollution by Explainable Machine Learning. Environmental Science & Technology Letters, 9 (2), 112-119. https://doi.org/10.1021/acs.estlett.1c00865 [pdf]
Xu, J.*, Harrison, R.M., Song, C., Hou, S., Wei, L., Fu, P., Li, H., Li, W. and Shi, Z.* (2022). PM2.5-bound silicon-containing secondary organic aerosols (Si-SOA) in Beijing ambient air. Chemosphere, 288, p.132377. https://doi.org/10.1016/j.chemosphere.2021.132377 [pdf]
Singh, A.*, Bartington, S.E., Song, C., Ghaffarpasand, O., Kraftl, M., Shi, Z., Pope, F.D., Stacey, B., Hall, J., Thomas, G.N. and Bloss, W.J. (2022). Impacts of emergency health protection measures upon air quality, traffic and public health: evidence from Oxford, UK. Environmental Pollution, 293, p.118584. https://doi.org/10.1016/j.envpol.2021.118584 [pdf]
2021
Shi, Z.#1,*, Song, C.#1,*, Liu, B., Lu, G., Xu, J., Van Vu, T., Elliott, R., Li, W., Bloss, W., & Harrison, R. (2021). Abrupt but smaller than expected changes in surface air quality attributable to COVID-19 lockdowns [ESI Highly Cited Paper]. Science Advances, 7(3). https://doi.org/10.1126/sciadv.abd6696 [pdf]
Song, C., Dallosto, M.*, Lupi, A., Mazzola, M., Traversi, R., Becagli, S., Gilardoni, S., Vratolis, S., Yttri, K., Beddows, D., Schmale, J., Brean, J., Kramawijaya, A., Harrison, R., & Shi, Z.* (2021). Differentiation of coarse-mode anthropogenic, marine and dust particles in the high arctic islands of svalbard. Atmospheric Chemistry and Physics, 21(14), 11317–11335. https://doi.org/10.5194/acp-21-11317-2021 [pdf]
Dai, Q., Ding, J., Hou, L., Li, L., Cai, Z., Liu, B., Song, C., Bi, X., Wu, J., Zhang, Y.* and Feng, Y. (2021). Haze episodes before and during the COVID-19 shutdown in Tianjin, China: Contribution of fireworks and residential burning. Environmental Pollution, 286, p.117252. https://doi.org/10.1016/j.envpol.2021.117252
Diao, L., Zhang, H., Liu, B.*, Dai, C., Zhang, Y., Dai, Q., Bi, X., Zhang, L., Song, C., & Feng, Y. (2021). Health risks of inhaled selected toxic elements during the haze episodes in shijiazhuang, China: Insight into critical risk sources. Environmental Pollution, 276. https://doi.org/10.1016/j.envpol.2021.116664
Liu, L., Zhang, J., Du, R., Teng, X., Hu, R., Yuan, Q., Tang, S., Ren, C., Huang, X., Xu, L., Zhang, Y., Zhang, X., Song, C., Liu, B., Lu, G., Shi, Z., & Li, W.* (2021). Chemistry of atmospheric fine particles during the COVID-19 pandemic in a megacity of eastern China [ESI Highly Cited Paper]. Geophysical Research Letters, 48(2). https://doi.org/10.1029/2020GL091611
Luo, L., Zhu, R.-G., Song, C., Peng, J.-F., Guo, W., Liu, Y., Zheng, N., Xiao, H.*, & Xiao, H.-Y.* (2021). Changes in nitrate accumulation mechanisms as PM2.5 levels increase on the north China plain: A perspective from the dual isotopic compositions of nitrate. Chemosphere, 263. https://doi.org/10.1016/j.chemosphere.2020.127915
Wang, Y., Liu, B.*, Zhang, Y., Dai, Q., Song, C., Duan, L., Guo, L., Zhao, J., Xue, Z., Bi, X., & Feng, Y. (2021). Potential health risks of inhaled toxic elements and risk sources during different covid-19 lockdown stages in linfen, China. Environmental Pollution, 284. https://doi.org/10.1016/j.envpol.2021.117454
2020
Song, C., Liu, Y., Sun, L., Zhang, Q., & Mao, H.* (2020). Emissions of volatile organic compounds (VOCs) from gasoline- and liquified natural gas (LNG)-fueled vehicles in tunnel studies. Atmospheric Environment, 234. https://doi.org/10.1016/j.atmosenv.2020.117626 [pdf]
Gu, Y., Liu, B.*, Li, Y., Zhang, Y., Bi, X., Wu, J., Song, C., Dai, Q., Han, Y., Ren, G., & Feng, Y. (2020). Multi-scale volatile organic compound (VOC) source apportionment in tianjin, China, using a receptor model coupled with 1-hr resolution data. Environmental Pollution, 265. https://doi.org/10.1016/j.envpol.2020.115023
Li, Y., Liu, B.*, Xue, Z., Zhang, Y., Sun, X., Song, C., Dai, Q., Fu, R., Tai, Y., Gao, J., Zheng, Y., & Feng, Y. (2020). Chemical characteristics and source apportionment of PM2.5 using pmf modelling coupled with 1-hr resolution online air pollutant dataset for linfen, China. Environmental Pollution, 263. https://doi.org/10.1016/j.envpol.2020.114532
Wang, L., Guo, P., Tong, H., Wang, A., Chang, Y., Guo, X., Gong, J., Song, C., Wu, L., Wang, T., Hopke, P., Chen, X.*, Tang, N.-J.*, & Mao, H.* (2020). Traffic-related metrics and adverse birth outcomes: A systematic review and meta-analysis. Environmental Research, 188. https://doi.org/10.1016/j.envres.2020.109752
Xu, J., Song, S., Harrison, R., Song, C., Wei, L., Zhang, Q., Sun, Y., Lei, L., Zhang, C., Yao, X., Chen, D., Li, W., Wu, M., Tian, H., Luo, L., Tong, S., Li, W., Wang, J., Shi, G., . . . Shi, Z.* (2020). An interlaboratory comparison of aerosol inorganic ion measurements by ion chromatography: Implications for aerosol pH estimate. Atmospheric Measurement Techniques, 13(11), 6325–6341. https://doi.org/10.5194/amt-13-6325-2020
Xu, L., Zhang, J., Sun, X., Xu, S., Shan, M., Yuan, Q., Liu, L., Du, Z., Liu, D., Xu, D., Song, C., Liu, B., Lu, G., Shi, Z., & Li, W.* (2020). Variation in concentration and sources of black carbon in a megacity of China during the COVID-19 pandemic. Geophysical Research Letters, 47(23). https://doi.org/10.1029/2020GL090444
Zhang, J., Peng, J., Song, C., Ma, C., Men, Z., Wu, J., Wu, L., Wang, T., Zhang, X., Tao, S., Gao, S., Hopke, P., & Mao, H.* (2020). Vehicular non-exhaust particulate emissions in chinese megacities: Source profiles, real-world emission factors, and inventories. Environmental Pollution, 266. https://doi.org/10.1016/j.envpol.2020.115268
2019
Song, C., Liu, B., Dai, Q., Li, H., & Mao, H.* (2019). Temperature dependence and source apportionment of volatile organic compounds (VOCs) at an urban site on the north China plain. Atmospheric Environment, 207, 167–181. https://doi.org/10.1016/j.atmosenv.2019.03.030 [pdf][One of the most cited articles from Atmospheric Environment published since 2020]
Dai, Q., Bi, X.*, Huangfu, Y., Yang, J., Li, T., Khan, J., Song, C., Xu, J., Wu, J., Zhang, Y., & Feng, Y. (2019). A size-resolved chemical mass balance (sr-cmb) approach for source apportionment of ambient particulate matter by single element analysis. Atmospheric Environment, 197, 45–52. https://doi.org/10.1016/j.atmosenv.2018.10.026
Dai, Q., Bi, X.*, Song, W., Li, T., Liu, B., Ding, J., Xu, J., Song, C., Yang, N., Schulze, B., Zhang, Y., Feng, Y., & Hopke, P. (2019). Residential coal combustion as a source of primary sulfate in Xi’an, China. Atmospheric Environment, 196, 66–76. https://doi.org/10.1016/j.atmosenv.2018.10.002 [One of the most cited articles from Atmospheric Environment published since 2020]
Sun, L.-N., Liu, Y., Zhao, J.-B., Sun, S.-D., Song, C., Zhang, J., Li, Y.-N., Lin, Y.-C., Wang, T., & Mao, H.-J.* (2019). Pollution characteristics and emission factors of VOCs from vehicle emissions in the tianjin tunnel. Huanjing Kexue/Environmental Science, 40(1), 104–113. https://doi.org/10.13227/j.hjkx.201804187
2018
Song, C., Ma, C., Zhang, Y., Wang, T., Wu, L.*, Wang, P., Liu, Y., Li, Q., Zhang, J., Dai, Q., Zou, C., Sun, L., & Mao, H.* (2018). Heavy-duty diesel vehicles dominate vehicle emissions in a tunnel study in northern China. Science of the Total Environment, 637-638, 431–442. https://doi.org/10.1016/j.scitotenv.2018.04.387 [pdf]
Dai, Q., Bi, X.*, Liu, B., Li, L., Ding, J., Song, W., Bi, S., Schulze, B., Song, C., Wu, J., Zhang, Y., Feng, Y., & Hopke, P. (2018). Chemical nature of PM2.5 and PM10 in Xi’an, China: Insights into primary emissions and secondary particle formation. Environmental Pollution, 240, 155–166. https://doi.org/10.1016/j.envpol.2018.04.111
Wang, A.-X., Chen, X., Song, C., Ying, S.-M., Li, Q., Wu, L., & Mao, H.-J.* (2018). Association between fine particulate matter and asthma hospital outpatient visits in Hangzhou. Huanjing Kexue/Environmental Science, 39(10), 4457–4462. https://doi.org/10.13227/j.hjkx.201712090
2017
Song, C., He, J.*, Wu, L., Jin, T., Chen, X., Li, R., Ren, P., Zhang, L., & Mao, H.* (2017). Health burden attributable to ambient PM2.5 in China [ESI Highly Cited Paper]. Environmental Pollution, 223, 575–586. https://doi.org/10.1016/j.envpol.2017.01.060 [pdf]
Song, C., Wu, L., Xie, Y., He, J., Chen, X., Wang, T., Lin, Y., Jin, T., Wang, A., Liu, Y., Dai, Q., Liu, B., Wang, Y.-N., & Mao, H.* (2017). Air pollution in China: status and spatiotemporal variations [ESI Highly Cited Paper]. Environmental Pollution, 227, 334–347. https://doi.org/10.1016/j.envpol.2017.04.075 [pdf]
Fang, X.-Z., Wu, L., Zhang, J., Li, H.-R., Mao, H.-J.*, & Song, C. (2017). Characteristics of particulate matter and carbonaceous species in ambient air at different air quality levels. Huanjing Kexue/Environmental Science, 38(9), 3569–3574. https://doi.org/10.13227/j.hjkx.201702090
He, J., Gong, S., Liu, H.*, An, X., Yu, Y., Zhao, S., Wu, L., Song, C., Zhou, C., Wang, J., Yin, C., & Yu, L. (2017). Influences of meteorological conditions on interannual variations of particulate matter pollution during winter in the beijing–tianjin–hebei area. Journal of Meteorological Research, 31(6), 1062–1069. https://doi.org/10.1007/s13351-017-7039-9
He, J.*, Gong, S., Yu, Y., Yu, L., Wu, L., Mao, H., Song, C., Zhao, S., Liu, H., Li, X., & Li, R. (2017). Air pollution characteristics and their relation to meteorological conditions during 2014–2015 in major chinese cities [ESI Highly Cited Paper]. Environmental Pollution, 223, 484–496. https://doi.org/10.1016/j.envpol.2017.01.050