Study on the exposure risk based on the PM_2.5 pollution characteristics of POIs and their attractiveness to the crowd

Reference

• Asakura Y, Iryo T. 2007. Analysis of tourist behaviour based on the tracking data collected using a mobile communication instrument. Transport Res Part A Policy Pract. 41(7):684–690.
   Web of Science ®Google Scholar
• Baysal ZN, Seda S. 2010. Evaluation of the primary school level students’ attitudes towards mobile phones. Procedia Soc Behav Sci. 2(2):4279–4284.
   Google Scholar
• Chan LY, Kwok WS, Chan CY. 2000. Human exposure to respirable suspended particulate and airborne lead in different roadside microenvironments. Chemosphere. 41(1-2):93–99. doi:10.1016/S0045-6535(99)00394-X
   PubMed Web of Science ®Google Scholar
• Chi J, Jiao L, Dong T, Gu Y, Ma Y. 2016. Quantitative identification and visualization of urban functional area based on POI data. J Geomatics. 41(2): 68–73.
   Google Scholar
• Feng X, Li Q, Zhu Y, Hou J, Jin L, Wang J. 2015. Artificial neural networks forecasting of PM2.5 pollution using air mass trajectory based geographic model and wavelet transformation. Atmos Environ. 107:118–128. doi:10.1016/j.atmosenv.2015.02.030
   Web of Science ®Google Scholar
• Gao Y, Guo X, Ji H, Li C, Ding H, Briki M, Tang L, Zhang Y. 2016. Potential threat of heavy metals and PAHs in PM2. 5 in different urban functional areas of Beijing. Atmos Res. 178-179:6–16. doi:10.1016/j.atmosres.2016.03.015
   Web of Science ®Google Scholar
• Guo X, Zhao L, Chen D, Jia Y, Zhao N, Liu W, Cheng S. 2018. Air quality improvement and health benefit of PM2.5 reduction from the coal cap policy in the Beijing–Tianjin–Hebei (BTH) region, China. Environ Sci Pollut Res. 25(32):32709–32720.
   PubMed Web of Science ®Google Scholar
• Han Y-J, Kim H-W, Cho S-H, Kim P-R, Kim W-J. 2015. Metallic elements in PM2. 5 in different functional areas of Korea: Concentrations and source identification. Atmos Res. 153:416–428. doi:10.1016/j.atmosres.2014.10.002
   Web of Science ®Google Scholar
• Hystad P, Setton E, Cervantes A, Poplawski K, Deschenes S, Brauer M, van Donkelaar A, Lamsal L, Martin R, Jerrett M, et al. 2011. Creating national air pollution models for population exposure assessment in Canada. Environ Health Perspect. 119(8):1123–1129. doi:10.1289/ehp.1002976
   PubMed Web of Science ®Google Scholar
• Johnston RJ. 1980. Multivariate statistical analysis in geography;.
   Google Scholar
• Kent JL. 2014. Driving to save time or saving time to drive? The enduring appeal of the private car. Transport Res Part A Policy Pract. 65:103–115. (JUL.):doi:10.1016/j.tra.2014.04.009
   Web of Science ®Google Scholar
• Kinney PL, Gichuru MG, Volavka-Close N, Ngo N, Ndiba PK, Law A, Gachanja A, Gaita SM, Chillrud SN, Sclar E. 2011. Traffic impacts on PM(2.5) Air Quality in Nairobi, Kenya. Environ Sci Policy. 14(4):369–378. doi:10.1016/j.envsci.2011.02.005
   PubMed Web of Science ®Google Scholar
• Lelieveld J, Evans JS, Fnais M, Giannadaki D, Pozzer A. 2015. The contribution of outdoor air pollution sources to premature mortality on a global scale. Nature. 525(7569):367–371. doi:10.1038/nature15371
   PubMed Web of Science ®Google Scholar
• Lian D, Zhao C, Xie X, Sun G, Chen E, 2014. and Y. Rui GeoMF: joint geographical modeling and matrix factorization for point-of-interest recommendation. Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.
   Google Scholar
• Liang W, Yang M. 2019. Urbanization, economic growth and environmental pollution: Evidence from China. Sustain Comput Informatics Syst. 21:1–9. doi:10.1016/j.suscom.2018.11.007
   Web of Science ®Google Scholar
• Lin JY, Liu Z. 2000. Fiscal decentralization and economic growth in China. Econ Dev Cultural Change. 49(1):1–21. doi:10.1086/452488
   Web of Science ®Google Scholar
• Lin L. 2014. Countermeasures and suggestions for realizing air pollution prevention and control target in Baoding City, China Environ Prot Industry. 2014(01):49–51.
   Google Scholar
• Lu J, Cao X. 2015. PM2.5 pollution in major cities in China: pollution status, emission sources and control measures. Fresenius Environ Bull. 24(4a):1338–1349.
   Web of Science ®Google Scholar
• Miao Q, Chen D, Buzzelli M, Aronson KJ. 2015. Environmental equity research: review with focus on outdoor air pollution research methods and analytic tools. Arch Environ Occup Health. 70(1):47–55. doi:10.1080/19338244.2014.904266
   PubMed Web of Science ®Google Scholar
• Nyhan M, Grauwin S, Britter R, Misstear B, McNabola A, Laden F, Barrett SR, Ratti C. 2016. “Exposure Track”– the impact of mobile-device-based mobility patterns on quantifying population exposure to air pollution. Environ Sci Technol. 50(17):9671–9681. doi:10.1021/acs.est.6b02385
   PubMed Web of Science ®Google Scholar
• Paunescu A‐C, Attoui M, Bouallala S, Sunyer J, Momas I. 2017. Personal measurement of exposure to black carbon and ultrafine particles in schoolchildren from PARIS cohort (Paris, France). Indoor Air. 27(4):766–779. doi:10.1111/ina.12358
   PubMed Web of Science ®Google Scholar
• Perlik M, Messerli P. 2001. Towns in the Alps: urbanization processes, economic structure, and demarcation of European Functional Urban Areas (EFUAs) in the Alps. Mount Res Dev. 21(3):243–252. doi:10.1659/0276-4741(2001)021[0243:TITA]2.0.CO;2
   Web of Science ®Google Scholar
• Qiu X, Duan L, Gao J, Wang S, Chai F, Hu J, Zhang J, Yun Y. 2016. Chemical composition and source apportionment of PM10 and PM2. 5 in different functional areas of Lanzhou, China. J Environ Sci. 40:75–83. doi:10.1016/j.jes.2015.10.021
   Web of Science ®Google Scholar
• Rodriguez A, Laio A. 2014. Machine learning. Clustering by fast search and find of density peaks. Science. 344(6191):1492–1496. doi:10.1126/science.1242072
   PubMed Web of Science ®Google Scholar
• Sinharay R, Gong J, Barratt B, Ohman-Strickland P, Ernst S, Kelly FJ, Jim Zhang J, Collins P, Cullinan P, Chung KF. 2018. Respiratory and cardiovascular responses to walking down a traffic-polluted road compared with walking in a traffic-free area in participants aged 60 years and older with chronic lung or heart disease and age-matched healthy controls: a randomised, crossover study. The Lancet. 391(10118):339–349.
   PubMed Web of Science ®Google Scholar
• Wang D, Zhong W, Yin Z, Xie D, Luo X. 2018. Spatio-temporal dynamics of population in shanghai: A case study based on cell phone signaling data. In Big Data Support of Urban Planning and Management. Berlin, Germany: Springer. p. 239–254.
   Google Scholar
• Wang H, Zhao L. 2018. A joint prevention and control mechanism for air pollution in the Beijing-Tianjin-Hebei region in china based on long-term and massive data mining of pollutant concentration. Atmos Environ. 174:25–42. doi:10.1016/j.atmosenv.2017.11.027
   Web of Science ®Google Scholar
• Wang J, Hu Z, Chen Y, Chen Z, Xu S. 2013. Contamination characteristics and possible sources of PM10 and PM2. 5 in different functional areas of Shanghai, China. Atmos Environ. 68:221–229. doi:10.1016/j.atmosenv.2012.10.070
   Web of Science ®Google Scholar
• Wang L, Zheng X, Stevanovic S, Wu X, Xiang Z, Yu M, & Liu J. 2018. Characterization particulate matter from several Chinese cooking dishes and implications in health effect. Journal of Environmental Sciences 72(10):98–106.
   Google Scholar
• Wei Z, Wang L, Ma S, Zhang F, Jing Y. 2015. Source contributions of PM2.5 in the severe haze episode in Hebei Cities. Sci World J. 2015:1–11. doi:10.1155/2015/480542
   Google Scholar
• Xu J, Qiu J, Chen J, Zou L, Feng L, Lu Y, Wei Q, Zhang J. 2012. Lifestyle and health-related quality of life: A cross-sectional study among civil servants in China. BMC Public Health 12(1):330.
   PubMedGoogle Scholar
• Ye M, Yin P, Lee W-C, 2011. and D-L. Lee Exploiting geographical influence for collaborative point-of-interest recommendation. Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval. doi:10.1145/2009916.2009962
   Google Scholar
• Yuan J, Zheng Y, Xie X. 2012. Discovering regions of different functions in a city using human mobility and POIs. Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining. doi:10.1145/2339530.2339561
   Google Scholar
• Yuan Q, Cong G, Ma Z, Sun A, Magnenat-Thalmann N. 2013. Time-aware point-of-interest recommendation. Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval. doi:10.1145/2484028.2484030
   Google Scholar
• Zhang YS, Ma GX, Yu F, Cao D. 2013. Health damage assessment due to PM2.5 exposure during haze pollution events in Beijing-Tianjin-Hebei region in January 2013. Zhonghua Yi Xue Za Zhi. 93(34):2707–2710.
   PubMedGoogle Scholar
• Zhao S, Chen L, Li Y, Xing Z, Du K. 2015. Summertime spatial variations in atmospheric particulate matter and its chemical components in different functional areas of Xiamen, China. Atmosphere. 6(3):234–254. doi:10.3390/atmos6030234
   Web of Science ®Google Scholar
• Zhou C, Chen J, Wang S. 2018. Examining the effects of socioeconomic development on fine particulate matter (PM2.5) in China's cities using spatial regression and the geographical detector technique . Sci Total Environ. 619-620:436–445. doi:10.1016/j.scitotenv.2017.11.124
   PubMed Web of Science ®Google Scholar
• Zou B, Peng F, Wan N, Gaines Wilson J, Xiong Y. 2014. Sulfur dioxide exposure and environmental justice: a multi–scale and source–specific perspective. Atmos Pollut Res. 5(3):491–499. doi:10.5094/APR.2014.058
   Web of Science ®Google Scholar