Skip to main content
SpringerLink
Log in

Leveraging individual-level data to advance air pollution health risk management

  • Comments
  • Published:
Frontiers of Engineering Management Aims and scope Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  • Barwick P J, Li S, Rao D, Zahur N B (2018). The healthcare cost of air pollution: Evidence from the world’s largest payment network. Working Paper 24688. National Bureau of Economic Research

  • Baylis P (2020). Temperature and temperament: Evidence from Twitter. Journal of Public Economics, 184: 104161

    Article  Google Scholar 

  • Caplin A, Ghandehari M, Lim C, Glimcher P, Thurston G (2019). Advancing environmental exposure assessment science to benefit society. Nature Communications, 10(1): 1236

    Article  Google Scholar 

  • Casas L, Simons K, Nawrot T S, Brasseur O, Declerck P, Buyl R, Coomans D, Nemery B, van Nieuwenhuyse A (2016). Respiratory medication sales and urban air pollution in Brussels (2005 to 2011). Environment International, 94: 576–582

    Article  Google Scholar 

  • Chaix B (2018). Mobile sensing in environmental health and neighborhood research. Annual Review of Public Health, 39(1): 367–384

    Article  Google Scholar 

  • Colmer J, Hardman I, Shimshack J, Voorheis J (2020). Disparities in PM2.5 air pollution in the United States. Science, 369(6503): 575–578

    Article  Google Scholar 

  • Deville Cavellin L, Weichenthal S, Tack R, Ragettli M S, Smargiassi A, Hatzopoulou M (2016). Investigating the use of portable air pollution sensors to capture the spatial variability of traffic-related air pollution. Environmental Science & Technology, 50(1): 313–320

    Article  Google Scholar 

  • Deville P, Linard C, Martin S, Gilbert M, Stevens F R, Gaughan A E, Blondel V D, Tatem A J (2014). Dynamic population mapping using mobile phone data. Proceedings of the National Academy of Sciences of the United States of America, 111(45): 15888–15893

    Article  Google Scholar 

  • Dewulf B, Neutens T, Lefebvre W, Seynaeve G, Vanpoucke C, Beckx C, van de Weghe N (2016). Dynamic assessment of exposure to air pollution using mobile phone data. International Journal of Health Geographics, 15(1): 14

    Article  Google Scholar 

  • Dons E, Laeremans M, Orjuela J P, Avila-Palencia I, Carrasco-Turigas G, Cole-Hunter T, Anaya-Boig E, Standaert A, de Boever P, Nawrot T, Götschi T, de Nazelle A, Nieuwenhuijsen M, Int Panis L (2017). Wearable sensors for personal monitoring and estimation of inhaled traffic-related air pollution: Evaluation of methods. Environmental Science & Technology, 51(3): 1859–1867

    Article  Google Scholar 

  • Fan Y, Palacios J, Arcaya M, Luo R, Zheng S (2021). Health perception and commuting choice: A survey experiment measuring behavioral trade-offs between physical activity benefits and pollution exposure risks. Environmental Research Letters, 16(5): 054026

    Article  Google Scholar 

  • Ghermandi A, Sinclair M (2019). Passive crowdsourcing of social media in environmental research: A systematic map. Global Environmental Change, 55: 36–47

    Article  Google Scholar 

  • Guo Y, Li Y (2018). Online amplification of air pollution risk perception: The moderating role of affect in information. Information Communication and Society, 21(1): 80–93

    Article  Google Scholar 

  • Hanigan I C, Rolfe M I, Knibbs L D, Salimi F, Cowie C T, Heyworth J, Marks G B, Guo Y, Cope M, Bauman A, Jalaludin B, Morgan G G (2019). All-cause mortality and long-term exposure to low level air pollution in the “45 and up study” cohort, Sydney, Australia, 2006–2015. Environment International, 126: 762–770

    Article  Google Scholar 

  • Hankey S, Lindsey G, Marshall J D (2017). Population-level exposure to particulate air pollution during active travel: Planning for low-exposure, health-promoting cities. Environmental Health Perspectives, 125(4): 527–534

    Article  Google Scholar 

  • Hong W, Wei Y, Wang S (2021). Left behind in perception of air pollution? A hidden form of spatial injustice in China. Environment and Planning C: Politics and Space, in press, doi: https://doi.org/10.1177/23996544211036145

  • Liu M, Huang Y, Ma Z, Jin Z, Liu X, Wang H, Liu Y, Wang J, Jantunen M, Bi J, Kinney P L (2017). Spatial and temporal trends in the mortality burden of air pollution in China: 2004–2012. Environment International, 98: 75–81

    Article  Google Scholar 

  • Nyhan M, Grauwin S, Britter R, Misstear B, McNabola A, Laden F, Barrett S R H, Ratti C (2016). “Exposure Track”—The impact of mobile-device-based mobility patterns on quantifying population exposure to air pollution. Environmental Science & Technology, 50(17): 9671–9681

    Article  Google Scholar 

  • Ou Y, West J J, Smith S J, Nolte C G, Loughlin D H (2020). Air pollution control strategies directly limiting national health damages in the US. Nature Communications, 11(1): 957

    Article  Google Scholar 

  • Piel F B, Fecht D, Hodgson S, Blangiardo M, Toledano M, Hansell A L, Elliott P (2020). Small-area methods for investigation of environment and health. International Journal of Epidemiology, 49(2): 686–699

    Article  Google Scholar 

  • Qin J, Han S (2009). Neurocognitive mechanisms underlying identification of environmental risks. Neuropsychologia, 47(2): 397–405

    Article  MathSciNet  Google Scholar 

  • Su J G, Barrett M A, Henderson K, Humblet O, Smith T, Sublett J W, Nesbitt L, Hogg C, van Sickle D, Sublett J L (2017). Feasibility of deploying inhaler sensors to identify the impacts of environmental triggers and built environment factors on asthma short-acting bronchodilator use. Environmental Health Perspectives, 125(2): 254–261

    Article  Google Scholar 

  • Sun C, Kahn M E, Zheng S (2017). Self-protection investment exacerbates air pollution exposure inequality in urban China. Ecological Economics, 131: 468–474

    Article  Google Scholar 

  • Tainio M, Jovanovic Andersen Z, Nieuwenhuijsen M J, Hu L, de Nazelle A, An R, Garcia L M T, Goenka S, Zapata-Diomedi B, Bull F, de Sá T H (2021). Air pollution, physical activity and health: A mapping review of the evidence. Environment International, 147: 105954

    Article  Google Scholar 

  • Tang R, Tian L, Thach T Q, Tsui T H, Brauer M, Lee M, Allen R, Yuchi W, Lai P C, Wong P, Barratt B (2018). Integrating travel behavior with land use regression to estimate dynamic air pollution exposure in Hong Kong. Environment International, 113: 100–108

    Article  Google Scholar 

  • Tsou M M, Lung S C C, Shen Y S, Liu C H, Hsieh Y H, Chen N, Hwang J S (2021). A community-based study on associations between PM2.5 and PM1 exposure and heart rate variability using wearable low-cost sensing devices. Environmental Pollution, 277: 116761

    Article  Google Scholar 

  • Vanroy C, Vanlandewijck Y, Cras P, Feys H, Truijen S, Michielsen M, Vissers D (2014). Is a coded physical activity diary valid for assessing physical activity level and energy expenditure in stroke patients? PLoS One, 9(6): e98735

    Article  Google Scholar 

  • Yang J, Qu S, Liu M, Liu X, Gao Q, He W, Ji J S, Bi J (2021). Gray cityscape caused by particulate matter pollution hampers human stress recovery. Journal of Cleaner Production, 279: 123215

    Article  Google Scholar 

  • Yue H, He C, Huang Q, Yin D, Bryan B A (2020). Stronger policy required to substantially reduce deaths from PM2.5 pollution in China. Nature Communications, 11(1): 1462

    Article  Google Scholar 

  • Zheng S, Wang J, Sun C, Zhang X, Kahn M E (2019). Air pollution lowers Chinese urbanites’ expressed happiness on social media. Nature Human Behaviour, 3(3): 237–243

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. State Key Laboratory of Pollution Control and Resource Reuse, School of Environment, Nanjing University, Nanjing, 210023, China

    Jianxun Yang, Wenjing Wu, Miaomiao Liu & Jun Bi

Authors
  1. Jianxun Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Wenjing Wu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Miaomiao Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jun Bi
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Miaomiao Liu.

Additional information

This work is supported by the National Natural Science Foundation of China (Grant Nos. 71921003, 72174084, and 71761147002) and the Fundamental Research Funds for the Central Universities (Grant No. 0211-14380171).

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Yang, J., Wu, W., Liu, M. et al. Leveraging individual-level data to advance air pollution health risk management. Front. Eng. Manag. 9, 337–342 (2022). https://doi.org/10.1007/s42524-022-0189-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s42524-022-0189-1

Search

Navigation