Estudio de la carga de enfermedades causada por la exposición prolongada a la contaminación por PM2.5 en China e India, 2000-2018

  • role: First author第一作者
  • Affiliation:

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    School of Electronic, Electrical and Communication Engineering, University of Chinese Academy of Sciences, Beijing 100049, China

  • Email:zhuyue19@mails.ucas.ac.cn
  • Introduction:E-mail zhuyue19@mails.ucas.ac.cn
ZHU Yue12,  
  • role: Corresponding author通信作者
  • Affiliation:

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

  • Email:shiys@aircas.ac.cn
  • Introduction:E-mail shiys@aircas.ac.cn
SHI Yusheng1*,  
  • Affiliation:

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

LI Zhengqiang1

resumen

El PM2.5 como contaminante del aire plantea una amenaza potencial para la salud humana. China e India son los dos países en desarrollo más poblados del mundo, y el problema de la carga de enfermedades causadas por la contaminación por PM2.5 es especialmente grave. Por lo tanto, en este estudio, se analizó la evolución temporal y espacial del patrón de PM2.5 y la exposición de la población en China e India durante 19 años (2000-2018) basándose en datos de concentración de PM2.5 invertidos a partir de series temporales de alta resolución (0.01°×0.01°) de satélites. Además, se evaluó exhaustivamente el número de muertes prematuras debido a 6 enfermedades (infecciones agudas del tracto respiratorio inferior, enfermedad pulmonar obstructiva crónica, diabetes tipo 2, enfermedad isquémica del corazón, cáncer de pulmón y accidente cerebrovascular) causadas por la exposición a largo plazo al PM2.5 en ambos países utilizando un modelo de respuesta de exposición integrada. Los resultados mostraron que las áreas con altas concentraciones de PM2.5 en China se concentran en Xinjiang, la cuenca de Sichuan, la llanura del norte de China y el cinturón económico del río Yangtsé, y la concentración ponderada por la población mostró una tendencia general a la disminución (50 μg∙m-3 en 2000 y 40.8 μg∙m-3 en 2018). Mientras que las áreas con altas concentraciones de PM2.5 en India se concentran en el norte y la concentración ponderada por la población ha mostrado una tendencia constante al aumento (51.5 μg∙m-3 en 2000 y 76.4 μg∙m-3 en 2018). En el caso de China, el número de muertes prematuras causadas por la exposición al PM2.5 aumentó de 908,000 en 2000 a 1,378,000 en 2018, lo que representó un aumento de 470,000. El accidente cerebrovascular fue la enfermedad terminal principal que causó muertes prematuras, representando el 45.9% del número total de muertes (563,000 personas). Mientras que el número de muertes prematuras causadas por la exposición al PM2.5 en India aumentó de 343,000 en 2000 a 750,000 en 2018, lo que representó un aumento de 407,000. La enfermedad isquémica del corazón y el accidente cerebrovascular fueron las principales enfermedades terminales que causaron muertes prematuras, representando el 39.9% (202,000 personas) y el 25.5% (129,000 personas) respectivamente. Los resultados del estudio podrían servir de referencia para los responsables de la toma de decisiones y los organismos de control de la contaminación, y podrían ayudar a formular políticas para el control de la contaminación del aire.

palabra clave

Teledetección; PM2.5; Carga de enfermedades; Mortalidad prematura; China; India; Series temporales largas

References

  1. 1.
    Brauer M, Amann M, Burnett R T, Cohen A, Dentener F, Ezzati M, Henderson S B, Krzyzanowski M, Martin R V, Van Dingenen R, van Donkelaar A and Thurston G D. 2012. Exposure assessment for estimation of the global burden of disease attributable to outdoor air pollution. Environmental Science and Technology, 46(2): 652-660
  2. 2.
    Chowdhury S and Dey S. 2016. Cause-specific premature death from ambient PM2.5 exposure in India: estimate adjusted for baseline mortality. Environment International, 91: 283-290
  3. 3.
    Ding D, Xing J, Wang S X, Liu K Y and Hao J M. 2019. Estimated contributions of emissions controls, meteorological factors, population growth, and changes in baseline mortality to reductions in ambient PM2.5 and PM2.5-related mortality in China, 2013—2017. Environmental Health Perspectives, 127(6): 067009
  4. 4.
    Fang D, Wang Q G, Li H M, Yu Y Y, Lu Y and Qian X. 2016. Mortality effects assessment of ambient PM2.5 pollution in the 74 leading cities of China. Science of the Total Environment, 569-570: 1545-1552
  5. 5.
    Global Burden of Disease Collaborative Network. 2018. Global Burden of Disease Study 2017 (GBD 2017) Population Estimates 1950—2017. Seattle, United States of America: Institute for Health Metrics and Evaluation (IHME)
  6. 6.
    Guan Y, Kang L, Wang Y, Zhang N N and Ju M T. 2019. Health loss attributed to PM2.5 pollution in China’s cities: economic impact, annual change and reduction potential. Journal of Cleaner Production, 217: 284-294
  7. 7.
    Hammer M S, van Donkelaar A, Li C, Lyapustin A, Sayer A M, Hsu N C, Levy R C, Garay M J, Kalashnikova O V, Kahn R A, Brauer M, Apte J S, Henze D K, Zhang L, Zhang Q, Ford B, Pierce J R and Martin R V. 2020. Global estimates and long-term trends of fine particulate matter concentrations (1998—2018). Environmental Science and Technology, 54(13): 7879-7890
  8. 8.
    Huang J, Pan X C, Guo X B and Li G X. 2018. Health impact of China’s Air Pollution Prevention and Control Action Plan: an analysis of national air quality monitoring and mortality data. The Lancet Planetary Health, 2(7): e313-e323
  9. 9.
    Jain V, Dey S and Chowdhury S. 2017. Ambient PM2.5 exposure and premature mortality burden in the holy city Varanasi, India. Environmental Pollution, 226: 182-189
  10. 10.
    Li Y, Zhao X G, Liao Q, Tao Y and Bai Y. 2020. Specific differences and responses to reductions for premature mortality attributable to ambient PM2.5 in China. Science of the Total Environment, 742: 140643
  11. 11.
    Li Y, Liao Q, Zhao X G, Bai Y and Tao Y. 2021. Influence of PM2.5 pollution on health burden and economic loss in China. Environmental Science, 42(4): 1688-1695
  12. 12.
    Liang F C, Yang X L, Liu F C, Li J X, Xiao Q Y, Chen J C, Liu X Q, Cao J, Shen C, Yu L, Lu F H, Wu X P, Zhao L C, Wu X G, Li Y, Hu D S, Huang J F, Liu Y, Lu X F and Gu D F. 2019. Long-term exposure to ambient fine particulate matter and incidence of diabetes in China: a cohort study. Environment International, 126: 568-575
  13. 13.
    Limaye V S, Schöpp W and Amann M. 2019. Applying integrated exposure-response functions to PM2.5 pollution in India. International Journal of Environmental Research and Public Health, 16(1): 60
  14. 14.
    Liu J, Han Y Q, Tang X, Zhu J and Zhu T. 2016. Estimating adult mortality attributable to PM2.5 exposure in China with assimilated PM2.5 concentrations based on a ground monitoring network. Science of the Total Environment, 568: 1253-1262
  15. 15.
    Lu X C, Lin C Q, Li W K, Chen Y A, Huang Y Q, Fung J C H and Lau A K H. 2019. Analysis of the adverse health effects of PM2.5 from 2001 to 2017 in China and the role of urbanization in aggravating the health burden. Science of the Total Environment, 652: 683-695
  16. 16.
    Maji K J. 2020. Substantial changes in PM2.5 pollution and corresponding premature deaths across China during 2015—2019: a model prospective. Science of the Total Environment, 729: 138838
  17. 17.
    Maji K J, Li V O K and Lam J C K. 2020. Effects of China's current Air Pollution Prevention and Control Action Plan on air pollution patterns, health risks and mortalities in Beijing 2014—2018. Chemosphere, 260: 127572
  18. 18.
    Manojkumar N and Srimuruganandam B. 2021. Health benefits of achieving fine particulate matter standards in India-A nationwide assessment. Science of the Total Environment, 763: 142999
  19. 19.
    Sahu S K, Sharma S, Zhang H L, Chejarla V, Guo H, Hu J L, Ying Q, Xing J and Kota S H. 2020. Estimating ground level PM2.5 concentrations and associated health risk in India using satellite based AOD and WRF predicted meteorological parameters. Chemosphere, 255: 126969
  20. 20.
    Wang H, Yin P, Fan W H, Wang Y, Dong Z M, Deng Q H and Zhou M G. 2021. Mortality risk associated with short-term exposure to particulate matter in China: estimating error and implication. Environmental Science and Technology, 55(2): 1110-1121
  21. 21.
    Wang Q, Wang J N, He M Z, Kinney P L and Li T T. 2018. A county-level estimate of PM2.5 related chronic mortality risk in China based on multi-model exposure data. Environment International, 110: 105-112
  22. 22.
    Wang Q, Zhu H H, Du P, Zhao L and Li T T. 2021. Health benefit of ‘14th Five-Year’ and medium and long-term PM2.5 control targets in Beijing-Tianjin-Hebei and its surrounding areas. Research of Environmental Sciences, 34(1): 220-228
  23. 23.
    Wei J, Li Z Q, Lyapustin A, Sun L, Peng Y R, Xue W H, Su T N and Cribb M. 2021. Reconstructing 1-km-resolution high-quality PM2.5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications. Remote Sensing of Environment, 252: 112136
  24. 24.
    Xiang J, Tao M H, Guo L, Chen L F, Tao J H and Gui L. 2022. Progress of near-surface PM2.5 concentration retrieve based on satellite remote sensing. National Remote Sensing Bulletin, 26(9): 1757-1776
  25. 25.
    Xiao Q Y, Geng G N, Xue T, Liu S G, Cai C L, He K B and Zhang Q. 2022. Tracking PM2.5 and O3 pollution and the related health burden in China 2013—2020. Environmental Science and Technology, 56(11): 6922-6932
  26. 26.
    Xue T, Zhu T, Zheng Y X, Liu J, Li X and Zhang Q. 2019. Change in the number of PM2.5-attributed deaths in China from 2000 to 2010: comparison between estimations from census-based epidemiology and pre-established exposure-response functions. Environment International, 129: 430-437
  27. 27.
    Yang W and Jiang X L. 2021. Evaluating the influence of land use and land cover change on fine particulate matter. Scientific Reports, 11: 17612
  28. 28.
    Yang X C, Wang Y, Zhao C F, Fan H, Yang Y K, Chi Y L, Shen L X and Yan X. 2022. Health risk and disease burden attributable to long-term global fine-mode particles. Chemosphere, 287: 132435
  29. 29.
    Yue H B, He C Y, Huang Q X, Yin D and Bryan B A. 2020. Stronger policy required to substantially reduce deaths from PM2.5 pollution in China. Nature Communications. 1462.
  30. 30.
    Zhang Y Q. 2021. All-Cause Mortality Risk and Attributable Deaths Associated with Long-Term Exposure to Ambient PM2.5 in Chinese Adults.Environmental Science & Technology, 55(9): 6116-6127.
  31. 31.
    Zhou M G, Wang H D, Zhu J, Chen W Q, Wang L H, Liu S W, and Li Y C. 2016. Cause-specific mortality for 240 causes in China during 1990—2013: a systematic subnational analysis for the Global Burden of Disease Study 2013. The Lancet, 387 (10015): 251-272.
  32. 32.
    Zou B, You J W, Lin Y, Duan X L, Zhao X G, Fang X, Matthew J C, and Li S X. 2019. Air pollution intervention and life-saving effect in China.Environment International, 125: 529-541.

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