Risk Perception of Air Pollution: History
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Contributor:
Liliana Cori
,
Gabriele Donzelli
,
Francesca Gorini
,
Fabrizio Bianchi
,
Olivia Curzio

The adverse health effects of exposure to air pollutants, notably to particulate matter (PM), are well-known, as well as the association with measured or estimated concentration levels. The role of perception can be relevant in exploring effects and pollution control actions.

  • air pollution exposure
  • particulate matter (pm)
  • environmental epidemiology

1. Risk Perception

Risk perception studies have been ancillary to different fields of knowledge, trying to disclose the reasons behind the behaviors of people and predict their future actions [1]. Risk perception can be defined as a person’s judgement about a risk, influenced by facts, knowledge (lay and scientific), personal preferences and attitudes (dread, trust, and interpretation of uncertainty), individual assessments (general and specific), and his/her social role (defined as “agency” by sociological disciplines; that is, the possibility/ability to act to change one’s condition). Beliefs, knowledge, values, and attitudes not only influence decisions, but also behaviors, psychophysical conditions, and exposure attitudes of people to environmental pressures [1]. Risk perception is not entirely rational since people assess risks using a mixture of cognitive skills (weighing the evidence and using reasoning and logic to reach conclusions) and emotional appraisals (intuition or imagination) [2][3][4].
In the domain of the environment and health, the study of risk perception has acquired increasing relevance as part of the knowledge required to understand social contexts and specific personal dimensions of exposure to pollutants; risk perception is fundamental in environment and health risk communication because it determines which hazards people care about and how they deal with them [5][6][7][8]. It reinforces the importance of epidemiology in evaluating the health of communities living in areas where the main perceptible sources of pollution are known, even if the evidence produced always maintains some uncertainty [9].
Complexity and uncertainty are specific features of this research activity and the inclusion of people’s perspective in the process could help to enhance the global understanding and the use of research results [7][10][11][12][13][14][15].
Nothing in risk is neutral and its perception is linked to multiple facts and motivations. Social science research in risk perception has explored and discovered how risk is understood, manufactured, or created socially, politically, and culturally [5][6][7][16][17][18][19][20][21]. Additionally, the economic evaluation of savings through which it is possible to achieve remediating high-risk areas includes risk perception calculated through the Willingness to Pay (WTP) index as an indirect indicator of health expenses [22].

2. Particulate Matter Pollution and Health

Ambient air pollution is the major environmental risk factor for the global disease burden, which has increased over the past 25 years, especially as a result of rising levels of pollution and increasing numbers of deaths from non-communicable diseases in low-income and middle-income countries [23].
Particulate matter (PM) comprises a class of pollutants consisting of a heterogeneous mixture of solid and liquid particles suspended in the air and it represents a considerable threat to health [24]. Primary PM can be released from both natural and anthropogenic sources, with road traffic considered the major source due to the erosion of pavements and abrasion of brakes and tires [25]. Secondary particles are products of the atmospheric transformation of nitrogen oxides and sulfur oxides, mainly emitted by traffic and the combustion of sulfur-containing fuels, respectively [26].
In 2013, the WHO International Agency for Research on Cancer (IARC) announced that there is sufficient evidence in humans for the carcinogenicity of outdoor air pollution and for PM in outdoor air pollution [27][28]. This understanding represented a turning point in research that focused on the health effects of inhalable PM, i.e., particles with diameters smaller than 10 (PM10) or 2.5 micrometers (PM2.5), and it was discovered that the size of particles is directly linked to their potential for causing health problems [29]. Human exposure to PM, both short and long term, has been quantitatively associated with numerous health effects, such as increased hospital admissions, emergency room visits, respiratory and cardiovascular morbidity, and mortality from cardiovascular and respiratory diseases and lung cancer [25]. Integrated exposure–response functions for each cause of death can be developed to estimate the relative risk of mortality attributable to PM. In particular, long-term exposure to PM2.5 was estimated to have caused 4.2 million deaths in 2015, corresponding to 7.6% of the total global mortality and making PM2.5 the fifth-ranking mortality risk factor [23].
For PM10 and PM2.5, concentration-response risk functions have been developed and proposed for health impact assessments. Many studies have included recommendations for actions and explorations of policy implications and the economic impact of PM reductions. Green energy policy in Europe includes air pollutant emission reduction in the motivation for reduction. Moreover, the international agreements addressing climate change consider PM in their reduction plans [30].

3. Policies

In several Asian cities, outdoor PM air pollution is increasing. In India, outdoor air pollution was responsible for more than 670,000 deaths in 2016. To deal with these health effects, several countries have launched large-scale policies, such as China [31][32] and India; in other countries like Thailand, there is a growing demand for policies to address the issue of polluted air [33]. Although in many countries there are no specific laws or protection rules, WHO guidelines are taken into consideration [26].
In China, to address the severe air pollution, the 2013 Action Plan on Prevention and Control of Air Pollution established a reduction of the PM2.5 concentration in Beijing, Nanjing, and Guangzhou cities by 25%, 20%, and 15%, respectively, between 2012 and 2017. After this, several plans and specific measures were implemented [34].
In the EU and US, air protection policies are similar and the reduction of air pollution is a central element. In the US, air quality (AQ) is a federal matter and the relevant policies apply to the whole country. In the EU, AQ policy is based on standards issued by the European Commission and national implementations, where Member States determine the best way to achieve them within each country. In addition, in the US, air pollution management is implemented through a combination of the AQ standard and the emission standard strategies, whereas in the EU, emission standards, emission taxation, and cost-benefit analysis are used [35].
In 2013, the European Commission adopted a Clean Air Policy Package for Europe in order to set new objectives for EU air policy and reduce the negative health impacts of air pollution, such as respiratory diseases and premature death, by almost 50% by 2030 [36].

4. Big Data Utilization and Applications

The use of search engine data and social media is changing the ways in which researchers investigate public opinion. Consequently, traditional survey research may play a less dominant role [37]. A recent review of the public’s use of big data from web searches shows that the use of Google Trends has increased dramatically in the last decade. In the process, the focus of research has shifted to forecasting changes. In contrast, in the past, the focus was merely on describing and diagnosing research trends, such as surveillance and monitoring [38]. One of the most recent applications of big data for the social sciences focused on an investigation of the phenomenon of vaccine hesitancy. Some studies have concluded that monitoring new media could be useful for detecting early signals of decreasing vaccine hesitancy and planning and targeting effective information campaigns [39][40].
This systematic research identified only five articles that studied perceived pollution using big data in the past five years. Three of them investigated perceived pollution using big data from web searches; namely, one of them used Google Trends [33] and the other two, the Baidu Index [41][42]. Although researchers found a correlation between the AQ level and perceived pollution in these three articles, researchers noticed that each study used different search terms, namely, “air pollution”, “cough”, and “asthma” [33]; “Shanghai air quality” [41]; and “haze” [42]. The other two articles collected messages from Sina Weibo, which is the most popular microblogging service in China. Both studies show that social media may be a useful proxy for measuring pollution, mainly when traditional measurement stations are unavailable, censored, or misreported [43][44].
Although these studies show promising results, several limitations should be considered, suggesting that researchers cannot completely abandon the research method of a questionnaire survey. In this regard, one of the main limitations is that big data can only provide an active collective public response compared to questionnaire surveys, which directly indicate public concern based on individual responses. Concerning Chinese studies, researchers should consider the effect of government censorship on using social media for informatics in China.

5. Communication and Recommendations

The disintermediation of communication, which has been growing exponentially in recent years, represents a relevant change in the circulation of information, with a potential relevant impact on risk perception and consequently, on health [45][46]. It is reflected in the studies examined here, with growing attention being placed on big data utilization and the continuous attention given to the utilization of results, the role of citizens, and the importance to inform and involve people to foster prevention and reduce environmental pollution.
In fact, it is clearly conceptualized by the scientific community and decision makers that the only way of managing complex problems in the environment and health domain is sharing responsibility and action to improve the quality and durability of decisions and actions. In particular, it is of utmost importance to gather information about risk perception to plan risk governance actions, including health literacy programs and communication and engagement activities, to be able to dialogue with different social actors and contribute to prevention and protection [1][19].

This entry is adapted from the peer-reviewed paper 10.3390/ijerph17176424

References

  1. Rosa, E.A.; Renn, O.; McCright, A.M. The Risk Society Revisited: Social Theory and Risk Governance; Temple University Press: Philadelphia, PA, USA, 2014.
  2. Ropeik, D. Understanding Factors of Risk Perception. Available online: https://niemanreports.org/articles/understanding-factors-of-risk-perception/ (accessed on 10 August 2020).
  3. Slovic, P.; Peters, E.; Finucane, M.L.; Macgregor, D.G. Affect, risk, and decision making. Health Psychol. 2005, 24, S35–S40.
  4. Yun, K.; Lurie, N.; Hyde, P.S. Moving mental health into the disaster-preparedness spotlight. N. Engl. J. Med. 2010, 363, 1193–1195.
  5. Flynn, J.; Slovic, P.; Mertz, C.K. Gender, Race, and Perception of Environmental Health Risks. Risk Anal. 1994, 14, 1101–1108.
  6. Pidgeon, N. Risk assessment, risk values and the social science programme: Why we do need risk perception research. Reliab. Eng. Syst. Saf. 1998, 59, 5–15.
  7. Renn, O. Perception of risks. Toxicol. Lett. 2004, 149, 405–413.
  8. Nelson, J.W.; Scammell, M.K.; Altman, R.G.; Webster, T.F.; Ozonoff, D.M. A new spin on research translation: The Boston Consensus Conference on Human Biomonitoring. Environ. Health Perspect. 2009, 117, 495–499.
  9. Nieuwenhuijsen, M.J. Exposure Assessment in Environmental Epidemiology; Oxford University Press: Oxford, UK, 2015; ISBN 978-0-19-937881-4.
  10. Funtowicz, S.O.; Ravetz, J.R. Risk management as a postnormal science. Risk Anal 1992, 12, 95–97.
  11. Coi, A.; Minichilli, F.; Bustaffa, E.; Carone, S.; Santoro, M.; Bianchi, F.; Cori, L. Risk perception and access to environmental information in four areas in Italy affected by natural or anthropogenic pollution. Environ. Int. 2016, 95, 8–15.
  12. Carducci, A.; Fiore, M.; Azara, A.; Bonaccorsi, G.; Bortoletto, M.; Caggiano, G.; Calamusa, A.; De Donno, A.; De Giglio, O.; Dettori, M.; et al. Environment and health: Risk perception and its determinants among Italian university students. Sci. Total Environ. 2019, 691, 1162–1172.
  13. Signorino, G. Proximity and risk perception. Comparing risk perception ‘profiles’ in two petrochemical areas of Sicily (Augusta and Milazzo). J. Risk Res. 2012, 15, 1223–1243.
  14. Mudu, P.; Terracini, B.; Martuzzi, M. Human Health in Areas with Industrial Contamination; WHO Regional Office for Europe: Copenhagen, Denmark, 2014; ISBN 978-9-289-05005-0.
  15. Carducci, A.; Donzelli, G.; Cioni, L.; Palomba, G.; Verani, M.; Mascagni, G.; Anastasi, G.; Pardini, L.; Ceretti, E.; Grassi, T.; et al. Air pollution: A study of citizen’s attitudes and behaviors using different information sources. Epidemiol. Biostat. Public Health 2017, 14.
  16. Zinn, J.O. Recent Developments in Sociology of Risk and Uncertainty. Hist. Soc. Res./Hist. Soz. 2006, 31, 275–286.
  17. Douglas, M.; Wildavsky, A. Risk and Culture; University of California Press: Berkeley, CA, USA, 1983; ISBN 978-0-520-05063-1.
  18. Kasperson, R.E.; Renn, O.; Slovic, P.; Brown, H.S.; Emel, J.; Goble, R.; Kasperson, J.X.; Ratick, S. The Social Amplification of Risk: A Conceptual Framework. Risk Anal. 1988, 8, 177–187.
  19. Aven, T.; Renn, O. Risk, Governance and Society. In Risk Management and Governance: Concepts, Guidelines and Applications; Springer: Berlin/Heidelberg, Germany, 2010; ISBN 978-3-642-13925-3.
  20. Renn, O.; Rohrmann, B. Risk, Governance and Society. In Cross-Cultural Risk Perception: A Survey of Empirical Studies; Springer US: New York, NY, USA, 2000; ISBN 978-0-7923-7747-4.
  21. Michaels, D.; Monforton, C. Manufacturing uncertainty: Contested science and the protection of the public’s health and environment. Am. J. Public Health 2005, 95, S39–S48.
  22. Guerriero, C. Cost-Benefit Analysis of Environmental Health Interventions; Elsevier: Amsterdam, The Netherlands, 2020; ISBN 978-0-12-812885-5.
  23. Cohen, A.J.; Brauer, M.; Burnett, R.; Anderson, H.R.; Frostad, J.; Estep, K.; Balakrishnan, K.; Brunekreef, B.; Dandona, L.; Dandona, R.; et al. Estimates and 25-year trends of the global burden of disease attributable to ambient air pollution: An analysis of data from the Global Burden of Diseases Study 2015. Lancet 2017, 389, 1907–1918.
  24. Health Effects of Particulate Matter. Policy Implications for Countries in Eastern Europe, Caucasus and Central Asia (2013). Available online: https://www.euro.who.int/en/health-topics/environment-and-health/air-quality/publications/2013/health-effects-of-particulate-matter.-policy-implications-for-countries-in-eastern-europe,-caucasus-and-central-asia-2013 (accessed on 14 July 2020).
  25. Kim, M.; Yi, O.; Kim, H. The role of differences in individual and community attributes in perceived air quality. Sci. Total Environ. 2012, 425, 20–26.
  26. Evolution of WHO Air Quality Guidelines: Past, Present and Future (2017). Available online: https://www.euro.who.int/en/health-topics/environment-and-health/air-quality/publications/2017/evolution-of-who-air-quality-guidelines-past,-present-and-future-2017 (accessed on 14 July 2020).
  27. IARC. Outdoor Air Pollution; WHO Press: New York, NY, USA, 2015; Volume 109, ISBN 978-92-832-0175-5.
  28. IARC Outdoor Air Pollution a Leading Environmental Cause of Cancer Deaths. Available online: https://www.iarc.fr/pressrelease/iarc-outdoor-air-pollution-a-leading-environmental-cause-of-cancer-deaths/ (accessed on 14 July 2020).
  29. US EPA. Health and Environmental Effects of Particulate Matter (PM). Available online: https://www.epa.gov/pm-pollution/health-and-environmental-effects-particulate-matter-pm (accessed on 14 July 2020).
  30. McMichael, A.J.; Woodruff, R.E.; Hales, S. Climate change and human health: Present and future risks. Lancet 2006, 367, 859–869.
  31. Feng, L.; Liao, W. Legislation, plans, and policies for prevention and control of air pollution in China: Achievements, challenges, and improvements. J. Clean. Prod. 2016, 112, 1549–1558.
  32. Ban, J.; Zhou, L.; Zhang, Y.; Brooke Anderson, G.; Li, T. The health policy implications of individual adaptive behavior responses to smog pollution in urban China. Environ. Int. 2017, 106, 144–152.
  33. Misra, P.; Takeuchi, W. Assessing population sensitivity to urban air pollution using google trends and remote sensing datasets. In Proceedings of the ISPRS—International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Baltimore, MD, USA, 6–11 October 2019; Volume XLII-3-W11, pp. 93–100.
  34. Wang, L.; Watanabe, T. Effects of environmental policy on public risk perceptions of haze in Tianjin City: A difference-in-differences analysis. Renew. Sustain. Energy Rev. 2019, 109, 199–212.
  35. Kuklinska, K.; Wolska, L.; Namiesnik, J. Air quality policy in the U.S. and the EU—A review. Atmos. Pollut. Res. 2015, 6, 129–137.
  36. EU Approves New Rules for Member States to Drastically Cut Air Pollution. Available online: https://ec.europa.eu/commission/presscorner/detail/en/IP_16_4358 (accessed on 14 July 2020).
  37. Murphy, J.; Link, M.W.; Childs, J.H.; Tesfaye, C.L.; Dean, E.; Stern, M.; Pasek, J.; Cohen, J.; Callegaro, M.; Harwood, P. Social Media in Public Opinion ResearchExecutive Summary of the Aapor Task Force on Emerging Technologies in Public Opinion Research. Public Opin. Q. 2014, 78, 788–794.
  38. Jun, S.-P.; Yoo, H.S.; Choi, S. Ten years of research change using Google Trends: From the perspective of big data utilizations and applications. Technol. Forecast. Soc. Chang. 2018, 130, 69–87.
  39. Aquino, F.; Donzelli, G.; De Franco, E.; Privitera, G.; Lopalco, P.L.; Carducci, A. The web and public confidence in MMR vaccination in Italy. Vaccine 2017, 35, 4494–4498.
  40. Donzelli, G.; Palomba, G.; Federigi, I.; Aquino, F.; Cioni, L.; Verani, M.; Carducci, A.; Lopalco, P. Misinformation on vaccination: A quantitative analysis of YouTube videos. Hum. Vaccines Immunother. 2018, 14, 1654–1659.
  41. Dong, D.; Xu, X.; Xu, W.; Xie, J. The Relationship between the Actual Level of Air Pollution and Residents’ Concern about Air Pollution: Evidence from Shanghai, China. Int. J. Environ. Res. Public Health 2019, 16, 4784.
  42. Lu, Y.; Wang, Y.; Zuo, J.; Jiang, H.; Huang, D.; Rameezdeen, R. Characteristics of public concern on haze in China and its relationship with air quality in urban areas. Sci. Total Environ. 2018, 637–638, 1597–1606.
  43. Li, F.; Zhou, T. Effects of objective and subjective environmental pollution on well-being in urban China: A structural equation model approach. Soc. Sci. Med. 2020, 249, 112859.
  44. Wang, S.; Paul, M.J.; Dredze, M. Social media as a sensor of air quality and public response in China. J. Med. Internet Res. 2015, 17, e22.
  45. McLaughlin, C.P.; Kaluzny, A.D.; Kibbe, D.C.; Tredway, R. Changing roles for primary-care physicians: Addressing challenges and opportunities. Healthc Q. 2005, 8, 70–78.
  46. Fontaine, G.; Lavallée, A.; Maheu-Cadotte, M.-A.; Bouix-Picasso, J.; Bourbonnais, A. Health science commu nication strategies used by researchers with the public in the digital and social media ecosystem: A systematic scoping review protocol. BMJ Open 2018, 8, e019833.
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