Published September 2021 | Version v1
Journal article

Characterizing air pollution risk perceptions among high-educated young generation in China: How does risk experience influence risk perception

  • 1. Department of Environmental Health, School of Public Health, Boston University, Boston, MA (United States)
  • 2. State Key Laboratory of Pollution Control and Resource Reuse, School of the Environment, Nanjing University, Nanjing (China)

Description

Highlights: • The young Chinese generation's overall risk perception for air pollution was surveyed. • Spatial heterogeneity of risk perception for air pollution was measured. • Groups sensitive to air pollution from the risk perception views were identified. • Roles of historical air pollution exposure in modifying risk perception were explored. Psychometric paradigms have been developed and extensively applied in risk perception analyses, but relatively few studies have examined risk perception of air pollution in developing countries where the public is exposed to extremely high pollution levels. We conducted a stratified sampling questionnaire survey among 1988 college students from throughout China studying in Nanjing, to examine how risk perceptions are influenced by socioeconomic factors and historical exposure among the high-educated young generation who will become leaders in future air pollution risk management and communications. First, a six-factor confirmatory factor analysis was conducted to estimate risk perception levels from the observable indices. 40 % of the participants felt air pollution levels in Nanjing were unacceptable, which suggested that air pollution control actions do not meet public expectations at the survey time. Hierarchical k-means clustering demonstrated difference in the spatial distribution of risk perception. Results showed that students from the northern part of China had higher risk acceptance, lower perceived risk, and higher government trust than other regions. Females, older participants, participants with higher education, and participants with higher economic levels were identified as risk-sensitive groups to air pollution by using linear regression analyses. The regression coefficients of risk perception and historical exposure decreased as the days tracking back to a pollution episode increased. The cut-off point where regression coefficients turned from significant to non-significant was around 60 days for risk acceptance, 10 days for perceived benefit, and 30 days for government trust. This indicates that a 2-month time window is a prime time for risk communication after a pollution episode.

Availability note (English)

Available from http://dx.doi.org/10.1016/j.envsci.2021.05.006

Additional details

Identifiers

DOI
10.1016/j.envsci.2021.05.006;
PII
S146290112100126X;

Publishing Information

Journal Title
Environmental Science and Policy
Journal Volume
123
Journal Page Range
p. 99-105
ISSN
1462-9011

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
53123906
Subject category
S54: ENVIRONMENTAL SCIENCES;
Descriptors DEI
AIR POLLUTION; AIR POLLUTION CONTROL; CHINA; DEVELOPING COUNTRIES; EDUCATIONAL FACILITIES; PUBLIC OPINION; REGRESSION ANALYSIS; RISK ASSESSMENT; SAMPLING; SPATIAL DISTRIBUTION
Descriptors DEC
ASIA; CONTROL; DISTRIBUTION; MATHEMATICS; POLLUTION; POLLUTION CONTROL; STATISTICS

Optional Information

Copyright
Copyright (c) 2021 Published by Elsevier Ltd.