Analysis on the influencing factors of residents dispose of discarded masks base on Probit regression model
IOP Conference Series. Earth and Environmental Science
; 983(1):012080, 2022.
Article
in English
| ProQuest Central | ID: covidwho-1730607
ABSTRACT
Objective Understanding the influencing factors of discarded masks disposed by residents in Dongguan City during the period of COVID-19 epidemic, so as to provide basis for avoiding the environmental pollution caused by discarded masks in the future. Methods Using random sampling way to make an Internet questionnaire survey among 1042 permanent residents in Dongguan city and using Probit regression model to analyze the current situation and influencing factors of disposing the discarded masks. Results The installation of disposal bins, residents’ environmental concern level and education level positively influenced the residents’ disposal behavior, while the residents’ age and total household size negatively influenced the residents’ willingness to dispose. These influencing factors are basically consistent with those derived from other scholars’ studies on residents’ willingness to dispose of household waste, it shows that residents do not treat the disposal of discarded masks differently from other household waste and ignore the potential environmental hazards of discarded masks. Conclusion In order to motivate residents to properly dispose of discarded masks, it is necessary to clarify and standardize the requirements for discarded mask disposal and increase publicity to enhance the public’s awareness of environmental concerns and hygiene. To avoid environmental problems such as microplastics brought by discarded masks, disposable masks should be replaced by reusable elastic respirators;the use of polypropylene in masks should be reduced;new mask materials should be developed.
Full text:
Available
Collection:
Databases of international organizations
Database:
ProQuest Central
Language:
English
Journal:
IOP Conference Series. Earth and Environmental Science
Year:
2022
Document Type:
Article
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