| Summary: | Economic and domestic activities have been causing a profound deterioration of air quality in
developed and developing countries. The health problems arising from air pollution, both indoor
and outdoor, have become apparent which result in welfare losses in society such as increased
workdays lost and high health cost. The empirical work on welfare losses as a result of air
pollution in South Africa has focussed only on urban settlements, hence the need of this study.
The main objective of this study was to explore the economic impact of air pollution in two
townships of Mangaung metro municipality.
The study was conducted in Phahameng and Rocklands areas. The sampling technique used was
the stratified random sampling technique. Data was collected through a Contingent Valuation
(CV) questionnaire. The 26 questions in the questionnaire were compiled through interaction
with knowledgeable individuals and completed via face-to-face interviews. A total sample of
300 households was surveyed with 111 questionnaires administered in Phahameng and 189 in
Rocklands.
The mitigating cost and the number of workdays lost as a result of an episode of air pollution
related illness was estimates from the survey. Mitigating cost is measured as the total cost
incurred (include consultation fee, cost of medication, hospitalisation and transportation fees) as
a result of treating the last episode (prior to interview) of air pollution related ailments.
Workdays lost is measured as the number of days lost for the last episode (prior to interview) of
ailment related to air pollution. For employed respondents, it is measured as number of days not
able to go to place of work; for self-employed or unemployed respondents, it is measured as the
number of days not able to perform daily routine or activities. For respondents that are studying,
it is measured as days absent from school. The factors influencing these economic parameters
(mitigating cost and workdays lost) were explored using Ordinary Least Square (OLS)
Regression Model. The Contingent Valuation questions measured welfare losses by asking a
hypothetical question regarding household willingness to pay for improved air quality.Willingness to pay for improved air quality was determined through a double bounded iterative
bidding. Based on the pilot survey and evaluation of previous studies, a starting bid of R100 was
chosen. The mean willingness to pay per household was estimated from the upper and lower
bound amount given by each household respondent. Three steps were taken to evaluate the
respondentsâ willingness to pay for improved air quality. Firstly, the Craggâs Model was used to
determine if the choice to pay and the amount that will be paid for improved air quality is onedecision
or two-decisions. A Probit Model was fitted to evaluate the factors that influence the
willingness to pay decision (whether or not to pay). Lastly, a Truncated Regression Model was
fitted to determine the factors that determine the amount that will be paid for improved air
quality as indicated by those who are willing to pay.
The empirical results revealed that the mean workdays lost and mitigating cost as a result of
illness associated with air pollution in both study areas is 3.43days and R112.27 respectively.
Health, duration of illness, age, district (Phahameng or Rocklands), mitigating cost and number
of visits to see a doctor or to pharmacy for treatment were found to be the principal factor
influencing workdays lost. High income level, duration of illness, district (Phahameng or
Rocklands), ailment (episode of air pollution related ailment), workdays lost, treatment methods
and unemployed were found to be the principal factors influencing mitigating cost. The mean
willingness to pay per household for improved air quality on a monthly basis from both study
areas is R110.59. The Craggâs Model showed that the choice to pay for improved air quality and
the amount to be paid is two separate decisions and should thus be modelled as such. Results
from the Probit Model shows that education and ailment (episode of air pollution related ailment)
are the principal factors that influence the decision of whether or not to pay. The Truncated
Regression Model indicated that the decision on how much to pay is determined by education
and high income.
The conclusion from the study is that the impact of air pollution should be seen beyond the
adverse health effect it poses. Air pollution can be reduced by creating environmental awareness
not only in the study areas but in South Africa.
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