Parameters influencing population annoyance pertaining to air pollution.

Annoyance caused by particulate matter qualifies as a public health problem, as it can be seen as an ambient stressor causing stress, diseases and affecting the quality of life. Previous studies have shown a complex relationship between annoyance and perception of air pollution, health problems occurrences, air pollutants concentration levels and location within the urban area, which should be better investigated. The objective of this work is to identify the parameters that influences perceived annoyance caused by air pollution. Additionally, we propose the analyses of exposure-response relationship between perceived annoyance and concentration levels of particulate matter (TSP and PM10). Questionnaire-based surveys were conducted in sub regions around of the air quality monitoring stations in metropolitan area of Vitoria, Brazil. Logistic regression was used to identify the associations between qualitative questionnaire variables and air pollution expressed by PM concentrations. Results have shown that 90% of the population reports nuisance by air pollution and about 80% of respondents frequently perceived air pollution by dust. The determinants parameters and subjective factors related to particles annoyance perception can be used in order to predict air pollution impact on the studied region population. By exposure-response relationship when the concentration level of PM increases, the probability of being annoyed also grows. The results and the methodology discussed here can be very useful for planning purposes where the stakeholders usually do not have access to detailed information, especially for micro-management in a regional or city-planning level.

Deconstruction of annoyance due to air pollution by multiple correspondence analyses.

Annoyance caused by air pollution is a matter of public health as it can cause stress and ill-health and affect quality of life, among other burdens. The aim of this study is to apply the multiple correspondence analyses (MCA) technique as a differential tooling to explore relationships between variables that can influence peoples' behaviour concerning annoyance caused by air pollution. Data were collected through a survey on air pollution, environmental issues and quality of life. Face-to-face survey studies were conducted in two industrialized urban areas (Vitoria in Brazil and Dunkirk in France). These two regions were chosen as their inhabitants often report feeling annoyed by air pollution, and both regions have similar industrial characteristics. The results showed a progressive correspondence between levels of annoyance and other active variables in the "air pollution" factor group: as the levels of annoyance increased, the levels of the other qualitative variables (importance of air quality, perceived exposure to industrial risk, assessment of air quality, perceived air pollution) also increased. Respondents who reported feeling annoyed by air pollution also thought that air quality was very important and were very concerned about exposure to industrial risks. Furthermore, they often assessed air quality as horrible, and they could frequently perceive air pollution by dust, odours and decreased visibility. The results also showed a statistically significant association between occurrence of allergies and high levels of annoyance.