A new methodology to derive settleable particulate matter guidelines to assist policy-makers on reducing public nuisance

Publication date: June 2018
Source:Atmospheric Environment, Volume 182
Author(s): Milena Machado, Jane Meri Santos, Valdério Anselmo Reisen, Neyval Costa Reis, Ilias Mavroidis, Ana T. Lima
Air quality standards for settleable particulate matter (SPM) are found in many countries around the world. As well known, annoyance caused by SPM can be considered a community problem even if only a small proportion of the population is bothered at rather infrequent occasions. Many authors have shown that SPM cause soiling in residential and urban environments and degradation of materials (eg, objects and surface painting) that can impair the use and enjoyment of property and alter the normal activities of society. In this context, this paper has as main contribution to propose a guidance to establish air quality standards for annoyance caused by SPM in metropolitan industrial areas. To attain this objective, a new methodology is proposed which is based on the nonlinear correlation between the perceived annoyance (qualitative variable) and particles deposition rate (quantitative variable). Since the response variable is binary (annoyed and not annoyed), the logistic regression model is used to estimate the probability of people being annoyed at different levels of particles deposition rate and to compute the odds ratio function which gives, under a specific level of particles deposition rate, the estimated expected value of the population perceived annoyance. The proposed methodology is verified in a data set measured in the metropolitan area of Great Vitória, Espirito Santo, Brazil. As a general conclusion, the estimated probability function of perceived annoyance as a function of SPM has shown that 17% of inhabitants report annoyance to very low particles deposition levels of 5 g/(m²∙30 days). In addition, for an increasing of 1 g/(m²∙30 days) of SPM, the smallest estimated odds ratio of perceived annoyance by a factor of 1.5, implying that the probability of occurrence is almost 2 times as large as the probability of no occurrence of annoyance.

Graphical abstract

from #ORL-AlexandrosSfakianakis via ola Kala on Inoreader https://ift.tt/2H0ReNy