TY - JOUR
T1 - Air quality assessment using a weighted Fuzzy Inference System
AU - Olvera-García, Miguel Ángel
AU - Carbajal-Hernández, José J.
AU - Sánchez-Fernández, Luis P.
AU - Hernández-Bautista, Ignacio
N1 - Publisher Copyright:
© 2016 Elsevier B.V.
PY - 2016/5/1
Y1 - 2016/5/1
N2 - Air pollution is a current monitored problem in areas with high population density such as big cities. In this sense, environmental modelling should be accurate in order to generate better air quality evaluations; but in consequence they are complex. Nowadays, the artificial intelligence based on heuristic methods allows assessing air quality parametres, providing a partial solution to this problem. Accordingly, this paper proposes a new evaluation model using fuzzy inferences combined with an Analytic Hierarchy Process, providing a new air quality index. Environmental parametres (PM2.5, PM10, O3, CO, NO2 and SO2) are evaluated according to toxicological levels and then, a fuzzy reasoning process assesses different air quality situations. Additionally, individual weights are computed and assigned according to the pollutant importance on the air evaluation. Finally, the model proposed considers five score stages: excellent, good, regular, bad and dangerous, based on data from the Mexico City Atmospheric Monitoring System (SIMAT). Experimental results show a good performance of the proposed air quality index against those in literature, providing better assessments when weights are assigned according to an importance level in atmosphere pollution.
AB - Air pollution is a current monitored problem in areas with high population density such as big cities. In this sense, environmental modelling should be accurate in order to generate better air quality evaluations; but in consequence they are complex. Nowadays, the artificial intelligence based on heuristic methods allows assessing air quality parametres, providing a partial solution to this problem. Accordingly, this paper proposes a new evaluation model using fuzzy inferences combined with an Analytic Hierarchy Process, providing a new air quality index. Environmental parametres (PM2.5, PM10, O3, CO, NO2 and SO2) are evaluated according to toxicological levels and then, a fuzzy reasoning process assesses different air quality situations. Additionally, individual weights are computed and assigned according to the pollutant importance on the air evaluation. Finally, the model proposed considers five score stages: excellent, good, regular, bad and dangerous, based on data from the Mexico City Atmospheric Monitoring System (SIMAT). Experimental results show a good performance of the proposed air quality index against those in literature, providing better assessments when weights are assigned according to an importance level in atmosphere pollution.
KW - Air quality assessment
KW - Analytic Hierarchy Process
KW - Artificial intelligence
KW - Fuzzy Inference System
KW - Mexico City area
UR - http://www.scopus.com/inward/record.url?scp=84963934440&partnerID=8YFLogxK
U2 - 10.1016/j.ecoinf.2016.04.005
DO - 10.1016/j.ecoinf.2016.04.005
M3 - Artículo
SN - 1574-9541
VL - 33
SP - 57
EP - 74
JO - Ecological Informatics
JF - Ecological Informatics
ER -