A simplified ozone model based on fuzzy rules generation

Ryoke, Mina; Nakamori, Yoshiteru; Heyes, C.; Makowski, M.; Schöpp, Wolfgang

doi:10.1016/s0377-2217(99)00245-3

Cited by 13 publications

(4 citation statements)

References 7 publications

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“…In the first step, since multiphase deterministic 3D modelling systems ( [29,30]) cannot be used to compute pollutant concentrations and air quality indexes, due to the required computational cost and the number of simulations needed to solve a multi-objective problem, they have been substituted by statistical surrogate models, identified processing the results of a set of Chemical Transport Models simulations ( [31][32][33]). In particular, following the methodologies presented in [34][35][36], models based on Artificial Neural Networks (ANNs), have been applied, mainly due to their features of low computational requirements, good performances and ability to reproduce non-linear functions.…”

Section: Multi-objective Model Setupmentioning

confidence: 99%

Combining a Multi-Objective Approach and Multi-Criteria Decision Analysis to Include the Socio-Economic Dimension in an Air Quality Management Problem

2019

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Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary P M 10 fractions are complex and non-linear, environmental authorities need tools to assess their plans designed to improve the air quality as requested from environmental laws. Multi-criteria decision analysis (MCDA) can be applied to support decision makers, by processing quantitative opinions provided by pools of experts, especially when different views on social aspects should be considered. The results obtained through this approach, however, can be highly dependent on the subjectivity of experts. To partially overcome these challenges, this paper suggests a two-step methodology in which an MCDA is fed with the solution of a multi-objective analysis (MOA). The methodology has been applied to a test case in northern Italy and the results show that this approach is a viable solution for the inclusion of subjective criteria in decision making, while reducing the impact of uncertain expert opinions for data that can be computed through the MOA.

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Section: Multi-objective Model Setupmentioning

confidence: 99%

Combining a Multi-Objective Approach and Multi-Criteria Decision Analysis to Include the Socio-Economic Dimension in an Air Quality Management Problem

2019

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show abstract

“…So, it is required to identify simplified models synthesizing the relationship between the precursor emissions and ozone concentrations. In literature source-receptor relationships have been described using ozone isopleths (Shih et al, 1998), or with reduced form models such as (a) simplified photochemical models, adopting semi-empirical relations calibrated with experimental data (Venkatram et al, 1994), and (b) statistical models, identified on the results of complex 3D Chemical Transport Models (Friedrich and Reis (2000), Ryoke et al (2000), Guariso et al (2004)). Therefore, all of these approaches do not consider the strategic issue due to the fact that different decisions can be taken in different times, making the optimization, essentially static.…”

Section: Introductionmentioning

confidence: 99%