Emissions in Austria in 10 air pollutants divided by the ratio between the gross value added of manufacturing and the gross value-added sourced from all economic activities (years 2008-2015)

Description

The dataset is provided by the AEA accounts (Air Emissions Account) collected yearly by EUROSTAT for the seven-year period 2008-2015. AEA accounts report emissions assigned to the country according to the residence principle (i.e. the residence of the operator causing the emission). The list of pollutants included in the analysis embraces 10 air pollutants that are particularly harmful for human health and environmental balance when highly concentrated in the atmosphere (see Caravaggio et al. 2019)

Usage

data(Austria)

Details

Caravaggio, N., Caravella, S., Ishizaka, A., & Resce, G. (2019). Beyond CO2: a multi-criteria analysis of air pollution in Europe. Journal of Cleaner Production.

Author(s)

Nicola Caravaggio, Serenella Caravella, Alessio Ishizaka, Giuliano Resce, Francesco Vidoli

References

https://doi.org/10.1016/j.jclepro.2019.02.115

Examples

data(Austria)

Preference Ranking Organization METHod for Enrichment of Evaluations

Description

Functions which can be used to support the Multicriteria Decision Analysis (MCDA) process involving multiple criteria, by PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluation)

Usage

PROMETHEE(dataset, PreferenceF,PreferenceT,IndifferenceT,Weights,Min_Max,S_Gauss)

Arguments

Details

Thanks are extended to Salvatore Greco, Alessio Ishizaka, and Gianpiero Torrisi for helpful comments

Value

Author(s)

Giuliano Resce, Menelaos Tasiou, Francesco Vidoli

Examples

# Dataset
dati<-as.data.frame(cbind(c(10,25,4,2),
                          c(250000,270000,320000,350000),
                          c(3,4,2,2),
                          c(20,10,15,7)))

colnames(dati) = c("Distance.to.work","Price","Bedrooms","Age")


# PreferenceF
PreF<-as.data.frame(rbind(c("Gaussian","Linear","V-shape","Level"),
                     c("Gaussian","Linear","V-shape","Level"),
                     c("Gaussian","Linear","V-shape","Level"),
                     c("Gaussian","Linear","V-shape","Level")))
colnames(PreF) = c("Distance.to.work","Price","Bedrooms","Age")


# PreferenceT
PreT<-as.data.frame(cbind(c(2,2,2,2),
                          c(50000,50000,50000,50000),
                          c(2,2,2,2),
                          c(5,5,5,5)))
colnames(PreT) = c("Distance.to.work","Price","Bedrooms","Age")


# IndifferenceT
IndT<-as.data.frame(cbind(c(1,1,1,1),
                          c(10000,10000,10000,10000),
                          c(0,0,0,0),
                          c(2,2,2,2)))
colnames(IndT) = c("Distance.to.work","Price","Bedrooms","Age")


#Weights
Weig<-as.data.frame(cbind(c(0.25,0.25,0.25,0.25),
                          c(0.25,0.25,0.25,0.25),
                          c(0.25,0.25,0.25,0.25),
                          c(0.25,0.25,0.25,0.25)))
colnames(Weig) = c("Distance.to.work","Price","Bedrooms","Age")


# Min_Max
MiMa<-as.data.frame(cbind(c("min","min","min","min"),
                          c("min","min","min","min"),
                          c("max","max","max","max"),
                          c("min","min","min","min")))
colnames(MiMa) = c("Distance.to.work","Price","Bedrooms","Age")


#S_Gauss
gauss<-as.data.frame(cbind(c(2,2,2,2),
                          c(0,0,0,0),
                          c(0,0,0,0),
                          c(0,0,0,0)))
colnames(gauss) = c("Distance.to.work","Price","Bedrooms","Age")


###############################

PF = PROMETHEE(dati, PreF,PreT,IndT,Weig,MiMa,gauss)

###############################

PCA_UNIC <- prcomp(PF$UnicriterionNetFlows,center = TRUE,scale. = TRUE)
GAIA=predict(PCA_UNIC)[,1:2]
rownames(GAIA)=rownames(dati)
print(GAIA)

Preference Ranking Organization METHod for the Enrichment of Evaluations with Optimal Weights

Description

Functions which can be used to support the Multicriteria Decision Analysis (MCDA) process involving multiple criteria, by a specific tool allowing joining the consolidated procedure usually employed for environmental evaluation (PROMETHEE), with a more flexible weighing process inspired by DEA

Usage

PROMETHEE_OW(dataset,PreferenceF,PreferenceT,IndifferenceT,Weights,Min_Max,S_Gauss,dir)

Arguments

Details

Caravaggio, N., Caravella, S., Ishizaka, A., & Resce, G. (2019). Beyond CO2: a multi-criteria analysis of air pollution in Europe. Journal of Cleaner Production.

Value

Author(s)

Giuliano Resce, Menelaos Tasiou, Francesco Vidoli

Examples

data(Austria)

PreferenceF= matrix("Level",nrow(Austria),ncol(Austria) )
PreferenceT=matrix(0,nrow(Austria),ncol(Austria) )
IndifferenceT=matrix(0,nrow(Austria),ncol(Austria) )
Weights=matrix(1,nrow(Austria),ncol(Austria) )
Min_Max=matrix("min",nrow(Austria),ncol(Austria) )
S_Gauss=matrix(0,nrow(Austria),ncol(Austria) )

PF=PROMETHEE_OW(Austria, PreferenceF,PreferenceT,IndifferenceT,Weights,Min_Max,S_Gauss,
                "Optimistic")
PF$Res
PF=PROMETHEE_OW(Austria, PreferenceF,PreferenceT,IndifferenceT,Weights,Min_Max,S_Gauss,
                "Pessimistic")
PF$Res