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2024 | OriginalPaper | Chapter

5. Prediction of RCCCI Index Values Under Four 2030 and 2100 Scenarios

Authors : Agnieszka Karman, Urszula Bronisz, Jarosław Banaś, Andrzej Miszczuk

Published in: Regional Competitiveness Towards Climate Change

Publisher: Springer Nature Switzerland

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Abstract

The chapter presents the results of projections of regional climate change competitiveness for 2030 and 2100 in a scenario-based setting. Four scenarios were used to prepare the projections: WEM and WAM scenarios submitted by countries to the United Nations Framework Convention on Climate Change and A1 and B1 scenarios which were adapted from European Shared Socio-economic Pathways. In the chapter, the projected values for individual regions and their changes with respect to 2020 are indicated. Moreover, the chapter shows the spatial distribution of the RCCCI index and national competitiveness projections for ten EU member states.

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Footnotes
1
The relative rate of sub-index fluctuation in the region under study for a given scenario and prediction year was determined as a quotient, where the numerator was the difference between the value of the sub-index (region, scenario, year) and the reference figure—the value of the sub-index in the base year (region), and the denominator was again the reference figure—the value of the sub-index in the base year (region) in absolute terms. The relative rate of change of the sub-index was described by the following formula:
$${\Delta W}_{{S}_{{RSS}_{c}{S}_{y}}}=\frac{{W}_{{S}_{{RSS}_{c}{S}_{y}}}- {W}_{{S}_{R{S}_{2020}}}}{\left|{W}_{{S}_{R{S}_{2020}}}\right|}$$
where:
\(\text{R}\)—region,
\(\text{S}\)—sub-index, \(S\in \left[Basic, Natural, Social, Innovation, Efficiency, Sector\right]\),
\({S}_{c}\)—scenario, \({S}_{c}\in \left[WEM, WAM, A1,B1\right]\),
\({S}_{y}\)—year for the scenario, \({S}_{y}\in \left[2030, 2100\right]\),
\({W}_{{S}_{{RSS}_{c}{S}_{y}}}\)—the index (value) of a sub-index for a specific region, scenario and year,
\({W}_{{S}_{R{S}_{2020}}}\)—the index (value) of the sub-index for a specific region, in the base year (2020),
\({\Delta W}_{{S}_{{RSS}_{c}{S}_{y}}}\)—the rate of change of the sub-index for a specific region, scenario and year.
As absolute values were used in the denominators, it was possible to obtain the rate of change for the value which, if negative, indicated a decrease in the value tested compared to the reference and if positive, an increase.
Example notation:
\(-{0.31}\) [decrease by approximately 0.31; record: − 0.31]; \({0.28}\), [increase by approximately 0.28; record: + 0.28].
 
2
Due to the very high relative change in the Basic sub-index compared to the other sub-indices, the upper limit of the y-axis was limited to 25 in the two graphs (Figs. 5.1 and 5.2).
 
3
The y-axis ranges in all the graphs were unified for greater readability and comparability. This solution was also applied in the analyses below in every visualisation of analytical results obtained under the WEM, WAM, A1 and B1 scenarios.
 
4
The relative rate of change of the RCCCI index was calculated from the following formula:
$${\Delta W}_{{\text{RCCCI}}_{{RSS}_{c}{S}_{y}}}=\frac{{W}_{{\text{RCCCI}}_{{RSS}_{c}{S}_{y}}}- {W}_{{\text{RCCCI}}_{{RS}_{2020}}}}{\left|{W}_{{\text{RCCCI}}_{{RS}_{2020}}}\right|}$$
Where:
\(\text{R}\)—region,
\({S}_{c}\)—scenario, \({S}_{c}\in \left[WEM, WAM, A1,B1\right]\),
\({S}_{y}\)—year for the scenario, \({S}_{y}\in \left[2030, 2100\right]\),
\({W}_{{\text{RCCCI}}_{{RSS}_{c}{S}_{y}}}\)—index indicator (value) for a specific region, scenario and year,
\({W}_{{\text{RCCCI}}_{{RS}_{2020}}}\)—index indicator (value) for a specific region, in the base year (2020),
\({\Delta W}_{{\text{RCCCI}}_{{RS}_{c}{S}_{y}}}\)—index change rate for a specific region, scenario and year.
 
5
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
6
Classification method: Quantile; Number of classes: 3 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
7
Such a large decrease is also due to the very small value of the reference sub-index of 0.001.
 
8
Due to the very high relative change in the Social sub-index as compared to the other sub-indices, the y-axis boundaries were limited to values between − 20 and 5 (Fig. 5.11).
 
9
Due to the very high value of the change in the Social sub-index compared to the others, it was decided to limit the y-axis boundaries to values between − 15 and 25 (Fig. 5.12).
 
10
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
11
Due to the very high relative change in the Sector sub-index as compared to the other sub-indices, the lower limit of the y-axis was limited to − 20 (Fig. 5.16).
 
12
Classification method: Quantile; Number of classes: 4 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
13
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
14
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
15
Due to the very high relative change in the Basic sub-index as compared to the other sub-indices, the y-axis boundaries were limited to values between − 5 and 10.
 
16
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
17
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
18
Due to the very high relative change forecasted in the Innovation sub-index as compared to other sub-indices, the upper limit of the y-axis was limited to 10 in the two graphs (Figs. 5.41 and 5.42).
 
19
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
20
Due to the very high relative change in the Innovation sub-index as compared to other sub-indices, the upper limit of the y-axis was limited to 15 in the two graphs (Figs. 5.46 and 5.47).
 
21
Classification method: Quantile; Number of classes: 3 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
22
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home].
 
23
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home]
 
24
Classification method: Quantile; Number of classes: 5 [Tool: https://​gisco-services.​ec.​europa.​eu/​image/​screen/​home]
 
Metadata
Title
Prediction of RCCCI Index Values Under Four 2030 and 2100 Scenarios
Authors
Agnieszka Karman
Urszula Bronisz
Jarosław Banaś
Andrzej Miszczuk
Copyright Year
2024
DOI
https://doi.org/10.1007/978-3-031-68767-9_5