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Natural gas supply cuts and searching alternatives in Germany: A disaggregated level energy consumption analysis for environmental quality by time series approaches

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Abstract

By considering the search for alternatives against Russia’s natural gas supply cuts, this study explores the impact and causality of disaggregated level energy consumption indicators on environmental quality. Hence, the study investigates Germany, which is the leading economy in Europe and highly dependent on Russia’s natural gas supply, by using carbon dioxide (CO2) emissions as the environment indicator, including annual data from 1970 to 2021, and applying novel time series approaches. In the empirical examination, Granger causality-in-quantiles (GCiQ), quantile-on-quantile regression (QoQR), and multivariate adaptive regression splines (MARS) are applied as base models while quantile regression (QR) and dynamic ordinary least squares (DOLS) are used for robustness. The empirical findings show that (i) there are causal impacts of disaggregated level energy consumption indicators on CO2 emissions; (ii) renewable energy and hydroelectricity consumption have a decreasing impact, whereas natural gas, coal, and oil energy consumption have an increasing impact on CO2 emissions; (iii) although nuclear energy has been discussed as a potential alternative, nuclear energy does not have a significant impact in decreasing CO2 emissions; (iv) natural gas consumption has an interaction with renewable energy, hydroelectricity, and coal energy consumption; (v) the power of disaggregated level energy consumption indicators on CO2 emissions vary according to quantiles, thresholds, and interactions between energy consumption indicators; (iv) alternative models validate robustness of the results obtained. Thus, the results imply that the most appropriate alternative is coal energy consumption in the short-term and renewable energy consumption in the long-term to compensate for Russia’s natural gas supply cuts, whereas nuclear energy consumption is not a real alternative for Germany.

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Data availability

Data will be made available on request.

Abbreviations

ADF:

Augmented Dickey-Fuller

AMG:

Augmented Mean Group

ARDL:

Autoregressive Distributed Lag

B-ARDL :

Bootstrap ARDL

BDS:

Broock, Scheinkman, Dechert, and LeBaron

BFGCiQ:

Bootstrap Fourier Granger Causality-in-Quantiles

BP:

British Petroleum

CCR:

Canonical Cointegration Regression

CO2 :

Carbon Dioxide

COP:

Conference of Parties

CR:

Cointegration Regression

CS-ARDL:

Cross-Sectional ARDL

D-ARDL:

Dynamic ARDL Simulations

DH:

Dumitrescu Hurlin

DOLS:

Dynamic Ordinary Least Squares

EF:

Ecological Footprint

EU:

European Union

FMOLS:

Fully Modified OLS

GC:

Granger Causality

GCiQ :

Granger Causality-in-Quantiles

GCV:

Generalized Cross-Validation

IEA:

International Energy Agency

KRLS:

Kernel-Based Least Squares

LCF:

Load Capacity Factor

MARS:

Multivariate Adaptive Regression Splines

ML:

Machine Learning Algorithms

PP:

Phillips-Perron

Q-ARDL :

Quantile ARDL

QoQR:

Quantile-on-Quantile Regression

QR:

Quantile Regression

SVAR:

Structural Vector Autoregressive Model

SW:

Shapiro-Wilk

TVAR:

Threshold Vector Autoregression

USA:

United States of America

VECM:

Vector Error Correction Model

WC:

Wavelet Coherence

WLMC:

Wavelet Local Multiple Correlation

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Mustafa Tevfik Kartal: The design of the study, Conceptualization; Methodology; Data Collection; Econometric Analysis; Writing—original draft; Writing—review & editing; Serpil Kılıç Depren: Writing—original draft; Fatih Ayhan: Writing—original draft.

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Kartal, M.T., Kılıç Depren, S. & Ayhan, F. Natural gas supply cuts and searching alternatives in Germany: A disaggregated level energy consumption analysis for environmental quality by time series approaches. Environ Sci Pollut Res 30, 93546–93563 (2023). https://doi.org/10.1007/s11356-023-28959-y

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