Table 1 Comprehensive literature review.

From: The key challenges and best alternatives to environmental sustainability: a comprehensive study

Author	Regions	Test	Outcome
Linkage of UB with emissions
Khan et al. ²⁵	Industrialized economies	BPC	UB \(\rightleftharpoons\) CO₂ emissions
Prastiyo et al. ²⁶	Indonesia	ARDL	UB \(\uparrow\) CO₂ emissions CO₂ emissions \(\to\) UB
Sun & Huang ⁷⁰	30 China’s provinces	SFM	UB \(\bigcap\) CO₂ emissions
Shah et al. ¹¹	Pakistan	VECM	UB \(\bigcup\) CO₂ emissions
Wang et al. ⁷	OECD economies	D-ARDL	UB \(\bigcap\) CO₂ emissions
Khan & Su ²⁷	Newly industrialized economies	PTR	UB \(\uparrow\) CO₂ emissions
Sun et al. ²⁸	MENA economies	CUP-FM & CUP-BC	UB \(\uparrow\) CO₂ emissions
Tan et al. ²⁹	China	TM	UB \(\uparrow\) CO₂ emissions
Xie et al. ³⁰	42 BRI economies	D-KSE	UB \(\uparrow\) CO₂ emissions
Chen et al. ⁷¹	125 economies	Spatial Model	UB \(\uparrow\) CO₂ emissions
Shah et al. ⁷²	15 natural gas economies	AMG & CS-ARL	UB \(\uparrow\) CO₂ emissions
Jianmin et al. ⁷³	29 provincial regions	FE	UB \(\downarrow\) CO₂ performance
Qi et al. ⁷⁴	China	SDA model	UB \(\downarrow\) CO₂ emissions
Linkage of RE with emissions
Nguyen & Kakinaka ³⁵	107 economies	FMOLS & DOLS	RE \(\uparrow \downarrow \downarrow\) CO₂ emissions in lower, middle and higher-income countries
Saidi & Omri ³⁶	15 energy transition	FMOLS & VECM	RE \(\downarrow\) CO₂ emissions
Akram et al. ³⁷	66 developing nations	OLS and fixed effect panel quantile regression	RE \(\downarrow\) CO₂ emissions
Doğan et al. ³⁸	28 OECD economies	FMOLS & DOLS	RE \(\downarrow\) CO₂ emissions
Vo et al. ³⁹	CPTPP countries	FMOLS & DOLS	RE \(\downarrow\) CO₂ emissions
Adekoya et al. ⁴⁰	17 economies	FE	Ambiguous outcomes
Zheng et al. ⁴¹	China	PA	RE \(\downarrow\) CO₂ emissions
Yuping et al. ⁷⁵	Argentina	ARDL	RE \(\downarrow\) CO₂ emissions
Ehigiamusoe & Dogan ⁴²	Low-income countries	FMOLS, PMG and AMG	RE \(\uparrow\) CO₂ emissions
Shah et al. ⁴³	8 Asian tourist economies	CS-ARDL	RE \(\downarrow\) CO₂ emissions
Akadiri & Adebayo ⁴⁴	India	NARDL	RE \(\downarrow\) CO₂ emissions
Chen et al. ⁴⁵	China’s economy	ARIMA	RE \(\downarrow\) CO₂ emissions
Li et al. ⁴⁶	BRICS	AMG & CCE-MG	RE \(\downarrow\) CO₂ emissions
Naqvi et al. ⁷⁶	87 middle-income countries	AMG	RE \(\downarrow\) CO₂ emissions
Rahman et al. ⁷⁷	Fossil fuel consuming economies	IFE	RE \(\downarrow\) CO₂ emissions
Balsalobre-Lorente et al. ⁷⁸	32 OECD economies	Q-GMM	RE \(\downarrow\) CO₂ emissions
Linkage of Income with Emissions
Altıntaş & Kassouri ⁴⁷	14 European economies	IFE	EKC validated
Leal & Marques ⁷⁹	20 OECD economies	DKSE	EKC validated
Villanthenkodath et al. ⁴⁸	India	ARDL	EKC validated
Tenaw & Beyene ⁸⁰	SSA economies	CCE-MG & PARDL	EKC validated
Al-Mulali et al. ⁸¹	170 economies	Sys. GMM	EKC validated
Ntim-Amo et al. ^49,50	Ghana	CCR, DOLS, & FMOLS	EKC validated
Wang et al. ¹²	56 countries	MAG & PTM	EKC validated
Long et al. ⁵¹	China	B-ARDL	EKC validated
Wang et al. ⁸²	147 countries	Threshold Effect	EKC validated
Li et al. ⁸³	38 countries	PTM & PQR	EKC validated
Gupta et al. ⁸⁴	43 economies	Sys. & GMM Estimators	EKC validated
Naqvi et al. ⁵²	Pakistan	Stochastic Model	EKC validated
Linkage of NRs with emissions
Kwakwa et al. ⁵⁵	Ghana	ARDL	NRs \(\uparrow\) CO₂ emissions
Wang et al. ⁵⁶	G7	CS-ARDL	NRs \(\uparrow\) CO₂ emissions
Balsalobre-Lorente et al. ⁵⁷	EU-5 economies	CS-ARDL	NRs \(\bigcap\) CO₂ emissions
Nwani & Adams ⁸⁵	93 economies	AMG	NRs \(\uparrow\) P&C emissions
Li et al. ⁵⁸	SEA region	CS-ARDL	NRs \(\uparrow\) CO₂ emissions
Li et al. ⁸⁶	China	RE, FE, & FGLS	Cut in NRs \(\downarrow\) CO₂ emissions
Bosah et al. ⁸⁷	159 economies	CS-ARDL	NRs \(\uparrow\) CO₂ emissions
Shang et al. ⁵⁹	10 polluted economies	Q-GMM estimator	NRs \(\uparrow\) CO₂ emissions
Yu ⁸⁸	China	ARDL	NRs \(\uparrow\) CO₂ emissions
Linkage of ICT with emissions
Nguyen et al. ⁸⁹	Selected G-20 economies	QR, FE, & FMOLS	Mixed outcomes
Avom et al. ⁶³	21 SSA economies	FGLS	ICT \(\uparrow\) CO₂ emissions
Usman et al. ⁹⁰	9 Asian economies	NARDL	Mixed outcomes
Charfeddine & Kahia ⁶⁴	MENA economies	P-VAR	ICT \(\uparrow\) CO₂ emissions
Zhong et al. ⁶⁵	Chinese provinces	PTM	ICT \(\uparrow\) CO₂ emissions
Jin & Yu ⁹¹	China	LASSO Method	ICT \(\uparrow\) CO₂ emissions
Li et al. ⁹²	91 countries	Sys. GMM	ICT \(\bigcap\) CO₂ emissions
Su et al. ⁶⁰	Chinese cities	Spatial Durbin Model	ICT \(\downarrow\) CO₂ emissions
Zhang et al. ⁶²	China	Two-Way FE	ICT \(\downarrow\) CO₂ emissions
Irfan et al. ⁶¹	BRICS	GMM, AMG, & CCE-MG	ICT \(\downarrow\) CO₂ emissions
Linkage of circular economy with emissions
Gallego-Schmid et al. ⁹³	Review article	N/A	CE \(\downarrow\) CO₂ emissions
Magazzino et al. ⁶⁶	Denmark economy	Causality test	CE \(\downarrow\) CO₂ emissions
Mawutor et al. ⁶⁷	Ghana	ARDL	CE \(\uparrow\) CO₂ emissions
Ren et al. ⁶⁸	Chinese cities	DID model	Mixed outcomes
Xiao ⁶⁹	China	FAPH model	CE \(\downarrow\) CO₂ emissions

\(\ne\): Insignificant, \(\uparrow\): Increasing, \(\downarrow\): decreasing, RE: Renewable Energy Consumption, CO2: Carbon Emissions, GMM: Generalized Method of Moments, PCA: Panel cointegration analysis, FMOLS: Fully Modified Ordinary Least Square, DOLS: Dynamic Ordinary Least Square, IV-GMM: Instrumental GMM, ARDL: Autoregressive Distributive Lag model, FE: Fixed Effect, RE: Random Effect, VECM: Vector Error Correction Model, OLS: Ordinary Least Square, PA: Path Analysis, PMG: Pooled Mean Group, AMG: Augmented Mean Group, CS-ARDL: Cross Sectional ARDL, NARDL: Non-linear ARDL, EKC: Environmental Kuznets Curve, NRs: Natural resource consumption, ICT: Information and communication technology.

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Table 1 Comprehensive literature review.

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