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China is the largest total pollution emitter country on the globe and a vast literature has investigated the environmental Kuznets curve (EKC) hypothesis in China. Thus, we aim to review empirical studies on the testing of the EKC hypothesis using different pollution proxies and area samples in China. The EKC hypothesis can be validated by establishing an inverted U-shaped or an N-shaped relationship between pollution and economic growth. In this review of the Chinese literature, the validity of the EKC hypothesis is found more often than its absence. In comparison, a higher proportion of the studies validated the EKC hypothesis using global pollution proxies compared with local pollution proxies. Moreover, a greater percentage of the studies substantiated the EKC hypothesis using Chinese provincial and city-level data compared with aggregate national data. To validate these findings, we applied logistic regression, and the chance of the validity of the EKC hypothesis was found to be 5.08 times higher than the absence of the EKC if a study used a global pollution proxy. Moreover, the chance of the existence of the EKC hypothesis was found to be 4.46 times higher than the nonexistence of the EKC if a study used Chinese provincial, city, sectoral, or industrial data.

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Purpose For India, with its low agricultural productivity and huge population, land acquisition has always been a serious policy challenge in the installation of land-intensive power projects. India has experienced a large number of projects getting stalled because of land conflict. Yet, there is a paucity of literature pertinent to India that tries to estimate future land requirements taking into consideration of land occupation metric. Design/methodology/approach In the present study, the dynamic land transformation and land occupation metrics of nine energy sources, both conventional and renewable, are estimated to further determine the magnitude of land requirement that India needs to prepare itself to fulfil its Intended Nationally Determined Contribution (INDC) commitments. This is illustrated through two different scenarios of energy requirement growth rates, namely, conservative and advanced. Findings This analysis suggests that, while nuclear energy entails the lowest dynamic land transformation when land occupation metric is taken into account, waste to energy source possesses least land requirement, followed by coal-fired source. Hydro energy source has highest requirement both in terms of dynamic land transformation and land occupation. It is also seen that land requirement will be 96% and 120% more in INDC scenario than business as usual (i.e. if India continues with its current share of renewables in its energy portfolio in 2030) considering a conservative and an advanced growth rate, respectively. Research limitations/implications Some policy recommendations are provided that may aid policymakers to better address the trade-off between clean energy and land and incorporate it into policy planning. This study has not been able to consider future technical efficiency improvement possibilities for all energy sources, which can be incorporated in the proposed framework for further insight. Originality/value This paper provides a framework for estimation of future land requirement to fulfil India’s INDC energy plans which is not available in existing literature. The authors confirm that this manuscript is an original work.