With growing global warming issues, the association between technological innovation and environmental pollution has created significant debate in recent years. This paper examines the long-run and causal impact of technological innovation, economic growth, and renewable energy on consumption-based carbon emissions in Japan. The study utilized quarterly data spanning between 1990 and 2015. The study utilized recent econometrics techniques such as Maki co-integration, ARDL bunds test, FMOLS, DOLS, and frequency domain causality techniques. To the author's understanding, no prior studies have been conducted in Japan using consumption-based carbon emissions as a proxy of environmental degradation. Thus, this empirical analysis contributes to the literature. The findings from the ARDL bounds and Maki co-integration tests revealed evidence of co-integration among the series. The results of FMOLS and DOLS reveal that both renewable energy and technological innovation improve the environmental quality, while economic growth harms the quality of the environment. The results of the frequency-domain causality technique reveal that technological innovation, renewable energy, and economic growth can significantly predict consumption-based carbon emissions in Japan. Based on these outcomes, we suggested that Japan's government should be careful when formulating policies that trigger growth, which will have a detrimental impact on the environmental quality. Our empirical outcome also revealed that any policy that encourages renewable energy should be encouraged since it enhances environmental quality.

This paper explores long-run and causal effects of financial development, real growth, urbanization, gross capital formation and energy consumption on CO2 emissions in Thailand by utilizing recent econometric techniques. The study employs ARDL technique to examine the long and short run interconnection between CO2 emissions and the regressors. Furthermore, we employ the FMOLS, DOLS and CCR as a robustness check to the ARDL long-run estimator. The study use time-series data spanning from 1971 to 2016. The study also utilizes the wavelet coherence technique to collect information on the association and causal interrelationship among these economic variables at different frequencies and timeframes in Thailand. The study objectives are structured to answer the following questions: (a) does the selected macroeconomic indicators impact CO2 emissions in Thailand? (b) if so, why? Findings reveal; (i) Negative and insignificant link between CO2 emissions and urbanization. (ii) GDP growth affects CO2 emissions positively. (iii) The interconnection between CO2 emissions and energy usage is positive. (iv) Gross capital formation impact CO2 emissions positively. (v) Positive interconnection exists between financial development and CO2 emissions in Thailand. Additionally, the wavelet coherence result provides a supportive evidence for the ARDL long run result. Based on these findings, policy directions were suggested.

The low value of nitrogen use efficiency (NUE) (around 30%) of crop production in China highlights the necessity to adopt reasonable N managements in national scale. After the implementation of ‘National Soil Testing and Formulated Fertilization’ program in 2005, many field experiments have reported an increase of NUE for crop productions in China. This has prompted discussion regarding the extent to which NUE in crop production has been improved. Here, we analyzed the temporal and spatial changes in NUE (crop N uptake/total N input) and cumulative synthetic and non-synthetic N fertilizer recovery efficiency of crop production in China during 1980–2014, and evaluated the relationship between NUE and economic growth (purchasing power parity, PPP) at national and provincial scale. The results showed that the overall NUE of crop production in China clearly increased from 35 to 42% during 2003–2014, and an increase in NUE was further evidenced by increases in cumulative recovery efficiency of both synthetic and non-synthetic N fertilizer. The relationship between NUE and PPP can be described by an environmental Kuznets curve at the national scale, with NUE first decreasing then increasing with PPP. However, this relationship exhibited large spatial variation: 1) In economically developed (e.g., Guangdong and Zhejiang) and undeveloped provinces (e.g., Yunnan and Guizhou), NUE generally decreased and then remained at low levels (20–35%) as PPP increased. 2) In major agricultural provinces with high (e.g., Shandong and Jiangsu) or intermediate levels (e.g., Hunan and Hebei) of economic development, a pronounced increasing trend in NUE with PPP was observed. These results highlight the necessity of developing region-oriented N management strategies to further increase the NUE of crop production in China, particularly in the economically developed and undeveloped provinces.

The relationship between economic growth, governance, and environmental outcomes, particularly mismanaged plastic waste (MPW) leaking out to the ocean, has been a focal point of policy and academic debates. This study aims to understand the dynamics of income and control of corruption across different levels of MPW. Utilizing Quantile Regression models, we explore the generalized and quantile-specific relationships between the variables. The findings confirm the validity of the Environmental Kuznets Curve (EKC), revealing an initial increase in MPW with economic growth, followed by a decline after surpassing a specific economic threshold. However, the EKC is not validated for all quantiles and the shifting point may vary across the distribution. Moreover, control of corruption emerged as a significant factor in determining MPW levels, emphasizing its moderating role at the highest levels of mismanagement. This study underscores the need for synergizing economic strategies with robust environmental policies, guided by strong governance mechanisms.

This paper looks into the causal association between economic growth, CO2 emission, trade volume, and human development indicator for Brazil, Russia, India, and China (BRIC countries) during 1980–2013. Following a generalized method of moments (GMM) technique, we have found out that bidirectional causality exists between CO2 emissions and economic growth. Feedback hypothesis is supported between CO2 emissions and human development, trade volume and human development, economic growth, and human development, and CO2 emissions and trade volume. Apart from finding out the unidirectional association from trade volume to economic growth, this study also validated the existence of Environmental Kuznets curve. Empirical findings of the study substantiate that the policymakers of the BRIC nations must focus on the green energy initiatives, either by in-house development or by technology transfer. This movement will allow them to control the ambient air pollution prevalent in these nations.

To become the fastest-growing large economy in the world, India has set a target growth rate of 9%, reaching an economy of $5 trillion by 2024-25. It is an immense challenge to meet the growth target and keep the CO2 emissions under control. The present paper aims to discover the determinants for explaining CO2 emissions in India by conducting a complete decomposition analysis, where the residuals are fully distributed to the determinants for the country from 1990-2018. The analysis reveals that the biggest contributor to the rise in CO2 emissions in India is the expansion of the economy (scale effect). The intensity of CO2 and the change in the composition of the economy, which nearly move in tandem, also contribute to the rise in CO2 emissions, although more slowly. A declining energy intensity of the Indian economy is responsible for a considerable reduction in CO2 emissions. As a typical result for an upcoming economy, this paper did not find evidence for an environmental Kuznets curve. This implies that continued economic growth will lead to increased CO2 emissions.