To protect the environment from any further damage, the implementation of the “smart cities” strategy supported by information and communication technologies (ICTs) is the need of the hour. Hence, this study estimates the impact of ICT and urbanization on environmental sustainability in China using the novel quantile autoregressive distributed lag (QARDL) method. The results of the QARDL model state the negative and significant impact of ICT on CO₂ emissions in China for all quantiles, implying that an increase in ICT proved to be an important factor in improving environmental quality. In contrast, the estimated coefficients of urbanization are positively significant for all quantiles. This finding sustains the idea that large-scale urbanization is detrimental to the environment because the process of urbanization is among the leading sources of carbon emissions. In the short run, the negative impact of ICT on CO₂ emissions can only be seen in higher quantiles, while the positive impact of urbanization on CO₂ emissions is confirmed for all quantiles. Lastly, the asymmetric impact of ICT and urbanization is confirmed in the short and long run with the help of Wald tests. The ICT diffusion and smart urbanization approach can help in attaining environmental sustainability targets.

Urbanization intensification seriously interferes with the supply capacity and demand level of ecosystem services (ESs); therefore, it affects the balance state of ESs. Coordination of urbanization development and ecosystem protection in the ecological economic belt is vital for ecological protection and high-quality development of the ecological economic belt. However, previous studies lacked multi-scale analysis of the impact of urbanization elements on the ESs balance index (ESBI) in the ecological economic belt. In this study, a geographically weighted regression model was employed to measure the spatial non-stationary patterns associated with the impact of urbanization elements on the ESBI at 5 km and 10 km in the Han River Ecological Economic Belt (HREEB) in China based on land use data. The main findings were shown as follows. The supply capacity and demand level of ESs in the HREEB increased from 2000 to 2020 simultaneously, while the ESBI showed a decreasing trend. In mountainous areas, the ESBIs were evidently higher than those in the plain areas. During the study period, the urbanization level in the HREEB improved evidently, and the urbanization levels of the middle and lower reaches of the Hanjiang River were relatively high. Significant spatial dependence between urbanization elements and the ESBI was identified. Urbanization had significant positive and negative impacts on ESBI, and there were significant differences among different scales. The findings of this study can act as a decision-making reference for ecological protection and high-quality development of the HREEB and can also provide a perspective for exploring the impact of urbanization on the ESBI of the ecological economic belt in other similar regions.

Green growth aims to foster economic development while ensuring environmental sustainability by optimizing resource use and reducing pollution. Despite growing attention, the nexus between forest trade, bioenergy, and green growth remains underexplored. Therefore, the main aim of this study is to investigate the impact of forest trade and bioenergy on green growth. To that end, we apply cross-sectional autoregressive distributed lag (CS-ARDL) using 33 global economies. The findings of the CS-ARDL show that forest trade helps enhance green growth both in the short- and long run. However, bioenergy significantly boosts green growth only in the long run, while the short-run estimate of bioenergy is insignificant. The estimates of the regional analysis signify that forest trade and bioenergy enhance green growth in both developed and developing economies only in the long run. Policymakers in both developed and emerging economies should focus on boosting forestry trade and promoting bioenergy production to stimulate green growth.

The coupling coordination degree (CCD) of the production-living-ecological space (PLES) functional index is an indicator of regional sustainable development potential. However, previous studies have failed to reveal the driving mechanisms of the CCD of PLES functional index on a global scale. Therefore, this study employed the CCD model to evaluate the CCD of the PLES functional index and spatial regression models to measure the heterogeneous drivers using multi-source data in 2000, 2010, and 2020. The results demonstrated that ecological spaces dominated (85%) globally, while living spaces comprised the smallest share (3%). The ecological functional index was higher than the production and living functional indices. Further analyses revealed that topographic factors were the main restricting factors for PLES; the proportion of production and living spaces decreased with increasing altitude and slope, whereas ecological spaces showed the opposite trend. The global CCD values of the PLES functional index in 2000, 2010, and 2020 were 0.186, 0.189, and 0.198, respectively, showing an increasing trend. High CCD was generally observed in areas with dense population and industry where human activity systems interact with natural ecosystems. The formation of the CCD of the global PLES functional pattern results from the joint action of natural and socioeconomic factors, with pronounced spatial heterogeneity. Our findings can help optimize global territorial space utilization, improve territorial space utilization efficiency, and realize global sustainable development goals.

Worldwide, the development of massive hydropower projects is becoming more common, especially when it comes to attempts to mitigate environmental degradation and increase a nation’s energy capacity. People affected by projects (PAPs) are forced to relocate in order to support large-scale development initiatives, which puts their lives and livelihoods at jeopardy. In comparison to the value of infrastructure development, which is mostly reaped by distant stakeholders, it comes at a high cost. In relation to CSR/resettlement and rehabilitation programs carried out by construction corporations in Pakistan’s hydropower development, this study on the quality-of-life (QoL) and happiness indicators of PAPs is being conducted. The analysis of factors affecting happiness and other aspects of quality-of-life indicators, including job and livelihood opportunities, housing, health, infrastructure, social interactions, environmental sustainability, inclusion, equity, and diversity, is the goal of this study. Using a questionnaire survey approach, data were directly gathered from PAPs, and about 424 replies were obtained to help with the model’s development. Structural equation modelling has been applied in conjunction with multivariate statistical analysis to analyse data. The outcome demonstrates the essential connections between the concepts that were taught in light of human, social, environmental, physical, and economic problems. The results also show that project supporters’ relocation and rehabilitation efforts fell short of what was needed to improve the quality of people’s lives. As a result, a conceptual framework specifically tailored to the hydropower construction region has been created and verified to provide PAPs with a high-quality living environment.