Do industrial solid waste recycling and technological innovation promote low-carbon development in China? New insights from NARDL approach.

Recycling waste is crucial for consolidating resources and promoting sustainable development, serving a pivotal role in achieving the objectives of carbon peak and carbon neutrality. Nonetheless, most existing research has primarily focused on municipal solid waste (MSW) recycling, often neglecting the significant volume of industrial solid waste (ISW). This study aims to explore the asymmetric effects of industrial solid waste recycling and technological innovation on the low-carbon development. To this end, this study selects GDP and carbon intensity as indicators representing economic growth and environmental quality. A variable that can enhance GDP growth while reducing carbon intensity signifies its contribution to low-carbon development. By collecting data from China over the period of 1985-2020, non-linear autoregressive distributed lag (NARDL) models of GDP and carbon intensity are established to discover whether the low-carbon development can be achieved by enacting ISW recycling and technological innovation. The results show the asymmetric shocks of ISW recycling and technological innovation on economic growth and environmental quality. In the long run, both ISW recycling and technological innovation promote low-carbon development. In the short run, technological innovation proved to be detrimental to economic growth and environmental quality. This paper also highlights the inhibitory effect of the labor force on economic growth. The "pollution haven hypothesis" is supported by the finding that foreign direct investment reduces carbon intensity. Additionally, the Granger test revealed the direction of the variables' causality. Based on empirical findings, policymakers can protect the environment and create economic value simultaneously through waste recycling and technological innovation, thereby realizing low-carbon development.

Impact of energy and industrial structure on environmental quality and urbanization: evidence from a panel of BRICS countries.

Global sustainable development demands boosting renewable energy and optimizing industrial structures. This study employs a panel vector autoregressive (PVAR) model to examine the dynamic relationship between energy structure, industrial structure, environmental quality, and urbanization in the BRICS countries from 1990 to 2021. Energy structure, industrial structure, environmental quality, and urbanization cointegrate empirically. Energy mix optimization and industrial structure upgrades can improve environmental quality. Energy enhancements also supported urbanization. Accelerating industrial change could adversely impact urbanization. The impulse response results demonstrate that expanding renewable energy and tertiary industries such as financial and service boost environmental quality and urbanization. The variance decomposition investigation reveals significant "path dependence" in reducing carbon emissions and increasing urbanization. Finally, based on the findings, policy insights for enhancing environmental quality and fostering urbanization are laid out and disputed, with long-term implications for environmental managers and urban planners.

How does renewable energy, newborn birth rates, industrialization, and economic growth affect environmental quality? New evidence from 90 Belt and Road countries.

Reducing carbon emissions is a critical approach for attaining global environmental sustainability and combating climate change. To investigate how energy, population, industry, and economic structure affect environmental quality. This study collects panel data for 90 Belt and Road (B&R) nations from 1995 to 2021. For the first time, the nonlinear dynamic impacts of renewable energy, newborn birth rate, industrialization, and economic growth on carbon emissions are investigated using a threshold panel model and a panel vector autoregression (PVAR) model. According to the study's findings: (1) models 1-4 demonstrate that all structural factors have substantial threshold impacts on carbon emissions, demonstrating a nonlinear connection. (2) Carbon emissions are negatively impacted by energy structure (renewable energy) and population structure (newborn birth rate). Industrial structure (industrialization) and economic structure (economic growth), on the other hand, have a beneficial influence on carbon emissions. However, when the structural variables grow in size, their threshold effects all increase this contribution. (3) In three groups of nations with varying wealth levels, differences in the influence intensity of structural factors on carbon emissions, particularly renewable energy and economic growth, were detected. The impact of renewable energy on carbon emissions is: middle-income (MI) countries > high-income countries (HI) > low-income countries (LI). The impact of economic growth on carbon emissions is MI countries > LI countries > HI countries. Based on the findings, relevant policy recommendations are provided to the policy makers of the "B&R" countries from the perspectives of structural factors and heterogeneity. It provides certain references for the realization of global environmentally sustainable development strategies and the coordinated development of economic, social and environmental systems.

Coupling coordination between new urbanisation and carbon emissions in China.

The strategic coordination of a new urbanisation and carbon emissions (NU-CE) systems in China is essential for advancing low-carbon urbanisation and sustainable urban planning. This paper introduces an improved coupling coordination degree (CCD) model, spatial auto-correlation and other methods to evaluate past and future states of coordination. The data, which are collected from the period 2010-2019 and 30 provinces in China, demonstrate the temporal and spatial evolution characteristics of the NU-CE coupling relationship. The relevant results are fourfold. (1) The level of NU in China continues to rise, alongside significant spatial heterogeneity, which is particularly evident in the eastern coastal areas. (2) The CE subsystem fluctuates slightly, also revealing differences between the southern and northern regions, where Shanxi and Inner Mongolia have the lowest levels. (3) The NU-CE CCD in each province continuously improved during the study period, which is closely related to different development stages and geographic locations. As a result, a ladder-type pattern of gradual decline emerges from the eastern coastal region to central and western regions. (4) NU-CE CCD has significant positive spatial correlation characteristics. The high-high CCD area exhibits a tendency to shift towards the central region, and the low-low cluster area from the southwest to the northwest region. (5) Finally, the grey GM(1,1) prediction model is used to predict the CCD of 30 provinces in 2020-2024. The findings illustrate a growing state of NU-CE coordination and strengthening spatial correlations in the future. Based on the findings of this study, a series of policy suggestions for improving China's new urbanisation and carbon emissions is proposed.

Surface-Anchored Acetylcholine Regulates Band-Edge States and Suppresses Ion Migration in a 21%-Efficient Quadruple-Cation Perovskite Solar Cell.

Although incorporating multiple halogen (bromine) anions and alkali (rubidium) cations can improve the open-circuit voltage (Voc ) of perovskite solar cells (PSCs), severe voltage loss and poor stability have remained pivotal limitations to their further commercialization. In this study, acetylcholine (ACh+ ) is anchored to the surface of a quadruple-cation perovskite to provide additional electron states near the valence band maximum of the perovskite surface, thereby enhancing the band alignment and minimizing the Voc loss significantly. Moreover, the quaternary ammonium and carbonyl units of ACh+ passivate the antisite and vacancy defects of the organic/inorganic hybrid perovskite. Because of strong interactions between ACh+ and the perovskite, the formation of lead clusters and the migration of halogen anions in the perovskite film are suppressed. As a result, the device prepared with ACh+ post-treatment delivers a power conversion efficiency (PCE) (21.56%) and a value of Voc (1.21 V) that are much higher than those of the pristine device, along with a twofold decrease in the hysteresis index. After storage for 720 h in humid air, the device subjected to ACh+ treatment maintained 70% of its initial PCE. Thus, post-treatment with ACh+ appears to be a useful strategy for preparing efficient and stable PSCs.