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In light of the carbon neutrality goals set post-Paris Climate Conference (COP21), this study delves into the relationship between green technology innovations, energy consumption, and CO2 emissions in China, spanning the period of 1990 to 2021. The objective of this paper is to creatively present the idea of a low-carbon digital economy from the viewpoint of digital technology. Utilizing the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) model, we scrutinize this relationship, employing unit-root testing to verify the integrative attributes of the variables, inclusive of structural break data. Further analysis using the bootstrap Autoregressive Distributed Lag (ARDL) bound testing method corroborates the relationship between these key variables. The study reveals unidirectional co-integration over time among green technology innovations, renewable and non-renewable energy, per capita income, population, and CO2 emissions as per the Granger causality test. Interestingly, our findings suggest that while green technology innovation, per capita income, and renewable energy contribute to the reduction of CO2 emissions, non-renewable energy consumption and population growth exacerbate them. These insights offer valuable guidance for policymakers in formulating comprehensive strategies to enhance environmental quality through the promotion of renewable energy and green technology innovations, with a specific emphasis on the Chinese context. [ABSTRACT FROM AUTHOR]

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In the Paris Agreement, there are targets set up for 2100 to be well below 2 °C. A more ambitious target of 1.5 °C also appears in the agreement. In order to address whether this target is achievable or not, studies about the 1.5 °C target's emission pathway are essential. Recently a few studies have presented modelling results of the global emission pathway for the 1.5 °C target. This paper presents an analysis for China under the global 1.5 °C pathway and budget, by looking at key options to go beyond the 2 °C target pathway. Similar to the global emission pathway, China's CO2 emissions have to be reduced quickly and reach zero emission between 2050 and 2060. China's energy system needs to make a rapid transition to much greater reduction in fossil fuel use from now on. End-use sectors need to increase electricity use significantly. Power generation will achieve negative emission before 2050. CCS will be widely used, and biomass energy with CCS (BECCS) must be adopted on a large scale by 2040. This is doable in China, but very near-term changes in policy are needed to make such a pathway happen. [ABSTRACT FROM AUTHOR]

In the wake of the Paris agreement, the adoption of green innovation practices has received substantial attention throughout the world. The consumers, manufacturers, governments, and communities have started realizing the severity and intensity of environmental hazards and climate change. The manufacturing sector is one of the leading industrial waste producers and contributors to environmental pollution, posing a threat to environmental sustainability. The adoption of green innovation practices in the manufacturing sector is indispensable to ensure environmental sustainability. However, it is pivotal to identify, assess, and evaluate the green innovation aspects and sub-aspects with the perspective of sustainability performance indicators in the manufacturing industry. This study services this purpose and proposes a hybrid multi-criteria decision-making (MCDM) by combining the fuzzy analytical hierarchy process (FAHP) and fuzzy technique for order of preference by similarity to ideal solution (FTOPSIS) to analyze the effects of green innovation aspects with sustainability performance of the manufacturing industry. The authors identify six green innovation aspects (criteria), twenty-four sub-aspects (sub-criteria), and three sustainability performance indicators (alternatives) for the manufacturing industry in China. The FAHP method indicates that green managerial innovation, green product innovation, and green technological innovation are the most influential aspects of implementing green innovation practices. Further, the FTOPSIS technique reveals that environmental performance is the most suitable sustainability performance indicator in adopting green innovation practices in the garment manufacturing industry of China. This research provides support to the managers and policymakers in understanding the green innovation practices in promoting sustainable development in the manufacturing industry. [ABSTRACT FROM AUTHOR]