The efficiency level, evolution characteristics, and factors driving the green economy in all provinces and regions should be clarified to achieve high-quality economic development and meet China's “double carbon” target. This study conducted the Super-Effective Slack-Based Model considering unexpected outputs to evaluate province-level Green Economic Efficiency (GEE) analysis (including 30 provinces, autonomous regions, and municipalities directly under the Central Government) in China from 2005 to 2020. Moreover, the distribution and dynamic evolution trend of GEE development was estimated through Kernel density estimation. Besides, GEE and its factors (i.e., industrial structure rationalization [ISR], industrial structure advancement [ISA], and urbanization level [UL]) were examined using a Panel vector autoregressive model that was built in this study. As indicated by the result of this study, China's GEE level generally displayed a “U-shaped” development trend of declining, stabilizing, and then rising, whereas the overall efficiency level is low, where the national GEE average reached 0.6934. The regional GEE level exhibited a significant “ladder” distribution, with the highest level, the second level, and the lowest level in the east, the middle, and the west, respectively. The GEE level varied significantly with the province, and most of the levels were at a medium efficiency level. Notably, 60% of regions had medium efficiency in 2020. The levels of ISR, ISA, and UL play significant roles in boosting green economic growth. This study provides valuable insights into the drivers of green economic growth in China guiding policy decisions on achieving a sustainable and low-carbon economy. As China strives to fulfill its ambitious carbon reduction goals, the findings of this study highlight the significance of continuing to prioritize green economic development at the provincial level.

Increasing the popularity of distributed photovoltaic technology among Chinese residents is of great significance to achieve the dual carbon goal (emission peak and carbon neutrality). In this study, we collected 1424 questionnaire samples and used PLS-SEM for group modeling and comparative analysis of bungalow and building residents. The results show that living conditions, costs, risks of installation, maintenance, and economic efficiency are the five significant influencing factors for residents to decide whether to install a distributed residential photovoltaic equipment. Compared with building residents, bungalow residents tend to feel more concerned about the cost and risk of residential photovoltaic equipment during installation, maintenance, and use. On the other hand, bungalow residents show greater sensitivity to the corresponding photovoltaic promotion policies. By contrast, building residents pay more attention to the direct benefit created by the installation of residential photovoltaic equipment. Therefore, adopting the strategy from bungalow residents to building residents could help promote the distributed photovoltaic system progressively. As for the subsidy decline, more attention shall be paid to the progress of a gradual reduction of the subsidies. It is advisable to pay attention to integrating the upstream and downstream industry chains of the distributed photovoltaic systems, thus reducing the concern of residents about the difficulty in installing, maintaining, and protecting the distributed photovoltaic equipment. By clarifying the different impacts of promotion policies on the demand side, this study provides a practical reference for the further adjustment made to distributed photovoltaic promotion policies.