Focusing on the Asia-Pacific region and the concept of inclusive green growth, this paper designs a four-dimensional analysis framework of economic prosperity, social inclusion, resource utilization, and environmental sustainability. It constructs a scientific and reasonable inclusive green growth indicator system for the Asia-Pacific region. In order to make the research results more robust, the research method mainly uses factor analysis, supplemented by clustering method and entropy method to evaluate and cross-validate the inclusive green growth level of 37 countries and regions in the Asia-Pacific region. The study finds that the level of inclusive green growth in the Asia-Pacific region is highly affected by the country’s economic development level. The latent heterogeneity in the distinct development stages of various countries explains why the in-region countries differ vastly regarding their inclusive green development levels. The inclusive green growth indicator system integrates the availability, accuracy, and standardization of data in selecting indicators, making the measurement results more referentially valuable. It helps grasp the actual state of inclusive green growth in the Asia-Pacific region. The paper summarizes the policy suggestions to promote inclusive green growth in the Asia-Pacific region, involving accelerating economic development and institutional improvement, and reinforcing regional cooperation in the Asia-Pacific area for elevating the overall regional inclusive green transformation.

China has initiated various dedicated policies on clean energy substitution for polluting fossil-fuels since the early 2010s to alleviate severe carbon emissions and environmental pollution and accelerate clean energy transformation. Using the autoregressive integrated moving average (ARIMA) regression, we project the potentials of substituting coal and oil with clean energy for different production sectors in China toward the year 2030. Based on the projections, a dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine: the impacts of future clean energy substitution on China’s energy production, outputs of non-energy sectors, macro-economy, and CO₂ emissions. First, we found that most production sectors are projected to replace polluting fossil-fuels with clean energy in their terminal energy consumption in 2017–2030. Second, clean energy substitution enables producing green co-benefits that would enable improvements in energy production structure, reductions in national CO₂ emissions, and better real GDP and employment. Third, technological progress in non-fossil-fuel electricity could further benefit China’s clean and low-carbon energy transformation, accelerating the reduction in CO₂ emissions and clean energy substitution. Furthermore, the most beneficiary are energy-intensive and high carbon-emission sectors owing to the drop in coal and oil prices, while the most negatively affected are the downstream sectors of electricity. Through research, various tentative improvement policies are recommended, including financial support, renewable electricity development, clean energy utilization technology, and clean coal technologies.

China’s government has enforced a series of renewable energy policies to promote renewable energy development and achieve the dual decarbonization goals. However, there exists great disparity in previous studies on the effectiveness and suitability of renewable energy policies in abating carbon emissions. This study employs a dynamic general equilibrium model and assesses the effectiveness and trade-offs of renewable energy policies in achieving the dual decarbonization goals by 2060 in China. These policies include carbon market (CRP), the reduction of feed-in tariffs (FIT), the reduction of fossil fuel subsidies (FSB), the reduction of renewable energy costs (REC), resource taxes (RTX), and renewable portfolio standards (REP) as well as the mix of these policies. We find that renewable energy policies together could abate China’s CO₂ emissions in 2060 by 2.57 billion tons, but their effectiveness is very different. The REC would have the greatest effectiveness in abating CO₂ emissions, followed by REP and CRP. Renewable energy policies would cause relatively slight damage to China’s GDP, with the exception of the REC (raising GDP by 1.1713%). Regarding trade-offs, most policies will sacrifice China’s internal and external demand but benefit employment. Renewable energy policies will effectively promote the low-carbon transformation of China’s energy structure.

The increasing amount of waste produced has been a challenge for human health and the environment, causing a call for effective waste management measures in which household waste separation is of great significance. Although an expanding body of literature has examined the impact of social capital on individual waste-separation behavior, few studies have explicitly discussed the endogeneity problem and the influence mechanisms. Accordingly, our study investigates the effect of social capital on waste-separation behavior and corresponding mechanisms using a national survey dataset of China. The study also reveals the heterogeneity of the influence of individual characteristics on waste-separation behavior. Our results demonstrate that social capital casts a significant positive impact on waste-separation behavior, providing opportunities for individuals’ social learning and strengthening the reputation effect. The heterogeneous effects of social capital reveal that women, higher-educated individuals, and political party members present better waste-separation behavior. Besides, the impact of social capital varies between urban and rural areas and among different age groups. Our study provides empirical evidence for policy making of household waste-separation management in developing countries from the perspective of informal institutions.

China’s logging ban policy has profoundly transformed the forestry industry, creating substantial impacts for forestry-worker households. Empirical evidence is needed to examine whether and how severe the transition policy produces vulnerability and relative poverty for the affected households. This paper samples forestry-worker households from the Greater Khingan Mountains state-owned forest region as the study subjects to evaluate their household vulnerabilities with the LVI approach proposed by IPCC. This study computes the relative poverty scores of the families and further identifies the relationships between the selected household’s socio-economic factors and the estimated vulnerability and poverty scores with OLS regression. This study derives a sleuth of valuable points. (1) The majority of the forestry-worker households have had to suffer downsized, vulnerable livelihoods with escalated relative poverty due to the policy’s impact. (2) Poverty closely connects with vulnerability, where the more impoverished the household, the more vulnerable it is. Poverty is, however, not the only factor affecting household vulnerability. Other factors, particularly of public and social-financial factors, are interconnected with poverty and, thus, compound the vulnerability issue. (3) Factors, e.g., family size, age and gender of household head, bank deposits, and life and job satisfaction, which are typically very beneficial for improving family vulnerability and poverty. (4) Regular financial assistance programs, particularly the commonly-trusted one-off household compensation program, might not provide solid support for addressing long-term household vulnerability and poverty. This study contributes to a broader understanding of household vulnerability and relative poverty for improved policy and program development addressing forestry workers and household vulnerabilities.