Hao Chen

The pursuit of sustainable development, particularly the mitigation of climate change (SDG 13), necessitates a thorough understanding of the environmental consequences of international trade. The form and pattern of international trade have changed with the rise of preferential trade agreements. The following important question arises: how do preferential trade agreements affect the transfer of trade-embodied carbon emissions? This study establishes a comprehensive bilateral trade database and uses a staggered difference-in-differences model to empirically examine how preferential trade agreements affect embodied carbon emissions. Furthermore, this study explores the underlying mechanisms and investigates heterogeneous effects in diverse contexts. The key findings of this study are as follows. (1) The signing of preferential trade agreements between bilateral trading partners helps reduce the level of carbon embodied in exports. (2) This reduction is achieved by improving production efficiency and facilitating technological spillovers, thereby reducing the carbon footprint associated with export activities. (3) The level of development of bilateral trading countries and the strength of environmental regulations play a role in the heterogeneous impact of preferential trade agreements on embodied carbon emissions. These findings provide critical empirical evidence for designing PTAs that not only facilitate trade but also actively contribute to global climate action and the achievement of broader sustainability objectives.

1. Climate change is among the most urgent challenges confronting global sustainable development in the 21st century. Its far-reaching consequences – from extreme weather events and ecological degr...

The existence of interprovincial embodied carbon transfer not only makes it difficult to achieve carbon emission reductions but also exacerbates the inequity, inefficiency, and high costs of interprovincial carbon emission reduction rights and responsibilities. This paper uses multi-regional input–output analysis (MRIOA) to measure the interprovincial embodied carbon transfer in 2017, obtains the net carbon transfer between 30 provinces (municipalities and autonomous regions) and eight regions in 2017, and accounts for the interprovincial carbon compensation amount based on the carbon price in the national carbon market. This study finds that carbon transfer from economically developed provinces to less developed provinces still exists in China, and the overall distribution shows a spatial transfer pattern from south to north and from east to west, with the northwestern region bearing most of the carbon emission pressure for which it should receive corresponding financial compensation. As part of the process to achieve the “dual carbon” target, appropriate emission reduction policies should be formulated according to the characteristics of provincial carbon transfer and the principle of “who benefits, who compensates”, and economically developed regions should give corresponding financial or technical compensation to less developed regions based on net carbon transfer. Compensation and support should be given to less developed regions based on net carbon transfer to prevent further regional development imbalances.

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.

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.

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.

Exploring the low-carbon energy transformation pathway is vital to coordinate economic growth and environmental improvement for achieving China’s carbon peak target. Three energy-target scenarios are developed in this paper, considering the targets of energy structure, electrification rate, and carbon mitigation towards 2030 announced by the Chinese government. A dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine the economic and environmental effects under different pathways of long-term low-carbon transformation. It detects that China’s energy structure would substantially transfer to the low-carbon and clean one, whereas CO₂, SO₂, and NO_X emissions in 2020–2030 would vastly abate along with all three energy-target scenarios. Different pathways would produce varying positive impacts on China’s macro-economy and achieve the different extent of double dividend effects. It is highly conceivable for China to peak its carbon emission at 12.4 GtCO₂ by 2028 if it serves the comparatively more stringent low-carbon transformation pathways.

Achieving low-carbon energy transformation is vital for coordinating economic growth and environmental improvement to satisfy the carbon emissions peak and carbon neutrality targets. Existing studies, however, have been dominated by the mere exploration of the low-carbon transformation pathway with little consideration of the importance of energy substitution in low-carbon transformation. Doing so is believably unable to gain the double dividend effect for the economy and environment. Accordingly, this paper develops three energy-target scenarios, taking into account energy structure, electrification level, and carbon mitigation targets by 2030 announced by the Chinese government. A dynamic multi-sectoral computable general equilibrium model, CHINAGEM, is employed to examine the economic and environmental effects under different pathways of long-term low-carbon transformation. Firstly, we detect that China's primary energy consumption and electricity production structure would substantially transfer to low-carbon and clean along with all three energy-target scenarios. Secondly, due to the anticipated decline of fossil energy consumption, especially coal consumption, China's CO₂, SO₂, and NO_X emissions in 2020-2030 would also possibly vastly abate with all the scenarios. Besides, it is highly conceivable for China to achieve its peak carbon emission of 12.4 GtCO₂ in 2028 if it serves the comparatively more stringent low-carbon transformation pathways. Lastly, different pathways would also produce varying positive impacts on China's macro-economy and achieve the different extent of double dividend effects. The research concludes with a recommendation of tentative improvement policies towards low-carbon transformation under the carbon peak and carbon neutrality goals, including promoting energy substitution, renewable energy development, and low-carbon technologies.

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.