Symphony of sustainability: how technology similarity impacts international trade patterns in environmental goods.

The global consensus on sustainable development and environmental cooperation has prompted the promotion of trade in environmental goods (EGs) for green growth. This study delves into the diversity of EGs trade patterns, using decomposed environmental technology similarity indicators to reveal the technological drivers. Linking innovation indicators to trade performance in EGs provides new insights into the determinants of inequality in environmental governance cooperation. Based on an extended gravity model, we empirically analyze their impact on bilateral EGs trade flows among 176 countries over the period 2002-2019. The study finds that (1) the global EGs trade network presents a "core-periphery" structure, with increased network density and participation of developing countries. (2) Technology similarity contributes significantly to EGs trade. Compared to competition, technology complementarity has a greater impact on EGs trade flows. (3) The influence of technology similarity varies across trade patterns and product complexity explains the mechanisms, with technology complementarity promoting more trade in high-complexity products, mainly concentrated in the trade from Northern countries, while technology competition greatly promotes the export of low-complexity products from the South. (4) Technology similarity helps to overcome information barriers in EGs trade, and its trade-enhancing effects exhibit geographical regionalization. The findings offer empirical evidence on the technological drivers of EGs trade and provide policy implications for fostering inclusive global environmental governance and enhancing the competitive advantages of Southern countries, fostering more opportunities for green growth.

Exploring the effect of emission trading system on marginal abatement cost-based on the frontier synthetic difference-in-differences model.

Evaluating the cost-effectiveness of emission trading system (ETS) will explore how to control the total emission amount while minimizing the economic cost. Most related studies employ the difference-in-differences (DID) and multi-period DID models. However, this research highlights the superiority of construction technique and estimation results in the synthetic DID model, and applies it to a new scenario for evaluating the cost-effectiveness of China's pilot ETS. From the construction technique, the synthetic DID model synthesizes more desirable control groups and allows more flexibility in matching treatment units with extreme values by setting weight combinations and intercept terms. From the estimation results, the treatment effects are considered more reliable because ideally satisfy the parallel trend assumption. Specifically, the synthetic DID model indicated that the pilot ETS effectively reduced the marginal abatement cost (MAC) by 24.39%, whereas the traditional DID and multi-period DID models may have overestimated the policy effects by 98.48% and 71.09%. The main reason was the MAC has shown a downward trend before the policy implementation. Moreover, the estimation results of heterogeneity analysis and mechanism test in different models were also different. The synthetic DID model integrates the strengths of the DID model and synthetic control method (SCM), making a methodologically grounded contribution to the existing policy evaluation system.

Gone with the epidemic? The spatial effects of the Covid-19 on global investment network.

The outbreak of Covid-19 epidemic has a prolonged impact on global economic activities. In recent years, many scholars have been motivated to estimate the effects of Covid-19 shock on global foreign direct investment (FDI). However, existing studies have not paid enough attention to the spillover effects caused by the epidemic. Although few academic works have explored the geographic-neighboring spillover effects of epidemic shock on global investment, we further extent the understanding of the spillover effects in an economic network. On the basis of country-month greenfield FDI panels, we construct a spatial Durbin model, and figure out that Covid-19 shock may have positive FDI spillover effects in an economic network via global FDI transfers. Furthermore, we find that such spillovers are greatly conditioned by country-level network position and institutional ties among nations. Our research suggests that global FDI transfers may partly offset economic-adverse effects of the Covid-19 shock. While global countries, especially those in the Global South, should be more closely embedded in the global investment network in such an uncertain environment.

How Does Urban Sprawl Affect Public Health? Evidence from Panel Survey Data in Urbanizing China.

This study takes urbanizing China as the research object, employs data from three follow-up surveys conducted by the Harmonized China Health and Retirement Longitudinal Study, and examines the effects of urban sprawl on public health from physical and mental health perspectives. Although urban sprawl does not necessarily increase the risk of each specific type of disease or psychological feeling, it has a significant impact on overall physical and mental health. Further analysis reveals significant heterogeneity in the effects of urban sprawl on the physical and mental health of different groups. Specifically, urban sprawl is detrimental to the physical health of males and females, but only has negative impact on the mental health of females. Younger groups are more vulnerable to physical and mental health damage from urban sprawl relative to middle-aged and older groups. In addition, urban sprawl has a significant negative impact on the health of the low-education group but a very limited impact on the health of the high-education counterpart. From an income perspective, however, the preference for suburban housing among middle- and high-income groups makes their health more vulnerable to the negative effects of urban sprawl than low-income groups living in urban centers.

Provincial and sector-level material footprints in China.

High-income countries often outsource material demands to poorer countries along with the associated environmental damage. This phenomenon can also occur within (large) countries, such as China, which was responsible for 24 to 30% of the global material footprint (MF) between 2007 and 2010. Understanding the distribution and development of China's MF is hence critical for resource efficiency and circular economy ambitions globally. Here we present a comprehensive analysis of China's MF at the provincial and sectoral levels. We combine provincial-level input-output data with sector- and province-specific trade data, detailed material extraction data, and the global input-output database EXIOBASE. We find that some provinces have MFs equivalent to medium-sized, high-income countries and limited evidence of material decoupling. Lower-income regions with high levels of material extraction can have an MF per capita as large as developed provinces due to much higher material intensities. The higher-income south-coastal provinces have lower MF per capita than equally developed provinces. This finding relates partly to differences in economic structure but indicates the potential for improvement across provinces. Investment via capital formation is up to 4 times more resource-intensive than consumption and drives 49 to 86% of provincial-level MFs (the Organisation for Economic Co-operation and Development average is 37%). Resource-efficient production, efficient use of capital goods/infrastructure, and circular design are essential for reductions in China's MF. Policy efforts to shift to a high-quality development model may reduce material intensities, preferably while avoiding the further outsourcing of high-intensity activities to other provinces or lower-income countries.

Direct Energy Consumption Associated Emissions by Rural-to-Urban Migrants in Beijing.

Hundreds of millions of rural residents have migrated to cities in China in recent years. Different lifestyles and living conditions lead to substantial changes in their household energy. Here, we present the result of a survey on direct household energy use of low-skilled rural-to-urban migrants in Beijing. The migrants moved up the energy ladder immediately after arriving in the city by replacing biomass fuels with coal, electricity, and liquefied petroleum gas. After the original shift, pattern of household energy use by the migrants has not changed much over decades, likely due to the long-existing household registration system (Hukou). As a result, the mix of energy types used by the rural-to-urban migrants were different from those by long-term urban residents, although total quantities were similar. Shifting from biomass fuels to coal, the migrants emitted 2.4 times more non-neutral CO2 than rural residents and 14% more than urban residents. The migration also resulted in significant increase in emissions of SO2 and mercury but dramatic decreases in some incomplete combustion products including particulate matter. All these changes have significant implication on air quality, health, and climate considering the scale of urbanization in China.

A new high-resolution N2O emission inventory for China in 2008.

The amount and geographic distribution of N2O emissions over China remain largely uncertain. In this study, county-level and 0.1° × 0.1° gridded anthropogenic N2O emission inventories for China (PKU-N2O) in 2008 are developed based on high-resolution activity data and regional emission factors (EFs) and parameters. These new estimates are compared with previous inventories, and with two sensitivity tests: one that uses high-resolution activity data but the default IPCC methodology (S1) and the other that uses regional EFs and parameters but starts from coarser-resolution activity data. The total N2O emissions are 2150 GgN2O/yr (interquartile range from 1174 to 2787 GgN2O/yr). Agriculture contributes 64% of the total, followed by energy (17%), indirect emissions (12%), wastes (5%), industry (2.8%), and wildfires (0.2%). Our national emission total is 17% greater than that of the EDGAR v4.2 global product sampled over China and is also greater than the GAINS-China, NDRC, and S1 estimates by 10%, 50%, and 17%, respectively. We also found that using uniform EFs and parameters or starting from national/provincial data causes systematic spatial biases compared to PKU-N2O. Spatial analysis shows nonlinear relationships between N2O emission intensities and urbanization. Per-capita and per-GDP N2O emissions increase gradually with an increase in the urban population fraction from 0.3 to 0.9 among 2884 counties, and N2O emission density increases with urban expansion.