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Abstract The rapid economic development of China has been accompanied by the emission of a great number of pollutants, which in turn have caused severe environmental problems. To strengthen environmental management and to establish a pollution source information database covering all key pollution sources and activities, China carried out its first National Census of Pollution Sources (NCPS) in 2007. The survey contents include the basic environmental situation in 2007, the generation levels of the main pollutants at that time, and the amount of pollution actually discharged into the environment after end-of-pipe treatment at all kinds of pollution sources. Based on the first NCPS report for China released in 2011, and taking two typical industry pollutants, sulfur dioxide (SO 2 ), and chemical oxygen demand (COD) as examples, we first revised the historical data concerning environmental statistics based on the NCPS documents. Subsequently, we analyzed the overall industrial scale in the change of SO 2 and COD emissions using index decomposition analysis, and then studied the contributions and comparative significance of the “three pollution emission reduction measures” put forward by the Chinese government. The latter are: Engineering Emission Reduction (EER), Structure Emission Reduction (SrER) and Supervision Emission Reduction (SuER). From these analyses, we were able to identify the main driving forces for SO 2 and COD emission reduction in China's industrial system. The results indicate that, with continually increasing pollution pressure caused by rapid economic development, EER and SuER have made the greatest contributions to reducing SO 2 and COD emissions; but SrER has not had an obvious effect. In the future, EER and SuER will gradually have less and less potential and become more challenging, while SrER should be achievable through adjusting the economic structure.

According to the United Nations population projections, the population of the elderly is expected to roughly triple in China from 2000 to 2050, particularly when the generations who were born between the 1950s and 1970s move through the age structure, and also because people are living longer and fertility rates have fallen, population aging is expected to put pressure on government's fiscal balance through higher old-age security benefits and health-care expenditures. This work draws together the broad range of elements involved within a consistent framework, based on a computable dynamic general equilibrium model with an overlapping generation structure. Further analysis using model simulation illustrates that the alternative schemes for the benefit rate, retirement age and technological progress are likely to be beneficial, and that an obvious slow-down in the growth of living standards is likely to be avoided.

Consumer interest in farmers’ markets (FMs) has dramatically increased during the past decade. The number of FMs in the United States has grown from 1755 in 1994 to 8140 in 2019 (USDA, 2019). To evaluate the economic impacts (EIs) of FMs in the Washington, DC metropolitan area, we collected FMs’ consumer data and used IMPLAN-based social accounting matrices to evaluate the direct, indirect, and induced economic impacts of FMs. The empirical results from IMPLAN provide the direct gross sales, income figures, and an estimate of the number of jobs in the study region. The results show the average total output of USD 36,181,059, total employment of 663 people, total value-added creation of USD 19,019,226, and total labor income created of USD 8,653,350 in the region. The FM average income multiplier is 1.51, which indicates that a USD 1 increase in personal income (PI) for an FM translates into USD 1.51 in PI across the economy of the region. We also highlight the impact of FMs as an important component of the circular economy (CE). To this end, we present a qualitative approach examining the potential of a CE as applied to the farmers’ markets in the Washington, DC metropolitan area using qualitative data from focus groups. The goal of the circular economy is to provide more sustainability in the local economy.

Abstract Eradicating poverty and mitigating greenhouse gas (GHG) emissions are core issues of global sustainable development goals (SDGs), and China is struggling in realizing these targets. The poverty reduction that leads to popualtion structure and lifestyle changes would have an impact on GHG emission changes. However, few studies have assessed the historical and future impacts of the poverty allevation on China's emissions. Here by linking Chinese Multi-Regional Input Output (MRIO) database to the global MRIO database EXIOBASE, and using provincial household consumption data, we identified the distribution of Chinese household greenhouse gas footprints (HGFs) by income groups in 2015 at the national and provinical levels. Moreover, we focused on the historical impact of poverty alleviation on HGFs during 2010–2015, and developed four scenarios to project future HGFs changes due to poverty alleviation by 2030. We find that eradicating extreme poverty in the secanrio S2, i.e., bringing people to an income above $1.9 daily, does not cause a large emission impact with current technological level. However, lifting people from a higher poverty line of $5.5 per day in the sceanrio S4 results in a 1.6% increase in emissions compared with the scenario S1 without any poverty reduction goals. Furthermore, realizing a higher poverty reduction target will result in an increase of emissions contribution from internatioanl supply chains due to the differences in consumption patterns among different income groups. Our study highlights the conflict between the high poverty alleviaition goal and emission reduciton in China, and reminds us of the need to make more technological efforts for avoiding the large emissions embodied in international supply chains.

River deltas and estuaries are disproportionally-significant coastal landforms that are inhabited by nearly 600 M people globally. In recent history, rapid socio-economic development has dramatically changed many of the World's mega deltas, which have typically undergone agricultural intensification and expansion, land-use change, urbanization, water resources engineering and exploitation of natural resources. As a result, mega deltas have evolved into complex and potentially vulnerable socio-ecological systems with unique threats and coping capabilities. The goal of this research was to establish a holistic understanding of threats, resilience, and adaptation for four mega deltas of variable geography and levels of socio-economic development, namely the Mekong, Yellow River, Yangtze, and Rhine deltas. Compiling this kind of information is critical for managing and developing these complex coastal areas sustainably but is typically hindered by a lack of consistent quantitative data across the ecological, social and economic sectors. To overcome this limitation, we adopted a qualitative approach, where delta characteristics across all sectors were assessed through systematic expert surveys. This approach enabled us to generate a comparative assessment of threats, resilience, and resilience-strengthening adaptation across the four deltas. Our assessment provides novel insights into the various components that dominate the overall risk situation in each delta and, for the first time, illustrates how each of these components differ across the four mega deltas. As such, our findings can guide a more detailed, sector specific, risk assessment or assist in better targeting the implementation of risk mitigation and adaptation strategies.

Abstract This paper provides the first estimates of China's global developmental finance institutions in general and China's policy bank lending to foreign governments for energy in particular. According to the China Global Energy Finance database, between 2000 and 2017, China Development Bank (CDB) and China Export-Import Bank (CHEXIM) provided $225.75 billion in overseas energy development finance. We find that: China's ‘policy banks’ and funds have doubled the availability of global development finance –and hold more assets than the major Western-backed MDBs operating in developing countries. With the onset of a new family of funds and multilateral development banks co-financed by China, China is poised to be the largest development lender in the world as Western-backed MDBs appear stagnated in their ability to increase their capital bases. China's global energy portfolio is heavily exposed to country, macroeconomic, climate, and social risks, however. To mitigate such risks and meet the broader sustainable development challenge for the 21st Century, China's development finance will need to shift the composition of its global energy lending in a significant manner.

The global community has set intensive targets in Sustainable Development Goals (SDGs) to better people’s lives after closing the Millennium Development Goals (MDGs). It corresponds to the 2030 aspirations of the United Nations to enhance and promote the sustainable development of human society. The current paper explores the impact of fiscal hedging and R&D in energy Using a green-energy system in SDGs. To do this, we used TOPSIS and QARDL methodologies on a 21-year dataset of South and Southeast Asian economies from 2000 to 2020. The study results show that fiscal hedging contributes favourably to the environmental degradation of the underlying economy. Research and development (R&D) in renewables has contributed negatively to ecological degradation and SDGs in the economies of South & Southeast Asia. This study suggests policy guidelines for advanced and developing economies based on fiscal stability and technical innovation through R&D to meet SDG.

Abstract China's carbon emissions have been ranking first in the world. This study filled in the gaps in research, decomposed carbon intensity from the perspective of time, space and industry. A decoupling effort model based on factor decomposition models was constructed to analyze the driving factors of carbon emissions and economic decoupling, which builded a foundation for achieving sustainable economic development. Using the Logarithmic Mean Divisia Index method (LMDI), the paper measured the carbon emission intensity of 29 provinces and cities in China from 1998 to 2019, and decomposed the decoupling effect between GDP and carbon emission on the basis of factor decomposition by tapio. The results showed that: (1) Carbon intensity declined first, then rise lightly, and finally declined steadily. For the primary industry and the tertiary industry, the carbon intensity declined steadily, while the carbon intensity increased accordingly to the overall carbon intensity. In terms of spatial evolution, the regional differences between different provinces decreased correspondingly. (2) The cumulative contribution rates of these three effects, i.e., technological progress, industrial structure and regional scale were 106.3299%, −15.1486% and 8.8188%, respectively. There were obvious differences of these cumulative contribution rates of carbon intensity among different provinces. (3) From the perspective of industrial, technological progress effect is the largest contribution for carbon intensity in the secondary industry. The Industrial structure effect mainly affects the primary and tertiary industries; and no significant difference in regional scale effect. (4) The decoupling effect gradually improved, and technological progress has played an absolute leading role in promoting the decoupling effect. Based on the research results, the key policy recommendation are put forward as follows: (1) Further improve the technological level and support clean technology enterprises. (2) Promote industrial upgrading in backward industrial provinces (3) Promote regional assistance and the introduction of high-quality foreign investment.