Zhifu Mi

Chinese CO2 emission flows have reversed since the global financial crisis

This study seeks to estimate the carbon implications of recent changes in China’s economic development patterns and role in global trade in the post-financial-crisis era. We utilised the latest socioeconomic datasets to compile China’s 2012 multiregional input-output (MRIO) table. Environmentally extended input-output analysis and structural decomposition analysis (SDA) were applied to investigate the driving forces behind changes in CO2 emissions embodied in China’s domestic and foreign trade from 2007 to 2012. Here we show that emission flow patterns have changed greatly in both domestic and foreign trade since the financial crisis. Some economically less developed regions, such as Southwest China, have shifted from being a net emission exporter to being a net emission importer. In terms of foreign trade, emissions embodied in China’s exports declined from 2007 to 2012 mainly due to changes in production structure and efficiency gains, while developing countries became the major destination of China’s export emissions.China has entered a new normal phase of economic development with a changing role in global trade. Here the authors show that emissions embodied in China’s exports declined from 2007 to 2012, while developing countries become the major destinations of China’s export emissions.

Regional efforts to mitigate climate change in China: a multi-criteria assessment approach

The task of mitigating climate change is usually allocated through administrative regions in China. In order to put pressure on regions that perform poorly in mitigating climate changes and highlight regions with best-practice climate policies, this study explored a method to assess regional efforts on climate change mitigation at the sub-national level. A climate change mitigation index (CCMI) was developed with 15 objective indicators, which were divided into four categories, namely, emissions, efficiency, non-fossil energy, and climate policy. The indicators’ current level and recent development were measured for the first three categories. The index was applied to assess China’s provincial performance in climate protection based on the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method. Empirical results show that the middle Yangtze River area and southern coastal area perform better than other areas in mitigating climate change. The average performance of the northwest area in China is the worst. In addition, climate change mitigation performance has a negative linear correlation with energy self-sufficiency ratio but does not have a significant linear correlation with social development level. Therefore, regional resource endowments had better be paid much more attention in terms of mitigating climate change because regions with good resource endowments in China tend to perform poorly.

China CO2 emission accounts 1997–2015

China is the world’s top energy consumer and CO2 emitter, accounting for 30% of global emissions. Compiling an accurate accounting of China’s CO2 emissions is the first step in implementing reduction policies. However, no annual, officially published emissions data exist for China. The current emissions estimated by academic institutes and scholars exhibit great discrepancies. The gap between the different emissions estimates is approximately equal to the total emissions of the Russian Federation (the 4th highest emitter globally) in 2011. In this study, we constructed the time-series of CO2 emission inventories for China and its 30 provinces. We followed the Intergovernmental Panel on Climate Change (IPCC) emissions accounting method with a territorial administrative scope. The inventories include energy-related emissions (17 fossil fuels in 47 sectors) and process-related emissions (cement production). The first version of our dataset presents emission inventories from 1997 to 2015. We will update the dataset annually. The uniformly formatted emission inventories provide data support for further emission-related research as well as emissions reduction policy-making in China.

China's “Exported Carbon” Peak: Patterns, Drivers, and Implications

Over the past decade, China has entered a “new normal” phase in economic development, with its role in global trade flows changing significantly. This study estimates the driving forces of Chinese export‐embodied carbon emissions in the new normal phase, based on environmentally extended multiregional input‐output modeling and structural decomposition analysis. We find that Chinese export‐embodied CO2 emissions peaked in 2008 at a level of 1,657 million tones. The subsequent decline in CO2 emissions was mainly due to the changing structure of Chinese production. The peak in Chinese export‐embodied emissions is encouraging from the perspective of global climate change mitigation, as it implies downward pressure on global CO2 emissions. However, more attention should focus on ensuring that countries that may partly replace China as major production bases increase their exports using low‐carbon inputs.

Risk assessment of oil price from static and dynamic modelling approaches

ABSTRACT The price gap between West Texas Intermediate (WTI) and Brent crude oil markets has been completely changed in the past several years. The price of WTI was always a little larger than that of Brent for a long time. However, the price of WTI has been surpassed by that of Brent since 2011. The new market circumstances and volatility of oil price require a comprehensive re-estimation of risk. Therefore, this study aims to explore an integrated approach to assess the price risk in the two crude oil markets through the value at risk (VaR) model. The VaR is estimated by the extreme value theory (EVT) and GARCH model on the basis of generalized error distribution (GED). The results show that EVT is a powerful approach to capture the risk in the oil markets. On the contrary, the traditional variance–covariance (VC) and Monte Carlo (MC) approaches tend to overestimate risk when the confidence level is 95%, but underestimate risk at the confidence level of 99%. The VaR of WTI returns is larger than that of Brent returns at identical confidence levels. Moreover, the GED-GARCH model can estimate the downside dynamic VaR accurately for WTI and Brent oil returns.

The rise of South–South trade and its effect on global CO 2 emissions

Economic globalization and concomitant growth in international trade since the late 1990s have profoundly reorganized global production activities and related CO2 emissions. Here we show trade among developing nations (i.e., South–South trade) has more than doubled between 2004 and 2011, which reflects a new phase of globalization. Some production activities are relocating from China and India to other developing countries, particularly raw materials and intermediate goods production in energy-intensive sectors. In turn, the growth of CO2 emissions embodied in Chinese exports has slowed or reversed, while the emissions embodied in exports from less-developed regions such as Vietnam and Bangladesh have surged. Although China’s emissions may be peaking, ever more complex supply chains are distributing energy-intensive industries and their CO2 emissions throughout the global South. This trend may seriously undermine international efforts to reduce global emissions that increasingly rely on rallying voluntary contributions of more, smaller, and less-developed nations.The rapid growth of South–South trade reflects a new phase of globalization. Here the authors show that some energy-intensive production activities, particularly raw materials and intermediate goods, and related CO2 emissions are relocating from China and India to other developing countries.

Structural decline in China's CO2 emissions through transitions in industry and energy systems

As part of the Paris Agreement, China pledged to peak its CO2 emissions by 2030. In retrospect, the commitment may have been fulfilled as it was being made—China’s emissions peaked in 2013 at a level of 9.53 gigatons of CO2, and have declined in each year from 2014 to 2016. However, the prospect of maintaining the continuance of these reductions depends on the relative contributions of different changes in China. Here, we quantitatively evaluate the drivers of the peak and decline of China’s CO2 emissions between 2007 and 2016 using the latest available energy, economic and industry data. We find that slowing economic growth in China has made it easier to reduce emissions. Nevertheless, the decline is largely associated with changes in industrial structure and a decline in the share of coal used for energy. Decreasing energy intensity (energy per unit gross domestic product) and emissions intensity (emissions per unit energy) also contributed to the decline. Based on an econometric (cumulative sum) test, we confirm that there is a clear structural break in China’s emission pattern around 2015. We conclude that the decline of Chinese emissions is structural and is likely to be sustained if the nascent industrial and energy system transitions continue.The decline in China’s CO2 emissions in the past few years is largely due to changes in industrial structure and a decline in the share of coal for energy production, according to a quantitative analysis of the drivers of CO2 emissions.

City-level climate change mitigation in China

Technological advancement in industrializing cities is critical for reducing CO2 emissions while maintaining economic growth. As national efforts to reduce CO2 emissions intensify, policy-makers need increasingly specific, subnational information about the sources of CO2 and the potential reductions and economic implications of different possible policies. This is particularly true in China, a large and economically diverse country that has rapidly industrialized and urbanized and that has pledged under the Paris Agreement that its emissions will peak by 2030. We present new, city-level estimates of CO2 emissions for 182 Chinese cities, decomposed into 17 different fossil fuels, 46 socioeconomic sectors, and 7 industrial processes. We find that more affluent cities have systematically lower emissions per unit of gross domestic product (GDP), supported by imports from less affluent, industrial cities located nearby. In turn, clusters of industrial cities are supported by nearby centers of coal or oil extraction. Whereas policies directly targeting manufacturing and electric power infrastructure would drastically undermine the GDP of industrial cities, consumption-based policies might allow emission reductions to be subsidized by those with greater ability to pay. In particular, sector-based analysis of each city suggests that technological improvements could be a practical and effective means of reducing emissions while maintaining growth and the current economic structure and energy system. We explore city-level emission reductions under three scenarios of technological progress to show that substantial reductions (up to 31%) are possible by updating a disproportionately small fraction of existing infrastructure.

China’s socioeconomic risk from extreme events in a changing climate: a hierarchical Bayesian model

China has a large economic and demographic exposure to extreme events that is increasing rapidly due to its fast development, and climate change may further aggravate the situation. This paper investigates China’s socioeconomic risk from extreme events under climate change over the next few decades with a focus on sub-national heterogeneity. The empirical relationships between socioeconomic damages and their determinants are identified using a hierarchical Bayesian approach, and are used to estimate future damages as well as associated uncertainty bounds given specified climate and development scenarios. Considering projected changes in exposure, we find that the southwest and central regions and Hainan Island of China are likely to have a larger percentage of population at risk, while most of the southwest and central regions could generally have higher economic losses. Finally, the analysis suggests that increasing income can significantly decrease the number of people affected by extremes.

Will Pollution Taxes Improve Joint Ecological and Economic Efficiency of Thermal Power Industry in China?: A DEA-Based Materials Balance Approach: Joint Ecological and Economic Efficiency of China

Previous studies of the efficiency of Chinese electricity industry have been limited in providing insights regarding policy implications of inherent trade-offs of economic and environmental outcomes. This study proposes a modified data envelopment analysis method combined with materials balance principle to estimate ecological and cost efficiency in the Chinese electricity industry. The economic cost and ecological impact of energy input reallocation strategies for improving efficiency are identified. The possible impacts of pollution taxes upon the levels of sulfur dioxide (SO2) emissions are assessed. Estimation results show that (i) both energy input costs and SO2 could be reduced through increasing technical efficiency. (ii) It is possible to adjust energy input mix to attain ecological efficient, and correspondingly, SO2 would reduce by 15%. (iii) The Chinese electricity industry would reduce its unit cost by 9% if optimal ecological efficiency is attained and reduce its unit pollution by 13% if optimal cost efficiency is attained, implying that there are positive ecological synergy effects associated with energy cost savings and positive economic synergy effects associated with SO2 pollution reductions. (iv) Estimated shadow costs of SO2 reduction are very high, suggesting that, in the short term, the Chinese electricity industry should pursue cost efficient point instead of ecological efficient point, since alternative abatement activities are less costly and some of the abatement cost could be further offset by energy input cost savings. (v) There would be no significant difference between the impacts of pollution discharge fees and pollution taxes on SO2 emissions levels because of the relatively low pollution tax rate.