Key global climate governance problems and Chinese countermeasures

Presently,the full implementation of the negotiations and collaborations under the Paris Agreement faces new key problems and severe challenges.These problems and challenges include the following:how to honor the principle of“common but differentiated responsibilities”to facilitate a comprehensive,balanced,and effective implementation of the key elements of the Paris Agreement,such as adaptation,mitigation,finance,technology,capacity building,and transparency;how to uphold and maintain the status of China and other emerging countries as developing countries in light of the requirements of the United Nations Framework Convention on Climate Change and the historical responsibilities of these countries;and how to assess the goal of limiting the global temperature increase to 1.5℃and what constitutes an equitable carbon mitigation pathway for different types of countries.Developed countries and developing countries have drastically diverging views on carbon border adjustment measures for trade with developing countries proposed by several developed countries such as the European Union.Developed countries have demonstrated obvious intentions and actions designed to weaken and neglect the principle of“common but differentiated responsibilities”,to impose mitigation pressure on developing countries,to shift the responsibilities for emissions onto others,and to pass on the costs of mitigation.The maneuvering among different types of countries and interest groups has become increasingly intense.In response,China must maintain its strategic focus,adhere to the goals and principles established by the Paris Agreement,stick to its strategic positioning as a developing country,solidify strategic support from the developing world,and safeguard the legitimate rights and interests of developing countries.China played a conducive role in facilitating the Paris Agreement and has become an active participant,contributor,and leader in global climate governance.China must continue to follow Xi Jinping Thought on Socialism with Chinese Characteristics for a New Era and its conception of ecological civilization and the concept of building a community of common destiny,to actively lead the cooperation process in the construction of a global climate governance system characterized by equity,justice,and win-win collaborations,and to promote compliance with the Paris Agreement.At the same time,China should accelerate the green,low-carbon,circular transformation of its economy;accelerate the coordinated governance of the economy,environment,and climate change;and formulate and implement a long-term low-carbon development strategy.By the middle of the 21st century,while achieving the goal of building a great modern socialist country,China can also achieve a deep decarbonization development path that is in line with the goal of limiting the global temperature increase to well below 2°C and pursuing efforts to limit the increase to 1.5℃.

Fuel consumption,vehicle quantities,and total factor inefficiency in China

Scale-controlling and technology-upgrading measures are considered effective for mitigating vehicle exhaust emissions.This study investigated the impacts of fuel consumption and vehicle quantities on the total factor inefficiency in China’s highway transport sector during 2011-2015,based on the Bounded Adjusted Measure Data Envelopment Analysis(BAM-DEA)model combined with natural and managerial disposability scenarios.The results showed that the average global inefficiency(GIE)score of the exhaust emissions(CO,HC,NOx,and PM)was 0.41 under the assumption of natural disposability and 0.23 in the managerial disposability situation.Moreover,the main causes of total factor inefficiency scores from the perspective of natural disposability were road length,fuel consumption,and exhaust emissions,whereas those from a managerial disposability perspective were road length and exhaust emissions.These two results suggested that environmental efficiency can be promoted by increasing the quantities of clean-energy vehicles and high-quality gasoline/diesel consumption.In terms of the spatial distribution of GIE,the scores showed a decreasing trend from China’s northwestern inland regions to its southeastern coastal regions under both natural and managerial disposability.Environmental efficiency in some provinces(such as Yunnan)demonstrated good progress under managerial disposability,but other regions did not(such as Hebei and Ningxia).Thus,each province should choose appropriate strategies regarding vehicle quantities and fuel consumption according to the technical inefficiency scores of differing disposability situations.

A Range Adjusted Measure of Super-Efficiency in Integer-Valued Data Envelopment Analysis with Undesirable Outputs

DEA(data envelopment analysis) models can be divided into two groups: Radial DEA and non-radial DEA, and the latter has higher discriminatory power than the former. The range adjusted measure(RAM) is an effective and widely used non-radial DEA approach. However, to the best of our knowledge, there is no literature on the integer-valued super-efficiency RAM-DEA model,especially when undesirable outputs are included. We first propose an integer-valued RAM-DEA mode with undesirable outputs and then extend this model to an integer-valued super-efficiency RAM-DEA model with undesirable outputs. Compared with other DEA models, the two novel models have many advantages: 1) They are non-oriented and non-radial DEA models, which enable decision makers to simultaneously and non-proportionally improve inputs and outputs;2) They can handle integer-valued variables and undesirable outputs, so the results obtained are more reliable;3) The results can be easily obtained as it is based on linear programming;4) The integer-valued super-efficiency RAM-DEA model with undesirable outputs can be used to accurately rank efficient DMUs. The proposed models are applied to evaluate the efficiency of China’s regional transportation systems(RTSs) considering the number of transport accidents(an undesirable output). The results help decision makers improve the performance of inefficient RTSs and analyze the strengths of efficient RTSs.