At the Sino-U.S. Climate summit in Beijing, iCET (Energy and Transportation Innovation Center) released an open collaborative initiative on global climate change. The initiative, co-sponsored and promoted by several organizations led by iCET, the Public Private Partnerships Alliance, will develop a global standard for quantifying sustainable environmental impacts through the application of big data - "measurable, reportable, verifiable "Standard (hereinafter referred to as" MRV standard "), used to promote the government and enterprises to establish quantitative monitoring system. In the pilot project developed by the MRV standard, iCET found that at times of traffic jams in large cities, the calculated carbon emission according to the real working conditions may be 78% higher than the traditional method. The transport sector is growing into one of the world's major sources of carbon emissions. The initiative calls for the development and application of MRV standards to tackle climate change in the transport sector through the joint efforts of public and private institutions. Through its pilot project in Chengdu, iCET demonstrated the potential of quantifying carbon emissions and using full value chain analysis with accurate and verifiable fact-finding data and explored the potential impact of the innovative "car sharing" innovation. Including the China Development and Reform Commission Energy Agency and China's Uber, including agencies involved in the pilot project, the pilot project by the National Geographic Society Environment and Water Conservation Fund to provide financial support. Due to technical bottlenecks and limited data resources, there has been a lack of MRV standards that can be implemented in the field of transportation. Cuneyt Oge, chairman of SAE International, a global authority on industry standards, once said: "In the era of information technology, we must make full use of cutting-edge technologies such as big data to address climate change Challenges. MRV is a key criterion for helping policymakers to more accurately assess the compliance of emission standards and is also a central element in advancing the establishment of a carbon accountability system. " Today, with the development of new technologies such as big data, cloud computing and vehicle interconnection, the world has the opportunity to acquire and verify traffic travel data in real time for the first time and to dynamically reflect the ever-changing traffic context of a city through data. For example, taxi big data resources accumulated by taxi software can provide a data source for analyzing the complicated supply-demand relationship of urban transport. The Live-Cycle methodology being developed by the research consortium is a methodological framework based on global value chain and big data analytics applications that will be used to support the development of MRV standards. The MRV standard in the future can establish a transparent accountability oversight mechanism to promote all parties in the value chain to fulfill their respective environmental obligations and address the challenges posed by climate change. iCET's preliminary study in Chengdu found that calculating carbon emissions using real-time data was 44% higher (under normal traffic conditions) and 78% (under peak hours) than traditional projections. From a macro perspective, the daily carbon footprint of transportation in Chengdu is about 17,500 tons per day, 59% higher than the figure estimated by traditional methods (11,000 tons). This apparent disparity underscores the importance of a set of MRV standards based on real-time data. Stephen Perkins, principal researcher at the Organization for Economic Co-operation and Development under the International Transport Forum (OECD-ITF), a major multilateral cooperation platform for transport in the world, said: "Results from the ITF model and Live-Cycle pilot The results of the project are basically in line with ITF's recognition that shared transport innovation including carpooling has the potential to reduce emissions. MRV-based principles monitor the impact of these initiatives on road conditions and understand the true operational performance of all vehicles. For emission reduction policies The effective implementation is a crucial element. " At the same time, these data can also be more intuitive to reflect the urban residents of passenger travel needs. The results show that 80% of traffic trips have a high degree of coincidence (starting and ending points are the same), that is, these trips have the conditions for carpooling. Through simulation of the data model, iCET found that if carpooling is used to increase the utilization rate of vehicles by 20%, the overall transportation carbon emission in Chengdu can be reduced by 28%. If the utilization rate can be increased to 60%, then Chengdu Traffic jams will be significantly alleviated, while 70% of transport carbon emissions can be avoided. In response, Nie Yuren, head of China's Utebu Research Institute, said Uber's internal research has yielded similar results to the pilot project. "Uber's carpool service in Chengdu has reduced mileage and total carbon emissions by 50 million kilometers and about 14,000 tons since July 2015. We support the sharing economy and the development of car sharing, and we are honored to be the one A member of the Public-Private Partnership Research Alliance to promote the development of public utilities through joint research. " In the follow-up period, iCET-led collaborative research alliance plans to conduct more in-depth research in the field of transportation and promote a better understanding of the efficiency of the urban transport system in all sectors of society. In addition, they will also use the carbon emission figures calculated by the MRV standard to support UNEP's Sustainable Consumption and Production initiative to promote people's sustainable consumption. Dr. An Feng, founder and executive director of iCET, stressed: "This project of public-private partnership is the first time that big data has been applied to establish a system of accountability for the environmental impact. To effectively achieve the goal of sustainable development, we Requires a pragmatic and sustainable action.And real sustainable action needs to quantify the sustainability of the MRV standard support, and the need for information-transparent environment through public-private cooperation mechanism to achieve.This is our development of this based on big data MRV standards of the original intention and a beautiful vision. "