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Shanghai Environmental Protection Key Lab of Environmental Big Data and Intelligent Decision-making

Approved by Shanghai Municipal Environmental Protection Bureau in 2017, the laboratory is jointly built by Shanghai Jiao Tong University, Shanghai Environmental Monitoring Center and Shanghai Environmental Protection Information Center. Targeting the environmental management demands of Shanghai, it takes big data-based intelligent decision-making for environmental management as its core function. By conducting forward-looking and applied researches on the application of environmental big data in environmental management practices, it provides technical and decision-making support for scientific and refined environmental management in Shanghai and across the country, as well as technical basis for formulating relevant technical policies, guidelines and regulations on pollution control. It currently has 22 full-time researchers.

Main Research Directions

Environmental Big Data Fusion and Platform Architecture
Core Algorithm Tools & Technologies for Environmental Decision-making
Business Application of Environmental Management

Leadership Team

Cheng Jinping
/ Research Fellow

His research focuses on pollution source control and big data application. He has solid research experience in environmental protection data verification, validity analysis, data supplementation and data mining. He boasts rich practical experience in real-time atmospheric environmental data analysis, research judgment, pollution source tracing and rapid elimination of pollution peak values. He has participated in air quality guarantee work for many major events and taken part in the Blue Sky Defense Campaign in more than ten prefecture-level cities.
Geng Yong
/ Professor
Distinguished Chair Professor, Dean of the School of Environmental Science and Engineering, Shanghai Jiao Tong University, Yangtze River Distinguished Scholar of the Ministry of Education, outstanding winner in the post-evaluation of the National Science Fund for Distinguished Young Scholars, and recipient of the National Hundred-Thousand-Talents Program. His research achievements were selected as outstanding achievements of the National Natural Science Foundation of China in 2013, and included in the 20th Anniversary Achievement Showcase of the National Science Fund for Distinguished Young Scholars as well as outstanding achievements during the 12th Five-Year Plan period. He has published 286 SCI/SSCI papers and 209 EI-indexed articles in top international journals including Science and Nature. His total citation reaches 11,562 with an H-index of 59, including 35 ESI Highly Cited Papers.
 
 

Representative Research Achievements

Research on the Construction of Comprehensive Decision-Making Database for Shanghai Environment and Development

This study comprehensively sorts out data requirements required for decision support and policy evaluation in Shanghai covering environmental economy, environmental society and pollution governance. It establishes the overall database framework from multiple dimensions including municipal-wide, industrial and regional levels, and develops parallel data requirement lists for horizontal comparison among major cities at home and abroad. Application indicator frameworks and statistical grouping schemes are designed for each dimension, so as to finalize the database structure oriented to collaborative analysis of environmental protection and socio-economic development.

Research on Big Data Processing and Analysis Technologies for Shanghai Environment and Development

This paper studies the application of big data in relevant macro decision-making fields at home and abroad. It mainly investigates the progress of big data development in developed countries such as the United States, the United Kingdom, Japan and Australia, sorts out domestic policy trends and technological advances in big data industry, and summarizes research achievements on the application of big data technologies in this field.

Application of Big Data in Air Pollution Control of Industrial Parks

Through tracking and analyzing online data from industrial parks, this research analyzes regional pollution characteristics and patterns from a spatio-temporal perspective. Combined with data examples from emergency situations such as over-limit alarms, it explores the application of data resources in pollution source apportionment and complaint correlation analysis in industrial parks. For characteristic pollutants in the region, source correlation analysis is conducted. Combined with meteorological data, the research analyzes flow field changes and identifies the spatial characteristics of pollution sources, providing a scientific basis for the refined management of air pollution in industrial parks.

Integrated Application of Urban Traffic and Environmental Big Data

Based on data from traffic pollution monitoring stations in Shanghai, in-depth analyses are conducted from the perspectives of traffic management policies and traffic pollution control technologies. The research provides environmental-oriented guidance for the formulation of urban traffic management policies and technical adjustment directions for oil product process research and development. It also offers important guiding significance for vehicle emission reduction and urban air quality improvement.

Research on Development of Municipal Comprehensive Environmental Decision-making Data Service and Support Platform

Extensive investigations and demand analyses are carried out on data services for comprehensive environmental decision-making. From the perspectives of environmental planning, pollution prevention plans, environmental policies, industrial park management and other administrative work, this study formulates the framework and detailed list of targeted service demands for comprehensive environmental decision-making.

Release of Three Major Carbon Indices for Real-time Dynamic Display of Carbon Emission Characteristics
Joint research team of the Laboratory and Reger Intelligence Research has applied big data and artificial intelligence technologies, combined with production, operation and pollutant emission status of industries and enterprises, to establish a real-time dynamic collaborative carbon and pollution reduction index system. Three carbon series indices have been developed and released, namely Carbon Emission Index, Carbon Target Index and Carbon Economy Index.
(Index query URL: https://jte.fieldsconsult.cn)
 
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