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    Prof. Xu receives the prestigious NSF Faculty Early Career Development (CAREER) Award
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    New ES&T paper on betweenness of critical transmission sectors for
    supply chain environmental pressure mitigation [link]
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    Prof. Xu was awarded the prestigious Robert A. Laudise Medal
    for “outstanding achievement in industrial ecology
    by a researcher under the age of 36.”
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    Prof. Xu appointed Editor-In-Chief of Elsevier journal
    Resources, Conservation & Recycling (2014 Impact Factor: 2.564)

About Prof. Xu

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Ming Xu is an Associate Professor in School of Natural Resources and Environment and Department of Civil and Environmental Engineering at the University of Michigan, Ann Arbor (faculty profile).

Prof. Xu's research interests lie in the fields of sustainable engineering and industrial ecology. He was awarded the prestigious Robert A. Laudise Medal which is to recognize "outstanding achievement in industrial ecology by a researcher under the age of 36."

Prof. Xu is a core faculty of the Center for Sustainable Systems and co-directs the Graduate Certificate Program on Industrial Ecology at the University of Michigan. He is the Editor-In-Chief of Resources, Conservation & Recycling (2015 Impact Factor: 3.280).

Download Prof. Xu's full CV.

Research

The overarching objective of our research is to understand the interactions between industrial systems and the biophysical environment. Our research consists of two core elements: 1) environmental footprints of societal consumption at the regional, national, and global levels, and 2) life cycle environmental impacts of emerging technologies. Through externally funded projects, our research ambition is to provide an understanding of driving forces of environmental pressures and to assist in finding alternative development pathways that can reduce these pressures.

Our research is inherently interdisciplinary, integrating concepts and methods from multiple disciplines including industrial ecology, data science, and complex systems science.

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    Research methods and applications
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    Word cloud of our paper titles
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    Our sponsors

Recent Projects

"Big Data" for Human Mobility

This is a spin-off of the DOE CERC-CVC project, aiming to understand human mobility dynamics and implications to transportation sustainability using "big data" and data science methods. In particular, we use large-scale, real-time taxi trajectory data for large cities (e.g., ~20,000 vehicles for 30 days) to characterize mobility dynamics at the individual level. Based on this characterization of individual mobility dynamics, we evaluate environmental implications of large-scale deployment of electric vehicles, optimize the siting of public charging infrastructure for electric vehicles, and assess the environmental benefits of ride-sharing.

Mobility

 

WaterRiskNetwork

Much work has been done to evaluate environmental impacts of international trade. Little attention has been paid to the other side of the coin, implications of the environmental challenges to the trade system. Funded by the National Science Foundation, this project addresses this intellectual gap using water scarcity risk as a case study. The project develops a probabilistic network analysis framework integrates methods from multiple fields, including input-output analysis, risk analysis, and network analysis. The integration of these methods is a unique contribution to research in sustainability implications of international trade. It allows evaluating cascading impacts of local water scarcity to upstream and downstream supply chains for each industry in each country of the global trade network. Multiple factors contributing to water scarcity risk are considered simultaneously, including the dependence of industries on local water resources, severeness of water scarcity across countries and river basins, and interconnectedness of the global trade network. This project focuses on industries in countries as the unit of analysis, improving the resolution of relevant, limited studies in the literature focusing only on countries.

WaterRiskNetwork

 

LCI Network

A quality life cycle assessment (LCA) depends on the availability and quality of life cycle inventory (LCI) data. LCA practitioners have been increasingly relying on dedicated LCI databases which provide LCI data for common unit processes of a wide range of products. Despite the convenience, these LCI databases still depend on time-consuming, expensive empirical data collection. Supported by a NSF CAREER grant, this project aims to transform the current practice of developing LCI databases into a faster, less expensive process that still generates reliable LCI data, by developing a computational and data-driven framework for estimating missing LCI data solely based on limited known LCI data, without relying on additional empirical data. It will (1) create a framework for modeling and analyzing LCI networks, (2) develop computational models for estimating missing LCI data, and (3) apply these models to evaluate LCI data quality and predict LCI data for emerging technologies.

Building upon the transformative promise seen from link prediction techniques in network science that enable the prediction of missing information of a network based on limited observations, this research develops computational and data-driven approaches as complementary alternatives for compiling LCI databases.

LCI Network

 

Urban FEW Nexus

With more than half of the world’s population living in urban areas, the efficient provision of food, energy, and water (FEW) has become a pressing challenge for urban sustainability. This challenge comes from not only the increasing demand for FEW resources due to increased urban population, but also the complex interdependence of the urban FEW systems. Policy and technological solutions addressing the urban FEW challenge needs to be assessed through the lens of FEW nexus to (1) identify co-benefits that a single policy or technology can simultaneously improve the efficiency of multiple systems, and (2) avoid unintended consequences that desired changes in one system lead to undesired changes in other systems.

This project aims to develop an integrated systems modeling framework understanding urban FEW nexus to promote the efficient utilization of FEW resources. Through a case study in the Detroit city-region, we will demonstrate the integrated systems modeling framework by (1) characterizing the urban FEW flow networks, (2) examining the structure of the integrated network of FEW flow networks, and (3) developing and evaluating policy and technology scenarios with stakeholder inputs to identify co-benefit opportunities without unintended consequences.

Urban FEW Nexus

 

IO Network

Input-output (IO) models are widely used in environmental studies to understand the relationship between production-related environmental pressures (e.g. greenhouse gas emissions) and consumption at the economy scale. However, little attention in the IO literature has been paid to study the structure of an economy as a complete, integrated system. Just as we cannot comprehend the dynamics of ecosystems by studying separated food chains or the behavior of cells by micro-scoping isolated biochemical pathways, we cannot fully understand the structure and its relation to the dynamics of an economy only by investigating isolated, separated interdependencies between sectors. A more “holistic” perspective is required. Modern “network analysis” offers an ideal framework to pursue such study using IO models.

IO Network

 

ABLCA

Life cycle assessment (LCA) quantifies the environmental impacts of a product or process in an effort to improve its environmental sustainability. LCA is easiest to implement on established industrial systems with available data; however, the systems that may benefit most from an LCA are emerging, uncertain, and difficult to quantify with traditional LCA methods. Funded by the National Science Foundation, this project develops a spatially-explicit agent-based LCA (ABLCA) framework to improve the standard LCA modeling technique by overcoming the issues involved with analyzing emerging technologies with dynamic and evolving supply chains. This improved LCA modeling framework is also applied to the U.S. switchgrass bioenergy system (biofuels and biomass electricity) to examine the supply chain dynamics and evolution and evaluate the associated life cycle environmental impacts.

ABLCA

 

CERC-CVC

As part of the US-China Clean Energy Research Center on Clean Vehicles (CERC-CVC) funded by the Department of Energy, this project assesses the feasibility of alternative vehicle fueling including biofuels and electricity for meeting significant penetration of clean vehicles. This project evaluates the impact on water and land resources in the US due to large-scale deployment of clean vehicles.

CERC-CVC

CEEIO

http://www.ceeio.com

The Chinese Environmentally Extended Input-Output (CEEIO) database is the result of our near decade-long research of using environmentally extended input-output models studying China's environmental issues. We provide open access to CEEIO for non-commerical uses at www.ceeio.com.

Teaching

NRE 573: Environmental Footprinting and Input-Output Analysis

Environmental footprints characterize the pressure on the environment driven by human consumption throughout increasingly globalized supply chains. Understanding the environmental footprints of human consumption is important for environmental decision-making in many areas. This course provides the conceptual and technical background for quantitatively measuring environmental footprints at multiple scales. In particular, it introduces theories and concepts of environmental footprints, methods and tools (input-output analysis) to quantify environmental footprints of consumption at the nation and international scales, and various applications such as carbon footprinting and hybrid life cycle assessment.

ENVIRON 367: Global Enterprise and Sustainable Development

Companies, especially those with global operations, have begun to embrace sustainability as a competitive strategy, rather than treating sustainability issues as an added cost. They view sustainability as an added opportunity to differentiate themselves in a competitive marketplace. Sustainability has become an integrated part of their core business functions and strategies to help obtain and maintain a competitive advantage. This course will explore this mega-trend, focusing on how businesses are affecting sustainability and how sustainability is affecting businesses. We will introduce various activities global enterprises are taking to be socially responsible and how these activities gain competitive advantages for them. This course was offered in Summer 2013 at the UM-SJTU Joint Institute at Shanghai Jiao Tong University.

Wikipedia Project

Collaborating with Wiki Education Foundation and Michigan Wikipedians, Prof. Xu has been using Wikipedia as a teaching tool for ENVIRON 367 (Global Enterprise and Sustainable Development). Students have created new Wikipedia pages or significantly improved existing pages to broadly disseminate knowledge they have learned from the course. Below are some of the examples.

Wiki Education Foundation Michigan Wikipedians

 

 

Brundtland Commission

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Current

Design for the Environment

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Current

Kalundborg Eco-industrial Park

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Current

Life Cycle Thinking

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Current


Material Criticality

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Current

Pollution Haven Hypothesis

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Current

Sustainable Urbanism

New page
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Current

Publication

 

Citation Profiles

(underlined: student/postdoc advisees; *corresponding author)

  1. Tian, X.; Wu, Y.-F.*; Qu, S.; Liang, S.; Xu, M.*, Zuo, T.-Y. The disposal and willingness to pay for residents’ scrap fluorescent lamps in China: a case study of Beijing. Resources, Conservation & Recycling 2016, 114, 103-111.

  2. Ji, L.; Jia, X.-P.; Chiu, A. S. F.; Xu, M.* Global electricity trade network: structures and implications. PLOS ONE 2016, 11 (8), e0160869.

  3. Liang, S.; Wang, H.-X.; Qu, S.; Feng, T.-T.; Guan, D.-B.; Fang, H.; Xu, M.* Socioeconomic drivers of greenhouse gas emissions in the United States. Environmental Science & Technology 2016, 50 (14), 7535-7545.

  4. Liu, D.; Xu, M.; Niu, D.-X.; Wang, S.-K.; Liang, S. Forecast modelling via variations in binary image-encoded information exploited by deep learning neural networks. PLOS ONE 2016, 11 (6), e0157028.

  5. Gu, Y.-F.; Wu, Y.-F.*; Xu, M.*; Mu, X.-Z.; Zuo, T.-Y. Waste electrical and electronic equipment (WEEE) recycling for a sustainable resource supply in the electronics industry in China. Journal of Cleaner Production 2016, 127, 331-338.

  6. Liang, S.; Feng, T.-T.; Qu, S.; Chiu, A. S. F.; Jia, X.-P.; Xu, M.* Developing the Chinese Environmentally Extended Input-Output (CEEIO) Database. Journal of Industrial Ecology 2016, in press.

  7. Cai, H.*; Zhan, X.-W.; Zhu, J.; Jia, X.-P.; Chiu, A. S. F.; Xu, M.* Understanding taxi travel patterns. Physica A: Statistical Mechanics and Its Applications 2016, 457, 590-597.

  8. Liang, S.; Qi, Z.-L.; Qu, S.; Zhu, J.; Chiu, A. S. F.; Jia, X.-P.; Xu, M.* Scaling of global input-output networks. Physica A: Statistical Mechanics and Its Applications 2016, 452, 311-319.

  9. Liang, S.; Qu, S.; Xu, M.* Betweenness-based method to identify critical transmission sectors for supply chain environmental pressure mitigation. Environmental Science & Technology 2016, 50 (3), 1330-1337.

  10. Gu, Y.-F.; Wu, Y.-F.*, Xu, M.*, Wang, H.-D.; Zuo, T.-Y. The stability and profitability of the informal WEEE collector in development countries: a case study of China. Resources, Conservation & Recycling 2016, 107, 18-26.

  11. Pandit, A.; Minne, E. A.; Li, F.; Brown, H.; Jeong, H.; James, J.-A. C.; Newell, J. P.; Weissburg, M.; Chang, M. E.; Xu, M.; Yang, P.; Wang, R.-S.; Thomas, V. M.; Yu, X.-W.; Lu, Z.-M.; Crittenden, J. C. Infrastructure ecology: an evolving paradigm for sustainable urban development. Journal of Cleaner Production, accepted. DOI: 10.1016/j.jclepro.2015.09.010.

  12. Liang, S.; Guo, S.; Newell, J. P.; Qu, S.; Feng, Y.; Chiu, A. S. F.; Xu, M.* Global drivers of Russian timber harvest. Journal of Industrial Ecology, 2016, 20 (3), 515-525.

  13. Ji, L.; Liang, S.; Qu, S.; Zhang, Y.-X.; Xu, M.*; Jia, X.-P.; Jia, Y.-T.; Niu, D.-X.; Yuan, J.-H.; Hou, Y.; Wang, H.-K.; Chiu, A. S. F.; Hu, X.-J. Greenhouse gas emission factors of purchased electricity from interconnected grids. Applied Energy, accepted. DOI: 10.1016/j.apenergy.2015.10.065.

  14. Yue, Y.; Wang, T.; Liang, S.*; Yang, J.; Hou, P.; Qu, S.; Zhou, J.; Jia, X.-P.; Wang, H.-T.; Xu, M.* Life cycle assessment of high speed rail in China. Transportation Research Part D: Transport and Environment 2015, 41, 367-376.

  15. Shahraki, N.; Cai, H.; Turkay, M.; Xu, M. Optimal locations of electric public charging stations using real world vehicle travel patterns. Transportation Research Part D: Transport and Environment 2015, 41, 165-176.

  16. Bichraoui-Draper, N.; Xu, M.*; Miller, S. A.; Guillaume, B. Agent-based life cycle assessment for switchgrass-based bioenergy systems. Resources, Conservation & Recycling 2015, 103, 171-178.

  17. Xu, M.*; Cai, H.; Liang, S. Big data and industrial ecology. Journal of Industrial Ecology 2015, 19 (2), 205-210.

  18. Liang, S.; Feng, Y.; Xu, M.* Structure of the global virtual carbon network revealing important sectors and communities. Journal of Industrial Ecology 2015, 19 (2), 307-320.

  19. Zhang, Y.-X.; Wang, H.-K; Liang, S.; Xu, M.; Zhang, Q.; Zhao, H.-Y.; Bi, J. A dual strategy for controlling energy consumption and air pollution in China’s metropolis of Beijing. Energy 2015, 81, 294-303.

  20. Pontau, P.; Hou, Y.; Cai, H.; Zhen, Y.; Jia, X.-P.; Chiu, A. S. F.; Xu, M. Assessing land-use impacts by clean vehicle systems. Resources, Conservation & Recycling 2015, 95, 112-119.

  21. Cai, H.; Jia, X.-P.; Chiu, A. S. F.; Hu, X.-J.; Xu, M.* Siting public electric vehicle charging stations in Beijing using big-data informed travel patterns of the taxi fleet. Transportation Research Part D: Transport and Environment 2014, 33, 39-46.

  22. Ji, L.; Niu, D.-X.; Xu, M.; Huang, G.-H. An optimization model for regional micro-grid system management based on hybrid inexact stochastic-fuzzy chance-constrained programming. International Journal of Electrical Power & Energy Systems 2015, 64, 1025-1039.

  23. Zhang, Y.-X.; Wang, H.-K.; Liang, S.; Xu, M.; Liu, W.-D.; Li, S.-L.; Zhang, R.-R.; Nielsen, C. P.; Bi, J. Temporal and spatial variations in consumption-based carbon dioxide emissions in China. Renewable and Sustainable Energy Reviews 2014, 40, 60-68.

  24. Liang, S.; Zhang, C.; Wang, Y.-F.; Xu, M.*; Liu, W.-D. Virtual atmospheric mercury emission network in China. Environmental Science & Technology 2014, 48 (5), 2807-2815.

  25. Choudhary, S.; Liang, S.; Cai, H.; Keoleian, G. A.; Miller, S. A.; Kelly, J.; Xu, M.* Reference and functional unit can change bioenergy pathway choices. The International Journal of Life Cycle Assessment 2014, 19 (4), 796-805.

  26. Liang, S.*; Liu, Z.; Crawford-Brown, D.; Wang, Y.-F.; Xu, M.* Decoupling analysis and socioeconomic drivers of environmental pressure in China. Environmental Science & Technology 2014, 48 (2), 1103-1113.

  27. Zeng, L.; Xu, M.*; Liang, S.; Zeng, S.-Y.; Zhang, T.-Z.* Revisiting drivers of energy intensity in China during 1997-2007: a structural decomposition analysis. Energy Policy 2014, 67, 640-647.

  28. Yuan, J.-H.*; Xu, Y.; Zhang, X.-P.; Hu, Z.*; Xu, M.* China’s 2020 clean energy target: consistency, pathways and policy implications. Energy Policy 2014, 65, 692-700.

  29. Liang, S.*; Xu, M.*; Suh, S.; Tan, R. R. Unintended environmental consequences and co-benefits of economic restructuring. Environmental Science & Technology 2013, 47 (22), 12894-12902.

  30. Cai, H.; Xu, M.* Greenhouse gas implications of fleet electrification based on Big Data-informed individual travel patterns. Environmental Science & Technology 2013, 47 (16), 9035-9043.

  31. Cai, H.; Hu, X.-J.; Xu, M.* Impact of emerging clean vehicle system on water stress. Applied Energy 2013, 111, 644-651.

  32. Liang, S.; Xu, M.; Liu, Z.; Suh, S.; Zhang, T.-Z. Socioeconomic drivers of mercury emissions in China from 1992 to 2007. Environmental Science & Technology 2013, 47 (7), 3234-3240.

  33. Liang, S.; Liu, Z.; Xu, M.; Zhang, T.-Z. Waste oil derived biofuels in China bring brightness for global GHG mitigation. Bioresource Technology 2013, 131, 139-145.

  34. Liang, S.; Xu, M.; Zhang, T.-Z. Life cycle assessment of biodiesel production in China. Bioresource Technology 2013, 129, 72-77.

  35. Liang, S.; Xu, M.; Zhang, T.-Z. Unintended consequences of bioethanol feedstock choice in China. Bioresource Technology 2012, 125, 312-317.

  36. Yuan, J.-H.*; Xu, Y.; Hu, Z.*; Yu, Z.-F.; Liu, J.-Y.; Hu, Z.-G.; Xu, M.* Managing electric power system transition in China. Renewable and Sustainable Energy Reviews 2012, 16 (8), 5660-5677.

  37. Yuan, J.-H.; Hou, Y.; Xu, M.* China’s 2020 carbon intensity target: consistency, implementations, and policy implications. Renewable and Sustainable Energy Reviews 2012, 16 (7), 4970-4981.

  38. Xu, M.*; Li, R.; Crittenden, J. C.; Chen, Y.-S. CO2 emissions embodied in China’s exports from 2002 to 2008: a structural decomposition analysis. Energy Policy 2011, 39 (11), 7381-7388.

  39. Xu, M.*; Allenby, B. R.; Crittenden, J. C. Interconnectedness and resilience of the U.S. economy. Advances in Complex Systems 2011, 14 (5), 649-672.

  40. Yang, J.; Xu, M.; Zhang, X.-Z.; Hu, Q.; Sommerfeld, M.; Chen, Y.-S. Life-cycle analysis on biodiesel production from microalgae: water footprint and nutrients balance. Bioresource Technology 2011, 102 (1), 159-165.

  41. Xu, M.* Development of the Physical Input Monetary Output model for understanding material flows within ecological-economic systems. Journal of Resources and Ecology 2010, 1 (2), 123-134.

  42. Xu, M.*; Crittenden, J. C.; Chen, Y.-S.; Thomas, V. M.; Noonan, D. S.; DesRoches, R.; Brown, M. A.; French, S. P. Gigaton problems need gigaton solutions. Environmental Science & Technology 2010, 44 (11), 4037-4041.

  43. Xu, M.*; Williams, E.; Allenby, B. Assessing environmental impacts embodied in manufacturing and labor input for the China-U.S. trade. Environmental Science & Technology 2010, 44 (2), 567-573.

  44. Xu, M.*; Allenby, B.; Chen, W.-Q. Energy and air emissions embodied in China-U.S. trade: eastbound assessment using adjusted bilateral trade data. Environmental Science & Technology 2009, 43 (9), 3378-3384.

  45. Xu, M.*; Allenby, B.; Kim, J.; Kahhat, R. A dynamic agent-based analysis for the environmental impacts of conventional and novel book retailing. Environmental Science & Technology 2009, 43 (8), 2851-2857.

  46. Kim, J.; Xu, M.; Kahhat, R.; Allenby, B.; Williams, E. Designing and assessing a sustainable networked delivery (SND) system: hybrid business-to-consumer book delivery case study. Environmental Science & Technology 2009, 43 (1), 181-187.

  47. Williams, E.; Kahhat, R.; Allenby, B.; Kavazanjian, E.; Kim, J.; Xu, M. Environmental, social, and economic implications of global reuse and recycling of personal computers. Environmental Science & Technology 2008, 42 (17), 6446-6454.

  48. Xu, M.; Zhang, T.-Z.; Allenby, B. How much will China weigh? perspectives from consumption structure and technology development. Environmental Science & Technology 2008, 42 (11), 4022-4028.

  49. Xu, M.; Jia, X.-P.; Shi, L.; Zhang, T.-Z. Societal metabolism in northeast China: case study of Liaoning Province. Resources, Conservation & Recycling 2008, 52 (8), 1082-1086.

  50. Kahhat, R.; Kim, J.; Xu, M.; Allenby, B.; Williams, E.; Zhang, P. Exploring e-waste management systems in the United States. Resources, Conservation & Recycling 2008, 52 (7), 955-964.

  51. Xu, M.; Zhang, T.-Z. Material flows and economic growth in developing China. Journal of Industrial Ecology 2007, 11 (1), 121-140.

  52. Xu, M.; Jia, X.-P.; Shi, L.; Zhang, T.-Z. Accounting and analyzing material metabolism in the economic system of Liaoning Province. Resources Science 2006, 28 (5), 127-133. [in Chinese]

  53. Xu, M.; Zhang, T.-Z. Material input analysis of China economic system. China Environmental Science 2005, 25 (3), 324-328. [in Chinese]

  54. Xu, M.; Zhang, T.-Z. Material flow analysis of fossil fuel usage in the Chinese economy. Journal of Tsinghua University (Science and Technology) 2004, 44 (9), 1166-1170. [in Chinese]

Data Visualization

Data-rich visualizations and animations that are spin offs of research projects

GEN
High resolution file

Sector Ranking

Rankings of 1,435 sectors in the global economic network

500 taxis
Play

Taxis in Beijing

Interactive animation of 24-hour travel trajectories of 500 taxis in Beijing

GVCN
High resolution file

Sector Ranking

Rankings of 1,435 sectors in the global virtual carbon network

US network
High resolution file

US Economic Network

The US economy as a network of sectors

Sector dependency
High resolution file

Sector Dependency

Dependency of sectors in The US economy

US IO
High resolution file

US IO Table

The 2002 US input-output table

Taxis in Beijing Metro
Open

Taxi Trajectories

Taxi trajectories in Beijing metro area on a Sunday

Taxis in Beijing
Open

Taxi Trajectories

Taxi trajectories in Beijing on a Sunday

Taxis in Beijing
Open

Taxi Trajectories

Taxi trajectories in Beijing in a week

US 2007 IO
Play

US IO 2007

Interactive animation of the US 2007 IO table

US 2012 IO
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US IO Network 2012

Interactive animation of the US 2012 IO network