University of Michigan
College of Engineering
Department of Civil and Environmental Engineering
Department of Atmospheric, Oceanic and Space Sciences









My research interests focus on characterizing complexity and quantifying uncertainty in environmental systems with the goal of improving our understanding of these systems and our ability to forecast their variability.  My current research interests focus on water quality monitoring and contaminant source identification, use of remote sensing data for earth system characterization, and atmospheric greenhouse gas emission and sequestration estimation.  The common theme of my research is the development and application of statistical and geostatistical data fusion methods for optimizing the use of limited in situ and remote sensing environmental data.  I am also interested in the environmental policy, economic and legal impact and applicability of environmental research.
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Data Fusion for Water Quality Monitoring and Forecasting

The broad availability of clean water is one of the biggest achievements of environmental engineering as a profession.  Despite the great technological and regulatory achievements that aim to protect potable and recreational water uses, however, water quality is still primarily addressed in a “real-time” framework.  The development of water quality forecasting systems is essential to long-term sustainable water resource management.  In anticipation of this goal, new tools are needed to merge water quality data in statistically rigorous manner while making optimal use of the information provided by the available measurements.  Unlike weather monitoring and forecasting, water quality assessment will always suffer from a relative sparsity of data due to the difficulty and expense associated with data collection.  As a result, a probabilistic framework is essential to the success of any water quality monitoring framework.  Our group’s work in this area focuses on inverse modeling methods for contaminant source identification, geostatistical data assimilation methods for surface and ground water quality monitoring, and statistical models for estimating the spatial and temporal distribution of groundwater contaminant plumes.  The long-term goal of this work is the development of water quality forecasting tools analogous to the existing weather forecasting products.  Such a data assimilation framework for water quality forecasting would have a great impact on environmental management and protection of human health.

Recent and ongoing projects:

   Development of Geostatistical Data Assimilation Tools for Water Quality Monitoring
Investigators:     Anna M. Michalak (PI)
Students:          Yuntao Zhou
Sponsor:           NSF Chemical, Bioengineering, Environmental, and Transport Systems (CBET) CAREER program
Links:               NSF project summary
  Sampling and Inversion Methods for Quantifying Effect of Incomplete Subsurface Characterization on Uncertainty Associated with Recovery of Contamination History
Investigators:     Anna M. Michalak (PI)
Students:          Shahar Shlomi
Sponsor:           NSF Chemical, Bioengineering, Environmental, and Transport Systems (CBET)
Links:               NSF project summary
  Incorporating Groundwater Transport Information in Contaminant Plume Distribution Estimation
Investigators:    Shahar Shlomi
Collaborators:   Anna M. Michalak, Tissa Illangasekare (Colorado School of Mines), Toshihiro Sakaki (Colorado School of Mines)
Sponsor:          Rackham Graduate Student Research Grant

For additional information, please refer to publications.


Assessing Anthropogenic Impacts on Biogeochemical Cycles

Human activity has had a significant impact on the cycling of trace gases, nutrients, water, and energy in the Earth system.  Understanding the Earth’s current climate and predicting its future variability requires knowledge about the relationships controlling the feedback among the various components of the Earth system.  Our group’s work in this area focuses on constraining the global and regional budgets of carbon dioxide through the development of new geostatistical inverse modeling tools, attributing observed variability to biospheric, oceanic, and anthropogenic activities, and developing tools for merging data from diverse types of measurements taken across various spatial and temporal scales.  In the long term, as restrictions on carbon emissions become more commonplace, the tools that we develop could be used to inform systems such as carbon markets and national/international treaties that will require scientific validation of carbon emission reduction and sequestration goals.

Recent and ongoing projects:

Constraining North American Fluxes of Carbon Dioxide and Inferring their Spatiotemporal Covariances through Assimilation of Remote Sensing and Atmospheric Data in a Geostatistical Framework
Investigators:       Anna M. Michalak (PI), Adam Hirsch, Arlyn Andrews, John C. Lin
Students:            Sharon Gourdji, Kim Mueller
Postdoc fellowsDeborah Huntzinger, Vineet Yadav
Sponsor:             NASA SMD North American Carbon Program
Links:                 NASA project summary
  High-Resolution Wind Fields for Constraining North American Fluxes of Carbon Dioxide in a Geostatistical Inverse Modeling Framework
Investigators:       Anna M. Michalak (PI), John C. Lin, Thomas Nehrkorn
Sponsor:             NASA Project Columbia High End Computing Facility
Links:                 Entry quad chart
  Evaluating the Biospheric and Fossil Fuel Components of North American CO2 Flux Using Auxiliary Environmental Data Within a Geostatistical Inverse Modeling Framework and Implications for Carbon Management
Investigators:       Sharon Gourdji
Collaborators:      Anna M. Michalak
Sponsor:             NASA Earth System Science Fellowship
Links:                 NASA selection list
  Evaluation of Process-Based Carbon Dioxide Flux Drivers through Regional Geostatistical Methods
Investigators:       Kim Mueller
Collaborators:      Anna M. Michalak, Peter Curtis, Vineet Yadav
Sponsor:             NSF-IGERT Fellowship in Biosphere-Atmosphere Research and Training (BART)
Project period:     2006 - 2008
Links:                 BART project summary
  Geostatistical Analysis of NOAA Climate Monitoring and Diagnostics Laboratory Carbon Dioxide Data for 1997-2001
Investigators:     Anna M. Michalak (PI)
Students:           Kim Mueller, Sharon Gourdji
Sponsor:            NOAA Earth System Research Laboratory
Project period:    2005 - 2007
  Use of Remote Sensing Data and Geostatistical Inverse Modeling for Validating Process-based Parameterizations in Biospheric Models
Investigators:      Anna M. Michalak (PI)
Students:           Yuntao Zhou
Sponsor:            NASA Michigan Space Grant Consortium Seed Grant
Project period:    2006 - 2007
  Auxiliary Environmental Data Assimilation in Geostatistical Inverse Modeling
Investigators:      Anna M. Michalak (PI)
Students:           Kim Mueller, Sharon Gourdji
Sponsor:            Elizabeth Caroline Crosby Research Fund, NSF ADVANCE at the University of Michigan
Project period:    2005 - 2006
  Quantification of Global Sources and Sinks of Methane Using Geostatistical Inverse Modeling
Investigators:      Anna M. Michalak
Sponsor:            UCAR Visiting Scientist Programs, NOAA Postdoctoral Program in Climate & Global Change
Project period:    2003 - 2004

For additional information, please refer to publications.


Global estimates

Sample influence function

Use of Remote Sensing Data for Earth System Characterization

Existing and upcoming remote sensing data products offer a unique opportunity for improving our understanding of the earth system, but they require new and rigorous statistical methods for merging information from data collected at different spatial and temporal resolutions.  Several of our ongoing research projects focus on the use of remote sensing data for characterizing environmental systems.  This work involves both existing instruments that provide data that can be used in conjunction with in situ measurements, and upcoming instruments aimed specifically at characterizing the global carbon cycle.  Through collaboration with the Orbiting Carbon Observatory (OCO) satellite team, we are developing sampling and gap-filling strategies for this satellite, which will allow it to characterize the spatial and temporal variability of atmospheric CO2.  This satellite will be launched in 2008, resulting in a unique atmospheric dataset that will make it possible to constrain the carbon budget with greater precision than is currently possible.  In several related new projects, we are using the current CO2 measurement network to understand the influence of processes and parameters that can be measured by satellite on carbon fluxes at global and regional scales.

Recent and ongoing projects:

Mapping Global CO2: Development and Application of Geostatistical Algorithms for Gap Filling and Uncertainty Assessment for the Orbiting Carbon Observatory
Investigators:     Anna M. Michalak (PI), Noel Cressie, Amy Braverman
Students:          Abhishek Chatterjee
Sponsor:           NASA SMD Carbon Cycle Science
Links:               NASA project summary
  Characterization of Spatio-temporal Covariance of Remote Sensing Data from Earth-observing Satellites with Applications to Data Fusion, Sampling Design, and Measurement Gap-filling
Investigators:     Charles Miller (PI), Anna M. Michalak (Co-I), Amy Braverman
Students:          Abhishek Chatterjee
Sponsor:           Jet Propulsion Laboratory Strategic University Partnership Program
  Estimation of Over-Lake Precipitation using In Situ and Radar Data
Investigators:     Abhishek Chatterjee
Collaborators:    Anna M. Michalak, Carlo DeMarchi
Sponsor:           Great Lakes Summer Student Fellowship Program
Project period:   2007
  Development of a Subsampling Strategy for the Orbiting Carbon Observatory Satellite
Investigators:    Anna M. Michalak (PI)
Students:          Alanood Alkhaled
Sponsor:           NASA Jet Propulsion Laboratory
Project period:   2006 - 2008
  Geostatistical Analysis of the Spatial Covariance Structure of Modeled Column Average Dry Air Carbon Dioxide Mole Fraction Distributions
Investigators:     Anna M. Michalak (PI)
Students:          Alanood Alkhaled
Sponsor:           NASA Jet Propulsion Laboratory
Project period:   2005 - 2006

For additional information, please refer to publications.

Representation error

XCO2 variability

Other Ongoing Projects

In addition to the main research areas described above, our research group also collaborates with the University of Michigan School of Public Health on projects related to exploring the links between air quality and human health.

Role of Diesel and Other Vehicular Exhaust in Exacerbation of Childhood Asthma
Investigators:     Thomas G. Robins (PI), Anna M. Michalak (Co-I), S. Batterman, B. Israel, T. Lewis, E. Parker
Sponsor:            National Institutes of Health
  The Detroit Asthma Morbidity, Air Quality and Traffic (DAMAT) Study
Investigators:    R. Wahl (PI), Anna M. Michalak (Co-PI), S. Batterman, E. Wasilevich, M.L. Hultin, B. Mukherjee, K. Dombkowski 
:           Environmental Protection Agency

Last modified: 05/21/10 by  Anna  M. Michalak