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Embrace complexity:
Visions for the future of environmental
(and air quality) science & engineering
Drew R. GentnerAssistant Professor
Chemical & Environmental Engineering
Yale University
Jan. 8th, 2016
AEESP/NSF
Grand Challenges
Workshop
Outline:
• Next generation
approaches for
environmental engineering
research
• Needs and trends in air
quality research
• Preparing the coming
generation of scientists and
engineers
Embrace complexity:
Visions for the future of environmental
(and air quality) science & engineering
Outline:
• Next generation
approaches for
environmental engineering
research
• Needs and trends in air
quality research
• Preparing the coming
generation of scientists and
engineers
Embrace complexity:
Visions for the future of environmental
(and air quality) science & engineering
“Goals:
• Identify areas of environmental research currently experiencing high
growth, both those consistent with traditional Environmental
Engineering and Science research themes, as well as those that are
currently outside the discipline’s traditional themes;
• Consider recommendations with respect to how the Environmental
Engineering community can better position itself to more rapidly
expand into high growth research areas;
• Develop suggestions regarding how curricula might be adapted to
prepare students for research or work in these new areas.”
Realizations: The (EnvE) devil is in the details…
Environmental systems/processes (including air & climate) are
exceedingly complex across chemical, spatial, and temporal
scales
Realizations: The (EnvE) devil is in the details…
• Environmental processes are very heterogeneous
across spatiotemporal scales
Environmental systems/processes (including air & climate) are
exceedingly complex across chemical, spatial, and temporal
scales
New York City Air Quality Survey
Realizations: The (EnvE) devil is in the details…
• Environmental processes are very heterogeneous
across spatiotemporal scales
Environmental systems/processes (including air & climate) are
exceedingly complex across chemical, spatial, and temporal
scales
New York City Air Quality Survey
Realizations: The (EnvE) devil is in the details…
• Environmental processes are very heterogeneous
across spatiotemporal scales
• Exceptional chemical diversity = 100,000’s of
compounds in the atmosphere
Environmental systems/processes (including air & climate) are
exceedingly complex across chemical, spatial, and temporal
scales
Snapshots of multi-dimensional
chromatography and multi-dimensional
mass spectrometry
Realizations: The (EnvE) devil is in the details…
• Environmental processes are very heterogeneous
across spatiotemporal scales
• Exceptional chemical diversity = 100,000’s of
compounds in the atmosphere
Environmental systems/processes (including air & climate) are
exceedingly complex across chemical, spatial, and temporal
scales
Snapshots of multi-dimensional
chromatography and multi-dimensional
mass spectrometry
Get ready: With advancements in the sensitivity and
efficiency of analytical instrumentation, the quantity and detail
of data streams are rapidly increasing
Rapidly growing capabilities for sensors and networks
• Small, affordable instruments
and the potential for
dispersed networks across
spatial scales
• New methods and tools for a
new era – capacity to probe
dynamics with
spatiotemporal resolution
Rapidly growing capabilities for sensors and networks
• Small, affordable instruments
and the potential for
dispersed networks across
spatial scales
• New methods and tools for a
new era – capacity to probe
dynamics with
spatiotemporal resolution
• Commercial trends: Growing
number of good sensor and
network system companies
• Required: Engineering
skills and extensive
QC/QA
Rapidly growing capabilities for sensors and networks
• Small, affordable instruments
and the potential for
dispersed networks across
spatial scales
• New methods and tools for a
new era – capacity to probe
dynamics with
spatiotemporal resolution
• Commercial trends: Growing
number of good sensor and
network system companies
• Required: Engineering
skills and extensive
QC/QA
Small-scale sensors are increasingly capable of producing
research-grade data that can catalyze a new generation of
environmental engineering research.
Think on the scale of your environment.
Think in networks and systems.
Embrace the complexity.
Multi-platform opportunities for transferable insights
• Multiplatform studies that connect the lab and the field (and
modelers) can constructively tackle this complexity
Multi-platform opportunities for transferable insights
• Multiplatform studies that connect the lab and the field (and
modelers) can constructively tackle this complexity
• Laboratory systems (simplified & complex), field sites
(stationary & mobile), sensor networks, airborne
measurements, satellites,…
Multi-platform opportunities for transferable insights
• Multiplatform studies that connect the lab and the field (and
modelers) can constructively tackle this complexity
• Laboratory systems (simplified & complex), field sites
(stationary & mobile), sensor networks, airborne
measurements, satellites,…
Multi-platform opportunities for transferable insights
• Multiplatform studies that connect the lab and the field (and
modelers) can constructively tackle this complexity
• Laboratory systems (simplified & complex), field sites
(stationary & mobile), sensor networks, airborne
measurements, satellites,…
• Tremendous potential of
remote sensing: Integrate
airborne and satellite
measurement capabilities
into your research
Multi-platform opportunities for transferable insights
• Multiplatform studies that connect the lab and the field (and
modelers) can constructively tackle this complexity
• Laboratory systems (simplified & complex), field sites
(stationary & mobile), sensor networks, airborne
measurements, satellites,…
• Tremendous potential of
remote sensing: Integrate
airborne and satellite
measurement capabilities
into your research
Coming soon!
Low Earth Orbit
Geostationary Satellites
Picture: CHRONOS (UCAR)
Sleeping in the bed you made (tackling the data)
A new generation of analytical and statistical capabilities
• Need to build the expertise and statistical methods resources
that are capable of deciphering the high resolution data
• Get comfortable with designing and using automated data
processing and analysis
• Further development of multivariate tools (e.g. positive matrix
factorization, Bayesian statistics, machine learning)
• Capitalize on the surge in computing resources
• High performance computing centers
• Single desktop processing power
• Need automated programs and workflows for multi-
dimensional analytical chemistry techniques
• Non-targeted analyses of complex chemical mixtures
Collaborative research at the nexus
• Inter-, multi-, and trans-
disciplinary research
collaborations at the nexus
are well-suited to tackle the
inherent complexity
• Provides the capabilities to
probe connections across
multifaceted systems
• Capitalize on opportunities
to work closely with
researchers in:
• Public health
• Climate
• Energy
Environmental engineering
and sustainability nexus
Air quality’s role in environmental pollution
Air pollution kills
8 million people
per year
The single largest
environmental health
risk in the world
1/8th of
global
deaths= =
Sources: W.H.O. (for 2012)
Air quality’s role in environmental pollution
Air pollution kills
8 million people
per year
Sources: W.H.O. (for 2012) & D.D. Parrish (NOAA)
The single largest
environmental health
risk in the world
1/8th of
global
deaths= =
A call help developing
regions and megacities:
• Urbanization, climate
change, and increased
energy use will likely
exacerbate existing
health effects
• Disproportionately
affects disadvantaged
populations
Air quality’s role in environmental pollution
Air pollution kills
8 million people
per year
A call help developing
regions and megacities:
• Urbanization, climate
change, and increased
energy use will likely
exacerbate existing
health effects
• Disproportionately
affects disadvantaged
populations
The single largest
environmental health
risk in the world
1/8th of
global
deaths= =
U.S. EPA Standard
Sources: W.H.O. (for 2012) & D.D. Parrish (NOAA)
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
• Research on source characterization and emissions
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
• Research on source characterization and emissions
• Interconnectivity of air quality impacts with climate and
health effects (incl. net effects of emitted aerosols and
co-emitted gases)
• Decarbonizing energy and transportation systems
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
• Research on source characterization and emissions
• Interconnectivity of air quality impacts with climate and
health effects (incl. net effects of emitted aerosols and
co-emitted gases)
• Decarbonizing energy and transportation systems
• Characterizing the atmosphere – much remains unknown
• Known unknowns and the unknown unknowns
• Transformations via multi-phase chemistry
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
• Research on source characterization and emissions
• Interconnectivity of air quality impacts with climate and
health effects (incl. net effects of emitted aerosols and
co-emitted gases)
• Decarbonizing energy and transportation systems
• Characterizing the atmosphere – much remains unknown
• Known unknowns and the unknown unknowns
• Transformations via multi-phase chemistry
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
• Research on source characterization and emissions
• Interconnectivity of air quality impacts with climate and
health effects (incl. net effects of emitted aerosols and
co-emitted gases)
• Decarbonizing energy and transportation systems
• Characterizing the atmosphere – much remains unknown
• Known unknowns and the unknown unknowns
• Transformations via multi-phase chemistry
• Indoor air quality and chemistry
Needs and trends in EnvE research on air quality(Based in part on survey of air quality EnvE community)
• Clear need for research at the nexus of air, climate, health,
and energy
• Multi-platform connections across lab, field, and models
• Research on source characterization and emissions
• Interconnectivity of air quality impacts with climate and
health effects (incl. net effects of emitted aerosols and
co-emitted gases)
• Decarbonizing energy and transportation systems
• Characterizing the atmosphere – much remains unknown
• Known unknowns and the unknown unknowns
• Transformations via multi-phase chemistry
• Indoor air quality and chemistry
Preparing the coming generation of students
• Need to foster complete engineering skill sets in our
undergraduate and graduate environmental engineering
students
• Computer programming – datasets and methods are too
big to tackle efficiently with Excel (Igor Pro, MatLab, R,
etc.)
• Sensors and networks require electrical engineering and
computer science skills (at least for the near future)
• Part engineers, part statisticians: Need to be comfortable
with advanced statistics to analyze driving factors in the
environment (e.g. sources, physical/chemical dynamics,
transport)
• Fluency in climate and energy sciences
Acknowledgements
For their helpful survey responses:
Chris Cappa (UC Davis)
Cort Anastasio (UC Davis)
Allen Goldstein (UC Berkeley)
Neil Donahue (CMU)
Chris Frey (NC State)
Andy Grieshop (NC State)
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