Transcript pptx - tempo

Intermountain
West Data
Warehouse –
Western Air
Quality Study
(IWDW-WAQS)
A Web System Application Framework for use of Remote
Sensing Obs in Air Quality Planning
Tom Moore –
WESTAR-WRAP
Shawn McClure
CIRA/CSU
NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
(FED)
Partners: NPS/ARD
Intermountain West
Data Warehouse
(IWDW)
Partners: NPS, BLM, USFS, EPA,
CO, WY, UT, NM
Partners: NPS, USFS
Databases
Websites
Hardware
Software
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: EPA, AL, FL, GA, KY, MS,
NC, SC, TN
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Relational database:
NPS Air Quality
Conditions & Trends Tools
(nps.gov)
Databases
Partners: NPS
• Schema design
• Data import & update
• Administration
Database
• Query design
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•
•
•
800,000,000 records
62 air quality networks
63 water quality networks
24 modeling and satellite datasets
Federal Land Manager
Environmental Database
Partners: NPS, USFS
File server:
Website
• ~107 Terabytes of online data
• ~100 Terabytes of offline data
• ~85 Terabytes downloaded/transferred
• 7 complete modeling platforms
Hardware
Intermountain West
Data Warehouse
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
Software
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: AL, FL, GA, KY, MS, NC, SC, TN
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NPS Air Quality
Conditions
& Trends Tools
Websites:
(nps.gov)
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•
Partners: NPS•
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•
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FED
SEMAP
IWDW
NPSCAT
TSS
IMPROVE
Federal Land Manager
Environmental Database
Websites
• Website design
• Web hosting
• Tool development
• Web services
Databases
Website
Hardware
Software
Intermountain West
Data Warehouse
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
Partners: NPS, USFS
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: AL, FL, GA, KY, MS, NC, SC, TN
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NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
Partners: NPS, USFS
Partners: NPS
Databases
Websites
Hardware
Software
Software
Intermountain West
Data Warehouse
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
• Data access libraries
Southeastern
• Data manipulation
Modeling, Analysis, and
• Visualization tools
Planning
• Data analysis
(SEMAP)
Partners: AL, FL, GA, KY, MS, NC, SC, TN
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NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
Partners: NPS, USFS
Partners: NPS
Databases
Websites
Hardware
Hardware
Software
• Server configuration
• Server maintenance
Intermountain West
Data Warehouse• Networking
• Troubleshooting & repair
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: AL, FL, GA, KY, MS, NC, SC, TN
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NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
(FED)
Partners: NPS
Intermountain West
Data Warehouse
(IWDW)
Partners: NPS, BLM, USFS, EPA,
CO, WY, UT, NM
Partners: NPS, USFS
Databases
Websites
Hardware
Software
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: EPA, AL, FL, GA, KY, MS,
NC, SC, TN
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NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
(FED)
Partners: NPS
Partners: NPS, USFS
Database
Websites
Hardware
Software
Intermountain West
Data Warehouse
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
http://views.cira.colostate.edu/fed
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: AL, FL, GA, KY, MS, NC, SC, TN
9
NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
Partners: NPS, USFS
Partners: NPS
Database
Website
Hardware
Software
Intermountain
West
http://views.cira.colostate.edu/semap
Data Warehouse
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
Partners: EPA, AL, FL, GA, KY, MS,
NC, SC, TN
10
NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
Partners: NPS, USFS
Partners: NPS
Intermountain West
Data Warehouse
(IWDW)
Database
Website
Hardware
Software
Southeastern
Modeling, Analysis, and
Planning
http://views.cira.colostate.edu/iwdw
(SEMAP)
Partners: NPS, BLM, USFS, EPA,
CO, WY, UT, NM
Partners: AL, FL, GA, KY, MS, NC, SC, TN
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IWDW-WAQS nested 36/12/4-km WRF/CAMx and CMAQ domains
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NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
Partners: NPS, USFS
Partners: NPS/ARD
Database
Website
Hardware
Software
Intermountain West
Data Warehouse
Partners: NPS, BLM, USFS, EPA, CO, WY,
UT, NM
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: AL, FL, GA, KY, MS, NC, SC, TN
http://www.nature.nps.gov/air/data/products/parks/index.cfm
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NPS Air Quality
Conditions & Trends Tools
Federal Land Manager
Environmental Database
(nps.gov)
(FED)
Partners: NPS/ARD
Intermountain West
Data Warehouse
(IWDW)
Partners: NPS, BLM, USFS, EPA,
CO, WY, UT, NM
Partners: NPS, USFS
Databases
Websites
Hardware
Software
Southeastern
Modeling, Analysis, and
Planning
(SEMAP)
Partners: EPA, AL, FL, GA, KY, MS,
NC, SC, TN
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NASA ROSES 2007:
Decision Support through Earth Science Research Results
Improving an Air Quality Decision Support System through the
Integration of Satellite Data
with Ground-based, Modeled, and Emissions Data
Uma Shankar (UNC) and Shawn McClure (CIRA/CSU) - co-PIs
Many collaborators, including Bret Schichtel (NPS) & Tom Moore (WESTAR-WRAP) at CIRA
Completed May 2011
Overall Project Goal
To enhance and add value to a currently operational air quality decision support system
(VIEWS/TSS) by integrating and utilizing satellite data from NASA satellites Aura, Terra,
Aqua, and CALIPSO.
Specific Project Goals
• Develop routine capture, analysis, and processing algorithms with high temporal and
spatial resolution to provide land use/land cover data as inputs to emissions and air
quality modeling
• Achieve more complete temporal and spatial resolution of activity data and emission
rates from natural and anthropogenic emission sources in remote areas and from
individual sources and source clusters
• Obtain multiple-dimensional vertical profiles and column measurements of pollutants
to improve model inputs and provide evaluation data for gridded chemistry-transport
models such as CMAQ
• Develop advanced analysis tools to better understand the relevant atmospheric
processes and their representation in the CTMs
• Visualize and analyze satellite data in combination with existing monitoring, emissions,
and modeling data within a unified decision support platform
Simplified, CIRA-specific project goal
Make it easier to…
• find
• visualize
• query
• download
…satellite and modeled data in conjunction with ground-based
data
Fulfilling our goal: Getting the data
Map Viewer: Three layers combined
Fulfilling our goal: Importing and integrating the data
Roadmap: Linking data to relevant photos and imagery
Exceptional event metadata (such as fires) can be stored and dynamically
associated with data, photos, and imagery at run time in order to provide
quick cross-referencing and discovery of related data. Thus, satellite and
modeled data can be quickly associated with aerosol events once these
linkages are complete.
Biscuit fire impacting Crater Lake in 2002
VIEWS/TSS (now IWDW) Interoperability: Services and standards
“Interoperability”: The ability of diverse systems and organizations to work
together to exchange and utilize information.
To facilitate, VIEWS and now IWDW offers the following services and features:
• Discovery, retrieval, and exchange of data and metadata
• On-the-fly transformation and formatting of data and metadata
• Upload and management of user-supplied data and metadata
• Generation of visualization and analysis products
• Availability of “embeddable” components and tools
• Support of OGC web standards for spatial data exchange
VIEWS/TSS and IWDW Data Value Chain Diagram
Background / Boundary
Conditions evaluations:
MOZART
GEOS-Chem
(to add AM3, others)
+++++++++++++++++++++++++++++++++++++++++++++++++++++++
Observations vs. Boundary Condition /
Background Monthly Mean MDA8 Ozone
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Animations of Modeled Daily Max
Concentrations
Background contribution
Difference plots for background minus
U.S. sources
O3, NOx, CO, PM2.5
+++++++++++++++++++++++++++++++++++++++++++++++++++++++
Animations of Daily Max Concentrations
for O3 and Dust Boundary Tracers
Data Warehouse and Modeling Center
http://views.cira.colostate.edu/tsdw/
Boundary conditions plots:
O3, Ox (O3+NO+NO2+PAN)
Coarse Dust (CCRS), Fine PM (FPRM+FCRS)
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Other Modeling efforts re: boundary/background
(certainly not all…)
AEROCOM – international science initiative on
aerosols and climate (http://aerocom.met.no/data.html
May 2016 ORD conclusions - changing emission patterns
across the northern hemisphere will impact background
pollution in a region. Sensitivity analysis indicates that:
EPA-ORD WRFCMAQ Coupled Model
– the background is increasing in North America and varies seasonally
– the source region contributions and their relative importance also vary seasonally
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NAAQS Implementation and Maintenance
Data for future infrastructure and transport SIPs
Exceptional Events
Develop technical support data and analysis
protocols
Implementation of Regional Haze SIPs
Identify and execute technical work needed for
201821 plans
WRAP Board
of Directors
Technical
Steering
Committee
Needs of sub-regional groups of states
Currently oil and gas, fire
Similar efforts in past – dust, BART, other topics
WRAP Staff
Work Groups
Project Teams
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Sources of O3 in the Western U.S.
O3 Source
Meteorological
Characteristics
Chemical characteristics
CAA
Controllable
Local
photochemical
buildup
Stagnation, high temperatures.
CO/NOx/VOCs/PM consistent with
local sources
Y
Regional transport from major
source regions (e.g., California)
- currently not well
characterized
CO/NOy/VOCs consistent with
upwind sources + chemistry
Y
Upper trop/Lower
strat intrusions
(UTLS)
Post-cold front
Broad spatial distribution
(high O3 in non-urban areas)
Very dry air.
N
Very long-range
transport (VLRT)
Important at higher elevation.
Subsidence and mixing into the
boundary layer can enhance
local concentrations.
Dry.
Can be hard to distinguish from
UTLS without good chemical data.
N
Warm.
Can be stagnant or not. Can
be regional or large distant
fires.
Chemistry complex & different from
typical urban.
O3 enhancements not always seen.
O3-PM often poorly correlated.
PM/CO/NOy always well correlated
and ratios very different from
typical urban.
N
Regional transport
(domestic sources)
Wildfire smoke
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Uncertainty in model estimates of U.S. Background
CAMx simulations for 2007 and 2008 at Canyonlands National Park – Eastern UT
EPA 2007 CAMx model platform:
Background contributions of 36-57
ppb; still substantial U.S.
anthropogenic contribution to ozone.
WRAP WestJumpAQMS 2008
CAMx model platform:
Background contributions of 50-72
ppb, much larger than OAQPS
modeling.
Same methodology - reasons for
modeled differences are not fully
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understood
Five Ozone Planning Needs – western U.S.
1. Ozone NAAQS planning – (realistically) requires
photochemical modeling for SIP attainment demonstrations
for nonattainment areas.
2. Ozone transport SIPs – photochemical source apportionment
modeling is tool of choice to quantify U.S. Ozone background
as well as transport between states and jurisdictions.
In the West
under CAA,
whom to do
which ?
3. Identification of Ozone exceptional events caused by
stratospheric intrusion and wildfires – can require variety of
observations & data analysis, supplemented with global /
regional scale photochemical models and regression models.
Alone or
together ?
4. Identification of international transport of Ozone for §179B
demonstrations: requires nested global and regional scale
photochemical modeling to evaluate international transport of
Ozone.
5. Identification of §182 Rural Transport Areas – combination of
data analysis and photochemical modeling.
- States/Locals
- Regional
- Federal
Area Burned for U.S. Wildfires (NIFC)
The last decade has seen a significant increase in the area burned.
Approximately 70% of these fires are in the Western U.S.
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Western Class 1 area Environment
PRELIMINARY DESIGN
VALUE by COUNTY*
(using AQS data 2013-2015)
> PM 2.5 2012
Standard
> Ozone 2015
Standard
Class 1 area
Alaska and Hawaii at reduced scale
> Both PM 2.5 and
Ozone Standards
* Based on monitor with
highest value in county
Western region characterized by complex terrain, several climactic zones, oceanic and international
source transport, dispersed population centers, large land mass, mix of nonattainment areas, unique
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geologic sources
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Acknowledgements
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State and federal cooperators – IWDW-WAQS
Gail Tonnesen and Rebecca Matichuk, EPA R8
Mike George, NPS Intermountain Region
Shawn McClure, Dustin Schmidt, & Rodger Ames, CIRA
Ralph Morris and colleagues, Ramboll-Environ
Zac Adelman and colleagues, UNC
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additional slides
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IWDW Update
Modeling Platform Inventory and File Transfer Status
Internal (WAQS-developed)
2008b
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WestJumpAQMS Met
3SAQS 2008b emissions - Base and Future
3SAQS 2008b CAMx - Base and Future
2011a
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3SAQS Met
3SAQS 2011a emissions (Phase I O&G) - Base and Future
3SAQS 2011a CAMx - Base and 2020 Future Case
3SAQS 2011a CMAQ output - Base
2011b
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3SAQS Met
WAQS Winter O3 Met
WAQS 2011b emissions (Phase II O&G) Base and 2025 Future Case
WAQS 2011b CAMx – Base and Future
WAQS 2011b CMAQ - Base and Future
2014
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WAQS Met (WRF, WRFCAMx, MCIP)
Other modeling platform components pending new WAQS contract
External (non-WAQS-developed) modeling studies
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CARMMS 1.0/Mancos Shale – underway
Utah ARMS – pending
Denver RAQC O3 SIP – pending
OKT - CAPs, HAPs, GHG emissions for O&G and mining sectors - pending
IWDW Update
Summary of Data Requests
2016
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Organic PM Reduced-form modeling for public health (Cornell) – 2011b
CARMMS 2.0 (BLM) – 2011b
Crescent Point EIS (BLM) – 2011b
Source Apportionment displays (API) – 2011a
CMAQ for FRAPPE (EPA R8) – 2011a/b
Met model performance (CIRA) – 2011a/b
Since April 2015
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SNMOS (State of NM) – 2011b CAMx
CMAS Training (UNC-IE) – 2011b CMAQ inputs
Project for USEPA (AECOM) – 2008b
Background Ozone Analysis (EPA R8) – 2011 WRF
Denver RAQC Ozone SIP (Denver Regional Air Quality Council / State of CO) – 2011a
Ozone sensitivities in Denver to cultivation emissions (UNC) – 2008b
BLM CO UFO oil and gas EA (BLM CO) - 2011 WRF
Single Source AQRV Analysis (NPS) – 2008b
Analysis of FRAPPE and DISCOVER-AQ (NCAR/CU) – 2011a
Methane VOC Control Sensitivity Study (Clean Air Task Force) – 2008b Future
Source Apportionment Modeling for Nitrogen in GYA (NPS/CIRA) – 2011a
Earlier
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16 Projects (NEPA, Research, NPS, FWS AQRV analysis, etc.)
IWDW Update
Summary of Computing and Data Storage Resources
Servers
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Views (Windows web server)
Viking (Linux ftp file server to host modeling platform data and service modeling platform
data requests)
Vibe (Windows SQL database server to hosts monitoring data; ancillary web server)
Vader (Windows SQL database server)
Viper (Windows staging server)
IWDW Team development machines
Online Storage Capacity
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109Tb (Viking)
External Disk Capacity
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100Tb of “shelf” storage for redundant backups and physical disk transfers
Future Allocations
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>100Tb on additional server for modeling platform data
>100Tb of additional “shelf” and NAS storage
IWDW Update
Immediate future - Modeling Platform Development Elements
2014 base case emissions, met domain expansion
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2014 NEIv1 and “best available” quasi-natural emissions
O&G comprehensive update north-south from AZ-NM to MT-ND basins
Met modeling at 4km for same north-south area and east-west KS-CO to UT-NV
2014 Global Models’ evaluation and assessment
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Use as CONUS regional model boundary conditions
PM, Ozone, other species
Develop and document evaluation methods
2014 base case air quality modeling /evaluation
• Apply criteria used in earlier IWDW-WAQS evaluations
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Option for 2015/16 years – lighter base year modeling effort/evaluation
Future projection years
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Anthropogenic emissions – 2020/21, 2025, 2028, 2030
Quasi-natural emissions – scenarios for biogenics, fire, ammonia, et cetera
Option for modified future met based on climate change scenarios
Future years’ air quality modeling runs
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Evaluate with MATS and pending Regional Haze reasonable progress goals
Serve as “No-Action” alternatives as inputs to NEPA studies