NASA ROSES08: Applying NASA Observations, Models and IT for Air Quality Proposal

Submitted Proposal PDF This wiki page still needs to be updated, see pdf for final version.

Title: Applying NASA Observations and Models for Air Quality: DSS for the Exceptional Event Rule.

Proposal Summary

The objective of this project is to develop a decision-support system (DSS) for the implementation of the new Exceptional Event (EE) Rule, which permits States to flag air quality (AQ) data caused by exceptional events, such as forest fires and dust storms. The Rule requires States to provide quantitative evidence for exceptional source contributions. Based on the reported evidence, EPA decides if the EE flag is justified.

Preparing and evaluating the EE evidence is a tedious, costly and technically challenging task for the State and EPA offices. A powerful EE DSS tool set will be developed that will allow users to (1) explore and analyze data for specific EEs (2) prepare EE flagging reports (3) evaluate and approve the EE reports. For the States, the powerful EE tools will make the event documentation easy and efficient, while for EPA, the standardized DSS tools will make the decisions more consistent and robust.

The project will achieve its goals primarily by linking, harmonizing and integrating and otherwise ‘connecting the pieces’ contributed by its autonomous core constituent partners represented by the projects GIOVANNI, NAAPS, VIEWS, AIRPACT and DataFed. The a wide range of distributed multi-sensory data (including MODIS, OMI, CALIPSO), suitably processed and packaged for the EE DSS using flexible web service orchestration. The EE DSS data browsing, processing, reporting and communication facilities will be combined and presented through a user-friendly EE DSS portal.

The broader benefits of this are project will include deeper scientific understanding of EEs and innovative application of remote sensing and information technologies to AQ regulatory processes. Building the EE DSS will also contribute to the creation of a persistent core network for supporting other AQ applications. The network will also exemplify multi-organization/agency collaboration using the principles and architecture of the Global Observing System of Systems.

Decision-making Activities and Baseline Performance

The proposed DSS is aimed at improving the management of the Nation’s air quality. The quality of ambient air is maintained at healthy levels by the setting and compliance with National Ambient air Quality Standards (NAAQS) based on measurements using Federal Reference Method (FRM) monitors. In 2006, the NAAQS for PM2.5 was significantly revised by reducing the daily standard from 65 to 35 ug/m3 and recently for ozone from 85 to 75 ppb. Since the 2006 NAAQS amendments, both PM2.5 and ozone are subject to the new Exceptional Event (EE) Rule which allows the exclusion of data strongly influenced by impacts from "exceptional events," such as smoke from a wildfire or dust from abnormally high winds. States "flag" data for those days that they believe to be impacted by exceptional events. Such flagged days, if concurred with by EPA, may be given special consideration in the compliance calculations. The tightening of the short-term standards and the EE Rule shifts the attention from controlling the yearly average to the reduction and control of short-term, episodic air pollution.

The EE Rule identifies different categories of uncontrollable events: (a) Exceedances Due to Transported Pollution (Transported African, Asian Dust; Smoke from Mexican fires; Smoke & Dust from Mining, Agricultural Emissions) (b) Natural Events (Nat. Disasters.; High Wind Events; Wildland Fires; Stratospheric Ozone; Prescribed Fires) and (c) Chemical Spills and Industrial Accidents; Structural Fires; Terrorist Attack.

Fig. 1.

The decisions related to the Exceptional Event flagging and exclusion are performed at three organizations: States, Regional EPA Offices and Federal EPA, as shown in the schematic Fig. 1. The States need to decide whether a particular sample is to be flagged and prepare a flag justification report. The EPA Regional Offices evaluate the submitted flagged requests and approve/deny the requested flag. The role of the federal EPA is to ensure regional consistency of the flag justification evaluations, resolution of difficult cases and to provide general help interpreting the EE Rule.

Currently, the implementation of the EE Rule is ad hoc and unstructured. The guidelines for preparing the flag justifications are intentionally somewhat vague. As a consequence, the current justifications are highly variable; some States submit very detailed and technical reports while others are brief and descriptive. Also, the EPA Regional Offices currently use ad hoc qualitative methods to understand the events, to evaluate the claims, and to make their recommendation. The lack of formal procedures and tools makes evaluation difficult and uneven.

Preparing and evaluating the evidence for flagged data is a technically challenging task both for the State and the Regulatory offices. It requires: Accessing a diverse array of data sources illustrating various aspects of the exceptional event; Integration of the heterogeneous data sources that are frequently incomplete and incompatible; Performing detailed data analysis and to establish "clear causal relationship" between the EE and the increased exceedance and the Rule requires a demonstration that the exceedance would not have occurred but for the presence of the EE. The flagging procedure has to be in accordance with section 40 CFR 50.14 (c)(3)(iii) of the EE rule.

Many State and Regional EPA offices lack the means for executing these challenging tasks. Currently, States are scanning their monitoring data for anomalous patterns and use media reports of fires, dust storms and other EEs. The impact of exceptional sources on the violating monitor site is justified in a qualitative sense. Formal DSS tools to support the States are currently not available. The evaluation of the State-provided reports by EPA also lacks supporting tools. Fortunately, there are now outstanding opportunities to develop credible and reasonably simple computer-supported methods for the preparation of flagging documentation through an EE DSS.

The proposed EE DSS will be used differently by the States and EPA. The flags and the flag justification reports are prepared by the individual States hence, the primary users of the DSS are the States. However, since the EE flag claims are evaluated by Regional EPA offices, they also represent users of EE DSS. The Federal EPA has a broader range of roles. It develops the NAAQS and the associated Rules, which requires considerable research on the nature of ESs and implementation options. EPA also develops EE reporting templates as guides to the States. The Federal EPA also plays a key role in the design of the EE DSS. In fact, EPA has been supporting and interactively guiding our CAPITA group to explore the design options for EE DSS. The preparation of this NASA ROSE proposal has also benefited greatly from the support, the ideas and the feedback from the federal EPA.

The EE DSS will save time for both the States and the EPA. The preparation of the qualitative reports is currently time consuming. One rough estimate provided by an officer of the Federal EPA is that currently it takes about a week of State analyst's time to prepare an EE report. Currently there are hundreds of flagged data samples, of which justification requires several person-years of effort. As the implementation of the EE Rule proceeds and the States get more familiar with data exclusion procedures, it is anticipated that the number of flagged samples will increase by at least an order of magnitude to thousands of flagged samples per year. The proposed EE DSS is anticipated to reduce the report preparation time from about one week to less than four hours per flag. This factor of 10 time-savings can then be used more prudently on analyzing and understanding the State's air quality pattern or exploring mitigation options. Furthermore, the quality of EE flag evaluation decisions will be more objective and uniform.

Earth Science Research Results

The EE Rule offers outstanding opportunity to infuse NASA data products and information technologies deep into EPA's operational activities on managing air quality. The global-scale, high spatial resolution satellites remote sensing data are particularly suitable for detecting and quantifying natural and manmade air pollution events. (dust smoke, haze). The intense aerosol and gaseous pollutant signal during these events have made satellites indispensable in detecting and following the evolution of such events. Additional AQ benefits of satellites is on evaluating and improving emission inventories for NOx, biogenic VOC and particulates.

Unfortunately, until recently, the role of satellites in EPAs air quality regulatory process was very modes. In fact, the EE Rule is the only air quality regulation that we are aware of, where the use of satellites is explicitly encouraged, as seen on the quote snippets from the EE Rule in Federal Register (Ref): Information demonstrating the occurrence of the event.. ... satellite-derived pixels indicating the presence of fires; satellite images of the dispersing smoke; Identification of the spatial pattern of the affected area (the size, shape, and area of geographic coverage). This could include, for instance, the use of satellite or surface measurement data; The simplest demonstrations could consist of newspaper accounts or satellite images to demonstrate that an event occurred…

The recent past and anticipated future use of satellite data is succinctly stated in his letter of support by N. Frank, the lead EPA scientist responsible for the development of the EE Rule: "... the fusion of satellite-derived measurements from its multiple sensors, combined with ambient air pollution measurements, meteorological data, and modeled estimates have recently been shown to be very valuable to separate the complex sources of air pollution into anthropogenic and natural components and for understanding when events are allowed to be judged exceptional.".

From the point of view of the proposed work, it is also important that NASA-supported IT, particularly the Service Orientated Architecture and Service Orchestration is also directly applicable to the development and implementation of a broadly usable decision support system that is assembled from the distributed components of the project team. These technologies will markedly improve the quality of EE flagging process and also help the implementation of tools for EE Anomaly Detection, Surface-Satellite Data Fusion and Event Climatology Analysis.

The incorporation of NASA data products into the EE DSS is primarily through the rich capabilities and keen interest of the Co-I partners of this project. The GIOVANNI data portal is a key is a key access portal to the most widely used satellite products in AQ analysis, including MODIS and MISR AOT, OMI and more recently CALIPSO. GIOVANNI also provides an array of useful data processing and fusion services. In the NAAPS global aerosol model a number of NASA datasets are assimilated and also used for validation. MODIS-derived fire location is derived hourly in real-time and converted into model-relevant emissions. The MODIS aerosol optical depth product is operationally assimilated into NAAPS. The MODIS Dust Enhancement Product is used to identify dust sources globally for NAAPS. The AIRPACT modeling system actively pursues the verification of CMAQ model with OMI columnar data for urban-industrial as well as for major fire emissions.

Technical Approach

Transition Approach

The end-state of the EE DSS will be an operational system managed and maintained by the key stakeholders: Federal and Regional EPA and the States. The transition to the post-project operational phase will be a smooth and natural completion of our research group's participation in the EE Rule evolution. Since 1998, the PI and his co-workers have facilitated or participated in dozens of air pollution event analyzes, most notably the "Asian Dust Events of April 1998", which documented exceptional impacts of Asian dust on Western North America. The analyzes of Central American Smoke of May 1998 caused record PM2.5 concentrations over much of Eastern U.S. and prompted EPA to issue the first set of guidelines (ref) (precursor to the EE Rule) on the treatment of EEs in compliance calculations. Recent EE analysis examples include the impact of Georgia Smoke on sites in the Eastern U.S. in May 2007 and the Southern California Smoke event of October 2007.

Upon EPA's request, the CAPITA group has actively participated in the development of EE analysis methods and contributed through exploratory illustrations of the candidate EE analysis methods. These were included in the Federal Register Docket as supporting documentation for the EE Rule. After the formal publication of the EE Rule in the Federal Register (ref, ) the CAPITA group was again asked to provide further illustrations of the methods that satisfy the EE Rule (ref wiki). The experience from both projects has clearly demonstrated that satisfying the regulatory requirements of the EE Rule can be supported by a suitable formal EE DDS information system. The need for such a support system has been strongly voiced by the supervising EPA officer and seconded by regional and State analysts who have seen and used those tools. (ref - Region 4 Georgia)

The transition of this AQ decision support project into a persistent operation is best expressed and illustrated in his letter of support by R. Poirot, CT Air Quality Planner, and also member of EPA’s Clean Air Science Advisory Board, Co-Chair of RPOs Monitoring and Analysis Committee etc.. “It is especially gratifying to see that NEDS will build directly on the existing DataFed infrastructure and utilize several related applications including the VIEWS, FASTNET and CATT tools which were specifically requested by and developed for the multi-state Regional Planning Organizations (RPOs). These “user designed” RPO data acquisition and analysis tools continue to attract and support a dynamic, collaborative network of empowered data analysts. By adding better connections to various NASA data products like GIOVANNI (and associated NASA science expertise), and adding other perspectives such as quantitative estimates of intercontinental smoke, dust and sulfate impacts from the NAAPS global aerosol forecast model and regional impacts from the AIRPACT forecast model, the NEDS project will substantially enhance the power and use of these existing analysis tools and provide invaluable assistance to state and EPA Air managers for implementing the complex new EE Rule. I look foreword to collaboration on this project in the near future."

Specific activities in the transition phase will include workshops and instruction sessions that will include the State, Regional and Federal AQ managers as users of the EE DSS system. The technical support will also include extensive web-based instructions provided through the EE DSS community workspace. As in the past, user workshops will be held on the use of DataFed, FASTNet, CATT and other tools voluntarily contributed by the Co_I team and others. In this project, special effort will be placed on harnessing the contributions of the partners.

Performance Measures

The most direct measure of the EE DSS performance is the number of flagged samples and the time required for the preparation and evaluation of the flag requests. Additional measures include the amount of data accessed, explored and used in the reports. A more subtle performance measure is the ratio of the requested and approved EE flags.

The preparation of the qualitative reports currently takes about a week and there are hundreds of flagged data samples requiring several person-years of effort. As the implementation of the EE Rule proceeds and the States get more familiar with data exclusion procedures, it is anticipated that the number of flagged samples will increase by at least an order of magnitude to thousands of flagged samples per year. The proposed EE DSS is anticipated to reduce the report preparation ten-fold.

Data usage in the EE DSS is the next important measure of system performance. The usage determined both by the ‘user pull’ forces (e.g. data relevance, data quality), as well as by the provider push (e.g. ease of access, tools for processing). The federated data access system using a common service orchestration engine will allow the counting of data accesses in fine detail. This will provide valuable measures on the most used datasets, requested formats and the frequency of tools use segmented by user type and location. Currently we use Google Analytics to analyze the DataFed service usages by the visitors, traffic sources and target contents requested and for how long. A key desired metric will be the number and distribution of State analysts who use the DSS. The user group membership will also be assessed by the numbers of attendees to the planned workshops during the project.

Cost savings in data use metric can be approached using two methods. 1) For those end users who had not used remote sensing data prior to the information services due to prohibitive cost, we can quantify the difference in cost between the estimated prohibitive level and the costs associated with using the developed information services. 2) For those users who have been using NASA data on a consistent basis both before and after the system, we can quantify the cost savings by the difference between costs incurred by the end user both before and after the system was implemented. These same user groups can be surveyed to determine if there was a change in data quality or in the quality of their own products and decision support system. The groups can also be surveyed to determine new capability gains by end users and user satisfaction. Surveys will likely be conducted during the planned workshops.

Anticipated Results

This project is built on the hypothesis that a powerful EE DSS tool will allow users to (1) explore and analyze data for specific EEs (2) prepare EE flagging reports (3) evaluate and approve the EE reports. For the States, the powerful EE tools will make the event documentation easy and efficient, while for EPA, the standardized DSS tools will make the decisions more consistent and robust. The hypothesis has been partially validated though developments and testing over the past 3 years.

The EE Rule is a new regulatory activity without a prior DSS. Thus, a "baseline" performance for the DSS does not exists, only isolated tests and examples. However, the improvements to be added by the proposed EE DSS can be clearly stated and well quantified.

The EE DSS tools will provide a formal venue for adding NASA Earth observations into AQ regulatory processes.
For the States, the powerful EE tools will make the Exceptional Event documentation easy and efficient.
For EPA, the standardized DSS tools will make the decisions more consistent and robust.
The NEDS infrastructure will also have broader benefits for the implementation of SOA, e.g. GEOSS.

The anticipated results of this project from the perspective of a State Air Quality Analyst is well-stated in his attached letter of support by R. Poirot of the Vermont Department of Environmental Conservation. "The NEDS project will provide direct and much needed support to State and EPA Air Quality Management Agencies as they work to better understand and implement EPA’s new Exceptional Event Rule (recently rendered much more critical by the newer and tighter daily standards for PM2.5 and ozone). In addition to this DSS support, I believe there will also be multiple “ancillary benefits” that result from NEDS, since in the course of identifying and documenting the relatively few events which are ultimately designated “exceptional” by EPA’s current rule, we - the networked teams of State, EPA, NASA and academic air quality analysts - will inevitably come to a better understanding of the nature and causes of many air pollution events of varying causes, spatial and temporal extents, and degrees of severity. This will aid the development of improved emission inventories, improve estimates of air quality model boundary conditions, lead to better model performance evaluation criteria for dispersion and receptor models, and provide valuable insights to air quality forecasters and health effects researchers. State Agencies will be better able to focus State Implementation Plan (SIP) control strategies for PM, ozone and regional haze on sources which are “jurisdictionally controllable” at the State level; utilize regional, national or international forums for synoptic-scale transport events; and predict, recognize and track uncontrollable events which result from natural sources."

The broader benefits of this are project will include deeper scientific understanding of EEs and innovative application of remote sensing and information technologies to AQ regulatory processes. Building the EE DSS will also contribute to the creation of a persistent core network for supporting AQ applications. The network will also exemplify multi-organization/agency collaboration using the principles and architecture of the Global Observing System of Systems.

Project Management

The proposed project will be a prototype for a novel collaborative approach to project management based largely on the 'System of systems' principles of GEOSS. The autonomous groups (data systems) participating in this project are keenly interested in sharing their experience and resources and forming a functioning 'system of systems'.

Project CO-Ia and Collaborators: (this section is to be extended on Monday, Tue to incorporate the specific contributions of the co-i, collaborators; expand this paragraph to full page) The project will achieve its goals primarily by linking, harmonizing and integrating and otherwise ‘connecting the pieces’ contributed by its autonomous core constituent partners represented by the projects GIOVANNI, NAAPS, VIEWS, AIRPACT, BARON and DataFed. The responsibilities are also distributed. The NASA GIOVANNI Group will provide key satellite data to the core network under direction of Senior Scientist, Greg Leptoukh. The VIEWS data system (Shawn McClure) will provide key aerosol chemical data to the core network. Washington State U. (Joseph Vaughn) will provide AQ forecast model data for the Northwest and also participate in air pollution event analysis. Baron Adv. Met. Services (John McHenry) will provide regional scale air quality simulation and forecast. The Naval Research Lab. (Doug Westphal) will provide global-scale model forecasts as an indicator of continental-scale transport.

In our view, the CAPITA group is well suited as the coordinator for this NASA ROSES Application and Decision Support project. The unique characteristics of CAPITA are the parallel expertise in the domains of air pollution science as well as in the application of information technologies. Being a small group (6-8 people), CAPITA does not have the resources to fully engage in both activities simultaneously but rather in sequential cyclic waves. We expect that with the past emphasis on IT development, the next five years at CAPITA will be devoted to the application of the advanced IT tools air quality applications.

Coordination and Integration: The loosely coupled 'system-of-systems approach will be fortified with concrete goals.The project will have clear deliverables in the form of the functioning EE DSS. The responsibility for overall coordination and for the delivery of the functioning EE DSS will be that of the PI, R. Husar, director of CAPITA. His group will also deliver most of the EE-specific tools through their federated data system DataFed. Husar has over 35 years of experience in event analysis and associated data processing and analysis. He has been providing tech/science support to EPA both as researcher as well as in high level advisory capacity.

The software development for the DataFed tools will be performed by Kari Hoijarvi whose experience includes about 15 years of software development at CAPITA. The project coordination will be supported by Erin Robinson, PhD student in Engineering, whose research includes collaboration support through new web technologies.

Management Approach: The specifications and the design of the EE DSS will be overseen by an advisory group which will be lead by user representatives from EPA, and the States and also include data providers and mediators. The advisory group will meet on a teleconference held at least every six months. A “virtual community” website will be created to allow team members as well as other interested parties to test and use the latest versions of data and tool services as well as submit comments. This interactive website will follow the well-established pattern of interactive web sites operated by CAPITA since mid-1990s. (Erin, wiki, workspace humanware, support to management?? )

Project will be open for the participation by the ESIP AQ and technical community. Also, ESIP will be one of the venues to link this project to other complementary projects. Project meetings are also planned to be in conjunction with the ESIP meetings. The upcoming participation in the GEOSS Architecture Implementation Pilot (AIP), AQ Scenario, will be a specific forum for open collaboration. Given the broad interest in EEs, the multitude of EE-related at local, regional, national and international level, it is anticipated that additional linkages will be established. For instance equivalent regulations to US Exceptional Event Rules are being considered by the European Environmental Protection Agency.

A summary work statement of the project activities is given in the Table below. The main activities

Program	Contact	Data Provision	EE Analysis	EE Tools	Data from EE DSS
VIEWS	S. McClure	x	?	?	?
NAAPS	D. Westphal	x	?	?	?
GIOVANNI	G. Leptoukh	x	?	x	x
AIRPACT	J. Vaughan	x	x	x	?
BAMS	J. McHenry	x	0	0	x
PULSENet	S. Falke	x	?	x	?
Hazard Mapping System	T. Habermann	x	?	?	?
BlueSkys	S. Larkin	x	?	?	?
NPS	B. Schictel	x	?	x	x
State, RPO	R. Poirot	?	x	?	?
Regional EPA	D. Garver	?	x	?	?
Federal EPA	N. Frank	?	x	?	?
GEOSS	G. Percivall	x	?	?	x
DataFed	R. Husar	1,2,3	1,2,3	1,2,3	1,2,3

Schedule

The schedule of this three-year project will give explicit consideration to the fact (1) substantial amount of preliminary work has already been prepared; (2) the proposing team has considerable resources and activities that has baring on the design and implementation of the project and (3) the EE DSS will proceed in parallel along all three components (Data Network, FASTNET and EE Tools), so that at any given time there is a functioning EE DSS that is being refined iteratively through user feedback. In Year I, the detailed specification of the EE DSS will be completed driven primarily by the needs of the end users. Also, the core standards-based data connectivity network will be expanded from DataFed to include the other Data systems. The main EE Tools will be developed. In Year II, focus primarily on exposing the EE DSS to the State, Regional and Federal EPA including a complete user-friendly interface, help instructions, tutorials and facilities for proactively gathering and incorporating user feedback. Year III will be devoted largely to the establishment of the operational EE DSS that will become the supporting decision system for the long-term implementation of the EE Rule.

Year I will include participation in the GEOSS Architecture Implementation Pilot.

Year II ...

Year III...

Statements of Commitment – Co-Is/Collaborators

Letters from End-User Organizations (4 1page letters)

Budget Justification: Narrative and Details

Personnel
The PI, Rudolf B. Husar, will be responsible for the research described in this proposal. Rudolf B. Husar is Professor of Energy, Environmental and Chemical Engineering and Director of the Center of Air Pollution and Trend Analysis (CAPITA) at Washington University in St. Louis. He will supervise one full time graduate research assistant (GRA) in all aspects of his or her studies. Husar’s annual effort devoted to this project is quantified in the budget detail.

Funds are requested to provide wages for a GRA’s each year. $26,914 is budgeted (for year one) to support the GRA’s and is a competitive rate necessary to attract a qualified student.

A three and one-half annual increase is budgeted for faculty salaries, three percent for the PI and 5% annually for each of the GRA’s. This increase rate is consistent with the University’s policy.

Fringe Benefits
The PI, and Co-PI qualify for University benefits which include contributions to FICA, 403B retirement plan, health, and disability. The Postdoctoral Research Assistant qualifies for all University benefits, except the 403B retirement plan. The salary budget includes fringe benefit costs. The GRAs are not eligible for University benefits.

Travel

First year total of $7,000 is itemized as follows: An annual trip to national AGU, San Francisco, CA
a. RT coach airfare $750
b. Registration Fee; $420
c. Hotel @ IRS per diem rate of $140/night: $700
d. Meal and IE @IRS per diem rate of $46/day; $230

One trip to the European Geophysical Union Annual Mtg,, Vienna, AUT (total cost $3630, one half of the cost ($1,815 charged to the proposal)
a. RT coach airfare $1,600
b. Registration fee; $800
c. Hotel @ IRS per diem rate of $196/night: $980
d. Meal and IE @IRS per diem rate of $46/day; $230

One trip to a national Federation of Earth Science Information Partners (ESIP) conference at t/b/n
a. RT coach airfare; $600
b. Registration fee; $300
c. Hotel @ IRS per diem rate of $140/night: $240
d. Meal and IE @IRS per diem rate of $46/day; $130

One trip to the EPA Coordination meeting RTP, NC (2 person trip)
a. RT coach airfare $400 x2 = 800
b. Hotel @ IRS per diem rate of $160/nightx 2 nights $320x 2=640
c. Car rental 200
d. Meal and IE @IRS per diem rate of $46/day; $92x2=$184

Supplies
To cover cost of software procurement and required small hardware for maintaining network, servers, and workstations, as well as purchase of books and PC journals; $3,500.

Consultants
Kari Hoijarvi, programming consultant, was instrumental in CAPITA programming for the last ten years. Hoijarvi will be responsible for programming data tools and applications.

Intragency Transfer
Interagency transfer to NASA GIOVANNI Group will provide key satellite data to core network. Covers Senior Scientist, Greg Leptoukh.

Subcontracts
VIEWS subcontract will support Shawn McClure in establishing connections to core network.

Washington State University subcontract will support Joe Vaughn in establishing connection to core network and participating in air pollution event analysis.

Baron Advanced Meteorological Services will be participating in core network by providing regional scale air quality simulation and forecasting.

Other Direct Costs
$3,100 is requested each year computer network, support and management charges as well as publication charges.

Indirect Cost
The Indirect Cost rate used for this proposal is 52.0% MTDC, approved 06/07/2005 by the DHHS. The MTDC for this proposal is $1,021,856, and corresponding indirect cost is $531,365.

Facilities and Equipment
Year 1: To cover the cost of a computer server with accessories; Year 2: to cover the cost of 2-3 workstations and laptops; Year 3: To cover the cost of server and workstations upgrades for technology development phase of the project.

Bios

Current/Pending Support

Name: Rudolf B. Husar August 2008
Center for Air Pollution Impact and Trend Analysis, Washington University, St.Louis

Total of five months (42% of time)

SUPPORTING AGENCY AND AGENCY ACTIVE AWARD/PENDING PROPOSAL NUMBER	TOTAL $ AMOUNT	EFFECTIVE AND EXPIRATION DATES	% OF TIME COMMITTED	TITLE OF PROJECT	PI
NASA Award 1322-59743	$1,524K	11/08/04-11/07/09	25 %	Application of ESE DATA and Tools to Particulate Air Quality Management	S. Falke/R. Husar
NASA thru Northrop Grumman Corp.	$60K	09/7/06-09/5/09	2 %	Sensor-Analysis-Model Interoperability Technology Suite (SAMITS)	S. Falke
EPA	$35K	07/11/07-07/11/08	5 %	Provide Exceptional Events Technical Guidance (Consulting PI)	R. Husar
EPA thru Sonoma Technology, Inc.	$12K	10/16/07-06/06/08	2%	Provide guidance on AirNOW International design, (Consulting PI)	T. Dye
NASA thru Baron Advanced Meteorological Systems	$188K	01/06/07-12/31/09	8%	Assimilating MODIS-derived Aerosol Optical Thickness into an Operational Air Quality Forecast Decision Support System, (Consulting PI)	J. McHenry

References and citations

GEOSS, Global Earth Observation System of Systems 10 –year Implementation Plan, Februaey 2205, ESA Publications Division, the Netherlands, Bruce Batrick, ed. ISSn No.: 0250-1589, ISBN No.: 92-9092-495-0
GEO, The Group on Earth Observations, was established by a series of three ministerial-level summits. It currently includes 68 member countries, the European Commission, and 46 participating organizations
GEO Secretariat, 2006
1998 Asian Dust Event
- Husar, R. B., D. Tratt, B. A. Schichtel, S. R. Falke, F. Li, D. Jaffe, S. Gassó, T. Gill, N. S. Laulainen, F. Lu. M Reheis, Y. Chun, D. L. Westphal, B. N. Holben, C. Geymard, I. McKendry, N. Kuring, G. C. Feldman, C. McClain, R. J. Frouin, J. Merrill, D. DuBois, F. Vignola, T. Murayama, S. Nickovic, W. E. Wilson, K. Sassen, and N. Sugimoto, 2001, The Asian Dust Events of April 1998. J. Geophys. Res., 106, 18,317-18,330.
070420GeorgiaSmoke
071022SoCalSmoke
DataFed
- Husar, R.B. S. R. Falke and K. Hoijarvi: Interoperability of Web Service-Based Data Access and Processing: Experience Using the DataFed System. ESTO Meeting, 2006, Paper A6P2
- Husar, R.B.; Hoijarvi, K., "DataFed: Mediated web services for distributed air quality data access and processing." Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International , vol., no., pp.4016-4020, 23-28 July 2007
FastNet
- R. Husar and R. Poirot, “DataFed and FASTNET: Tools for agile air quality analysis” EM , Air an Waste Management Association, , September vol., pp. 39-41, 2005.
OGC, GALEON http://www.opengeospatial.org/initiatives/?iid=173
OGC GEOSS Services Network (GSN), http://www.ogcnetwork.net/node/56
The User and the GEOSS Architecture V – Denver http://www.ogcnetwork.net/node/137
The User and the GEOSS Architecture XIV – Barcelona, http://www.ogcnetwork.net/node/265
SHAiRED, The goal of this REASoN applications and technology project is to deliver and use Earth Science Enterprise (ESE) data and tools in support of air quality management. The project aims to develop a federated PM information sharing network that includes data from NASA, EPA, and US States. This is the primary project for the DataFed infrastructure development. Period: 2005-2009. Support: NASA. Investigators: S. Falke, R. Husar, K. Hojarvi
CATT
GEOSS AIP
“National Ambient Air Quality Standards for Lead; Proposed Rule,” 63 Federal Register 102 (28 May 1998), pp. 29150 - 29151.
Precursor to EE Rule
Illustration of EE Rule - Wiki
VIEWS, Visibility Information Exchange Web System, http://vista.cira.colostate.edu/views/
NAAPS, Navy Aerosol Analysis and Prediction System, http://www.nrlmry.navy.mil/aerosol_web/Docs/globaer_model.html
GIOVANNI, GES-DISC (Goddard Earth Sciences Data and Information Services Center) Interactive Online Visualization ANd aNalysis Infrastructure, http://daac.gsfc.nasa.gov/techlab/giovanni/
AIRPACT, Air Indicator Report for Public Awareness and Community Tracking, http://lar.wsu.edu/airpact%2D3/
BAMS, Baron Advanced Meteorological Systems, http://www.baronams.com/
NOAA HMS, NOAA Hazard Mapping System, http://www.ssd.noaa.gov/PS/FIRE/hms.html
BlueSky, http://www.ssd.noaa.gov/PS/FIRE/hms.html
PULSENet, Persistent Universal Layered Sensor Exploitation Network
NPS IMPROVE, ...

United States Air Force Scientific Advisory Board (2005); Report on System-of-Systems Engineering for Air Force Capability Development; Public Release SAB-TR-05-04