The Visibility Information Exchange Web System is a database system and set of online tools originally designed to support the Regional Haze Rule enacted by the EPA to reduce regional haze in national parks and wilderness areas.

Web Address:Sponsor:

Guiding Body:

Location:

Staff:

Affiliations:

http://vista.cira.colostate.edu/viewsFive EPA Regional Planning Organizations (RPOs)

VIEWS Steering Committee

Cooperative Institute for Research in the Atmosphere (CIRA),

Colorado State University, Fort Collins, CO

Scientists, researchers, and IT professionals

Interagency Monitoring of Protected Visual Environments (IMPROVE)

What is VIEWS? Some facts:

Provide easy online access to a wide variety of air quality data. Provide online tools for exploring and analyzing this data. Maintain a catalog of relevant air quality-related resources. Facilitate the research and understanding of global air quality issues.

What are some of its other goals?

Over 600 registered users

Over 200 organizations represented

Almost 100 countries represented

300+ unique hits a day

Linked to by over four dozen sites

Over 40 million records of air data

Dozens of monitoring networks

CSU Research Initiative Award

Uses the new Manifold GIS

Monitoring site photographs

Class I Area webcams

Visibility photographs

Visibility Grey Literature

Periodic Newsletter

Contour Maps

Trends Analysis

Air Mass Composition Analysis

Why NADP? 2

• Because deposition data is an important component of the overall air quality picture.

• Because VIEWS is expanding its inventory of deposition data, including NADP data.

• Because comparisons between aerosol and deposition data are valuable analysis tools.

• To facilitate collaboration and data sharing between U.S., Canadian, and international air

quality researchers.

• Because important lessons in data modeling and management have been learned

from generalizing our originally aerosol-centric system to handle broader

categories of air quality data, such as deposition data.

VIEWS Architecture Overview 3

Source Data

Import

Source Data

Source Data

Validation

DatabaseRules

ProgramLogic

Storage Retrieval Presentation

Analysis Interpretation

Transformation

Back End Front End

Import: Getting data into the system

Validation: Ensuring data accuracy

Storage: Managing data, backup, and archival

Transformation: Sorting, joining, aggregating

Retrieval: Getting the data out

Presentation: Displaying the data

Analysis: Making the data understandable

Interpretation: Making the data usable

VIEWS Architecture Detail: Data Acquisition & Import

Data Acquisition System:Data Acquisition System:

• Accepts submission of data in a variety of

schemas and formats• Can automatically extract data from known

online sources• Uses database replication where possible• Initially imports data and metadata “as-is”

into the source database

Data Import System:

• Extracts data from the source database• Scrubs data and performs conversions• Maps source metadata to integrated metadata• Transforms the data into an integrated

schema• Verifies and validates imported data• Loads data into the back-end OLTP system

Metadata Import System:

• Facilitates the entry of new

metadata• Validates new metadata

entries• Detects overlap with existing

metadata

VIEWS Architecture Detail (cont’d): Data Management

OLTP:OLTP:

• Functions as the “back-end” database• Fully relational and in 3rd normal form• Used for data import, validation, and

management• Technologies: Microsoft SQL Server

Data Warehouse Generation System:Data Warehouse Generation System:

• Extracts data from the OLTP• De-normalizes and transforms data• Loads data into the Data Warehouse• Builds table indexes• Archives “snapshots” of the database• Technologies: VB, stored procedures

Data Warehouse:Data Warehouse:

• Functions as the “front-end” database• Uses a de-normalized “star schema”• Used for querying and archiving data• Automatically generated from the OLTP• Technologies: Microsoft SQL Server

VIEWS Architecture Detail (cont’d): Data Backup, Restore, and Archival

Backup and Restore System:Backup and Restore System:

• Automatically and periodically backs-up critical VIEWS

databases• Restores database backups on demand

Replication and Archival System:Replication and Archival System:

• Vertically partitions the Data Warehouse by time period• Takes a full “snapshot” of the data warehouse at regular

intervals• Creates a historical audit trail for verifying archive integrity

VIEWS Architecture Detail (cont’d): Data Presentation and Analysis

ASCII Data File Collection:A collection of data and metadata in ASCII text file format.

Site Browser:For exploring detailed monitoring site metadata, history, photographs.

Third Party Tools:A collection of relevant air quality research tools provided by various organizations and institutions.

Class I Area Webcams:A growing collection of links to Class I Area webcams that provide a visual method for assessing visibility and general air quality in national parks and wilderness areas.

VIEWS Architecture Detail (cont’d): Data Presentation and Analysis

NADP National Trends Network (NTN) Import Detail

• Used SQL Server DTS Wizard to

import NTN sites metadata

• Used SQL Server DTS Wizard to

import NTN data

• Manually entered NTN SOP and

method information

Sites Data

SOP

SQL Sever DTS

SOURCE DB

Entry Forms

Data Acquisition System

• Used SQL scripts to extract

unique Sites, Parameters,

Methods, and Flags from source

data

• Created new records in the OLTP

for NTN Sites, Parameters,

Methods, and Flags using the

extracted metadata

Metadata Import System

Data Import System

• Transformed the data into the

common relational schema• Applied DB integrity

constraints• Mapped source codes to

relational primary keys (IDs)• Validated the data using a

series of row and column

checksums and record counts

Browsing NADP NTN and IMPROVE Aerosol Sites

Simple Comparison Between IMPROVE Aerosol and NADP NTN Data:

This simple comparison was performed by “normalizing” the aerosol units (ug/m3) and the deposition units (mg/L) to a common scale and plotting on a single graph.

Aerosol and Deposition Comparisons 12

Wet Deposition (NADP/NTN) Aqueous rain water concentration (mg/L). Precipitation weighted mean concentration (mg/L). Deposition (kg/ha) - the product of aqueous SO42- concentration in collected rain water

and total precipitation over a given time period (e.g. season, year).

Dry Deposition (CASTNet) Dry deposition (kg/ha) for atmospheric particles and gas phase species (e.g. SO2,

HNO3, NH3) - the product of the species’ deposition velocity and the ambient air concentration integrated over time (e.g. season, year).

Air Concentrations (IMPROVE, CASTNet, STN, other speciated networks) Aerosol and gas phase air concentrations (ug/m3).

Inter-comparisons (Sulfur) Compare raw concentration data (ug/m3 to mg/L) Compare slopes in respective trends, for example S (SO2 plus SO42-) air concentrations

to S deposition expressed as %/season, %/yr.

Data Status

NADP AIRMoN and NTN data has been imported into the VIEWS database.

AIRMoN data is currently available from the VIEWS website.

NTN data will be available when we’ve completed a full description of the NTN

metadata mappings for inclusion with downloaded data.

Next Steps

Explore the issues involved in comparing deposition and aerosol data.

Investigate new and better methods for comparing the two types of data.

Provide automatic tools and/or case studies for viewing the comparisons.

Foster communication and collaboration within the air quality community.

Facilitate research by sharing data, technologies, and experiences.

http://vista.cira.colostate.edu/views

Author: Shawn McClure

mcclure@cira.colostate.edu