Welcome to the Emission Inventory (EI)/Tribal Emission Inventory Software Solution (TEISS) s2

Welcome to the Emission Inventory (EI)/Tribal Emission Inventory Software Solution (TEISS) Training Curriculum: Course 2-EI Advanced

Module 13-EI Data Management

SLIDE 1: This presentation discusses managing EI data. It includes a demonstration of the TEISS QA/QC tools. Learning objectives for this session:

·  Know what data to collect and report for your sources

·  Know how to use the TEISS QA/QC tools.

SLIDE 2: Homework Discussion

Are there any questions on the unit conversion exercise?

Does anyone have an experience with unit conversions that they would like to share? The story of the NASA Mars Climate Orbiter is a famous example of a unit conversion error. Thruster performance data in English units was used in a software program. Another program was coded to expect the data output from the first program to be in metric units of Newton-seconds, but instead the output was in units of pound-seconds. Therefore, the trajectory of the orbiter was underestimated by a factor of 4.45, the conversion factor from force in pounds to Newtons. Because the trajectory of the orbiter was then approximately 170 kilometers lower than it was supposed to be, it is likely that the orbiter disintegrated in the atmosphere of Mars. Source: Mars Climate Orbiter Mishap Investigation Board Phase I Report, November 10, 1999 (http://sunnyday.mit.edu/accidents/MCO_report.pdf).

Remember that units are very important. Most often, numbers are meaningless without units. As an example, imagine a recipe that specified the ingredients like this:

5 vegetable broth

2 rice

1 salt

½ oregano.

I cook often enough to guess that this ingredient list should have been specified as 5 cups vegetable broth, 2 cups rice, 1 teaspoon salt, and ½ teaspoon oregano, but these are only guesses. If I had guessed that the recipe called for a tablespoon of salt, I would have very salty rice. If I see a value of 100 for the emissions from a source in your EI, I could guess that means 100 tons, however, it might actually be only 100 pounds. That is a huge difference in emissions. Do not make your audience guess the units in your EI. Report units for every number in your EI, from the activity data through the emissions.

SLIDE 3: Data Management Definition

In simple terms, emission inventory data management is keeping track of information used to estimate emissions. You track this information in the notes in your project file, in your TEISS project, and in your written emission inventory.

SLIDE 4 and SLIDE 5: The “answer” you get from an EI

An EI tells you the sources of air pollutants and the amount of air pollution from each source. For example, an EI can tell you that residential woodstoves is a source of emissions. It also can tell you that it is estimated that 10 tons per year of CO, 50 tons per year of PM10, etc. are emitted from residential woodstove heating.

SLIDE 6: Data Management

Data management is describing how you got the emission values in your EI. It is a “road map” to how you got the answers. Can anyone give me some reasons of why you would draw a map? (The two answers I am looking for or so we can make it back to a location and that others can make it to that location.) For your EI, you have a “road map” so that you can update your emissions in years to come and so that others can understand how you got to your answers. Do not rely on simply your memory of how you calculated emissions.

SLIDE 7: Data Management – How?

There are three opportunities for data management in your EI. It is best to use all three of these opportunities for data management.

·  Keep information in notes

o  These notes can be electronic or written versions. It is important to store them in an organized project file. If they are electronic, they should be stored in a designated folder on your computer that is also backed up to an external location, such as a memory stick or server. If they are written notes, you should have a drawer in a file cabinet assigned to your EI, with a different folder for each source.

·  Include information in EI report

o  In your written EI, for each source, include information on how you obtained the data used to calculate the emissions. More on this in an upcoming slide.

·  Store in spreadsheet or database

o  TEISS could be the database that you store the information in.

SLIDE 8: Calculators: Printing Blank Forms

TEISS can assist you with data management in more ways than simply as the database to store your data. The TEISS calculators are equipped with a Print Blank function that allows you to print the calculator screen and use it as a data collection form. You can take these forms into the field and collect your data on them. This can help you focus on what data you need to collect. Keeping these data collection forms you filled out in your project file gives you a good start on a comprehensive notes system.

To print blank data collection sheets from the TEISS calculators, go to the File menu of the calculator and select the Print Blank option.

SLIDE 9: Data Management – Why?

·  Data management proves the quality of your emission estimates because a reviewer can go back and verify calculations, data from sources, etc. The reviewer cannot verify the data if you have not noted in your EI where you got your data.

·  Helps when updating EI, think of the road map, it helps you get there. Without the road map, it would be much more difficult. If the EI reports that the emissions from woodstoves are 10 tons per year of CO, that does not help us update those emissions. We need the road map to get to those emissions.

·  Don’t have to redo/refigure everything.

SLIDE 10: You start with…

What do you need to estimate emissions from woodstoves

·  Data that you collect

o  Amount of wood burned for residential heating (i.e., number of cords)

o  Types of stoves people are using

·  Tools that TEISS provides

o  Emission factors

o  Equation that puts all these numbers together to calculate your emissions estimate

SLIDE 11: Data Management: Records

Continuing on with the estimating emissions from woodstoves example, here are three methods that could have been used to estimate the number of cords of wood burned for residential heating:

·  Guessed based on personal knowledge of your reservation

·  Used population and estimate of percent of homes burning wood

·  Did survey to count woodstove types and amount of wood burned.

These methods are listed in order of least reliable to most reliable in data quality. If you come back to this EI in a few years, or if someone else wants to update the emissions, you are going to want to know information like “how did I estimate how much wood was burned”. Do not rely on your memory only for this.

SLIDE 12 and SLIDE 13: Data Management: Records (cont.)

Here is an example formula for estimating woodstove emissions:

·  E = EF x (W x H x % x D)

o  E = emission rate

o  EF = emission factor for given pollutant

o  W = volume of wood burned annually for one home

o  H = number of tribe households

o  % = percent houses heating with wood

o  D = Dry density of wood.

Multiplying the W, H, %, and D value together gives the activity data value.

Where you got each variable that you used in the equation needs to be recorded in your notes, EI report, and TEISS project. If you use TEISS to calculate your emissions, you can look at the opening screen of the TEISS calculator to find out the source of the EFs. Here is an example of the source identification for each variable in the equation:

·  EFs from EPA AP-42, fifth edition

·  W from tribal housing office estimate

·  H and % from tribal housing office

·  D from EPA AP-42, Fifth edition.

SLIDE 14: Data Management Report Example

Please take a moment to open and read the DataManagementReportEx document posted on the training website. This shows an example of how to include information on how data were obtained for the residential wood heating source in an EI. (Give 5 minutes to read the document.) Does anyone have any questions on the document?

SLIDE 15: Data Management Spreadsheet Example

I am going to demonstrate the spreadsheet associated with the report example. (Open the RevisedResidential wood burning emissions calcs.xls spreadsheet.)

·  The formula to calculate the number of cords burned for residential heating on the reservation is written out at the top of the spreadsheet.

·  The same formula is coded as a function in cell B13. Show the formula in cell B13. Notice how this formula is “behind the scenes”. It is good to have the formula written out, as shown at the top of this spreadsheet, so that it is visible in the spreadsheet.

·  Show how entering a value in cell B6 populates the other cells.

If you were using TEISS, you would only need to write a function for determining the tons or cords of wood burned, for example, the formula in B13, because that is the value that you would need to enter into the TEISS calculator to estimate emissions. This kind of spreadsheet is beneficial if you need to calculate activity data to enter into TEISS. If you use spreadsheets to calculate the activity data, you should include them in your EI report as an appendix section. You would also want to keep a copy of this spreadsheet in your electronic EI files.

If you would like to play with this spreadsheet more, it is posted on the training website as “RevisedResidential wood burning emissions calcs”.

SLIDE 16: Crucial Data

·  Collect the mandatory data elements, as specified by TEISS, at a minimum, for every source you inventory

·  Having these data allows your tribal sources to be included in

o  National Emission Inventory (NEI)

o  Regional air quality modeling

o  Market trading negotiations

SLIDE 17 and SLIDE 18: Data from Point Sources

Point sources have more data elements than other source types. Record the following data at a minimum:

·  Name of facility

·  North American Industry Classification System code (NAICS code)

·  Complete street address

·  Lat/long or UTM coordinates (with datum, for example NAD 83 or WGS 84)

·  Start and end date of emission process

·  Source Classification Code (SCC)

·  Estimated emission for each inventoried pollutant

·  Period of emission estimate (annual, weekly, daily, etc.)

·  Specify units of emission estimate (tons/year, lbs/month, etc.).

SLIDE 19: Point Source – Process Level

EPA prefers that emissions be reported for each process at a facility rather than the total facility emissions. For example, if there is a boiler and charbroiler at a casino being inventoried as a point source, emissions for those two processes should be reported separately instead of reporting the total casino emissions. Here is an example of how a facility gets subdivided in TEISS for reporting purposes:

·  Site: ABC Gravel Company

·  Units: Screening operation, excavating operation

·  Processes: Loading, screening, output

·  Release points: stacks, vents, fugitive

·  Control devices and their efficiency.

The accuracy and usefulness of your data increases with the level of detail of the data.

SLIDE 20: Processes Example

This is a simple flow chart shows a sand and gravel pit point source. The processes at the screening unit are shown as loading, screening, and output.

SLIDE 21: Nonpoint and Mobile Sources

Record the following data at a minimum:

·  SCC

·  Period of emission estimate (for example, annual)

·  Estimated emission for each inventoried pollutant

·  Specify units of emission estimate (tons/year, lbs/month, etc.).

SLIDE 22: Data Management Summary

·  Make sure you include the answers to these questions in your notes, TEISS project, and EI report:

o  WHAT you are calculating

o  HOW you calculated emissions estimate

o  WHERE you got data

o  WHEN you collected data

o  WHO you got your data from.

·  Include mandatory data for NEI

SLIDE 23: TEISS QA/QC Tools

As you worked through the Case Project, you might have noticed that most data entry screens have sections titled Data Entry, Data Collected, and Data Checked. The Data Entry section and Data Collected section are for storing QC information about where you got the information you entered. These sections allow a QA checker to view the QC data. The Data Checked section provides a place where the QA checker can document their check of the information.

SLIDE 24: QA/QC Report

Any time you want to check who modified the information for a particular source, you can use the Report button in the Data Entry section to open the QA/QC report that shows who logged into the TEISS project and made changes in that particular data entry screen. You would need to have added a distinct username for each person working on your TEISS project rather than having each person log in as the Administrator to have a record of who made the modifications.

You can add users to TEISS by going to the File menu and selecting Administration, then Define Groups/Users.

Demonstration of TEISS QA/QC Function

First, I am going to add a nonroad source to my project. I am adding this source for demonstration purposes only. None of the data entered are actual data.

Notice that when I first enter the data, the Data Entry section is not filled in.