Emissions Tracking

What is "Emissions Tracking"?

Emissions tracking involves accurately tracking and predicting emissions from various sources and is important for several reasons.  Obviously there is the regulatory aspect; exceed limits and you can get fined or even have to shut down a process.  But there are other important reasons to know what’s going on with your emissions.  With “greenhouse gasses” being a hot topic these days, one use of the DataPipe modules is calculating "greenhouse gas emission". 

See the Air Emission Program Fact Sheet at Harvard University for more info.

If you keep track over time you can see how the processes are behaving.  Being able to estimate when, say, a monthly cap on cumulative emissions may be reached can help you schedule processes.  Isn’t it better to know in advance than find out after the fact?  If emissions are going to be under limits you may be able to sell or trade “credits.” 

How does DataPipe deal with Emissions tracking?

DataPipe has several ways for tracking emissions, one based on current measurements the other on calculations.  Either or both may be used individually or in combination, based on your particular (and possibly changing) needs. 

The Source Tests Module tracks “sources,” chemical and physical limits (regulatory and/or self-imposed), and the results of tests on each “source” over time. 

A “source” may be anything you want.  Obvious candidates are stacks and outfalls; there are others (valves, vehicles, etc.)  Sources may be air, water, waste and anything else your heart desires.  Sources can have chemical and/or physical limits, with limits being below or above values, in or out of a range, etc.  However, a limit need not be set for a test to be conducted. 

Source tests track the results of periodic testing of the source.  Again, chemical and/or physical parameters may be included in a test or tests.  A chemical test would be something like how much of various agents (agents are referenced to the Agent Parameters database in DataPipe) are present.  In a stack this might be SO2, NOx, solvents, etc.  Physical tests might be for pH, temperature, opacity, etc. 

How are results entered in DataPipe?

As with any DataPipe module, results can be entered multiple ways. You can always hand enter the results of a test (if you have the necessary security permissions on the form).  But could also set up a process to import results e-mailed in from a lab and/or take a feed from a continuous emissions monitoring system (CEM). 

If you do have limits established for any sources, as you enter test results they are automatically compared to the limits and you get visible feedback.  Later, as you step through test records the comparisons are made, so you always can see how a set of tests compared to the limits. 

As previously mentioned, a “source” can be man things and need not be the typical  exhaust stack or discharge pipe.  In one instance a utility customer (who you would expect to have the typical sources for air and water emissions) also used the Source Test Module for tracking water fountains, of which they had over 300.  Each fountain was set up as a “source.”  Monthly tests were collected from each fountain and the results entered in DataPipe.  They were interested in both chemical properties (mostly various metals, like lead and copper) and physical properties such as pH, temperature, turbidity (cloudiness) and suspended solids. 

As we said, almost anything can be set up as a “source” for testing! 

The second type of emissions information is based on  calculations and using “emissions factors” along with other information.  If you’re familiar with AP-42, the Environmental Protection Agency’s (EPA) table of emission factors and how they’re used you have some idea of how the DataPipe Process Model Module works. 

An emission factor is a rare number or formula used to calculate the quantity of an emission produced based on some variable in the operating or manufacturing process.  Here’s what the EPA says:

(see http://www.epa.gov/ttn/chief/ap42/ for more details)

Emissions Factors & AP 42

An emissions factor is a representative value that attempts to relate the quantity of a pollutant released to the atmosphere with an activity associated with the release of that pollutant. These factors are usually expressed as the weight of pollutant divided by a unit weight, volume, distance, or duration of the activity emitting the pollutant (e.g., kilograms of particulate emitted per megagram of coal burned). Such factors facilitate estimation of emissions from various sources of air pollution. In most cases, these factors are simply averages of all available data of acceptable quality, and are generally assumed to be representative of long-term averages for all facilities in the source category (i.e., a population average).

The general equation for emissions estimation is: E = A x EF x (1-ER/100) where: E = emissions; A = activity rate; EF = emission factor, and ER =overall emission reduction efficiency, %

For example, if you’re manufacturing batches of polystyrene here are AP-42 emissions for various steps in the process: 

(Metric Units). EMISSION FACTORS FOR BATCH PROCESS POLYSTYRENEa

EMISSION FACTOR RATING: C

Stream Identification	Emission Stream	Nonmethane VOC
A	Monomer storage and feed dissolver tanks	0.09b
B	Reactor vent drum vent	0.12 - 1.35c
C	Devolatilizer condenser vent	0.25 - 0.75c
D	Devolatilizer condensate tank	0.002b
E	Extruder quench vent	0.15 - 0.3c
F	Product storage	negligible
	Total Plant	0.6 - 2.5

a.  Stream identification refers to Figure 6.6.3-1. Units are grams VOC per kilogram of product.

b.  Based on fixed roof design.

c.  Reference 4. The higher factors are more likely during the manufacture of lower molecular weight products. Factor for any given process train will change with product grade. 

The major vent is the devolatilizer condenser vent (Stream C). This continuous offgas vent emits 0.25 to 0.75 grams of VOC per kilogram (gVOC/kg) of product depending on the molecular

weight of the polystyrene product being produced.  If we split the difference to formula for the production of nonmethane VOC would be 

            0.5g/Kg*Kg Product Produced 

Other parts of the process would have their equations, all based on Kg of product produced.  We could sum up everything into one equation or keep each part separate, as needed. 

Process model calculations in DataPipe can be much more complex.  Multiple independent variables can be defined for a source, them multiple formulas, one for each output can be set up.  DataPipe has its own “calculator” so as the quantities of the inputs are entered the formulas are evaluated to determine how much of something is created or released over the time interval. 

For example, calculating the amount of Toluene vapor lost when a storage tank is filled (the “working loss) depends on five (5) independent variables: 

X01 - Liquid pumped to the tank over time, ft^3 (Qw)

X02 - Ambient temperature, F (Temp)

X03 - Day-night temperature fluctuation (Delta Temp)

X04 - Liquid level in tank, as % of height (L-Level)

X05 - Vapor pressure at ambient temp, mmHg (VP) 

Using a conventional formula for calculating the pounds of Toluene lost, the formula in DataPipe is: 

x01*(1/359)*(273.15/((5/9)*(x02-32)+273.15))*(x05/760)*1*1

Given the five input variables DataPipe can calculate the greenhouse gas emissions from the tank filling process. 

Here is the information for an older diesel-powered heavy truck.  The inoput variables are 

X01 - Cumulative Mileage (odometer reading)

X02 - Miles driven for the month (change in miles)

For CO emissions, in grams:

(11.440 + (0.160 * (X01/10000))) * X02 

For hydrocarbon emissions, in grams:

(3.920 + (0.060 * (X01/10000))) * X02 

And for NOx emissions, in grams:

(25.500 + (0.190 * (X01/10000))) * X02 

In this example entering the odometer reading and the miles driven for the month one time all the emissions for the vehicle can be calculated.  You could set up appropriate formulas for each vehicle, feed in the mileage information from your fleet information system (or the DataPipe MV Fleet Module) and do all the calculations for the fleet for the month. 

In one instance a customer had to calculate the monthly fugitive dust emissions from an open pit mine.  One source was the trips taken by truck, which were in three sizes.  They determined how much dust (pounds) of dist was generated for each truck type on a round trip.  They set up a formula using three independent variables, the number of trips per month of each of the three truck type.  The formula used the amount of duct generated by each truck type times the number of trips for that truck type and added the results for the total dust generated for the month.  Each month they just enter the number of truck trips for each of the three types and the calculation is made.

You may determine emission factors based on anything you want; hours of operation, number of widgets produced, amount of fuel consumed, quantity and type of appliances spray painted, etc.  The actual testing of your sources can be used as a basis for the emission factors if you don’t use AP-42 or similar published factors (they can’t determine factors for everything!). Your formulas for calculating the emissions of as many things as you want are then based on these input parameters.

 

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DataPipe is a complete EH&S information management software solution.  If you are interested in taking a look at our modules or want to learn more about occupational health software and the various modules within that suite or if you want to look at industrial hygiene software and the various modules that make up that suite, please review our modules page.

Knorr Associates Inc. (KAI) is the leading US and Global provider of Environmental, Health & Safety (EHS) and Crisis Management software. The company, headquartered in Butler, new jersey was founded in 1979 as the first EHS Software developer on the scene, integrating EHS instruments long before PCs were on the market.  It wasn't until 1989 when the very fist windows based EHS software application - DataPipe - was released (and it really was one of the first windows based software applications - period).  Since then KAI has grown to be the premier EHS software provider with a global client base representing companies of all sizes from many major industry sectors.