Andrew Blackman, Senior

Joey Placencia, Senior

Chris Yarbro, Senior

Computer Technology Class

Silver High School, Silver City, NM

May 5, 2000

Supercomputing Challenge

Project Number 016

Teacher: Mrs. Peggy Larisch

Mentor: Ms. Mechelle Taylor

Abstract

Do the emissions from cars really hurt the o-zone layer. The problem that we are trying to solve is to see if there is a correlation between the different gasses that a vehicle blows out of its exhaust pipe. This project will use a computer program to find a correlation between two different gasses. We will get emissions reports from the EPA. The results of our project will be represented graphically.

Abstract 1

E.0 Executive Summary 2

1.0 Introduction 3

1.1 Purpose 3

1.2 Computer Program 3-4

2.0 Problem Statement 5

2.1 Problem Statement 5

3.0 Method of Solution 6

3.1 Mathematical Model 6

4.0 Results 7

4.1 Calculations 7

4.2 Graphs, Tables 7

5.0 Conclusions 8

5.1 Computer Programs 8

5.2 Data 8

References

Acknowledgements

Appendix

In the world today, there seems to be a constant problem with pollution and the depleting O-zone layer. Vehicles driven today contribute greatly to the problem of pollution. Many laws have been passed making the producers add items such as catalytic converters, which reduce the amount and severity of emissions released into the atmosphere each day. It would be even greater if it were possible to identify the gases that affect the atmosphere the greatest and cut down of the amount and severity of those specific gases.

The solution is to first figure out which gas released by vehicles does the most damage to the atmosphere. When this information is obtained, work can be done on a vehicle to try and cut down on the gases that are especially harmful to the atmosphere. Information on emissions has been obtained by way of the EPA. A program was made that pulled pollution data from the EPA and then processed the data to see if there is a correlation between the amount of emissions vehicles release. The results of running the program showed that there is in fact a correlation between the amount of gas released into the atmosphere. These amounts still need to be lowered in order to keep the atmosphere healthy.

The purpose of this project is to determine if the pollutants created by automobiles are correlated in their amount of emissions. "Between 1994 and 1995 emissions decreased for all criteria are pollutants" (National Air Pollutant Emissions Trends, 1). It is felt that the decrease in N0x emissions resulted in implementation of RACT (Reasonably Available Control Technology). Reduction in phase 1 unit utility S02 emissions resulted from requirements in Title IV of the CAAA (Clean Air Act Amendments). If this trend is true, then there should be a correlation between the pollutants that are created by automobiles. Thus, this project examines automobile emissions to determine the correlation between the major pollutants created by both on road and off road vehicles.

Dick Allen originally created this program in the Fortran 90 computer language. The first step in our project was to type in the program, emission.f90. We then added three subroutines to our program. These subroutines allowed the user to choose from five different gasses. The user could input two gasses out of the five to correlate. We then setup a DO loop that allowed the computer program to find out which gasses were chosen. The program then would run through the information, and print out the regression and the x and y intercept.

Databases are created as part of the program for storing the information generated for the gaseous emissions. The databases are for two types of vehicles, on road and off road. This information is available from the EPA web sight. The group members entered the different information into the databases. There is a total of four on road, and five off road databases (see Appendix C).

Another program was added to find the amount of ozone that would be depleted in a 17 year period. This program is written in C++, and it shows data via mathematical model. The program will run and output how much of the ozone layer is left after seventeen years of depletion without replenishment. This was phase II of our project.

It can be anticipated that the number of on and off road vehicles will increase in the future. With all these vehicles there is also a pollution problem. There are millions of vehicles in the USA alone. This does not include the rest of the world. It has been a known fact that the gasses from vehicles are bad for your health. Significantly large quantities of carbon dioxide when present in the atmosphere causes a warming trend due to the Green House Effect. In the United States on road motor vehicles are the number one polluters, and non-road vehicles are number five. Surprisingly the amount of emissions produced since 1975 have gone down or stayed at a constant level due to the technology advancements in vehicles. The off road vehicles have increased in emissions due to the increase of use in industrial and commercial applications. Part of our problem is to evaluate the reduction in emissions.

The computer program was made to correlate two different types of gases. The program will print out five different gases, and asks the user to pick two gases. The program then runs through a do loop to be able to find the different information about the gases. The different information about the gasses is stored in eleven different databases. Once the program has uploaded the information, it runs the information through the program and finds the x-axis and y-axis. With this information, a graph can be developed. The program takes the sum of the on road and off road emissions, and then divides this number by the total number of emissions. This makes a point that is plotted on a graph.

The program, emission.f90, was originally created in Fortran 70 by Dick Allen. The first step in our project was to enter the program into the computer. We then added three subroutines to our program. These subroutines allowed the user to choose from five different gases. The user could select two gases out of the five to correlate. We then setup a DO loop that allowed the computer program to find out which gases were chosen. The program then would process through the information, and print out the regression and the x and y intercepts.

Information about the gases created is stored in databases. The databases are for two types of vehicles, on road and off road. The information was found off the EPA web sight. A total of four on road, and five off road databases (see Appendix C).

When comparing the correlation of the on road emissions, there were not any negative correlation's. When comparing the correlation of off road gases, surprisingly there were some negative correlation's. The FORTRAN 90 program was run eighty-four times to attain this information.

The FORTRAN program was run eighty-four times. Below are five of the on road and five of the off road vehicles. The following shows examples of the correlation of each gas.

OFF ROAD

CO2 & NO2 0.1270 51.0723 0.9989

NO2 & VOC -0.3740 607.263 -0.3389

NO2 & PM-10 0.1122 10.9930 0.8711

SO2 & PM-10 -0.4237 90.3740 -0.4017

It is noted that when comparing off road vehicles, there was some negative correlation's, yet when comparing CO2 & VOC, there is an extremely strong regression factor of 0.9989.

On Road

CO2 & VOC 0.1154 6.6541 0.9831

NO2 & VOC 1.2340 379.8032 0.7552

NO2 & PM-10 0.0491 29.5726 0.5439

SO2 & PM-10 0.6657 8.3895 0.8835

It is interesting to note that when comparing on road vehicles, there were no negative correlation's. Most were over 0.5, the highest was CO2&VOC with a regression factor of 0.9831.

See Appendix C for the graphs.

The program did exactly what it was supposed to do. All the program was

meant to do, was correlate on road and off road gases. The program correlated the

gases, and output a data table showing all of the intercepts. From these intercepts,

it was possible to create graphs. There was a correlation between on road gases,

while sometimes there were negative correlation's of off road gases.

On road gases were correlated in their emissions. With some of the off

road gases, there was a negative correlation. This disproves the groups hypothesis

of all the gases being correlated. Although, most of the gases that were tested had

a correlation. Therefore, there still needs to be a reduction in the amount of

Mrs. Peggy Larisch-Teacher

Ms. Mechelle Taylor-Mentor