Haze and Visibility Research In the

Paso del Norte and West Texas

December 2002 – August 2003 FINAL REPORT FOR PROJECT 582-3-60797

FY 2003

To the Texas Commission on Environmental Quality

(Formerly Texas Natural Resource Conservation Commission) Technical Analysis Division

Submitted by N. J. Parks, R.W. Gray, W.W. Li, D. Raina,

Center for Environmental Resource Management And

Department of Civil Engineering University of Texas at El Paso

El Paso, TX 79968 August 15, 2003

Executive Summary

This is a report of visibility research activities undertaken by the Center for

Environmental Resource Management, University of Texas at El Paso on behalf of the

Texas Commission on Environmental Quality (formerly, Texas Natural Resource

Conservation Commission). In this report, the performance data for digital image

acquisition and archiving at each of several urban El Paso sites and West Texas National

Park or rural sites, collectively denoted as “wilderness.” is presented. In general, the

urban El Paso sites operated 80% or more of the time, as they are available for

convenient maintenance of hardware and re-establishment of the dial-up connection to

the UTEP server. Wilderness site up time varied from 70% up-time for The McDonald

Observatory (University of Texas, Austin) site which was enabled to send large (400kB)

files quickly over the U.T. system internet to a nominal 50% time for the National Park

Service images archived also by this project, and thence, to 20% time for the new Big

Bend installation (stopped by lightning). TCEQ Region VI coordinated a new

deployment of a Guadalupe Mountain National Park camera; that site has operated

continuously since installation in July 2003.

In the image parameters section, a site image is presented along with the “regions of

interest” (ROI) for quality assurance and visibility indexing of the systems. The ROI for

each image is integrated and average pixel brightness is determined. The values obtained

for the period of this study (December 2002 to July 2003) are interpreted in terms of a

contrast ratio (CR) where adequate contrast of juxtaposed image sections can be

identified or in terms of brightness variation, which is indexed as the coefficient of

variation (CV) for chosen ROI.

An initial examination of the relationship of image visibility parameters and reported air

quality and meteorological data by TCEQ was performed and will be continued as part of

an ongoing graduate research project. The results of multiple regression analysis with an

image contrast value as the dependent variable and various of the air quality and

2

meteorological values as independent variables indicated that about 70% of the variation

in contrast (R2 ≈ 0.7) could be explained on the basis of gaseous urban aerosol

component concentrations, various meteorological values, and the solar radiation flux for

the preceding hour. The inclusion of PM 2.5 or PM10 from geographically peripheral

CAMS sites did not markedly improve the statistical associations. The presumption at

this time is that the gaseous components are more ubiquitously distributed and measured,

and therefore, represent a better characterization of the urban aerosol in the camera sight

path (for the long term El Paso downtown view from Chelsea). This latter observation is

salient because of the limited PM 2.5 measurement locations. A comparison to the one

short range (meters) visibility monitor data at Ascarate Park (CAMS 37) showed

remarkable agreement with the 6000-meter path from Chelsea 1 to downtown even

though the park was behind the Chelsea 1 site by several kilometers in the opposite

direction. This separation did lead to dramatic differences in visibility on occasion but

agreement was more common than not. This work also is being continued as part of a

graduate research project that is ongoing under separate auspices.

3

Table of Contents

Executive Summary 02

I. Introduction 06

II. Operation Summary for the Digital Cameras 10

III. Regions of interest and Results 17

IV. Visibility Degradation Parameters and Preliminary Data Analysis 46

V. References 54

4

Acknowledgements

We are grateful to Stuart Dattner, who originally conceived and supported the project,

Fernando Mercado who is the current manager for the project at TCEQ, Bethany

Georgeolis, and Erik Gribben of TCEQ (Technical Assessment) for all their efforts.

We would like to thank Archie Clouse, Victor Valenzuela and Joe Saenz and local

program staff of TCEQ, Region 6.

We would also like to thank Henry Del Rio and Jesus – Chuy Reynoso of the El Paso

City for all the help extended from time to time during the duration of the project.

Additionally we thank Gautam Kumar Agrawala (PhD Candidate ESE Program-UTEP)

for all the help extended to us with data analysis; Ritesh Mariadas and Aqiles Ramos for

data acquisition, files maintenance, and other critical information technology related

activities.

5

I. Introduction

This is the final report for a series of visibility activities undertaken by the Center for

Environmental Resource Management of the University of Texas at El Paso on behalf of

the Texas Commission on Environmental Quality (formerly, Texas Natural Resource

Conservation Commission). In this report, the performance data for digital image

acquisition and archiving at each of several urban El Paso sites and West Texas National

Park or rural sites collectively denoted as “wilderness.” is presented in Section II. In

Section III, site images are presented along with “regions of interest” (ROI) for quality

assurance and visibility indexing of the scenes. Where adequate contrast of juxtaposed

image sections can be identified, the values obtained for the period of this study

(December 2002 to July 2003) are interpreted in terms of a contrast ratio (CR).

Otherwise, brightness variation is indexed as the coefficient of variation (CV) existing for

a chosen ROI.

A long-standing interest has been to get to the point where some continuous PM 2.5 data

was available for image sections chosen for either CR or CV. The interest in PM 2.5

derives for the fact that the visible part of the particulate matter size fraction is 0.4 to 0.8

µm approximate diameter and is contained in the PM 2.5 fraction obtained by current

sampling systems based on effective aerodynamic diameter separations. Section IV

shows some early results of an ongoing graduate research project of one of us (D. Raina)

where the correlation of various air quality parameters reported by TCEQ and the image

parameters computed from pixel brightness levels in various ROI are presented.

In this report, we also have examined the correlation image parameters with PM10 values

available from two CAMS sites that geographically bracket the main view path of the

longest installed visibility site (Chelsea 1) in El Paso (Orquiz, Li, et. al. 2001). The mean

value of the PM 2.5 fraction is about 25% by mass of the PM10 in El Paso. Additionally,

we address in Section IV the influence of solar radiation (various times of the year at the

same MST or GMT) on the intrinsic contrast of chosen targets. Finally, the Visibility

6

values obtained from CAMS 37 have been compared to that of the Contrast Ratio values

calculated for the different sites as part of the contract. The CAMS 37 site uses the

Visibility Sensor – Model 6230 A, manufactured by the Belford Co.

Nine digital image systems operating under the auspices of the Texas Commission on

Environmental Quality (TCEQ) were originally deployed at some time during the period

of this interim report and were continuously acquiring and transmitting images to the

University of Texas Regional Haze archive server (See list in Table I). Since the

original deployment of some of these cameras, two were uninstalled during the fall of

2003 in the course of activities carried out under the auspices of TCEQ Region VI. Of

these two, one was redeployed in July 2003 at in a new location at Guadalupe Mountain

National Park. The other is the Midland camera originally located near the edge of the

Permian Basin.

The UTEP program has archived in the past, five sets of daily images from the Paso del

Norte urban network and 4 sets of daily images from sites in west Texas. In north to

south order, the west Texas sites are Midland-Odessa (Permian Basin), Guadalupe

Mountain National Park (near Carlsbad Caverns National Park), an interstitial area

surveyed from The McDonald Observatory atop Mt. Locke near Ft. Davis, TX, and Big

Bend National Park (the view extends to the Sierra del Carmen in Mexico).

This project has digitally stored images from all the visibility imaging sites. The first,

and most extensive, results are from the archive of urban Paso del Norte digital images

taken at the Chelsea Retirement Home in El Paso with a westerly view of downtown El

Paso and the Sierra de Juarez. The last deployed system in August of 2002 was at The

McDonald Observatory, Ft. Davis, TX, and introduced a changeover from remote

systems using Windows 98 and Kodak DC290 cameras to systems using Windows 2000

and Olympus C2100 cameras.

The performance data for the digital camera systems is given in Section II in terms of

figures and charts showing number of days per month from inception (December 2000)

7

to February 28, 2003 that the unit was judged operational. Generally, this is interpreted

as over 50 percent of the possible images were archived. This study found similar image

quality for the Kodak DC260 used originally in the Big Bend Regional Aerosol and

Visibility Observation (BRAVO) study and currently at BBNP, the Kodak DC290’s

initially deployed for this project, and the Olympus C2100 recently deployed. Improved

reliability of systems (especially those ca. 300 miles from the UTEP laboratories) was the

anticipated result of the changeover to the Olympus C2100. However, improvements in

configuration of DC290 systems have been made and existing such systems are not being

replaced. The Big Bend data is, to date, from the National Park Service camera.

Permission to install a TCEQ camera has been obtained and therefore, images from a

second BBNP camera are expected later in FY 2003.

The Data Appendix DVD accompanying the report contains the spreadsheets with these

data and the image archive and also, a “. PDF” copy of the report. The images and data

for this digital visibility imaging project have been deposited with the University of

Texas El Paso Library, Special Collections, from which they can also be retrieved upon

request.

This project has put in place the initial TNRCC web server technology for the Visibility

Camera Program at http://cams.utep.edu, featuring a satellite image of the Paso del Norte

Air shed with site " yellow dot” icons. Summary of archive numbers are given in Section

II.

The image files are 40KB in size except Mc Donald’s where they are about 400KB

transferred over a LAN connection.

8

Table I.1: TCEQ West Texas Visibility Camera Systems

Name Location Description Camera Type CommunicationChelsea 1 Chelsea

Retirement Center Roof

Westerly View of Downtown El Paso and distant Sierras de Juarez

Kodak DC290

Modem

Chelsea 2 Chelsea Retirement Center Roof

Southerly View toward Ciudad Juarez

Kodak DC290

Modem

Ranger 1 Ranger Peak Southerly View toward Juarez from Ranger Peak Aerial Tramway

Kodak DC290

Modem

Ranger 2 Ranger Peak Southwesterly View of Juarez includes Downtown El Paso and UTEP

Kodak DC290

Modem

GMNP Guadalupe Mountain National Park

Easterly view from Dell City.

Kodak DC290

Modem

UGLC UTEP Undergraduate Learning Center Roof

Southerly view of IH-10, railway and Ciudad Juarez and mountains.

Panasonic WV CP450

LAN

McDonald McDonald Observatory catwalk of 107” telescope.

Southerly view of various mountain peaks and ranges

Olympus 2100

LAN

BBNP 1 Big Bend National Park (NPS site)

Southerly view of Sierra del Carmen Mountains

Kodak DC260

Modem

BBNP 2 Big Bend National Park (TCEQ site)

Easterly view Chisos Mountain Lodge

Kodak DC290

Modem

9

II. Summary of Site Operating Days

The following are the charts that represent the number of days the cameras were

operational, it also includes the time period for the current contract.

05

101520253035

Nov-01

Dec-01

Jan-0

2

Feb-02

Mar-02

Apr-02

May-02

Jun-0

2Ju

l-02

Aug-02

Sep-02

Oct-02

Nov-02

Dec-02

Jan-0

3

Feb-03

Mar-03

Apr-03

May-03

Jun-0

3Ju

l-03

Big Bend National ParkTotal Days with Images by month

Fig. II.1. Big Bend National Park camera (Kodak DC260). National Park Service maintains this camera.

Images are obtained by saving the image from their web site. Single archived images taken at 3:00 pm

local time, can be viewed from the National Park Service website:

http://www2.nature.nps.gov/ard/cams/bibe/bibejpgfram.cfm.

10

05

101520253035

Jul-0

1

Sep-01

Nov-01

Jan-0

2

Mar-02

May-02

Jul-0

2

Sep-02

Nov-02

Jan-0

3

Mar-03

May-03

Jul-0

3

Chelsea 1Total Days with Images by Month

Fig. II.2. Chelsea 1 is the original site in December 2000, but archiving records at UTEP only extend from

July 2001. Back up CD’s from the site does exist.

0

5

10

15

20

25

30

35

Jul-0

1

Sep-01

Nov-01

Jan-0

2

Mar-02

May-02

Jul-0

2

Sep-02

Nov-02

Jan-0

3

Mar-03

May-03

Jul-0

3

Guadalupe Mountain National ParkTotal Days with Images by Month

Fig. II.3. Guadalupe Mountain National Park was deployed in 2001 and uninstalled for a move to a new

location by TCEQ Region VI. It has now been relocated to a new site by TCEQ and UTEP in July 2003.

11

0

5

10

15

20

25

30

35

Jul-0

1

Sep-01

Nov-01

Jan-0

2

Mar-02

May-02

Jul-0

2

Sep-02

Feb-03

Apr-03

Jun-0

3

UTEP Undergraduate Learning CenterTotal Days with Images by Month

Fig. II.4. UTEP Undergraduate Learning Center (UGLC). This site is a live video camera from which

periodic images are archived. The UGLC camera is a Panasonic video camera connected to a Panasonic

NT104 network and Internet server. Images are displayed live via internal proprietary java scripting by

Panasonic. Images are collected from the web page using a recorded sequence includes an image save

routine. Reliability of the image archives is dependent on network and Internet conditions. Local archive

of the images is possible through a video recorder.

12

05

101520253035

Jul-0

1Sep

-01Nov

-01Ja

n-02

Mar-02

May-02

Jul-0

2Fe

b-03

Apr-03

Jun-0

3

Ranger Peak 1Total Days With Images by Month

Fig. II.5. Ranger Peak 1 in the Franklin Mountains overlooking El Paso and Ciudad Juarez.

0

5

10

15

20

25

30

Sep-01

Oct-01

Nov-01

Aug-02

Aug-02

Sep-02

Oct-02

Nov-02

Dec-02

Jan-0

3

Midland OdessaTotal Days with Images by Month

Fig. II.6. Midland-Odessa camera originally placed in the TCEQ offices in September 2001 for testing. In

late August, it was deployed at the Bob Derrington Water Treatment plant south of Odessa with a westerly

view of the plains east of Guadalupe Mountain National Park. TCEQ Region VI uninstalled this camera on

October 10, 2002 for potential relocation. Images during testing are not included in the tabulation. This

camera was relocated to Big Bend National Park (Stopped by lightning).

13

0

5

10

15

20

25

30

35

Jun-0

2

Aug-02

Oct-02

Dec-02

Feb-03

Apr-03

Jun-0

3

Chelsea 2Total Days with Images by Month

Fig. II.7. Chelsea 2 provides a southerly view toward Cd. Juarez.

14

0

5

10

15

20

25

30

35

Aug-02

Sep-02Oct-

02

Nov-02

Dec-02

Jan-03

Feb-03

Mar-03Apr-0

3

May-03

Jun-03

Jul-0

3

McDonald ObservatoryTotal Days With Images by Month

Fig. II.8. McDonald Observatory camera is located on the catwalk of the 107-inch telescope and provides a

southerly view of various mountain ranges and peaks. The system resides permanently on the local area

network and is accessible via the Internet.

05

101520253035

Aug-01

Oct-01

Dec-01

Feb-02

Apr-02

Jun-0

2

Aug-02

Oct-02

Dec-02

Feb-03

May-03

Jul-0

3

Ranger Peak 2Total Days with Images by Month

Fig. II.9. Ranger Peak 2 supplements the images from Ranger 1. It was temporarily removed by TCEQ in

December of 2002.

15

Observations and Conclusions:

The visibility camera systems have presented a number of challenges to provide for

reliability and image quality. The factors include Internet status, computer-camera

software, operating systems, communications, system security and others. In summary,

the Kodak DC290 systems have proven to be reliable with the ability to restart the

systems remotely. The Olympus system has been most robust. Restarting the computer,

loss of connectivity or other factors have no affect on the ability to activate the software

and restart collection of images. In general, the “ARS DIGICAM” software and systems

have been reliable, relatively easy to maintain, and provide high quality images for

documentation and analysis of visibility.

The archive results for this report are not completely representative of the complete

available archive of images from these systems. In some cases, a communication or file

transfer problem exists and images being recorded on the local attached computer were

not transmitted to the ftp and archives at UTEP. During the course of this project,

however, the missing archives will be obtained and added to those available at

ftp://tnrcc.utep.edu for download via the Internet.

16

III. Regions of Interest and Results for the Contrast Ratio and Coefficient of

Variation Analysis for the nine visibility imaging sites

Contrast Ratio (CR) analysis and Contrast Variance (CV) analysis are being performed

on the images at defined times each day that provide acceptable target contrast. The

theoretical foundation for our analyses derives from the classical approach described in

Von Koschmieder’s Habilitationschrift (Koschmieder, 1924, Pt. I and II). The first use

of the present adaptation by us was described by Turner and Parks (Turner, 1998) for

digitized TNRCC video images. Application of an older form of NIH IMAGE©

has been shown to be a facile means to get the basic data out of images as integrals of

pixels brightness from selected ROI’s (Parks 2002, and Sawant 2002). The current work

uses IMAGE-J© (Image 2002), a JAVA language based incarnation of the earlier form

which features a variety of operational improvements.

Contrast Ratio and Contrast Variation are collectively referred to as Visual Air Quality

(VAQ) factors. They are defined by the following equation:

Contrast Ratio: CR = Mean (Bright ROI) – Mean (Dark ROI) Eq. III.1

Mean (Bright ROI)

Contrast Variation: CV = SD (ROI) Eq. III.2

Mean (ROI)

Where;

SD (ROI) = Standard Deviation of the pixel intensities (0 – 255).

Mean (ROI) = the mean of the pixel light intensities.

Where possible (dark and light targets), CR is used. Where no discrete targets exist, CV

is used.

17

In some instances the CR values obtained are negative, this is attributed to the fact that on

that particular day the sky was darker as compared to the ridge and hence the change in

values of the mean and thereby in the CV.

Methods & Materials:

1. The images were analyzed using ImageJ 1.29x Analysis software.

2. The data in Section IV has been analyzed using SPSS statistical package.

18

Chelsea (Site 1):

This camera located atop the Chelsea Retirement Home, produces a westerly view of

downtown El Paso and distant Sierra de Juarez. The classic view has now been used for

over 10 years, it is the best-studied and understood site. Regions of Interest are marked

and labeled in the various figures.

CR Analysis - The four ROI’s that have been used for the TNRCC (now TCEQ)

contracts for 2001 and 2002, have been retained.

Fig. III.1

CR values are being computed for the downtown target buildings (A; B) located

approximately 5 km from the Chelsea site. CR is also being computed for the edge of the

Sierra de Juarez for a ridge-sky two-target basis (C; D) at ca. 12 km.

CV Analysis - Contrast Variance (CV) would be used to look at the spread of color pixel

values for urban zones in El Paso (E) and Ciudad Juarez (F).

19

A ROI encompassing both the black and the white target has been evaluated and can be

used to calculate the CV values, for this view.

In addition the complete image could be used as ROI for CV or Fourier Transform and

spatial frequency evaluation. Spatial frequency can approach zero in parts of the image

during heavy inversions and the total image during sand storms (wind events).

20

Results:

CR & CV Values For BlckWht Bldg Dec 2002

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

12/1/

2002

12/3/

2002

12/5/

2002

12/7/

2002

12/9/

2002

12/11

/2002

12/13

/2002

12/15

/2002

12/17

/2002

12/19

/2002

12/21

/2002

12/23

/2002

12/25

/2002

12/27

/2002

12/29

/2002

12/31

/2002

Days

CR

/CV CR BW

CV BW

Fig. III.2 CR & CV Values for the Black & White building-Dec 2002

CR & CV Values for Blck Wht Bldg Jan 2003 - Mar 2003

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

1/1/

2003

1/8/

2003

1/15

/200

3

1/22

/200

3

1/29

/200

3

2/5/

2003

2/12

/200

3

2/19

/200

3

2/26

/200

3

3/5/

2003

3/12

/200

3

3/19

/200

3

3/26

/200

3

Days

CR

/CV CR BW

CV BW

Fig. III.3 CR & CV Values for the Black & White building-Jan – Mar 2003

21

CR & CV Values for Blck Wht Bldg Apr 2003-June 2003

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

4/1/

2003

4/8/

2003

4/15

/200

3

4/22

/200

3

4/29

/200

3

5/6/

2003

5/13

/200

3

5/20

/200

3

5/27

/200

3

6/3/

2003

6/10

/200

3

6/17

/200

3

6/24

/200

3

Days

CR

/CV CR BW

CV BW

Fig. III.4 CR & CV Values for the Black & White building-Apr – June 2003

CR & CV Values of Blck Wht Bldg July 2003

0

0.1

0.2

0.3

0.4

0.5

0.6

7/1/20

03

7/3/20

03

7/5/20

03

7/7/20

03

7/9/20

03

7/11/2

003

7/13/2

003

7/15/2

003

7/17/2

003

7/19/2

003

7/21/2

003

7/23/2

003

7/25/2

003

7/27/2

003

7/29/2

003

7/31/2

003

Days

CR

/CV CR BW

CV BW

Fig. III.5 CR & CV Values for the Black & White building-July 2003

22

Quality Assurance for the Equipment:

The quality assurance protocol assumes that a sufficiently close target to the camera will

be minimally affected by haze. This is approximately true except for unique events like

sand storms, snow etc. An example from Chelsea 1 is given. An ROI under the bridge

next to the freeway is selected and CV Analysis revealed that the camera functioned

satisfactorily.

Fig. III.5.a

23

The result of the QA test is displayed below;

CV

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

12/5

/200

2

12/1

9/20

02

1/2/

2003

1/16

/200

3

1/30

/200

3

2/13

/200

3

2/27

/200

3

3/13

/200

3

3/27

/200

3

4/10

/200

3

4/24

/200

3

5/8/

2003

5/22

/200

3

6/5/

2003

6/19

/200

3

7/3/

2003

7/17

/200

3

Days

CV CV

Fig. III.6 CV values for the Contract Period for ROI under bridge

24

Chelsea (Site2):

This camera is located on the Chelsea Building but has a different view that in the

Southerly direction toward Ciudad Juarez.

Fig. III.7

CR Analysis - The CR Analysis has been performed on the mountain (A) and the sky (B). CV Analysis - The ridge of the mountain with respect to the sky (C) has been used to calculate the value of CV.

25

RESULTS:

CR & CV for Ridge-Sky & CV for the common ROI (Dec 2002)

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

12/1/

2002

12/3/

2002

12/5/

2002

12/7/

2002

12/9/

2002

12/11

/2002

12/13

/2002

12/15

/2002

12/17

/2002

12/19

/2002

12/21

/2002

12/23

/2002

12/25

/2002

12/27

/2002

12/29

/2002

12/31

/2002

Days

CR

/CV

CR BW

CV COMMON

Fig. III.8 CR & CV values for the Ridge-Sky ROI-Dec 2002

CR/CV for Chelsea 2 Ridge-Sky and Common ROI

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

1/1/20

03

1/8/20

03

1/15/2

003

1/22/2

003

1/29/2

003

2/5/20

03

2/12/2

003

2/19/2

003

2/26/2

003

3/5/20

03

3/12/2

003

3/19/2

003

3/26/2

003

Days

CR

/CV

CR BW

CV COMMON

Fig. III.9 CR & CV values for the Ridge-Sky ROI-Jan – Mar 2003

26

CR for Ridge-Sky and CV for common ROI Apr 03-Jun 03

0

0.05

0.1

0.15

0.2

0.25

4/1/03 4/10/03 4/19/03 4/28/03 5/7/03 5/16/03 5/25/03 6/3/03 6/12/03 6/21/03 6/30/03

Days

CR

/CV

CR BW

CV COMMON

Fig. III.10 CR & CV values for the Ridge-Sky ROI-Apr – June 2003

CR Ridge-Sky CV Common ROI Jul 2003

0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

0.18

0.2

7/1/20

03

7/3/20

03

7/5/20

03

7/7/20

03

7/9/20

03

7/11/2

003

7/13/2

003

7/15/2

003

7/17/2

003

7/19/2

003

7/21/2

003

7/23/2

003

7/25/2

003

7/27/2

003

7/29/2

003

7/31/2

003

Days

CR

/CV

CR BWCV COMMON

Fig. III.11 CR & CV values for the Ridge-Sky ROI-July 2003

27

Ranger Peak (Site1):

This camera has a Southerly View toward Juarez from Ranger Peak Aerial Tramway.

Fig. I.12

CR Analysis - Fig 3 shows the region of r the view from ranger peak 1. The contrast was taken between the mountain and sky nd black building and White building.

in

owntown El Paso and another Block in Ciudad Juarez. Also, a new ROI is to be added

II

interest fo a

CV Analysis - The Coefficient of Variation analysis was performed on the block

D

that encompasses the mountain ridge.

28

Results:

Ranger1 CR Black-White Bldg. & CV Sky-Ridge Common ROI Jan 2003- Mar 2003

0

0.1

0.2

0.3

0.4

0.5

0.6

1/1/20

03

1/8/20

03

1/15/2

003

1/22/2

003

1/29/2

003

2/5/20

03

2/12/2

003

2/19/2

003

2/26/2

003

3/5/20

03

3/12/2

003

3/19/2

003

3/26/2

003

Days

CR

and

CV

CRBW

CVCOMMON

Fig. III.13 CR & CV values for Ranger 1 Jan – Mar 2003

Ranger1 CR Black-White Bldg. & CV Sky-Mountain Common ROI Apr-June 2003

0

0.05

0.1

0.15

0.2

0.25

0.3

4/1/20

03

4/8/20

03

4/15/2

003

4/22/2

003

4/29/2

003

5/6/20

03

5/13/2

003

5/20/2

003

5/27/2

003

6/3/20

03

6/10/2

003

6/17/2

003

6/24/2

003

Days

CR

and

CV

CRBWCV Common

Fig. III.14 CR & CV values for Ranger 1 Apr-May 2003

29

Ranger1 CR Black-White Bldg. & CV Sky-Mountain Common ROI July 2003

0

0.1

0.2

0.3

0.4

0.5

0.6

7/1/20

03

7/3/20

03

7/5/20

03

7/7/20

03

7/9/20

03

7/11/2

003

7/13/2

003

7/15/2

003

7/17/2

003

7/19/2

003

7/21/2

003

7/23/2

003

7/25/2

003

7/27/2

003

7/29/2

003

7/31/2

003

Days

CR

and

CV

CRBWCV Common

Fig. III.15 CR & CV values for Ranger 1 July 2003

30

Ranger Peak (Site2):

he Camera has a Southwesterly View of Juarez including Downtown El Paso and

TEP.

Fig. III.16

CR Analysis – The contrast ratio was performed for the mountain ridge with respect to

e.

T

U

the sky. Two different lengths of ROI’s were taken as shown in the Fig. III.16 abov

31

RESULTS:

RANGER2 CR Ridge-Sky Shrt & CR Ridge-Sky Long Apr-Jun 2003

0

0.05

0.1

0.15

0.2

0.254/

26/2

003

5/3/

2003

5/10

/200

3

5/17

/200

3

5/24

/200

3

5/31

/200

3

6/7/

2003

6/14

/200

3

6/21

/200

3

6/28

/200

3

7/5/

2003

7/12

/200

3

7/19

/200

3

7/26

/200

3

Days

CR

RIJ

SKY(

SHR

T&LN

G)

CR RIJSKY(SHRT)0.3

CR RIJSKY(LNG)

Fig. III.17 CR Ridge-Sky short & CR Ridge-Sky long ROI Apr-Jun 2003

RANGER2 CR Ridge-Sky Shrt & Ridge-Sky Long July 2003

0

0.05

0.1

0.15

0.2

0.25

7/1/20

03

7/3/20

03

7/5/20

03

7/7/20

03

7/9/20

03

7/11/2

003

7/13/2

003

7/15/2

003

7/17/2

003

7/19/2

003

7/21/2

003

7/23/2

003

7/25/2

003

7/27/2

003

7/29/2

003

7/31/2

003

CR

RIJ

SKY(

SHR

T&LN

G)

CR RIJSKY(SHRT)

CR RIJSKY(LNG)

Fig. III.18 CR Ridge-Sky short & CR Ridge-Sky long ROI-July - 2003

32

33

UGLC:

This is the Southerly view of IH-10, railway and Ciudad Juarez and mountains.

Fig. III.19

CR Analysis: The CR analysis was performed for the mountain ridge with respect to the

sky.

CV Analysis: The CV analysis was performed by taking a ROI that encompasses the

ridge of the mountain and the sky.

RESULTS:

UGLC CR Ridge-Sky & CV Common ROI Jan-Mar 2003

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

1/1/20

03

1/8/20

03

1/15/2

003

1/22/2

003

1/29/2

003

2/5/20

03

2/12/2

003

2/19/2

003

2/26/2

003

3/5/20

03

3/12/2

003

3/19/2

003

3/26/2

003

Days

CR

RIJ

SKY

AN

D C

V C

OM

MO

N

CR RIJSKYCV COMMON

Fig. III.20 CR Ridge-Sky mon ROI Jan-Mar 2003 & CV Com

UGLC July 2003

0

0.05

0.1

0.15

0.25

7/1/03 7/6/03 7/11/03 7/16/03 7/21/03 7/26/03

Days

CR

RIJ

SKY

& C

V C

OM

MO

CR RIJSKY

CV COMMON

Fig. III.21 CR Ridge-Sky & CV Common ROI July 2003

0.2

N

34

McDonald Observatory:

This view gives the southerly view form the observatory of various mountain peaks and

ranges.

Fig. III.22 The McDonald Observatory, Department of Astronomy, University of Texas at Austin, atop Mt. Locke (altitude ca. 2200 meters). The central peak in the “notch” of Twin Mountains is Cathedral Peak in Big Bend National Park at a distance of ca. 65 km.

CR Analysis:

This was performed by taking a ROI on the twin mountain and compare it to that of the

ROI of sky above it.

The same procedure was adopted for the Cathedral Peak, which is at a distance of 65 km

from the camera site.

CV Analysis was performed by taking a ROI encompassing the twin mountain ridge and

the sky together.

35

RESULTS:

C R T w in M o u n t/C R C ath ed ra l Peak F eb 2003 - M ar 2003

-0 .2

-0 .1

0

0 .1

0 .2

0 .3

0 .4

0 .5

2/1/20

03

2/8/20

03

2/15/2

003

2/22/2

003

3/1/20

03

3/8/20

03

3/15/2

003

3/22/2

003

3/29/2

003

D ay s

CR

/CV

C R T MC R C P

Fig. III.23 CR Twin Mountains/CR Twin Mountains Feb – Mar 2003

CR Twin Mount/CR Cathedral Peak Apr-June 2003

0

0.3

4/1/03 4/9/03 4/17/03 4/25/03 5/3/03 5/11/03 5/19/03 5/27/03 6/4/03 6/12/03 6/20/03 6/28/03

0.25

0.15

0.2

CR

/CV

0.05

0.1

0.35

0.4CR TM

CR CP

Fig. III.24 CR Twin Mountains/CR Twin Mountains Apr – Jun 2003

Days

36

CR Twin Mount/CR Cathedral Peak July 2003

-0.25

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

7/1/20

03

7/2/20

03

7/3/20

03

7/4/20

03

7/5/20

03

7/6/20

03

7/7/20

03

7/8/20

03

7/9/20

03

7/10/2

003

7/11/2

003

7/12/2

003

7/13/2

003

7/14/2

003

7/15/2

003

7/16/2

003

7/17/2

003

7/18/2

003

7/19/2

003

7/20/2

003

7/21/2

003

7/22/2

003

7/23/2

003

7/24/2

003

7/25/2

003

7/26/2

003

7/27/2

003

7/28/2

003

7/29/2

003

7/30/2

003

7/31/2

003

Days

CR

/CV

CR TM

CR CP

Fig. III.25 CR Twin Mountains/CR Twin Mountains July 2003

37

Quality Assurance for the Equipment:

The Quality Assurance was performed by taking an ROI on the handrail, which is at a

distance of about 2 meters from the camera, and a CV Analysis revealed that the camera

functioned satisfactorily during the duration of the project. A couple of images were

taken every month, for the entire contract period.

Fig III.26 The ROI on the handrail at Mc Donald Observatory

Results:

CV

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

2/5/

2003

2/19

/200

3

3/5/

2003

3/19

/200

3

4/2/

2003

4/16

/200

3

4/30

/200

3

5/14

/200

3

5/28

/200

3

6/11

/200

3

Day

CV CV

s

Fig. III.27 CV values fo e ROI on the handrail

r th

38

BBNP:

39

Fig. III.28

R Analysis: The contrast ratio analysis was performed by taking the contrast of an ROI

untain with respect to that of the sky.

CV Analysis: was performed by taking the ROI encompassing both the sky and the ridge

together.

C

on the mo

Results:

CR Ridge-Sky/ CV Common Mar 2003

-0.2

-0.1

0

0.1

0.2

0.3

0.4

3/1/03 3/4/03 3/7/03 3/10/03 3/13/03 3/16/03 3/19/03 3/22/03 3/25/03 3/28/03 3/31/03

Days

CR

/CV

CR RIJSKY

CV COMMON

-0.3

Fig. III.28 CR Ridge-Sky/CV Common ROI Mar

2003

40

CR Ridge-Sky/CV Common ROI Apr 2003-June 2003

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

4/1/

2003

4/8/

2003

4/15

/200

3

4/22

/200

3

4/29

/200

3

5/6/

2003

5/13

/200

3

5/20

/200

3

5/27

/200

3

6/3/

2003

6/10

/200

3

6/17

/200

3

6/24

/200

3

Days

CR

/CV

CR RIJSKYCV COMMON

Fig. II 003 I.29 CR Ridge-Sky/CV Common ROI Apr - June 2

CR Ridg-Sky/CV Common ROI July 2003

-0.04

-0.02

0

0.02

0.04

0.06

0.08

0.1

7/1/03 7/5/03 7/9/03 7/13/03 7/17/03 7/21/03 7/25/03 7/29/03

Days

CR

/CV

CR RIJSKY

CV COMMON

Fig. III.30 CR Ridge-Sky/CV Common ROI July 2003

41

42

New Big Bend Site (Chisos Lodge) – Westerly View:

Fig. III.31

CR Analysis: This was performed by taking a ROI on the mountain and compare it to that

of the ROI of sky a

CV Analysis: This was performed by taking an ROI encompassing the ridge and the sky

at the distance.

bove it.

Results:

CR Ridge-Sky/CV Ridg ommon ROI July 2003

-0.2

-0.15

-0.1

-0.05

0

0.05

0.1

0.15

7/13/2003 7/14/2003 7/15/2003 7/16/2003 7/17/2003 7/18/2003 7/19/2003 7/20/2003 7/21/2003 7/22/2003 7/23/2003

Days

CR

/CV

CR RijSky

CV Ridge

e C

Fig. III.32 CR Ridge-Sky/CV Common ROI July 2003

43

Guadalupe Mountain National Park (New):

Fig. II 33

ast 2002 views were early December 2002. This camera was uninstalled by TCEQ

egion 6 for re-deployment at a location approximately 15km west of the current site.

he Camera has been reinstalled at a new location in July 2003 by TCEQ and UTEP.

R Analysis. : The CR was computed using the ROI’s shown by the small squares and

quation III.1.

V Analysis: This was performed by taking an ROI encompassing the ridge and the sky

t the distance of the mountain and Equation III.2

I.

L

R

T

C

E

C

a

44

Results:

CR Ridge-Sky/CV Common ROI over mountain and sky July 26 - July 31 2003

0

0.05

0.1

0.15

0.2

0.25

7/26/2003 7/27/2003 7/28/2003 7/29/2003 7/30/2003 7/31/2003

Days

CR

/CV

CR RIJSKY

CV COMMON

Fig. III.34 CR Ridge-Sky/CV Common ROI July 26-31, 2003

45

IV: Additional Analysis of Air Quality Parameters and Visibility

Visibility impairment primarily takes place as a consequence of light scattering by

particles in the Accumulation Mode. It has been reported recently that for El Paso there is

a significant correlation between CO and both ultra-fine and accumulation mode (those

between 0.1 and 1 microns in diameter) particle count. The Pearson correlation

coefficient (r) values reported are 0.81 (r2 ca. 0.64) and 0.87 (r2 ca.0.7) respectively.

(Noble et. al. 2003). This finding is particularly important in the examination of the

relationship of TCEQ reported air quality data and the results of visibility image analyses

for the traditional downtown black-white building target (Chelsea 1). Data sets from most

CAMS stations contain CO, whereas, PM 2.5 (a putatively important indice of visibility)

is only available at field of view.

he analytical work in this section is largely derived from a current, in progress Master of

cience project by one of us (Raina 2003). It is included as a useful tool for the possible

pplications or interpretation of the analytical data described in this section. The work

escribed herein is based on the long term (12 years) traditional westerly field of view

om Chelsea 1 toward downtown El Paso initiated by Stuart Dattner (TCEQ Technical

nalysis Division).

n a priori interest in PM 2.5 derives for the fact that the visible part of the particulate

atter size fraction is 0.4 to 0.8 µm approximate physical diameter and is contained in

e PM 2.5 fraction obtained by current sampling systems based on effective aerodynamic

iameter separations. Various multiple linear regression analyses have been performed

ith the data from the contract period with variables, PM 2.5, PM10, CO, NOx, Wind

peed, Relative Humidity, Sun Angle and Azimuth against the dependent variable,

ontrast Ratio (CR)(see for example, Table IV.1). The CR data was that of the images

nalyzed. The air quality data was obtained from the TCEQ monitored CAMS sites in El

aso (CAMS 12, 37, 40,41).

CAMS sites peripherally positioned to the Chelsea 1

T

S

a

d

fr

A

A

m

th

d

w

S

C

a

P

46

The additi tors

fluencing CR in the downtown Chelsea images over the simple comparison of CR-

omplement (1 – CR chosen for presentation convenience) and PM 2.5 from CAMS 12

izal

roup of warm days. The difference in winter and summer visibility situations is readily

ry

plot of the uncertainty distribution about the curve of maximum

kelihood (straight lines in the 2D plots). With the geographic constraints on PM 2.5 and

)

ion

ip of CR and typical reported air quality and

eteorological values.

onal variables notably improved the understanding of the important fac

in

C

(UTEP) and CAMS 41 (Sun Metro) or the comparison to average PM10 from Cham

(CAMS 40) and UTEP (CAMS 12). The latter two CAMS sites are located on north and

south sides, respectively, of the field of view of Chelsea 1.

Preliminary Data Analysis:

The search for correlations of the CR data with air quality and meteorological data was

addressed with the statistical software, SPSS. The various analyses described herein were

performed for a December, January, February group of days and for a May, June, July

g

apparent from the images (Section III) and the hours of sunlight prior to the 9 AM

analysis time chosen vary from 0.5 to 3.

The first results obtained are presented in Figures IV.1 a, b, c, d. They are the elementa

comparison of PM 2.5 or PM10 with CR. These results are presented two ways. One as a

plot and one as a 3D

li

PM10 measurements (deriving from CAMS site location), it is not surprising that the

Correlation Coefficients (indicating the variability of Y explained by association with X

for CR versus PM are ca. 0.15 to 0.3.

Subsequent addition of all the air quality and meteorology data improved the correlat

coefficients to 0.6 to 0.7. (See Figure IV.2). However, it was suspected that the

correlation of CR with vapor phase components of the urban aerosol — notably fine

particle coupled CO — available from most CAMS sites, might represent an improved

demonstration of the relationsh

m

47

Multiple regression results for three sites, CAMS 12, CAMS 37, and CAMS 41,

representing sites to the north, behind, and ahead of the field of view of Chelsea 1 are

given in Table IV.1. These results do not include any PM data. The

t

t” through the field of view

at is integrated by the methods used herein and described in Section III.

R2 value, in at leas

one case (Sun Metro), improved by removing the PM 2.5 data as a variable. This is

presently attributed to the site of PM 2.5 data collection being physically located behind

the downtown buildings and removed from the “line-of-sigh

th

48

ig. IV.1a. Scatter plot of C-Comp versus PM 2.5 from CAMS 12 (above)

ig. IV 1b. Probability distribution about the red line of Fig IV.1a above.

F

01.

12.

23.

34.

45.

56.

67.

7

8.8

9.9

11

12.1

13.2

14.3

15.4

16.5

0

0.65

00.10.20.30.40.50.60.70.8

0.9

1

Rel. Freq

PM2.5

Ccomp

CR Complement with PM2.5

F

49

ig. IV.1c. Scatter plot of PM 2.5 average data from CAMS 12 and CAMS 40 versus C-comp

Fig. IV.1d. Probability distribution about the red line f Figure IV.1c.

F

0

9

18

27

36

45

54

63

72

81

90

99

108

117

126

135

144

0

0.55

0

0.02

0.04

0.06

0.08

0.1

0.12

Rel. Freq

PM10

Ccomp

CR Complement with PM10

o

50

R2 Values

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

PM2.5 w ithRel.Humidity

PM2.5 w ith Met Data PM10 w ithRel.Humidity

PM10 w ith Met Data

Variable

Con

cent

ratio

n

Winter

Summer

Fig. IV.2. Comparison of Correlation Coefficients from multiple regression of either a limited air quality

data set or data sets (marked “with met”) that include all the meteorological and air quality data.

uring the winter (Dec, 02-Feb, 03), PM 2.5 and relative humidity explains only 30% of

e variability associated with visibility. On the other hand up to 70% of the variability

an be explained with all meteorological and air quality data.

able V.1. Multiple regression coefficients (c) and Coefficient of Determination (R2) for comparison of

R to various gas phase urban aerosol components and meteorological data

Parameters/coefficients CAMS12 (UTEP)

CAMS37 (Ascarate)

CAMS41 (Chamizal)

D

th

c

T

C

Constant 0.553955315 0.331308595 0.637027331 CO_1_PPM -0.144260345 0.032924972 -0.252941274 NOx_1 ppb -0.001014248 -0.001524366 0.000884885 O3_2_PPB -0.003454084 -0.002079178 0.002681624

WSR_1 mph -0.01093396 0.002399688 -0.013540955 Out Temp_1 deg F -0.000834302 -0.002557625 -0.003147041

Rel. Humid_1 % -0.003277 48 -0.002779647 -0.003139329 0Solar Rad_1 Ly/min

20.673898816 0.890823854 0.602488015

R 0.643 0.541 0.762

51

52

In the summer (May, 03-Jul, 03) variability up to 15% can be explained when PM 2.5 is

analyzed with relative humidity. Similarly the explainable variability for all

meteorological factors is 50 to 70%. Subsequently, three CAMS sites data sets for the

vapor phase and meteorological data alone (no PM) was compared to CR. These

intriguing results are contained in Table IV.1. These preliminary results suggest that

indeed, the vapor phase fraction (most likely CO) is an important influence on CR and

visibility.

Lastly, it has been possible to make a comparison of CR for the downtown Chelsea 1

field of view with the Visibility data reported on the TCEQ air data web URL from

Ascarate Park. Ascarate (CAMS 37) is located physically behind Chelsea 1 in an easterly

direction. The visibility unit has a relatively short path length (on the order of meters) in

comparison to the path length from Chelsea 1 to downtown, which is ca. 6000 meters.

The results are shown in Figure V.3. Extensive data cleaning has not been performed.

For example, the one point a approximately CR = 0 is presumed to be an event that

dramatically affected the 6000 meter Chelsea 1 view and not the orders of magnitude

orter Ascarate Park measurement. Given the physical separation and the different

Fig.

iles from the monitor at Ascarate Park (CAMS 37).

sh

measurement methods, the agreement is notable.

y

0.6

0.7

values from C -White building d Visibility

CR V S V is ib ilty

= 0.1695x + 0 .1304R2 = 0 .4224

0.5

0.8

1 2.5 4

y

V.3. Comparison of CR helsea 1 (Black ) and the reporte in

00 0.5

0.1

0.2

0.3

0.4CR

1.5 2 3 3.5

V is ib ilt

m

The four outliers correspond to days, which are relatively infrequent in El Paso. They

represent situations, which are typically “off-scale” for the present 6000-met

to compute CR or CV for downtown. They are included here for completeness. Withou

these points, R2 is ca. 0.45.

er path used

t

53

54

29x. Rasband W., National Institutes of Health; Washington,

.C.

oschmieder, Von H. (1924). Theory der horizontalen sichtweite. Beitrage zur physik

er freien atmosphare. Vol. 12, p.p.: 33-53 (Part I) and 171-181 (Part II).

i (2001). Li Wen-Whai, Orquiz R., Garcia J., Espino, T., Pingitore, N.E., Gardea-

orresdey, J., Chow, J., and Watson, J.G., – “Analysis of temporal and spatial

ichotomous PM air samples in El Paso-Cd. Juarez air quality basin” – AMWA Nov.

arks (2002). Parks, N.J., Gray, R.W., Li, W.W., Sawant, R.R., – “Visibility Research ith the Texas Commission on Environmental Quality Camera Systems in the Paso del orte and West Texas Regions 2001-2002”.

oble (2003) Noble, C.A., Mukerjee, S., Gonzales, M., Rodes, C.E., Lawless, P.A.,

atarajan,S., Myers, E.A., Norris, G.A., Smith, L., Ozkaynak, H., Neas, L.M. –

Continuous measurement of fine and ultrafine particulate matter, criteria pollutants and

eteorological conditions in urban El Paso, Texas” – Atmospheric Environment, 37,

sue 6, February, Pages 827-840.

awant (2002) Sawant, R.R. – “Haze and Visibility in wilderness and urban areas” –

aster’s Thesis, University of Texas at El Paso.

urner (1998) Turner, C.D., Parks, N.J. – “Trans-Boundary visibility Analysis” –

outhwestern Consortium for Environmental Research and Policy, 1995-1996.

V. References

IMAGE-J (2002). ImageJ 1.

D

K

d

L

T

d

PwN

N

N

“

m

Is

S

M

T

S