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SURVEILLANCE PROJECT
MEASUREMENT
OF AIR POLLUTION
USIN
STATIC MONITOR
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U. S. ENVIRONMENTAL PROTECTION AGENC
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INTERSTATE SURVEILLANCE PROJECT:
MEASUREMENT OF AIR POLLUTION
USING STATIC MONITORS
James H. Cavender
William M. Cox
Maurice Georgevich
Norman A. Huey
George A. Jutze
Charles E. Zimmer
U.S. ENVIRONMENTAL PROTECTION AGENCY
Air Pollution Control Office
Research Triangle Park, North Carolina
May 1971
For sale by the Superintendent of Documents, U.S. Government Printing Office, Washington, D.C. 20402 - Price $1.25
Stock Number 5503-0006
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The APTD (Air Pollution Technical Data) series of reports is issued by the Air Pollution Control
Office to report technical data of interest to a limited readership. Copies of APTD reports are
available free of charge to APCO staff members, current contractors and grantees, and nonprofit
organizations -as supplies permit - from the Office of Technical Information and Publications, Air
Pollution Control Office, U.S. Environmental Protection Agency, P.O. Box 12055, Research Triangle
Park, North Carolina 27709.
Air Pollution Control Office Publication No. APTD -0666
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ACKNOWLEDGMENTS
The monitoring network for the Interstate Surveillance Project could not have been established and operated
without the support of the many individuals in the local and state agencies who provided much of the on-site
servicing and day-to-day operation. The Air Pollution Control Office of the Environmental Protection Agency
offers its sincere thanks to those organizations and to their employees.
Contributors George Jutze and Charles Zimmer of Resources Research, Inc., performed their portion of this
project under contract with Research Triangle Institute.
111
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CONTENTS
Section Page
LIST OF FIGURES vii
LIST OF TABLES viii
1. INTRODUCTION
Maurice Georgevich and George Jutze 1
1.1 Objectives 1
1.2 Data Limitations . . . ... 1
1.3 Surveillance Network 2
1.3.1 Station Classification 2
1.3.2 Station Types 2
1.3.3 Station Operation 2
2. DESCRIPTION OF MONITORING UNIT
Norman Huey and Maurice Georgevich 9
2.1 Basic Structure 9
2.2 Monitor Components . . . . 10
2.3 Measuring Metal Corrosion 11
2.3.1 Zinc Panel 11
2.3.2 Steel Panel 11
2.4 Evaluating Color Fading 11
2.4.1 Causes 12
2.4.2 Dyed-Fabric Panels 12
2.5 Measuring Material Deterioration 12
2.5.1 Nylon Panel 13
2.5.2 Silver Plate 13
2.5.3 Rubber Panel 13
2.6 Measuring Sulfation 14
2.6.1 Sulfation Candle 14
2.6.2 Sulfation Plate 14
2.7 Evaluating Soiling 14
2.7.1 Dustfall Bucket 14
2.7.2 Sticky Paper 15
3. DISCUSSION OF PROJECT DATA
James Cavender 17
3.1 Frequency Distributions for all Components 17
3.1.1 Background Stations 17
3.1.2 Stations by Classification 17
3.2 Seasonal Effects on Components 25
3.3 Annual Averages for all Components 25
3.4 Summary 31
4. AREA EVALUATION
Norman Huey and George Jutze 33
4.1 Frequency Distribution of Areas 33
4.1.1 Assigning Pollutant Code Numbers (PCN's) 33
4.1.2 Defining Pollutant Problems 36
4.2 Evaluation of Particulate Problems 38
4.3 Evaluation of Sulfur Oxide Problems 39
4.4 Evaluation of Hydrogen Sulfide Problems 39
4.5 Evaluation of Acid Aerosol Problems 41
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Section Page
4.6 Evaluation of Nitrogen Oxide Problems 43
4.7 Evaluation of Oxidant Potential Problems 43
4.8 Summary 45
5. STATISTICAL EVALUATION OF DATA
William Cox and Charles Zimmer 47
5.1 Correlations between Components 47
5.2 Correlations of Components and Meteorological Parameters 47
5.2.1 Relative Humidity 47
5.2.2 Moisture and Temperature 50
5.3 Correlations Between Components and Air Quality Data 51
5.4 Factor Analysis 52
5.4.1 Factor Analysis Technique 52
5.4.2 Results 53
5.4.3 Factor-Score Matrix 54
5.5 Discussion of Analyses 54
5.6 Discussion of Components 56
5.6.1 Zinc Panels 56
5.6.2 Steel Panels 57
5.6.3 Sulfation Candles and Plates 57
5.6.4 Rubber Panels 57
5.6.5 Dustfall Buckets 57
5.6.6 Sticky Paper 57
5.6.7 Nylon Panels 57
5.6.8 Dye-Fabric Combinations 57
5.6.9 Silver Plates 58
6. CONCLUSIONS
James Cavender and Norman Huey 59
7. REFERENCES 61
Appendix A
List of Interstate Surveillance Project Stations by State 63
Appendix B
Data Summary 73
Appendix C
1968 Quartile Rankings of Components by Area and Station 147
VI
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LIST OF FIGURES
Figure Page
2-1 "Effects Network" Sampler 9
31 Distribution of Rubber Deterioration Results by Month, 1968 25
3-2 Distribution of Sulfation Results by Month, 1968 26
3-3 Distribution of Dustfall Results by Month, 1968 26
3-4 Distribution of Fabric No. 8 Results by Quarter, 1968 27
3-5 Distribution of Fabric No. 9 Results by Quarter, 1968 27
36 Geographic Distribution of Lead Candle Sulfation Measurements, 1968 ... 30
VII
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LIST OF TABLES
Table
1-1 Interstate Surveillance Project Network Areas 3
2-1 Effects of Pollutants on Monitor Components 1°
2-2 Dye-Fabric Combinations for Nine Components 12
3-1 Frequency Distribution of Measurements, 1967-1968 18
3-2 Frequency Distribution of Background Stations, 1968 20
3-3 Frequency Distribution of Industrial Stations, 1968 21
34 Frequency Distribution of Commercial Stations, 1968 22
3-5 Frequency Distribution of Residential Stations, 1968 23
3-6 Frequency Distribution of Rural Stations, 1968 24
3-7 Effects Network Annual Averages Cumulative Frequency Distribution, 1967-1968 28
4-1 Component-Pollutant Relationship Shown by Pollutant Code Number 33
4-2 Maximum Pollutant Code Number Tabulation, By Area 34
4-3 Number and Relative Severity of Air Pollution Problems in ISP Areas 37
4-4 Relationship of Particulate Emission Density to ISP Particulate Problem Severity Index, 1968 . . 39
4-5 Other ISP Areas for Which Particulate Emission Density Estimates Are Available 40
4-6 Relationship of Sulfur Oxides Emission Density to ISP Sulfur Oxides Problem Severity Index . . 40
4-7 Other ISP Areas for Which Sulfur Oxides Emission Density Estimates Are Available 41
4-8 Relationship of Sources to ISP Hydrogen Sulfide Problem Severity Index 42
4-9 Relationship of Sources to ISP Acid Aerosol Problem Severity Index 42
410 Nylon Deterioration in Volunteer Arsenal Area 43
411 Relationship of Sources to ISP Nitrogen Oxides Problem Severity Index 44
412 Oxidant-Potential Areas 44
5-1 Effects Correlation Matrix, 1967 48
5-2 Effects Correlation Matrix, 1968 49
5-3 Correlations Among Monthly CAMP and Effects Components 51
5-4 Factor Loadings for 1967 and 1968 53
5-5 Comparison of "Dirtiness" Factor Severity Index and Particulate Severity Index 55
5-6 Comparison of "Corrosive" Factor Severity Index and Sulfur Oxides Severity Index 56
6_! Components Used in Effects Sampling 59
A1 Interstate Surveillance Project Stations 64
B-l Data Summary 74
C1 Component Ranks, 1968 148
VIll
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INTERSTATE SURVEILLANCE PROJECT:
MEASUREMENT OF AIR POLLUTION
USING STATIC MONITORS
1. INTRODUCTION
Maurice Georgevich and George Jutze
The Interstate Surveillance Project (ISP), originally called the Effects Network, was initiated in 1965 to meet
a responsibility for collecting data and evaluating interstate air pollution. This responsibility, outlined in Section
105 (c) of the Clean Air Act of 1963 and reinforced by the Air Quality Act of 1967, was assigned to the
Division of Abatement* of the Air Pollution Control Office (APCO) of the Environmental Protection Agency.
If traditional methods of data gathering had been used, it would not have been possible to gather detailed air
quality data on the type and severity of emissions for all areas within the constraints of the projected
time-frame and resources. For this reason the Branch decided to use relatively unsophisticated measurement
techniques based on the use of static pollutant indicators. The indicator or field measurement device was to be
the so-called "effects package," a static monitoring unit used for measuring pollutant levels and for identifying
effects.
1.1 OBJECTIVES
To partially fulfill its responsibility, the Abatement Branch formulated the following ISP objectives:
To obtain interstate, intrastate, and international information on the types and degrees of air pollution in these
areas, and to provide information for later in-depth studies.
To demonstrate the validity of the static monitor as a tool for measuring the effects of air pollutants on
materials.
To provide continuing surveillance to determine air pollution trends in these areas.
In the early phases of the project, primary emphasis was directed to interstate areas, although some stations,
located in intrastate areas, were usually operated in conjunction with state or university programs. As the regional
aspects of air pollution control were expanded, the project increased its nationwide coverage by adding a number
of intrastate and international areas.
1.2 DATA LIMITATIONS
A detailed evaluation of climatological effects on the ISP components was found to be not feasible for this
project. A number of meteorological parameters, however, were identified, evaluated, and later compared with
data from the surveillance network to identify significant cause-effect relationships. The comparison was limited
by several constraints:
1. Requisite control chamber studies had not been undertaken to establish a scientific data base from which
the meteorological sensitivity of the components could be determined.
2. Changes in site location between time of meteorological measurements and time of effects measurements
together with changes in sampling times made statistical or mathematical analysis very difficult.
3. A network of field stations for climatological measurement had not been specifically included in the design
of the ISP network.
4. Component measurements are the result of the complex interrelationships of climatological and
demographic effects, which are extremely difficult to separate.
To the extent that a limited comparative analysis was performed, a number of cause-effect relationships will be
discussed in the statistical evaluation section of this report.
*Then called the Abatement Branch of the Division of Air Pollution.
1
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1.3 SURVEILLANCE NETWORK
The first stations of the surveillance network were placed on-line in January 1966; 106 stations were operating
by the end of the year. By December 1967, the network had increased to 224 stations, and by December 31,
1968, to 269. About 20 percent of the 269 are in intrastate areas, and 80 percent are near state boundaries. A
complete listing by state, Table A-l of Appendix A, provides station numbers, names, and addresses.
The 269 surveillance network stations are grouped into 144 areas, some areas with as many as ten stations,
others with one. Generally, the number of stations will vary according to the size and complexity of the area. In
Table 1-1 is an alphabetical listing of the 144 areas with station numbers, locations, types, and classifications for
each area.
Data from the ISP network, used in abatement activities by the Division of Abatement, form part of the data
base from which specific conclusions and recommendations were drawn. Moreover, the Office of Regional
Activities, APCO, has used ISP network data and other data to define the Air Quality Control Regions.
1.3.1 Station Classification
The varied objectives of the ISP make it mandatory that the individual stations be located in highly polluted
areas as well as in more remote, less polluted areas. The population and the complexity of the area emissions
determine the number and location of the stations.
To aid in data interpretation, sampling site locations were classified by general location into four groups:*
residential, commercial, industrial, and rural. Residential areas, as the name implies, are comprised almost entirely
of residential dwellings, with few or no commercial enterprises. Commercial areas, used primarily for business
purposes, are usually downtown urban areas. Industrial areas are those used primarily for manufacturing or
production. Rural areas, those away from the city or town, have few residential dwellings; they are not
necessarily considered as unpolluted areas since they may be near to or influenced by point emission sources;
they are not the same as background stations, discussed below under "Station Types."
Of the 269 stations on-line through 1968, 130 were located in residential, 73 in commercial, 43 in industrial,
and 23 in rural areas.
1.3.2 Station Types
Although ISP stations are categorized as one of four types depending upon area location, pollution components
for all types of stations remain the same.
Type 1 stations, referred to as regular monitoring stations, are located in interstate areas.
Type 2 stations, referred to as CAMP stations, are located close to Public Health Service Continuous Air
Monitoring Program (CAMP) stations. CAMP stations at six locations, Washington, Cincinnati, Chicago, St. Louis,
Philadelphia, and Denver, monitor sulfur dioxide, nitrogen dioxide, nitrogen oxide, carbon monoxide, methane,
and hydrocarbons. ISP stations were located in these areas so that data on gas pollutants from the continuously
monitored CAMP sites could be correlated with data accumulated by the static devices of the "effects package."
Type 3 stations, referred to as experimental stations, are usually set up in intrastate areas in conjunction with
state and/or university air pollution programs.
Type 4 stations, referred to as background stations, are located in areas with no significant air pollution sources;
they were selected to provide normative background data.
1.3.3 Station Operation
Operation of a network of this magnitude, with the limited manpower available, made it necessary to obtain the
assistance of local volunteers for on-site servicing and day-to-day site operation. In most cases this assistance was
provided by local health departments or air pollution agencies through arrangements made by regional directors
of Public Health Service air pollution control programs and by heads of the appropriate state agencies for air
pollution control.
Supplies and analytical or statistical services provided by APCO to local agencies included complete instructions,
shipping containers, and other equipment. On-site visits were made by APCO personnel to resolve problems and
to insure rapport with the servicing agencies.
*The classifications do not necessarily correspond to existing municipality zoning categories.
Introduction
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Table 1-1. ISP NETWORK AREAS
Area name
Albany
Anchorage
Ann Arbor
Augusta
Austin
B astro p
Beaumont
Bellingham
Binghamtom
Blacksburg
Block Island
Bluefield
Bogalusa
Boston
Boulder City
Bridgeport
Bristol
Broward County
Brownsville
Brown wood
Buffalo
Bullfrog
Burlington
Cairo
Calexico
Cannon Mountain
Carville
Chapel Hill
Charleston
Charlotte
Chattanooga
Cheyenne
Chicago
Station
number
22
30
246
224
131
133
120
216
208
121
122
123
124
77
25
195
189
159
160
214
192
89
243
148
158
135
119
125
23
24
264
265
266
267
262
181
258
93
175
219
237
238
263
31
32
33
140
141
252
26
52
53
54
Station location
Albany, New York
Albany, New York
Anchorage, Alaska
Ann Arbor, Michigan
Augusta, Georgia
North Augusta, South Carolina
Austin, Texas
Bastrop, Louisiana
Crossett, Arkansas
Beaumont, Texas
Port Arthur, Texas
Orange, Texas
Sulfur, Louisiana
Bellingham, Washington
Binghamton, New York
Blacksburg, Virginia
Block Island, Rhode Island
Bluefield, West Virginia
Bluefield, Virginia
Bogalusa, Louisiana
Boston, Massachusetts
Boulder City, Nevada
Bridgeport, Connecticut
Bristol, Tennessee
Bristol, Virginia
Broward County, Florida
Brownsville, Texas
Brownwood, Texas
Niagara Falls, New York
Buffalo, New York
Cheektowaga, New York
Buffalo, New York
Niagara Falls, New York
Niagara Falls, New York
Bullfrog, Utah
Burlington, Vermont
Cairo, Illinois
Calexico, California
Cannon Mountain, New Hampshire
Carville, Louisiana
Chapel Hill, North Carolina
Chapel Hill, North Carolina
Charleston, Indiana
Charlotte, North Carolina
Charlotte, North Carolina
Rock Hill, South Carolina
Chattanooga, Tennessee
Chattanooga, Tennessee
Cheyenne, Wyoming
Chicago, Illinois
East Chicago, Illinois
Hammond, Indiana
Chicago, Illinois
Station
classification3
R
C
R
R
C
R
R
I
R
R
R
R
R
I
I
R
Rural
C
C
C
C
R
I
C
C
R
C
R
I
I
I
R
I
I
R
R
C
R
Rural
R
Rural
R
R
R
R
R
C
R
R
C
1
R
R
Station
type
1
1
3
3
1
1
3
1
1
1
1
1
1
1
1
4
4
1
1
1
3
1
1
1
1
3
1
4
1
1
1
1
1
1
4
1
1
1
4
3
4
3
3
1
1
1
1
1
1
2
1
1
1
INTERSTATE SURVEILLANCE PROJECT
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Table 1-1 (continued). ISP NETWORK AREAS
Area name
Chicago (continued)
Cincinnati
Clarkston
Clifton
Columbus
Columbus
Corvallis
Custer
Davenport
Del Rio
Denver
Detroit
Douglas
Dubuque
Dulce
Duluth
Station
number
55
136
137
138
139
149
6
70
154
155
74
75
76
261
142
143
37
69
244
57
58
59
115
27
34
35
162
163
165
170
196
102
227
228
100
49
50
Eagle Pass I 116
East Helena
Easton
El Paso
254
14
230
103
104
| 105
Evansville j 44
| 161
Fairbanks | 247
Fall River j 188
! 191
Fargo
Farmington
198
249
98
99
i Station
Station locat,on classification3
Calumet City, Illinois
Cicero, Illinois
Bedford Park, Illinois
Chicago Heights, Illinois
Palatine, Illinois
Gary, Indiana
Cincinnati, Ohio
Cincinnati, Ohio
Covington, Kentucky
Cincinnati, Ohio
Lewiston, Idaho
Lewiston, Idaho
Clarkston, Washington
Clifton, Arizona
Columbus, Georgia
Phenix City, Alabama
Columbus, Ohio
Corvallis, Oregon
Custer, South Dakota
Rock Island, Illinois
Moline, Illinois
Davenport, Iowa
Del Rio, Texas
Denver, Colorado
Detroit, Michigan
River Rouge, Michigan
Grosse lie, Michigan
Livonia, Michigan
Ojibway, Ontario, Canada
Windsor, Ontario, Canada
Dearborn, Michigan
Douglas, Arizona
Dubuque, Iowa
East Dubuque, Iowa
Dulce, New Mexico
Duluth, Minnesota
Superior, Wisconsin
Eagle Pass, Texas
East Helena, Montana
Easton, Pennsylvania
Kintnersville, Pennsylvania
Sunland Park, New Mexico
Anthony, New Mexico
El Paso, Texas
Evansville, Indiana
Henderson, Kentucky
Fairbanks, Alaska
North Tiverton, Rhode Island
Fall River, Massachusetts
Fargo, North Dakota
Moorhead, Minnesota
Shiprock, New Mexico
Farmington, New Mexico i
R
R
Station
type
1
1
1
I | 1
I
R
R
R
R
R
C
I
C
C
R
R
R
R
R
Rural
C
C
C
R
C
R
I
I
R
C
Rural
I
R
I
C
R
R
R
C
I
R
Rural
R
R
R
R
R
C
C
C
C
R
R
R
1
1
1
2
1
1
1
1
1
1
1
1
1
3
4
4
1
1
1
1
2
1
1
1
1
1
1
1
1
1
1
4
1
1
1
3
1
4
1
1
1
1
1
3
1
1
1
1
1
1
Introduction
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Table 1-1 (continued). ISP NETWORK AREAS
Area name
Fernandina Beach
Fort Smith
Frankfort
Frannie
Gainesville
Grand Forks
Hartford
Hennepin
Hilo
Honolulu
Huntington
International Falls
Jackson
Joplin
Kansas City
Kenosha
Keyser
Laredo
Lawrence
Lebanon
Leesburg
Longview
Los Angeles
Louisville
Luray
Madawaska
May's Landing
McAllen
Memphis
Milbank
Mobile
Montauk Point
Station
number
134
231
232
210
211
106
253
233
197
248
184
56
242
241
65
66
67
251
269
206
207
47
48
85
86
87
51
150
151
152
153
117
173
177
171
180
114
80
81
239
240
39
40
172
193
1
118
147
209
245
250
146
144
Station location
St. Marys, Georgia
Fernandina Beach, Florida
Fernandina Beach, Florida
Fort Smith, Arkansas
Sallisaw, Oklahoma
Frankfort, Kentucky
Frannie, Wyoming
Gainesville, Florida
Grand Forks, North Dakota
East Grand Forks, North Dakota
Hartford, Connecticut
Hennepin, Illinois
Hilo, Hawaii
Honolulu, Hawaii
Huntington, West Virginia
Ironton, Ohio
Ashland, Kentucky
International Falls, Minnesota
Jackson, Mississippi
Joplin, Missouri
Miami, Oklahoma
Kansas City, Kansas
Kansas City, Missouri
Independence, Missouri
Kansas City, Missouri
Kansas City, Kansas
Kenosha, Wisconsin
Cumberland, Maryland
Bloomington, Maryland
Piedmont, West Virginia
Keyser, West Virginia
Laredo, Texas
Salem, New Hampshire
Lawrence, Massachusetts
Lebanon, New Hampshire
White Plain Junction, Vermont
Leesburg, Virginia
Longview, Washington
Rainier, Oregon
Los Angeles, California
Los Angeles, California
Louisville, Kentucky
Jeffersonville, Indiana
Luray, Virginia
Madawaska, Maine
May's Landing, New Jersey
McAllen, Texas
Memphis, Tennessee
West Memphis, Arkansas
Milbank, South Dakota
Ortonville, Minnesota
Mobile, Alabama
Montauk Point, L.I., New York
Station
classification3
C
R
R
C
R
R
R
R
R
R
C
Rural
Rural
R
I
I
C
R
R
C
R
I
C
R
R
I
C
C
R
R
R
C
R
R
C
C
R
R
R
I
C
C
R
Rural
R
Rural
C
R
R
R
R
R
R
Station
type
1
1
1
1
1
3
1
3
1
1
3
4
4
3
1
1
1
1
3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
4
1
1
3
3
1
1
4
1
4
1
1
1
1
1
1
3
INTERSTATE SURVEILLANCE PROJECT
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Table 1-1 (continued). ISP NETWORK AREAS
Area name
Natchez
Needles
New Orleans
New York
Nogales
Oakland
Omaha
Oneca
Overland Park
Owensboro
Paducah
Parkersburg
Pascagoula
Pensacola
Petersburg
Philadelphia
Phoenix
Portland
Portsmouth
Providence
Puerto Rico
Pullman
Rooseveltown
St. Joseph
St. Louis
San Ysidro
Sarnia
Station
number
215
235
90
91
218
2
3
4
5
19
20
21
229
101
95
202
203
130
88
41
42
43
259
260
63
64
234
145
29
11
12
13
17
268
82
83
84
174
176
187
190
255
256
257
73
194
204
205
28
45
46
94
166
Station location
Vidalia, Louisiana
Natchez, Mississippi
Davis Dam, Arizona
Needles, California
New Orleans, Louisiana
Perth Amboy, New Jersey
Elizabeth, New Jersey
Staten Island, New York
Brooklyn, New York
Mineola, New York
White Plains, New York
Greenwich, Connecticut
Metuchen, New Jersey
Nogales, Arizona
Oakland, California
Omaha, Nebraska
Council Bluffs, Iowa
Oneca, Florida
Overland Park, Kansas
Hawesville, Kentucky
Tell City, Indiana
Owensboro, Kentucky
Metropolis, Illinois
Paducah, Kentucky
Parkersburg, West Virginia
Marietta, Ohio
Pascagoula, Mississippi
Pensacola, Florida
Petersburg, New York
Philadelphia, Pennsylvania
Philadelphia, Pennsylvania
Philadelphia, Pennsylvania
Camden, New Jersey
Phoenix, Arizona
Portland, Oregon
Portland, Oregon
Vancouver, Washington
Portsmouth, New Hampshire
Eliot, Maine
Pawtucket, Rhode Island
Attleboro, Massachusetts
Guaynabo, Puerto Rico
Salinas, Puerto Rico
El Yungue, Puerto Rico
Pullman, Washington
Rooseveltown, New York
Elwood, Kansas
St. Joseph, Missouri
St. Louis, Missouri
St. Louis, Missouri
East St. Louis, Missouri
San Ysidro, California
Port Huron, Michigan
Station
classification8
R
I
Rural
C
C
I
R
I
I
R
R
I
C
R
C
R
R
Rural
Rural
Rural
R
R
R
I
I
R
R
R
Rural
C
R
R
C
C
C
R
R
C
R
C
C
Rural
Rural
Rural
R
Rural
R
C
I
I
C
Rural
R
_
Station
type
1
1
1
1
1
1
1
1
1
1
1
1
1
1
3
1
1
4
4
1
1
1
1
1
1
1
1
1
4
1
1
2
1
3
1
3
4
4
4
1
1 1
1
2
1
1
1
1
Introduction
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Table 1-1 (continued). ISP NETWORK AREAS
Area name
Sarnia (continued)
Sault St. Marie
Savannah
Seattle
Sherman
Shreveport
Sioux City
Sioux Falls
South Tahoe
Spokane
Spray
Springfield
Steubenville
Sumpter Township
Tampa
Texarkana
The Dalles
Ticonderoga
Toledo
Trenton
Vicksburg
Volunteer Arsenal
Washington, D.C.
Westerly
Wichita Falls
Wilmington
Winona
Station
number
167
168
169
223
132
78
127
212
213
200
201
199
96
97
71
72
156
157
222
182
183
60
61
62
220
221
164
68
128
129
79
178
179
36
18
217
236
107
108
109
110
7
111
112
113
185
186
126
8
9
10
16
225
Station location
St. Clair, Michigan
Sarnia, Ontario, Canada
Sarnia, Ontario, Canada
Sault St. Marie, Michigan
SavanrlphJGeorgia
Seattle,' Washington
Sherman; Texas
Marshall, Texas
Shreveport, Louisiana
South Sioux City, Nebraska
Sioux City, Iowa
Sioux Falls, South Dakota
South Tahoe, California
Incline Village, Nevada
Coeur D'Alene, Idaho
Spokane, Washington
Spray, North Carolina
Danville, Virginia
Martinsville, Virginia
Springfield, Massachusetts
Thompsonville, Connecticut
Wheeling, West Virginia
Steubenville, Ohio
Weirton, West Virginia
Mingo Junction, Ohio
Steubenville, Ohio
Sumpter Township, Michigan
Tampa, Florida
Texarkana, Texas
Texarkana, Arkansas
The Dalles, Oregon
Ticonderoga, New York
Shoreman, Vermont
Toledo, Ohio
Trenton, New Jersey
Tallulah, Louisiana
Vicksburg, Mississippi
Volunteer Arsenal, Tennessee
Volunteer Arsenal, Tennessee
Volunteer Arsenal, Tennessee
Volunteer Arsenal, Tennessee
Washington, D.C.
Cheverly, Maryland
Alexandria, Virginia
Washington, D.C.
Pawcatuck, Connecticut
Westerly, Rhode Island
Wichita Falls, Texas
Wilmington, Delaware
Claymont, Delaware
Chester, Pennsylvania
Penns Grove, New Jersey
Winona, Minnesota
Station
classification3
R
R
R
I
I
C
C
C
C
R
C
C
R
R
C
R
R
R
R
C
C
C
R
R
I
R
Rural
R
R
C
R
R
Rural
I
C
C
C
I
I
I
I
R
Rural
C
C
R
C
R
C
R
C
I
I
Station
type
1
1
1
1
1
3
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
4
3
1
1
1
1
1
1
1
1
1
3
3
3
3
2
1
1
1
1
1
1
INTERSTATE SURVEILLANCE PROJECT
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Table 1-1 (continued). ISP NETWORK AREAS
Area name
Winona (continued)
Youngstown
Yuma
Station
number
226
15
38
92
Station location
La Cross, Wisconsin
Sharon, Pennsylvania
Youngstown, Ohio
Yuma, Arizona
Station
classification3
R
I
C
R
Station
type
1
1
1
1
C = commercial; I = industrial; R = residential.
Introduction
-------
2. DESCRIPTION OF MONITORING UNIT
Norman Huey and Maurice George vich
The monitoring unit, or "effects package," has a stand and a body to which the various components* can be
attached or mounted for exposure, as shown in the photograph of Figure 21. The unit, designed for ease of
shipping and emplacement, was constructed of aluminum for strength, minimal weight (about 45 pounds), and
ease of maintenance. The static unit requires no power and little servicing.
Figure 2-1. "Effects network" sampler.
2.1 THE BASIC STRUCTURE
The body has an exterior frontal dimension of 18 inches (in.) by 18 in. by 17 in., which slopes to 13-1/2 in. at
the rear. The sandwich-type roof measures 30 in. by 30 in. Each vertical wall contains a lightproof framed
aluminum louvre measuring 12 in. by 12 in. by 1 in., which permits the free movement of air through the unit
but does not permit the passage of light. In the front, a door consisting of a lightproof louvre is hinged at the top
with keepers in open and shut positions; it permits access to the interior and still maintains the light-tight
characteristic of a closed door.
Components such as the rubber strip and fabric panels, which may be affected by light, are exposed inside the
body. Other components are attached to the stand or the roof: one zinc and two steel panels are attached at the
rear of the roof to permit a 30-degree(°) angle of exposure to the south. Another component is an insulated silver
*Although designed for the specific components used in this project, other components may be added with
minor modification.
-------
plate mounted under the roof eave. A horizontal aluminum slide holder, 4 to 6 inches from the roof surface
permits attachments of two nylon panels and petri dishes. Two aluminum extension arms, attached to the sides ot
the body and to the roof, extend to a height of 62 in. for attachment of one dustfall bucket holder on one arm
and one lead candle shelter and one sticky-paper jar on the other arm.
The base of the leg assembly measures 32 in. by 32 in. at the bottom and 18 in. by 18 in. at the top, and has
been designed so that the body can be rotated in between the two legs to conserve shipping space. Symmetric
mounting brackets are fastened at the top of the assembly so that the body can be attached in an inverted
position when the unit is shipped or can be rotated into the on-line position. To prevent penetration into the
supporting surface, the entire bottom edge of the base has been framed with an aluminum angle. All parts are
welded.
2.2 MONITOR COMPONENTS
The components of the monitoring unit have a two-fold purpose: to indicate potentials for individual air
pollutants, and to indicate the material damage caused by air pollution in general.
To screen individual pollutant potentials in an area, dustfall buckets are used to collect settleable particulates,
and "sticky" or adhesive impaction paper and dyed fabrics No. 2 and No. 6 are used to collect windblown par-
ticulates. The zinc panel, steel panels, sulfation plate, and sulfation candle are used to indicate sulfur dioxide pol-
lution, and a silver plate is used to indicate the presence of hydrogen sulfide. Nylon panels are used in detecting
the presence of severe acidic particulate pollution. Auto exhaust or nitrogen dioxide is detected by the use of
dyed fabric No. 3. Rubber panels and dyed fabrics No. 4 and No. 5 are used as indicators of photochemical pol-
lutants. The remaining four dyed fabrics, No. 1, No. 7, No. 8, and No. 9, used as detectors because they react dif-
ferently from the other five listed,* were exposed to ambient air so that data might be collected about their
reactions to known pollutants.
Material damage caused by air pollution in general can be measured by use of the same components. The degree
of damage to zinc and steel panels can be evaluated to establish metal corrosion rates. Damage to the nine dyed
fabric combinations can be used to assess dye destruction of colorfast fabrics; and damage to nylon, silver, and
rubber panels may be indicative of deterioration of these three products. Sulfur dioxide traces on the sulfation
candle and plate can be measured to assess potential building damage in S02 environments, and the degree of
general soiling of materials can be gauged by dustfall buckets and "sticky" paper. In Table 2-1 are tabulated the
exposure times, units of measure, and effects demonstrated by these components.
Table 2-1. EFFECTS OF POLLUTANTS ON MONITOR COMPONENTS
Component
Steel or zinc panel
Dyed fabric panel
Nylon panel
Silver plate
Rubber strip
Sulfation candle
Sulfation plate
Dustfall bucket
"Sticky" paper
Exposure
time, days
90; 365
90
30; 90
30
7
30
30
30
7
Effects of pollutants
Metal corrosion by sulfur dioxide, in microns/year (/n/yr)
Color fading by ozone or nitrogen dioxide, in National
Bureau of Standards (NBS) units
Materials deterioration by acid aerosols, in fiber breaks/
exposure time
Tarnishing by hydrogen sulfide, as loss of reflectance
Cracking by ozone, as depth in millimeters/year (mm/yr)
Accumulation of sulfur dioxide, in milligrams of sul-
fur trioxide/100 square centimeters-day (mg S03/
100cm2-day)
Accumulation of sulfur dioxide, in micrograms of
suifur dioxide/square centimeter-day (//gSO2/cm2 day)
Soiling by settleable particulates, in grams/square meter-
month (g/m2-mo)
Soiling by windblown particulates, in square millimeters/
week (mm2/wk)
*0f the five listed, No. 2 and No. 4 were used in 1967 only, and No. 5 and No. 6 in 1968 only.
10 Description of Monitoring Unit
-------
2.3 MEASURING METAL CORROSION
Although metallic corrosion is considered to be caused by weathering, atmospheric pollution greatly accelerates
these corrosion rates. In early studies on the rusting of iron and steel, Vernon established that rusting was scarcely
a problem in highly purified air, even at relative humidities up to 99 percent.1 When a trace of sulfur dioxide was
introduced into the air, however, corrosion would initiate at about 50 percent relative humidity and increase
markedly at approximately 80 percent. Solid particles of ammonium sulfate or charcoal in the presence of sulfur
dioxide also greatly increased the rates.
The annual cost of the deterioration of metals amounts to many billions of dollars. Most estimates are
conservative since it is rarely possible to put a price tag on the man-hours required to combat corrosion or on the
loss of function of the damaged material.
2.3.1 Zinc Panel
Before exposure, the new 4 in. by 3 in. zinc panels were scrubbed twice in warm detergent solution, rinsed with
water, and then rinsed with acetone. The panels were then air dried, weighed to the nearest 10 milligrams, and
placed in a kraft envelope for transport to the exposure location.
At the exposure site, a single zinc panel of 99.94 percent zinc, 600 ppm lead, 50 ppm cadmium, and 40 ppm
iron was mounted on the rear edge of the roof between plastic insulators at an angle of 30° from the horizontal,
facing south, for exposure from January to December.
After exposure, the panel was scrubbed and rinsed in water, immersed for 5 minutes in a warm (160° to 180°F)
solution of ammonium chloride, and then scrubbed and re-rinsed with water. If corrosion still remained on the
panel, it was dipped for 20 seconds in a hot (200° to 212°F), 5 percent chromic acid solution, re-rinsed with
water, and then rinsed in acetone to facilitate air drying before weighing.
Corrosion is measured as weight loss. Because weight loss depends on the size and shape of the panel, it is more
meaningful to report results as units of depth of penetration of the corrosion. The weight loss expressed in grams
is converted to penetration depth in microns per year, or ju/yr. The measurement is corrected for time exposure
expressed in days.
3,300 (wt in grams)
ju/yr =
days exposed
Annual corrosion rates vary from 0.1 to 17 ju/yr.
2.3.2 Steel Panel
Before exposure, steel panels were scrubbed with detergent, rinsed several times with water, rinsed with
acetone, and were then air dried. They were then dipped in concentrated hydrochloric acid to remove rust spots,
rinsed several times with water, rinsed with acetone, and air dried over a hot plate. Finally, each panel was
weighed to the nearest milligram and placed in a kraft envelope for shipment to the exposure site.
Two steel panels measuring 4 in. by 3 in. were exposed. The low-carbon (200 to 400 ppm), low-copper (300 to
500 ppm) steel panels were mounted on the rear edge of the roof between plastic insulators at an angle of 30°
from the horizontal, facing south. One panel remained exposed for the entire year, beginning in January; the
other was replaced every 3 months.
After exposure, the plates were wire-brushed to remove loose rust, rinsed in an inhibited acid solution* to
remove the rest of the corrosion products, and rinsed with water, then acetone, before air drying over a hot plate.
Each cleaned panel was then weighed to the nearest 10 milligrams.
The corrosion penetration rate in microns per year is calculated from the following relationship:
3,300 (wt in grams)
At/yr =
days exposed
The annual corrosion rates varied from 0 to 108 M/yr; the 3-month rate, from 0 to 186 ju/yr.
2.4 EVALUATING COLOR FADING
The effects of atmospheric contaminants on dyed fabrics have been studied by the American Association of
Textile Chemists and Colorists (AATCC) since 1938.2 The extent of fading damage or dye destruction has been
*Prepared by adding 2 grams of organic cationic inhibitor (Rodine 213) and 50 grams of stannous chloride to
1,000 grams of concentrated hydrochloric acid.
INTERSTATE SURVEILLANCE PROJECT 11
-------
reported by LaBarthe,3 who showed that the fading of dyes by atmospheric contaminants can constitute a
significant percentage of the complaints received by department stores and dry cleaners.
Results of a study carried out by the Public Health Service in cooperation with AATCC indicated that dyed
fabrics can be grouped according to patterns of fading as related to certain air pollutants. More than 50 percent of
the fading-prone, fabric-dye combinations* had correlation coefficients greater than 0.7 with the standard
nitrogen oxide fabric.
2.4.1 Causes
Some of the causes of fading are strong sunlight, washing, heat, and humidity. Recently, ozone and oxides of
nitrogen have been suspected as causes of dye fading; in fact, AATCC has developed two standard dyed fabrics,
one sensitive to nitrogen oxide and the other to ozone.
2.4.2 Dyed-Fabric Panels
In this project nine different 2 in. by 1 in. dyed-fabric panels were exposed for 3-month periods, January
through March, April through June, July through September, and October through December. In Table 2-2 are
described the dye-fabric combinations. In 1967, only the first four dyed fabrics were exposed; in 1968, only
seven were exposed. Fabrics No. 2 and No. 4 were not exposed.
Table 2-2. DYE-FABRIC COMBINATIONS FOR NINE COMPONENTS
Fabric number Description of dyed fabric
1 | Cotton muslin dyed with 1% C.I. Direct Blue 86
2 Orion dyed with 0.25% Disperse Blue 3
3
4
Acetate dyed with Disperse Blue 3
Acetate dyed with Disperse Blue 27, Disperse Red 35, and
Disperse Yellow 37
Triacetate dyed with same three as No. 4
Bleached muslin with no dye added
7 I Wool flannel with Acid Red 151
i
8 Cotton muslin dyed with 0.45% Disperse Blue 3
9 Nylon taffeta dyed with 1% Disperse Blue 3
Samples of each of the nine dyed fabrics were glued to 2-3/4-inch-square pieces of cardboard with 2-inch
cutouts by using silicone contact adhesive. Before exposure, the appearance of each fabric was measured with a
color-difference meter containing tristimulus filter-photocell combinations. After exposure, each was measured
again with the meter. The differences in the "before" and "after" appearances were calculated and reported in
NBS color-difference units (AE).
Dye-fabric combination No. 1 faded, but the cause of fading is not fully understood. Combination No. 2 is
stable; color changes were probably the result of soiling.
Dye-fabric combination No. 3 is an AATCC standard control fabric known to be sensitive to oxides of
nitrogen.4 Combinations No. 4 and No. 5, also standard control fabrics, are both known to be sensitive to
ozone.4
Dye-fabric No. 6 is a bleached muslin fabric with no dye added; it was used as an indicator of soiling.
Combinations No. 7, No. 8, and No. 9 did not indicate specific effects caused by individual pollutants.
2.5 MEASURING MATERIAL DETERIORATION
Nylon, silver, and rubber panels were used as indicators of materials deterioration caused by air pollutants.
*Hopefully, future studies will indicate that relatively few dyed-fabric combinations will be needed to estimate
damages to materials.
1 2 Description of Monitoring Unit
-------
2.5.1 Nylon Panel
The life of nylon goods, particularly women's hose, is often shortened by air pollution.5 Incidences of severe
nylon hose deterioration have been reported in the United States, Canada, England, and aboard some ships. The
primary cause has been called "acidic soot." The probable destructive agents are hot particles in smoke, drops of
sulfuric acid in soot, phenolic particles and aldehydes from internal combustion engines, and acid aerosols,
nitrogen oxides, and solvent vapors from other sources.
A sample of good quality (15 denier) nylon hose is stretched and glued between the halves of a standard
Polaroid slide mount. The 3-1/4 in. by 2-3/8 in. panel has an exposure area of 7.7 square inches. One of these
panels is exposed on the top of the roof in a horizontal position for 30 days and another for 90 days.
After exposure, the samples are examined for breaks in the fiber. An image of the samples can be projected
onto a screen and examined macroscopically or, with the aid of a low-power objective, microscopically. Monthly
values ranged from 0 to 100 defects.
2.5.2 Silver Plate
In ancient times, when the atmosphere was relatively free of sulfur compounds, silver remained bright and
untarnished for long periods of time. Air pollutants, especially hydrogen sulfide and sulfur dioxide, affect not
only the aesthetic but also the electrical properties of silver.6 For example, increased resistance across closed
silver contacts tarnished by sulfides may freeze the contacts or cause transmission failure.
Although it is impossible to calculate precisely the economic loss in maintenance costs due to deterioration of
electrical contacts, it must be considerable. Gold and other precious metals are often substituted for other
contact materials because they are less reactive than silver and possibly because of silver's deterioration by air
pollutants. At present, the annual cost of gold used for electrical contacts is estimated at $15 million;6 if silver
were used, the annual savings for the nation would be about $14.8 million.
Before exposure, the reflectance of each silver panel was measured with a photovolt reflection meter (Model
610 with a 610-D search unit)* and with a green tristimulus filter.
At the exposure site, a single silverplated place plate (William A. Rogers, No. 1120, 6 in. in diameter) was
exposed monthly in an upside down position under the overhanging roof of the shelter to protect the silver film
from particulates and precipitation.
After exposure, the reflectance was again measured, and the reflectance loss was calculated as the percent loss
per month of exposure. The precision of the laboratory techniquef was within 2 percent of the recorded
reflection loss.
2.5.3 Rubber Panel
Atmospheric oxygen, especially ozone, can cause rubber cracking. In 1946, the attack of natural rubber by
light-energizing oxygen and ozone was reported by Crabtree and Kemp.7'8 Unsaturated elastomers** are
attacked by ozone at the double bond in the carbon-carbon chain;9 if the chain under stress breaks, it leaves its
neighbors under additional strain. Synthetic rubber, such as unsaturated butadiene-styrene or butadiene-
acrylonitrile, is affected in the same manner; neoprene, although unsaturated, resists ozone attack, presumably
because of the chlorine bond adjacent to the double bond.
The measurement of rubber cracking rate furnishes information on the relative life of rubber products in
different areas. This measurement has been accepted by some investigators as an indirect measurement of ozone.
The most significant variables affecting the degree of cracking are the rubber formulation, the amount of stress
placed on the rubber, and the amount of ozone contacted by the rubber. By controlling the first two variables,
the relative amount of ozone can be approximated.
Natural rubber, ozone-sensitive test slabs measuring 9 in. by 9 in. by 1/6 in., are cut into 8-millimeter-wide
strips. (The length is not critical; about 2 in. is sufficient.) These strips are exposed for 1 week under a constant
stress caused by the gravitational pull of a 360-gram lead weight. The rubber strip is exposed inside the body of
the "effects package" by clamping one end to the top of the sampler and the other to the lead weight.
After exposure, the rubber strips are prepared for microscopic examination. A small corner is cut off to identify
the edge of the strip, and the strip is cut in half lengthwise. The half with the corner cut is placed under a SOX
lens so that the freshly cut edge may be observed. The cut strip is stretched slightly to make crack depth easier to
*Mention of a specific company or product does not constitute endorsement by the Environmental Protection
Agency.
fTo our knowledge, no studies have been conducted that provide an objective estimate of precision of
replicate samples.
**Saturated polymers are highly resistant to ozone attack.
INTERSTATE SURVEILLANCE PROJECT 13
-------
measure; only the cracks within 1/2 in. from the center of the strip length are measured since the cracking of the
strip may be inconsistent at the ends where the strips are fastened. The depths of nine consecutive cracks are
measured by using precalibrated eyepieces in the microscope; the average of the nine is calculated and reported.
According to Vega and Seymour,10 if the exposure is 7 days, the average ozone concentration can be
approximated in parts per hundred million by multiplying the average crack depth in millimeters by six. Replicate
exposures of rubber strips to the atmosphere have suggested that rubber cracking exhibits a coefficient of
variation of about 10 percent; this imolies that approximately 68 percent of replicate observations should be
within ±10 percent of the average.
2.6 MEASURING SULFATION
The measurement of sulfation was introduced in the early 1930's in England to give a direct index of the
activity of sulfur impurities, such as in the attack of polluted air upon building stone, exposed metal, and the like.
Sulfur oxides in the presence of moisture convert the calcium and magnesium carbonates of stone into soluble
sulfates, which are either washed away or dried to form hydra ted crystals that are of greater volume than those in
solution. This formation causes increased internal pressures within the material, and results in the formation of
encrustations and friable scales that produce blistering, flaking, and exfoliation.
Sulfur oxides are also given much credit for increased metal corrosion rates. It has been reported that railway
tracks wear more rapidly in industrial than in nonindustrial atmospheres.11 Leathers used in book-binding have
been found to accumulate up to nearly 5 percent sulfate; paper discolors and becomes brittle, and artwork such
as paintings undergoes color changes as well as canvas deterioration.
2.6.1 Sulfation Candle
A sulfation candle was exposed monthly. The candle surface-prepared by coating it with lead dioxide, which is
sensitive to sulfur dioxide-is a cylinder 10 centimeters in height with a total reactive area of 100 square
centimeters. When atmospheric sulfur dioxide comes in contact with the lead dioxide on the candle, it is
converted to lead sulfate.
After exposure, the lead sulfate is removed by adding sodium carbonate to the surface. Then the amount of
soluble sodium sulfate formed is measured turbidemetrically as barium sulfate.12
The amount of sulfur dioxide collected per 100 square centimeters of surface area per daymeasured as barium
sulfatewas converted to and reported as the equivalent amount of sulfur trioxide (mg of SOs/100 cm2-day).
Past measurements by similar methods yielded an empirical relationship between sulfation and sulfur dioxide
concentrations: sulfur dioxide in ppm can be estimated from milligrams of sulfur trioxide per square centimeter
per day by multiplying the sulfation rate by 0.03 5 ;13 the daily measurements ranged from 0.1 to 15 milligrams.
Above 0.5 milligram, precision of about ±10 percent can be expected, but below 0.5 milligram, the error may be
as much as 0.2 milligram.
2.6.2 Sulfation Plate
In 1968 a comparison study of the plate and sulfation candle methods of detection was made.13 In the plate
method, sulfation was measured monthly by a sulfation plate exposed upside down in a small petri dish. Both the
plate and the candle use the same materials and have identical reactions, but the plate has a much smaller surface,
only 18 square centimeters compared to the 100 of the candle. Furthermore, the plate is more stable, easier to
fabricate and analyze, and less expensive to expose than the candle.
The amount of sulfate, determined the same way as for the candle, was converted to and reported as the
amount of sulfur dioxide per square centimeter per day Oug of SO2/cm2-day). The factor used to convert the
micrograms of sulfur dioxide to milligrams of sulfur trioxide is 0.125.
2.7 EVALUATING SOILING
The soiling effects of particulates are usually noticed by the public. Buildings, automobiles, outer clothing
garments, windows, curtains, drapes, walls, floors, and rugs are among the many things soiled by both settleable
and windblown particulates.
2.7.1 Dustfall Bucket
Particulates settled out of the atmosphere by gravity14 are collected monthly in an open-top Tupperware
5-quart canister with an area of 0.029 square meter. The particles collected are generally greater than 20 microns
in diameter and, because of their size, settle relatively close to their points of origin.
After exposure of the canister, its contents are transferred to a glass beaker, the water is evaporated, and the
remaining solids are weighed. The results are reported as the equivalent weight of material (in grams) that settled
over a surface of 1 square meter during the month. The factor for converting grams per square meter to tons per
square mile per month is 2.86.
14 Description of Monitoring Unit
-------
Values ranged from 0 to 100 grams per square meter per month. An investigation by Nader15 indicated that
replicate dust-bucket collections exhibit a coefficient of variation of approximately 15 percent.
2.7.2 Sticky Paper
Particulates in the size range of 20 to 100 microns are collected on sticky paper.16 These particulates, which
indicate the soiling potential of the atmosphere, are carried by wind from a source of pollution and captured by
adhesive-coated paper mounted on a cylinder perpendicular to the earth's surface.
The sampler is called an adhesive impactor or sticky-paper sampler. It is prepared by wrapping a 2-in. strip of
contact paper (Fassons Pli-a-Print, R-135) around a jar (diameter, 2-3/4 in.; height, 3-1/4 in.) with the adhesive
side out. Only the north direction is marked on the paper.
After an exposure of 7 days, the sampler is sprayed with clear enamel to fix the particulates and to eliminate
entrapment of others.
In the laboratory, the particulate loading (particles/mm2) at eight points, representing eight directions of the
compass, is estimated by comparing the sample to a series of standardsphotographs of samples previously
counted microscopically and ranging from 15 to 100 particles per square millimeter.
Results of extensive sampling17 using sticky paper indicate that replicate samples may exhibit a variation of 20
percent.
INTERSTATE SURVEILLANCE PROJECT 15
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3. DISCUSSION OF PROJECT DATA
James Cavender
Although the primary purpose of the project is to provide data for internal use, data tabulations of the sampling
results for all components at all stations are routinely published at 6-month intervals and are distributed to
cooperating agencies for use in their air pollution control programs.
3.1 FREQUENCY DISTRIBUTIONS FOR ALL COMPONENTS
These data are summarized for 1967 and 1968 in Table B-l of Appendix B. The table gives the smallest,
largest, and average value (arithmetic mean) for each year. An annual average value is recorded only for those
stations that were on-line for at least 6 months. For the zinc and steel components, exposed for a year, only the
annual results are shown.
Frequency distributions of the 1967 and 1968 results are given in Table 31. These include all values from all
components at all stations and show the percent of values that were less than the values specified in the table; for
example, 10 percent of all zinc results for the entire network in 1967 were less than 0.43 micron per year.
Little difference was detected between the 1967 and 1968 distributions. For 1968, dyed fabrics No. 1 and No.
3 results were consistently larger than for 1967, but differences were small; sticky-paper results were also slightly
larger for 1968 than for 1967. In contrast, results of the rubber panel, silver plate, and sulfation candle were
slightly less in 1968 than in 1967; again, the differences were not significant.
Some of the distribution differences can be explained by the fact that the number of stations and
corresponding measurements were not the same for 1967 and 1968. Six new components were added to the
monitoring unit in 1968; these were dyed fabrics No. 5, No. 6, No. 7, No. 8, No. 9, and a sulfation plate. Two
components, however, dyed fabrics No. 2 and No. 4, were exposed in 1967 but not in 1968. Thus, the 1968 unit
had 18 components compared to 14 in 1967.
3.1.1 Background Stations
Frequency distributions of all background stations computed for 1968 are presented in Table 32. In the
majority of cases, significantly lower values were recorded at the background sites. The most notable exceptions
are the results for dyed fabrics No. 5, No. 8, and the rubber panel; the consistently higher backgrounds,
particularly for No. 5 and the rubber panel, may be partially explained by the fact that both components are
sensitive to ozone.
Other studies have indicated that ozone exists, in limited amounts, even in so-called clean areas, and that the
background level may account for the rubber cracking and color fading at these sites. The fact that lesser amounts
of cracking and fading occurred in more polluted areas may be due to decreased ozone levelsnot necessarily a
decreased number of oxidantscaused by chemical reactions of active ozone with other pollutants, or it may be
due to substantial decreases in the amount of sunlight, which is needed for the formation of ozone.
3.1.2 Stations by Classification
Stations were grouped according to four area classificationsindustrial, commercial, residential, or rural
(Section 1.3.1). Frequency distributions of the 1968 annual averages were computed for each of the four.
The classifications cover a range of pollution impacts. An industrial area would normally be expected to have
multiple pollution sources and highest overall levels of emissions. Similarly, commercial classification implies a
business area with considerable activity and probably a few pollutant sources. Residential and rural are considered
areas with lowest emission levels.
Frequency distributions for the four classifications are presented in Tables 33, 3-4, 3-5, and 3-6. The
highest levels were generally found at the industrial sites. Commercial and residential sites generally had lower
levels, and rural sites, the lowest. These results, expected because of the population density and emission levels of
the site locations, lend validity to the monitoring unit's capability for pinpointing pollution levels of varying
magnitudes.
There were a few exceptions to the general trend-highest levels at industrial sites and lowest at rural sites. The
most notable was the effect upon the rubber panel and upon fabric No. 5; both showed a complete reversal of the
normal pattern. Distribution of these two components revealed highest results at rural sites and succeedingly
lower values at residential, commercial, and industrial sites. Reasons for these apparent inconsistencies were
brought out in the preceding subsection.
In summary, based on the frequency distribution by station classification, the components were selective to the
degree that pollutants or their effects were detected at levels of varying magnitudes.
17
-------
Table 3-1. FREQUENCY DISTRIBUTION OF MEASUREMENTS
1967-1968
Component
Zinc (/u/yr)
Annual steel (/u/yr)
Quarterly steel (jU/yr)
Dye fabric No. 1
(Color difference, NBS units)
Dye fabric No. 2
(Color difference, NBS units)
Dye fabric No. 3
(Color difference, NBS units)
Dye fabric No. 4
(Color difference, NBS units)
Dye fabric No. 5
(Color difference, NBS units)
Dye fabric No. 6
(Color difference, NBS units)
Dye fabric No. 7
(Color difference, NBS units)
Dye fabric No. 8
(Color difference, NBS units)
Dye fabric No. 9
(Color difference, NBS units)
Silver tarnishing
(% decrease, reflectance)
Sulfation candle
(mg SO3/100 cm2-day)
Sulfation plate
(MgSO2/cm2-day)a
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
No. of
samples
124
216
129
204
558
874
574
839
569
583
822
518
796
830
834
826
844
1,749
2,835
1,758
2,787
2,587
Minimum
0.16
0.10
0
0
0
0
6.2
8.7
0.5
6.2
6.8
6.5
2.3
2.2
1.8
1.4
4.2
1
0
0
0
0
% of values less than stated value
10
0.43
0.64
4
6
2
3
11.7
15.3
1.0
12.3
16.2
10.5
6.1
5.0
3.4
4.3
12.1
24
22
0
0
0
25
0.79
1.05
18
16
17
11
13.7
17.1
1.4
15.3
19.7
12.8
8.0
6.4
5.3
5.8
15.5
40
36
0.2
0
0
50
1.42
1.87
31
29
45
38
15.8
19.0
2.4
19.6
23.8
17.2
11.0
8.3
7.9
7.8
20.3
58
55
0.5
0.4
0.4
75
2.94
3.53
44
42
68
67
17.6
21.0
3.9
26.6
31.0
22.6
13.4
10.5
11.0
9.9
26.1
76
75
1.2
1.0
0.9
90
4.36
4.93
58
53
87
89
19.2
22.8
6.0
35.1
41.1
26.3
15.2
12.8
14.1
13.2
30.7
86
85
2.2
1.7
1.8
Maximum
17.00
15.40
107
88
185
194
27.1
29.3
17.9
53.2
62.8
37.4
22.6
25.5
24.2
14.1
43.0
100
100
10.7
8.7
9.0
I
o'
9
O
S?
-------
g Dustfall
J^ (g/m2-mo)
vi Monthly nylon
^ (Total No. of defects)
tfl Quarterly nylon
g (Total No. of defects)
<; Rubber deterioration
Zj
S (Average crack depth, LI)
F*
C Sticky paper
2 (particles/mm2)
o
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1,735
2,807
1,728
2,849
540
921
7,202
1 1 ,349
1,785
2,550
0.1
0.1
0
0
0
0
0
0
0
1
1.6
1.5
0
0
0
0
0
0
5
6
2.6
2.6
0
0
0
0
0
0
12
15
4.6
4.4
0
0
0
0
58
48
24
29
7.8
6.9
0
0
1
1
172
144
40
46
12.2
10.8
2
2
7
5
260
220
57
63
101.1
161.2
185
223
235
255
663
683
91
93
m
J§ aSulfation plate measurements are reported in /ug S02/cm2-day. These values have been converted to mg SO3/100 cm -day for comparison with sulfa-
O tion candle values (mg S03/100 cm2-day = .125 jug S02/cm2-day).
w
n
H
-------
Table 3-2. FREQUENCY DISTRIBUTION OF BACKGROUND STATIONS
1968
Component
No. of
samples
Minimum
Annual zinc (n/yr) j 50 0.5
Annual steel (jU/yr)
Quarterly steel (jU/yr)
Fabric No. 1 (color difference, NBS units)
Fabric No. 3 (color difference, NBS units)
10 13
39 0
53 9.7
37
8.4
Fabric No. 5 (color difference, NBS units) 39 7.9
Fabric No. 6 (color difference, NBS units) 56
Fabric No. 7 (color difference, NBS units) 56
Fabric No. 8 (color difference, NBS units)
53
Fabric No. 9 (color difference, NBS units) 56
Quarterly nylon (total No. of defects) 43
Monthly nylon (total No. of defects) | 137
Silver tarnish (% decrease, reflectance) 136
Dustfall (g/m2-mo) 133
Sulfation candle (mg S03/100 cm2-day) 133
Sulfation plate (jugS02 /cm2 -day)3 124
Rubber deterioration (average crack depth, ju) 515
Sticky paper (particles/mm2) 1 13
3.0
1.9
1.4
4.2
% of values less than stated value
10
1.0
20
6
14.0
13.6
8.9
3.9
2.7
5.0
8.5
0 I 0
0 I 0
4
17
0.2 i 0.9
0 0
o ; o
0 ; 0
1 2
25
1.0
24
10
15.8
16.5
11.0
4.7
4.9
7.0
13.9
0
0
27
1.4
i 0
0
0
3
50
1.2
30
29
18.0
20.5
12.8
6.1
6.5
9.3
17.9
0
0
35
2.2
0.1
0.1
104
7
75
1.4
41
47
19.9
22.6
16.2
8.2
8.5
14.1
25.9
0
0
45
3.2
0.3
0.2
217
16
90
3.0
47
65
20.9
29.2
18.6
10.6
11.1
18.2
29.3
3
0
55
4.2
0.5
0.4
315
31
Maximum
3.4
55
114
23.6
36.8
22.6
12.9
16.7
23.4
35.2
16
2
69
13.6
1.0
0.9
612
46
8
I
§'
"8
1
ft
O
aSulfation plate measurements are reported in p.g SO2/cm2-day. These values have been converted to mg SO3/100 cm2-day for comparison with sulfa-
tion candle values (mg S03/100 cm2-day = .125^9 SO2/cm2-day).
-------
M
»
CA
S
w
Table 3-3. FREQUENCY DISTRIBUTION OF INDUSTRIAL STATIONS
1968
Component
Annual zinc (ju/yr)
Annual steel (/i/yr)
Quarterly steel (/i/yr)
Fabric No. 1 (color difference, NBS units)
Fabric No. 3 (color difference, NBS units)
Fabric No. 5 (color difference, NBS units)
Fabric No. 6 (color difference, NBS units)
Fabric No. 7 (color difference, NBS units)
Fabric No. 8 (color difference, NBS units)
Fabric No. 9 (color difference, NBS units)
Quarterly nylon (total No. of defects)
Monthly nylon (total No. of defects)
Silver tarnish (% decrease, reflectance)
Dustfall (g/m2-mo)
Sulfation candle (mg SO3/100 cm2 -day)
Sulfation plate (fig S02/cm2-day)a
Rubber deterioration (average crack depth, /u)
Sticky paper (particles/mm2)
No. of
samples
32
29
38
37
37
36
37
37
38
38
38
38
38
38
38
36
35
34
Minimum
0.9
12
10
16.3
11.6
5.8
5.0
3.3
4.4
16.3
0
0
12
3.0
0
0
25
5
% of values less than stated values
10
1.0
21
18
17.4
18.6
7.2
6.2
6.2
6.0
17.6
0
0
42
4.0
0.1
25
1.6
27
35
18.5
23.7
8.8
7.3
7.3
6.6
21.1
0
0
53
4.7
0.2
0.1 0.2
40 52
50 | 75 90
2.4
40
58
20.0
27.8
10.3
9.2
9.2
8.3
23.1
0
0
64
6.6
0.7
0.5
64
4.5 6.0
54 61
77 ; 104
22.2 : 23.2
37.0 ! 41.5
11.2 i 11.6
11.4 i 12.2
11.0 j 13.8
10.0 ' 11.5
24.6 26.2
4 ! 24
1 i 8
74 j 87
9.0 t 12.5
1.5 I 2.9
1.2 ; 2.0
84 99
8 26 37 48 64
Maximum
15.4
88
139
26.6
57.6
14.2
17.4
14.8
14.9
33.6
99
34
90
25.9
4.7
5.0
201
80
w
w
o
aSulfation plate measurements are reported in jug S02/cm2-day. These values have been converted to mg SO3/100 cm2-day for comparison with sulfa-
tion candle values (mg SO3/100 cm2-day = .125/jg S02/cm2-day).
-------
Table 3-4. FREQUENCY DISTRIBUTION OF COMMERCIAL STATIONS
1968
Component
Annual zinc (/u/yr)
Annual steel (ju/yr)
Quarterly steel (/u/yr)
Fabric No. 1 (color difference, NBS units)
Fabric No. 3 (color difference, NBS units)
Fabric No. 5 (color difference, NBS units)
Fabric No. 6 (color difference, NBS units)
Fabric No. 7 (color difference, NBS units)
Fabric No. 8 (color difference, NBS units)
Fabric No. 9 (color difference, NBS units)
Quarterly nylon (total No. of defects)
Monthly nylon (total No. of defects)
Silver tarnish (% decrease, reflectance)
Dustfall (g/m2-mo)
Sulfation candle (mg S03/100 cm2 -day)
Sulfation plate (/zg SO2/cm2-day)a
Rubber deterioration (average crack depth, /i)
Sticky paper (particles/mm2)
No. of
samples
64
55
67
68
65
67
66
66
67
67
70
71
70
67
70
67
60
64
Minimum
0.2
1
1
12.7
17.8
4.0
6.4
4.7
5.2
10.3
0
0
9
2.0
0
0
9
14
% of values less than stated value
10
0.6
4
4
17.3
18.7
7.3
7.0
6.6
6.0
17.2
0
0
25
3.0
0
0
44
20
25
0.9
8
13
18.2
21.7
9.1
7.8
7.4
6.6
19.5
0
0
41
3.6
0.1
0.1
57
24
50
2.1
25
35
19.3
25.4
10.5
9.5
8.7
7.6
21.7
0
0
54
5.1
0.4
0.4
74
34
75
3.7
38
70
20.5
36.6
11.6
10.8
10.7
8.9
23.8
2
0
69
7.6
1.2
1.0
96
47
90
5.2
50
85
21.4
42.5
13.1
12.5
12.0
13.4
25.9
8
2
77
9.5
1.6
1.5
116
57
Maximum
7.1
53
142
24.0
53.8
15.1
19.6
18.2
15.3
37.4
59
20
89
27.8
3.3
3.6
194
74
B
o
9
O
w»
I
n
a
aSulfation plate measurements are reported in /ug SO2/cm2-day. These values have been converted to mg S03/100 cm2-day for comparison with sulfa-
tion candle values (mgSO3/100 cm2-day = .125^9 S02/cm2-day).
-------
S
n
w
Table 3-5. FREQUENCY DISTRIBUTION OF RESIDENTIAL STATIONS
1968
Component
Annual zinc (ju/yr)
Annual steel (/u/yr)
Quarterly steel (/J/yr)
Fabric No. 1 (color difference, NBS units)
Fabric No. 3 (color difference, NBS units)
Fabric No. 5 (color difference, NBS units)
Fabric No. 6 (color difference, NBS units)
Fabric No. 7 (color difference, NBS units)
Fabric No. 8 (color difference, NBS units)
Fabric No. 9 (color difference, NBS units)
Quarterly nylon (total No. of defects)
Monthly nylon (total No. of defects)
Silver tarnish (% decrease, reflectance)
Dustfall (g/m2-mo)
Sulfation candle (mg SO3/100 cm2 -day)
Sulfation plate (/ug S02/cm2-day)a
Rubber deterioration (average crack depth, n)
Sticky paper (particles/mm2)
No. of
samples
103
104
124
116
117
114
116
117
117
120
123
122
124
123
123
120
111
116
Minimum
0.1
0
0.5
13.5
10.6
5.6
3.4
3.9
4.5
9.5
0
0
5
0.8
0
0
21
4
% of values less than stated value
10
0.4
4
2
16.5
15.6
8.4
5.6
5.1
5.7
12.8
0
0
22
2.1
0
0
51
10
25
0.9
13
3
17.7
18.7
9.6
6.5
6.2
6.6
17.8
0
0
35
2.7
0.1
0.1
62
17
50
1.6
26
28
18.6
22.6
10.9
7.8
7.7
7.6
20.1
0
0
53
4.5
0.2
0.2
80
28
75
2.8
41
64
20.1
26.4
12.4
9.9
9.6
9.1
23.6
1
0
68
6.0
0.9
0.8
105
37
90
4.6
52
84
21.6
34.8
13.8
11.4
11.7
11.1
25.6
2
1
81
8.2
1.5
1.4
129
52
Maximum
15.1
67
120
24.6
50.2
15.8
14.4
14.8
15.8
30.0
30
12
93
29.0
2.5
2.2
210
75
Sulfation plate measurements are reported in ;ug SO2/cm2-day. These values have been converted to mg SO3/100 cm2-day for comparison with sulfa-
tion candle values (mg S03/100 cm2-day = .125jug SO2/cm2-day).
-------
Table 3-6. FREQUENCY DISTRIBUTION OF RURAL STATIONS
1968
Component
Annual zinc (/z/yr)
Annual steel (,u/yr)
Quarterly steel (/x/y)
Fabric No. 1 (color difference, NBS units)
Fabric No. 3 (color difference, NBS units)
Fabric No. 5 (color difference, NBS units)
Fabric No. 6 (color difference, NBS units)
Fabric No. 7 (color difference, NBS units)
Fabric No. 8 (color difference, NBS units)
Fabric No. 9 (color difference, NBS units)
Quarterly nylon (total No. of defects)
Monthly nylon (total No. of defects)
Silver tarnish (% decrease, reflectance)
Dustfall (g/m2-mo)
Sulfation candle (mg SO3/100 cm2-day)
Sulfation plate (jug S02/cm2-day)a
Rubber deterioration (average crack depth, ;u)
Sticky paper (particles/mm2)
No. of
samples
16
16
21
19
19
20
19
19
17
19
22
21
22
20
22
20
Minimum
0.2
3
1
11.5
9.0
8.8
3.9
3.9
4.9
7.7
0
0
6
0.2
0
0
17 0
17 ' 2
% of values less than stated value
10
0.5
13
2
13.0
9.2
9.6
4.0
4.3
6.0
9.4
0
0
25
0.8
0
0
59
3
25 '
0.9
26
16
16.8
17.5
11.9
4.7
5.8
6.7
15.7
0
0
30
1.7
0.1
0.1
84
3
50
1.3
31
31
18.2
20.6
13.1
6.8
7.1
9.7
19.0
0
0
41
2.3
0.1
0.1
110
9
75
2.5
40
44
18.9
25.3
13.9
8.2
7.6
12.0
21.8
1
0
50
2.8
0.3
0.4
126
23
90
3.8
41
65
20.0
28.2
14.7
8.9
9.4
13.6
25.3
4
0
60
3.7
0.7
0.6
196
26
Maximum
4.2
55
132
22.9
41.4
17.8
10.2
10.7
17.9
28.8
14
1
72
23.2
1.1
0.8
316
32
S
%
I
o"
&
o
(U
BSulfation plate measurements are reported in fj.g SO2/cm2-day. These values have been converted to mg S03/100 cm2-day for comparison with sulfa-
tion candle values (mg SO3/100 cm2-day = .125;ug S02/cm2-day).
s?
-------
3.2 SEASONAL EFFECTS ON COMPONENTS
Monthly and quarterly frequency distributions were computed to investigate seasonal effects on individual
components. Seasonal effects were noted for several components.
Deterioration of rubber and fabrics No. 4 and No. 5 increased during the two warmer seasons, April through
June and July through September. Figure 3- 1 is a plot of the distribution of the 50th percentile of the rubber
deterioration results by month; plots are not shown for fabrics No. 4 and No. 5 because they follow the same
pattern but give less information since they had quarterly instead of monthly exposures. All three components
measure ozone, and because the warmer period of the year is when ozone levels are highest, the seasonal trend
was expected. The bimodal curve with the maximum in April is not a typical oxidant curve and is, therefore,
somewhat confusing; the explanation probably is that the seasonal pattern is not the same for ozone as it is for
oxidants.
140
JAN FEB MAR APR MAY JUN JUL AU G SEP OCT NOV DEC
MOnTH
Figure 3-1. Distribution of rubber deterioration results by month, 1968,
Lead peroxide candles and plates showed highest levels during the colder months. Maximum levels were
recorded in January. This is to be expected, since the instruments are sensitive to sulfur dioxide, which is
normally emitted in larger amounts during the colder months because more fuel is burned in heating. A plot of
the sulfation candle results is in Figure 3-2; lead plate results are not given because they are identical to the
candle results.
Dustfall and sticky-paper values, highest during March and April, may be related to higher windspeeds in the
spring that increase movement of natural and man-made particulates. Figure 3-3 presents the distribution of
dustfall by month. Sticky paper followed the same pattern and was therefore not presented.
Two additional components, dye fabrics No. 8 and No. 9, recorded highest levels from July to September.
These seasonal effects, which are not as readily explainable as the others, are discussed in more detail in the
statistical evaluation section. Figures 34 and 3-5 are plots of these distributions.
Seasonal effects were not noted for components not discussed here.
3.3 ANNUAL AVERAGES FOR ALL COMPONENTS
The annual average for each component was calculated for each station for 1967 and 1968. It was arbitrarily
decided that to be included, a station had to have been on-line for at least half of the year. The annual averages
INTERSTATE SURVEILLANCE PROJECT
25
-------
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
Figure 3-2. Distribution of sulfation results by month, 1968.
JAN FEB MAR APR MAY JUN JUL AUG SEP OCT NOV DEC
3.5
26
Figure 3-3. Distribution of dustfall results by month, 1968.
Discussion of Project Data
-------
JAN-MAR
APR.JUN
QUARTER
JUL-SEP
OCF-DEC
Figure 3-4. Distribution of fabric No. 8 results by quarter, 1968.
27.5
12.5
OCT-DEC
Figure 3-5. Distribution of fabric No. 9 results by quarter, 1968.
INTERSTATE SURVEILLANCE PROJECT
27
-------
Table 3-7. EFFECTS NETWORK ANNUAL AVERAGES CUMULATIVE FREQUENCY DISTRIBUTION
1967-1968
Component
Annual zinc (/u/yr)
Annual steel (jit/yr)
Quarterly steel (M/yr)
^Fabric No. 1
(Color difference, NBS units)
Fabric No. 2
(Color difference NBS units)
Fabric No. 3
(Color difference, NBS units)
Fabric No. 4
(Color difference, NBS units)
(Color difference, NBS units)
Fahrir l\ln R
(Color difference, NBS units)
Fabric No. 7
(Color difference, NBS units)
FaKrio Mn R
(Color difference, NBS units)
(Color difference, NBS units)
Silver tarnish
(% decrease, reflectance)
Sulfation candle
(mg SO3/100 cm2 -day)
Sulfation plate
(^g SO 2 /cm2 -day)
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QKS
1967
1968
1967
1968
1QfJ7
1968
1QK7
1968
1967
1968
1QR7
1968
1QR7
1968
1967
1968
1967
1968
1967
1968
No. of
samples
124
216
129
204
152
250
152
240
151
152
238
141
237
238
239
239
244
145
254
145
253
243
Minimum
0.2
0.1
0
0
1
1
10.1
11.5
1.0
9.3
9.0
10.4
4.0
3.4
3.3
4.4
7.7
4
5
0
0
0
% of values less than stated value
10
0.4
0.6
4
6
4
4
12.5
16.7
1.1
13.4
16.8
13.4
7.9
5.8
5.3
5.8
15.9
31
26
0
0
0
25
0.8
1.0
18
16
18
13
14.2
17.7
1.7
16.0
20.0
15.0
9.3
6.9
6.7
6.6
18.2
42
38
0.1
0.1
0.1
50
1.4
1.9
31
29
44
38
15.5
18.9
2.8
19.7
24.1
17.9
10.7
8.4
....
8.1
7.8
21.1
58
55
0.4
0.4
0.4
75
2.9
3.5
44
42
67
69
17.2
20.6
3.8
25.8
31.3
21.1
12.3
10.4
10.2
9.4
23.9
71
70
1.3
1.1
1.0
90
4.4
4.9
58
53
84
89
18.6
21.9
5.5
33.0
40.2
24.2
13.7
12.0
12.2
11.8
26.1
79
81
1.9
1.7
1.6
Maximum
17.0
15.4
107
88
144
142
25.4
26.6
14.4
50.7
57.6
28.7
17.8
19.6
18.2
17.9
37.4
91
93
5.2
4.7
5.0
5
o
o
a
S?
-------
VI
H
W
I
«
5§
o
Dustfall
(g/m2-mo)
Monthly nylon
(total No. of defects)
rv * i i
(total No. of defects)
0 UU -1
Hubber deterioration
(average crack depth, ju)
(particles/mm2)
1967
1968
1967
1968
iyt>/
1968
1967
1968
1 QR ~7
i yt>/
1968
140
248
145
252
~ " "
253
_ _ _
233
231
0.1
0.2
0
0
_ _ _ _
0
- ...
0
2
2.0
2.2
0
0
- _ - _
0
... -
41
11
3.1
3.1
0
0
0
_ _ _ _
56
21
4.9
4.6
0
0
0.2
_ _ . _
75
30
7.8
6.9
0.2
0.3
1.4
100
42
12.0
9.6
2.6
1.4
4.5
128
54
22.2
29.0
41.8
34.2
99.0
316
80
Sulfation plate measurements are reported in /ug SO2/cm2-day. These values have been converted to mg S03/100 cm2-day for comparison with sulfa-
tion candle values (mg S03/100 cm2-day = .125jug S02/cm2-day).
VO
-------
A
=r=s-
i
i
I
i
i
'i_
w ^-^-j
"""i
H r
I
01
"v>
I
c"°>-oi..i5 ]
FREQUENCY DISTRIBUTION
BY QUARTILE
0 - 25%
26 - 50 %
QS1 - 75%
A?6 - 100%
Figure 3-6. Geographic distribution of lead candle sulfation measurements, 1968.
-------
were then tabulated and the cumulative frequency distributions derived (Table 3-7). Results in this table are not
directly comparable with Table 31, in which the frequency distributions were derived from individual measure-
ments. Table 37 can be used as a yardstick in describing the severity of a pollution problem for an individual
station by relating its annual average to that for all stations.
Geographic distribution of the 1968 annual sulfation results is presented in Figure 36. This distribution was
obtained by determining the position of an individual station's annual average on the frequency distribution of
annual averages for all stations (Table 37).
Stations within an area were grouped together and plotted as one value.
Highest levels were generally found in the Northeastern and North-Central sections of the United States. These
areas have relatively high population densities and are generally more industrialized than other sections; coal is a
fairly common source of heat in both areas. Although other sections of the United States show an occasional area
with high levels, they do not have the same consistent, overall pattern of high sulfation concentrations.
A strong relationship between sulfation levels and presence of sulfur dioxide has been shown. This relationship
will be discussed in detail in the statistical evaluation section of this report. From these latter data, it becomes
apparent that the Northeastern and North-Central sections of the United States have potentially greater overall
sulfur dioxide problems than do other areas.
3.4 SUMMARY
Frequency distributions of data for all components of the surveillance network revealed the following: Results
for 1967 and 1968 were not significantly different. Levels at the background stations were significantly lower for
components other than those related to an oxidant or ozone effect. Seasonal effects were noted for rubber
panels, for dyed fabrics No. 4, No. 5, No. 8, and No. 9, for the sulfation candle and plate, and for dustfall buckets
and sticky paper. Frequency distributions of annual averages permitted comparisons of stations and/or areas as to
relative severity of pollution problems.
INTERSTATE SURVEILLANCE PROJECT 31
-------
4. AREA EVALUATION
Norman Huey and George Jutze
A primary objective of the Interstate Surveillance Project is to provide data on the overall impact of pollution
on an area as well as the type of pollutant that appears to be a major problem within the area.
4.1 FREQUENCY DISTRIBUTION OF AREAS
Appendix C presents a tabulation of data from the 14 indicators that, in the authors' judgment, yielded data
relative to specific pollutants. All reported measurements were accumulated for the year 1968, and each
component's data were ordered into quartiles of the annual frequency distribution. These quartiles were labeled
from 1 to 3, starting with the initial quartile, 0 to 25 percent, and going to the third quartile, 51 to 75 percent.
The fourth, or upper, quartile was split into two groups: data in the 76 to 90 percent range were labeled 4, while
the top decile, 91 to 100 percent, of all data was designated as 5. Thus, the order of each digit represents the
specific quartile, or maximum decile, range in which that site may be found in the frequency distribution of
annual data from ah1 reporting sites as follows:
1, for the first quartile, 0 to 25%.
2, for the second quartile, 26 to 50%.
3, for the third quartile, 51 to 75%.
4, for the fourth quartile: up to the maximum decile, 76 to 90%.
5, for the fourth quartile: within the maximum decile, 91 to 100%.
In other words, each number label, 1 to 5, represents the specific quartile or decile of the frequency distribution
and determines the location of the annual average for a specific station as it relates to the distribution of annual
averages for all stations.
4.1.1 Assigning Pollutant Code Numbers (PCN's)
To further summarize the data, the component rankings, 1 through 5, were grouped according to six major
pollutant types, and each station was assigned a six-digit pollutant code number (PCN). When more than one
component was used to measure a single pollutant (for example, dustfall, sticky paper, and fabric No. 6, were
used to measure particulates), the component rankings were averaged to obtain a single PCN digit for that
pollutant. Thus, each station was assigned a six-digit PCN to relate the components to the six major pollutants, as
illustrated in Table 4 1.
Table 4-1. COMPONENT-POLLUTANT RELATIONSHIP SHOWN BY
POLLUTANT CODE NUMBER
PCN digit
First digit
Second digit
Third digit
Fourth digit
Fifth digit
Sixth digit
Pollutant indicated
Particulates
Sulfur oxides
Hydrogen sulfide
Acid aerosols
Oxides of nitrogen
Oxidation potential
Component
Dustfall bucket
Sticky paper
Fabrics No. 2a and No. 6
Lead candle and plate
Steel panel, 3 mo; 1 yr
Zinc panel
Silver plate
Nylon panel, 1 mo; 3 mo
Fabric No. 3
Rubber panel
Fabrics No. 4a and No. 5
aUsed in 1967 but not in 1968.
The PCN's listed in Table 42 are for the one station within each area that has the greatest number of large
digits for the six pollutant types. For example, Station No. 52, Chicago, has a PCN of 555442, which indicates
33
-------
that in 1968 the data from this site ranked in the upper decile for participates, sulfur oxides, and hydrogen
sulfide; in the fourth quartile for acid aerosols and nitrogen oxides; and in the second quartile for the oxidation
potential.
Table 4-2. MAXIMUM POLLUTANT CODE NUMBER TABULATION, BY AREA
34
Area name
Albany, New York
Anchorage, Alaska
Ann Arbor, Michigan
Augusta, Georgia
Austin, Texas
Bastrop, Louisiana
Beaumont, Texas
Bellingham, Washington
Binghamton, New York
Blacksburg, Virginia
Block Island, Rhode Island
Bluefield, Virginia
Bogalusa, Louisiana
Boston, Massachusetts
Boulder City, Nevada
Bridgeport, Connecticut
Bristol, Tennessee
Broward County, Florida
Brownwood, Texas
Buffalo, New York
Burlington, Vermont
Calexico, California
Cannon Mountain, New Hampshire
Carville, Louisiana
Chapel Hill, North Carolina
Charlotte, North Carolina
Chattanooga, Tennessee
Cheyenne, Wyoming
Chicago, Illinois
Cincinnati, Ohio
Clarkston, Washington
Columbus, Georgia
Columbus, Ohio
Con/all is, Oregon
Custer, South Dakota
Davenport, Iowa
Del Rio, Texas
Denver, Colorado
Detroit, Michigan
Douglas, Arizona
Dubuque, Iowa
Dulce, New Mexico
Duluth, Minnesota
Eagle Pass, Texas
East Helena, Montana
Easton, Pennsylvania
El Paso, Texas
Evansville, Indiana
Station
number3
30
246
224
131
120
208
122
77
25
195
189
159
214
192
89
243
148
135
125
24
181
93
175
219
237
33
140
252
52
6
74
143
37
69
244
59
115
27
34
102
227
100
50
116
254
14
103
161
Pollutant code number
1967
442541
123224
113214
235234
222212
331242
211214
32122-
222312
211214
555451
41322-
123234
322422
555432
422242
325211
112322
223222
111212
421221
311214
411232
444242
321213
111213
222222
31321-
243432
323413
1968
343441
211231
222222
224322
113244
425232
234235
222221
232232
222225
232235
432234
235224
443541
211215
443552
332233
222312
312214
555341
132434
414225
221213
113414
121324
223334
333332
21121-
555442
433341
325212
112223
232231
111312
111414
421222
211213
411232
544342
431214
421212
111214
33321 1
414215
44141?
T^ 1 1 1 £.
343432
243414
343234
Area Evaluation
-------
Table 4-2 (continued). MAXIMUM POLLUTANT CODE NUMBER TABULATION, BY AREA
Area name
Fairbanks, Alaska
Fall River, Massachusetts
Fargo, North Dakota
Farmington, New Mexico
Fernandina Beach, Florida
Fort Smith, Arkansas
Frankfort, Kentucky
Frannie, Wyoming
Gainesville, Florida
Grand Forks, North Dakota
Guaynabo, Puerto Rico
Hartford, Connecticut
Hennepin, Illinois
Hilo, Hawaii
Honolulu, Hawaii
Huntington, West Virginia
International Falls, Minnesota
Kansas City, Missouri
Kenosha, Wisconsin
Keyser, West Virginia
Laredo, Texas
Lawrence, Massachusetts
Lebanon, New Hampshire
Leesburg, Virginia
Longview, Washington
Los Angeles, California
Louisville, Kentucky
Luray, Virginia
Madawaska, Maine
McAllen, Texas
Memphis, Tennessee
Milbank, South Dakota
Mobile, Alabama
Montauk Point, New York
Natchez, Mississippi
Needles, California
New Orleans, Louisiana
New York, New York
Nogales, Arizona
Oakland, California
Omaha, Nebraska
Oneca, Florida
Overland Park, Kansas
Owensboro, Kentucky
Parkersburg, West Virginia
Pensacola, Florida
Petersburg, New York
Philadelphia, Pennsylvania
Portland, Oregon
Portsmouth, New Hampshire
Providence, Rhode Island
Rooseveltown, New York
St. Joseph, Missouri
Station
number3
247
191
198
99
134
211
106
253
233
197
255
184
56
242
241
66
251
48
51
152
117
177
180
114
80
239
39
172
193
118
147
245
146
144
215
91
218
5
101
95
202
130
88
43
63
145
29
11
83
174
190
194
204
Pollutant code number
1967
31221-
145244
122224
231214
535422
322422
342324
213213
233212
432442
325224
32243-
211214
544551
311213
222231
111414
432223
234232
323435
445552
123212
1968
211221
442353
321221
221214
245325
111315
122224
2252
224224
321212
4435-4
442551
221214
111212
221322
545331
545211
332322
332232
335222
414212
332242
232431
122424
234211
223255
443332
121213
5512
314224
312233
211211
324323
242245
114224
211314
425232
444551
311223
222241
311212
122324
111212
343332
234332
233334
121314
445552
133412
353443
343452
234334
311212
INTERSTATE SURVEILLANCE PROJECT
35
-------
Table 4-2 (continued). MAXIMUM POLLUTANT CODE NUMBER TABULATION, BY AREA
Area name
St. Louis, Missouri
San Ysidro, California
Sarnia, Ontario, Canada
Sault St. Marie, Michigan
Savannah, Georgia
Seattle, Washington
Sherman, Texas
Shreveport, Louisiana
Sioux City, Iowa
Sioux Falls, South Dakota
South Tahoe, California
Spokane, Washington
Spray, North Carolina
Springfield, Massachusetts
Steubenville, Ohio
Sumpter Township, Michigan
Tampa, Florida
Texarkana, Texas
The Dalles, Oregon
Ticonderoga, New York
Toledo, Ohio
Trenton, New Jersey
Vicksburg, Mississippi
Volunteer Arsenal, Tennessee
Washington, D.C.
Westerly, Rhode Island
Wichita Falls, Texas
Wilmington, Delaware
Winona, Minnesota
Youngstown, Ohio
Yuma, Arizona
Station
number3
45
94
166
223
132
78
127
212
201
199
97
71
157
182
62
164
68
129
79
178
36
18
217
107
7
185
126
8
225
38
92
Pollutant code number
1967
445532
121235
344434
231532
111224
111212
221412
445342
245424
214224
121212
434232
443541
343543
333451
211214
445542
545242
211214
1968
455531
212235
344222
333222
334233
232431
311224
2124-4
411212
311312
121214
3113-1
122234
442552
555341
232225
335234
213324
211212
135414
444232
343343
412222
333542
433352
242344
111214
444542
221412
545241
211215
aStation selected is the one exhibiting greatest number of maximum values within its region.
It should be emphasized that the use of a single station to depict all stations in an area has some known
limitations, but these limitations are not considered critical since the primary emphasis of the ISP is to detect
problems within an area, not to determine "area-wide" problems.
An area is considered to have a problem with a type of pollutant if the PCN has digits of either 4 or 5 (upper
quartile). For example, in Table 4-2, Chicago with a PCN of 555442 is considered to have three "severe
problems" and two that are "problems."
Table 4-3, based on data in Table 4-2, lists 74 of 144 areas that had at least one pollution problem in 1968.
The relative severity of the problems is designated by either an "X" or an "S", which are equivalent to "4" and
"5", respectively. The table shows the wide range of pollution problems that can be detected and characterized
by the monitoring techniques used in the ISP. The table also provides a first-order estimation of the magnitude of
the pollution impact within an area; this estimation helps in the pollution control activities conducted by all
levels of regulatory agencies.
4.1.2 Defining Pollutant Problems
The ISP provides information from which action priorities could be established; the surveillance network thus
can serve as a "screening" mechanism. Areas with multiple or specific problems, when compared to all other areas
surveyed, should rank in or near the maximum quartile, and those with lesser problems, in or near the minimum
36 Area Evaluation
-------
Table 4-3. NUMBER AND RELATIVE SEVERITY OF AIR POLLUTION PROBLEMS
IN ISP AREAS
Area name
Albany, New York
Augusta, Georgia
Austin, Texas
Bastrop, Louisiana
Beaumont, Texas
Bluefield, West Virginia
Bogalusa, Louisiana
Boston, Massachusetts
Bridgeport, Connecticut
Buffalo, New York
Calexico, California
Carville, Louisiana
Chicago, Illinois
Cincinnati, Ohio
Clarkston, Washington
Custer, South Dakota
Davenport, Iowa
Denver, Colorado
Detroit, Michigan
Douglas, Arizona
Dubuque, Iowa
Eagle Pass, Texas
East Helena, Montana
Easton, Pennsylvania
El Paso, Texas
Evansville, Indiana
Fall River, Massachusetts
Fernandina Beach, Florida
Frannie, Wyoming
Gainesville, Florida
Guaynabo, Puerto Rico
Hartford, Connecticut
Huntington, West Virginia
International Falls, Minnesota
Keyser, West Virginia
Laredo, Texas
Lawrence, Massachusetts
Lebanon, New Hampshire
Leesburg, Virginia
Longview, Washington
Los Angeles, California
Louisville, Kentucky
Madawaska, Maine
McAllen, Texas
Mobile, Alabama
Montauk Point, New York
Natchez, Mississippi
New Orleans, Louisiana
New York, New York
Owensboro, Kentucky
Pollutant severity index (1968 data only)3
Partic-
ulate
X
X
X
X
S
X
S
X
X
X
S
X
X
X
X
X
X
X
S
S
X
X
S
X
X
S°x
X
X
X
S
S
X
X
X
X
X
X
X
X
X
X
X
X
S
X
X
H2S
X
S
X
S
S
X
S
S
X
X
S
S
X
S
S
S
X
X
X
X
X
S
X
Acid
aerosol
X
S
S
X
X
X
X
X
X
S
S
X
X
S
N°v
A
X
X
X
S
X
X
X
X
S
S
X
S
X
S
INTERSTATE SURVEILLANCE PROJECT
37
-------
Table 4-3 (continued). NUMBER AND RELATIVE SEVERITY OF AIR POLLUTION
PROBLEMS IN ISP AREAS
Area name
Parkersburg, West Virginia
Philadelphia, Pennsylvania
Portland, Oregon
Portsmouth, New Hampshire
Providence, Rhode Island
Rooseveltown, New York
St. Louis, Missouri
Sarnia, Ontario, Canada
Savannah, Georgia
Seattle, Washington
Shreveport, Louisiana
Sioux City, Iowa
Springfield, Massachusetts
Steubenville, Ohio
Tampa, Florida
Toledo, Ohio
Trenton, New Jersey
Vicksburg, Mississippi
Volunteer Arsenal, Tennessee
Washington, D.C.
Westerly, Rhode Island
Wilmington, Delaware
Winona, Minnesota
Youngstown, Ohio
Pollutant severity index (1968 data only)3
Partic-
ulate
S
X
X
X
S
X
X
X
X
S
S°x
X
S
X
S
X
X
S
X
X
X
X
X
H2S
X
S
X
S
X
X
S
S
X
X
S
Acid
aerosol
X
X
X
X
S
X
X
S
S
S
X
NOX
S
X
S
S
X
X
X
S
X
X
X
aS = Results in maximum frequency distribution decile or top 10 percent.
X = Results in maximum frequency distribution quartile or top 25 percent.
quartile. (By the nature of the network design, clear-cut definitions could not be expected for the mid-portion or
"gray area" of the data.) It seems reasonable, however, to expect that areas ranking in the top decile or quartile
of data measurement would have a more severe problem than areas in the lower half.
In an effort to study this hypothesis, the ISP data were related either to emission density estimates of
particulates and sulfur oxides (if this information was available) or to the presence of emission sources in a
specific area.* These comparisons are discussed in succeeding subsections.
4.2 EVALUATION OF PARTICULATE PROBLEMS
Among the sources of particulates are fuel combustion, various manufacturing and processing operations (e.g.,
production of steel, cement, primary metals, pulp and paper, and petroleum products), and open burning and
incineration of refuse. Estimates of particulate densities for 62 urban areas (all that were available) were obtained
from the Division of Air Quality and Emissions, APCO, to evaluate the'network used by the ISP to define
particulate problems.
These emission densities are listed in order of magnitude in Tables 4-4 and 4-5. Twenty-two of these
areas had emissions of 15 tons per square mile per year or greater. In these 22 areas, the corresponding PCN
*It must be emphasized that no attempt was made to predict emission density or to quantify specific sources'
impacts An attempt was made to demonstrate the utility of this unsophisticated and easily implemented network
to provide basic data that can assist in supporting decisions.
38
Area Evaluation
-------
index pinpointed the particulate problems-one exception was Easton, Pennsylvania. In fact, ISP components also
showed the same five areas highest in particulate emissions. Although these comparisons do not prove that
selected ISP components measure particulate levels, they lend support to the belief that these components are
good indicators of relative levels of particulate pollution.
Table 4-4. RELATIONSHIP OF PARTICULATE EMISSION DENSITY TO ISP PARTICULATE PROBLEM
SEVERITY INDEX
1968
Particulate
emission density,
tons/mi2-yr
155
120
115
110
90
90
90
70
65
50
45
40
40
Area name
Detroit, Mich.
Steubenville, Ohio
Youngstown, Ohio
Buffalo, New York
Chicago, Illinois
Easton, Pa.
Fall River, Mass.
Bridgeport, Conn.
Louisville, Ky.
New York, New York
Philadelphia, Pa.
Cincinnati, Ohio
St. Louis, Mo.
Relative
severity
index
S
S
S
S
S
X
X
X
X
S
X
X
Particulate
emission density,
tons/mi2 -yr
35
30
30
30
25
25
25
25
15
10
10
10
10
Area name
Huntington, W.Va.
Wilmington, Del.
Toledo, Ohio
Denver, Colo.
Boston, Mass.
Springfield, Mass.
Washington, D.C.
New Orleans, La.
Laredo, Texas
Hartford, Conn.
Davenport, Iowa
Dubuque, Iowa
Sioux City, Iowa
Relative
severity
index
S
X
X
X
X
X
X
X
X
X
X
X
X
4.3 EVALUATION OF SULFUR OXIDE PROBLEMS
The sulfur oxides that are of concern as atmospheric pollutants are sulfur dioxide, sulfur trioxide, and their
acids and acidic salts. When fossil fuels such as coal and petroleum are burned, their sulfur content is converted to
sulfur dioxide and, to a lesser degree, sulfur trioxide. Because fossil fuels are burned abundantly to heat buildings
and to generate electric power, pollution from the oxides of sulfur is widespread, especially in cities. Petroleum
refineries, smelting plants, coke-processing plants, sulfuric acid manufacturing plants, coal refuse banks, and
refuse-burning activities are also major sources of sulfurous pollution.
Table 46 relates sulfur oxide emission densities to the respective sulfur oxide PCN index for the areas defined,
and Table 4-7 presents emission density estimates for other ISP areas. Again the PCN index corresponded well to
the emission density estimates; all areas, except two, with a sulfur oxide density of 50 tons per square mile per
year or more exhibited an index of "S" or "X." In the case of the two apparent discrepancies, Cincinnati and
Beaumont, approximately 70 percent of the sulfur dioxide estimated for Cincinnati was attributed to two large,
high-level emission sources at least 25 miles from the nearest sampler, and for Beaumont, the samplers are at least
the same distance from the source. Thus, as in the case of the particulate PCN index, the sulfur oxide PCN index
is a good indicator of the presence of sulfur oxides.
4.4 EVALUATION OF HYDROGEN SULFIDE PROBLEMS
The known point sources of ambient hydrogen sulfide include paper mills, oil refineries, steel mills, oil and gas
wells, and anaerobic lagoons. In kraft paper mills, the recovery furnaces are the largest contributors; in steel mills,
the contributors are the associated coking operations. Hydrogen sulfide sources can be relatively easily identified
by the presence of their unique odor.
The hydrogen sulfide severity index, unlike the ISP indexes for particulates and sulfur oxides, cannot be
compared with hydrogen sulfide emission data or air quality information because neither type of data is available.
Accordingly, only the known types of hydrogen sulfide sources within each area in which high indexes were
found can be compared with silver-plate data.
INTERSTATE SURVEILLANCE PROJECT 39
-------
Table 4-5. OTHER ISP AREAS FOR WHICH PARTICULATE EMISSION DENSITY ESTIMATES
ARE AVAILABLE3
Particulate
emission density,
tons/mi2-yr
Area name
Particulate
emission density,
tons/mi2 -yr
Area name
10
9
9
g
8
8
8
8
8
7
7
6
6
5
5
4
4
3
Chattanooga, Tennessee
Evansville, Indiana
Kansas City, Missouri
Providence, Rhode Island
Memphis, Tennessee
Mobile, Alabama
Los Angeles, California
Columbus, Ohio
Trenton, New Jersey
Kenosha, Wisconsin
Honolulu, Hawaii
Duluth, Minnesota
Omaha, Nebraska
Beaumont, Texas
Savannah, Georgia
Lawrence, Massachusetts
El Paso, Texas
St. Joseph, Missouri
3
2
2
2
2
2
1
1
Ann Arbor, Michigan
Augusta, Georgia
Binghampton, New York
Charlotte, North Carolina
Pensacola, Florida
Seattle, Washington
Portland, Oregon
Spokane, Washington
Columbus, Georgia
Fargo, North Dakota
Fort Smith, Arkansas
Boulder City, Nevada
San Diego, California
Shreveport, Louisiana
Sioux Falls, South Dakota
Texarkana, Texas
Wichita Falls, Texas
Austin, Texas
aThe particulate PCN digit for all of these areas was 3 or less (i.e., there were no values in the upper quartile or
top decile.
Table 48 lists the areas ranking in the upper quartile according to their annual average silver-tarnishing rate
(percent loss of reflectance per month) and their relative severity index. The table also lists the types of point
sources known to exist in the areas.
Nearly all areas rated in the upper quartile and/or upper decile contain industries that are known to emit
hydrogen sulfide. Frannie, Wyoming, in the upper decile and coded with an "S", is the only area that does not
Table 4-6. RELATIONSHIP OF SULFUR OXIDES EMISSION DENSITY TO ISP SULFUR
OXIDES PROBLEM SEVERITY INDEX
SOX emission
density,
tons/mi2 -yr
475
460
440
400
360
340
270
245
210
200
150
145
140
135
Area name
Fall River, Mass.
Steubenville, Ohio
Bridgeport, Conn.
Chicago, Illinois
New York, New York
Louisville, Kentucky
Boston, Mass.
Detroit, Michigan
St. Louis, Missouri
Philadelphia, Pa.
Cincinnati, Ohio
Beaumont, Texas
Toledo, Ohio
Youngstown, Ohio
Relative
severity
index
X
S
X
S
X
X
X
X
S
X
X
X
SOX emission
density,
tons/mi2 -yr
125
125
120
110
110
110
80
75
70
65
65
55
50
Area name
Springfield, Mass.
Hartford, Conn.
El Paso, Texas
Easton, Pa.
Buffalo, New York
Wilmington, Dela.
Albany, New York
Sarnia, Ontario
Trenton, New Jersey
Evansville, Indiana
Owensboro, Kentucky
Providence, R.I.
Huntington, W. Va.
Relative
severity
index
X
X
X
X
S
X
X
X
X
X
X
X *
X
40
Area Evaluation
-------
Table 4-7. OTHER ISP AREAS FOR WHICH SULFUR OXIDES EMISSION DENSITY
ESTIMATES ARE AVAILABLE8
SOX emission
density
tons/mi2-yr
45
45
45
45
40
40
30
30
30
30
25
25
20
15
15
15
10
10
Area name
Augusta, Georgia
Chattanooga, Tennessee
Savannah, Georgia
Washington, D.C.
Memphis, Tennessee
Columbus, Ohio
Kansas City, Missouri
Kenosha, Wisconsin
Omaha, Nebraska
Los Angeles, California
Dubuque, Iowa
Mobile, Alabama
Lawrence, Massachusetts
Pensacola, Florida
St. Joseph, Missouri
Seattle, Washington
Binghampton, New York
Ann Arbor, Michigan
SOX emission
density
tons/mi2 -yr
10
Area name
Denver, Colorado
Charlotte, North Carolina
Columbus, Georgia
Duluth, Minnesota
Fargo, North Dakota
Forth Smith, Arkansas
Laredo, Texas
Boulder City, Nevada
Portland, Oregon
San Ysidro, California
Shreveport, Louisiana
Sioux City, Iowa
Sioux Falls, South Dakota
Spokane, Washington
Texarkana, Texas
Wichita Falls, Texas
Austin, Texas
Honolulu, Hawaii
aThe sulfur dioxide PCN digit for all of these areas was 3 or less (i.e., there were no values in the upper quartile or
top decile).
contain either paper mills, steel mills, or oil refineries. This location was sampled because of the known hydrogen
sulfide pollution problem associated with the nearby sour-gas oil fields.
Three areas labeled "X" are not explained by the three types of industry in Table 48. The Calexico,
California, area is thought to be influenced by hydrogen sulfide emissions from a sewage treatment operation
across the Mexican border. The Gainesville, Florida, area is influenced by a large water cooling tower 200 yards
away, which aerates ground water of high hydrogen sulfide content. The Parkersburg, West Virginia, arealike
Gainesvilleappeared to be an oddity, but it was learned from local people that this area has an odor problem
caused by various sulfur compounds, including hydrogen sulfide, emitted by a small nearby chicken-processing
operation.
Although the comparisons in this subsection are not based on emission density data, it is felt that the detailed
sources of hydrogen sulfide listed in Table 4-8 provide sufficient information to be able to state with reasonable
confidence that the silver plate is a good indicator of the presence of hydrogen sulfide. This is not to imply that
levels of hydrogen sulfide can be estimated from these data; rather, the data can be used to determine hydrogen
sulfide presence.
4.5 EVALUATION OF ACID AEROSOL PROBLEMS
The only available measurements of acid aerosols at present are those made using nylon panels. Acid aerosols in
large quantities are known to be emitted at times from sulfuric acid plants; aerosols are also emitted from large
combustion sources, especially oil-fired sources, but to a somewhat lesser degree.
Nylon panels detect only excessive conditions that generally are associated with strong local point sources.
Table 4-9 lists the ISP areas that exhibited severe acid aerosol problems. With the limited knowledge available, it
is not possible to explain why, in terms of industry type, each area is in the upper decile. Credibility of the
measurements, however, can be obtained from limited knowledge about some of the areas.
For example, St. Louis is known to have a severe acid aerosol problem; reportedly, an acid plant in East St.
Louis occasionally emits large quantities that cause severe damage to women's nylon hose. New York is
INTERSTATE SURVEILLANCE PROJECT
41
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Table 4-8. RELATIONSHIP OF SOURCES TO ISP HYDROGEN SULFIDE PROBLEM
SEVERITY INDEX
Suspected sources
Paper
mill
*
*
*
*
*
#
#
*
*
#
*
*
Steel
mill
*
#
#
*
#
#
#
#
X-
*
#
Oil
refinery
*
*
*
*
#
#
*
#
#
#
*
*
*
Area name
Chicago, Illinois
Huntington, West Virginia
Fernandina Beach, Florida
Keyser, West Virginia
Buffalo, New York
Clarkston, Washington
St. Louis, Missouri
Steubenville, Ohio
International Falls, Minnesota
New Orleans, Louisiana
Tampa, Florida
Frannie, Wyoming
Bogalusa, Louisiana
Ticonderoga, New York
Youngstown, Ohio
Philadelphia, Pennsylvania
New York, New York
Longview, Washington
McAllen, Texas
Gainesville, Florida
Bastrop, Louisiana
Beaumont, Texas
Natchez, Mississippi
Eagle Pass, Texas
Parkersburg, West Virginia
Savannah, Georgia
Wilmington, Delaware
Augusta, Georgia
Detroit, Michigan
Toledo, Ohio
Mobile, Alabama
Sarnia, Ontario, Canada
Calexico, California
Relative
severity index
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
S
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Tarnishing
rate
90
90
89
89
88
87
87
86
86
85
84
82
82
82
81
81
80
78
78
78
77
77
76
75
74
74
74
73
72
71
71
70
70
42
Table 4-9. RELATIONSHIP OF SOURCES TO ISP ACID AEROSOL
PROBLEM SEVERITY INDEX
Suspected source
Acid production
Undefined
Acid production
Acid production/TNT
Undefined
Acid production
Undefined
Acid production
Undefined
Area name
Wilmington
Bridgeport
St. Louis
Volunteer Arsenal
Springfield
Boston
Hartford
New York
Guaynabo
Severity
index
S
S
s
s
s
s
s
c
S
Area Evaluation
-------
influenced by a large, sporadically uncontrolled acid plant near Elizabeth, New Jersey; the nylon deterioration
rate averaged 12 and 30 defects, respectively, for 1967 and 1968, and high-volume samples from this area,
analyzed for total acid and for sulfate content, revealed high results. The Volunteer Arsenal area, which is rated in
the top decile in Table 4-9, contained four stations. Values for these four stations are shown in Table 4-10, all
of these values fall in the upper decile. These excessive deterioration rates indicate the existence of a severe
problem due to a TNT production plant known to emit acid aerosols; it has been reported that teachers in
adjacent schools cannot wear nylon hose because the aerosol causes excessive nylon damage.
Table 4-10. NYLON DETERIORATION IN VOLUNTEER
ARSENAL AREA
107
108
109
110
Number of fiber breaks/period
30 days
8
28
34
6
90 days
24
79
99
21
4.6 EVALUATION OF NITROGEN OXIDE PROBLEMS
Oxides of nitrogen are emitted from many man-made sources such as automobiles, industrial and domestic
combustion equipment, electric arc processes, and chemical reactions. In Los Angeles it is estimated that 50 to 60
percent of the emissions come from the automobile; half of the remaining percentage is from point-source power
plants; the remainder is from the small-to-medium area sources such as domestic and commercial gas appliances,
metallurgical furnaces, nonmetallurgical kilns, stationary internal combustion engines, chemical processes, steel
furnaces, glass furnaces, and incinerators.
Accordingly, the highest levels of nitrogen oxides are expected in large metropolitan areas, especially those with
poor ventilation, near specific point sources.
Table 411 lists all ISP areas with an "S" or "X" severity index for fabric No. 3. All of the upper decile areas,
coded S, are either high automobile density areas or extremely well-trafficked corridors between major urban
areas. Eleven New England areas are found in the upper quartile; this large portion might be attributable to the
combustion of fuel oil for the extended heating season.
4.7 EVALUATION OF OXIDANT POTENTIAL PROBLEMS
The oxidizing substances in the atmosphere have three possible origins. They may occur naturally; they may
result from man-made emissions; or they may be formed by chemical interaction. Ozone occurs naturally in
amounts from 0.01 to 0.05 ppm at sea level. The concentration increases with altitude. In the outer atmospheric
layers, ultraviolet radiation reacts continuously with oxygen to form natural ozone. At the earth's surface, natural
ozone is formed by ultraviolet action on the terpenes of the pine forests.
Ozone and other oxidants represent a significant link in the smog-forming reactions characteristic of the
Southwestern United States. When strong sunlight falls on air containing hydrocarbons and nitrogen dioxide,
both usually from automobiles, ozone and other photochemical oxidants are formed. In Los Angeles, values up to
1 ppm of oxidant have been measured during smog conditions.
Because the formation of photochemical oxidants depends on the interaction of hydrocarbon emissions and
sunlight, diurnal and seasonal variations in pollutant levels are expected. Also, because greater irradiation of
airborne pollutants occurs in the areas in lower latitudes, and because the Southern areas of the United
States-particularly those in the Southwest-have less cloudiness and more sunlight than the Northern areas, the
Southern areas normally have a longer potential oxidant season.
Annual averages reflect the summation of the length of the season and the severity of the daily occurrences.
Because of this averaging affect, and because of the natural ozone background and the short duration of high
concentrations, high annual averages of ozone and other oxidants will not be indications of photochemical
INTERSTATE SURVEILLANCE PROJECT 43
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Table 4-11. RELATIONSHIP OF SOURCES TO ISP NITROGEN OXIDES PROBLEM SEVERITY INDEX
Suspected source
Autos
#
#
#
*
#
*
*
_
*
_
__
_
*
#
_
*
#
Point source
Miscellaneous
Miscellaneous
Power/metallurgy
Power/metallurgy
Metallurgy
Miscellaneous
Miscellaneous
Metallurgy
Metallurgy
Metallurgy
Chemical
TNT production
Miscellaneous
Metallurgy
Power
Miscellaneous
Metallurgy
Area name
Los Angeles
New York
Providence
Hartford; Washington, D.C.
Springfield
Fall River; Philadelphia; Bridgeport
Boston
Steubenville
Buffalo
Youngstown
Wilmington
Volunteer Arsenal
Detroit; Westerly; Albany; Cincinnati
Trenton; Montauk Point
Portsmouth; Austin
Chicago
Lawrence
Severity
index
S
S
S
S
S
S
X
X
X
X
X
X
X
X
X
X
X
problems, but will be indications of an area's natural potential for ozone and photochemical oxidants. Since
ozone problems are usually of short duration and infrequent, long-term averages will not necessarily reflect this
fact. Thus, to determine if there is a problem from ozone, the individual weekly, daily, or hourly values must be
considered.
Table 4-12 lists the areas with the greatest potential for the production of photochemical ozone and/or other
oxidants. The tabulation indicates that this potential has been realized in the reported occurrence of
photochemical smog in many of these areas.
Table 4-12. OXIDANT-POTENTIAL AREAS
Area name
San Ysidro
Montauk Point
Boulder City
Needles
Los Angeles
Block Island
Blacksburg
Sumpter Township
Beaumont
Fernandina Beach
Calexico
Natchez
Fort Smith
El Paso
Farmington
McAllen
Severity
index
S
S
S
S
S
S
S
S
S
S
S
S
S
X
X
X
Area name
Dulce
Yuma
Kintnersville
Chapel Hill
Spray
Fall River
Carville
Gainesville
Detroit
Owensboro
Oneca
Westerly
Sherman
Shreveport
Wichita Falls
Brownsville
Burlington
Severity
index
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
44
Area Evaluation
-------
4.8 SUMMARY
A relative severity index (PCN) for five major pollutants-particulates, sulfur dioxide, hydrogen sulfide, acid
aerosols, and nitrogen oxides-and for an oxidation potential was determined for each of the 144 areas. Areas
with a severity index of S (severe) or X (moderately severe) were further analyzed by category of estimated
emission densities of particulates and sulfur oxides, and from known sources of pollution for the other four major
types.
All areas with particulate emission densities of at least 15 tons per square mile per year had a severity index of
either S or X. Other areas with indexes of S or X lacked data on particulate emission densities, but are known to
have sources of high particulate emissions.
Similarly, areas with sulfur oxide emission densities of 50 tons per square mile per year, except for Cincinnati
and Beaumont, had a severity index of either S or X. Most other areas with an index of S or X, for which sulfur
oxide emission densities were not available, are known to have major point sources.
No direct estimate of hydrogen sulfide emission densities were available but, based on prior knowledge of the
areas, it was determined that most of these areas with an index of S or X had known sources of hydrogen sulfide,
such as paper mills, steel mills, or oil refineries.
Detailed information was not available for emissions of nitrogen oxides and acid aerosols; however, many of the
areas with S or X, for either of the two categories, were known to have potential emission sources of these two
pollutants.
Areas that were relatively unpolluted from the standpoint of particulates, sulfur oxides, nitrogen oxides,
hydrogen sulfide, and acid aerosols showed a rather high oxidation potential.
INTERSTATE SURVEILLANCE PROJECT 45
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5. STATISTICAL EVALUATION OF DATA
William Cox and Charles Zimmer
To demonstrate the validity and feasibility of the "effects package" as a monitoring and intelligence-gathering
tool, it is necessary to study the following factors:
1. Interrelationships between components.
2. The effects of meteorological conditions.
3. Relationships between components and air quality data.
Data from the ISP network and air quality measurements from the Continuous Air Monitoring Program
(CAMP), the National Air Sampling Network (NASN), and Environmental Science Services Administration
(ESSA) meteorological weather stations were statistically analyzed. The results are presented and discussed in this
section.
5.1 CORRELATIONS BETWEEN COMPONENTS
The data base for the statistical analysis consisted of a collation of annual averages for each component. To
compute annual averages from these quarterly and monthly reports, it became necessary to obtain data over at
least 6 months to establish valid annual averages. Thus, only those stations with valid annual averages for all
components were included in the data base. As a result, the data base contained information from 109 stations
for 1967 and from 158 stations for 1968. Matrices of correlation coefficients are presented in Tables 5-1 and
5-2.
As previously noted, the network was expanded in 1968 when fabrics No. 5 and No. 6 were used in place of
fabrics No. 4 and No. 2, and fabrics No. 7, No. 8, and No. 9 and the sulfation plates were added.
Correlations among the components were generally positive. This suggests that highly polluted areas tend to be
contaminated by most types of pollutants. The exceptions were in the data collected on fabrics No. 4 and No. 5
and on the rubber panels; these data were negatively correlated with every other component.
Components that were designed to measure particular pollutants were generally more strongly related to one
another than with components of other groups. For example, dustfall buckets, fabric No. 2 (soiling), and sticky
paper were all thought to measure particulates and, hence, should correlate well. Inspection of the 1967
correlation matrix showed this to be the case: sticky paper versus dustfall were correlated at 0.69; sticky paper
versus fabric No. 2 at 0.63; and dustfall versus fabric No. 2 at 0.62.
Similarly, the steel panel and sulfation candle rates should relate to one another because of the tendency of
sulfur oxides to accelerate the rate of metal corrosion. As expected, quarterly steel corrosion was correlated in
1967 at 0.72, and in 1968 at 0.74 with lead candle sulfation rates.
High correlations were observed in 1968 between 1- and 3-month nylon deterioration, 0.99, and between
sulfation plate and sulfation candle rates, 0.99. Apparently, data from pollutant collections on one nylon
component and on one sulfation component would be adequate to describe these types of effects.
Discussions of additional trends follow the discussion of potential meteorological effects.
5.2 CORRELATIONS OF COMPONENTS AND METEOROLOGICAL PARAMETERS
Because of the long-term (monthly, quarterly, yearly) nature of the effects components, it was not possible to
identify completely how meteorological parameters might effect these measurements. Gross effects of
meteorology, however, were determined from annual averages for components and from annual averages of
windspeed, relative humidity, degree days, temperature, and precipitation measured at the Weather Bureau
Stations nearest the ISP stations.
5.2.1 Relative Humidity
In general, correlations between components and meteorological parameters (cf. Tables 51 and 52) were
substantially lower than correlations between components. A few of these correlations, however, warrant further
comment. For example, relative humidity was correlated postively with annual steel corrosion (0.27 and 0.62) for
both years; the correlation was expected because steel corrosion is known to be accentuated in moist
atmospheres, especially in the presence of sulfur dioxides.18
The only fabric that displayed relatively high correlations with relative humidity were the nonspecific fabrics
No. 1 and No. 9. The 1968 correlation matrix shows correlations of fabric No. 1 (0.45) and fabric No. 9 (0.52)
with relative humidity; these two fabrics also correlated better with each other (0.58) than with any other
47
-------
Table 5-1. EFFECTS CORRELATION MATRIX
1967
c/3
s
K-
1
w
ANS
QS
FA 1
FA 2
FAS
FA 4
AGT
PBC
DUST
NY1
R C
SP
TEMP
DD
PPCT
WS
R H
ZINC
0.42
0.40
0.21
0.30
0.38
-0.05
0.20
0.44
0.33
0.04
-0.27
0.17
-0.22
0.25
0.31
0.31
0.25
ZINC
ANS
0.94
0.54
0.31
0.62
0.16
0.66
0.63
0.42
0.13
-0.43
0.11
-0.33
0.32
0.51
0.20
0.62
ANS
QS
0.46
0.38
0.66
0.03
0.68
0.72
0.49
0.07
-0.45
0.24
-0.29
0.30
0.47
0.26
0.53
QS
FA 1
0.27
0.29
0.34
0.48
0.23
0.23
0.19
-0.23
-0.01
-0.10
0.08
0.55
0.05
0.61
FA 1
FA 2
0.53
-0.42
0.30
0.66
0.62
0.00
-0.40
0.63
-0.44
0.48
0.08
0.41
0.14
FA 2
FAS
-0.09
0.55
0.77
0.57
0.10
-0.44
0.37
-0.29
0.30
0.35
0.30
0.30
FAS
FA 4
0.13
-0.32
-0.36
0.06
0.40
-0.55
0.42
-0.44
0.40
-0.10
0.25
FA 4
AGT
0.53
0.45
0.05
-0.34
0.25
0.03
-0.01
0.44
0.08
0.46
AGT
AGT
ANS
DD
DUST
FA 1
FA 2
FAS
FA 4
NY 1
PBC
0.67
0.08
-0.46
0.58
-0.37
0.41
0.21
0.39
0.22
PBC
= Silver plate
= Annual steel corrosion
= Degree days
= Dustfall
= Fabric No. 1
= Fabric No. 2
= Fabric No. 3
= Fabric No. 4
= Nylon, monthly
DUST
0.05 NY 1
-0.45 -0.12 RC
0.69 -0.12 -0.17
-0.32
0.37
0.16
0.26
0.21
DUST
-0.01
-0.02
0.17
-0.25
0.14
NY1
0.46
-0.45
-0.40
-0.17
-0.54
R C
PB C = Lead candle
PPCT = Precipitation
QS = Quarterly steel corrosion
RC = Rubber cracking
RH = Relative humidity
SP = Sticky paper
TEMP = Temperature
WS = Windspeed
ZINC = Annual zinc corrosion
SP
-0.17
0.22
-0.22
0.34
-0.26
SP
TEMP
-0.97
-0.01
-0.28
-0.28
TEMP
D D
0.00
0.37
0.23
DD
PPCT
0.13
0.78
PPCT
WS
0.03
WS
o
3
-------
NTERSTATE SURVEILLAr
3
M
3 ANS
O as
W FA1
H FA3
FA 5
FA 6
FA 7
FAS
FA 9
ACT
PB C
SULF
DUST
NY 1
NY 3
R C
SP
TEMP
D D
PPCT
WS
R H
Table 5-2. EFFECTS CORRELATION MATRIX
1968
ZINC
0.43
0.43
0.26
0.42
-0.25
0.30
0.17
0.23
0.11
0.30
0.51
0.51
0.30
0.35
0.33
-0.10
0.30
-0.14
0.13
-0.07
0.05
-0.11
ZINC
ANS
0.93
0.41
0.60
-0.23
0.43
0.27
0.35
0.38
0.61
0.67
0.64
0.37
0.16
0.18
-0.35
0.26
-0.39
0.38
0.23
0.20
0.27
AN S
QS
0.36
0.64
-0.30
0.49
0.33
0.27
0.36
0.63
0.74
0.71
0.46
0.17
0.19
-0.33
0.40
-0.33
0.33
0.22
0.25
0.18
QS
FA 1
0.24
-0.11
0.40
0.33
0.22
0.58
0.44
0.28
0.28
0.27
0.06
0.08
-0.21
0.22
-0.05
0.04
0.25
-0.04
0.45
FA 1
FAS
-0.32
0.57
0.36
0.38
0.51
0.53
0.67
0.64
0.40
0.27
0.28
-0.22
0.43
-0.18
0.16
0.08
0.22
0.10
FA 3
FA 5
-0.47
-0.45
0.25
0.03
-0.21
-0.47
-0.49
-0.56
-0.13
-0.12
0.59
-0.58
0.29
-0.28
-0.06
-0.17
-0.13
FA 5
FA 6
0.68
0.10
0.35
0.42
0.68
0.68
0.46
-0.02
-0.01
-0.25
0.64
-0.33
0.32
0.03
0.27
0.08
FA 6
FA 7
0.03
0.21
0.28
0.49
0.51
0.58
-0.04
-0.02
-0.23
0.62
-0.30
0.33
-0.09
0.20
0.08
FA 7
FAS
0.36
0.10
0.12
0.11
-0.04
0.16
0.20
0.21
-0.06
-0.01
0.01
0.00
0.00
0.04
FAS
FA 9
0.49
0.24
0.21
0.19
0.13
0.14
-0.13
0.13
0.22
-0.21
0.40
0.01
0.52
FA 9
AGT
AN S
DD
DUST
FA 1
FAS
FA 5
FA 6
AG T
0.56 PB C
0.55 0.99
0.43 0.51
0.09 0.17
0.10 0.18
-0.20 -0.29
0.33 0.64
0.01 -0.32
-0.01 0.32
0.28 0.01
-0.08 0.33
0.30 -0.02
AG T PB C
= Silver plate
= Annual steel corrosion
= Degree days
= Dustfall
= Fabric No. 1
= Fabric No.
= Fabric No.
= Fabric No.
SULF
0.52
0.16
0.17
-0.28
0.65
-0.31
0.31
0.01
0.32
-0.02
SULF
DUST
0.10
0.10
-0.40
0.69
-0.22
0.24
0.00
0.10
0.09
DUST
3
5
6
NY 1
0.99
-0.16
0.00
-0.02
0.02
0.00
-0.06
0.02
NY 1
NY 3
-0.17
0.00
-0.02
0.02
0.02
-0.06
0.03
NY 3
FA 7 = Fabric No. 7
FA 8 = Fabric No. 8
FA 9 = Fabric No. 9
NY 1 = Nylon, monthly
NY 3 = Nylon, quarterly
PB C = Lead candle
PPCT = Precipitation
QS = Quarterly steel corrosion
RC = Rubber cracking
RH = Relative humidity
SP = Sticky paper
SULF = Sulfation plate
TEMP = Temperature
WS = Windspeed
ZINC = Annual zinc corrosion
RC
-0.19 SP
0.42 -0.14 TEMP
-0.44 0.16 -0.98 D D
-0.42 -0.23 0.01 0.00 PPCT
-0.18 0.30 -0.34 0.38 0.00 WS
-0.46 -0.20 -0.15 0.14 0.69 -0.02
R C S P TEMP D D PPCT WS
VO
-------
components. These facts possibly suggest a mutual response to humidity and contaminants that was neither
monitored nor suspected.
The negative correlation of temperature with most components probably reflects the combined effects of
northern industrialization and winter heating requirements. Only rubber panels and fabric No. 4 were positively
correlated with temperature.
Because the interactions between air contaminants and meteorology parameters are complex, multiple
regression was used as a technique for estimating and separating the meteorological effects on certain
components. This technique suggested several statistical models for explaining the corrosion of metals. One such
model related annual steel corrosion to lead candle sulfation rates and relative humidity as in the following
equations:
1967 Y = -27.3 + 23.7 PB - 4.2 PB2 + 0.7 RH
Y = -22.6 + 27.5 PB - 4.4 PB2 + 0.6 RH
where Y is annual steel corrosion (ju/yr), PB is lead candle sulfation (mg of S03/ 100cm2 -day), and RH is relative
humidity (%).
These equations account for 70 and 61 percent of the total station-to-station variations in annual steel
corrosion. Because temperature did not appear to enhance the prediction power of these equations, it was not
included in the equations.
The two equations imply not only that increased sulfation rates are accompanied by increased steel corrosion,
but that a point is probably reached when additional sulfur dioxide would not contribute significantly to
additional corrosion. A similar result was noted in work done by Upham:2 a parabolic curve resulted when
corrosion results were plotted as a function of exposure time.19 Humidity also appears to enhance the rate of
steel corrosion, but it was not as large a factor as sulfur oxides.
Quarterly steel exhibited a similar pattern in 1968:
Y = -38.9 + 59 PB - 10 PB2 + 0.8 RH
This regression equation explains 71 percent of the variances.
A slightly more realistic relationship-the interaction between moisture and sulfation rates and their combined
effect on average quarterly steel corrosion is given by:
1967 Y = -72 + 0.78 PB RH 9.9 PB2 + 0.78 RH
1968 Y^ -33 + 0.99 PB RH 11.6 PB2 + 0.53 RH
where Y is the quarterly steel corrosion Ou/yr). These equations explained 76 and 74 percent of the variances.
Both of the latter equations imply that humidity enhances the rate of corrosion at a greater rate with higher
levels of lead candle sulfation. Moreover, the two equations imply that sulfation levels are most important in
determining corrosion when the relative humidity is greater than 25 times the average sulfation level, a condition
that exists at most sampling sites.
For example, Station 103, Sunland Park, N. M., exhibited a lead candle sulfation rate of 1.9 units in the upper
decile, a relative humidity of 44 percent in the lower decile, and a quarterly steel corrosion of 28 units in the
second quartile. Station 104, Anthony, N. M., reported a lower sulfation rate, 0.1, and a correspondingly lower
quarterly steel corrosion rate, 8, even though it was exposed to the same annual humidity as Station 103. These
data indicate that sulfur oxides have a detrimental effect on steel even in a relatively low-moisture environment.
5.2.2 Moisture and Temperature
Silver, as previously noted, tarnished rapidly in the presence of hydrogen sulfide (H2S). It is also known,
however, that sulfur oxides (SOX) induce a discoloration of silver that might interfere with that caused by
hydrogen sulfide. To test this assumption, a regression approach was used to relate sulfation levels to silver
tarnishing and to test whether or not the interaction was affected by moisture and temperature:
1967 Y = -60 + 22 PB 2.9 PB2 + 1.0 T + 0.7 RH
1968 Y = -57 + 25 PB - 3.1 PB2 + 0.8 T + 0.8 RH
where Y is silver tarnishing (percent reflectance loss) and T is temperature (°F). These equations explained 53 and
51 percent of the variances.
50 Statistical Evaluation of Data
-------
The equations suggest that higher sulfation rates are accompanied by high silver-tarnishing rates and that
temperature and humidity slightly enhance the tarnishing. The relatively small percent of explained variances is
probably attributable to the effects of hydrogen sulfide.
In the analysis of zinc corrosion, humidity and temperature were found not to be significant contributors to the
corrosion rate. Moreover, sulfation rate correlated poorly with zinc corrosion, and it now appears that unknown
factors influence this measurement.
Screening of other components failed to add any significant explanations concerning meteorological effects,
probably due to the averaging effects and lack of good simultaneous air quality data. In summary, meteorological
parameters appear to affect, but not to be the major factors in determining, the responsiveness of the
components.
5.3 CORRELATIONS BETWEEN COMPONENTS AND AIR QUALITY DATA
An ISP network station was located adjacent to each of the six CAMP stations. The monthly CAMP data for
1967 and 1968 were averaged for oxides of nitrogen, total oxidants, and sulfur dioxide. Then a correlation matrix
(Table 5-3) was computed between the components and the CAMP values. The components used in this analysis
were silver plates, lead candles, dustfall buckets, nylon panels, rubber panels, and sticky paper; components
sampled for longer than a month were not included.
Table 5-3. CORRELATIONS AMONG MONTHLY CAMP AND EFFECTS COMPONENTS
Component
Silver plate
Lead candle
Dustfall bucket
Monthly nylon panel
Rubber panel
Sticky paper
so2
1967
0.61
0.92
0.36
0.41
-0.35
0.18
1968
0.53
0.91
0.46
0.57
-0.51
0.32
N0x
1967
0.38
0.68
0.37
0.42
-0.59
0.20
1968
0.21
0.55
0.20
0.28
-0.35
0.17
OX
1967
-0.27
-0.40
0.10
-0.09
0.63
0.06
1968
-0.12
-0.50
0.07
-0.24
0.60
0.13
The most significant correlations for both years, 0.92 and 0.91, were observed between average sulfur dioxide
concentrations and lead candle sulfation. After the data were plotted, the slopes of the least-squares line showed
25.7 and 23.5 milligrams of sulfur trioxide per 100 square centimeters per ppm of sulfur dioxide.
Reciprocals of these numbers, which approximate the factor for converting lead candle sulfation to ppm of
sulfur dioxide, indicate a suitable range of from 0.03 to 0.04 ppm of sulfur dioxide per milligram of sulfur
trioxide per 100 square centimeters per day.
It was anticipated that the extent of rubber cracking would correlate well with concentrations of ozone in the
ambient air. The only air quality data that reflected ozone levels were the measurements of total oxidant taken at
the CAMP stations; correlations of 0.63 and 0.60 were obtained in 1967 and 1968, respectively.
Other relationships were expected between some of the fabrics used in the effects package and CAMP air
quality data. As expected, although further averaging of the 1968 quarterly CAMP data reduced the size of the
data base and possibly the significance of the correlations, fabric No. 5 correlated with total oxidants, 0.56, and
fabric No. 3 correlated with oxides of nitrogen, 0.72.
In each of the above correlation analyses, various meteorological parameters were included in an attempt to
assess their impact. For example, wind speed, temperaure, and relative humidity were studied in determining the
sulfation rate of lead candle, but the correlation between lead candle and sulfur dioxide was not significantly
enhanced by the inclusion of these variables. Again, the averaging tendency of the component measurements
probably suppressed substantially the apparently small influences of the weather variables. Similar statements can
be made about rubber panels, other fabric panels, and the particulates.
Other air quality data from 19 NASN stations adjacent to ISP stations were analyzed. Suspended-particulate
data from high-volume samplers were averaged to provide an annual 1968 mean, and these data were
supplemented by data from high-volume samplers at the six CAMP stations. Correlations from all 25 pieces of
data were computed between the values of total suspended particulates and the values reported by three
components, dustfall bucket, sticky paper, and fabric No. 6, which were designed to measure particulates. The
correlation coefficients, 0.71, 0.66, and 0.53, respectively, corroborate the belief that all of the measurements are
INTERSTATE SURVEILLANCE PROJECT
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an index of particulate contaminants. A further attempt to clarify the mutual responsiveness of the three
components is presented below in the subsection on factor analysis.
5.4 FACTOR ANALYSIS
The "effects package" may be considered to be a network of measuring devices that is sensitive to basic air
pollution factors. For example, dustfall collection buckets and sticky-paper samplers are two measurement
devices that logically associate with one another because they are, to some degree, mutually affected by
particulates, one aspect of air pollution. Similarly, measurements of sulfation and silver tarnishing are related to
sulfur oxide and perhaps to other corrosive substances.
Although the relationships between the entire set of effects components is complex, the total variation in
measurements can be summarized if a small number of air pollution factors can be identified and related to all
components.
5.4.1 Factor Analysis Technique
The technique for estimating pollution factors is known as factor analysis, which approximates the covariation
of a large number of variables by the variation in a few hypothetical constructs, or factors.
Portions of the following example of factor analysis appear in a monograph on multivariant analysis by
Kendall.20
Nine body measurements taken on several male volunteers were analyzed for "types" of body build by factor
analyses.
These measurements included standing height, sitting height, arm length, leg length, thigh length, abdomen
girth, hip girth, shoulder girth, and weight.
The hypothesis was that each body measurement for an individual is determined by several independent
factors.
The analysis indicated that two such factors accounted for 70 percent of the variation in the nine body
measurements. The first factor was one which correlated with length and height variables and supposedly
determined the lankiness of an individual.
The second factor was one which positively correlated with girths and weight. This factor appeared to
determine the bulkiness of an individual, apart from his length measurements.
The statistical procedure begins by assuming that each variable is the result of "loading" (or correlation) with
each of several basic factors. The model expressing this relationship with the first variable is
Xi = anfj + auf2 + . . . + Ui
where Xj is the value of variate 1; ft... .fm are the basic air pollution factors; and ax t. .. .at m correlate variable
1 with factors 1 through m. Variable U, which represents the unexplained portion of the variable, is assumed to
be a combination of unaccounted for factors or the "uniqueness" of that particular variable. A large uniqueness
element implies that the basic factors do not account for the variation exhibited by that variable. Further
assumptions in the factor model are that the factors are independent of one another, and that the unique element
for each variable is independent of the basic factors and the other variables.
The factor-loading matrix is an array of correlations between variables and factors. Each row represents the
correlations of a variable with all factors. The coefficients (ai;j) in the equation are the first row of the
factor-loading matrix, and the pattern in which the factor-loadings associate with the variables describes the
factors. Within each factor, only a few variables will have high loadings; these may be denoted as factor
descriptors. The sum of squares of all loadings for a factor represents the portion of the total experimental
variation that is attributable to that factor; the success of the factorization is partly measured by the total of
these explained variances.
The particular factor analysis technique used for the effects data is known as principal factor analysis.2' This
method consists of performing a principal analysis of the correlation matrix of components to extract successive
independent factors that maximally explain the total variation of the original variates. The first principal
component is thus a combination of the effects variables that explains the largest fraction of the experimental
variation. (When the correlation matrix is used for the analysis, the total variance is equal to the number of
variables.) The procedure continues with the rotation of these principal components in such a manner that the
basic relationship among the variables is unaltered. The criterion for the rotation-that each of the resulting
factors have large correlations with some variables and low correlation with the others-is achieved by a "varimax
technique," in which the sum of the variances of the factor-loadings is maximized.
52 Statistical Evaluation of Data
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All of the variables, or components, were not used in the factor analysis. Fabrics No. 1 and No. 9 are sensitive
to humidity and were discarded as candidates for describing air pollution. Fabric No. 8, thought to be nonspecific
to air pollutants, was omitted when its insensitivity became more apparent. Nylon panels were omitted because
they were not strongly associated with other components; they tended to respond in a manner that yielded an
extremely skewed frequency distribution. Moreover, because nylon appears to react to acid aerosols and to short
intervals of air pollution, it is not suited for this type of analysis.
The data for the factor analysis were collected by networks and key components that varied slightly over the
2-year period. First, there was an increase in the number of stations: sufficient data were available for 115
stations in 1967 and 168 stations in 1968. The number of stations differs slightly from those given in Section 5.1
because fewer meteorological restrictions were in effect for the factor analysis. Second, different components
were included: fabrics No. 2 and No. 4 were used in 1967 only, and fabrics No. 5, No. 6, and No. 7 and the petri
dish sulfation method were included in 1968 only.
5.4.2 Results
Results of the factor analyses for the two years are presented in Table 54. Only three factors were considered
because of the variance explained by each factor; that is, other factors did not contribute significantly to the
percentage of total variance explained.
Table 5-4. FACTOR LOADINGS FOR 1967 AND 1968
Variable
Zinc, annual
Steel, annual
Steel, quarterly
Lead candle
Sulfation plates
Silver tarnishing
Fabric No. 2
Fabric No. 3
Fabric No. 4
Fabric No. 5
Fabric No. 6
Fabric No. 7
Rubber cracking
Sticky paper
Dustfall
% of variance ex-
plained by
factors
Factor
Corrosion
1967
0.51
0.94
0.92
0.67
0.73
0.29
0.74
0.31
-0.37
0.08
0.38
36
1968
0.56
0.91
0.90
0.74
0.71
0.71
0.72
-0.06
0.39
0.15
-0.16
0.21
0.26
33
Dirtiness
1967
0.20
0.01
0.14
0.61
0.10
0.77
0.40
-0.58
-0.11
0.93
0.70
26
1968
0.21
0.02
0.15
0.54
0.57
0.17
0.33
-0.53
0.74
0.80
-0.05
0.85
0.62
26
Oxidation
potential
1967
-0.03
-0.08
-0.09
-0.14
-0.12
-0.17
-0.07
0.64
0.89
0.00
-0.27
13
1968
0.01
-0.16
-0.17
-0.12
-0.12
-0.13
-0.03
0.72
-0.06
-0.12
0.93
-0.16
-0.44
13
% of variance
explained
1967
30
89
88
84
56
70
71
84
93
86
70
75
1968
36
86
87
85
84
54
63
80
71
68
89
80
64
72
Note the consistency between the results of the factor analysis for 1967 and 1968. Despite the basic differences
in the data sets for the 2 years, the percentages of total variance explained by the three factors were nearly the
same: 75 percent for 1967 and 72 percent for 1968. In addition, the variances explained by the individual factors
are amazingly similar for the 2 years.
The right-hand column of Table 5-4 indicates the extent to which the three factors, when combined, explain
the variability of an effects measurement between sampling stations. The data for zinc stand out because the
three factors explain only about one-third of the between-station variability in the weight loss of the exposed
panels. The loss suggests that zinc is affected by mechanisms not considered in this study. As can be seen, how-
ever, the three factors explain nearly 90 percent of the variability in measurements such as steel deterioration and
rubber cracking.
The highest corrosion loadings for 1967 and 1968, coded as Factor 1, respectively, are associated with annual
steel, 0.94 and 0.91; quarterly steel, 0.92 and 0.90; fabric No. 3,0.74 and 0.72; silver tarnishing, 0.73 and 0.71;
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lead candle sulfation, 0.67 and 0.74; sulfation plates, 0.71 in 1968; and annual zinc, 0.51 and 0.56. Thus Factor 1
has been tentatively labeled a measure of the corrosive effects of atmospheric pollutants.
Factor 2 shows highest loadings with sticky paper, 0.93 and 0.85; dustfall bucket, 0.70 and 0.62; fabric No. 2
for 1967, 0.77; fabric No. 6 for 1968, 0.74; fabric No. 7 for 1968, 0.80; lead candle, 0.61 and 0.54; and sulfation
plate for'l968,'o.57. In addition, this factor exhibits a loading of-0.53 for fabric No. 5 in 1968. Fabrics No. 4
and No. 5 were initially selected for their presumed sensitivity to'ozone. Ozone bleaches the fabrics and changes
them from a darker to a lighter color. If a fabric were to be sensitive to dirtiness, the fabric would darken, and
there would be an indirect relationship between color change and dirtiness. Factor 2 appears to be a measure of
dirtiness or soiling potential.
Factor loadings for Factor 3 are the highest for rubber cracking, 0.89 and 0.93; fabric No. 4 for 1967, 0.64; and
fabric No. 5 for 1968, 0.72. As before, fabrics No. 4 and No. 5 were selected for their sensitivity to ozone
concentrations, which are correlated with the cracking of rubber. Thus, Factor 3 has been identified as an index
of oxidation potential, not necessarily a smog index.
5.4.3 Factor-Score Matrix
A measure of the severity represented by a particular factor at a particular station is provided by a factor-score
matrix. A factor-score matrix is composed of normalized factor-scores, such as mean zero or standard deviation of
one, which may be related to cumulative frequencies of occurrence in a fashion similar to other summarizing
statistics. For example, if it can be assumed that the factor-scores are approximately normally distributed, those
greater than one would occur about 15 percent of the time.
A factor-score matrix was computed for both years. The consistency among the factor-scores for the 2 years
was remarkable. Computed scores, available at 88 stations for both years, were highly correlated: for example,
corrosion was correlated at 0.95, dirtiness at 0.93, and oxidation potential at 0.91. These results demonstrate the
tendency of areas to remain relatively constant from year to year.
In addition, factor severity indexes (FSI) were defined for corrosion and for dirtiness. A value of X was assigned
if the factor-scores were among the top quartile, 0.7 to 1.4; S was assigned if they were among the top decile,
1.4 or greater. The FSI indexes were compared with the pollution code numbers (PCN) and their corresponding
relative severity indexes from Section 4.1.1. Stations in areas listed in Tables 53 and 5-4 were compared for
effects from particulates and sulfur oxides. (Factor-scores were not availableand were coded NAfor areas not
included.) These data are presented in Table 55.
In general, agreement was good between the particulate code number indexes and the dirtiness FSI. Table 5-5
shows that Detroit, Steubenville, and Huntington have dirtiness FSI's that indicate a less severe problem than the
corresponding severity indexes for particulates. The factor-scores were 1.3 for Huntington and 1.2 for Detroit;
these were close to the upper decile, 1.4. The discrepancy is not large, but the factor-score for Steubenville, which
was relatively low, at 0.7, cannot be explained at this time.
The FSI's also indicated that Denver and New York have severe dirtiness problems. Although the PCN's indicate
only moderate problems for both areas, Appendix C shows that dustfall bucket and sticky-paper results ranked in
the upper decile, and fabric No. 6 ranked in the third quartile. The averaging of these indexes indicates only a
moderate problem, or X. The factor-scores are based on a linear combination of these three components with
more weight being given to data from sticky paper and dustfall collectors than to data from fabric No. 6; for this
reason, the FSI is larger for the first two components.
The corrosion FSI was compared with the PCN for sulfur oxide in Table 5-6. Because corrosion is affected by
elements other than sulfur oxides, the two indexes are not necessarily measurements of the same quantity;
nevertheless, there is generally good agreement.
All areas designated severe, S, by PCN's were rated severe by the corrosion FSI. The FSI selected Boston as an
area with severe corrosion, but the PCN for sulfur oxides indicated only moderate corrosion. Corrosion, however,
does not necessarily correspond to sulfur oxides only.
5.5 DISCUSSION OF ANALYSES
The complex relationships among the components and the ways they respond to air pollutants and
meteorological parameters are not easily determined by correlation techniques. Many of the air contaminants that
probably affect the components were not monitored, and their influences could not be directly measured. These
unmeasured quantities frequently revealed themselves as correlations with other variables that probably have little
influence on the components. One example of this was the case in which sulfur dioxide "explained" variability in
silver tarnishing not only because of the effect of sulfur dioxide, but probably also because of the mutual
occurrence of sulfur dioxide and hydrogen sulfide, which also tarnish silver.
54
Statistical Evaluation of Data
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Table 5-5. COMPARISON OF "DIRTINESS" FACTOR SEVERITY AND
PARTICULATE SEVERITY INDEX
Area name
Detroit, Michigan
Steubenville, Ohio
Youngstown, Ohio
Buffalo, New York
Chicago, Illinois
Fall River, Massachusetts
Bridgeport, Connecticut
Louisville, Kentucky
New York, New York
Philadelphia, Pennsylvania
Cincinnati, Ohio
St. Louis, Missouri
Huntington, West Virginia
Wilmington, Delaware
Toledo, Ohio
Boston, Massachusetts
Springfield, Massachusetts
Denver, Colorado
Washington, D.C.
New Orleans, Louisiana
Laredo, Texas
Hartford, Connecticut
Davenport, Iowa
Dubuque, Iowa
Sioux City, Iowa
PCN relative
severity index
Sa
s
s
s
s
X
X
X
X
s
X
X
s
X
X
X
X
X
X
X
X
X
X
X
X
Factor severity
index (FSI)
Xb
X
S
s
s
c
Nd
X
S
N
X
X
X
N
X
X
s
X
X
X
X
X
X
N
aS indicates among top decile.
"X indicates among top quartile.
c indicates among lower three quartiles.
°N indicates no score available.
In other words, correlation and multiple correlations must be viewed in the light of known and suspected
mechanisms that govern component responses, and the likelihood of the presence of these factors at sampling
sites. In spite of these limitations, a few general statements can be made.
The effects of meteorology on the components' responsiveness appear to be less dominant factors than the
quality of the air. This statement is supported by the relatively small degree of correlation observed between
components and meteorological parameters. The most significant relationship was the effect of the interaction of
relative humidity and oxides of sulfur, as measured by lead candle, on the rate of steel corrosion; this correlation
demonstrated that the corrosiveness of the atmosphere is greatly enhanced by the presence of sulfur oxides,
especially in a humid environment.
Many of the components were well related to corresponding air quality measurements. In particular, sulfation
plates and sulfation candles were highly correlated, 0.9 or above, with sulfur dioxides concentrations. In addition,
data from dustfall, sticky paper, and fabric No. 6 components correlated positively, 0.71, 0.66, and 0.53, with
annual averages of total suspended particulate data collected on high-volume samplers. The correlation was
observed even though not all of these four methods measure the same types of particulates.
Correlations between air quality measurements, which are partly representative of ozone levels and rubber
cracking, were reasonably good at 0.63 and 0.60.
In addition, data from fabric No. 3, which was designed to measure oxides of nitrogen, were reasonably well
correlated at 0.72 with oxides of nitrogen.
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Table 5-6 COMPARISON OF "CORROSIVE" FACTOR SEVERITY INDEX
AND SULFUR OXIDES SEVERITY INDEX
Area name
Fall River, Massachusetts
Steubenville, Ohio
Bridgeport, Connecticut
Chicago, Illinois
New York, New York
Louisville, Kentucky
Boston, Massachusetts
Detroit, Michigan
St. Louis, Missouri
Philadelphia, Pennsylvania
Cincinnati, Ohio
Beaumont, Texas
Toledo, Ohio
Youngstown, Ohio
Springfield, Massachusetts
Hartford, Connecticut
El Paso, Texas
Easton, Pennsylvania
Buffalo, New York
Wilmington, Delaware
Albany, New York
Sarnia, Ontario, Canada
Trenton, New Jersey
Evansville, Indiana
Owensboro, Kentucky
Providence, Rhode Island
Huntington, West Virginia
PCN relative
severity index
X
S3b
Xb
s
X
X
X
X
s
X
X
X
X
X
X
X
s
X
X
X
X
X
X
X
X
Factor severity
index (FSI)
X
Sd
Na
S
X
c
S
X
s
N
N
X
X
s
X
N
N
X
-
X
X
aS indicates among top decile.
"X indicates among top quartile.
c_ indicates among lower three quartiles.
N indicates no score available.
The results of a factor analysis of the component responses revealed that three basic factors, corrosion, dirtiness
or soiling potential, and oxidation potential, explain most of the variation. The three variables that correlated
most highly with the three base factors were quarterly steel corrosion, sticky paper, and rubber cracking,
respectively. Therefore, if information is desired about these three factors from the measurement of only three
variables, these probably would provide the most information.
Factor-scores are apparently good indicators of the relative severity of these three types of problems. This
statement is supported by the good association between emission density and the factor severity index (FSI).
Several components, however, which did not respond to these factors, were apparently responsive primarily to
meteorological parameters or unmeasured air pollution factors. Fabrics No. 1 and No. 9 responded more strongly
in more humid atmospheres; nylon panels seemed to respond in a manner that could not be explained by either
the predominance of these three factors or by the influences of meteorological fluctuations.
5.6 DISCUSSION OF COMPONENTS
The following is a brief discussion of each component of the sampler.
5.6.1 Zinc Panels
The correlation analysis showed the zinc panel to be positively correlated with most of the other 17
components in the effects package sampler. The highest correlations, about 0.50, were with the sulfation candle
56
Statistical Evaluation of Data
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and plate components. In the factor analysis, the zinc panel was a significant parameter in the factor identified as
corrosion, but since the loading of 0.50 was much lower than those for steel corrosion and sulfation, 0.90 and
0.70, respectively, the zinc panel is probably a less desirable indicator of atmospheric corrosion than steel panels.
5.6.2 Steel Panels
Both quarterly and annual corrosion rates for steel panels correlated positively with sulfation and relative
humidity. The quarterly analysis showed the highest corrosion rates in the winter months; because of the seasonal
pattern, quarterly measurements provide more information about pollutant effects than annual measurements. A
multiple regression analysis showed that the variability in sulfation rates and relative humidity accounted for
between 60 and 70 percent of the variance (multiple correlation about 0.8) in steel corrosion rates. Thus, for a
given level of sulfur oxides in the atmosphere, the effect of steel corrosion is enhanced by increased relative
humidity.
In the factor analysis, steel corrosion rates appeared to be the most significant parameter in the factor labeled
corrosion; the factor loading was greater than 0.90.
5.6.3 Sulfation Candles and Plates
Sulfation measurements can be made equally well with candles and plates: the correlation between the two
methods was 0.99. In the comparison between sulfation candles and sulfur dioxides (conductivity) measured at
six CAMP stations, the correlations were 0.92 and 0.91 for 1967 and 1968. (The conversion factor to convert
sulfation rates to sulfur dioxide is approximately: 1 milligram of sulfur trioxide per 100 square centimeters per
day equals 0.04 ppm sulfur dioxide.) Sulfation rates for both candles and plates loaded reasonably high in the
corrosion factor, indicating the influence of sulfur dioxide upon corrosion.
5.6.4 Rubber Panels
Many researchers have reported that the amount of cracking of exposed rubber panels and the amount of
ambient ozone concentrations are related. The six CAMP stations showed a correlation of 0.60 between rubber
cracking and total oxidants. At stations in comparatively unpolluted urban and rural areas, the high values
observed were probably related to the amount of ozone, not total oxidant, present. The factor analysis showed
rubber cracking as the most significant parameter in the factor identified as oxidation potential.
5.6.5 Dustfall Buckets
Dustfall measurements provide an estimation of settleable particulates. These measurements had a fairly high
loading with the factor labeled "dirtiness" of the factor analysis study.
5.6.6 Sticky Paper
Sticky paper is used to estimate the amount of windblown particulates. The correlation with dustfall
measurements was 0.69 for both 1967 and 1968. In the factor analysis, sticky paper was the most significant
parameter in the factor labeled "dirtiness;" this measurement, therefore, appears to be a better estimator of the
factor labeled "dirtiness" than dustfall.
5.6.7 Nylon Panels
Exposed nylon primarily measures sulfuric acid mist and acid aerosols. There was a high correlation, 0.99,
between the monthly and quarterly deterioration rates, but essentially no correlation between nylon and the
other 17 components. Nylon was therefore not considered in the factor analysis.
5.6.8 Dye-Fabric Combinations
Fabric No. 1 did not correlate highly with any other component. Fading of this fabric, which correlated
reasonably well with relative humidity, indicated a tendency toward increased color loss with increased humidity.
Fabric No. 2 was quite stable. Any color changes caused by exposure probably resulted from soiling. The rate
of color change was positively correlated with dustfall and sticky-paper measurements, 0.62 and 0.63,
respectively, and with sulfation rates, 0.66. In the factor analysis for 1967, it was a significant parameter in the
factor labeled "dirtiness."
Fabric No. 3, thought to be sensitive to oxides of nitrogen, correlated highly, at 0.72, with nitrogen oxides. The
rate of color fading was also positively correlated with steel corrosion and sulfation rates. In the factor analysis,
the rate of color fading showed up as a significant parameter in the factor labeled corrosion.
Fabric No. 4, known to be sensitive to ozone, showed the highest negative correlation with sticky paper, -0.55,
indicating greater color loss in cleaner atmospheres-atmospheres with less particulates-but its correlation with
rubber cracking was 0.40. In the factor analysis for 1967, fabric No. 4 was the second most significant parameter
in the factor labeled oxidation potential.
INTERSTATE SURVEILLANCE PROJECT 57
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Fabric No. 5, also known to be sensitive to ozone, was used in 1968 in place of fabric No. 4. It showed a
positive correlation, 0.59, with rubber cracking, and negative correlations of -0.49, -0.56, and -0.58 with
sulfation, dustfall, and sticky-paper measurements, respectively. In the factor analysis, fabric No. 5 had the second
highest loading, 0.72, in the factor labeled oxidation potential.
Fabric No. 6, selected as an indicator of soiling, correlated highly with sulfation rates, 0.68, and sticky paper,
0.64. In the factor analysis, fabric No. 6 was a significant parameter in the factor labeled dirtiness.
Fabric No. 7, selected with no prior knowledge of specific pollutant effects, showed a positive correlation with
sulfation rates, dustfall, and sticky paper. Of special significance is that fabric No. 7 had the second highest
loading, 0.80, for the factor labeled dirtiness, for which sticky paper was the most important parameter.
Fabrics No. 8 and No. 9, selected with no particular pollutant effect in mind, did not show any
interrelationships with other components. Because of the low correlations, these fabrics were not included in the
factor analysis. These fabrics provided essentially no information about exposures to pollutants.
5.6.9 Silver Plates
Silver tarnishing, selected as an indicator of hydrogen sulfide, is also known to be affected by sulfur dioxide.
Silver tarnished by hydrogen sulfide, however, has a distinctive dark blue or black appearance not normally
associated with the tarnishing effects of sulfur dioxide. The highest correlations, greater than 0.60, were observed
with annual and quarterly steel corrosion rates; correlations with sulfation rates were slightly more than 0.50. In
the factor analysis, silver tarnishing showed up as a significant parameter in the corrosion factor, but its loadings
of 0.73 and 0.71 for 1967 and 1968 were much lower than those for annual and quarterly steel, about 0.90.
58
Statistical Evaluation of Data
-------
6. CONCLUSIONS
James Cavender and Norman Huey
The effects-sampling system was designed to be used in estimating the nature and extent of air pollution on a
long-term basis. Individual components used in the sampler were selected because of their simplicity and
relatively low cost of preparation, operation, and analysis. In keeping with the concepts of simplicity and low
cost, the system was designed to be a static testing device requiring no electricity. As a result the system can be
easily located in remote locations.
After evaluating the performance of the effects sampler network, the investigators made the following
conclusions:
1. The effects sampler is capable of detecting the existence of five major pollutants and one potential problem.
These are sulfur oxides, particulates, nitrogen oxides, hydrogen sulfide, acid aerosols, and oxidation potential.
The conclusion is based upon either direct correlation of sampler data with air quality or emissions data, or on
strong evidence of source-receptor relationships. Detection of evidence of these pollutants does not necessarily
imply knowledge of specific concentration levels.
2. The effects sampler can be used to detect gross differences in pollution levels. This conclusion was
substantiated by the differences observed in the frequency distribution of pollutants at various classes of
stations, by comparison of pollutant levels with emission levels, and by correlations with air quality data. By
computing the frequency distribution of annual averages and comparing individual stations and/or areas to this
nationwide distribution, an indication of relative severity could be obtained. This procedure would have the
same limitations as those implied by the basic data; it would, however, provide a means of comparison
between stations for a variety of pollutant indicators.
3. Components of the sampler can provide evidence of air pollution effects. The most notable effects are
related to corrosion; however, damage to rubber and nylon was also noted. It was shown that corrosion was
enhanced by air pollutants, specifically sulfur dioxide. (The best indicator of corrosion was quarterly steel.) No
direct relationships were found to explain the amount of damage for specific pollutant levels.
4. The effects sampler currently has 18 components. Evaluation has shown, however, that some of the
components are redundant and other are not specific indexes of air pollution. Evaluation shows that the eight
components listed in Table 61 provide valid data relative to the pollutant or effect cited.
Table 6-1. COMPONENTS USED IN EFFECTS SAMPLING
Component
Saltation plate
Sticky paper
Dustfall
Quarterly steel
Fabric No. 3
Silver plate
Rubber strip
Monthly nylon
Pollutant or effect
Sulfur dioxide
Soiling potential, particulate
Soiling potential, settleable particulate
Corrosion
Oxides of nitrogen
Hydrogen sulfide
Oxidation potential
Acid aerosol
5. The effects network has limitations:
a. Exposure periods for the components vary from 7 days to 1 year, which makes it difficult to analyze
the results.
b. Air pollutants or their effects cannot be determined over short time intervals.
c. Data provided by some of the components are questionable in that specific knowledge of what they are
measuring is lacking.
d. Detailed knowledge of replicate sampling errors for the individual components is not available.
e. The network does not permit a detailed assessment of meteorological influences on the data.
6. The effects sampler is a valid measuring device for its original purpose. The network-or a modified version
of itcan provide the following information:
59
-------
a. Pollution problems or potential problems in areas where few data are available.
b. Preliminary information for further expenditure of resources.
c. Gross estimates of pollution levels for the pollutants described previously and continuing gross data in
an area over time.
d. Data from an individual station for comparison with frequency distributions of nationwide data as an
index of relative severity.
e. Data from the exposure of other promising static devices on a nationwide scale.
60
Conclusions
-------
7. REFERENCES
1. Vernon, W. H. J. A Laboratory Study of Atmospheric Corrosion of Metals. Trans. Farad. Soc. 31: 1668-
1700,1935.
2. American Association of Textile Chemists and Colorists. Effects of Atmospheric Contaminants on Light-
fastness Testing. American Dyestuff Reporter. 450-451, June 1958.
3. LaBarthe, J. Ten Thousand and One Customer Complaints. Text. Res. J., 24: 329, April 1954.
4. Slayin, V. S. Effect of Air Pollutants on Dyed Fabrics. J. Air Pollut. Contr. Ass., 13: 416-422, September
1963.
5. Greenburg, L., and M. B. Jacobs. Corrosion Aspects of Air Pollution. Amer. Paint J. 39: 64-78, July 1955.
6. Antler, M., and J. Gilbert. Effects of Air Pollution on Electric Contacts. J. Air Pollut. Contr. Ass. 13: 405-
415, September 1963.
7. Crabtree, J., and A. R. Kemp. Weathering of Soft Vulcanized Rubber. Ind. Engr. Chem. 38: 278-296, 1946.
8. Accelerated Ozone Weathering Test for Rubber. Anal. Chem., 18: 769-774, December 1946.
9. Gaughan, J. E. Ozone Cracking of Natural and Synthetic Rubber. Rubber World, 133(6): 803-808, March
1956.
10. Vega, T., and C. J. Seymour. A Simplified Method for Determining Ozone Levels in Community Air Pol-
lution Surveys. J. Air Pollut. Contr. Ass. 11: 28-44, January 1961.
11. Parker, A. Destructive Effects of Air Pollution on Material. (Sixth Des Voeux Memorial Lecture. Presented
at the Annual Conference of the National Smoke Abatement Society. Bournemouth, England, September
28,1965, p. 3-15.)
12. Huey,N. A. Lead Dioxide Estimation of Sulfur Dioxide Pollution, J. Air Pollut. Contr. Ass. September 1968.
13. Huey, N. A., and W. Waller. Field Evaluation of an Improved Sulfation Measurement System. National Air
Pollution Control Administration. Paper No. 69-133. Presented at the 62nd Annual Meeting of APCA,
June 1969.
14. ASTM Standard Method D-1739. Part 23. Philadelphia, American Society for Testing and Materials. 1968.
p. 505-508.
15. Nader, J. S. Dust Retention Effluences of Dustfall Collectors. J. Air Pollut. Contr. Ass. 8: 35-38.
16. Gruber, C. W., and G. A. Jutze. The Use of Sticky Paper in an Air Pollution Monitoring Program. J. Air
Pollut. Contr. Ass., 7: 115-117, August 1957.
17. Faulkner, Dean L., Charles E. Schumann, and Charles W. Gruber. Particulate Sampling by Adhesive-
Coated Materials. U.S. Public Health Service. Raleigh, N.C. Final Report. October 1969.
18. Sereda, P. J. Atmospheric Factors Affecting the Corrosion of Steel. Ind. Eng. Chem. 2: 157-160, February
1960.
19. Upham, J. B. Atmospheric Corrosion Study in the St. Louis-East St. Louis Metropolitan Area. Unpublished
NAPCA report. Undated.
20. Kendall, M. G. A Course in Multivariant Analysis. London, Charles Griffin and Co., 1961.
21. Harmon, H. H. Modern Factor Analysis. 2nd ed. Chicago, University of Chicago Press, 1967. Chapter 8.
61
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APPENDIX A.
LIST OF INTERSTATE SURVEILLANCE PROJECT
STATIONS BY STATE
-------
Table A-1. INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
143
146
246
247
90
92
101
102
261
268
129
208
209
210
91
93
94
95
96
239
240
27
21
183
184
185
243
8
9
68
130
135
145
231
64
ALABAMA
Phenix City - 1302 Broad Street, Phenix City, Alabama
Mobile - Mobile County Board of Health Building, 248 Cox Street, Mobile,
Alabama
ALASKA
Anchorage - 527 East Fourth Street, Anchorage, Alaska
Fairbanks - Third and Cushman Sts., Federal Post Office, Fairbanks, Alaska
ARIZONA
Davis Dam - Davis Dam, Bullhead City, Arizona
Yuma - Court House, Second Ave. and Second St., Yuma Arizona
Nogales - U.S. Quarantine Station, Nogales, Arizona
Douglas - U.S. Quarantine Station, Douglas, Arizona
Clifton - Court House, Clifton, Arizona
Phoenix - 4019 North 33rd Avenue, Phoenix, Arizona
ARKANSAS
Texarkana U.S. Post Office, Texarkana, Arkansas
Crossett Forth and Main, Crossett, Arkansas
West Memphis Fire Station No. 1, 7th and Thompson, W. Memphis, Arkansas
Ft. Smith Civic Auditorium, Parker-Wheeler Ave., Fort Smith, Arkansas
CALIFORNIA
Needles - City Hall, Front and G St., Needles, California
Calexico - Calexico Fire Department, Calexico, California
San Ysidro - Brown Field, Otay Mosa Road, San Ysidro, California
Oakland - Howden Building, 337 W. 17th St., Oakland, California
South Tahoe - City Hall, South Lake Tahoe, California
Los Angeles - 228 W. Palm, Burbank, California
Los Angeles - 434 S. San Pedro St., Los Angeles, California
COLORADO
Denver - 2105 Broadway, Denver, Colorado
CONNECTICUT
Greenwich - Port Chester Fire Station, Greenwich, Connecticut
Thompsonville - Pearl St., Thompsonville, Connecticut
Hartford Hartford, Connecticut
Pawcatuck - Pawcatuck Fire Headquarters, 33 Liberty Street, Pawcatuck,
Connecticut
Bridgeport - 274 Middle Street, Bridgeport, Connecticut
DELAWARE
Wilmington - City Hall, Tenth and King St., Wilmington, Delaware
Claymont - Fire Station No. 13, 3223 Philadelphia Pk., Claymont, Delaware
FLORIDA
Tampa - Fire Station, 17 E. Davi Blvd. and Cayuga, Tampa, Florida
Oneca - State Ranger Fire Tower, State Road 70 Oneca Florida
Broward - 2421 S.W. Sixth Avenue, Ft. Lauderdale, Florida
Pensacola - Plaza Bldg., Pace Blvd. and Fairfield Drive, Pensacola, Florida
Fernandina Beach - Amelia Light Station, Fernandina Beach, Florida
Appendix A. List of Interstate Surveillance Project Stations by State
-------
Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
232
233
131
132
134
141
142
241
242
71
74
75
26
46
54
55
56
57
58
136
137
138
139
228
258
259
40
42
44
52
53
149
263
59
201
203
227
FLORIDA (continued)
Fernandina Beach 4th and Ash, Fernandina Beach, Florida
Gainesville - University of Florida Campus, Gainesville, Florida
GEORGIA
Augusta 10001 Ballis Drive, Augusta, Georgia
Savannah City Hall, Bull and Bay Street, Savannah, Georgia
St. Marys - City Hall, St. Marys, Georgia
Rossville 1430-Suggs Street, Rossville, Georgia
Columbus 1958 8th Avenue, Columbus, Georgia
HAWAII
Honolulu - 1250 Punchbowl St., Honolulu, Hawaii
Hilo Mauna Loa Obs., Mauna Loa Volcano, Hilo, Hawaii
IDAHO
Coeur D'Alene - City Hall, Coeur D'Alene, Idaho
Lewiston St. Highway Garage, North-South Highway, Lewiston, Idaho
Lewiston - 1221 F Street, Lewiston, Idaho
ILLINOIS
Chicago 445 S. Plymouth Court, Chicago, Illinois
East St. Louis - 628 North 20th., East St. Louis, Illinois
Chicago - Taft School, 5625 W. Natoma, Chicago, Illinois
Calumet City - N. School, 755 Pulaski Road, Calumet City, Illinois
Hennepin Hennipin Grade School, Hennipin, Illinois
Rock Island - 1528 Third Avenue, Rock Island, Illinois
Moline City Hall, 619 Sixteenth Street, Moline, Illinois
Cicero Roosevelt School, 15th Street and 50th, Cicero, Illinois
Bedford Park - Public Works, 6535 S. Central, Bedford Park, Illinois
Chicago Heights - B. Township School, Dixie Highway and Tenth, Chicago
Heights, Illinois
Palatine - Palatine Township School, 1000 Quentin, Palatine, Illinois
East Dubuque Fire Department, 197 Sinsinawa, East Dubuque, Illinois
Cairo - Police Headquarters, City-County Building, Cairo, Illinois
Metropolis - Massac Hospital, Adkins Circle, Metropolis, Illinois
INDIANA
Jeffersonville - Fire Station No. 1, 8th and Wall, Jeffersonville, Indiana
Tell City - Tell and 12th Street, Tell City, Indiana
Evansville - 1065 W. Pennsylvania St., Evansville, Indiana
East Chicago - Pine Street and Broad, E. Chicago, Indiana
Hammond - 5925 Calumet Avenue, Hammond, Indiana
Gary - 1 Fire Station, Gary, Indiana
Charlestown - City Building, 701 Main Street, Charlestown, Indiana
IOWA
Davenport - 331 Scott, Davenport, Iowa
Sioux City - City Hall, 405 6th Street, Sioux City, Iowa
Council Bluffs - Fire Station No. 2, 27th St.-1st Ave., Council Bluffs, Iowa
Dubuque - City Garage, 14th and Elm, Dubuque, Iowa
INTERSTATE SURVEILLANCE PROJECT
65
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Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
47
87
88
204
39
41
43
67
106
154
161
260
124
213
214
215
216
217
218
219
176
193
111
150
151
177
182
190
191
192
34
35
162
163
164
166
KANSAS
Kansas City - 3rd and Richmond Sts., Kansas City, Kansas
Kansas City - Morse School, Miami and Baltimore, Kansas City, Kansas
Overland Park - D. Moody School, 10101 England, Overland Park, Kansas
Elwood - Elwood Fire Station, Kentucky and 6th St., Elwood, Kansas
KENTUCKY
Louisville - 7th St. and W. Jefferson, Louisville, Kentucky
Hawesville - Route 60 and 271, Hawesville, Kentucky
Owensboro - 1316 W. Fourth Street, Owensboro, Kentucky
Ashland - Kentucky State Bldg., 19th and Carter, Ashland, Kentucky
Frankfort - 275 E. Main Street, Frankfort, Kentucky
Covington - Post Office, 7th. and Scott, Covington, Kentucky
Henderson - Henderson City Health Dept., 438 5th St., Henderson, Kentucky
Paducah - Seventh and Washington, Paducah, Kentucky
LOUISIANA
Sulfur - Sulfur Health Unit, 201 Edgar, Sulphur, Louisiana
Shreveport 1866 Kings Highway, Shreveport, Louisiana
Bogalusa - Fire Station No. 2, Arkansas Street, Bogalusa, Louisiana
Vidalia - Fire Station, 500 Fifth Street, Vidalia, Louisiana
Bastrop Franklin and Cypress St., Bastrop, Louisiana
Tallulah - 400 E. Green Street, Tallulah, Louisiana
New Orleans Civil Court Building, Loyola-Poydras St., New Orleans,
Louisiana
Carville Power Plant, Roof of Hospital, Carville, Louisiana
MAINE
Eliot - Eliot Fire Station, 141 St., Route 103, Eliot, Maine
Madawaska - Fire Station, Main Street, Madawaska, Maine
MARYLAND
Cheverly - Health Department, Hospital Drive, Cheverly, Maryland
Cumberland - City Hall, N. Center and Frederick, Cumberland, Maryland
Bloomington - Bloomington Elementary School, Bloomington, Maryland
MASSACHUSETTS
Lawrence - Lawrence Exp. Station, 37 Shattuck St., Lawrence, Massachusetts
Springfield - 148 Taylor St., Springfield, Massachusetts
Attleboro - Park and Union St., Attleboro, Massachusetts
Fall River - 123 N. Main Street, Fall River, Massachusetts
Boston - Ford Building, Somerset and Ashburton Place, Boston, Massachusetts
MICHIGAN
Detroit - Bell Island Police Radio Station, Detroit, Michigan
River Rouge - Ann Visger Elementary School, 11121 W. Jefferson Street,
River Rouge, Michigan
Grosse lie - Wyandotte Chemical, Hennepin Island, Gross Me, Michigan
Livonia - Bentley High School, 15100 Hubbard, Livonia, Michigan
Sumpter Township - Hoffman Jr. High School, 50700 Willow Road,
Sumpter Township, Michigan
Port Huron - Port Huron Water Filter Plant, 1200 Pinegreen Avenue, Port
Huron, Michigan
66
Appendix A. List of Interstate Surveillance Project Stations by State
-------
Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
167
196
223
224
49
225
248
249
250
251
234
235
236
269
28
45
48
85
86
205
206
254
200
202
89
97
171
173
174
175
MICHIGAN (continued)
St. Clair - St. Clair State Police Post, St. Clair, Michigan
Dearborn Dearborn, Michigan
Sault St. Marie - Portage Street, Sault St. Marie, Michigan
Ann Arbor - School of Public Health, Ann Arbor, Michigan
MINNESOTA
Duluth - West Irst St., and 4th Avenue, Duluth, Minnesota
Winona Center Fire Station, 3rd and Laird, Winona, Minnesota
East Grand Forks - Fire Dept., 115 N. 4th East, Grand Forks, Minnesota
Moorhead 6th and Main, Moorhead, Minnesota
Ortonville Municipal Hospital, Eastvold Avenue, Ortonville, Minnesota
International Falls Customs Building, Highway 71-51, International Falls,
Minnesota
MISSISSIPPI
Pascagoula Fire Station No. 4, Pascagoula, Mississippi
Natchez Liberty Road and Sargent Prentiss Drive, Natchez, Mississippi
Vicksburg Central Fire Station, Vicksburg, Mississippi
Jackson 416 North State Street, Jackson, Mississippi
MISSOURI
St. Louis - 215 S. 12th Street, St. Louis, Missouri
St. Louis Hurck and Broadway, St. Louis, Missouri
Kansas City Police Garage, 1325 Oak Street, Kansas City, Missouri
Independence Independence City Health Department, 210 S. Main St.,
Independence, Missouri
Kansas City - U.M.K.C., 51st St. and Troost, Kansas City, Missouri
St. Joseph Southwestern Telephone Company, 10th and Jules St., St.
Joseph, Missouri
Joplin Joplin Municipal Building, 303 E. 3rd St., Joplin, Missouri
MONTANA
East Helena City Garage, E. Helena, Montana
NEBRASKA
South Sioux City - City Hall, 1617 Dakota Avenue, S. Sioux City, Nebraska
Omaha Omaha-Douglas County Health Dept., S. 42nd St., Omaha, Nebraska
NEVADA
Boulder City 500 Railroad Street, Boulder City, Nevada
Incline Village - Sewage Pump Station No. 1, Incline V. and Highway 50,
Incline Village, Nevada
NEW HAMPSHIRE
Lebanon Lebanon Fire Station, Lebanon, New Hampshire
Salem Central Fire Station, Main St., Salem, New Hampshire
Portsmouth Federal Building, 80 Daniel Street, Portsmouth, New Hampshire
Cannon Mountain Franconia Notch State Reservation, Cannon Mountain,
New Hampshire
NEW JERSEY
Mays Landing Mays Landing Meteorological Site, Mays Landing, New Jersey
INTERSTATE SURVEILLANCE PROJECT
67
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Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
2
3
16
17
18
229
98
99
100
103
104
4
5
19
20
22
23
24
25
29
30
144
178
194
264
265
266
267
31
32
156
237
238
197
198
68
NEW JERSEY (continued)
Perth Amboy - Perth Amboy Hospital, New Brunswick and Broad Head,
Perth Amboy, New Jersey
Elizabeth - Lombard Trucking Company, North Avenue, E. Elizabeth, New
Jersey
Penns Grove - Penns Grove Post Office, 56 W. Main St., Penns Grove, New
Jersey
Camden - Fire Station, Camden, New Jersey
Trenton - Courthouse, Trenton, New Jersey
Metuchen - Raritan Depot No. 236, Metuchen, New Jersey
NEW MEXICO
Shiprock - Fairgrounds Exhibit Hall, Route 666, Shiprock, New Mexico
Farmington - San Juan County Health Department, 620 S. Lake, Farmington,
New Mexico
Dulce - Public Housing Building, Dulce, New Mexico
Sunland Park - Sunland Park Elementary School, Sunland Park, New Mexico
Anthony Anthony Elementary School, Anthony, New Mexico
NEW YORK
Staten Island Willow Brook State School, Staten Island, New York
Brooklyn - Brooklyn Navy Yard, Main Guard Station, Brooklyn, New York
Mineola - Nassau County Government Registration Bldg., Mineola, New York
White Plains - Arch Stepinac High School, Mamaroneck Ave., White Plains,
New York
Albany - 84 Holland Avenue, Albany, New York
Niagara Falls - City Hall Building, 7th - Main Sts., Niagara Falls, New York
Buffalo - Public School No. 26, 24 Harrison, Buffalo, New York
Binghamton - Broome County Health Dept., 62-68 Water St., Binghamton,
New York
Petersburg Petersburg, New York
Albany - Grants Department Store, Downtown Store, Albany, New York
Long Island - Montauk Point, Long Island, New York
Ticonderoga - Junion-Senior High School, Calkins Place, Ticonderoga, New
York
Rooseveltown - U.S. Customs Building, Rooseveltown, New York
Cheektowaga - Municipal Building, Broadway and Union Roads, Buffalo,
New York
Buffalo - Biological Hazard Building, 666 Elm St., Buffalo, New York
Niagara Falls - City Hall, 7th and Main Sts., Niagara Falls, New York
Niagara Falls - Niagara Falls, New York
NORTH CAROLINA
Charlotte - Community Hospital, 801 S. Graham, Charlotte, North Carolina
Charlotte - Fire Station No. 11, 620 Moretz St., Charlotte, North Carolina
Spray - Center Elementary School, Virginia Avenue, Spray, North Carolina
Chapel Hill - Research Triangle, Chapel Hill, North Carolina
Chapel Hill - 311 Pittsboro, Chapel Hill, North Carolina
NORTH DAKOTA
Grand Forks - Water Treatment Plant, 4th and Franklin, Grand Forks, North
Dakota
Fargo - Civic Center, 201 N. 4th Street, Fargo, North Dakota
Appendix A. List of Interstate Surveillance Project Stations by State
-------
Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
6
36
37
38
61
64
66
70
155
220
221
207
211
69
79
81
82
83
10
11
12
13
14
15
230
186
187
188
189
33
133
199
244
245
Station location
OHIO
Cincinnati Central Avenue and Ann Street, Cincinnati, Ohio
Toledo Fire Station No. 12, Summit and Cleveland, Toledo, Ohio
Columbus Ohio Health Department, 1147 Chesapeaks, Columbus, Ohio
Youngstown No. 1 Fire Station, W. Federal and Belmont, Youngstown,
Ohio
Steubenville - Fire Station, 518 South St., Steubenville, Ohio
Marietta Fire House, City Building, Marietta, Ohio
Ironton State Highway Building, S. 6th and Clinton, Ironton, Ohio
Cincinnati 1055 Laidlaw, Cincinnati, Ohio
Cincinnati Library, 8th and Vine, Cincinnati, Ohio
Mingo Junction Fire Station, 501 Commercial St., Mingo Junction, Ohio
Steubenville - W.E. Fire House, 3700 Sunset Blvd., Steubenville, Ohio
OKLAHOMA
Miami - Will Rogers Jr. High School, Goodrich Blvd. E St., Miami, Okla.
Sallisaw Water Treatment Plant, Sallisaw, Oklahoma
OREGON
Corvallis - Chemical Engineering Bldg., 21st and Monroe, Corvallis, Oregon
The Dallas - County Health Department, 400 E. 5th, The Dallas, Oregon
Rainier - Rainier Elementary School, 3rd and C Sts., Rainier, Oregon
Portland - Communicable Service, 718 S.W. Burnside, Portland, Oregon
Portland Roosevelt High School, 6941 N. Central, Portland, Oregon
PENNSYLVANIA
Chester - Municipal Building, 5th-Walsh St., Chester, Pennsylvania
Philadelphia - Health Department, 500 S. Broad St., Philadelphia, Penn.
Philadelphia - Health Department Lab, 1501 E. Lycoming, Philadelphia,
Pennsylvania
Philadelphia - 2031 Race Street, Philadelphia, Pennsylvania
Easton City Hall, Ferry St. and Union, Easton, Pennsylvania
Sharon City Hall, Fire House, Sharon, Pennsylvania
Kintnersville Palisades High School, Route 611 N., Kintnersville, Penn.
RHODE ISLAND
Westerly - Police Station, 9 Union Street, Westerly, Rhode Island
Pawtucket - Fire Station, Roosevelt St., Pawtucket, Rhode Island
North Tiverton - Police Station, 232 Hilton Street, North Tiverton, Rhode
Island
Block Island - Block Island Airport, Block Island, Rhode Island
SOUTH CAROLINA
Rock Hill - Fire Station No. 1, Elizabeth Lane-E. Black St., Rock Hill, South
Carolina
North Augusta - N. Augusta Police Department, 400 B. Vista, North
Augusta, South Carolina
SOUTH DAKOTA
Sioux Falls - City Hall, 224 W. 9th St., Sioux Falls, South Dakota
Custer - Tepee Ranger Station, Route 16, Custer, South Dakota
Milbank - Rea Building, E. Highway 12, Milbank, South Dakota
INTERSTATE SURVEILLANCE PROJECT
69
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Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
107
108
109
110
140
147
148
105
115
116
117
118
119
120
121
122
123
125
126
127
128
212
262
179
180
181
112
114
157
158
160
172
195
222
72
73
70
TENNESSEE
Volunteer Arsenal (Chattanooga) - U.S. Volunteer Army Depot, Chattanooga,
Tennessee
Volunteer Arsenal (Chattanooga) - U.S. Volunteer Army Depot, Chattanooga,
Tennessee
Volunteer Arsenal (Chattanooga) - U.S. Volunteer Army Depot, Chattanooga,
Tennessee
Volunteer Arsenal (Chattanooga) - U.S. Volunteer Army Depot, Chattanooga,
Tennessee
Chattanooga - Post Office, Georgia Avenue and Ninth, Chattanooga, Tennessee
Memphis 814 Jefferson Avenue, Memphis, Tennessee
Bristol Court House, Bristol, Tennessee
TEXAS
El Paso - City County Health Unit, 118 W. Missouri, El Paso, Texas
Del Rio V/2 Mi. NW Downtown, Del Rio Courthouse, Del Rio, Texas
Eagle Pass - U.S. Quarantine Station, Eagle Pass, Texas
Laredo - Laredo Bridge, Convent Street at International Bridge, Laredo, Texas
McAllen - U.S. Quarantine Station, McAllen, Texas
Brownsville U.S. Quarantine Station, Brownsville, Texas
Austin - 820 East 53rd Street, Austin, Texas
Beaumont 950 Washington, Beaumont, Texas
Port Arthur - 246 Lake Shore Drive, Port Arthur, Texas
Orange - 701 Second Street, Orange, Texas
Brownwood 500 W. Commerce, Brownwood, Texas
Wichita Falls- Fire Station No. 10, 1215 N. Beverly, Wichita Falls, Texas
Sherman City Hall, Sherman, Texas
Texarkana - Texas Central Fire Station, 524 W. Third, Texarkana, Texas
Marshall - Court House, Peter Whetstone Square, Marshall, Texas
UTAH
Bullfrog - Glen Canyon, Bullfrog, Utah
VERMONT
Shoreman - West of Shoreham near La. Champlain, Shoreham, Vermont
White River Junction Hotel Coolidge, White River Junction, Vermont
Burlington - C. H. Goss Motor Company, 237 North Avenue, Burlington,
Vermont
VIRGINIA
Alexandria - 600 North Saint Asaph Street, Alexandria, Virginia
Leesburg - 18 North King Street, Leesburg, Virginia
Danville - Danville Community College Hill Building, Kemper Road, Danville,
Virginia
Bristol - Bristol, Va. Fire Hall, Lee St., Bristol, Virginia
Bluefield - City Municipal Building, S. College Avenue and Virginia Avenue,
Bluefield, Virginia
Luray - Park Headquarters, 5 mi. East of Luray on 211, Luray, Virginia
Blacksburg - Virginia Polytechnic Institute, Blacksburg, Virginia
Martinsville - Armory Road, Martinsville, Virginia
WASHINGTON
Spokane - KXLX TV, 500 Boone, Spokane, Washington
Pullman - Carpenter Hall, Spokane & College Sts., Pullman, Washington
Appendix A. List of Interstate Surveillance Project Stations by State
-------
Table A-1 (continued). INTERSTATE SURVEILLANCE PROJECT STATIONS
Station number
Station location
76
77
78
80
84
7
113
60
62
63
65
152
153
159
50
51
226
252
253
255
256
257
165
168
169
170
WASHINGTON (continued)
Clarkston - City Hall, 830 5th Street, Clarkston, Washington
Bellingham - 509 Girard Street, Bellingham, Washington
Seattle - 510 Smith Tower, 2nd Ave. and Yisler, Seattle, Washington
Longview - Department of Parks Bldg., 30 & Douglas, Longview,
Washington
Vancouver - Federal Building, 12th and Franklin, Vancouver, Washington
WASHINGTON, D.C.
Washington, D.C. - 1027 First St., N.W., Washington, D.C.
Washington, D.C. - 1100 Ohio Drive, Washington, D.C.
WEST VIRGINIA
Wheeling - WCB City County Building, 1500 Chapline St., Wheeling, West
Virginia
Weirton Weirton Community Center, Main and Cove Road, Weirton, West
Virginia
Parkersburg Camden-Clark Hos., Ann St., Parkersburg, West Virginia
Huntington Marshall University Warehouse, 5th & 19th St., Huntington,
West Virginia
Piedmont Fire Hall, 3rd Street, Piedmont, West Virginia
Keyser Science Building, Potomac State College, Keyser, West Virginia
Bluefield - Federal Office Building, Federal St.-Hi Street-Scott Street, Blue-
field, West Virginia
WISCONSIN
Superior Douglas County Court House, Hammond and Belknap, Superior,
Wisconsin
Kenosha Kenosha Technical Institute, 7th Ave. and 52nd St., Kenosha,
Wisconsin
La Crosse Fire Station No. 1, Monitor and Rose, La Crosse, Wisconsin
WYOMING
Cheyenne State Office Building, 22nd and Central, Cheyenne, Wyoming
Frannie Highway 310 and Main Street, Frannie, Wyoming
PUERTO RICO
Guaynabo Buchanan Military Reservation, Guaynabo, Puerto Rico
Salinas U.S. Army Reserve Center, Rt. 1, Salinas, Puerto Rico
El Yungue Ranger Station, Fajardo, Puerto Rico
CANADA
Ojibway, Ontario - Ooji-Martin Terminal Dock, Ojibway, Ontario
Sarnia, Ontario - Sar-Yackt Club, Ontario and Russell Sts., Sarnia, Ontario
Sarnia, Ontario Sar-Res. Found Trailer, Ontario-Russell Sts., Sarnia, Ontario
Windsor, Ontario - Win-Highway 3 and 114, Windsor, Ontario
INTERSTATE SURVEILLANCE PROJECT
71
-------
APPENDIX B.
DATA SUMMARY
-------
I
it
I
CA
Table B-1. DATA SUMMARY
State/city
ALABAMA
Phenix City
Mobile
ALASKA
Anchorage
Fairbanks
ARIZONA
Davis Dam
Yuma
Nogales
Douglas
Clifton
Phoenix
R KANSAS
Texarkana
Crossett
West Memphis
Fort Smith
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRQ
Zinc
Sam pi
size
1
1
1
1
1
1
1
1
1
1
1
1
1
Min
...
Max
...
Mean
1.7
1.0
0.3
0.2
0.4
1.6
0.3
0.3
0.5
2.6
0.9
1.1
3.8
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
14
41
2
3
4
3
0
3
7
11
13
8
15
A
Quarterly steel
Sample
size
2
4
2
4
2
2
3
4
4
4
4
4
4
4
2
1
3
4
2
4
4
Min.
4
3
62
47
1
1
1
1
1
1
1
0
0
0
8
1
5
3
7
5
)
Max.
8
7
96
86
3
1
2
2
2
4
2
8
25
42
9
1
13
11
16
19
R
Mean
6
6
79
59
2
1
1
2
2
2
1
2
7
11
8
9
7
12
10
4
Fabric No. 1
Sample
size
2
3
2
4
3
3
4
3
4
3
3
3
4
3
1
3
3
1
1
4
1
4
Min.
17.5
15.9
15.3
17.4
14.6
13.4
7.1
9.7
9.0
12.2
9.5
15.2
9.3
15.8
13.3
15.9
17.1
21.2
15.6
16.8
13.8
15.8
Max.
18.5
20.6
16.9
21.9
19.3
23.4
12.0
13.9
13.5
16.7
15.6
26.3
14.2
26.4
13.3
18.1
21.2
21.2
15.6
21.1
13.8
18.6
Mean
18.0
17.5
16.1
19.9
17.0
17.6
10.1
11.5
11.3
14.3
12.2
20.4
11.5
20.0
17.1
19.4
18.8
17.2
Fabric No. 2
Sample
size
2
2
4
3
3
4
3
1
1
Min.
1.2
1.5
1.0
1.6
1.4
1.4
1.4
1.2
0.5
Max.
1.3
2.2
1.3
2.2
5.1
2.6
3.5
1.2
0.5
Wean
1.2
1.8
1.1
1.8
3.8
2.0
2.4
-------
I
Table B-1 (continued). DATA SUMMARY
State/city
ALABAMA
Phenix City
Mobile
ALASKA
Anchorage
Fairbanks
ARIZONA
Davis Dam
Yuma
Nogales
Douglas
Clifton
Phoenix
ARKANSAS
Texarkana
Crossett
West Memphis
Fort Smith
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 3
Sample
size
2
2
2
3
3
3
4
2
3
3
4
2
4
4
1
3
3
2
1
3
1
4
Min.
16.2
21.8
22.7
21.6
20.8
17.3
8.2
13.8
14.9
16.4
11.8
22.3
11.2
16.2
14.5
16.3
20.4
21.0
15.4
22.2
10.4
14.7
Max.
16.3
22.2
23.6
25.5
36.0
28.1
24.0
14.9
16.4
18.8
21.3
22.9
14.1
23.8
14.5
21.1
22.7
23.4
15.4
24.5
10.4
20.3
Mean
16.2
22.0
23.2
23.9
26.8
21.7
14.2
14.4
15.5
17.8
15.6
22.6
12.0
18.7
18.2
21.9
22.2
23.3
18.6
Fabric No. 4
Sample
size
1
2
3
3
3
3
2
1
1
Min.
26.4
21.8
16.2
13.5
12.9
8.8
24.2
13.7
13.2
Max.
26.4
26.8
23.2
18.1
19.9
19.2
26.9
13.7
13.2
Mean
24.3
19.6
16.1
15.7
14.0
25.6
Fabric No. 5
Sample
size
3
4
2
2
3
3
2
2
1
2
2
4
3
Min.
9.8
10.0
6.5
3.6
9.6
12.3
7.4
8.4
12.2
11.2
6.4
7.8
9.0
Max.
12.5
15.6
7.3
6.6
15.9
14.1
9.9
12.9
12.2
15.5
15.9
16.0
14.6
Mean
10.7
12.4
6.9
5.1
13.0
13.1
8.6
10.6
13.4
11.2
11.9
11.7
Fabric No. 6
Sample
size
3
4
3
3
3
3
3
4
1
3
1
4
4
Min.
4.7
6.1
8.1
9.3
3.7
5.4
10.1
7.2
7.4
8.5
5.7
7.3
5.9
Max.
8.5
8.6
9.7
10.3
4.1
9.2
13.4
12.8
7.4
10.8
5.7
9.2
11.1
Mean
6.7
7.5
9.2
9.7
3.9
6.7
11.5
9.8
9.4
8.1
7.6
Fabric No. 7
Sample
size
3
4
2
2
4
3
2
4
1
3
1
4
4
Min.
8.7
4.9
7.7
5.6
2.5
4.4
6.0
7.0
5.0
5.4
9.1
6.8
4.0
Max
11.6
9.3
11.0
11.6
15.5
10.8
18.9
12.0
5.0
9.2
9.1
8.6
9.8
Mean
10.2
7.2
9.4
8.6
7.1
7.3
12.4
8.7
7.5
7.6
7.8
I
p
w
I
H
-------
-J
ON
Table B-1 (continued). DATA SUMMARY
State/city
ALABAMA
Phenix City
Mobile
ALASKA
Anchorage
Fairbanks
ARIZONA
Davis Dam
Yuma
Nogales
Douglas
Clifton
Phoenix
ARKANSAS
Texarkana
Crossett
West Memphis
Fort Smith
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
3
4
4
3
2
3
3
2
4
1
3
1
4
4
Min.
4.1
5.4
5.4
4.1
6.2
1.4
3.5
8.5
4.7
3.1
5.6
6.2
4.6
4.9
Max. Mean
10.0
9.8
9.8
8.9
6.2
14.3
8.9
15.3
6.5
3.1
7.2
6.2
10.3
8.9
! 7.0
7.9
7.9
6.8
6.2
7.6
8.4
11.9
5.6
6.5
8.0
6.4
Fabric No. 9
Sample
size
3
4
4
3
3
3
3
3
4
1
1
2
2
4
3
Min. Max.
12.4
16.8
16.8
9.8
17.2
5.4
7.9
17.5
13.6
8.0
18.6
19.7
21.7
16.5
18.5
29.3
33.3
26.9
24.0
11.8
15.1
Mean
22.0
26.0
19.5
20.6
7.7
11.4
23.6! 21 .3
22.9 16.3
8.0
18.6
26.8 23.2
37.0 29.4
29.6 ; 22.6
27.1 22.9
Quarterly nylon
Sample
size
2
4
1
4
3
2
A
3
A
4
4
4
4
1
1
3
2
2
4
4
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max. Mean
5
0
0
2
0
0
0
0
0
o
0
0
0
0
0
0
0
4
0
1
1
2.5
0
0.5
0
0
0
0
0
0
0
0
0
0
0
2.0
0
0.2
0.2
Monthly nylon
Sample ...
. Mm. Max.
size
7
12
5
12
7
7
11
12
12
11
9
11
11
12
5
3
9
10
2
5
2
12
2
11
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
I
0
4
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
Mean
0
0.3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Silver tarnishing
Sample
size
7
12
5
12
7
7
12
12
12
12
10
12
12
12
5
3
9
12
1
6
i 2
12
2
11
Min.
31
34
56
49
4
6
16
11
12
1 1
11
12
9
8
9
15
47
47
7
66
54
18
45
16
Max.
58
69
83
83
20
21
96
86
92
83
30
29
27
41
83
38
90
89
7
93
67
58
46
56
Vlean
43
47
71
10
12
57
52
38
32
19
21
15
19
71
64
81
39
32
8s
w
-------
§
Table B-1 (continued). DATA SUMMARY
State/city
ALABAMA
Phenix City
Mobile
ALASKA
Anchorage
c h i,c
rail D3DKS
ARIZONA
Davis Dam
Yuma
Nogales
Douglas
fl iftnn
\sl II tun
Phoenix
ARKANSAS
Texarkana
Crossett
West Memphis
Fort Smith
Year
1967
1968
1967
1968
1967
1968
1QR7
1 UU /
1968
1967
1968
1967
1968
1967
1968
1967
1968
1 QR7
1 OO /
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead perioxide candle
Sample
size
7
12
5
12
7
7
12
12
12
12
9
11
12
12
6
3
9
12
1
5
2
12
2
12
Min.
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
2.0
0.0
0.3
0.0
0.0
0.0
Max.
0.1
0.3
0.5
0.6
0.1
0.1
0.1
0.1
0.1
0.1
0.4
0.3
1.4
1.9
1.3
0.3
0.2
0.2
2.0
0.1
0.4
0.5
0.1
0.1
Mean
0.0
0.3
0.3
0.1
0.0
0.1
0.0
0.0
0.0
0.1
0.1
0.6
0.8
0.1
0.1
0.1
Lead plates
Sample
size
12
12
7
7
12
12
12
10
5
4
12
7
12
0.1 10
Min.
0
0
0
0
0
0
0
0
6
0
0
0
0
0
Max.
2
6
1
2
2
1
2
11
6
2
2
3
3
1
Mean
1
2
0
1
1
0
1
5
1
1
1
Dustfall
Sample
size
7
12
5
12
7
3
12
11
11
12
7
13
12
12
5
3
9
12
2
6
2
12
2
1 11
Min.
2.1
1.8
3.7
3.4
0.9
3.7
0.2
0.4
1.3
1.2
1.1
1.4
2.5
1.4
0.5
1.0
1.7
1.7
1.0
4.7
6.1
2.5
4.2
2.3
Max.
Mean
3.1
5.1
12.1
12.3
4.7
5.1
2.4
2.6
13.5
4.4
8.7
8.2
12.5
10.6
1.7
4.1
3.7
3.6
3.7
11.1
6.5
7.7
4.7
10.4
2.5
2.7
7.3
3.1
0.9
0.8
3.6
2.6
4.6
4.2
5.6
6.0
Sticky paper
Sample
size
7
12
6
12
5
6
11
11
12
11
10
12
12
12
5
i
3
i
2.5 9
2.7
11
1
7.6 5
3
5.4 ; 11
3
4.8 10
Min.
6
6
6
1
5
11
3
8
14
14
13
19
27
34
10
17
6
7
7
8
15
3
17
1
Max
20
39
36
49
29
54
34
66
78
64
60
62
74
79
28
20
34
47
7
29
70
48
70
42
Mean
12
26
12
22
27
21
26
38
36
36
42
51
54
16
21
...
23
20
Rubber cracking
Sample
size
30
51
23
52
27
25
52
47
50
48
32
52
50
50
21
12
38
52
7
27
9
50
10
45
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.383
.280
.249
.230
0
.260
.570
.527
.481
.464
.491
.411
.469
.429
.351
.197
403
.353
0
.212
0
301
.260
.335
Mean
.076
.089
..063
0
.260
.210
.158
.131
.136
.120
.167
.128
.137
.099
.040
.097
.095
1
r
n
w
e
o
-------
-J
oo
Table B-1 (continued). DATA SUMMARY
State/city
CALIFORNIA
Needles
Calexico
San Ysidro
Oakland
South Tahoe
Los Angeles
(239)
Los Angeles
(240)
COLORADO
Denver
:ONNECTICUT
Greenwich
Thompsonville
Hartford
Pawcatuck
Bridgeport
JELAWARE
Wilmington
Claymont
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1968
1967
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
0.3
0.2
0.5
0.4
0.9
0.8
0.9
0.8
0.6
3.5
0.5
2.4
2.4
2.2
4.6
2.6
2.6
3.3
5.6
3.4
2.6
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1
1
5
4
33
28
33
35
1
0
17
18
2
54
54
53
48
42
54
47
38
56
56
Quarterly steel
Sample
size
4
4
2
4
3
3
4
3
4
4
2
3
3
4
4
4
4
4
3
2
4
2
4
4
Min.
1
0
2
2
21
26
24
17
0
0
11
16
2
64
64
69
64
55
65
62
57
56
73
71
Max.
1
1
6
10
48
43
56
32
2
1
23
27
6
81
81
83
78
71
80
105
75
112
100
96
Mean
1
1
4
7
34
35
41
26
1
1
17
24
4
71
71
74
71
62
70
84
68
84
87
80
Fabric No. 1
Sample
size
4
3
2
1
3
4
4
3
3
3
2
2
3
4
4
4
1
4
1
4
3
3
4
4
4
4
i
Min. i Max.
j
8.0
11.6
11.9
14.9
14.7
17.4
12.4
15.4
10.0
15.2
18.8
23.2
14.8
12.8
12.8
16.6
15.8
12.3
14.9
16.1
17.8
18.0
13.0
14.9
12.7
14.2
11.6
14.1
14.0
14.9
18.1
20.4
17.6
19.9
14.3
16.6
21.0
23.6
20.0
17.3
17.3
20.5
15.8
19.6
14.9
21.8
22.7
22.2
19.2
23.4
18.1
?09
Mean
10.2
12.7
13.0
16.4
19.0
15.6
17.6
12.3
15.9
19.9
23.4
17.9
15.8
15.8
18.6
17.0
18.6
19.6
20.7
15.8
19.4
15.1
17.6
Fabric No. 2
Sample
size
4
2
3
4
4
Min.
1.1
3.3
0.8
1.7
0.8
4
4
1
1
4
4
2.5
2.5
1.8
3.6
Max.
2.4
4.9
2.3
3.8
3.6
5.3
5.3
1.8
3.6
1.9
6.2
1.4 | 2.9
Mean
2.0
4.1
1.5
2.8
2.1
3.6
3.6
3.7
2.2
13
"O
3
-------
H
W
JO
I
F
0
w
=5
2
Table B-1 (continued). DATA SUMMARY
State/city
CALIFORNIA
Needles
Calexico
San Ysidro
Oakland
South Tahoe
Los Angeles
(239)
Los Angeles
(240)
COLORADO
Denver
CONNECTICUT
Greenwich
Thompsonville
Hartford
Pawcatuck
Bridgeport
DELAWARE
Wilmington
Claymont
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRQ
Fabric No. 3
Sample
size
4
3
2
2
3
4
4
3
4
4
2
2
4
4
4
4
1
3
1
3
3
3
4
4
4
A
Mm.
10.0
17.5
18.5
20.3
20.0
23.5
22.0
28.8
8.1
10.8
52.3
52.2
17.0
24.1
28.9
39.8
32.5
31.1
38.9
41.7
34.5
36.5
26.0
37.2
13.6
tO Q
Max.
16.4
21.4
18.8
25.3
21.9
31.9
29.8
34.8
14.0
12.8
62.8
55.5
23.0
30.7
40.3
43.7
32.5
40.3
38.9
49.2
37.3
44.5
37.3
39.2
32.6
?« 1
Mean
13.9
19.7
18.6
22.8
20.7
26.7
25.1
32.0
11.0
12.2
57.6
53.8
20.6
26.5
35.5
42.0
35.2
44.9
36.0
41.2
32.6
38.3
25.3
1& 1
Fabric No. 4
Sample
size
4
2
2
3
3
4
3
1
1
4
3
Min.
12.5
11.2
24.4
10.3
11.3
7.8
10.7
17.6
11.8
8.7
11.7
Max.
21.5
15.1
27.3
16.7
16.2
15.2
28.9
17.6
11.8
25.8
30.6
Mean
16.2
13.2
25.8
13.9
13.0
11.0
20.6
16.1
19.6
Fabric No. 5
Sample
size
3
1
4
3
4
2
2
3
4
3
4
3
2
4
*
Min.
9.1
9.0
10.3
6.8
01.2
7.4
9.9
4.3
8.0
7.5
5.0
9.7
7.6
5.5
s n
Max.
15.4
9.0
19.1
7.4
11.7
21.1
16.4
9.0
14.9
15.3
12.8
18.1
13.3
15.6
n s
Mean
12.8
14.7
7.1
10.9
14.2
13.2
6.3
11.0
11.9
8.3
12.6
10.4
9.6
m A.
Fabric No. 6
Sample
size
1
3
4
3
4
2
2
3
4
4
4
3
3
4
A
Min.
11.6
8.9
6.0
5.7
5.4
8.8
7.8
9.1
5.0
4.8
8.9
6.4
8.2
7.1
R 7
Max
11.6
13.3
8.9
9.1
9.9
9.0
15.3
11.2
10.0
11.8
13.2
10.2
10.4
11.7
a Q
Mean
10.4
6.8
7.0
6.8
8.9
11.6
9.9
8.1
8.4
11.4
8.7
9.2
8.9
7 n
Fabric No. 7
Sample
size
1
2
4
3
4
2
2
4
4
4
4
3
2
4
A
Min.
10.6
3.2
4.4
5.0
4.2
5.7
6.8
7.1
3.6
3.1
5.3
3.7
6.0
7.2
O 7
Max.
10.6
13.1
8.9
8.8
5.8
7.1
13.7
16.3
12.7
12.9
17.1
9.8
8.6
11.2
1 n A
Mean
8.2
6.5
7.0
5.1
6.4
10.2
12.0
8.0
7.2
11.9
7.1
7.3
8.8
C Q
SO
-------
oo
o
Table B-1 (continued). DATA SUMMARY
State/city
CALIFORNIA
Needles
Calexico
San Ysidro
Oakland
South Tahoe
Los Angeles
(239)
Los Angeles
(240)
:OLORADO
Denver
:ONNECTICUT
Greenwich
Thompsonville
Hartford
Pawcatuck
Bridgeport
JELAWARE
Wilmington
Claymont
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
i size
I
Min.
2 5.3
2 9.6
4
3
3
2
2
4
4
2
4
3
3
4
4
7.2
5.1
4.7
13.1
10.6
6.0
6.3
8.1
6.4
9.5
4.5
4.8
5.4
Max.
8.5
9.8
15.8
6.4
7.9
13.6
16.4
9.8
15.4
10.5
9.8
18.2
13.7
7.3
10.1
Mean
6.9
9.7
11.7
5.9
5.9
13.4
13.5
7.6
10.3
9.3
8.6
14.7
9.8
6.0
7.6
Fabric No. 9
Sample
size
3
1
4
3
3
2
2
4
4
3
4
3
3
4
4
Min.
7.2
13.2
17.0
17.3
6.8
27.6
Max.
16.6
13.2
24.3
20.3
31.0
39.7
36.0 38.9
[
1
13.0
15.1
12.3
16.7
16.8
17.5
12.5
13.1
21.6
33.9
33.2
33.2
35.3
29.7
31.2
31.8
Mean
10.3
21.4
18.5
16.2
33.6
37.4
16.6
22.5
23.9
23.8
23.7
24.6
22.8
22.6
Quarterly nylon
Sample
size
4
4
4
4
3
3
4
4
3
3
3
3
2
3
4
4
1
4
4
3
3
2
4
4
3
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
8
0
5
0
16
31
12
0
0
Max. Mean
0
3
0
0
0
0
0
0
0
0
0
1
0
0
4
17
8
17
31
7
57
35
86
14
1
0
0.8
0
0
0
0
0
0
0
0
0
0.3
0
0
2.5
5.0
5.2
15.0
2.3
30.0
33.0
58.7
8.8
0.3
Monthly nylon Silver tarnishing
Sample
size
11
12
12
12
10
12
12
12
10
12
9
9
11
12
12
12
3
12
1
12
1
11
3
8
12
12
12
12
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
2
0
2
0
0
0
0
1
0
0
Max.
0
0
0
0
1
0
0
0
2
0
3
0
0
1
1
3
8
6
2
10
2
1
2
49
28
78
1
0
Sample
Mean sjze
0
0
0
0
0.1
0
0
0
0.2
0
0.3
0
0
0.1
0.2
1.0
2.0
3.0
0.1
24.0
8.7
20.0
0.3
0
12
12
12
12
12
12
12
11
7
12
9
9
10
6
12
12
2
12
2
12
12
7
11
12
12
' 12
Min.
8
5
44
34
31
27
21
39
1
1
52
61
13
19
43
37
32
30
35
36
24
39
65
65
37
60
Max.
30
39
91
95
55
60
76
66
55
12
88
76
45
48
64
68
53
70
55
56
61
65
89
83
92
89
Mean
15
15
68
70
42
46
49
51
18
5
62
66
27
32
55
; 52
45
46
39
56
80
74
67
77
S8
CO
s?
p
-------
Table B-1 (continued). DATA SUMMARY
State/city
Year
CALIFORNIA
Needles 1967
Calexico
San Ysidro
Oakland
South Tahoe
Los Angeles
(239)
Los Angeles
(240)
COLORADO
DGnvsr
CONNECTICUT
frppnwirh
Thompsonville
MartforH
rial I HJI U
D L.
rSWCaTUCK
Bridgeport
DELAWARE
Wilmington
Claymont
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1Qfi7
1 S\J 1
1968
1967
1968
1QR7
1 sy\J /
1968
1QR7
1 "D /
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample ' ...
.. Mm.
size
10
11
12
12
19
i ^
12
19
1 £.
12
m
1 U
11
8
8
12
12
19
I £.
12
3
10
11
1
1
12
6
12
12
12
12
0.0
0.0
0.0
0.0
n n
\j,\j
0.0
n n
\j.\j
0.0
n n
Max.
0.1
0.1
0.2
0.2
n 6.
v.*+
0.5
n R
\j,\j
0.5
n 1
\j.\j *j. i
0.0 0.1
I
0.0
0.0
0.0
0.0
n R
U.3
0.1
0.7
0.4
1 ^
i .0
0.5
n R
U.D
0.2
1.0
0.8
0.7
0.7
0.2
0.3
Mean
0.0
0.1
0.1
0.1
01
. 1
0.1
n 7
u.o
0.2
n n
\j.\j
0.0
0.1
0.4 | 0.2
0.5
0.6
9 n
£..\J
2.0
1.3
2.2
9 1
£.,0
3.2
n R
\j.\j
1.3
2.9
3.0
3.3
2.3
2.6
0.3
0.2
1.0
0.8
0.9
1.5
0.7
1.6
1.8
1.6
1.3
1.2
Lead plates
Sample
size
11
12
11
11
11
9
9
8
11
12
9
9
6
12
12
Min.
0
0
0
0
0
0
1
0
2
3
6
2
0
5
3
Max.
0
2
2
2
0
2
3
3
14
15
19
8
18
23
Mean
0
0
0
1
0
1
2
2
6
6
12
5
10
12
Dustfall
Sample
size
11
12
12
in
1 U
11
1 9
1 £.
10
Q
O
12
9
9
19
1 £.
11
19
1 £.
12
3
12
0
£.
12
i
i
11
7
12
12
12
17 9 12
Min.
0.8
1.1
n R
u.o
2.5
n a.
U.*T
1.0
2 A
.*+
2.6
07
./
0.4
2.5
3.7
<; &.
-------
00
10
Table B-1 (continued). DATA SUMMARY
State/city
FLORIDA
Tampa
Oneca
B reward
Pensacola
Fernandina Beach
(232)
Fernandina Beach
(231)
Gainesville
3EORGIA
Augusta
Savannah
St. Marys
Rossville
Columbus
1AWAII
Honolulu
Hilo
DAHO
Coeur d'Alene
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
2.0
1.4
5.1
1.3
2.5
1.8
4.9
2.1
0.9
1.2
1.9
2.3
6.3
2.5
0.8
4.0
0.8
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
64
54
27
31
21
16
28
38
20
24
19
66
41
64
24
12
28
10
16
Quarterly steel
Sample
size
:
3
3
3
4
2
3
3
2
2
3
4
3
4
3
4
2
4
2
3
3
3
4
4
Min.
79
72
26
28
30
28
37
18
Max.
114
87
39
46
76
115
61
53
57 | 73
I
65
16
14
12
70
53
68
66
0
16
4
5
34
1
1
3
89
23
27
19
103
66
90
132
29
29
6
16
61
4
9
15
Mean
97
80
33
38
58
57
49
37
63
77
20
20
15
88
58
80
91
15
21
5
10
45
3
4
10
Fabric Mo. 1
Sample
size
4
4
3
4
3
2
2
3
3
3
3
3
4
3
4
3
3
2
4
1
2
4
4
4
1
Min.
17.3
22.5
14.8
17.7
14.4
14.4
17.6
19.8
16.7
18.0
15.8
13.4
16.4
17.6
20.1
14.4
18.3
19.8
16.4
18.0
10.8
15.4
12.9
11.7
16.7
Max.
21.9
26.4
18.8
23.4
16.9
19.0
19.3
22.9
21.1
22.1
21.3
17.3
20.6
22.5
23.2
18.8
22.4
26.5
23.2
18.0
19.1
21.6
21.0
14.7
16.7
Wean
19.6
24.6
7.4
20.0
15.4
16.7
18.4
21.7
19.3
20.2
19.4
15.8
18.8
19.8
21.7
17.3
20.5
23.2
20.3
17.4
17.0
16.1
13.0
Fabric No. 2
Sample
size
4
3
3
2
3
3
3
2
1
4
Win.
0.8
0.9
0.9
1.7
1.0
0.7
0.9
1.5
1.2
1.2
t/lax.
2.0
1.1
2.5
4.6
2.7
2.6
1.1
4.2
1.2
5.2
i/lean
1.3
1.0
1.7
3.2
1.6
1.4
1.0
2.8
2.4
I
i/a
-------
Table B-1 (continued). DATA SUMMARY
State/city
FLORIDA
Tampa
Oneca
B toward
Pensacola
Fernandina Beach
(231)
Fernandina Beach
(232)
Gainesville
GEORGIA
Augusta
Savannah
St. Marys
Rossville
Columbus
HAWAII
Honolulu
Hilo
IDAHO
Coeur d'Alene
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QKR
Fabric No. 3
Sample
size
4
4
3
3
3
3
2
3
3
3
3
3
4
3
4
3
3
2
4
1
3
4
3
4
i
Min.
12.2
21.4
13.7
16.9
12.9
7.1
23.9
23.2
21.9
20.7
19.0
14.1
22.3
19.6
19.6
13.3
22.0
11.1
19.5
15.1
17.7
13.1
6.8
11.2
1R 7
Max.
Mean
20.1 16.8
26.8 24.4
23.2 18.6
27.2 1 21 .8
18.2 14.8
24.3 17.6
24.4 24.2
26.3 24.6
23.2
23.3
26.0
21.3
24.4
23.3
26.9
21.5
23.1
14.0
24.0
15.1
24.6
38.0
12.0
12.9
1R 7
22.7
21.9
22.0
18.1
23.2
21.3
24.2
17.3
22.6
12.6
21.8
21.2
23.6
9.0
12.0
Fabric No. 4
Sample
size
4
2
2
2
2
2
2
1
1
4
Min.
20.8
22.1
18.8
26.4
21.5
21.7
23.2
26.4
28.1
11.8
Max.
24.5
27.5
22.3
27.4
28.0
25.8
31.5
26.4
28.1
16.6
Mean
22.9
24.8
20.6
26.9
24.8
23.8
27.4
14.2
Fabric No. 5
Sample
size
4
3
2
3
3
3
3
4
4
3
4
2
2
3
3
Min.
10.1
11.4
4.9
10.6
13.9
13.5
11.8
7.6
9.0
12.9
9.4
5.8
9.3
8.5
7 4
Max.
15.1
15.8
10.8
14.4
16.6
15.9
17.6
15.2
14.8
17.1
15.2
11.5
10.2
11.6
inn
Mean
12.6
13.0
7.8
12.8
15.4
14.5
14.6
11.6
12.1
15.1
12.4
8.6
9.8
9.6
R K
Fabric No. 6
Sample
size
4
4
2
2
3
3
3
4
4
3
4
3
3
4
1
Min.
5.8
4.1
4.9
6.3
4.4
4.9
3.5
7.5
5.6
3.8
5.2
5.1
5.7
2.7
R Q
Max
9.6
5.8
9.2
7.5
6.6
7.9
8.2
14.9
10.3
9.4
8.2
12.0
11.2
12.6
R Q
Mean
7.8
5.0
7.0
6.9
5.2
6.8
5.6
9.8
7.7
6.4
6.5
7.8
8.0
6.7
Fabric No. 7
Sample
size
4
4
3
3
2
3
3
4
4
3
4
2
2
3
)
Min.
3.5
1.9
3.7
6.9
5.0
2.8
1.9
2.1
4.3
2.5
6.9
9.1
5.5
2.4
R B
Max
13.4
7.1
7.6
11.2
5.4
6.5
6.5
8.8
12.8
9.2
12.7
12.5
5.9
6.1
K n
Mean
8.6
4.3
5.1
9.5
5.2
4.3
3.9
4.8
8.3
5.5
9.2
10.8
5.7
3.9
K Q
m
I
C/5
I
PI
2
o
en
a
w
o
00
-------
Table B-1 (continued). DATA SUMMARY
State/city
FLORIDA
Tampa
Oneca
B reward
Pensacola
Fernandina Beach
(231)
Fernandina Beach
(232)
Gainesville
3EORGIA
Augusta
Savannah
St. Marys
Rossville
Columbus
IAWAII
Honolulu
Hilo
DAHO
Coeur d'Alene
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
T968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
3
3
3
3
3
3
4
4
3
4
3
3
4
Min.
4.9
6.2
7.0
7.4
7.4
Max.
12.7
9.4
12.3
8.9
18.1
7.1 11.0
i
9.3. 13.4
3.8
6.9
12.1
5.2
4.6
5.8
4.1
11.7
9.4
18.1
10.5
12.2
10.7
15.0
Mean
9.1
8.0
9.6
8.4
13.6
9.1
10.8
7.4
8.1
14.8
7.3
8.6
8.8
9.6
Fabric No. 9
Sample ...
size Mln'
4
4
2
3
3
3
3
4
4
3
4
3
4
4
1
18.6
17.8
21.6
21.9
26.4
23.2
17.0
13.3
19.0
23.0
16.3
12.4
18.8
8.9
20.2
Max.
32.0
35.2
27.1
35.9
33.0
31.7
33.4
30.0
32.4
31.3
30.7
21.3
31.7
32.7
20.2
Mean
26.2
28.8
24.4
29.2
30.0
28.4
26.1
22.8
28.4
28.2
21.5
15.8
24.8
18.8
Quarterly nylon
Sample ...
size !Mm-
4
4
4
4
2
4
2
3
3
3
3
3
4
3
4
2
3
2
3
3
3
3
3
3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
2
4
2
2
2
2
3
2
1
1
0
0
3
3
0
0
2
0
0
1
2
0
3
2
Mean
1.0
1.2
0.5
1.0
1.0
0.5
1.5
1.0
0.3
0.3
0
0
0.8
1.7
0
0
0.7
0
0
0.3
0.7
0
0.2
1.3
Monthly nylon
Sample
size
12
12
8
12
7
12
6
11
11
10
9
9
12
12
8
12
6
12
7
12
9
8
11
9
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
Max.
3
3
0
0
3
1
1
1
3
0
1
0
0
1
0
0
0
1
0
0
0
2
0
1
2
Mean
0.2
0.2
0
0
0.4
0.1
0.2
0.1
0.3
0
0.1
0
0
0.1
0
0
0
0.2
0
0
0
0.1
0
0.2
0.3
Silver tarnishing
Sample
size
12
12
9
12
9
12
6
11
10
8
10
9
12
9
12
8
12
7
12
7
11
9
8
11
11
Min.
75
59
31
33
31
30
40
53
71
87
69
49
52
64
56
67
80
42
32
23
29
22
13
5
2
Max.
94
95
60
67
60
55
77
79
91
96
86
82
87
90
89
95
95
70
73
57
78
41
72
19
24
Wean
83
84
51
48
51
44
64
67
84
93
78
66
73
74
74
84
89
52
53
36
42
31
33
9
9
I
-------
Table B-1 (continued). DATA SUMMARY
State/city
FLORIDA
Tampa
Oneca
Broward
Pensacola
Fernandina Beach
(231)
Fernandina Beach
(232)
Gainesville
GEORGIA
Augusta
Savannah
St. Marys
Rossville
Columbus
HAWAII
Honolulu
Hilo
IDAHO
Coeur d'Alene
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
19RR
Lead peroxide candle
Sample
size
12
12
8
12
7
11
6
12
10
10
10
9
11
9
12
9
11
7
12
7
12
9
6
12
19
Min.
0.6
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
no
Max.
1.4
1.5
0.5
0.2
0.2
0.2
0.3
0.3
0.7
0.8
0.2
0.3
0.4
0.9
1.3
0.6
0.6
0.4
0.5
0.1
0.3
0.5
0.0
0.3
0.?
Mean
0.9
0.8
0.1
0.1
0.1
0.1
0.2
0.1
0.2
0.3
0.0
0.1
0.2
0.6
0.5
0.2
0.3
0.2
0.2
0.0
0.1
0.3
0.0
0.1
0.1
Lead plates
Sample
size
11
8
10
11
4
10
6
11
12
12
12
12
8
8
Min.
3
0
0
0
0
0
0
0
0
0
0
0
0
0
1? n
Max.
8
2
2
2
3
5
1
2
6
5
4
2
4
2
}
Mean
5
0
1
1
2
0
1
3
2
1
1
2
0
n
Dustfall
Sample
size
12
12
8
11
8
12
5
12
Min.
2.9
2.4
0.9
0.7
1.0
0.9
2.2
2.6
8 ' 0.7
8
9
8
12
8
11
7
11
7
12
7
12
8
8
12
m
1.9
0.3
1.7
1.9
4.2
2.5
1.6
1.2
4.3
3.1
1.2
1.1
1.3
0.1
2.5
7 7
Max.
9.8
17.4
4.7
3.4
6.0
6.2
6.6
7.3
13.7
9.5
15.5
4.0
3.3
9.1
14.9
9.0
6.6
6.0
11.3
4.2
4.9
3.2
0.5
16.1
19 R
Mean
5.0
6.1
2.1
2.3
3.5
3.0
4.1
4.7
3.9
5.4
2.6
2.6
6.2
5.2
4.5
4.5
5.3
7.2
2.4
2.2
2.3
0.2
5.7
4 Q
Sticky paper Rubber cracking
Sample
size
12
11
8
5
9
10
5
7
9
8
9
9
12
9
12
8
8
6
12
6
12
9
8
11
7
Min.
11
11
0
1
4
8
4
8
1
7
1
2
11
10
12
1
3
1
9
2
1
16
1
6
n
Max.
43
54
16
24
39
52
18
20
62
47
33
27
41
54
66
34
37
10
40
4
43
57
5
31
57
.. Sample
Mean size
30
33
6
20
34
14
14
24
12
9
14
32
37
11
23
4
17
3
12
38
2
15
50
51
32
32
33
i 46
21
40
41
35
45
38
50
37
50
33
41
28
50
27
47
38
34
28
1Q
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
n
Max
.328
.338
.224
.368
.295
.343
.322
.404
.280
237
297
270
353
381
345
272
376
184
310
295
275
246
0
280
1RA
Mean
.132
.098
.080
.124
.130
.108
.106
.087
.095
.083
.124
.073
.126
.101
.103
.130
.062
.073
.082
.071
.077
0
.101
I
I
r
o
w
a
8
H
oo
-------
oo
OS
Table B-1 (continued). DATA SUMMARY
State/city
IDAHO (continued)
Lewiston (74)
Lewiston (75)
ILLINOIS
Chicago (26)
East St. Louis
Chicago (54)
Calumet City
Hennipen
Rock Island
Moline
Cicero
Bedford Park
Chicago Heights
(138)
Palatine
East Dubuque
Metropolis
Cairo
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.0
2.4
0.7
3.5
6.4
5.2
2.7
3.3
3.0
2.4
1.1
1.1
1.3
0.8
1.5
4.6
3.4
0.9
1.4
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
28
21
8
10
38
31
44
45
34
37
31
24
19
29
21
31
35
40
23
28
Quarterly steel
Sample
size
4
3
4
4
4
4
4
3
4
1
4
4
4
3
4
3
4
2
2
3
2
4
2
2
2
3
1
1
1
Min.
8
7
2
2
23
30
68
62
50
44
52
46
30
35
4
22
5
9
72
50
60
54
66
72
33
36
41
63
63
Max.
38
35
25
19
102
83
82
73
86
44
124
83
55
49
39
36
70
30
81
104
65
90
73
140
38
44
41
63
63
Mean
26
18
11
10
62
50
72
69
62
80
65
46
41
24
31
33
20
76
78
62
72
70
106
36
40
Fabric No. 1
Sample
size
4
4
4
4
4
4
4
4
4
3
2
4
4
3
4
3
4
4
2
2
2
4
2
4
2
3
4
1
2
Min.
11.4
15.9
11.0
13.9
14.0
15.4
15.0
23.0
13.5
15.8
16.4
19.5
14.8
17.7
17.0
21.0
15.6
14.9
10.6
18.6
16.7
17.6
17.5
19.0
17.4
16.8
18.0
23.7
17.0
Max.
14.4
16.8
14.5
17.0
18.4
21.9
21.2
25.7
17.8
19.4
19.0
23.6
16.6
20.7
19.6
21.8
18.4
18.4
16.2
21.3
19.1
22.6
18.2
22.8
18.0
22.5
20.1
23.7
187
Mean
12.5
16.3
12.0
15.8
16.2
18.6
18.4
24.0
15.8
17.4
17.7
21.4
15.9
18.9
18.4
21.4
17.0
17.3
13.4
20.0
17.9
20.0
17.8
20.9
17.7
19.5
19.0
17.8
Fabric No. 2
Sample
size
4
4
4
4
4
3
4
4
4
3
2
2
2
Win.
0.9
0.9
5.9
1.8
2.8
4.9
0.9
1.3
1.9
2.7
4.9
2.3
2.6
Max.
3.7
5.9
12.2
6.3
7.5
10.1
3.3
6.8
8.6
3.8
8.5
3.2
4.6
Mean
2.4
2.9
9.5
3.6
4.6
8.1
1.8
3.5
4.6
3.4
6.7
2.8
3.6
I
03
OS
V)
-------
Table B-1 (continued). DATA SUMMARY
State/city
IDAHO (continued)
Lewiston (74)
Lewiston (75)
ILLINOIS
Chicago (26)
East St. Louis
Chicago (54)
Calumet City
Hennepin
Rock Island
Moline
Cicero
Bedford Park
Chicago Heights
(138)
Palatine
East Dubuque
Metropolis
Cairo
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRQ
Fabric No. 3
Sample
size
4
4
3
4
4
4
4
4
4
2
3
4
4
3
4
2
4
4
3
2
2
3
2
3
2
3
1
1
1
Min.
12.0
14.6
12.1
17.1
35.4
47.9
16.9
18.7
23.1
32.8
18.1
25.0
9.2
15.0
10.1
20.7
12.2
18.5
17.7
39.5
26.4
33.5
18.0
23.1
16.7
21.6
20.2
24.2
ISt Q
Max.
17.5
19.3
18.5
20.9
48.6
54.0
22.4
29.3
40.1
36.8
26.4
33.2
19.6
21.9
18.8
22.5
20.0
20.1
39.5
44.2
29.5
43.7
25.0
27.3
24.7
27.8
20.2
24.2
18 Q
Vlean
15.4
16.7
14.6
18.7
42.8
50.7
19.6
25.4
29.8
34.8
20.9
28.0
14.9
17.5
15.0
21.6
16.5
19.3
28.9
41.8
28.0
37.0
21.5
24.5
20.7
24.1
Fabric No. 4
Sample
size
4
4
3
4
4
3
3
4
4
3
2
2
2
Min.
9.0
7.8
7.8
10.9
11.0
12.9
16.5
10.6
11.0
12.4
11.4
13.4
15.7
Max.
17.6
15.1
14.5
23.6
29.1
26.0
25.8
22.7
19.1
22.9
22.7
25.1
27.2
Mean
13.6
11.8
11.1
16.4
18.1
20.1
21.7
15.9
15.0
15.9
17.0
19.2
21.4
Fabric No. 5
Sample
size
4
4
4
4
3
4
3
3
4
4
4
3
2
1
>
Min.
4.9
3.6
2.3
5.5
5.4
6.7
9.7
6.3
7.8
5.1
6.5
7.5
7.9
15.1
in i
Max.
14.5
10.8
5.8
14.3
10.7
15.9
16.3
12.5
13.7
12.2
14.4
14.3
12.2
15.1
n 1
Mean
9.7
7.6
4.0
9.3
7.9
10.4
11.9
10.3
10.8
8.3
10.4
10.4
10.0
11 R
Fabric No. 6
Sample
size
3
3
4
3
3
4
3
3
3
2
3
4
4
3
1
7
Min.
6.5
6.3
13.0
8.3
9.4
7.8
5.2
8.5
7.2
11.3
9.9
8.8
9.8
6.1
8.2
B A
Max.
8.7
7.8
17.7
10.9
18.6
15.7
11.0
14.4
12.1
17.5
13.3
11.8
13.6
10.0
8.2
no
Mean
7.3
6.8
14.8
9.5
12.6
12.3
7.7
10.7
8.9
14.4
11.5
9.9
11.6
7.6
Q Q
Fabric No. 7
Sample
size
3
4
4
3
4
4
2
4
4
2
4
4
3
o
Min.
6.1
6.5
9.9
4.6
8.9
7.6
10.6
7.2
4.6
11.8
7.2
7.8
9.6
A 0
Max
12.8
10.7
22.1
12.9
14.5
12.9
10.8
11.3
15.1
17.9
20.0
14.2
15.6
1 n o
Mean
10.2
8.7
15.3
10.1
12.0
9.6
0.7
9.0
9.5
4.8
4.2
0.0
2.2
~t O
=
CW
M
8
w
r
n
w
n
00
-------
00
00
Table B-1 (continued). DATA SUMMARY
State/city
IDAHO (continued)
Lewiston (74)
Lewiston (75)
ILLINOIS
Chicago (26)
East St. Louis
Chicago (54)
Calumet City
Hennepin
Rock Island
Moline
Cicero
Bedford Park
Chicago Heights
(138)
Palatine
East Dubuque
Metropolis
Cairo
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
3
4
4
4
4
4
2
3
4
2
4
4
3
2
1
2
Min.
2.9
3.9
6.4
5.5
5.3
5.0
5.3
4.9
2.7
7.0
5.3
4.6
6.1
3.2
7.9
8.8
Max
6.7
9.2
13.5
8.1
8.7
9.7
7.7
6.2
6.6
12.4
10.7
9.7
10.0
10.9
17.9
18.7
Mean
5.1
6.4
8.8
7.1
7.8
8.1
6.5
5.7
5.2
9.7
7.8
7.6
7.5
7.0
13.8
Fabric No. 9
Sample
size
4
4
4
4
3
4
3
3
4
2
4
4
3
3
2
2
Min.
10.5
11.4
20.2
16.0
10.3
10.9
12.1
14.1
12.0
19.4
15.4
14.2
16.2
11.7
17.9
22.5
Max.
26.1
26.7
28.7
29.7
29.6
23.4
25.2
26.0
24.6
31.9
25.2
25.9
25.9
26.9
39.6
27.6
Mean
16.3
18.5
23.0
22.0
19.8
18.0
18.2
19.9
17.8
25.6
21.1
18.5
19.8
19.9
28.8
25.0
Quarterly nylon
Sample
size
4
4
4
4
4
4
4
4
4
2
4
4
4
3
3
4
4
4
2
4
2
4
2
4
2
3
1
2
2
Min.
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
1
0
0
13
15
7
2
0
0
6
3
0
0
1
2
4
0
0
0
0
0
0
0
0
5
0
0
0
Mean
0
0.2
0
0
5.5
8.8
2.5
0.5
0
0
2.2
0.8
0
0
0.3
0.5
1.2
0
0
0
0
0
0
0
0
1.7
0
0
Monthly nylon
Sample
size
11
12
12
12
12
12
12
12
12
9
12
11
10
12
12
12
12
9
7
11
6
12
6
12
7
12
10
6
3
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
1
0
0
19
11
3
1
0
0
2
2
0
0
0
1
1
1
0
3
0
1
0
5
0
0
1
0
0
Mean
0
0.1
0
0
3.3
3.0
0.7
0.2
0
0
0.4
0.4
0
0
0
0.1
0.1
0.1
0
0.3
0
0.1
0
0.7
0
0
0.1
0
Silver tarnishing
Sample
size
12
12
11
12
11
10
12
12
11
10
10
12
12
12
12
12
12
9
7
12
6
12
5
12
7
11
10
6
K
Min.
58
74
32
46
39
50
48
50
27
53
26
44
12
21
11
20
15
9
68
74
61
59
62
44
33
29
12
36
3fi
Max.
96
96
93
99
96
88
82
90
82
79
92
74
64
52
54
50
47
59
91
88
87
91
85
80
60
58
40
61
R9
Mean
84
87
64
77
72
77
65
71
47
64
68
60
34
34
34
34
32
37
80
81
78
79
64
42
42
24
46
I
»
s
-------
Table B-1 (continued). DATA SUMMARY
State/city
IDAHO (continued)
Lewiston (74)
Lewiston (75)
ILLINOIS
Chicago (26)
East St. Louis
Chicago (54)
Calumet City
Hennepin
Rock Island
Moline
Cicero
Bedford Park
Chicago Heights
(138)
Palatine
East Dubuque
Metropolis
Cairo
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRR
Lead peroxide candle
Sample
size
12
11
12
11
12
12
12
12
10
10
10
11
11
12
12
11
12
8
7
12
6
12
6
12
7
11
11
6
d
Min.
0.0
0.0
0.0
0.0
1.4
0.9
0.7
0.9
0.6
0.5
0.8
0.9
0.0
0.0
0.0
0.0
0.1
0.1
1.5
1.3
1.1
1.1
0.9
0.5
0.2
0.0
0.0
0.2
n n
Max.
0.4
0.2
0.2
0.2
6.9
8.7
2.8
4.7
2.5
3.0
2.9
2.2
0.5
0.8
0.5
1.1
1.6
2.0
3.7
6.0
3.0
4.3
1.3
2.1
0.7
1.1
1.8
1.3
1 n
Mean
0.2
0.1
0.1
0.1
3.8
3.3
1.8
1.6
1.4
1.3
1.6
1.6
0.3
0.2
0.4
0.3
0.7
0.8
2.4
2.5
2.0
1.9
1.1
1.1
0.5
0.5
0.6
0.7
Lead plates
Sample
size
10
11
11
12
8
11
12
12
8
9
11
10
9
10
3
Min.
0
0
6
6
5
0
0
2
0
9
6
3
1
5
Max.
2
2
63
23
21
18
6
7
18
30
30
14
11
11
9
Mean
1
1
29
12
11
11
2
3
6
18
13
9
4
5
Dustfall
Sample
size
12
10
12
11
12
12
12
12
12
12
10
12
12
11
12
12
12
9
7
11
6
11
6
12
7
12
10
4
c.
Min.
4.0
4.4
3.6
4.3
14.0
13.5
4.4
4.7
2.4
2.2
2.4
3.6
1.2
1.4
2.9
1.5
3.6
3.1
3.5
5.7
7.4
6.0
2.5
1.7
0.6
1.1
4.4
4.3
1 9
Max.
40.9
11.5
42.5
14.7
35.3
27.6
10.4
10.2
8.4
6.4
16.1
17.5
62.7
5.6
14.3
9.7
18.0
11.8
9.6
10.3
13.9
18.2
11.9
7.9
4.7
7.3
25.0
4.9
1 1
Mean
10.1
7.9
9.4
8.2
22.1
20.0
7.3
7.7
5.0
4.2
6.1
7.1
9.2
3.7
6.2
5.2
7.9
6.9
6.5
6.9
10.1
9.0
5.3
4.2
2.0
4.0
9.5
Sticky paper
Sample
size
12
12
12
12
12
12
12
11
11
12
12
12
12
12
9
8
3
10
8
9
6
10
6
7
11
5
K
Min.
22
8
38
57
32
12
8
4
24
24
4
1
13
9
7
2
49
33
29
44
14
10
1
9
16
5
a
Max
48
39
78
87
68
77
51
62
71
78
39
38
58
61
59
78
66
73
62
79
28
73
27
48
66
23
OQ
Mean
25
28
58
74
52
51
23
35
45
42
12
14
29
35
33
42
59
47
57
20
33
11
22
35
Rubber cracking
Sample
size
45
1
42
2
50
51
52
52
44
43
45
51
51
46
51
49
44
40
29
50
25
40
26
50
28
45
45
19
1 1
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
n
Max
.242
0
.304
0
.136
.150
.234
.355
.278
.348
.413
.232
.353
.451
.312
.369
.383
.363
295
257
.242
365
.320
.394
353
404
300
232
OQC
Mean
.065
.063
.030
.021
.093
.069
.070
.060
.098
.082
.126
.110
.074
.068
.094
.051
.107
.052
.067
.118
.069
.123
.106
.067
I
F
n
w
I
OO
-------
Table B-1 (continued). DATA SUMMARY
State/city
INDIANA
Jeffersonville
Tell City
Evansville
East Chicago
Hammond
Gary
Charlestown
OWA
Davenport
Sioux City
Council Bluffs
Dubuque
:ANSAS
Kansas City
(47)
Kansas City
(87)
Overland Park
El wood
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
...
...
Max.
...
Mean
1.3
1.8
5.5
1.4
1.6
2.0
11.7
3.1
4.8
1.3
2.2
0.5
0.5
1.1
1.0
1.0
1.4
0.7
0.5
0.5
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
43
43
33
37
33
38
61
62
28
19
5
14
26
23
20
21
17
13
9
Quarterly steel
Sample
size
4
3
4
3
4
4
4
4
4
4
2
3
4
4
4
4
4
4
3
3
3
4
4
4
Min.
56
71
30
29
43
40
71
69
60
64
60
40
5
11
1
-2
23
18
6
8
7
4
5
1
Max.
84
107
53
51
60
72
111
131
91
84
69
74
34
35
8
10
46
32
62
31
17
21
18
8
Mean
71
89
39
42
53
52
91
99
76
77
65
55
21
20
4
5
35
25
31
15
11
11
9
4
Fabric No. 1
Sample
size
4
3
3
4
4
3
3
3
4
4
2
3
4
4
1
3
1
4
4
4
2
4
2
4
3
4
Min.
15.8
18.7
12.9
16.4
14.2
17.7
22.3
23.6
14.9
20.6
15.9
17.0
11.0
18.0
17.0
18.7
15.0
16.6
17.9
14.9
22.1
14.0
18.4
13.2
16.1
13.9
Max.
20.5
24.9
16.5
20.6
18.9
23.4
27.1
29.1
19.0
23.2
20.4
25.5
17.9
20.7
17.0
20.3
15.0
18.8
21.7
20.0
22.3
18.2
20.4
16.8
19.2
19.0
Mean
8.3
21.3
5.0
8.2
6.6
21.1
24.2
25.8
17.5
21.9
18.2
20.7
14.8
19.4
19.3
17.9
19.6
16.7
22.2
15.6
19.4
14.9
17.4
1fi8
Fabric No. 2
Sample
size
4
3
4
3
4
2
4
1
1
3
3
3
1
Min.
3.8
1.1
1.9
11.6
2.5
6.4
1.9
1.4
1.2
1.8
2.4
1.3
1.1
Max.
10.3
2.8
7.1
17.9
10.1
8.9
3.3
1.4
1.2
4.0
7.9
2.2
1.1
Wean
5.8
1.7
3.3
4.4
5.0
7.6
2.5
3.1
4.5
1.6
a
n
I
CA
-------
Table B-1 (continued). DATA SUMMARY
State/city
INDIANA
Jeffersonville
Tell City
Evansville
East Chicago
Hammond
Gary
Charlestown
IOWA
Davenport
Sioux City
Council Bluffs
Dubuque
KANSAS
Kansas City
(47)
Kansas City
(87)
Overland Park
El wood
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRS
Fabric No. 3
Sample
size
4
2
3
4
4
4
3
4
4
4
2
4
4
3
1
4
1
4
4
4
2
4
2
4
3
1
A
Min.
17.7
19.9
13.4
22.5
15.6
24.1
26.1
29.5
16.3
27.9
18.1
24.6
13.5
19.3
18.4
16.2
11.0
15.6
14.7
12.2
23.2
14.5
21.8
12.9
16.3
9.1
11 1
Max.
27.0
31.4
16.9
22.9
22.0
32.5
31.5
33.3
28.2
35.5
24.6
30.8
21.1
23.6
18.4
19.5
11.0
20.8
21.1
22.8
24.2
21.4
24.8
17.2
21.0
9.1
1fi O
Mean
22.2
25.6
14.9
22.7
19.2
27.2
25.8
32.0
21.6
30.2
21.4
28.0
18.2
21.5
18.3
18.0
18.6
19.0
23.7
18.2
23.3
15.8
18.7
14 R
Fabric No. 4
Sample
size
4
2
4
3
4
2
4
1
3
4
3
Min.
10.2
14.3
14.3
10.5
12.1
11.2
7.3
9.6
10.6
10.6
11.9
Max.
25.5
17.6
25.1
21.0
23.5
16.2
20.2
9.6
21.0
23.8
25.6
Mean
17.4
16.0
18.6
15.8
16.9
13.7
14.8
17.5
17.4
20.9
Fabric No. 5
Sample
size
3
4
4
4
4
4
4
3
3
4
1
2
2
a.
Min.
5.0
8.2
6.4
4.6
5.7
4.9
5.6
7.8
8.0
7.4
13.0
11.4
8.7
7 T
Max.
11.9
16.3
13.6
10.3
11.8
11.1
13.5
12.5
13.0
12.6
13.0
11.7
8.9
n )
Mean
8.4
12.2
9.9
7.2
8.5
7.7
9.5
9.4
11.1
10.0
11.6
8.8
m n
Fabric No. 6
Sample
size
3
4
4
3
4
4
4
4
4
4
2
2
3
/i
Min.
9.1
5.2
5.9
15.5
9.4
9.0
8.1
6.2
6.2
6.9
5.7
8.4
5.7
R n
Max
12.7
10.6
9.6
18.6
17.4
12.5
9.8
10.1
10.0
11.5
6.6
9.9
8.4
Q n
Mean
10.4
8.3
7.8
17.4
13.3
10.4
8.6
8.0
7.6
8.9
6.2
9.2
6.7
7 1
Fabric No. 7
Sample
size
3
4
4
4
4
4
4
4
4
4
2
2
3
A
Min.
9.9
1.8
3.0
6.9
8.1
9.0
6.7
6.5
8.2
6.9
2.7
7.5
5.4
t 1
Max
13.2
17.3
13.5
19.3
17.4
12.5
14.4
10.7
12.0
11.5
3.9
10.9
7.2
1C n
Mean
11.4
7.3
9.0
14.5
2.8
1.0
1.3
8.9
9.8
0.4
3.3
9.2
6.1
"7 C
I
I
r
73
o
-------
Table B-1 (continued). DATA SUMMARY
State/city
INDIANA
Jeffersonville
Tell City
Evansville
East Chicago
Hammond
Gary
Charlestown
OWA
Davenport
Sioux City
Council Bluffs
Dubuque
:ANSAS
Kansas City
(47)
Kansas City
(87)
Overland Park
Elwood
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
2
4
4
4
4
4
4
4
4
4
2
2
3
4
Min.
6.6
6.6
8.4
7.4
3.0
5.6
7.3
3.0
3.8
3.1
6.1
6.8
3.7
4.8
Max.
8.9
11.6
14.9
10.5
10.4
8.8
12.3
10.4
13.4
9.7
6.4
9.8
7.3
7.8
Mean
7.8
9.2
11.1
9.0
8.2
7.5
8.7
6.6
7.8
6.3
6.2
8.3
4.9
6.2
Fabric No. 9
Sample
size
3
4
4
3
4
4
4
4
4
4
2
2
3
4
Min.
14.0
13.9
14.0
19.3
12.4
14.4
16.6
9.1
13.1
12.0
17.5
24.2
10.9
9.5
Max.
27.6
26.8
28.2
27.2
26.9
28.2
24.5
23.6
29.9
26.9
25.4
24.7
25.8
23.1
Mean
19.7
18.9
20.8
24.2
19.4
21.8
20.8
16.1
18.7
17.9
21.4
24.4
17.2
16.2
Quarterly nylon
Sample
size
4
3
4
4
2
4
4
4
4
4
2
4
1
4
4
4
4
4
4
4
4
4
4
4
4
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
2
0
2
0
2
6
9
0
1
2
4
0
0
0
0
0
1
2
0
2
0
2
0
1
Mean
0
0.7
0
0.5
0
1.2
4.0
3.5
0
0.2
1.0
2.0
0
0
0
0
0.2
0.5
0
0.5
0
0.5
0
0.2
Monthly nylon
Sample
size
12
11
11
11
11
12
11
12
11
11
5
12
4
12
12
12
12
10
12
12
12
12
12
12
12
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
0
0
0
1
2
20
3
1
2
1
4
0
0
0
0
0
0
0
0
2
0
2
0
1
vtean
0
0
0
0
0.1
0.4
2.4
1.0
0.2
0.3
1.0
0
0
0
0
0
0
0
0.2
0
0.2
0
0.1
Silver tarnishing
Sample
size
12
12
12
11
12
12
12
12
12
12
5
12
4
12
12
2
12
2
12
10
12
12
12
12
12
12
2
12
Win.
39
35
36
33
28
25
79
82
48
55
45
51
26
17
14
11
10
22
15
12
26
25
14
20
20
16
37
22
Max.
69
79
95
73
57
49
100
94
96
91
86
86
46
66
59
20
59
94
42
67
91
84
76
67
55
47
39
50
Mean
54
58
48
55
37
35
90
90
77
74
72
36
33
25
26
i
| 32
60
59
40
44
34
29
33
>
o
£
CO
I
-------
1
Table B-1 (continued). DATA SUMMARY
State/city
INDIANA
Jeffersonville
Tell City
Evansville
East Chicago
Hammond
Gary
Charlestown
IOWA
Davenport
Sioux City
Council Bluffs
Dubuque
KANSAS
Kansas City
(47)
Kansas City
(87)
Overland Park
Elwood
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
12
12
12
11
12
12
11
10
11
11
5
12
4
11
11
12
12
11
12
12
12
11
12
12
12
Min.
0.6
0.6
0.0
0.0
0.6
0.5
2.9
1.5
1.3
0.9
0.5
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Max.
1.9
2.2
0.7
1.5
1.9
2.8
10.7
7.3
7.3
3.1
2.4
3.7
0.6
1.0
1.0
0.3
0.5
1.2
0.8
1.0
0.7
0.4
0.3
0.4
0.4
Mean
1.1
1.2
0.4
0.4
1.2
1.3
5.2
4.7
2.3
1.8
1.5
0.4
0.3
0.1
0.1
0.6
0.4
0.3
0.2
0.2
0.1
0.1
0.1
Lead plates
Sample
size
7
9
12
12
11
12
3
12
2
11
8
11
12
12
12
Min.
3
0
3
10
7
3
0
0
0
0
0
0
0
0
0
Max.
18
8
20
72
21
26
6
8
0
3
10
7
6
2
2
Mean
8
3
9
40
13
12
3
1
3
2
2
1
0
Dustfall
Sample
size
12
12
12
12
12
12
12
12
10
11
5
11
4
12
12
11
12
11
11
12
11
12
12
12
12
Min.
4.5
8.0
0.7
2.3
3.9
3.5
4.3
5.6
3.9
4.6
14.8
7.3
3.7
6.1
6.0
1.1
3.2
4.6
5.3
5.4
3.8
3.9
1.0
0.8
2.3
Max
31.1
14.6
6.6
6.2
12.2
10.3
22.0
23.0
17.3
14.8
26.9
29.3
5.3
27.4
20.6
16.2
12.7
11.0
20.5
16.3
8.9
11.7
6.2
5.7
18.5
Mean
10.9
11.3
3.5
4.0
6.3
5.9
13.1
12.5
10.0
8.3
20.4
12.6
9.7
27.8
7.2
8.1
9.8
8.6
5.6
6.6
2.7
2.8
7.9
Sticky paper
Sample
size
12
9
12
12
12
12
12
12
12
12
6
12
1
12
12
3
12
2
12
10
12
11
12
11
12
12
2
11
Min
12
19
2
1
27
12
51
53
34
14
50
57
7
18
16
12
5
22
14
18
11
10
23
12
4
4
3
3
Max
54
64
33
48
65
76
81
89
71
82
78
88
7
71
93
29
80
36
77
79
68
65
67
76
54
46
12
71
Mean
29
37
14
20
43
46
69
75
40
54
70
74
46
60
48
43
48
32
29
38
39
17
23
30
Rubber cracking
Sample
size
47
42
51
47
46
52
49
51
50
50
23
48
11
53
50
10
49
7
50
45
49
47
50
48
50
51
7
50
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.252
.216
.514
.660
.388
.413
.330
.358
.340
.292
.272
223
154
353
388
0
255
0
209
249
418
224
335
411
426
489
0
431
Mean
.100
.068
.126
.124
.107
.091
.094
.070
.097
.075
.051
.048
.034
.064
.062
.078
.106
.060
.104
.093
.148
.103
.093
n
M
"0
50
O
so
-------
Table B-1 (continued). DATA SUMMARY
State/city
KENTUCKY
Louisville
Hawesville
Owensboro
Ashland
Frankfort
Covington
Henderson
Paducah
LOUISIANA
Sulfur
Shreveport
Bogalusa
Vidalia
Bastrop
Tallulah
New Orleans
Carville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.8
2.0
1.2
1.2
2.2
1.9
1.2
1.5
1.3
1.6
3.9
1.0
1.6
0.8
2.6
4.1
1.4
1.9
0.8
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
30
33
38
41
48
42
37
44
28
35
29
50
31
29
11
11
6
23
23
Quarterly steel
Sample
size
4
3
4
4
4
4
4
4
4
4
2
4
3
1
3
4
4
2
4
3
4
3
3
Min.
47
54
37
32
54
46
32
41
34
36
31
31
55
21
19
23
4
41
8
32
2
26
17
Max.
69
97
56
58
73
88
58
75
47
50
42
74
77
21
36
36
13
173
11
44
8
43
27
Mean
58
76
46
44
60
63
46
54
39
41
36
47
68
30
27
8
107
9
39
4
35
21
Fabric No. 1
Sample
size
4
4
4
4
4
4
2
2
3
4
2
4
1
3
1
3
3
1
4
1
2
1
4
1
4
3
1
3
1
4
Min.
15.9
19.9
12.4
14.8
16.1
19.3
15.0
20.8
13.1
15.8
14.1
17.5
18.2
20.2
18.9
16.3
18.3
14.9
19.8
15.8
19.0
14.4
16.7
15.1
17.8
18.1
17.3
19.9
17.2
17.5
Wax.
20.1
25.8
15.9
19.4
23.3
24.0
20.0
26.0
16.1
22.7
15.7
22.5
18.2
25.0
18.9
18.8
21.7
14.9
21.7
15.8
22.7
14.4
22.4
15.1
22.3
20.3
17.3
23.7
17.2
23.9
Mean
18.3
22.9
14.1
17.0
19.0
21.0
17.5
23.4
15.1
18.5
14.9
20.5
22.4
17.7
20.5
20.6
20.8
19.4
20.0
19.1
21.6
21.2
Fabric No. 2
Sample
size
4
4
4
2
4
2
1
3
1
1
1
1
1
Win.
3.1
1.0
1.2
1.9
1.0
1.4
5.7
1.1
0.8
0.9
1.2
4.3
1.2
Max.
9.6
2.7
12.8
2.1
2.8
7.1
5.7
1.3
0.8
0.9
1.2
4.3
1.2
(/lean
6.0
1.8
7.8
2.0
1.8
4.2
1.2
o
69
e
-------
Table B-1 (continued). DATA SUMMARY
State/city
KENTUCKY
Lousiville
Hawesville
Owensboro
Ashland
Frankfort
Covington
Henderson
Paducah
LOUISIANA
Sulfur
Shreveport
Bogalusa
Vidalia
Bastrop
Tallulah
New Orleans
Carville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRS
Fabric No. 3
Sample
size
4
4
4
4
4
4
3
2
4
4
2
4
1
3
1
3
3
1
4
1
2
1
4
1
4
3
1
3
1
a.
Min.
25.3
24.0
15.4
19.6
16.4
23.1
9.9
20.5
15.0
20.4
19.0
26.8
22.1
23.9
20.0
13.4
21.1
14.8
19.4
16.0
20.3
13.9
19.5
14.3
20.5
17.0
21.2
27.4
15.1
1fi 1
Max.
31.9
30.6
21.9
21.8
21.3
28.6
20.7
23.8
20.4
29.3
33.0
39.8
22.1
25.0
20.0
22.7
25.6
14.8
23.3
16.0
26.0
13.9
21.2
14.3
24.0
24.6
21.2
30.2
15.1
)) Q
Mean
27.5
27.9
19.2
20.6
19.2
25.2
15.0
22.2
17.6
24.1
26.0
32.2
24.5
18.0
23.8
21.8
23.2
20.2
22.1
21.8
28.9
1Q R
Fabric No. 4
Sample
size
4
3
4
3
3
2
1
2
1
1
1
1
1
Min.
10.7
17.6
12.2
11.1
18.2
12.9
16.6
25.6
14.9
15.1
13.0
14.0
17.2
Max.
21.8
29.3
30.4
26.0
28.7
17.5
16.6
26.8
14.9
15.1
13.0
14.0
17.2
Mean
16.2
23.0
20.7
16.4
23.2
15.2
26.2
Fabric No. 5
Sample
size
4
4
4
2
4
4
3
4
4
2
4
4
3
2
T
Min.
5.6
8.3
6.7
5.9
8.6
5.8
9.0
9.8
7.8
10.5
11.9
10.2
8.7
9.0
11 Q
Max.
13.2
18.3
16.6
10.5
16.8
13.4
16.0
15.5
13.8
15.3
17.1
14.0
12.3
12.0
1R R
Mean
9.5
13.7
11.4
8.2
12.5
9.4
13.5
13.5
10.8
12.9
13.8
11.4
10.5
10.5
n H
Fabric No. 6
Sample
size
3
4
4
2
4
4
3
1
4
4
2
4
4
2
3
A
Min.
9.5
4.5
7.7
8.0
3.8
7.1
7.4
4.3
3.3
6.7
5.6
5.1
6.1
9.9
11.3
A 1
Max.
12.1
6.6
13.4
9.6
8.0
12.4
9.6
4.3
8.7
9.4
7.1
8.0
8.4
11.0
15.4
H c;
Mean
10.8
5.9
10.6
8.8
6.0
10.2
8.5
5.6
7.7
6.4
6.2
7.3
10.4
12.8
CL K
Fabric No. 7
Sample
size
4
4
4
2
4
4
4
1
4
4
2
4
3
3
3
A
Min
6.6
6.1
10.3
5.1
4.9
6.3
3.8
2.1
4.6
5.6
6.7
3.9
7.7
6.0
8.8
t i
Max
13.5
7.7
16.8
14.8
11.0
14.6
16.1
2.1
14.3
11.0
7.0
8.1
8.5
12.8
12.6
R a
Mean
9.8
7.1
12.9
10.0
8.0
10.3
9.5
....
8.6
7.6
6.8
5.5
8.1
9.5
10.7
c a
tfl
ye
I
W
P
s
90
I
H
-------
Table B-1 (continued). DATA SUMMARY
State/city
KENTUCKY
Louisville
Hawesville
Owensboro
Ashland
Frankfort
Covington
Henderson
Paducah
.OUISIANA
Sulfur
Shreveport
Bogalusa
Vidalia
Bastrap
Tallalah
New Orleans
Carville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
4
4
2
4
4
3
1
3
4
2
4
4
3
3
4
Min.
4.4
5.7
5.2
5.5
8.0
5.4
7.1
5.6
5.6
5.7
5.4
5.7
4.7
4.6
8.3
3.8
Max
7.7
16.5
9.3
7.6
10.6
9.7
12.0
5.6
8.6
9.5
9.5
8.4
11.5
0.9
0.2
2.4
Mean
6.0
9.7
8.1
6.6
8.8
8.0
9.3
7.4
7.0
7.4
7.4
7.9
7.6
9.4
7.4
Fabric No. 9
Sample
size
4
4
4
2
4
4
3
1
4
4
2
3
4
3
3
4
Min.
13.6
15.6
14.6
22.1
10.3
13.4
18.8
40.7
19.0
17.4
22.0
16.3
16.5
18.7
27.8
17.1
Max.
29.8
26.5
30.0
24.9
27.5
28.7
31.2
40.7
29.7
31.8
34.6
26.0
33.9
34.3
34.9
29.6
Mean
20.3
20.4
23.6
23.5
17.4
19.9
24.0
24.6
23.6
28.3
21.4
23.6
25.2
31.4
23.7
Quarterly nylon
Sample
size
4
3
4
4
4
4
3
3
4
4
2
4
1
3
1
3
4
4
2
4
4
4
4
4
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
2
2
5
5
0
0
0
0
0
0
1
2
0
1
0
0
3
0
0
0
0
0
0
6
Mean
0.8
0.7
1.2
1.8
0
0
0
0
0
0
0.5
0.5
0.3
0
1.5
0
0
0
0
0
0
1.5
Monthly nylon
Sample
size
12
12
11
12
12
12
11
11
12
12
5
11
4
11
1
9
10
2
12
2
7
2
12
2
12
12
2
11
2
11
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
1
3
0
0
0
0
0
0
0
0
1
0
0
0
0
0
2
0
0
0
0
0
0
0
2
1
0
0
0
8
Mean
0.2
0.3
0
0
0
0
0
0
0
0
0
0
0
0.2
0
0
0
0.2
0.1
0
1.2
Silver tarnishing
Sample
size
11
12
12
12
12
12
12
12
12
12
5
12
4
12
9
12
2
12
2
8
2
12
2
12
12
2
12
1
12
Min.
37
41
33
37
33
38
47
41
24
23
41
33
51
30
53
44
71
45
j 85
; 62
78
39
i 78
56
13
74
73
68
34
Max.
69
76
58
58
78
81
91
88
61
74
66
78
86
84
81
73
88
85
90
93
79
94
87
90
74
79
91
68
83
Mean
52
63
43
46
58
56
73
77
45
46
52
59
64
58
65
82
76
77
40
85
65
-------
Table B-1 (continued). DATA SUMMARY
State/city Year
KENTUCKY
Louisville 1967
1968
Hawesville 1967
1968
Owensboro 1967
1968
Ashland 1967
1968
Frankfort 1967
1968
Covington 1 967
1968
Henderson 1 967
1968
Paducah 1967
1968
LOUISIANA
Sulfur 1967
1968
Shreveport 1967
1968
Bogalusa 1967
1968
Vidalia 1967
1968
Bastrop 1967
1968
Tallulah 1967
1968
New Orleans 1967
1968
Carville 1967
1968
Lead peroxide candle
Sample
size
12
12
11
11
12
12
12
12
12
11
5
12
4
12
9
12
2
12
2
8
2
12
2
12
12
2
12
2
12
Min.
0.7
0.9
0.2
0.0
0.3
0.0
0.0
0.0
0.0
0.0
0.4
0.0
0.5
0.0
0.0
0.0
0.1
0.0
0.1
0.0
0.0
0.0
0.2
0.0
0.0
0.3
0.0
0.0
0.0
Max.
2.2
2.8
0.6
1.0
2.8
2.9
0.7
0.8
0.4
0.9
0.9
1.5
2.4
2.7
0.1
0.2
0.1
0.1
0.4
0.9
0.2
0.2
0.3
0.4
0.1
0.3
0.6
0.2
0.2
Mean
1.5
1.5
0.3
0.3
1.2
1.1
0.4
0.4
0.2
0.3
0.7
1.2
0.0
0.0
0.0
0.4
0.0
0.1
0.1
0.3
0.1
Lead plates
Sample
size
11
10
12
12
12
11
10
12
12
6
11
12
12
10
11
Min.
7
0
2
0
0
1
2
0
0
0
0
0
0
2
0
Max.
19
4
17
5
6
10
18
3
1
4
1
2
2
4
1
Mean
11
2
8
3
2
4
9
1
0
2
0
1
0
3
1
Dustfall
Sample
size
12
12
12
11
12
11
12
12
12
12
5
12
4
12
9
12
2
10
2
8
2
12
2
12
11
2
12
2
12
Min. Max.
1.7 12.0
2.8 12.1
1.2 10.8
1.7 3.3
4.0 8.0
3.8 8.4
3.5 11.2
3.5 9.4
1.2 4.5
1.4 31.7
2.9 9.1
2.3 7.6
3.6 7.8
2.8 18.4
1.6 14.5
1.7 7.4
2.3 3.2
1.8 10.1
4.3 8.4
2.9 9.6
2.3 3.4
1.9 4.5
10.7 11.4
3.9 26.0
5.0 9.7
3.2 5.5
1.0 6.8
1.2 1.6
0.8 5.1
Mean
8.2
9.1
3.9
2.5
5.6
6.1
5.9
6.4
2.3
4.6
4.8
6.2
4.5
4.0
5.3
5.8
3.0
12.5
7.5
4.6
2.0
Sticky paper
Sample
size
12
11
12
12
12
12
12
12
12
12
5
12
5
12
10
12
3
11
2
5
2
11
2
12
12
2
11
2
12
Min.
16
31
0
1
8
9
5
3
0
1
12
6
18
7
1
1
18
1
20
4
5
2
17
1
2
37
6
4
1
Max
64
72
46
28
57
55
42
55
20
28
36
66
41
65
11
25
50
51
31
46
17
36
41
54
52
53
68
16
15
Mean
38
47
10
7
26
30
20
23
7
9
31
34
4
7
23
25
13
24
30
47
4
Rubber cracking
Sample
size
52
50
50
49
48
50
49
51
48
51
20
50
19
52
40
52
8
40
8
28
7
45
6
50
51
9
46
9
51
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.239
.235
.514
.436
.386
.241
.345
.405
.456
.388
.285
.235
466
290
428
363
0
272
280
295
201
396
074
290
370
126
472
360
310
Mean
.081
.064
.155
.124
.125
.076
.094
.082
.133
.091
.078
.088
.105
.082
.075
.066
.129
.084
.080
.100
.094
w
X)
on
8
p
n
w
2
8
H
VO
-a
-------
00
Table B-1 (continued). DATA SUMMARY
State/city
MAINE
Eliot
Madawaska
MARYLAND
Cheverly
Cumberland
Bloomington
MASSACHUSETTS
Lawrence
Springfield
Attleboro
Fall River
Boston
ICHIGAN
Detroit
River Rouge
Grosse He
Livonia
Sumpter Township
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max
Mean
5.0
4.0
4.2
2.2
1.6
2.7
4.6
6.0
5.5
4.8
2.8
3.7
2.6
5.7
2.8
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
37
35
53
50
44
51
52
52
49
51
41
48
37
40
Quarterly steel
Sample
size
1
3
2
3
2
2
4
2
4
1
4
1
4
1
4
1
4
1
4
4
4
4
4
1
4
4
1
2
Min.
13
51
71
49
40
52
36
58
66
64
64
84
65
61
74
84
75
85
51
63
69
57
75
56
39
45
31
41
Max.
13
53
151
75
63
68
58
79
112
64
86
84
88
61
90
84
98
85
111
83
90
75
79
56
85
56
31
53
Mean
52
111
63
52
60
46
68
81
73
74
82
82
87
74
75
66
77
64
50
47
Fabric No. 1
Sample
size
1
4
2
4
2
2
3
2
4
1
3
1
4
1
3
1
4
1
3
4
4
4
3
1
3
3
1
2
Min.
17.8
15.7
17.4
12.2
15.0
15.7
17.0
18.1
15.8
15.9
16.8
16.5
17.5
17.5
16.3
18.0
19.3
16.1
17.2
14.2
16.7
18.9
19.9
18.6
21.7
19.0
10.3
17.7
Max.
17.8
20.9
21.4
16.9
20.4
15.9
20.0
18.2
21.1
15.9
19.9
16.5
20.3
17.5
22.1
18.0
23.9
16.1
23.0
17.7
21.3
22.7
23.0
18.6
23.2
23.8
10.3
18.9
Mean
18.8
19.4
15.6
17.7
15.8
18.3
18.2
18.8
18.6
18.8
18.6
21.9
20.5
16.3
19.4
17.5
21.5
22.6
21.0
18.3
Fabric No. 2
Sample
size
1
4
2
2
1
1
1
1
1
4
4
1
1
i/lin.
0.5
1.3
1.3
2.3
1.4
4.1
2.0
4.8
3.4
3.9
3.0
2.4
0.9
Max.
0.5
3.9
3.2
2.5
1.4
4.1
2.0
4.8
3.4
8.2
6.2
2.4
0.9
Wean
3.0
2.2
2.4
5.8
4.6
13
"8
ea
s?
-------
i
Cfl
Table B-1 (continued). DATA SUMMARY
State/city
MAINE
Eliot
Madawaska
MARYLAND
Cheverly
Cumberland
Bloomington
MASSACHUSETTS
Lawrence
Springfield
Attleboro
Fall River
Boston
MICHIGAN
Detroit
River Rouge
Grosse Me
Livonia
Sumpter Township
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRB
Fabric No. 3
Sample
size
1
4
1
4
2
2
3
2
3
1
4
1
4
1
3
1
3
1
3
4
4
4
3
1
3
3
1
i
Min.
20.3
21.2
20.7
28.3
37.5
18.2
26.1
11.3
19.6
38.9
28.2
40.0
39.6
44.2
49.8
38.2
38.2
44.2
37.4
24.5
30.5
18.0
29.5
23.7
25.4
25.8
15.8
91 1
Max.
20.3
25.1
20.7
34.3
45.4
26.9
41.7
21.3
22.8
38.9
37.3
40.0
43.6
44.2
51.6
38.2
45.0
44.2
41.0
40.7
41.5
28.3
38.5
23.7
28.5
28.5
15.8
91 R
Mean
22.6
31.0
41.4
22.6
31.6
16.3
21.6
31.5
41.7
50.8
42.5
39.8
32.0
35.6
24.0
33.5
26.5
27.4
91 4
Fabric No. 4
Sample
size
1
3
2
1
1
1
1
1
1
4
4
1
1
Min.
26.2
10.4
11.7
14.9
12.7
14.2
23.8
23.4
19.2
12.9
9.6
16.3
19.3
Max.
26.2
28.9
16.9
14.9
12.7
14.2
23.8
23.4
19.2
24.2
22.3
16.3
19.3
Mean
20.4
14.3
17.5
15.4
Fabric No. 5
Sample
size
4
2
2
2
3
4
3
3
3
3
4
3
2
3
)
Min.
11.4
9.1
8.4
12.6
9.2
8.2
6.9
9.1
7.9
4.8
6.6
8.4
7.0
8.0
11 T
Max.
15.1
10.4
15.2
15.2
14.1
13.2
11.8
15.3
15.7
11.8
13.5
13.9
15.5
13.4
1R 7
Mean
13.2
9.8
11.8
13.9
11.6
10.8
10.1
11.4
12.9
8.9
9.6
11.1
11.2
11.5
14 n
Fabric No. 6
Sample
size
4
2
3
4
4
3
4
3
4
3
4
3
3
3
}
Min.
3.9
11.3
5.5
9.2
7.2
7.6
9.5
6.2
9.8
11.3
8.6
9.9
5.0
8.9
R R
Max
6.5
17.0
10.6
17.3
8.6
10.9
14.9
12.4
15.8
16.0
16.5
13.6
11.6
10.2
m Q
Mean
4.9
14.2
8.8
12.0
7.9
9.4
12.4
10.0
12.2
13.7
12.1
12.4
9.0
9.7
n 9
Fabric No. 7
Sample
size
4
2
2
4
3
4
4
3
3
3
4
3
3
3
9
Min
2.4
9.6
5.7
5.5
2.4
2.5
8.5
2.7
5.2
4.8
9.1
5.0
7.3
6.3
Q C
Max
7.2
12.1
8.5
13.0
9.7
12.4
15.7
9.7
18.6
13.9
8.1
24.2
7.5
9.9
1 n 1
Mean
4.8
10.8
7.1
8.9
6.9
7.2
2.2
7.2
1.1
7.8
3.4
2.8
7.4
7.6
n n
n
w
"0
-------
Table B-1 (continued). DATA SUMMARY
State/city
MAINE
Eliot
Madawaska
MARYLAND
Cheverly
Cumberland
Bloomington
MASSACHUSETTS
Lawrence
Springfield
Attleboro
Fall River
Boston
MICHIGAN
Detroit
River Rouge
Grosse Me
Livonia
Sumpter Township
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
2
1
3
4
4
4
3
4
3
3
3
3
3
2
Min.
8.6
7.6
9.5
5.0
6.6
8.2
5.4
10.6
11.6
7.4
9.3
7.5
6.5
4.7
8.5
Max.
15.5
9.1
9.5
7.7
11.4
13.4
13.8
20.0
18.6
10.1
11.6
11.0
11.2
8.7
14.5
Mean
11.8
8.4
6.7
9.2
10.0
9.5
15.3
14.1
8.8
10.4
9.0
8.8
7.4
11.5
Fabric No. 9
Sample
size
4
2
2
4
4
3
4
3
4
3
4
3
3
3
2
Min.
7.7
14.2
27.6
10.2
13.1
14.3
12.5
17.6
20.0
23.9
12.9
21.4
13.8
13.2
13.1
Max.
22.8
34.0
28.7
30.1
29.0
23.2
36.1
41.8
31.6
27.9
29.1
34.8
29.0
35.7
25.0
Mean
16.4
24.1
28.2
21.4
19.8
17.9
23.4
25.9
25.9
26.4
21.7
26.2
21.3
24.0
19.0
Quarterly nylon
Sample
size
1
4
1
1
4
2
4
2
4
1
3
1
4
1
4
1
4
1
4
3
4
3
3
1
3
4
1
3
Min.
2
2
1
0
0
0
0
0
0
3
0
80
0
11
0
6
0
39
0
0
0
0
0
0
0
0
0
0
Max.
2
7
1
0
0
5
2
0
4
3
0
80
48
11
12
6
6
39
26
1
4
1
1
0
0
0
0
3
Mean
3.5
0
2.5
0.5
0
1.0
0
17.0
5.8
4.2
14.5
0.3
2.3
0.3
0.3
0
0
1.0
Monthly nylon
Sample
size
3
10
2
4
7
11
5
12
4
12
3
11
3
11
3
12
3
11
3
12
11
12
12
12
4
11
12
3
10
Min.
0
0
0
0
0
0
0
0
0
0
0
0
12
0
0
0
0
0
5
0
0
0
0
0
0
0
0
0
0
Max.
1
0
0
0
26
3
1
1
0
1
1
1
24
20
3
3
3
2
8
10
0
2
0
2
0
0
0
0
0
Mean
0
4.0
0.4
0.1
0.1
0.1
5.0
1.0
0.4
3.5
0
0.2
0
0.2
0
0
0
Silver tarnishing
Sample
size
3
9
2
6
8
10
4
12
4
12
3
12
2
11
3
12
3
12
3
12
12
12
12
12
4
11
11
3
10
Min.
28
23
33
23
60
37
67
46
84
48
28
31
42
37
41
43
31
27
51
39
61
48
47
49
60
48
48
30
34
Max.
40
48
41
52
80
84
81
84
98
95
40
68
55
75
70
70
51
77
61
84
90
88
88
92
78
78
73
49
61
Mean
35
36
69
58
70
83
50
54
57
52
61
75
72
72
71
62
59
46
a
"S
i
69
-------
ta
en
W
o
W
13
Table B-1 (continued). DATA SUMMARY
State/city
MAINE
Eliot
Madawaska
MARYLAND
Cheverly
Cumberland
Bloomington
MASSACHUSETTS
Lawrence
Springfield
Attleboro
Fall River
Boston
MICHIGAN
Detroit
River Rouge
Grosse He
Livonia
Sumpter Township
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
2
10
2
6
11
9
4
11
5
12
3
12
3
11
3
12
3
11
3
11
12
11
12
12
3
9
11
3
11
Min.
0.4
0.0
2.3
1.2
0.4
0.0
0.5
0.4
0.4
0.2
0.6
0.3
1.7
0.8
1.0
0.4
1.2
0.4
2.6
1.0
0.8
1.0
0.7
0.7
1.1
0.1
0.3
0.3
0.0
Max.
0.5
0.5
3.1
3.6
1.8
2.1
2.4
3.4
1.1
1.4
1.0
1.4
2.4
3.1
1.8
2.5
2.2
3.5
3.5
4.7
2.0
2.9
1.9
2.3
1.4
1.4
1.0
0.6
0.8
Mean
0.3
2.3
1.4
1.1
1.2
0.6
0.8
1.7
1.2
1.5
2.4
1.4
1.4
1.3
1.3
1.0
0.6
0.4
Lead plates
Sample
size
10
4
10
11
1
10
11
12
12
11
11
9
11
12
10
Min.
0
11
0
2
2
2
5
3
4
5
6
6
4
1
0
Max.
3
20
14
20
9
10
17
19
34
38
20
15
18
7
7
Mean
2
5
8
4
6
10
8
12
18
12
10
9
4
3
Dustfall
Sample
size
2
10
2
6
11
10
5
12
5
12
3
11
3
10
3
12
3
11
3
11
12
12
12
12
3
10
12
3
10
Min.
1.2
0.8
5.6
6.5
1.6
2.2
0.5
2.0
4.3
2.1
1.7
1.4
7.8
3.3
3.4
1.3
3.6
0.2
4.5
3.0
5.1
3.1
9.9
6.5
8.7
3.6
3.5
2.1
1.8
Max.
1.2
2.3
5.8
14.5
6.4
4.7
2.4
4.9
16.7
20.8
2.1
6.7
23.5
16.9
4.3
5.4
6.3
7.0
10.5
9.8
17.5
18.2
19.3
27.3
11.1
12.3
15.1
3.9
13.3
Mean
1.3
9.8
4.4
3.8
3.4
8.2
3.3
7.6
3.1
4.2
6.0
10.7
10.3
13.5
12.2
6.8
6.1
3.6
Sticky paper
Sample
size
3
9
2
5
11
4
5
11
11
5
12
3
12
4
11
4
12
4
7
12
12
12
10
2
8
12
4
6
Min.
3
2
13
9
4
31
7
2
5
9
16
27
23
20
6
42
38
22
13
25
31
35
45
24
13
12
3
2
Max
9
20
20
46
46
47
27
59
59
36
64
50
78
35
65
58
71
57
72
71
77
72
80
46
71
59
10
19
Mean
7
28
30
38
34
48
41
51
51
44
57
56
64
46
31
10
Rubber cracking
Sample
size
12
37
7
21
32
21
19
48
18
49
10
52
10
50
12
49
14
52
9
37
52
52
49
47
18
38
16
51
33
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.182
.249
0
.242
.365
.312
.239
.247
.184
.285
0
363
n
194
0
401
117
356
149
290
363
265
378
300
252
410
393
290
438
Mean
.066
.096
.076
.068
.068
.047
.074
.075
.057
.078
.058
.072
.063
.113
.071
.142
-------
Table B-1 (continued). DATA SUMMARY
State/city
MICHIGAN (continue
Port Huron
St. Clair
Dearborn
Sault St. Marie
Ann Arbor
MINNESOTA
Duluth
Winona
E. Grand Forks
Moorhead
Ortonville
International Falls
MISSISSIPPI
Pascagoula
Natchez
Vicksburg
Jackson
Year
1)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
3.3
2.6
1.8
1.6
0.9
1.6
0.9
0.9
2.7
0.6
Annual steel
Sample
size
1
1
1
1
1
1
1
1
Min.
Max.
Mean
30
56
34
22
25
29
12
4
Quarterly steel
Sample
size
1
4
1
4
3
4
4
4
3
2
1
2
2
1
2
3
2
Min.
67
63
52
53
33
32
7
22
24
2
12
7
94
50
5
1
?
Max.
67
89
52
115
49
39
29
25
38
4
12
21
147
50
16
60
2
Mean
72
84
41
34
19
23
33
3
14
120
10
21
Fabric No. 1
Sample
size
1
4
1
3
1
4
3
4
4
3
3
2
1
2
1
1
1
Min.
22.3
18.0
17.3
17.4
13.9
16.8
16.8
13.7
17.0
16.9
17.2
11.6
14.3
18.5
24.5
22.0
14.5
Wax.
22.3
22.9
17.3
22.0
13.9
23.7
20.0
17.3
24.6
20.4
20.5
18.2
14.3
20.0
24.5
22.0
14.R
t/lean
21.1
20.1
20.2
18.4
15.5
19.8
18.5
18.7
14.9
19.2
Fabric No. 2
Sample
size
1
1
1
4
Win.
3.9
1.2
1.1
1.0
Max.
3.9
1.2
1.1
10.7
Wean
4.5
I
-------
Table B-1 (continued). DATA SUMMARY
State/city
MICHIGAN (continue
Port Huron
St. Clair
Dearborn
Sault St. Marie
Ann Arbor
MINNESOTA
Duluth
Winona
E. Grand Forks
Moorhead
Ortonville
International Falls
MISSISSIPPI
Pascagoula
Natchez
Vicksburg
Jackson
Year
d)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRQ
Fabric No. 3
Sample
size
1
4
1
4
4
3
4
4
3
3
2
1
2
1
1
1
Min.
25.6
20.8
19.9
19.6
20.7
20.8
11.5
16.7
15.7
12.6
17.5
11.6
14.4
21.4
21.9
O1 7
Max.
25.6
25.7
19.9
25.8
25.0
23.9
26.0
23.6
20.9
19.5
17.7
11.6
17.6
21.4
21.9
O1 7
Mean
24.1
23.4
22.4
22.4
17.4
20.4
18.8
16.4
17.6
16.0
Fabric No. 4
Sample
size
1
1
4
Min.
15.8
18.9
11.8
Max.
15.8
18.9
22.9
Mean
16.0
Fabric No. 5
Sample
size
3
4
4
3
4
3
2
'M
1
1
2
1
1
Min.
8.6
7.5
10.6
7.4
6.4
6.5
6.8
7.0
8.9
4.7
16.9
12.0
Max.
14.1
16.2
13.7
14.6
10.3
13.2
10.2
7.0
8.9
7.7
16.9
12.0
Mean
12.1
12.0
11.8
11.9
8.5
10.7
8.5
6.2
Fabric No. 6
Sample
size
4
4
4
3
4
3
3
2
1
1
1
1
Min.
7.9
4.7
9.9
7.1
6.9
6.5
5.3
4.3
2.2
6.9
5.4
O K
Max
12.3
8.3
11.2
8.0
11.9
6.7
7.0
9.0
2.2
6.9
5.4
O K
Mean
9.8
6.8
10.6
7.6
9.2
6.6
6.3
6.6
Fabric No. 7
Sample
size
4
4
4
3
3
3
2
1
2
1
1
Min
6.6
3.7
7.2
4.3
7.7
4.5
7.6
11.9
10.4
3.5
O 1
Max
12.3
8.5
13.4
8.7
15.7
9.8
12.2
11.9
1.1
3.5
n 1
Mean
9.3
6.1
10.6
6.3
1.9
6.8
9.9
0.8
w
3
O
w
2
-------
Table B-1 (continued). DATA SUMMARY
State/city
MICHIGAN (continue
Port Huron
St. Clair
Dearborn
Sault St. Marie
Ann Arbor
MINNESOTA
Duluth
Winona
E. Grand Forks
Moorhead
Ortonville
International Falls
MISSISSIPPI
Pascagoula
Natchez
Vicksburg
Jackson
Year
d)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
3
3
3
4
3
3
2
1
2
1
2
1
Min.
5.7
4.4
8.0
4.9
4.9
4.2
5.9
5.4
4.4
8.3
8.0
2.2
4.4
Max.
10.9
9.1
12.7
9.7
8.8
7.6
19.6
9.7
4.4
9.4
8.0
6.6
4.4
Mean
8.4
7.3
10.7
7.4
6.7
6.2
11.2
7.6
8.8
4.4
Fabric No. 9
Sample
size
4
3
4
3
4
3
3
2
2
2
1
2
1
1
Min.
15.1
13.6
10.0
14.7
12.2
9.9
10.4
8.8
10.2
12.1
30.9
30.9
6.4
16.7
Max.
28.9
31.1
24.8
27.5
28.1
31.1
21.6
10.9
11.4
26.1
30.9
30.9
6.4
16.7
Mean
21.8
22.1
17.6
20.9
18.1
21.9
16.3
9.8
10.8
19.1
30.9
Quarterly nylon
Sample
size
1
4
1
3
4
4
4
4
4
3
2
2
2
1
2
3
1
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
Max.
0
0
0
1
0
1
0
0
4
0
0
0
0
1
0
0
0
(/lean
0
0.3
0
0.2
0
0
1.2
0
0
0
0
0
0
Monthly nylon
Sample
size
4
12
4
12
1
11
9
12
12
11
6
7
7
7
6
8
8
3
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
0
0
0
0
0
0
0
0
3
0
0
0
0
6
0
0
0
Mean
0
0
0
0
0
0
0.5
0
0
0
0
1.0
0
0
Silver tarnishing
Sample
size
3
12
3
12
1
12
8
12
12
11
7
7
7
7
5
6
8
Win.
60
57
32
37
77
49
35
24
22
8
17
18
9
78
79
36
45
Max.
88
85
54
75
77
90
63
74
66
60
33
35
45
90
88
83
86
Wean
70
52
68
48
46
41
34
22
27
22
86
60
66
Is
CO
I
»
-------
Table B-1 (continued). DATA SUMMARY
State/city
MICHIGAN (continuec
Port Huron
St. Clair
Dearborn
Sault St. Marie
Ann Arbor
MINNESOTA
Duluth
Winona
E. Grand Forks
Moorhead
Ortonville
International Falls
MISSISSIPPI
Pascagoula
Natchez
Vicksburg
Jackson
Year
i)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
3
12
3
10
1
12
8
11
12
12
7
7
6
7
5
9
8
Min.
1.2
0.8
0.5
0.4
0.5
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.3
0.0
0.0
0.0
Max.
2.2
2.2
1.0
1.7
0.5
0.8
0.6
0.5
0.5
1.2
0.1
0.6
0.1
2.2
0.2
0.1
0.1
Mean
1.2
1.0
0.4
0.2
0.3
0.2
0.4
0.0
0.2
0.0
1.5
0.0
0.0
Lead plates
Sample
size
10
8
11
8
11
9
7
7
5
6
5
7
6
1
Min.
6
4
1
0
2
0
0
0
0
4
1
0
0
n
Max.
14
12
6
5
5
6
1
3
2
17
2
1
1
0
Mean
9
6
3
2
2
2
0
1
11
1
0
0
Dustfall
Sample
size
4
12
4
10
1
12
9
12
12
12
7
7
6
7
5
7
8
Min.
2.4
1.6
2.5
2.4
1.6
0.6
3.2
0.9
1.5
1.3
1.7
1.6
2.1
13.1
1.4
4.3
0.8
Max.
11.7
11.7
5.9
10.2
1.6
9.4
9.3
8.6
10.7
9.0
12.3
4.4
6.2
44.3
3.8
8.4
9.5
Mean
7.6
5.3
4.9
5.0
4.7
5.8
4.6
8.3
2.5
4.8
29.0
5.8
4.8
Sticky paper
Sample
size
4
12
4
12
12
8
12
12
12
6
4
5
7
4
2
5
Min.
25
5
7
15
11
3
2
10
4
31
27
6
27
1
18
1
Max
36
64
38
68
62
38
46
57
48
77
58
56
80
16
39
34
Mean
34
37
37
16
24
27
26
53
58
Rubber cracking
Sample
size
46
14
47
5
50
37
51
51
48
29
23
23
28
18
18
22
3
Min.
0
0
0
0
0
0
0
0
0
0
0
. . _
0
0
0
0
0
n
Max
.353
.403
.413
.078
.337
.381
.428
.277
.358
.262
.237
.394
.237!
.353
.307
.601
Mean
.058
.056
.067
.076
.078
.021
.052
.060
.041
ncr?
1
w
I
w
o
PI
o
-------
o
ON
Table B-1 (continued). DATA SUMMARY
State/city
MISSOURI
St. Louis
(28)
St. Louis
(45)
Kansas City
(48)
Independence
Kansas City
(86)
St. Joseph
Joplin
MONTANA
East Helena
NEBRASKA
S. Sioux City
Omaha
JEVADA
Boulder City
Incline Village
JEW HAMPSHIRE
Lebanon
Salem
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
2.4
6.0
3.9
4.9
1.2
3.7
1.0
1.3
0.8
0.9
0.6
0.6
0.5
0.4
0.4
0.4
3.8
3.0
1.7
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
27
33
50
54
18
17
8
20
17
20
7
9
5
8
2
1
1
1
36
Quarterly steel
Sample
size
4
4
4
4
4
4
4
4
4
1
4
4
2
4
4
4
4
4
3
4
1
4
Min.
38
43
86
78
9
2
9
5
2
5
2
3
28
1
3
1
1
1
1
43
37
37
Max.
56
77
109
123
40
41
69
32
18
47
8
44
46
10
9
1
2
1
2
55
37
53
Vlean
49
54
95
102
21
16
34
17
12
19
4
14
37
5
6
1
1
1
1
47
46
Fabric No. 1
Sample
size
4
4
4
3
4
4
4
4
4
4
1
4
1
4
2
1
4
1
4
4
4
4
4
1
4
1
4
Min.
16.8
20.6
12.1
17.6
12.8
17.6
14.4
17.7
13.8
17.0
13.6
16.6
14.8
18.1
18.8
15.1
16.8
16.0
17.4
7.2
11.8
9.9
14.0
17.1
14.7
19.4
16?
Max.
19.6
24.2
18.7
21.5
17.0
21.9
19.9
22.6
15.9
20.4
13.6
20.5
14.8
21.0
19.9
15.1
18.7
16.0
19.8
13.1
15.5
12.8
15.0
17.1
18.2
19.4
?05
Vlean
17.7
21.7
16.4
19.4
15.1
19.7
17.2
19.9
15.0
18.6
18.5
19.4
19.4
17.7
19.0
10.6
13.5
11.4
14.6
16.3
18.3
Fabric No. 2
Sample
size
4
3
3
3
3
1
1
1
1
4
4
1
1
i/lin.
4.8
1.4
2.6
1.6
1.3
1.1
3.0
1.6
1.2
0.5
1.0
2.9
2.5
Max.
6.0
7.7
4.3
6.0
5.1
1.1
3.0
1.6
1.2
2.4
1.4
2.9
2.5
Mean
5.6
3.7
3.3
3.2
2.8
1.2
1.2
n
I
W
I
-------
5
H
en
m
&
to
p
o
M
tfl
O
Table B-1 (continued). DATA SUMMARY
State/city
MISSOURI
St. Louis
(28)
St. Louis
(45)
Kansas City
(48)
Independence
Kansas City
(86)
St. Joseph
Joplin
MONTANA
East Helena
NEBRASKA
S. Sioux City
Omaha
NEVADA
Boulder
Incline Village
NEW HAMPSHIRE
Lebanon
Salem
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRB
Fabric No. 3
Sample
size
4
4
4
3
4
4
4
4
4
4
1
4
1
4
2
1
3
1
4
4
4
4
4
1
3
1
A
Min.
19.0
27.9
23.1
27.1
17.0
19.9
12.0
20.5
15.3
17.0
9.5
16.6
14.8
17.5
17.2
9.3
18.5
28.6
17.3
8.4
14.3
7.9
10.3
23.6
19.4
18.8
99 B
Max.
30.6
37.7
28.7
28.8
23.7
25.7
20.9
23.7
21.6
22.8
9.5
20.9
14.8
22.2
20.1
9.3
22.0
28.6
21.4
13.8
16.2
12.5
11.5
23.6
26.2
18.8
31 fi
Mean
24.3
33.5
25.8
27.8
19.3
24.0
17.5
21.7
18.4
20.7
19.0
20.1
18.6
19.7
19.6
12.1
15.2
10.4
10.6
22.1
9fi 9
Fabric No. 4
Sample
size
3
4
3
4
4
1
1
1
3
4
1
1
Min.
8.7
13.0
8.9
13.8
12.6
7.3
11.3
7.7
15.9
13.7
24.2
24.3
Max.
19.7
23.9
22.7
26.7
24.5
7.3
11.3
7.7
22.2
18.4
24.2
24.3
Mean
14.4
17.6
16.6
19.8
18.2
18.7
15.6
Fabric No. 5
Sample
size
4
3
4
3
4
4
3
2
3
4
4
4
3
A.
Min.
4.6
7.2
6.8
8.2
7.0
6.7
7.8
9.5
7.5
5.6
13.3
10.7
8.4
a R
Max.
9.0
11.9
12.3
12.6
13.4
14.2
13.0
11.3
10.3
14.5
17.6
12.6
13.1
14 A
Mean
6.8
8.9
9.5
10.1
10.7
10.6
10.4
10.4
8.8
9.9
15.2
11.9
11.3
11 7
Fabric No. 6
Sample
size
4
2
3
4
4
2
4
2
3
4
4
4
3
A
Min.
8.9
11.5
6.0
8.2
4.8
6.2
4.6
8.5
5.0
6.1
2.7
2.9
5.0
K A
Max
10.9
12.9
8.7
10.9
8.9
7.2
11.7
12.9
7.5
13.7
9.7
5.5
0.3
in A
Mean
9.6
12.2
7.2
9.2
6.4
6.7
8.4
0.7
6.4
0.5
5.6
4.0
7.4
7 A
Fabric No. 7
Sample
size
4
3
4
4
4
2
4
2
2
4
3
4
3
A
Min
4.0
11.0
7.1
5.5
5.0
7.2
5.4
14.1
6.6
6.5
1.9
2.3
3.4
A C
Max
15.9
14.1
11.4
12.8
8.6
9.7
12.3
5.4
1.1
7.6
0.7
1.1
0.8
n c
Mean
10.8
13.0
9.2
9.5
7.1
8.4
8.1
4.8
8.8
1.0
6.0
5.6
7.2
-------
o
00
Table B-1 (continued). DATA SUMMARY
State/city
MISSOURI
(28)
(45)
Kansas City
(48)
Independence
Kansas City
(86)
St. Joseph
Joplin
MONTANA
MEBRASKA
S. Sioux City
_ .
JEVADA
Boulder
Incline Village
JEW HAMPSHIRE
Year
1 QR7
1968
1QR7
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1Qfi7
1968
1967
1968
1967
1968
1QR7
1968
1 QR7
1968
Fabric No. 8
Sample
size
4
3
4
4
4
4
4
2
3
4
4
4
3
4
Min.
5.1
7.1
3.0
4.6
2.8
4.8
5.7
6.3
4.4
4.7
2.9
3.3
4.3
5.1
Max.
6.9
8.8
8.8
8.2
13.2
9.3
7.8
8.8
13.1
11.9
11.5
10.9
15.4
14.8
Mean
6.0
8.0
5.4
6.8
7.0
6.9
6.8
7.6
7.5
7.6
6.1
5.7
8.8
10.0
Fabric No. 9
Sample
size
3
3
4
2
4
2
4
2
2
4
4
4
4
4
Min
17.5
19.3
11.5
11.8
13.2
13.1
15.0
16.1
13.3
10.3
4.9
7.8
8.0
13.9
Max.
27.4
36.1
21.6
25.0
27.3
23.8
25.5
19.1
26.1
21.2
21.1
12.6
21.4
30.5
Mean
21.1
24.9
17.2
18.4
18.9
18.4
20.5
17.6
19.7
16.6
10.5
10.1
14.8
22.2
Quarterly nylon
Sample
size
4
4
A
4
4
4
3
4
4
4
3
4
2
4
4
4
4
3
3
4
i
3
1
4
Min.
0
7
13
0
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
0
0
Max.
4
5
^7
97
3
4
0
0
0
0
0
0
7
0
15
0
0
0
0
0
0
4
Mean
1 9
1.5
90 c
39.0
1.2
1.5
0
0
0
0
0
0
4.5
3.8
0
0
0
0
0
0
1.2
Monthly nylon
Sample
size
19
12
1 0
12
11
12
11
12
11
12
2
12
2
12
6
2
11
12
11
12
12
12
12
11
Min.
0
i
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
9
4
9O
50
7
1
1
0
2
0
0
0
0
0
8
0
2
0
0
0
3
0
3
0
Mean
Oc
0.6
7 O
11.6
0.7
0.1
0.1
0
0.3
0
0
0
2.0
0.2
0
0
0
0.2
0
0.8
0
Silver tarnishing
Sample
size
1 9
12
19
12
12
12
11
12
12
12
1
11
2
12
6
2
12
11
10
12
12
11
12
2
12
Min.
40
23
01
77
28
29
22
34
14
26
41
12
43
16
5
18
11
8
8
8
1
1
JO
23
30
25
Max.
OA
83
QR
96
83
76
79
83
59
66
41
71
92
48
18
22
22
45
89
89
10
8
46
59
31
64
Mean
fifi
64
QQ
87
48
47
43
50
41
38
41
31
12
17
27
28
32
4
5
34
38
I
60
-------
Table B-1 (continued). DATA SUMMARY
State/city
MISSOURI
St. Louis
(28)
St Louis
(45)
Kansas City
(48)
I n dependence
Kansas City
(86)
St. Joseph
Joplin
MONTANA
East Helena
NEBRASKA
S. Sioux City
r\ u
umana
NEVADA
Q ii
DOUIQer
Incline Village
NEW HAMPSHIRE
Lsbanon
Salem
Year
1967
1968
1967
1968
1967
1968
1967
1968
1QR7
i \yu i
1968
1967
1968
1967
1968
1967
1 QRft
1 C7OO
1967
1968
1QR7
1 S7U /
1QR7
1 OD/
1968
1967
1968
1QR7
I SO /
1968
1967
1968
Lead peroxide candle
Sample
size
12
12
12
12
12
11
11
12
19
i £-
11
2
12
2
12
R
U
2
12
)
£.
19
1 £.
12
12
12
12
2
12
Min.
0.4
1.1
1.7
1.0
0.0
0.0
0.0
0.0
n n
\J.\J
0.0
0.0
0.0
0.2
0.0
T n
o.u
0.2
0.0
n ?
u.o
n n
u.u
0.0
0.0
0.0
n R
u.o
0.0
0.3
0.0
Max.
2.2
2.4
5.7
4.7
0.9
1.2
0.7
1.0
n 4
U.f
2.1
0.2
0.5
0.2
0.9
4 fi
t.D
0.2
0.1
n 4
U.H
01
. 1
0.1
0.1
0.1
n 7
u. /
1.0
0.4
0.5
Mean
1 R
1 .U
1.5
T R
o.o
2.9
0.4
0.4
n T
u.o
0.4
n 9
u.z
0.3
0.1
0.1
a n
*T.U
0.0
n n
u.u
0.0
0.0
0.0
0.4
0.2
Lead plates
Sample
size
11
11
12
11
11
12
11
10
11
12
12
11
Min.
8
6
0
0
0
0
0
1 °.
1 O
0
0
0
0
0
Max.
15
33
9
6
13
3
2
04
ot
2
2
2
6
3
Mean
10
21
3
3
3
1
1
0
0
0
3
2
Dustfall
Sample
size
1 9
1 £.
12
19
1 Z
11
19
1 £.
12
19
1 Z
12
1 9
I Z
12
2
12
2
11
2
11
m
I U
12
12
12
12
3
10
Min.
87
. /
9.2
60
.O
3.0
37
. /
0.4
20,
O
0.3
1Q
.y
0.4
1.1
2.9
0.6
1.4
31
. i
4.9
3.3
n R
u.o
n A
U.*T
0.5
0.3
0.4
2H
.u
1.2
2.0
1.1
Max.
17 T
i / .>j
21.1
9*3 A
tO.t
12.8
1R 1
i *J. l
9.2
in £
1 U.O
6.2
0 Q
O.O
6.9
5.4
12.1
1.6
3.2
m 1
I U. I
6.3
13.1
9 R
z.o
5C
.0
1.2
2.5
3.3
o n
o.U
5.0
3.6
5.1
Mean
n n
1 O.U
15.7
1 O Q
1 Z.O
7.5
R 4
D.H
5.6
R 4
o.^
3.8
0 0
o.O
4.0
6.6
2.2
R Q
\j.;y
9.0
1 R
i .y
0.8
1.2
1.3
3.1
2.7
Sticky paper
Sample
size
19
i ^
12
1 9
l z
12
19
i ^
11
1 9
i z
12
1 9
I Z
12
2
12
2
12
3
11
1 9
1 Z
11
12
8
9
3
3
Min.
9D
£U
36
1 R
1 U
13
12
7
/
3
3
4
5
17
5
20
16
1 9
1 Z
10
1 U
15
2
1
3
14
7
Max
74
/ H
84
CO
DZ
74
RR
uo
76
4R
*r3
69
CO
Oo
66
10
65
21
62
RQ
oy
43
79
1 R
I O
CO
OO
52
28
22
1 O
iy
58
19
41
Mean
RR
Uo
65
AA
HH
48
TR
O J
40
oo
zo
28
1 Q
I O
32
34
28
OQ
oy
42
OQ
OO
31
7
12
22
Rubber cracking
Sample
size
4Q
to
51
R1
o l
51
R9
o^
51
47
t /
51
R1
O I
51
7
52
9
52
94
Z*T
10
48
R1
O 1
50
45
38
1 O
1 Z
39
12
16
Min
n
\j
0
n
\j
0
Q
0
n
U
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
9?7
.^o /
.174
9^4
.^o^
.300
.323
.378
4^1
.HO 1
.365
A1P.
.M- I O
.550
0
573
0
398
OOR
ZOD
0
282
con
DOU
549
653
363
I
318
i
406
Mean
057
.050
.078
.043
.082
.073
nfi
. 1 OU
.109
in.9
. 1 UZ
.107
.096
.116
057
94 Q
ZHo
210
100
105
051
M
tn
n
w
-------
Table B-1 (continued). DATA SUMMARY
State/city
NEW HAMPSHIRE (c
Portsmouth
Cannon Mountain
NEW JERSEY
May's Landing
Perth Amboy
Elizabeth
Penns Grove
Camden
Trenton
Metuchen
MEW MEXICO
Shiprock
Farmington
Dulce
Sunland Park
Anthony
slEWYORK
Staten Island
Year
ontinued]
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
4.1
1.4
1.4
7.1
4.9
3.3
15.1
2.7
2.0
4.2
3.1
3.9
4.9
0.3
0.4
0.3
8.1
0.3
0.2
9.9
0.3
0.3
4.2
3.6
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
50
55
61
58
57
44
55
56
44
40
52
5
7
4
6
2
18
4
8
63
63
Quarterly steel
Sample
size
4
1
4
2
4
3
4
3
4
4
3
3
1
1
3
4
4
4
3
4
3
4
3
4
4
4
4
Min.
74
12
58
53
86
84
68
57
77
82
68
33
79
18
89
1
1
2
1
0
1
0
13
0
1
99
83
Max.
146
13
70
114
118
121
89
130
99
96
74
67
79
18
115
9
4
3
2
2
5
9
53
4
14
152
120
Mean
102
66
84
100
104
74
96
86
86
70
46
98
4
3
2
1
1
3
4
28
2
5
114
104
Fabric No. 1
Sample
size
1
4
1
3
4
1
3
4
4
4
4
3
4
3
2
2
3
4
3
4
4
4
3
3
4
4
4
3
4
Min.
20.5
19.3
23.3
14.9
13.3
16.0
14.1
15.9
11.9
15.1
14.0
16.2
15.5
17.0
13.2
16.4
18.0
11.0
16.7
10.9
14.6
8.8
13.4
6.2
14.3
7.4
13.3
17.6
17.1
Max.
20.5
21.1
23.3
21.8
19.5
16.0
16.5
21.6
16.3
19.2
17.4
18.3
19.7
20.3
17.1
19.6
23.4
17.6
17.3
13.5
16.4
13.5
15.4
14.8
20.0
13.9
18.3
18.8
23.9
Mean
20.2
18.2
16.6
15.3
19.1
14.6
17.7
16.2
16.9
17.3
18.3
15.2
18.0
20.9
14.4
17.0
11.8
15.6
11.3
14.1
10.6
17.8
10.2
16.5
18.1
20.2
Fabric No. 2
Sample
size
1
1
4
3
3
4
4
2
4
4
4
3
4
3
Win.
8.5
1.6
1.0
2.9
2.6
1.1
2.9
4.3
1.2
2.0
0.9
1.6
0.9
1.4
Wax.
8.5
1.6
1.6
8.7
4.8
5.4
4.9
7.5
3.4
4.2
1.5
4.1
2.4
2.1
Mean
1.3
5.1
3.4
2.5
3.7
5.9
2.7
2.9
1.1
2.9
1.4
1.8
!
-------
93
29
s
H
r
n
w
I
t_N
8
H
Table B-1 (continued). DATA SUMMARY
State/city
NEW HAMPSHIRE (c
Portsmouth
Cannon Mountain
NEW JERSEY
May's Landing
Perth Amboy
Elizabeth
Penns Grove
Camden
Trenton
Metuchen
NEW MEXICO
Shiprock
Farmington
Dulce
Sunland Park
Anthony
NEW YORK
Staten Island
Year
ontinued)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRQ
Fabric No. 3
Sample
size
1
4
1
2
4
3
4
3
4
4
3
4
3
2
2
3
4
4
4
4
4
3
4
4
4
4
4
A
Min.
32.2
29.4
19.5
16.6
18.3
21.8
35.8
33.7
44.1
28.2
36.8
26.5
40.4
25.1
32.8
33.3
7.5
12.7
12.8
14.2
6.2
9.9
10.2
14.7
6.5
12.8
32.2
1A Q
Max.
32.2
40.2
19.5
21.3
29.9
36.8
42.8
45.4
51.6
42.3
49.5
37.3
47.2
39.8
36.8
43.1
20.2
15.8
16.6
18.3
11.7
12.8
14.7
16.1
12.4
15.0
45.2
AA A
Mean
34.0
19.0
21.8
30.1
40.2
37.9
48.9
35.2
44.4
33.1
44.6
32.4
34.8
39.5
14.7
14.2
14.4
15.8
9.9
11.0
12.9
15.5
10.6
14.2
37.4
At R
Fabric No. 4
Sample
size
1
1
4
4
4
4
3
2
4
3
4
2
3
4
Min.
22.9
28.9
20.1
8.5
11.7
15.3
9.1
13.6
12.5
12.8
11.7
9.9
10.2
16.5
Max.
22.9
28.9
37.4
28.6
24.3
30.9
24.1
13.7
20.0
17.5
22.0
11.0
20.7
27.1
Mean
27.5
17.2
16.6
21.7
17.1
13.6
15.4
14.8
15.0
10.4
15.1
21.1
Fabric No. 5
Sample
size
4
3
1
4
4
3
3
2
3
3
4
2
4
4
A
Min.
8.2
7.9
12.4
5.6
4.5
7.7
4.9
6.2
7.5
10.8
8.7
10.2
9.5
8.4
5 H
Max.
14.0
16.4
12.4
13.9
14.8
18.7
10.9
15.6
16.8
12.9
13.0
10.2
13.7
12.5
IK ~i
Mean
11.0
13.4
9.5
9.1
11.8
7.0
10.9
10.6
12.0
10.4
10.2
11.7
10.6
1 1 K
Fabric No. 6
Sample
size
4
3
4
4
2
3
2
3
3
4
3
4
4
A
Min
7.5
5.2
9.7
8.4
7.7
8.3
5.1
8.2
6.3
5.4
2.7
5.5
3.5
in n
Max
16.7
12.7
13.1
13.0
12.9
14.6
11.3
12.8
10.1
6.6
4.7
8.5
9.4
n K
Mean
10.8
8.6
11.4
10.0
10.3
12.5
8.2
0.2
7.8
6.2
3.9
6.8
6.0
1 Q
Fabric No. 7
Sample
size
4
3
1
3
4
3
3
2
3
3
4
3
4
4
A
Min
5.6
3.3
15.4
5.1
3.5
9.3
6.5
3.7
8.6
2.4
3.6
3.0
3.9
1.9
o n
Max
20.8
8.9
15.4
11.9
15.3
20.0
13.4
11.2
13.7
7.1
7.7
5.7
0.9
8.2
Mean
11.7
5.8
7.6
7.4
3.8
1.1
7.4
0.7
5.1
6.0
4.0
6.7
5.0
-------
Table B-1 (continued). DATA SUMMARY
State/city
NEW HAMPSHIRE (c
Portsmouth
Cannon Mountain
NEW JERSEY
May's Landing
Perth Amboy
Elizabeth
Penns Grove
Camden
Trenton
Metuchen
MEW MEXICO
Shiprock
Farmington
Dulce
Sunland Park
Anthony
MEW YORK
Staten Island
Year
ontinued
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
2
1
4
4
3
2
3
4
3
4
3
4
4
4
Min.
10.7
10.4
5.1
6.4
6.7
7.1
4.1
4.9
8.0
4.9
3.5
3.4
4.0
2.6
7.4
Max.
15.1
14.6
5.1
10.9
10.2
14.2
8.7
9.7
19.8
12.5
9.9
8.8
17.0
8.1
12.6
Mean
13.4
12.5
8.6
8.8
11.0
6.4
7.3
12.0
7.9
7.2
5.3
8.4
5.2
10.0
Fabric No. 9
Sample
size
4
3
3
4
2
3
2
4
3
4
3
4
4
4
Min.
17.1
8.5
18.3
15.2
13.9
10.1
17.8
13.0
9.2
9.6
5.1
6.8
4.5
16.9
Max.
29.6
17.1
31.4
28.3
20.9
23.4
37.7
34.8
15.6
17.1
14.8
17.2
17.0
36.3
Mean
23.8
14.0
23.4
21.7
17.4
17.5
27.8
23.2
12.3
11.8
9.5
12.8
9.8
25.2
Quarterly nylon
Sample
size
1
3
1
3
3
1
3
2
4
4
3
4
3
3
2
4
4
4
4
4
2
4
3
4
4
3
4
2
4
Min.
4
2
0
0
0
0
10
8
10
4
3
0
3
0
0
1
0
0
0
0
0
0
0
0
0
0
0
5
0
Max.
4
5
0
0
0
0
80
14
17
82
10
6
18
4
20
4
3
0
0
0
0
0
0
2
1
0
0
10
6
Mean
3.7
0
0
33.3
11.0
12.5
30.2
6.0
3.5
9.0
1.7
10.0
2.5
1.2
0
0
0
0
0
0
0.8
0.5
0
0
7.5
1.8
Monthly nylon
Sample
size
3
11
3
11
9
3
11
10
12
12
12
12
11
12
10
10
11
11
11
11
10
9
11
10
12
11
12
10
12
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
1
9
0
0
0
0
31
21
5
76
5
4
3
4
24
1
1
0
1
0
0
0
0
1
3
0
0
5
3
Mean
2.6
0
0
6.9
5.2
1.9
12.0
2.2
0.8
0.8
1.1
5.7
0.1
0.4
0
0.1
0
0
0
0
0.2
0.9
0
0
1.9
0.8
Silver tarnishing
Sample
size
2
12
2
11
12
2
12
12
12
12
12
12
12
10
9
7
11
12
10
12
8
9
8
9
11
12
12
10
12
Min.
65
25
27
11
38
47
35
44
28
21
65
41
59
32
40
35
42
15
13
29
21
4
1
33
30
10
11
56
55
Max.
79
85
27
41
76
55
70
74
89
82
88
91
92
86
86
78
82
77
70
64
55
16
13
92
86
66
65
82
85
Mean
62
27
56
52
60
68
64
74
69
77
74
68
63
64
34
32
43
35
8
5
61
59
33
33
67
72
"8
i
pa
s?
s
-------
z
H
1
Pi
w
r
r
PI
"0
JO
o
Table B-1 (continued). DATA SUMMARY
State/city
NEW HAMPSHIRE (c
Portsmouth
Cannon Mountain
NEW JERSEY
May's Landing
Perth Amboy
Elizabeth
Penns Grove
Camden
Trenton
Metuchen
NEW MEXICO
Shiprock
Farmington
Dulce
Sunland Park
Anthony
NEW YORK
Staten Island
Year
ontinued)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
3
9
3
11
10
3
12
12
12
12
12
12
12
11
8
12
10
12
12
12
10
11
11
9
11
12
12
11
12
Min.
3.4
0.4
0.2
0.0
0.1
0.0
1.6
0.4
0.9
0.0
0.7
0.8
0.9
0.9
1.0
0.6
0.2
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
1.1
0.7
Max.
6.2
6.5
0.3
0.3
0.8
0.5
3.6
4.2
3.0
4.0
2.3
2.1
4.2
3.2
2.4
2.1
2.0
0.1
0.2
0.1
0.1
0.2
0.1
6.5
4.0
0.2
0.3
3.0
5.1
Mean
2.4
0.1
0.4
2.5
1.8
1.9
1.5
1.2
1.2
2.6
2.1
1.6
1.1
1.3
0.0
0.0
0.0
0.0
0.0
0.0
1.4
1.9
0.1
0.1
2.0
1.9
Lead plates
Sample
size
9
10
2
10
12
4
10
10
6
12
10
9
9
12
11
Min.
3
0
2
7
3
6
14
4
6
0
0
0
1
0
7
Max.
35
2
2
26
23
7
32
14
17
1
1
1
30
2
32
Mean
15
1
16
11
21
7
10
0
0
0
15
1
16
Dustfall
Sample
size
3
12
2
12
10
3
12
11
12
12
12
12
12
12
5
10
9
11
9
11
11
11
11
9
12
12
12
10
12
Min.
1.6
1.1
0.1
0.2
0.7
2.9
4.0
2.1
3.8
3.3
3.2
2.3
6.5
4.5
3.0
2.1
1.5
0.8
1.1
1.2
1.3
0.9
0.6
0.7
0.7
1.4
1.7
0.8
2.1
Max.
4.3
10.8
0.6
3.3
3.6
3.3
12.7
8.6
11.2
14.7
7.8
6.1
17.4
13.8
7.5
7.2
5.8
5.9
3.8
7.8
4.2
33.7
4.1
5.6
4.1
7.8
7.9
9.9
6.6
Mean
3.6
1.3
1.9
7.0
5.7
8.0
6.3
5.1
4.0
10.1
9.1
5.0
3.1
3.2
2.2
2.8
2.3
1.8
2.0
2.7
2.6
4.1
3.7
3.7
4.1
Sticky paper
Sample
size
3
6
3
5
10
2
12
10
12
12
12
11
12
9
7
7
10
12
8
11
8
12
6
9
10
12
10
11
12
Min.
21
11
2
1
0
10
14
9
5
2
6
11
38
32
16
6
6
15
16
15
7
1
2
32
22
18
11
4
11
Max
45
60
6
19
20
20
63
66
58
67
40
45
74
79
43
47
57
90
70
85
62
58
46
70
71
75
55
4
57
Mean
33
6
37
40
24
33
21
27
55
37
32
30
32
58
46
43
30
20
23
53
49
46
33
24
35
Rubber cracking
Sampl
size
9
26
11
32
35
11
51
51
51
52
49
47
44
42
26
29
43
42
36
40
42
48
30
37
45
50
49
44
52
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
0
.337
0
.388
.436
.318
.282
.399
.307
.209
.391
.275
.368
.323
.474
.171
.318
.488
.496
.539
494
524
515
481
360
426
398
417
441
Mean
.080
.059
.155
.076
.084
.076
.063
.095
.070
.106
.088
051
050
115
186
146
139
144
156
133
175
160
158
103
102
099
-------
Table B-1 (continued). DATA SUMMARY
State/city
NEWYORK(contin
Brooklyn
Mineola
White Plains
Albany
Niagara Falls
Buffalo
Binghamton
Petersburg
Albany
Long Island
Ticonderoga
Rooseveltown
Cheektowaga
Buffalo
Niagara Falls
(266)
Niagara Falls
I7fi7>
Year
ued)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
4.8
4.0
3.0
2.9
1.0
2.3
3.0
6.0
7.1
1.6
1.6
1.0
0.9
3.4
3.0
3.0
2.1
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
43
39
64
61
53
52
26
46
40
72
88
36
40
37
27
41
44
42
36
Quarterly steel
Sample
size
4
4
4
4
3
3
4
2
4
3
4
3
4
3
4
4
4
3
2
3
1
3
1
2
1
1
Min.
60
46
86
102
71
69
60
55
58
54
94
104
33
43
16
18
44
32
102
83
42
51
55
5
50
179
Max.
74
86
111
115
136
108
84
83
69
71
106
164
46
77
39
29
76
83
185
155
42
63
55
62
50
179
Mean
68
70
94
107
102
89
72
69
62
65
98
128
40
59
28
24
56
58
144
115
55
34
Fabric No. 1
Sample
size
4
4
4
4
4
2
4
1
3
4
4
3
4
2
4
4
4
3
2
3
1
3
1
2
Min.
11.6
15.0
11.5
13.8
14.5
16.2
14.4
17.8
19.1
20.6
18.0
20.0
12.6
16.3
12.6
14.4
11.7
13.7
21.1
19.6
16.2
12.8
16.9
19.5
Max.
15.3
20.6
18.6
22.0
18.6
20.9
18.7
17.8
23.0
26.4
21.4
25.9
15.3
19.7
16.8
19.5
16.0
16.1
21.5
24.2
16.2
18.8
16.9
20.6
Mean
14.1
17.2
15.6
18.3
16.4
18.6
16.0
21.5
23.2
20.3
22.9
14.1
18.0
14.8
16.8
13.8
15.0
21.3
21.8
15.9
20.0
Fabric No. 2
Sample
size
4
4
4
4
4
4
4
4
4
2
1
1
Min.
2.7
3.0
2.6
1.6
2.4
5.2
2.0
0.9
1.8
3.3
1.0
2.0
t/lax.
8.8
5.1
4.4
6.4
9.9
10.2
4.8
1.2
7.4
8.4
1.0
2.0
Wean
4.6
4.1
3.1
3.7
6.2
7.0
3.0
1.1
4.0
5.8
8
i
w
I
cw
-------
Table B-1 (continued). DATA SUMMARY
State/city
NEWYORK(continu
Brooklyn
Mineola
White Plains
Albany
Niagara Falls
Buffalo
Binghamton
Petersburg
Albany
Long Island
Ticonderoga
Rooseveltown
Cheektowaga
Buffalo
Niagara Falls
(266)
Niagara Falls
(267)
Year
ed)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1367
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 3
Sample
size
4
4
4
4
4
2
4
1
3
4
4
4
4
2
4
4
4
3
2
3
1
3
3
Min.
49.2
48.2
30.4
45.6
29.1
37.9
17.7
27.7
17.7
23.6
27.9
36.1
23.3
27.9
15.3
15.1
23.9
26.7
18.1
31.1
18.7
18.0
20.1
Max.
53.2
60.9
46.9
54.7
41.5
46.2
31.0
27.7
23.3
27.5
41.7
43.9
43.8
29.4
19.3
20.2
40.6
41.2
24.5
40.7
18.7
18.6
34.1
Mean
50.7
54.5
39.6
49.5
33.6
42.0
23.4
20.2
25.0
35.6
39.2
30.7
28.6
17.0
17.9
28.9
35.1
21.3
35.4
18.4
25.3
Fabric No. 4
Sample
size
4
4
4
4
3
4
4
4
4
1
1
Min.
10.2
14.5
12.9
11.8
12.9
9.4
11.4
15.6
7.7
35.1
18.7
Max.
20.3
33.9
31.7
26.6
24.7
20.5
36.5
30.0
20.7
35.1
18.7
Mean
14.9
22.9
22.0
17.3
19.5
14.2
22.0
22.8
13.8
Fabric No. 5
Sample
size
4
4
2
2
4
4
2
4
1
2
3
3
Min.
3.9
7.3
7.5
5.1
7.1
4.1
8.2
9.9
5.4
12.3
9.0
9.9
Max.
9.1
15.6
14.7
6.2
14.1
7.9
13.3
15.3
5.4
19.4
14.3
15.0
Mean
6.4
11.1
11.1
5.6
10.3
5.8
10.8
13.1
15.8
12.4
13.2
Fabric No. 6
Sample
size
4
4
2
1
4
4
2
4
3
3
3
3
Min.
7.2
9.9
7.1
8.7
6.2
10.4
7.7
3.8
6.8
5.9
4.5
7.7
Max
11.6
11.8
10.9
8.7
13.2
18.3
8.7
5.3
10.1
9.7
7.0
10.5
Mean
9.9
11.0
9.0
10.3
15.6
8.2
4.6
8.4
7.8
5.6
9.5
Fabric No. 7
Sample
size
4
4
3
2
4
4
2
4
3
2
3
2
Min
4.0
3.7
8.0
9.8
6.4
6.6
6.8
2.4
5.0
8.3
2.5
2.4
Max
14.7
14.3
16.2
14.8
12.3
20.5
12.6
0.3
9.7
4.1
7.9
2.7
Mean
8.8
8.7
11.0
12.3
9.4
3.0
9.7
6.9
7.3
1.2
4.4
7.6
w
?o
I
w
c/o
C
2
n
w
2
M
O
-------
Table B-1 (continued). DATA SUMMARY
State/city
NEW YORK (continu
Brooklyn
Mineola
White Plains
Albany
Niagara Falls
Buffalo
Binghamton
Petersburg
Albany
Long Island
Ticonderoga
Rooseveltown
Cheektowaga
Buffalo
Niagara Falls
(266)
Niagara Falls
(267)
Year
ed)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
4
2
1
4
4
2
4
3
2
3
3
Min.
5.1
6.5
6.7
5.8
7.4
8.5
4.5
8.7
4.3
13.3
4.2
8.1
Max.
16.4
17.3
15.5
5.8
12.4
12.2
8.7
21.2
16.7
18.3
10.7
11.7
Mean
9.5
11.6
11.1
8.9
10.2
6.6
13.6
9.6
15.8
7.4
10.3
Fabric No. 9
Sample
size
4
4
2
1
4
4
3
4
2
2
3
3
1
1
1
Min.
16.4
16.3
14.7
16.1
12.6
19.3
9.9
7.9
14.6
16.3
9.2
18.1
20.5
20.1
32.9
Max.
31.7
34.2
32.5
16.1
23.5
33.6
43.0
27.5
19.7
25.5
25.2
29.0
20.5
20.1
32.9
Mean
24.0
26.0
23.6
18.8
25.7
24.9
15.4
17.2
20.9
18.4
21.8
Quarterly nylon
Sample
size
4
4
3
3
3
4
4
2
4
4
3
4
4
3
3
4
4
3
1
3
1
4
4
1
1
1
Min.
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
Max.
14
22
1
4
0
12
1
2
0
1
2
2
0
0
0
16
41
19
0
0
0
4
1
0
0
0
Mean
7.0
8.0
0.7
1.7
0
5.0
0.2
1.5
0
0.2
1.0
0.8
0
0
0
4.0
18.2
11.3
0
1.5
0.2
Monthly nylon
Sample
size
12
12
11
11
12
12
12
6
10
12
12
11
12
11
11
12
12
12
5
11
5
12
3
12
4
4
4
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
6
7
1
8
0
1
2
0
0
0
4
2
0
0
1
0
17
10
2
2
2
4
1
5
0
0
1
t/lean
3.0
3.6
0.2
1.4
0
0.2
0.2
0
0
0
0.3
0.2
0
0
0.1
0
5.8
2.0
0.2
0.8
0.6
Silver tarnishing
Sample
size
12
12
12
12
12
11
12
6
11
12
12
11
12
11
12
12
12
12
5
11
3
12
3
12
4
4
4
Min.
46
64
43
29
38
27
40
40
59
60
85
80
24
24
7
9
25
32
53
37
66
57
56
41
46
59
78
Max.
93
88
71
73
87
71
81
62
98
93
96
96
50
63
47
45
81
78
72
77
86
93
78
95
68
75
95
Mean
78
80
55
57
54
56
56
50
80
78
91
88
38
42
20
25
52
57
54
82
72
I
w
I
i
5
-------
I
Table B-1 (continued). DATA SUMMARY
State/city
NEW YORK (continuf
Brooklyn
Mineola
White Plains
Albany
Niagara Falls
Buffalo
Binghamton
Petersburg
Albany
Long Island
Ticonderoga
Rooseveltown
Cheektowaga
Buffalo
Niagara Falls
(266)
Niagara Falls
(9R7)
Year
3d)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
12
12
12
11
12
10
12
7
11
11
12
10
12
9
12
11
12
12
5
9
3
11
3
11
4
3
3
Min.
2.0
1.6
0.8
0.2
1.0
0.7
0.9
0.5
0.6
0.5
2.4
2.0
0.2
0.0
0.0
0.0
0.8
0.5
0.4
0.3
0.4
0.0
0.6
0.0
0.7
0.9
0.6
Max.
5.9
7.7
2.8
3.6
2.6
3.1
1.9
2.2
1.5
2.2
5.5
6.3
0.9
1.3
1.9
0.4
3.0
3.9
0.9
1.1
0.7
1.3
0.9
1.8
1.0
1.4
1.8
Mean
3.6
3.1
1.6
1.5
1.5
1.4
1.4
1.5
0.9
1.0
3.9
3.8
0.5
0.6
0.3
0.1
1.7
1.6
0.6
0.4
0.6
Lead plates
Sample
size
12
10
8
6
11
8
11
9
11
9
11
5
4
4
4
Min.
10
6
6
9
5
15
0
0
5
2
0
0
5
7
7
Max.
44
24
18
18
14
44
10
2
26
11
7
13
6
14
16
Mean
22
11
11
13
8
30
4
1
11
5
3
Dustfall
Sample
size
12
10
12
12
11
11
12
7
11
12
12
10
12
11
12
12
11
12
5
10
3
12
2
10
4
4
4
Min.
12.2
9.0
1.5
1.1
0.3
1.8
3.8
1.5
3.2
2.7
6.2
2.7
2.9
2.1
0.9
0.4
7.7
6.0
2.2
1.2
1.0
0.5
2.0
0.9
5.7
5.6
14.9
Max.
43.2
38.5
10.2
6.5
6.8
3.6
10.9
7.3
15.3
9.6
13.5
10.8
7.4
7.2
8.0
4.4
18.1
18.0
5.7
10.8
6.8
3.8
2.5
3.1
11.8
6.4
32.2
Mean
22.2
15.1
3.9
3.0
2.6
2.6
6.0
4.5
6.5
5.8
10.0
7.8
5.0
4.7
2.6
2.2
11.5
8.4
4.2
1.9
2.1
Sticky paper
Sample
size
12
12
12
12
12
12
12
5
8
12
11
10
12
8
12
10
12
12
5
10
3
6
3
12
3
4
4
Min.
18
43
3
4
10
7
10
19
23
18
33
45
5
9
0
1
8
9
5
3
4
1
7
5
15
20
54
Max
79
81
43
54
42
63
57
56
62
64
74
81
35
53
4
8
62
68
24
38
9
30
11
30
23
47
75
Mean
59
64
25
32
24
32
28
37
39
55
56
20
28
2
3
34
36
15
10
14
Rubber cracking
Sample
size
52
49
49
49
50
50
48
26
36
52
41
46
50
36
52
46
49
51
23
41
9
26
11
50
16
16
16
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.239
.318
.504
.272
.549
.285
.435
.335
.428
.533
.295
203
397
227
411
411
257
199
655
683
0
426
057
504
132
287
132
Mean
.046
.052
.093
.063
.136
.070
.070
.030
.104
.089
.037
.040
.072
.064
.124
.084
.059
.054
210
078
092
3
o
w
"0
50
-------
00
Table B-1 (continued). DATA SUMMARY
State/city
NORTH CAROLINA
Charlotte
(31)
Charlotte
(32)
Spray
Chapel Hill
(237)
Chapel Hill
(238)
NORTH DAKOTA
Grand Forks
Fargo
OHIO
Cincinnati
(6)
Toledo
Columbus
Youngstown
Steubenville
Marietta
Ironton
Cincinnati
(70)
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.0
0.9
1.1
1.2
1.2
0.7
0.7
1.6
1.9
2.0
1.5
1.5
2.9
7.1
3.5
6.0
5.5
1.6
1.2
1.9
2.8
1.5
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
22
18
31
22
21
18
17
17
20
18
40
43
31
34
50
45
61
62
46
38
51
30
36
Quarterly steel
Sample
size
4
4
4
4
3
3
3
4
4
4
3
4
4
4
4
4
4
4
3
4
4
4
3
4
4
Min.
16
9
22
8
18
17
8
7
6
24
19
46
56
33
41
56
40
84
93
3
44
64
95
48
39
Max.
37
27
46
28
29
18
14
30
23.
55
33
80
79
47
46
77
102
111
132
93
158
80
114
59
54
Mean
28
18
33
18
23
18
10
14
13
43
25
58
66
40
44
69
72
94
113
53
90
72
106
52
46
Fabric No. 1
Sample
size
4
4
4
4
1
2
1
1
3
1
1
4
4
4
4
4
3
4
4
4
4
3
3
3
3
4
2
Min.
13.5
19.5
12.8
18.3
14.0
16.5
18.1
15.0
15.9
15.0
19.6
13.5
15.3
16.6
20.6
13.1
15.9
13.0
16.8
12.4
17.8
11.7
17.9
15.5
19.4
16.8
190
Max.
18.0
23.1
16.7
20.6
14.0
20.3
18.1
15.0
22.0
15.0
20.3
17.0
18.6
20.3
24.1
16.4
22.0
16.7
22.6
16.6
21.5
16.6
23.9
21.5
28.3
21.9
24.9
Wean
16.2
21.3
15.0
19.8
18.4
18.2
20.1
15.6
17.5
18.8
22.2
14.8
18.0
15.3
19.7
14.8
19.5
14.1
20.9
13.8
23.2
19.2
22.0
Fabric No. 2
Sample
size
4
4
1
1
1
4
4
4
4
4
4
3
4
Win.
2.1
1.9
3.0
0.6
5.5
2.8
1.7
1.3
4.0
2.8
0.7
2.4
1.4
Wax.
6.4
4.7
3.0
0.6
5.5
5.5
10.5
2.9
7.2
6.3
2.4
7.0
3.9
Wean
3.7
2.8
4.1
5.0
1.9
5.5
5.2
1.6
4.0
2.6
I
t/J
-------
Table B-1 (continued). DATA SUMMARY
State/city
NORTH CAROLINA
Charlotte
(31)
Charlotte
(32)
Spray
Chapel Hill
(237)
Chapel Hill
(238)
NORTH DAKOTA
Grand Forks
Fargo
OHIO
Cincinnati
(6)
Toledo
Columbus
Youngstown
Steubenville
Marietta
Ironton
Cincinnati
(70)
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 3
Sample
size
4
4
4
4
1
1
3
1
1
3
1
3
4
4
4
4
4
3
4
4
4
3
3
3
4
3
4
2
Min.
18.8
22.8
23.0
24.4
26.6
44.4
20.3
20.9
10.5
14.7
9.7
18.2
28.0
32.0
19.1
19.3
17.5
23.6
26.9
33.7
22.0
33.1
21.0
24.9
11.4
23.8
17.5
25.9
Max.
24.3
28.7
29.8
37.1
26.6
44.4
22.9
20.9
10.5
18.5
9.7
23.9
36.5
39.6
21.5
36.4
23.2
26.8
37.7
43.7
36.6
44.4
25.7
27.2
24.0
28.4
47.6
29.0
Mean
22.2
26.6
26.6
30.2
21.7
17.2
20.7
30.4
34.8
20.5
26.9
19.6
25.5
31.0
38.7
30.1
39.7
22.9
25.7
17.8
26.3
27.3
27.4
Fabric No. 4
Sample
size
4
4
1
1
1
4
4
4
4
3
3
4
3
Min.
12.9
16.2
28.5
10.2
6.5
10.3
12.1
140
10.2
10.1
12.7
9.8
9.1
Max.
31.2
29.6
28.5
10.2
6.5
20.2
22.3
24.4
22.2
21.3
28.6
23.1
20.9
Mean
20.2
21.8
14.8
16.6
18.5
15.5
15.8
20.4
15.4
14.0
Fabric No. 5
Sample
size
4
4
3
1
3
3
3
4
3
4
4
3
3
Min.
7.5
8.1
13.1
15.5
7.2
5.8
5.3
6.6
6.0
3.8
4.6
5.7
6.5
Max.
15.2
15.7
19.4
15.5
11.5
9.9
11.9
12.7
13.6
12.6
11.5
17.0
11.8
Mean
10.6
12.2
16.5
9.5
8.5
9.3
9.6
9.1
7.9
8.0
12.1
8.4
Fabric No. 6
Sample
size
4
4
1
3
1
4
4
3
4
3
4
4
4
3
2
Min.
7.4
6.9
10.8
3.4
4.7
5.1
5.2
8.8
7.8
8.4
10.3
6.7
6.4
8.6
8.2
Max
17.1
12.6
10.8
6.4
4.7
9.0
15.4
16.5
13.3
9.2
14.8
12.4
10.3
13.4
12.9
Mean
11.3
9.9
4.7
7.7
10.4
12.1
10.5
8.7
12.9
9.4
8.7
10.6
0.6
Fabric No. 7
Sample
size
4
4
3
1
4
3
4
4
3
4
4
4
3"
4
Min
4.2
3.3
3.5
3.6
6.1
9.9
4.6
4.6
3.7
12.7
7.8
3.8
10.1
4.5
Max
20.8
10.5
6.9
3.6
12.1
16.9
12.8
14.1
13.2
24.1
11.6
10.1
14.4
11.3
Mean
13.6
7.4
5.3
7.8
3.3
7.7
0.3
8.6
8.2
9.9
7.2
1.8
8.0
w
N"<
n
w
9
§
«
n
H
-------
Table B-1 (continued). DATA SUMMARY
State/city
NORTH CAROLINA
Charlotte
(3D
Charlotte
(32)
Spray
Chapel Hill
(237)
Chapel Hill
(238)
NORTH DAKOTA
Grand Forks
Fargo
OHIO
Cincinnati
(6)
Toledo
Columbus
Youngstown
Steubenville
Marietta
Ironton
Cincinnati
(70)
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
4
3
1
3
3
4
4
3
4
4
3
3
2
Min.
4.1
5.7
8.4
10.3
5.1
8.7
3.1
6.6
5.4
7.2
4.0
5.8
4.3
5.9
Max.
10.4
24.8
19.6
10.3
7.1
13.9
10.7
12.2
8.5
10.2
10.2
10.0
9.3
6.3
Mean
6.9
12.8
14.1
_ - - - -
6.2
10.5
6.2
9.2
6.8
8.4
7.4
7.8
6.2
6.1
Fabric No. 9
Sample
axe
4
4
3
2
3
4
4
4
3
4
4
3
2
2
Min.
16.9
18.0
20.2
19.4
7.5
10.1
13.6
17.6
10.8
15.7
13.9
17.0
22.9
14.3
Max.
28.3
27.3
30.0
22.7
21.0
26.0
21.8
25.4
19.3
25.2
29.0
34.9
32.2
33.2
Mean
21.6
22.7
25.3
21.0
15.8
19.8
17.3
22.9
15.0
19.9
20.8
25.3
27.6
23.8
Quarterly nylon
Sample
size
2
3
4
4
1
4
3
3
1
4
1
3
4
4
4
4
4
4
4
4
3
4
4
3
4
2
4
4
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
1
0
0
0
0
11
0
0
0
0
0
0
2
3
1
0
0
0
0
1
7
0
0
0
2
0
2
Mean
0
0.3
0
0
0
3.7
0
0
0
0
0.5
0.8
0.2
0
0
0
0
0.3
1.8
0
0
0
1.0
0
0.5
Monthly nylon
Sample
size
11
12
12
12
5
11
9
9
2
12
2
12
12
12
12
12
12
12
12
12
12
12
11
12
12
11
12
11
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
0
0
2
3
0
0
Mean
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.2
0
0
0
0.2
0.3
0
0
Silver tarnishing
Sample
size
12
12
12
12
3
12
9
9
2
12
2
12
12
12
12
12
12
12
12
12
12
12
12
12
12
10
11
10
Min.
8
42
43
46
38
22
24
10
29
12
21
13
30
34
53
41
30
33
74
73
65
81
35
33
77
84
48
22
Max.
76
78
80
79
42
64
37
40
36
47
30
33
83
81
89
95
93
63
90
92
94
92
87
76
95
95
80
86
Mean
60
59
61
59
42
33
25
26
23
57
55
78
71
64
48
82
81
80
86
57
58
88
90
63
59
f
V)
3
-------
Table B-1 (continued). DATA SUMMARY
State/city
NORTH CAROLINA
Charlotte
(31)
Charlotte
(32)
Spray
Chapel Hill
(237)
Chapel Hill
(238)
NORTH DAKOTA
Grand Forks
(82)
Fargo
OHIO
Cincinnati
(6)
Toledo
Columbus
Youngstown
Steubenville
Marietta
Ironton
Cincinnati
(70)
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
12
11
12
12
5
11
9
9
2
9
2
11
11
12
12
12
12
12
12
11
12
12
11
10
12
9
12
10
Min.
0.1
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.3
0.0
0.6
0.0
0.9
0.8
0.3
0.2
0.7
0.8
1.1
1.0
0.4
0.5
0.7
0.7
0.4
0.4
Max.
0.7
0.8
0.5
0.8
0.3
0.4
0.1
0.1
0.3
0.4
0.4
0.4
1.5
2.2
2.6
1.9
1.2
1.5
1.8
2.2
3.0
4.1
1.0
1.4
1.6
. 1.7
1.1
1.8
Mean
0.4
0.2
0.3
0.3
0.1
0.0
0.0
0.1
0.1
0.9
0.8
1.4
1.2
0.5
0.5
1.3
1.3
2.0
1.8
0.7
0.7
1.0
1.0
0.8
0.8
Lead plates
Sample
size
10
11
10
9
6
11
11
11
12
11
11
9
11
9
9
Min.
2
0
0
0
0
0
0
2
6
2
5
6
2
4
7
Max.
5
6
3
2
1
4
2
15
17
10
19
31
8
10
14
Mean
3
3
1
0
0
1
1
6
10
4
10
14
5
8
fi
Dustfall
Sample
size
12
12
12
12
5
11
9
9
2
11
2
12
12
12
11
12
11
12
12
12
12
12
12
12
12
10
11
9
Min.
2.7
3.8
1.7
2.1
1.0
2.0
0.9
1.8
2.5
0.8
1.9
1.0
3.9
3.2
6.5
6.7
2.0
2.9
8.9
10.6
11.0
8.5
3.3
2.1
2.7
1.4
4.1
R4
Max.
8.6
9.5
4.9
5.5
7.9
9.3
4.3
3.8
4.5
14.2
2.5
9.2
36.0
8.7
13.3
12.5
6.6
6.2
27.3
26.7
25.4
30.6
8.7
9.2
39.9
32.0
12.9
11 4
Mean
5.3
6.2
3.2
3.4
4.6
2.1
2.8
8.0
4.7
8.2
5.6
8.6
9.1
4.0
4.5
15.4
15.5
17.5
19.4
5.4
5.4
21.2
22.4
7.8
7 7
Sticky paper
Sample
size
12
10
12
10
5
11
9
8
3
10
3
12
12
12
12
12
12
12
12
12
12
12
10
9
12
8
11
R
Min.
12
8
11
6
2
1
1
1
5
5
35
16
28
8
27
36
7
6
21
50
20
14
3
3
29
68
10
17
Max.
52
65
43
51
15
44
10
29
56
57
56
73
67
78
70
83
49
48
77
85
62
79
31
31
86
90
45
4R
Mean
29
38
24
29
17
3
10
9R
2s
43
43
42
44
52
17
24
54
65
39
52
12
16
68
80
19
Rubber cracking
Sample
size
52
46
51
46
18
49
37
37
10
50
7
50
48
50
50
52
52
52
52
52
52
44
32
42
50
41
41
37
Min. i Max
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
n
.290
.300
.368
.366
.244
.349
.469
.328
0
.250
.058
323
.285
.194
.350
.216
.343
.227
.305
.237
.285
.190
.459
.403
.297
.197
.323
9Qn
Mean
.096
.107
.124
.117
.090
.118
.090
.028
.044
.099
.058
.078
.063
.092
.056
.079
.057
.081
.059
.088
.062
.088
.025
.106
r>7s
p
n
w
a
8
-------
N)
Table B-1 (continued). DATA SUMMARY
State/city
OHIO (continued)
Cincinnati
(155)
Mingo Junction
Steubenville
OKLAHOMA
Miami
Sallisaw
OREGON
Corvallis
The Dalles
Ranier
Portland
(82)
Portland
(83)
PENNSYLVANIA
Chester
Philadelphia
(11)
Philadelphia
(12)
Philadelphia
(13)
Easton
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
2.1
4.5
6.0
3.5
0.9
0.8
1.7
1.0
0.7
1.9
1.8
1.1
1.8
1.3
3.8
3.8
3.4
4.2
3.1
3.7
3.7
3.9
2.9
2.7
3.0
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
25
73
54
9
7
12
13
20
12
34
26
23
29
28
54
41
49
107
45
39
34
50
43
Quarterly steel
Sample
size
4
4
4
3
4
4
3
4
4
4
3
4
4
4
4
4
2
4
3
4
4
4
3
4
4
Min.
26
121
72
2
2
2
6
1
5
15
19
24
16
11
26
71
74
65
51
71
18
56
48
61
50
Max.
55
162
140
5
15
21
18
64
15
59
45
61
45
64
52
98
146
102
91
90
106
78
64
102
76
Mean
34
139
103
4
7
9
12
28
10
37
31
38
30
39
38
79
110
78
71
80
64
65
58
80
68
Fabric No. 1
Sample
size
4
4
4
1
4
1
4
4
4
4
4
4
3
4
3
4
4
3
3
4
4
4
4
4
4
3
4
Min.
14.9
14.8
17.0
14.3
15.9
13.5
15.8
11.6
17.2
10.6
15.4
12.6
18.5
12.4
18.6
12.7
18.5
12.4
17.9
12.1
17.0
13.2
15.6
13.0
15.8
13.3
18.9
Max.
20.6
20.7
19.7
14.3
17.9
13.5
20.4
15.7
18.2
15.9
18.4
19.0
18.8
15.7
19.6
16.9
19.0
19.0
21.8
18.0
24.2
17.8
21.5
18.4
20.6
17.4
21.7
Mean
18.2
17.8
18.5
16.9
17.8
13.4
17.5
12.7
17.2
15.3
18.6
13.7
19.1
14.3
18.8
15.3
19.6
14.9
20.2
15.3
18.5
15.6
18.4
15.7
20.3
Fabric No. 2
Sample
size
1
1
4
4
4
4
4
4
4
4
4
3
Min.
0.9
1.1
0.7
1.0
0.8
2.2
0.8
1.9
2.8
1.9
3.3
1.4
Max.
0.9
1.1
2.5
1.8
1.4
3.3
1.8
8.8
6.3
6.9
6.7
3.7
Mean
1.4
1.5
1.1
2.8
1.2
5.3
4.3
4.0
5.2
2.8
03
s?
-------
Table B-1 (continued). DATA SUMMARY
State/city
OHIO (continued)
Cincinnati
(155)
Mingo Junction
Steubenville
OKLAHOMA
Miami
Sallisaw
OREGON
Corvallis
The Dalles
Ranier
Portland
(82)
Portland
(83)
PENNSYLVANIA
Chester
Philadelphia
(11)
Philadelphia
(12)
Philadelphia
(13)
Easton
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRO
Fabric No. 3
Sample
size
1
3
4
4
1
4
1
4
4
4
4
4
4
2
4
3
4
4
4
3
4
4
4
4
4
4
3
A
Min.
30.5
27.7
28.6
30.1
9.2
14.2
10.1
14.4
11.8
13.3
12.5
16.3
12.0
14.1
17.1
21.1
14.5
15.7
28.5
39.8
28.7
40.3
35.0
45.9
33.1
45.1
19.6
97 R
Max.
30.5
32.3
44.0
35.9
9.2
18.8
10.1
18.7
12.9
18.3
13.6
18.8
16.1
15.8
20.0
22.9
19.2
18.4
42.3
46.8
41.1
42.8
49.6
56.1
40.7
52.3
25.3
39 A
Mean
30.4
37.6
32.8
16.8
16.1
12.3
15.2
13.2
17.4
13.7
15.0
18.8
22.0
15.8
17.4
34.2
43.1
34.9
41.2
32.1
50.2
35.9
47.9
22.3
90 a
Fabric No. 4
Sample
size
1
1
1
4
3
4
4
4
4
4
4
3
3
Min.
10.2
11.5
14.2
13.0
10.6
14.5
8.2
13.6
11.7
8.1
11.0
9.1
13.9
Max.
10.2
11.5
14.2
17.8
17.0
20.6
16.1
18.8
28.7
22.3
24.1
21.4
26.6
Mean
15.4
14.0
16.4
11.4
15.6
18.5
14.6
16.4
15.3
20.2
Fabric No. 5
Sample
size
4
3
4
4
3
4
3
3
3
4
3
4
4
4
4
Min.
5.3
5.3
7.8
10.7
12.9
8.5
5.1
9.2
4.5
9.0
6.3
4.1
5.4
4.1
« n
Max.
13.5
11.3
14.7
14.2
16.4
11.9
12.4
12.0
9.0
11.3
16.2
13.2
13.9
13.4
n R
Mean
8.7
7.6
11.5
12.3
15.2
10.2
9.8
10.5
7.3
10.5
9.8
8.5
9.6
8.8
in ?
Fabric No. 6
Sample
size
2
4
4
4
4
4
4
3
3
4
3
4
4
4
A
Min.
7.5
8.9
9.3
3.7
3.7
4.4
5.5
4.6
7.5
4.5
9.7
9.7
8.2
11.5
H 9
Max
8.1
15.6
15.4
8.7
7.0
9.2
8.8
7.2
11.7
9.1
11.2
14.9
14.7
13.4
\A A
Mean
7.8
12.2
13.0
6.4
5.3
6.2
7.0
5.8
9.4
6.5
Fabric No. 7
Sample
size
4
4
3
4
4
4
4
3
2
4
10.3 4
11.4 4
11.5
12.5
1 1 n
4
4
yl
Min
2.8
8.2
7.6
3.8
2.5
2.6
4.2
3.1
5.7
2.7
6.0
3.6
4.1
5.2
3 1
Max
14.4
23.9
14.7
8.6
7.9
10.8
13.8
13.6
9.3
7.3
16.5
14.8
14.2
15.6
1 1 n
Mean
7.9
14.6
12.3
5.5
5.8
5.3
8.4
6.8
7.5
4.3
0.8
7.8
8.6
0.7
I
\
r
o
w
N)
-------
to
Table B-1 (continued). DATA SUMMARY
State/city
OHIO (continued)
Pin rinnati
(155)
Mingo Junction
c, u ...
OKLAHOMA
- ;
C I!'
OREGON
Corvallis
The Dalles
D
Portland
(82)
Portland
(83)
PENNSYLVANIA
Philadelphia
(11)
Philadelphia
(12)
Philadelphia
(13)
Easton
Year
1QR7
1968
1967
1968
1967
1968
1QR7
1968
1QR7
1968
1967
1968
1967
1968
1QR7
1968
1967
1968
1967
1968
1QR7
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
4
4
4
4
4
4
3
3
4
2
4
4
4
4
Min.
4.4
8.7
8.7
3.4
3.8
3.4
2.2
2.7
4.6
3.3
4.8
2.4
5.1
5.3
3.1
Max.
8.0
14.1
22.7
8.3
7.8
7.5
8.0
10.0
9.5
9.6
6.9
9.7
10.8
7.6
10.1
Mean
6.1
11.5
14.6
6.7
6.1
5.6
5.6
5.9
7.0
5.6
5.8
6.4
7.5
6.0
6.8
Fabric No. 9
Sample
size
4
4
4
4
4
4
4
3
3
4
3
4
4
3
4
Min.
13.6
15.1
14.4
10.8
11.8
13.6
15.0
15.7
17.3
16.8
14.7
13.2.
14.8
19.5
13.5
Max.
27.1
32.1
35.9
23.8
25.7
19.3
20.5
17.7
19.2
23.6
32.6
31.6
31.5
35.3
28.6
Mean
20.2
22.1
22.7
18.0
19.5
15.8
16.4
17.0
18.3
20.1
23.1
22.6
24.4
26.7
21.9
Quarterly nylon
Sample
size
1
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
3
4
4
4
4
4
4
4
4
4
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
0
1
3
0
1
3
0
1
3
Max.
0
0
4
1
3
0
5
1
1
1
1
1
0
3
14
13
37
36
7
9
14
5
8
9
Mean
0
0
1.5
0.2
0.8
0
1.2
0.2
0.2
0.2
0.5
0.2
0
1.8
in 7
7.8
20.2
15.5
2.2
3.7
7.0
1.8
3.5
5.0
Monthly nylon
Sample
size
12
1
12
1
12
12
o
11
10
12
11
12
1 9
12
11
12
12
12
in
12
12
12
12
11
11
12
11
12
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
1
0
0
0
1
0
1
0
1
0
1
2
0
2
0
3
9
22
14
4
4
4
3
5
2
Mean
0.2
0
0
0
0.2
0
0.5
0
0.5
0.8
0
0.8
0
1.5
1 T
1.9
8.0
4.4
0.7
0.6
1.7
0.5
1.1
0.6
Silver tarnishing
Sample
size
12
1
12
1
12
12
12
12
12
12
12
11
12
12
12
12
12
12
11
12
12
12
12
12
11
Min.
77
40
79
73
7fi
59
7
13
00
17
10
15
10
10
65
24
28
32
33
36
60
42
64
52
76
52
48
39
Wax.
CO
80
79
91
7R
88
7
33
OQ
40
49
50
71
55
94
88
83
81
89
88
93
89
93
91
93
93
84
82
Wean
56
82
78
22
30
28
27
31
28
78
56
53
62
59
69
80
81
77
80
85
84
70
67
"8
I
60
-------
Table B-1 (continued). DATA SUMMARY
State/city
OHIO (continued)
(155)
OKLAHOMA
OREGON
The Dalles
(82)
(83)
PENNSYLVANIA
Philadelphia
(11)
Philadelphia
(12)
Philadelphia
(13)
East on
Year
1967
1968
1967
1968
1967
1968
1QR7
1968
1967
1968
1967
1968
1967
1968
1967
1968
1QR7
1968
1QR7
1968
1QR7
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
4
12
1
12
1
12
i
12
1
12
12
10
19
12
12
11
19
12
19
11
in
12
12
10
12
11
12
12
12
12
Min.
n R
0.2
? R
0.8
1 fi
0.8
o n
0.0
n n
0.0
0 0
0.0
n n
0.0
0 0
0.0
01
0.0
n n
0.0
1 n
1.0
1.0
1.3
0.9
1.2
1.2
1.5
0.6
0.2
Max.
1 0
1.7
2 8
4.6
1 8
2.7
9 n
0.2
n n
0.1
0 1
0.1
0 4
0.4
0 3
0.2
n Q
0.8
0 4
0.5
") 8
3.7
4.0
4.8
4.4
.4.1
4.5
4.6
1.9
2.5
Mean
0.7
1.8
1.4
0.0
0.0
0 0
0.0
n 9
0.1
0 2
0.1
n R
0.5
n ?
0.2
1 R
1.8
2.2
2.2
2.3
2.0
2.6
2.5
1.1
1.1
Lead plates
Sample
size
10
11
10
12
12
11
12
8
9
12
10
9
11
11
9
Min.
2
4
6
0
0
0
0
0
2
0
7
9
9
10
3
Max.
10
33
19
2
2
1
2
2
6
8
21
29
22
28
15
Mean
5
14
10
0
0
0
1
1
4
2
14
16
13
15
7
Dustfall
Sample
size
A
12
12
11
11
10
19
12
1 O
12
1 9
12
1 1
12
1 9
11
1 9
12
12
11
12
12
12
11
12
12
Min.
6n
4.6
17.7
2.1
3n
3.1
1 R
1.0
0 7
0.6
n R
1.1
1 1
0.2
1 R
2.8
n 1
0.5
T Q
3.6
4.2
5.1
2.4
2.6
8.4
3.9
4.1
1.4
Max.
6C
11.4
35.1
6.9
7.3
5.2
T 9
3.8
2C
7.2
9 7
7.2
51
25.7
T R
3.5
19 9
11.3
18.0
19.7
6.1
9.0
15.6
18.1
14.3
21.6
Mean
7.1
25.9
5.4
4.7
2.6
1 7
1.6
1 R
2.3
1 Q
2.6
Q n
7.9
1 Q
2.1
7 R
6.5
10.3
9.7
4.4
4.5
11.1
9.6
7.2
6.7
Sticky paper
Sample
size
12
12
12
12
11
1 9
11
1 9
12
1 9
9
11
1 9
11
11
12
10
12
12
12
12
12
12
Min.
on
19
21
8
3
1
1
1
i
6
3
1
4
0
2
in
12
11
4
10
10
20
33
4
1
Max.
7R
62
75
55
42
32
1R
11
00
47
^n
33
C1
55
9R
30
fi1
65
65
81
58
59
70
77
50
57
Mean
36
46
31
16
8
6
99
23
14
16
01
30
14
00
45
41
49
35
41
50
53
22
28
Rubber cracking
Sample
size
10
51
49
A
51
51
48
C1
47
R1
52
A~J
46
C1
49
CO
49
50
46
45
49
49
51
49
52
51
Min
n
0
n
0
0
0
0
0
0
n
0
0
0
0
0
0
0
0
0
0
0
0
Max. I Mean
944
.196
n
.191
.431
.391
.620
97R
242
471
302
31R
164
999
166
01 0
187
9Qfl
252
260
222
272
222
260
207
265
224
I
.049
.049
.114
.086
.127
fl79
.026
.055
077
.021
nco
.029
nfiR
034
074
075
062
076
058
058
067
080
068
w
I
p
n
w
2
8
-------
OS
Table B-1 (continued). DATA SUMMARY
State/city
PENNSYLVANIA (co
Sharon
Kintnersville
RHODE ISLAND
Westerly
Pawtucket
North Tiverton
Block Island
SOUTH CAROLINA
Rock Hill
North Augusta
SOUTH DAKOTA
Sioux Falls
Custer
Milbank
TENNESSEE
Volunteer Arsenal
(107)
Volunteer Arsenal
(108)
Volunteer Arsenal
final
Year
ntinued)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.7
2.0
1.7
0.8
2.9
2.5
1.2
1.6
1.0
1.3
0.5
0.4
4.2
15.4
0.8
1.6
1.0
4.6
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
40
41
47
53
49
44
55
26
22
12
20
2
63
59
30
37
35
Quarterly steel
Sample
size
4
4
4
1
4
1
4
1
4
1
4
4
4
3
3
4
3
2
2
3
2
4
2
4
Min.
48
56
35
67
60
87
59
46
60
61
66
13
14
10
12
2
0
4
58
37
18
22
24
?7
Max.
65
64
76
67
80
87
94
46
76
61
76
39
20
46
17
4
3
5
89
79
50
51
38
42
Mean
58
59
65
70
80
66
71
28
18
26
14
2
1
4
73
54
34
33
31
35
Fabric No. 1
Sample
size
4
3
3
1
4
1
4
1
4
1
3
4
4
3
4
1
4
2
2
3
4
3
4
4
4
Min.
13.1
16.1
15.6
18.5
16.3
17.4
16.4
19.3
16.6
20.0
19.2
12.9
17.4
13.2
15.8
15.3
16.5
11.9
19.5
24.9
25.2
17.9
23.3
12.3
18.1
Max.
16.0
20.9
20.5
18.5
20.7
17.4
20.9
19.3
21.8
20.0
23.6
17.9
20.0
18.4
20.2
15.3
19.3
14.2
27.6
25.9
29.3
25.8
26.1
18.0
71 5
Mean
14.6
17.8
18.0
18.2
18.6
19.4
21.4
15.1
18.5
16.1
18.0
17.8
13.0
23.6
25.4
26.6
22.3
25.0
15.8
19.6
Fabric No. 2
Sample
size
4
1
1
1
1
4
3
1
3
3
4
Min.
1.8
1.2
2.7
0.9
1.0
1.5
0.8
2.5
1.2
1.6
0.8
Max.
6.5
1.2
2.7
0.9
1.0
4.8
1.4
2.5
2.1
6.9
1.9
i/lean
4.4
2.6
1.0
1.8
3.8
1.3
I
03
I/I
-------
Table B-1 (continued). DATA SUMMARY
State/city
PENNSYLVANIA (cc
Sharon
Kintnersville
RHODE ISLAND
Westerly
Pawtucket
North Tiverton
Block Island
SOUTH CAROLINA
Rock Hill
North Augusta
SOUTH DAKOTA
Sioux Falls
Custer
Milbank
TENNESSEE
Volunteer Arsenal
(107)
Volunteer Arsenal
(108)
Volunteer Arsenal
/ mo\
Year
ntinued)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRQ
Fabric No. 3
Sample
size
4
3
4
1
4
1
4
1
3
1
4
4
4
3
4
1
4
2
3
3
4
3
4
4
A
Min.
17.4
25.9
23.0
23.7
29.3
30.3
31.6
20.4
27.4
18.8
28.2
17.7
24.1
17.8
19.7
9.3
17.4
8.4
17.3
21.8
29.6
17.5
23.7
23.3
OB n
Max.
27.3
32.8
29.8
23.7
35.2
30.3
43.9
20.4
32.1
18.8
36.8
24.3
30.2
23.3
24.5
9.3
19.3
10.0
23.1
35.7
41.5
29.6
40.2
29.8
37 A
Mean
21.7
28.2
26.3
33.3
36.6
29.6
31.1
20.9
26.4
20.4
22.0
18.3
9.2
19.7
27.2
36.3
22.3
31.8
25.6
T5 H
Fabric No. 4
Sample
size
3
1
1
1
1
4
3
1
2
3
3
Min.
12.6
26.1
22.6
26.0
30.6
17.0
19.7
7.5
23.6
22.2
12.3
Max.
21.3
26.1
22.6
26.0
30.6
31.9
27.1
7.5
24.4
30.1
23.5
Mean
17.3
24.2
22.2
24.0
25.5
19.4
Fabric No. 5
Sample
size
3
3
4
5
4
4
4
3
4
2
1
4
4
A
Min.
6.0
11.2
8.3
5.9
10.9
12.3
10.4
9.6
7.2
11.1
13.4
8.0
8.8
R 7
Max.
13.8
21.1
18.5
14.1
19.1
22.6
15.5
14.2
14.3
13.6
13.4
12.5
13.6
19 1
Mean
8.8
14.5
13.1
10.2
14.8
17.8
13.0
12.6
10.4
12.4
10.2
11.2
irtA
Fabric No. 6
Sample
size
3
3
4
4
3
4
4
4
4
2
2
4
4
A
Min.
9.0
7.2
4.5
6.0
4.7
4.8
4.4
5.9
6.5
3.7
6.2
4.9
5.5
a. a
Max.
14.2
8.7
9.5
9.1
8.3
12.9
13.6
9.4
8.1
5.2
8.4
9.1
7.3
R R
Mean
11.5
8.1
7.3
7.6
7.0
8.9
9.7
7.0
7.2
4.4
7.3
7.0
6.5
K n
Fabric No. 7
Sample
size
3
4
4
4
4
4
4
4
4
2
2
4
4
A
Min.
6.5
4.1
3.5
3.1
2.9
3.5
2.6
2.7
4.0
7.3
5.0
2.8
2.9
9 Q
Max
12.0
8.0
11.2
10.3
8.3
16.7
11.6
9.4
12.6
7.6
11.8
10.8
9.1
7 K
Mean
9.8
6.4
7.4
6.6
6.4
9.4
6.8
6.8
8.1
7.4
8.4
6.3
5.4
c o
I
c
I
o
n
o
H
to
-------
to
00
Table B-1 (continued). DATA SUMMARY
State/city
PENNSYLVANIA (ca
ouarnn
... ...
RHODE ISLAND
Westerly
0
M +U 1" r+
SOUTH CAROLINA
Rock Hill
North Augusta
SOUTH DAKOTA
MMKanL-
TENNESSEE
Volunteer Arsenal
(107)
Volunteer Arsenal
(108)
Volunteer Arsenal
(109)
Year
ntinued)
1QR7
1968
1968
1967
1968
1968
1QR7
1968
1Qfi7
1968
1967
1968
1967
1968
1968
1QR7
1968
1Q.R7
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
2
4
4
4
4
4
4
4
4
2
2
4
4
4
Min.
3.9
6.4
9.1
7.0
8.6
10.0
8.0
3.7
3.2
6.1
6.8
4.7
7.2
3.9
Max.
5.3
18.9
17.4
12.1
20.6
23.4
16.7
8.7
18.3
7.3
10.3
20.6
16.7
18.2
Mean
4.6
12.0
13.4
9.1
15.0
17.9
11.5
5.7
8.2
6.7
8.6
14.1
11.2
12.5
Fabric No. 9
Sample
size
2
4
3
4
4
4
4
4
4
2
3
4
4
4
Min.
16.7
15.6
15.4
13.4
13.0
12.4
15.1
11.5
8.5
4.2
15.8
14.5
17.3
12.9
Max.
27.1
27.8
25.7
25.5
27.3
33.6
27.7
32.4
21.7
14.7
23.1
30.1
31.4
31.2
Mean
21.9
21.8
19.1
18.4
21.7
22.8
21.9
21.8
16.0
9.4
19.8
25.6
24.0
23.1
Quarterly nylon
Sample
size
4
4
4
1
4
i
4
1
4
1
4
4
4
3
4
3
2
3
4
4
4
4
3
4
Min.
n
0
0
1.0
0
1 n
0
0
0
0
0
0
0
0
0
0
3
0
15
7
47
43
Max. Mean
1
0
1
1.0
4
1 n
6
0
0
0
2
1
0
4
0
0
30
51
115
206
235
255
n ")
0
0.2
1.0
1.8
0
0
0
0.5
0.3
0
1.3
0
0
15.5
24.2
47.0
79.0
111.0
99.0
Monthly nylon
Sample
size
19
12
10
3
12
12
12
12
12
11
9
12
11
8
8
10
12
10
11
10
12
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
5
Max.
1
2
2
2
2
i
1
0
2
0
0
0
0
0
0
1
20
31
65
130
185
223
Mean
n 1
0.5
0.3
0.3
0.2
0
0.2
0
0
0
0
0
0
0.1
5.8
8.2
22.7
27.6
41.8
34.2
Silver tarnishing
Sample
size
Min.
19 ! 97
12 I 20
10
2
11
12
12
12
12
12
9
12
12
8
8
11
12
11
12
11
12
32
32
31
oc
32
on
30
on
30
36
18
21
11
9
4
11
52
46
41
19
33
25
Max.
Rfi
59
77
34
57
55
AC
67
AA
60
82
84
63
76
52
8
41
88
82
61
62
72
65
Mean
44
44
55
42
48
41
41
60
58
45
45
25
6
26
70
65
48
42
49
44
I
wa
-------
I
wa
3
r
n
w
2
S
H
Table B-1 (continued). DATA SUMMARY
State/city
PENNSYLVANIA (co
Sharon
Kintnersville
RHODE ISLAND
Westerly
Pawtucket
North Tiverton
Block Island
SOUTH CAROLINA
Rock Hill
North Augusta
SOUTH DAKOTA
Sioux Falls
Custer
Milbank
TENNESSEE
Volunteer Arsenal
(107)
Volunteer Arsenal
(108)
Volunteer Arsenal
(109)
Year
itinued)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
12
12
10
3
11
3
12
3
12
3
11
11
12
9
12
2
11
7
8
11
12
11
12
11
12
Min.
0.5
0.2
0.4
0.5
0.0
0.9
0.4
0.3
0.2
0.4
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
Max.
1.5
2.0
2.9
0.7
0.9
1.4
2.3
0.6
1.4
0.5
0.6
0.4
0.6
0.2
0.3
0.3
0.4
0.1
0.1
2.0
0.4
0.4
0.4
0.3
0.3
Mean
0.8
0.7
1.0
0.5
1.2
0.6
0.3
0.2
0.1
0.0
0.0
0.1
0.0
0.0
0.4
0.2
0.2
0.1
0.1
0.1
Lead plates
Sample
size
12
6
11
11
11
11
11
11
4
8
8
12
12
11
Min.
2
4
0
2
2
1
0
0
0
0
0
0
0
0
Max.
11
9
8
15
8
7
5
1
0
1
2
2
3
2
Mean
5
6
4
7
4
3
2
0
0
0
1
1
1
Dustfall
Sample
size
12
12
11
3
12
3
12
3
11
2
12
12
12
8
12
2
12
7
5
9
10
11
12
10
12
Min.
7.5
4.9
1.1
1.3
2.0
6.3
3.9
1.6
1.2
3.3
0.5
0.7
1.9
1.7
1.7
2.5
1.0
0.3
0.7
7.8
5.1
2.5
2.7
1.5
1.2
Max.
12.3
17.3
5.6
5.9
7.1
9.2
13.4
4.0
9.9
3.3
13.6
5.5
6.5
4.6
5.2
2.6
17.6
4.1
3.7
17.1
17.7
6.7
5.7
10.5
10.2
Mean
9.6
10.7
2.4
3.4
7.0
3.2
2.6
3.1
3.2
2.8
2.7
6.0
2.0
13.7
10.1
4.3
4.1
3.5
3.9
Sticky paper
Sample
size
12
1
10
3
12
3
12
3
11
4
12
12
11
2
9
3
7
6
8
12
12
12
12
12
12
Min.
13
44
1
18
16
18
11
4
1
6
1
2
1
7
2
11
19
1
4
5
5
1
1
0
1
Max.
49
44
49
40
63
41
61
14
49
11
17
28
38
9
17
31
78
10
56
46
59
21
16
i
9
17
Mean
29
19
38
44
16
9
15
18
9
46
6
24
27
23
8
8
3
5
Rubber cracking
Sample
size
42
30
42
11
52
12
52
12
52
9
52
52
52
35
46
10
38
Min
0
0
0
i
0
0
0
0
0
0
0
0
0
0
0
0
0
0
26 0
33
48
52
49
52
49
51
0
0
0
0
0
0
0
Max
.249
.356
.449
.126
.454
.030
.277
.169
.340
.542
.572
426
340
230
217
0
38"0
219
391
272
255
446
378
212
257
Mean
.065
.081
.122
.115
.063
.104
.196
.126
.080
.069
.064
.076
.053
.046
.082
.058
.140
.094
.072
.056
-------
Table B-1 (continued). DATA SUMMARY
State/city
TENNESSEE (contini
Volunteer Arsenal
(110)
Chattanooga
(140)
Memphis
Bristol
TEXAS
El Paso
Del Rio
Eagle Pass
Laredo
McAllen
Brownsville
Austin
Beaumont
Port Arthur
Orange
Brown wood
Wichita Falls
Year
ed)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.0
4.1
3.4
0.7
1.2
0.4
0.4
0.4
0.4
0.7
0.7
0.9
3.4
0.6
0.9
1.2
1.7
1.6
1.2
1.3
1.2
0.6
0.9
0.6
0.1
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
27
25
19
10
29
2
4
6
5
8
7
28
12
7
42
47
44
36
29
23
3
3
5
4
Quarterly steel
Sample
size
2
4
2
4
2
4
2
4
3
4
3
4
3
3
3
3
2
3
1
1
3
4
3
4
3
4
3
4
3
4
3
4
Min.
17
11
25
12
5
2
26
21
1
1
4
1
2
4
3
2
29
21
88
40
3
4
55
49
44
42
25
20
2
1
1
?
Max.
26
26
52
33
13
18
26
48
6
10
6
5
8
6
5
14
64
26
88
40
11
6
83
81
76
84
36
26
4
2
3
5
Mean
22
21
38
24
9
8
26
28
3
4
5
3
4
5
4
6
47
23
8
6
72
66
56
58
31
24
3
2
3
3
Fabric No. 1
Sample
size
4
4
2
4
2
4
2
3
4
4
2
4
2
3
2
2
2
4
2
3
4
3
4
3
2
3
4
3
3
2
4
Min.
21.2
21.6
17.0
16.6
16.2
18.5
15.7
18.5
10.7
13.7
10.8
12.7
12.0
19.4
12.1
16.5
17.6
18.2
18.5
8.8
16.1
17.0
21.0
16.1
21.3
16.1
17.5
11.6
13.6
14.8
14.9
Max.
23.4
25.5
18.3
21.3
17.3
20.4
18.4
23.0
15.2
17.8
15.9
19.7
18.5
20.4
15.8
18.7
19.2
23.1
24.3
15.4
19.0
19.5
24.3
19.5
22.2
19.1
22.6
15.4
21.4
15.0
19.1
Mean
21.9
23.3
17.6
19.3
16.8
19.4
17.0
21.2
12.8
15.9
13.4
16.5
15.2
20.0
13.9
17.6
18.4
21.4
21.4
12.9
18.0
18.5
22.4
17.8
21.8
17.2
20.0
13.2
17.9
14.9
17B
Fabric No. 2
Sample
size
4
2
2
2
4
2
2
2
2
3
3
3
3
3
3
t/lin.
0.8
2.5
3.0
2.6
1.3
1.3
1.3
1.5
3.1
0.0
1.0
0.6
0.7
1.5
3.0
i/lax.
1.2
3.4
4.0
9.9
5.2
1.5
5.6
1.7
3.3
1.0
1.2
1.1
1.5
2.4
4.2
Wean
1.0
3.0
3.5
6.2
3.4
1.4
3.4
1.6
3.2
1.0
1.1
0.9
1.1
1.9
3.5
1
I
3
2
1
-------
I
W5
I
C/3
Table B-1 (continued). DATA SUMMARY
State/city
TENNESSEE (contim
Volunteer Arsenal
(110)
Chattanooga
(140)
Memphis
Bristol
TEXAS
El Paso
Del Rio
Eagle Pass
Laredo
McAllen
Brownsville
Austin
Beaumont
Port Arthur
Orange
Brownwood
Wichita Falls
Year
ed)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QRR
Fabric No. 3
Sample
size
4
4
2
4
2
4
2
3
4
4
2
4
2
2
2
2
2
2
1
3
3
3
4
3
2
3
3
3
3
3
a.
Min.
19.7
22.9
15.9
22.7
23.3
23.0
15.8
23.4
14.3
17.9
10.3
11.9
14.2
16.9
11.7
17.7
15.1
19.4
18.3
12.2
18.9
15.3
22.3
16.6
21.2
14.5
24.1
10.3
17.4
10.5
1R 1
Max.
37.5
39.7
21.4
32.1
24.9
25.6
19.9
26.3
18.9
22.1
14.2
17.4
15.3
20.4
17.6
17.8
24.3
23.7
18.3
19.1
22.9
24.5
28.5
28.1
27.3
22.1
27.8
18.1
21.4
30.4
->) n
Mean
25.1
32.6
18.6
27.0
24.1
24.6
17.8
25.2
17.5
20.2
12.2
15.6
14.8
18.6
14.6
17.8
19.7
21.6
15.3
21.1
19.7
25.5
21.4
24.2
17.8
26.1
13.8
19.9
19.0
1RR
Fabric No. 4
Sample
size
4
1
1
1
4
1
1
1
3
3
3
s2
2
3
Min.
11.0
22.9
23.8
22.5
10.1
23.1
20.7
25.6
20.2
23.5
26.7
24.2
21.8
17.5
Max.
27.5
22.9
23.8
22.5
19.8
23.1
20.7
25.6
25.4
25.8
31.8
26.0
23.0
25.0
Mean
20.8
14.2
23.3
24.3
28.7
25.1
22.4
22.1
Fabric No. 5
Sample
size
3
4
3
3
4
4
3
2
3
1
3
4
2
3
3
A
Min.
9.9
7.3
8.6
6.8
6.9
9.7
12.9
9.5
11.0
14.5
12.2
10.1
13.6
11.2
11.6
Q n
Mcx.
13.6
14.5
13.2
14.3
11.9
13.2
15.7
11.7
12.8
14.5
13.4
12.5
14.2
13.2
13.2
1d Q
Mean
11.2
10.6
11.2
10.5
9.6
11.8
14.3
10.6
12.0
13.0
11.4
13.9
12.5
12.6
1? T
Fabric No. 6
Sample
size
4
3
4
3
4
4
2
2
1
2
4
4
2
4
3
A
Min.
4.2
8.4
6.9
8.6
7.2
2.4
8.8
6.6
12.7
5.8
5.9
3.6
5.3
4.2
6.9
A Q
Max
6.0
11.0
12.5
18.2
12.4
4.3
12.3
7.4
12.7
9.8
7.6
6.0
7.3
7.6
12.6
Q C
Mean
5.0
9.3
10.2
12.8
9.3
3.4
10.6
7.0
7.8
6.6
4.8
6.3
5.8
8.9
K ~7
Fabric No. 7
Sample
size
4
4
4
3
4
4
2
2
1
2
4
4
2
4
3
A
Min
1.9
3.5
5.6
6.0
5.1
2.4
2.9
10.3
14.1
4.0
2.4
2.1
8.2
5.4
2.9
Max
6.5
23.7
9.5
15.5
11.4
14.8
10.6
15.1
14.1
5.4
1.6
8.4
8.7
1.2
9.6
Mean
4.7
10.4
7.8
10.5
8.0
6.6
6.8
2.7
4.7
6.6
4.7
8.4
7.6
5.4
o
m
e
90
O
1*
w
n
H
-------
Table B-1 (continued). DATA SUMMARY
State/city
TENNESSEE (contim
Volunteer Arsenal
(110)
Chattanooga
(140)
Memphis
Bristol
TEXAS
El Paso
Del Rio
Eagle Pass
Laredo
McAllen
Brownsville
Austin
Beaumont
Port Arthur
Orange
Brown wood
Wichita Falls
Year
jed)
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
4
4
3
4
4
2
2
4
2
4
4
2
3
3
4
Min.
3.6
5.8
4.5
4.3
3.8
4.6
7.7
3.6
7.1
6.4
4.9
5.8
6.0
9.4
6.0
6.1
Max
23.2
8.4
8.7
11.2
16.1
8.8
7.8
7.5
10.8
10.7
9.1
13.5
13.9
12.4
7.2
10.5
Mean
14.9
7.3
6.6
7.8
8.0
6.1
7.8
5.6
9.1
8.6
7.2
8.4
10.0
11.3
6.6
8.6
Fabric No. 9
Sample
size
4
4
4
3
4
4
3
3
1
2
4
4
2
4
3
4
Min.
17.1
15.2
20.7
22.3
10.7
17.2
18.3
19.0
35.6
20.8
20.4
23.3
20.4
19.6
16.9
18.5
Max.
32.1
26.0
30.1
29.9
19.5
20.2
30.6
27.1
35.6
.37.7
29.8
31.3
26.3
35.7
25.0
31.7
Mean
24.6
20.4
24.2
25.8
14.1
18.8
24.3
24.1
29.2
25.1
27.8
23.4
28.6
19.9
24.6
Quarterly nylon
Sample
size
3
4
1
4
2
4
2
4
3
4
3
4
3
4
3
3
4
3
1
2
2
4
3
4
3
4
3
4
2
4
3
4
Min.
4
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
Max.
17
40
0
1
5
0
0
0
2
1
0
0
0
0
0
0
0
0
0
0
0
0
5
0
2
0
0
0
0
0
0
0
Mean
9.7
20.8
0.5
2.5
0
0
0
1.3
0.2
0
0
0
0
0
0
0
0
0
0
0
2.3
0
0.7
0
0
0
0
0
0
0
Monthly nylon
Sample
size
10
12
7
12
6
12
6
12
11
10
8
12
7
9
9
11
7
12
4
7
6
12
9
12
9
12
9
12
9
12
9
11
Min.
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
19
25
2
0
3
0
0
1
1
4
0
1
0
5
0
1
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
Mean
5.3
5.5
0.3
0
0.7
0
0
0.2
0.2
0.9
0
0.1
0
0.6
0
0.2
0
0
0
0
0.2
0
0
0
0
0
0
0
0
0
0
Silver tarnishing
Sample
size
11
12
7
12
6
12
6
12
11
9
6
12
7
9
9
10
8
12
4
9
12
9
12
9
12
9
12
9
11
9
12
Min.
50
35
43
52
34
27
19
21
15
36
26
20
51
58
39
45
68
56
36
55
51
69
57
56
63
55
58
24
25
25
20
Max.
80
86
74
84
65
81
54
55
87
89
59
78
90
90
82
90
98
90
69
85
92
90
83
92
90
89
90
61
60
68
66
Mean
69
59
54
68
51
52
40
43
49
64
35
38
70
75
60
70
82
78
67
68
81
76
81
77
74
75
32
39
41
36
1
-------
Table B-1 (continued). DATA SUMMARY
State/city
TENNESSEE
Volunteer Arsenal
(110)
Chattanooga
(140)
Memphis
Bristol
TEXAS
El Paso
Del Rio
Eagle Pass
Laredo
McAllen
Brownsville
Austin
Beaumont
Port Arthur
Orange
Brownwood
Wichita Falls
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
11
12
7
12
6
12
6
12
11
7
9
12
7
10
9
11
8
10
4
5
9
12
9
11
9
12
9
12
8
12
8
12
Min.
0.0
0.0
0.2
0.0
0.0
0.0
0.0
0.0
0.2
0.6
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.0
0.0
0.0
0.0
Max.
0.2
0.2
0.9
1.0
0.3
0.4
0.8
1.3
2.0
1.5
0.1
0.4
0.1
0.2
0.1
0.1
0.2
0.2
0.1
0.2
0.1
0.2
0.5
0.7
0.7
0.6
0.2
0.3
0.1
0.2
0.1
0.2
Mean
0.1
0.1
0.4
0.4
0.2
0.2
0.4
0.5
0.9
0.9
0.0
0.1
0.0
0.0
0.0
0.0
0.1
0.1
0.0
0.0
0.2
0.2
0.3
0.3
0.1
0.1
0.0
0.0
0.0
0.0
Lead plates
Sample
size
11
11
9
10
9
10
6
8
11
5
12
12
10
12
12
11
Min.
0
0
0
0
2
0
0
0
0
0
0
0
0
0
0
0
Max.
2
7
1
8
10
17
1
1
2
1
1
4
10
2
1
1
Mean
1
3
1
3
6
0
0
0
0
0
1
3
0
0
0
Dustfall
Sample
size
11
12
7
12
5
11
6
12
10
10
7
11
6
10
8
12
8
11
1
5
9
11
9
12
9
12
9
12
9
12
9
12
Min.
2.0
2.4
5.0
4.1
3.2
5.0
2.3
1.7
1.3
1.9
1.2
1.2
2.8
3.8
2.1
1.4
1.1
1.8
4.8
6.8
1.3
1.1
2.1
2.5
3.3
1.1
2.0
0.6
3.2
2.3
1.1
0.6
Max
10.8
11.1
21.3
11.2
44.5
11.1
4.2
4.2
4.1
9.2
56.8
15.3
5.8
19.1
7.7
13.9
5.8
6.4
4.8
21.6
3.7
11.0
9.0
5.3
11.2
9.5
8.2
35.9
7.9
11.4
6.9
4.1
Mean
4.8
4.9
9.9
6.2
8.5
3.4
3.0
2.8
5.2
11.8
3.3
3.8
8.2
4.9
7.7
3.6
3.9
2.1
3.3
3.9
2.8
6.5
4.1
3.7
5.8
5.5
5.7
2.7
2.2
Sticky paper
Sample
size
12
12
7
11
6
12
6
11
11
6
8
12
7
5
10
10
8
12
5
10
11
8
6
10
10
9
11
9
10
9
12
Min
1
1
9
4
12
2
3
2
43
27
12
13
23
22
26
41
40
23
33
2
3
1
1
10
7
5
1
10
13
10
5
Max
19
15
42
49
57
60
29
44
71
89
46
47
56
68
59
79
72
78
87
35
19
14
30
46
40
28
34
47
54
66
67
Mean
7
5
25
25
28
37
11
21
51
61
28
29
38
44
57
54
57
12
10
6
6
21
24
11
15
21
28
34
28
Rubber cracking
Sample
size
49
50
31
52
21
52
25
47
56
35
30
52
20
23
37
48
31
50
15
25
34
52
35
31
35
45
34
46
34
49
39
51
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.335
.207
.262
.237
.239
.343
.355
.358
.428
.348
532
323
381
403
612
287
350
352
129
419
469
501
267
214
539
547
446
262
323
462
489
462
Mean
.098
.063
.082
.085
.080
.106
.164
.149
.139
.082
107
080
130
137
109
098
087
048
145
137
116
101
110
108
180
111
I
>
tn
V)
w
n
w
"d
§
S
o
H
-------
Table B-1 (continued). DATA SUMMARY
State/city
TEXAS (continued)
Sherman
Texarkana
Marshall
UTAH
Bull Frog
VERMONT
Shoreman
White River
Junction
Burlington
VIRGINIA
Alexandria
Leesburg
Danville
Bristol
Bluefield
Luray
Blacksburg
Martinsville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
0.8
0.5
0.7
3.8
4.7
2.0
2.0
5.4
4.1
1.1
1.6
1.2
1.5
3.4
3.9
0.8
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
4
14
9
6
30
38
28
34
37
33
26
31
29
22
24
20
Quarterly steel
Sample
size
3
4
3
4
1
2
2
1
4
1
4
1
4
4
3
3
4
1
4
1
4
1
4
1
4
1
3
3
Min.
4
3
4
2
44
4
0
24
23
45
30
47
20
36
31
28
29
29
17
41
17
28
20
14
9
22
25
6
Max.
7
4
10
9
44
14
1
24
36
45
53
47
46
56
50
44
41
29
30
41
48
28
37
14
21
22
29
27
Mean
5
3
7
4
9
0
31
42
35
46
40
37
36
22
36
27
16
27
14
Fabric No. 1
Sample
size
3
4
3
3
1
1
1
4
1
4
1
3
4
4
3
4
1
4
1
4
1
4
1
4
1
4
1
3
Min.
14.2
16.6
16.4
12.1
14.5
8.7
8.0
16.4
15.0
13.8
15.6
17.1
12.0
18.4
14.4
15.0
17.4
16.0
22.7
20.3
16.2
15.1
16.1
12.4
15.5
17.0
16.6
177
Max.
18.2
21.5
18.2
20.6
14.5
8.7
8.0
21.7
15.0
19.8
15.6
17.9
18.6
22.2
16.9
19.2
17.4
19.4
22.7
22.0
16.2
20.1
16.1
19.2
15.5
18.3
16.6
71 q
Mean
16.0
19.5
17.3
17.7
18.8
17.6
17.4
15.4
20.1
15.8
17.6
17.8
21.3
18.5
16.3
17.8
20.1
Fabric No. 2
Sample
size
3
3
1
1
1
1
4
3
1
1
1
1
1
Min.
1.5
1.8
0.9
1.3
1.0
2.6
2.5
1.3
1.5
1.8
1.4
1.9
1.4
Wax.
1.8
3.6
0.9
1.3
1.0
2.6
4.7
1.4
1.5
1.8
1.4
1.9
1.4
Mean
1.6
2.6
3.8
1.4
I
ft
CL
-------
Table B-1 (continued). DATA SUMMARY
State/city
TEXAS (continued)
Sherman
Texarkana
Marshall
UTAH
Bull Frog
VERMONT
Shoreman
White River
Junction
Burlington
VIRGINIA
Alexandria
Leesburg
Danville
Bristol
Bluefield
Luray
Blacksburg
Martinsville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
mcQ
Fabric No. 3
Sample
size
3
4
3
3
1
1
1
4
1
4
1
4
4
4
3
4
1
4
1
4
1
3
1
3
1
3
1
3
Min.
15.9
18.4
14.3
19.2
16.6
14.4
17.1
16.5
25.9
21.0
23.0
19.7
25.2
33.4
12.8
20.4
16.2
22.7
14.4
20.2
18.3
21.0
37.8
12.2
20.3
20.9
22.6
on T
Max.
20.9
23.1
19.9
23.7
16.6
14.4
17.1
22.2
25.9
35.2
23.0
30.4
36.0
46.5
20.3
22.3
16.2
28.0
14.4
23.8
18.3
27.2
37.8
15.3
20.3
26.1
22.6
O7 1
Mean
17.9
21.2
17.1
21.8
20.2
27.4
25.2
31.3
39.9
16.1
21.2
25.0
22.0
24.2
13.3
24.1
T3 7
Fabric No. 4
Sample
size
3
2
1
1
1
1
3
2
1
1
1
1
Min.
19.9
20.8
16.4
25.2
20.7
22.8
10.7
23.1
16.9
15.9
16.2
14.5
Max.
27.1
22.1
16.4
25.2
20.7
22.8
26.8
31.3
16.9
15.9
16.2
14.5
Mean
23.9
21.4
19.0
27.2
Fabric No. 5
Sample
size
4
3
1
4
3
4
4
4
4
4
2
4
3
5
Min.
10.4
6.7
13.1
12.2
7.6
9.5
7.2
8.0
11.2
8.1
8.6
9.2
10.7
1-) i
Max.
15.1
11.6
13.1
15.8
11.4
15.6
16.1
18.3
16.5
14.2
12.7
12.9
17.7
1K 7
Mean
12.8
9.4
13.9
9.1
12.3
11.6
13.0
14.0
11.1
10.6
11.6
14.2
14 A
Fabric No. 6
Sample
size
4
3
1
4
4
3
4
4
4
4
4
4
4
T
Min.
8.1
6.4
3.3
6.2
5.1
5.4
8.7
5.5
3.8
6.3
8.2
3.0
6.1
f, A
Max
11.8
9.0
3.3
8.6
10.0
9.4
13.2
7.4
6.8
15.3
17.6
4.4
11.7
m 1
Mean
9.3
7.9
7.6
7.9
7.8
11.4
6.8
5.6
0.7
3.4
4.0
1.4
a n
Fabric No. 7
Sample
size
4
3
1
4
4
4
4
4
4
4
4
4
4
A
Min
3.9
5.7
7.0
4.2
3.3
3.9
4.9
3.4
3.6
4.3
3.9
2.7
4.2
3 }
Max
12.7
10.3
7.0
11.4
8.4
11.8
12.9
7.2
10.7
6.1
2.4
6.6
9.5
Q O
Mean
7,8
7.8
8.6
6.0
8.2
9.0
5.9
8.7
9.8
8.6
4.4
7.4
K 7
VI
r
PI
Q
-------
Table B-1 (continued). DATA SUMMARY
State/city
TEXAS (continued)
Sherman
Texarkana
Marshall
UTAH
Bull Frog
VERMONT
Shoreman
White River
Junction
Burlington
VIRGINIA
Alexandria
Leesburg
Danville
Bristol
Bluefield
Luray
Blacksburg
Martinsville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
3
1
4
4
4
4
4
4
4
3
4
4
3
Min.
3.3
2.9
6.7
9.4
5.4
7.6
6.7
5.2
7.1
5.2
6.2
3.6
7.9
9.5
Max.
9.7
8.5
6.7
12.6
15.2
12.4
9.3
14.9
13.0
8.9
10.9
9.9
9.6
10.1
Mean
7.0
5.6
10.5
8.9
9.8
8.4
9.2
9.3
6.6
8.1
6.0
8.9
9.8
Fabric No. 9
Sample
size
4
3
1
4
3
4
4
4
4
4
3
4
4
3
Min.
14.9
13.8
14.5
8.5
13.9
13.6
13.1
11.2
11.0
17.6
15.1
5.3
14.9
19.0
Max.
28.8
38.0
14.5
26.8
23.9
23.8
29.9
26.6
27.7
23.9
26.6
26.0
25.1
23.1
Mean
22.0
24.3
16.6
19.5
18.0
23.5
20.0
20.6
20.8
21.4
15.9
19.4
21.1
Quarterly nylon
Sample
size
3
4
3
4
3
1
1
4
1
4
1
4
4
4
3
4
1
4
1
4
1
4
1
4
1
4
1
4
Min.
0
0
0
0
0
0
0
0
9
0
47
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
2
0
0
2
5
0
0
0
9
4
47
30
2
3
2
25
0
0
0
0
0
0
0
0
0
0
0
0
Mean
0.7
0
0
0.5
1.7
0
2.5
8.7
0.8
1.2
1.0
8.2
0
0
0
0
0
0
0
Monthly nylon
Sample
size
9
11
9
12
2
9
3
5
3
12
3
12
3
12
11
12
11
12
4
12
4
12
4
12
4
12
3
12
1
12
Min.
0
0
0
0
0
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
0
0
0
0
6
0
0
0
0
2
5
11
10
1
3
4
10
0
0
0
0
1
0
4
1
0
0
0
0
Mean
0
0
0
0
0.9
0
2.0
2.3
0.1
0.4
0.5
2.1
0
0
0
0.1
0
0
Silver tarnishing
Sample
size
8
11
9
12
2
9
5
3
12
3
12
3
12
9
11
10
12
4
12
4
12
4
12
3
12
3
11
1
11
Min.
18
16
55
40
55
27
0
42
44
34
17
38
24
40
39
22
22
20
22
17
33
30
26
16
15
48
23
65
31
Wax.
65
49
94
83
70
70
10
82
80
51
72
59
75
84
73
58
58
44
69
60
60
59
71
48
69
55
76
65
84
Mean
38
34
77
63
52
60
39
42
63
56
43
42
41
46
45
30
39
59
1/3
-------
Table B-1 (continued). DATA SUMMARY
State/city
TEXAS (continued)
Sherman
Texarkana
Marshall
UTAH
Bull Frog
VERMONT
Shoreman
White River
Junction
Burlington
VIRGINIA
Alexandria
Leesburg
Danville
Bristol
Bluefield
Luray
Blacksburg
Martinsville
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
9
12
8
11
2
8
5
2
12
3
12
3
12
10
12
11
12
4
12
4
11
4
11
3
12
3
12
1
11
Min.
0.0
0.0
0.0
0.0
0.1
0.0
0.0
0.4
0.0
0.3
0.0
1.0
0.0
0.4
0.0
0.0
0.0
0.0
0.0
0.1
0.0
0.2
0.0
0.0
0.0
0.2
0.0
0.4
0.0
Max.
0.2
0.2
0.1
0.2
0.2
0.2
1.0
0.4
1.1
0.6
1.1
1.4
1.7
6.4
2.8
1.0
1.0
0.4
0.6
1.2
1.2
0.5
0.8
0.2
0.3
0.5
0.6
0.4
0.6
Mean
0.0
0.0
0.0
0.1
0.1
0.2
0.3
0.5
1.5
0.9
0.3
0.3
0.2
0.4
0.3
0.1
0.2
0.2
Lead plates
Sample
size
12
12
6
5
10
12
12
12
12
12
12
12
12
11
9
Min,
0
0
0
0
0
0
0
2
0
0
0
0
0
0
0
Max.
2
2
1
2
3
6
11
19
11
3
8
6
1
4
3
Mean
0
1
0
2
2
4
7
3
1
3
2
0
1
1
Dustfall
Sample
size
9
12
9
12
4
5
3
12
3
12
3
12
9
12
10
12
5
12
5
12
5
12
4
12
3
12
1
11
Min.
0.6
1.4
2.1
2.1
0.9
0.9
0.2
0.3
2.6
1.1
0.9
0.4
2.7
2.0
1.4
1.1
1.0
1.4
1.7
2.3
2.8
2.6
0.6
0.3
2.6
1.0
3.2
1.1
Max.
4.7
0.1
5.4
6.7
2.1
3.3
1.1
3.8
3.6
5.4
3.4
3.0
5.4
7.5
4.2
4.5
2.8
3.3
4.5
5.8
3.6
8.9
1.9
3.0
2.9
4.8
3.2
7.5
Mean
2.9
3.8
3.4
3.4
1.7
3.6
1.7
4.3
4.7
2.6
2.2
2.2
3.5
4.8
1.5
2.7
3.1
Sticky paper
Sample
size
9
11
9
12
3
7
4
4
12
3
12
3
11
11
10
11
11
5
11
5
11
5
11
4
12
3
12
9
Min
9
6
5
2
4
5
18
1
1
7
2
16
1
6
13
1
1
1
1
5
18
4
6
1
1
5
1
9
Max
39
62
31
48
50
37
70
5
25
8
41
24
39
69
65
47
28
7
13
36
61
25
53
2
11
19
45
57
Mean
22
36
14
20
21
8
15
14
30
30
18
15
7
34
24
3
16
28
Rubber cracking
Sample
size
35
48
38
51
8
33
16
11
51
12
50
13
52
36
42
44
46
20
50
18
51
19
49
16
51
9
52
5
39
Min
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.444
.444
.383
.323
0
.353
.255
.284
.572
.078
.298
0
.424
438
308
418
393
260
371
360
333
466
396
139
315
0
451
0
388
Mean
.156
.116
.124
.080
.114
.104
.058
.105
.134
.100
138
093
091
096
064
078
143
106
a
8
=5
2
-------
Table B-1 (continued). DATA SUMMARY
State/city
WASHINGTON
Spokane
Pullman
Clarkston
Bellingham
Seattle
Longview
Vancouver
WASHINGTON, D.C.
Washington, D.C.
(7)
Washington, D.C.
(113)
WEST VIRGINIA
Wheeling
Weirton
Parkers burg
Huntington
Piedmont
Keyser
Bluefield
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QR8
Zinc
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.4
0.4
0.4
0.8
0.5
1.2
0.9
1.6
2.1
1.6
3.0
1.6
1.1
1.9
1.6
1.8
1.5
2.9
3.4
2.2
5.4
1.3
1.5
1.4
2.5
4.0
4.7
Annual steel
Sample
size
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Min.
Max.
Mean
16
17
4
2
10
8
38
27
34
28
34
39
38
36
29
25
28
28
55
50
56
67
37
41
39
32
42
30
Quarterly steel
Sample
size
4
4
4
4
3
3
4
4
4
4
4
4
3
4
4
3
4
4
4
4
4
4
4
4
4
2
3
2
4
1
3
Min.
1
2
0
1
1
44
36
16
35
32
41
8
29
38
37
48
37
80
72
63
96
33
50
34
42
60
52
63
58
32
30
Max.
33
32
5
5
21
63
52
89
60
87
83
103
74
66
50
57
54
114
100
132
121
63
64
74
58
62
128
72
75
32
38
Mean
16
16
2
3
9
54
43
46
50
49
59
59
46
50
44
54
46
96
85
93
104
46
55
55
48
61
78
67
63
33
Fabric No. 1
Sample
size
4
4
4
4
2
1
4
4
4
4
4
3
3
4
4
4
3
4
4
3
4
4
4
4
3
4
2
4
2
4
1
3
Min.
11.6
16.5
9.4
17.6
11.5
13.8
11.8
14.5
12.4
15.3
13.4
19.3
12.7
18.0
13.2
15.1
11.6
15.4
11.7
14.6
12.1
15.3
12.7
16.5
15.1
19.8
14.9
15.2
16.2
14.9
17.2
13.3
Max.
15.6
18.9
19.7
20.2
15.2
13.8
15.7
20.6
17.2
20.7
16.4
19.4
14.4
19.3
17.0
20.3
17.2
22.4
15.7
21.1
15.7
21.8
18.5
20.7
18.5
27.3
15.5
21.4
16.3
19.9
17.2
7RO
Wean
13.1
17.7
14.5
18.9
13.4
13.7
17.4
14.4
19.2
15.0
19.4
13.7
18.6
14.9
18.1
14.8
19.6
14.2
17.8
14.3
18.1
15.4
18.3
16.9
22.5
15.2
18.6
16.3
17.7
1PR
Fabric No. 2
Sample
size
4
4
2
4
3
4
3
4
3
4
4
4
3
1
2
1
Win.
1.7
0.8
2.0
0.6
2.2
1.9
1.7
2.4
2.6
1.7
0.8
0.7
2.9
1.3
1.2
3.0
Max.
4.2
3.9
3.6
1.5
3.8
2.8
3.5
4.2
5.1
7.7
4.8
2.1
3.7
1.3
1.3
3.0
Mean
2.7
2.3
2.8
1.1
3.2
2.3
2.9
3.2
2.6
3.4
3.0
1.4
3.3
1.2
00
"8
-------
w
JO
I
W
n
w
2
8
H
Table B-1 (continued). DATA SUMMARY
State/city
WASHINGTON
Spokane
Pullman
Clarkston
Bellingham
Seattle
Longview
Vancouver
WASHINGTON, D.C.
Washington, D.C.
(7)
Washington, D.C.
(113)
WEST VIRGINIA
Wheeling
Weirton
Parkersburg
Huntington
Piedmont
Keyser
Bluefield
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1C1KS
Fabric No. 3
Sample
size
4
4
4
4
3
1
4
4
4
4
4
3
4
4
4
4
3
4
4
3
3
4
4
4
4
4
2
4
2
4
1
q
Min.
13.2
17.5
9.4
14.9
13.2
16.1
13.1
18.6
16.4
23.6
8.6
15.8
15.2
17.9
30.0
36.9
26.5
37.3
26.0
34.4
24.1
29.2
14.6
26.3
12.8
24.3
13.5
19.1
15.8
23.4
17.2
9T Fi
Max.
16.3
20.3
14.8
21.0
15.8
16.1
17.7
24.1
23.7
26.9
18.1
19.2
19.4
23.0
45.9
53.5
33.5
53.6
39.0
47.2
29.8
44.4
26.1
28.6
24.3
29.4
14.6
24.3
16.9
26.4
17.2
31 7
Mean
14.6
19.2
12.4
17.0
14.2
15.1
20.1
20.4
25.2
13.9
17.5
17.5
20.0
37.5
44.0
29.2
43.6
32.7
39.6
27.3
34.2
19.8
27.2
18.9
27.0
14.0
22.4
16.4
24.3
9fi fi
Fabric No. 4
Sample
size
4
3
2
4
3
3
3
4
3
3
4
4
4
2
2
1
Min.
9.7
14.5
8.4
13.5
10.8
13.6
10.9
9.3
13.3
11.3
9.5
11.9
10.9
12.7
15.6
15.3
Max.
15.7
15.5
14.2
19.0
15.6
19.5
14.1
21.7
24.8
23.1
19.9
23.6
23.2
18.0
19.9
15.3
Mean
12.4
15.0
11.3
15.7
12.9
16.0
12.7
14.5
19.0
17.5
14.3
16.8
17.0
15.4
17.8
Fabric No. 5
Sample
size
4
4
1
4
4
3
4
4
4
3
4
4
3
4
4
i
Min.
6.1
9.0
7.3
8.3
5.4
6.8
4.0
6.0
7.5
6.2
5.0
7.1
6.4
7.6
6.0
n 1
Max.
9.0
11.2
7.3
11.1
7.4
9.1
9.9
15.3
18.4
14.1
12.5
13.3
11.3
13.9
14.5
14 1
Mean
7.9
10.0
8.8
5.9
7.7
7.2
9.8
12.2
9.5
8.8
10.2
8.0
10.5
10.7
m fi
Fabric No. 6
Sample
size
3
4
1
4
4
3
4
4
4
3
3
4
4
4
4
4
Min.
8.5
6.0
7.0
5.1
8.3
5.9
8.0
9.2
7.9
7.6
9.5
5.7
9.6
6.8
6.6
m T
Max
13.0
7.2
7.0
10.5
9.1
12.5
10.4
13.2
12.4
16.6
12.9
6.7
14.7
9.3
11.4
> o
Mean
10.3
6.4
6.9
8.7
8.7
8.7
11.2
10.2
10.7
11.1
6.0
1.6
8.1
8.2
1 1
Fabric No. 7
Sample
size
4
4
1
4
4
4
4
3
4
4
3
4
4
4
4
Q
Min
7.0
4.9
5.8
3.2
4.3
3.5
3.4
5.9
3.8
7.7
6.5
2.9
5.1
3.2
2.6
n ~l
Max
15.8
8.1
5.8
10.4
13.4
5.6
9.6
13.8
9.5
14.1
12.7
21.9
3.7
4.4
9.0
7 A
Mean
10.2
6.4
7.0
8.6
5.0
6.8
10.0
6.8
1.7
9.6
1.0
9.3
8.8
6.2
o n
-------
Table B-1 (continued). DATA SUMMARY
State/city
WASHINGTON
Spokane
Pullman
Clarkston
Bellingham
Seattle
Longview
Vancouver
WASHINGTON, D.C.
Washington, D.C.
(7)
Washington, D.C.
(113)
WEST VIRGINIA
Wheeling
Weirton
Parkersburg
Huntington
Piedmont
Keyser
Bluefield
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Fabric No. 8
Sample
size
4
4
1
4
4
3
3
4
4
3
3
4
4
4
4
3
Min
4.1
2.9
2.7
2.8
4.1
2.6
5.3
6.0
6.2
4.4
2.5
2.7
5.8
2.2
2.2
8.2
Max.
9.9
8.0
2.7
11.1
11.1
8.3
7.8
8.6
10.1
12.3
13.5
10.0
11.4
9.1
8.7
9.3
Mean
6.5
6.1
7.4
6.4
5.4
6.4
7.5
7.8
7.7
8.3
6.6
8.2
5.1
5.4
8.8
Fabric No. 9
Sample
size
4
3
1
4
4
3
4
4
4
3
4
4
4
4
4
4
Min.
13.3
7.8
12.7
13.1
13.6
17.7
10.4
14.3
10.9
13.3
15.5
12.0
18.0
8.9
11.0
13.3
Max.
19.1
12.9
12.7
19.6
20.7
19.9
21.2
30.8
30.5
31.7
26.4
27.5
31.6
25.9
27.6
29.8
Mean
16.8
10.9
16.5
17.0
19.0
18.1
22.0
21.7
20.5
21.6
20.1
24.4
17.8
17.4
22.1
Quarterly nylon
Sample
size
4
3
4
4
4
1
4
4
4
4
4
4
4
4
4
4
3
4
4
4
4
4
4
4
4
4
2
3
2
4
1
2
Min.
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2
0
Max.
0
0
0
1
0
0
0
0
40
12
1
0
0
0
3
5
0
4
2
1
2
2
0
6
2
1
1
0
1
0
2
0
Mean
0
0
0
0.5
0
0
0
12.0
5.8
0.2
0
0
0
1.0
2.0
0
1.0
0.5
0.2
0.5
0.5
0
1.5
0.8
0.8
0.5
0
0.5
0
0
Monthly nylon
Sample
size
12
12
12
12
12
6
12
12
12
12
11
12
12
12
12
12
11
12
12
12
11
11
12
12
12
11
5
10
4
12
4
9
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
0
0
0
0
1
0
0
2
20
7
0
0
0
0
1
1
1
0
1
0
1
0
0
3
0
0
1
1
0
0
0
0
Mean
0
0
0
0
0.1
0
0
0.3
4.0
1.8
0
0
0
0
0.2
0.1
0.1
0
0.1
0
0.1
0
0
0.3
0
0
0.1
0
0
Silver tarnishing
Sample
size
12
12
12
12
12
6
12
12
12
12
12
12
12
12
12
12
9
11
12
12
11
12
12
12
12
12
4
11
4
12
4
9
Min.
11
16
15
15
42
66
19
25
24
21
51
58
40
40
50
40
56
55
51
44
78
78
47
55
57
48
85
71
91
79
30
23
Max.
28
38
74
34
90
85
93
95
65
75
86
98
91
83
86
81
81
83
82
80
91
89
92
85
84
81
99
100
100
96
59
72
Wean
18
24
27
22
77
82
55
53
42
48
71
78
66
63
68
66
69
68
70
69
84
83
72
74
71
69
89
90
47
n
3
s?
s
to
I
-------
H
W
JO
Table B-1 (continued). DATA SUMMARY
State/city
WASHINGTON
Spokane
Pullman
Clarkston
Bellingham
Seattle
Longview
Vancouver
WASHINGTON, D.C
Washington, D.C.
(7)
Washington, D.C.
(113)
WEST VIRGINIA
Wheeling
Weirton
Parkers burg
Huntington
Piedmont
Keyser
Bluefield
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
12
12
12
12
11
6
12
12
12
12
12
12
12
12
12
11
10
12
12
12
12
11
12
12
12
11
5
11
5
12
4
9
Min.
0.0
0.0
0.0
0.0
0.0
0.0
0.2
0.0
0.4
0.0
0.0
0.0
0.1
0.1
0.7
0.3
0.6
0.4
0.8
0.8
1.0
0.5
0.3
0.2
0.2
0.2
0.5
0.3
0.5
0.4
0.2
0.0
Max.
0.6
0.6
0.2
0.1
0.3
0.4
0.7
0.9
1.4
1.4
0.4
0.5
1.0
1.2
2.4
3.0
1.8
2.5
2.5
3.4
2.3
1.6
0.7
1.9
0.8
0.7
1.8
2.9
1.4
2.0
0.8
1.2
Wean
0.3
0.2
0.0
0.0
0.1
0.1
0.4
0.2
0.9
0.9
0.2
0.1
0.6
0.5
1.4
1.0
1.0
1.0
1.5
1.3
1.5
1.1
0.5
0.6
0.6
0.5
1.0
1.0
0.4
Lead plates
Sample
size
12
11
4
11
11
11
11
12
12
12
10
12
8
10
10
8
Min.
0
0
0
0
3
0
1
3
3
5
6
2
2
2
2
0
Max.
4
1
2
3
10
3
8
18
17
26
17
8
5
16
13
8
Mean
2
0
2
6
2
4
8
7
10
9
4
3
6
7
3
Dustfall
Sample
size
12
12
12
12
12
7
12
12
11
11
12
11
12
12
12
12
10
12
12
12
11
12
11
12
12
12
5
11
5
12
5
9
Min.
1.7
2.9
3.5
2.9
2.2
2.0
1.6
1.6
0.5
2.0
3.1
3.4
1.9
0.9
3.9
3.2
1.9
1.8
4.8
2.8
6.0
7.3
2.2
4.6
3.1
2.6
0.8
2.9
0.6
1.6
2.8
2.3
Max.
11.7
8.8
01.1
8.1
42.4
6.0
10.3
4.8
3.0
3.9
6.8
6.8
5.6
3.3
9.0
16.9
5.3
5.0
15.2
8.9
29.0
33.3
12.3
9.2
10.8
9.7
3.9
9.5
2.7
6.7
4.3
8.0
Mean
4.5
4.8
13.1
5.0
7.0
4.0
3.8
3.1
2.1
2.8
4.5
5.0
2.7
2.4
6.9
8.2
3.3
3.4
8.0
6.5
18.3
16.5
6.7
6.9
6.1
6.0
4.9
4.1
5.1
Sticky paper
Sample
size
12
12
12
12
12
6
12
12
12
12
12
12
12
12
12
12
10
12
12
11
12
11
12
11
12
12
5
10
5
11
5
4
Min.
7
16
6
9
3
10
7
5
10
14
6
5
7
5
17
13
6
4
10
15
24
36
3
1
7
21
11
26
3
1
2
10
Max
38
57
53
46
37
29
34
41
39
38
31
47
37
41
65
72
42
55
44
48
66
84
30
42
42
70
45
76
32
55
35
53
Mean
24
30
22
24
20
17
18
22
22
24
18
20
18
25
42
51
27
30
22
28
47
56
12
14
23
42
47
22
Rubber cracking
Sample
size
41
52
52
52
51
26
51
52
52
52
51
50
52
51
52
52
44
52
50
49
49
50
50
48
51
51
19
47
20
50
20
19
Min
0
0
0
0
0
0
0
6
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max
.310
.356
.353
.446
.244
.087
.297
.247
.194
.154
.340
.187
.403
.171
.272
.227
.328
.315
312
169
275
169
307
202
315
207
234
272
312
398
471
297
Mean
.071
.062
.085
.071
.052
.003
.053
.033
.031
.009
.058
.032
.062
.029
.066
.057
.110
.079
.064
.050
.086
.054
.082
.052
.110
.038
.051
.103
3
r
w
n
H
-------
Table B-1 (continued). DATA SUMMARY
State/city
WISCONSIN
Superior
Kenosha
La Crosse
WYOMING
Cheyenne
Frannie
PUERTO RICO
Guaynabo
Salinas
El Yungue
CANADA
Ojibway, Ontario
Sarnia, Ontario
(168)
Sarnia, Ontario
(169)
Windsor, Ontario
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Zinc
Sample
size
1
1
1
1
1
1
1
1
Min.
Max.
Mean
1.3
1.7
4.6
0.9
2.3
1.3
1.4
4.1
Annual steel
Sample
size
1
1
1
1
1
1
1
Min.
Max.
Mean
24
30
35
32
26
49
47
Quarterly steel
Sample
size
4
4
4
4
4
2
2
2
2
2
2
3
3
1
2
Min.
25
36
40
40
20
0
2
131
22
38
89
71
65
37
1
Max.
47
45
65
53
27
3
6
133
23
40
194
82
86
37*
60
Mean
34
40
49
46
24
2
4
132
22
39
142
76
76
30
Fabric No. 1
Sample
size
4
3
4
4
3
2
1
1
1
2
2
3
2
Min.
15.0
19.5
15.2
19.1
17.2
13.7
22.0
13.5
21.5
21.5
21.5
18.2
21.3
Max.
18.2
25.2
19.0
23.2
19.6
18.9
22.0
13.5
21.5
23.7
23.7
23.6
24.5
Wean
6.8
21.7
7.4
21.2
8.4
6.3
22.6
22.6
21.6
22.9
Fabric No. 2
Sample
size
4
4
Min.
3.1
1.5
Wax.
4.8
5.5
Wean
3.7
4.0
D.
R-
w
on
-------
tfl
I
3
r
n
m
"0
o
H
Table B-1 (continued). DATA SUMMARY
State/city
WISCONSIN
Superior
Kenosha
La Crosse
WYOMING
Cheyenne
Frannie
PUERTO RICO
Guaynabo
Salinas
El Yungue
CANADA
Ojibway, Ontario
Sarnia, Ontario
(168)
Sarnia, Ontario
(169)
Windsor, Ontario
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1 QCQ
Fabric No. 3
Sample
size
4
3
4
4
3
2
1
1
1
2
3
3
o
din.
5.8
6.2
5.6
21.9
17.4
12.7
25.9
19.7
29.4
29.2
23.9
19.7
T7 A
Max.
0.7
2.5
2.7
7.2
9.5
14.8
25.9
19.7
29.4
33.6
25.6
24.1
on Q
Mean
7.9
9.5
8.8
24.7
8.8
13.8
31.4
24.7
21.9
OR 1
Fabric No. 4
Sample
size
4
3
Min.
11.8
13.8
Wax.
21.6
30.1
Mean
16.6
21.8
Fabric No. 5
Sample
size
3
4
3
2
2
1
1
3
2
3
)
Min.
7.6
5.8
8.7
8.1
10.6
12.5
12.1
5.7
12.5
7.6
104
Max.
10.2
16.0
14.3
10.5
14.5
12.5
12.1
14.5
15.5
14.5
1fi a
Mean
8.9
10.5
12.0
9.3
12.6
9.7
14.0
11.8
13fi
Fabric No. 6
Sample
size
3
4
3
2
1
1
1
2
3
4
.1
Min.
4.7
5.9
7.6
4.9
7.3
9.4
6.7
13.7
7.3
4.6
a q
Max.
14.5
12.3
10.0
6.3
7.3
9.4
6.7
25.5
13.6
10.2
11 R
Mean
8.9
10.0
9.2
5.6
19.6
10.3
7.6
in )
Fabric No. 7
Sample
size
4
4
4
2
1
1
1
3
3
3
)
Min.
5.0
6.3
3.3
4.1
6.9
8.0
4.9
12.9
10.0
2.8
f, n
Max.
17.7
20.8
13.3
7.1
6.9
8.0
4.9
23.6
16.6
9.3
1K 1
Mean
11.7
12.0
8.0
5.6
17.6
12.6
5.1
m n
-------
Table B-1 (continued). DATA SUMMARY
State/city
WISCONSIN
Superior
Kenosha
La Crosse
WYOMING
Cheyenne
Frannie
PUERTO RICO
Guaynabo
Salinas
El Yungue
CANADA
Ojibway, Ontario
Sarnia, Ontario
(168)
Sarnia, Ontario
(169)
Windsor, Ontario
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1QCP
Fabric No. 8
Sample
size
2
4
3
2
1
1
1
1
2
2
1
Min.
4.3
4.0
5.5
6.8
5.2
8.1
16.0
10.0
4.7
3.8
in n
Max.
4.7
12.3
8.4
8.1
5.2
8.1
16.0
10.0
9.1
9.5
m n
Mean
4.5
9.0
8.0
7.4
6.9
6.6
Fabric No. 9
Sample
size
3
4
3
2
1
1
1
1
2
3
3
T
Min.
10.2
14.6
12.1
4.2
9.2
27.8
23.3
38.4
19.0
14.6
12.2
17 5
Max.
25.6
24.4
26.5
17.5
9.2
27.8
23.3
38.4
30.4
35.7
26.0
-?n o
Mean
18.0
20.4
19.7
10.8
24.7
24.4
20.1
OAA
Quarterly nylon
Sample
size
4
4
4
4
4
2
2
2
2
2
4
4
4
3
Min.
0
0
0
0
0
0
0
9
0
0
0
0
0
n
Max.
0
1
0
0
1
1
0
18
0
0
0
0
2
R
Mean
0
0.2
0
0
0.2
0.5
0
13.5
0
0
0
0
0.5
1 7
Monthly nylon
Sample
size
11
12
12
12
11
7
6
5
6
6
10
9
10
Q
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
n
Max.
0
0
2
0
2
1
0
8
0
0
0
0
0
n
Mean
0
0
0.2
0
0.3
0.1
0
0
0
0
0
0
n
Silver tarnishing
Sample
size
12
12
12
12
10
6
6
6
6
6
9
10
11
in
Min.
34
36
24
35
10
6
78
53
30
1
53
30
57
1A
Max.
67
86
74
57
30
48
89
77
55
21
84
85
85
-70
Wean
54
58
51
46
20
26
82
67
40
11
69
64
71
en
X
ee
CP
-------
I
a
60
n
w
o
w
n
Table B 1 (continued). DATA SUMMARY
State/city
WISCONSIN
Superior
Kenosha
La Crosse
WYOMING
Cheyenne
Frannie
PUERTO RICO
Guaynabo
Salinas
El Yungue
CANADA
Ojibway, Ontario
Sarnia, Ontario
(168)
Sarnia, Ontario
(169)
Windsor, Ontario
Year
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
1967
1968
Lead peroxide candle
Sample
size
11
12
12
12
10
6
6
6
6
6
9
9
9
9
Min.
0.1
0.0
0.0
0.0
0.0
0.0
0.4
0.3
0.0
0.0
1.0
0.7
0.7
0.4
Max.
.0
.4
.2
.7
0.5
0.1
0.9
0.9
0.1
0.1
1.9
1.8
1.5
1.1
Vlean
0.5
0.4
0.6
0.6
0.2
0.0
0.6
0.7
0.0
0.1
1.5
1.2
1.1
0.7
Lead plates
Sample
size
11
12
10
7
6
6
6
5
9
9
9
8
Min.
2
2
0
0
2
0
0
0
9
6
6
3
Max.
11
10
5
2
5
5
0
0
17
17
12
7
Mean
4
5
2
1
4
4
0
12
9
8
5
Dustfall
Sample
size
10
12
12
11
11
7
7
6
5
4
9
10
10
8
Vlin.
1.7
2.2
2.5
3.3
1.5
0.5
0.8
16.7
0.4
1.0
2.9
3.5
1.9
1.3
Max.
6.1
8.9
9.5
13.0
8.6
30.0
3.2
39.8
2.3
3.5
7.1
7.7
6.4
4.5
Mean
3.9
5.2
5.0
6.6
4.1
6.0
2.0
23.2
.
4.9
5.9
5.2
2.8
Sticky paper
Sample
size
11
9
12
10
11
6
6
6
5
5
7
10
10
8
Min.
8
15
4
8
6
22
4
18
7
2
35
3
14
6
Max.
46
72
34
53
62
31
47
41
52
10
76
69
62
62
Mean
24
33
19
28
25
28
25
31
55
36
29
25
Rubber cracking
Sample
size
44
52
52
48
48
25
28
23
23
25
11
35
14
42
43
36
Min.
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Max.
.435
.363
.504
.392
.269
.252
.264
.161
.18/
255
244
441
252
288
295
383
Mean
.101
.049
.144
.088
.063
.077
.143
.060
.055
.126
-------
APPENDIX C.
1968 QUARTILE RANKINGS OF COMPONENTS
BY AREA AND STATION
-------
Table C-1. COMPONENT RANKS, 1968
Area name
Albany, New York
Anchorage, Alaska
Ann Arbor, Michigan
Augusta, Georgia
Austin, Texas
Bastrop, Louisiana
Beaumont, Texas
Bellingham, Washington
Binghampton, New York
Blacksburg, Virginia
Block Island, Rhode Island
Bluefield, Virginia
Bogalusa, Louisiana
Boston, Massachusetts
Boulder City, Nevada
Bridgeport, Connecticut
Broward County, Florida
Bristol, Tennessee
Brownsville, Texas
Brownwood, Texas
Buffalo, New York
Station
number
22
30
246
224
131
133
120
216
208
121
122
123
124
77
25
195
189
159
160
214
192
89
243
135
148
158
119
125
23
24
Particulates
£ *
& ^»
d? ^ **
? ^
^ ^
"*» ^
y£ 5?
(fr ff
<$ ^
4 2
5 4
2 2
2 2
4 2
2 2
2 2
2 2
2 2
2 2
2 2
2 2
4 2
2 2
2 2
2 2
2 2
2 2
2 2
2 2
5 5
2 2
5 5
4 2
2 2
2 2
2 2
2 2
2 2
4 2
NOX
fW
Q.
^*
$»
/
1
4
3
2
2
2
4
2
2
3
3
3
2
2
3
2
3
3
3
2
4
1
5
1
3
2
1
3
4
Oxidation
potential
^
-------
H
PI
90
on
en
§
r
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Buffalo, New York (continued)
Bullfrog, Utah
Burlington, Vermont
Cairo, Illinois
Calexico, California
Cannon Mountain, New Hampshire
Carville, Louisiana
Chapel Hill, North Carolina
Charleston, Indiana
Charlotte, North Carolina
Chattanooga, Tennessee
Cheyenne, Wyoming
Chicago, Illinois
Cincinnati, Ohio
Station
number
264
265
266
267
262
181
258
93
175
219
237
238
263
31
32
33
140
141
252
26
52
53
54
55
136
137
138
139
149
6
Particulates
«.
/ j?'
/ //
__
_ _ _
_ _ _
_ _ _
_ _ _
1 1 2
_ _ _
344
1 - 2
1 1 1
1 1 1
1 1
_ _ _
334
223
2 1 3
323
4 1 1
3 2 1
555
555
455
235
445
455
454
233
224
554
345
S02
Jf
^ & ^ /
/ // / j
_ _ _
-----
-----
_____
_ _ 1 _ _
33223
_____
11111
2 2 - - -
11221
11222
1112-
_____
23221
23222
22222
33223
22223
1 1 1 - -
55335
55555
554-4
4 4
54333
55434
55433
4 4 5 - -
33321
4 5 3 - -
33223
H2S
$
/
-
-
2
4
1
3
1
1
-
3
3
3
3
2
1
4
5
4
3
3
5
4
3
2
4
3
Acid
aerosol
/ /
^f j*
//
- -
-
5 4
2
2 2
2 2
4 4
4 2
2 2
-
2 2
2 2
4 2
4 2
2 2
2 2
5 5
4 4
2 2
2 2
4 2
2 2
2 2
2 4
4 2
4 4
4 2
IMOX
^>-
/
_
-
3
2
1
1
2
3
3
3
3
2
1
5
4
3
4
3
5
4
3
2
3
4
Oxidation
potential
<£
-------
VI
o
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Cincinnati, Ohio (continued)
Clarkston, Washington
Clifton, Arizona
Columbus, Georgia
Columbus, Ohio
Corvallis, Oregon
Custer, South Dakota
Davenport, Iowa
Del Rio, Texas
Denver, Colorado
Detroit, Michigan
Douglas, Arizona
Dubuque, Iowa
Dulce, New Mexico
Duluth, Minnesota
Station
number
70
154
155
74
75
76
261
142
143
37
69
244
57
58
59
115
27
34
35
162
163
165
170
196
102
227
228
100
49
50
Particulates
/ *
£ N?'
^ ? A ..$»
£ -^ ^
-------
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Eagle Pass, Texas
Easton, Pennsylvania
East Helena, Montana
El Paso, Texas
Evansville, Indiana
Fairbanks, Alaska
Fall River, Massachusetts
Fargo, North Dakota
Farmington, New Mexico
Fernandina Beach, Florida
Fort Smith, Arkansas
Frankfort, Kentucky
Frannie, Wyoming
Gainesville, Florida
Grand Forks, North Dakota
Hartford, Connecticut
Hennepin, Illinois
Hilo, Hawaii
Honolulu, Hawaii
Station
number
116
14
230
254
103
104
105
44
161
247
188
191
198
249
98
99
134
231
232
210
211
106
253
233
197
248
184
56
242
241
Particulates
* / /
^> /\ .^>
5" i^" "^
4-4
324
1 1 2
434
1 4 1
2 3 1
353
342
332
- 2 3
2 1 2
245
244
1 - 1
1 4 2
1 3 1
2 2 1
2 1 1
2 2 1
3 1 2
1 1 1
2 1 1
1 2
3 1 1
422
4 4 1
444
2 1 2
1 1 1
1 3 2
S02
*
£ & j? $
C? $ ^* ^
/ / / / /
11111
43443
33342
5 - 2 - -
55225
21111
331-1
44333
44343
1 1 1
33342
45445
22221
2 2 - - -
11111
11115
225-5
2-333
2 2 4 - -
1111-
11111
22332
3 3 1 - -
1122-
22221
1 1 1 - -
45343
22232
1 1 1 - -
22321
H2S
$
$
/
4
3
3
1
3
1
3
1
3
1
2
2
1
1
1
1
5
5
5
1
1
2
5
4
1
1
2
1
1
1
Acid
aerosol
/ ^
jf ^
!& &
-
.fc
/
1
3
3
1
1
1
2
3
3
2
3
5
2
1
1
1
2
2
2
1
1
2
2
1
1
5
1
1
2
Oxidation
potential
^
-------
to
to
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Huntington, West Virginia
International Falls, Minnesota
Jackson, Mississippi
Joplin, Missouri
Kansas City, Missouri
Kenosha, Wisconsin
Keyser, West Virginia
Laredo, Texas
Lawrence, Massachusetts
Lebanon, New Hampshire
Leesburg, Virginia
Longview, Washington
Los Angeles, California
Louisville, Kentucky
Luray, Virginia
Station
number
65
66
67
251
269
206
207
47
48
85
86
87
51
150
151
152
153
117
173
177
171
180
114
80
81
239
240
39
40
172
i
Particulates
& fc
& *f
& -\ .0
<3^ £ tf
344
554
323
55-
_ _ _
1 2 2
2 1 1
4 2 1
332
223
2 3 1
333
323
234
432
342
222
452
1 - 2
233
222
2 1 2
1 1 1
3 1 3
1 1 1
1 2 3
234
444
534
1 1 1
SO2
*
c7 $" £" ^
/ /
/ /
1 1
1 1
3 1
1
4 2
3 4
2 _
2 2
4 2
4 3
3 3
3 2
2 5
2 3
1 2
4 3
3 2
3
2 3
1 3
1 1
3 4
1 1
1 2
5 5
5 4
2 2
2 1
3 3
f
VO
o\
oo
O
o
o
I
o
0*
v;
O.
I
-------
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Madawaska, Maine
May's Landing, New Jersey
Me All en, Texas
Memphis, Tennessee
Mil bank, South Dakota
Mobile, Alabama
Montauk Point, New York
Natchez, Mississippi
Needles, California
New Orleans, Louisiana
New York, New York
Nogales, Arizona
Oakland, California
Omaha, Nebraska
Oneca, Florida
Overland Park, Kansas
Owensboro, Kentucky
Station
number
193
1
118
147
209
245
250
146
144
215
235
90
91
218
2
3
4
5
19
20
21
229
101
95
202
203
130
88
41
42
Particutates
* />/«£ T ^
5 - 5 - -
4
1 1 2
22111
12114
111-1
1 - 2 - -
22331
3 3 5 - -
11113
11113
11111
1-111
23223
55555
44545
55554
55434
44553
4 4 5
33453
44545
22111
22231
22111
21111
11332
11111
22332
33332
H2S
-------
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Owensboro, Kentucky (continued)
Paducah, Kentucky
Parkersburg, West Virginia
Pascagoula, Mississippi
Pensacola, Florida
Petersburg, New York
Philadelphia, Pennsylvania
Phoenix, Arizona
Portland, Oregon
Portsmouth, New Hampshire
Providence, Rhode Island
Puerto Rico, Guaynabo
Puerto Rico, Salinas
Puerto Rico, El Yungue
Pullman, Washington
Rooseveltown, New York
St. Joseph, Missouri
St. Louis, Missouri
Station
number
43
259
260
63
64
234
145
29
11
12
13
17
268
82
83
84
174
176
187
190
255
256
257
73
194
204
205
28
45
46
Particulates
/
-------
a
8
w
p
n
pn
2
tn
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
San Ysidro, California
Sarnia, Ontario, Canada
Sault St. Marie, Michigan
Savannah, Georgia
Seattle, Washington
Sherman, Texas
Shreveport, Louisiana
Sioux City, Iowa
Sioux Falls, South Dakota
South Tahoe, California
Spokane, Washington
Spray, North Carolina
Springfield, Massachusetts
Steubenville, Ohio
Sumpter Township, Michigan
Tampa, Florida
Station
number
94
166
167
168
169
223
132
78
127
212
213
200
201
199
96
97
71
72
156
157
222
182
183
60
61
62
220
221
164
68
Particulates
* to
* a'
/ //
1 3 1
433
3 3 1
333
322
334
332
1 2 3
233
- 2 -
322
4 4 1
542
342
1 2 1
1 1 1
3 - -
333
2 1
1 1 1
222
445
1 2 2
324
543
554
545
335
2 1 2
332
S02
&
* $ 3*
^ q, *» »
cf / ^/ /
11221
44433
33453
44442
44442
333-3
33333
33323
11 11
11 1 -
11 11
11 1 -
1 - 11
1-111
1-11-
11114
21111
22222
2 2 2 - -
22222
22221
54444
33444
44443
55555
44555
55554
44555
3333-
33452
H2S
?
2
4
2
3
4
3
4
2
1
2
3
1
1
1
1
1
1
1
2
2
3
2
2
3
5
5
5
4
2
5
Acid
aerosol
/
-------
l/t
OS
Table C-1 (continued). COMPONENT RANKS, 1968
Area name
Texarkana, Texas
The Dalles, Oregon
Ticonderoga, New York
Toledo, Ohio
Trenton, New Jersey
Vicksburg, Mississippi
Volunteer Arsenal, Chattanooga,
Tennessee
Washington, D.C.
Westerly, Rhode Island
Wichita Falls, Texas
Wilmington, Delaware
Winona, Minnesota
Youngstown, Ohio
Yuma, Arizona
Station
number
128
129
79
178
179
36
18
217
236
107
108
109
110
7
111
112
113
185
186
126
8
9
10
16
225
226
15
38
92
Particulates
< ta
» / *
/ / /
2 1 2
1 2 3
1 2 2
1 1 1
1 1 2
444
332
434
3 - -
522
2 1 1
2 1 1
3 1 1
444
2-3
234
233
1 2 3
232
1 2 1
543
222
343
223
2 2 1
223
5-4
555
1 3 1
S02
Sj.
«, ^P x
/ ///t
11111
11112
21111
33343
22234
4434-
4 3 - - 4
11112
11211
22355
222-2
21234
11224
34322
43334
333-5
33322
33453
33451
11111
55435
44453
55533
4-453
32231
22221
33333
44445
11112
H2S
e/
3
3
1
5
3
4
3
2
3
3
2
2
3
3
3
3
3
2
2
1
4
4
3
3
1
1
2
5
1
Acid
aerosol
,/
C^ ^
//
------- |