SEPA
United States
Environmental Protection
Agency
Region IE Office
26 Federal Plaza
New York, N.Y. 10007
EPA 902/4-78-009
October 1978
Air
New Jersey Portion of the
Metropolitan Philadelphia
AQCR Nonattainment
and Maintenance Study
For TSP
-------
GCA-TR-78-54-G
NEW JERSEY PORTION OF THE
METROPOLITAN PHILADELPHIA AQCR
NONATTAINMENT AND MAINTENANCE
STUDY FOR TSP
Final Report
Prepared for
U.S. ENVIRONMENTAL PROTECTION AGENCY
Region II
Air Programs Branch
New York, New York 10007
Contract No. 68-02-2539
Task Order No. 6
Project Officer
George Kerr
Prepared by
Victor L. Corbin
Susan Pultz
October 1978
GCA CORPORATION
GCA/TECHNOLOGY DIVISION
Bedford, Massachusetts
-------
DISCLAIMER
This Final Report was prepared for the Environmental Protection Agency by
GCA Corporation, GCA/Technology Division, Burlington Road, Bedford, Massachusetts
01730, in fulfillment of Contract No. 68-02-2539, Task Order No. 6. The opi-
nions, findings, and conclusions expressed are those of the authors and not
necessarily those of the Environmental Protection Agency. Mention of company
or product names is not to be considered as an endorsement by the Environmental
Protection Agency.
-------
ABSTRACT
The Camden Area is not attaining the secondary TSP standard and is unclassi-
fied with regard to the primary TSP standard. The objective of this study
was to use dispersion modeling and filter analysis to identify the reasons for
the secondary standard violation, and to propose, demonstrate and analyze, by
means of dispersion modeling, various control strategies to attain and maintain
the secondary standards through 1990. The data utilized and developed under
this contract were to be formatted such that the data would satisfy the minimum
data requirements for SIP submission as outlined in the Clean Air Act Amendments
of 1977.
iii
-------
iv
-------
CONTENTS
Abstract
List of Figures vi
List of Tables vii
1. Introduction 1
2. Development of Emission Inventory 2
Development of Point Source Emissions Data 2
Projection of Point Source Emissions 2
Development of Area Source Emissions Data 2
Projection of Area Source Emissions 8
3. Calibration of AQDM for TSP 15
4. Calculated Air Quality 20
5. Air Quality Analysis and Recommendations 35
Air Quality Data at the NASN Site in Camden 35
Attainment of the Primary Annual TSP Standard 36
Attainment of the Secondary TSP Standard 36
Recommendations for Further Study 36
References 39
Appendices
A. Source Contribution Files for Selected Receptors 41
B. Emission Tracking System 57
Rationale for a Tracking System 57
Tracking Area Sources 58
Tracking Point Sources 60
Tracking Methodology 60
Tracking Methodology Using Monitoring Data 64
Data Sources 67
-------
LIST OF FIGURES
Nos.
1 TSP Calibration for 43 Select New Jersey and Pennsylvania
Monitors (1974) 16
2 TSP Calibration for all 17 New Jersey Monitors (1974) 17
3 TSP Calibration for 16 Select New Jersey Monitors (1974) 18
4 Arithmetic Average TSP in ug/m3 1982 Air Quality no Strategy .... 21
5 Arithmetic Average TSP in yg/m3 1990 Air Quality no Strategy .... 22
6 Camden TSP Air Quality for 1982 27
7 Camden TSP Air Quality for 1990 28
8 Frequency Distribution for Cherry Hill Site 31
9 Frequency Distribution for Berlin Township Site 32
10 Frequency Distribution for South Park Drive Site 33
11 Frequency Distribution for NASN Site 34
12 Distribution of the Location of Sources Impacting Selected
Receptors in Camden City in 1974 37
13 Distribution of the Location of Sources Impacting Selected
Receptors in Camden City in 1982 38
vi
-------
LIST OF TABLES
Nos. Page
1 Revised Particulate Emission Rates 3
2 Point Source Growth Factors, 1982 4
3 Point Source Growth Factors, 1990 5
4 Point Source Emissions of Particulate by SIC for 1982 6
5 Point Source Particulate Emissions by SIC for 1990 7
6 Area Source Growth Factors (1982) 9
7 Area Source Growth Factors (1990) 10
8 Projection Parameter for Area Source Categories 11
9 Motor Vehicle Emission Factor for Particulates 12
10 Area Emissions of Particulate for 1982 (ton/yr) 13
11 Area Emissions of Particulate for 1990 (ton/yr) 14
12 Comparison of Predicted and Observed Annual Arithmetic Average
TSP Levels 19
13 TSP Air Quality 1982 23
14 TSP Air Quality 1990 25
15 TSP Air Quality in Camden 1982 29
16 TSP Air Quality in Camden 1990 29
17 Geometric Standard Deviations for the Camden Area 30
18 Analysis of Point Source Emissions - 1978 61
19 Companies With Individual Point Sources Emitting More Than 100 t/yr
Particulates 62
20 Companies With Individual Point Sources Emitting More Than 25 t/yr
Particulates 63
vii
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LIST OF TABLES (continued)
Nos.
21 Projected Emissions 1982 - 1990 ................... 65
22 Proportional Roll-Forward Model ................... 66
viii
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SECTION 1
INTRODUCTION
Based on the NASN monitoring site in the City of Camden, the region around
this monitor is not in attainment of the TSP standard. The reason for the non-
attainment of the standard is unknown. Since the Clean Air Act Amendments of
1977 specify that all nonattainment areas must have a new SIP submission by
January 1, 1979, this contract was awarded to try and determine the reason for
the nonattainment of the standard, and to develop control strategies which would
attain and maintain the standard through 1990. In addition to developing the
control strategies, a detailed set of backup information is required to sub-
stantiate the recommendations and conclusions of the SIP. The minimum data
requirements, as outlined in the Clean Air Act Amendments of 1977, were satis-
fied, and the data are included in the appropriate sections of this report.
This study examined the attainment and maintenance of the secondary TSP
standards through 1990 for the City of Camden. In order to determine the air
quality for future years and perform strategy analysis, a number of distinct
tasks had to be implemented. In order to better understand the steps followed
in the performance of this contract, the project was broken down into a number
of small and clearly identifiable tasks which are defined and described in the
following sections.
-------
SECTION 2
DEVELOPMENT OF EMISSION INVENTORY
DEVELOPMENT OF POINT SOURCE EMISSIONS DATA
The basic point source emission inventory which was initially utilized in
this study was the inventory previously developed under Contract No. 68-02-1376,
Task No. 24.l Since Contract No. 68-02-1376, Task Order No. 24 was completed,
GCA has developed a number of error checking programs to check the consistency
of the NEDS data. As a result of this analysis, only the U.S. Steel Fairless-
Works had any changes made to the emissions, and this was a decrease in TSP of
6,000 ton/year from one of the sources.
Based on additional information on compliant sources, a number of changes
were made to the inventory for the projection years. The sources which were
changes are listed in Table 1.
PROJECTION OF POINT SOURCE EMISSIONS
In order to calculate air quality for future years, the emissions have to
be projected to the year of interest. For most of the counties, the projection
parameters which were utilized are not the same as the projection values used
in Contract 68-02-1376. The new projection parameters are from the final Re-
gional Development Guide which was developed by the Delaware Valley Regional
Planning Commission (DVRPC). Tables 2 and 3 list the growth factors for the
various categories for each county in the region. For Salem and New Castle
Counties, the same projections were utilized as in the previous study under
Contract No. 68-02-1376.
Power plants were not projected using the growth factors, but rather data
obtained under Contract No. 68-02-1376 was utilized to calculate future year
emissions from the various power plants. For the Owens-Corning Plant listed
in Table 1, three point sources were added for the future years to the inven-
tory for completeness and accuracy. Tables 4 and 5 list the major point source
emissions in each county by SIC category.
-------
TABLE 1. REVISED PARTICULATE EMISSION
RATES
Emission rate (ton/yr)
Company name
Old Revised
Owens-Corning 0 107
Gulf & Western 18 1.4
Kewanee Oil Corp. 504 5.6
Certain-Teed 299 1.0
-------
TABLE 2. POINT SOURCE GROWTH FACTORS, 1982
SIC code
Bucks
Chester
Delaware
Montgomery
Philadelphia
Burlington
Camden
Gloucester
Mercer
Salem
New Castle
Agriculture Mining
1 to 9 10 to 14
0.901
0.826
0.890
0.833
0.899
0.898
0.901
0.910
0.890
0.870
0.870
0.973
0.954
0.959
0.959
0.959
0.993
0.988
1.018
0.929
0.957
0.957
Construction
15 to 17
1.
0.
0.
1.
1.
1.
1.
1.
1.
1.
1.
052
987
991
027
051
069
056
123
107
046
046
Manufacturing
18 to 39
0
0
1
1
1
1
1
0
1
1
1
.989
.996
.007
.006
.026
.053
.020
.995
.044
.409
.409
Transportation
and Wholesale
Communication 50 to 51
40 to 49
1.
0.
1.
1.
1.
1.
1.
1.
1.
1.
1.
034
982
059
240
006
117
053
107
079
366
366
0
0
1
0
1
1
1
0
1
1
1
.951
.970
.001
.999
.059
.028
.026
.944
.042
.600
.600
Retail
52 to 59
1.041
1.051
1.107
1.099
1.066
1.099
1.109
1.173
1.062
1.600
1.600
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TABLE 3. POINT SOURCE GROWTH FACTORS, 1990
U1
„_ . Agriculture Mining
SIC code **x to 9 1() to"*4
Bucks
Chester
Delaware
Montgomery
Philadelphia
Burlington
Camden
Gloucester
Mercer
Salem
New Castle
0.803
0.652
0.780
0.666
0.798
0.795
0.801
0,820
0.780
0.740
0.740
0.947
0.909
0.918
0.918
0.917
0.986
0.977
1.036
0.857
0.914
0.914
Construction
15 to 17
1.105
1.975
0.981
1.053
1.103
1.137
1.111
1.245
1.214
1.092
1.092
Manufacturing
18 to 39
0
0
1
1
1
1
1
0
1
1
1
.978
.991
.015
.013
.053
.106
.039
.989
.087
.818
.818
Transportation
and Wholesale
Communication 50 to 51
40 to 49
1.069
0.964
1.118
1.049
1.013
1.235
1.106
1.215
1.158
1.732
1.732
0.901
0.940
1.001
0.997
1.117
1.055
1.052
0.887
1.084
2.200
2.200
Retail
52 to 59
1.083
1.102
1.215
1.198
1.132
1.198
1.218
1.346
1.124
2.200
2.200
Finance
Insurance
Real Estate
60 to 67
1.191
1.091
1.026
1.060
1.078
1.239
1.052
1.225
1.145
2.200
2.200
Services
68 to 84
1.125
1.039
1.349
1.175
1.285
1.383
1.424
1.621
1.150
2.200
2.200
Government
85 to 97
1.285
1.173
1.217
1.285
1.327
1.170
1.316
1.511
1.302
2.200
2.200
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TABLE 4. POINT SOURCE EMISSIONS OF PARTICULATES BY SIC FOR 1982 (TPY)
Sic code Burlington
13
14
20
?6
2U 65
29
J2 1,384
3) 352
'34 83
36
37
)9
49 39
Lflrm> point 1,923
sou rccs
Small point 182
sourci-H
Total 2,105
Camden Gloucester Mercer Salem Total
8 8
170 170
79 79
54 54
82 27 300 254 728
214 2,613 901 3,728
403 2 311 448 2,548
83 435
29 112
30 30
3 3
3 3
402 1,635 72 2,148
1,069 3,127 2,249 1,678 10,046
4,469 354 115 165 1,285
1,538 3,481 2,364 1,843 11,331
Category
Oil and gas
extract Ion
Quarrying and mining
Food and kindred
products
Paper and allied
products
Chemicals and
allied products
Petroleum refining
Stone, clay, glass
and concrete
Primary metals
Fabricated metal
products
Electrical and elec-
tronic machinery
Transportation
equipment
Miscellaneous
manuf ac tur ing
Electricity production
-------
TABLE 5. POINT SOURCE EMISSIONS BY SIC FOR 1990 (TYP)
Sic code
13
14
20
26
28
29
32
33
34
liurllngton Camdon
8
168
82
54
69 85
218
1,456 406
370
88 29
Gloucester Mercer Salem Total
8
168
82
54
27 312 327 820
2,597 1,164 3,979
2 320 581 2,765
82 452
117
Category
Oil and gas
extraction
Mining and quarrying
Food and kindred
products
Paper and allied
products
Chemical and allied
products
Petroleum refining
Stone, clay, glaas
and concrete
Primary metals
Fabricated metal
products
36 30 30 Electrical and elec-
tronic machinery
37 33 Transportation
equipment
39 44 Miscellaneous
manufacturing
49 31 441 1,353 63 1,888 Electricity
. ™ ' • ' produc tIon
Large point 2,014 1,080 3,149 1,988 2,139 10,370
sources
Small point 192 483 353 120 210 1,358
sources
Total 2,206 1,563 3,502 2,108 2,349 11,728
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DEVELOPMENT OF AREA SOURCE EMISSIONS DATA
Under Contract No. 68^-02-1376, an area emissions inventory was prepared
for 1974, and this inventory was utilized for this study. No changes were
made in the methodology or allocation of emissions.
PROJECTION OF AREA SOURCE EMISSIONS
The 1974 area emission inventory was projected to 1982 and 1990 using
the growth factors in Tables 6 and 7. These factors were obtained from the
Regional Development Guide developed by DVRPC. These factors differ from
those used in Contract No. 68-02-1376. In addition to projecting the inven-
tory, the emission factor for particulate emissions from motor vehicles was
modified to account for the reduction in particulates from the increasing
number of vehicles equipped with catalytic converters. Table 8 lists the
emission factors utilized, and Tables 9 and 10 list the emissions by source
category for 1982 and 1990.
-------
TABLE 6. AREA SOURCE GROWTH FACTORS (1982)
Population
Bucks
Chester
Delaware
Montgomery
Philadelphia
Burlington
Camden
Gloucester
Mercer
Salem
New Castle
1.073
1.019
1.039
1.061
1.008
1.073
1.071
1.118
1.058
1.108
1.108
Households
1.071
1.069
1.099
1.122
1.065
1.092
1.130
1.150
1.092
1.108
1.108
Commercial
Institutional
Employment
1.057
1.029
1.107
1.072
1.104
1.115
1.129
1.197
1.092
1.600
1.600
Industrial
Employment
0.991
0.994
1.012
1.008
1.021
1.062
1.025
1.008
1.047
1.409
1.409
VMT
Freeway
1.096
1.019
1.271
1.140
1.141
1.006
1.115
1.073
1.148
1.218
1.218
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TABLE 7. AREA SOURCE GROWTH FACTORS (1990)
Bucks
Chester
Delaware
Montgomery
Philadelphia
Burlington
Camden
Gloucester
Mercer
Salem
New Castle
Population
1.146
1.038
1.078
1.121
1.015
1.145
1.142
1.236
1.116
1.215
1.215
Households
1.143
1.137
1.198
1.244
1.131
1.185
1.260
1.300
1.183
1.215
1.213
Commercial
Institutional
Employment
1.114
1.059
1.215
1.144
1.209
1.231
1.258
1.393
1.183
2.200
2.200
Industrial
Employment
0.982
0.988
1.024
1.015
1.043
1.124
1.049
1.017
1.095
1.818
1.818
VMT
Freewi
1.191
1.03*
1.54:
1.28:
1.28
1.0 1:
1.23
1.14
1.29
1.47
1.43
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TABLE 8. PROJECTION PARAMETER FOR AREA SOURCE CATEGORIES
Category
number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
Major
classification
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Comm'l & institl fuel
Coinm'l & institl fuel
Comm'l & institl fuel
Comm'l & institl fuel
Comm'l & institl fuel
Comm'l & institl fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
On-site incineration
On-site incineration
On-site incineration
Open burning
Open burning
Open burning
Gasoline fuel
Gasoline fuel
Gasoline fuel
Diesel fuel
Diesel fuel
Diesel fuel
Aircraft
Aircraft
Aircraft
Vessels
Minor
classification
Anthracite coal
Bituminous coal
Distillate oil
Residual oil
Natural gas
Wood
Anthracite coal
Bituminous coal
Distillate oil
Residual oil
Natural gas
Wood
Anthracite coal
Bituminous coal
Coke
Distillate oil
Residual oil
Natural gas
Wood
Process gas
Residential
Industrial
Comm's & institl
Residential
Industrial
Comm's & institl
Light vehicle
Heavy vehicle
Off highway
Heavy vehicle
Off highway
Rail locomotive
Military
Civil
Commercial
Anthracite coal
Projection
parameter
*
NP
NP
Housing units
NP
Housing units
NP
C/I employment
C/I employment
C/I employment
C/I employment
C/I employment
NP
Industrial employment
Industrial employment
NP
Industrial employment
Industrial employment
Industrial employment
NP
NP
NP
NP
NP
NP
NP
NP
Average VMT projection
Average VMT projection
Population
Average VMT projection
Population
Population
Projected aircraft
operation
Projected aircraft
operation
Projected aircraft
operation
NP
(Continued)
11
-------
TABLE 8 (continued).
Category
number
Major
classification
Minor
classification
Projection
parameter
37 Vessels
38 Vessels
39 Vessels
40 Evaporation
41 Evaporation
42 Measured VEH miles
43 Measured VEH miles
44 Measured VEH miles
45 Measured VEH miles
46 Dirt roads traveled
47 Dirt airstrips
48 Construct land area
49 Rock handlg & storage
50 Forest fires
51 Slash burning
52 Frost control
53 Structure fires
54 Coal refuse burning
Diesel oil
Residual oil
Gasoline
Solvent purchased
Gas marketed
Limited access rds
Rural roads
Suburban roads
Urban roads
Area-acres
Area-acres
Orchard heaters
No. year
Size of bank
Population
Population
NP
Population
Average VMT projection
VMT FWY projections
VMT FWY projections
VMT nonFWY projections
VMT nonFWY projections
NP
NP
NP
NP
NP
NP
NP
NP
NP
NP = No growth was projected for those categories.
TABLE 9. MOTOR VEHICLE EMISSION FACTOR
FOR PARTICIPATES
Year
g/mi
1974
1982
1990
0.33
0.29
0.25
12
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TABLE 10. AREA EMISSIONS OF PARTICULATE FOR 1982 (ton/yr)
County
No.
\
1
3
4
5
6
7
8
9
10
11
12
13
1 A
1*+
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Source
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Com/lnst. fuel
Com/lnat. fuel
Com/inst. fuel
Com/ ins t. fuel
Com/inst. fuel
Com/lnst. fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Incineration
Incineration
Incineration
Open burning
Open burning
Open burning
Gasoline fuel
Gasoline fuel
Gasoline fuel
Diesel fuel
Diesel fuel
Diesel fuel
Aircraft
Aircraft
Aircraft
Vessels
Vessels
Vessels
Vessels
[evaporation
Evaporation
Measured miles
Measured miles
Measured miles
Measured miles
Total
Category
Anthracite coal
Bituminous coal
Distillate oil
Residual oil
Natural gas
Wood
Anthracite coal
Bituminous coal
Distillate oil
Residual oil
Natural gas
Wood
Anthracite coal
Bituminous coal
Coke
Distillate oil
Residual oil
Natural gas
Wood
Process gas
Res identlal
Industrial
Com/inst .
Residential
Industrial
Com/inst.
LDV
HDV
Off highway
HDV
Off highway
Rail locomotive
Military
Civil
Commercial
Anthracite coal
Diesel oil
Residual oil
Gasoline
Solvent
Gas marketed
LTD access roads
Rural roads
Suburban roads
Urban roads
Burlington
61
0
68
0
36
4
0
0
23
77
10
0
0
0
0
0
0
0
0
0
8
1
0
0
4
0
0
15
0
13
31
445
23
71
0
10
0
0
0
0
256
0
0
845
2,165
Camden
93
0
126
0
62
1
0
0
53
166
19
0
0
lil Q
417
0
0
0
14
0
0
0
5
4
0
2
3
0
0
24
0
21
47
0
4
1
0
27
6
0
0
0
319
0
0
753
2,169
Gloucester
27
0
54
0
18
3
0
0
11
35
0
0
0
1 L~J
It /
0
0
0
0
0
0
0
87
0
0
1
187
0
0
9
0
8
18
0
31
0
0
46
0
0
0
0
209
0
0
476
1,367
Mercer
57
0
86
0
38
2
0
0
42
137
17
0
0
618
0
0
69
16
0
0
0
0
2
0
0
3
0
0
16
0
14
30
74
48
44
0
1
0
0
0
0
222
0
0
564
2,100
Salem
9
0
23
0
3
6
0
0
5
17
2
0
0
175
0
0
0
0
0
0
0
5
0
0
1
2
0
0
4
0
3
6
3
2
0
0
107
0
0
0
0
114
110
30
50
677
Total
247
0
357
0
157
16
0
0
134
432
48
0
0
1,523
0
0
69
30
0
0
0
105
7
0
4
199
0
0
68
0
59
132
522
108
116
0
191
6
0
0
0
1,120
110
30
2,688
8,478
Percent
2.9
0
4.2
0
1.8
0.2
0
0
1.6
5.1
0.6
0
0
18.0
0
0
0.8
0.3
0
0
0
1.2
0.1
0
0.05
2.3
0
0
0.8
0
0.7
1.6
6.2
1.3
1.4
0
2.3
0.1
0
0
0
13.2
1.3
0.3
31.7
13
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TABLE 11. AREA EMISSIONS OF PARTICULATE FOR 1990 (ton/yr)
Couuty
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
Source
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Residential fuel
Com./inst. fuel
Com/ ins t. fuel
Com/ ins t. fuel
Com/inst. fuel
Com/inst. fuel
Com/inst. fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Industrial fuel
Incineration
Incineration
Incineration
Open burning
Open burning
Open burning
Gasoline fuel
Gasoline fuel
Gasoline fuel
Diesel fuel
Diesel fuel
Diesel fuel
Aircraft
Aircraft
Aircraft
Vessels
Vessels
Vessels
Vessels
Evaporation
Evaporation
Measured miles
Measured miles
Measured miles
Measured miles
Total
Category
Anthracite coal
Bituminous coal
Distillate oil
Residual oil
Natural gas
Wood
Anthracite coal
Bituminous coal
Distillate oil
Residual oil
Natural gas
Wood
Anthracite coal
Bituminous coal
Coke
Distillate oil
Residual oil
Natural gas
Wood
Process gas
Residential
Industrial
Com/inst.
Residential
Industrial
Com/inst.
LDV
HDV
Off highway
HDV
Off highway
Rail locomotive
Military
Civil
Commerc ial
Anthracite coal
Diesel oil
Residential oil
Gasoline
Solvent
Gas marketed
LTD access roads
Rural roads
Suburban roads
Urban roads
Burlington
61
0
74
0
39
5
0
0
26
84
11
0
0
173
0
0
0
0
0
0
0
8
1
0
0
4
0
0
16
0
14
33
445
31
97
0
11
0
0
0
0
238
0
0
841
2.212
Camden
93
0
140
0
69
2
0
0
60
185
21
0
0
429
0
0
0
14
0
0
0
5
4
0
2
3
0
0
27
0
23
50
0
5
1
0
28
6
0
0
0
323
0
0
766
2,256
Gloucester
27
0
61
0
21
3
0
0
12
40
0
0
0
149
0
0
0
0
0
0
0
87
0
0
1
187
0
0
10
0
9
20
0
42
0
0
50
0
0
0
0
209
0
0
509
1,437
Mercer
57
0
93
0
41
2
0
0
46
149
18
0
0
646
0
0
72
16
0
0
0
0
2
0
0
3
0
0
18
0
16
32
74
66
60
0
1
0
0
0
0
230
0
0
560
2,202
Salem
9
0
25
0
3
7
0
0
7
23
3
0
0
226
0
0
0
0
0
0
0
5
0
0
1
2
0
0
4
0
4
7
3
2
0
0
117
0
0
0
0
130
127
34
56
795
Total
247
0
393
0
173
19
0
0
151
481
53
0
0
1,623
0
0
72
30
0
0
0
105
7
0
4
199
0
0
75
0
66
142
522
146
158
0
207
6
0
0
0
1,130
127
34
2,732
8,902
Percent
2.8
0
4.4
0
1.9
0.2
0
0
1.7
5.4
0.6
0
0
18.2
0
0
0.8
0.3
0
0
0
1.2
0.1
0
0.1
2.2
0
0
0.8
0
0.7
1.6
5.9
1.6
1.8
0
2.2
0.1
0
0
0
12.7
1.4
0.4
30.7
14
-------
SECTION 3
CALIBRATION OF AQDM FOR TSP
An analysis of the TSP monitoring data was performed, and attempts were
made to calibrate the AQDM model for TSP. The starting point for this task was
the TSP calibration in the Metropolitan Philadelphia study performed under EPA
Contract No. 68-02-1376, Task 24. Two additional monitoring sites were added
to the data base, a site in Cherry Hill, New Jersey (Site Code 310740003), and
the NASN site in Camden, New Jersey (Site Code 310720001). A regression anal-
ysis was performed for all TSP monitors in the Metropolitan Philadelphia region
which were not highly influenced by fugitive sources. Seven of the 50 monitors
were found to be highly influenced by fugitive sources and were eliminated from
the analysis. The results are plotted in Figure 1. Since the correlation co-
efficient was low (0.493), another regression analysis was performed for only
the New Jersey monitoring data. The results, Figure 2, were encouraging in
that the correlation coefficient increased (0.682) substantially over the case
where all monitors in the Metropolitan Region were utilized. An analysis of
the two outlying points was made, and it became apparent that one outlying mon-
itor, which was located in Mercer County, was being largely influenced by the
U.S. Steel Fairless Works. The Pennsylvania Department of Environmental Pro-
tection was contacted regarding the emissions we were utilizing, and they were
found to be high. In addition, due to the large particle size of the emissions,
considerable deposition occurs within the plant boundaries. As a result of this
information, the Mercer site was removed from the data base, and the model was
recalibrated using 16 monitors, rather than all 17 monitors, giving a correla-
tion coefficient of 0.844 (Figure 3). The air quality and site data for the
New Jersey monitors is listed in Table 12.
For all air quality modeling runs, the regression line plotted in Figure 3
was utilized.
One difficulty with the adopted regression line is the 16 yg/m3 under-
prediction of the NASN site in Camden. The model is unable to predict the high
concentrations at this monitor based on the emission rates in the inventory.
It appears that this site is being influenced by a localized emission source.
Until this source is identified, and the emissions quantified for input to the
model, the air quality of this monitor cannot be adequately predicted.
15
-------
150
R =0.493
Y =47.7 + 0.79x
0
30 60 90
CALCULATED ANNUAL AVERAGE ,
120
150
Figure 1. TSP calibration for 43 select New Jersey and Pennsylvania
monitors (1974).
16
-------
100
IO
E
-s.
O»
4.
ui
80
60
<
z
Q
UI
>
IT
UI
CO
03
O
40
20
R = 0.682
Y = 30.5 + 0.79x
• 2
20 40 60 80
CALCULATED ANNUAL AVERAGE,/xg/m3
100
Figure 2. TSP calibration for all 17 New Jersey monitors (1974)
17
-------
100
R =0.844
Y=23.0tl.l6x
20 40 60 80
CALCULATED ANNUAL AVERAGE,/ig/m3
100
Figure 3. TSP calibration for 16 select New Jersey monitors (1974)
18
-------
TABLE 12. COMPARISON OF PREDICTED AND OBSERVED ANNUAL ARITHMETIC AVI
Station
county
Burlington
Burlington
Burlington
Burlington
Camden
Camden
Camden
Gloucester
Camden
Gloucester
Gloucester
Mercer
Mercer
Mercer
Salem
Mercer
Gloucester
SAROAD
site code
310640002
310660003
310660004
310660005
310720001
310740003
310740003
310900001
311000001
311700001
311760001
312980001
312980002
312980003
314900001
315400001
316060001
Station
type
SUB-RES
SUB-RES
RUR-AGR
RUR-AGR
CC-IND.
RUR-NR.URB
SUB -RES
RUR-AGR
SUB-RES
SUB-RES
RUR-AGR
RUR-AGR
SUB-RES
SUB-COMM
RUR-AGR
CC-COMM
SUB-RES
UTM
Station
coordinates
Easting
(km)
526
514
530
514
489
505
496
491
494
489
475
512
533
524
469
519
487
.3
.7
.6
.1
.4
.3
.5
.6
.7
.4
.0
.4
.6
.9
.3
.5
.4
Northing "
(km)
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
,434
,416
,440
,434
,421
,404
,419
,391
,419
,395
,400
,462
,462
,448
,387
,452
,408
.7
.3
.5
.7
.4
.7
.3
.9
.0
.3
.8
.6
.4
.0
.0
.0
.9
Xbserved air
lality (yg/m3;
49.
41.
44.
48.
90.
53.
55.
39.
58.
45.
40.
46.
47.
48.
39.
68.
49.
-------
SECTION 4
CALCULATED AIR QUALITY
With the calibration of the model, and the projection of emissions to 1982
and 1990, the air quality for TSP can be calculated for future years. The
meteorology and model assumptions for the future years are the same as the as-
sumptions and meteorology utilized in Contract 68-02-1376, Task Order 24. The
STAR summary of windspeed, direction and stability for Philadelphia International
Airport in 1974 was used for model calibration, while long-term averages were
used for projection years. The model runs were separated into area contribution
and point contribution, and a source receptor file was written on tape for each
receptor used. In Figures 4 and 5 the regional TSP air quality contours are
shown for 1982 and 1990. The calculated air quality values at each receptor are
listed in Tables 13 and 14.
Since the air quality has been calculated as an arithmetic annual average,
and the primary annual standard for TSP is given as a geometric average, a method
is required to convert arithmetic to geometric average. With the use of Larsen2
statistics, the geometric average can be calculated as follows:
m
mg
exp (0.5 In2 s )
o
where m = geometric mean
O
m = arithmetic mean
s = geometric standard deviation
O
A typical s for this region is 1.70, giving the following relationship:
O
m = m/1.15
O
The highest calculated TSP concentration in the region was 82 yg/m3 (annual
arithmetic average); dividing by 1.15 yields 71.3 or the estimated geometric
mean. Since 71.3 yg/m3 is less than the primary annual standard, the region is
in attainment of this primary standard.
In order to examine in closer detail the air quality in the City of Camden,
the air quality was calculated for a 2 km grid. The resulting air quality is
presented in Figures 6 and 7 and tabulated by receptor in Tables 15 and 16. The
high concentration at the top of the figures is due to the dock-side grain load-
ing facility in Philadelphia which causes a very localized high TSP concentra-
tion which did not appear in the 5 km resolution grid used for Figures 4 and 5.
20
-------
4465,:,
4385
itm»reotv»r >T SUCKS
LEGEND
(UG/M3)
20. 0
40. 0
50. 0
60. 0
70. 0
80. 0
90. 0
450
KM (EflSTING)
530
Figure 4. Arithmetic average, TSP in yg/m3, 1982 air quality (no strategy)
21
-------
4 4 E 5 r.._, 1
HOMTSOtt,
e*r
HICKS
~»«Wr»
\
K
\ '
1 A x
T \ *
- "V
£ \^
±i r * X
n r'
, ^
t ,<
=c <
i, $^/f
^
zjr"*
id 4- ^^^\
V <^ "-V3
N \ "
X\^ >
V
"-, / * /I
'U
V - *'•>
^
s.
v
>„
/ \
/ /^
r1^ V^
^
2r*
/^
> V
.
H*r»
"*4i>
,'"6
>^
LEGEND
(UG/M3)
0= 20.0
A= 40.0
+ = 50.0
x= 60.0
= 70.0
^= 80.0
X =
Si LEU
450
GLOUCfSTER
KM (EflSTING)
530
Figure 5. Arithmetic average, TSP in yg/m3, 1990 air quality (no strategy)
22
-------
HO.
t»ST
NORTH UG/««*3
u>
1
4
J
10
13
16
19
2?
25
28
31
34
37
40
43
46
49
52
55
58
61
64
67
70
73
76
79
«2
85
88
9J
94
97
190
103
106
109
112
115
418
121
124
127
130
113
11*
139
142
145
148
455.0
455.0
455.0
455.0
455.0
460.0
460.0
46U.O
460.0
460.0
465.0
465.0
465,0
465.0
465.0
470.0
470.0
470.0
470^0-
470.0
475.0
475, «
475.0
475.0
475,0-
480.0
480.0
460,0
480.0
480.0
48-5,0-
485.0
485.0
485.0
485.0
490.0
490,-0
490.0
490.0
4M-.-&-
495.0
495.0
495,0
495.0
495.0
500.0
500.0
500.0
500,0
500.0
4}96j«
1405.0
4U20.0
44 3%. »
4450.0
4390.0
4405.0
uu?0.0
JU35.0
4«bO.O
4390.0
4405.0
442«.«
4415.0
4450.0
4390 ^0-
4405.0
4420,0
UH35 Q
4450.0
4390.0
440S.-0- -
4420.0
4435.0
4450, O
4390.0
4405.0
4420,O-
4435.0
4450.0
4-MOrO- —
4405.0
4420.0
4435,0
4450.0
4190.0
44O5-^0
4420.0
4415.0
4450.^-
4390.0
4405.0
4420.0
4435.0
4450.0
4394,0
44Q5.0
4420.0
4435,0
J450.0
35.
40.
ia.
42.
18.
34.
41.
39.
39,
37.
35.
43.
4V.
41.
38.
3*.
42.
45.
-Ub-r-
39.
15.
•4-U-
52.
52.
«?,-
35.
43.
-65,
53.
43.
5*,
46.
75.
56,
44,
36.
*S,
68.
58.
-«*T-
16.
44,
60.
60.
45.
36,
43.
54.
60.
"8.
TABLE 13
NO.
2
5
8
11
14
17
20
23
26
29
i2
35
18
41
44
47
50
53
54
59
62
65
68
71
74
77
80
81
86
69
92
95
98
101
10U
107
1 10
111
116
119
122
125
128
131
134
Ii7
140
143
146
149
. TSP
fc*ST
455.0
455.0
055.0
455.0
455.0
460.0
460.0
460.0
460.0
460.0
465.0
465.0
465.0
465.0
465.0
470.0
470.0
470.0
470,0
470,0
475.0
475.0
475,0
475.0
475,0
480.0
480,0
U80.0
460.0
480,0
485.0
485.0
485.0
485.0
485.0
490.0
490.0
490,0
490.0
490,0
495,0
495.0
495.0
495. 0
495.0
500.0
500.0
500.0
500.0
500.0
AIR QUALITY 1
NORTH
4395.0
4410.0
U425.0
4U40.0
4U55.0
4395.0
4410.0
4425.0
U4UO.O
"455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4J95.0
4410.0
4425,0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455,0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4U40.0
4455.0
UG/»**3
39.
37.
38.
37.
35.
45,
40.
39.
10.
35.
43.
45.
41.
41.
36.
37.
46.
45.
47,
38.
37.
46.
51.
50.
41,
J7.
49.
59.
54.
41.
38.
53.
69.
51.
42.
39.
51.
79.
54.
43.
18.
49.
68,
54.
49.
37.
47.
57.
55.
80.
N(
(continued)
-------
TABLE 13 (continued).
NO.
EAST
NORTH UG/M**3
NO.
tAST
NORTH uG/M**3
to
151
15U
157
160
163
16b
169
172
17b
17S
161
184
187
190
19}
190
199
202
205
206
211
214
217
220
221
226
5*5 rO
505.0
505.0
5*5,0
505.0
sio.c
510.0
•510.0
510,0
510, 6
515.0
515.0
515.0
515.0
515.0
520.0
520.0
520.0
530 ^0
520.0
525.0
52J»-r*
525.0
525,0
S2S,0
489,4
OJlJft.O
U405.0
4420.0
UAJ5.0
ua50.0
«390.0
ii«0b, o
y u 2 il . 0
UU35.0
«-«50,0
aj90.0
iao5.o
1W20.0
««35.0
(HJ50.0
0390.0
uaos.o
4120.0
-1445-^5-
4450.0
4390,0
4-4&5,-0~
4420.0
4415.0
UflSO^O
4421.4
J5,
43.
49.
So.
47.
35,
40,
"b.
53.
-4«.
35.
39.
44.
51.
51.
i«^
i8.
44.
-sa^
68.
34.
37,
42.
48.
5».
69.
152
155
158
161
164
167
170
173
176
179
182
185
US
191
194
197
200
203
206
209
212
215
218
221
224
505.0
505.0
505.0
505.0
505.0
510.0
510.0
510,0
510.0
510.0
515.0
515.0
515.0
515,0
515.0
520.0
520.0
520.0
S20.0
520.0
525.0
525.0
525.0
525.0
525.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410,0
4425.0
4440,0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410,0
4425.0
4440.0
4455.0
37.
46.
51.
54.
49.
37.
4
-------
TABLE 14. TSP AIR QUALITY 1990
to
0.
1
4
7
10
13
16
19
2?
25
£M
31
34
37
40
43
46
49
52
55
58
61
64
67
70
74
76
79
&i
85
88
91
94
0!
100
103
106
149
112
115
148
121
124
127
130
133
136
139
142
145
1 u8
EAST
455.0
455.0
455.0
455.0
455.0
460.0
460.0
4eO .0
460.0
460.0
465.0
465.0
465.0
465.0
465.0
470.0
470.0
470.0
470.0
470.0
475.0
475.-0-
475.0
475.0
47^.0
480.0
430.0
484.4
480.0
480.0
485.0
485.0
485.0
485,0
485,0
490,0
490.0
490.0
490,0
490.4
495.0
495,0
495.0
495.0
495.0
500,0
500.0
500.0
500.0
500.0
SOUTH
439O.O
4405.0
4420.0
4435rO
4450.0
4390.0
4405.0
au ' ' 0
443 _ ^ •>
4450.0
4390.0
4405.0
4426-. 0
4435.0
4450.0
4i90,»
4405.0
4420.0
4435,-Q —
4450,0
4390,0
4404^-0—
4420.0
4435.0
4450 rO -
4390,0
4405.0
442Q..4-
4435.0
4450.0
4394.0- --
4405.0
4420.0
4435.4
4450,0
4390,0
4405,0- -
4420,0
4435.0
4454.4
4390.0
4405.0
4424.0
4435.0
4450.0
4394.4
4405,0
4420.0
443-5,0
4450,0
UG/M*«3
36.
•12.
38.
42.
38.
36.
46.
40.
59.
5'.
57.
45.
uf.
42.
58.
36,
43,
46.
46,--
40.
36.
-**.-
53.
52.
-4J-T-
36.
44.
66.
54.
44,
47,
47.
77,
57.
45.
37.
^*.
70.
59.
4fr»
37.
45.
.64-,
61 .
46.
36.
44.
55.
W.
49.
NO.
tAST
NORTH i)G/«»«3
2
5
8
1 1
14
17
20
23
26
29
32
35
38
41
44
47
50
53
56
59
62
65
68
71
7«
77
80
83
86
89
92
95
98
101
104
107
110
113
116
H9
122
125
128
131
134
137
140
143
146
149
455.0
455,0
455.0
455.0
455.0
460.0
460.0
460.0
460.0
460.0
465.0
U65.0
465,0
465.0
465,0
470.0
470.0
470.0
470,0
470.0
475.0
475.0
475.0
475.0
«75.0
480.0
480.0
480.0
480,0
480.0
485.0
485.0
485.0
485.0
485.0
490.0
490.0
490.0
490.0
490.0
495.0
495.0
495.0
495.0
495.0
500,0
500.0
500.0
500.0
500.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425,0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4595.0
4410,0
4425,0
4440.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4400.0
4455.0
4395.0
4410.0
4425.0
41)40.0
4455.0
4395.0
4410.0
4425.0
4440.0
4455,0
4395.0
4410.0
4425.0
4440.0
4455.0
4395.0
4410.0
4425.0
4440,0
4455.0
41.
39.
38.
37.
35.
50.
41.
39.
40.
36.
«7.
46.
41.
4?.
37.
39.
47.
«5.
48.
38.
38.
47.
51.
51.
41.
39.
51.
59,
55.
41.
39.
54.
70.
54.
43.
40.
52.
81.
55.
44,
39.
50.
69,
55.
49.
58.
48.
58.
56.
80.
NO.
b
9
\i
\c>
IB
21
24
^^
30
33
4b
39
42
45
48
51
54
57
60
63
66
69
72
7S
78
61
84
87
90
9J
96
99
102
105
108
111
114
117
120
123
126
129
1J2
1J5
138
141
144
147
150
(continued)
-------
TABLE 14 (continued)
u.
151
154
157
166
165
1 66
169.
172
175
178
181
184
1 87
190
193
196
199
202
205
208
211
214
217
220
223
226
tAST
505.0
505.0
505.0
595.6
505.0
510.0
510.0
510.0
510.0
510.9
515.0
515.0
-5 l^i 0
515.0
515.0
520,0
520.0
520,0
-sao.-o-
520.0
525.0
-525-^0
525,0
525.0
SiS^a--
489.4
MIRTH
4396-iO-
4 a o 5 . o
4420. 0
4435.6
4450. 0
4390.0
4405.0
4420 . 0
4435.0
4450, 0
4390. 0
4405, 0
4 4 2^i 0
4435. 0
4450. 0
4390.0
4405.0
4420.0
iMlJ^-O
4450.0
4390.0
UU-05,-0
4420.0
a«J5.0
«U154»«-
4421,4
UG/"*»3
36.
144 .
50.
5^.
48.
ife.
41 .
a7.
54.
49.
35.
40,
II C
45 .
52.
52,
15.
39.
44 .
^^
68.
34.
}&.
«2.
«8.
WJ,
71 ,
MO.
EAST
NORTH OG/"**3
152
155
158
lei
164
167
1 70
1 73
1 7b
179
182
185
188
191
1 94
197
200
203
206
209
212
215
218
221
220
505.0
505.0
505.0
505. 0
505.0
510.0
510.0
510.0
510.0
510.0
515.0
515.0
515.0
515.0
515.0
520,0
520.0
520.0
520.0
520,0
525.0
525.0
525.0
52S.O
S2S.O
4395,0
4410.0
4425.0
4440.0
4«55.0
4395,0
4410.0
4425.0
4440,0
4455.0
4395,0
4410,0
4425.0
4440.0
4455.0
4395.0
4410,0
4425.0
4J440.0
4455.0
4395.0
U410.0
4425,0
4440.0
44155.0
38.
47.
52.
55.
49.
37.
45,
149,
55.
47.
37.
42.
47.
58.
49,
36.
"1 ,
47.
59,
53.
35.
39,
««.
58.
«•».
NO.
153
156
159
162
165
168
171
174
177
180
183
186
189
192
195
198
201
204
207
210
213
2lb
219
222
225
-------
.428
oc
€3
Z
4412 1 _
486
HHIIIIMMH. RVF.RflGE 11)I' IN M
1982 RIR QURLITY NO STRRTEGY
-H-
KM (EflSTING)
Figure 6. Camden TSP air quality for 1982.
27
-------
4428 ,
flRITHMETIC RVERRGE TSP IN UG/M**3
1990 RIR QURLITY NO STRRTEGY
ir
•r.
t—
cc
-J
4412
486
KM (EflSTING)
Figure 7. Camden TSP air quality for 1990.
28
-------
TABLE 15. TSP AIR QUALITY IN CAMDEN 1982
MO.
LAST
NUSTH UG/M«*3
1
a
7
10
1}
16
11
22
25
28
31
34
488.0
160.0
188.0
4*0.0
190.0
492.0
192.0
494.0
194.0
191.0
49t>.0
496.0
illl. 0
1120.0
112&.0
441R.O
1121.0
4410,0
4422.0
4414.0
1120.0
442o.O
1418.0
1121.0
60.
71.
72.
t>6.
73.
60.
67.
Si.
61.
81.
56.
62.
EAST
MONTH Uli/M**3
NO
2
5
8
11
11
17
20
23
26
29
32
35
188.0
168.0
190.0
190.0
190.0
192.0
192.0
194.0
194.0
496.0
496.0
496.0
4416.0
4422.0
1114.0
4 '4 ? 0 . 0
H26.0
1418.0
1424.0
4116.0
1122. a
4414.0
4420.0
4426.0
67.
71.
50.
69.
75.
63.
72.
56.
63.
52.
58.
66.
N>
VD
TABLE 16. TSP AIR QUALITY IN CAMDEN 1990
Nil.
LAST
NUKTH
NO.
EAST
1
a
7
10
13
16
19
22
25
28
31
34
4Ht*.0
486.0
468.0
490.0
190. n
492.0
192.0
u
-------
The high concentrations do not exceed the primary annual standard anywhere in
the New Jersey portion of the Metropolitan Philadelphia AQCR.
An analysis was performed to ascertain whether or not the secondary 2-hour
standard of 260 yg/m3 was being attained (attainment is defined as not exceed-
ing this value more than once per year). Through Larsen statistical analysis,
the annual average which should not be exeeded if the 24-hour standard is not
to be exceeded, can be calculated. The generally accepted geometric annual
value is 60 yg/m3 which is determined assuming a geometric standard deviation
of about 1.75. This corresponds to an arithmetic annual average value of
69 yg/m3. Based on the annual arithmetic value of 69 yg/m3, a section of the
City of Camden would be in nonattainment of the secondary standard. To determine
whether the 69 yg/m3 was applicable for the Camden area, an analysis was per-
formed to graphically calculate the average geometric standard deviation (see
Figures 8 through 11), and to compare these calculated values with the values
calculated directly from the air quality measurements. Table 17 lists the re-
sulting values.
TABLE 17. GEOMETRIC STANDARD DEVIATIONS FOR THE CAMDEN AREA
. r. . Calculated Graphical
Site code Site identification
s s
g g
310740003 Cherry Hill 1.58 1.92
Sub-Res
310730003 Berlin Township 1.62 1.71
Rur-Nr.Urb
311000001
Sub -Res
310720001
CC-Ind
South Park Drive
NASN (Fire Station)
Average
1.78
1.58
1.64
1.88
1.72
1.81
If the geometric standard deviation of 1.64 is utilized to calculate the
annual arithmetic value which should not be exceeded to attain the 24-hour
standard, the annual arithmetic value would be about 80 yg/m3. However, if
the geometric standard deviation of 1.81 is utilized to calculate the annual
arithmetic value not to be exceeded, the value is 65 yg/m3. The graphical
technique utilized to determine the geometric standard deviation is more
sensitive to the high end of the distribution, and considers the fact that
the maximum value is more a function of the tail of the distribution rather
than the complete distribution. Since any year has a maximum of 60 values in
the frequency distribution, it may be advantageous to add the distributions
from a number of years to obtain a more statistically significant geometric
standard deviation. The importance of obtaining an accurate geometric standard
deviation can be seen in that if 1.64 is the correct value, Camden is in attain-
ment of the secondary standard; however, if 1.81 is the correct geometric stan-
dard deviation only a portion of the City is in attainment of the secondary
standard. O
-------
1000
9OO -
800
700
600
500
400
300
200
99.99
98.9 99,8
99 98
95
90
80 70 SO 5O 40 30 20
10
to
E
100
90
80
70
60
50
40
30
20
10
J I
T
I
C.Ol 0.050.1 0.2 0.3
3 10 20 30 40 50 60 70 80 90
CUMULATIVE FREQUENCY DISTRIBUTION
95
98
Figure 8. Frequency distribution for Cherry Hill s:
-------
u>
1000
900
800
700
600
500
400
300
200
in
E
•^ 100
J 90
80
70
60
50
40
30
20
99.99
10
98.9 99,8
f 1
99 98
i
_i
i
l
95
~T
90
—r~
80
70 60 50 40 30
r~
20
10
~l T
O-Ol 0.050.1 0.2 0.3
3 1C 20 30 40 50 60 70 80 90
CUMULATIVE FREQUENCY DISTRIBUTION
95
91
Figure 9. Frequency distribution for Berlin Township
-------
99.99
99,8
99 98
95
90
80
TO 60 5O 40 30 20
10
900
eoo
7OO
6OO
500
400
300
200 -
I
I
I
I
I
E
^
9
=t
100
90
80
70
60
50
40
30
20
10
I
_L
J L
o.oi 0.050.1 0.2 as
3 10 20 30 40 50 60 70 80 90 95
CUMULATIVE FREQUENCY DISTRIBUTION
98
Figure 10. Frequency distribution for South Park Driv
-------
OJ
-P-
1000
900
800
700
600
500
400
300
200
99.99
98.9 99.8
99 98
100
90
80
70
60
50
40
30
20
10
i i i
95
~r
90
80
70
—r
60 50 40 30
~l 1 1 T~
20
—T~
10
O.Ol 0.0501 0,2 0.3
J L
3 10 20 30 40 50 60 70 80 90 95
CUMULATIVE FREQUENCY DISTRIBUTION
98
Figure 11. Frequency distribution for NASN sit
-------
SECTION 5
AIR QUALITY ANALYSIS AND RECOMMENDATIONS
AIR QUALITY DATA AT THE NASN SITE IN CAMDEN
The air quality, as measured at the NASN site, is above the standard.
Under this program, a short analysis was performed to determine the reason
for the high air quality values. Modeling has underpredicted this monitor
by about 16 yg/m3, thus indicating that the source of the high TSP concentra-
tions is not in the inventory, and it may be a localized fugitive source.
In order to determine the principal source types impacting the monitor,
a study of the trace element analysis was performed for the filters analyzed
by EPA. To conduct a reliable elemental balance determination of the sources
contributing to TSP levels at a monitor, some eight tracer elements are required.
These include: Sodium (marine tracer), Vanadium (oil combustion tracer), Lead
(auto tracer), Zinc (incineration tracer), and Aluminum, Iron, Manganese, and
Arsenic (soil and coal tracers). Both soil and coal are high in Iron and
Aluminum, so Manganese (depleted in coal particulates) and Arsenic (depleted
in windblown soil) are needed in order to separate these two similar
particulates.
In the case of the NASN data, only four of these eight tracer elements
have been analyzed. As a result, a meaningful total elemental balance is not
possible with the NASN data. Certain source contributions can be roughly de-
termined, however. For instance, the 1973-1974 annual average lead content
(approximately 1.5 percent) of the sample at the City of Camden NASN station
indicates that about 10 percent of the particulate load is due to automobile
emissions. The Vanadium content (approximately 0.1 percent) indicates that
oil combustion contributes only 1 to 2 percent of the ambient TSP load at this
station. The other four TSP components (i.e., soil, marine, incineration, and
coal) are not as confidently determined.
If the coal combustion is assumed to be zero, then the Iron content at the
site (1.9 percent) indicates that soil makes up one-half of all particulates
at the site. Applying this percentage contribution to the soil Manganese con-
tent (0.09 percent), however, underpredicts the ambient concentration found.
Also, without considering the Aluminum content, the Iron content cannot be
accurately used as a soil-tracer, due to possible interferences by other Iron
sources such as auto body rust particulates, or industrial process emissions.
Thus, it is not possible to confidently state the soil contribution without a
complete elemental balance of all eight tracers.
35
-------
It is interesting to note, however, that the Iron content at the Glassboro
site in Gloucester County is much lower than that at the Camden site (25 percent
versus 50 percent). Thus, if windblown urban particulates are the cause of the
higher Iron content, this would explain why the AQDM model is better able to
predict concentrations at the Glassboro site. If the above considerations are
to be resolved, it seems clear that a- more complete elemental balance analysis
of TSP samples at the Camden site is required (including all eight tracer ele-
ments) . Moreover, at least one other (complying) site should be similarly
analyzed for comparative purposes.
ATTAINMENT OF THE PRIMARY ANNUAL TSP STANDARD
Attainment of the Primary Annual Standard in the region has been achieved,
and it will be maintained through 1990. The high TSP air quality near Trenton
is primarily due to the U.S. Steel Fairless Works. However, the actual impact
of this source is considerably less than the calculated concentrations indi-
cated because the emissions are predominantly large particles which, for the
most part, settle onto the company's property. This conclusion was derived
from discussions with the local field office of the Pennsylvania Department
of Environmental Resources, and from the fact that the monitoring site in Tren-
ton has considerably less observed TSP concentration than the model predicts.
ATTAINMENT OF THE SECONDARY TSP STANDARD
Based on the discussions in Section 4, the determination of the attainment
of the secondary 24-hour standard is questionable. The main difficulty lies
in the determination of the appropriate geometric standard deviation. Examin-
ing the limited data available at the Camden NASN and Cherry Hill sites gave
low (1.58) geometric standard deviations. However, the data represented only
about one-third of the year. The Berlin Township and South Park Drive sites
had higher geometric standard deviations, but the peak observed concentrations
were 152 yg/m3 and 192 yg/m3, both above the secondary standard.
From the available data it appears that there may be a problem in attain-
ing the secondary standard; however, it is not clear whether or not there is a
problem. Further analysis of a more complete data base for all Camden monitors
will be required to better define whether or not a problem exists.
Strategies were not presented to reduce emissions and make sure the sec-
ondary standard was achieved. The primary reason for not recommending any
strategy is the large percentage of the air quality concentrations which are
due to background and area sources. Figures 12 and 13 display the relative
contributions of various regions to the recorded air quality. It becomes
apparent that New Jersey's contribution is small; thus, controls by New Jersey
alone would not radically improve the air quality. Appendix A contains the
source contribution files for selected receptors in the region.
RECOMMENDATIONS FOR FURTHER STUDY
Two suggestions can be made concerning the air quality in the Camden area.
The first is a detailed study around the NASN site to determine the reason for
36
-------
NON NEW JERSEY <-
\ 49%
COORDINATES 490,4420
COORDINATES 490,4422
COORDINATES 492,4422
Point Sources, 19%
Area Sources, 30%
Point Sources, 3%
•Area Sources, 15%
Point Sources,20%
Area Sources, 31%
Point Sources, 5%
•Area Sources, 15%
NON NEW JERSEY
50%
Point Sources, 21 %
Area Sources, 29%
Point Sources, 3%
Point Sources, 13%
Figure 12. Distribution of the location of sources impacting
selected receptors in Camden City in 1974.
37
-------
POINT SOURCES
21%
AREA SOURCES
28%
POINT SOURCES
3%
AREA SOURCES
14%
'OINT SOURCES
23%
AREA SOURCES
30%
POINT SOURCES
4%
AREA SOURCES
10%
COORDINATES, 490, 4420
COORDINATES, 490, 4422
POINT SOURCES
22%
AREA SOURCES
29%
POINT SOURCES
3%
AREA SOURCES
12%
COORDINATES, 492, 4422
Figure 13. Distribution of the location of sources impacting
selected receptors in Camden City in 1982.
38
-------
the high concentrations observed at the site. The second recommendation is to
look at a complete data base for the monitoring site in Camden to make a better
determination of the geometric standard deviation, and to examine the concentra-
tion data to determine if values above the secondary standard are being observed.
Our recommendations for resolving the reason for the high TSP concentra-
tions at the Camden NASN site are as follows:
1. Examine historical data to assess the trends in air
quality.
2. Perform a complete elemental analysis to determine the
principal source categories which are contributing to
the high TSP concentrations.
3. Perform a detailed mini-inventory around the site.
4. Perform some modeling to see if the new inventory accounts
for the observed concentrations.
5. Perform the above analysis for a nearby compliance site to
help assess the differences between the sites which may
account for the high concentrations.
6. Set up a special monitoring program to identify the emis-
sion sources and emission rates.
Some of these recommendations can be easily implemented with a minimal ex-
penditure of manpower and funds, while others are very extensive and expensive.
We recommend that the above steps be followed in the order presented so that
no more effort than required would be expended to resolve the problem.
39
-------
REFERENCES
1. Emission Inventory and Sulfur Dioxide Alternatives for the Metropolitan
Philadelphia Region. U.S. Environmental Protection Agency, Region III,
Air Programs Branch, Philadelphia, Pennsylvania. EPA 903/9-77-030.
August 1977
2. Larsen, Ralph I. A Mathematical Model for Relating Air Quality Measure-
ments to Air Quality Standards. U.S. Environmental Protection Agency,
Office of Air Programs, Research Triangle Park, North Carolina. AP-89.
November 1971.
40
-------
APPENDIX A
SOURCE CONTRIBUTION FILES FOR
SELECTED RECEPTORS
County name
New Castle
Burlington
Camden
Gloucester
Mercer
Salem
Bucks
Chester
Delaware
Montgomery
Philadelphia
County code
0180
0660
0740
1760
2980
4900
1200
1660
2360
6000
7160
41
-------
1974 DATA
COORDINATES FOR T»IS SOURCE RECEPTO" ftLE »RE 520.0 4450.0
POINT SOURCE CONTRIBUTION IS 23.68
COUNTY COUNTY CONTRIBUTION
COOE
COUNTY
coot
2960
1200
1200
1200
1200
7160
POINT
COOE
0007
0025
0029
0006
0006
2060
CONTRIBUTION COUNTY
UG/»««3 COOE
0.26 1200
0.53 1200
0.05 1200
0.26 1200
1.65 1200
0.25
POINT
COOE
0020
0029
0036
0046
0046
0160
0660
2960
OOOC
1200
lt>60
2360
6000
7160
CONTRIBUTION
UG/>"«3
0.37
0.10
0.28
0.10
0.27
0.22
0.51
0.17
O.I 1
0.62
O.H
19.56
0.26
0.20
0.00
1.63
COUNTY
COOE
1 200
1200
1200
1200
1200
ARE* SOURCE CONTRIBUTION
COUNT T
CUOE
2980
2960
2980
»RE«
COOE
0102
0200
0214
CONTRIBUTION COUNTY
UG/»*«J COOE
0.36 2980
0.62 2960
0.12 2960
CODE
0100
021 1
0302
COUNTY COUNTY
COOE
0180
160
660
700
1760
2960
0900
1200
(660
2)60
6000
7160
CONTRIBUTION
UG/M«*3
0.14
4.66
0.19
POINT CONTRIBUTION
COOE UG/M««3
0025 3.39
0029 0.45
0006 6.35
0046 3.22
0053 0.26
IS 19.36
COUNTY
COOE
1200
1200
1200
1200
7160
POINT CONTRIBUTION
COOE UG/«««3
0025 0.41
0029 0.14
0006 0.25
0046 0.02
1567 0.12
CONTRIBUTION
UG/M**3
0.0
0.42
0.93
0.69
0.31
6.15
0.10
2.85
0.32
0.07
2.01
3.09
COUNTY
COOE
2960
2960
2980
*RE« CONTRIBUTION
CODE UG/«**3
01 13 0.10
0212 0.17
0303 0.15
COUNTY
CODE
2960
?9(0
2960
«RE« CONTRIBUTION
CODE UG/"*»3
0203 O.U
0213 0.53
0311 0.12
42
-------
1974 DATA
CUO»01K»res K> T»IS SOURCE BtCtPTOrf 'ILE »RE uoO.O
POINT SOURCE CONTRIBUTION IS 4.51
COUNTY COUNTY CONTRIBUTION
COUNTY
CODE
0180
• 900
1200
CODE
0130
0660
0740
1760
2980
4900
1200
1660
2360
6000
7160
POINT CONTRIBUTION COUNTY POINT CONTRIBUTION
CODE UG/M««! CODE CODE UG/1-"!
0008 0.15 0180 0010 0.28
0001 0.13 4900 0002 0.25
0046 0.11
UG/"** 3
1 . $2
0.04
0.08
O.Od
0.02
5.91
0.15
0.15
0.28
0.2U
0.35
COUNTY POINT
CODE CODE
0180 0016
U900 0010
CONTRIBUTION COUNTY POINT CONTRIBUTION
UG/"*«3 CODE CODE UC/M««3
0.14 4900 0001 0.17
1.29 4*00 0011 3.55
• REi SOURCE CONTSIBUHON IS 7.71
COUNTY COUNTY CONTRIBUTION
COUNTY
CODE
180
180
1*0
4900
CODE
0180
iao
660
740
IT60
2980
• 900
1200
1660
2160
6000
7160
»RE« CONTRIBUTION COUNTY «RE« CONTRIBUTION
CODE UG/»«'l CODE CODE UG/M««!
0610 0,23 I80 06UO 0.16
Oral 0.25 180 074U 0.16
0)61 O.S7 l»0 0961 0.14
07H 0.19 7160 0101 0.11
UG/****1
0.0
1.57
0.10
0.24
0.11
0.04
1.09
0.12
0.4Z
0.53
0.59
D. 52
COUNTY 4REA CONTRIBUTION COUNTY
CODE CODE UG/"«»! CODE
ISO 0720 0.12 180
180 0842 0.11 180
4900 0600 0.19 (900
"Kit CONTRIBUTION
CUOE UG/H««3
0742 0.20
0851 0.19
0702 «,17
43
-------
1974 DATA
POINT SOURCE CONTRIBUTION IS 9.51
COUNTY COUNTY CONTRIBUTION
COOE UG/»«"3
COUNTY
COOE
0180
1)900
1200
0180
0660
0790
1760
2960
• 900
1200
1660
2160
6000
7160
POINT CONTRIBUTION COUNTY POINT CONTRIBUTION
CODE UG/«**3 COOE COOE UG/M*»3
OOOB 0.15 01 80 0010 0.28
0001 0.33 1900 0002 0.25
0046 0.11
1 . P2
0.00
0. 08
0.08
0.02
5.91
0.55
0.55
0.28
0.20
O.J5
COUNTY POINT CONTRIBUTION COUNTY POINT
COOE COOE U6/M«*5 COOE CODE
0180 0016 0.10 0900 0001
0900 0010 1.29 0900 0011
CONTRIBUTION
UG/M*«5
0.17
5.55
•BE* SOURCE CONTRIBUTION IS 7.75
COUNTY
CODE
01 BO
1BO
660
700
1760
2980
• 900
1200
1*60
2360
6000
71bO
COUNTY CONTRIBUTION
o.o
3.57
0.10
0.20
0.13
0.00
1 .09
0.12
o!s3
0.59
n.52
COUNTY
cooe
180
190
190
9900
ARE* CONTRIBUTION COUNTY
CODE UG/»«*3 COOE
0630
0703
0863
0711
0.25
0.25
0.57
0.19
160
160
180
7160
»BE» CONTRIBUTION COuNTr
COOE UG/M«'3 COOE
06QO
0961
0103
0. 16
0.16
o.ia
0.11
180
1BO
0900
«RE« CONTRIBUTION COUNTY
COOE UG/««*3 CODE
0720
0902
0600
0.12
0.1]
0.19
leo
190
0900
«RE» CONTRIBUTION
CODE UG/»««3
07"2
0851
0702
0.20
0.19
0.17
44
-------
1974 DATA
CCOMOISiTCS 'OK I«IS SOURCE "fCfC" MLE «'E U90.0 0022.u
POINT SOURCE CONTRIBUTION IS |5.»)
COUNTY
coot
0700
1200
7160
MM
Tl»0
MINT
CODE
0006
00116
I5B7
206*
9T02
CONTRIBUTION
ue/«««j
0.17
0.13
0.31
2.01
0.11
COUNTY
CODE
07110
1200
7160
7160
POINT
CODE
0037
0006
15"'
9500
COUNTY COUNTY
CODE
oieo
0660
0790
1760
2980
0900
1200
1660
2360
6000
7160
CONTRIBUTION
U6/»"«)
0.60
0.23
0.12
1.02
CCNTOI6UTION
UG/W**)
0.°3
0.25
1.93
0.3S
0.06
0.31
1.35
0.00
0.06
0.59
9.70
COUNTY
CODE
0700
7160
7160
7160
»RE» 30UOCE CONTRIBUTION
COUNT <
CODE
140
700
no
740
• 000
7160
7160
7160
7160
7160
7160
7160
7160
»RE4
CODE
0»6)
0611
070?
07la
0100
0212
0723
OSI3
0320
OHIO
0020
011)11
0512
CONTRIBUTION
UG/««« J
O.la
0.2)
0.69
0.2*
0.10
0.12
1.0"
0.16
0.07
0.11
0.33
O.I*
0.3)
COUNT*
CODE
7110
700
700
1760
6000
7160
7160
7160
7160
7160
7160
7160
7l(,n
4RE1
crot
OSO)
0612
0711
0720
0210
0213
0300
0310
0002
0021
0031
0501
OM3
COUNTY COUNTY
CODE
01 BO
ISO
660
710
1760
2980
0900
1MO
1660
2)60
6000
7160
CONTRIBUTION
UG/M**i
0.12
0.11
O.B6
0.12
0.11
0.23
0.29
0.01
0.13
O.B2
0.60
0.12
0.1*
POINT
CODE
003B
1S1I
2005
950«
13 27
CONTRIBUTION
UG/«*«)
0.76
0.11
0.11
1.02
.31
COUNTY
CODE
0900
7160
7160
7160
MINT
CODE
0011
1573
2060
»S05
CONTRIBUTION
Ut/«««5
0.10
0.11
0.11
0.11
CONTf I8UIION
UG/*«")
0.0
O.B6
0.67
0.63
1.02
0.16
0.20
0.<2
o.SH
1.63
2.35
10. BO
COUNTY
CODE
700
700
700
1760
6000
7160
7160
7160
7160
7160
7160
7160
7160
• RE»
CODE
0602
0613
0712
0813
0053
0210
0311
0321
0011
0022
0032
0502
1521
CONTRIBUTION
UG/H**3
0.11
0.30
0.26
0.11
0.11
0.36
0.09
0.90
0.12
1.03
0.15
0.11
1.19
COUNTY
CODE
700
700
700
2360
7160
7160
7160
7160
7160
7160
7160
7160
7160
1REI
CODE
0600
0610
071)
0431
0103
0221
0312
012)
0012
0023
00))
0511
052?
CONTRIBUTION
UG/"**3
0.11
0.11
O.SI
0.10
l.*2
0.11
0.52
O.BO
0.37
0.01
0.2B
0,20
O.lf
45
-------
1974 DATA
CCOR01S1TES FC= T»I5 SOURCE RECEPTOR FILE IRE 400.0 0420.0
POINT SOURCE CONTRIBUTION IS 13.61
COUNTY COUNTY COtTRIBUTION
COUNTY
CODE
07UO
4900
7160
7160
71(0
POINT
CODE
0037
0011
1561
2060
9507
CONTRIBUTION
UG/««.)
0.10
0.10
0.12
0.10
0.11
COUNTY
CODE
0700
1200
7160
7160
7160
POINT
CODE
0036
0006
1587
2060
9507
CODE
0180
0660
0740
1760
0900
1200
1660
2360
6000
7160
CONTRIBUTION
UC/»««3
0.10
0.38
0.30
1.81
0.11
UG/«««)
0.02
0.21
0.67
0.00
0.06
0.32
, 1.20
0.36
0.02
0.54
8.75
COUNTY
CODE
0700
1200
7160
7160
7160
IRE> SOURCE CONTRIBUTION
COUNTY
CODE
180
740
700
740
2360
7160
7160
7160
7160
7160
7160
7 ' ..
1RE1
CODE
0663
0611
0702
0714
0031
0210
0)11
0)21
0012
0123
10 JO
-.t i t
CONfRIBuTITS
UG/«««3
O.lll
0.20
0.70
0.19
0.12
0.4)
0.61
0.90
0.25
0.20
0.15
".Io
COUNTT
CODE
700
700
700
1760
7160
7160
7160
7160
7160
7160
7160
'I*'
»Ht 4
coot
OS03
0612
0711
0724
0103
0221
0312
0)23
0010
0420
0501
•5?'
COUNTY COUNTY
CODE
0180
180
660
740
1760
2980
0900
1200
1660
2)60
6000
7160
CONTRIBUTION
UG/M..J
0.15
0.13
3.53
0.15
1.01
0.17
0.57
0.60
0.11
0.2S
0.12
".IS
POINT
CODE
0006
0046
1580
9504
9702
13 28
CONTRIBUTION
UG/—3
0.11
0.21
0.12
0.07
0.15
.01
COUNTY
CODE
1760
7160
7160
7160
POINT
CODE
0026
1501
2045
9504
CONTRIBUTION
U8/X..3
0.12
0.11
0.11
0.17
CONTRIBUTION
UG/»>«3
0.0
0.87
0.61
7.46
1.23
0.15
0.21
0.30
O.KJ
1.67
2.00
13.20
COUNTY
CODE
700
700
700
1760
7160
7160
7160
7160
7160
7160
7160
7160
»RE»
CODE
0602
0613
0712
0813
0212
0223
0)1)
0320
0421
0431
OStl
"522
CONTRIBUTION
UG/M..3
0.15
0.45
.31
.14
.1)
.29
.37
.64
.62
.45
.16
".1 !
COUNTY
CODE
740
T40
T40
2)60
7160
7160
7160
7160
7160
7160
7160
«RE1
CODE
0604
0614
071)
0222
021)
0104
0)14
0402
0422
04)3
0512
CONTRIBUTION
UG/««*3
0.17
0.14
0.10
0.10
0.22
0.2)
0.35
O.I)
0.69
0.2)
0.2o
46
-------
1982 DATA
COOKO|N»TES F0» TnlS S0u»ce "ECf'TON FILE «RE 090.0 0420.0
POINT SOURCE CONTRIBUTION 19 la. 01
COUNTY COUNTY CONTR1BUT ION
CODE
0180
06*0
0740
17*0
4900
1200
16*0
2)*0
6000
71*0
Ut/"•••!
0.44
0.22
0.71
0.42
0.01
0.18
1.04
0.18
0.60
0.54
9.IT
COUNTY POINT CONTRIBUTION COUNTY POINT CONTRIBUTION COUNTY POINT CONTRIBUTION COUNTY POINT CONTRIBUTION
CUOf CODE UC/-..S CODE. CODE U6/».«J CODE CODE UG/»«) CODE COM US/M..I
0740
1200
71*0
71*0
71*0
0017
004*
20*4
958T
0.19
0.15
0740
1200
7160
71*0
71*0
0018
004*
1589
9504
9507
0.1S
0.21
0,12
0.55
0.11
17*0
71*0
71*0
71*0
71*0
002*
1501
2045
9S04
9SII
0.13
0.11
0.11
0.55
O.lt
4400
71*0
71*0
71*0
71*0
0011
1581
20*4
95«5
9702
0.20
0.12
0.11
o.ll
O.IT
•Rl« SOUKCt CONTRIBUTION 15 25.25
COUNTY COUNTY CONTRIBUTION
CODE US/«««1
OIHO H.O
180 0.911
6*0 0.51
740 6.42
1760 1.1)
2960 0.11
0900 0.22
1200 O.lu
16*0 0.45
21*0 1,56
6000 1.9*
71*0 11.51
COUNTY
CODE
1RE« CONTRIBUTION COUNTY
CODE ue/«««l CODE
«Rt« CONTRIBUTION COUNTY
CODE U6/""l CODE
>RE* CONTRIBUTION COUNTY
CODE Ut/N»5 COOC
•BE* CONTRIBUTION
CODE U6/n««)
180
740
740
17*0
TlkO
08*1
0*11
0702
OTZ4
0212
0.70
0.15
0.12
740 0501
7+0 0*12
740 0711
17*0 0611
71*0 0211
0.14
0.12
2.9*
0.14
0.20
740 0*02
740 061)
740 0712
21*0 04)1
7160 0214
0.10
0.41
0.28
O.ll
O.IT
740
740
740
71*0
71*0
0*04
0*14
0714
0101
0221
O.I*
0.1)
0.17
'1.28
0.17
71*0 0221
71*0 0)1)
71*0 0)24
71*0 0422
71*0 04)1
71*0 0112
,1)
.11
!54
.2*
,21
71*0
71*0
7160
71*0
71*0
71*0
0)00
0)14
0402
042)
04)4
0511
0.19
0.10
O.ll
0.25
0.1)
0.14
71*0
7160
71*0
7160
71*0
TlkO
0)11
0)21
0412
0424
0501
0521
0.52
0.85
0.21
0.22
0.10
0.11
71*0
71*0
71*0
71*0
71*0
71*0
0112
0121
0421
0411
0511
0522
0.49
0.5*
0.52
0.40
0.15
O.ll
47
-------
1982 DATA
UH 'his Sl>uBCf HfCtPlUh f l^F »«E
POINT 30URCE CONTRIBUTION 13 16, 38
4422.0
COUNTY COUNTV CONTRIBUTION
COUNTY
CODE
0740
1200
71*0
71*0
71*0
POINT
COOF
0006
0046
1589
CON1HIBUTION
0.17
0.21
0.12
o!l2
COUNTY
CODE
0740
1200
71*0
71*0
POINT
CODE
0037
004*
2045
9S04
CODE
01*0
0660
0740
1760
24SO
0900
1200
1*60
2360
6000
7160
CONTRIBUTION
0.61
0.23
0.11
1.19
US/»««3
0.50
0.26
1.81
0.37
0.04
0.37
1.12
0.40
0.6S
0.60
10.25
COUNTY
CODE
0740
7160
7160
71*0
POINT CONTRIBUTION
CODE UC/M..}
0038 0.77
1511 0.12
20*4 0.12
9505 0.13
COUNTY POINT
CUOC CODE
4400 0011
71*0 1587
71*0 20*4
71** »SH
CONTRIBUTION
US/M..J
0.1*
O.K
2.12
O.I*
•RE1 30UHCE CONTRIBUTION 13 24.41
COUNTY COUNTV CONTRIBUTION
CODE US/B..S
OIBO 0.0
180 0.93
6*0 0.57
740 4.0*
17*0 0.94
29BO 0.14
4900 0.21
1200 O.I*
16*0 0.45
23*0 1.57
6000 2.20
COUNT!
COM
180
740
740
17*0
7160
7160
7160
7160
TI60
7160
7160
71*0
• 111
CODt
0163
0*12
0712
0813
0213
0304
0314
0402
0431
0501
0521
CONTRIBUTION
0.19
0.10
0.2'
0.11
0.21
0.2"
0.36
o.ll
o!se
0.11
0.17
COUNTY
CODE
790
790
740
(.000
7160
71*0
7160
7160
71*0
7160
7160
7160
• RE*
CODt
050]
0613
0711
0210
0214
0311
0321
0411
osn
0522
7160
CONTRIBUTION
JG/H**)
0.11
0.27
0.47
0.11
0.30
0.42
0.81
0,10
0,88
oilT
0.14
13.01
COUNTY
CODE
740
740
740
7160
71*0
71*0
71*0
71*0
71*0
71*0
7 1*0
AREA
CODE
0*04
0702
0714
0101
OKI
0312
"323
0412
0423
04J1
0512
CONTRIBUTION
0.10
0,60
0.24
o!u
0.4S
0.69
0.31
0.3*
0.2S
0.28
COUNTY
CODE
740
740
17*0
71*0
71*0
71*0
71*0
71*8
71*0
71*0
71*0
-------
1982 DATA
CCO«OINMIS fOR I-IS SOUHCE UlCtPTO" F H-E • "£ U42.0 aull.1
POINT SOURCE CONTRIBUTION IS 1«.6I
COUNT' COUNTY CONTRIBUTION
COUNTY
coot
0740
1200
7160
7140
,
POINT
CODE
00)7
0024
1587
4S04
CONTR1HUTIUN
UG/M.*)
O.IS
0.11
1.50
0.40
COUNTY
CODE
0740
1200
7160
7160
POINT
CODE
00)8
0024
2015
4505
CODE
0180
0660
0700
1 760
2480
0400
1200
1660
2)60
6000
7160
CONTRIBUTION
UC/M.*)
0.18
0.11
0.14
0.13
UG/»««1
0,47
0.27
0.70
o.ie
o.oa
0,)S
1.14
0,)4
0.58
0.57
4.68
COUNTY
coot
1760
1200
7160
7160
•REl SOURCE CONTRIBUTION
COUNTY
COM
740
7«0
740
1760
7160
7160
7160
7160
7160
7160
7160
• REt
CODE
0604
06|a
071)
OBI)
0214
0)11
0121
0421
0511
0522
CONTKIHUTION
US/*..)
0.10
O.I)
0.15
0.10
0.27
0.)4
0.6)
0.62
0.64
0.18
0.20
COUNTY
CODE
740
740
7<10
6000
7160
7160
7160
7160
7160
7160
7160
>Rb>
CODE
0611
0702
0710
0210
0221
0)12
0)2)
0622
04)2
0512
Oi2o
COUNTY COUNTY
COM
0180
ISO
660
740
1760
2480
4400
1200
1660
2)60
6000
7160
CONTRIBUTION
US/-.. 3
0.18
0.46
1.12
0.11
0.12
0.12
0.56
0,75
0.22
0.25
0.11
POINT
CODE
0026
0046
2064
4702
18 2),
CONTRIBUTION
"«'"••»
0.11
0.21
1.54
0.11
,*.
COUNTY
coot
11400
1200
7160
POINT
CODE
0011
0046
4504
CONTRIBUTION
UC/H>.)
«.*»
0.24
0.40
CONTRIBUTION
UG/M..1
0.0
0.84
0.65
a. 44
0.45
0.15
0.21
0,)8
0.44
1.17
2.11
11.51
COUNTY
coot
700
700
700
7160
7160
7160
7160
7160
7|60
7160
7160
• RE»
CODE
0612
0711
0723
010)
022)
0)1)
0)24
042)
04)1
051)
05)1
CONTRIBUTION
US/M..J
0.12
0.86
0.11
1.06
0,75
0.)2
0.60
0.24
0.27
0.12
0.14
COUNTY
CODE
740
740
1760
7160
7160
7160
7160
7160
7160
7160
«REt
CODE
061)
0712
0724
021)
0)04
0)14
0412
0424
04)4
OS2I
CONTRIBUTION
0.24
0.28
O.I)
0,17
0.21
0.28
0.24
0.26
0.26
0.17
49
-------
1982 DATA
CCOHDINaTfS to" This SOURCE XfCiPlOB FILE «»E 460.
POINT SOuUCE CONTRIBUTION IS 11.71
COUNT! COUNT* CONTRIBUTION
COUNTY
CODE
0180
4900
4900
*U1NI
COOt
0008
0002
001 1
0.14
0.10
5,J8
COUNT Y
coot
0180
4900
COOE
0180
0660
0740
1 760
2980
4900
1200
1 660
2360
6000
7160
POINT CONTRIBUTION
CODt UC/«««3
0015 0,10
0002 0,34
UG/M*"3
1,95
0.06
0.04
0.1 1
0.01
7.90
0,35
0,30
0.33
0.20
0,08
COUNTY POINT CONTRIBUTION COUNTY
COOt CODE u6/«««3 COOE
0180 0016 0.19 0180
4900 0002 0.10 4900
POINT CONTRIBUTION
CODE UG/M««J
0058 0,11
0010 1.65
IRE' SOURCE CONTRIBUTION IS r.St>
COUNTY fl«t»
CJUL CODt
180 061C
180 173-
180 1l"Jj
4900 0702
CONTNjH.jTIUN COUNTY
uli/"«3 CODE
0.10
'j. 1 y
1.15
i.ti
130
4SO J
COOE
0 1 BO
180
660
740
1700
2980
4900
1200
1660
2360
0000
7160
COMBIBUTION
O.I*
0,22
0.15
COUNTY CONTRIBUTION
0.0
3.51
0.12
0.27
0.36
o.ot
1.12
0.11
0.44
0.47
0.47
0.63
COUNTY
CucE
ISO
18C
180
uQOO
IHta CONTRIBUTION COUNTY «RE» CONTRIBUTION
COOE uG/»««3 COOt COOt UG/f«i3
0640 0 . 1 H 180 0720 0.13
074i 0.28 180 0744 0.18
0863 0.35 4900 0600 0.16
J«OI 0.10 M60 0103 0,14
50
-------
1982 DATA
COUROIN4TE8 fOR THIS 1OUKCI RECEPTOR FILE *RE 520,0 4050.0
POINT SOURCE CONTRIBUTION IS 21.02
COUNTY COUNTV CONTRIBUTION
we*
0180
0660
»W«
176*
2980
1200
1660
2JKI
6000
7160
U6/1U«I
0.26
0.60
»,0*
0.12
0.26
0,17
16.93
0.25
0.«S
0.40
1.71
COOE
1200
1200
11*0
1200
ll.H
WJW.T.
CODE
0020
0025
002°
004*
0046
. 20*4
CQNTHIBUTIO'H
UG/«**3
0.41
0.47
0.24
1."
"It
- COUNtI
CODE
1200
1200
1200
1200
1200
POWT
CODE
0020
0025
0029
0046
0046
UC/HO)
0.11
0.61
(Mil
0.25
0.34
COUNTY POINT CONTRIBUTION COUNTY
CODE CODE UC/M<«3 CODE
1200 0020
1200 0029
1200 OOU
1200 0046
1200 0053
POINT CONTRIBUTION
CODE UG/N»«)
0.10
0.11
0*27
3.26
0.2T
1200
1200
1200
1200
7160
0025
0029
004*.
0046
1SB7
3.62
0.41
KM
0.44
0.13
*«£-» SOURCE CONTRIBUTION IS 17.60
UJUNIY COUNTY CONTRIBUTION
CODE UG/«"«3
0180 0.0
ISO 0.48
660 0.8*
7110 0.66
1760 0.31
2980 7.46
4900 0.11
1660 OJ26
2360 0.46
6000 1.70
7160 2.84
COUNTY
f nnr
4RE> CONTRIBUTION CUUNTY
CODf. - Ufiy»«J»3_ COOE
CONTRIBUTION COUNTY
CODE UG/--.J CODE
ARE* CONTRIBUTION COUNTY
COOE UG/M.«1 CODE
«HE«
COOE
CONTRIBUTION
UG/M>«3
040
2980
29BO
1204
7160
0214
0103
0.11
0.41
0.12
0.12
0.27
2980
1240
7160
0102
0211
0302
0.14
4.52
O.IS
0.20
0.11
2980 0104
2980 0212
2900 0303
1200 0451
7160 0422
0.16
0.11
0.11
2980
2980
1200
1200
0113
0213
0234
0452
0.11
0.4J
0.12
0.16
51
-------
1990 DATA
CODRU1NATES FOR THIS SUURCE RECtPTOH FILE »RE «90,U
SOuStE CONTRIBUTION IS I«.7J
COUNTY COUNTY CONTRIBUTION
CODE UI./M..3
OJ80 0.60
0660 0.22
0700 0.75
L76J) 0.00
2980 0.03
1900 0.19
1200 1.0!
1660 0.38
2)60 0.00
6000 0.55
COUNTY
CODE
0710
1900
7160
7160
Ti 6*
7160
POINT
CODE
00)7
0011
1562
2005
9500
9507
CONTRIBUTION
UG/H.O
0,10
0.26
0.10
0.12
o!l5
COUNTY
COOE_
0700
120^~
7160
7160
716V
7160
POINT
CODE
00)6
0006
1581
2056
9500
9511
7160
CONTRIBUTION
JIC/M**)
0.15
OVl 9
0.12
0.10
O.SS
0.1)
9.80
COUNTY
CODE
1760
1200
7160
7160
^160
7160
ARE* SOURCE CONTRIBUTION
COUNTY
COUE
100
7:10
7UU
1760
7 ley
7160
7160
7160
7160
7^60
7160
AREA
CODE
o»6)
"611
-------
1990 DATA
CUOROINITE8 FOR THIS SOURCE RICtPTOR FILE »»€ 4»0.0 "122.0
POINT SOURCE CONTRIBUTION IS IT.2»
COUNTY COUNTY CONTRIBUTION
COUNTY
CUDE
07«0
1200
7160
7160
7160
7160
POINT
CODE
0006
0046
1581
2064
4505
4511
CONTRIBUTION
UG/M..J
0.17
0.21
0.10
0.12
0.15
0.12
COUNTY
CODE
0740
1200
7160
7160
7]60
7160
POINT
CODE
0037
0046
1587
20611
950?
9702
CODE
0180
0660
0740
1760
2460
1900
1200
1660
2360
6000
7160
CONTRIBUTION
UG/M..3
0.61
0.21
0.15
2.24
0.10
0.14
UG/"'«3
0.62
0.27
1.88
U.18
0.03
0.47
1.11
0.10
0.«4
0.60
11. Oa
COUNTY
CODE
0740
7160
7160
7160
7160
POINT
CODE
0018
1511
1589
9504
9507
ARE* SOURCE CONTRIBUTION IS 25
CONTRIBUTION
UG/M..3
0.79
0.12
0.12
1.15
0.10
.05
COUNTY
CODE
4900
7160
7160
7160
7160
POINT
CODE
0011
1576
2045
9504
9508
CONTRIBUTION
ue/»««i
0.25
0.10
0.12
1.15
0.10
COUNTY COUNTY CONTRIBUTION
CUUNTY
CODE
IHO
7UO
700
1760
71*0
7160
716U
7160
7160
7160
7160
7160
APf A
CUDE
0863
0612
071 1
072->
"? 1 e1
0221
0124
0414
04(4
0414
0511
CuMRIbUTIUN
HG/M..3
0.11
0.10
11.75
0.12
!• . 1 2
0.42
6^»6
0.10
Oj24
0.16
0.16
COUNTY
cout
740
740
76V
176
716
716
716
716
7160
716*
7160
7160
AKEA
CUDE
0503
0613
071?
0613
0213
0104
0114
0402
0411
0411
0501
0521
coot
0180
180
660
740
1760
2480
4900
1200
1660
2360
6000
7160
CONTt. I8UT ION
UG/"«"3
0.11
0.29
0.25
O.I 1
.21
.24
.16
.11
.64
.58
.11
.17
U6/M*»
0.0
1.11
0.59
a. 22
0.98
0.15
0.26
0.37
0.«6
1.53
2.26
13.13
CUUNTY
cout
nil
40
uo
6 00
7 6i'
7 60
7160
7160
7140
7160
7160
7|60
AREA
COOE
060«
06 14
0713
0210
U2I4
0111
0121
0411
0422
0412
0511
OS22
CONTRIBUTION
UG/»««3
0.10
0.10
0.49
0.11
0 . 30
0.42
0.81
0.10
0.8*
0.14
0.17
0.14
CUUNTY
COOE
7110
740
740
7160
7 160
7160
7160
7160
7160
7160
7160
AREA
CUOE
0611
0702
0714
0103
02<>1
0112
0121
0412
0421
0411
OSI2
CONTRIBUTION
UG/N..S
0.14
0.62
0.25
1.37
1.11
0.45
0.70
0.11
0.16
0.25
0.24
53
-------
1990 DATA
FOR ThtS SOURCE RECEPTOR FILt AUE 191.0 U022.0
POINT SOURCE CONTRIHUIIPN IS 15,36
COUNTY COUNTY I.UNTW It-UT ION
Cflj'"It
CUOl
07«u
1200
71 DO
7160
POINT cuMHiBuTIdN
COOC UG/M««3
0017 0,15
0029 0,11
1587 1.13
9500 1.02
COUMY
CODE
07«0
1200
7160
7160
POINT
CUDE
0038
0029
2015
9505
CODE
0160
OhDO
07UO
1760
U900
1200
1660
2360
6000
7 160
CONTRIBUTION
UC/M..3
0.18
0.11
0.1S
0.14
0.58
0.28
0.72
0.39
ii.O!
0.15
1.18
0.39
0.«2
0.58
10.34
COUNTY
CODE
1760
1200
7160
7160
4BE» SOURCE CONTRIBUTION
POINT
CODE
0026
0046
2064
9702
IS 21
CONTRIBUTION
U&/MX3
0.12
0.21
1.63
0.1)
.23
COUMY
CODE
4900
1200
7160
COIN!
CODE
0011
0046
9500
CONTRIBUTION
U6/M..J
0.24
0.23
1.02
COUNTY COUNTY CONTRIBUTION
COo'.TY
CuDE
0
0
u
1 0
7 i.
7 0
7 0
' 0
7 0
7
0.18
0.20
UG/v**3
0.0
1.06
0.67
5.13
0.98
0.15
0.25
0.18
O.«0
1.38
2.17
11.62
COUNTY
COUE
7UO
7
-------
1990 DATA
F0f* IHIS SUUHCt »tC£PTO« FILE Ak£
PuJNT SliUHCE CONTHIMUT JO* IS la,
UttO.O "595,0
COUNTY
CODE
0160
OIBO
0900
COUNTY COUNTY
COOE
0180
0660
07110
1 760
2960
4900
1200
1660
2360
6000
7160
POINT CONTRIBUTION COUNTY POINT CONTRIBUTION
CODE UG/M>*3 COUt CODE UG/M»«3
0008 1.1" 0160 0010 0.10
002J 0.11 OIBO 0056 0.111
0002 0.13 11900 0001 0.13
CUNTHIHUT ION
2. "i
0.06
0.04
0.11
0.01
10.16
0.3«
0.30
0.26
0.20
0.51
COUN1Y POINT CONTRIBUTION COUNTY POINT
CODE CODE UG/M**3 CODE CODE
01BU 0015 0.13 0160 0016
4900 0002 0.13 4900 0002
4900 0010 2.19 4900 0011
CONTRIBUTION
UG/M4.3
0.24
0.44
6.82
Aut» SOURCE CQNTRlBUTIut IS 8.56
COUNTY COUNTY
COOE
OIBO
180
660
700
1760
2960
11900
1200
1660
2360
6000
7160
CONTRIBUTION
UG/«««3
0.0
a. if
0.12
0.26
0.36
0.0
1.3
0. 1
0."
0.4
0.4
0.6
COUNTY
cuor
180
100
IBO
160
4900
• RE*
coot
•J61U
07J2
07m.
0961
0601
CONTRIBUTION
uG/«*«3
'.13
".12
0.22
0,11
n.13
COUNTY
COOE
180
180
III!
490U
7160
«RE»
coot
0630
0734
0642
0600
0103
CONTRIBUTION
UG/»««3
0.29
0.13
0.16
0.22
0,15
COUNTY
COOE
I8U
180
160
4900
AREA
coot
06UO
07«2
0651
0702
CONTRIBUTION
UG/M.-5
0.23
0.23
0.27
0.24
COUNTY
COut
160
160
1FO
4900
AHt ft
coot
07211
0743
0863
0711
CONTRIBUTION
UG/M..J
0.16
0.34
0.37
0.17
55
-------
1990 DATA
CLOHMLATES I-UK i»is sojuct >)tCLPiu* FILE «»t 520,0
fCINT St.u»CE CL"«l«I6uT10N IS 21.08
COUNTY
CCOE
0 1 nO
0710
1760
2960
moo
1200
1660
2360
6000
7160
COUNTY CONTRIBUTION
u&/»***4
0.32
oiio
0.12
11.26
0.22
16. 78
0.2S
0.2U
O.ul
1 .B2
CUUNTT awt*
cuof cnnt
060 0962 U, 1 I
^960 02t>a 0. bi
2^80 <>?)J 0.13
1?00 nJ5« ".1?
7 leO 0 1 0 J •i.r'9
COUNTY
CODE
1200
1200
1200
1200
1200
7160
POINT
CODE
0020
0025
0029
0016
0046
2064
CONTRIBUTION
UC/»««3
o.al
O.U7
0.15
0.24
1.75
0.29
COUNTY
COOE
1200
1200
1200
1200
1200
• RtA SOORCE CONTRIBUTION
COUNT t
CfiDt
2900
29fln
2960
1200
7 1 eO
• RtA
COOE
0102
0211
0302
0363
o223
COUNTY COUNTY
CODE
0160
160
660
740
1760
29BO
U900
1200
1660
2360
6000
7160
CONTRIBUTION
1-C/-.-1
0.35
« .66
0.15
u.20
0.1 1
PI1IM
CUOE
0020
0025
0029
0046
0016
IS 18
CONTRIBUTION
UG/M..J
0.11
0.61
0.11
0.20
0.34
.13
COUNTY
CODE
1200
1200
1200
1200
1200
POINT
COOE
0020
0029
0036
OOM6
0053
CONTR1BUT ION
UG/M..1
0.10
0.13
0.26
3.23
0.27
CONTRIBUTION
UG/***3
0.0
0.58
0.90
0.69
0.33
7.73
0.13
2.13
0.26
0.16
1.75
2.a?
COUNTY
coot
2960
2980
296V
1200
7160
AREA
coot
0) 01
U212
0303
0151
0122
CONTRIBUTION
U6/ — 3
0, 15
0.19
0.19
0.11
0. 1 1
COUNTY
COOE
i9(0
29AO
1200
1200
AHtA
CCOE
0113
0213
0231
0452
CONTRIBUTION
UG/...3
0.11
0.41
0.1 1
0.15
56
-------
APPENDIX B
EMISSION TRACKING SYSTEM
RATIONALE FOR A TRACKING SYSTEM
Tracking procedures constitute a regular assessment of air quality prob-
lems by determining whether or not actual emissions are comparable to pro-
jected emissions and whether or not emissions growth is occurring as slowly as
predicted. Tracking thus facilitates the identification of areas where in-
creases in emissions may cause the NAAQS to be violated. These procedures
allow problems to be anticipated and addressed through control strategy modi-
fications before the problems become critical.
The tracking system can also help identify specific sources of air quality
problems. If air quality, as estimated by monitor data, remains poor despite
the fact that emissions growth has occurred as predicted, then sources which
were not included in the initial inventory or in the tracking procedures must
be examined. For example, particulates from sources located outside of the
five New Jersey counties may have a significant impact on air quality problems
within these counties even though the counties emissions are growing as slowly
as predicted. Sources beyond the New Jersey borders should, therefore, be
tracked by asking local air pollution agencies for their most current air
quality estimates, and emissions reduction schedules.
Section 301(a) of the Clean Air Act, Part 51 - "Requirements for Prepara-
tion, Adoption, and Submittal of Implementation Plans," requires that all areas
of the state be assessed every 5 years to determine if any areas are in need
of plan revisions. New Jersey must undertake detailed tracking every 5 years,
but some level of tracking should be conducted in all counties annually.
Frequent detailed tracking is particularly important in rapidly growing areas
where the amount and type of new sources and their influence on air quality
are most difficult to project. Areas experiencing less rapid growth may re-
quire less detailed annual tracking.
The procedures described here are designed to be applied in steps as more
and more accuracy and detail is desired. A more detailed level of analysis is
recommended whenever a review of the major growth indicators reveals that
actual emissions growth differs substantially from projected emissions growth
or if the most recent projections differ from the original projections.
Whenever tracking is conducted, sources which generate large quantities
of particulates should be examined more thoroughly than sources which add
relatively little to the air quality problem. For example, since about
57
-------
46 percent of the area source emissions (or about 22 percent of all particulate
emissions) are produced by motor vehicles, it is worthwhile to acquire the
most detailed data available to estimate emissions from this source. Similarly,
since only about 20 companies own point sources which produce about 70 percent
of the point source emissions, these sources should be more carefully tracked
than smaller point sources. Tracking the smaller area and point sources would
require a large expenditure of time and add little accuracy to the total
estimate.
The tracking procedures necessitate the continual gathering of data which
can be used to estimate emissions for the analysis year, so that these esti-
mates can be compared with the projected emissions for that year. Level A
data provid'es for the least detailed level of tracking suggested while Level B
data provides more accurate estimates. All data described here is available
in New Jersey.
TRACKING AREA SOURCES
The major area sources of particulate emissions are motor vehicles, air-
craft, residential, industrial and commercial/institutional development.
Together these sources produce about 91 percent of the area source emissions.
So these sources are emphasized in the tracking system. (See Section 2,
Tables 9 and 10).
The growth indicators used for estimating each of these emission sources
should be obtained for each of the five counties. County level data is recom-
mended because data broken-down in this way is manageable, and available, yet
fine enough for the required accuracy.
Motor Vehicles
Level A—
The growth indicator used to estimate motor vehicle emissions is vehicle
miles traveled (VMT) as estimated for each county.
Level B—
A more accurate growth indicator for estimating motor vehicle emissions
is VMT by each of the five following motor vehicle classifications: light-duty
vehicles, light-duty trucks, heavy-duty gasoline vehicles, heavy-duty diesel
vehicles and motorcycles. Still more accuracy can be added by acquiring the
age mix of vehicles for each of the vehicle categories and annual miles driven
by vehicles of each age group. Emissions factors are substantially lower for
vehicles produced after 1973, when the catalytic converter came into use. So
it is advisable to obtain estimates of how much VMT was generated by vehicles
produced before and after 1973.
Residential, Commercial/Institutional and Industrial
Area Source Emissions
Level A—
The growth indicator used to estimate emissions from the residential sector
is number of households. The indicators for the commercial/institutional sector
58
-------
are population and commercial employment. The industrial sector's emissions
may be estimated using industrial employment.
Level B—
Estimates of area source fuel use by sector for each state are published
annually by the Bureau of Mines. These data must be apportioned to the coun-
ties. For example, the state residential fuel total should be apportioned to
the counties according to the percentage of the state's dwelling units which
are located within that county (e.g., county residential fuel total
= state residential fuel total x No. county dwelling units }>
No. state dwelling units
Similarly, state commercial/institutional fuel use should be apportioned to the
counties according to the percentage of the state population living in each
county. Industrial fuel is apportioned according to industrial employment.
Another method for estimating area source emissions requires information
from fuel dealers concerning their annual sales by county to each source cate-
gory (residential, industrial, commercial/institutional). The area source totals
are the fuel dealers figures minus any fuel consumed by point sources that are
included in the source categories.
Data from fuel dealers can be used as an indicator of local use patterns
that would not be discovered using Bureau of Mines data alone. But this data
source is best used only as a supplement to Bureau of Mines data since not all
dealers will be able to furnish adequate information.
If information from the two sources is not in agreement, state totals from
Bureau of Mines are probably more accurate. The distribution to source cate-
gories, particularly residential and commercial/institutional may be more ac-
curately provided by the fuel dealers. Assuming the residential and commercial/
institutional area source totals can be adjusted, if necessary, so that the state
total equals the state total figure provided by the Bureau of Mines. If fuel
dealers can provide information only for groups of counties, these data can be
distributed to individual counties using the apportioning method described above.
Aircraft Area Source Emissions
Level A—
Aircraft emissions are estimated using projections of demand for air travel.
These projections are revised every few years, so the growth factor for the anal-
ysis year will sometimes be determined through interpolation.
Level B—
More accuracy in estimating aircraft emissions can be obtained by acquiring
for each airport in each of the five counties, the number and type of aircraft
operating from the airport and the number of LTOs for each aircraft.
59
-------
Other Area Sources (Incineration. Open Burning. Off-Highway Fuel Usage, Vessels.
Railroads'
Level A—
These sources can be tracked using population as the growth indicator.
Level B: Fugitive Dust Tracking (other miscellaneous sources, such as forest
fires, slash burning and agricultural frost control, are not included)—
A major source of fugitive dust is from the handling and storage of mineral
products. Large rock-handling operations are generally included as point sources
so they do not need to be tracked separately. Area source rock-handling opera-
tions would cover any smaller scale activities such as small sand and gravel
yards, stone products manufacturers and other mineral products industries. These
sources can be tracked by surveying these operations to determine tons of min-
erals processed per year,
TRACKING POINT SOURCES
Prepare a tabulation of emissions from all major point sources by sur-
veying either all point sources emitting more than 25 tons per year of par-
ticulates or all point sources emitting more than 100 tons per year of par-
ticulatee, depending upon the amount of detail desired. Point sources pro-
ducing more than 100 ton/year particulates are responsible for about 70 per-
cent of all point source emissions, while point sources emitting over
25 ton/year particulates create about 86 percent of the particulates from
point sources. See Tables 18, 19 and 20.
TRACKING METHODOLOGY
Step 1
Acquire estimates of the indicators used to project the area source
emissions inventory. The Level A area source growth indicators are popula-
tion, employment, households, vehicle miles travelled and air travel demand.
Determine growth factors for these indicators and then multiply base year
emissions by these factors:
Source
a. Motor vehicle emissions
b. Residential area source emissions
c. Commercial/Institutional area
source emissions
d. Industrial area source emissions
e. Aircraft emissions
f. Miscellaneous sources emissions
Proceed to Step 2 if:
Growth factors
VMT
Households
Population
Industrial employment
Air travel demand
Population
a.
Level A estimates of emissions for the analysis year exceed
emissions projections for the analysis year.
60
-------
TABLE 18. ANALYSIS OF POINT SOURCE EMISSIONS - 1978
Emission points >_ 25 ton/yr Emission points ^ 100 ton/yr
Area sources Point sources Total _______^_____—_
County ton/yr No. companies Percentage No. companies Percentage
ton/yr percent ton/yr percent area and point and of and of
No. points total points No. points total points
Burlington 2,814 54 2,375 46
Camden 2,649 64 1,506 36
Gloucester 1,633 28 4,103 72
Mercer 2,498 51 2,387 49
Salem
690 18 3,161 82
Total 10,284 43 13,532 57
5,189
4,155
5,736
4,885
3,851
23,816
86
59
88
94
94
86
63
21
69
84
87
70
-------
TABLE 19. COMPANIES WITH INDIVIDUAL POINT SOURCES EMITTING
MORE THAN 100 TON/YR PARTICULATES
Burlington:
1. Kaiser Gypsum, 2700 Burlington Ave., Delanco
2. U.S. Pipe, E. Pearl St., Burlington
3. National Gypsum Co., River Rd., Burlington
4. C. E. Glass, 700 Union Landing Rd., Cinnaminson
Camden:
5. Lafferty Asphalt, Gibsboro Rd., Voorhees
6. Johns Manville Corp., P.O. Box 130, Berlin
Gloucester:
7. Texaco, Rte. 130, W. Deptford Township
8. Rollins-Purle, Rte. 322E, Bridgeport
9. Mobil Oil Paulsboro, Billingsport
10. Matteo 1708, U.S. Rte. 130, W. Deptford Township
Mercer:
11. Public Service Electric, Lambert Rd., Trenton
12. Stauffer Chemical, 4407 S. Broad St., Yardville
13. Wenczel Tile, Klag & Enterprise, Trenton
Salem:
14. Atlantic City Electric, Pennsgrove
15. E.I. Dupont, Carneys Pt.
16. Anchor Hocking, Griffith St., Salem
17. A. Clemente Inc., Box 471, Pennsgrove
18. Meckel R. & Son, S. Gershal Ave.
62
-------
TABLE 20. COMPANIES WITH INDIVIDUAL POINT SOURCES EMITTING
MORE THAN 25 TON/YR PARTICULATES
Burlington:
19. Public Service Electric, W. Broad & Devlin, Burlington
20. Tenneco Plastic, Beverly Rd., Burlington 08016
21. Hoeganaes, River Rd. & Taylors Lane, Riverston
22. Griffin Pipe, 1100 W. Front, Florence 08518
Camden:
23. Georgia Pacific, Front of Desousse, Delair 08110
24. RCA Corp., Front & Cooper, Camden
25. Campbell Soup, 100 Market St., Camden
26. Formigli Corp., Plant 1, P.O. Box F, Berlin
27. Pettinos, G. F. Inc., New Freedom Rd., Winstown
28. Owens-Corning Fiberglass Corp., Fiberglass Rd., Barrington
Gloucester:
29. Shieldalloy Corp., Division of Metallurgical Inc., NE
30. Rollins Environmental Service, Rte. 322, Logan Township
31. South State Inc., P.O. Box 68
63
-------
b. Growth in an area is particularly rapid, as in Gloucester
County.
c. Particulate concentrations are particularly high or close
to the NAAQS as in Camden County.
d. A detailed analysis has not been conducted in over a year.
Step 2
Use Level B data to estimate emissions for the analysis year by applying
AP-42 emissions factors to the data. If the Level B estimates exceed projec-
tions, proceed to Step 3.
Step 3
Acquire the most recent projections for the year 1990 (final analysis
year) for the area source growth indicators (population, households, employ-
ment, etc.). If the new projections of the growth indicators for 1990 do not
exceed the original projections of the growth indicators for 1990, then no
further tracking is necessary. Even though the estimated population, for
example, is higher than the projected population in the analysis year, the
most recent projections may predict the same 1990 population as the original
projections. So, ultimately, emissions growth should not exceed the original
projections. However, if the new projections of the growth indicators for
1990 exceed the old projections, proceed to Step 4.
Step 4
Estimate emissions for 1990 by applying growth factors from the new 1990
projections of population, vehicle miles travelled, etc. to base year emis-
sions. Use the Proportional Roll-Forward model to estimate air quality levels
in 1990. See Tables 21 and 22. If NAAQS are not violated, no further tracking
is necessary. If a violation is predicted, proceed to Step 5.
Step 5
Conduct a detailed analysis such as that described in Guidelines for Air
Quality Maintenance Planning and Analysis, Volumes 7, 12, and 13.
TRACKING METHODOLOGY USING MONITORING DATA
• Compare monitor data for the analysis year with air quality
projections for the analysis year. If monitor data exceeds
projections, proceed to Step 2.
• Refer to Step 2 of the emissions tracking procedure described
previously. If monitor data exceeds air quality proiections
and emissions estimates exceed emissions projections, continue
with the emissions tracking procedures. If monitor data
exceeds air quality projections, but emissions estimates are
64
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TABLE 21. PROJECTED EMISSIONS 1982 - 1990
Burlington
Area
Point
Caraden
Area
Point
Gloucester
Area
Point
Mercer
Area
Point
Salem
Area
Point
Total
Area
Point
1982
2,165
2,105
2,167
1,538
1,367
3,481
2,101
2,363
676
1,843
8,476
11,330
1983
2,171
2,119
2,178
1,541
1,376
3,484
2,114
2,369
691
1,908
8,530
11,421
1984
2,177
2,132
2,189
1,544
1,385
3,486
2,127
2,375
706
1,972
8,583
11,509
1985
2,182
2,138
2,200
1,547
1,394
3,489
2,139
2,081
721
2,027
8,637
11,282
1986
2,188
2,152
2,212
1,551
1,403
3,492
2,152
2088
736
2,091
8,691
11,374
1987
2,194
2,165
2,223
1,554
1,412
3,494
2,165
2,094
751
2,156
8,744
11,463
1988
2,200
2,179
2,234
1,557
1,421
3,497
2,178
2,100
766
2,220
8,798
11,553
1989
2,205
2,192
2,245
1,560
1,430
3,499
2,190
2,106
781
2,284
8,851
11,641
1990
2,211
2,206
2,256
1,563
1,439
3,502
2,203
2,112
796
2,349
8,905
11,732
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TABLE 22. PROPORTIONAL ROLL-FORWARD MODEL
Present air quality may be projected 10 years for
particulates using the proportional roll-forward
model as shown in the following formula:
.
current
t
where X = projected air quality level
X^ = background concentration
X = current air quality level
L«
0_ = projected emissions in 10 years
0 ^ = current year emissions
current J
66
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comparable to emissions projections, then (a) investigate emissions
sources outside of the five county area, and (b) determine whether
or not meteorological conditions have been unusual during the past
year. It is possible that emissions growth is occurring as pre-
dicted, but air quality is worse than predicted because of sources
outside of New Jersey or because of unusual weather.
Perform analysis to determine if the composition of the elements
found on the filter differs substantially from the base year
composition.
DATA SOURCES
1. Population and Households:
New Jersey Department of Labor and Industry
Office of Demographic and Economic Analysis
P.O. Box 845
Trenton, N.J. 08625
Shirley Goetz (609) 292-0076
2. Vehicle Miles Travelled:
State Highway Department
Planning Division
Trenton, N.J. 08625
(609) 292-4135
Data for Salem County
Delaware Valley Regional Planning Commission
Department of Transportation
Ronald Fijalkowski (215) L07-3000
Data for Burlington Camden, Mercer and Gloucester
3. Employment:
New Jersey Department of Labor and Industry
Division of Planning and Research
P.O. Box 359
Trenton, N.J. 08625
Ray Janowski (609) 292-8524
Jerry Tischio (609) 292-1859
4. Residential/Commercial/Institutional and Industrial
Area Source Fuel Use:
Mineral Industry Survey
U.S. Department of the Interior
Bureau of Mines
Washington, D.C.
New Jersey Department of Energy, Technical Assistance
101 Commerce Street
Newark, N.J. 07102
Kenneth Warren (201) 648-6290
67
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This agency was established recently and is in the process
of building a data base. Currently they do not compile
information from the fuel companies, aside from data from
annual reports, but they anticipate doing so. The New
Jersey Department of Energy should be contacted and encouraged
to develop data which could be useful in emissions monitoring.
Aircraft:
Bureau of Aviation Planning
1035 Parkway Ave.
Trenton, N.J. 08625
John J. Santarsiero, Bureau Chief
(609) 292-3052
FAA Air Traffic Activity Fiscal Year 19XX
U.S. Department of Transportation,
Federal Aviation Administration
Washington, D.C.
68
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TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
1. HtPORTIMO. ~
EPA-902/4-78-OOQ
2.
I.TITLE AND SUBTITLE "
NEW JERSEY PORTION OF THE METROPOLITAN PH
AQCR NONATTAINMENT AND MAINTENANCE STUDY
I.AUTHOR(S)
VICTOR L. CORBIN, SUSAN PULTZ
(.PERFORMING ORGANIZATION NAME AND ADDRESS
GCA CORPORATION
GCA/ TECHNOLOGY DIVISION
BURLINGTON ROAD
BEDFORD, MASSACHUSETTS 01730
12. SPONSORING AGENCY NAME AND ADDRESS
U.S. ENVIRONMENTAL PROTECTION AGENCY
REGION II
AIR PROGRAMS BRANCH
NEW YORK, NEW YORK 10007
3. RECIPIENT'S ACCESSIOONO.
5. REPORT DATE
TT.AnFT.PHTA October 1978
„-_ „,„_ 6. PERFORMING ORGANIZATION CODE
rUK lor
8. PERFORMING ORGANIZATION REPORT NO.
GCA-TR-78-54-G
10. PROGRAM ELEMENT NO.
11. CONTRACT/GRANT NO.
13. TYPE OF REPORT AND PERIOD COVERED
14. SPONSORING AGENCY CODE
15. SUPPLEMENTARY NOTES
If. ABSTRACT
THE CAMDEN AREA IS NOT ATTAINING THE SECONDARY TSP STANDARD AND IS UNCLASSIFIED WITH
REGARD TO THE PRIMARY TSP STANDARD. THE OBJECTIVE OF THIS STUDY WAS TO USE DISPER-
SION MODELING AND FILTER ANALYSIS TO IDENTIFY THE REASONS FOR THE SECONDARY STANDARD
VIOLATION, AND TO PROPOSE, DEMONSTRATE AND ANALYZE, BY MEANS OF DISPERSION MODELING,
VARIOUS CONTROL STRATEGIES TO ATTAIN AND MAINTAIN THE SECONDARY STANDARDS THROUGH
! 1990. THE DATA UTILIZED AND DEVELOPED UNDER THIS CONTRACT WERE TO BE FORMATTED SUCH
THAT THE DATA WOULD SATISFY THE MINIMUM DATA REQUIREMENTS FOR SIP SUBMISSION AS
OUTLINED IN THE CLEAN AIR ACT AMENDMENTS OF 1977.
' KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
'.DISTRIBUTION STATEMENT
RELEASE UNLIMITED
b.lDENTIFIERS/OPEN ENDED TERMS
19. SECURITY CLASS (This Report)
UNCLASSIFIED
20. SECURITY CLASS (This page)
UNCLASSIFIED
c. COSATI Field/Group
21. NO. OF PAGES
77
22. PRICE
69
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