1
2
3
4
5
Supplemental Material
6
Sensitivity Studies
7
Several assumptions were tested to determine their sensitivity on urban excess estimates. These
8
assumptions included (1) the effect of using interpolated rural concentrations at the location of
9
the CSN site versus the average concentration at nearby sites, (2) the effects of altitude
Spatial and seasonal patterns in urban influence on regional concentrations of speciated aerosols
across the United States, by Hand et al.
10
corrections on urban excess, (3) the sensitivity of excess to elevation differences between urban
11
and rural sites, (4) the impact of the distance limit between urban and rural sites, and (5) the
12
relationship between city population and urban excess estimates.
13
A major challenge in computing urban excess is quantifying the regional concentration at an
14
urban site. Excess often has been computed using concentrations at urban and nearby rural site
15
pairs. If more than one nearby rural site is available, rural concentrations can be averaged or
16
considered separately. Spatial averaging of rural concentrations removes some of the subjectivity
17
of the choice of rural site and allows for a regional concentration to be determined at the actual
18
location of the urban site. To test the sensitivity to the choice of rural concentrations, we
19
compared excess ratio estimates using interpolated rural concentrations at the location of the
20
urban site to estimates calculated using the average of concentrations from nearby (<150 km)
21
rural sites (usually 5 sites or less). Annually across the United States, the error in excess ratio
22
associated with using interpolated concentrations relative to averaged concentrations was ~12%
23
or less depending on species, with the largest error associated with AN. The biases for all species
24
were low (<5%) and the excess ratio estimates were highly correlated (Table S1). Estimates of
25
errors for monthly mean aggregated excess ratios are shown in Figures S1a and S1b for sites in
26
the West and East, respectively. The biggest errors occurred during winter months for sites in
27
the West, especially for AN. Higher errors were associated with outliers that corresponded to
28
urban sites in California with only two or three nearby IMPROVE sites. December mean AN
29
interpolated concentrations at the location of a CSN site are compared to the average of
30
measured IMPROVE concentrations from nearby sites in Figure S2. The outliers in Figure S2
31
corresponded to sites at Fresno and Visalia, California. In both cases the rural sites were at
1
32
higher elevation compared to the urban sites. The higher errors in winter suggested that
33
meteorological effects (wintertime low boundary layer and wind speeds) were enhanced when
34
the average of two or three rural sites was used to compute excess, rather than a spatial
35
interpolation of concentrations from surrounding sites. In the East, lower errors were associated
36
with excess ratios.
37
The second sensitivity test investigated the impact of altitude corrections on urban excess. We
38
compared excess ratios computed with rural concentrations that were altitude adjusted to the
39
elevation of the urban site to ratios computed with concentrations corresponding to local
40
elevations of rural sites. Across the United States the error associated with altitude adjustments
41
was 2.4% (bias of 4.7%), with somewhat higher excess ratios for nonadjusted rural
42
concentrations. The error was higher in the West (8.5%) where higher elevation sites were
43
located. This altitude correction does not account for effects of boundary layer height and
44
sampling of different air masses.
45
The third sensitivity test investigated the relationship between urban excess and elevation
46
difference between rural and urban sites. Much of the analysis has pointed to the importance of
47
meteorological influences on excess especially for sites in the West in winter when elevation
48
differences could lead to the sampling of different air masses. To explore this possibility we
49
examined the relationship between excess and difference in elevation between the CSN site and
50
the average elevation of nearby IMPROVE sites within 150 km. A linear regression performed
51
between urban excess and elevation differences did not reveal a clear dependence of excess on
52
elevation difference (see Figure S3a and S3b for West and East, respectively). Correlation
53
coefficients (r) were actually negative for most species and months in the West. Mostly positive
54
correlation coefficients were computed for all species for eastern sites even though seasonal
55
patterns in excess were less evident for eastern sites.
56
The fourth sensitivity test examined the assumption of the distance limit applied for rural and
57
urban sites. Based on the spatial gradients in the rural concentration field (see Figure 2), rural
58
sites too far from an urban site may not be representative of the regional conditions near that
59
urban site. The excess analysis was repeated by varying the site distance limits (10, 20, 40, 60,
60
80, 100, 125, 150, 175, and 200 km) to evaluate the sensitivity to the distance of rural sites. The
61
rural interpolated concentration fields remained the same, but excess values were computed at
2
62
CSN sites that were located within the distance limit to an IMPROVE site. Obviously, the
63
aggregated estimates of urban excess depended on which and how many sites were included in
64
the analysis. For distance limits greater than 80 km, the annual mean excess ratios were nearly
65
constant up to a distance limit of 200 km for all species (see Figure S4a and S4b for West and
66
East, respectively). However, the number of sites included in the analysis did not change
67
significantly for sites in the West, although the number of sites did increase in the East where
68
urban site density is higher. Lower ratios at shorter distance limits (10–60 km) suggested that
69
the closest IMPROVE sites may be more influenced by urban sources and therefore not as
70
representative of regional concentrations as sites somewhat farther away. In the West, EC and
71
AN were most sensitive to shorter distance limits (<80 km), while in the East, EC was the most
72
sensitive, suggesting that these species may have steeper spatial gradients relative to other
73
species. We chose a distance limit of 150 km to achieve a statistically representative number of
74
sites (35 in the West and 81 in the East) for regional analyses and to capture the transport of
75
primary aerosols [Wangstrom and Pandis, 2011].
76
Finally, relationships between population and urban excess were examined using 2010 census
77
data (http://www.census.gov/popest/data/cities/totals/2012/SUB-EST2012.html) for estimates of
78
city population for CSN site locations. No clear relationships emerged between the population of
79
a city and urban excess for any species, and in fact the highest-population cities did not
80
correspond to the highest excess ratios. This result is not surprising given that the influence of
81
meteorology on urban excess affects cities regardless of size.
82
83
84
85
Table S1. Comparison Statistics for Annual Mean Excess Ratios Calculated with Interpolated
versus Measured IMPROVE Data and CSN Data for CSN Sites within 150 km of an IMPROVE
Site
Species
Errora (%)
Biasb (%)
Correlation (r)
Ratio of meansc
(meas./interp.)
ASd
5.8
-0.4
0.82
0.99
ANe
12.3
4.8
0.77
1.08
POMf
6.0
1.2
0.96
1.02
ECg
8.0
0.3
0.98
1.02
3
86
87
88
89
90
91
92
93
94
95
96
97
98
 X  Yi 
 ; X i and Yi are the monthly mean data for CSN and IMPROVE concentrations,
Error  median  i
 Y

i


respectively.
1 N X  Yi
b
Bias   i
; The number of data points is given by N =116.
N i Yi
c
Measured/Interpolated refers to the ratio of the mean measured IMPROVE concentrations to mean interpolated
IMPROVE concentrations at the location of a CSN site.
d
Ammonium sulfate = 1.375*sulfate ion
e
Ammonium nitrate = 1.29*nitrate ion
f
Particulate organic matter = 1.8*organic carbon
g
Elemental carbon
a
Figures
99
100
101
102
103
104
Figure S1. Monthly mean error (%) in urban to rural ratios computed using measured and
interpolated IMPROVE concentrations for CSN sites (a) West and (b) East of -100° longitude
for ammonium sulfate (AS), ammonium nitrate (AN), particulate organic matter (POM), and
elemental carbon (EC).
105
4
106
107
108
109
Figure S2. 2008-2011 December monthly mean ammonium nitrate (AN) concentration (µg m-3)
for average measured IMPROVE data and interpolated data at the location of the CSN site. Sites
east and west of -100° longitude are shown in black and red, respectively.
110
111
112
113
114
115
Figure S3. Monthly mean correlation coefficient (r) for urban to rural ratio estimates versus
elevation difference between CSN and averaged nearby (<150km) IMPROVE site elevations for
sites (a) West and (b) East of -100° longitude for ammonium sulfate (AS), ammonium nitrate
(AN), particulate organic matter (POM), and elemental carbon (EC).
116
117
5
118
119
120
121
122
Figure S4. Distance limit (km) versus annual mean urban to rural ratio estimates for sites (a)
West and (b) East of -100° longitude for ammonium sulfate (AS), ammonium nitrate (AN),
particulate organic matter (POM), and elemental carbon (EC). The number of CSN sites
associated with each distance limit is shown above the plotting symbol.
123
124
Sites used in the analysis
125
126
Table S2. CSN Sites Used in the Analysis (with IMPROVE Site within 150 km)
CSN Site ID
10730023
10732003
10890014
40139997
40191028
51190007
60190008
60290014
60371103
60658001
60670006
60730003
60731002
60850005
60990005
61072002
61112002
80010006
80310025
80770017
81230008
Latitude
33.553
33.5
34.688
33.504
32.295
34.756
36.781
35.356
34.067
34
38.614
32.791
33.128
37.348
37.642
36.332
34.278
39.826
39.704
39.064
40.209
Longitude
-86.815
-86.924
-86.586
-112.096
-110.982
-92.281
-119.772
-119.04
-118.227
-117.416
-121.367
-116.942
-117.075
-121.895
-120.994
-119.29
-118.685
-104.937
-104.998
-108.561
-104.824
Elevation (m)
177
180
180
355
710
77
91
118
126
250
19
169
237
21
19
91
308
1558
1606
1524
1464
6
90090027
100010003
100032004
110010043
120111002
120573002
120730012
121030026
130590001
130690002
130890002
131150003
160010010
180190006
180372001
180970078
181630021
191130037
191530030
201730010
202090021
211110067
220150008
220330009
240053001
240330030
250130008
250250042
271095008
290470005
291860005
300630031
300930005
310550019
320030020
320310016
340230006
340273001
340390004
350010023
360010005
360050110
360310003
360551007
360610134
41.301
39.155
39.739
38.922
26.083
27.966
30.44
27.85
33.946
31.513
33.688
34.261
43.6
38.278
38.391
39.811
38.013
42.008
41.603
37.701
39.118
38.229
32.536
30.462
39.311
39.055
42.194
42.329
43.997
39.303
37.901
46.875
46.002
41.246
36.245
39.525
40.473
40.788
40.641
35.134
42.642
40.816
44.393
43.146
40.714
-72.903
-75.518
-75.558
-77.013
-80.238
-82.23
-84.348
-82.715
-83.372
-82.75
-84.29
-85.323
-116.348
-85.74
-86.929
-86.115
-87.578
-91.679
-93.643
-97.314
-94.636
-85.655
-93.749
-91.179
-76.474
-76.878
-72.555
-71.082
-92.45
-94.377
-90.424
-113.995
-112.501
-95.973
-115.092
-119.808
-74.423
-74.676
-74.208
-106.585
-73.755
-73.902
-73.859
-77.548
-73.995
5
6
31
31
3
28
16
2
214
64
244
240
853
140
139
240
120
254
282
405
269
161
47
16
10
47
60
5
318
273
250
1020
1697
347
583
1403
24
256
3
1578
30
14
584
146
5
7
360810124
361010003
370210034
370350004
371190041
371590021
390350038
390350060
390490081
390811001
390990014
391510017
391530023
401091037
401431127
410510080
420010001
420030008
420030064
420110011
420210011
420270100
420290100
420430401
420490003
420710007
421010004
421010055
421255001
421290008
421330008
440070022
450190049
450450015
460990008
470370023
470654002
470931020
470990002
471251009
500070012
510870014
530110013
530330057
530330080
40.736
42.091
35.607
35.729
35.24
35.552
41.477
41.494
40.088
40.322
41.096
40.787
41.088
35.614
36.205
45.497
39.92
40.466
40.324
40.383
40.31
40.811
39.834
40.245
42.142
40.047
40.009
39.923
40.445
40.305
39.965
41.808
32.791
34.844
43.548
36.176
35.051
36.019
35.116
36.514
44.48
37.558
45.648
47.563
47.568
-73.822
-77.21
-82.583
-81.366
-80.786
-80.395
-81.682
-81.678
-82.96
-80.606
-80.658
-81.394
-81.542
-97.475
-95.977
-122.602
-77.31
-79.961
-79.868
-75.969
-78.915
-77.877
-75.768
-76.845
-80.039
-76.283
-75.098
-75.187
-80.421
-79.506
-76.699
-71.415
-79.959
-82.415
-96.701
-86.739
-85.293
-83.874
-87.47
-87.328
-73.214
-77.4
-122.587
-122.34
-122.308
13
490
651
341
223
224
186
197
263
266
281
334
313
344
193
86
241
312
279
92
455
354
91
125
202
99
25
12
344
378
125
17
0
303
439
153
258
309
230
139
42
34
64
19
58
8
530530029
530530031
530611007
540511002
540690010
47.186
47.266
48.056
39.916
40.115
-122.452
-122.386
-122.176
-80.734
-80.701
97
29
6
245
262
127
128
129
130
Table S3. IMPROVE Sites Used in the Analysis.
Site ID
ACAD1
ADPI1
AGTI1
AREN1
BADL1
BALD1
BAND1
BIBE1
BLIS1
BLMO1
BOAP1
BOLA1
BOND1
BOWA1
BRCA1
BRID1
BRIG1
BRIS1
BRMA1
CABA1
CABI1
CACO1
CACR1
CADI1
CANY1
CAPI1
CEBL1
CHAS1
CHER1
CHIR1
CLPE1
Latitude
44.3771
42.0912
33.4636
39.9232
43.7435
34.0584
35.7797
29.3027
38.9761
43.7158
33.8695
42.85
40.052
47.9466
37.6184
42.9749
39.465
30.1086
44.1074
43.8325
47.9549
41.9758
34.4544
36.7842
38.4587
38.3022
38.7701
28.7484
36.9562
32.0094
44.3335
Longitude
-68.261
-77.2099
-116.971
-77.3079
-101.941
-109.441
-106.266
-103.178
-120.103
-96.1913
-106.852
-109.64
-88.3733
-91.4955
-112.174
-109.758
-74.4492
-89.7617
-70.7292
-70.0644
-115.671
-70.0242
-94.1429
-87.8501
-109.821
-111.293
-99.7634
-82.5549
-97.0313
-109.389
-106.956
Elevation (m)
157
512
507
267
736
2508
1988
1066
2130
473
1389
2296
263
526
2481
2626
5
-7
233
26
1441
49
683
191
1798
1896
665
4
342
1554
2470
9
COGO1
COHU1
CORI1
CRES1
CRLA1
CRMO1
DENA1
DEVA1
DOME1
DOSO1
DOUG1
EGBE1
ELDO1
ELLI1
EVER1
FLAT1
FOPE1
FRRE1
GAAR1
GAMO1
GICL1
GLAC1
GRBA1
GRCA2
GRGU1
GRRI1
GRSA1
GRSM1
GUMO1
HACR1
HALE1
HAVO1
HECA1
HEGL1
HOOV1
IKBA1
INGA1
ISLE1
JARB1
JARI1
JOSH1
KAIS1
KALM1
LABE1
LASU2
45.5693
34.7852
45.6644
41.7627
42.8958
43.4605
63.7233
36.5089
35.7278
39.1053
31.3492
44.2312
37.7009
36.0853
25.391
47.7734
48.308
39.7058
66.9025
46.8262
33.2204
48.5105
39.0052
35.9731
44.3082
43.9373
37.7249
35.6334
31.833
20.7585
20.8086
19.4309
44.9702
36.6138
38.0881
34.3405
36.0778
47.4596
41.8926
37.6266
34.0695
37.2207
42.552
41.7117
40.6932
-122.21
-84.6265
-121.001
-102.434
-122.136
-113.555
-148.967
-116.848
-118.138
-79.4261
-109.54
-79.7832
-94.0348
-99.9354
-80.6806
-114.269
-105.102
-79.0122
-151.517
-111.711
-108.235
-113.997
-114.216
-111.984
-71.2177
-91.4052
-105.519
-83.9416
-104.809
-156.248
-156.282
-155.258
-116.844
-92.9221
-119.177
-111.683
-112.129
-88.1491
-115.426
-79.5125
-116.389
-119.155
-124.059
-121.507
-92.0059
230
735
178
1207
1996
1817
658
130
927
1182
1230
251
297
697
1
1580
638
767
196
2387
1775
975
2065
2267
453
370
2498
810
1672
2158
1153
1258
655
404
2560
1297
1166
182
1869
289
1235
2597
80
1459
229
10
LAVO1
LIGO1
LIVO1
LOST1
LYBR1
MACA1
MAKA1
MAVI1
MEAD1
MELA1
MEVE1
MING1
MKGO1
MOHO1
MOMO1
MONT1
MOOS1
MORA1
MOZI1
NEBR1
NOAB1
NOCA1
NOCH1
OKEF1
OLYM1
ORPI1
PACK1
PASA1
PEFO1
PENO1
PINN1
PMRF1
PORE1
PRIS1
QUCI1
QURE1
QUVA1
RAFA1
REDW1
ROMA1
ROMO1
SACR1
SAFO1
SAGA1
SAGO1
40.5398
35.9723
38.5346
48.6419
43.1482
37.1318
48.3718
41.3309
36.0193
48.4871
37.1984
36.9717
41.4269
45.2888
41.8214
47.1222
45.1259
46.7583
40.5383
41.8888
44.7448
48.7316
45.6495
30.7405
48.0065
31.9506
42.8619
48.3877
35.0777
44.948
36.4833
44.5284
38.1224
46.6964
39.9428
42.2985
33.2939
34.7339
41.5608
32.941
40.2783
33.4598
39.9791
34.2969
34.1939
-121.577
-81.9331
-86.2604
-102.402
-73.1268
-86.1479
-124.595
-70.7846
-114.068
-104.476
-108.491
-90.1432
-80.1453
-121.784
-73.2973
-113.154
-67.2661
-122.124
-106.677
-100.339
-109.382
-121.065
-106.557
-82.1283
-122.973
-112.802
-71.8786
-119.927
-109.769
-68.6479
-121.157
-72.8688
-122.909
-68.0333
-81.3378
-72.3346
-111.286
-120.007
-124.084
-79.6572
-105.546
-104.404
-95.5682
-118.028
-116.913
1732
968
281
696
1015
235
-999
2
902
606
2172
111
379
1531
521
1282
77
439
3243
883
2482
568
1283
48
599
504
695
1627
1766
45
302
401
97
165
366
317
661
956
243
4
2760
1072
293
1791
1726
11
SAGU1
SAMA1
SAPE1
SAWE1
SAWT1
SENE1
SEQU1
SHEN1
SHMI1
SHRO1
SIAN1
SIKE1
SIME1
SIPS1
SNPA1
STAR1
SULA1
SWAN1
SYCA1
TALL1
THBA1
THRO1
THSI1
TONT1
TRCR1
TRIN1
TUXE1
ULBE1
UPBU1
VIIS1
VILA1
VOYA2
WEMI1
WHIT1
WHPA1
WHPE1
WHRI1
WICA1
WIMO1
WRIG1
YELL2
YOSE1
ZICA1
32.1746
30.0926
36.0139
32.2486
44.1705
46.2889
36.4894
38.5229
37.3038
35.3937
34.0908
32.0574
55.3255
34.3433
47.422
45.2249
45.8598
35.451
35.1406
38.4341
44.6634
46.8948
44.291
33.6548
62.3153
40.7864
59.9925
47.5823
35.8258
18.3363
40.969
48.4126
37.6594
33.4687
46.6243
36.5854
39.1536
43.5576
34.7323
34.38
44.5653
37.7133
37.1983
-110.737
-84.1614
-106.845
-111.218
-114.927
-85.9503
-118.829
-78.4348
-107.484
-82.7744
-110.942
-92.435
-160.506
-87.3388
-121.426
-118.513
-114
-76.2075
-111.969
-96.5602
-105.287
-103.378
-122.043
-111.107
-150.316
-122.805
-152.666
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941
7
2935
714
1990
214
519
1079
2351
1617
1600
45
57
286
1049
1259
1895
-3
2046
390
1195
852
885
775
155
1014
15
891
722
51
371
429
2750
2063
1827
3366
3413
1296
509
2106
2425
1603
1215
131
12