EPA-600/4-77-016
April 1977
Environmental Monitoring Series
DIURNAL VARIATIONS IN TRAFFIC FLOW AND
CARBON MONOXIDE CONCENTRATIONS
Environmental Sciences Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
esearch Triangle Park, North Carolina 27711
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RESEARCH REPORTING SERIES
Research reports of the Office of Research and Development, U.S. Environmental
Protection Agency, have been grouped into nine series. These nine broad cate-
gories were established to facilitate funher development and application of en-
vironmental technology. Elimination of traditional grouping was consciously
planned to foster technology transfer and a maximum interface in related fields.
The nine series are:
1. Environmental Health Effects Research
2. Environmental Protection Technology
3. Ecological Research
4. Environmental Monitoring
5. Socioeconomic Environmental Studies
6. Scientific and Technical Assessment Reports (STAR)
7. Interagency Energy-Environment Research and Development
8. "Special" Reports
9. Miscellaneous Reports
This report has been assigned to the ENVIRONMENTAL MONITORING series.
This series describes research conducted to develop new or improved methods
and instrumentation for the identification and quantification of environmental
pollutants at the lowest conceivably significant concentrations. It also includes
studies to determine the ambient concentrations of pollutants in the environment
and/or the variance of pollutants as a function of time or meteorological factnrc
This document is available to the public through the National Technical Informa-
tion Service, Springfield, Virginia 22161.
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EPA-600/4-77-016
April 1977
DIURNAL VARIATIONS IN TRAFFIC FLOW
AND CARBON MONOXIDE CONCENTRATIONS
Gerard A. DeMarrais
Meteorology and Assessment Division
Environmental Sciences Research Laboratory
Research Triangle Park, N.C. 27711
ENVIRONMENTAL SCIENCES RESEARCH LABORATORY
OFFICE OF RESEARCH AND DEVELOPMENT
U.S. ENVIRONMENTAL PROTECTION AGENCY
RESEARCH TRIANGLE PARK, N.C. 27711
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DISCLAIMER
This report has been reviewed by the Office of Research and Develop-
ment, U.S. Environmental Protection Agency, and approved for publication.
Mention of trade names or commercial products does not constitute endorse-
ment or recommendation for use.
Mr. DeMarrais is a meteorologist in the Meteorology and Assessment
Division, Environmental Sciences Research Laboratory, Environmental
Research Center, Research Triangle Park, N.C. 27711. He is on assign-
ment from the National Oceanic and Atmospheric Administration, U.S.
Department of Commerce.
11
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ABSTRACT
Traffic count and carbon monoxide (CO) data for January and July from
three states are compared in order to reveal any diurnal variations in the
two measurements. The diurnal patterns for the 18 traffic count stations
indicate that there are average patterns of traffic flow that are represen-
tative of all stations for periods of one month. Comparisons of data for
the 36 CO monitoring stations show correlations which vary from large posi-
tive to large negative. However, eliminating a few monitoring stations
which show relatively poor correlations yields groups within each state
that have consistent patterns. The diurnal variations in CO concentrations
are not well correlated with traffic patterns. Part of the poor correla-
tion appears to be due to the diurnal variations in vertical mixing and
wind speeds and part to the exposures and locations of the sampling
instruments.
iii
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CONTENTS
Abstract iii
Figures vi
Tables viii
1. Introduction 1
2. Conclusion 2
3. Methodology 3
Traffic count data 3
Carbon monoxide concentrations 3
Traffic densities versus concentrations 4
Analyses of data 4
4. Results 5
Traffic counts 5
CO concentrations 6
Intermonth correlation of CO concentrations 9
Comparison of traffic and CO'concentrations 9
5. Summary 11
References 13
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FIGURES
Number Pa9e
1 Diurnal variation in percentage of 24-hour traffic flow for
each hour at 18 stations during January 15-16
2 Diurnal variation in percentage of 24-hour traffic flow for
each hour at 18 stations during July 17-18
3 Diurnal variation in average traffic, 18 stations (vertical
lines show ranges of +_ 1 standard deviation 19
4 Diurnal variation in CO concentrations, Colorado stations,
January (numbers in parentheses are average hourly concent-
rations in ppm) 20
5 Diurnal variations in CO concentrations, Colorado stations,
July (numbers in parentheses are average hourly concen-
tration? in ppm) 21
6 Diurnal variations in CO concentrations, Maryland stations,
January (numbers in parentheses are average hourly concent-
in ppm) 22
7 Diurnal variations in CO concentrations, Maryland stations,
July (numbers in parentheses are average hourly concent-
rations in ppm) „ 23
8 Diurnal variations in CO concentrations, New Jersey stations,
January (numbers in parentheses are average hourly concent-
rations in ppm) „ 24-25
9 Diurnal variations in CO concentrations, New Jersey stations,
July (numbers in parentheses are average hourly concent-
rations in ppm) 26-27
10 Diurnal variations of CO concentrations, composite for six
Colorado stations (vertical lines show ranges of + 1
standard deviation) ~~ 28
11 Diurnal variation of CO concentrations, composite for selected
Maryland stations (vertical lines show ranges of +_ 1
standard deviation) ~~ 29
VI
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FIGURES
Number Page
12 Diurnal variation of CO concentrations, composite for selected
New Jersey stations (vertical lines show ranges of +_
standard deviation) 30
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TABLES
Number Pa9e
1 Types and Locations of Traffic Counting Stations 31
2 Description of CO Monitoring Sites 32-36
3 Correlations of Less Than 0.90 in Diurnal Variations in Traffic
for January 37
4 Correlations of Less Than 0.90 in Diurnal Variations in Traffic
for July, 18 Stations3 ....... 38
5 Correlation Between January and July Diurnal Variations in
Traffic at Individual Stations8 39
6 Bivariate Correlations of Diurnal Variations in CO Concentrations
at Colorado Stations, January 40
7 Bivariate Correlations of Diurnal Variations in CO Concentrations
Colorado Stations, July 41
8 Bivariate Correlations of Diurnal Variations in CO Concentrations
Maryland Stations, January ..... 42
9 Bivariate Correlations of Diurnal Variations in CO Concentrations,
Maryland Stations, July 43
10 Bivariate Correlations of Diurnal Variations in CO Concentrations
at 13 Selected New Jersey Stations, January 44
11 Bivariate Correlations of Diurnal Variations in CO Concentrations
at Five Selected New Jersey Stations, January. 45
12 Bivariate Correlations of Diurnal Variations in CO Concentrations
at 13 Selected Stations July . 46
13 Bivariate Correlations of Diurnal Variations in CO Concentrations
at 6 Selected New Jersey Stations, July 47
14 Correlations of January and July Diurnal Variations of CO
Concentrations 48
15 Correlations of Diurnal Variations, January and July 49
v i i i
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1. INTRODUCTION
The major source of man-made carbon monoxide (CO) in the atmosphere is
the automobile. In evaluating the CO air pollution problem, attempts have
been made to correlate CO concentrations with traffic density (1-5). The
findings of a short study (T) conducted in ar. unidentified city in the north-
eastern United States during the summer of 1959, and a year-long study
(2) in 1964-1965 in Frankfurt/Main, Germany, found that the correlations
between CO concentrations and traffic density were relatively high. A
more recent study by the author (3) using data for 1973 from the Baltimore
area showed correlations less than 0.50 between hourly CO concentrations
and traffic counts. Since the results of this third study were inconsistent
with those of the two earlier studies a large volume of CO concentration
and traffic count data were sought. The objective was to determine the
diurnal patterns of CO concentration and traffic at a number of sites
and then compare the patterns. Meteorological phenomena are discussed
only when they obviously caused an anomaly or when they did not appear
to be the cause of a discrepancy. A better understanding of the combined
effects of traffic and meteorology on CO concentrations is being sought
in a separate study in which wind data from the individual monitoring sites,
area mixing height data, CO concentrations from four Maryland sites, and
local traffic counts are being analyzed.
To minimize the possibility of differences in CO concentrations being
attributed to differences in sampling procedures or times, new data, which
were collected in a standard manner, were sought for this study. Each
state air pollution control agency is now required by Federal regulations
(6) to continuously collect hourly CO data at stations within its boundary
according to a standard procedure. Highway agencies throughout the United
States also collect hourly traffic data at a number of permanent counting
stations. In order to determine whether there might be differences in
diurnal patterns of CO concentrations between states or possibly between
regions, data from the air pollution control agencies and highway depart-
ments of the States of Colorado, Maryland, and New Jersey were obtained.
The National Air Data Bank (NADB) of the U.S. Environmental Protection
Agency, (EPA), which stores air pollution data gathered from throughout
the United States, provided the carbon monoxide information for the three
states considered in the study.
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2. CONCLUSIONS
Traffic at 18 sites, which ranged from resorts in Colorado to the
beltline in Baltimore, showed relatively consistent patterns in diurnal
variations. By comparison, the diurnal variation in CO concentrations
at 36 sites showed large differences and were not well-correlated with
traffic patterns. Much of the poor agreement was due to: 1) diurnal
variations in vertical mixing and wind speed and 2) the differences in
the locations of the air sampling intakes with regard to sources (tail-
pipes). The poor agreement due to intake locations will be eliminated
when agencies comply with the U.S. Environmental Protection Agency
guidelines (12) for siting CO instruments; more readily comparable CO
data will then be available for correlating with traffic and meteorology
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3. METHODOLOGY
TRAFFIC COUNT DATA
The traffic data collection programs of Colorado, Maryland, and New
Jersey differ slightly, although all three states use automatic counters at
permanent stations. In Colorado, data are continuously collected for
opposing lanes of traffic and the total count is listed for each hour. In
Maryland, the traffic for each direction is recorded separately
on Interstate highways, but only the total is recorded on other roads.
In New Jersey, traffic is recorded for one direction at a time; every
week or two the counters are moved from one side of the road to the other.
Hourly traffic counts for Colorado (7) were obtained for four urban
stations in the Denver area, an urban station in Pueblo, and two stations
in resort areas. Of the 39 available Maryland stations (8), the following
were selected: two on major highways between Baltimore and Hashington,
two on the beltline around Baltimore, two near a small city, one at an
ocean resort, and one at a mountain resort. The available New Jersey
data (9) consisted of one station on a truck route in Jersey City, one
on a highway in a resort city, and one on a road on the outskirts of a
small city. A brief description of each station is given in Table 1.
CARBON MONOXIDE CONCENTRATIONS
The CO data collection programs of the three states are similar
because all states are required to summarize the data in an identical
format for submission to the NADB.
Hourly CO concentrations for Colorado were obtained for three stations
in the downtown Denver area and three in areas that were 5 to 6 miles from
downtown Denver. In Maryland, data were obtained for one site in Baltimore;
four in Washington, DC, suburbs; four in Baltimore suburbs; and one in
Cumberland in the northwest part of the state. New Jersey stations
included: eight in the metropolitan New York area--Bayonne, Elizabeth
(Broad St.), Elizabeth (Turnpike), Hackensack, Jersey City, Newark,
Paterson, and Perth Amboy; three in coastal areas--Asbury, Atlantic City,
and Toms River; two in the Philadelphia-Camden conplex--Camden (N. 6th St.)
and Camden (Copewood); one in Trenton; and six in smaller cities and towns
throughout the state—Burlington, Camden (Ancora), Freehold, Paulsboro,
Penns Grove, Phillipsburg, and Somerville. A brief description of each
station is shown in Table 2. The intakes (third column of Table 2) for
the sample air are located from 10 to 17 feet above the ground over a
trailer or out over city streets at a majority of the stations.
The Colorado and Maryland networks are predominantly trailer-type
operations, but most of the New Jersey data are collected by instruments
exposed over city streets. The intakes of the New Jersey instruments
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are generally much closer to the traffic, and the stations except Camden 3
(Ancora) are in metropolitan or urban areas. Another major difference in
intake exposures is that a majority of the Maryland stations have metal
boxes (approximately (I1 x I1 x 2') covering the intakes (opening is
toward the ground). Thus there may be large differences in concentrations
patterns because: 1) New Jersey collects at sampling sites which for the
most part are in confined street canyons very close to the traffic;
2) Colorado collects air samples over trailers parked in open lots some
distance from traffic; and 3) Maryland uses trailers in open lots and
restricts the free air flow, at most stations, with metal boxes.
TRAFFIC DENSITIES VERSUS CONCENTRATIONS
In each of the three states, no permanent counting station is closer
than 2 miles to a CO monitoring station. Because high CO concentrations
are localized phenomenon (10), data from individual traffic count sites
and CO monitoring stations are not directly comparable. However, pre-
dominant statewide patterns of the diurnal variations of CO concentrations
and traffic density can be compared.
ANALYSES OF DATA
The distribution of traffic count and CO monitoring stations provides
for an analysis of spatial similarities and differences. For seasonal
comparisons January and July data are examined. To indicate how the
absolute values differed among the stations, the average daily traffic
(ADT) for each counting station and the average hourly CO concentration
in parts per million (ppm) for each monitoring station are shown in
graphical presentations. Each hourly value is plotted as a point at the
midpoint of the observation period. All the data were normalized before
being graphically presented or analyzed; all hourly values were converted
to percentage of the 24-hour total.
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4. RESULTS
TRAFFIC COUNTS
The diurnal variations of traffic during January for the 18 counting
stations are shown in Figure 1. A consistent feature of the distribution is
the occurrence of a traffic peak late in the afternoon. In addition, two-
thirds of the stations show pronounced morning peaks. All stations have
marked increases in volume in the early morning, and a few show the increase
persisting until the afternoon peak is attained. All stations also show a
steep, generally steady decline in traffic density between the afternoon
peak and midnight. All three of the mountain resort stations (C7, C39, M35)
are single-peak stations, but both ocean resorts (M17, NJ208) show two
marked peaks, similar to those found in the heavy traffic stations (C22,
M31, M32) in metropolitan areas. Only 30 to 40 percent of the total 24-
hour traffic is counted before noon at all of the stations. The ADT ranges
from 1,137 at a mountain resort in Colorado (C39) to 94,818 in downtown
Denver (C22).
In July, (Figure 2), all stations except one (M25) experience greater
ADT than they do in January (see Figure 1). The average increase in volume
from January to July at the 13 nonresort stations in 19 percent; whereas, at
the five resort stations it is 200 percent. The ADT during July for all
stations ranges from 5,796 to 115,812. Although features of the January
distribution reoccur in July, they appear in a modified form. The peak
hourly flow still occurs in the afternoon at all stations except Ml7 but
is not as marked as in January. At most stations, the morning peak is
also lower. The sharp increase in traffic in the morning and the steep
decline during the evening (6 PM to 9 PM) are almost as prominent as they
were in January. At all of the resort stations except NJ208, the traffic
count is high from late in the morning until 4 to 5 PM. Overall, the
general traffic patterns at the 13 nonresort sites do not vary much
between January and July.
To examine the interrelationships among the traffic count distributions,
the data in Figures 1 and 2 were statistically analyzed. The bivariate
correlation analyses of the January data showed that 75 percent of the
paired stations were correlated at the 0.90 level or greater. Correlations
that were less than 0.90 are shown in Table 3. The lower valued correla-
tions are associated with the New Jersey sites and the resort stations.
Even the poorest correlation (0.78 between MJ409 and C39) means that
more than 60 percent of the variance at the resort in Colorado can be
explained by the variations at a suburban site in New Jersey. It is
concluded, therefore, that traffic patterns are similar among these
18 diverse stations. The bivariate analyses of the July data showed
that 80 percent of the correlations were 0.90 or greater. Table 4 shows
the correlations that were less than 0.90. The lower-valued correlations
generally occur where heavy urban traffic is compared with resort traffic
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and with the suburban traffic of the small New Jersey city. The poorest
correlation in July (0.76) occurs between the mountain resort in Maryland
and an interstate highway location in Denver. In this case, 58 percent
of the variance at one place is explained by the variation at the other.
Again, traffic patterns appear fairly consistent among the 18 stations.
The seasonal variations at the individual stations were checked by
comparing the diurnal variations of January and July. The results are
shown in Table 5. The poorest correlation is 0.87 and a majority of
the correlations are 0.97 or more. Thus, winter and summer patterns are
very similar for these stations.
Because the statistical results indicate that the monthly average daily
traffic pattern varies little from station to station, the data for the 18
stations were combined. The composite traffic patterns for January and
July, including standard deviations, are quite similar (see Figure 3).
The standard deviations indicate that the greatest spatial variations occur
around the time of the morning peak traffic flow in both months and the
afternoon peak flow in January.
CO CONCENTRATIONS
The results of the CO analyses showed more intrastate than interstate
consistency. The results for each state, therefore, are considered sepa-
rately.
The January diurnal variations of CO concentrations for the six stations
in Colorado (Figure 4) show a fairly consistent pattern. There are two
peaks in concentrations that approximately coincide with times of peak
traffic flow (see Figure 3). The average hourly concentrations, shown
in parentheses in the figure, range from 3.1 to 7.8 ppm. The morning
peak in concentrations is as high or higher than the afternoon peak at
all stations. At half of the stations, the midday concentrations and the
lowest nighttime concentrations are very similar. This phenomenon of
concentrations being the same at night and midday was common (it occurred
at Maryland and New Jersey stations) and is attributed to the diluting
capacity (vertical mixing and wind speed) of the atmosphere. Vertical
mixing spreads emissions through a surface-based layer which varies in
depth from a minimum during the nighttime hours to a maximum in late
afternoon or evening and wind speed transports and spreads emissions down-
wind and is also at a minimum at night and maximum in the afternoon or
evening. During midday the diluting capacity is near the maximum so the
concentrations are reduced to low values. There are seasonal and spatial
differences in these mixing height and wind speed patterns (11) but the
timing of the maximum and minimum dilution change only a little. The
cross-relation analyses of station data show that the Wei by station is
the least correlated with other stations (Table 6). Excluding Welby,
all the correlations are 0.61 or better. (By comparison, the poorest
correlation in January among the seven traffic counting stations in
Colorado was 0.85.)
The July diurnal variations of CO concentrations for the Colorado
stations, (Figure 5) show no consistent pattern. The average hourly
concentrations, except at Colfax, are at most half of the January levels,
ranging from 1.1 to 3.9 ppm. Although there is a peak in concentration
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at 6 to 7 AM at five of the six stations, the afternoon concentration
peak corresponding to the peak traffic hours is seen at only three
stations. The morning peaks in July are displaced to slightly earlier
times than those of January (Note that these CO concentrations are
plotted at standard times and in July daylight times were observed).
At five stations, marked peaks occur between 8 and 11 PM. These time
delayed peaks in concentrations in July were common (they occurred at
Maryland and New Jersey stations) and are attributed to meteorological
causes; the principal causes of dilution, vertical mixing and wind
speed, are at their maximums (11) at the time of peak traffic flow and
do not subside until evening. At Julian, the concentration is consider-
ably Tower in the middle of the day than it is at night, but the reverse
is true at Arvada, Broadway, Colfax, and Huron. The correlations for
July (see Table 7) show that the distributions are much less correlated
than they were in January, with most correlations less than 0.60 and
many of these negative. Since the traffic patterns are fairly consistent
(Table 4) one might suspect that variations in meteorology (mainly
vertical mixing and wind speed) might cause these relatively poor
correlations. However it is difficult to believe that differences
in the meteorology in such a small area (all of the Colorado stations
are within six miles of downtown Denver) could be large enough to
account for inconsistent correlations.
In January diurnal variations in CO concentrations for the 10
stations in Maryland (Figure 6) are very similar to the January variations
in Colorado. There are two peaks in concentrations that approximately
coincide with the peaks in traffic flow. The average hourly concen-
trations, which range from 0.9 to 3.7 ppm, are considerably less than
those for Colorado. At all but one of the sampling sites, the morning
peaks are markedly higher than the afternoon peaks and the lowest
daytime concentrations are very similar to those at night. As shown
in the figure, the distributions at Riviera Beach are obviously incon-
sistent with those from the remaining nine stations and, therefore,
are rot included in the summary statements that follow. Results of
the regression analyses of these January data (Table 8) show that the
variations for Riviera Beach are very poorly correlated with the
variations for the other stations. In general, the correlations among
the other nine stations are high and comparable to the January correla-
tions found in Colorado.
The July variations in CO concentrations for the Maryland stations
(Figure 7) show a fairly consistent pattern when the results from Riviera
Beach are not considered. The average hourly concentrations, which range
from 0.5 to 2.9 ppm, are generally slightly lower than they were in
January. The morning peaks are displaced to earlier times (the morning
rush hour is earlier because of daylight saving time) and are smaller
than they were in January. The afternoon peaks are displaced to much
later times, generally 8 to 10 PM; there is very little indication of
a peak in CO concentrations occurring at the time of peak traffic flow.
At seven of the nine stations, the afternoon peak concentrations are
higher than the morning peak concentrations; during January the peaks
were higher in the morning. At a majority of the stations, the midday
concentrations are lower than the lowest concentrations that occur
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at night. The bivan ate analyses of the July data (Table 9) shew
similar results to those ^cr January. Piviera Beach data are, again,
very poorly correlated. The correlations among the other nine stations
are comparable tc those for January at the Maryland stations but are
generally greater than the correlations shown in July in Colorado.
The January diurnal variations in CO concentrations for the 20
stations in New Jersey (Figure £) are not similar to the January varia-
tions for Colorado and Maryland. Close inspection indicates that
increases in concentration do occur at the times of peak traffic volumes
at most stations. These January peaks are not as pronounced as those
for Colorado and Maryland, however. The average concentrations range
from 1.0 to 8.7 ppm and span the relatively high values of Colorado
and low values of Maryland. The Maryland data for January consistently
showed that the highest concentrations occurred during the morning peak
traffic flow; whereas, this phenomenon occurs at only six stations in
New Jersey. Again in contrast to the Maryland data, the New Jersey
data do not show similar values in the middle of the day and the early
morning. The regression analyses demonstrate that about two-thirds of
the stations correlate reasonably well (all pairings were 0.72 or greater.
Table 10 lists the stations showing correlations of 0.72 or greater while-
Table 11 lists trhe 5 stations (in the vertical) and values associated
with poorer correlations (in Figure 8 the stations showing correlations
of 0.72 or greater are marked with an asterisk and the poorer with two
asterisks). Note that four of the five stations showing poorer
correlations also show relatively low average hourly concentrations.
The variations of CO concentrations for the New Jersey stations
(Figure 9) show less consistency in July than in January and are thus
similar to the Colorado and Maryland data. The values of average hourly
concentration range from 1.3 to 7.3 ppm, a slightly lower average concen-
tration than in January. It is interesting that 10 stations show increases
and 10 show decreases in average hourly concentration from January to
July. Features that do stand out in the July diurnal variations are:
1) at a majority of the stations, there is an increase in early morning
concentrations that appears associated with the morning peak traffic flow;
2) at seven stations, the lowest concentrations occur in the middle of
the day; 3) no increase in concentration cccurs at the time of increased
traffic (4 to 5 PM standard time); and 4) at a majority of stations,
as with the stations in Colorado and Maryland, there are late evening
(7 to 10 PM) peaks in concentrations. The July statistics for the
stations that showed good and poor correlations in January are shown
in Tables 12 and 13, respectively. It is obvious that the correlations
from January to July decrease markedly. A sixth station, Camden 3,
is added to the poorly correlated, group because it showed correlations
ranging from 0.69 to -0.72.
Five of these New Jersey stations, Bayonne, Elizabeth 1 and 2,
Jersey City, and Newark, are in a five mile square area and three show
well correlated data with other stations while two show poorer correla-
tions. Again it is difficult to believe that meteorological variations
from place to place would be great enough to cause these large differences
in the small area.
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INTERMONTH CORRELATION OF CO CONCENTRATIONS
Because the bivariate analyses showed that the correlations between
stations decreased from January to July, a month-to-month comparison
was made at each station. The resulting comparisons, Table 14, show:
1. No correlations better than 0.70 among the Maryland stations
2. Correlations that range from 0.55 to 0.86 at the Colorado sites
3. Correlations that range from -0.26 to 0.94 in New Jersey
COMPARISONS OF TRAFFIC AND CO CONCENTRATIONS
The composite distribution for the six CO monitoring stations in
Colorado for January and July are presented in Figure 10. The vertical
line at the middle of the hour shows the range of one standard deviation.
The January data show a smooth two-peak distribution with the peaks
appearing to coincide or follow within 1 hour of the peak in traffic
flow (see Figure 3). The morning peak CO concentration is 50 percent
greater than the afternoon peak concentration although the traffic data
show the afternoon peak to be half again as great as the morning peak.
The lower concentrations with the greater traffic flow (greater emissions)
is attributed to the meteorology; in the morning, vertical mixing and
wind speed, the causes of dilutions, are at their minimums and in the
afternoon at their maximums. The standard deviations are relatively
small during the night and early morning hours, indicating that there
is generally little spatial variation from this CO pattern. The daytime
standard deviations are moderate, indicating there is a fair amount of
spatial variation from the composite pattern. The July pattern is not
as smooth as that for January, but the CO peak associated with the heavy
morning traffic is again evident. A slight peak occurs in the afternoon
just before the time of peak traffic flow; a dip in concentration levels
is then evident just before the primary evening peak concentration occurs
at between 8 and 9 PM (9 to 10 PM daylight time). The standard deviations
are relatively large, indicating considerable spatial variation from
the average July pattern.
The composite results for the nine selected CO monitoring stations
in Maryland (Riviera Beach data are not included in the average) for
January and July are seen in Figure 11. These January data show a
smooth two-peak distribution similar to those for Colorado. Each CO
peak coincides or follows within 1 hour of the peak in traffic density.
The morning CO concentration peak is 50 percent larger than the after-
noon peak; the direct opposite is true of the comparable traffic peaks.
Unlike the Colorado results, the Maryland data show concentrations as
low during the day as they are at night. The standard deviations indicate
that there is a large amount of spatial variation at the time of the
morning peak and a fair amount at other times. The July pattern, like
the January pattern, has two peaks. The morning peak, however, occurs
earlier and is diminished in size, and the evening peak occurs later
and is greater. Compared to the July CO pattern for Colorado, the
Maryland pattern is more systematic. Like the Colorado results, the
peak afternoon CO concentration occurs several hours after the peak
in traffic flow. In addition, at the time of the peak traffic, no
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marked increase in CO concentration occurs. In the middle of the
day, concentrations are very similar to the lowest nighttime values.
The standard deviations are large after 7 PM, indicating that there is
a considerable amount of spatial variation in the evening.
The composite results for the 15 selected CO monitoring stations
in New Jersey (the five stations with poor correlations are not included)
are seen in Figure 12. Like the Colorado and Maryland data for January,
the New Jersey data show a smooth two-peak distribution, although the
peaks are less pronounced. The peaks do coincide with the peaks in
traffic flow, however. Unlike the Maryland data, the New Jersey data
show the daytime concentrations remaining high after the morning peak
and always being about 2.5 times as great as the lowest morning values.
The afternoon peak is higher in Mew Jersey; the morning peak was higher
in Colorado and Maryland. The smal-1 standard deviations indicate that
the spatial variations are relatively small, however. The July data,
like those for Colorado and Maryland, show a less systemized variation
than the January data. These July data show three slight peaks: one
with the morning peak traffic; the second about the time of the afternoon
peak traffic; and the final several hours after the peak traffic flow.
The second and third peaks are similar to the July afternoon peaks in
Colorado. The standard deviations are larger in July than in January,
indicating that the July pattern shows larger spatial variations.
The numerical correlations of the statewide variations of CO
concentrations with the traffic pattern averaged for the 18 counting
stations vary over a large range (see Table 15). In January, the
poorest correlation, 0.25, is associated with the Maryland CO data
and the best, 0.94, with the New Jersey data. The indication is that
traffic variations explain only 6 percent of the CO variation in
Maryland, 27 percent in Colorado, and 88 percent in Mew Jersey. In
July, the correlation between traffic and Colorado Co variations
increases, but in the other two cases it decreases. The Maryland data,
in fact, even show a negative correlation. The interstate CO comparisons
in Table 15 show wide variations in correlations in both January and
July. In January, the correlation between Maryland and New Jersey data
is only 0.42, and in July it decreases to 0.31. In July, the variation
in one state can be used to explain less than 10 percent of the
variation in the other. With the states being so close to one another,
a better correlation was anticipated. The interesting phenomena in
the Colorado-Maryland and Colorado-New Jersey correlations is the exchange
of absolute values from January to July. It is strange that the variations
in CO in Colorado can be used to explain 72 percent of the variation in
Maryland in January and only 43 percent in July; for New Jersey the
Colorado concentrations explain 41 percent in January and better than
75 percent in July.
10
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5. SUMMARY
The results of the study are summarized in the following paragraphs:
The hourly variations of ADT at 18 permanent counting stations located
in various types of areas in three states during January and July showed
considerable spatial and temporal consistency even though the ADT counts
ranged from 1,000 to 100,000 vehicles. For periods of a month, there
are average patterns of diurnal variation of traffic flow that are
representative of all stations.
The diurnal variations of CO concentrations for 36 monitoring
stations, located for the most part in urban areas or near well-traveled
roads in the three states, showed correlations that varied from large
positive to large negative when one-to-one comparisons were made.
Although comparisons of data from all 36 monitoring stations
showed correlations varying over a large range, intrastate comparisons
showed smaller ranges in July and much smaller ranges in January.
Eliminating stations that showed poor correlations yielded groups within
each state that showed consistent patterns.
The Maryland stations generally showed lower average hourly concen-
trations than the Colorado and New Jersey CO monitoring stations. The
Maryland stations have metal boxes over their intakes that may account
for the differences with the Colorado stations. The New Jersey stations
are generally closer to the traffic than the Maryland stations—a fact
that may account for the higher observed values. Before attempting
to correlate traffic and meteorology with CO concentrations in various
states, it would be desirable to have the siting of instruments
standarized. The U.S. Environmental Protection Agency has published
guidelines (12) for siting instruments and with time state and local
agencies may comply with these guidelines and provide comparable data.
The relatively high CO concentrations that occur late in the
day in July were an unexpected anomaly. Because they occurred in so
many places, there is little doubt that they are real. This time delay
in peak concentration is attributed to the diurnal variations in
vertical mixing and wind speed. These pheonmena provide for
maximum dilution at the time of peak traffic flow and at later
times, when the speeds and mixing heights are much lower, concentrations
increase.
The comparison of the January versus July CO variations at the
individual stations showed: 1) poor correlations in Maryland (all
less than 0.70); 2) correlations in Colorado ranging from 0.55 to
0.86; and 3) correlations ranging from -0.26 to 0.94 in New Jersey.
These correlations are much more erratic than the comparable traffic
correlations, which ranged upward from 0.87 with a majority being
greater than 0.96. It appears there is a significant seasonal change
in CO concentrations.
11
-------
In comparing the January diurnal variations of CO concentrations
and traffic volume, there was an obvious correlation of the timing of
the diurnal peaks of each. There was not a good one-to-one correlation
between concentrations and traffic density, however, because the traffic
pattern showed an afternoon peak that was twice as great as the morning
peak. In addition, Colorado and Maryland concentration patterns showed
peaks in the afternoon that were half as great as those in the morning.
The diurnal variations in vertical mixing and wind speed partially
account for this apparent anamoly. These phenomena allow for minimum
dilution of emissions with peak morning traffic and maximum dilution
with peak afternoon traffic.
In Maryland in January and July and at three stations in Colorado
in January and seven stations in Mew Jersey in July, the midday concen-
trations were consistently as low as the lowest nighttime values.
There was almost an order of magnitude difference in traffic volume at
the two different times. Traffic density and concentration were very
poorly correlated at these stations and times. The diurnal variation
of meteorological parameters are the cause of this discrepancy.
Emissions are diluted very little at night because vertical mixing and
wind speed are at their minimums and around midday emissions are
readily spread through much larger volumes as vertical mixing and wind
speed are approaching maximums.
Even when the CO data were compiled into average diurnal variations
for each state, the correlations between traffic and CO concentrations
were still erratic; in Colorado in January, 27 percent of the variation
in CO concentrations was explained by the traffic and in July 33
percent; in Maryland the correlation was 0.25 in January and -0.19
in July; in New Jersey 88 percent of the variation in CO concentrations
was explained by the traffic in January and 62 percent in July.
The results of this study are inconsistent with those studies
(1,2) that found high correlations between CO concentrations and traffic.
The instruments used in this study were modern, were checked for accuracy.
and were in locations comparable tc those used in the other studies
(about 30 to 50 feet from traffic in the northeastern city [1] and
about ? to 3 meters from the building walls in Frankfurt/Main [2]).
This study indicates that the diurnal variations of traffic are
spatially and seasonally consistent but that the diurnal variations
of CO concentrations are inconsistent. There are times and places,
however, at which there may be a high correlation between the variations
of the parameters. This appears to have been the situation in the
northeastern city and in Frankfurt/Main in the earlier studies.
12
-------
REFERENCES
1. Brief, R.S., A.R. Jones, and D. Yoder. Lead, Carbon Monoxide and
Traffic. J. Air Poll. Cont. Assoc. 10:384-388, 413, 1960.
2. Georgii, H.W., E. Busch, and E. Weber. EPA translation #^77 of
Investigation of the Temporal and Spatial Distribution of the
Emission Concentration of Carbon Monoxide in Frankfurt/Main.
Report of the Institute for Meteorology and Geophysics of the
University of Frankfurt/Main. May 1967. 66 p.
3. DeMarrais, G.A. Diurnal Variations in Carbon Monoxide Concentrations
Traffic Counts and Meteorology. U.S. Environmental Protection
Agency, Research Triangle Park, NC. (In press, 1976).
4. McCormick, R.A., and C. Xintaras. Variation of Carbon Monoxide-
Concentrations as Related to Sampling Interval, Traffic and
Meteorological Factors. J. of Appl. Meteor. 1:237, 1962.
5. Johnson, W.B., F.L. Ludwig, W.F. Dabberdt, and R.J. Allen. An
Urban Diffusion Simulation Model for Carbon Monoxide. J. Air
Poll. Cont. Assoc. 23:490, 1973.
6. Clean Air Act of 1970. PL 61-604, 42 USC 1857 et seq, United
States Congress, Washington, DC. December 1970.
7. Fritts, 6.W. Hourly Traffic Data, Seven Selected Stations, State
Department of Highways, Denver, CO., 1975.
8. Bureau of Traffic Engineering, Traffic Trends 1973, State Highway
Administration of Maryland Department of Transportation, Baltimore,
MD., 1974.
9. Kandu, J.C. Hourly Traffic Data, Three Selected Stations, Department
of Transportation, Trenton, NJ, 1975.
10. Midurski, T.P., and A.M. Castaline. Guidelines for Identification
and Evaluation of Localized Violations of Carbon Monoxide Standards.
GCA Corporation, Bedford, MA., GCA-TR-75-35-G(l), 1976.
11. Holzworth, G.C. Mixing Heights, Wind Speeds and Potential for
Urban Air Pollution Throughout the Contiguous United States
AP-101. U.S. Environmental Protection Agency, Research Triangle
Park, North Carolina, 1972. 118 pp.
13
-------
12. Ludwig, F.L. and J.H.S. Kealoha. Selecting Sites for Carbon
Monoxide Monitoring. Report prepared for U.S. Environmental
Protection Agency by Stanford Research Institute, MenTo Park,
California, Contract No. 68-02-1471, 1975. 150 pp.
14
-------
STATION C1
METRO-D
ADT 16,311
STATION C8
METRO-D
ADT 20,683
STATION C22
—METRO-D
ADT 94,818
STATION Cl
RESORT
ADT 2918
STATION C23
METRO-D
ADT 31.612
STATION C40
URBAN
ADT 36,475
STATION C39
RESORT
ADT 1137
STATION M39
INT-C-H
ADT 39 307
STATION M25
INT-C-H
ADT 38.631
LEGEND:
9 NOON 3
TIME
C = COLORADO
NJ = NEW JERSEY
6 9 NOON 3 6 9 12
TIME
INT-C-H = INTERCITY HIGHWAY
D = DENVER
12 3 6 9 NOON 3 6
TIME
B = BALTIMORE
ADT = AVERAGE DAILY TRAFFIC
M = MARYLAND METRO = METROPOLITAN
Figure 1. Diurnal variation in percentage of 24-hour traffic flow for each hour at 18 stations during January.
9 12
-------
STATION MB
SMALL CITY
ADT 14.338
STATION M31
METRO B
ADT 81,945
STATION M32
METRO B
ADT 84,461
STATION M35
MOUNTAIN
RESORT
ADT 2763
STATION M23
SMALL CITY
ADT 10.983
STATION M17
OCEAN RESORT
ADT 5824
STATION NJ409
SMALL CITY
ADT 6191
STATION NJ204
TRUCK ROUTE
ADT 31,575
STATION NJ208
OCEAN RESORT
ADT 18,485
6 9 NOON
TIME
C = COLORADO
NJ = NEW JERSEY
9 NOON 3
TIME
INT-C-H = INTERCITY HIGHWAY
D = DENVER
9 NOON 3 6
TIME
B = BALTIMORE
ADT = AVERAGE DAILY TRAFFIC
M = MARYLAND METRO = METROPOLITAN
Figure 1 (continued). Diurnal variation in percentage of 24-hour traffic flow for each hour at 18 stations
during January.
-------
9 NOON 3
TIME
9 NOON 3
TIME
9 NOON 3
TIME
9 NOON 3
TIME
9 NOON 3
TIME
12
STATION C23
METRO-D
ADT 35.235
STATION C40
URBAN
ADT 43.179
STATION C7
— RESORT
AOT6733
12 12
9 NOON 3
TIME
STATION M39
INT-C-H
ADT 48.160
STATION M25
INT-C-H
ADT 38,393
STATION C39
RESORT
ADT 5796
12 3
LEGEND:
6 9 NOON 3
TIME
C = COLORADO NJ = NEW JERSEY
M = MARYLAND METRO = METROPOLITAN
9 NOON 3 6 !
TIME
INT-C-H = INTERCITY HIGHWAY
D = DENVER
12 12
6 9 NOON 3 6
TIME
B = BALTIMORE
ADT = AVERAGE DAILY TRAFFIC
12
Figure 2. Diurnal variation in percentage of 24-hour traffic flow for each hour at 18 stations during July.
-------
00
STATION M31
METRO-B
ADT 88.828
STATION M32
METRO-B
ADT 98.868
369 NOON 369
TIME
9 NOON 3 6
TIME
STATION M23
SMALL CITY
ADT 13.136
STATION M35
MOUNTAIN
RESORT
STATION M17
OCEAN RESORT
ADT 21.022
9 NOON 3
TIME
9 NOON 3 6
TIME
12 3
10
I
STATION NJ204
TRUCK ROUTE
ADT 33.857
10
0
12 3
LEGEND:
6 9 NOON 3
TIME
C = COLORADO
STATION NJ208
OCEAN RESORT
ADT 29,198
12
NJ = NEW JERSEY
12 3 6 9 NOON 369
TIME
INT-C-H = INTERCITY HIGHWAY
9 12
STATION NJ409
SMALL CITY
ADT 6822
M = MARYLAND METRO = METROPOLITAN
D = DENVER
12 12 3 6 9 NOON 3 6
TIME
B = BALTIMORE
ADT = AVERAGE DAILY TRAFFIC
9 12
Figure 2 (continued). Diurnal variation in percentage of 24-hour traffic flow for each hour at 18 stations
during July.
-------
= 12
Q
LLJ
C3
cc
114
u
cc
9 NOON 3
LOCAL STANDARD TIME
12
LOCAL DAYLIGHT TIME
Figure 3. Diurnal variation in average traffic, 18 stations (vertical lines
show ranges of + 1 standard deviation).
19
-------
10
no
CD
BROADWAY
(7.8)
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
10
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
WE LBV
(4.3)
6 9 NOON 3 6
LOCAL STANDARD TIME
Figure 4. Diurnal variation in CO concentrations, Colorado stations, January (numbers in parentheses are average
hourly concentrations in ppm).
9 12
9 12
-------
6 9 NOON 3 6
LOCAL STANDARD TIME
6 9 NOON 3
LOCAL STANDARD TIME
9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
6 9 NOON 3 6
LOCAL STANDARD TIME
Figure 5. Diurnal variations in CO concentrations, Colorado stations, July (numbers in parentheses are average
hourly concentrations in ppm).
9 12
-------
10
10
6 9 NOON 3 6
LOCAL STANDARD TIME
BALTIMORE
(1.9)
U- <
o cr
CUMBERLAND
(1.6)
12 12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6 9
LOCAL STANDARDTIME
10
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
Figure 6. Diurnal variations in CO concentrations, Maryland stations, January (numbers in parentheses are average
hourly concentrations in ppm).
12
12
-------
ro
CO
10
u- <
o cc
cc «=
UJ O
Q_ CJ
LINTHICUM
(1.7)
10
CM ,_
U. <^
O CC
1-1-5
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
BALTIMORE (JUNE, NOT JULY)
(1.3)
12
12
•a- 2
a cc
si
CO CJ
CUMBERLAND
(1.3)
10
6 9 NOON 3 6
LOCAL STANDARD TIME
12
BETHESDA (AUGUST, NOT JULY)
(0.5)
6 9 NOON 3 6
LOCAL STANDARD TIME
GAITHERSBURG
(2.9)
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
6 9 NOON 3 6
LOCAL STANDARD TIME
9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
Figure 7. Diurnal variations in CO concentrations, Maryland stations, July (numbers in parentheses are average
hourly concentrations in ppm).
12
12
RIVIERA (JUNE, NOT JULY)
BEACH
(1.6)
-------
10
u. <
O CC
ASBURY
(3.8)
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
u- <
o cc
CAMDEN1
(2.9)
12
10
u. <
o cc
i- t: 5
6 9 NOON 3 6
LOCAL STANDARD TIME
ELIZABETH 1
(6.1)
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
u. et
O CC
CC ^
LU O
Q. CJ
HACKENSACK
(4.9)
12
6 9 NOON 3 6
LOCAL STANDARD TIME
10
II
CXI ,_
O CC
111 O
0- U
BAYONNE
(1.0)
10
u. <
o cc
1-1-5
uj O
0. CJ
BURLINGTON
(5.6)
12
12
10
6 9 NOON 3 6
LOCAL STANDARDTIME
12
12
CAMDEN2
(2.7)
10
6 9 NOON 3 6
LOCAL STANDARD TIME
ex, ,_
U- <
0 0=,
O CJ
CC ^
LU O
D- LJ
CAMDEN3
(1.3)
12
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
'12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
O
Q.CJ
JERSEY CITY
(5.8)
10
9 NOON 3 6
LOCAL STANDARD TIME
o o
cc ^
LU O
NEWARK
(4.4)
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
12
12
Figure 8. Diurnal variations in CO concentrations. New Jersey stations, January (numbers in parentheses are average
hourly concentrations in ppm).
-------
ro
01
10
LL. <
o cc
PATERSON
(6.6)
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
~
O OC
CJ CJ
CC. Z
LLJ O
Q- O
PERTH AMBOY
(5.9)
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
10
u. <
O CC
PAULSBORO
(4.2)
12
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
PHILLIPSBURG
(1.9)
*#
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
TRENTON
(8.7)
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
10
UJ O
Q. U
PENNSGROVE
(5.9)
12
10
12 3 6 9 NOON 3 6
LOCAL STANDARD TIME
12
it •*
o oc,-
K 1-5
0 CJ
oc z
SUMERVILLE
(5.3)
12
12
I 9 NOON 3 6
LOCAL STANDARD TIME
12
12
* STATIONS SHOWING 0.72 OR GREATER
CORRELATIONS
** STATIONS WITH MAJORITY OF CORRE-
LATIONS LESS THAN 0.72
NO* STATIONS IN-BETWEEN ABOVE TYPES
(CORRELATIONS BASED ON STATION-TO-
STATION COMPARISONS - SEE TEXT)
Figure 8 (continued). Diurnal variations in CO concentrations, New Jersey stations, January (numbers in parentheses
are average hourly concentrations in ppm).
-------
IV)
CTl
10
LL, <
O CC
oc 2
UJ O
Q. O
ASBURY
(2.0)
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
u. <
O DC
CC 2
LLJ O
CAMDEN1
(3.4)
12
6 9 NOON 3 6
LOCAL STANDARD TIME
6 9 NOON 3 6
LOCAL STANDARD TIME
10
u. <
O CC
CC ^
LLJ O
0- LJ
HACKENSACK
(3.3)
12
6 9 NOON 3 6
LOCAL STANDARD TIME
10
O CC
1-1-5
.
in O
0
BAYONNE
(2.1)
12 12
10
9 NOON 3 6
LOCAL STANDARD TIME
0.0
CAMDEN 2
(4.0)
12 12
10,—
9 NOON 3 6
LOCAL STANDARD TIME
ELIZABETH 2
(2.9)
12 12
10r—
9 NOON 3 6
LOCAL STANDARDTIME
JERSEY CITY
(6.4)
12 12
9 NOON 3 6
LOCAL STANDARD TIME
10
u. <
O CC
LU O
O- O
0
BURLINGTON
(4.0)
12 12
101—
6 9 NOON 3 6
LOCAL STANDARD TIME
<» _
-------
10
<
cc
cc
LU
Ou
PATERSON
(3.9)
10
•» r
LL. <
O CC
PAULSBORO
(4.7)
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
. «f
DC
PERTH AMBOY
(7.3)
12 12
10|—
6 9 NOON 3 6
LOCAL STANDARD TIME
u-«t
occ ,
PHILLIPSBURG
(1.3)
12
10
6 9 NOON 3 6
LOCAL STANDARD TIME
6 9 NOON 3 6
LOCAL STANDARD TIME
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
10
LL. <
O CC
o"
ocg
LU O
a. u
PENNSGROVE
(3.5)
12 12
10i—
6 9 NOON 3 6
LOCAL STANDARD TIME
a- O
SOMERVILLE
(3.8)
12
12
6 9 NOON 3 6
LOCAL STANDARD TIME
12
12
* STATIONS SHOWING 0.72 OR GREATER
CORRELATIONS IN JANUARY
** STATIONS SHOWING WITH POORER COR-
RELATIONS IN JANUARY
NO* STATIONS IN-BETWEEN ABOVE TYPES
(CORRELATIONS BASED ON STATION-TO-
STATION COMPARISONS SEE TEXT)
Figure 9 (continued). Diurnal variations in CO concentrations, New Jersey stations, July (numbers in parentheses
are average hourly concentrations in ppm).
-------
LOCAL STANDARD TIME
Figure 10. Diurnal variations of CO concentrations, composite for six
Colorado stations (vertical lines show ranges of + 1 standard deviation).
28
-------
10
12
9 NOON 3
LOCAL STANDARD TIME
Figure 11. Diurnal variation of CO concentrations, composite for selected
Maryland stations (vertical lines show ranges of + 1 standard deviation).
29
-------
o
p
<
O
o
cc
u
cc
LOCAL STANDARD TIME
Figure 12. Diurnal variation of CO concentrations, composite for selected
New Jersey stations (vertical lines show ranges of + 1 standard deviation).
30
-------
TABLE 1. TYPES AND LOCATIONS OF TRAFFIC COUNTING STATIONS
Station0
Type
Location
C 1 Urban
C 8 Urban
C 22 Urban
C 23 Urban
C 40 Urban
C 7 Resort
C 39 Resort
M 25 Intercity highway
M 39 Intercity highway
M 31 Urban beltway
M 32 Urban beltway
I'M 5 Small city highway
.M 23 Small city highway
M 17 Ocean resort
M 35 Mountain resort
NJ 204 Truck route in city
NJ 208 Ocean resort
NJ 409 Small city roadway
1-25 North of downtown Denver
US-36 Southeast of Broomfield (near Denver)
1-25 Valley Highway in Denver
First Avenue in downtown Denver
1-25 Freeway in Pueblo
1-70 East of Glenwood Springs (140 miles
west of Denver)
US-34 East of Estes Park (60 miles NW of
Denver)
Baltimore-Washington Expressway South of
MD-176
1-95 North of MD-175
1-695 West of Raltimore-Harrisburg Express-
way
1-695 South of U.S. 40
U.S. 301 South of Waldorf
MD-5 East of Waldorf
U.S. 50 West of Ocean City
U.S. 219 at McHenry
U.S. IT, Jersey City, between Duncan and
Sip Avenues
U.S. 30 Atlantic City, 0.5 mile East of
Delilah Road
South Collins Road, Camden, between
Kearsarqe and Tuckahoe Road
Numbering system is that used by the respective states; C=Colorado, M=Maryland,
NJ=New Jersey
bBetween Baltimore and Washington
-------
TABLE 2. DESCRIPTION OF CO MONITORING SITES
Station
Area description
Intake
Exposure
Nearby traffic
Arvada
(C)
Broadway
(C)
Julian
(C)
Col fax
(C)
Huron
(C)
Wei by
(C)
Baltimore
(M)
(Calvert St)
Bethesda
(M)
Cumberland
(M)
Open field in a residential area
6 miles northwest of downtown area
Small triangular plot in downtown
area
Small parking lot near hospital
2 miles west of downtown area
Field near hospital in center
city commercial area
Field 5 miles south of downtown
area
Open field in rural area 6 miles
north northeast of downtown
100-car parking field next to
thoroughfare
Meadow in metropolitan area
Grassy field next to thoroughfare
(c)
17 feet above
ground on side
of building
(c)
(c)
(c)
(c)
(d)
(d)
(d)
60 feet to road carrying 3,500
vehicles
21 feet to road carrying 1,700 vehicles
and 30 feet to road carrying 7,500
vehicles
36 feet to dne road and 61 feet to
another; each carries 1,000 vehicles
Many major intersections and road-
ways nearby
Adjacent streets carry .light traffic
but nearby streets carry heavy traffic
42 feet to road carrying less than
1,000 vehicles
90 feet to road carrying heavy after-
noon traffic
300 feet to road carrying about
100 vehicles
20 feet to road carrying heavy
morning traffic
-------
TABLE 2. (continued).
OJ
CO
Station3
Gaithersburg
(M)
Hyattsville
(M)
Linthicum
(M)
Riviera Beach
(M)
Silver Spring
(M)
Suit! and
(M)
Tows on
(M)
Asbury
(MJ)
Bayonne
(NJ)
Area description
Near thoroughfare in suburb
Grassy field near the thoroughfare
in metropolitan area
Packed earth parking field at
end of road
Parking field next to little
used side road
Park area next to thoroughfare
Edge of 500-car, asphalt covered
parking field
Edge of wooas
City street
City park
Intake
Exposure
35 feet above
ground, 18 in.
from side of
building
(d)
(d)
(d)
(d)
(d)
12 feet above
ground atop
building
(e)
(f)
Nearby trafficb
75 feet from road carrying 27,000
vehicles
Below level of road and 75 feet from
road carrying 30,000 vehicles
80 feet from road carrying about 100
vehicles and 600 feet from major
thoroughfare
10 feet from road carrying 100 vehicles
and 0.25 miles from thoroughfare
50 feet from 8-land thoroughfare
carrying 90,000 vehicles
150 feet from road carrying 18,500
vehicles
Closest road, 500 feet away, carries
76,500 vehicles
Road carries moderate to light traffic
3 blocks from ocean
Trailer is 0.75 miles from road with
moderate traffic
-------
TABLE 2. (continued).
OJ
-pi
Station3
Burlington
(NJ)
Camden 1
(NJ)
(N. 6th st.)
Area description
City street
City street
Camden 2 Open field at medical research
(NJ) center
(Copewood & Davis)
Camden 3
(NO)
(Ancora)
Elizabeth 1
(NJ)
(Broad St.)
Elizabeth 2
(NJ)
(N.J. Turnpike)
Freehold
(.NJ)
Hackensack
(NJ)
Jersey City
(NJ)
Rural state hospital 20 miles
southeast of Camden
Center city street
Turnpike interchange
Center city street
City street
Street near city center
Intake
Exposure
(e)
(e)
(f)
About 30 feet
above ground
3 feet from side
of building
(e)
(f)
(e)
(e)
(e)
Nearby trafficb
Road is a main street but carries
only moderate to light traffic
Downtown road which carries light
traffic
A block from light traffic; 3 blocks
from heavy traffic
No nearby traffic; heavily travelled
2 and 3 miles away
Road carries heavy traffic
Trailer is about 150 feet from exit-
entrance area
Street carries moderate to light
traffic
Sampler is about 50 feet from light
traffic and 400 feet from heavy traffic
Street carries very heavy traffic
-------
TABLE 2. (continued).
to
en
Station3
Newark
(NJ)
Paterson
(NJ)
Paulsboro
(NJ)
Penns Grove
(NJ)
Perth Amboy
Phillipsburg
(NJ)
Somerville
(NJ)
Toms River
(NJ)
Trenton
(NJ)
Area description
Corner of two streets
City street
Center city street
Center city street
Center city street
Near corner of two streets
Center city street
Near corner on main street
Center city street
Intake
Exposure
(f)
(e)
(e)
(e)
(e)
(e)
(e)
(e)
(e)
Nearby traffic
Each street is a one-way street; each
carries heavy traffic
Street carries light traffic; large
amount of heavy-duty, gasoline-burning
equipment used in nearby city dump
Street carries light traffic
Street carries light, traffic
Street carries very heavy traffic
Sampler is 20 feet above sidewalk;
street 20 feet away carries light traffic
street 50 feet away carries heavy traffic
Street carries moderate traffic
Street carries heavy traffic typical
of area with a small population
Street is now a mall; traffic was
heavy
-------
TABLE 2. (continued).
All Colorado (C) stations are in Denver area; (M)=Maryland; (NJ)=New Jersey
Vehicle counts are in counts per day; estimate of NJ traffic based on observation
Exposure is 15 feet above ground atop trailer
CTl
Exposure is 10 feet above ground atop trailer
Exposure is 3 feet from side of building (projecting out from window) about 10-12 feet above ground
Exposure is 12 feet above ground atop trailer
-------
TABLE 3. CORRELATIONS OF LESS THAN 0.90 IN DIURNAL VARIATIONS IN TRAFFIC FOR JANUARY, 18 STATIONS'
C7
C39
Ml 7
M35
NJ204
NJ208
NJ409
CMCCCCCMM
1 8 22 23 40 7 39 25 39
0.89 0.85 ------
0.88 0.87
_________
0.89 0.87
_________
0.87 0.88 - 0.84 - - -
0.82 0.83 0.80 0.84 0.84 0.82 0.78 0.83 0.81
M M M M M M NJ NJ NJ
31 32 5 23 17 35 204 208 409
0.87 0.88 ----- 0.84 0.82
0.89 0.89 - - - - - 0.78
0.79
0.86 0.31
0.83 O.u4
0.89 0.89 0.89 - 0.86 0.88 - 0.39
0.81 0.83 0.83 0.81 0.79 0.81 0.84 0.89
All pairs not shown or marked by '- were 0.90 or more.
C=Colorado, M=Maryland, NJ=New Jersey
-------
CO
oo
TABLE 4. CORRELATIONS OF LESS THAN 0.90 IN DIURNAL VARIATIONS IN TRAFFIC FOR JULY, 18 STATIONS3
C7
C39
HI 7
M35
NJ409
C C
1 8
0.86
0.88
0.87
0.86 0.80
0.89 0.87
C C
22 23
0.83
0.85 -
0.83 -
0.76 0.86
0.84 0.89
C C C M
40 7 39 25
0.85
0.87
0.87
0.83
0.83 0.82 0.89
M
39
0.89
_
0.82
0.86
M
31
0.81
0.83
0.85
0.77
0.87
M M
32 5
0.80 -
0.82 -
0.84 -
0.79 -
0.89 -
M M M NJ NJ NJ
23 17 35 204 208 409
0.83
0.82
_
______
aAll pairs not shown or marked by ••-- were 0.90 or more.
C=Colorado, M=Maryland, NJ=New Jersey
-------
TABLE 5. CORRELATION BETWEEN JANUARY AND JULY DIURNAL VARIATIONS IN
TRAFFIC AT INDIVIDUAL STATIONS3
Station
Cl
C8
C22
C23
C40
C7
C39
M25
M39
Correlation
0.99
0.99
0.99
0.99
0.98
0.98
0.95
0.98
0.99
Station Correlation
M31
M32
M5
M23
M17
M35
NJ204
NJ208
NJ409
0.98
0.97
0.97
0.95
0.87
0.93
0.98
0.92
0.91
aC=Colorado, M^Maryland, NJ=New Jersey
39
-------
TABLE 6. BIVARIATE CORRELATIONS OF DIURNAL VARIATIONS IN CO CONCENTRATIONS
AT COLORADO STATIONS, JANUARY
Wei by
Huron
Col fax
Julian
Broadway
Arvada
0.88
0.71
0.75
0.85
0.77
Broadway
0.51
0.66
0.90
0.61
Julian
0.77
0.84
0.66
Col fax Huron
0.46 0.46
0.83
40
-------
TABLE 7. BIVARIATE CORRELATIONS OF DIURNAL VARIATIONS IN CO CONCENTRATIONS,
j COLORADO STATIONS, JULY.
Wei by
Huron
Col fax
Jul ian
Broadway
Arvada
0.23
0.84
0.80
-0.07
0.67
Broadway Julian
0.58 0.75
0.51 -0.19
0.48 -0.21
0.04
Col fax Huron
-0.02 -0.03
0.92
41
-------
TABLE 8. BIVARIATE CORRELATIONS OF DIURNAL VARIATIONS IN CO CONCENTRATIONS, MARYLAND STATIONS,
JANUARY
Towson
Suitland
Silver Spring
Riviera Beach
Hyattsville
Gaithersburg
Cumberland
Bethesda
Baltimore
Linth-
icum
0.79
0.78
0.92
0.08
0.77
0.88
0.88
0.88
0.80
Balti-
more
0.84
0.62
0.81
-0.04
0.81
0.63
0.63
0.66
Cumber- Gaithers- Hyatts- Riviera Silver Suit-
Bethesda land burg ville Beach Spring land
0.71 0.59 0.70 0.84 0'.03 0.87 0.60
0.70 0.81 0.89 0.46 0.20 0.77
0.90 0.81 0.85 0.84 0.25
0.31 0.38 0.33 0.16
0.78 0.56 0.60
0.84 0.92
0.81
-------
co
TABLE 9. BIVARIATE CORRELATIONS OF DIURNAL VARIATIONS IN CO CONCENTRATIONS, MARYLAND STATIONS,
JULY
Tows on
Suitland
Silver Spring
Riviera Beach
Hyattsville
Gaithersburg
Cumberland
Bethesda
Baltimore
Linth-
icum
0.64
0.89
0.45
-0.36
0.77
0.66
0.69
0.65
0.54
Balti-
more
0.76
0.77
0.91
-0.02
0.75
0.70
0.84
0.71
Bethesda
0.86
0.69
0.74
-0.24
0.85
0.75
0.72
Cumber-
land
0.77
0.84
0.83
-0.02
0.71
0.87
Gaithers-
burg
0.78
0.78
0.77
0.13
0.61
Hyatts-
ville
0.84
0.81
0.66
-0.44
Riviera Silver Suit-
Beach Spring land
-0.19 0.69 0.75
-0.32 0.69
0.09
-------
TABLE 10. BIVARIATE CORRELATIONS OF DIURNAL VARIATIONS IN CO CONCENTRATIONS AT 13 SELECTED NEW JERSEY
STATIONS, JANUARY.
Trenton
Toms River
Perth Amboy
Penns Grove
Paulsboro
Newark
Jersey City
Hackensack
Freehold
Elizabeth 1
Camden 2
Burlington
Asbury
0.88
0.90
0.90
0.93
0.91
0.95
0.93
0.93
0.93
0.95
0.89
0.92
Burl-
ington
0.94
0.90
0.94
0.94
0.82
0.86
0.85
0.88
0.95
0.96
0.91
Camden
2
0.88
0.85
0.82
0.87
0.78
0.87
0.83
0.80
0.88
0.90
Eliza-
beth 1
0.93
0.93
0.92
0.97
0.88
0.91
0.92
0.90
0.97
Free-
hold
0.85
0.87
0.84
0.92
0.91
0.85
0.89
0.89
Hack-
ensack
0.80
0.77
0.84
0.82
0.88
0.82
0.83
Jersey Pauls-
City Newark boro
0.83 0.87 0.72
0.90 0.89 0.80
0.84 0.87 0.73
0.91 0.91 0:83
0.89 0.87
0.95
Penns Perth Toms
Grove Amboy River
0.95 0.96 0.93
0.97 0.93
0.94
,
-------
TABLE 11. BIVARIATE CORRELATIONS OF
Bayonne
Camden 1
Elizabeth 2
Paterson
Phillipsburg
Asbury
0.32
0.69
0.78
0.29
0.72
Bay-
onne
0.27
0.13
-0.21
0.23
Burl-
ington
0.48
0.67
0.69
0.28
0.66
DIURNAL
Camden
1
0.27
0.87
0.45
0.83
VARIATIONS IN CO CONCENTRATIONS
STATIONS, JANUARY
Camden
2
0.37
0.59
0.65
0.20
0.57
Camden
3
0.25
0.56
0.51
0.32
0.49
Eliza-
beth 1
0.36
0.68
0.74
0.33
0.70
Eliza-
beth 2
0.13
0.87
0.62
0.93
AT FIVE SELECTED NEW JERSEY
Free-
hold
0.37
0.76
0.81
0.48
0.76
Hack-
ensack
0.32
0.83
0.87
0.37
0.82
Jersey
City
0.08
0.55
0.73
0.38
0.64
Newark
0.14
0.53
0.69
0.28
0.63
-------
Table 12. Bivariate Correlations of Diurnal Variations in CO Concentrations at 13 Selected Stations,
July.
en
Trenton
Toms River
Perth Amboy
Penns Grove
Paulsboro
Newark
Jersey City
Hackensack
Freehold
Elizabeth 1
Camden 2
Burlington
Asbury
0.85
0.90
0.80
0.29
0.19
0.72
0.70
0.23
0.73
0.79
0.80
0.65
Burl-
ington
0.73
0.55
0.18
0.72
0.64
0.52
0.27
0.63
0.76
0.68
0.78
Camden
2
0.93
0.74
0.42
0.28
0.26
0.74
0.54
0.29
0.89
0.71
Eliza-
beth 1
0.67
0.78
0.67
0.60
0.60
0.90
0.83
0.26
0.69
Free-
hold
0.90
0.81
0.44
0.43
0.34
0.62
0.46
0.06
Hack-
ensack
0.22
-0.05
-0.25
0.44
0.52
0.22
-0.07
Jersey Pauls- Penns Perth
City Newark boro Grove Amboy
0.48 0.67 0.19 0.24 0.49
0.68 0.65 0.18 0.33 0.83
0.82 0.59 -0.03 0.09
0.17 0.29 0.85
0.25 0.41
0.86
Toms
River
0.83
-------
Table 13. Bivariate Correlations of Diurnal Variations in CO Concentrations at 6 Selected New Jersey
Stations, July.
Bayonne
Camclen 1
Elizabeth 2
Paterson
Phillipsburg
Camden 3
As bury
0.29
0.36
0.12
0.36
0.75
0.52
Bay-
onne
0.77
0.66
0.52
0.20
-0.72
Burl-
ington
0.27
0.10
0.35
0.60
0.81
-0.09
Camden
1
0.77
0.70
0.65
0.15
-0.64
Camden
2
-0.12
-0.25
0.29
0.44
0.61
0.15
Camden
3
-0.72
-0.64
-0.44
-0.29
0.24
1.00
Eliza-
beth 1
0.18
0.13
0.64
0.74
0.84
0.19
Eliza-
beth 2
0.66
0.70
0.82
0.41
-0.44
Free-
ho!4
-0.06
-0.33
0.21
0.30
0.58
0.18
Hack-
ensack
0.29
0.47
0.27
0.61
0.55
-0.33
Jersey
City
-0.05
0.01
0.54
0.48
0.52
0.35
Newark
-0.04
0.10
0.62
0.66
0.65
0.23
-------
Table 14. Correlations of January and July Diurnal Variations of
CO Concentrations
Station
Linthicum
Baltimore
Bethesda
Cumberland
Gai thersburg
Hyattsvi lie
Riviera Beach
Silver Spring
Sui tland
Towson
Arvada
Broadway
Correlation
0.15
0.35
0.28
0.39
0.34
0.24
0.61
0.44
0.24
0.38
0.55
0.86
Station
Julian
Col fax
Huron
Uelby
Asbury
Bayonne
Burlington
Camden 1
Camden 2
Camden 3
Elizabeth 1
Elizabeth 2
Correlation
0.58
0.80
0.57
0.70
0.79
-0.26
0.39
-0.08
0.55
0.47
0.65
0.68
Station
Freehold
Hackensack
Jersey City
Newark
Paterson
Paulsboro
Penns Grove
Perth Amboy
Phillipsburg
Somerville
Toms River
Trenton
Correlation
0.90
0.80
0.79
0.82
0.65
0.67
0.87
0.94
0.78
0.66
0.90
0.90
-------
Table 15. Correlations of Diurnal Variations, January and July.
Basic
traffic
verses
statewide CO
Traffic:
Traffic:
Traffic:
Traffic:
Traffic:
Traffic:
January
Colorado
Maryland
patterns
patterns
CO
CO
New Jersey CO
July
Colorado
Maryland
CO
CO
New Jersey CO
0
0
0
0
-0
0
.52
.25
.94
.58
.19
.79
Interstate CO
correlations
January
Colorado
Colorado
Maryland
Colorado
Colorado
Maryland
CO
CO
CO
CO
CO
CO
: Maryland CO
: New
: New
July
Jersey
Jersey
CO
CO
: Maryland CO
: New
: New
Jersey
Jersey
CO'
CO
0
0
0
0
0
0
.85
.54
.42
.56
.37
.31
49
-------
TECHNICAL REPORT DATA
(Please read Instructions on the reverse before completing)
i. REPORT NO.
EPA-600/4-77-016
3. RECIPIENT'S ACCESSIOI^NO.
4. TITLE AND SUBTITLE
DIURNAL VARIATIONS IN TRAFFIC FLOW AND CARBOr
MONOXIDE CONCENTRATIONS
5. REPORT DATE
April 1977
6. PERFORMING ORGANIZATION CODE
7. AUTHOR(S)
8. PERFORMING ORGANIZATION REPORT NO
Gerard A. DeMarrais*
9. PERFORMING ORGANIZATION NAME AND ADDRESS
Environmental Sciences Research Laboratory
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
10 PROGRAM ELEMENT NO.
1AA603
11. CONTRACT/GRANT NO.
12. SPONSORING AGENCY NAME AND ADDRESS
Environmental Sciences Research Laboratory - RTP, NC
Office of Research and Development
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
13. TYPE OF REPORT AND PERIOD COVERED
Inhouse 3/76-2/77
14. SPONSORING AGENCY CODE
EPA/600/09
15. SUPPLEMENTARY NOTES
*0n assignment from the National Oceanic and Atmospheric Administration,
U.S. Department of Commerce.
16. ABSTRACT
Traffic count and carbon monoxide (CO) data for January and July from three
states are compared in order to reveal any diurnal variations in the two
measurements. The diurnal patterns for the 18 traffic count stations indicate
that there are average patterns of traffic flow that are representative of all
stations for periods of one month. Comparisons of data for the 36 CO monitoring
stations show correlations which vary from large positive to large negative.
However, eliminating a few monitoring stations which show relatively poor
correlations yields groups within each state that have consistent patterns. The
diurnal variations in CO concentrations are not well correlated with traffic
patterns. Part of the poor correlation appears to be due to the diurnal variations
in vertical mixing and wind speeds and part to the exposures and locations of the
sampling instruments.
KEY WORDS AND DOCUMENT ANALYSIS
DESCRIPTORS
b.IDENTIFIERS/OPEN ENDEDTERMS
cos AT I Field/Group
Air pollution
Carbon monoxide
Traffic surveys
Diurnal variations
Correlation
Meteorological data
13B
07B
13B
04B
RELEASE TO PUBLIC
19. SECURITY CLASS (This Report)
UNCLASSIFIED
21. NO. OF PAGES
58
20. SECURITY CLASS (This page)
UNCLASSIFIED
22. PRICE
EP.
2220-1 (9-73)
50
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