Technical Report 

Analysis of April 12-13, 2003 

Kansas City Ozone 

Exceedances 

18 February 2004 

Prepared by: 

Bret A. Anderson 

Michael F. Davis 

Air Technical Analysis Group 

United States Environmental Protection Agency Region 7 

901 N. 5th Street 

Kansas City, KS 66101 
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Table of Contents 

1. INTRODUCTION ..................................................................................................................................................3 

2. CLIMATIC CHARACTERISTICS.......................................................................................................................7 

2.1 METEOROLOGICAL ANALYSIS .................................................................................................................14 

2.2 LAGRANGIAN PARTICLE MODELING ANALYSIS ................................................................................15 

3. AIR QUALITY CHARACTERIZATION .........................................................................................................19 

3.1 EXPLORATION OF THE CAUSE OF EXCEEDANCES..............................................................................20 

3.1.1 CLIMATOLOGICAL EFFECTS ON MONITORING DATA ...................................................................20 

3.1.2 CO-OCCURRENCE OF GASEOUS POLLUTANTS RELATED TO COMBUSTION SOURCES AND

THE EFFECT ON OZONE CONCENTRATIONS...............................................................................................24 

3.1.3 CO-OCCURRENCE OF PARTICULATE POLLUTANTS RELATED TO COMBUSTION 

SOURCES ..................................................................................................................................................................28 

4. PM2.5 SOURCE APPORTIONMENT ANALYSIS ...........................................................................................32 

5. CONCLUSIONS...................................................................................................................................................37 

6. REFERENCES..................................................................................................................39 

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1. Introduction 

On April 12 and 13, 2003, three monitors (hereafter referred to as Liberty, Watkins Mill, 

and Rocky Creek) in the Kansas City ozone monitoring network recorded values in 

excess of the 0.084 ppm 8-hour average daily maximum ozone national ambient air 

quality standard (NAAQS). On July 8, 2003, the USEPA Region VII received a request 

from the Missouri Department of Natural Resources (MDNR) to “flag” the data due to 

the occurrence of large scale agricultural burning that occurred in central and southern 

Kansas and north central Oklahoma. 

The guideline document that provides national guidance for flagging ambient air quality 

data influenced by exceptional events is, “Guideline on the Identification and Use of Air 

Quality Data Affected by Exceptional Events” (EPA-450/4-86-007), July 1986. This 

guideline defines the term “exceptional event” as an event that is not expected to recur 

routinely at a given location, or that is possibly uncontrollable or unrealistic to control 

through the SIP process. In addition, for air quality data to be flagged as influenced by 

an exceptional event, a clear relationship between the event and the elevated air quality 

measurement must be established. 

A qualitative description of the events and conditions surrounding the agricultural fires 

provided by the Kansas Department of Health and Environment indicates that due to 

severe drought conditions persistent in that region, a burn ban had been placed by the 

Kansas Fire Marshal’s Office. Just prior to April 10, 2003, a small yet sufficient amount 

of precipitation was received that allowed the local fire officials to temporarily lift the

burn ban. Seizing upon this narrow window of opportunity, many in the local farming 

community initiated their burning of the tall grass prairie, resulting in a spate of fires over 

small period of time. In summary, it was the contention of the MDNR that the large 

quantity of emissions resulting from these fires over the short period of time were the 

primary cause of the exceedances measured in Kansas City. 

Figures 1a and 1b demonstrate the rapid change in active burns as detected by satellite. 

On April 9, 2003 (Figure 1a) there were few active burns over the region detectable by 

satellite. By April 11, 2003 (Figure 1b) active burn signatures were detected over much 

of Kansas and north central Oklahoma, signifying the rapid onset of the agricultural 

burning in the Flint Hills Region. High resolution satellite imagery and thermal analysis 

taken on April 11, 2003 (Figure 1c) provides a glimpse at the spatial extent of these fires 

and the resultant smoke plume. Smoke can be seen in the visible imagery extending as 

far north as the Iowa-Minnesota border emanating from the fires in Kansas and 

Oklahoma. Normal range management practice dictates that range burning occur in the 

Flint Hills region over a period of time characterized as “late spring”. This correlates 

normally with a period of weeks between mid-March through early May. The burn ban 

that was in effect prior to April 10, 2003 prevented range managers from performing any 

early spring burns. Therefore, when the burn ban was lifted, a very large area of 

grassland was ignited simultaneously. 

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In the initial review of the request submitted by the State, EPA Region VII technical staff

concluded that the limited data provided in support of the original request was 

insufficient to establish causality between the quantity of emissions from agricultural 

burning and the April 2003 ozone exceedances. However, one compelling fact was, that 

in twenty plus years of ozone monitoring in Kansas City, no values in excess of an 8-hour 

average of 0.084 ppm have been observed in the month of April. Therefore, solely on the 

merit of the unusual nature of observing ozone values uncharacteristic for that portion of 

the ozone monitoring season, meteorological and air quality monitoring staff from EPA 

Region VII undertook a two month data analysis effort to characterize air quality and 

climatic conditions of that period in order to elucidate what conditions likely gave rise to 

the events of April 12 and 13, 2003. 

The information contained herein is a summary of that effort. Section 2 of this document 

describes the climatic patterns normally observed in April and the synoptic characteristics 

of the April 12-13, 2003 time frame. Section 3 describes the regional air quality 

characteristics during that time period, and Section 4 details the results of a receptor 

modeling study undertaken to augment the air quality characterizations analyzed in 

Section 3. 

This analysis provides clear causal linkage between the high level of emissions produced 

by the exceptional geographic extent of the burning that occurred in the Flint Hills region 

over a two day period and the elevated ozone measurements in Kansas City on April 12 

and 13, 2003. 

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Figure 1a. MODIS Active Fire Detection for April 9, 2003. 

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Figure 1b. MODIS Active Fire Detection for April 11, 2003. 

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Figure 1c. High resolution visible satellite imagery from April 11, 2003. 

2. Climatic Characteristics 

In the summer of 2003, EPA Region VII modeling staff undertook a data analysis effort 

to characterize the nature of Kansas City climatology during ozone monitoring season. 

The study had two major focuses. The first was to assist in the development of a more 

comprehensive understanding of the meteorological and climatic conditions normally 

associated with elevated ozone in Kansas City. This is often referred to as conceptual 

model development. The second focus was to test the application of relatively new 

statistical methodologies designed to facilitate climatic classification and determine their 

efficacy for selection of candidate episodes for future photochemical studies. Two 

methodologies, one based upon classification of backward air trajectories, and the other 

based upon multivariate analysis of surface and upper air meteorological data. Ozone 

data was stratified with the identified synoptic patterns to provide an understanding of the 

air quality characteristics associated with each weather pattern type. 

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The results of the climatological study concluded that one major climatic type or 

“cluster” accounts for almost 82% of all ozone exceedance days in Kansas City 

(Anderson, 2003). The pattern, referred to as C1 in the report, is most prevalent during 

the months of June, July, and August with 82.5% of all instances of this pattern occurring 

in these three months (Anderson, 2003). Only 2 instances of this pattern occurred in the 

month of April during the study period. C1 is characterized by the presence of the classic 

anticyclonic system over the Eastern and Southeastern United States and meteorological 

conditions local to the Kansas City area are typified by high temperatures, light southerly 

winds, and high incoming solar radiation – all of which are conditions most favorable for 

ozone formation as identified by many previous studies. Of five other exceedance days 

between 2000-2002 that fell outside of the C1 pattern, the second highest frequency was 

two exceedance days that fell into the C5 pattern. The C5 pattern is characterized by the 

absence of strong synoptic scale systems over the Central United States, often times 

seeing weak anticyclonic systems located to the south of Kansas City and the presence of 

a stationary front situated to the north of Kansas City. Resultant meteorological 

conditions show light wind speed conditions at the surface with less coherence to the 

horizontal structure of the flow field. The C5 pattern occurs most frequently in the 

months of April and May, with just over 50% of the instances of this pattern occurring in 

those two months. However, the two exceedance days that were associated with the C5 

pattern occurred in the months of August and September. 

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Figure 2. Typical synoptic meteorological characteristics for C1 pattern. C1 pattern associated with 

westward extension of quasi-permanent pressure feature known as Bermuda High. C1 pattern 

characterized by light southerly flow at surface, high temperatures, and high incoming solar

radiation. The C1 pattern accounts for over 32% of all days of ozone monitoring season, and 82% of 

summer days (Anderson, 2003). 

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Figure 3. C1 ozone concentrations statistics by month. C1 pattern consistently exhibits high ozone 

concentrations across all months except October in comparison with other synoptic regimes. C1 

accounts for 82% of all ozone exceedances in Kansas City (Anderson, 2003). 

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-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

1-Apr

16-Apr

1-

May

16-May31-May

15-Jun30-Jun

15-Jul30-Jul

14-Aug29-Aug

13-Sep28-Sep

13-Oct28-Oct

Figure 4. Daily mean time series for ozone seasons 2000-2002 of standardized principal component

score associated with the Liberty monitoring site, Kansas City, MO (Anderson, 2003). 

Another multivariate statistical analysis was used to assess the normal ozone trend in 

Kansas City for this study as well. This phase of the Kansas City Ozone Climatology 

Study utilized principal components analysis (PCA) to analyze both the spatial and 

temporal characteristics of variations in ozone concentrations. The time series of PC 

Scores for the Liberty monitoring site (see Figure 4), can be plotted to show the normal 

ozone concentration during the ozone monitoring season. According to Anderson (2003), 

the seasonal trend of ozone concentrations begins with below normal concentrations 

during the month of April continuing through the middle of May when the ozone 

concentrations reach values equivalent to the seasonal mean value. Peak values are 

normally observed in the middle of July and return to seasonal mean values by the middle 

of September. This analysis is important in that it is another statistical tool that elucidates 

the normal trend in ozone patterns in Kansas City. The smoothed ozone pattern 

represented by the solid line in Figure 5 shows that typical ozone concentrations are well 

below the seasonal mean value in the month of April and do not approach seasonal mean 

values until the middle of May. As a result, the PCA time series demonstrate that the 

ozone concentrations observed at the Cass County, MO monitoring sites on April 12-13, 

2003 are well above the average 8-hour ozone concentration for the equivalent time 

period. A value of 93 ppb, 8-hour concentration as observed on April 12, 2003 would 

have a standard deviation of two-three times greater than the ozone seasonal mean value, 

and is well beyond any single day that has been recorded for the month of April. 

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Figure 5. Typical C5 synoptic pattern. C5 pattern characterized by the absence of strong synoptic 

features, often resulting in calm or light wind speeds at the surface, moderate daytime temperatures 

and insolation. Dominant early season pattern. 

The results form the basis of our understanding of normal ozone climatological 

characteristics for the Kansas City area for the month of April and also for what is 

typically observed on ozone exceedance days. In summary, the highest ozone 

concentrations are associated with the C1 (summertime anticyclonic) pattern, and this 

pattern also accounts for the vast majority of ozone exceedance days (29 of 34 

exceedance days from 2000 – 2000 or 82% all exceedance days). Of all 633 days of the 

study period, only two instances of the C1 pattern occurred in the month of April. With 

this understanding of the frequency of occurrence of the C1 pattern in the early period of 

the ozone monitoring season, it was highly unusual to observe such an extreme ozone 

event in the month of April. Days in April were most evenly distributed among patterns 

C4-C6, which also exhibit strong seasonality, being most prevalent in the early and late 

months of the ozone monitoring season. Of the five remaining exceedance days, ozone 

stratification placed two exceedance days in the C5 pattern, and the remainder in C2, C4, 

and C6. 

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Figure 6. C5 summary ozone statistics by month. C5 dominant in April and May period, accounting

for 50% of the instances of this cluster in these months. Note that median ozone concentration for 

C5 pattern in month of April is 48 ppb, with maximum value for C5 pattern in April being 65 ppb. 

Having established a basis for normal ozone climatology for the month of April and also 

for ozone exceedance days in Kansas City, the analysis procedures of Anderson (2003) 

were reapplied to the April 2003 period to compare conditions for this period with the 

results of our the previous study. Specifically for the exceedance days of April 12 and 

13, 2003, each day fell into the C5 pattern. From the basis of climatic norms, the 

occurrence of the C5 pattern during this period of the year is reasonable, as over 22% of 

instances of this pattern normally occur in the month April. However, recall the 

discussion of the results of the analysis when 8-hour ozone concentrations are stratified 

by meteorological pattern, we find an entirely different situation. While it is routine for 

the C5 pattern to occur in the month of April, on the basis of statistical analysis we would 

not expect to observe any exceedances under this pattern in April. The summary 

statistics for the daily maximum 8-hour average concentration distribution for the C5 

pattern in April show that the median ozone concentration is approximately 48 ppb, and 

the maximum observed concentration of the C5 pattern in April is approximately 65 ppb 

(see Figure 4). The occurrence of a 93 ppb 8-hour average observation on April 12, 

2003 would be statistically classified as an extreme observation well outside the normal 

distribution for this pattern in the month of April. Likewise, using simple probability 

statistics, the probability of an exceedance occurring during any period of the ozone 

monitoring season under the C5 pattern is at maximum 0.3% (Anderson, 2003). 

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2.1 Meteorological Analysis 

The climatological analysis results described in Section 2.0 of this document indicated 

that the April 12 – 13, 2003 period were both classified as a type C5 pattern, typified by 

the presence of weak synoptic systems, usually anticyclones positioned to the south of the 

Kansas City area with a frontal system, usually a stationary front, located to the north of 

the Kansas City. 

Surface synoptic charts for the April 12 and 13, 2003 period confirm the high degree of 

similarity to the mean conditions of the C5 classification. On April 12, 2003 (see Figure 

6), an anticyclonic system was located just to the southeast of the Kansas City area with a 

stationary front just to the north of Kansas City. On April 13, 2003 (see Figure 7) an 

anticyclonic system previously located over North Dakota appears to have migrated to 

the east and was positioned over Michigan. At the same time, a low pressure system

started to developed on the leeside of the Rocky Mountains over Montana and North 

Dakota with a trailing trough. The twofold effect of the migration of the anticyclone and 

formation of the leeside cyclone created a southerly flow in advance of the developing 

low and front, and also the retrograde of the stationary front located to the north of the 

Kansas City area. 

Figure 7. Surface synoptic chart for April 12, 2003. Analysis valid at 0600LST. 

 

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The additive effect of these synoptic changes likely played a significant role in limiting 

the dispersive capacity of the atmosphere significantly. First, the presence of the 

anticyclonic system over South Central Missouri on April 12, 2003 likely resulted in very 

light and less coherent windfields over Western Missouri and Eastern Kansas near the 

core of the system. The result likely would contribute to near stagnation over this region 

on that day. The retrograde of the stationary front from the April 12-13, 2003 time frame

back across Missouri compounded this by serving as a blocking mechanism to any 

normal zonal flow (west-east) wind flow pattern. 

Figure 8a. Surface synoptic chart for April 13, 2003. Analysis valid for 0600 LST.

2.2 Lagrangian Particle Modeling Analysis 

In order to test this hypothesis, it was necessary to run dispersion simulations to simulate 

the effect of the cumulative effect of the presence of the anticyclonic system and the 

retrograde of the stationary front with hypothetical emissions in the general geographic 

location where the Flint Hills fires occurred during the April 10-13, 2003 timeframe. The 

Pennsylvania State/National Center for Atmospheric Research (NCAR) nonhydrostatic 

numerical meteorological model MM5 was run for the period of April 9 – 13, 2003. The 

MM5 simulation was run in a two-way nested configuration with 36 km and 12 km

domains. MM5 was initialized with 3DAnal and SfcAnal data from the ETA model 

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available from NCAR. The MM5 solution was then processed to extract wind and other 

thermodynamic information necessary to drive the lagrangian particle dispersion model 

(LPDM) FLEXPART. 

 

The results from the forward lagrangian simulation confirm the hypothesis (see Figure 

8b). In three days time starting on April 9, 2003, the majority of the hypothetical 

emissions of the simulated Flint Hills fires had not progressed beyond the border of 

Missouri. This age of the air mass in this simulation is indicated by the color of the 

particles, with older particles exhibiting the warmer colors of orange, red, and purple. 

From the forward simulation, we can see that emissions that would have been three days 

old were still present within the Eastern Missouri region. The effect of the retrograde of 

the stationary front can also be observed in this simulation. The stratification of particles 

along the northwest-southeast axis shown in Figure 8b is actually the blocking effect due 

to wind directional difference on the both sides of the front. Therefore, the northeastward 

movement of the particles is severely restricted by the presence of the front. As the front 

continued to retrograde back across Missouri, many of the emissions that had been 

transported farther north and east are actually being transported back towards the Kansas 

City area, adding to the already accumulating emissions from the Flint Hills fires. 

As long as only linear processes are considered, it is possible to reverse a dispersion 

problem simply by running a LPDM backward in time. This is referred to as inverse 

lagrangian particle modeling. In analogy to forward simulations we may call the particle 

cloud produced by a backward simulation a ‘‘retroplume’’. Essentially, a large number of 

particles is released at a receptor and transported backward in time. Then the residence 

time of all particles, normalized by the total number of released particles, can be 

determined on a uniform grid. The residence time in a particular grid cell is proportional 

to the contribution a source with unit strength in this cell would make to the mixing ratio 

at the receptor. From here, it also possible to construct a spatial plot which delineates the 

regional extent of areas which the air mass passed over prior to arriving at the receptor 

location. This is often referred to as an “influence function.” This technique was utilized 

for the Liberty monitoring site. Using the FLEXPART LPDM, the wind fields were 

reversed for the same study period as described for the forward simulation. The resultant 

“retroplume” delineates the areal extent in which an air mass passed over prior to arriving 

at the Liberty monitor. Therefore, we are able to more accurately judge potential source 

regions of influence. As shown in Figure 8c, the retroplume for the Liberty monitor at 0Z 

on April 11, 2003 clearly shows that the areas of eastern and central Kansas and north 

central Oklahoma were the most likely areas at a regional level that influenced the 

Liberty monitoring site. Utilization of this technique confirms that these regions and the 

burning activities within each likely reached the Clay County monitoring sites and 

influenced the ozone values therein. 

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Figure 8b. Time series of FLEXPART analysis for the time period April 8 – 13, 2003. 

Color coding of particles represents age of particle from release time. Each color

represents a delta of twelve hours.

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Figure 8c. Inverse lagrangian model analysis for Liberty, MO Ozone Monitor. Analysis valid at 0Z

11 April 2003. 

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3. Air Quality Characterization 

The table below summarizes historical eight-hour maximum values measured during the 

month of April for the past twenty years at the Liberty, Missouri monitoring location 

(Site ID 29-047-0005). 

Year Monthly

High 

(ppm)

Date

1982 0.062 4/24/1982

1983 0.073 4/26/1983

1984 0.051 4/5/1984

1985 0.060 4/19/1985

1986 0.072 4/11/1986

1987 0.063 4/25/1987

1988 0.077 4/13/1988

1989 0.068 4/22/1989

1990 0.064 4/8/1990

1991 0.076 4/16/1991

1992 0.053 4/30/1992

1993 0.071 4/10/1993

1994 0.079 4/24/1994

1995 0.070 4/8/1995

1996 0.071 4/24/1996

1997 0.074 4/18/1997

1998 0.072 4/23/1998

1999 0.075 4/7/1999

2000 0.064 4/28/2000

2001 0.074 4/29/2001

2002 0.067 4/14/2002

Mean 

Value 

‘82-‘02

0.068

Std. Dev. 

‘82-‘02

0.0075

2003 0.093 4/12/2003

Table 1: Historical 8-hour Maximum Ozone Concentrations at the Liberty Site

The highest 8-hour maximum value measured during the twenty-year period between 

1982 and 2002 is 0.079 ppm. The mean value of the ‘82-‘02 monitoring data is 0.068 

ppm and the standard deviation is 0.0075. Hence, the April 2003 maximum 8-hour ozone 

value of 0.093 is more than three standard deviations greater than the mean value for the 

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‘82-‘02 time frame. The maximum value measured in 2003 is clearly not representative 

of the mean historical maximum 8-hour ozone concentration measured at the Liberty 

monitoring site location in April. The ozone monitoring data for calendar year 2003 has 

been validated by review of the Missouri Department of Natural Resources’ quality 

assurance records and on-site assessment of monitoring equipment operations. This 

review confirms that the data are valid and accurate. 

3.1 Exploration of the Cause of Exceedances

If air monitoring data are validated and accurate, yet not representative of typical 

conditions, an examination of the atmospheric and pollution source conditions under 

which the data were measured is undertaken to determine the cause. For monitoring data 

to be flagged as an unusual or an exceptional event, the conditions that cause the 

monitored value must have a low likelihood of recurrence. 

There were multiple interrelated, but distinctly separate events that occurred 

simultaneously from April 9 through April 16, 2003 that severely impacted ozone 

formation at the Liberty, MO monitor and also affected monitors across the entire state of 

Missouri. Each of these events, when considered individually would not necessarily 

cause an exceedance of the 8-hour ozone standard to occur. When the events occur 

simultaneously, however, the cumulative effect resulted in an exceptionally high 8-hour 

ozone value to be measured on April 12, 2003 in Liberty, Missouri and an unusual April 

ozone episode to occur across eastern Kansas and across the State of Missouri which 

caused exceedances of the 8-hour average daily maximum ozone national ambient air 

quality standard (NAAQS) to be measured at three monitoring locations in the Kansas 

City ozone monitoring network on April 12 and 13, 2003. 

3.1.1 Climatological Effects on Monitoring Data

Previous sections of this report discussed the regional scale climatological conditions that 

were in place during the period under consideration. The conditions during the period 

from April 12-13, 2003 are characterized as predominantly stagnant with little vertical 

mixing, coupled with a stationary front that was moving in a retrograde fashion from east 

to west. The net effect of the meteorology in play during this time period was to establish 

a large stagnant airmass with a boundary generally located along the Mississippi River 

valley. This frontal boundary prevented the ventilation of pollutants from this spatial 

domain. 

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Figure 9. Skew-T Log P Diagram Upper Air Chart for Topeka, KS. Analysis valid for 12 UTC (0600

LST) 12 April 2003. 

Upper atmospheric charts taken from the Topeka National Weather Service site for 0600 

LST on April 12 and 13, 2003 (Figures 9 and 10 respectively) provide greater clarity 

regarding the local state of the atmosphere on these days. The red line represents the 

vertical temperature lapse rate and blue represents dew point temperature lapse rates. 

Figures 9 and 10 depict the typical nocturnal inversion that usually develops shortly after 

dusk and continues until the next morning when daytime heating finally breaks up this 

inversion. However, what we find of significant importance on these days is the strength 

of the noctural inversion and its shallow depth. On both days, the temperature increased 

10° - 15° C over the first 300 – 400 meters of the atmosphere, creating a very strong yet 

shallow inversion. While a statistical comparison of the strength of nocturnal inversions 

is beyond the scope of this analysis, based upon our experiences with such data, we 

believe that these inversions are considerably stronger than would normally be observed. 

Combined with light, almost incoherent winds at the surface, this would result in the 

trapping and buildup of ground based emissions during the night into early morning 

hours. 

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Figure 10. Skew-T Log P Diagram Upper Air Chart for Topeka, KS. Analysis valid for 12 UTC 13

April 2003. 

An examination of the raw hourly ozone monitoring data across the spatial domain from

east-central Kansas, across to the Mississippi River follows. Hourly ozone values are 

displayed because they can be readily correlated with the prevailing meteorological 

conditions and other gaseous and particulate pollutant species, which are collected 

simultaneously across the spatial domain under study. 

For comparative purposes, first consider the ozone monitoring data collected at the Cedar 

Bluff, Kansas monitoring location (Figure 11). This monitoring site is situated in a rural 

location and is unimpacted by either the stagnant air mass or the combustion products 

present in the atmosphere across eastern Kansas and Missouri from the Flint Hills fires

(recall Figure 1). When examining the data from the Cedar Bluff monitor, you observe a 

pattern which is typical of rural background ozone monitoring locations with low 

maximum values and a flat daily profile across the time period from April 7 – 15. Hourly 

ozone concentrations are observed to cycle up and down around the 0.02 ppm line on a 

daily basis, consistent with daylight and night time hours. (Note: In all graphs presented, 

the x-axis grid intercepts on the graphic correlate with the midnight hour on the specified 

day) 

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Figure 11: Cedar Bluff Ozone Data

The data presented in Figure 12 clearly illustrates the effect of a large stagnant airmass on 

ambient air ozone concentrations across east-Central Kansas and all of Missouri. Recall 

the modeling analysis presented in Figure 8b which depicted the extent of airmass 

stagnation during the five day period from April 8-13 which essentially trapped emissions 

and emission by-products across eastern Kansas and the entire State of Missouri. Note 

that during the period of April 7 and 8, there is little apparent correlation between the 

monitoring locations east of Cedar Bluff. By April 9, however, the monitoring sites 

respond in the same manner across a very large spatial domain. This indicates that all 

monitoring sites were equally affected by ozone simultaneously, which could only occur 

under regional scale stagnation conditions. It is also instructive to observe that that 

monitoring sites which are closer to the eastern edge of the domain (Kansas City area) 

trend higher in absolute concentration. Finally, note how all monitoring sites east of 

Cedar Bluff trend upward in concentration from April 10 through the 13th and then trend 

down afterward. This is also due to the large scale stagnation present and lack of 

ventilation which would normally allow the pollutant rich atmosphere to be diluted or 

transported further to the east. 

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Figure 12: Hourly ozone across the spatial domain. Note: Cedar Bluff Data at bottom

3.1.2 Co-occurrence of Gaseous Pollutants Related to 

Combustion Sources and the Effect on Ozone 

Concentrations 

In addition to a large-scale ozone event, additional pollutants were measured across the 

affected spatial domain that led to the conclusion that a significant combustion source 

was impacting the entire area. Specifically, the coincidence of simultaneous 

measurement of Carbon Monoxide (CO), particulate matter less than or equal to 2.5 

microns in aerodynamic diameter (PM2.5), Nitric Oxide (NO), and Nitrogen Dioxide 

(NO2) are all attributed to smoke producing combustion sources. Figures 13, 14, 15, and 

16 illustrate clear correlation between these pollutants. Unfortunately, not all ambient air 

monitoring stations are equipped with monitors for all the criteria pollutants. The data 

presented illustrate the presence of smoke emissions across the entire spatial domain. 

 

With background ozone concentrations already elevated across the eastern State of 

Kansas and all of Missouri due to a lack of atmospheric mixing and dispersion, the 

conditions in the Kansas City area were ripe for ozone formation due to the presence of 

fresh emissions of nitric oxide and other ozone precursors from the large scale burning of 

biomass occurring in the Flint Hills region of eastern Kansas. 

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While the chemistry of ozone production is complex, the main features are well 

established and can be summarized as follows. Nitric oxide (NO) introduced into the 

atmosphere reacts rapidly with O3 to form nitrogen dioxide (NO2, reaction 1). NO2 can 

efficiently absorb sunlight and photo-dissociate to yield oxygen atoms (O) and NO (R2). 

These oxygen atoms in turn will react rapidly with molecular oxygen (O2) to reproduce 

O3 (R3; M represents a third molecule such as molecular oxygen or nitrogen (N2) that

absorbs the excess energy released in this reaction, thereby stabilizing the newly formed 

O3 molecule). 

R1) NO + O3 ¤ NO2 + O2

R2) NO2 + h4 (280< 2 < 430nm) ¤ NO + O 

R3) O + O2 + M ¤ O3 + M 

Ozone is removed from the atmosphere through several processes, including both 

gaseous and aqueous chemical reactions, and deposition to the ground. In polluted 

atmospheres, during the nighttime, R2 ceases to occur since it is driven by sunlight. 

Consequently, R1 can dominate nighttime reactions leading to a complete removal of 

ozone when sufficient NO is present. This process is dubbed NOx scavenging. In rural 

areas, NO concentrations are generally too low to scavenge ozone appreciably. NOx

scavenging can also occur during the daytime where NO concentrations are high. 

Therefore, ozone levels experienced during the day depend on the relative amounts of 

different pollutants in the atmosphere available to contribute to the photochemical 

reaction, which in turn determines which of the chemical reactions are driving ozone 

chemistry at a particular time. 

The set of equations presented above represent the most basic and least complex 

equilibrium conditions for formation of ozone. Other, more complex, but well 

established reactions that provide additional ozone formation potential include the 

interaction between volatile organic compounds, hydroxy radicals, carbon monoxide, and 

ultraviolet radiation (sunlight). The presence of these additional ozone precursor 

materials in the atmosphere is confirmed by highly correlated concentrations of carbon 

monoxide with nitric oxide in Wichita, Kansas (Figure 13). 

The monitoring data from the Wichita site shows a classic profile of fresh combustion 

source pollutants impacting the monitoring site with CO, NO, and NO2 concentrations

rising and falling simultaneously. The reason the emissions are classified as fresh is due 

to the dominance of the nitric oxide signal. Nitric oxide is a highly reactive ozone 

precursor during daylight hours and an active ozone scavenger during nighttime hours. 

The Wichita data set reflect this behavior quite well with ozone concentrations dropping 

to near zero in the presence of excess NO during the night while, during daytime hours, 

ozone concentrations rise as NO is consumed in the photochemical reaction. 

EPA Region VII/Air Analysis Group Analysis of April 2003 KC Ozone Exceedances 

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Figure 13: Wichita Health Dept. gaseous pollutant data

The data from the JFK site (Figure 14) show similar, but significantly different behavior. 

Once again, the data are correlated with smoke emissions, but this site has continuous 

ozone, NO, and PM2.5 monitors. This site illustrates the relationship between NO and 

fine particulate smoke concentrations due to the high correlation between peak values of 

NO (ppm) and PM2.5 (3g/m3

) over the time series. The only important difference in this 

data set is that the correlation ceases to exist as excess NO is consumed in the atmosphere 

during conversion to NO2 and subsequently, ozone. Note the y-axis scale of figure 13, 

where the maximum NO concentrations measured in Wichita during this time frame were 

in the 70 ppb range, the available NO for conversion to ozone at this monitoring location 

was in the range of 220-270 ppb, yet ozone concentrations at the JFK site did not exceed 

the ozone standard, largely due to the excess reactive NO in the atmosphere titrating out 

available ozone. Observe that ozone concentrations drop to zero during the nighttime 

hours on April 10-12 with very high excess NO still present in the atmosphere. 

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Figure 14: JFK Monitoring Site Data

The data from the Liberty monitoring site (Figure 15) also illustrate similar but different 

behavior. At the Liberty monitoring site, the NO/NO2 ratios are reversed where the 

prevalent oxide of nitrogen present is NO2. The prevalence of NO2 and the lack of 

measured NO is a clear indicator that photochemical oxidation of NO has taken place to 

form excess ozone at this site. The Liberty monitoring site is located approximately 

twenty miles directly northeast of the JFK location, which is sufficiently downwind under 

the prevailing stable meteorological conditions for photochemical formation of ozone to 

occur. Note the correlation of NO peaks on April 10 and 11 between the JFK and Liberty 

sites. They occur during the same time, yet NO concentrations at Liberty are 

substantially diminished due to ozone formation. Observe also, the lack of NO signal at 

the Liberty monitoring site on the 12th, accompanied by elevated NO2 and high ozone 

concentrations that carry over into the 13th. This effect is not seen anywhere else in the 

ozone-monitoring network because all of the available NO for excess ozone formation 

has been consumed in the photochemical reaction. 

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Figure 15: Liberty Monitoring Data

3.1.3 Co-occurrence of Particulate Pollutants Related to 

Combustion Sources 

In addition to gaseous pollutant monitors, the national air monitoring network consists of 

monitors for particles, both fine (PM2.5) and coarse (PM10). The fine particle sampling 

network also has a subset of sites that collect PM2.5 samples for chemical speciation

analysis. Data from the speciation sampling network can be very useful to characterize 

emission sources and their potential to impact pollutant concentrations. Samples 

collected by the chemical speciation network represent a 24-hour average concentration

instead of the hourly averages reported by the gaseous pollutant network. There were six 

monitoring sites in operation simultaneously on April 12 which can be used to 

characterize the origin of fine particle pollution on that day. 

Figure 16 provides the profile of chemically speciated PM2.5 across eastern Kansas and 

the state of Missouri. Virtually all chemical species measured respond equally and 

simultaneously across the entire domain with the exception of the total fine particle mass 

and the carbon fraction data. Total mass is characterized as the sum of the mass of all 

chemical species present, the data indicate that the highest mass concentrations were 

measured on the western side of the monitoring network and trended downward on April 

12 as distance increases to the east. 

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Figure 16: PM2.5 Chemical Speciation Profile for April 12

The prevalence of organic carbon collected on April 12 clearly indicates that a 

combustion source is the primary contributor to fine particle mass. In order to 

characterize the type of combustion source, analysis of the metal species data must be 

undertaken (Figure 17). 

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Figure 17: PM2.5 Speciated Metals Profile on April 12

The primary metal species of interest is potassium as displayed in Figure 18. On April 

12th, potassium is elevated across the entire monitoring network in a manner similar to 

the organic carbon and the calcium distributions. On all other days in the time series, 

concentrations are low and well grouped. 

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Figure 18: Speciated PM2.5 Potassium Time Series 

In order to further elucidate the relationship between fine particle chemical species and

potential pollutant sources the PM2.5 major constituents and trace metal species data are 

analyzed using positive matrix factorization in the next section. 

 

 

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4. PM2.5 Source Apportionment Analysis 

Chemical composition data for fine and particles collected at JFK PM2.5 speciation site in Kansas 

City, KS was analyzed using positive matrix factorization (PMF). The objective was to identify 

the possible particle sources contributing mass at the sampling site. PMF uses estimates of the 

error in the data to provide optimum data point scaling and permits a better treatment of missing 

and below-detection-limit values. It also applies the non-negativity constraints to the factors. 

Seven possible source factors were obtained from the fine particle data set and have been 

identified as possible aerosol sources for the fine particles. They are: (1) motor vehicles described 

by the high concentrations of organic carbon (OC) and elemental carbon (EC) with some soil dust 

components, (2) biomass burning which is typified by high concentrations of OC, EC and K, with 

presence of soil dust, (3) unidentified combustion source characterized by OC, SO4, S, Cu, Zn, 

and Pb, (4) a possible second type of biomass signature, characterized by OC and K, (5) soil 

factor represented by Al, Si, Ca, Ti and Fe, (6) S-factor (secondary sulfate) which is likely to

represent coal power plant emissions, and (7) N-factor (secondary nitrate) which is likely to 

represent more distant combustion emissions during the winter and spring months when the 

formation potential for ammonium nitrate is the greatest.

0

200

400

600

800

1000

1200

1400

NH4

NO3

SO4

EC

OC

Al

At

Br

Ca

Cl

Cu

Fe

Pb

Mg

Mn

Ni

K

Se

Si

Na

St

S

Ti

V

Zn

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Figure 19a. Source profile for Factor 1. 

Fortunately, the PM2.5 speciation network was operational on April 12, 2003, coinciding 

with the first day of the exceedances in Kansas City. Three source profiles exhibited a 

rather strong signal on April 12, 2003. Factors 1, 5, and 7 exhibited the strongest signals. 

Factor 1 is characterized by the presence of high OC/EC loading with smaller amounts of 

EPA Region VII/Air Analysis Group Analysis of April 2003 KC Ozone Exceedances 

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Al, Ca, Fe, K, and Si. High OC and K are usually indicative of biomass burning. The 

presence of the Al, Ca, Fe, and Si are soil dust components. Factor 5 is similar with the 

high OC/EC loadings, with lesser amounts of K, Al, Fe, and Zn. Upon initial 

investigation, both profiles share similar characteristics and are thus somewhat difficult to 

interpret decisively. A literature search of possible source profiles was conducted and 

results of the Kansas City PMF analysis compared to published literature. It was 

concluded that the Factor 1 profile was more likely due to biomass burning and Factor 5 

more likely associated with motor vehicles with a small road dust component. It is 

important to note that there is a high degree of uncertainty, based largely upon the human 

interpretation and comparison of known profiles, in the results of this analysis. Factor 1 

(Figure 19a) displayed a lower OC to EC ratio in comparison to Factor 5 (Figure 19b). 

An example from the literature search (Figure 20) indicates that the lower OC/EC ratio 

and larger K contribution is associated with biomass burning. The higher OC/EC ratio 

combined with the Fe, Al, and Zn in Factor 5 are more consistent with the mobile source 

signatures with reentrained road dust. On April 12, 2003 the strength of these two factors 

were 4 and 6 times higher than normal (Factors 1 and 5 respectively, see Figures 19c and 

19d). 

Each factor score is the highest of the two year dataset, and is consistent in that, while the 

interpretation what the possible factors represent can be somewhat uncertain, the strength 

of these factors clearly indicate the characteristcs of a combustion source present in the 

dataset on April 12, 2003. The combination of high OC with K, Al, Ca, Fe, and Si 

confirm the presence of the biomass burning on April 12, 2003. The higher loadings due 

to the presence of the trace elements more commonly associated with soils are theorized 

to be due, in part, to the nature of the burning activity conducted in Kansas and 

Oklahoma. Most literature surrounding source profiles for biomass burning refer more to 

wood burning activity than to most other sources of biomass combustion. Prairie fires, 

by their nature, burn closer to the land surface than combustion from wild fires (forest) or 

domestic wood burning. It is our theory that the convective heat from the burning of the 

tall grass prairie likely entrains a small amount of soil from either the land surface or soil 

present on the vegetation and is carried aloft and transported downwind. This would 

account for the presence of a soil signature in concert the with biomass signature 

observed in Factor 1. Due to the confirmation of the presence of a large biomass burn 

concurrent with the April 12 sampling date, we are reasonably confident in our analysis 

that this signature likely represents to biomass burning. 

Factor 5 is more difficult to interpret, both in terms of identification and in understanding 

the timing of the presence of the factor strength, especially on April 12. In our judgment, 

Factor 5 was most likely attributable to mobile source activity than to other possible 

profiles. Curiously, the strength of the factor on April 12 is not consistent with our 

understanding of mobile source activity, both in terms of diurnal, weekly, and seasonal 

activity patterns. April 12, 2003 landed on a Saturday, which would mean that normal 

weekend traffic patterns for Kansas City likely would have occurred. Weekend traffic 

patterns are normally lighter than weekdays. This difficulty is also compounded by the 

fact that April 12, 2003 was during the Easter weekend period. Traffic patterns would 

have likely been lighter during this period in comparison to other normal weekends. As 

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such, the strength of the factor does not comport well with our understanding of the 

expected influence of traffic patterns and, as a result, we are not able to provide a 

confident judgment on the actual nature of the source represented by Factor 5. Initial 

sensitivities were conducted to determine if the Factor 5 solution was an artifact of either 

too many or too few factors selected for the initial solution. Factor solutions from six to 

eleven were briefly explored. As the number of factors increase, the Factor 1 and Factor 

5 signatures appear to merge and the single source strength for that profile increases to

nearly 10 in that analysis, indicating the high similarity of the profiles. This may be an 

indication that these may indeed be the same source, with just a slight differentiation. 

However, two other issues arise from this. Recall that we are characterizing the entire 

PM2.5 data set for the JFK site, not just the sample from April 12, 2003. Other solutions 

degrade as the number of factors increase. For example, in our understanding of the 

chemistry of secondary aerosol formation, there should be similar amounts of ammonium

ion that are present in both the S-factor and the N-factor. However, when the number of 

factors increase, most of the ammonium ion loads on the S-factor to the exclusion of the 

N-factor. Secondly, the PMF analysis tends to stratify the speciation data in ways that 

produce “phantom” profiles, or tries to stratify the data too far thus generating too many 

profiles, some of which simply would been part of another profile in solutions with fewer 

factors selected. Since time was limited to fully analyze the results and explore different 

factor solutions, we recommend further PMF analysis of the JFK speciation to further 

elucidate the nature of potential sources influencing PM2.5 values in Kansas City. 

0

200

400

600

800

1000

1200

NH4

NO3

SO4

EC

OC

Al

At

Br

Ca

Cl

Cu

Fe

Pb

Mg

Mn

Ni

K

Se

Si

Na

St

S

Ti

V

Zn

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Figure 19b. Source profile for Factor 5. 

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0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

6/6/20017/6/20018/6/20019/6/2001

10/6/200111/6/200112/6/2001

1/6/20022/6/20023/6/20024/6/20025/6/20026/6/20027/6/20028/6/20029/6/2002

10/6/200211/6/200212/6/2002

1/6/20032/6/20033/6/20034/6/20035/6/20036/6/20037/6/2003

Figure 19c. Time series of estimated Factor 1 source strength. 

0

1

2

3

4

5

6

7

6/6/20017/6/20018/6/20019/6/2001

10/6/200111/6/200112/6/2001

1/6/20022/6/20023/6/20024/6/20025/6/20026/6/20027/6/20028/6/20029/6/2002

10/6/200211/6/200212/6/2002

1/6/20032/6/20033/6/20034/6/20035/6/20036/6/20037/6/2003

Figure 19d. Time series of estimated Factor 5 source strength. 

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Figure 20. Source profiles identified by Ramadan, et al. (2000) for PM2.5 speciation data for 

Phoenix, AZ. 

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5.0 Conclusion 

The Missouri Department of Natural Resouces requested that EPA Region VII “flag” 8-

hour ozone monitoring data collected on April 12 and 13, 2003 on the basis of the fact 

that emissions from agricultural burning were documented to be impacting eastern 

Kansas and virtually all of the State of Missouri. At first glance, and in accordance with 

existing guidance documents related to granting exceptional events flags for monitoring 

data, the request did not appear to withstand the test for consideration as an exceptional 

event. It is important to point out, however, that the existing EPA guidance for flagging 

air quality data is “Guideline on the Identification and Use of Air Quality Data Affected 

by Exceptional Events” EPA-450/4-86-007, July 1986. This guidance document 

provides no specific guidance on data flagging considerations for either 8-hour ozone or 

PM2.5 monitoring values. The ’86 guidance document does specifically address 

prescribed burning, but only to the extent that direct emissions from burning activities 

may affect PM or CO data. Upon further consideration, staff from EPA Region VII 

determined that a more detailed examination of the climatological conditions and the 

ambient air monitoring data may elucidate a relationship between biomass burning in the 

Flint Hills region of Kansas and elevated 8-hour ozone concentrations measured in the

Kansas City metro. 

The key test for determination of whether a specific event may be considered as 

exceptional is the likelihood of recurrence of the cause of that event. Clearly the 

likelihood of recurrence of agricultural burning in the Flint Hills of Kansas is very high, 

but the likelihood of having the entire burn occur again within 2 days is very unlikely. 

Thus, we do not expect to measure an 8-hour ozone exceedance in Kansas City during the 

month of April. Analysis of historical maximum 8-hour ozone concentrations measured 

in the month of April led to the determination that the value of 0.093 ppm reported on 

April 12, 2003 at the Liberty monitoring site is highly atypical based upon statistical 

analysis of historical climatological trends. If this situation would occur again, it would 

not likely be considered an exceptional event. 

Knowing that one of the key factors influencing ground level ozone formation is 

meteorology, an analysis of the historical climatological conditions conducive to ozone 

formation was performed. The analysis conducted by Anderson (2003) concluded that 

the probability of occurrence of the synoptic weather pattern observed over the region 

during April 12-13, 2003 was approximately 22%. Therefore, we are able to conclude 

that there was nothing atypical or otherwise exceptional about the meteorological 

characteristics of those days. While these meteorological conditions were not atypical for 

the April timeframe, the occurrence of a 93 ppb 8-hour ozone exceedance is highly 

improbable. According to Anderson (2003), the probability of an 8-hour exceedance 

under this synoptic pattern during any period of the ozone monitoring season is 0.3% at 

maximum.

The LPDM analysis clearly illustrates that the synoptic pattern in place during the April 

12-13 timeframe caused emissions from the Flint Hills burning to be transported 

northward along the Missouri/Kansas border where they were trapped and actually 

EPA Region VII/Air Analysis Group Analysis of April 2003 KC Ozone Exceedances 

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transported from east to west in a retrograde fashion due to the presence of a blocking 

front. The net effect of this meteorological pattern resulted in trapping fresh and aged 

emissions from the Flint Hills fires for as much as five days over eastern Kansas and 

western Missouri. Likewise, the inverse LPDM analysis confirms that the areas of 

eastern Kansas and north central Oklahoma were within the source region of influence of 

the Clay County, MO ozone monitors. 

Analysis of the ambient air monitoring dataset was undertaken to determine if such 

pollutant build-up across the region could be determined and whether sufficient 

monitoring data existed to draw a conclusion about the likelihood of recurrence of the 

cause of the ozone exceedances. 

Ambient air monitoring data clearly illustrate the build-up of ozone concentrations across 

the entire State of Missouri and eastern Kansas during the April 10-15 timeframe. In 

addition to ozone data, monitoring data analysis of carbon monoxide, nitric oxide, 

nitrogen dioxide, and PM2.5 data was undertaken. High correlation between the gaseous 

products of biomass combustion existed across the entire study area. Specific analysis of 

the Kansas City area monitoring data was undertaken to ascertain a causal relationship 

between the emissions from biomass burning and 8-hour ozone exceedances. 

Exceptionally high concentrations of nitric oxide (approx 270 ppb hourly max) were 

measured at the JFK recreation center in downtown Kansas City, Kansas on April 10, 11, 

and 12 with corresponding high ozone values measured at the Liberty monitoring site 

which is located approximately twenty miles downwind. Furthermore, the ratio of NO to 

NO2 is reversed at Liberty which indicates photochemical oxidation of NO in the 

atmosphere during the ozone formation process. 

Of course, biomass burning is not the only possible source of nitric oxide, as power 

plants and other combustion sources can produce significant NO emissions. Therefore, 

analysis of the PM2.5 chemical speciation data was undertaken to ascertain the presence 

and source of pollutant smoke that was present in the atmosphere during the April 12 

timeframe. Positive matrix factorization analysis of the sulfate, nitrate, ammonium ion, 

and carbonate species in conjunction with metals species data in the PM2.5 dataset from

the JFK monitoring site indicate that the most likely and influential source on fine 

particle concentrations on April 12 was biomass burning. While other factors may have 

influenced the speciation data observed on April 12, 2003, we are unable to conclude if 

these influences did indeed exist or were part of the same signature. Other factors such 

as mobile source/soil appear present on these days, but the timing and strength of the 

signature is inconsistent with our understanding of the behavior of mobile source 

patterns. It is important to note the high degree of similarity between these profiles and 

therefore there exists the potential for error in human judgement when analyzing these 

profiles. We recommend further, more detailed study of the source apportionment 

analysis to determine the actual nature of these profiles. 

Therefore, it is our opinion based upon the available forensic, meteorological, and air 

quality data, that large scale air mass stagnation conditions caused a gradual build up of 

EPA Region VII/Air Analysis Group Analysis of April 2003 KC Ozone Exceedances 

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ozone concentrations across all of eastern Kansas and the State of Missouri. Based upon 

multiple corroborating analyses (satellite imagery, inverse LPDM analysis, air quality 

analysis, and source apportionment), we believe the exceedances of April 12 and 13, 

2003 to be highly related to the concurrent biomass burning in the Flint Hills region of 

Kansas. Likely, the trapping mechanism created by the retrograde of the stationary front 

moving across Missouri in conjunction with the presence of an anti-cyclonic system

situated over the south central United States caused the build up of fresh gaseous 

pollutants from the Flint Hills fires to occur in far eastern Kansas at the JFK site. 

Although we conclude that the meteorological conditions of April 12 and 13 were not 

typically conducive to ozone formation as evidenced by climatological characteristics 

(Anderson, 2003), sufficient excess nitric oxide was present in the atmosphere to react 

and add incrementally to the already elevated ozone background concentrations present at 

the Liberty, Watkins Mill, and Rocky Creek monitoring locations to cause exceedances 

of the 8-hour ozone standard to occur only at those sites. The coincidence of all of these 

factors that contributed simultaneously to 8-hour ozone exceedances at the Liberty, 

Watkins Mill, and Rocky Creek monitoring locations is considered to be truly 

exceptional and highly unlikely to recur. 

6. References 

Anderson, Bret A. (2003a): Airmass History Analysis During High and Low Ozone Days 

in the Kansas City Metropolitan Area. Presentation to Regional Science Forum, United 

States Environmental Protection Agency Region 7, Kansas City, KS. 23 May 2003. 

Anderson, Bret A. (2003b): Synoptic Climatological Analysis of Surface Ozone for the 

Kansas City Metropolitan Area (2000-2002). Draft United States Environmental 

Protection Agency Region 7 Technical Report, Kansas City, KS. 31 December 2003. 

Eder, Brian K., Jerry M. Davis, and Peter Bloomfield (1993): A Characterization of the 

Spatiotemporal Variability of Non-Urban Ozone Concentrations Over the Eastern United 

States. Atmospheric Environment 27A, 2645-2668. 

Moody, J.L., Oltmans, Samuel J., Levy, Hiram II, and Merrill, J.T. (1995): Transport 

climatology of tropospheric ozone: Bermuda, 1988-1991. Journal of Geophysical 

Research 100, 7179-7194. 

Moody, J.L., Munger, J.W., Goldstein, A.H., Jacob, D.J. and Wofsy, S.C. (1998): 

Harvard Forest regional-scale air mass composition by Patterns in Atmospheric Transport 

History (PATH). 

Journal of Geophysical Research 103, 13181-13194. 

Ramadan, Ziad, Xin-Hua Sing, and Philip K. Hopke (2000). Identification of Sources of 

Phoenix Aerosol by Positive Matrix Factorization. Draft submitted to Journal of Air and 

Waste Management Association. 

EPA Region VII/Air Analysis Group Analysis of April 2003 KC Ozone Exceedances 

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Stohl, Andreas (1996): Trajectory statistics – a new method to establish source-receptor 

relationships of air pollutants and its application to the transport of particulate sulfate in 

Europe. Atmospheric Environment 30, 579-587. 

Stohl, Andreas (1998): Computation, accuracy and applications of trajectories – a review 

and bibliography. Atmospheric Environment 32, 947-966. 

Stohl, Andreas, and Trickl, Thomas (1999): A textbook example of long-range transport: 

Simultaneous observation of ozone maxima of stratospheric and North American origin 

in the free troposphere over Europe. Journal of Geophysical Research 104, 30445-30462. 

Stohl, Andreas (2002): A replacement for simple back trajectory calculations in the 

interpretation of atmospheric trace substance measurements. Atmospheric Environment 

36, 4635-4648. 

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