PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 1

A CONCEPTUAL MODEL FOR AMBIENT FINE PARTICULATE 

MATTER OVER SOUTHEAST MICHIGAN: 

HIGH CONCENTRATION DAYS 

Version 1.0 

October 1, 2008 

Prepared by 

Jay R. Turner 

Washington University 

Campus Box 1180, One Brookings Drive 

St. Louis, MO 63130-4899 

telephone: 314-935-5480 

facsimile: 314-935-7211 

email: JRTURNER @WUSTL.EDU 

Prepared for 

Southeast Michigan Council of Governments (SEMCOG) 

535 Griswold Street, Suite 300 

Detroit, MI 48226-3602 

telephone: 313-961-4266 

facsimile: 314-961-4869 

email: INFOCENTER@SEMCOG.ORG 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 2

A CONCEPTUAL MODEL FOR AMBIENT FINE PARTICULATE MATTER 

OVER SOUTHEAST MICHIGAN: HIGH CONCENTRATION DAYS 

Version 1.0; October 1, 2008 

Prepared by Jay R. Turner*

, Washington University in St. Louis 

Prepared for Southeast Michigan Council of Governments (SEMCOG) 

EXECUTIVE SUMMARY 

In 2006, the USEPA promulgated revisions to the National Ambient Air Quality Standard 

(NAAQS) for particulate matter (PM) which tightened the 24-hour (daily) PM2.5 standard from 

65 μg/m3 to 35 μg/m3. This revision profoundly increased the frequency of exceedance days 

observed in Southeast Michigan with fourteen of the fifteen compliance monitors violating the 

standard for the period 2004-2006. An understanding of the drivers for high PM2.5 days is 

needed to support the development of effective controls strategies; this study seeks to provide 

insights into such drivers. 

At most sites in Southeast Michigan, exceedances occur predominantly – and in some cases 

exclusively – on days when the entire network is exhibiting high PM. For thirteen of the fifteen 

monitors, at least 85% of exceedances from 1999 to 2006 occurred on days when the entire 

network was exhibiting high PM. Drivers for network-wide high PM are regional transport, poor 

atmospheric ventilation across the network, or both of these conditions. Two monitors in 

particular – Dearborn and Wyandotte – frequently had exceedances on days when the entire 

network was not exhibiting high PM with 38% of the Dearborn exceedances and 27% of the 

Wyandotte exceedances occurring on such days. On these days, these sites are significantly 

influenced by nearby emission sources. Dearborn continues to be influenced by nearby emission 

sources which drive exceedances (or near exceedances) on days when the network-wide base 

concentration is as much as 15 μg/m3

 below the standard, although the frequency of such days 

appears to be decreasing. In contrast, at Wyandotte all of the days for which nearby emission 

sources were disproportionately contributing to exceedances (or near exceedances) of the 

standard were prior to 2004. At those sites not significantly impacted by plumes from nearby 

emission sources, high PM days are most often observed when the area is experiencing a 

multiday high PM episode. 

Seasonal variations in surface winds can explain the seasonal differences in frequency of sitespecific high PM days between sites in the greater Wayne County area. Sites such as Allen Park, 

which are relatively free of impacts from nearby sources, exhibit similar seasonal behavior with 

high PM days most frequent in the summer followed by the winter. The monthly distribution of 

high PM days is distorted for sites with significant nearby emission sources since there is a 

strong seasonality to the surface winds distributions. For example, Dearborn has as many high 

PM days in the winter as in the summer, with the winter season having a stronger contribution 

from nearby sources located to the southwest of the site. 

 

*

 Campus Box 1180, Washington University, One Brookings Drive, St. Louis, MO 63130-4899. 

 telephone: 314-935-5480, facsimile 314-935-7211, email JRTURNER @WUSTL.EDU 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 3

Network-wide high PM days have disproportionately high contributions from the major ions 

(sulfate, nitrate, and ammonium) compared to other days. Summertime events are dominated by 

sulfate and wintertime events are dominated by ammonium nitrate. However these so-called 

high nitrate days typically have ammonium sulfate concentrations that are at least 50% of the 

ammonium nitrate concentration. The role of sulfate on such days should not be overlooked 

when considering the impact of SO2-based regional control strategies. In general, network-wide 

PM base concentrations above ~20 μg/m3

 tend to be disproportionately influenced by major ion 

contributions and are indicative of a disproportionately high influence from regional sources. 

On network-wide high PM days the sulfate and nitrate concentrations are typically several times 

higher than the corresponding monthly median concentrations. In contrast, EC is on average 

only 1.3 times higher. This pattern suggests that network-wide high PM days are primarily 

influenced by regional transport and are to a lesser extent influenced by increased levels of 

urban-scale emissions arising from poor atmospheric ventilation. As previously stated, emission 

sources near the monitoring sites can still exert significant plume impacts regardless of the 

network-wide PM behavior driven by regional and urban-scale contributions. 

Many network-wide high PM days coincide with high nitrate, and in some cases there is 

substantial variability in PM mass concentration across the network on these days. It is 

important to determine whether the variability is real or a measurement artifact, because these 

days can influence the site-specific design values and in general can explain many of the 

exceedingly high PM levels observed at certain sites that otherwise do not appear to be 

disproportionately impacted by nearby local emission source plumes on high PM days. 

A conceptual model for fine PM over central Southeast Michigan includes four elements. The 

largest contributor to annual average PM is regionally transported material that is temporally 

varying but spatially homogeneous over the domain (indeed, this defines the spatial extent of the 

domain for the conceptual model which in this case excludes the distant sites such as Luna Pier 

and Port Huron). On some days, regionally transported PM contributions can be sufficiently 

high to cause exceedances of the daily standard when coupled with average contributions from 

urban- and finer-scale emission sources and, in relatively rare cases, the regionally transported 

PM alone can cause exceedances of the daily standard. Urban-scale emission sources (mobile, 

area, and point sources) create a spatial PM gradient across central Southeast Michigan. For 

winds from a fixed direction, these contributions create an “urban plume” with decreasing 

impacts with increasing distance from the zone of highest emissions activity. The spatial 

gradients can be clearly discerned when binning data from days with common wind patterns and 

become smeared, to some extent, when averaging over periods with varying wind patterns. At 

many sites (e.g., Linwood, East 7 Mile) a PM plume emanating from the Detroit commercial / 

industrial zone, which is nominally Dearborn and areas to its southeast towards the Detroit River, 

including Zug Island, can be distinguished from the aforementioned urban plume. At sites 

further downwind, such as New Haven, these two plumes have essentially merged into a single 

urban plume. Average impacts from these plumes depend on the monitoring site location 

relative to the Detroit population and commercial/industrial core zones and the frequency that 

winds from these zones transport the plumes to the monitoring site. Finally, certain monitors in 

the Detroit commercial/industrial zone are significantly impacted by emissions from nearby 

sources that ultimately contribute to the distant PM plume emanating from this zone. At 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 4

Dearborn and Wyandotte these sources are located southwest of the monitoring sites and 

historically have contributed to exceedances (or nears exceedances) of the daily standard. These 

sources also disproportionately influence the annual standard because they are oriented upwind 

of the sites for prevailing winds from the southwest. 

The analyses presented in this report exploited the relatively high spatial and temporal PM2.5

FRM measurement density across Southeast Michigan. Each site provided added value to the 

analysis. Future reductions in either spatial or temporal measurement density would likely affect 

the ability to update this analysis towards tracking the accountability of emission control 

programs. 

In summary, emission controls that reduce regionally transported PM are needed to reduce the 

frequency of violations of the 24-hour PM2.5 standard. Emission reductions from a few specific 

point sources, especially near Dearborn, are also needed. While regional and point source 

controls will decrease annual average PM2.5 concentrations for standardized synoptic weather 

patterns, relatively small but significant decreases could also be realized by controls on other 

urban emission sources such as mobile, area, and other point sources.
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 5

1. MOTIVATION 

In 2006, the USEPA promulgated revisions to the National Ambient Air Quality Standard 

(NAAQS) for particulate matter (PM) which tightened the 24-hour (daily) PM2.5 standard from 

65 μg/m3

 to 35 μg/m3. This revision profoundly increased the frequency of exceedance days 

observed in Southeast Michigan. For fifteen monitors over the time period 1999-20061

, there 

were 7 and 179 exceedance days (days with one-or-monitors in the area with concentration 

greater than or equal to 35 μg/m3

) under the old and new standards, respectively. While none of 

the monitors violated the old standard, for the period 2004-2006 fourteen of the fifteen monitors 

violated the new standard. Only one of the eleven sites elsewhere in the state – Grand 

Rapids – violated the standard for the 2004-2006. This behavior motivates the need for a refined 

understanding of the drivers for high concentration days in Southeast Michigan. In particular, a 

detailed description is needed of the emissions, meteorology and atmospheric processes that 

modulate PM concentrations. This “conceptual model”, with explicit emphasis on understanding 

PM2.5 high mass concentration days over the Southeast Michigan, could be utilized towards 

developing effective control strategies. 

The conceptual model presented in this document is focused on the information needed to 

support the development and implementation of control strategies to meet the 24-hour PM2.5

NAAQS. It intentionally excludes a detailed treatment of annual average concentration patterns 

and instead focuses on the subset of days exhibiting high concentrations. Figure 1-1 shows the 

elements that go into the development of a conceptual model which is necessarily dynamic and 

must be refined as new knowledge becomes available. Content and presentation of the 

conceptual model for PM2.5 over Southeast Michigan loosely follows the framework used by 

Vickery (2004) for nine North American geographic regions and as revisited by Allen and 

Turner (2008). A conceptual model for PM2.5 over St. Louis was recently developed which 

included the following elements: annual and seasonal levels of PM2.5 in relation to the massbased standards; compositional analysis of PM2.5; meteorological influences; atmospheric 

processes contributing to PM2.5; sources and source regions contributing to the principle 

chemicals of concern; and implications to policy makers (Turner and Garlock, 2007). For this 

study, the framework has been modified to accommodate the emphasis on those days with high 

PM concentrations. 

An assessment of the drivers for high concentration days, compared to annual average behavior, 

is complicated by several factors. First, high concentration days are relatively infrequent and 

thus there is limited data to probe. Second, while the standard defines a bright line for 

exceedance days, the use of threshold concentration values to censor data can mask some of the 

key features. The sensitivity of key findings to the operational definition of a high concentration 

day is important and care has been taken in this study to ensure the results are resistant to the 

selection of the threshold concentration. 

 

1

 Some of these monitors did not operate for the entire eight year period, and the monitors collect samples with 

frequency from every day to every sixth day. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 6

refinements as new knowledge emerges

Figure 1-1. Development of a conceptual model (adapted from Vickery, 2004). 

This conceptual model is grounded in an analysis of eight years of PM2.5 FRM mass 

concentration data and allied data for particle speciation and meteorology. Nonetheless, it 

should be treated as a living document, to be periodically updated as additional data becomes 

available (in particular to capture temporal trends) and revised as more-detailed analysis is 

performed on the existing data. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 7

2. APPROACH 

Extensive monitoring and data analysis has been performed for Southeast Michigan. From a 

regulatory context, most of the data analysis effort has focused on the annual-average NAAQS. 

This work focuses on the drivers for exceedances of the daily (24-hour) NAAQS. This metric 

presents certain challenges to the characterization effort. In contrast to the annual average 

NAAQS, which requires an understanding of the average contribution of sources to observed 

burdens, consideration of the daily standard must necessarily focus on a much smaller number of 

days and with interest in the drivers of the concentrations specifically on those days. Many of 

the data analysis tools, such as receptor modeling by positive matrix factorization (PMF), are 

most powerful when considering the average behavior; estimates for high concentration days are 

less reliable and indeed in many analyses extreme values are down-weighted to improve the 

stability of the solution. Air quality surveillance is relatively sparse with sustained daily FRM 

measurements at only one site (Allen Park); this provides a challenge to placing an observed 

exceedance day in a temporal context. However, the Southeast Michigan FRM network is 

relatively dense, and this greatly facilitated the ability to the analyses presented in this report. 

Semicontinuous PM mass and composition measurements certainly provide considerable insight 

and in the future their deployment should be very beneficial in refining our knowledge of high 

concentration events. 

A significant body of work has been assembled to characterize PM in Southeast Michigan with 

most-recent emphasis on the annual average PM2.5 NAAQS. Indeed, efforts currently underway 

to address the annual average standard are expected to improve the area’s status with regard to 

the daily standard. However, additional measures might be needed to eliminate violations and 

bring the area into attainment with the daily standard. Thus, the key findings from this analysis 

are compared and contrasted with the Weight-of-Evidence (WOE) developed for the annual 

standard to more fully understand the synergies between the drivers and control strategies. 

Many questions can be raised towards characterizing an observed exceedance of the daily 

standard. Was it driven by local emissions, regional transport, or both? Did it arise from an 

exceptional event, such as a structural fire or unusual industrial emission, or was it the 

conventional mix of emission sources with their contributions amplified by poor atmospheric 

ventilation conditions such as a persistent stagnation? Exceptional events will be experienced 

that cannot be explained with the typical types and levels of surveillance. For example, 

documented exceptional events at the St. Louis – Midwest Supersite in East St. Louis, IL, 

included nearby structural fires that in some cases were captured by the images from an on-site 

camera and in other cases were visually observed by site operators. The ability to identify 

exceptional events in the East St. Louis time series decreased as the site operations became 

routine and staff spent less time at the site. It is possible the observed high concentrations are 

more susceptible to measurement error (indeed, in some cases even result solely from 

measurement error) and uncontrollable measurement bias. We will examine this issue in the 

context of spatial variability in FRM values on high nitrate days. The Regional Haze Rule 

construct of isolating the 20% worst days – whether visibility or mass concentration – is closer in 

spirit to the information needed for examining drivers for high concentration days. However, in 

its most-commonly applied form it is inadequate because the average behavior on the 20% worst 

days might not represent the condition on an actual day if there are a variety of drivers for high 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 8

concentration days. The separation of contributions emanating from different spatial scales 

(e.g., regional-, urban-, and even finer local-scales) is particularly challenging and the data 

analysis approaches adopted for this study have been customized to elucidate the contributions 

from these scales to the extent practicable. In consideration of the above issues, it is apparent 

that analyses to capture the drivers for high concentration days must focus on distributions of 

behavior rather than average (central tendency) behavior. The data analysis methods reflect this 

consideration. 

There are many possible drivers for intraurban variability in PM2.5 mass, including the following 

six factors: local sources of primary PM emissions; transient emission events; topographic 

barriers that isolate subregions of the urban area; meteorological phenomena that vary on spatial 

scales within the urban area; differences in behavior of semi-volatile components; and 

measurement error (Pinto et al. 2004; Turner and Allen, 2008). While this analysis does not 

definitively identify which of these factors are responsible for observed differences across the 

network, it does reflect upon these factors to explain the observed differences. 

Figure 2-1 shows a conceptualization of intraurban variability arising from PM emission sources 

acting on various spatial scales. The air mass is transecting the domain with persistent surface 

winds from the left. Panel (a) shows the emission sources where the regional-scale contributions 

are assumed to be homogeneous across the domain (this assumption neglects interactions 

between regionally transported material and urban area emissions, such as urban plume 

processing of regionally-transported PM precursor gases). Urban-scale emissions from mobile 

sources, area sources, and point sources distributed across the metro core contribute to an 

increase in PM mass concentration (dashed line) which is skewed towards the downwind end of 

the domain. Neighborhood- and finer-scale emissions create local hot spots which disperse 

downwind and become part of the urban-scale contributions. The red line in panel (b) shows the 

concentration profile that would be observed along the transect. Monitor locations will dictate 

which features of the profile are captured. For example, panel (c) shows the location of five 

monitors (the “network-wide baseline” will be discussed later in this report). Monitor A is 

located upwind of the urban area and measures the regional contributions. However, a wind 

reversal would render it downwind of the urban area and in this case it might be impacted by the 

urban plume (such as monitor D). Monitor B is impacted by both a local plume and upwind 

urban contributions. The plume would miss the site with a wind reversal. Monitor C is located 

near the core of the urban area (from an urban-scale emissions perspective). For this scenario it 

is not impacted by local plumes but measures the cumulative contributions from upwind sources, 

including point sources in the urban area. A wind reversal, however, might render monitor C

impacted by a local plume. Monitor D is outside the urban area emissions zone but nonetheless 

is impacted by the “urban plume” as it is advected downwind, while monitor E is far enough 

downwind that the urban plume has dispersed to the extent that the urban PM mass contributions 

cannot be distinguished from the underlying regional contributions. A wind reversal would 

render monitors D and E upwind of the urban area. This spatial concentration field represents a 

snapshot in time which becomes smeared for a 24-hour sample as winds shift during the day, and 

becomes further smeared when averaging results over many days. It is also a 1-D representation 

of a 2-D surface which adds complexity. That said, it does motivate the use of surface winds as 

a discriminator for studying site-specific PM mass trends to place each monitor in an emissions 

field context. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 9

conc.

surface 

winds regional-scale contributions

urban-scale contributions

metro core (emissions perspective) downwind 

distance

neighborhood- and finer-scale 

contributions (e.g., point sources)

conc.

surface 

winds regional-scale contributions

urban-scale contributions

metro core (emissions perspective) downwind 

distance

neighborhood- and finer-scale 

contributions (e.g., point sources)

conc.

surface 

winds

metro core (emissions perspective) downwind 

distance

network-wide 

baseline

A B C D E

(a)

(b)

(c)

Figure 2-1. The influence of emissions acting on various spatial scales to observed concentrations at 

monitoring sites.
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 10

The report is structured as follows. Section 3 presents an overview of the monitoring network 

and key descriptive statistics and trends, including but not limited to the regulatory metrics. 

Section 4 examines the drivers for high concentration days by taking advantage of the relatively 

dense compliance monitoring network and particle speciation data. Section 5 refines the 

understanding of local emission source contributions by exploiting spatial and temporal 

variability within the network. Key findings, policy-relevant implications and recommendations 

for future work are summarized in Section 6. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 11

3. SOUTHEAST MICHIGAN PM2.5 FRM NETWORK AND CONCENTRATION 

TRENDS 

The PM2.5 FRM monitoring network used in this analysis is summarized in Figures 3-1 and 3-2 

and Table 3-1. For the PM2.5 compliance monitoring period of 1999-2006, there were fifteen 

PM2.5 FRM monitoring sites in Southeast Michigan; three sites had collocated PM2.5 FRM 

samplers. All FRM monitoring sites in the Detroit-Warren-Flint CSA are included except Flint. 

For the purpose of this report, the spatial zone of Wayne County with highest population density 

(>10 persons/acre) shall be called the Detroit population core and the spatial zone which includes 

the Detroit central business district and industrialized zones to the south through west (e.g., 

Dearborn, Zug Island) shall be called the Detroit commercial/industrial core. This latter zone 

roughly includes the area covered by the five tightly clustered monitors in Figures 3-1 and 3-2 

(Dearborn, Southwest High School, FIA/Lafayette, Newberry, and Linwood). Greater Wayne 

County sites shall refer to the monitoring sites located in Wayne County plus the Oak Park 

monitor site which is just across the county line in Oakland County. 

Daily measurements have been maintained at Allen Park through the eight year period; most 

other sites operated on a 1-in-3 day schedule although some were cut back to 1-in-6 day in recent 

years due to budget constraints. There were 2,782 days with valid data reported for one-or-more 

sites (95.2% of days), with this high temporal data density driven by the daily sampling at Allen 

Park. There were 14,044 sampling events (neglecting collocated measurements). The historical 

compliance status of each site with respect to the 24-hour PM2.5 NAAQS is presented in 

Table 3-2. Exceedances of the 24-hour standard were observed on 179 days which is 6.1% of 

the days with one-or-more monitors reporting valid data. There were 546 total exceedances 

which correspond to 3.9% of all sampling events. 

This report reflects on the conditions and drivers for high PM2.5 mass concentration days 

(hereafter called “high PM days”). We are interested in both the frequency and intensity 

(magnitude) of high concentration days since both factors are important in establishing the 

design value. Figure 3-3 shows the site-specific frequencies of high concentration days using 

thresholds of 25, 30, and 35 μg/m3

. Exceedances were observed on 2-8% of sample days with 

5-14%, and 8-24% of sample days having concentrations above 30 μg/m3

 and 25 μg/m3, 

respectively. Dearborn exhibits the highest frequency of high concentration days, followed by 

SW High School and Wyandotte. The remaining monitors in Greater Wayne County exhibit 

similar behavior. The frequencies for FIA/Lafayette and Newberry sites might be impacted by 

the relatively short sampling histories at these sites and caution should be used in comparing and 

contrasting these sites to the rest of the network. Ann Arbor and New Haven exhibit the lowest 

frequencies of high concentration days; they are 50-60 km from the Detroit commercial / 

industrial core to the west and northeast, respectively. However, these two sites do not represent 

the spatial extents of the SE Michigan network with Luna Pier ~70 km to the southwest and Port 

Huron ~80 km to the northeast. 

Figure 3-4 shows the frequency of PM2.5 high concentration days by month for Allen Park, 

Dearborn, Southwest High School and New Haven (frequency plots for all sites are presented in 

Figure A-1, Appendix A). The pattern for Allen Park is generally representative of those 

Greater Wayne county sites with relatively modest impacts from nearby sources, as will be 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 12

Figure 3-1. Southeast Michigan PM2.5 FRM monitoring sites superposed on county boundaries and 2000 

census tracts. The red rectangle includes a portion of Wayne County. 

Figure 3-2. Southeast Michigan PM2.5 FRM monitoring sites (excluding Luna Pier and Port Huron) 

superposed on 2000 census tract level population density data.

Wayne 

County 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 13

Table 3-1. Southeast Michigan PM2.5 monitoring network as of December 2006, including 

exceedances days for the NAAQS daily PM2.5 standard of 35 μg/m3

.

(A) (B) (C) (D) (E) (F) (G)

Site Name AIRS ID

Sampling 

Dates

Maximum 

Sampling 

Frequency

Number of 

Sampling Days

Number of 

Exceedance 

Days

Speciation Site 

(Dates)? 

Allen Park 261630001 05/99-- daily 2497 92 12/00-

Ann Arbor 261610005 06/99-12/05 1-in-3 day 714 13 no

Dearborn 261630033 02/99-- 1-in-3 day 879 67 05/02--

E 7 Mile 261630019 04/00-- 1-in-3 day 724 29 12/00-04/02

FIA/Lafayette 261630039 08/05-- 1-in-3 day 155 1 no

Linwood 261630016 05/99-- daily 2273 102 no

Livonia 261630025 08/99-- 1-in-3 day 777 28 no

Luna Pier 261150005 12/99-- 1-in-3 day 804 28 05/02--

New Haven 260990009 01/99-- 1-in-3 day 878 22 no

Newberry 261630038 12/04-- 1-in-3 day 161 6 no

Oak Park 261250001 01/99-- 1-in-3 day 793 32 no

Port Huron 261470005 01/99-- 1-in-3 day 841 32 no

SW High Sch. 261630015 02/99-- 1-in-3 day 881 41 no

Wyandotte 261630036 02/99-- 1-in-3 day 838 35 no

Ypsilanti 261610008 08/99-- 1-in-3 day 829 18 06/03--

discussed later in this report. High concentration days are most frequent in the summer months 

followed by the winter months, while high concentration days are relatively infrequent in the 

spring. Dearborn exhibits higher frequencies of high concentration days for all months with the 

winter frequencies comparable to the summer frequencies. Southwest High School monthly 

frequencies fall between Allen Park and Dearborn, while New Haven has relatively few high 

concentration days but with the same overall pattern as Allen Park – highest frequencies in the 

summer followed by the winter. 

Table 3-2. Southeast Michigan PM2.5 monitoring network compliance status for the daily PM2.5 NAAQS 

(POC = 1 samplers only). 

Three-Year Averages of 98th Percentiles

Site AIRS ID 1999 2000 2001 2002 2003 2004 2005 2006 99-01 00-02 01-03 02-04 03-05 04-06

Allen Park 261630001 43.7 38.6 44.2 39.6 40.5 36.9 43.0 34.1 42 41 41 39 40 38

Ann Arbor 261610005 38.2 33.1 38.5 31.3 33.3 28.4 39.1 37 34 34 31 34 34

Dearborn 261630033 45.1 45.1 43.2 45.7 42.8 39.4 50.2 43.1 44 45 44 43 44 44

E 7 Mile 261630019 --- 42.0 42.0 34.4 37.1 35.0 52.3 36.2 42 39 38 36 41 41

FIA/Lafayette 261630039 --- --- --- --- --- --- 43.9 32.4 --- --- --- --- --- 38

Linwood 261630016 44.5 40.3 40.9 42.7 46.2 38.3 51.8 36.9 42 41 43 42 45 42

Livonia 261630025 38.4 35.9 44.7 32.7 38.1 32.2 40.2 30.4 40 38 39 34 37 34

Luna Pier 261150005 18.1 37.2 39.2 42.7 34.7 35.0 49.3 32.6 32 40 39 37 40 39

New Haven 260990009 31.9 33.2 42.0 35.6 31.8 31.9 41.5 34.4 36 37 36 33 35 36

Newberry 261630038 --- --- --- --- --- 36.8 57.5 28.6 --- --- --- --- --- 41

Oak Park 261250001 42.8 40.7 39.4 38.4 36.6 32.5 52.2 33.0 41 40 38 36 40 39

Port Huron 261470005 44.5 33.1 40.5 35.3 37.2 32.2 47.6 37.9 39 36 38 35 39 39

SW High Sch. 261630015 50.2 44.5 42.9 38.2 33.6 36.0 49.7 36.2 46 42 38 36 40 41

Wyandotte 261630036 45.0 42.7 46.6 34.1 34.8 32.3 46.7 33.2 45 41 39 34 38 37

Ypsilanti 261610008 40.6 30.3 39.7 30.9 38.8 31.5 52.1 31.3 37 34 36 34 41 38

Annual 98th Percentiles 

 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 14 Allen Park Ann Arbor Dearborn E 7 Mile FIA/Lafayette Linwood Livonia Luna Pier New Haven Newberry Oak Park Port Huron SW High Sch. Wyandotte Ypsilantipercentage of total sampling days above threhold concentration

0

5

10

15

20

25

30

> 35 ug/m3

> 30 ug/m3

> 25 ug/m3

1999-2006

(a) 

Allen Park

Ann Arbor

Dearborn

E 7 Mile

FIA/Lafayette

Linwood

Livonia

Luna Pier

New Haven

Newberry

Oak Park

Port Huron

SW High Sch.

Wyandotte

Ypsilanti

percentage of total sampling days above threhold concentration

0

5

10

15

20

25

30

> 35 ug/m3

> 30 ug/m3

> 25 ug/m3

2004-2006

(b) 

Figure 3-3. Site-specific frequency of total sampling days above the designated concentration for 

periods: 1999-2006 (a); and 2004-2006 (b), 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 15

Allen Park

fraction of days greater than threshold

0.00

0.05

0.10

0.15

0.20 > 35 ug/m3

> 30 ug/m3

Dearborn

fraction of days greater than threshold

0.00

0.05

0.10

0.15

0.20

Southwest High Sch.

fraction of days greater than threshold

0.00

0.05

0.10

0.15

0.20

New Haven

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold

0.00

0.05

0.10

0.15

0.20

Figure 3-4. Distribution of PM2.5 high concentration days by month for Allen Park (top) and Dearborn 

(second from top), Southwest High School (second from bottom), and New Haven (bottom), 1999-2006. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 16

Surface winds dictate the coupling between local emission sources and the monitoring sites. 

The wind rose for hourly values from Detroit Metropolitan Wayne County Airport is shown in 

Figure 3-5 for the period 1999-2006. Prevailing surface winds are from the southwest with 

frequent winds also from the west. Winds from the east are relatively infrequent. Hourly surface 

winds distributions exhibit a distinct seasonality (Figure 3-6) albeit with some degree of 

year-to-year variation (Figure B-1, Appendix B). Fall and winter months are more advective 

with a pronounced southwesterly component while spring and summer months have lighter 

winds and less distinct prevailing features. Seasonal variations in surface winds can explain the 

seasonal differences in frequency of high PM days between the Greater Wayne County sites. For 

example, Dearborn has a disproportionately higher frequency of high PM days in the winter 

compared to Allen Park. This is consistent with the increased frequency of surface winds from 

the southwest during the winter and the location of nearby emission sources in this direction (and 

indeed located between Dearborn and Allen Park). 

Figure 3-5. Wind rose for non-calm hours, observations at Detroit Metropolitan Wayne County Airport 

(DTW), 1999-2006. Calms (wind speeds less than 2 mph) were 11% of total hours. 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

Winter Spring Summer Fall 

6% 10% 13% 12% 

Figure 3-6. Seasonal wind roses for non-calm hours, observations at Detroit Metropolitan Wayne 

County Airport (DTW), 1999-2006. Calms (wind speeds less than 2 mph) are listed to the lower-left of 

each wind rose. The wind speed scales are shown in the legend for Figure 3-5. 

>2 - 4

>4 - 8

>8 - 16

>16

WS (mph)
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 17

4. CLIMATOLOGY OF NETWORK-WIDE HIGH PM DAYS 

As previously described, a high fine PM mass concentration day at a given site can arise from 

regional contributions, local contributions, or a combination of these factors. The climatology of 

network-wide high PM days was examined to understand the drivers for such days. Regionally 

transported materials might be higher or atmospheric ventilation might be poorer. The extent to 

which these drivers act synergistically is not clear. For example, a summertime high pressure 

system advecting regionally transported PM might stall out over the area. However, the lower 

winds speeds might be partially offset by a large mixing layer depth on such days. While we 

cannot make definitive statements about such coupling, this section provides a perspective on 

these issues. 

Descriptive analyses, including but not limited to those summarized in the previous section, 

demonstrate a high coherence in high PM days across the network. Thus, an exploratory 

analysis was performed to determine the frequency and nature of network-wide high PM days. 

A subset of sampling days with network-wide high PM mass concentrations was identified by 

first identifying those days with at least ten of the twelve Southeast Michigan FRM monitor sites 

reporting a valid PM2.5 FRM mass concentration value2

; these days are called valid network 

days. Subsequently, the valid network days were screened to include only those days with at 

least 2/3 of the reporting monitors having a PM concentration greater than a threshold value 

(e.g., 30 μg/m3); these days are called network-wide high PM days. Table 4-1 summarizes the 

characteristics of the valid network days and network-wide high PM days data sets. For the 

period 1999-2006 there were 727 sampling days with ten-or-more FRM monitor sites reporting 

valid PM2.5 concentrations (valid network days). 41 of these days (5.6%) had at least 2/3 of the 

monitors above 30 μg/m3 (network-wide high PM days) and all of these days had one-or-more 

monitor exceedance. Exceedances were also observed at one-or-more monitors on 35 days 

(5.1%) that were below the network-wide high PM threshold; these days likely have stronger 

influences from nearby emission sources impacting one or at most two sites. Figure 4-1 shows 

the distribution of network-wide high PM days by month. The days are concentrated in the 

summer followed by the winter, with few days in the seasonal transition months of April, May, 

and November. This pattern is insensitive to the concentration threshold used to define networkwide high PM days. 

 Table 4-1. Valid network days and network-wide high PM days by year.

Year Valid Network Days Network-Wide High PM Days

1999 014 01 7%

2000 084 04 5%

2001 104 10 10%

2002 101 04 4%

2003 113 05 4%

2004 117 05 4%

2005 121 09 7%

2006 073 03 4%

total 727 41 6%

 

2

 Ann Arbor, FIA/Lafayette and Newberry were excluded form this analysis due to their limited period of operation. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 18

Month

1 2 3 4 5 6 7 8 9 10 11 12

# days with at least 2/3 monitors 

above stated concentration

0

2

4

6

8

10

12

14

16

> 35 ug/m3

> 30 ug/m3

> 25 ug/m3

Figure 4-1. Frequency of network-wide high PM days by month using three different thresholds for 

defining a high PM day: ≥25; ≥30; and ≥35 μg/m3

. 

The relevance of this analysis to understanding drivers for exceedances of the 24-hour standard 

is demonstrated in Table 4-2. Valid network days, as defined above, capture 27-92% of all 

sampling days (column D). The capture is relatively low at sites with daily sampling (Allen 

Park, Linwood) because ten-or-more monitors must report valid data for the day to be designated 

a valid network day. However, the percentage of total exceedances that fall on a valid network 

day (column E) is nearly identical to the percentage capture of all sampling days by valid 

network days (column D) and we conclude that the subset of sampling days captured by valid 

network days is representative of all sampling days. Having established the representativeness 

of valid network days, we observed that at most sites exceedances occur predominantly – and in 

some cases exclusively – on days when the entire network is exhibiting high PM (column F). For 

example, 96% of the exceedances at Allen Park on valid network days occurred on days when 

the entire network was exhibiting high PM. Assuming the valid network days are representative 

of all sampling days at Allen Park, we would assign 88 of the 92 total observed exceedances to 

days with network-wide high PM. Similarly, 100% of the exceedances at Ypsilanti on valid 

network days occurred on days when the entire network was exhibiting high PM. Assuming the 

valid network days are representative of all sampling days at Ypsilanti, we would assign all of 

the 18 total observed exceedances to days with network-wide high PM.3

 Dearborn represents the 

other extreme of behavior with only 62% of exceedances occurring on network-wide high PM 

days. In summary: (1) For nine of the fifteen monitors, more than 90% of the exceedances 

occurred on days when the entire network was exhibiting high PM; (2) Four monitors in the core 

region had a high frequency of exceedances on days when the entire network was not exhibiting 

high PM (Dearborn – 38%, Wyandotte – 27%, East 7 Mile – 15%, Linwood – 13%); and (3) At 

Luna Pier and Port Huron, which are located at the geographic extents of the Southeast Michigan 

 

3

 In contrast to Allen Park where only 25 of the 92 exceedances were captured by valid network days (27%), at 

Ypsilanti 16 of the 18 exceedances where captured by valid network days (89%) and the assertion that the valid 

network days are representative of all sampling days is not even necessary. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 19

 Table 4-2. Site-specific exceedance trends on valid network days. 

(A) (B) (C) (D) (E) (F)

Site Name

Number of Sampling 

Days

Number of 

Exceedance Days

% Sampling Days 

on Valid Network 

Days

% Exceedances on Valid 

Network Days

% Network Day 

Exceedances on NetworkWide High PM Days

Allen Park 2497 92 27.2% 27.2% 96.0%

Ann Arbor 714 13 82.9% 92.3% 100.0%

Dearborn 879 67 77.1% 77.6% 61.5%

E 7 Mile 724 29 92.1% 89.7% 84.6%

FIA/Lafayette 155 1 68.4% 100.0% 100.0%

Linwood 2273 102 29.5% 29.4% 86.7%

Livonia 777 28 87.1% 89.3% 92.0%

Luna Pier 804 28 82.8% 85.7% 87.5%

New Haven 878 22 80.4% 86.4% 100.0%

Newberry 161 6 71.4% 100.0% 100.0%

Oak Park 793 32 82.0% 75.0% 91.7%

Port Huron 841 32 81.8% 81.3% 88.5%

SW High Sch. 881 41 78.4% 73.2% 93.3%

Wyandotte 838 35 80.2% 85.7% 73.3%

Ypsilanti 829 18 82.8% 88.9% 100.0%

region, 12-13% of the exceedances were on days when the entire network was not exhibiting 

high PM. It is possible the construct of network-wide high PM days is less robust for these sites 

since they might not always be bathed in the same regional air mass as the core region. 

The threshold concentration used to define a network-wide high PM day does not itself capture 

the network-wide baseline PM level on that day (it is merely the bright line used to identify the 

days). Thus, for the purposes of this report a base concentration for each valid network day was 

defined as the 5th lowest concentration value across the network. Since at least ten monitors 

must have valid data for the day to be designated a valid network day, the 5th lowest 

concentration is no higher than the median concentration and ensures the base concentration is 

not significantly influenced by the monitors at the geographic extents (Luna Pier and Port Huron) 

which might be bathed in different air masses on certain days, and removes the influence of 

one-or-two anomalously low concentration values. The base concentration includes regionally 

transported PM and some portion of the urban-scale contributions. Excess mass at a given site, 

relative to the base concentration, can be negative for cases such as monitors A and E in 

Figure 2-1c. 

Figure 4-2 shows the network-wide maximum and second maximum concentrations as a 

function of the base concentration for valid network days. The maximum concentration is often 

much greater than the base concentration and on these days there is a large local excess at the 

maximum concentration site. However, the second maximum concentration is typically within 

5 μg/m3

 of the base concentration and thus on a given day there is typically at most one site with 

a large local excess, regardless of the base concentration. This behavior holds at both high and 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 20

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

maximum concentration, ug/m3

0

10

20

30

40

50

60

70

80

(a)

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

second maximum concentration, ug/m3

0

10

20

30

40

50

60

70

80

(b)

Figure 4-2. Network-wide maximum concentration (a) and second maximum concentration (b) for each 

valid network day compared to the respective network-wide base concentration. The analysis excludes 

three sites – Ann Arbor, Lafayette/FIA, and Newberry. The solid line is the base concentration (1:1 line) 

and the dashed line is 5 μg/m3

 above the base concentration. 

low base concentrations; the extreme maximum values possibly arise from nitrate hot spots or 

measurement artifacts as will be described later in this report. 

Day- and site-specific concentrations are compared to the base concentrations in Figure 4-3 for 

valid network days. Most sites had a few exceedances days with concentrations in large excess 

of the base concentration. Assuming poor atmospheric ventilation affects the sites similarly and 

thus contributes to the base concentration, the extreme excursions above the base concentrations 

likely arose from nearby emission source plumes, exceptional events (including but not limited 

to releases from the local emission sources) or measurement error including but not limited to a 

possible nitrate artifact. With the exception of Dearborn and Wyandotte, most exceedances were 

clustered about the base concentration. Dearborn and Wyandotte had exceedances on days with 

base concentrations as low as 20 μg/m3

 demonstrating significant excess above the base 

concentration. 

The analysis so far has primarily focused on the relative frequency of network-wide high PM 

days and their associations with exceedances. Figure 4-4 captures the influence of the extreme 

values observed at each site (Figure 4-3), showing the 5th highest maximum excess and the 

median excess compared to the base concentration for exceedance days falling on valid network 

days. Several sites have low excess for the 5th highest maximum (yellow bars), although this 

metric is sensitive to sampling frequency. Most sites have median excess below 5 μg/m3

. 

Excluding Dearborn and Wyandotte, and pooling the site-specific highest three excess 

concentrations across the remaining ten sites, 23 of the 30 values occurred on only three days – 

3/1/2003, 2/3/2005 and 2/6/2005. On all three days the network exhibited high and variable 

concentrations, and the latter two days were the highest nitrate at Allen Park over all valid 

network days (no speciation data for 3/1/2003). Further inspection of network-wide behavior on 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 21

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Allen Park

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Dearborn

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

East 7 Mile

 base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Linwood

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Livonia

 base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Luna Pier

Figure 4-3. Site-specific concentrations versus base concentrations for valid network days. Solid line is 

the base concentration (1:1 line) and dashed line is 35 μg/m3

. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 22

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

New Haven

 base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Oak Park

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Port Huron

 base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

SW High Sch.

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Wyandotte

 base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Ypsilanti

Figure 4-3 (continued). Site-specific concentrations versus base concentrations for valid network days. 

Solid line is the base concentration (1:1 line) and dashed line is 35 μg/m3

. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 23

0

5

10

15

20

Allen Park

Dearborn

E 7 Mile

Linwood

Livonia

Luna Pier

New Haven

Oak Park

Port Huron

SW High Sch.

Wyandotte

Ypsilanti

site conc. in excess of network-wide base conc., ug/m3

5th max

50th percentile

Figure 4-4. Site-specific exceedance days: 5th-highest excess concentration compared to base 

concentration (yellow); and 50th-precentile excess concentration compared to base concentration (green). 

high nitrate days shows the spatial variability can range from nearly homogeneous to quite 

heterogeneous (such as the above noted days). It is likely that nitrate is driving the variability on 

such days and is responsible for many of the outlier mass concentrations at high base 

concentrations in Figure 4-3. There are at least two possible explanations for this behavior. 

First, there might be nitrate hot spots on high nitrate days. These hot spots are most likely to 

occur on days with a liquid aerosol due to high humidity. A qualitative inspection of surface 

weather on high nitrate days suggests they often coincide with fog events. The aerosol state 

(liquid versus dry), and degree of water content if wet, might vary across the network due to 

micrometeorology and this could influence nitrate uptake. Spatial variations in crustal material 

could also influence the pH of the liquid aerosol which in turn influences nitrate uptake. Second, 

there might be varying nitrate measurement artifact on certain high nitrate days. Even if the 

ambient nitrate concentration is spatially homogeneous, perhaps the Teflon filters are retaining 

nitrate to varying degrees and this artificially induces a spatial variability in both nitrate in FRM 

mass. A better understanding of the drivers for high spatial variability in FRM mass on high 

nitrate days is needed since only a few such events can dramatically affect the site-specific 

design values for the 24-hour standard. When such patterns are observed, perhaps the Teflon 

filters could be analyzed for nitrate by IC to determine the extent of nitrate retention; this would 

be particularly insightful for days coinciding with speciation sampler operation. 

Figure 4-5 shows the same data as Figure 4-3 for Dearborn and Wyandotte but stratified to 

isolate the period 2004-2006 (the most-recent three-year period for the data set used in this 

study). Focusing on those days with base concentration below 35 μg/m3

 (to the left of the 

vertical solid line) but with site-specific concentrations approaching or greater than 35 μg/m3

 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 24

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Dearborn

(a)

base concentration, ug/m3

0 10 20 30 40 50 60 70 80

site-specific concentration, ug/m3

0

10

20

30

40

50

60

70

80

Wyandotte

(b)

Figure 4-5. Site-specific concentrations versus base concentrations for valid network days at Dearborn 

(a) and Wyandotte (b) stratified by year: 1999-2003 (red markers); and 2004-2006 (green markers). Solid 

diagonal line is the base concentration (1:1 line), and the solid vertical line and dashed horizontal line are 

35 μg/m3

. 

(above the dashed horizontal line), these days correspond to cases where nearby local emission 

sources are likely significant contributors to an exceedance (or near exceedance) that otherwise 

would not occur. For Dearborn (Figure 4-4a), there has been a decrease in frequency of such 

local plume days but they are certainly still present for the 2004-2006 period. For Wyandotte 

(Figure 4-4b), however, virtually all of the days with local source plumes driving an exceedance 

(or near exceedance) of the standard were prior to 2004. For the most recent data (2004-2006), 

Wyandotte does not appear to be disproportionately influenced by local plumes on exceedance 

(or near exceedance) days. Again, these figures do not represent all sample days but rather the 

subset of days with ten-or-more reporting monitors such that network-wide behavior could be 

characterized; however, as previously demonstrated, this subset of days does appear to be 

representative of the overall data set. 

The analysis presented to this point clearly demonstrates that exceedances at most sites 

correspond to days when the entire network is exhibiting high PM concentrations and the rare 

extreme values are likely due to exceptional events or possibly a nitrate hot spot or measurement 

artifact. Some sites, especially Dearborn and Wyandotte, have a significant excess superposed 

on the base concentration leading to exceedances when the base concentration is as low as 

20 μg/m3

. It would be helpful to determine whether the day-to-day variability in the base 

concentration is driven by regional transport, poor atmospheric ventilation of urban-scale 

emissions, or a combination of these factors. There is no direct methodology to partition these 

influences but insights can be obtained by examining the PM speciation data and surface winds 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 25

FRM mass concentration, ug/m3

0 10 20 30 40 50 60 70

total ion concentration, ug/m3

0

10

20

30

40

50

60

70

December - April

May - November 

Figure 4-6. Total major ion concentration (sulfate, nitrate and ammonium) versus FRM mass at Allen 

Park, stratified by season. 

distributions.4

 Figure 4-6 shows the contribution of major ions (sulfate, nitrate, and ammonium) 

to FRM mass at Allen Park for the period December 2002 through December 2006. There were 

valid FRM and speciation data for 21 of the 71 exceedances observed at Allen Park during this 

time period. Six (29%) of these 21 exceedances days exhibited major ion concentrations greater 

than 35 μg/m3 and thus the major ions alone were sufficient to cause the exceedance.5 Over all 

21 exceedance days the major ion contribution was 56-112% of the standard (median 84%) and 

53-85% of the FRM PM2.5 mass concentration (median 71%). At Allen Park the major ions are 

more than half of the PM on all exceedance days and, since Allen Park is representative of the 

network-wide base concentration (Figure 4-3), the major ions are deemed the dominant PM 

component at all sites with small local plume impacts. 

Aerosol composition at Allen Park was examined in more detail for the network-wide high PM 

days. Speciation data was available for 31 of the 41 days. Figure 4-7 is a scattergram for sulfate 

and nitrate on these days with all sulfate assumed to be ammonium sulfate and all nitrate 

assumed to be ammonium nitrate. Summertime events typically exhibit high sulfate and 

relatively low nitrate. Wintertime events exhibit high nitrate but sulfate is typically ~50% or 

more of the nitrate concentration. Thus, while the wintertime events are often called high nitrate 

days, it should be noted that sulfate is also quite significant on these days. Overall, 55% of these 

 

4

 Typically synoptic winds would be analyzed to identify days conducive to regional transport but sulfate and nitrate 

will be used as a surrogate for regional transport in this work since the sulfate at Allen Park is overwhelmingly from 

regional transport and the nitrate is dominated by regional transport. 

5

 This assumes nitrate does not appreciably volatile from the FRM Teflon filter; in practice, the major ion 

concentration will be lower due to nitrate volatilization. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 26

0

5

10

15

20

25

30

35

40

0 10 20 30 40

sulfate as ammonium sulfate, μg/m3

nitrate as ammonium nitrate ,μg/m3

May-November

December-April 1:1

2:1

1:2

Figure 4-7. Ammonium nitrate and ammonium sulfate concentrations at Allen Park on network-wide 

high PM days. 

31 days have a combined ammonium sulfate plus ammonium nitrate concentration exceeding 

25 μg/m3

 although, as previously mentioned, the contribution of these ions will be less on certain 

days after correcting for ammonium nitrate loss from the FRM Teflon filters. 

Previous work has demonstrated that sulfate at Allen Park is overwhelmingly from regional 

transport; nitrate is likely dominated by regional transport but the precise split between regional 

and local sources remains unknown. Assuming the sulfate and nitrate are regionally transported, 

the total contribution from regional sources would likely be larger than the sum of the major ions 

(after correction for nitrate loss), but cannot be further quantified because organic matter likely 

has significant regional and local contributions and at this time the organic matter concentrations 

in Southeast Michigan cannot be apportioned to regional and local contributions on an average 

basis, no less a day-to-day basis. A multivariable linear regression was performed to explain the 

observed organic carbon (OC) in terms of observed sulfate and elemental carbon (EC). The 

unconstrained regression yielded (R2

 = 0.50, all units in μg/m3); 

OC = (1.53 ± 0.22) + (0.176 ± 0.029)SO4 + (2.49 ± 0.26)EC

where the 95% confidence interval for each regression parameter is reported. There are many 

caveats to this very simple approach to apportioning the OC. For example OC associated with 

sulfate would likely vary by season due to differences in secondary formation rates. The 

approach is merely intended as a crude way to assign OC to a component that associates with 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 27

local, primary emissions (OC associating with EC) and a component that scales with sulfate. 

The results should not be over-interpreted. Assuming an OM/OC ratio of 1.8, the scaling factor 

for organic matter associated with sulfate would be 0.32×SO4. Figure 4-8 shows the 

contribution of major ions measured at Allen Park to the base concentration on valid network 

days (Figure 4-8a) and the contribution of the major ions plus this crude estimate of the OM 

associated with sulfate (Figure 4-8b). The inclusion of associated OM substantially closes the 

mass balance on the base concentration. High base concentrations can largely be explained by 

regionally transported material alone and any concomitant increase in urban- and finer-scale 

contributions (for example, due to poorer atmospheric ventilation) might be relatively modest. 

From Figure 4-8a it can also be discerned that the major ion contribution deviates positively from 

the median contribution at base concentrations above ~ 20 μg/m3

; it is above this value that 

major ions – and thus presumably regional transport – disproportionately influences the 

observed PM2.5 mass concentrations. 

Concentration enhancements in surrogates for regional transport (sulfate and nitrate as 

surrogates) and urban-scale local emissions (EC as surrogate) were examined for the 

network-wide high PM days. For each valid network day with speciation data at Allen Park, 

concentrations for the major aerosol components were compared to the monthly median values 

obtained by pooling over all valid network days and over all years. Sulfate was on average 

4.5 times higher and nitrate was on average 2.8 times higher on network-wide high concentration 

days compared to the corresponding monthly median value. In contrast, EC was on average only 

1.3 times higher on network-wide high concentration days compared to the corresponding 

monthly median EC concentration.6

 Using the EC enhancement as an indicator for the 

atmospheric ventilation of urban-sale emissions, this analysis suggests reduced atmospheric 

ventilation on network-wide high PM days does indeed increase the urban- and-finer scale 

contributions but, in the absence of direct plume hits from near-field sources, the enhancement is 

much smaller than observed for the major ions which are associated with regional transport. OC 

was on average 1.6 times higher on network-wide high PM days compared respective monthly 

median concentration (1.8 times higher if the OC data is blank-corrected). This enhancement is 

between the values ascribed to regionally transported material and urban-scale emissions, 

consistent with OC contributions from a combination of local (urban or finer-scale) primary 

sources and secondary formation (whether local or regional in origin). 

Lastly, the daily FRM sampling at Allen Park is exploited to determine whether high PM days at 

each site correspond to a spatially- and temporally- isolated excursion (high PM not observed at 

Allen Park which, as shown in Figure 4-3, largely captures the network-wide PM base 

concentration), a temporally-isolated excursion (high PM also observed at Allen Park on that day 

but not the preceding or following day), or a multiday PM episode (high PM observed at Allen 

Park on adjacent days). Multiday PM episodes are stratified into two groups – two successive 

high PM days at Allen Park, and three-or-more successive high PM days at Allen Park. Two 

successive high PM days could arise from a brief event that straddles midnight, while 

three-or-more more successive high PM days clearly indicate an episode with temporal 

persistence, whether caused by regional transport or sustained areawide air mass stagnations. 

 

6

 EC has a day-of-week trend at Allen Park (higher on weekdays) so the analysis was repeated by first stratifying 

days as weekends and weekdays and then calculating the day-specific enhancement compared to the respective 

weekend or weekday monthly median value. The same average enhancement – a factor of 1.3 – was obtained. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 28

High PM conditions were defined as >30 μg/m3

 for the interrogated site and >25 μg/m3 for the 

reference site (Allen Park). Figure 4-9 shows the site-specific distributions. Dearborn has the 

highest frequency of spatially- and temporally-isolated high PM days (red bars; dates for all sites 

listed in Appendix C). As previously described, nearby emission sources are most important at 

this site and can drive high PM days even when the network-wide base concentration is as low as 

20 μg/m3. Relatively high frequencies of spatially- and temporally-isolated high PM days were 

also observed at Wyandotte, Southwest High School, and East 7 Mile. At all sites except 

Dearborn, high PM days most frequently correspond to multiday PM episodes (blue plus green 

bars) and most frequently to longer-persistence episodes (three- or-more days with high PM at 

Allen Park). 

In summary – 

• Network-wide high PM days are observed primarily in the summertime but are also 

observed in the wintertime. 

• Network-wide high PM days in the summer typically have high sulfate and relatively low 

ambient nitrate. The nitrate contributions to FRM mass will be even lower after 

accounting from ammonium nitrate volatilization from the Teflon filter. 

• Network-wide high PM days in the winter typically have high nitrate but ammonium 

sulfate is typically at least 50% of the ammonium nitrate mass so these events are 

actually high nitrate and high sulfate. 

• Network-wide high PM days are primarily driven by regional transport with 

intensification of urban-scale emissions due to low atmospheric ventilation being 

relatively less important. Plume impacts from nearby emission sources are superposed 

on the network-wide baseline. 

• Site-specific high PM days are most often observed when the area is experiencing a 

multiday high PM episode. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 29

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

FRM mass, ug/m3

total ion concentration, ug/m3

all valid network days

network-wide high PM day

1:1

median mass 

fraction

(a) 

0

10

20

30

40

50

60

70

0 10 20 30 40 50 60 70

FRM mass, ug/m3

total ion concentration plus associated OM, ug/m3

all valid network days

network-wide high PM day

1:1

median mass 

fraction

(b) 

Figure 4-8. Allen Park species contributions to the base concentration on valid network days: major ions 

only (a); and major ions plus associated organic matter (b). 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 30 Dearborn East 7 Mile Linwood Livonia Luna Pier New Haven Oak Park Port Huron Southwest HS Wyandotte Ypsilanti fraction in stated category

0.0

0.2

0.4

0.6

0.8

1.0

AP < 25 ug/m3 on same day

AP > 25 ug/m3 on same day only

AP > 25 ug/m3 on two consecutive days

AP > 25 ug/m3on three-or-more consecutive days

Figure 4-9. Classification of high PM days (PM2.5 > 30 μg/m3) at each site in Southeast Michigan by the 

time series behavior of daily PM2.5 at Allen Park. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 31

5. RELATIONSHIPS BETWEEN SITE-SPECIFIC EXCESS MASS AND SURFACE 

WINDS 

The previous section demonstrates that exceedances of the 24-hour PM2.5 NAAQS at most sites 

in Southeast Michigan are primarily driven by an enhancement of regionally transported material 

which elevates the concentration baseline upon which local contributions are superposed. There 

is typically a modest enhancement in the urban-scale contributions on high PM days, presumably 

due to coincident air mass stagnations. This does not imply that urban-scale contributions are 

small, but rather they are not significantly modulated on high PM days. At a few sites, plumes 

from nearby emission sources can substantially contribute to exceedances and near exceedances. 

This section presents relationships between the excess mass (relative a reference concentration 

that should capture regional- and larger-scale influences, and to some extent urban-scale 

influences) and surface winds for each site. This analysis does not focus on excess mass 

observed on high PM days exclusively, but rather excess mass over the entire concentration 

distribution. While in principle there might be different local sources contributing on high PM 

days compared to all other days, the previous analyses do not provide any evidence for such 

preferential behavior and there is much statistical power to be gained from using the entire data 

set. Allen Park was initially chosen as a reference site for generating the times series of excess 

mass. Figure 4-3 demonstrates that Allen Park is indeed highly correlated with the network-wide 

base concentration on most days, although it is modestly influenced by nearby emissions for 

winds from the northeast (Dearborn) (Wade et al. 2008). Thus, the calculated excess mass 

concentrations at other sites might be biased low for winds from the northeast and sources in this 

direction might be damped or even missed. This limitation does not significantly affect the 

results for other bearings. Certain analyses were repeated using the network-wide base 

concentration as the reference for calculating excess mass. This reduces the number of sample 

days used in the analyses but removes any issues with directional bias introduced by using a 

single site as the reference. Finally, this methodology also relies on having representative 

surface winds at the site. It is not clear that hourly winds from Detroit Metropolitan Wayne 

County Airport will be representative for sites such as Luna Pier and Port Huron; however, the 

excess mass construct using Allen Park or the entire Southeast Michigan network to define a 

base concentration is perhaps an equally limiting factor when examining these distant sites. 

Relationships between excess mass and surface winds were probed using Conditional Probability 

Function (CPF) and 1-D Nonparametric Wind Regression (NWR) plots. A brief summary of the 

methods and their utility is presented in Appendix D. The stability of CPF and NWR results 

was examined in various ways. Many analyses were run with the entire data set (1999-2006) and 

the most recent three years (2004-2006) since greatest interest is in current conditions. The 

former includes substantially more data and is less susceptible to spurious results. The threshold 

for high excess mass in the CPF analysis was chosen as the top quartile and each analysis was 

repeated using the top decile. Finally, sensitivity to days with high excess mass at the reference 

site (Allen Park) was examined by running most of the analyses on the full data set and then 

repeating the analyses with the data censored to exclude days where the excess mass was less 

than -2 μg/m3

. This threshold is based on two times the propagated collocated precision for the 

concentration difference using a collocated precision of 0.7 μg/m3

for a single measurement. 

Since the excess mass concentration is a 24-hour integrated parameter but the surface winds data 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 32

are hourly, care must be taken in handling calm hours. Calms days (operationally defined as 

six-or-more calm hours in the day) were retained but calm hours (wind speeds less than 2 mph) 

were removed.7

 

Figure 5-1 shows the CPF analysis results for each site using the top decile of the excess mass 

distribution as the threshold for a high concentration and for the period 1999-2006. Plots for 

Luna Pier, New Haven and Oak Park are excluded because they were either sensitive to the 

methodology or indistinguishable from the CPF plot for the absolute mass concentration at the 

site. The plots were nearly identical when using 1999-2006 data and 2004-2006 data only, 

which means the bearings of sources driving the excess mass have not changed over time. 

Dearborn, Newberry, and Wyandotte CPF plots all implicate sources to the southwest. These are 

likely nearby sources and, recalling that the prevailing wintertime surface winds are from the 

southwest (Figures 3-4 and 3-5) it is not surprising that the analyses in Section 4 implicated local 

sources as significant contributors to the excess mass at these sites given the favorable wind 

directions for advecting emissions from the sources to these sites. East 7 Mile, Linwood, and 

Southwest High School CPF plots exhibit higher frequency of excess mass with winds from the 

south/southwest, albeit weaker signatures than observed for Dearborn / Newberry / Wyandotte. 

Ann Arbor and Ypsilanti have a higher frequency of high excess mass when the winds are from 

the east and Livonia has a higher frequency of high excess mass when the winds are from the 

southeast. All three of these cases correspond to bearings in the direction of the Detroit 

population and/or commercial/industrial cores. However, surface winds from the east are not 

common and thus these sites are rarely downwind of the urban core zones. The CPF plot for 

Port Huron implicates sources at bearings east through south of the site which is consistent with 

the industrial zones along the U.S./Canada border including but not limited to petroleum 

refineries. In summary, the CPF plots are consistent with the local source impacts identified in 

Section 4 and consistent with known emission source regions. It appears this analysis can pick 

up the urban plume advected from Detroit to sites that are outside the urban emissions zone. 

NWR plots show the expected excess concentration as a function of wind direction. Several 

analyses were performed using Allen Park data for the reference concentrations (see footnote 

#11). Subsequently, NWR plots were constructed using the network-wide base concentration 

estimates for the reference concentrations and those results, which were generally consistent with 

the results that were obtained using Allen Park as a reference, are presented here. Yearly box 

plots were generated for the excess PM2.5 mass at each site compared to the network-wide base 

concentration. FRM data for 2007 was also included in these time series plots but have not been 

examined in sufficient detail for incorporation into wind regression analyses. Given the seasonal 

and year-to-year variability in surface winds, the representativeness of valid network days was 

assessed by comparing to the annual surface winds for all days. Figure B-2 shows annual wind 

roses for all days and valid network days. 

 

7 The following analyses were performed with results available upon request: CPF for top quartile of absolute 

concentration distribution (no subtraction of Allen Park concentration values), 1999-2006; CPF for top decile of 

entire excess mass distribution, 1999-2006; CPF for top quartile of entire excess mass distribution, 1999-2006; CPF 

for top quartile of censored excess mass distribution, 1999-2006; CPF for top decile of entire excess mass 

distribution, 2004-2006; CPF for top quartile of entire excess mass distribution, 2004-2006; NWR for entire excess 

mass distribution, 1999-2006; NWR for entire excess mass distribution, 2004-2006; and NWR for censored excess 

mass distribution, 1999-2006. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 33

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

330

345

0 0.1 0.2 0.3 0.4

Ann Arbor

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

330

345

0 0.1 0.2 0.3 0.4

Dearborn

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

330

345

0 0.1 0.2 0.3 0.4

E 7 Mile

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

330

345

0 0.1 0.2 0.3 0.4

FIA/Lafayette

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

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345

0 0.1 0.2 0.3 0.4

Linwood

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

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345

0 0.1 0.2 0.3 0.4

Livonia

Newberry

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

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345

0 0.1 0.2 0.3 0.4

Port Huron 0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

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255

285

300

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345

0 0.1 0.2 0.3 0.4

SW High Sch.0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

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0 0.1 0.2 0.3 0.4

Wyandotte

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

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345

0 0.1 0.2 0.3 0.4

Ypsilanti

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

330

345

0 0.1 0.2 0.3 0.4

Figure 5-1. Conditional probability function plots for excess mass at each site relative to Allen Park, 

1999-2006. Probabilities are for the top decile of the excess mass distribution.
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 34

Data for 1999 were excluded from the concentration time series because the network was being 

phased in during that year; there were only 14 valid network days and the valid network days 

winds distribution was markedly different from the 1999 annual surface winds distribution. For 

the remaining years the annual wind roses for valid network days showed good agreement with 

the annual wind roses for all days (Figure B-2), including 2006 which had a relatively low 

number of valid network days (also seasonally biased towards the first quarter) due to a 

reduction in sampling frequency at certain sites. These favorable comparisons demonstrate the 

representativeness in using valid network days to capture annual average behavior for the sitespecific excess mass. 

Figure 5-2 shows annual distributions of the network-wide base concentration. Similar 

distributions were observed for the first four years (2000-2003) with substantial year-to-year 

variability for the subsequent four years (2004-2007). The lowest median value was in 2004, 

followed by a relatively high mean value in 2005. 

Excess mass annual time series and NWR plots were generated for each site with selected results 

presented in this report. NWR was performed after stratifying the data into two time periods: 

2000-2003 and 2004-2006. Hourly surface winds distributions, Figure 5-3, exhibit a lower 

frequency of winds from the southwest for the 2004-2006 period compared to the 2000-2003 

period. However, the NWR results are presented as the expected concentration value for each 

wind direction and thus are not influenced by the frequency distribution of wind direction. An 

apportionment of the average excess mass to wind sectors (and thus emission sources in that 

sector) would require a weighting of the sector-specific expected concentration by the sectorspecific frequency of wind direction. This step is discussed in Section 6 as a recommendation 

for future work. For the purpose of identifying whether emission source strengths have changed 

over time, the expected concentration as presented in this section is appropriate since it is not 

influenced by year-to-year differences in the distribution of surface wind directions. 

2000 2001 2002 2003 2004 2005 2006 2007

network-wide baseline concentration, ug/m3

0

5

10

15

20

25

30

35

40

( 84) (104) (101) (113) (117) (121) ( 73) (120)

Figure 5-2. Annual distributions of the network-wide base concentration. Open circles are 5th and 95th

percentile values; the red and black lines are mean and median values (solid within box for yearly, dashed 

for entire data set); and the number of samples is in parenthesis at the top of each plot. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 35

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

10% 11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

 (a) 2000-2003 (b) 2004-2006 

Figure 5-3. Wind rose for non-calm hours, observations at Detroit Metropolitan Wayne County Airport 

(DTW): (a) 2000-2003; and (b) 2004-2006. Calms (wind speeds less than 2 mph) are listed to the 

lower-left of each wind rose. 

Ann Arbor, FIA/Lafayette, Newberry were excluded because sampling was not sustained over 

the 2000-2006 time period. Luna Pier and Port Huron were excluded because they are at the 

spatial extents of the geographic domain and both the base concentration estimates and surface 

winds might not be representative. Figures 5-4 through 5-7 show the time series and NWR plots 

for Dearborn, Wyandotte, Southwest High School and Linwood, respectively. NWR results as 

polar plots are presented with the radial concentration units in μg/m3

; the red line is the average 

contribution and the pink lines are the 95% confidence intervals. NWR results were also 

generated after first censoring the data to remove extreme values and thereby stabilize the 

expected concentration estimates.8

 The bottom plot in each panel of Figure 5-4 shows the NWR 

results for censored data, and includes the difference in expected concentration values between 

the two time periods (blue line). Figure E-1 (Appendix E) presents NWR results for all sites as 

Cartesian plots for all data and censored data. 

Dearborn (Figure 5-4) exhibits the average highest average excess mass. Both the mean and 

median excess mass decreased beginning in 2005 despite an increase that year in the mean base 

concentration (Figure 5-2). The time series for the annual base concentration and excess mass 

concentration are decoupled which adds confidence that the decreases in excess mass are real. 

Expected mass concentrations of at least 2 μg/m3

 were observed for all wind directions (center 

and bottom plots in Figure 5-4) with elevated excess mass for bearings 120-300°N and a 

maximum in the expected concentration at ~225°N of with concentrations 9 and 7 μg/m3

 for 

2000-2003 and 2004-2006, respectively. The excess mass floor of ~2 μg/m3 might be real since 

the Detroit population core, perhaps a surrogate for mobile source and area emissions, is to the 

 

8

 Extreme values were defined as those values exceeding the upper outer fences (UOF) and lower outer fences 

(LOF) of the nonparametric distribution of excess mass: CUOF = C75 + 3×CIQR; and CLOF = C25 - 3×CIQR where Ci is 

concentration i, subscripts 25 and 75 denote 25th and 75th percentiles, and IQR is the interquartile range (C75 - C25). 

>2 - 4

>4 - 8

>8 - 16

>16

WS (mph)
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 36

DEARBORN

2000 2001 2002 2003 2004 2005 2006 2007

excess above network-wide baseline, ug/m3

-5

0

5

10

15

20

( 76) ( 98) ( 96) (105) (105) (114) ( 70) (114)

Dearborn

2000-2003 2004-2006

0 2 4 6 8 10

9

60

30

0

330

300

70

240

210

180

150

120

0 2 4 6 8 10

9

60

30

0

330

300

70

240

210

180

150

120

-2

0

2

4

6

8

10

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Dearborn, 2000-2003

Dearborn, 2004-2006

[2004-2006] minus [2000-2003]

Figure 5-4. Excess PM2.5 mass compared to the network-wide base concentration. Top: box plots of 

annual excess mass concentration distributions. Open circles are 5th and 95th percentile values; the red 

and black lines are mean and median values (solid within box for yearly, dashed for entire data set); and 

the number of samples is in parenthesis. Center: 1-D NWR for excess mass at each site relative to the 

network-wide baseline concentration for 2000-2003 (left) and 2004-2006 (right). Average concentrations 

and 95% confidence intervals are red and pink lines, respectively, and radial units are μg/m3

. Bottom: 

1-D NWR expected excess mass concentrations after censoring the data to remove extreme values. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 37

WYANDOTTE

2000-2003 2004-2006

2000 2001 2002 2003 2004 2005 2006 2007

excess above network-wide baseline, ug/m3

-5

0

5

10

15

20 Wyandotte

( 82) ( 99) ( 90) (100) (107) (112) ( 69) (116)

012345

9

60

30

0

330

300

70

240

210

180

150

120

012345

9

60

30

0

330

300

70

240

210

180

150

120

2000-2003 2004-2006

-2

0

2

4

6

8

10

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Wyandotte, 2000-2003

Wyandotte, 2004-2006

[2004-2006] minus [2000-2003]

Figure 5-5. Excess PM2.5 mass compared to the network-wide base concentration. Top: box plots of 

annual excess mass concentration distributions. Open circles are 5th and 95th percentile values; the red 

and black lines are mean and median values (solid within box for yearly, dashed for entire data set); and 

the number of samples is in parenthesis. Center: 1-D NWR for excess mass at each site relative to the 

network-wide baseline concentration for 2000-2003 (left) and 2004-2006 (right). Average concentrations 

and 95% confidence intervals are red and pink lines, respectively, and radial units are μg/m3

. Bottom: 

1-D NWR expected excess mass concentrations after censoring the data to remove extreme values. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 38

SOUTHWEST HIGH SCHOOL

2000-2003 2004-2006

2000 2001 2002 2003 2004 2005 2006 2007

excess above network-wide baseline, ug/m3

-5

0

5

10

15

20 Southwest High Sch.

( 82) ( 102) ( 94) (105) (110) (114) ( 70) (113)

012345

9

60

30

0

330

300

70

240

210

180

150

120

012345

9

60

30

0

330

300

70

240

210

180

150

120

-2

-1

0

1

2

3

4

5

6

7

8

9

10

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

SW High Sch., 2000-2003

SW High Sch., 2004-2006

[2004-2006] minus [2000-2003]

Figure 5-6. Excess PM2.5 mass compared to the network-wide base concentration. Top: box plots of 

annual excess mass concentration distributions. Open circles are 5th and 95th percentile values; the red 

and black lines are mean and median values (solid within box for yearly, dashed for entire data set); and 

the number of samples is in parenthesis. Center: 1-D NWR for excess mass at each site relative to the 

network-wide baseline concentration for 2000-2003 (left) and 2004-2006 (right). Average concentrations 

and 95% confidence intervals are red and pink lines, respectively, and radial units are μg/m3

. Bottom: 

1-D NWR expected excess mass concentrations after censoring the data to remove extreme values. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 39

LINWOOD

2000-2003 2004-2006

2000 2001 2002 2003 2004 2005 2006 2007

excess above network-wide baseline, ug/m3

-5

0

5

10

15

20 Linwood

( 80) ( 98) ( 91) (106) (105) (110) ( 66) (111)

0.0 0.5 1.0 1.5 2.0 2.5

9

60

30

0

330

300

70

240

210

180

150

120

0.0 0.5 1.0 1.5 2.0 2.5

9

60

30

0

330

300

70

240

210

180

150

120

-2

0

2

4

6

8

10

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Linwood, 2000-2003

Linwood, 2004-2006

[2004-2006] minus [2000-2003]

Figure 5-7 Excess PM2.5 mass compared to the network-wide base concentration. Top: box plots of 

annual excess mass concentration distributions. Open circles are 5th and 95th percentile values; the red 

and black lines are mean and median values (solid within box for yearly, dashed for entire data set); and 

the number of samples is in parenthesis. Center: 1-D NWR for excess mass at each site relative to the 

network-wide baseline concentration for 2000-2003 (left) and 2004-2006 (right). Average concentrations 

and 95% confidence intervals are red and pink lines, respectively, and radial units are μg/m3

. Bottom: 

1-D NWR expected excess mass concentrations after censoring the data to remove extreme values. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 40

north and east and the site is located in the Detroit commercial/industrial core. It is possible, 

however, that the excess mass floor reflects contamination in the NWR analysis from using 

daily-integrated FRM mass together with hourly winds which might vary over the course of the 

day and thus smear short duration, high intensity contributions from the local emission sources 

across other wind directions. The period 2004-2006 does indeed exhibit lower excess mass 

concentrations compared to 2000-2003, consistent with Figure 4-5, with maximum reductions of 

~2 μg/m3

 from ~195-255°N. The Dearborn NWR results were insensitive to the censoring of 

data to remove extreme values (Figure E-1). In summary, Dearborn is significantly influenced 

by local emission sources to the southwest of the site. This is also the direction of the prevailing 

wind and thus emission controls on these sources would have a dramatic impact on observed 

concentrations at the Dearborn site. There is also a significant urban scale contribution 

regardless of wind direction with expected concentration greater than 2 μg/m3 (the excess mass 

floor is 2 μg/m3 plus there are urban-scale contributions to the base concentration) although the 

relative contributions of mobile, area, and dispersed point source emissions is not clear. 

Wyandotte and Southwest High School have similar mean and median excess mass, second after 

Dearborn. Let us first consider Wyandotte. The top plot in Figure 5-5 shows a dramatic and 

steady reduction in mean and median excess mass starting in 2004. Expected mass 

concentrations were lowest for wind directions from the east/southeast (indeed, ~0 μg/m3

 for 

2004-2006) which is consistent with the orientation of the site relative to local sources and the 

Detroit population and commercial / industrial cores. There are two sectors with high expected 

excess mass concentrations. One sector is broadly to the north/northwest with expected excess 

mass concentrations ~2 μg/m3 for 2000-2003 and with ~50% decrease for 2004-2006. This 

bearing is consistent with the location of the Detroit population and commercial / industrial cores 

which are north of Wyandotte. The other sector is to the southwest with a maximum excess 

mass concentration of nearly 4 μg/m3 for 2000-2003 and with ~50% decrease for 2004-2006. 

Given both the alignment of this sector with the prevailing wind direction and the magnitude of 

the expected concentrations, the emission reductions achieved from this sector are most 

responsible for the observed decrease in the excess mass concentration over time. Local 

emission sources in this sector include a large quarry. Like Dearborn, the NWR results are 

relatively insensitive to the censoring of extreme values (Figure E-1). In summary, the wind 

direction dependence of expected excess mass concentration at Wyandotte is consistent with 

known emission sources / source regions. Expected concentrations have decreased over the past 

few years for two wind distinct bearings – north and southwest of the site – which suggest that 

emission reductions have taken place in both sectors. The reductions from the southwest are 

more significant to both annual average concentrations and high PM days. 

Annual mean and median excess mass concentrations at Southwest High School also decreased 

starting in 2005 (Figure 5-6). NWR polar plots suggest the excess mass decrease was driven by 

emission reductions to the south/southwest. However, NWR results for all data and censored 

data (Figure E-1) demonstrate that a few extreme events were driving the higher expected mass 

from the south/southwest for 2000-2003 compared to 2004-2006. Indeed, the NWR plot for 

censored data (Figure 5-6, bottom) shows essentially no difference in expected excess mass at 

the location of the maximum (~190°N). Emission reductions might be driving small differences 

in expected excess concentration between 2000-2003 and 2004-2006 at bearings of ~105, 

250-300, and 355°N. The expected excess mass concentration floor was ~2 μg/m3

 for 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 41

2000-2003 and was modestly lower for 2004-2006. This floor is similar to the excess mass 

concentration floor observed at Dearborn which is consistent with their close proximity. In 

summary, in contrast to Dearborn and Wyandotte, individual local sources contributing to excess 

mass at Southwest High School appear to have smaller average impact and are potentially more 

numerous. Highest expected concentrations are from bearing of ~190°N and with extreme 

events realized primarily in the period 2000-2003. Based on Figure 4-3 these events typically 

occurred on relatively clean days (base concentrations 10-20 μg/m3

) and were not sufficiently 

high to cause exceedances. Like Dearborn, there is a relatively high floor for the excess mass 

over all wind directions but the relative contributions of mobile, area, and dispersed point source 

emissions is not known. 

Linwood is located near the northeast corner of the Detroit industrial core. There are no 

discernible changes in the excess mass distribution over time (Figure 5-7). NWR polar plots 

show different features for the 2000-2003 and 2004-2006 time periods; the differences are driven 

by extreme values and NWR on the censored data yields very consistent concentrations profiles 

for the two time periods (Figure 5-7, bottom plot). The excess mass concentration floor is 

~0.5 μg/m3 with perhaps modestly lower values for bearings to the east/northeast (60-105°N). 

Increased excess mass is observed over the range 120-240°N with a broad maximum at 150-

210°N. This behavior suggests that Linwood is at the fringe of the high emissions zone in the 

Detroit commercial/industrial core. Excess mass concentrations when the winds are from the 

southwest approach 1.5-2 μg/m3, consistent with the floors at Dearborn and Southwest High 

School. For other wind directions, the expected concentrations are lower. 

The above detailed analysis of four sites – Dearborn ,Wyandotte, Southwest High School, and 

Linwood – contributes to our understanding of local and urban-scale emissions contributions to 

observed PM mass. Local point source impacts are historically large at both Dearborn and 

Wyandotte but have been decreasing. In both cases, the largest contributors are located 

southwest of the sites, which is consistent with the prevailing winds. Dearborn and Southwest 

High School have expected excess mass concentrations of a least 1.5-2 μg/m3 from all wind 

directions, while the minimum expected mass concentrations are lower at Wyandotte and 

Linwood. Thus, Dearborn and Southwest High School appear to be within the high emissions 

zone with contributions from multiple point sources and possibly significant contributions from 

area and mobile sources. The plume from this high emissions zone is advected downwind, 

consistent with the higher expected excess mass concentrations at Wyandotte and Linwood for 

winds from the north and south/southwest, respectively. Thus plume is superposed on the 

broader urban-scale emissions contributions from mobile, area, and possibly other point sources, 

which presumably also disperse as advected downwind. 

This conceptual model is tested by examining excess mass patterns at sites outside the 

commercial/industrial core. Figure 5-8 shows the Allen Park, Dearborn, Linwood, East 7 Mile, 

and New Haven NWR results for 2004-2006 censored data (note the concentration scale range is 

different than Figures 5-4 to 5-7). These five sites fall roughly along a transect oriented ~225°N 

and thus can be examined using the framework of Figure 2-1. The right figure shows that Allen 

Park (black line) and Linwood (red line) concentration profiles are nearly mirror images 

spanning the range 0.25-2 μg/m3 with a Linwood maximum and Allen Park minimum at 

180-220°N. These sites are on opposite ends, and nearly equidistant, from Dearborn (clearly a 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 42

-2

-1

0

1

2

3

4

5

6

7

8

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Allen Park, 2004-2006

Dearborn, 2004-2006

Linwood, 2004-2006

East 7 Mile, 2004-2006

New Haven, 2004-2006

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Allen Park, 2004-2006

Linwood, 2004-2006

East 7 Mile, 2004-2006

New Haven, 2004-2006

Figure 5-8. NWR expected concentrations for excess PM2.5 mass compared to the network-wide base 

concentration, 2004-2006 data censored to remove extreme values as described in footnote #12. 

hot spot, left figure) and the industrialized zone to its southeast. This suggests there is an 

emissions plume emanating from Dearborn and industrial areas to its southeast, extending to the 

Detroit River, which impact Allen Park and Linwood similarly in terms of expected 

concentrations. Average mass contributions to these sites will differ with the frequency 

distribution of wind directions. The expected concentration from this plume decreases at more 

distant sites. It is still evident at East 7 Mile and is barely discernible from the baseline at New 

Haven. In addition to this plume from the Detroit commercial/industrial core, there appears to be 

a broader urban scale emissions profile as evidenced by the decreasing excess mass 

concentration floors with increasing distance from the Detroit population core. Expected excess 

mass concentrations for bearings outside the commercial / industrial core plume are ~ 0.5 μg/m3

at Allen Park and Linwood, ~0 μg/m3 at East 7 Mile, and about -1 μg/m3 at New Haven. Recall 

that the base concentration includes regional and some urban-scale contributions and the 

negative excess concentrations at New Haven suggest a maximum of at least 1.5μg/m3 (based on 

-1 μg/m3

 at New Haven and +0.5 μg/m3 at Allen Park/Linwood) for the urban-scale 

contributions within the metro area. 

Six sites – Allen Park, East 7 Mile, Livonia, New Haven, Oak Park, and Ypsilanti – are 

considered from a complementary perspective. Figure 4-3 demonstrates that large excess mass 

excursions above the network-wide base concentration are relatively rare at these sites. There 

are occasional extreme excess values which are both positive and negative with respect to the 

base concentration, so the excess mass distributions were stabilized by censoring to remove 

extreme values.12 NWR results for all these sites using both all data and censored data are 

presented in Figure E-1. For each site, all expected concentrations were scaled so the lowest 

expected concentration as a function of wind direction was zero (concentrations are negative 

when the expected concentration is below the base concentration) and the normalized to a 

maximum expected concentration of unity. Figure 5-9 shows the scaled NWR concentration 

plots are superposed on 2000 census tract level population density data. The plots are ordered 

clockwise about Detroit area starting with Ypsilanti and ending with Allen Park. The following 

features are observed. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 43

YPSILANTI LIVONIA

OAK PARK EAST 7 MILE

NEW HAVEN ALLEN PARK

Figure 5-5. 1-D NWR for excess mass at each site (green circle) relative to the network-wide 

baseline concentration for 2004-2006, censored to remove extreme values according to footnote 

#12. NWR results are superposed on 2000 census tract population density data.
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 44

• Ypsilanti. The expected excess mass concentration ranged from -1 to +1 μg/m3

. 

Bearings of highest excess mass concentration correspond to an urban plume emanating 

from the east, consistent with the Detroit population and commercial/industrial cores. 

• Livonia. The expected excess mass concentration ranged from -1 to +1 μg/m3. Bearings 

of highest excess mass concentration correspond to an urban plume emanating from the 

Detroit population and commercial/industrial cores with potentially larger impacts from 

the latter core. 

• Oak Park. The expected excess mass concentration ranged from -0.5 to +1 μg/m3

. The 

higher floor is consistent with this site being closer to the Detroit population and 

commercial/industrial cores than Ypsilanti and Livonia. Bearings of highest excess mass 

concentration range from due east to due south, consistent with the Detroit population 

and commercial/industrial cores. 

• East 7 Mile. The expected excess mass concentration ranged from 0 to +1 μg/m3

. 

Highest concentration bearings are to southwest with elevated expected concentrations 

also to the west, consistent with the Detroit commercial/industrial and population cores, 

respectively. 

• New Haven. The expected excess mass concentration is nearly constant at -1 μg/m3

. A 

bearing of modestly elevated expected excess mass concentrations is to the southwest, 

aligned with the Detroit commercial/industrial and population core. 

• Allen Park. The expected excess mass concentration ranged from 0.5 to +2 μg/m3. 

High concentration bearings are to the north through east of the site, consistent with the 

Detroit population and commercial/industrial cores. 

These six sites completely surround the Detroit population and commercial / industrial cores and 

in each case demonstrate highest expected excess mass for winds from the core zones. This 

analysis clearly demonstrates the ability to decouple excess mass concentrations from the 

network-wide base and to draw a consistent interpretation from the results across all sites. 

Ypsilanti, Livonia and New Haven all have expected excess mass concentrations of about -

1 μg/m3

 when the sites are upwind of the Detroit population and commercial/industrial cores. 

Thus a reasonable estimate for the average urban-scale contribution to the average network-wide 

base is about 1 μg/m3

. The 2004-2006 average base concentration of 13.5 μg/m3 could be 

apportioned as 12.5 μg/m3

 from regional sources and a 1 μg/m3 portion of the urban-scale 

contributions. Urban-scale emissions contribute, on average, up to 3 μg/m3

 depending on 

location within the Greater Wayne County area and the specified wind pattern. They appear to 

be greatest in the Detroit commercial/industrial core and might include significant contributions 

from point sources that are either far enough from the monitor and/or low enough in emissions to 

not be distinguished from the urban-scale contributions. Large local emission sources can exert 

significant influence on near-field monitors as demonstrated for Dearborn and Wyandotte. 

In summary, analyses of PM2.5 mass concentrations – separated into network-wide base and 

site-specific excess mass components – together with surface winds provide the following model 

for PM2.5 mass concentrations over Southeast Michigan (excluding the distant sites of Ann 

Arbor, Luna Pier, and Port Huron): 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 45

• At most sites, high PM days coincide with network-wide high PM levels and typically 

occur when the area is experiencing a multiday high PM episode (Section 4). 

• Hot spots of high PM concentration arise near large emission sources and, in the cases of 

Dearborn and Wyandotte, can drive exceedances (or near exceedances) of the daily 

standard. In both cases, the high emissions zones are located to the southwest of the 

monitoring sites. This is consistent with the prevailing winds from the southwest 

exacerbating the frequency of high impact days. Expected concentration contributions 

from these zones have decreased in recent years, presumably due to emission reductions. 

• An idealized conceptual model for PM behavior, that explains, both daily and annual PM 

mass trends, consists of four layers: (1) regionally transported PM with average 

concentration of about 12.5 μg/m3

 over the 2004-2006 period; (2) urban-scale emissions 

from mobile, area, and point sources that contribute up to 3 μg/m3 for specific surface 

winds patterns, depending on location, with less impact when averaged over the 

distribution of wind directions impacting a given site; (3) a PM plume from the Detroit 

commercial/industrial core that remains distinct from the other urban-scale contributions 

for sites as distant as East 7 Mile and possible New Haven; and (4) localized hot spots for 

cases when certain monitoring sites are directly impacted by emission plumes from 

nearby sources with high potentially impacts on a given day and less impact when 

averaged of the distribution of wind directions impacting such sites. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 46

6. SUMMARY, POLICY-RELEVANT IMPLICATIONS, AND RECOMMENDATIONS 

Summary

At most sites in Southeast Michigan, exceedances occur predominantly – and in some cases 

exclusively – on days when the entire network is exhibiting high PM. For thirteen of the fifteen 

monitors, at least 85% of exceedances occurred on days when the entire network was exhibiting 

high PM. Drivers for network-wide high PM are regional transport, poor atmospheric ventilation 

across the network, or both of these conditions. Two monitors in particular – Dearborn and 

Wyandotte – frequently had exceedances on days when the entire network was not exhibiting 

high PM with 38% of the Dearborn exceedances and 27% of the Wyandotte exceedances 

occurring on such days. On these days, these sites are significantly influenced by nearby 

emission sources. Dearborn continues to be influenced by nearby emission sources which drive 

exceedances (or near exceedances) on days when the network-wide base concentration is as 

much as 15 μg/m3

 below the standard, although the frequency of such days appears to be 

decreasing. In contrast, at Wyandotte all of the days for which nearby emission sources were 

disproportionately contributing to exceedances (or near exceedances) of the standard were prior 

to 2004. At those sites not significantly impacted by plumes from nearby emission sources, high 

PM days are most often observed when the area is experiencing a multiday high PM episode. 

Seasonal variations in surface winds can explain the seasonal differences in frequency of high 

PM days between sites in the Greater Wayne County area. Sites such as Allen Park, which are 

relatively free of impacts from nearby sources, exhibit similar seasonal behavior with high PM 

days most frequent in the summer followed by the winter. The monthly distribution of high PM 

days is distorted for sites with significant nearby emission sources since there is a strong 

seasonality to the surface winds distributions. For example, Dearborn has as many high PM days 

in the winter as in the summer, with the winter season having a stronger contribution from 

nearby sources located to the southwest of the site. 

Network-wide high PM days have disproportionately high contributions from the major ions 

(sulfate, nitrate, and ammonium) compared to other days. Summertime events are dominated by 

sulfate and wintertime events are dominated by ammonium nitrate. However these so-called 

high nitrate days typically have ammonium sulfate concentrations that are at least 50% of the 

ammonium nitrate concentration. The role of sulfate on such days should not be overlooked 

when considering the impact of SO2-based regional control strategies. In general, network-wide 

PM base concentrations above ~20 μg/m3

 tend to be disproportionately influenced by major ion 

contributions and are indicative of a disproportionately high influence from regional sources. 

On network-wide high PM days the sulfate and nitrate concentrations are typically several times 

higher than the corresponding monthly median concentrations. In contrast, EC is on average 

only 1.3 times higher. This pattern suggests that network-wide high PM days are primarily 

influenced by regional transport and are to a much lesser extent influenced by a increased levels 

of urban-scale emissions arising from poor atmospheric ventilation. As previously stated, 

emission sources near the monitoring sites can still exert significant plume impacts regardless of 

the network-wide PM behavior driven by regional and urban-scale contributions. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 47

Many network-wide high PM days coincide with high nitrate, and in some cases there is 

substantial variability in PM mass concentration across the network on these days. It is 

important to determine whether the variability is real or a measurement artifact, because these 

days can influence into the site-specific design values and in general can explain many of the 

exceedingly high PM levels observed at certain sites that otherwise do not appear to be 

disproportionately impacted by nearby local emission source plumes on high PM days. 

A conceptual model for fine PM over central Southeast Michigan includes four elements. The 

largest contributor to annual average PM is regionally transported material that is temporally 

varying but spatially homogeneous over the domain (indeed, this defines the spatial extent of the 

domain for the conceptual model which in this case excludes the distant sites such as Luna Pier 

and Port Huron). On some days, regionally transported PM contributions can be sufficiently 

high to cause exceedances of the daily standard when coupled with average contributions from 

urban- and finer-scale emission sources and, in relatively rare cases, the regionally transported 

PM alone can cause exceedances of the daily standard. Urban-scale emission sources (mobile, 

area, and point sources) create a spatial PM gradient across central Southeast Michigan. For 

winds from a fixed direction, these contributions create an “urban plume” with decreasing 

impacts with increasing distance from the zone of highest emissions activity. The spatial 

gradients can be clearly discerned when binning data from days with common wind patterns and 

become smeared, to some extent, when averaging over periods with varying wind patterns. At 

many sites (e.g., Linwood, East 7 Mile) a PM plume emanating from the Detroit commercial / 

industrial zone, which is nominally Dearborn and areas to its southeast towards the Detroit River, 

including Zug Island, can be distinguished from the aforementioned urban plume. At sites 

further downwind, such as New Haven, these two plumes have essentially merged into a single 

urban plume. Average impacts from these plumes depend on the monitoring site location 

relative to the Detroit population and commercial/industrial core zones and the frequency that 

winds from these zones transport the plumes to the monitoring site. Finally, certain monitors in 

the Detroit commercial/industrial zone are significantly impacted by emissions from nearby 

sources that ultimately contribute to the distant PM plume emanating from this zone. At 

Dearborn and Wyandotte these sources are located southwest of the monitoring sites and 

historically have contributed to exceedances (or nears exceedances) of the daily standard. These 

sources also disproportionately influence the annual standard because they are oriented upwind 

of the sites for prevailing winds from the southwest. 

In summary, emission controls that reduce regionally transported PM are needed to reduce the 

frequency of violations of the 24-hour PM2.5 standard. Emission reductions from a few specific 

point sources, especially near Dearborn, are also needed. While regional and point source 

controls will decrease annual average PM2.5 concentrations for standardized synoptic weather 

patterns, relatively small but significant decreases could also be realized by controls on other 

urban emission sources such as mobile, area, and other point sources. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 48

Policy-Relevant Implications 

The policy-relevant implications are framed using the Weight-of-Evidence (WOE)9

 prepared in 

support of the control strategy package for the attaining the PM2.5 annual average standard. The 

WOE elements are in regular typeface with comments, based on this work, added in italics. 

I. Inventory 

• I(c)... National stationary source controls, including CAIR and the NOx SIP call, are expected to 

reduce point source NOx emissions by 40% and SO2 emissions by 15% between 2002 and 2009. 

These reductions are very important to the daily standard control strategy because exceedances of 

the daily standard tend to occur on days with network-wide high PM from regional transport of 

species including but likely not limited to ammonium sulfate and ammonium nitrate.

• I(c)... [There] is compelling evidence that areas in Southeast Michigan that are currently attaining the 

[annual] standard will remain in compliance. For the period 2004-2006, only one monitor in 

Southeast Michigan was in compliance with the 24-hour standard. While reductions in local 

emissions should prevent backsliding, daily exceedances are coupled to the frequency and severity of 

regional transport episodes which can vary from year to year. For example, 2005 was severe in 

terms of regional transport and this is reflected in the elevated 98th percentile concentrations across 

all sites in Southeast Michigan.

• I(d)... While these [programmed] reductions are already having a significant, positive impact in 

Southeast Michigan and will continue to do so in future, we cannot assume that they will result in 

attainment at Dearborn and Southwestern High School (SWHS), the two monitoring sites that are still 

exceeding the annual standard. Additional reductions in the vicinity of these sites are needed. 

Dearborn is currently the design value site for the daily standard. This study has demonstrated that 

contributions from certain local emission source have decreased in recent years. In contrast, the 

magnitude of the urban plume, which includes a broader range of emission sources, has not 

significantly decreased in recent years as evidenced by expected concentration patterns observed at 

sites such as East 7 Mile and Linwood. 

• I(e)... The area surrounding the two non-attaining monitors in Southeast Michigan contains a 

complex array of emission sources. Some of these sources may be significant contributors because 

their emissions occur closer to ground level and/or because of their proximity to a monitor. However, 

many of these are area sources that are exempt from MDEQ’s emissions inventory reporting 

requirements so their exact contribution is unknown. In addition, many of these smaller sources have 

little or no emission controls while larger sources already have controls in place. At these sites and a 

few other sites, the analysis in Section 5 point towards the bearings where efforts should be focused 

to refine emission estimates – in particular, zones southwest of the monitoring sites due to prevailing 

wintertime surface winds lead to lead to higher PM than the rest of the Southeast Michigan network. 

• I(f)... A number of industrial facilities in the area surrounding the Dearborn, Southwestern High 

School, and Wyandotte monitors have either closed or scaled back their operations since 2002. These 

changes are likely contributing to the more rapid decrease in PM2.5 levels observed at industrial 

monitoring sites. While we have indeed identified decreased local emission source contributions at 

some sites. 

• I(g)... In addition to changes that have already taken place, significant local PM2.5 reductions will be 

achieved from controls that are currently being phased in at the Severstal and U.S Steel facilities as 

well as the Marathon oil refinery. All three of these facilities are less than three miles from the 

 

9

 “Weight of Evidence for the Southeast Michigan PM2.5 Attainment Strategy”, 8/28/2007 draft, prepared by 

SEMCOG and MDEQ. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 49

monitors measuring the highest PM2.5 concentrations in the region - Dearborn and Southwestern High 

School. Based on a recent EPA study as well as permit application data, MDEQ estimates these 

controls will provide a combined PM2.5 emission reduction of 330 tons per year. These reductions 

should reduce the frequency of high PM days that occur at these sites when the network-wide 

baseline concentration is relatively low, thereby reducing the frequency of spatially isolate 

exceedances and near exceedances. Conditions on network-wide high PM days will also be 

improved. Note that in these cases the sources are located at bearings where prevailing winds can 

favor plume impacts at the monitoring sites, especially in the wintertime. Impacts can be tracked by 

periodically updating the NWR plots and the evaluating shifts in the distribution of site-specific high 

PM days by month. For example, if local source impacts at Dearborn are indeed reduced, we would 

expect the distribution of high PM days by month for Dearborn to shift to more-closely resembling 

Allen Park. Intersite differences between Allen Park and Dearborn should also decrease for the 

relevant species in the CSN data.

• I(h)... There are a significant number of storage piles, unpaved lots, and parcels of barren land in the 

vicinity of the Dearborn and SWHS monitors. While most emissions from these sources are larger 

than 2.5 microns, their collective impact is cause for concern. As part of a previous particulate SIP, a 

number of facilities in the area do have fugitive dust plans. However, many others do not. The 

contribution of fugitive dust to high PM days was not explicitly examined. 

II. Monitoring: 

• II(a)...PM2.5 in Southeast Michigan is comprised largely of sulfates, nitrates, and organic carbon. At 

the Dearborn monitoring site, there is also a significant “crustal” component, which is largely iron. 

The excess iron at Dearborn is largely related to steelmaking operations and efforts to reduce these 

emissions will reduce the local source impacts on exceedance and near exceedance days at 

Dearborn.

• II(b)... Southeast Michigan’s current nonattainment designation pertains to the annual standard, not 

the daily standard. Developing a control strategy to address an annual standard is complicated 

because sources may be significant contributors on certain days or during certain times of the year but 

not during others. However, recent source apportionment studies show that the source contributions to 

PM2.5 on an annual average basis are similar to those on high PM2.5 concentration days. This suggests 

that a strategy designed to reduce annual average PM2.5 concentrations will also be effective in 

reducing high daily PM2.5 concentrations. Strategies targeting regional sulfate and nitrates will be 

important towards meeting both standards; in the absence of significant sulfate reduction it might be 

very challenging to meet the daily standard, even with aggressive local source controls. SO2

reductions might not be fully realized as PM reductions if ammonium nitrate formation is ammonia 

limited. 

• II(c)... The entire Southeast Michigan area has been designated nonattainment. However, the only 

monitors measuring violations of the standard are located in a small portion of eastern Wayne 

County. For 2004-2006 all Southeast Michigan sites except Ann Arbor violated the daily standard. 

However, based on 2005-2007 data several sites were in compliance. This demonstrates the year-toyear variations that can be induced by synoptic weather patterns which in turn include the frequency 

and severity of regional transport events.

• II(f)... Since 2000, PM2.5 concentrations at all sites in the region have steadily declined. The 3-year 

average concentration dropped 1.6 μg/m3

 between 2002 and 2006.. The largest decreases have 

occurred at the sites with the highest concentrations: Dearborn (2.69 μg/m3

), SWHS (2.16 μg/m3), and 

Wyandotte (3.04 μg/m3

). Dramatic year-to-year swings in the 98th percentile concentration are 

observed throughout the Southeast Michigan network due to varying impacts from regional transport. 

In this sense the daily stand is more “volatile” and it is harder to discern long term trends.

• II(g)... PM2.5 concentrations at monitoring sites in the industrial core of Southeast Michigan’s 

nonattainment area (Dearborn, SWHS & Wyandotte) have been decreasing faster than other sites. 

This is likely due to changes in emissions in the industrial area. Reduced impacts from local emission 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 50

sources at Dearborn and especially Wyandotte have indeed been demonstrated in this study; average 

reductions are smaller at SWHS and are coupled to a lower frequency of extreme events which might 

have been caused by upsets at industrial facilities. Of course, any future industrial activity expansions 

that increase emissions could at least partially reverse these trends.

• II(k)... At the time Southeast Michigan was designated nonattainment, monitoring data showed the 

Luna Pier monitor in Monroe County was violating the annual standard. This monitor is located in the 

southeastern corner of the county, one mile north of the Ohio border. In its February 2004 PM2.5 

nonattainment designation recommendation to EPA, MDEQ argued strongly that Monroe and Wayne 

counties should be designated as separate nonattainment areas because PM2.5 levels at the Luna Pier 

monitor tracked far more closely with those in Toledo. Many regional events operate on a large 

enough spatial scale to similarly impact Luna Pier and the Wayne County area. Indeed, the behavior 

at these two areas appears coupled on high PM days. That said, Figure 4-3 demonstrates that Luna 

Pier and Port Huron have the greatest dispersion about the network-wide base concentration – 

including many days that are lower than the base concentration – and thus they are not fully coupled. 

• II(l)... MDEQ and SEMCOG also showed that levels at the site had been decreasing in recent years 

and trend data indicated the monitor would likely measure attainment by the end of 2004. This was 

an accurate prediction. Levels at the site have continued to track those in Toledo and monitors in 

both areas have measured attainment of the standard since 2004. In 2005, EPA redesignated the 

Toledo area as attainment. Luna Pier continues to violate the daily standard (2004-2006 data).

• II(m)... In addition, as of 2006, monitors at Allen Park, Linwood and Wyandotte are now measuring 

attainment [of the annual average NAAQS]. Allen Park, Linwood and Wyandotte continue to violate 

the daily standard (2004-2006 data). 

• II(n)... The area where the two remaining violating monitors (Dearborn and SWHS) are located is 

one with a history of particulate matter problems, associated with local industrial sources. [...] the 

areas are nearly identical. The primary source of the former PM10 problem was determined to be a 

few local industrial sources. Emissions from these sources were reduced and the region came into 

compliance in 1996. The overlap of the Total Suspended Particulate (TSP) and PM10 nonattainment 

areas with the PM2.5 nonattainment area, and the successful attainment of those standards after the 

application of local controls, suggests that the most effective attainment strategy is to focus on local 

emission reductions from sources in this area. Reductions in local emissions near Dearborn have 

decreased the frequency of high PM days resulting from local emission sources (Figure 4-5) and the 

programmed emission reductions should further help to lower the local emission source influences. 

Local emissions near SWHS frequently lead to near exceedances when the network-wide PM levels 

are otherwise low but, unlike Dearborn and Wyandotte, the local source contributions appear to be 

just low enough to avoid exceedances on otherwise relatively clean days. 

• II(o)... Various analyses of both local and regional monitoring data all indicate that Southeast 

Michigan’s nonattainment problem is caused by a combination of regional transport and local 

emissions from sources in the vicinity of the violating monitors. This has also been demonstrated for 

the daily standard in this study with local source impacts driving the frequency of exceedances at a 

few sites and regional transport contributing to exceedances at all sites. 

• II(o)(3)... Lake Michigan Air Directors Consortium (LADCO) analysis of rural background 

concentrations versus urban excess in the Midwest shows that the vast majority of PM2.5 measured in 

our region is coming from outside Southeast Michigan. This pattern is certainly the case on networkwide high PM days that coincide with the most frequent exceedances of the daily standard. 

• II(o)(6)... A wind rose for the iron component of PM2.5 at Dearborn points directly to the 

southwest. Conversely, the iron wind rose for Allen Park, while measuring much lower levels, 

points to the northeast. The Allen Park monitor is approximately five miles southwest of Dearborn. 

Additional wind direction analysis shows that, when winds are from the southwest average crustal 

concentrations at Dearborn are over 2.5 μg/m3 higher than those at Allen Park and are sometimes as 

much as 6 μg/m3

 higher. This clearly indicates a significant local iron source directly between these 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 51

two sites (which are approximately five miles apart) and closer to the Dearborn monitor. The 

importance of local emission sources to the southwest of Dearborn has been demonstrated in this 

study. These sources likely lead to the high frequency of wintertime high PM days at Dearborn 

compared to the Allen Park and the rest of the network since the prevailing surface winds are from 

the southwest during the winter.

• II(p)... The localized nature of Southeast Michigan’s nonattainment problem makes broad-based 

application of control measures throughout the official seven-county nonattainment area an 

ineffective and unproductive strategy for bringing the region into compliance. All available data 

show that targeted local organic carbon emission reductions, coupled with the iron reductions 

resulting from planned steel mill controls, will be the most cost-effective way to bring the region into 

attainment. Similarly, while the relative roles of regional- and urban-scale contributions have not 

been quantified in this study, it has been shown that regionally transported species concentrations 

are enhanced much more than urban-scale tracer species on high PM days. 

• II(y)... The difference in PM2.5 is highest from the southwest and west wind directions when nearby 

monitors are subtracted out of the Dearborn concentration. This would indicate that there is a large 

local source [or sources] between the Dearborn and “background” monitors (Allen Park, Luna Pier & 

Ypsilanti). This was clearly demonstrated in Section 5 of this study. 

Recommendations for Future Work 

Projects currently funded by LADCO will likely provide considerable refinements to this 

analysis. For example, sampling for organics speciation and the planned data analysis – 

including source apportionment – should inform the assignment of organic carbon to local and 

regional sources. . MDEQ is deploying semicontinuous monitors for particle speciation and 

high time resolution data can be particularly powerful for identifying source contributions. 

Results from the summer 2007 USEPA/ORD measurement intensive should be particularly 

insightful since PM elements were measured at high time resolution. Outdoor measurement data 

from USEPA’s DEARS project could also be exploited. 

A background monitoring site would be helpful, but care is needed to ensure it is sufficiently 

coupled to the Detroit area in terms of air mass behavior. The site needs to be far enough away 

to not be influenced by the urban area, but close enough to still be similarly impacted by regional 

transport. This is even more critical if measurements will be conducted for 24-hour periods once 

every few days as the “snapshots” at each monitor must be synchronized across the domain. For 

example, the background site effectively used for St. Louis is about 100 km to the south which 

places it upwind of the city for the prevailing surface winds. Perhaps more importantly, 

however, the line connecting this site to the urban area is nearly perpendicular the direction of 

summertime synoptic air mass flows which lead to high PM in St. Louis (St. Louis is often on 

the backside of a high pressure system located over the Great Lakes, which lead to regional 

transport from the east/southeast). This orientation might actually be preferred as an upwind site 

– from the surface winds perspective – because the sites will be impacted at the same time for 

regional air masses with spatial extents greater than the site separation. 

A better understanding of the drivers for high spatial variability in FRM mass on high nitrate 

days is needed since only a few such events can dramatically affect the site-specific design 

values for the 24-hour standard. When such patterns are observed, perhaps the Teflon filters 

could be analyzed for nitrate by IC to determine the extent of nitrate retention; this would be 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 52

particularly insightful for days coinciding with speciation sampler operation to place the Teflon 

filter nitrate levels in context of the ambient concentrations. 

It might be possible to better characterize the spatial pattern of urban-scale emission source 

contributions by performing reflectrometry measurements on archived PM2.5 FRM samples. The 

parameter from these measurements is typically highly correlated with thermo-optical EC. Thus, 

it provides an inexpensive approach to characterizing EC spatial profiles which might be a 

reasonable surrogate for urban-scale emission sources. 

FIA/Lafayette and Newberry sites were excluded from this analysis because they commenced 

operation relatively recently. The analysis used concentration percentiles across the network to 

define network-wide behavior and thus it was necessary to use a temporally consistent subset of 

the network. The base concentrations generated from this work could be applied to the 

FIA/Lafayette and Newberry data to split observed concentrations into base and excess mass 

components, and then nonparametric wind regression (NWR) could be used to determine 

expected excess mass concentrations as a function of wind direction. This work, which is 

relatively modest in level of effort, could significantly contribute to our understanding of PM 

behavior in the Detroit commercial/industrial core. 

Relatively little attention has been given to the behavior at Luna Pier and Port Huron on high 

concentration days. The analysis approach taken in this report has limitations when applied to 

sites at such large distances from the Greater Wayne County area. Locally-collected surface 

winds should be used to examine behavior at these sites. Luna Pier and Port Huron must also be 

considered within the context of emissions from Toledo and Sarnia, respectively. 

NWR results are presented in Section 5 in terms of the expected concentration of excess mass 

observed at a site when the winds are from a given direction. This has proven to be insightful 

because the results do not depend on the frequency distribution of wind directions which can 

vary from year-to-year and confound the identification of temporal changes in emissions. From 

this analysis we can state that emissions from a certain wind sector have been modulated by a 

certain amount over time. However, we are also interested in an apportionment of the 

contributions of such emission sources to the PM burden at the monitoring site. This would 

require weighting the expected concentrations by the frequency of winds from each direction 

sector. We have developed a conceptual model based on the network behavior for various 

surface wind patterns. The next step is to incorporate the observed distribution of wind patterns 

to quantify how the observed PM levels are being modulated. We have shown that a PM plume 

from the Detroit commercial/industrial core impacts Linwood. By incorporating the observed 

distribution of surface wind directions we could quantify the annual-average PM mass from this 

plume impacting the site. This analysis would extend the focus of this report on high PM days to 

more robustly characterize annual average behavior and could be instrumental in providing a 

framework for assessing the effectiveness of emission control programs. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 53

7. REFERENCES 

Allen, D.T.; Turner, J.R. (2008) “Transport of Atmospheric Fine Particulate Matter: Part 1. 

Findings from Recent Field Programs on the Extent of Regional Transport within North 

America”, J. Air Waste Manage. Assoc., 58, 254-264. 

Pinto, J.P.; Lefohn, A.S.; Shadwick, D.S. (2004) “Spatial variability of PM2.5 in urban areas in 

the United States”, J. Air Waste Manage. Assoc., 54, 440-449. 

Turner, J.R.; Allen, D.T.; (2008) “Transport of Atmospheric Fine Particulate Matter: Part 2. 

Findings from Recent Field Programs on the Intraurban Variability in Fine Particulate Matter”, 

J. Air Waste Manage. Assoc., 58, 196-215. 

Turner, J.R.; Garlock, J.L. (2007) “A conceptual model for ambient fine particulate matter over 

the St. Louis area”, Revision 3.0 (10/10/2007), prepared by the Air Quality Laboratory at 

Washington University in St. Louis, submitted to the Missouri Department of Natural Resources. 

Vickery, J.S. (2004) “Conceptual Models of PM for North American Regions”, Chapter 10 in 

Particulate Matter Science for Policy Makers: A NARSTO Assessment, P.H. McMurry, M.F. 

Shepherd, J.S. Vickery, eds., Cambridge University Press. 

Wade, K.S.; Turner, J.R.; Brown, S.G; Garlock, J.L., Hafner, H.R. (2008) “Data analysis and 

source apportionment of PM2.5 in selected Midwestern cities”, Report # STI-907018.03-3264-FR 

(February 2008), prepared by Sonoma Technology, Inc. (Petaluma, CA), submitted to the Lake 

Michigan Air Directors Consortium (LADCO). 

ACKNOWLEDGEMENTS 

The analysis summarized in this report benefited from constructive input provided by members 

of the Southeast Michigan Ozone Study (SEMOS) group and project management provided by 

Ms. Joan Weidner and Mr. Chuck Hersey (SEMCOG). Technical assistance provided by 

Michigan DEQ staff (especially Mary Ann Heindorf, Cindy Hodges and Amy Robinson) and 

Ms. Ann Burns (SEMCOG) is also gratefully acknowledged. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 54

APPENDIX A: PM2.5 HIGH CONCENTRATION DAYS BY MONTH 

Allen Park

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

East 7 Mile

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Dearborn

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Luna Pier

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

New Haven

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Oak Park

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Wyandotte

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Ypsilanti

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Livonia

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Southwest High Sch.

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Linwood

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Port Huron

Month

1 2 3 4 5 6 7 8 9 10 11 12

fraction of days greater than threshold 0.00

0.05

0.10

0.15

0.20

Figure A-1. Distribution of PM2.5 high concentration days by month, 1999-2006. Ann Arbor, 

FIA/Lafayette, and Newberry are excluded because FRM data was not collected at these sites over the 

entire time period.
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 55

APPENDIX B: HOURLY WIND ROSES 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

Dec98-Feb99 

Winter Spring Summer Fall 

Mar99-May99 Jun99-Aug99 Sep99-Nov99 

Dec99-Feb00 Mar00-May00 Jun00-Aug00 Sep00-Nov00 

2011% 14% 13% 

7% 10% 11% 10% 

 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

Dec00-Feb01 

Winter Spring Summer Fall 

Mar01-May01 Jun01-Aug01 Sep01-Nov01 

Dec01-Feb02 Mar02-May02 Jun02-Aug02 Sep02-Nov02 

4% 9% 13% 9% 

4% 7% 15% 11% 

 Figure B-1. Seasonal wind roses for non-calm hours, observations at Detroit Metropolitan Wayne 

County Airport (DTW). Calms (wind speeds less than 2 mph) are listed to the lower-left of each wind 

rose. 

>2 - 4

>4 - 8

>8 - 16

>16

WS (mph)
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 56

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

Dec02-Feb03 

Winter Spring Summer Fall 

Mar03-May03 Jun03-Aug03 Sep03-Nov03 

Dec03-Feb04 Mar04-May04 Jun04-Aug04 Sep04-Nov04 

6% 11% 17% 11% 

7% 7% 9% 16% 

 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

Dec04-Feb05 

Winter Spring Summer Fall 

Mar05-May05 Jun05-Aug05 Sep05-Nov05 

Dec05-Feb06 Mar06-May06 Jun06-Aug06 Sep06-Nov06 

7% 11% 14% 12% 

6% 12% 14% 12% 

Figure B-1 (continued). Seasonal wind roses for non-calm hours, observations at Detroit Metropolitan 

Wayne County Airport (DTW). Calms (wind speeds less than 2 mph) are listed to the lower-left of each 

wind rose. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 57

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

1999 

11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2000

9% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2001

9% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2002 

10% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

1999 

19% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2000

9% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2001

9% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2002 

10% 

All Days Valid Network Days

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2003 

11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2004 

10% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2005 

11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2006

11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2003 

11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2004 

10%

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2005 

11% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2006

11% 

All Days Valid Network Days

 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2007 

13% 

NNE

NE

ENE

E 

ESE

SE

SSE

S

SSW

SW

WSW

W 

WNW

NW

NNW

N

0% 5% 10% 15%

2007 

13% 

 

Figure B-2. Annual wind roses for non-calm hours, observations at Detroit Metropolitan Wayne County 

Airport (DTW) for all days and valid network days. Calms (wind speeds less than 2 mph) are listed to the 

lower-left of each wind rose. 

>2 - 4

>4 - 8

>8 - 16

>16

WS (mph)
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 58

APPENDIX C: SITE-SPECIFIC HIGH PM DAYS NOT OBSERVED THROUGHOUT 

THE NETWORK, 1999-2006 

Dearborn E 7 Mile Linwood Livonia Luna Pier Oak Park Port Huron SWHS Wyandotte

07/05/1999 (2) 05/12/2000 (1) 11/18/1999 (2) 12/17/2000 (1,2) 05/10/2001 (1,2) 11/25/2006 (1) 05/07/2005 (1,2) 09/27/1999 (2) 07/05/1999 (2)

01/01/2000 (2) 04/18/2004 (1,2) 12/08/1999 (2) 03/12/2002 (2) 07/18/2005 (1,2) 07/17/2000 (1,2) 05/06/2000 (1)

01/31/2000 (2) 01/28/2005 (1,2) 01/02/2000 (2) 04/02/2002 (1,2) 02/09/2001 (1,2) 05/12/2000 (1)

02/24/2000 (1,2) 05/07/2005 (1,2) 02/24/2000 (1,2) 11/02/2003 (1) 05/10/2001 (1,2) 12/26/2000 (1,2)

03/07/2000 (1,2) 08/23/2001 (1) 01/10/2001 (1,2)

05/06/2000 (1,2) 02/14/2003 (1) 01/28/2001 (1)

05/12/2000 (1) 08/25/2003 (1) 07/09/2001 (1)

06/08/2000 (1,2) 11/02/2003 (1) 08/23/2001 (1)

09/09/2000 (1) 12/29/2003 (1,2) 11/28/2002 (1,2)

12/23/2000 (1,2) 03/25/2004 (1,2) 03/19/2003 (1,2)

01/10/2001 (1,2) 04/30/2004 (1) 08/25/2003 (1)

01/28/2001 (1) 02/16/2006 (1) 02/06/2004 (1)

03/02/2001 (1,2) 12/13/2006 (1) 07/18/2005 (1)

08/23/2001 (1) 12/06/2005 (1,2)

12/27/2001 (1,2) 12/21/2005 (1,2)

01/05/2002 (2) 02/10/2006 (1)

01/08/2002 (1,2)

02/07/2002 (1,2)

03/06/2002 (1)

11/13/2002 (1,2)

11/28/2002 (1,2)

01/18/2003 (1,2)

02/08/2003 (1,2)

02/14/2003 (1)

02/20/2003 (1,2)

04/15/2003 (1,2)

11/11/2003 (1,2)

03/25/2004 (1,2)

04/30/2004 (1)

10/15/2004 (1)

12/02/2004 (1,2)

03/29/2005 (1,2)

04/19/2005 (1,2)

07/18/2005 (1,2)

10/31/2005 (1,2)

12/06/2005 (1,2)

02/16/2006 (1)

09/08/2006 (1,2)

12/13/2006 (1,2)

* Ann Arbor, FIA/Lafayette and Newberry excluded from the analysis. 

* No high PM days meeting these criteria for New Haven and Ypsilanti. 

(1) denotes site concentration >30 μg/m3

 while Allen Park <25 μg/m3. 

(2) denotes site concentration >30 μg/m3

 while network-wide base <25 μg/m3 (limited to those days which are valid 

network days) (red bars in Figure 4-9). 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 59

APPENDIX D: CPF AND NWR PLOTS10

PM2.5 mass concentrations (both absolute and excess with respect to a reference site) were 

examined using Conditional Probability Function (CPF) plots and 1-D Nonparametric Wind 

Regression (NWR) plots. Kim and Hopke (2004) compared and contrasted the CPF and NWR 

methodologies and demonstrated that they provide complementary and largely consistent 

information. CPF plots provide insights into the bearing of emission sources impacting the 

monitoring site from a perspective that is not biased by the prevailing wind patterns. The plots 

address the question: “for the ensemble of hourly winds from a given direction, what fraction of 

these hours corresponds to high concentration days?”. The threshold for defining a “high 

concentration day” is typically chosen as the top 25th percentile of the concentration distribution 

(either absolute concentrations or mass fractions). For example, Figure D-1(a) shows the CPF 

plot for the PMF-resolved copper factor at the Springfield site in Chicago. Nearly 70% of the 

hours with winds from 180°N coincided with a daily contribution in the top quartile of the 

concentration distribution for the copper factor contributions. This pattern suggests a copper 

source south of the monitoring site but it does not address the magnitude of the impacts which 

depend on source strength, dispersion characteristics and the frequency of winds from this 

direction. 

One dimensional nonparametric wind regression estimates the expected value of concentration as 

a function of wind direction (Kim and Hopke, 2004). It is similar to a pollution rose but with 

more robust mathematical support. NWR results can be multiplied by the wind direction 

frequency distribution to determine the contribution of each wind direction to average PM mass. 

Figure D-1(b) shows the NWR plot for the PMF-resolved copper factor at the Springfield site in 

Chicago. Factor contributions (red line) for winds from 180°N are three times greater than the 

study-average factor contribution (pink circle). In aggregate the CPF and NWR plots provide 

insights into both the location of emission sources and their impacts. 

0

45

90

135

180

225

270

315

15

30

60

75

105

120

150

195 165

210

240

255

285

300

330

345

0 0.2 0.4 0.6 0.8 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8

9

60

30

0

330

300

270

240

210

180

150

120

(a) (b)

Figure D-1. Surface wind analyses for the PMF-resolved copper factor at the Springfield site in Chicago: 

(a) conditional probability function plot for the top quartile of absolute contributions; and (b) 1-D 

nonparametric wind regression plot (radial units in μg/m3

) where the red line denotes the observed 

contributions from each bearing and the pink circle denotes the study-average contribution. 

 

10 Adapted from Wade et al. (2008). 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 60

APPENDIX E: 1-D NWR ON PM2.5 EXCESS MASS 

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Allen Park, 2000-2003

Allen Park, 2004-2006

[2004-2006] minus [2000-2003]

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Allen Park, 2000-2003

Allen Park, 2004-2006

[2004-2006] minus [2000-2003]

-2

0

2

4

6

8

10

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Dearborn, 2000-2003

Dearborn, 2004-2006

[2004-2006] minus [2000-2003]

-2

0

2

4

6

8

10

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Dearborn, 2000-2003

Dearborn, 2004-2006

[2004-2006] minus [2000-2003]

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR source apportionment on excess mass, ug/m3

E. 7 Mile, 2000-2003

E. 7 Mile, 2004-2006

[2004-2006] minus [2000-2003]

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR source apportionment on excess mass, ug/m3

E. 7 Mile, 2000-2003

E. 7 Mile, 2004-2006

[2004-2006] minus [2000-2003]

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Linwood, 2000-2003

Linwood, 2004-2006

[2004-2006] minus [2000-2003]

ALL DATA CENSORED DATA

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Linwood, 2000-2003

Linwood, 2004-2006

[2004-2006] minus [2000-2003]

Figure E-1 (continued). 1-D NWR results for PM2.5 excess mass relative to the network-wide base for 

all network days (left column) and censored to remove extreme values as defined in footnote #12 (right 

column). The blue line is the change between 2004-2006 and 2000-2003 and the error bands are 95% 

confidence intervals. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 61

ALL DATA CENSORED DATA

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Livonia, 2000-2003

Livonia, 2004-2006

[2004-2006] minus [2000-2003]

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Livonia, 2000-2003

Livonia, 2004-2006

[2004-2006] minus [2000-2003]

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Luna Pier, 2000-2003

Luna Pier, 2004-2006

[2004-2006] minus [2000-2003]

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Luna Pier, 2000-2003

Luna Pier, 2004-2006

[2004-2006] minus [2000-2003]

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

New Haven, 2000-2003

New Haven, 2004-2006

[2004-2006] minus [2000-2003]

-3.50

-3.00

-2.50

-2.00

-1.50

-1.00

-0.50

0.00

0.50

1.00

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

New Haven, 2000-2003

New Haven, 2004-2006

[2004-2006] minus [2000-2003]

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Oak Park, 2000-2003

Oak Park, 2004-2006

[2004-2006] minus [2000-2003]

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Oak Park, 2000-2003

Oak Park, 2004-2006

[2004-2006] minus [2000-2003]

Figure E-1 (continued). 1-D NWR results for PM2.5 excess mass relative to the network-wide base for 

all network days (left column) and censored to remove extreme values as defined in footnote #12 (right 

column). The blue line is the change between 2004-2006 and 2000-2003 and the error bands are 95% 

confidence intervals. 
PM2.5 High Concentration Days over Southeast Michigan 

Washington University in St. Louis October 1, 2008 62

ALL DATA CENSORED DATA

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Port Huron, 2000-2003

Port Huron, 2004-2006

[2004-2006] minus [2000-2003]

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Port Huron, 2000-2003

Port Huron, 2004-2006

[2004-2006] minus [2000-2003]

-1

0

1

2

3

4

5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

SW High Sch., 2000-2003

SW High Sch., 2004-2006

[2004-2006] minus [2000-2003]

-1

0

1

2

3

4

5

000 045 090 135 180 225 270 315 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

SW High Sch., 2000-2003

SW High Sch., 2004-2006

[2004-2006] minus [2000-2003]

-1

0

1

2

3

4

5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Wyandotte, 2000-2003

Wyandotte, 2004-2006

[2004-2006] minus [2000-2003]

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Ypsilanti, 2000-2003

Ypsilanti, 2004-2006

[2004-2006] minus [2000-2003]

-1

0

1

2

3

4

5

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, μg/m3

Wyandotte, 2000-2003

Wyandotte, 2004-2006

[2004-2006] minus [2000-2003]

-2.0

-1.5

-1.0

-0.5

0.0

0.5

1.0

1.5

2.0

2.5

3.0

000 030 060 090 120 150 180 210 240 270 300 330 360

wind direction, o

N

1-D NWR excess mass expected concentration, ug/m3

Ypsilanti, 2000-2003

Ypsilanti, 2004-2006

[2004-2006] minus [2000-2003]

Figure E-1 (continued). 1-D NWR results for PM2.5 excess mass relative to the network-wide base for 

all network days (left column) and censored to remove extreme values as defined in footnote #12 (right 

column). The blue line is the change between 2004-2006 and 2000-2003 and the error bands are 95% 

confidence intervals.