### PM 2.5 

### 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

### PM 2.5 

### 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) PM 2.5 

### standard from 65 μ g/m 3 

### to 35 μ g/m 3 

### . 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 PM 2.5 

### days is needed to support the development of effective controls strategi es; this study seeks to provide insights into such drivers. At most sites in Southeast Michigan, exceedan ces occur predominantly – and in some cases exclusively – on days when the en tire 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 netw ork-wide high PM are re gional transport, poor atmospheric ventilation across th e network, or both of these conditions. Two monitors in particular – Dearborn and Wyandotte – frequent ly 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 exc eedances) on days when the network-wide base concentration is as much as 15 μ g/m 3 

### below the standard, although the frequency of such days appears to be decreasing. In contrast, at Wy andotte 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 ofte n 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 sign ificant nearby emission sources since there is a strong seasonality to the surface winds distribu tions. For example, Dearborn has as many high PM days in the winter as in the summer, with the winter season havi ng 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

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 3 Network-wide high PM days have disproportionately high contri butions from the major ions (sulfate, nitrate, and ammonium) compared to ot her 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 concen tration. The role of sulfate on such days should not be overlooked when considering the impact of SO 2 

### -based regional control strategies. In general, network-wide PM base concentrations above ~20 μ g/m 3 

### tend to be disproportionately influenced by major ion contributions and are indicative of a disproportio nately high influence from regional sources. On network-wide high PM days the sulfate and ni trate concentrations are typically several times higher than the corresponding monthly median con centrations. In contrast, EC is on average only 1.3 times higher. This pattern suggests th at network-wide high PM days are primarily influenced by regional transport and are to a le sser 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-sc ale contributions. Many network-wide high PM days coincide with high nitrate, and in some cases there is substantial variability in PM mass concentra tion 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 va lues 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 em ission source plumes on high PM days. A conceptual model for fine PM over central Sout heast Michigan includes four elements. The largest contributor to annual average PM is regi onally transported material that is temporally varying but spatially homogeneous over the domain (indeed, this defi nes the spatial extent of the domain for the conceptual model which in this cas e excludes the distant sites such as Luna Pier and Port Huron). On some days, regionally tr ansported PM contributi ons can be sufficiently high to cause exceedances of the daily standard when coupled with average contributions from urban- and finer-scale emission s ources and, in relatively rare cases, the regionally transported PM alone can cause exceedances of the daily st andard. Urban-scale emission sources (mobile, area, and point sources) create a spatial PM gr adient across central S outheast Michigan. For winds from a fixed direction, th ese contributions create an “urban plume” with decreasing impacts with increasing distance from the zone of highest emissions activity. The spatial gradients can be clearly discer ned when binning data from days with common wind patterns and become smeared, to some extent, when averagin g 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 south east 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 pl umes have essentially merged into a single urban plume. Average impacts from these pl umes depend on the monitoring site location relative to the Detroit population and commercial/industrial co re zones and the frequency that winds from these zones transport the plumes to th e monitoring site. Finally, certain monitors in the Detroit commercial/industrial zone are si gnificantly impacted by emissions from nearby sources that ultimately contribute to the dist ant PM plume emanating from this zone. At

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 4 Dearborn and Wyandotte these sources are loca ted southwest of the monitoring sites and historically have contributed to exceedances (or nears exceedances ) of the daily standard. These sources also disproportionately influence the annu al standard because th ey are oriented upwind of the sites for prevailing winds from the southwest. The analyses presented in this report exploi ted the relatively high sp atial and temporal PM 2.5 

### FRM measurement density across Southeast Michig an. 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 th at reduce regionally transporte d PM are needed to reduce the frequency of violations of the 24-hour PM 2.5 

### standard. Emission reductio ns from a few specific point sources, especially near Dearborn, are also needed. While regional and point source controls will decrease annual average PM 2.5 

### concentrations for standardized synoptic weather patterns, relatively small but significant decreases could also be realized by controls on other urban emission sources such as mob ile, area, and other point sources.

### PM 2.5 

### 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) PM 2.5 

### standard from 65 μ g/m 3 

### to 35 μ g/m 3 

### . This revision profoundly increased the frequency of exceedance days observed in Southeast Michigan. For fift een monitors over the time period 1999-2006 1 

### , there were 7 and 179 exceedance days (days with one-o r-monitors in the area with concentration greater than or equal to 35 μ g/m 3 

### ) 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 mo tivates 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 emissi ons, meteorology and atmospheric processes that modulate PM concentrations. This “conceptual model”, with explicit emphasis on understanding PM 2.5 

### high mass concentration days over the South east Michigan, could be utilized towards developing effective control strategies. The conceptual model presented in this documen t is focused on the information needed to support the development and implementation of control strategies to meet the 24-hour PM 2.5 

### NAAQS. It intentionally exclude s a detailed treatment of annua l 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 conc eptual model which is necessarily dynamic and must be refined as new knowledge becomes av ailable. Content and presentation of the conceptual model for PM 2.5 

### over Southeast Michigan loosel y follows the framework used by Vickery (2004) for nine North American geog raphic regions and as revisited by Allen and Turner (2008). A conceptual model for PM 2.5 

### over St. Louis was recently developed which included the following elements: a nnual and seasonal levels of PM 2.5 

### in relation to the massbased standards; compositional analysis of PM 2.5 

### ; meteorological influences; atmospheric processes cont ributing to PM 2.5 

### ; sources and source regions c ontributing to the principle chemicals of concern; and implications to pol icy 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 concentrat ion days, compared to annual average behavior, is complicated by several factors. First, high co ncentration days are relatively infrequent and thus there is limited data to probe. Second, while the standard defi nes a bright line for exceedance days, the use of threshold concentrati on 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 thres hold concentration.

1 Some of these monitors did not operate for the entire ei ght year period, and the monitors collect samples with frequency from every day to every sixth day.

### PM 2.5 

### 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 PM 2.5 

### FRM mass concentration data and allied da ta for particle speciation a nd meteorology. Nonetheless, it should be treated as a living document, to be pe riodically updated as ad ditional data becomes available (in particular to captu re temporal trends) and revised as more-detailed analysis is performed on the existing data.

### PM 2.5 

### 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 Southeas t 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 av erage 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 c oncentrations specifically on those days. Many of the data analysis tools, such as receptor mode ling by positive matrix f actorization (PMF), are most powerful when considering the average behavi or; estimates for high concentration days are less reliable and indeed in many analyses extr eme values are down-weighted to improve the stability of the solution. Air qua lity surveillance is relatively sparse with sustained daily FRM measurements at only one site (Allen Park); th is provides a challenge to placing an observed exceedance day in a temporal context. Howe ver, the Southeast Michigan FRM network is relatively dense, and this greatly facilitated the ab ility to the analyses presented in this report. Semicontinuous PM mass and composition measurem ents certainly provide considerable insight and in the future their deployment should be ve ry beneficial in refining our knowledge of high concentration events. A significant body of work has been assembled to characterize PM in Sout heast Michigan with most-recent emphasis on the annual average PM 2.5 

### NAAQS. Indeed, efforts currently underway to address the annual average sta ndard are expected to improve th e 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 stan dard. Thus, the key findings from this analysis are compared and contrasted with the Wei ght-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 charac terizing 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 thei r contributions amplified by poor atmospheric ventilation conditions such as a persistent sta gnation? 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 th at in some cases were captured by the images from an on-site camera and in other cases were visually observe d by site operators. The ability to identify exceptional events in the East St. Louis time se ries 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 – whethe r visibility or mass concentration – is closer in spirit to the information needed for examining dr ivers 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 actua l day if there are a vari ety of drivers for high

### PM 2.5 

### 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 particul arly challenging and the data analysis approaches adopted for this study have been customized to eluc idate the contributions from these scales to the extent practicable. In consid eration of the above i ssues, it is apparent that analyses to capture the drivers for high concentration days must focus on distributions of behavior rather than average (cen tral tendency) behavior. The data analysis methods reflect this consideration. There are many possible drivers for intraurban variability in PM 2.5 

### mass, including the following six factors: local sources of primary PM emissions; transi ent 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-vol atile components; and measurement error (Pinto et al. 2004; Turner and Allen, 2008). While this analysis does not definitively identify which of these factors ar e 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 aris ing from PM emission sources acting on various spatial scales. The air mass is transecting the domain wi th persistent surface winds from the left. Panel (a) shows the emission sources where the region al-scale contributions are assumed to be homogeneous across the dom ain (this assumption ne glects interactions between regionally transported material and urban area emissions, such as urban plume processing of regionally-transpor ted PM precursor gases). Urba n-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 emi ssions create local hot spots which disperse downwind and become part of the urban-scale cont ributions. The red line in panel (b) shows the concentration profile that would be observed alon g the transect. Monitor locations will dictate which features of the profile are captured. For example, panel (c) show s 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 (f rom an urban-scale emissions perspe ctive). For this scenario it is not impacted by local plumes but measures th e 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 em issions 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 th e extent that the urban PM mass contributions cannot be distinguished from the underlying re gional contributions. A wind reversal would render monitors D and E upwind of the urban area. This spat ial 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 ove r many days. It is also a 1-D representation of a 2-D surface which adds complexity. That sa id, it does motivate the use of surface winds as a discriminator for studying site-specific PM mass trends to place each m onitor in an emissions field context.

### PM 2.5 

### 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.

### PM 2.5 

### 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, includ ing but not limited to the regulatory metrics. Section 4 examines the drivers for high concentra tion days by taking advantage of the relatively dense compliance monitoring network and particle speciation data. Section 5 refines the understanding of local emission source contri butions by exploiting spatial and temporal variability within the network. Key findings, policy-relevant implications and recommendations for future work are summarized in Section 6.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 11 3. SOUTHEAST MICHIGAN PM 2.5 

### FRM NETWORK AND CONCENTRATION TRENDS The PM 2.5 

### FRM monitoring network used in th is analysis is summarized in Figures 3-1 and 3-2 and Table 3-1 . For the PM 2.5 

### compliance monitoring period of 1999-2006, there were fifteen PM 2.5 

### FRM monitoring sites in Southeast Michigan; three sites had collocated PM 2.5 

### FRM samplers. All FRM monitoring sites in the Detroi t-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 cal led the Detroit population core and the spatial zone which includes the Detroit central business dist rict 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 tigh tly 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 loca ted in Wayne County plus the Oak Park monitor site which is just acro ss the county line in Oakland County. Daily measurements have been maintained at A llen Park through the ei ght 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 da ta density driven by the daily sampling at Allen Park. There were 14,044 sampling events (neglecti ng collocated measurements). The historical compliance status of each site with respect to the 24-hour PM 2.5 

### 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 va lid data. There were 546 total exceedances which correspond to 3.9% of all sampling events. This report reflects on the condi tions and drivers for high PM 2.5 

### mass concentration days (hereafter called “high PM days”). We are interested in both the frequency and intensity (magnitude) of high concentration days since bo th factors are important in establishing the design value. Figure 3-3 shows the site-specific frequencie s of high concentration days using thresholds of 25, 30, and 35 μ g/m 3 

### . Exceedances were observed on 2- 8% of sample days with 5-14%, and 8-24% of sample days having concentrations above 30 μ g/m 3 

### and 25 μ g/m 3 

### , respectively. Dearborn exhibits the highest fr equency 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/Lafaye tte and Newberry sites might be impacted by the relatively short sampling hist ories at these sites and caution s hould be used in comparing and contrasting these sites to the re st of the network. Ann Arbor a nd 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 w ith Luna Pier ~70 km to the southwest and Port Huron ~80 km to the northeast. Figure 3-4 shows the frequency of PM 2.5 

### high concentration days by month for Allen Park, Dearborn, Southwest High School and New Haven (fre quency 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

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### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 12 Figure 3-1. Southeast Michigan PM 2.5 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 PM 2.5 FRM monitoring sites (excluding Luna Pier and Port Huron) superposed on 2000 census tract level population density data. 

### Wayne County

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 13 Table 3-1. Southeast Michigan PM 2.5 monitoring network as of December 2006, including exceedances days for the NAAQS daily PM 2.5 standard of 35 μ g/m 3 . (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 concentr ation days are relatively infrequent in the spring. Dearborn exhibits higher fr equencies 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 Dear born, while New Haven has relatively few high concentration days but with the same overall patt ern as Allen Park – highest frequencies in the summer followed by the winter. Table 3-2. Southeast Michigan PM 2.5 monitoring network compliance status for the daily PM 2.5 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

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### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 14Allen ParkAnn ArborDearbornE 7 MileFIA/LafayetteLinwoodLivoniaLuna PierNew HavenNewberryOak ParkPort HuronSW High Sch.WyandotteYpsilantipercentage of total sampling days above threhold concentration

0 5 10 15 20 25 30 > 35 ug/m 3 > 30 ug/m 3 > 25 ug/m 3 

### 1999-2006

(a)Allen ParkAnn ArborDearbornE 7 MileFIA/LafayetteLinwoodLivoniaLuna PierNew HavenNewberryOak ParkPort HuronSW High Sch.WyandotteYpsilantipercentage of total sampling days above threhold concentration

0 5 10 15 20 25 30 > 35 ug/m 3 > 30 ug/m 3 > 25 ug/m 3 

### 2004-2006

(b) Figure 3-3. Site-specific frequency of total sampli ng days above the designated concentration for periods: 1999-2006 (a); and 2004-2006 (b),

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 15 Allen Parkfraction of days greater than threshold

0.00 0.05 0.10 0.15 0.20 > 35 ug/m 3 > 30 ug/m 3

Dearbornfraction 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 12fraction of days greater than threshold

0.00 0.05 0.10 0.15 0.20

Figure 3-4. Distribution of PM 2.5 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.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 16 Surface winds dictate the coupling between local em ission 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 relative ly 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 southwesterl y component while sp ring and summer months have lighter winds and less distinct prevailing features. Seasonal variations in su rface 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 w ith the increased frequency of surface winds from the southwest during the winter a nd the location of nearby emission sources in this direction (and indeed located between Dear born 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% Spring Summer Fall Winter

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)

### PM 2.5 

### 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 con centration day at a given site can arise from regional contributions, local contri butions, or a combination of thes e factors. The climatology of network-wide high PM days was examined to unde rstand the drivers for such days. Regionally transported materials might be higher or atmospheri c ventilation might be poor er. The extent to which these drivers act synergistically is not cl ear. 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 larg e 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 frequenc y 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 PM 2.5 

### FRM mass concentration value 2 

### ; these days are called valid network days . Subsequently, the valid netw ork days were screened to in clude only those days with at least 2/3 of the reporting monito rs having a PM concentration gr eater than a threshold value (e.g., 30 μ g/m 3 

### ); 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 sa mpling days with ten-or-mor e FRM monitor sites reporting valid PM 2.5 

### concentrations (valid network days). 41 of these days (5.6%) had at least 2/3 of the monitors above 30 μ g/m 3 

### (network-wide high PM days) and a ll 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 netw ork-wide high PM threshold; th ese days likely have stronger influences from nearby emission sources im pacting one or at most two sites. Figure 4-1 shows the distribution of network-wide high PM days by month. The da ys 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.

### PM 2.5 

### 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 monitorsabove stated concentration

0 2 4 6 8 10 12 14 16 > 35 ug/m 3 > 30 ug/m 3 > 25 ug/m 3

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 μ g/m 3 . 

### The relevance of this analysis to understandi ng drivers for exceedances of the 24-hour standard is demonstrated in Table 4-2 . Valid network days, as defi ned above, capture 27-92% of all sampling days (column D). The capture is rela tively 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 pe rcentage capture of all sampling days by valid network days (column D) and we conclude that the subset of sampling da ys captured by valid network days is representa tive of all sampling days . Having established the representativeness of valid network days, we observed that at most sites exceedances o ccur predominantly – and in some cases exclusively – on days when th e entire network is exhibiting high PM (column F). For example, 96% of the exceedances at Allen Park on valid netw ork days occurred on days when the entire network was exhibiting high PM. Assu ming 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 enti re network was exhibiting high PM. Assuming the valid network days are representati ve of all sampling days at Yps ilanti, 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 exhi biting 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 th e 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 exce edances where captured by valid network da ys (89%) and the assertion that the valid network days are representative of all sampling days is not even necessary.

### PM 2.5 

### 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 DayExceedances 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 cons truct of network-wide high PM da ys is less robust for these sites since they might not always be bathed in th e same regional air mass as the core region. The threshold concentration used to define a ne twork-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 5 th 

### 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 5 th 

### lowest concentration is no higher than the median concentration and ensu res the base concentration is not significantly influenced by th e monitors at the geographic exte nts (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 concentrat ion includes regionally transported PM and some portion of the urban-sc ale contributions. Excess mass at a given site, relative to the base concen tration, 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 netw ork 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 μ g/m 3 

### 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 concen tration. This behavior holds at both high and

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 20 base concentration, ug/m 3 0 10 20 30 40 50 60 70 80maximum concentration, ug/m3

0 10 20 30 40 50 60 70 80 

### (a)

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80second 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 networ k-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 μ g/m 3 above the base concentration. 

### low base concentrations; the extreme maximum va lues possibly arise from nitrate hot spots or measurement artifacts as will be desc ribed 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 exceedan ces days with concentrations in large excess of the base concentration. Assuming poor atmos pheric ventilation affects the sites similarly and thus contributes to the base c oncentration, 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 concen tration. Dearborn and Wyandotte had exceedances on days with base concentrations as low as 20 μ g/m 3 

### demonstrating significant excess above the base concentration. The analysis so far has primarily focused on th e 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 5 th 

### 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 5 th 

### highest maximum (yellow bars), although this metric is sensitive to sampling frequency. Most sites have median excess below 5 μ g/m 3 

### . 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 tw o days were the highest nitrat e at Allen Park over all valid network days (no speciation data for 3/1/2003). Further inspection of network-wide behavior on

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 21 base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Allen Park

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Dearborn

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 East 7 Mile

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Linwood

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Livonia

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Luna Pier

Figure 4-3. Site-specific concentrations versus base concen trations for valid network days. Solid line is the base concentration (1:1 lin e) and dashed line is 35 μ g/m 3 .

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 22 base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 New Haven

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Oak Park

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Port Huron

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 SW High Sch.

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Wyandotte

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Ypsilanti

Figure 4-3 (continued). Site-specific concentrations versus b ase concentrations for valid network days. Solid line is the base concentration (1:1 line) and dashed line is 35 μ g/m 3 .

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 23 0 5 10 15 20

All

e n Park Dearborn E 7 Mil

e Linw o od L ivo

n ia L una

P

i er New Haven Oak Park Port H u r on

SW

High S ch . Wyando t te Ypsil a ntisite conc. in excess of network-wide base conc., ug/m3 5th max 50th percentile

Figure 4-4. Site-specific exceedance days: 5 th -highest excess concentration compared to base concentration (yellow); and 50 th -precentile excess concentration compared to base concentration (green). 

### high nitrate days shows the spat ial 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 leas t two possible explanations for this behavior. First, there might be nitrate hot spots on high nitr ate days. These hot spots are most likely to occur on days with a liquid aerosol due to hi gh humidity. A qualitative inspection of surface weather on high nitrate days sugge sts 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 in fluence nitrate uptake. Spatial variations in crustal material could also influence the pH of th e liquid aerosol which in turn in fluences nitrate uptake. Second, there might be varying nitrate measurement artif act 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 va riability in both nitrate in FRM mass. A better understanding of the drivers fo r high spatial variability in FRM mass on high nitrate days is needed since only a few such ev ents can dramatically affect the site-specific design values for the 24-hour standard. When su ch patterns are observed, perhaps the Teflon filters could be analyzed for nitrate by IC to dete rmine 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-y ear period for the data set used in this study). Focusing on those days w ith base concen tration below 35 μ g/m 3 

### (to the left of the vertical solid line) but with site-specific concentrations a pproaching or greater than 35 μ g/m 3

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 24 base concentration, ug/m 3 0 10 20 30 40 50 60 70 8 0site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Dearborn 

### (a)

base concentration, ug/m 3 0 10 20 30 40 50 60 70 80site-specific concentration, ug/m3

0 10 20 30 40 50 60 70 80 Wyandotte 

### (b)

Figure 4-5. Site-specific concentrations versus base con centrations 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 μ g/m 3 . 

### (above the dashed horizontal line), these days correspond to cases where nearby local emission sources are likely significant contributors to an exceedance (or near exce edance) that otherwise would not occur. For Dearborn (F igure 4-4a), there has been a d ecrease 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 sour ce plumes driving an exceedance (or near exceedance) of the st andard were prior to 2004. For the most recent data (2004-2006), Wyandotte does not appear to be disproportionate ly influenced by local plumes on exceedance (or near exceedance) days . Again, these figures do not represen t all sample days but rather the subset of days with ten-or-more reporting monito rs such that network-wi de behavior could be characterized; however, as previously demonstrat ed, 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 ex hibiting 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 signif icant excess superposed on the base concentration leading to exceedances when th e base concentration is as low as 20 μ g/m 3 

### . It would be helpful to determine whethe r the day-to-day variability in the base concentration is driven by re gional transport, poor atmospheri c 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 examin ing the PM speciation data and surface winds

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 25 FRM mass concentration, ug/m 3 0 10 20 30 40 50 60 7 0total ion concentration, ug/m3

0 10 20 30 40 50 60 70 December - April May - November

Figure 4-6. Total major ion concentration (sulfate, n itrate 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 μ g/m 3 

### and thus the major ions alone were sufficient to cause the exceedance. 5 

### Over all 21 exceedance days the major ion contribution wa s 56-112% of the standard (median 84%) and 53-85% of the FRM PM 2.5 

### 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 avai lable for 31 of the 41 days. Figure 4-7 is a scattergram for sulfate and nitrate on these days with all sulfate a ssumed to be ammonium sulfate and all nitrate assumed to be ammonium nitrate. Summertim e events typically exhibit high sulfate and relatively low nitrate. Wintertime events exhib it 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 da ys conducive to regional transport but sulfate and nitrate will be used as a surrogate for regional transport in this work since the sulfat e 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.

### PM 2.5 

### 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, μ g/m 3nitrate as ammonium nitrate ,μg/m3 May-November December-A p ril 1:1 2:1

1:2

Figure 4-7. Ammonium nitrate and ammonium sulfate c oncentrations at Allen Park on network-wide high PM days. 

### 31 days have a combined ammonium sulfate plus ammonium nitrate concentration exceeding 25 μ g/m 3 

### although, as previously mentioned, the contribu tion 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 regiona l transport but the precise split between regional and local sources remains unknown. Assuming the su lfate and nitrate are regionally transported, the total contribution from regiona l 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 cont ributions on an average basis, no less a day-to-day basis. A multivaria ble linear regression was performed to explain the observed organic carbon (OC) in terms of obs erved sulfate and elemental carbon (EC). The unconstrained regression yielded (R 2 

### = 0.50, all units in μ g/m 3 

### ); EC SO OC ) 26 . 0 49 . 2 ( ) 029 . 0 176 . 0 ( ) 22 . 0 53 . 1 ( 4 

### ± + ± + ± = 

### where the 95% confidence interval for each regr ession parameter is reported. There are many caveats to this very simple appr oach to apportioning the OC. Fo r example OC associated with sulfate would likely vary by season due to diffe rences in secondary formation rates. The approach is merely intended as a crude way to assign OC to a component that associates with

### PM 2.5 

### 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. Assu ming an OM/OC ratio of 1.8, the scaling factor for organic matter associated with sulfate would be 0.32 × SO 4 

### . Figure 4-8 shows the contribution of major ions measured at Allen Pa rk to the base concentration on valid network days (Figure 4-8a) and the contri bution of the major ions plus this crude estimate of the OM associated with sulfate (Figure 4-8b). The incl usion 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 incr ease in urban- and finer-scale contributions (for example, due to poorer atmo spheric 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 bas e concentrations above ~ 20 μ g/m 3 

### ; it is above this value that major ions – and thus presumably regional tran sport – disproportionately influences the observed PM 2.5 

### mass concentrations . Concentration enhancements in surrogates for regional transport (sul fate and nitrate as surrogates) and urban-scale local emissions (EC as surrogate) were examined for the network-wide high PM days. For each valid netw ork 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 netw ork days and over all years. Su lfate was on average 4.5 times higher and nitrate was on average 2.8 ti mes 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 concentr ation 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-f ield 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 tr ansported material and urban-scale emissions, consistent with OC contributions from a combin ation 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, la rgely captures the network-wide PM base concentration), a temporally-isolated excursion (h igh PM also observed at Allen Park on that day but not the preceding or following day), or a mu ltiday 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 ev ent that straddles midnight, while three-or-more more successive high PM days cl early indicate an episode with temporal persistence, whether caused by regi onal transport or sustained areaw ide 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.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 28 High PM conditions were defined as >30 μ g/m 3 

### for the interroga ted site and >25 μ g/m 3 

### for the reference site (Allen Park). Figure 4-9 shows the site-specific dist ributions. Dearborn has the highest frequency of spatially- a nd 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 th e network-wide base concentration is as low as 20 μ g/m 3 

### . Relatively high frequencies of spatially- and temporally-isolated high PM days were also observed at Wyandotte, Southwest High Scho ol, and East 7 Mile. At all sites except Dearborn, high PM days most frequently co rrespond 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 pr imarily 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 contributi ons to FRM mass will be even lower after accounting from ammonium nitrate vola tilization from th e 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 ofte n observed when the area is experiencing a multiday high PM episode.

### PM 2.5 

### 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/m 3total ion concentration, ug/m3 all valid network days network-wide hi g h PM da y 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/m 3total ion concentration plus associated OM, ug/m3 all valid network days network-wide hi g h PM da y 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).

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 30DearbornEast 7 MileLinwoodLivoniaLuna PierNew HavenOak ParkPort HuronSouthwest HSWyandotteYpsilantifraction in stated category

0.0 0.2 0.4 0.6 0.8 1.0 AP < 25 ug/m 3 on same day AP > 25 ug/m 3 on same day only AP > 25 ug/m 3 on two consecutive days AP > 25 ug/m 3 on three-or-more consecutive days

Figure 4-9. Classification of high PM days (PM 2.5 > 30 μ g/m 3 ) at each site in Southeast Michigan by the time series behavior of daily PM 2.5 at Allen Park.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 31 5. RELATIONSHIPS BETWEEN SITE-SPEC IFIC EXCESS MASS AND SURFACE WINDS The previous section demonstrates that exceedances of the 24-hour PM 2.5 

### NAAQS at most sites in Southeast Michigan are primarily driven by an enhancement of regionally transported material which elevates the concentration baseline upon whic h 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 doe s not imply that urban-scale contributions are small, but rather they are not significantly modul ated on high PM days. At a few sites, plumes from nearby emission sources can substantially cont ribute to exceedances and near exceedances. This section presents relationships between th e 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 rath er excess mass over the entire concentration distribution. While in principl e there might be different loca l 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 ga ined from using the entire data set. Allen Park was initially chosen as a refere nce site for generating th e times series of excess mass. Figure 4-3 demonstrates that Allen Park is indeed highly co rrelated 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 lo w for winds from the northeast and sources in this direction might be damped or even missed. Th is 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 ex cess mass. This reduces the number of sample days used in the analyses but removes any issu es with directional bi as 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 th at hourly winds from Detroit Metropolitan Wayne County Airport will be representati ve for sites such as Luna Pier and Port Huron; however, the excess mass construct using Allen Park or the en tire 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 wi nds were probed using Conditional Probability Function (CPF) and 1-D Nonparametric Wind Regres sion (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 we re run with the entire data set (1999-2006) and the most recent three years (2004-2006) since gr eatest interest is in current conditions. The former includes substantially more data and is le ss 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, sensitivit y 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 μ g/m 3 

### . This threshold is based on two times the propagated collocated precision for the concentration difference usi ng a collocated precision of 0.7 μ g/m 3 

### for a single measurement. Since the excess mass concentration is a 24-hour in tegrated parameter but the surface winds data

### PM 2.5 

### 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 s ite using the top dec ile of the excess mass distribution as the threshold for a high con centration 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 wh en 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 im plicate 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 analys es in Section 4 implicated local sources as significant contributors to the exce ss mass at these sites given the favorable wind directions for advecting emissions from the sour ces 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 frequenc y 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 dire ction 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 co re zones. The CPF plot for Port Huron implicates sources at bearings east thr ough 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 consis tent with the local source impacts identified in Section 4 and consistent with known emission source regions. It appears th is analysis can pick up the urban plume advected from Detroit to site s that are outside the urban emissions zone. NWR plots show the expected ex cess concentration as a functi on of wind direction. Several analyses were performed using Allen Park data for the reference concentrations (see footnote #11). Subsequently, NWR plots were constructe d using the network-wide base concentration estimates for the reference concentrations and those results, which were generally consistent with the results that were ob tained using Allen Park as a refere nce, are presented here. Yearly box plots were generated for the excess PM 2.5 

### 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 analys es. Given the seasonal and year-to-year variabil ity in surface winds, the representa tiveness 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 ava ilable 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 qu artile 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.

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Washington University in St. Louis October 1, 2008 33 0
45

90

135
180 225 270 315 15 30

60 75

105 120

150 165 195 210 240 255 285 300 330 345

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

150 165 195 210 240 255 285 300 330 345

0 0.1 0.2 0.3 0.4 

### Dearborn

0
45

90

135
180 225 270 315 15 30

60 75

105 120

150 165 195 210 240 255 285 300 330 345

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

150 165 195 210 240 255 285 300 330 345

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

150 165 195 210 240 255 285 300 330 345

0 0.1 0.2 0.3 0.4 

### Linwood

0
45

90

135
180 225 270 315 15 30

60 75

105 120

150 165 195 210 240 255 285 300 330 345

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

150 165 195 210 240 255 285 300 330 345

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

150 165 195 210 240 255 285 300 330 345

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

150 165 195 210 240 255 285 300 330 345

0 0.1 0.2 0.3 0.4 

### Wyandotte
0
45

90

135
180 225 270 315 15 30

60 75

105 120

150 165 195 210 240 255 285 300 330 345

0 0.1 0.2 0.3 0.4 

### Ypsilanti
0
45

90

135
180 225 270 315 15 30

60 75

105 120

150 165 195 210 240 255 285 300 330 345

0 0.1 0.2 0.3 0.4 Figure 5-1. Conditional probability function plots for ex cess mass at each site relative to Allen Park, 1999-2006. Probabilities are for the top decile of the excess mass distribution.

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Washington University in St. Louis October 1, 2008 34 Data for 1999 were excluded from the concentra tion time series because the network was being phased in during that year; there were only 14 va lid 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 va lid 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 seasonall y biased towards the fi rst 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 netw ork-wide base concentration. Similar distributions were observed for the first four years (2000-2003) with subs tantial 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 af ter 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 fo r 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 dist ribution 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 Secti on 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 2007network-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 5 th and 95 th 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.

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### 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) 2004-20 06. Calms (wind speeds less than 2 mph) are listed to the lower-left of each wind rose. 

### Ann Arbor, FIA/Lafayette, Newberry were excl uded because sampling was not sustained over the 2000-2006 time period. Luna Pier and Port Hu ron were excluded because they are at the spatial extents of the geographic domain and bot h 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, respectivel y. NWR results as polar plots are presented with th e radial concentr ation units in μ g/m 3 

### ; the red line is the average contribution and the pink lines are the 95% c onfidence intervals. NW R results were also generated after first censoring th e data to remove extreme values and thereby stabilize the expected concentration estimates. 8 

### The bottom plot in each pa nel of Figure 5-4 shows the NWR results for censored data, and includes the diffe rence 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 high est average excess mass. Both the mean and median excess mass decreased beginning in 2005 desp ite an increase that year in the mean base concentration (Figure 5-2). The time series fo r 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 μ g/m 3 

### 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 μ g/m 3 

### for 2000-2003 and 2004-2006, respectively. The excess mass floor of ~2 μ g/m 3 

### might be real since the Detroit population core , perhaps a surrogate for mobile s ource 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: C UOF = C 75 + 3 × C IQR ; and C LOF = C 25 - 3 × C IQR where C i is concentration i , subscripts 25 and 75 denote 25 th and 75 th percentiles, and IQR is the interquartile range (C 75 - C 25 ). >2 - 4 >4 - 8 >8 - 16 >16 

### WS (mph)

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Washington University in St. Louis October 1, 2008 36 

# DEARBORN

2000 2001 2002 2003 2004 2005 2006 2007excess 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
7 0
240 210 180 150 120 0 2 4 6 8 10 9 60 30 0 330 300
7 0
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 N1-D NWR excess mass expected concentration,μg/m3 Dearborn, 2000-2003 Dearborn, 2004-2006 [2004-2006] minus [2000-2003]

Figure 5-4. Excess PM 2.5 mass compared to the network-wide base concentration. Top: box plots of annual excess mass concentration distributions. Open circles are 5 th and 95 th percentile values; the red and black lines are mean and median values (solid with in 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 (l eft) and 2004-2006 (right). Average concentrations and 95% confidence intervals are red and pink lines, respectively, and radial units are μ g/m 3 . Bottom: 1-D NWR expected excess mass concentrations after censoring the data to remove extreme values.

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Washington University in St. Louis October 1, 2008 37 

# WYANDOTTE

2000-2003 2004-2006 2000 2001 2002 2003 2004 2005 2006 2007excess 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
7 0
240 210 180 150 120 012345 9 60 30 0 330 300
7 0
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 N1-D NWR excess mass expected concentration,μg/m3 Wyandotte, 2000-2003 Wyandotte, 2004-2006 [2004-2006] minus [2000-2003]

Figure 5-5. Excess PM 2.5 mass compared to the network-wide base concentration. Top: box plots of annual excess mass concentration distributions. Open circles are 5 th and 95 th percentile values; the red and black lines are mean and median values (solid with in 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 (l eft) and 2004-2006 (right). Average concentrations and 95% confidence intervals are red and pink lines, respectively, and radial units are μ g/m 3 . Bottom: 1-D NWR expected excess mass concentrations after censoring the data to remove extreme values.

### PM 2.5 

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Washington University in St. Louis October 1, 2008 38 

# SOUTHWEST HIGH SCHOOL

2000-2003 2004-2006 2000 2001 2002 2003 2004 2005 2006 2007excess 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
7 0
240 210 180 150 120 012345 9 60 30 0 330 300
7 0
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 N1-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 PM 2.5 mass compared to the network-wide base concentration. Top: box plots of annual excess mass concentration distributions. Open circles are 5 th and 95 th percentile values; the red and black lines are mean and median values (solid with in 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 (l eft) and 2004-2006 (right). Average concentrations and 95% confidence intervals are red and pink lines, respectively, and radial units are μ g/m 3 . Bottom: 1-D NWR expected excess mass concentrations after censoring the data to remove extreme values.

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Washington University in St. Louis October 1, 2008 39 

# LINWOOD

2000-2003 2004-2006 2000 2001 2002 2003 2004 2005 2006 2007excess 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
7 0
240 210 180 150 120 0.0 0.5 1.0 1.5 2.0 2.5 9 60 30 0 330 300
7 0
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 N1-D NWR excess mass expected concentration,μg/m3 Linwood, 2000-2003 Linwood, 2004-2006 [2004-2006] minus [2000-2003]

Figure 5-7 Excess PM 2.5 mass compared to the network-wide base concentration. Top: box plots of annual excess mass concentration distributions. Open circles are 5 th and 95 th percentile values; the red and black lines are mean and median values (solid with in 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 (l eft) and 2004-2006 (right). Average concentrations and 95% confidence intervals are red and pink lines, respectively, and radial units are μ g/m 3 . Bottom: 1-D NWR expected excess mass concentrations after censoring the data to remove extreme values.

### PM 2.5 

### 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 Detr oit commercial/industrial co re. It is possible, however, that the excess mass floor reflects cont amination in the NWR analysis from using daily-integrated FRM mass together with hourly winds which mi ght 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 exhi bit lower excess mass concentrations compared to 2000-2003, consistent with Figure 4-5, with maximum reductions of ~2 μ g/m 3 

### 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 si gnificantly influenced by local emission sources to the sout hwest of the site. This is also the direction of the prevailing wind and thus emission controls on these sour ces would have a dramatic impact on observed concentrations at the Dearborn site. There is also a significant ur ban scale contribution regardless of wind direction with exp ected concentration greater than 2 μ g/m 3 

### (the excess mass floor is 2 μ g/m 3 

### plus there are urban-scale contributions to the base concen tration) although the relative contributions of mobile, area, and dispersed point source emissions is not clear. Wyandotte and Southwest High School have sim ilar mean and median excess mass, second after Dearborn. Let us first consider Wyandotte. Th e top plot in Figure 5- 5 shows a dramatic and steady reduction in mean and median exce ss mass starting in 2004. Expected mass concentrations were lowest for wind dire ctions from the east/southeast (indeed, ~0 μ g/m 3 

### for 2004-2006) which is consistent with the orientation of the site re lative to local sources and the Detroit population and commercial / industrial cores. There are two sectors with high expected excess mass concentrations. One sector is broadl y to the north/northwest with expected excess mass concentrations ~2 μ g/m 3 

### for 2000-2003 and with ~50% decrease for 2004-2006. This bearing is consistent with the location of the Detroit population a nd commercial / industrial cores which are north of Wyandotte. The other sector is to the southwest with a maximum excess mass concentration of nearly 4 μ g/m 3 

### for 2000-2003 and with ~50% decrease for 2004-2006. Given both the alignment of this sector with th e prevailing wind direction and the magnitude of the expected concentrations, the emission redu ctions 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 larg e quarry. Like Dearbor n, the NWR results are relatively insensitive to the censoring of extr eme values (Figure E-1). In summary, the wind direction dependence of expected excess mass concentration at Wy andotte is consistent with known emission sources / source regi ons. 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 sect ors. The reductions from the southwest are more significant to both annual averag e concentrations and high PM days. Annual mean and median excess mass concentrati ons at Southwest High School also decreased starting in 2005 (Figure 5-6). NWR polar plots suggest the exce ss mass decrease was driven by emission reductions to the south/southwest. Ho wever, NWR results for all data and censored data (Figure E-1) demonstrate that a few extrem e 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 essent ially 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 μ g/m 3 

### for

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 41 2000-2003 and was modestly lower for 2004-2006. Th is 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 concen trations are from bearing of ~190 ° N and with extreme events realized primarily in the period 2000-2003. Based on Figur e 4-3 these events typically occurred on relatively clean da ys (base concentrations 10-20 μ g/m 3 

### ) 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 re lative 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 distribu tion 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 yi elds very consistent concentrations profiles for the two time periods (Figure 5-7, bottom plot). The excess mass concentration floor is ~0.5 μ g/m 3 

### with perhaps modestly lower values fo r 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 th at 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 μ g/m 3 

### , consistent with the floors at Dearborn and Southwest High School. For other wind direc tions, the expected concen trations are lower. The above detailed analysis of four sites – Dearborn ,Wyandotte, Southwest High School, and Linwood – contributes to our unders tanding of local and urban-scal e 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 wi th the prevailing winds. Dearborn and Southwest High School have expected excess mass concentrations of a least 1.5-2 μ g/m 3 

### from all wind directions, while the minimum expected mass concentrations are lo wer at Wyandotte and Linwood. Thus, Dearborn and Southwest High School appear to be within the high emissions zone with contributions from multiple point sour ces 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 ma ss concentrations at Wyandotte and Linwood for winds from the north and south/southwest, re spectively. 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 examin ing 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 da ta (note the concentr ation 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) con centration profiles are nearly mirror images spanning the range 0.25-2 μ g/m 3 

### 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

### PM 2.5 

### 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 N1-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 N1-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 PM 2.5 mass compared to the network-wide base concentration, 2004-2006 data cen sored to remove extreme values as described in footnote #12. 

### hot spot, left figure) and the indus trialized zone to its southeast. This s uggests there is an emissions plume emanating from Dearborn and industr ial areas to its southeast, extending to the Detroit River, which impact Allen Park a nd 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 eviden t at East 7 Mile and is barely di scernible from the baseline at New Haven. In addition to this plume from the Detroi t commercial/industrial core, there appears to be a broader urban scale emissions profile as evidenced by the decreasing excess mass concentration floors with increa sing distance from the Detroit popul ation core. Expected excess mass concentrations for bearings outside the commercial / in dustrial core plume are ~ 0.5 μ g/m 3 

### at Allen Park and Linwood, ~0 μ g/m 3 

### at East 7 Mile, and about -1 μ g/m 3 

### at New Haven. Recall that the base concentration includes regional and some urba n-scale contributions and the negative excess concentrations at New Ha ven suggest a maximum of at least 1.5 μ g/m 3 

### (based on -1 μ g/m 3 

### at New Haven and +0.5 μ g/m 3 

### 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 concentra tion are relatively rare at these sites. There are occasional extreme excess values which are bo th positive and negative with respect to the base concentration, so the exce ss mass distributions were stab ilized by censoring to remove extreme values. 12 

### NWR results for all these sites usi ng both all data and censored data are presented in Figure E-1. For each site, all expect ed concentrations were scaled so the lowest expected concentration as a f unction 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 po pulation density data. The plots are ordered clockwise about Detroit area star ting with Ypsilanti and ending with Allen Park. The following features are observed.

### PM 2.5 

### 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 (g reen 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.

### PM 2.5 

### 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 μ g/m 3 

### . Bearings of highest excess mass concentra tion 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 μ g/m 3 

### . Bearings of highest excess mass concentration corres pond to an urban plume emanating from the Detroit population and commercial/industrial co res with potentially larger impacts from the latter core. • Oak Park. The expected excess mass concentration ranged from -0.5 to +1 μ g/m 3 

### . The higher floor is consistent w ith this site being closer to the Detroit population and commercial/industrial cores than Ypsilanti and Livonia. Bear ings of highest excess mass concentration range from due east to due s outh, consistent with the Detroit population and commercial/industrial cores. • East 7 Mile. The expected excess mass concentration ranged from 0 to +1 μ g/m 3 

### . Highest concentration bearings are to southwest with elevat ed expected concentrations also to the west, consistent with the Detroi t commercial/industrial and population cores, respectively. • New Haven. The expected excess mass concentr ation is nearly constant at -1 μ g/m 3 

### . A bearing of modestly elevated expected exce ss mass concentrations is to the southwest, aligned with the Detroit commercia l/industrial and population core. • Allen Park. The expected excess mass concentration ranged from 0.5 to +2 μ g/m 3 

### . High concentration bearings are to the north through east of th e site, consistent with the Detroit population and comm ercial/industrial cores. These six sites completely surround the Detroit population and commercial / industrial cores and in each case demonstrate highest expected exces s 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 in terpretation from the results across all sites. Ypsilanti, Livonia and New Haven all have expected ex cess mass concentrations of about - 1 μ g/m 3 

### when the sites are upwind of the Detroit population and co mmercial/industrial cores. Thus a reasonable estimate for the average urban- scale contribution to the average network-wide base is about 1 μ g/m 3 

### . The 2004-2006 average ba se concentration of 13.5 μ g/m 3 

### could be apportioned as 12.5 μ g/m 3 

### from regional sources and a 1 μ g/m 3 

### portion of the urban-scale contributions. Urban-scale emission s contribute, on average, up to 3 μ g/m 3 

### depending on location within the Greater Wayne County area a nd the specified wind pattern. They appear to be greatest in the Detroit comme rcial/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 ur ban-scale contributions. Large local emission sources can exert significant influence on near-fie ld monitors as demonstrated for Dearborn and Wyandotte. In summary, analyses of PM 2.5 

### mass concentrations – separated in to network-wide base and site-specific excess mass components – together with surface winds provi de the following model for PM 2.5 

### mass concentrations over Southeast Mich igan (excluding the di stant sites of Ann Arbor, Luna Pier, and Port Huron):

### PM 2.5 

### 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 concentra tion arise near large emission sources and, in the cases of Dearborn and Wyandotte, can drive exceedance s (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 w ith the prevailing winds from the southwest exacerbating the frequency of high impact days . Expected concentration contributions from these zones have decrease d in recent years, presumably due to emission reductions. • An idealized conceptual model for PM behavi or, that explains, bot h daily and annual PM mass trends, consists of four layers: (1) regionally transported PM with average concentration of about 12.5 μ g/m 3 

### over the 2004-2006 period; (2) urban-scale emissions from mobile, area, and point sources that contribute up to 3 μ g/m 3 

### 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 possi ble New Haven; and (4) localized hot spots for cases when certain monitoring sites are di rectly impacted by emission plumes from nearby sources with high potentially imp acts on a given day and less impact when averaged of the distribution of wind di rections impacting such sites.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 46 6. SUMMARY, POLICY-RELEVANT IMPL ICATIONS, AND RECOMMENDATIONS Summary At most sites in Southeast Michigan, exceedan ces occur predominantly – and in some cases exclusively – on days when the en tire 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-wi de high PM are regional transpor t, 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 exceedance s and 27% of the Wyandotte exceedances occurring on such days. On these days, thes e sites are significantly influenced by nearby emission sources. Dearborn continues to be in fluenced by nearby emission sources which drive exceedances (or near exceedances) on days when the network-wide base concentration is as much as 15 μ g/m 3 

### below the standard, although the freque ncy 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 th e standard were prior to 2004. At those sites not significantly impact ed 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 Count y area. Sites such as Allen Park, which are relatively free of impacts from nearby sources, e xhibit similar seasonal behavior with high PM days most frequent in the summer followed by th e winter. The monthly distribution of high PM days is distorted for sites with significant nearby emission sources si nce there is a strong seasonality to the surface winds distributions. For example, D earborn has as many high PM days in the winter as in the summer, with the wi nter season having a str onger contribution from nearby sources located to the southwest of the site. Network-wide high PM days have disproportionately high contri butions from the major ions (sulfate, nitrate, and ammonium) compared to ot her 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 concen tration. The role of sulfate on such days should not be overlooked when considering the impact of SO 2 

### -based regional control strategies. In general, network-wide PM base concentrations above ~20 μ g/m 3 

### tend to be disproportionately influenced by major ion contributions and are indicative of a disproportio nately high influence from regional sources. On network-wide high PM days the sulfate and ni trate concentrations are typically several times higher than the corresponding monthly median con centrations. In contrast, EC is on average only 1.3 times higher. This pattern suggests th at 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 atmo spheric 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.

### PM 2.5 

### 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 concentra tion 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 em ission source plumes on high PM days. A conceptual model for fine PM over central Sout heast Michigan includes four elements. The largest contributor to annual average PM is regi onally transported material that is temporally varying but spatially homogeneous over the domain (indeed, this defi nes the spatial extent of the domain for the conceptual model which in this cas e excludes the distant sites such as Luna Pier and Port Huron). On some days, regionally tr ansported PM contributi ons can be sufficiently high to cause exceedances of the daily standard when coupled with average contributions from urban- and finer-scale emission s ources and, in relatively rare cases, the regionally transported PM alone can cause exceedances of the daily st andard. Urban-scale emission sources (mobile, area, and point sources) create a spatial PM gr adient across central S outheast Michigan. For winds from a fixed direction, th ese contributions create an “urban plume” with decreasing impacts with increasing distance from the zone of highest emissions activity. The spatial gradients can be clearly discer ned when binning data from days with common wind patterns and become smeared, to some extent, when averagin g 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 south east 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 pl umes have essentially merged into a single urban plume. Average impacts from these pl umes depend on the monitoring site location relative to the Detroit population and commercial/industrial co re zones and the frequency that winds from these zones transport the plumes to th e monitoring site. Finally, certain monitors in the Detroit commercial/industrial zone are si gnificantly impacted by emissions from nearby sources that ultimately contribute to the dist ant PM plume emanating from this zone. At Dearborn and Wyandotte these sources are loca ted southwest of the monitoring sites and historically have contributed to exceedances (or nears exceedances ) of the daily standard. These sources also disproportionately influence the annu al standard because th ey are oriented upwind of the sites for prevailing winds from the southwest. In summary, emission controls th at reduce regionally transporte d PM are needed to reduce the frequency of violations of the 24-hour PM 2.5 

### standard. Emission reductio ns from a few specific point sources, especially near Dearborn, are also needed. While regional and point source controls will decrease annual average PM 2.5 

### concentrations for standardized synoptic weather patterns, relatively small but significant decreases could also be realized by controls on other urban emission sources such as mob ile, area, and other point sources.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 48 Policy-Relevant Implications The policy-relevant implications are fram ed using the Weight-of-Evidence (WOE) 9 

### prepared in support of the control strategy p ackage for the attaining the PM 2.5 

### annual average standard. The WOE elements are in regular t ypeface with comments, based on this work, added in italics. I. Inventory • I(c)... National stationary source controls, including CAIR and the NO x SIP call, are expected to reduce point source NO x emissions by 40% and SO 2 emissions by 15% between 2002 and 2009. These reductions are very important to the daily st andard control strategy because exceedances of the daily standard tend to occur on days with netw ork-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 S outheast 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 exceedan ces are coupled to the frequency and severity of regional transport episodes which can vary from year to year. For exa mple, 2005 was severe in terms of regional transport and this is reflected in the elevated 98 th percentile concentrations across all sites in Southeast Michigan. • I(d)... While these [programmed] reductions are al ready 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 vici nity of these sites are needed. Dearborn is currently the design value site for the dai ly 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 yea rs as evidenced by expected c oncentration 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 th ese 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 to wards the bearings where efforts should be focused to refine emission estimates – in particular, zones so uthwest 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 PM 2.5 levels observed at industrial monitoring sites. While we have indeed iden tified decreased local emission source contributions at some sites. • I(g)... In addition to changes that have already taken place, significant local PM 2.5 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.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 49 monitors measuring the highest PM 2.5 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 PM 2.5 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, thereb y 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 lo cated at bearings where prevailing winds can favor plume impacts at the monitoring sites, especial ly in the wintertime. Impacts can be tracked by periodically updating the NWR plots and the evaluatin g shifts in the distribution of site-specific high PM days by month. For example, if local source im pacts 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 A llen Park and Dearborn should also decrease for the relevant species in the CSN data. • I(h)... There are a significant number of storage pil es, 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 imp act 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)...PM 2.5 in Southeast Michigan is comprised largely of sulfates, nitrates, and organic carbon. At the Dearborn monitoring site, there is also a signifi cant “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 im pacts 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 cer tain days or during certain times of the year but not during others. However, recent source apportionmen t studies show that the source contributions to PM 2.5 on an annual average basis are similar to those on high PM 2.5 concentration days. This suggests that a strategy designed to reduce annual average PM 2.5 concentrations will also be effective in reducing high daily PM 2.5 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. SO 2 reductions might not be fully realized as PM reduc tions 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 A nn 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 we ather patterns which in tu rn include the frequency and severity of regional transport events. • II(f)... Since 2000, PM 2.5 concentrations at all sites in the region have steadily declined. The 3-year average concentration dropped 1.6 μ g/m 3 between 2002 and 2006.. The largest decreases have occurred at the sites with the highest concentrations: Dearborn (2.69 μ g/m 3 ), SWHS (2.16 μ g/m 3 ), and Wyandotte (3.04 μ g/m 3 ). Dramatic year-to-year swings in the 98 th 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)... PM 2.5 concentrations at monitoring sites in th e 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

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 50 sources at Dearborn and especially Wyandotte have i ndeed 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 designa ted nonattainment, monitoring data showed the Luna Pier monitor in Monroe County was violating th e 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 PM 2.5 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 co ncentration – 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 me asure attainment by the end of 2004. This was an accurate prediction. Levels at the site have c ontinued to track those in Toledo and monitors in both areas have measured attainment of the st andard 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 violatin g 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 PM 10 problem was determined to be a few local industrial sources. Emissions from th ese sources were reduced and the region came into compliance in 1996. The overlap of the Total Suspended Particulate (TSP) and PM 10 nonattainment areas with the PM2.5 nonattainment area, and the su ccessful 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 emi ssions near Dearborn have decreased the frequency of high PM days resulting fr om 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 ne ar 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 PM 2.5 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 PM 2.5 

### at Dearborn points directly to the southwest. Conversely, the iron wind rose for Allen Pa rk, 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, wh en winds are from the southwest average crustal concentrations at Dearborn are over 2.5 μg/m 3 higher than those at Allen Park and are sometimes as much as 6 μg/m 3 higher. This clearly indicates a significant local iron source directly between these

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 51 two sites (which are approximately five miles ap art) 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 frequen cy of wintertime high PM days at Dearborn compared to the Allen Park and the rest of the ne twork since the prevailing surface winds are from the southwest during the winter. • II(p)... The localized nature of Southeast Mich igan’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 PM 2.5 is highest from the southwest and west wind directions when nearby monitors are subtracted out of the Dearborn concentr ation. This would indicate that there is a large local source [or sources] between the Dearborn and “b ackground” 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 pla nned data analysis – including source apportionment – should inform the assignment of organic carbon to local and regional sources. . MDEQ is deploying semic ontinuous monitors for particle speciation and high time resolution data can be particularly powerful for identifying source contributions. Results from the summer 2007 USEPA/ORD meas urement 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 urba n area, but close enough to still be similarly impacted by regional transport. This is even more critical if m easurements will be conducted for 24-hour periods once every few days as the “snapshots” at each monito r must be synchronized across the domain. For example, the background site effectively used fo r St. Louis is about 100 km to the south which places it upwind of the city for the prevaili ng surface winds. Perhaps more importantly, however, the line connecting this si te 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 orientat ion 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 sp atial extents greater than the site separation. A better understanding of the drivers for high sp atial 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 re tention; this would be

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 52 particularly insightful for days coinciding with specia tion sampler operation to place the Teflon filter nitrate levels in context of the ambient concentrations. It might be possible to better characterize th e spatial pattern of urban-scale emission source contributions by performing reflectrom etry measurements on archived PM 2.5 

### FRM samples. The parameter from these measurements is typically highly correlated with ther mo-optical EC. Thus, it provides an inexpensive appr oach to characterizing EC spat ial profiles which might be a reasonable surrogate for urba n-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 te mporally consistent subset of the network. The base concentrations genera ted from this work could be applied to the FIA/Lafayette and Newberry data to split observ ed concentrations into base and excess mass components, and then nonparametric wind regr ession (NWR) could be used to determine expected excess mass concentratio ns as a function of wind direction. This work, which is relatively modest in level of e ffort, could significantly contribu te to our unders tanding of PM behavior in the Detroit co mmercial/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 fr om 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 Sa rnia, respectively. NWR results are presented in S ection 5 in terms of the expect ed concentration of excess mass observed at a site when the winds are from a given direction. Th is has proven to be insightful because the results do not depend on the frequenc y distribution of wind directions which can vary from year-to-year and conf ound the identification of temporal changes in emissions. From this analysis we can state that emissions from a certain wind s ector have been modulated by a certain amount over time. However, we are al so interested in an apportionment of the contributions of such emission sources to the PM burden at the monito ring site. This would require weighting the expected concentrations by the frequency of winds from each direction sector. We have developed a conceptual m odel based on the network behavior for various surface wind patterns. The next step is to inco rporate the observed dist ribution of wind patterns to quantify how the observed PM levels are bei ng modulated. We have shown that a PM plume from the Detroit commercial/industrial core imp acts Linwood. By incorporating the observed distribution of surface wind direct ions we could quantify the annual-average PM mass from this plume impacting the site. This analysis would ex tend the focus of this report on high PM days to more robustly characterize annual average behavi or and could be instrumental in providing a framework for assessing the effectiven ess of emission control programs.

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### 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 Ex tent 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 PM 2.5 

### 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), pr epared by the Air Quality Laboratory at Washington University in St. Louis, submitted to th e 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 PM 2.5 

### 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 benefi ted from constructive i nput provided by members of the Southeast Michigan Ozone Study (SEM OS) group and project management provided by Ms. Joan Weidner and Mr. Chuck Hersey (S EMCOG). Technical assistance provided by Michigan DEQ staff (especially Mary Ann He indorf, Cindy Hodges and Amy Robinson) and Ms. Ann Burns (SEMCOG) is al so gratefully acknowledged.

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 54 APPENDIX A: PM 2.5 

### HIGH CONCENTRATION DAYS BY MONTH Allen Park

Month 1 2 3 4 5 6 7 8 9 10 11 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction 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 12fraction of days greater than threshold

0.00 0.05 0.10 0.15 0.20

Figure A-1. Distribution of PM 2.5 high concentration days by month, 1999-2006. Ann Arbor, FIA/Lafayette, and Newberry are excluded because FR M data was not collected at these sites over the entire time period.

### PM 2.5 

### 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 Spring Summer Fall Winter 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 Spring Summer Fall Winter 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)

### PM 2.5 

### 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 Spring Summer Fall Winter 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 Spring Summer Fall Winter 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 l ess than 2 mph) are listed to the lower-left of each wind rose.

### PM 2.5 

### 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%

Valid Network Days All 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%

Valid Network Days All 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, observa tions 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)

### PM 2.5 

### 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 Newb erry excluded from the analysis. * No high PM days meeting these criteria for New Haven and Ypsilanti. (1) denotes site concentration >30 μ g/m 3 while Allen Park <25 μ g/m 3 . (2) denotes site concentration >30 μ g/m 3 while network-wide base <25 μ g/m 3 (limited to those days which are valid network days) (red bars in Figure 4-9).

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 59 APPENDIX D: CPF AND NWR PLOTS 10 

### PM 2.5 

### mass concentrations (both absolute and exce ss with respect to a reference site) were examined using Conditional Probability Func tion (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 pr ovide 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 bi ased 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 c oncentration days?”. The th reshold for defining a “high concentration day” is typi cally chosen as the top 25 th 

### percentile of the co ncentration 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 Sp ringfield site in Chicag o. Nearly 70% of the hours with winds from 180 ° N coincided with a daily contribu tion in the top quartile of the concentration distribution for the copper factor contributions. This pa ttern 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 characteri stics and the frequency of winds from this direction. One dimensional nonparametric wind regression estimat es 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 re sults can be multiplied by the wind direction frequency distribution to determine the contributio n of each wind direction to average PM mass. Figure D-1(b) shows the NWR plot for the PMF-resolv ed copper factor at th e 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 lo cation of emission sources and their impacts.

0
45

90

135
180 225 270 315 15 30

60 75

105 120

150 165 195 210 240 255 285 300 330 345

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 μ g/m 3 ) where the red line denotes the observed contributions from each bearing and the pink circ le denotes the study-average contribution. 10 Adapted from Wade et al. (2008).

### PM 2.5 

### High Concentration Days over Southeast Michigan

Washington University in St. Louis October 1, 2008 60 APPENDIX E: 1-D NWR ON PM 2.5 

### 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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 PM 2.5 excess mass relative to the network-wide base for all network days (left column) and censored to re move 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.

### PM 2.5 

### 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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 PM 2.5 excess mass relative to the network-wide base for all network days (left column) and censored to re move 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.

### PM 2.5 

### 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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 N1-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 PM 2.5 excess mass relative to the network-wide base for all network days (left column) and censored to re move 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.