Introduction to the PM Data Analysis Workbook

1. Objectives of the PM Monitoring Program Critical Issues for Data Uses and Interpretation Motivating Examples References Introduction Workbook Content PM2.5 Background Common PM2.5 Emission Sources Properties of PM PM Formation in the Atmosphere Atmospheric Transport of PM Introduction to the PM Data Analysis Workbook The objective of the workbook is to guide federal, state, and local agencies and other interested people in using particulate matter data to meet their objectives. PM Data Analysis Workbook: Introduction

2. Introduction • Particulate matter (PM) is a general term for a mixture of solid particles and liquid droplets found in the air. • Scientific studies show a link between PM and a series of significant health effects. • The new standards for particles <2.5 m (PM2.5) are 15 g/m3 annual and 65 g/m3 24-hr. • PM2.5, fine particles, result from sources such as combustion and from the transformation of gaseous emissions such as sulfur dioxide (SO2), nitrogen oxide (NOx), and volatile organic compounds (VOCs). PM Data Analysis Workbook: Introduction

3. Introduction Nature and sources of particulate matter (PM). Particulate matter is the general term used for a mixture of solid particles and liquid droplets found in the air. These particles, which come in a wide range of sizes, originate from many different stationary, area, and mobile sources as well as from natural sources. They may be emitted directly by a source or formed in the atmosphere by the transformation of gaseous emissions. Their chemical and physical compositions vary depending on location, time of year, and meteorology. Health and other effects of PM. Scientific studies show a link between PM (alone or combined with other pollutants in the air) and a series of significant health effects. These health effects include premature death, increased hospital admissions and emergency room visits, increased respiratory symptoms and disease, and decreased lung function, and alterations in lung tissue and structure and in respiratory tract defense mechanisms. Sensitive groups that appear to be at greater risk to such effects include the elderly, individuals with cardiopulmonary disease such as asthma, and children. In addition to health problems, particulate matter is the major cause of reduced visibility in many parts of the United States. Airborne particles also can cause soiling and damage to materials. New PM standards. The primary (health-based) standards were revised to add two new PM2.5 standards, set at 15µg/m3 (annual) and 65 µg/m3 (24-hr), and to change the form of the 24-hr PM10 standard. The selected levels are based on the judgment that public health will be protected with an adequate margin of safety. The secondary (welfare-based) standards were revised by making them identical to the primary standards. In conjunction with the Regional Haze Program, the secondary standards will protect against major PM welfare effects, such as visibility impairment, soiling, and materials damage. PM2.5 composition. PM2.5 consists of those particles that are less than 2.5 micrometers in diameter. They are also referred to as "fine" particles, while those between 2.5 and 10 µ m are known as "coarse" particles. Fine particles result from fuel combustion from motor vehicles, power generation, and industrial facilities and from residential fireplaces and wood stoves. Fine particles can also be formed in the atmosphere by the transformation of gaseous emissions such as SO2, NOx, and VOCs. Coarse particles are generally emitted from sources such as vehicles traveling on unpaved roads, materials handling, crushing and grinding operations, and windblown dust. Goals of PM2.5 monitoring. The goal of the PM2.5 monitoring program is to provide ambient data that support the nation's air quality programs, including both mass measurements and chemically resolved, or speciated, data. Data from this program will be used for PM2.5 National Ambient Air Quality Standard (NAAQS) comparisons, development and tracking of implementation plans, assessments for regional haze, assistance for studies of health effects, and other ambient PM research activities. U.S. EPA, 1999a PM Data Analysis Workbook: Introduction

4. PM Data Analysis Workbook: Design Goals • Relevant. The workbook should contain material that state PM data analysts need and omit material that they don’t need. • Technically sound. The workbook should be prepared and agreed upon by experienced PM analysts. • Educational. The workbook content should be presented in a manner that enables state PM data analysts to learn relevant new PM analysis techniques. • Practical. Beyond theory, the workbook should contain practical advice and access to examples, tools and methods. • Gateway. The core workbook should be a gateway to additional on-line resources. • Evolving. The on-line and hard copy workbooks should improve in time through feedback from the user communities. The on-line workbook and data analysis forum is available at http://capita.wustl.edu/PMFine/. Contributions to the workbook and site are encouraged and welcome! PM Data Analysis Workbook: Introduction

5. Why PM Data Analysis by Individual States? • The new PM2.5 regulations will further increase the need to better understand the nature, causes, effects, and reduction strategies for PM. • States collecting data have unique “local” perspectives on data quality, meteorology, and sources, and in articulating policy-relevant data analysis questions. States also face: • large quantities of complex new PM2.5 data, • large uncertainties about causes and effects, • immature nature and inherent complexity of analysis techniques, • importance of both local and transport sources for PM2.5, and • connections between PM2.5, visibility, ozone, climate change, and toxics. • Collaborative data analysis is needed to develop and support linkages between: • data analysis “experts,” “novices,” and “beginners” • data analysts, modelers, health researchers, and policymakers • multiple states, regions, nations, environmental groups and industrial stakeholders Poirot, 1999 PM Data Analysis Workbook: Introduction

6. Workbook Content • Introduction • Ensuring High Quality Data • Quantifying PM NAAQS Attainment Status • Characterizing Ambient PM Concentrations and Processes • Quantifying Trends in PM and its Precursors • Quantifying the Contribution of Important Sources to PM Concentrations • Evaluating PM and Precursor Emission Inventories • Identifying Control Strategies to Meet the NAAQS for PM2.5 • Using PM Data to Assess Visibility (to be added later) • Glossary • Workbook References PM Data Analysis Workbook: Introduction

7. Workbook Preparation Strategy (1 of 2) • This workbook was designed to: • Serve as a companion document to the PM2.5 Data Analysis Workshops. • Reflect a snapshot in time of the workbook available on the website. By design, the website will have the most current information. • Serve as an overview to the large topic of PM2.5 data analysis (not an official guidance document). • For some topics, more information is provided by adding pages in 12 point font. A summary page in larger, presentation-friendly font is typically given to summarize these information-laden pages. PM Data Analysis Workbook: Introduction

8. Workbook Preparation Strategy (2 of 2) • Workshop presenters will use most, but not all, of the workbook pages in their presentations. The goal is that workshop attendees will walk away with all the presentation materials and more. • The document was prepared in landscape format using a single software package to facilitate the presentation, HTML transfer, and printing of the hard copy document. Each topic area could be an entire workbook on its own. • The web version of the workbook will eventually contain active links to methods, tools, data, and references. • References are provided for readers who want more detail. PM Data Analysis Workbook: Introduction

9. Using the Workbook Decision matrix to be used to identify example activities that will help the analyst meet policy-relevant objectives. To use the matrix, find your policy-relevant objective at the top left. Follow this line across to see which example activities will be useful to meet the objective. For each of these activities, look down the column to see which data and data analysis tools are useful for the activity. Adapted from Main et al., 1998 PM Data Analysis Workbook: Introduction

10. Primary PM (directly emitted): Suspended dust Sea salt Organic carbon Elemental carbon Metals from combustion Small amounts of sulfate and nitrate Gases that form PM in the atmosphere (secondary PM): Sulfur dioxide (SO2): forms sulfates Nitrogen oxides (NOx): forms nitrates Ammonia (NH3): forms ammonium compounds Volatile organic compounds (VOC): forms organic carbon compounds PM2.5 Background Emissions that Contribute to PM Mass PM is composed of a mixture of primary and secondary compounds. PM Data Analysis Workbook: Introduction

11. NaCl: Salt is found in PM near sea coasts, open playas, and after de-icing materials are applied. Organic carbon (OC): consists of hundreds of separate compounds containing mainly carbon, hydrogen and oxygen. Elemental carbon (EC): Composed of carbon without much hydrocarbon or oxygen. EC is black, often called soot. Liquid Water: soluble nitrates, sulfates, ammonium, sodium, other inorganic ions, and some organic material absorb water vapor from the atmosphere. Geological material: suspended dust consists mainly of oxides of Al, Si, Ca, Ti, Fe, and other metal oxides. Sulfate: results from conversion of SO2 gas to sulfate-containing particles. Nitrate: results from a reversible gas/particle equilibrium between NH3, HNO3, and particulate ammonium nitrate. Ammonium: ammonium bisulfate, sulfate, and nitrate are most common. Major PM2.5 Components Most PM mass in urban and nonurban areas is composed of a combination of the following chemical components: Chow and Watson, 1997 PM Data Analysis Workbook: Introduction

12. Common PM2.5 Emission Sources: Profiles PM Data Analysis Workbook: Introduction Fujita, 1998

13. Properties of PM • Physical, Chemical and Optical Properties • Size Range of Particulate Matter (PM) • Mass Distribution of PM vs. Size: PM10, PM2.5 • Fine and Coarse Particles • Fine Particles: PM2.5 • Coarse Particle Fraction: PM10-PM2.5; Relationship of PM2.5 and PM10 • Chemical Composition of PM vs. Size • Internal and External Mixtures • Optical Properties of PM Husar, 1999 PM Data Analysis Workbook: Introduction

14. Physical, Chemical and Optical Properties • PM is characterized by its physical, chemical, and optical properties. • Physical properties include particle size and shape. Particle size refers to particle diameter or “equivalent” diameter for odd-shaped particles. Particles may be liquid droplets, regular or irregular shaped crystals, or aggregates of odd shape. • Particle chemical composition may vary including dilute water solutions of acids or salts, organic liquids, earth's crust materials (dust), soot (unburned carbon), and toxic metals. • Optical properties determine the visual appearance of dust, smoke, and haze and include light extinction, scattering, and absorption. The optical properties are determined by the physical and chemical properties of the ambient PM. • Each PM source type produces particles with a specific physical, chemical, and optical signature. Hence, PM may be viewed as several pollutants since each PM type has its own properties and sources and may require different controls. PM Data Analysis Workbook: Introduction

15. Size Range of Particulate Matter • The size of PM particles ranges from about tens of nanometers (nm) (which corresponds to molecular aggregates) to tens of microns (1 m  the size of human hair). • The smallest particles are generally more numerous, and the number distribution of particles generally peaks below 0.1 m. The size range below 0.1 m is also referred to as the ultrafine range. • The largest particles (0.1-10 m) are small in number but contain most of the PM volume (mass). The volume (mass) distribution can have two or three peaks (modes). The bi-modal mass distribution has two peaks. • The peak of the PM surface area distribution is always between the number and the volume peaks. Husar, 1999 PM Data Analysis Workbook: Introduction

16. Mass Distribution of PM vs. Size: PM10, PM2.5 • The mass distribution tends to be bi-modal with the saddle in the 1-3 m size range. • PM10 refers to the fraction of the PM mass less than 10 m in diameter. • PM2.5,or fine mass, refers to the fraction of the PM mass less than 2.5 m in size. • The difference between PM10 and PM2.5 constitutes the coarse fraction. • The fine and coarse particles have different sources, properties, and effects. Many of the known environmental impacts (health, visibility, acid deposition) are attributed to PM2.5. • There is a natural division of atmospheric particulates into Fine and Coarse fraction based on particle size. Husar, 1999 Fine Coarse PM Data Analysis Workbook: Introduction

17. Fine and Coarse Particles Adapted from: Seinfeld and Pandis, 1998 PM Data Analysis Workbook: Introduction

18. Fine Particles: PM2.5 • Fine particles ( 2.5 m) result primarily from combustion of fossil fuels in industrial boilers, automobiles, and residential heating systems. • A significant fraction of the PM2.5 mass over the U.S. is produced in the atmosphere through gas-particle conversion of precursor gases such as sulfur oxides, nitrogen oxides, organics, and ammonia. The resulting secondary PM products are sulfates, nitrates, organics, and ammonium. • Some PM2.5 is emitted as primary emissions from industrial activities and motor vehicles, including soot (unburned carbon), trace metals, and oily residues. • Fine particles are mostly droplets, except for soot which is in the form of chain aggregates. • Over the industrialized regions of the U.S., anthropogenic emissions from fossil fuel combustion contribute most of the PM2.5. In remote areas, biomass burning, windblown dust, and sea salt also contribute. • Fine particles can remain suspended for long periods (days to weeks) and contribute to ambient PM levels hundreds of km away from where they are formed. PM Data Analysis Workbook: Introduction

19. Coarse Particle Fraction: PM10-PM2.5 • Coarse particles (2.5 to 10 m) are generated by mechanical processes that break down crustal material into dust that can be suspended by the wind, agricultural practices, and vehicular traffic on unpaved roads. • Coarse particles are primary in that they are emitted as windblown dust and sea spray in coastal areas. Anthropogenic coarse particle sources include flyash from coal combustion and road dust from automobiles. • The chemical composition of the coarse particle fraction is similar to that of the earth's crust or the sea, but sometimes coarse particles also carry trace metals and nitrates. • Coarse particles are removed from the atmosphere by gravitational settling, impaction to surfaces, and scavenging by precipitation. Their atmospheric residence time is generally less than a day, and their typical transport distance is below a few hundred km. Some dust storms tend to lift the dust to several km altitude, which increases the transport distance to many thousand km. Albritton and Greenbaum, 1998 PM Data Analysis Workbook: Introduction

20. Relationship of PM2.5 and PM10 • PM10 and PM2.5 are related to each other when most of the PM10 is contributed by PM2.5 (e.g., Northeast example above). • Different areas and/or different seasons may have different relationships between PM2.5 and PM10. • PM2.5 comprises a larger fraction of PM10 in the northeastern U.S. than in southern California. • PM2.5 seasonal patterns are similar to those for PM10 in the northeast; seasonal patterns of PM2.5 and PM10 differ in Southern California. Husar, 1999 PM Data Analysis Workbook: Introduction

21. Chemical Composition of PM vs. Size • The chemical species that make up the PM occur at different sizes. • For example in Los Angeles, ammonium and sulfate occur in the fine mode, <2.5 m in diameter. Carbonaceous soot, organic compounds, and trace metals tend to be in the fine particle mode. • The sea salt components, sodium and chloride, occur in the coarse fraction, > 2.5 m. Wind-blown and fugitive dust are also found mainly in the coarse mode. • Nitrates may occur in fine and coarse modes. Husar, 1999 PM Data Analysis Workbook: Introduction

22. Internal and External Mixtures of Particles • During their multi-day atmospheric residence time, particles from different sources and with different compositions are mixed together by a range of atmospheric processes. The resulting particles can be either external or internal mixtures. • In an external mixture, the particle composition will be non-uniform because the components from different sources remain separate (e.g., a soot particle inside a sulfate droplet, as illustrated by the electron micrograph below). • In an internal mixture, the particle composition is uniform because the individual components are completely mixed. • The main process that produces internal mixtures is processing by water such as in fog and/or cloud scavenging and subsequent evaporation. Electron micrograph of a PM2.5 droplet residue. Evidently, the droplet contained a solid particle, possibly soot. Husar, 1999 PM Data Analysis Workbook: Introduction

23. Optical Properties of PM • Particles effectively scatter and absorb solar radiation. • The scattering efficiency per PM mass is highest at about 0.5 m. This is why, for example, 10 g of fine particles (0.2 < D < 1 m) scatter over ten times more than 10 g of coarse particles (D > 2.5 m) Husar, 1999 PM Data Analysis Workbook: Introduction

24. PM Formation in the Atmosphere Sulfate Formation in the Atmosphere Sulfate Formation in Clouds Seasonal SO2--to-Sulfate Transformation Rate Residence Time of Sulfur and Organics Nitrate Formation in the Atmosphere Links to Ozone Formation, Health, and Visibility PM Data Analysis Workbook: Introduction

25. Sulfate Formation in the Atmosphere • Sulfates constitute about half of the PM2.5 in the eastern U.S. Virtually all the ambient sulfate (99%) is secondary, formed within the atmosphere from SO2. • About half of the SO2 oxidation to sulfate occurs in the gas phase through photochemical oxidation in the daytime. NOx and hydrocarbon emissions tend to enhance the photochemical oxidation rate. Husar, 1999 • The condensation of H2SO4 molecules results in the accumulation and growth of particles in the 0.1-1.0 m size range – hence the name “accumulation-mode” particles. PM Data Analysis Workbook: Introduction

26. Sulfate Formation in Clouds Husar, 1999 • At least half of the SO2 oxidation takes place in cloud droplets as air molecules pass through convective clouds at least once every summer day. • Within clouds, the soluble pollutant gases, such as SO2, get scavenged by the water droplets and rapidly oxidize to sulfate. • Only a small fraction of the cloud droplets rain out; most droplets evaporate at night and leave a sulfate residue or “convective debris”. Most elevated layers above the mixing layer are pancake-like cloud residues. • Such cloud “processing” is responsible for internally mixing PM particles from many different sources. It is also believed that such “wet” processes are significant in the formation of the organic fraction of PM2.5. PM Data Analysis Workbook: Introduction

27. Season SO2-to-Sulfate Transformation Rate SO2-to-sulfate transformation rates peak in the summer due to enhanced summertime photochemical oxidation and SO2 oxidation in clouds. Transformation rates derived from the CAPITA Monte Carlo Model, Schichtel and Husar (1997). Husar, 1999 PM Data Analysis Workbook: Introduction

28. Residence Time of Sulfur and Organics • SO2 is depleted mostly by dry deposition (2-3%/hr) and also by conversion to sulfate (up to 1%/hr). This gives SO2 an atmospheric residence time of only 1 to 1.5 days. • It takes about a day to form the sulfate PM. Once formed, sulfate is removed mostly by wet deposition at a rate of 1-2 %/hr yielding a residence time of 3 to 5 days. • Overall, sulfur as SO2 and sulfate is removed at a rate of 2-3%/hr, which corresponds to a residence time of 2-4 days. • These processes have at least a factor of two seasonal and geographic variation. • It is believed that the organics in PM2.5 have a similar conversion rate, removal rate, and atmospheric residence time. Husar, 1999 PM Data Analysis Workbook: Introduction

29. Nitrate Formation and Removal in the Atmosphere • NO2 can be converted to nitric acid (HNO3) by reaction with hydroxyl radicals (OH) during the day. • The reaction of OH with NO2 is about 10 times faster than the OH reaction with SO2. • The peak daytime conversion rate of NO2 to HNO3 in the gas phase is about 10 to 50% per hour. • During the nighttime, NO2 is converted into HNO3 by a series of reactions involving ozone and the nitrate radical. • HNO3 reacts with ammonia to form particulate ammonium nitrate (NH4NO3). • About 1/3 of anthropogenic NOx emissions in the U.S. are estimated to be removed by wet deposition. • Thus, PM nitrate can be formed at night and during the day; daytime photochemistry also forms ozone. PM Data Analysis Workbook: Introduction

30. PM and Ozone (1 of 2) The formation of a substantial fraction of secondary PM2.5 depends on photochemical gas phase reactions which also produce ozone. • Concentrations of OH radicals, ozone, and hydrogen peroxide (H2O2), formed by gas phase reactions involving VOCs and NOx, depend on the concentrations of the reactants and on meteorological conditions including temperature, solar radiation, wind speed, mixing volume, and synoptic weather conditions. NESCAUM, 1992 PM Data Analysis Workbook: Introduction

31. PM and Ozone (2 of 2) • An illustration of some of the environmental factors that influence the production of ozone and secondary PM formation. • Meteorological (e.g., mixing heights, transport) and chemical conditions (e.g., emissions composition and intensity) affect the concentration of secondary PM and ozone precursors. RRWG Policy Team, 1999 PM Data Analysis Workbook: Introduction

32. PM, Health, and Visibility • Human health research indicates that PM mass correlates with sickness and death. The components of PM that cause these health effects are not known. • Fine particles and/or coarse particles may contribute to these health effects. • Visibility, the distance one can distinguish a target, is influenced by lighting, contrast of the target to the background, and most importantly, the size, color, and concentration of the particles between the observer and the target. Thus, we need to better understand the chemical and physical characteristics and the formation of PM in order to identify the links between and reduce the influence of PM on health and visibility. PM Data Analysis Workbook: Introduction

33. Summary of Factors Influencing PM Concentrations: Meteorology • Meteorological parameters important to PM concentration variations include: temperature, relative humidity, mixing heights, wind speed, and wind direction. • Seasonal changes in meteorology effect diurnal, seasonal, and chemical patterns of PM. Chu and Cox, 1998 PM Data Analysis Workbook: Introduction

34. Summary of Factors Influencing PM Concentrations: Emissions • Time patterns of emissions • Diurnal patterns (e.g., traffic, biogenics) • Weekday/weekend patterns • Source type and location of emissions • Point vs. area vs. mobile source emissions • Height of emissions • Primary PM emissions vs. secondary PM • Chemical composition (e.g., Ni and V from oil, Se from coal, Na from sea salt or winter road salt) Temporal, spatial, and chemical emissions characteristics influence PM concentrations and provide clues to source contributions. PM Data Analysis Workbook: Introduction

35. Atmospheric Transport of PM • Transport Mechanisms • Influence of Transport on Source Regions • Plume Transport • Long-range Transport • Atmospheric Residence Time and Spatial Scales • Residence Time Dependence on Height • Range of Transport PM Data Analysis Workbook: Introduction

36. Transport Mechanisms Pollutants are transported by the atmospheric flow field which consists of the mean flow and the fluctuating turbulent flow. Husar, 1999 The three major airmass source regions that influence North America are the northern Pacific, the Arctic, and the tropical Atlantic. During the summer, the eastern U.S. is influenced by the tropical airmass from the Gulf of Mexico. The three transport processes that shape regional dispersion are wind shear, veer, and eddy motion. Homogeneous hazy airmasses are created through shear and veer at night followed by vigorous vertical mixing during the day. PM Data Analysis Workbook: Introduction

37. Influence of Transport on Source Regions Horizontal Dilution Vertical Dilution Husar, 1999 Low wind speeds over a source region allows for pollutants to accumulate. High wind speeds ventilate a source region preventing local emissions from accumulating. In urban areas, during the night and early morning, the emissions are trapped by poor ventilation. In the afternoon, vertical mixing and horizontal transport tend to dilute the concentrations. PM Data Analysis Workbook: Introduction

38. Plume Transport Much of the man-made PM2.5 in the eastern U.S. is from SO2 emitted by power plants. • Plume transport varies diurnally from a ribbon-like layer near the surface at night to a well-mixed plume during the daytime. • Even during the daytime mixing, individual power plant plumes remain coherent and have been tracked for 300+ km from the source. • Most of the plume mixing is due to nighttime lateral dispersion followed by daytime vertical mixing. Husar, 1999 PM Data Analysis Workbook: Introduction

39. Long-range Transport • In many remote areas of the U.S., high concentrations of PM2.5 have been observed. Such events have been attributed to long-range transport. • Long-range transport events occur when there is an airmass stagnation over a source region, such as the Ohio River Valley, and the PM2.5 accumulates. Following the accumulation, the hazy airmass is transported to the receptor areas. • Satellite and surface observations of fine particles in hazy airmasses provide a clear manifestation of long-range pollutant transport over eastern North America. Husar, 1999 PM Data Analysis Workbook: Introduction

40. Atmospheric Residence Time and Spatial Scales • PM2.5 sulfates reside 3 to 5 days in the atmosphere. • Ultrafine 0.1 m coagulate while coarse particles above 10 m settle out more rapidly. • PM in the 0.1-1.0 m size range has the longest residence time because it neither settles nor coagulates. • Atmospheric residence time and transport distance are related by the average wind speed, about 5 m/s. • Residence time of several days yields “long- range transport” and more uniform spatial pattern. • On average, PM2.5 particles are transported 1000 or more km from the source of their precursor gases. PM Data Analysis Workbook: Introduction Husar, 1999

41. Residence Time Dependence on Height Husar, 1999 • The PM2.5 residence time increased with height. • Within the atmospheric boundary layer (the lowest 1-2 km), the residence time is3 to 5 days. • If aerosols are lifted to 1-10 km in the troposphere, they are transported for weeks and many thousand miles before removal. • The lifting of boundary layer air into the free troposphere occurs by deep convective clouds and by converging airmasses near weather fronts. PM Data Analysis Workbook: Introduction

42. Range of Transport • The residence time determines the range of transport. For example, given a residence time of 4 days (~100 hrs) and a mean transport speed of 10 mph, the transport distance is about 1000 miles. • The range of transport determines the “region of influence” of specific sources. Husar, 1999 PM Data Analysis Workbook: Introduction

43. Objectives of the PM Monitoring Program • The primary objective of the PM monitoring program is to provide ambient data that support the nation’s air quality program objectives. At a minimum, this includes: • Determine whether health and welfare standards (NAAQS) are met. • Assess annual and seasonal spatial characterization of PM. • Track progress of the nation and specific areas in meeting Clean Air Act requirements (provided, for example, through national trends analyses). • Develop emission control strategies. Homolya et al., 1998 PM Data Analysis Workbook: Introduction

44. Overview of National PM2.5 Network Homolya et al., 1998 PM Data Analysis Workbook: Introduction

45. PM2.5 Implementation Update • The bulk of all compliance and continuous monitoring sites are to be established by December 31, 1999. • The first chemical speciation sites will begin operation by November 1999, and installations will continue through December 31, 2000. • The IMPROVE sites were to have been deployed by December 31, 1999; however, this schedule has been delayed. • Operation of the Super-sites began with Atlanta in August 1999; the site in Fresno will be next, followed by the remaining areas (to be announced once grants are awarded). Byrd, 1999 PM Data Analysis Workbook: Introduction

46. PM2.5 Sampling Schedule • Compliance sites [those with federal reference method samples (FRMS)] will operate largely on an everyday or one-in-three-day schedule. Some sites will operate on a one-in-six-day schedule. • Continuous sites will operate every day. • Fifty-four speciation sites will operate on a one-in-three-day schedule. • The remaining sites will operate on a one-in-six-day or episodic schedule, depending on data needs. • The IMPROVE sampling schedule will ultimately match a one-in-three-day schedule. Byrd, 1999 PM Data Analysis Workbook: Introduction

47. Site Types Homolya et al., 1998 The larger check marks reflect the primary use of the data. PM Data Analysis Workbook: Introduction

48. Data Collected Homolya et al., 1998 PM Data Analysis Workbook: Introduction

49. Sampling Artifacts and Interferences(1 of 2) Homolya et al., 1998 PM Data Analysis Workbook: Introduction

50. Sampling Artifacts and Interferences(2 of 2) • Organic gas adsorption (positive bias) comprised up to 50% of the organic carbon measured on quartz-fiber filters in southern California (Turpin et al., 1994). These studies also indicated that adsorption was much more important than organic particle volatilization (negative bias). • Sampling losses on the order of 30% of the annual federal standard for PM2.5 may be expected due to volatilization of ammonium nitrate in those areas of the country where nitrate is a significant contributor to the fine particle mass and where ambient temperatures tend to be warm (Hering and Cass, 1999). PM Data Analysis Workbook: Introduction