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Detailed Monitoring Protocol

4.0 Monitoring Methods

4.1 MSAT and Surrogate Monitoring Methods

4.1.1 USEPA Method TO-11A5 for the Collection and Analysis of Aldehydes and Ketones

TO-11A is a method used for the determination of formaldehyde and other carbonyl compounds (aldehydes and ketones) in ambient air that relies on reaction of the carbonyl compounds with 2,4-dinitrophenyl hydrazine (DNPH) to produce characteristic DNPH-carbonyl derivatives. This method uses a DNPH coated-solid adsorbent for the collection of carbonyls from an ambient air sample, followed by high performance liquid chromatographic (HPLC) analysis of the collected DNPH derivatives. The method calls for the use of commercially available pre-coated DNPH cartridges for sample collection. These cartridges are used as received and discarded after a single use. The collected and uncollected cartridges should be stored in culture tubes with polypropylene caps and placed in cold storage when not in use.

In the TO-11A method, ambient air is drawn through the DNPH cartridge at a known sampling rate of 100 to 2,000 milliliters per minute (ml/min) for an appropriate period of time. The sampling rate and time are dependent upon the expected carbonyl concentrations in the test atmosphere. After sampling, the sample cartridges and field blanks are individually capped and should be placed in shipping tubes with polypropylene caps. The capped tubes are then refrigerated to subambient temperature (~4o C), and returned to the laboratory for analysis. In the laboratory, the cartridges are washed by gravity feed elution with 5 ml of acetonitrile from a plastic syringe reservoir to a graduated test tube or a 5 ml volumetric flask. The eluate is then diluted to a known volume and refrigerated until analysis.

For determining formaldehyde and other carbonyls, the DNPH-formaldehyde derivatives are analyzed by isocratic reverse phase HPLC with an ultraviolet (UV) absorption detector operated at 360 nm. The HPLC system is operated in the linear gradient program mode. For quantitative evaluation of formaldehyde and other carbonyl compounds, a cartridge blank is likewise desorbed and analyzed. Formaldehyde and other carbonyl compounds in the sample eluate are identified and quantified by comparison of their retention times and peak heights or peak areas with those from analysis of standard solutions. Typically, C1 to C10 carbonyl compounds are measured effectively to less than 0.5 parts per billion by volume (ppbv) (i.e., 1x10-9 v/v) using this method.

4.1.2 USEPA Method TO-156 for the sampling and analysis of VOCs in ambient air

TO-15 is a standard method used for the sampling and analysis of volatile organic compounds (VOCs) in ambient air including the MSATs benzene and 1,3-butadiene. VOCs are defined here as organic compounds having a vapor pressure greater than 10 Torr. In this method, whole ambient air is sampled collected in a specially-prepared evacuated stainless steel canister. After the air sample is collected, the canister valve is closed and the canister is transported to the laboratory for analysis.

The analysis of the collected samples involves the use of a high resolution gas chromatograph coupled to a mass spectrometer (GC/MS). To analyze the sample, a known volume of sample is directed from the canister through a solid multisorbent concentrator. A portion of the water vapor in the sample breaks through the concentrator during sampling, to a degree depending on the multisorbent composition, duration of sampling, and other factors. Water content of the sample can be further reduced by dry purging the concentrator with helium while retaining target compounds. After the concentration and drying steps are completed, the VOCs are thermally desorbed, entrained in a carrier gas stream, and then focused in a small volume by trapping on a reduced temperature trap or small volume multisorbent trap. The sample is then released by thermal desorption and carried onto a gas chromatographic column for separation.

After separation, the analytes are detected in the mass spectrometer. If the mass spectrometer is a linear quadrupole system, it is operated either by continuously scanning a wide range of mass to charge ratios (SCAN mode) or by monitoring select ion monitoring mode (SIM) of compounds on the target list. If the mass spectrometer is based on a standard ion trap design, only a scanning mode is used (note however, that the Selected Ion Storage (SIS) mode for the ion trap has features of the SIM mode). For any given compound, the intensity of the primary ion fragment is compared with the system response to the primary fragment for known amounts of the compound to determine the compound concentration in the sample. The stability of benzene and 1,3-butadiene in the collected air sample is sufficient that accurate analyses can be obtained at least 14 days after sample collection.

4.1.3 Carbon Monoxide

Carbon monoxide (CO) is produced from the incomplete combustion of carbonaceous fuels. In urban areas, automobiles are a substantial source of CO, and thus CO is recommended for measurement as a surrogate for vehicle emissions. It is expected that patterns in CO concentration may correlate well with MSAT concentrations.

The standard reference method for the determination of ambient CO is non dispersive infrared spectrophotometry (NDIR). The NDIR CO measurement principle is the absorption of infrared (IR) radiation, with a wavelength of 4.7 micrometers (?m), by CO. The USEPA has designated a number of commercial CO analyzers as Federal Reference Methods (FRM).7 For each of these monitoring studies, FRM-designated CO analyzers should be used for the continuous monitoring of CO.

4.1.4 Nitrogen Oxides

Nitrogen oxides (NO and NO2, collectively called NOx) are emitted from all combustion sources, including motor vehicles. Nitrogen oxide monitoring should be carried out as a surrogate for vehicle emissions in general. Nitrogen oxides should be measured using any of several continuous chemiluminescence instruments that are commercially available and that have been designated by the USEPA as being an Automated Equivalent Method.7

The chemiluminescence approach is based on the gas-phase reaction of NO with excess ozone (O3), which produces a characteristic near-infrared luminescence (broad-band radiation from 500 to 3,000 nm, with a maximum intensity at approximately 1,100 nm) with an intensity that is proportional to the concentration of NO.

To determine the concentration of NO by chemiluminescence, the sample gas flow is mixed with O3 in a reaction chamber causing electronic excitation and relaxation reactions to occur. The chemiluminescence that results from these reactions is monitored by an optically filtered high sensitivity photomultiplier, that responds to NO2 chemiluminescence emission at wavelengths longer than 600 nm. The electronic signal produced in the photomultiplier is proportional to the NO concentration in the sample air. Measurement of NOx is achieved by means of a heated converter that reduces NO2 to NO for measurements. For the studies conducted under this Protocol, NO, NO2, and NOx concentrations should all be reported.

4.1.5 Black Carbon

A major component of urban aerosol is elemental carbon (EC), which is frequently called "soot". EC is emitted from all types of combustion, including from diesel exhaust. Although EC is not a unique surrogate for motor vehicle, in the absence of other common EC sources (i.e., woodsmoke), EC can serve as an indicator of diesel emissions. Thus monitoring of EC as an indicator for diesel emissions should be conducted for studies under this Protocol. Monitoring for EC can be achieved using an Aethalometer which is a commercial instrument that provides a near real-time readout of the concentration of "black carbon" (BC) in ambient air. Black carbon is operationally defined by the Aethalometer and comprises a subset of EC, but is highly correlated to EC concentrations. The Aethalometer measures the airborne concentration of BC using a continuous filtration and optical measurement method to give a continuous readout of aerosol optical absorption. During operation, the Aethalometer draws the air sample through an inlet port, typically at a flow rate of a few liters per minute, and collects the particulate sample on a quartz fiber filter tape. As the sample collects on the tape, a continuous optical analysis is conducted to monitor the attenuation of light through the tape. That attenuation is due almost entirely to absorption of light by BC in the collected particles. The analysis gives one new reading usually every 1 to 5 minutes based on the requirements of the user.

4.1.6 PM2.5 and Surrogates for PM2.5

Fine particulate matter (referred to as PM2.5) is component of vehicle emissions and should be measured as a surrogate for vehicle exhaust. The only accepted means of measuring PM2.5 is the filter based FRM8 that involves the collection of a 24-hour average PM2.5 sample. Monitoring for PM2.5 should be conducted using FRM designated PM2.5 samplers.7 In addition to the PM2.5 FRM measurements, continuous surrogate measurements of fine particle concentrations should also be made using commercially available instruments, e.g., either a beta attenuation monitor (BAM) or a tapered element oscillating microbalance (TEOM) monitor. Prior to implementation of either of these monitors into a monitoring study, the limitations of these techniques should be understood. Because of the nature of the measurement techniques employed in these monitors, their respective responses to aerosols will be dependent upon the aerosol properties and will not necessarily agree with one another, or with the PM2.5 FRM.

4.1.7 Summary

Table 4-1 present a summary of the recommended monitoring methods for the MSATs and surrogate compounds to be measured during the studies conducted under this Protocol. Included in this table are values for some of the key data quality indicators (DQIs) that are recommended. Discussions of these DQIs are given below.

Table 5. Summary of Pollutant Measurements and DQIs
Pollutant Sampling Approach Accuracy Precision Data Completeness
Carbon monoxide(surrogate) Continuous monitoring(NDIR FRM CO analyzer) 20% 10% 80%
Nitrogen oxides(surrogate) Continuous monitoring(Chemiluminescence NOx analyzer) 20% 10% 80%
Black carbon(surrogate) Continuous monitoring (Aethalometer) 5% 5% 80%
PM2.5(surrogate) Continuous monitoring (Beta gauge or TEOM) 5% 5% 80%
PM2.5 (surrogate) Integrated filter sampling (PM2.5 FRM method) 5% 5% 90%
Acetaldehyde (MSAT) Integrated sampling/HPLC analysis (USEPA Method TO-11A) 10% 5% for flow rate 10% for HPLC 90%
Acrolein (MSAT) Integrated sampling/HPLC analysis(USEPA Method TO-11A) 10% 5% for flow rate 10% for HPLC 90%
Benzene (MSAT) Canister sampling-GC/MS analysis (USEPA Method TO-15) 10% 5% for flow rate 10% for GC/MS 90%
1,3-Butadiene (MSAT) Canister sampling-GC/MS analysis (USEPA Method TO-15) 10% 5% for flow rate 10% for GC/MS 90%
Formaldehyde (MSAT) Integrated sampling/HPLC analysis (USEPA Method TO-11A) 10% 5% for flow rate 10% for HPLC 90%
4.1.7.1 Accuracy

Accuracy is defined as the agreement between a measured value and the true value for a given parameter. Accuracy includes components of random error associated with variability from imprecision and systematic error associated with instrumental bias. Accuracy should be determined for the MSAT and surrogate monitoring systems and for the meteorological sensors. For the continuous gas analyzers (CO and NOx) accuracy should be assessed by challenging each analyzer with audit gases of known and certified concentration using a flow dilution system checked against a National Institute of Standards and Technology (NIST) traceable flow standard. Accuracy should be expressed in terms of a percent difference between the measured concentration and the known concentration of the audit gas. Particulate matter standards do not exist, therefore, accuracy for the continuous aerosol monitors and the integrated PM2.5 samplers should be established based on flow rate audit measurements, as is customary for these methods. For the meteorological sensors, accuracy should be assessed by comparisons to collocated transfer standards.

Accuracy of the MSAT integrated methods (canister sampling/GC/MS analysis and DNPH cartridges/HPLC analysis) is assessed in two ways, i.e., by sampling flow checks and by laboratory calibrations. The air sampling flow rates of the MSAT sampling methods should be audited in the field, using NIST-traceable flow standards. The GC/MS and HPLC analytical methods are calibrated using commercially prepared gas standards, and using liquid phase standards of the carbonyl compounds, respectively. Accuracy thus depends on the quality of these primary standards, and the variability of the method calibration results. Accuracy of these laboratory calibrations should be assessed by comparison of independent standards in the laboratory.

Values for the accuracy DQIs should be established for each study prior to initiation of the monitoring. Recommended values for accuracy DQIs for the pollutant measurements are ±20% for the continuous gas analyzers; ±5% in flow rate for the continuous aerosol monitors, the PM2.5 samplers, and the MSAT samplers; and ±10% for the MSAT laboratory analytical methods. For the meteorological sensors, the recommended accuracy DQIs are set equal to those recommended by the U.S Environmental Protection Agency (USEPA).8

4.1.7.2 Precision

Precision is an assessment of the mutual agreement among multiple independent measurements under similar conditions. For the continuous gas analyzers, precision should be assessed by challenging each analyzer with a standard gas of constant known concentration at least once every 2 weeks during the monitoring period. Since generation and delivery of constant known concentrations of aerosols is impractical for these studies, precision does not need to be assessed directly for the continuous aerosol monitors or the PM2.5 samplers. However, at least one of the monitoring sites should be equipped with duplicate monitoring systems for some part of the study if feasible. If duplicate monitors are used at one site, precision can be established by comparison of simultaneous measurements from the duplicate monitors. An additional estimate of precision for the aerosol monitors, PM2.5 samplers, and MSAT samplers can be based on the variation of the flow audits conducted periodically for these devices. Precision does not need to be assessed for the meteorological sensors since repeated measurements under stable conditions will not be practical during these studies.

In addition to assessing the precision of the sample flow rates for the MSAT samplers, the precision of the laboratory analytical methods for the MSATs should be assessed. This can be done both in terms of the variability in the calibration curves obtained with the respective gaseous or liquid phase standards over the duration of the study, and the variability of repeated analyses of the same standard or sample. The former provides an estimate of the long-term precision of the analysis, and the latter provides a measure of precision in individual sample analysis.

The recommended precision tolerance for the continuous surrogate (CO and NOx) monitors is ±10% as relative standard deviation (RSD), calculated from the periodic challenges with calibration gas during the study. The recommended precision for flow checks on the continuous aerosol monitors, the PM2.5 samplers, and the MSAT samplers is ±5%, with a recommended tolerance of duplicate PM2.5 mass results from paired samplers of ±10%. The precision of the GC/MS and HPLC analytical methods for volatile organics and carbonyl compounds, respectively, is recommended to be within 10% as RSD.

4.1.7.3 Data Completeness

Data completeness is a measure of the amount data actually collected compared with the amount of data that could be collected for a given measurement. For the continuous monitoring systems (i.e., gas analyzers, continuous aerosol analyzers, meteorological sensors), data completeness will be determined from the number of valid hourly measurements that were made divided by the total number of hourly periods during the monitoring study. This ratio multiplied by 100 provides data completeness in terms of percentage. For the MSAT and PM2.5 samplers, data completeness will be determined from the number of valid samples collected, divided by the number of sampling periods, multiplied by 100.

Recommended minimum values for data completeness DQIs are 80% for the continuous measurements and 90% for the MSAT and meteorological measurements.

4.1.7.4 Representativeness

Data collected from these studies should be representative of the actual conditions during the monitoring study. Representativeness is ensured through proper site selection, sample collection and handling, and sample analysis. Chapter 40 of the CFR, Part 58, Appendix E provides guidance on instrument siting to help ensure representativeness of the measurements.

No quantitative values are recommended for representativeness of DQIs.

4.2 Meteorological Monitoring

Meteorological monitoring should include the measurement of wind speed, wind direction, ambient temperature, barometric pressure, relative humidity, solar radiation, and precipitation. The meteorological sensor used for each monitoring study should meet the specifications recommended by the USEPA in "Meteorological Monitoring Guidance for Regulatory Modeling Applications."8 Table 4-2 presents the recommended specifications for the meteorological sensors that should be used for these studies. The use of averaging times of 10 seconds or less is recommended.

Table 6. Recommended Specifications for Meteorological Sensors
Variable Range Accuracy Resolution Time/Distance Constants
Wind Speed 0.5 to 50 m/s ±0.2 m/s + 5% 0.1 m/s 5 m (63% response)
Wind Direction 0 to 360° ±5° 5 m (50% recovery)
Air Temperature -20 to 40°C ±0.5° C 0.1°C 60 seconds (63% response)
Dew Point -30 to 30°C ±1.5°C 0.1°C 30 min
Relative Humidity 0 to 100% RH ±3% RH ±5% RH @ >90% RH 0.5% RH 60 seconds (63% response)
Solar Radiation 0 to 1200 W/ m2 ±5% 10 W/m2 60 seconds (99% response)
Barometric Pressure 800 to 1100 hPa ±3 hPa 0.5 hPa 60 seconds(63% response)
Precipitation 0 to 30 mm/hour ±10% 0.25 mm 60 seconds (63% response)

4.3 Traffic Detection/Monitoring Equipment

The following sections present brief summaries of the current traffic counting and vehicle classification technologies that might be used for studies conducted under this Protocol. Since traffic monitoring is likely to be an on-going effort at the study locations selected, the discussion below is largely for informative purposes only. However in the event that traffic monitoring is not already conducted at a study location and that a contractor conducting a study under this Protocol must implement the traffic monitoring, a summary table is presented in Section 4.3.3 presenting capabilities and the advantages and disadvantages of the different traffic monitoring systems. Table 4-3 presents recommended values for some key DQIs for traffic monitoring systems.

Table 7. Recommended DQI Values for Traffic Monitoring Equipment
Variable Accuracy Data Completeness
Vehicle Count 80% 90%
Vehicle Speed 80% 90%
Vehicle Classification 70% 80%

4.3.1 Intrusive Options

4.3.1.1 Inductive Loop Detector (ILD)

The most prevalent type of vehicle detector currently in use is the inductive loop detector (ILD). The ILD has a long history of use at individual signalized intersections as well as multiple signal systems. It has also been widely used in freeway monitoring systems and as a key component in automated incident detection.

An ILD consists of the following components:

As a vehicle passes over an ILD, the electrical inductance is decreased and an electronic amplifier detects this change. This change is processed and used to measure volume and occupancy. Loops are installed as a single installation, in the case of a minor roadway approach to an intersection, or in multiple loop configurations. Loops placed in pairs are used to determine vehicle speed as well as vehicle classification information.

4.3.1.2 Fiber Optic Sensors

Fiber optic sensors consist of fiber optic cables installed in the pavement that measure variations in light due to compression from an overhead source (i.e. vehicle axles, foot traffic, etc.) When a vertical load is applied to the sensor, a small amount of light escapes from the sensor fiber causing the light level at the sensor output to decrease. The amount of the light is compared to a factory set reference by the optical interface for producing an output signal. Fiber optic sensors are insensitive to adjacent lane vibrations. Control electronics can be located long distances away from the sensors due to the low loss of the optical fiber.

4.3.1.3 Magnetic Sensors

Detection using magnetic sensors is achieved by placing the device directly within the pavement or within a buried conduit and measuring the change in the vertical component of the earth's magnetic field. When a vehicle passes over the magnetometer, a voltage change is detected and causes a closure of an output relay. This change is used as a vehicle count or passage measurement.

4.3.1.4 Piezoelectric/Weigh-in-Motion

Piezoelectric sensors are axle sensors installed within the roadway surface to register changes in piezoelectric energy when a vehicle passes over the sensor. These detectors register the overall change in energy from the passing vehicle and translate that into a corresponding weight. They are widely used in weigh-in-motion applications.

4.3.1.5 Pneumatic Road Tube

Pneumatic road tubes are simply tubes installed across one or more lanes of a roadway with brackets. These tubes are connected to a control box off of the roadway. When vertical loads are applied to these tubes (i.e. through vehicular axles), bursts of air are forced through the tube to the control box and are registered as an axle. This method is very simple and effective in counting vehicles and can be used in pairs to register vehicle speeds (with the assumption of standard vehicle lengths between axles). It is not effective for detecting vehicle presence or classification.

4.3.2 Non-Intrusive Options

4.3.2.1 Radar/Microwave Detectors

Radar and microwave type detectors are similar in that both transmit microwave energy toward an area of roadway from a detector mounted overhead. In the case of radar, a measurement of energy reflected back from the roadway is used to determine vehicle speed based on the Doppler effect. The microwave detector measures the time it takes to transmit a pulse from the detector to the roadway and back. The presence of a vehicle is detected by the difference in time of this pulse reflection with and without a vehicle in the roadway.

4.3.2.2 Infrared Detectors

Infrared detectors are classified as active or passive. In the active system, the detection zone is illuminated with low power infrared energy supplied by light emitting diodes. The infrared energy reflected off vehicles within the detection zones is used by real time signal processing within the unit to determine presence of a vehicle. The passive system is a similar design but uses an energy detector element to measure passage or motion change only. This detection technology can give traffic volume, vehicle classification, and speed.

4.3.2.3 Passive Acoustic Array Sensors

Passive acoustic array sensors are acoustical sensors that can detect changes in background noise from a passing vehicle. The sensors are mounted non-intrusively on an existing overhead bridge or adjacent pole. Based on the vehicle characteristics, the acoustical changes can be detected, counted and classified.

4.3.2.4 Video Detection

Video Image Detection (VIDs) is one of the newer forms of roadway detection that has been developed over the last decade. VIDs utilize closed circuit television cameras with microprocessor hardware and software to analyze images of the roadway. Real time data within a defined zone can be collected including volume, speed, occupancy, and vehicle classification. VIDs have become a proven technology option. However, installation and operational costs are comparatively higher than other type detection devices and need to be carefully evaluated for individual applications.

4.3.2.5 Automated Vehicle Identification (AVI)

With the proliferation of electronic toll collection throughout the nation, automatic vehicle identification has become increasingly attainable on a wide scale. Automatic vehicle identification systems utilize radio frequency identification (RFID) tags mounted inside a vehicle to collect traffic data from a reader or series of readers along the roadway. These readers could be the same readers used for electronic toll collection (ETC) or could be additional readers mounted off the roadway between toll plazas. Vehicle information such as classification is stored within the tags and uploaded to the readers when the vehicle passes within range. When readers are utilized in pairs, vehicle speeds can also be easily computed.

4.3.3 Summary

Table 4-4 presents a summary of currently available traffic detectors and their capabilities. Each detector type discussed above is listed along with associated advantages and disadvantages. The traffic data that are collected for the studies conducted under this Protocol should be logged at least hourly for easy synchronization with the pollutant and meteorological data collection and at a minimum must be collected during all MSAT integrated sampling periods. Continuous data collection for the duration of each monitoring study is recommended, to allow for correlation with the continuous surrogate data.

Some ongoing debate exists within the industry that revolves around the accuracy and appropriateness of vehicle classification data from many detectors. Several newer models of radar/microwave type devices use measured vehicle length as a surrogate for vehicle classification. The accuracy of the data is assumed to be at a level that would require visual verification. These factors should be considered when determining which technologies should be used for the studies conducted under this Protocol.

Table 8. Summary of Traffic Monitoring Detectors and Capabilities
Detector Installation Volume Speed Class Advantages Disadvantages
Intrusive
Inductive Loops In Pavement √ (1)   Easy to install. Relatively inexpensive. In-pavement installation requires saw cutting and lane closures.
Fiber Optic Sensors In Pavement √ (1)   Easy to install. Relatively inexpensive. In-pavement installation requires saw cutting or boring for conduit.
Magnetic Sensors In Pavement √ (1)   Easy to install. Relatively inexpensive. Poorly defined detection zone susceptible to errors.
Piezoelectric/Weigh in Motion In Pavement √ (1)   Easy to install. Relatively inexpensive. In-pavement installation requires saw cutting or boring for conduit.
Pneumatic Road Tube In Pavement √ (1)   Easy to install. Relatively inexpensive. Susceptible to breakage/removal with large volumes of traffic.
Non-Intrusive
Radar/Microwave Overhead/Adjacent √ (2) Non-invasive installation. Quick implementation. Setback and line of sight requirements.
Infrared Overhead √ (1)   Non-invasive installation. Accuracy can be susceptible to environmental conditions.
Passive Acoustic Array Overhead     Non-invasive installation. Accuracy can be susceptible to adjacent noise sources.
Video Overhead/Adjacent Can measure all parameters. Relatively expensive. Maintenance of detection zone alignment required.
AVI Overhead/Adjacent √ (3) √ (3) Utilizes existing ETC infrastructure for traffic data collection. Relatively expensive. Vehicles to be detected require a tag be installed.

√(1) - When used in pairs.
√(2) - Limited.
√(3) - With additional equipment at ETC locations.

Also, identification of diesel vehicle percentages cannot be obtained from typical vehicle classification data collection methodologies. In the absence of diesel classification capabilities, diesel vehicle percentages may be obtained from the USEPA's MOBILE emission factor model or from state agencies which typically maintain the diesel vehicle percentages based on vehicle registration data. If appropriate local data are not available, the default MOBILE data, which is based upon national data, can be used as estimations for diesel classification.

Updated: 6/28/2017
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