Final Draft

August 4March 1, 2005

ANSI/ANS-3.11-2005

AMERICAN NATIONAL STANDARD FOR DETERMINING

METEOROLOGICAL INFORMATION AT NUCLEAR FACILITIES

AugustMarch, 2005

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Contents Section Page

1.Scope .........................................................................................................1

2.Definitions.....................................................................................................1

3.Meteorological Monitoring System................................................................23.1 Basic Meteorological Measurements....................................................23.2 Supplemental Meteorological Measurements (Site Specific).............433.3 Remote Sensing Technologies............................................................53.4 Sources of Other Surface Observations...............................................53.5 Meteorological Observation Towers...................................................653.6 Meteorological Monitoring for Stability Class Determination................6

4.Siting of Meteorological Observation Instruments.......................................874.1 Overview............................................................................................874.2 Topographic Effects...........................................................................874.3 Instrument Orientation..........................................................................94.4 Optional Site Selection Techniques...................................................10

5.Data Acquisition..........................................................................................105.1 Recording Mechanisms......................................................................105.2 Sampling Frequencies......................................................................1105.3 Data Processing.................................................................................11

6.Data Base Management.............................................................................126.1 Site Data Base(s).................................................................................126.2 Data Validation...................................................................................1326.3 Data Substitution..................................................................................136.4 Data Recovery Rates.........................................................................1436.5 Data Archiving......................................................................................146.6 Data Reporting.....................................................................................14

7.System Performance...................................................................................147.1 System Accuracy...............................................................................1547.2 System Calibrations...........................................................................1547.3 System Protection, Maintenance, and Service..................................1657.4 Quality Assurance Program and Documentation.................................16

8.References..................................................................................................21

Tables

Table 1 Minimum System Accuracy and Resolution Requirements...17Table 2 Frequency Distribution of Wind Direction,

Wind Speed and Stability Class .......................................... 19..................................................................................................

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Exhibits

Exhibit 1 Method for Calculating System Accuracy..............................20

Bibliography ..............................................................................................42

AppendicesAppendix A Supplemental Meteorological Measurements.......................26Appendix B Meteorological Tower Siting Considerations

in Complex Terrain................................................................30Appendix C Meteorological Monitoring for Stability Class

Determination........................................................................31

Appendix D Optional Site Selection Techniques......................................34Appendix E Guidelines for Performing Wind Computations.....................35Appendix F Recommended Calibration Practices...................38

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AMERICAN NATIONAL STANDARD FOR DETERMINING METEOROLOGICAL INFORMATION AT NUCLEAR FACILITIES

FOREWORD(This Foreword is not a part of the American National Standard for Determining Meteorological Information at Nuclear Facilities, ANSI/ANS-3.11-2005, but is included for information purposes only.)

Meteorological data collected at nuclear facilities play an important role in determining the effects of radiological effluents on workers, facilities, the public, and the environment. Accordingly, meteorological program design is normally based on the needs and objectives of the facility and the guiding principles for making accurate and valid meteorological measurements. American National Standard for Determining Meteorological Information at Nuclear Power Sites, ANSI/ANS-2.5, was issued in 1984 to address nuclear power facility meteorological data acquisition programs. ANSI/ANS-2.5 was referenced by proposed Revision 1 to Regulatory Guides 1.23. However, ANSI/ANS-2.5 was, however, narrowly focused on commercial nuclear power plant siting considerations, and did not provide much guidance on meteorological data application from startup to operations to decommissioning (i.e., life cycle).

In 1996, the Nuclear Utility Meteorological Data Users Group (NUMUG) and the Department of Energy (DOE) Meteorological Coordinating Council (DMCC) undertook comprehensive reviews of the applicability of ANSI/ANS-2.5 and recommended major refinements in the following areas:

Operational data applications (especially emergency preparedness) in addition to siting applications;

Availability of guidance for both public and private sector entities; Life cycle considerations of meteorological monitoring systems; Addressing the need to monitor multiple locations to acquire sufficient

data for models to characterize three-dimensional flows in regions of complex terrain; and,

Inclusion of state-of-the-art meteorological monitoring equipment, including remote sensing instrumentation.

The meteorological data that are acquired, according to ANSI/ANS-2.5 principles, are primarily used in supporting licensing applications of commercial nuclear power plants. More common operational applications to support protection of the health and safety of site personnel and the public, such as emergency preparedness consequence assessments and environmental compliance analyses, were not addressed, since these programs had not fully matured at that time. Meteorological data required to support consequence assessments associated with emergency response differ significantly from the archived data used for climate characterization,

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environmental impact assessment, and compliance analysis purposes, in that data must be available in real-time. Real-time meteorological data availability may require significant upgrades to existing monitoring systems to limit data loss, and to focus attention on the diurnal and seasonal effects that complex terrain, if present, have on the meteorological wind fields (and therefore plume trajectory) in the region of transport. Nuclear facilities in the public sector, non-regulatory domains of the Department of Energy and the Department of Defense (DoD), were not represented in ANSI/ANS-2.5. Government agencies resorted to issuing their own technical guidance (such as Environmental Regulatory Guide for Radiological Effluent Monitoring and Environmental Surveillance, DOE EH-0173T). The need to develop a standard that was also applicable to the public sector was enhanced by the recent DOE initiative, through its Technical Standards Program (TSP), which set a goal of operating DOE facilities under voluntary standards by 2000, in compliance with the Federal guidance contained in the Office of Management and Budget's circular OMB-119A.

Meteorological data monitored at public sector nuclear facilities are used for:

(1) routine radiological and chemical release consequenceanalyses;

(2) real-time consequence assessments of accidental releases of radiological and chemical species; and,

(3) potential environmental impacts resulting from design basisaccidents from projected new facilities or from modifications toexisting facilities.

The use of meteorological data can also play an important role in various types of environmental, decontamination and decommissioning, air quality, and engineering studies. Other uses of meteorological data include assessments of environmental remediation activities, industrial hygiene, construction, and waste management. A comprehensive meteorological monitoring system requires instrumentation that will meet the programmatic purposes for which it is intended.

Meteorological measurements are most commonly taken with in situ sensors that are mounted on towers and are directly in contact with the atmosphere. Additionally, atmospheric properties can be inferred with "remote" sensors, which emit or propagate electromagnetic or acoustic waves into the atmosphere. The criteria for upgrading a sensor include improved accuracy, durability, dependability, or a decrease in required maintenance that would increase the level of data recovery and cost effectiveness of the measurement system while maintaining or improving appropriate measurement capabilities. When it becomes necessary to replace, upgrade, or supplement the meteorological monitoring system equipment, the most effective technology available which is appropriate to meet the objectives is normally employed. In

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the case where a new type of sensor replaces an existing sensor, a demonstration of the effectiveness of the new sensor is necessary before the replacement is completed (see ASTM D4430-96, Standard Practice for Determining the Operational Comparability of Meteorological Measurements).

ANSI/ANS-3.11 (2000) was developed to address life cycle issues associated with nuclear facility meteorological monitoring programs. This standard was also developed to address technological advances for in situ and remote sensing instrumentation to monitor meteorological parameters (e.g., sonic anemometers, lidar, Doppler sodar, radar wind profilers, etc.), modifications in analytical requirements, and other considerations. The aforementioned remote sensing systems provide the nuclear facility meteorologist, or meteorological program manager, with additional means to acquire sufficient data to characterize the three-dimensional wind field in the vicinity of the facility and within the region of transport. ANSI/ANS-3.11 (2000) also provides additional information on instrument siting and measurement issues, based on the results of wind tunnel studies, which have given insight into the aerodynamic effects of obstacles on a local wind field.

ANSI/ANS-3.11 (2000) was designed with sufficient depth and breadth to address the needs of the entire meteorological monitoring community associated with all nuclear facilities nationwide, including commercial electric generating stations and nuclear installations at federal sites, ranges, and reservations. It does not attempt to define the exact monitoring criteria for every possible type of facility or site environment. It does identify the minimum information that comprise a successful monitoring program but dictates that the details of such programs be delegated to subject matter expert meteorologists who analyze each particular site and application in order to arrive at an acceptable program for that particular application.

The ANSI/ANS-3.11 working group was reconstituted in February 2003 to evaluate the currency of the 3-year old standard, and determine whether it should be simply recertified on its February 18, 2005 sunset, or whether it needed to be updated to account for new reference standards, advances in ex situ and in situ instrumentation, advances in data management equipment and techniques, advances in meteorological program management, integration with facility programs (e.g., configuration management), and other considerations. The working group unanimously determined to update the standard and ANSI/ANS-3.11 (2005) is a result of this work. In 2008, the ANSI/ANS-3.11 working group will again re-evaluate the actions to be taken on the standard prior to its 5-year sunset.

The ANSI/ANS-3.11 (2005) Working Group of the Standards Committee of the American Nuclear Society had the following membership:

S. Marsh, Co-Chairman, Southern California Edison CompanyC. Mazzola, Co-Chairman, Shaw Environmental & Infrastructure, Incorporated

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M. Abrams, ABS Consulting, IncorporatedR. Addis, Westinghouse Savannah River CompanyD. Bailey, Environmental Protection AgencyR. Banta, National Oceanic and Atmospheric AdministrationR. Baskett, University of CaliforniaR. Baxter, T & B Systems, IncorporatedT. Bellinger, Illinois Emergency Management AgencyB. Carson, Pennsylvania Power & Light CompanyK. Clawson, Air Resources Laboratory, Field Research DivisionJ. Crescenti, Florida Power & Light CompanyM. Duranko, First Energy CorporationJ. Fairobent, National Nuclear Security AdministrationP. Fransioli, Bechtel SAIC Co., LLCC. Glantz, Pacific Northwest National LaboratoryR. Harvey, Nuclear Regulatory CommissionJ. Holian, Science Applications International CorporationJ. Irwin, National Oceanic and Atmospheric AdministrationD. Katz, Climatronics CorporationS. Krivo, Environmental Protection AgencyM. Parker, Westinghouse Savannah River CompanyD. Pittman, Tennessee Valley AuthorityD. Randerson, Air Resources Laboratory, Special Operations & Research DivisionW. Schalk, Air Resources Laboratory, Special Operations & Research DivisionR. Swanson, Climatological Consulting CorporationG. Vasquez, Department of EnergyS. Vigeant, Shaw Environmental & Infrastructure, IncorporatedP. Wan, Bechtel Power CorporationK. Wastrack, Tennessee Valley AuthorityR. Yewdall, Public Service Electric & Gas Company

Subcommittee ANS-25, Reactor Operations, had the following membership at the time of its approval of this standard:

Carl Mazzola, ChairmanC. CostantinoK. HansonW. LettisJ. LitehiserS. MarshM. McCannR. NobleD. OstromD. L. SiefkenR. SpenceJ. Stevenson

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The Nuclear Facility Standards Committee (NFSC) had the following membership at the time of its approval of this standard:

D.J. Spellman, Chairman

J. Brault..............................................Westinghouse Savannah River CompanyC.W. Brown............................................Southern Nuclear Operating CompanyR.H. Bryan, Jr..........................................................Tennessee Valley AuthorityH. Chandler..............................................................U.S. Department of EnergyM.T. Cross.......................................................Westinghouse Electric CompanyT. Dennis.............................................................................................. IndividualD.L. Eggett...............................................................................AES EngineeringR. Hall...........................................................Exelon Generation Company, LLCP.S. Hastings ..................................................................................Duke EnergyR. A. Hill................................................................................GE Nuclear EnergyN. P. Kadambi..........................................U.S. Nuclear Regulatory CommissionM. La Bar..................................................................................General AtomicsE. Lloyd................................................................................Exitech CorporationJ.E. Love..................................................................Bechtel Power CorporationJ. F. Mallay...............................................................................Framatome ANPC. A. Mazzola....................................Shaw Environmental & Infrastructure, Inc.R. McFetridge..........................................Westinghouse Electric Company, LLCC.H. Moseley, Jr...................................................................................IndividualW. B. Reuland................................................Mollerus Engineering CorporationM. Ruby ..............................................................................Constellation Energy

J. C. Saldarini......................................................................Tetra Tech FW, Inc.R. E. Scott................................................................................Scott EnterprisesS. L. Stamm..................................................................Shaw Stone & Webster J. D. Stevenson.......................................................J.D. Stevenson ConsultantsC. D. Thomas........................................IndividualDuke Engineering & ServicesJ.A. Werenberg......................................................Southern Company ServicesM.J. Wright...............................................................Grand Gulf Nuclear Station

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1.0 SCOPE

This document provides criteria for gathering and assembling meteorological information at commercial nuclear electric generating stations, Department of Energy (DOE)/National Nuclear Security Administration (NNSA) nuclear facilities, and other national or international nuclear facilities. Meteorological data collected, stored, and displayed through implementation of this standard are utilized to support the siting, operation, and decommissioning of nuclear facilities. The meteorological data are employed in determining environmental impacts, consequence assessments supporting routine release and design basis accident evaluations, emergency preparedness programs, and other applications.

2.0 DEFINITIONS

Calm. Any measured wind speed below the starting threshold of the wind speed or direction sensor, whichever is greater.

Damped Natural Wavelength. A characteristic of a wind vane empirically related to the delay distance and the damping ratio [11ASTM 2002(4), D5366].

Damping Ratio. Ratio of the actual damping, related to the inertial-driven overshoot of wind vanes to direction changes, to the critical damping, the fastest response where no overshoot occurs.

Delay Distance. The distance that air flowing past a wind vane moves while the vane is responding to 50 percent of the step change in the wind direction [11ASTM 2002(4), D5366].

Instrument System. All components from sensor to and including data recording and display. (Herein referred to as “system”)

Mesoscale. The scale of atmospheric phenomena having overall horizontal dimensions from a few kilometers to a several hundred kilometers.

Sensor Accuracy. The accuracy of the sensor used to make a meteorological measurement. Sensor accuracy can be based on manufacturer specifications, test results, or direct comparison with a standard (i.e., calibration).

Shall, Should, and May. The word “shall” is used to denote a requirement; the word “should” is used to denote a recommendation; and the word “may” is used to denote permission, neither a requirement nor a recommendation.

Sigma Phi. The standard deviation of the vertical wind direction fluctuations.

Sigma Theta. The standard deviation of the horizontal wind direction.

Stability Class. A classification of atmospheric stability, or the amount of turbulent mixing in the atmosphere and its effect on effluent dispersion.

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Starting Threshold. The minimum wind speed above which the measuring instrument is performing within its minimum specification.

Survival Speed. The maximum wind speed at which the sensor can operate properly.

System Accuracy. The extent to which results of a calculation or the readings of an instrument approach the true values of the calculated or measured quantities. System accuracy encompasses all components of the system (sensor, data processing equipment, computer, calibrations, etc.). System accuracy is compared with applicable requirements to evaluate the adequacy of the monitoring program.

System Calibration. The process of validating the output of an observing system against known reference observations or standards.

Traceability. The documented ability to trace the history, application, or location of an entity. In a calibration sense, traceability relates measuring equipment to national or international standards, primary standard, basic physical constants or properties, or reference materials. In a data collection sense, it relates calculations and data generated throughout the process back to the requirements for quality for the project [2].

Wind Direction. The direction from which the wind is blowing. Wind direction isdata should be reported in degrees azimuth measured clockwise from true north and ranging from 0 ° to 360° (e.g., north is 0° or 360°, east is 90°, etc).

Wind Speed. The ratio of the distance covered by the air to the time taken to cover it.

3.0 METEOROLOGICAL MONITORING SYSTEM

The meteorological monitoring system design shall be deployed to adequately meet site requirementsbased on the needs and objectives of the facility and the guiding principles for making accurate and valid meteorological measurements. A basic meteorological monitoring program shall consist of measurements of wind speed, wind direction, air temperature, including ambient and the difference between two vertical levels on a tower, precipitation, and any combination of additional measurements necessary to determine stability class. Supplemental meteorological measurements involving more sophisticated monitoring approaches or monitoring at more than one location should be deployed where appropriate to adequately meet site data requirements.

3.1 Basic Meteorological Measurements

3.1.1 Wind Speed

Wind speed shall be measured with a sensor suitable for continuous, accurate operation. Several types of devices are available to measure wind speed including cup, propeller, and sonic anemometers. Wind speed measurements shall be made to meet the criteria for accuracy and resolution shown in Table 1. Wind speed sensors shall have a starting threshold of less than 0.5 ms-1 (1.1 mph) and shall operate over the expected range of wind speed conditions, based on regional climatology which is at least 22 ms -1 (50 mph) for most locations.

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The survival speed should be approximately twice the normal operating range. The standard vertical location or height for wind speed measurements should be at 10 m above ground level. Additional measurements should be made at the level representative of the most probable atmospheric release height applicable to activities involving radioactive and hazardous chemical materials, considering the input data requirements of dispersion models being used by the facility. In some cases, wind speed measurements may be taken at other levels to meet specific requirements of the meteorological monitoring program. Additional information on wind speed measurements can be found in [5, 8, 9, 19, 210, 4039].

3.1.2 Wind Direction

Wind direction shall be measured with a sensor suitable for continuous, accurate operation. Wind vanes are used to make measurements of the horizontal wind direction although bi-directional wind vanes and sonic wind sensors may be used to measure both the horizontal and vertical wind direction. Wind direction measurements shall be made to meet the criteria for accuracy and resolution defined in Table 1. Wind vane sensors used for sigma theta (sq) or sigma phi (sf) applications shall have a damping ratio between 0.4 to 0.7 inclusive, at a 10° azimuth offset and the damped natural wavelength shall be less than 10 m. Wind direction sensors shall have a starting threshold of less than 0.5 ms -1 (1.1 mph) and shall operate over the expected range of wind speed conditions, which is at least 22 ms -1 (50 mph) for most locations. The survival speed should be approximately twice the normal operating range. The standard vertical location or height for wind direction measurements should be at 10 m above ground level. The criteria for determining the appropriate monitoring heights for wind direction are the same as those used for wind speed (see Section 3.1.1). Wind direction sensors shall be aligned such that the data collected will be referenced to true geographic north. Additional information on wind direction measurements can be found in [5, 8, 9, 19, 210, 4039].

3.1.3 Temperature

Ambient air temperature shall be measured with a sensor suitable for continuous, accurate operation over the range of expected temperature extremes based on regional climatology. If applicable to program requirements, aAmbient temperature measurements and vertical temperature difference measurements (i.e. delta temperature) shall be made (if applicable to program requirements) to meet the criteria for accuracy and resolution defined in Table 1. The monitoring levels for delta temperature shall be spaced such that the profile is representative of, and characterizes the magnitude of, atmospheric turbulence at any potential release height(s) from the affected facility. A typical pair of sensor heights is 60 m and 10 m above ground level.

Temperature sensors shall be mounted in protective shields to minimize the adverse influences of thermal radiation and precipitation. Shields shall provide at least natural ventilation of the sensor. Mechanically aspirated shields with internal airflow rates between 3 ms-1 (6.7 mph) and 10 ms-1 (22.4 mph) shall be used when making delta temperature measurements for atmospheric stability determination purposes. The shield inlet should be a distance at least one and one half times the tower horizontal width away from the nearest point on the tower. The shield inlet shall be pointed either downward or toward the north in the Northern Hemisphere, or either downward or toward the south in the Southern Hemisphere. Additional information on ambient temperature measurements can be found in [11].

3.1.4 Precipitation3

The measurement of precipitation shall be determined by direct measurements and shall be made to meet the criteria for accuracy and resolution contained in Table 1. Three types of precipitation measuring devices suitable for meteorological monitoring programs are the tipping bucket rain gauge, weighing rain gauge, and storage gauge. These Ggauges mayshould be equipped, where necessary, with heater devices to melt frozen precipitation or with an anti-freeze solution, using a system appropriate for the location, and operated to minimize underestimation due to evaporation caused by the heater device. Additional information on rain gauges can be found in [19, 4039].

3.2 Supplemental Meteorological Measurements (Site Specific)

In addition to the basic meteorological measurements discussed in Section 3.1, one or more supplemental meteorological measurements maycould be necessary to address site-specific concerns such as characterization of atmospheric motions in complex terrain, ocean-land interfaces, building wake effects, etc., which can potentially affect dispersion of effluents and airflow trajectories. In addition, special applications maycould involve the need to monitor meteorological parameters on or below the soil surface. These supplemental measurements may include atmospheric moisture, solar and net radiation, barometric pressure, mixing height, soil temperature, soil moisture, lightning detection, and those parameters measured using remote sensing technologies. Brief discussions of these supplemental meteorological measurements follow, with more detailed discussions provided in Appendix A.

3.2.1 Atmospheric Moisture

Atmospheric moisture is determined from measurements of dew-point temperature, wet-bulb temperature, or relative humidity. Dew-point temperature, wet-bulb temperature, and relative humidity measurements shall be made to meet the criteria for accuracy and resolution defined in Table 1. If implemented, the atmospheric moisture measurement system shall be designed to operate over the range of 10%-95% relative humidity. Additional information on the measurement of atmospheric moisture is found in [4, 19, 210].

3.2.2 Solar and Net Radiation

Both solar and net radiation may be used as part of an atmospheric stability classification scheme (see Section 3.6.4) or to monitor solar insolation. When performed, solar or net radiation measurements shall be made to meet criteria for accuracy and resolution contained in Table 1. Any solar radiation sensor shall be located so that it is unobstructed from the sun at all daylight times of the year and it is located away from objects likely to reflect sunlight or otherwise influence measurements. Additional information on the measurement of solar and net radiation is available in [19, 4039].

3.2.3 Barometric Pressure

When performed, measurements of barometric pressure shall meet the criteria for accuracy and resolution contained in Table 1. The barometric pressure measurement system shall be designed to operate over the expected range of barometric pressures for the site based on regional climatology [equivalent to sea level pressures of 940 to 1050 hectopascals (940 to 1050 millibars)]. Additional information on barometric pressure measurements can be found in [6, 19, 21, 4039].

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3.2.4 Mixing Height

Mixing height (or mixing depth) is a key parameter in many atmospheric contaminant dispersion regimes because it defines the upper boundary of the volume through which contaminants are capable of being mixed. During daytime, mixing in the convective boundary layer (CBL) or mixed layer is driven predominantly by surface heating, and in late morning the CBL may grow rapidly from about 300 m (984 ft) to roughly 1-2 km (3280-6560 ft) over a period of less than an hour. When performed, methods for measuring mixing height shall be able to operate within these ranges. A more detailed discussion of the many issues concerning the measurement of mixing height is given by [15] and [19].

The most common measurement method for determining mixing height during the daytime involves establishing the inversion height on an atmospheric temperature sounding by a radiosonde, tethersonde or other sounding method [28]. Where an onsite measurement of mixing height is not available, National Weather Service (NWS) mixing height information from a nearby representative site may be employed. In addition, estimates based on climatological studies of radiosonde data may be acceptable for long term average modeling purposes [254]. However, caution is recommendedshould be exercised when using climatological estimates of mixing height since the limitations in spatial, temporal, and vertical resolution will constrain accuracy. Mixing height information maycan also be obtained using remote sensing technology such as sound detection and ranging (SODAR)sodar and radio acoustic sounding system (RASS).

3.2.5 Soil Temperature

The measurement of soil temperature can be important for establishing puddle evaporation from ground-level chemical spills or releases, modeling applications, or for determining the influence of soil temperature on the height of the convective boundary layer. When performed, soil temperature measurements shall be made to meet the criteria for accuracy and resolution shown in Table 1. Relative diurnal and seasonal variations in soil temperatures are described in [354].

3.2.6 Soil Moisture

The measurement of soil moisture can be used for characterizing environmental conditions for the underground storage of nuclear materials, gasoline or fuels, or hazardous materials, and for increasing the understanding of the behavior of chemical spills. The soil moisture content can be very important for determining the surface heating and the mixing height (see Section 3.2.4). When performed, soil moisture measurements shall meet the criteria for accuracy and resolution shown in Table 1.

3.3 Remote Sensing Technologies

In situ measurements discussed above may also be augmented by measurements from remote sensing technologies. Two classes of remote sensing technology are:

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1. Widely deployed systems, such as sodarsodar,, radar wind profilers, NEXRAD, microwave radiometers and satellite data that can be included in operational monitoring programs to determine the wind field, and transport and dispersion of effluents; and,

2. Less widely deployed systems that could be available for large intensive field programs

and site surveys (i.e., specialized radars and lidars).

An important functional difference between remote sensing systems is "active” versus “passive". Active remote sensors transmit a signal that interacts with the medium of propagation and returns to a receiver. Examples of active remote sensing techniques include lidars, radars, and sodars that transmit pulses or continuous signals of light, radio waves (microwaves), or sound, respectively, which scatter off of inhomogeneities or particles in the atmosphere and return to the receiver. Passive systems, such as radiometers, do not transmit a signal, but measure natural emissions from surfaces, atmospheric layers, or other atmospheric phenomena. Additional information is available in [16, 19, 210, 287, 3029].

3.4 Sources of Other Surface Observations

Meteorological data from additional monitoring locations shouldmay be used to supplement basic meteorological measurements when needed to obtain realistic estimates of atmospheric transport and dispersion at distances from several kilometers to several tens of kilometers from the release location. Meteorological data from such supplementary monitoring locations are especially important for sites located in a complex terrain environment or near the ocean or large lakes where land/sea breezes are prevalent. Supplementary data mayshould be obtained from spatially representative meteorological stations providing data of adequate quality. When such data are not available from the site monitoring network, data from other monitoring networks may be used.

3.5 Meteorological Observation Towers

The following are acceptable approaches pertaining to meteorological observation towers. Additional considerations for tower installations in areas of complex terrain are discussed in Appendix B.

3.5.1 Fixed Meteorological Tower

A meteorological monitoring program shouldmay have one or more fixed meteorological observation towers. Guidance on installing and maintaining a stable and reliable tower structure can be found in [354] or other appropriate civil or structural engineering sources. A back-up power supply system mayshould be used to avoid extended data losses. If meteorological monitoring measurements cannot be made from a dedicated tower and must be taken on a multi-purpose tower, special care shouldshall be taken when siting meteorological instruments to avoid flow obstructions from transmitter dishes or other equipment installed on that tower (See Section 4.3.1).

3.5.2 Lightning Protection

Lightning protection systems mayshould be installed on meteorological towers to minimize potential electrical surge damage. The need for a lightning protection system is site dependent. The lightning protection system deployed should be appropriate given the amount of

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atmospheric electrical activity that is characteristic of the site based on regional climatology. Lightning protection systems shall comply with applicable design codes.

3.5.3 Extreme Phenomena

Facility needs and objectives maycould specifically require the availability of real-time onsite meteorological measurements immediately after extreme but rare environmental conditions. In that case, consideration should be given to installing a secondary or back-up meteorological monitoring and data acquisition system that will survive extreme phenomena such as high wind speeds (e.g., hurricane force), ice storms, sand storms, etc. may be required If hardware options are limited by available technology, more robust sensors with less sensitivity may be considered for a secondary system, so that the system can temporarily provide minimum required measurements after the extreme events. A surface (i.e., 10 m) monitoring level on a platform independent of the primary system may be used.

3.6 Meteorological Monitoring for Stability Class Determination

The determination of the stability of the atmosphere is an important consideration for atmospheric transport and dispersion modeling at nuclear facilities. Stability categories or classifications (e.g., Pasquill-Gifford Stability Classes, see [19, 265] for a detailed description) have been used to determine atmospheric stability for use in Gaussian transport and dispersion models to estimate consequences, unless dispersion model input requires a more sophisticated parameterization of atmospheric mixing.

The determination of the appropriate method to be used for atmospheric stability classification shall be developed by a qualified meteorologist based on the intended application of the information. If stability classification schemes are used, they maycould need adjustment based on local influences such as surface roughness or terrain. The methodology shouldshall be documented. The most common methods are summarized in the following subsections with a more detailed discussion provided in Appendix C. The order of the following subsections is not intended to imply any preference.

3.6.1 Delta Temperature/Delta Height (Delta T/Delta Z)

The difference in temperature with height (see Section 3.1.3) maycan be used to infer the stability classification of the lower portion of the planetary boundary layer (PBL) under clear nighttime conditions. However, this method may cannot always accurately determine the stability classification under daytime conditions when either near-neutral or superadiabatic conditions exist. Therefore, an additional means of characterizing daytime stability classes should be considered when using this method.

3.6.2 Monin-Obukhov Length

The Monin-Obukhov length can may be used very reliably to characterize the stability of the PBL [354]. However, the instrumentation required to obtain the necessary fast response wind, temperature, and humidity measurements are typically research grade. As meteorological instrumentation advances, the measurements necessary to obtain the Monin-Obukhov length maymight soon become practical for the nuclear industry.

3.6.3 Wind Speed, Cloud Cover, and Ceiling Height7

Stability classification maycan be inferred through the use of the measurement of wind speed, percentage of opaque cloud cover, and the cloud ceiling height. Estimates of the net solar radiation are made with the cloud information and expected solar angle for the facility geographic coordinates, based on time of day (hour), and time of year (date).

3.6.4 Solar Radiation and Delta Temperature

The use of the solar radiation/delta temperature (SRDT) method [19] is similar in concept to the use of wind speed, opaque cloud cover, and ceiling height. The major difference is that the measurement of solar radiation replaces and generally improves upon the cloud cover and cloud ceiling information. The combination of solar radiation and wind speed during the day and a delta temperature measurement between 2 m and 10 m and wind speed measurement at night canmay be used to infer the stability classification.

3.6.5 Standard Deviation of the Vertical Wind Direction Fluctuations and Wind Speed

The standard deviation of the vertical wind direction fluctuations (sf) may be used in combination with the mean scalar wind speed to categorize atmospheric stability. Since vertical wind fluctuations vary as a function of measuring height, surface roughness, stability, and in response to gravity waves, careful siting balance and placement of the sensor is extremely important (see Section 4.0). These sensors need to be statically balanced to operate correctly, which requires careful installation and maintenance.

3.6.6 Standard Deviation of the Horizontal Wind Direction Fluctuations and Wind Speed

The standard deviation of the horizontal wind direction fluctuations (sq) may be used in combination with the mean scalar wind speed to categorize atmospheric stability. As with the measurement of the vertical wind direction, sensor placement should be carefully consideredexercised (see Section 4.0).

4.0 SITING OF METEOROLOGICAL OBSERVATION INSTRUMENTS

4.1 Overview

Siting of meteorological monitoring stations, and selecting instrument exposures, shouldshall be a case-by-case process based on the program purposes and objectives, local meteorological characteristics (including influences of topography and structures), and characteristics of the meteorological sensors and data recording and processing equipment.

Meteorological monitoring programs should be reviewed at least annually for conformance to siting requirements, evolving program objectives, changing regulatory requirements, facility operating status, and equipment capabilities. Monitoring station relocation or measurement method changes shall not be made without careful consideration of these variables. Site-specific meteorological characterizations can take three to five years or more of consistent measurements.

Site characteristics shall be documented and shall include:

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Identification of the location using a geographic coordinate system; Sensor heights above ground level at the site or facility; Special siting factors (e.g., distance to obstacles); and, Description of the measuring and data recording equipment sensor make,

model, and serial number.

4.2 Topographic Effects

Local topographical characteristics and surface features can sufficiently influence atmospheric transport and dispersion to warrant consideration when planning or evaluating a monitoring program. The choice of monitoring site location(s) and measurement(s) shouldshall be based on the need to acquire sufficient data to satisfy the monitoring program objectives. The primary monitoring site shouldshall be representative of transport pathways.

4.2.1 Flat Terrain Sites

A single monitoring station located an adequate distance (see Section 4.3.1) away from obstacles such as buildings, cooling towers, large trees, ponds, and large paved areas isshould be adequate to provide spatially representative site-specific meteorological information in flat terrain. Wind measurements shall be made at least at 10 m (33 ft) above ground level. Additional wind measurements at higher levels mayshould be used to characterize dispersion from release heights greater than about 30 m (99 ft). At or at sites that have nocturnal surface-based temperature inversions, and that require model inputs, additional wind measurements shall be used to characterize dispersiondepending on model input requirements.

4.2.2 Complex Terrain Sites

4.2.2.1 Mountain (Complex-Land) Sites

For transport and dispersion modeling and various types of airflow studies, areas with terrain elevations as high as or higher than the source release height are considered complex terrain. The terrain influences canmay create site specific dispersion characteristics that require additional monitoring than is necessary at flat terrain sites.

The additional required monitoring may be made at greater heights above ground level than the standard 10-meter level, and/or at additional monitoring sites. In areas of airflow channeling, at least one additional monitoring location is needed to determine the atmospheric dispersion along the airflow pathway toward the most important potential receptor. The additional monitoring stations may require only 10-meter level measurements if the vertical profile is adequately represented by the primary monitoring station. This monitoring effort may include atmospheric tracer studies designed and implemented to identify air flow trajectories and dispersion characteristics.

In complex topography, airflow can vary significantly in both the horizontal and vertical dimensions. In such cases, adequate representation of the airflow may require deployment of a mesoscale network of meteorological towers (i.e., mesonet) or remote sensing devices (see Section 3.3) at sufficiently fine spacing to sample flows or flow features relevant to contaminant transport.

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4.2.2.2 Shoreline (Complex-Water) Sites

Facilities located near large water bodies can be influenced by sea or lake breezes, land breezes, wake effects during onshore airflow, and long-range transport of stable plumes over water. An important feature of shoreline sites is the shallow thermally-induced internal boundary layer (TIBL) at the coastline that deepens with increasing distance away from the water body (see reference [15]).

The primary meteorological tower shall be located and be of sufficient height so that at least one measurement level is within the TIBL. Supplemental measurements (see Section 3.2) are advisable to establish the appropriate height for the primary tower, and to determine the mesoscale meteorology near the facility. Meteorological buoys and remote sensing techniques such as Doppler sodars, radar wind profilers, and satellite imagery may be needed to supplement meteorological tower measurements to identify periods of onshore and offshore airflow and provide measurements at appropriate heights for dispersion calculations.

4.3 Instrument Orientation

Monitoring site locations shall be chosen to minimize influences of obstructions and external factors that adversely affect the representativeness of the measurements.

4.3.1 Aerodynamic Effects of Obstacles

Wind measurements shall be made at locations and heights that avoid airflow modification by obstructions such as large structures, trees, or nearby terrain with heights exceeding one-half the height of the wind measurement. The separation between the wind sensor and the obstruction should be ten times the obstruction height. Measurements made with less separation may be adversely influenced by air flow changes caused by the obstructions. The separation can be reduced to about five times the height for objects with cross-sectional dimensions less than about one meter, such as utility poles or isolated small trees. Detailed information on siting wind stations and making the measurements is available in [9, 19].

Wind sensors should be located on top of the measurement tower or mast where possible to reduce airflow modification and turbulence induced by the supporting structure itself. Since the tower structure can affect downwind measurements, sensors on the side of a tower should be mounted at a distance equal to at least twice the longest horizontal dimension of the tower (i.e., the side of a triangular tower, or the diameter of a circular mast or pole). The sensors should be on the upwind side of the mounting object in areas with a dominant prevailing wind direction. In areas with two distinct prevailing wind directions (e.g., mountain valley), the sensors should be mounted in a direction perpendicular to the primary two directions.

4.3.2 Diabatic Effects

Unless dictated by purposes of the monitoring program, air temperature and relative humidity measurements shall be made in such asa way as to avoid air modification by heat and moisture sources, such as ventilation sources, water bodies, or large parking lots. To this end, the tower should not be located on or near man-made surfaces such as concrete, asphalt, etc. Detailed information on siting temperature and vertical temperature difference stations and making the measurements is available in Section 3.1.3 and in [265].

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4.4 Optional Site Selection Techniques

Supplemental information should be obtained for monitoring programs faced with complex terrain or complicated man-made structural environments before committing the resources to monitoring station locations. Such options may include remote sensing, tracer studies, numerical modeling, physical modeling (i.e., wind tunnels) and other techniques. Remote sensing equipment may be used to obtain wind and turbulence measurements from heights greater than 60 meters above ground level without using tall towers with fixed sensors. See Appendix A for additional discussions of remote sensing techniques.

5.0 DATA ACQUISITION

5.1 Recording Mechanisms

Meteorological monitoring systems should use electronic digital data acquisition systems housed in a climate-controlled environment as the primary data recording system. The use of a backup recording system (either analog or digital) should be considered for those stations where a high assurance of valid data is needed.

Where analog data recording systems are used, wind speed and wind direction should be recorded on continuous trace strip charts. Because of continuously fluctuating sensor output, wWind speed and direction should not be recorded on multipoint charts. However, other variables may be recorded on multipoint charts. Analog charts should provide adequate resolution in the data reduction process to achieve the system accuracy given in Table 1.

The use of an analog data recording system as a backup system (or a video graphics recorder as either a primary or backup recording system) can provide an advantage in the early identification of equipment problems (e.g., early wind direction sensor potentiometer failure can be identified as “spikes” on a smooth data trace). Time-averaged digital data can mask such equipment problems that would otherwise be evident in a time-series shown graphically. A computer-based statistical review of incoming digital samples may also be useful in identifying equipment problems.

5.2 Sampling Frequencies

For digital data acquisition systems, averaged values should be calculated using at least 30 samples at intervals no longer than 60 seconds spaced equally over not less than a 10-minute period. For multi-point recorders, the sampling rate per channel should be at least once per minute and the selected chart speed should permit adequate resolution of the data.

Standard deviation values of selected meteorological parameters should be calculated using at least 180 equally spaced samples. For an hourly standard deviation value, the data should be sampled at least once every 20 seconds. If the data are first combined into 15-minute averages, then the data should be sampled at least once every 5 seconds to provide 180 samples during each of the 15-minute periods, even if the four 15-minute values are later combined into an hourly value. Similarly, if the data are first combined into 10-minute averages, then the data should be sampled at least once every 3.3 seconds to provide 180

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samples during each of the 10-minute periods, even if the six 10-minute values are later combined into an hourly value.

5.3 Data Processing

In order to be able to identify rapidly changing meteorological conditions for use in performing emergency response dose consequence assessments, either 10-minute or 15-minute average values should be compiled for real-time display in the appropriate emergency response facilities (e.g., control room, technical support center, and emergency operations facility).1 Other time periods and calculated variables can be displayed depending on the application. The basic data should be compiled into hourly-averaged values for use in historical climatic and dispersion analyses. The hourly-averaged values may be generated by using one 10-minute, or one 15-minute average value per hour (if the same 10-minute or 15-minute period is used each hour), or by averaging all of the 10-minute or 15-minute average values recorded during the hour. In the case of sq, 10-minute or 15-minute values should be combined as described in Appendix E. Hourly maximum wind speed gust values may also be archived for use in establishing wind loading criteria for the design of buildings and other structures.

5.3.1 Wind Data

The wind has both an orientation (i.e., direction) and a magnitude (i.e., speed), and is therefore a vector quantity. However, speed and direction can also be treated separately as scalar quantities. Algorithms for performing both scalar and vector wind computations are presented in Appendix E.

Atmospheric transport and dispersion estimates should be based on the scalar mean wind speed because these estimates are a function of the magnitude and not the direction of the wind vector. In a variable trajectory atmospheric dispersion model or a model that accepts a separate wind speed to estimate transport time, the vector mean wind speed may also be appropriate. The transport wind direction for straight-line Gaussian models should be based on the scalar mean (or unit vector) wind direction. The transport wind direction for variable trajectory atmospheric dispersion models should be based on the vector mean wind direction.

Wind speed and direction measured using anemometers and vanes can be processed into either scalar or vector quantities while Doppler sodars and radar wind profilers, by design, employ vector processing for estimating mean wind speed and direction [9,19].

5.3.2 Other Meteorological Variables

For other meteorological variables (e.g., air temperature, delta temperature, dew point temperature, barometric pressure, solar radiation), hourly averaged values may be determined by averaging samples over the entire hour or by averaging a group of shorter period averages. For precipitation, the hourly value should represent the total amount of precipitation measured during the hour.

6.0 DATA BASE MANAGEMENT

1 Note that the commercial nuclear power industry has typically compiled 15-minute data values for use in their emergency response facilities since the 1979 Three Mile Island accident. However, a more recent ASTM standard, D5741-96, advocates collecting wind data as 10-minute averages. [9]

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6.1 Representative Site Data Base(s)

It is important that every facility with a radiological and/or toxic chemical hazard have a valid, accurate and representative meteorological data base. This data base shall be utilized to evaluate environmental impacts and the consequences of routine and accident radiological releases. The collection of onsite meteorological data provides a more accurate representation of meteorological conditions affecting the transport and dispersion from a specific source than by using meteorological data from a more distant and likely less representative location.

When using meteorological data for licensing or other regulatory purposes, 3-5 years of data areshould be sufficient to ensure that meteorological conditions have been adequately represented for use in transport and dispersion calculations (i.e., temporal representativeness). The years of data should be compared with other local data to ensure they are representative of long-term meteorological conditions (i.e., temporally representative). For proposed future facilities, this shallould consist of at least one year of pre-construction data and two years of pre-operational data. Each year shallould meet or exceed data recovery requirements discussed below. A facility shall continue to collect meteorological data once it becomes operational. These data aremay be used for ongoing impact assessments during facility operation. While the facility is being decommissioned, the continued need for onsite meteorological data should be evaluated based on the remaining hazard footprint. Any major modifications to the meteorological data acquisition system shall not be undertaken without considering the effects on the overall facility data base (see Section 3.0).

6.2 Data Validation

Data validation should begin with a periodic review of the data by personnel experienced in the interpretation of local meteorological conditions and the monitoring program. The data should then be compared with other available representative meteorological measurements from the site region. Finally, a review of the maintenance and calibration records should be undertaken to identify possible operational problem areas.

Data processing should compare measured values to an expected range of values, and checks should be made of selected sequential periods for proper temporal variations. Analog strip charts, if available, may be used as a diagnostic tool for identifying possible problem areas. This screening process should be done at the time the data are collected or shortly after the selection process has been completed. When problems are discovered in the data screening process, they should be corrected prior to the data’s use in any application. In addition, the source of the problem must be identified and corrected.

Data should also be validated by comparing each parameter with other levels on the tower or with data from redundant sensors, if available. If such data are not available, comparisons should be made with another reliable data source (as specified in Section 3.4). The comparison should be performed at random time intervals. The instrumentation at the alternate site should be comparable and representative of the primary tower site before it is considered for use. Special attention should be paid to periods following severe weather conditions, when instruments are under calibration, or when maintenance records indicate

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specific instrument malfunction. Abnormal climatic conditions (e.g., ice, snow, and drought) willcan affect the measurements due to a build up of ice, dust, foreign material, etc., in aspirators and sensors, which will result in the modification of sensor characteristics.

Questionable data periods resulting from the data quality checks should be evaluated by experienced personnel, for the purpose of making decisions on the need to adjust, invalidate and /or replace the questionable data [17, 19]. Micrometeorological trends associated with the site location (e.g., extreme inversions, sea breeze extent and orientation) should be taken into consideration in evaluating questionable data. Synoptic weather maps may be used in this analysis.

6.3 Data Substitution

Some applications require continuous data for the purpose of analyzing consequences. When data from the primary data source are not available, values may be substituted from an alternative source where it has been demonstrated that the alternative data are representative. Except where data comes directly from the primary tower location, the substituted data should not be included in the site database.

Data shall be archived as recorded before the adjustment process begins to ensure original data will be available. If it is necessary to replace site data, one of the following methods should be used in the order shown.

1) If the site location has a multiple level meteorological tower or a backup tower, valid measurements from a redundant sensor at the same level or measurements from another level should be used. If the measurement height is significantly different, adjustments should be made based on vertical profiles of wind speed and wind direction. Site-specific profiles based on at least 3 years of onsite data should be used, if possible.

2) If the missing period is short (i.e., one to two hours), the missing data might be resolved using linear interpolation. If the missing period occurs during the day-night transition period or during a weather event such as a thunderstorm or frontal passage, linear interpolation may not be appropriate.

3) When there are other nearby sites, (e.g., NWS stations, military bases) it may be possible to substitute these data for missing periods. This data substitution technique should only be used when previous studies have confirmed that data for parameters from both sites compare favorably. Differences in instrument thresholds or data collection procedures could make some data from two locations incompatible, even if the sites are representative.

6.4 Data Recovery Rates

Meteorological data recovery for wind speed, wind direction, stability class and delta temperature shall be at least 90% annually [18, 19]. The 90% recovery rate (number of valid hours divided by total number of hours in period) applies to both individual parameters as well as the composite of wind speed, wind direction, and stability class used in the compilation of joint frequency tables. This 90% rate applies to all data sets of wind speed, wind direction and

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stability classes that are used in consequence assessments.

For other parameters (e.g., dew-point temperature, barometric pressure, precipitation), the data recovery rate shall also be at least 90% [19]. This rate should also be maintained for any remote sensing devices.

6.5 Data Archiving

The raw meteorological data, including analog strip charts, if used, shall be retained for a minimum of 5 years and configured with the site records management program per standard computing industry practices. The validated data shall be retained for the life of the facility in hard copy or current state-of-the-art form [19}. The archived data should be hourly averages for annual time periods.

6.6 Data Reporting

Since there are different input requirements for different types of analyses, there is no fixed format that applies to processed meteorological data. Data should be collected chronologically and tabulated according to observation time. At a minimum, the processed data should be compiled into annual joint frequency distributions of wind speed and wind direction versus atmospheric stability class. An example of one stability group (i.e., one of seven) for this type of summary is shown in Table 2.

7.0 SYSTEM PERFORMANCE

Recommended accuracy limits, calibration tasks, and tasks related to meteorological monitoring program reliability are addressed in this section. The recommended accuracy limits apply to the anticipated range of operations applicable to the objectives of the monitoring program.

7.1 System Accuracy

Accuracy values shall reflect the performance of the total system, and shall be based on the more stringent of the individual facility requirements or the minimum system accuracy and resolution requirements given in Table 1, which provides values for a monitoring system using typical tower-mounted sensors and digital data processing systems.

System accuracy should be estimated by performing system calibrations, or by calculating the overall accuracy based on the system's individual components. Accuracy tests involve configuring the system near to normal operation, exposing the system to multiple known operating conditions representative of normal operation, and observing results. Data channels may be separated into sequential components, as long as results from each component are directly used as input for the next component in sequence. Exhibit 1 provides a method that should be used to calculate system accuracy from individual component accuracy values.

7.2 System Calibrations

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System calibrations verify the system performance and allow for correction of bias differences to meet program requirements. System calibrations of meteorological monitoring equipment are designed to evaluate the combined responses from the sensor through intermediate signal processing equipment to data recording equipment. System calibrations encompass the entire data channel and may be performed by a series of sequential, overlapping, or total channel steps such that the entire channel is calibrated. For example, a wind speeddirection sensor may be removed from the system and calibrated in a wind tunnel, while the remainder of the data channel is calibrated by input of known test signals at the sensor connection.

As a minimum, system calibration tests shall be made when installing the components to assure proper operation within the total system and at periodic intervals thereafter. Routine calibrations include obtaining both "as-found" (prior to maintenance) and "as-left" (final configuration for operation) results, unless impossible due to equipment failure. Calibrations may simply verify component or system performance within stated accuracy limits, or it may involve adjusting response to conform to desired results. Calibrations shall be made using standards that are calibrated and traceable to the National Institute of Standards and Technology (NIST) or equivalent. The calibration program shall be established as part of the quality assurance (QA) program described in Section 7.4 [19, 20].

The general interval for calibrations should be six months [19, 20], unless the operating history of the equipment demonstrates that longer periods would not adversely jeopardize data quality and data recovery rates. Shorter periods should be used if unacceptable performance is noted. Sensors and components calibrated off-line may be stored in a controlled environment without activating the normal calibration period if the storage will not degrade performance.

System calibrations may be made with the sensors removed from normal operating positions when necessary, (e.g., temperature sensors removed from shields and placed in controlled temperature environments, sensors mounted on instrument carriages operated through auxiliary connections when carriage is lowered to near ground level, etc.). Separate sensor calibrations using auxiliary equipment are recommended for equipment with performance characteristics that cannot be completely tested in the field or during routine bench-top maintenance. For example, wind sensors may be tested in a calibrated wind tunnel. Appendix F identifies recommended techniques for calibrations. Further information on calibration checks for meteorological equipment is found in [210].

7.3 System Protection, Maintenance, and Service

The monitoring and data recording systems shall be protected from electrical faults. Exposed instruments and sensors should, when possible, be protected against severe environmental conditions (e.g., icing, blowing sand and dust, salt spray, or other air contaminants). Monitoring systems shall be maintained to reasonably assure that the program will meet its data recovery criteria. Functional checks of instrumentation should be performed after exposure to extreme meteorological conditions or other events that may compromise system integrity. Finally, the monitoring system must be operated so that it is safe for maintenance personnel (including tower climbers, if applicable) and must provide an operating environment suitable for electronic equipment. Therefore, tThe maintenance program should also include safety checks of the structures and facilities, as well as the electrical power system and the heating ventilation air conditioning (HVAC) system.

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When meteorological data acquisition systems are remotely accessed; applicable procedures shall clearly identify responsibilities for activities (e.g., operational checks, software changes), describe methodologies for remote access, and specify actions to be taken when problems are detected.

7.4 Quality Assurance Program and Documentation

Within the scope of this standard, quality (or data quality) is the level of conformance of the total system with specified requirements. A QA program shall be established to document how the desired quality is accomplished. As a minimum, the following criteria shall be addressed:

1) Owner or Project Organization;2) Indoctrination and Training;3) Assessment and Audit Programs; *4) Procedures Adherence;5) Maintenance;6) Corrective Actions;7) Plant Records Management;8) Procurement and Materials Control;9) Measuring and Test Equipment, Traceability of Standards; and,10) Software and Database Control.

* Assessment Programs (item 3 above) should include field surveillances performed by individuals knowledgeable in meteorological measurement criteria. Field surveillances allow determination of whether good engineering practices and instrument siting criteria have been employed (as they apply to installation, operation, and maintenance activities).

Additional information about QA programs features can be found in [3, 19, 210].

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TABLE 1. MINIMUM SYSTEM ACCURACY AND RESOLUTION REQUIREMENTS

Measurement 1 Units 2 Accuracy 3 (±) Resolution 4

Wind Speed (WS) meters per second 0.2 or 5% of 0.1Standard Deviation of observed WSWind Speed:

Sigma-u (horizontal) meters per second n/a6 0.01Sigma-w (vertical) meters per second n/a 0.01

Wind DirectionHorizontal degrees azimuth 5 1.0Vertical degrees elevation 5 0.1

Standard Deviation of Horizontal Wind Direction FluctuationsSigma Theta (or Sigma-a) degrees azimuth n/a 0.1

Standard Deviation of Vertical Wind DirectionFluctuationsSigma Phi (or Sigma-e) degrees elevation n/a 0.1

Air Temperature degrees Celsius 0.5 0.1

Vertical Air TemperatureDifference (delta T) degrees Celsius 0.1 0.01

Dew-point Temperature degrees Celsius 1.5 0.1

Wet Bulb Temperature degrees Celsius 0.5 0.1

Relative Humidity percent 4 0.1

Barometric Pressure millibars 3 0.1 (hectopascals)

Precipitation millimeters 10% of volume5 0.25

Solar/Terrestrial Radiation watts per square meter 10 1 5% of observed 1

Soil Temperature degrees Celsius 1 0.5

Soil Moisture percent 10% of actual 1

Time minutes 5 1

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1 For measurements that are not listed, accuracy should be based on the manufacturer’s guidance.

2 Other measurement units, (e.g., miles per hour, degrees Fahrenheit, inches, hours) may be used to be consistent with monitoring program objectives.

3These are both system accuracy and sensor accuracy values. The system accuracy encompasses all components impacting system accuracy (sensors, data processing equipment, computer, calibrations, etc). The sensor accuracy applies to the manufacturer’s instrument specification. If calculations described in Section 7.1 indicate that the system accuracy is not adequate, a sensor with accuracy better than that listed below may be required.

4 Recommended resolutions are based on the recommended units.

5 Accuracy is for volume equivalent to 2.54 mm precipitation and rate <50 mm per hour.

6 n/a = not applicable

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TABLE 2. JOINT FREQUENCY DISTRIBUTION OF WIND DIRECTION, WIND SPEED AND STABILITY CLASS

Period of Record:

Extremely Unstable (ΔT/ ΔZ <-1.9 C/100m)Pasquill-Gifford Stability Class A

Wind Speed (ms-1) at 10-m Level

WindDirection <=0.49 0.50-1 1.1-2 2.1-3 3.1-4 4.1-5 5.1-6 6.1-8 8.1-10 10.1-13 13.1-18 >18

NNNENEENEEESESESSE (COUNTS OR PERCENTAGE)SSSWSWWSWWWNWNWNNW

Total (COUNTS OR PERCENTAGE)

Number of Calms

Number of Missing Hours

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Exhibit 1. Method for Calculating System Accuracy

1. Identify the individual components that contribute to system accuracy ( ); sensor, dataprocessing equipment, computer, calibrations, etc.

2. Classify the error for each component as a bias error ( ) or a random error ( ).

• Bias (or systematic) errors consistently affect the system accuracy in a known manner.An example is solar heating that increases temperature values only during daytime.

• Random errors are independent and can fluctuate within the range between the extrememaximum and minimum values.

3. Estimate the values of the component errors based on engineering analysis, vendor specifications, accuracy tests, or operational experience.

• If a bias applies to only a portion of the sampling period (e.g., solar heating), multiplecalculations of the system accuracy, using different bias values, are necessary (step 6).

• The random errors of the individual components should represent ±2s values or 2 timesthe standard deviation of errors based on component testing (i.e., assuming a normalerror distribution, the error of the system will be within the stated value 95.5% of thetime). Unless otherwise stated, manufacturer's data for random errors can normallybe assumed to be ±2s values.

4. Perform time-average adjustments for random error components.

where: are random error components (determined above). is the number of samples to which component applies.

are adjusted random error components. is the number of components.

Note: For instantaneous values (where ), .

5. Calculate "root sum of the squares" ( ) for the adjusted random error components.

6. Add bias errors to obtain .

When necessary, repeat step 6 with different bias values to determine extreme values.

7. Compare the extreme values with applicable requirements to evaluate systemperformance.

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8.0 REFERENCES

This standard shall be used in conjunction with the following publications:

1. Angevine, W. M., A. B. White, and S. K. Avery, 1994: Boundary-layer depth and entrainment zone characterization with a boundary layer profiler. Boundary Layer Meteorology 68, 375-385.

2. ANSI-ASQC E4-1994. Specifications and Guidelines for Quality Systems for Environmental Data Collection and Environmental Technology Programs.

3. ANSI/ANS-3.2, 1994: Administrative Controls and Quality Assurance for the Operational Phase of Nuclear Power Plants, American Nuclear Society, La Grange Park, IL.

4. ASTM, 2002 (Dec. 2002): Standard Test Method of Measuring Humidity with Cooled-Surface Condensation (Dew-Point) Hygrometer (D4230-02), in Volume 11.03 Atmospheric Analysis; Occupational Health and Safety; Protective Clothing, American Society for Testing and Materials, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

5. ASTM, 2002: Standard Practices for Measuring Surface Wind and Temperature by Acoustic Means (D5527-00(2002) E1), in Volume 11.03 Atmospheric Analysis; Occupational Health and Safety; Protective Clothing, American Society for Testing and Materials, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

6. ASTM, 1999: Standard Test Methods for Measuring Surface Atmospheric Pressure (D3631-99), in Volume 11.03 Atmospheric Analysis; Occupational Health and Safety; Protective Clothing, American Society for Testing and Materials, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

7. ASTM, 2000: Standard Practice for Determining the Operational Comparability of Meteorological Measurements, ASTM D4430-00e1. American Society for Testing and Materials, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

8. ASTM, 2003 (2): Standard Test Method for Determining the Performance of a Sonic Anemometer/Thermometer (D6011, reapproved 2003), in Volume 11.03 Atmospheric Analysis; Occupational Health and Safety; Protective Clothing, American Society for Testing and Materials, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

9. ASTM, 2002 (3): Standard Practice for Characterizing Surface Wind Using a Wind Vane and Rotating Anemometer (D5741-96(2002)e1), in Volume 11.03 Atmospheric Analysis; Occupational Health and Safety; Protective Clothing, American Society for Testing and Materials, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

10. ASTM, 2003: Standard Practice for Measuring Surface Atmospheric Temperature with Electrical Temperature Sensors (D6176-97(2003)), in Volume 11.03 Atmospheric Analysis; Occupational Health and Safety; Protective Clothing, ASTM International, 100 Barr Harbor Drive, West Conshohocken, PA 19428.

11. ASTM, 2002 (4): Standard Test Method Determining the Dynamic Performance of a Wind Vane (D5366-96(2002)e1), in Volume 11.03 Atmospheric Analysis; Occupational Health

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and Safety; Protective Clothing, ASTM International, 100 Barr Harbor Drive, West Conshohocken, PA 19428

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13. Banta, R. M. (ed.), 1996: ETL/EPA Workshop on Open Burning/Open Detonation (OB/OD). (NOAA Technical Memorandum ERL ETL-267). United States National Oceanic and Atmospheric Administration, Environmental Research Laboratories, Boulder, CO.

14. Banta, R. M., C. J. Senff, A. B. White, M. Trainer, R. T. McNider, R. J. Valente, S. D. Mayor, R. J. Alvarez, R. M. Hardesty, D. Parrish, and F. C. Fehsenfeld, 1998: Daytime buildup and nighttime transport of urban ozone in the boundary layer during a stagnation episode. J. Geophys. Res.,Vol. 103, No. D17, 22519-22544.

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16. Clifford, S. F., J. C. Kaimal, R. J. Lataitis, and R. G. Strauch, 1994: Ground-based remote profiling in atmospheric studies: An overview. Proc. IEEE, 82, 313-355.

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18. DOE, 1991: Environmental Regulatory Guide for Radiological Effluent Monitoring and Environmental Surveillance (DOE EH-0173T). United States Department of Energy, Washington, DC 20585.

19. EPA, 2000: Meteorological Monitoring Guidance for Regulatory Modeling Applications (EPA-450/R-99-005). United States Environmental Protection Agency, Research Triangle Park, NC 27711.

20. EPA, 1987: Ambient Monitoring Guidelines for Prevention of Significant Deterioration (EPA_45-/4-87-007). United States Environmental Protection Agency, Research Triangle Park, NC 27711.

210. EPA, 1995: Quality Assurance Handbook for Air Pollution Measurement Systems, Volume IV Meteorological Measurements (EPA/600/R-94/038d). United States Environmental Protection Agency, Research Triangle Park, NC 27711.

221. FCM, 1994: Federal Standard for Siting Meteorological Sensors at Airports (FCM-S4-1994). Federal Coordinator for Meteorological Services and Supporting Research 6010 Executive Blvd. Suite 900, Rockville, MD 20852.

232. Fischer. B.E.A., et al. (Eds.), 1998: Harmonisation of the pre-processing of meteorological data for atmospheric dispersion models. COST Action 710—Final Report. European Union, EUR 18195 EN, 412 pp.

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243. Glickman,T.S. (ed.), 2000: Glossary of Meteorology. (ISBN 1-878220-34-9) American Meteorological Society, Boston, MA 02108.

254. Holzworth, G., 1964: Estimates of mean monthly mixing depths in the contiguous United States. Mon. Wea. Rev., 92, 235-242.

265. IAEA, 1980: Atmospheric Dispersion in Nuclear Power Plant Siting, A Safety Guide (50-SG-S3). International Atomic Energy Agency, Vienna, Austria.

276. Kaimal, J. C., N. L. Abshire, R. B. Chadwick, M. T. Decker, W. H. Hooke, R. A. Kropfli, W. D. Neff, and F. Pasqualucci, 1982: Estimating the depth of the daytime convective boundary layer. J. Appl. Meteor., 21, 1123-1129.

287. Lenschow, D. H. (ed.), 1986: Probing the Atmospheric Boundary Layer. (ISBN 0-933876-63-7) American Meteorological Society, Boston, MA 02108.

298. May, P.T., K.P. Moran, and R.G. Strauch, 1989: The accuracy of RASS temperature measurements. J. Appl. Meteor., 28, 1329-1335.

3029. Neff, W.D., 1994: Mesoscale air quality studies with meteorological remote sensing systems. Int. J. Remote Sensing, 15, 393-426.

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321. Potter, Thomas D. and Bradley R. Colman (Eds.), 2000: Handbook of Weather, Climate and Water. Wiley-Interscience, John Wiley & Sons, Inc. 2003.

332 Schwiesow, R. L, 1986: A comparative overview of active remote-sensing techniques. in Probing the Atmospheric Boundary Layer, D.H. Lenschow (ed.), Amer. Meteor. Soc., Boston, MA, pp. 129-138.

343. Stull, R. B., 1988: An Introduction to Boundary Layer Meteorology. (ISBN 90-277-27868-6). Kluwer Academic Publishers, Dordrecht, The Netherlands.

354. TIA, 1996: Structural Standards for Steel Antenna Towers and Antenna Supporting Structures. (TIA/EIA-222-F) Telecommunications Industry Association/Electronics Industry Association American National Standard.

365. Turner, D. Bruce, “Comparison of Three Methods for Calculating the Standard Deviation of the Wind Direction,” J. Clim. Appl. Met. , Vol. 25, No. 5, pp. 703-707 (May 1986).

376. Westwater, E.R., 1997: Remote sensing of tropospheric temperature and water vapor by integrated observing systems. Bull. Amer. Meteor, Soc., 78, 1991-2006.

387. White, A. B., 1993: Mixing depth detection using 915-MHz radar reflectivity data. Preprints, 8th Symp. on Observations and Instrumentation. Amer. Meteor. Soc., Boston, pp. 248-250.

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398. Wilczak, J.M., E.E. Gossard, W.D. Neff, and W.L. Eberhard, 1996: Ground-based sensing of the atmospheric boundary layer: 25 years of progress. Bound-Layer. Meteor., 78, 321-349.

4039. World Meteorological Organization, 1983: Guide to Meteorological Instruments and Methods of Observation (Fifth Edition). WMO No. 8, Secretariat of the World Meteorological Organization, Geneva, Switzerland.

410. Yamartino, R.J., “A Comparison of Several “Single-Pass” Estimators of the Standard Deviation of Wind Direction,” J. Clim. Appl. Met., Vol. 23, No. 9, pp. 1362-1366 (September 1984).

25

APPENDICES

26

Appendix A

This appendix is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

SUPPLEMENTAL METEOROLOGICAL MEASUREMENTS

A1 Mixing Height

Mixing height defines the upper boundary of the volume through which contaminants are mixed thus directly affecting contaminant concentrations. Over land, the daytime mixing height is the result of fundamentally different processes from that of the nighttime stable boundary layer. During daytime, mixing in the convective boundary layer (CBL), or mixed layer, is driven predominantly by surface heating. In late morning the CBL may grow rapidly from about 300 m to roughly 1-2 km over a period of less than 1 hour. Methods for measuring mixing height shall be able to operate within these ranges. A more detailed discussion of many considerations concerning the measurement of mixing height is given in [15].

The most fundamental measurement method for determining mixing height during the daytime involves finding the inversion height on an atmospheric temperature sounding by a radiosonde or tethersonde [298]. However, the inversion height is also often associated with a discontinuity in humidity, or with a layer of strong wind shear. These strong gradients or peaks lead to the use of several remote sensing techniques (see Section 3.3.1). For example, a sharp peak in vertical profile of the radar wind profiler reflectivity data, which indicate the magnitude of the microwave refractive index structure-function parameter, often marks the top of the CBL [1, 387]. In addition, the sudden drop-off of aerosol concentration and acoustic backscatter, frequently noted between the CBL and the free atmosphere above, have been used to identify zi in profiles of lidar aerosol backscatter and sodar acoustic backscatter. Afternoon convective clouds can vent material up and out of the CBL. In addition, horizontal variability of the mixing height, which can occur over distances of a few tens of kilometers even over relatively flat terrain [14], can complicate the measurement of mixing height by remote sensing techniques.

At night, the determination of mixing height is more difficult, in part because it is often not well defined. If the atmosphere is weakly stable in the lowest 100 m above the surface and has some shear in the wind profile, turbulence may be continuous with height. This condition results in a reasonably well-defined mixing height, which may be evident in sodar backscatter profiles or time-height plots. However, if the lowest layer is very stable, the turbulence is generally intermittent, and the upper limit of vertical transport of material from the surface is poorly defined. In these cases, local drainage flows may be an important component of the physical processes affecting both horizontal and vertical transport.

In some cases where a measurement of mixing height is not available, estimates based on climatological studies of radiosonde data may be acceptable for modeling purposes [254]. However, caution should be exercised when using climatological estimates of mixing height, since the limitations in spatial, temporal, and vertical resolution will strongly limit accuracy.

A2 Soil Temperature

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The measurement of soil temperature can be important for ground-level spills or releases, modeling applications, or for determining the influence of soil temperature on the height of the atmospheric boundary layer. Typically, three or more sensors are buried at different levels to determine a temperature profile. Special care should be given to ensure that the representative ground cover (e.g., grass, sand, etc.) is not disturbed by the installed sensors. Relative diurnal and seasonal variations in soil temperatures are described in [343].

A3 Soil Moisture

Soil moisture content can be very important for determining the mixing height (see Section 3.2.1). The measurement of soil moisture should also be used for characterizing conditions for the underground storage of nuclear materials, fuels, or other hazardous wastes and for the behavior of chemical spills. Methods to measure soil moisture vary widely, but typically only electrical resistance methods and time-domain reflectrometry are used for continuous operation applications. Electrical resistance measurements made through a porous material that is buried and, hence, comes into aqueous equilibrium with the soil moisture content can be used to determine soil moisture. Significant calibration errors are possible with electrical resistance methods. Time-domain reflectrometry (electromagnetic wave propagation variations) can also be used to more accurately determine soil moisture on a real-time basis.

A4 Remote Sensing Technologies

Ground based remote sensing is a fast-growing area of atmospheric measurement technology. Not only are new remote-sensing systems being developed to address a wider range of issues, but previously developed technologies are becoming less expensive, smaller, and easier to operate. As a result, those systems are being more widely and routinely deployed. This has led to two classes of technology:

1. Widely deployed systems, such as sodar, radar wind profilers, NEXRAD, and satellite data, that can be included in operational schemes to determine the wind field and dispersion of contaminants; and,

2. Less widely deployed systems that could be available for large intensive field programs and site surveys (i.e., specialized radars and lidars).

Remote sensing systems have the ability to provide needed spatial coverage or frequent profile information. Sites with especially difficult wind flow configurations, such as those which result from complex terrain influences, may need to consider an intensive site-survey measurement campaign to identify flow features that affect atmospheric transport of emissions, and to aid in optimum siting of instrumentation.

An important functional difference between remote sensing systems is "active” versus “passive". Active remote sensors transmit a signal that interacts with the medium of propagation and returns to a receiver. For example, lidars, radars, and sodars transmit pulses or continuous signals of light, radio waves (e.g., microwaves), or sound, respectively, which scatter off inhomogeneities or particles in the atmosphere and return to the receiver. The signal is often calculated as a function of range using the "time of flight" of the signal and the appropriate propagation speed. Passive systems, such as radiometers, do not transmit a signal, but measure natural emissions from surfaces, atmospheric layers, or other atmospheric processes.

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The following sections list some examples of remote sensing technology currently available although these are not intended to be complete. Additional information is available in [16, 287, 3029, 332].

A4.1 Active Remote Sensors

Sodars, or Doppler sodars, are commercially available and provide vertical profiles of acoustic backscatter to 1 km or more. The atmospheric boundary layer (ABL) height, large eddy or thermal structure, and gravity wave turbulence structure can be determined. Doppler systems give profiles of vertical velocity and the horizontal wind vector. Values represent volume-averages of layers that are horizontal slices of a narrow cone. Scatterers are the small-scale acoustic index of refraction fluctuations, which are in turn functions of the small-scale (i.e., < 1 m) fluctuations of virtual temperature and velocity. Because the signal is a sound pulse, range or usefulness may be restricted in noisy environments such as urban areas, and near highways or construction sites.

A radar wind profiler can provide vertical profiles of the horizontal wind velocity and the radar reflectivity, which is a measure of the microwave refractive index structure function parameter. This is essentially a measure of the strength of the small-scale (i.e., <1 m) turbulent fluctuations in temperature and humidity. If RASS (radio acoustic sounding system) is included, it provides profiles of virtual temperature by emitting a sound pulse and measuring the speed of sound, which is also a function of virtual temperature, with the profiler [28]). Index of refraction fluctuations can be used to determine mixing height in the daytime convective boundary layer (see Section 3.3.1). The 900 MHz series (i.e., "UHF") profilers, that can reach heights of 2 km at a resolution of 60 m, and 3-4 km at a resolution of 100 m, are usually used for boundary layer work. The National Oceanographic and Atmospheric Administration (NOAA) National Wind Profiler Network (NWPN) uses 404 MHz profilers, which achieve greater heights, about 12 km, but have a much coarser vertical resolution, about 250 m.

Radar or Doppler radar can provide reflectivity (i.e., backscatter) within cloud or precipitation systems where hydrometeors are the scattering targets. Doppler systems give velocity structure, or, if cloud systems are wide spread, can give area wind fields. For sufficiently sensitive radars, insects and other suspended matter in the boundary layer during the warm season in continental areas often provide a strong enough signal to estimate boundary layer winds and other kinematic properties including vertical profiles of the horizontal wind. NOAA NEXRAD radars provide vertical azimuth display (VAD) data, which can include wind speed and direction as often as every 6 minutes at 300-m vertical intervals. These winds are derived from hydrometeors in precipitation systems, or from insects and turbulence in the clear air mode. Installations near NEXRAD radar sites should consider using this capability.

Optical remote sensing is a rapidly growing research area. Lidar, similar in many respects to radar, transmits a pulse of light (i.e., ultraviolet, visible, infrared) usually from a laser source, instead of radio waves. Because of the wavelength of the signal, the atmospheric scattering targets are usually particles. Techniques have been developed to use lidar backscatter intensity to calculate aerosol profiles, mixing height, and mean wind profiles (by tracking inhomogeneities in the aerosol field). Doppler lidar techniques have been used to reveal details of the wind flow, mean wind profiles, and turbulence profiles [12, 13]. Absorption properties of atmospheric constituents have been used to develop experimental techniques (such as differential absorption lidar, or DIAL) to measure profiles or to map out various

29

chemical species, including ozone and water vapor. Each of these types of lidar have been used to sample the atmosphere both as ground-based sensors and on airborne platforms.

A4.2 Passive Remote Sensors

Radiometers can provide integrated values of water vapor or temperature along a path. Multiple wavelengths can be used to provide vertical profile information, and technologies have been developed for using multiple data sources (i.e., ground-based radiometers combined with satellite radiometers, RASS, lidar, temperature data from commercial aircraft) to provide profiles that agree quite well with radiosonde measurements [376]. Radiometry has also been used to measure path-averaged concentrations of chemical species. For example, the Fourier-transform infrared (FTIR) spectrometer can provide path-averaged concentrations of many chemical species simultaneously.

Radiometers and other instrumentation on satellite platforms provide a wealth of meteorological information, including cloud coverage and type, integrated water vapor, winds via cloud tracking, smoke-plume tracking, soil moisture, greenness indices for vegetation, sea state, and many other environmental parameters. Greater detail on what is available from satellite is beyond the scope of this Appendix.

30

Appendix B

This appendix is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

METEOROLOGICAL TOWER SITING CONSIDERATIONS IN COMPLEX TERRAIN

Complex wind conditions occur when terrain and/or surface conditions influence the meteorological parameters that control transport and dispersion of emissions. For example, significant terrain features, such as large hills, mountains, or water bodies that are up to a few tens of kilometers from the monitoring area can still influence the vertical wind and temperature profiles enough to be considered complex terrain areas.

The most significant influences of complex terrain on atmospheric dispersion when selecting monitoring site locations and wind measurement heights are slope winds (i.e., anabatic, katabatic), airflow channeling, surface based nocturnal stable layers, and low level nocturnal jets. Slope winds tend to travel upslope during daytime heating (anabatic) and down slope (i.e., katabatic) during nocturnal surface cooling. Shallow cold air slope or drainage winds in layers less than 10-m deep can occur along hillsides, but in larger-scale topography (especially mountainous areas), such thermally forced wind layers can be a few hundred meters (for nighttime cold air down slope) to several hundred meters (for daytime upslope) deep. Airflow channeling is the tendency for prevailing wind directions in complex terrain to follow the axis of relatively lower terrain, such as a valley. Channeling occurs during most combinations of wind speed and atmospheric stability, though it is more dominant during periods of greater stability and lesser wind speed. Channeling tends to follow the direction of the larger scale slope winds, such as the major valley feature.

In areas of complex terrain, the formation of nocturnal surface based stable layers and temperature inversions is modified. The cooler, hence more dense, air in higher terrain causes a down slope wind. Areas of open airflow drainage, such as hillsides and open valleys, tend to form shallow surface-based inversions with stable, occasionally isothermal, layers extending in depth to the elevation of nearby terrain. Enclosed basin areas tend to form cold pools of air with little air motion and strong surface-based temperature inversions extending in depth to the elevation of the enclosing terrain.

31

Appendix C

This appendix is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

METEOROLOGICAL MONITORING FOR STABILITY CLASS DETERMINATION

C1 Overview

The determination of the stability of the atmosphere is a crucial consideration for atmospheric dispersion modeling at nuclear facilities. In Gaussian plume transport and dispersion modeling applications, the calculation of the dilution and transport of a pollutant is straight-forward and is derived from mean values of the wind speed and wind direction, respectively. However, the diffusion of the pollutant is entirely dependent upon atmospheric turbulence intensity that is more difficult to ascertain. Stability categories or classifications (e.g., Pasquill-Gifford Stability Classes), see [19, 265], are generally used to determine atmospheric stability to estimate diffusion. It should be noted that not every atmospheric dispersion model uses stability classifications to estimate diffusion. Some of the more recent models incorporate continuous measurements of estimates of atmospheric turbulence to calculate diffusion. The method used to categorize atmospheric stability should be compatible with the assessment methodology.

To understand the origin of the stability classification schemes, a brief discussion of the turbulence kinetic energy (TKE) is necessary (see [343]). The TKE of the atmospheric boundary layer (ABL) can be described in a budget equation that shows the relative effects of local storage, advection, buoyancy, mechanical or shear forces, transport, pressure, and dissipation on the production of turbulence in the ABL. The ratio of the buoyant force to the mechanical or shear force is called the flux Richardson number (R i). The magnitude and sign of Ri can be used to determine atmospheric stability. Therefore, a stability classification scheme that is based on the complete set of measurements required to determine R i or other appropriate TKE terms or derivatives (i.e., Monin-Obukhov length) can be optimal for classifying the stability of the ABL.

In practice, the meteorological measurements required to calculate R i directly are not always readily available. However, stability categories or classifications have been developed to estimate Ri based on a few key atmospheric measurements. There are several methods used to determine the stability category of the ABL, and each method has advantages and disadvantages. As new technology becomes commercially available, the measurements required to calculate Ri will become more realistic for a meteorological monitoring program as opposed to exclusively for a short-term research field experiment. The most common methods are summarized, with advantages and disadvantages, in C2.

The methodology used for atmospheric stability classification for atmospheric dispersion modeling purposes at any individual nuclear facility can be complex and should be developed by a qualified meteorologist or atmospheric scientist. Often, it is necessary to adjust stability classification schemes based on local influences such as surface roughness or terrain. It is incumbent upon the person or group developing the meteorological monitoring program to justify and document the appropriateness of the methodology used.

C2 Parameterization32

C2.1 Monin-Obukhov Length

The Monin-Obukhov length (see [354]) can be used very reliably to characterize the stability of the ABL. Fast-response sonic anemometers and temperature sensors can be used to directly measure the wind speed and temperature fluctuations used in the computation of the Monin-Obukhov length. Sonic anemometer technology, which has been used extensively in ABL field experiments for many decades, has become more robust and operational. Operational instrumentation to measure water vapor fluctuations, required in Monin-Obukhov length calculations, is also more readily available than years past.

C2.2 Wind Speed, Cloud Cover, and Ceiling Height

Stability classification can be established through the use of the measurement of wind speed, estimation of the percentage of cloud cover, and the estimation of the cloud ceiling height. Net solar radiation can be estimated with the cloud information and solar angle, time of day (hour), and time of year (date). The combination of the solar insolation and wind speed information are combined to estimate the stability classification. Although these measurements are readily available from NWS stations, a nuclear facility may have to take onsite measurements to ensure the appropriate representativeness.

The advantage of this method is that information from the measurements can provide a good estimate of the actual value of Ri. Unfortunately, measurement of cloud characteristics, in this case amount and ceiling height, is not cost-effective for most meteorological monitoring programs at nuclear facilities.

C2.3 Solar Radiation and Delta Temperature

The use of the solar radiation/delta temperature (SRDT) method is similar in concept to the use of wind speed, cloud cover, and ceiling height. The major difference is that the measurement of solar radiation replaces the cloud cover and ceiling information. The combination of solar radiation and wind speed during the day and a delta temperature measurement between 2 m and 10 m and wind speed measurement at night is used to infer the stability classification.

This method provides a good estimate of the actual value of R i and is relatively easy to make compared to gathering cloud information. The use of the combination of solar radiation and temperature difference measurements ensures representative measurements during any given period of the day. Difficulties can arise when making the delta temperature measurement if the relative accuracy between sensors does not meet those identified in Table 1. Sensors shall be matched when direct difference measurements are used along with identical solar shield and mechanical aspiration systems.

C2.4 Standard Deviation of the Vertical Wind Direction Fluctuations and Mean Wind Speed

Standard deviation of the vertical wind direction fluctuations (sf) and vertical wind speed (sw) can be used in combination with the mean scalar wind speed to classify categories of atmospheric stability. Since vertical wind fluctuations vary as a function of measuring height,

33

surface roughness, stability, and due to gravity waves and wind meander, proper siting and placement of the sensor is extremely important (see Section 4.0).

This method has the advantage of using a direct measurement of atmospheric turbulence. Typically, vertical wind measurements are made with bivanes, vertical wind propellers, or sonic anemometers, all of which generally require additional calibration and maintenance attention.

C2.5 Standard Deviation of the Horizontal Wind Direction Fluctuations and Mean Wind Speed

The standard deviation of the horizontal wind direction fluctuations (sq) can be used in combination with the mean scalar wind speed to classify categories of atmospheric stability. As with the measurement of the vertical wind direction, sensor siting and placement must be considered very carefully (see Section 4.0).

Although relatively inexpensive to obtain, this method only characterizes the horizontal atmospheric turbulence. Careful data handling (see Section 6.0) must be used to avoid spurious values at low wind speeds and to correctly interpret the effects of meandering on sq

magnitudes. This is accomplished through processing of the 10 or 15-minute subintervals using techniques described in [210].

C2.6 Delta Temperature/Delta Height (Delta T/Delta Z)

The difference in temperature at two measurement heights can be used to accurately infer the stability classification of the ABL under clear nighttime conditions. Historically, this method has been used for continuous stability class determination at many nuclear facilities based on the relative ease of the temperature measurement process. However, this method can fail to accurately determine the stability classification under daytime conditions when either near-neutral or superadiabatic conditions exist. Therefore, an additional means of characterizing daytime stability classes should be considered when using this method.

34

Appendix D

This appendix is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

OPTIONAL SITE SELECTION TECHNIQUES

D1 Overview

Monitoring programs faced with complex terrain or complex surface environments should obtain supplementary information for the determination of proper monitoring station locations. Such information includes remote sensing studies, tracer studies, numerical modeling, physical modeling (i.e., wind tunnels) and other techniques. Careful experimental design and utilization of experts knowledgeable in local meteorological characteristics is advised to obtain the best value from any short-term field program or technical study.

D2 Techniques

D2.1 Remote Sensing

The Doppler sodars, radar wind profiler measurements, and RASS, described previously, can be used in some circumstances to provide vertical profiles of wind, turbulence, and temperature. Tethered balloons with wind, temperature, and moisture sensors strung along the tether line are also useful tools in obtaining vertical measurements of wind, temperature, and humidity. These profile measurements can help resolve questions related to multiple stable layers aloft during nocturnal airflow in complex terrain environments, or airflow around obstacles.

D2.2 Atmospheric Tracer Studies

Some terrain and obstacle airflow problems can be addressed by atmospheric tracer studies. Ground-based, or even airborne, measurements of tracer material during potentially significant airflow conditions can provide the most direct indications of likely receptor locations and relative concentrations for a variety of flow regimes.

D2.3 Numerical Modeling

Some terrain and obstacle airflow problems can be addressed by numerical modeling to define the critical measurements needed in a monitoring program, and possibly the likely receptor locations and relative concentrations. While numerical modeling can provide insight into airflow situations, investigators should be aware of the accuracy limitations, particularly in data sparse areas. Questions will remain about how well the model represents reality, unless some model verification work has been performed for the particular site.

D2.4 Physical Modeling (Wind Tunnels)

Some terrain and obstacle airflow problems can be addressed by physical modeling of the obstructions in wind tunnels. Some air and water tunnels are capable of simulating either neutral or stable conditions. The flow patterns can identify critical flow areas downwind of obstacles, such as downwash and eddy locations, or likely flow patterns around and over

35

obstacles.

36

Appendix E

This appendix is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

GUIDELINES FOR PERFORMING WIND COMPUTATIONS

This Appendix provides suggested algorithms for calculating both scalar and vector wind speed and direction averages as well as wind direction standard deviation.

E1 Scalar Wind Computations

For an observed set of wind speed samples , the scalar mean wind speed is defined as:

where N is the number of valid samples in the averaging period. In determining the scalar mean wind direction , standard statistical methods for linear data sets are difficult to implement since wind direction is a circular function with a crossover point at 360 ° or 0°. For example, it is possible when using digital data to incorrectly average 1 ° and 359° (both North winds) and get 180° (i.e., South wind). As such, special care is required when calculating mean wind direction values.

The scalar mean wind direction can be approximated by the unit vector wind direction [19, 33]; that is, by the arctangent of the mean sine and mean cosine of the valid wind direction samples in the averaging period, where the mean sine and mean cosine are defined as:

; (Eq. 2)

If an arctangent function (tan-1) is employed which gives the resulting angle in degrees in a range between -90° to +90°, the magnitudes and signs of and shall be taken into account to determine as follows:

if = 0 and > 0 = 0°if > 0 and > 0

if > 0 and = 0 = 90°if > 0 and < 0

if = 0 and < 0 = 180°if < 0 and < 0

if < 0 and = 0 = 270°if < 0 and > 0

37

(Eq. 1)

Note that for any compilation of scalar wind direction statistics, the mean wind direction is not well defined for calm or near calm conditions.

E2 Vector Wind Computations

The vector mean wind speed and vector mean wind direction are defined as a function of the mean east-west component and the mean north-south component of the valid wind vector samples in the averaging period as follows:

; (Eq. 3)

where is an observed wind speed sample, qi is the corresponding observed wind direction sample, and N is the number of valid samples in the averaging period. The vector mean wind speed is:

(Eq.4)

If the same arctangent (tan-1) function described above is employed, the vector mean wind direction is defined as:

if = 0 and > 0 = 0°if > 0 and > 0

if > 0 and = 0 = 90°if > 0 and < 0

if = 0 and < 0 = 180°if < 0 and < 0

if < 0 and = 0 = 270°if < 0 and > 0

E3 Wind Direction Standard Deviation Computations

Because wind direction is a circular function, it is also difficult to employ standard statistical methods for calculating the standard deviation of the wind direction, . A recommended method for calculating which provides excellent results in most cases is given by Yamartino [19, 33, 38]:

(Eq. 5)

where:

(Eq. 6)

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Note that calculating values for a one-hour sampling could be inflated by contributions from long period oscillations associated with light wind speed conditions (e.g., plume meander). To minimize the effects of wind meander, six 10-minute values should be combined to represent an hourly sampling period as follows:

(Eq. 7)

Likewise, four 15-minute values should be combined to represent an hourly sampling period as follows:

(Eq. 8)

39

Appendix F

This appendix is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

RECOMMENDED CALIBRATION PRACTICES

Two types of calibrations are discussed in this appendix. The normal calibration interval for the meteorological sensors is six months. Additional guidance can be found in [210].

Field Calibration. A calibration performed with the sensor in a normal operating configuration (except for test equipment, as needed) with normal connections to the data processing and recording system. The sensor is directly exposed to known characteristics and results are displayed by the system output.

Laboratory Calibration. A calibration performed with the sensor removed from its normal operating position.

Measurement(s) Field Calibration1 Laboratory Calibration1

All Sensors Visually inspect for damage Visually inspect for damagewithout disassembly and, without disassembly.where possible (e.g., windvane, anemometer),compare observed sensoroperation with simultaneousoutput.

Wind Speed (as measured by cup or propeller)

Starting threshold Check bearing integrity; | Wind tunnel calibration measure torque. | ([F1]).

|Anemometer Rotate shaft at known rates. |

1 Calibration checks for measurement methods not listed should be based on manufacturer recommendations.

40

Measurement(s) Field Calibration1 Laboratory Calibration1

Wind Direction (as measured by vane)

Starting threshold Check bearing integrity and Wind tunnel calibrationmeasure starting torque. ([F2]).

Sensor Aim vane toward at least | Simulate aiming vane towardfour (4) directions in a full | multiple known directionsrange of known azimuths. | for a full range of azimuths.

|Alignment Orient vane or crossarm |

toward known landmark(s) |referenced to true north. |

Wind Direction and Wind Speed (as measured by sonic wind sensor)

Starting threshold Not applicable. | Wind tunnel calibration | ([F3]).

Sensor Make collocated measurement. |Check zero using appropriate |field chamber. |

Temperature

Air Temperature Take collocated measurement Take measurement in knownwith standard adjacent to conditions sensor intake or with with standard in isothermalstandard in isothermal environments (5 points).environments (5 points).

Delta Temperature Take measurements Take measurements withwith standard both sensors in isothermaladjacent to both sensors environments or compare in isothermal environments. with standard (5 points).

.

1 Calibration checks for measurement methods not listed should be based on manufacturer recommendations.

41

Measurement(s) Field Calibration1 Laboratory Calibration1

Dew Point Temperature Take collocated measurement Take measurement in multipleor Humidity in air or measurement of air known conditions (e.g., known

sample with known dew dew point/humidity).point/humidity.

Barometric Pressure Take collocated measurement Compare with standardin air using a barometer barometer. Use pressure andof known accuracy vacuum to simulate([F4]) pressure range.

Precipitation

Storage Compare measured water | Not applicable since sensor amount with reported | can usually be fully calibrated

accumulation. | in normal operating | configuration.

accumulation. | normal operating configuration.|

Incremental Measure response with |known water volume2 (or |equivalent). |

Solar/Terrestrial Check reading when covered Collocate with standardRadiation (for zero check) and and compare output for

collocate with standard for multiple readings inupscale response. uniform controlled lighting

of proper wavelengths.

1 Calibration checks for measurement methods not listed should be based on manufacturer recommendations.2 When adding water, be sure to add slowly to simulate rainfall rates and avoid underestimation. The rainfall rate should be less than 1 inch per hour.

References

[F1] Standard Test Method for Determining the Performance of a Cup Anemometer or Propeller Anemometer, ASTM D5096-02.

[F2] Standard Test Method for Determining the Dynamic Performance of a Wind Vane, ASTM D5366-96(2002)e01.

[F3] Standard Test Method for Determining the Performance of a Sonic Anemometer/Thermometer, ASTM D6011-96(2003).

42

[F4] Standard Test Methods for Measuring Surface Atmospheric Pressure, ASTM D3631-99.

43

Bibliography

This bibliography is not part of American National Standard ANSI/ANS-3.11, but is included for information only.

The following documents provide useful information related to the subject of this standard.

Kaimal, J. C.,N. L. Abshire, r. B. Chadwick, M. T. Decker, W. H. Rooke, R. A. Kropfle, W. D. Neff, and F. Pasqualucci, “Estimating the Depth of the Daytime Convective Boundary Layer,” J. Appl. Meteor., 21, 1123-1129 (1982).

OMB Circular A-119, Federal Participation in the Development and Use of Voluntary Consensus Standards and in Conformity Assessment Activities, Office of Management and Budget; accessible online at http://tis.eh.doe.gov/techstds/tspofram.html.

National Technology Transfer and Advancement Act, PL 104-113; accessible online at http://tis.eh.doe.gov/techstds/tspofram.html.

Wilczak, J. M., E. E. Gossard, W. D. Neff, and W. L. Eberhard, “Ground-Based Sensing of the Atmospheric Boundary Layer: 25 Years of Progress,” Boundary Layer. Meteorology, 78, 321-349 (1996).

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