The Scoop on Sensor Selection

Tips on how to pick sensors that accurately measure wind speed, vertical temperature differences, and solar radiation

• By David I. Katz
• Oct 01, 2006

Meteorological monitoring for air quality studies has evolved over the past four decades. During the summer of 1956 an experimental program to study micrometeorology and dispersion from near-surface releases was conducted near the town of O'Neil in north-central Nebraska. This comprehensive turbulence and diffusion program of 70 tracer experiments was given the name Project Prairie Grass and was instrumental in providing a basis for development of practical methods for the characterization of atmospheric dispersion. One of the first papers to discuss these data was by Cramer, in which a Gaussian plume model was described that related the horizontal and vertical dispersion to the observed standard deviations of lateral and elevation angles of the wind fluctuations. Barad and Haugen used the Project Prairie Grass results to specifically investigate the veracity of Sutton's model for plume dispersion. Not long after, Dr. F. Pasquill offered a pragmatic technique for the estimation of Gaussian plume vertical and lateral dispersion that could be implemented with easily acquired meteorological observations, namely insolation and wind speed, as shown in Table 1.

Dr. Pasquill was corresponding with F.A. Gifford, Jr. (who was then with the Oak Ridge Field Research Division), R. McCormick, and D.Bruce Turner (who were then with the Cincinnati Field Research Division) prior to 1961. So it was that Gifford offered a conversion of Pasquill's angular spread values to standard deviations of plume spread, and Turner offered a conversion of Pasquill's stability classification criteria that employed hourly airport observations. These extensions to Pasquill's scheme simplified its use and made it practical for it to be converted to a numerical algorithm. The plume-spread coefficients of ¥ò_z in the vertical dimension and ¥ò_y in the horizontal, which he displayed as curves for each stability category on log-log plots of dispersion parameters as a function of downwind distance from the source. These dispersion parameters came to be known as Pasquill-Gifford (P-G) parameters.

As the Clean Air Act regulations have evolved over the years, it became more important to make meteorological and air-quality observations at locations away from the traditional airport observation sites. These monitoring sites became more and more automated with the advent of computer technology. Without human observers to report on the cloud cover, proxies for the data used by Pasquill and Gifford were necessary. This has resulted in the use, at various times, of vertical temperature difference (delta-T), standard deviation of wind direction¥ò_¥è, and various adjustments to these, especially based on the wind speed and the time of processing the data.

The Development of SRDT
In an effort to avoid the need for onsite cloud cover observations as called for by Turner's method, the U.S. Environmental Protection Agency (EPA) developed a technique that uses onsite measurements of solar radiation or vertical temperature difference between 10 and two meters on a 10-meter tower as a function of wind speed to determine the local P-G stability class. This technique, identified by the abbreviation SRDT, was first used in the EPA guideline, "Meteorological Monitoring Guidance for Regulatory Modeling Applications," United States Environmental Protection Agency, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, February 2000, EPA-454/R-99-005.
Table 2 is the reproduction of the table from the guideline showing how these measurements are used to determine the P-G stability class.

The upper half of Table 2 is the equivalent to left half the daytime insolation portion of Table 1, and the bottom half of Table 2 is the equivalent of the right side (nighttime cloud cover) of Table 1. Using SRDT measurements avoids having to have a local observation of the cloud cover or a laser ceilometer, which is available at airports to measure the cloud height, but is not customarily used at air quality monitoring systems.

Overview of Sensor Types
Selecting the sensors needed to accurately make the SRDT measurements is described in the EPA guideline. Wind-speed sensor selection has been well defined for many years since wind speed has determined the pollutant diffusion and has been a primary measurement since these stations and guidelines were first developed. Traditional cup anemometers can easily meet the performance requirements of the guideline for accuracy and response. In the past 10 years, sonic anemometers have been developed that are designed for ambient wind sensing and as a direct replacement for conventional mechanical anemometers, both in terms of performance and cost. An added benefit is that they require no periodic maintenance or calibration. The solid-state sonic anemometers will tend to report more very-low wind speeds since they have no moving parts and the associated inertia to overcome at low wind speeds. Otherwise, they will tend to report very similar wind speeds over the range of the sensors.

A critical measurement in the SRDT scheme is the temperatures at the two levels on the 10-meter tower. Officially stated as the vertical temperature difference between two and 10 meters, the vertical temperature difference is more practically between two and nine meters, since the wind sensors are at 10 meters and need to be unobstructed by other equipment on the tower.

It is quite apparent that the motor-aspirated shield for the temperature sensor is at least one meter below the height of the anemometer cup set and wind-direction vane, or about nine meters above ground level. So, in selecting temperature sensors, it is critical that they be both accurate and precise. This is achieved by testing the temperature sensors either at the factory or before placing them in the field to be certain that if they vary from a known value, the variation is of the same sign. Then if the sensors vary within the tolerance allowed by the guideline, the user will know that they will report an accurate temperature difference. This is key since the guideline requires an accuracy of +/- 0.10 degrees Celsius for the delta-T measurement. This is achievable through normal monitoring methods only if the two sensors are matched to assure a precise measurement.

The last measurement needed to use the SRDT method is solar radiation, which is measured with a pyranometer. The guideline requires that the pyranometer respond to radiation in the wavelength range of 285 to 2,800 nanometers. This wavelength range extends into the near-infrared, which contains approximately 25 percent of the total incoming solar radiation. This is the sensitivity range of most thermopile pyranometers. The thermopile consists of a series of thermojunction pairs, an optically black primary junction, and an optically white reference junction (in some pyranometers, the reference thermojunction is embedded in the body of the instrument). The temperature difference between the primary and reference junctions that results when the pyranometer is operating generates an electrical potential proportional to the solar radiation.

Other pyranometers, which use photovoltaic-sensing elements, should not be used when SRDT will be used to calculate the local P-G stability class, since the spectral response of the photovoltaic pyranometer is limited to the visible spectrum. This can result in the stability class being off by one or two classes and would drastically affect the results of a dispersion modeling analysis.

When care is taken in the selection of sensors used to make the measurements needed to use the SRDT method of determining the P-G stability class, the gathered data will be of great value to the user. It will also be relatively easy to meet the 90 percent valid data requirement as set forth in the guideline when starting with top quality equipment.

Acknowledgment: Thanks to John Irwin for his input.

This article originally appeared in the 10/01/2006 issue of Environmental Protection.