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Title: CO2 MONITORING FOR DEMAND CONTROLLED VENTILATION IN COMMERCIAL BUILDINGS

Technical Report ·
DOI:https://doi.org/10.2172/983161· OSTI ID:983161

Carbon dioxide (CO{sub 2}) sensors are often deployed in commercial buildings to obtain CO{sub 2} data that are used, in a process called demand-controlled ventilation, to automatically modulate rates of outdoor air ventilation. The objective is to keep ventilation rates at or above design specifications and code requirements and also to save energy by avoiding excessive ventilation rates. Demand controlled ventilation is most often used in spaces with highly variable and sometime dense occupancy. Reasonably accurate CO{sub 2} measurements are needed for successful demand controlled ventilation; however, prior research has suggested substantial measurement errors. Accordingly, this study evaluated: (a) the accuracy of 208 CO{sub 2} single-location sensors located in 34 commercial buildings, (b) the accuracy of four multi-location CO{sub 2} measurement systems that utilize tubing, valves, and pumps to measure at multiple locations with single CO{sub 2} sensors, and (c) the spatial variability of CO{sub 2} concentrations within meeting rooms. The field studies of the accuracy of single-location CO{sub 2} sensors included multi-concentration calibration checks of 90 sensors in which sensor accuracy was checked at multiple CO{sub 2} concentrations using primary standard calibration gases. From these evaluations, average errors were small, -26 ppm and -9 ppm at 760 and 1010 ppm, respectively; however, the averages of the absolute values of error were 118 ppm (16%) and 138 ppm (14%), at concentrations of 760 and 1010 ppm, respectively. The calibration data are generally well fit by a straight line as indicated by high values of R{sup 2}. The Title 24 standard specifies that sensor error must be certified as no greater than 75 ppm for a period of five years after sensor installation. At 1010 ppm, 40% of sensors had errors greater than {+-}75 ppm and 31% of sensors has errors greater than {+-}100 ppm. At 760 ppm, 47% of sensors had errors greater than {+-}75 ppm and 37% of sensors had errors greater than {+-}100 ppm. A significant fraction of sensors had errors substantially larger than 100 ppm. For example, at 1010 ppm, 19% of sensors had an error greater than 200 ppm and 13% of sensors had errors greater than 300 ppm. The field studies also included single-concentration calibration checks of 118 sensors at the concentrations encountered in the buildings, which were normally less than 500 ppm during the testing. For analyses, these data were combined with data from the calibration challenges at 510 ppm obtained during the multi-concentration calibration checks. For the resulting data set, the average error was 60 ppm and the average of the absolute value of error was 154 ppm. Statistical analyses indicated that there were statistically significant differences between the average accuracies of sensors from different manufacturers. Sensors with a 'single lamp single wavelength' design tended to have a statistically significantly smaller average error than sensors with other designs except for 'single lamp dual wavelength' sensors, which did not have a statistically significantly lower accuracy. Sensor age was not consistently a statistically significant predictor of error.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Organization:
Environmental Energy Technologies Division
DOE Contract Number:
DE-AC02-05CH11231
OSTI ID:
983161
Report Number(s):
LBNL-3279E; TRN: US201014%%576
Country of Publication:
United States
Language:
English