Mean of Autocorrelated Air Quality Measurements

by Cynthia S. Hirtzel, (A.M.ASCE), Asst. Prof.; Dept. of Chemical and Environmental Engrg., Rensselaer Polytechnic Inst., Troy, N.Y. 12181,
Jimmie E. Quon, (F.ASCE), Former Professor and Chmn., Dept. of Civil Engineer; Northwestern Univ., Evanston, Ill. 60201,
Ross B. Corotis, (M.ASCE), Prof.; Dept. of Civ. Engrg./Material Science and Engrg., Johns Hopkins Univ., Baltimore, Md. 21218,

Serial Information: Journal of the Environmental Engineering Division, 1982, Vol. 108, Issue 3, Pg. 488-501

Document Type: Journal Paper

Discussion: Cluis Daniel A. (See full record)
Discussion: Tsai Chia-Ei (See full record)
Closure: (See full record)

Abstract: The high degree of autocorrelation present among the observations in a continuous record of air quality has significant implications with respect to the estimation of the mean value of air pollutant concentration and to the determination of data collection requirements for estimating air quality levels. Based on the characterization of the form of the autocorrelation function, equations are derived for the equivalent number of independent observations in a sample of given size. An expression for the variance of the sample mean of an autocorrelated series is derived; and equations to estimate data collection requirements for a sequence of air quality measurements are developed. These equations yield both the number of equivalent independent measurements and the number of measurements in a continuous record needed to estimate the mean value at given levels of precision and significance. The derived results are applied to observed ambient carbon monoxide measurements.

Subject Headings: Air quality | Data collection | Quality control | Carbon monoxide |

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