Statistics for Environmental Engineers

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76


Mile 30-40


East


2


208


Mile 30-40


East


3


230


Mile 30-40


West


1


30


Mile 30-40


West


2


272


Mile 30-40


West


3


242

26

Multiple Factor Analysis of Variance


KEY WORDS air pollution, dioxin, furan, incineration, samplers, ANOVA, analysis of variance, factorial experiment, sampling error.


Environmental monitoring is expensive and complicated. Many factors may contribute variation to measured values. An obvious source of variation is the sampling method. An important question is: “Do two samplers give the same result?” This question may arise because a new sampler has come on the market, or because a monitoring program needs to be expanded and there are not enough samplers of one kind available.


It might seem natural to compare the two (or more) available sampling methods under a fixed set of conditions. This kind of experiment would estimate random error under only that specific combination of conditions. The samplers, however, will be used under a variety of conditions. A sampler that is effective under one condition may be weak under others. The error of one or both samplers might depend on plant operation, weather, concentration level being measured, or other factors. The variance due to laboratory measurements may be a significant part of the total variance. Interactions between sampling methods and other possible sources of variation should be checked. The experimental design should take into account all these factors.


Comparing two samplers under fixed conditions pursues the wrong goal. A better plan would be to assess performance under a variety of conditions. It is important to learn whether variation between samplers is large or small in comparison with variation due to laboratory analysis, operating conditions, etc. A good experiment would provide an analysis of variance of all factors that might be important in planning a sampling program.

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