Introduction to Environmental Data Acquisition - Fundamentals of Environmental Sampling and Analysis - page 6

collected (''born''); (4) the sample is transferred to the laboratory; (5) the sample
is analyzed; (6) the sample expires and is discarded; and (7) the sample reincarnates
as a chemical data point. Simply, the scope of environmental sampling addressed in
this topic will include the following aspects related to sampling:
Where to take samples
When to take samples
How to take samples
How many samples to take
How often samples will be taken
How much sample is needed
How to preserve samples
How long the sample will be stable
What to take (air, soil, water)
What to analyze (physical, chemical, biological)
Who will take samples (sample custody)?
1.2.2 Where, When, What, How, and How Many
Many think of field sampling as simply going out to the field and getting some
material, then bringing it back to a lab for analysis. Although such ''random''
sampling is often suggested as the basis of a sampling design, it is rarely the most
appropriate approach, particularly when there is already some knowledge of the
nature of the sample source and the characteristics of the variable being monitored.
The choice of where (spatially) and when (temporally) to take samples generally
should be based on sound statistics (simple random sampling, stratified random
sampling, systematic sampling, composite sampling, as given in Chapter 3).
Although guidelines exists (detailed in Chapters 3 and 4), there is no set rule
regarding the number, the amount, and the frequency of samples/sampling. For
instance, the optimum number of samples to collect is nearly always limited by the
amount of resources available. However, it is possible to calculate the number of
samples required to estimate population size with a particular degree of accuracy.
The best sample number is the largest sample number possible. But one should keep
in mind that no sample number will compensate for a poor sampling design. In other
words, quantity should not be increased at the expense of quality. Data in a poor
quality will have more inherent error and, therefore, make the statistics less powerful.
1.3 ENVIRONMENTAL ANALYSIS
Whereas some of the environmental analyses are conducted in the field, the majority
of the work is conducted in the laboratory. Depending on the data objectives,