Which goal best describes composite sampling?

Which goal best describes composite sampling?

• A. Reducing cost per surface
• B. Maximizing measurement sensitivity at each location
• C. Avoiding lab digestion entirely
• D. Increasing sample count with no cost change

Answer: (A)

Composite sampling is the practice of pooling several small surface samples into one combined sample for laboratory analysis, so you get an overall estimate for a larger area while performing fewer analyses. This approach is best described by reducing the cost per surface, because one analysis now covers multiple surfaces, spreading the lab cost over more area. It does involve a trade-off: you lose some site-specific detail and the ability to detect very high values at a single surface may be diluted in the composite. It doesn’t eliminate lab prep, and it doesn’t increase the number of samples without changing costs; in fact, it reduces the total number of analyses and lowers the cost per surface.

Composite sampling is the practice of pooling several small surface samples into one combined sample for laboratory analysis, so you get an overall estimate for a larger area while performing fewer analyses. This approach is best described by reducing the cost per surface, because one analysis now covers multiple surfaces, spreading the lab cost over more area. It does involve a trade-off: you lose some site-specific detail and the ability to detect very high values at a single surface may be diluted in the composite. It doesn’t eliminate lab prep, and it doesn’t increase the number of samples without changing costs; in fact, it reduces the total number of analyses and lowers the cost per surface.