When you are taking measurements at the detection limit of any molecule that is widespread in the environment, you are going to have a difficult time of distinguishing signal from background. This requires sampling and replication and rigorous application of statistical inference.
> Another thing to consider is that papers generally compare against baseline/control samples,
Right, that’s what a control is.
> and overestimating microplastics in baseline samples may lead to a lower ratio of reported microplastics in the test samples, not higher.
There’s no such thing as “overestimating in baseline samples”, unless you’re just doing a different measurement entirely.
What you’re trying to say is that if there’s a chemical everywhere, the prevalence makes it harder to claim that small measurement differences in the “treatment” arm are significant. This is a feature, not a bug.
> There’s no such thing as “overestimating in baseline samples”
What do you mean? Contamination and mis-measurement of control samples is a thing that actually happens all the time, and invalidates experiments when discovered.
> What you’re trying to say is that if there’s a chemical everywhere, the prevalence makes it harder to claim that small measurement differences in the “treatment” arm are significant.
No. What I was trying to say is that if the control is either mis-measured, for example by accidentally counting stearates as microplastics, or contaminated, then the summary outcome may underestimate or understate the prevalence of microplastics in the test sample, even though the measurement over-estimated it.