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Stratified Sampling Method

Stratified Sampling Method

Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a stratified sample, divide the population into groups called strata and then take a...

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Related Experiment Video

Updated: Sep 11, 2025

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Continuous Hydrologic and Water Quality Monitoring of Vernal Ponds

Published on: November 13, 2017

Decoding dynamic water concentration fluctuations in passive sampling: Triphasic modeling-experiment-field validation

Peiyu Jiang¹, Yiping Xu², Kaifeng Rao²

¹Key Laboratory of Environmental Aquatic Chemistry, State Key Laboratory of Regional Environment and Sustainability, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China.

|August 15, 2025

Summary

Passive samplers accurately estimate contaminant levels in water, even with fluctuating concentrations. Performance reference compounds (PRCs) enable temporal stratification to correct for dynamic environmental changes, improving accuracy.

Keywords:

Concentration fluctuation Organophosphate esters Passive sampling Performance reference compound (PRC)Pesticide Time-weighted average (TWA) concentration

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Last Updated: Sep 11, 2025

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Published on: November 13, 2017

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Area of Science:

Environmental Chemistry
Analytical Chemistry
Water Quality Monitoring

Background:

Passive samplers are crucial for monitoring trace contaminants in water.
Their accuracy is poorly understood under dynamic, fluctuating contaminant concentrations.
Fluctuation characteristics (magnitude, timing, duration) significantly impact sampling.

Purpose of the Study:

To systematically investigate how fluctuation parameters and contaminant-specific sampling kinetics bias time-weighted average (TWA) concentration estimates.
To develop and validate a method for improving passive sampler accuracy in dynamic aquatic environments.
To pioneer the use of performance reference compounds (PRCs) for temporal stratification.

Main Methods:

Integrated framework combining numerical modeling (27 scenarios), laboratory experiments, and field validation.
Analysis of contaminant-specific release rate constants (k_e) and fluctuation regimes.
Application of PRCs for temporal stratification and stratified fitting strategies.

Main Results:

Passive sampling errors correlate nonlinearly with k_e and fluctuation regimes.
Linear-phase uptake maintained <25% error even with 20-fold concentration spikes.
PRC-based stratified fitting reduced root mean square error (RMSE) by 80.6% compared to conventional models.

Conclusions:

A framework was established to optimize passive sampling reliability in dynamic aquatic environments.
PRC-based temporal stratification effectively differentiates fluctuation impacts from environmental variables.
The developed stratified fitting protocol enhances passive sampling accuracy and reliability.