Developing a geostatistical simulation method to inform the quantity and placement of new monitors for a follow-up air sampling campaign

Jesse Berman, L. Jin, M. L. Bell, F. C. Curriero

Research output: Contribution to journalArticle

2 Scopus citations

Abstract

Sampling campaign design is a crucial aspect of air pollution exposure studies. Selection of both monitor numbers and locations is important for maximizing measured information, while minimizing bias and costs. We developed a two-stage geostatistical-based method using pilot NO 2 samples from Lanzhou, China with the goal of improving sample design decision-making, including monitor numbers and spatial pattern. In the first step, we evaluate how additional monitors change prediction precision through minimized kriging variance. This was assessed in a Monte Carlo fashion by adding up to 50 new monitors to our existing sites with assigned concentrations based on conditionally simulated NO 2 surfaces. After identifying a number of additional sample sites, a second step evaluates their potential placement using a similar Monte Carlo scheme. Evaluations are based on prediction precision and accuracy. Costs are also considered in the analysis. It was determined that adding 28-locations to the existing Lanzhou NO 2 sampling campaign captured 73.5% of the total kriged variance improvement and resulted in predictions that were on average within 10.9 μg/m 3 of measured values, while using 56% of the potential budget. Additional monitor sites improved kriging variance in a nonlinear fashion. This method development allows for informed sampling design by quantifying prediction improvement (accuracy and precision) against the costs of monitor deployment.

Original languageEnglish (US)
Pages (from-to)248-257
Number of pages10
JournalJournal of Exposure Science and Environmental Epidemiology
Volume29
Issue number2
DOIs
StatePublished - Mar 1 2019

Keywords

  • Air pollution
  • Interpolation
  • Kriging
  • Method development
  • Monitor network
  • Sampling

PubMed: MeSH publication types

  • Journal Article
  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

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