Statistics Research » Statistical Design & Analysis

Environmental Statistics

For four decades, we have provided environmental statistics support to our clients to address health and environmental concerns. RTI statisticians work with health and social scientists, epidemiologists, economists, toxicologists, biologists, ecologists, engineers, and environmental scientists to provide advice on environmental issues such as monitoring, species abundance, pollutant plumes, and human exposure and risk assessment.

Our work results in developing methodologies, technical cooperation, data collection, and implementation of environmental, spatial, and spatiotemporal statistics. Since 1980, we have led in designing and implementing studies of human exposures to toxicants, conducting more than 30 exposure field studies concerning multimedia, multipathway, and multichemical components.

View a sample list of the environmental statistics projects we conduct.

Focus Areas

  • Environmental sampling and monitoring program design
  • Geostatistics, spatial, and spatiotemporal models
  • Exposure studies
  • Toxicology studies
  • Risk assessment

Methodologies and Techniques

  • Standard probability-based sample designs, including stratified, cluster, systematic, multistage, and double sampling or two-phased sampling
  • Environmental-specific sample designs, such as generalized random tessellation designs, capture-recapture designs, ranked set sampling, line transects, variable circular plot sampling, area sampling, grid sampling, adaptive sampling, and composite sampling
  • Experimental designs for conducting causality studies, for controlling spurious causality, and for evaluating the effects of combinations of treatments
  • Kriging, nearest neighbor, and spatial smoothing techniques
  • Hierarchical and multilevel models to account for uncertainty and latent (spatial and nonspatial) effects
  • Bayesian models to account for a priori scientific knowledge
  • Markov Chain Monte Carlo techniques for parameter estimation
  • Parametric (mixed models involving repeated measures, cluster correlated data, or both, as well as generalized mixed models) and nonparametric models
  • Exploratory data analysis
  • Simulation (Monte Carlo techniques), jackknife, and bootstrap
  • Sensitivity analysis

Capabilities

  • Propose probability- and non-probability-based surveys as a basis for field studies involving direct exposure measurements, monitoring network design, and environmental and ecological variables
  • Apply spatial and spatiotemporal techniques for monitoring network assessment and modeling environmental processes
  • Propose models that facilitate incorporating data from multiple sources (surveys, geographic information system [GIS] layers, monitoring networks, etc.)
  • Provide statistical consulting services for a variety of animal and plant toxicology studies conducted under the Federal Insecticide, Fungicide, and Rodenticide Act good laboratory practice (GLP) guidelines and as regulated by the Toxic Substances Control Act
  • Analyze safety assessment studies, including neurobehavioral, developmental toxicity and teratology, carcinogenicity, endocrine toxicity, avian toxicity, and acute studies for estimating LD50s and related parameters
  • Apply parametric, nonparametric, and Bayesian methods for analyzing exposure data and performing risk assessments
  • Use simulation techniques (e.g., Monte Carlo methods, jackknife, bootstrap) to assess uncertainties in current risk assessment practices, exposure studies and emission factors

Applications

  • Through the years, we have developed sampling designs for collecting data on water quality, air quality, and human exposure to contaminants, including the Total Exposure Assessment Methodology studies and the national Human Exposure Assessment Survey field test in Region 5 of the Environmental Protection Agency (EPA).
  • We have applied experimental design techniques to evaluate the effects of four management practices on the reproduction and growth of a threatened orchid species. We also assessed optional modes of data collection to identify and assess the magnitude and characteristics of measurement error and to examine how these vary temporally.
  • We developed designs for estimating dose-response relationships and have investigated properties of calibration designs (spacing and replication of standard concentrations) aimed at optimal estimation of detection limits.
  • We participated in studies to determine the association between adverse birth outcomes and exposures to drinking water contaminated with arsenic, and between environmental exposures to polychlorinated biphenyls (PCBs) and other hormonally active agents on the ability of couples to conceive a child.
  • Working with risk experts, we have applied modeling techniques to help the EPA compare regulatory with nonregulatory options for fossil fuel waste management.
  • We have conducted a wide variety of toxicology studies for government and commercial clients, including identifying and characterizing hazards to human health and the environment and supporting pharmaceutical development.