Integral developed software to apply a powerful numerical technique to environmental investigations. Known as unmixing analysis, this mathematical technique provides strong lines of evidence for characterizing sources and estimating the relative contribution of different sources to site contaminants.
Hierarchical Principal Component Analysis
To analyze multivariate data sets with small numbers of samples, we apply hierarchical principal components analysis. This technique analyzes the data set in multiple blocks of variables, and then assembles the results into a global model, thus capturing the entire multivariate complexity of the data.
Graphical Similarity Analysis
Integral has developed a new tool for visualizing the similarity between samples, locations, or variables. The resulting superposition of spatial and statistical relationships results in a clear, comprehensible visual display of complex or otherwise imperceptible relationships.
Environmental measurements can be interpolated and contoured in 2 or 3 dimensions to predict likely concentrations at locations where no data exist. Integral uses geostatistical modeling techniques to efficiently assess site conditions, estimate the mass and volume of contamination, and support visualization and evaluation of remedial alternatives.
Connectivity Modeling for Ecological Landscapes
Incorporating ecological enhancements in site remediation and restoration is gaining momentum with stakeholders. Integral uses landscape connectivity modeling in the early planning process to ensure habitat projects are meeting stakeholders’ needs while maximizing ecological value at the broader landscape scale.
Modeling of Ecological Populations, Communities, and Ecosystems
Evaluating ecological risk is fundamental to most regulatory frameworks; however, such risks are often based on simplistic assumptions rooted in organism-level endpoints. Integral uses numerical models to estimate risks to higher levels of ecological organization, providing better insight for informed risk management decisions.
Habitat Analysis Using Remote Sensing
Habitat or vegetation surveys for large areas can be substituted by photogrammetric tools employing satellite imaging. Spatially resolved measures of habitat type, patch size, fragmentation, and quality thus obtained can serve as inputs for population models or risk assessments for plant communities.
Microexposure Event Modeling
Integral uses a microexposure event model to assess both uncertainty and variability in potential human health risks. This model profiles an individual’s day-to-day exposure throughout a lifetime, yielding population risks that are more realistic than those estimated using typical probabilistic methods.
Air Dispersion and Deposition Modeling
Integral models air emissions from stationary and mobile sources to support compliance and/or permitting. Using modeling output, we also perform direct (inhalation) and indirect (food chain) risk assessments. We use the regulatory suite of models and develop customized dispersion models for project-specific estimates.
Geologic and Groundwater Modeling
Integral has developed a 3-dimensional geologic and groundwater model to support watershed management. Our model was successfully used to calculate the volume of existing groundwater per unit change in the potentiometric surface for a large-scale aquifer storage and recovery feasibility study.