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Human Exposure and Atmospheric Sciences

Systems Reality Modeling:
An EPA Pathfinder Innovation Project

Issue
The urgent need to improve our ability to characterize, measure, and model human exposures to chemicals is a 21st century reality. Exposure inputs to dosimetry models, which link environmental concentration to target tissue dose, are commonly based on assumptions and estimates drawn from surveys and observations of human behavior.

Humans are exposed to chemicals based on the activities they perform in everyday life. These exposures come from "far-field" sources, such as persistent organic pollutants or other ubiquitous air-pollutants that have extended half-lives due to their chemical stability and resistance to environmental degradation. These chemicals can travel "far" distances and result in exposures through indirect routes. Chemical exposures also come from "near-field" sources within our immediate surroundings through either unintentional and direct application or routes. For the latter, acquisition of key information has to date been limited by our inability to keep up with the ever-changing chemicals used in consumer products and by incomplete characterization of the diversity in human activity and product use patterns. We envision that collecting personal product inventories and human activity profiles will eliminate current data gaps and enable individualized chemical exposure estimation.

Action
The Systems Reality Modeling (SRM) project will evaluate the potential use of modern technologies -such as smart phones, social networking, mobile product scanning, and multiple data-stream mash-ups - to characterize and model human exposures to environmental chemicals to develop a better understanding of exposure sources present in microenvironments.

There are ways (see Figure below) to curate both real-world activities and associated consumer products with demographic information through the use of modern technologies as defined above. These valuable data streams are largely untapped sources of exposure information for the population.

This information will be used to develop realistic simulations of human activities and activity-based chemical exposures for virtual populations. The simulations will be displayed via life-simulation computer games or virtual reality environments, (such as Second Life™ and The Sims™) which provide a tangible and visual understanding of potential exposure events. We refer to these methods of data collection and use of these data to develop simulation models as “Systems Reality Modeling” (SRM).

SRM is the data-driven modeling of physical reality to explore interactions of humans with their environment in virtual reality. It integrates information on human activity with chemical use to achieve systems or holistic modeling.

Results and Impact
This work outlines the information model and potential use of modern technology, such as smart phones, in characterizing and modeling human exposures to environmental chemicals. Specifically, the first portion of the project is to better understand the exposure sources present in micro-environments through a proof-of-concept study using this ubiquitous technology to gather individualized product/chemical inventories.

Despite its preeminence in the source-exposure-dose-effect continuum, chemical source information is generally not well integrated in exposure and risk assessment. In exposure studies, source information is often collected in an ad hoc fashion either by the investigators attempting to inventory products in homes or offices; or by study participants attempting to interpret chemical information from consumer product labels.

Our approach significantly increases the collection efficiency, amount, and quality of source data one can collect in a short period of time. This approach holds the potential to reduce the uncertainty and errors in real time data acquisition and interpretation. Ultimately, it will support and lead the Agency’s mission for a safer and more sustainable world through the use of innovative technologies that reduce consumption of material and natural resources with the digitalization of chemical inventories, human time/location and activity data, as well as their linkages to chemical, exposure, and toxicity databases and models.

Anticipated Products

  • Systems Reality Information Model: An outline of the datasets, databases, available repositories, and methods integrated into a workflow that defines how to go from activity patterns to use patterns to product space and personal chemical exposure space.
  • An integrated GUI front-end for a database to rapidly curate (through crowdsourcing) MSDS inventories
  • A Product chemical and % composition database: inventory derived from public MSDS literature mapped out to ACToR
  • Product Use Codes harmonization and mapping (SPIN, EFH, CHAD, HPDB, REACH, CPSC/NEISS etc...)
  • From Social Streams to Human Activity Patterns :Development of an archival and text mining process for NLP to convert social streams (Twitter / Facebook etc...) directly into human activity/location codes currently used in exposure estimation
  • Smart-phone APP UI/UX development for
    • low-burden activity/location journaling
    • conversion and mark-up of personal space to personal chemical exposure (AREA: Augmented Reality For Exposure Awareness)
  • A DIY comic book that captures the process of personal chemical informatics

Collaboration
Systems Reality Modeling Project on the Environmental Science Connector Collaboration Platform
(Contact individuals below to be added to the project for collaboration)

Contacts
Rocky Goldsmith, Ph.D.
Curtis C. Dary, Ph.D.

srm diagram

(Left:) To better characterize Human Matter interactions, and personal chemical exposure
(Right:) the schema demonstrating the overlap between three main enabling technologies (A,B,C) that form the foundation of personal chemical exposure informatics app development is provided. (A) Ubiquitous computing or smart-phones with embedded cameras can scan household product inventories by microenvironment. (B) Life streaming technologies serve as a low-burden means of reporting or background activity comparison, as well as actigraphy logging, reducing consumer burden on data-entry while effectively minimizing the Hawthorne effect from passive social stream mining by life-stage, gender, ethnicity and culture with geo-tagged entries. (C) just as all capturing mechanisms, reporting mechanisms, and actigraphy are embedded in smartphones, the full life-cycle of personal chemical informatics originates on smartphone devices, and concludes through judicious and effective communication of personal chemical exposures to everyday products via judicious visualization and analytics representations (C to A)

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