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Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Ecological information needs for environmental justice.

Joanna Burger1, Stuart Harris, Barbara Harper

  • 1Division of Life Sciences, Environmental and Occupational Health Sciences Institute, Consortium for Risk Evaluation with Stakeholder Participation, 604 Allison Road, Piscataway, NJ 08854-8082, USA. burger@biology.rutgers.edu

Risk Analysis : an Official Publication of the Society for Risk Analysis
|April 23, 2010
PubMed
Summary
This summary is machine-generated.

Environmental justice (EJ) requires understanding community-specific ecological data. Standardizing information on demographics, resource use, and cultural practices is crucial for assessing environmental risks in vulnerable populations.

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Last Updated: Jun 13, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
12:44

Watershed Planning within a Quantitative Scenario Analysis Framework

Published on: July 24, 2016

Area of Science:

  • Environmental Science
  • Public Health
  • Sociology

Background:

  • Environmental justice (EJ) emphasizes equitable participation in decisions affecting community well-being.
  • Vulnerable populations, including those in small towns, rural areas, and low-income or minority communities, often face barriers to environmental decision-making due to information gaps.

Purpose of the Study:

  • To propose a template for essential ecological information needed to assess environmental risks to environmental justice populations.
  • To highlight the need for standardized information specific to environmental justice communities and populations.

Main Methods:

  • Case studies from South Carolina (DOE site), Washington (DOE site), and New Jersey (urbanized pollution) were used.
  • Analysis of available ecological and public health data relevant to risk assessments.
  • Identification of data gaps concerning EJ-specific information.

Main Results:

  • Standard ecological and public health data for risk assessments are often well-described.
  • Information on EJ communities, including demographics, resource use (consumptive/non-consumptive), eco-dependency, and eco-cultural attributes, is less standardized.
  • While data on standard consumption (e.g., fish) is available, detailed information on medicinal, cultural, and religious uses of regional environments is often lacking.

Conclusions:

  • A comprehensive understanding of environmental risks to EJ populations requires data beyond basic demographics.
  • Information on eco-dependency webs and eco-cultural attributes is vital for accurately assessing impacts on EJ communities.
  • Standardizing the collection of EJ-specific ecological and cultural information is necessary for effective environmental risk evaluation and policy development.