Spatial Analysis of Environmental Inequalities with Biomonitoring Data: A Cumulative Risk Assessment

摘要

Differential and not fair exposure to environmental risk factors across socio-demographic groups, called environmental justice (EJ), may contribute to inequalities in health and most often put disadvantaged groups at higher risk for environmental health effects. Main literature has difficulties to consider the potential exposure of populations to different levels of air pollutants. Cumulative and long-term exposures are still seldom considered. We propose a comprehensive EJ methodology to prioritize and characterize neighborhoods which takes into account the cumulative impact of health determinants. For this purpose, the use of environmental biomonitoring is an innovative approach to consider the integrated and long-term exposure to complex air pollution. Cumulative Impact Screening (CIS) methodology was used for two contrasted living areas of France. CIS is based on synthetic and composite index construction. Three scores were attributed to each neighborhood according to a cumulative calculation of key parameters: environmental score (using 3 air biomonitoring parameters: trace elements loads in lichens, lichenic biodiversity and dust deposition on poplar leaves), socioeconomic deprivation score and susceptible population score. Each score can be considered as a dimension of health vulnerability. CIS analysis and maps highlighted the unequal spatial distribution of EJ. After the multi-criteria hierarchization of spatial units, the influence of each dimension was characterized in each neighborhood with radar charts. We demonstrated that environmental biomonitoring is a smart approach to fill the lack of available data on multiple air pollution at the local scale. The tool developed is specific to the territory and transposable, which facilitate adoption by a variety of community and stakeholders and prioritization of public health actions. Correlations between EJ and health data are currently assessed to explain the spatial heterogeneity of chronic disease incidence.