Atmospheric metal pollutants and environmental injustice: A methodological approach to environmental risk analysis using fuzzy logic and tree bark

Air pollution is the single largest environmental risk today and is increasing in developing countries. In addition, exposure to air pollution is correlated to poor socioeconomic conditions owing to political processes and cultural and historic occupation of land. Ports have several structures that are potential emitters of pollutants such as large ship engines, diesel trucks, and trains. Owing to the considerable costs of implementing direct monitoring networks, alternatives like biomonitoring are an interesting approach to evaluate the environmental status of a particular area using living organisms or their parts such as bark, even though the use of bark as a biomonitor has several problems such as difficulties in determining the exposure period and its correlation with human exposure. Therefore, the use of a complementary mathematical logic is necessary. This study describes a methodological approach to evaluate the environmental risk from air pollution integrating data on environmental pollutants from tree bark using Fuzzy logic, based in the port city of Paranagua in the state of Parana in Brazil, and validated using income indicators. The results indicate that the risk distribution patterns have an inverse relationship with the income indicator, i.e., higher risk levels indicate lower income levels and vice versa. It was concluded that the system was able to identify the distribution of risk and that there is a context of environmental injustice in the region, where the environmental risk related to air pollution is inversely proportional to income levels. This type of information provides a decision making tool for environmental risk analysis from air pollution and can be used in the definition of public policies. (C) 2016 Elsevier Ltd. All rights reserved.