Researchers from Universidad Politécnica de Madrid (UPM) are developing a tool to estimate the health effects of urban agriculture.
A team of expert from the School of Mining and Energy Engineering at UPM has assessed the health risk for users of urban garden thanks to a calculation routine of own elaboration (EnviroPRA) of free access. By optimizing the models through a probabilistic analysis, researchers have proved that users of urban gardens in Madrid have a level of exposure to pollutants low enough to not exceed the risk thresholds for the health.
Urban agriculture has recently resurged worldwide. This activity contributes to the achievement of several Sustainable Development Goals set by the United Nations General Assembly for the year 2030, among others: 2) Achieve food security and improved nutrition and promote sustainable agriculture, 11) Make cities and human settlements inclusive, safe, resilient and sustainable, 12) Ensure sustainable consumption and production patterns or 13) Take urgent action to combat climate change.
Therefore, urban agriculture could help cities become more self-sufficient and could promote a sustainable circular economy. However, urban soils are frequently enriched in contaminants due to past and present human activities. “For this reason, it could exist a potential health risk for users of these gardens either gardeners or consumers of the products” Miguel Izquierdo explains, a UPM researcher involved in this study.
Previous work carried out by the PROMEDIAM research group at UPM, researchers revealed acceptable levels of risk for the population except for a worst-case scenario in which children use urban gardens as recreational areas and also eat the produce grown in them.
However, the factors considered in this analysis are very conservative and they are based on the criteria set by the U.S. Environmental Protection Agency that sets out the need to increase the detail level of the risk analysis by conducting a probabilistic analysis that includes habits of use and characteristics of the local population (these parameters can vary among the different populations).
Thus the goal of this research project was to collect specific data of the population and establish the accumulation factors of contaminants in food to add these parameters and performs a more refined risk assessment” Fernando Barrios, another researcher involved in this study, says.
The probabilistic risk analysis was conducted through a statistical tool of own elaboration (EnviroPRA). To feed this model, data from trace elements concentrations in soils and lettuces from urban gardens in the region of Madrid were obtained as well as data of habits and characteristics of users.
The use of specific data of the local population showed considerably lower risk rates than those obtained with generic values that were more reduced through the probabilistic estimation. The variables that statistically determined this result were the frequency of the visits and the vegetable consumption from the urban gardens.
These results show that standard exposure parameters and generic levels of reference for agriculture use are not the most suitable factors to establish the limit concentration risk of contaminants in urban gardens since the habits of use of these spaces vary greatly from one region to another.
“This research is especially interesting for administrations and environmental consultants since they can optimize the budget for remediation of contaminated sites”, Izquierdo explains. “The obtained results reveal that urban gardens could help cities become more auto-sufficient and promote a sustainable and circular economy” he concludes.
F. Barrio-Parra, M. Izquierdo-Díaz, A. Dominguez-Castillo, R. Medina, E. De Miguel. Human-health probabilistic risk assessment: the role of exposure factors in an urban garden scenario. (2019). Landscape and Urban Planning: 191-199.
M. Izquierdo, E. De Miguel, M.F. Ortega, J. Mingot. Bioaccessibility of metals and human health risk assessment in community urban gardens. (2015). Chemosphere 135: 312-318.
