Modeling the dynamics of DDT in a remote tropical floodplain: indications of post-ban use?

Abstract

Significant knowledge gaps exist regarding the fate and transport of persistent organic pollutants like dichlorodiphenyltrichloroethane (DDT) in tropical environments. In Brazil, indoor residual spraying with DDT to combat malaria and leishmaniasis began in the 1950s and was banned in 1998. Nonetheless, high concentrations of DDT and its metabolites were recently detected in human breast milk in the community of Lake Puruzinho in the Brazilian Amazon. In this work, we couple analysis of soils and sediments from 2005 to 2014 at Puruzinho with a novel dynamic floodplain model to investigate the movement and distribution of DDT and its transformation products (dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD)) and implications for human exposure. The model results are in good agreement with the accumulation pattern observed in the measurements, in which DDT, DDE, and DDD (collectively, DDX) accumulate primarily in upland soils and sediments. However, a significant increase was observed in DDX concentrations in soil samples from 2005 to 2014, coupled with a decrease of DDT/DDE ratios, which do not agree with model results assuming a post-ban regime. These observations strongly suggest recent use. We used the model to investigate possible re-emissions after the ban through two scenarios: one assuming DDT use for IRS and the other assuming use against termites and leishmaniasis. Median DDX concentrations and p,p'-DDT/p,p'-DDE ratios from both of these scenarios agreed with measurements in soils, suggesting that the soil parameterization in our model was appropriate. Measured DDX concentrations in sediments were between the two re-emission scenarios. Therefore, both soil and sediment comparisons suggest re-emissions indeed occurred between 2005 and 2014, but additional measurements would be needed to better understand the actual re-emission patterns. Monte Carlo analysis revealed model predictions for sediments were very sensitive to highly uncertain parameters associated with DDT degradation and partitioning. With this model as a tool for understanding inter-media cycling, additional research to refine these parameters would improve our understanding of DDX fate and transport in tropical sediments.

Mapping Geospatial Processes Affecting the Environmental Fate of Agricultural Pesticides in Africa

“…Only three out of 24 identified models were developed, calibrated and validated in tropical or sub-tropical areas: the Dynamic Multimedia Environmental Fate Model [22] was developed for the tropical floodplains of Brazil, the Chemical Fate Model [18] was developed for a tropical river catchment in Australia and the Pesticides RIsks in the tropics to Man, Environment and Trade Pesticide model (PRIMET) [34] was developed in Southeast Asia and later adapted to Ethiopia (PRIMET-Ethiopia) [79]. Some models were developed elsewhere, but applied in tropical and sub-tropical areas.…”

Enabling forecasts of environmental exposure to chemicals in European agriculture under global change

“…Boxall et al (2009) identified the need to generate flood emersion models in the context of chemical exposure pathways for agricultural systems. Since their review, a handful of studies have developed modelling frameworks that investigate the impact of flood dynamics on chemical fate and transport (e.g., Mendez et al, 2016;Camenzuli et al, 2012). Camenzuli et al (2012), for example, developed a model to simulate flooding within an Australian river basin and the impact of this on the mobilization of diuron.…”

Limnological perspectives on conservation of floodplain lakes in the Amazon basin

“…Road crossings block streams and alter instream habitat, connectivity, and biological assemblages (Leal et al, 2016; Leitão et al, 2018). Control of insect vectors of diseases has employed widespread use of DDT (now prohibited, although persistent) and other pesticides that contaminate aquatic ecosystems and their biota (Mendez et al, 2016).…”