Publications

Pesticides have many different properties that affect their behaviour in the environment. Pesticide’s solubility
in water has a great impact on leaching potential and environmental fate. The objective of this study was to determine the
relationship between organic carbon based partition coefficient (koc) and pesticides solubility (S) of pesticides used along the
shore of Lake Naivasha using regression analysis. The properties (S, and soil/water equilibrium partition coefficient (kd)) of
pesticides selected from an inventory of pesticides used in farms around Lake Naivasha, were determined from the
manufacturers’ materials safety data sheets. The organic carbon (foc) of the soil from the study area was then determined using
the loss-on-ignition (LOI) method and used to calculate koc. The results showed that the soils around Lake Naivasha had a
mean organic carbon (foc) content of 1.770% and a regression equation for koc and S for the area to be log koc = -0.368logS +
3.256. It was concluded that this relationship can be used to estimate the organic carbon based partition coefficient (koc) of a
pesticide where S is available, and the results compared with values determined experimentally and from other models.

In this work, ZnO thin films were investigated to sense NO2, a gas exhausted by the most common combustion systems polluting the environment. To this end, ZnO thin films were grown by RF sputtering on properly designed and patterned substrates to allow the measurement of the electrical response of the material when exposed to different concentrations of the gas. X-ray diffraction was carried out to correlate the material’s electrical response to the morphological and microstructural features of the sensing materials. Electrical conductivity measurements showed that the transducer fabricated in this work exhibits the optimal performance when heated at 200 °C, and the detection of 0.1 ppm concentration of NO2 was possible. Ab initio modeling allowed the understanding of the sensing mechanism driven by the competitive adsorption of NO2 and atmospheric oxygen mediated by heat. The combined theoretical and experimental study here reported provides insights into the sensing mechanism which will aid the optimization of ZnO transducer design for the quantitative measurement of NO2 exhausted by combustion systems which will be used, ultimately, for the optimized adjustment of combustion resulting into a reduced pollutants and greenhouse gases emission.

© 2016 The Author(s).Background: Motor vehicle collisions (MVCs) are a substantial contributor to the global burden of disease and lead to subsequent post-traumatic stress disorder (PTSD). However, the relevant literature originates in only a few countries, and much remains unknown about MVC-related PTSD prevalence and predictors. Methods: Data come from the World Mental Health Survey Initiative, a coordinated series of community epidemiological surveys of mental disorders throughout the world. The subset of 13 surveys (5 in high income countries, 8 in middle or low income countries) with respondents reporting PTSD after life-threatening MVCs are considered here. Six classes of predictors were assessed: socio-demographics, characteristics of the MVC, childhood family adversities, MVCs, other traumatic experiences, and respondent history of prior mental disorders. Logistic regression was used to examine predictors of PTSD. Mental disorders were assessed with the fully-structured Composite International Diagnostic Interview using DSM-IV criteria. Results: Prevalence of PTSD associated with MVCs perceived to be life-threatening was 2.5 {%} overall and did not vary significantly across countries. PTSD was significantly associated with low respondent education, someone dying in the MVC, the respondent or someone else being seriously injured, childhood family adversities, prior MVCs (but not other traumatic experiences), and number of prior anxiety disorders. The final model was significantly predictive of PTSD, with 32 {%} of all PTSD occurring among the 5 {%} of respondents classified by the model as having highest PTSD risk. Conclusion: Although PTSD is a relatively rare outcome of life-threatening MVCs, a substantial minority of PTSD cases occur among the relatively small proportion of people with highest predicted risk. This raises the question whether MVC-related PTSD could be reduced with preventive interventions targeted to high-risk survivors using models based on predictors assessed in the immediate aftermath of the MVCs.