Modelling the bioaccumulation of persistent organic pollutants in agricultural food chains for regulatory exposure assessment

New models for estimating bioaccumulation of persistent organic pollutants in the agricultural food chain were developed using recent improvements to plant uptake and cattle transfer models. One model named AgriSim was based on K OW regressions of bioaccumulation in plants and cattle, while the other was a steady-state mechanistic model, AgriCom. The two developed models and European Union System for the Evaluation of Substances (EUSES), as a benchmark, were applied to four reported food chain (soil/air-grass-cow-milk) scenarios to evaluate the performance of each model simulation against the observed data. The four scenarios considered were as follows: (1) polluted soil and air, (2) polluted soil, (3) highly polluted soil surface and polluted subsurface and (4) polluted soil and air at different mountain elevations. AgriCom reproduced observed milk bioaccumulation well for all four scenarios, as did AgriSim for scenarios 1 and 2, but EUSES only did this for scenario 1. The main causes of the deviation for EUSES and AgriSim were the lack of the soil-air-plant pathway and the ambient air-plant pathway, respectively. Based on the results, it is recommended that soil-air-plant and ambient air-plant pathway should be calculated separately and the K OW regression of transfer factor to milk used in EUSES be avoided. AgriCom satisfied the recommendations that led to the low residual errors between the simulated and the observed bioaccumulation in agricultural food chain for the four scenarios considered. It is therefore recommended that this model should be incorporated into regulatory exposure assessment tools. The model uncertainty of the three models should be noted since the simulated concentration in milk from 5th to 95th percentile of the uncertainty analysis often varied over two orders of magnitude. Using a measured value of soil organic carbon content was effective to reduce this uncertainty by one order of magnitude.

Crocodiles in the regulatory swamp: navigating the dangers of outsourcing, SaaS and shadow IT

Corporates are entering the brave new world of the internet and digitization without much regard for the fine print of a growing regulation regime. More traditional outsourcing arrangements are already falling foul of the regulators as rules and supervision intensifies. Furthermore, ‘shadow IT’ is proliferating as the attractions of SaaS, mobile, cloud services, social media, and endless new ‘apps’ drive usage outside corporate IT. Initial cost-benefit analyses of the Cloud make such arrangements look immediately attractive but losing control of architecture, security, applications and deployment can have far reaching and damaging regulatory consequences. From research in financial services, this paper details the increasing body of regulations, their inherent risks for businesses and how the dangers can be pre-empted and managed. We then delineate a model for managing these risks specifically focused on investigating, strategizing and governing outsourcing arrangements and related regulatory obligations

Post-crisis regulatory reforms and bank performance: lessons from Asia

Based on a large dataset from eight Asian economies, we test the impact of post-crisis regulatory reforms on the performance of depository institutions in countries at different levels of financial development. We allow for technological heterogeneity and estimate a set of country-level stochastic cost frontiers followed by a deterministic bootstrapped meta-frontier to evaluate cost efficiency and cost technology. Our results support the view that liberalization policies have a positive impact on bank performance, while the reverse is true for prudential regulation policies. The removal of activities restrictions, bank privatization and foreign bank entry have a positive and significant impact on technological progress and cost efficiency. In contrast, prudential policies, which aim to protect the banking sector from excessive risk-taking, tend to adversely affect banks cost efficiency but not cost technology.