A data-centric framework to perform end-of-life chemical flow analysis

[ES] Los productos químicos están presentes en actividades comerciales, industriales y de consumo en todo el mercado mundial. El número de sustancias químicas que circulan por el mercado no deja de crecer, lo que puede dificultar a los organismos gubernamentales la gestión del riesgo químico mediante la imposición de restricciones reglamentarias y a las empresas la selección de químicos con perfiles más seguros antes de lanzar los productos al mercado o utilizarlos en los procesos de fabricación. La identificación de los escenarios de exposición a las sustancias químicas y de las cantidades que pueden liberarse en el medio ambiente son tareas importantes para la evaluación del riesgo. Sin embargo, para estas tareas hay que recopilar datos exhaustivos, lo que las convierte en una tarea larga y difícil. Además, estas tareas son aún más difíciles en la fase de fin de vida (EoL, por sus siglas en inglés) debido a la incertidumbre epistémica sobre las vías exactas que siguen las sustancias químicas a través de la cadena de gestión EoL. Esta tesis pretende avanzar en el desarrollo de un marco holístico que permita realizar rápidamente el análisis del flujo químico (CFA, por sus siglas en inglés) para la estimación y asignación de emisiones y la identificación de escenarios de exposición en la fase de fin de vida. Se propone un enfoque centrado en los datos, en el que la ingeniería de datos desempeña un papel crucial en la recopilación, transformación, armonización y almacenamiento de datos procedentes de sistemas de bases de datos de acceso público, reglamentarios y aislados. En primer lugar, esta tesis explora el uso de los datos reglamentarios de Estados Unidos para rastrear las sustancias químicas contenidas en los flujos de EoL transferidos por las instalaciones industriales estadounidenses a lugares externos para su posterior gestión. En segundo lugar, este trabajo se adentra en las instalaciones industriales para identificar las posibles tecnologías de reducción de la contaminación aplicadas por las industrias, mejorando así el CFA y la asignación de flujos. En tercer lugar, los resultados de los dos pasos anteriores se conectan y amplían para describir el comportamiento de la cadena de gestión de EoL y el bucle de reciclaje, permitiendonos la identificación de transferencias de flujo entre industrias y los posibles escenarios de exposición posteriores al reciclaje. En cuarto lugar, se hace un esfuerzo por ampliar el marco más allá de la información estadounidense e incorporar datos de inventario de otros países y años. Por último, los datos obtenidos en el cuarto paso se utilizan para explorar el desarrollo de modelos basados en datos capaces de identificar posibles escenarios de exposición a la EoL y de incorporarlos al marco de comprensión de la cadena de gestión de EoL. Estos estudios están destinados a contribuir al desarrollo e implementación de una metodología para la detección rápida de posibles escenarios de exposición química de EoL y estimaciones de emisiones, así como para abordar los desafíos en la realización de la evaluación de riesgos químicos para la toma de decisiones regulatorias y la selección de productos químicos de perfil más seguro basado en el pensamiento del ciclo de vida. [EN] Chemicals are involved in commercial, consumer, and industrial activities across the world marketplace. The number of chemicals circulating in the market keeps growing, which can make it difficult for government agencies to manage chemical risk by imposing regulatory restrictions and for businesses to select chemical candidates with safer profiles before launching products into the market or using them in manufacturing processes. The identification of chemical exposure scenarios and the quantities of chemicals that may be released into the environment are important tasks for risk evaluation. Nonetheless, comprehensive data must be collected for these tasks, making them time-consuming and challenging. In addition, these tasks are even more difficult at the end-of-life (EoL) stage due to the epistemic uncertainty about the exact pathways taken by chemicals through the EoL management chain. This thesis aims at moving forward to develop a holistic framework to rapidly perform chemical flow analysis (CFA) for release estimations and allocation and exposure scenario identification at the EoL stage. A data-centric approach is proposed where data engineering plays a crucial role in collecting, transforming, harmonizing, and storing data from publicly-accessible, regulatory, and siloed database systems. First, this thesis explored the use of U.S. regulatory data to track chemicals contained in EoL flows transferred by U.S. industrial facilities to off-site locations for further EoL management. Second, this work moves into industrial facilities to identify the potential pollution abatement technologies implemented by industries, thereby improving the CFA and flow allocation. Third, the results of the above two steps are connected and extended to describe the behavior of the EoL management chain and recycling loop, allowing us to identify the inter-industry flow transfers and potential post-recycling exposure scenarios. Fourth, an effort is made to extend the framework beyond U.S. information and incorporate inventory data from other countries and years. Finally, the data obtained in the fourth step is used to explore the development of data-driven models able to identify potential EoL exposure scenarios and be incorporated into the framework for understanding the EoL management chain. These studies are intended to contribute to the development and implementation of a methodology for the rapid screening of potential EoL chemical exposure scenarios and release estimates, as well as to address the challenges in performing chemical risk evaluation for regulatory decisionmaking and selecting safer profile chemicals based on life cycle thinking

Development and application of a simulated urban system for geographical studies of environmental health

Urban areas are highly dynamic and diverse systems and the interactions and networks within an urban area are, at present, only partly understood, although some of the most important impacts on human health occur in these areas. It is essential, therefore, to develop a deeper understanding of these urban dynamics and processes especially with regard to exposure and health risk assessment. This thesis describes the development and application of an urban SImulation for ENvironmental health Analysis (SIENA). SIENA provides a controlled, simplified urban environment to develop and test spatial epidemiological concepts and models, to simulate processes and interactions relating to environmental exposure and to explore theoretical and methodological problems in the spatial analysis of environmental health. The development of the simulated urban system focuses on identifying and quantifying fundamental processes and inter-dependencies in the structure of urban areas in Great Britain. Twelve cities are chosen as sample cities and their spatial data structure (topography, transport network, land cover) and relationships between these structures and the urban population are statistically analysed. Based on the results of the statistical analysis SIENA is developed within a Geographic Information System (GIS) using probabilistic models and spatial analysis tools. Beside the identified core structure, topography, transport network, land cover and population, additional data such as traffic flow, air pollution monitoring networks or emissions from industrial sources amongst others are modelled and incorporated into SIENA. To demonstrate the potential of the simulation, SIENA is applied in two case studies both focusing on the misclassification of human exposure to urban air pollution. The first case study explores the representativeness of various air pollution monitoring networks and the resulting implications for exposure assessments. For the second case study, personal exposure is simulated within SIENA and then compared to the use of a location-based exposure proxy and the potential exposure misclassification spatially analysed

ECOS 2012

The 8-volume set contains the Proceedings of the 25th ECOS 2012 International Conference, Perugia, Italy, June 26th to June 29th, 2012. ECOS is an acronym for Efficiency, Cost, Optimization and Simulation (of energy conversion systems and processes), summarizing the topics covered in ECOS: Thermodynamics, Heat and Mass Transfer, Exergy and Second Law Analysis, Process Integration and Heat Exchanger Networks, Fluid Dynamics and Power Plant Components, Fuel Cells, Simulation of Energy Conversion Systems, Renewable Energies, Thermo-Economic Analysis and Optimisation, Combustion, Chemical Reactors, Carbon Capture and Sequestration, Building/Urban/Complex Energy Systems, Water Desalination and Use of Water Resources, Energy Systems- Environmental and Sustainability Issues, System Operation/ Control/Diagnosis and Prognosis, Industrial Ecology

Safety and Reliability - Safe Societies in a Changing World

The contributions cover a wide range of methodologies and application areas for safety and reliability that contribute to safe societies in a changing world. These methodologies and applications include: - foundations of risk and reliability assessment and management - mathematical methods in reliability and safety - risk assessment - risk management - system reliability - uncertainty analysis - digitalization and big data - prognostics and system health management - occupational safety - accident and incident modeling - maintenance modeling and applications - simulation for safety and reliability analysis - dynamic risk and barrier management - organizational factors and safety culture - human factors and human reliability - resilience engineering - structural reliability - natural hazards - security - economic analysis in risk managemen