Modeling Flood Stage-Duration-Frequency: A Risk Assessment of Critical Infrastructure in the Tidal Potomac

The service of a critical infrastructure, such as a municipal wastewater treatment plant (MWWTP), is taken for granted until a flood or another low frequency, high consequence crisis brings its fragility to attention. The unique aspects of the MWWTP call for a method to quantify the flood stage-duration-frequency relationship. By developing a bivariate joint distribution model of flood stage and duration, this study adds a second dimension, time, into flood risk studies. A new parameter, inter-event time, is developed to further illustrate the effect of event separation on the frequency assessment. The method is tested on riverine, estuary and tidal sites in the Mid-Atlantic region. Equipment damage functions are characterized by linear and step damage models. The Expected Annual Damage (EAD) of the underground equipment is further estimated by the parametric joint distribution model, which is a function of both flood stage and duration, demonstrating the application of the bivariate model in risk assessment. Flood likelihood may alter due to climate change. A sensitivity analysis method is developed to assess future flood risk by estimating flood frequency under conditions of higher sea level and stream flow response to increased precipitation intensity. Scenarios based on steady and unsteady flow analysis are generated for current climate, future climate within this century, and future climate beyond this century, consistent with the WWTP planning horizons. The spatial extent of flood risk is visualized by inundation mapping and GIS-Assisted Risk Register (GARR). This research will help the stakeholders of the critical infrastructure be aware of the flood risk, vulnerability, and the inherent uncertainty.

Mercury in Gas Operations - Occupational Health Risk Assessment

The project goal was to determine plant operations and maintenance worker’s level of exposure to mercury during routine and non-routine (i.e. turnarounds and inspections) maintenance events in eight gas processing plants. The project team prepared sampling and analysis plans designed to each plant’s process design and scheduled maintenance events. Occupational exposure sampling and monitoring efforts were focused on the measurement of mercury vapor concentration in worker breathing zone air during specific maintenance events including: pipe scrapping, process filter replacement, and process vessel inspection. Similar exposure groups were identified and worker breathing zone and ambient air samples were collected and analyzed for total mercury. Occupational exposure measurement techniques included portable field monitoring instruments, standard passive and active monitoring methods and an emerging passive absorption technology. Process sampling campaigns were focused on inlet gas streams, mercury removal unit outlets, treated gas, acid gas and sales gas. The results were used to identify process areas with increased potential for mercury exposure during maintenance events. Sampling methods used for the determination of total mercury in gas phase streams were based on the USEPA Methods 30B and EPA 1631 and EPA 1669. The results of four six-week long sampling campaigns have been evaluated and some conclusions and recommendations have been made. The author’s role in this project included the direction of all field phases of the project and the development and implementation of the sampling strategy. Additionally, the author participated in the development and implementation of the Quality Assurance Project Plan, Data Quality Objectives, and Similar Exposure Groups identification. All field generated data was reviewed by the author along with laboratory reports in order to generate conclusions and recommendations.

FLOOD RISK ASSESSMENT UNDER HISTORICAL AND PREDICTED LAND USE CHANGE USING CONTINUOUS HYDROLOGIC MODELING

Current procedures for flood risk estimation assume flood distributions are stationary over time, meaning annual maximum flood (AMF) series are not affected by climatic variation, land use/land cover (LULC) change, or management practices. Thus, changes in LULC and climate are generally not accounted for in policy and design related to flood risk/control, and historical flood events are deemed representative of future flood risk. These assumptions need to be re-evaluated, however, as climate change and anthropogenic activities have been observed to have large impacts on flood risk in many areas. In particular, understanding the effects of LULC change is essential to the study and understanding of global environmental change and the consequent hydrologic responses. The research presented herein provides possible causation for observed nonstationarity in AMF series with respect to changes in LULC, as well as a means to assess the degree to which future LULC change will impact flood risk. Four watersheds in the Midwest, Northeastern, and Central United States were studied to determine flood risk associated with historical and future projected LULC change. Historical single framed aerial images dating back to the mid-1950s were used along with Geographic Information Systems (GIS) and remote sensing models (SPRING and ERDAS) to create historical land use maps. The Forecasting Scenarios of Future Land Use Change (FORE-SCE) model was applied to generate future LULC maps annually from 2006 to 2100 for the conterminous U.S. based on the four IPCC-SRES future emission scenario conditions. These land use maps were input into previously calibrated Soil and Water Assessment Tool (SWAT) models for two case study watersheds. In order to isolate effects of LULC change, the only variable parameter was the Runoff Curve Number associated with the land use layer. All simulations were run with daily climate data from 1978-1999, consistent with the 'base' model which employed the 1992 NLCD to represent 'current' conditions. Output daily maximum flows were converted to instantaneous AMF series and were subsequently modeled using a Log-Pearson Type 3 (LP3) distribution to evaluate flood risk. Analysis of the progression of LULC change over the historic period and associated SWAT outputs revealed that AMF magnitudes tend to increase over time in response to increasing degrees of urbanization. This is consistent with positive trends in the AMF series identified in previous studies, although there are difficulties identifying correlations between LULC change and identified change points due to large time gaps in the generated historical LULC maps, mainly caused by unavailability of sufficient quality historic aerial imagery. Similarly, increases in the mean and median AMF magnitude were observed in response to future LULC change projections, with the tails of the distributions remaining reasonably constant. FORE-SCE scenario A2 was found to have the most dramatic impact on AMF series, consistent with more extreme projections of population growth, demands for growing energy sources, agricultural land, and urban expansion, while AMF outputs based on scenario B2 showed little changes for the future as the focus is on environmental conservation and regional solutions to environmental issues.

Structured professional judgement approach to risk assessment: generalisability across patient groups for the prediction of adverse outcomes in secure mental health care

This is a redacted version of the the final thesis. Copyright material has been removed to comply with UK Copyright Law.

EPA Radon Risk Assessment Table for Smokers and Non-Smokers

This chart gives the long term effects of radon on smokers and non-smokers.

Methodology for climate risk assessment of maize intercropped with Brachiaria in the Cerrado of Brazil.

2015

Risk assessment of the herbicide clomazone in the aquatic life.

Clomazone (2-(2-chlorophenyl)methyl-4.4-dimethyl-3-isoxazolidinone) is a post emergence herbicide widely used in rice fields in Rio Grande do Sul (Brazil) with high activity against Gramineae at the recommended application rate(AR).of 700g/ha. The herbicide input into the aquatic ecosystem may occur by aerial application or water drainage. The presence of this chemical in the water may affect non-target organisms leading to impairments in the aquatic food chain. Studies were conducted in this work to evaluate the risk of Clomazone using the estimated mean affective concentration (EC50) for the microalgae Selenastrum capricornutum(96h), the duckweed Lemna valdiviana(96h) and the crustacean Daphnia similis(48h). The EC50 values were 11.2; 31.7 and 13.8 mg/l, respectively. According to the obtained data, and considering a direct input of the herbicide in a 10cm column water, the estimated maximum application rate that doesn't cause acute effects is 5.3 AR for S. capricornutum, 6.5 AR for D. similis and 15.0 AR for L. valdiviana. The estimated maximum application rate that doesn't cause chronic effects is 2.0 AR for D. similis, 1.6 AR for S. capricornutum and 4.5 AR for L. valviana.

Research, development, and innovations in health risk assessment for brazilian agriculture.

Agriculture and livestock are key sectors of the Brazilian economy, which are essential for the country?s economic growth and for the equality between the domestic currency?s supply and demand. Agribusiness answered for about 23% of the gross domestic product (GDP) in 2015, according to Confederação Nacional da Agricultura (CNA), and reached 50.3% of total exports in February 2016, according to Secretaria de Relações Internacionais do Agronegócio (SRI) of Ministério da Agricultura, Pecuária e Abastecimento (Mapa) (Brasil, 2016). Currently, this sector is recognized as the most competitive and efficient in Brazil, considering the global scenario.

New methodologies for risk assessment of GMOs: an experiment of public consultation in Brazil.

2008

Consideration of problem formulation and option assessment (PFOA) for environmental risk assessment: Bt cotton in Vietnam.

2008

Development of a patient-specific model for stroke risk assessment in atrial fibrillation patients

Atrial fibrillation is associated with a five-fold increase in the risk of cerebrovascular events,being responsible of 15-18% of all strokes.The morphological and functional remodelling of the left atrium caused by atrial fibrillation favours blood stasis and, consequently, stroke risk. In this context, several clinical studies suggest that stroke risk stratification could be improved by using haemodynamic information on the left atrium (LA) and the left atrial appendage (LAA). The goal of this study was to develop a personalized computational fluid-dynamics (CFD) model of the left atrium which could clarify the haemodynamic implications of atrial fibrillation on a patient specific basis. The developed CFD model was first applied to better understand the role of LAA in stroke risk. Infact, the interplay of the LAA geometric parameters such as LAA length, tortuosity, surface area and volume with the fluid-dynamics parameters and the effects of the LAA closure have not been investigated. Results demonstrated the capabilities of the CFD model to reproduce the real physiological behaviour of the blood flow dynamics inside the LA and the LAA. Finally, we determined that the fluid-dynamics parameters enhanced in this research project could be used as new quantitative indexes to describe the different types of AF and open new scenarios for the patient-specific stroke risk stratification.

Risk assessment to improve food safety along different food chains

The great challenges of today pose great pressure on the food chain to provide safe and nutritious food that meets regulations and consumer health standards. In this context, Risk Analysis is used to produce an estimate of the risks to human health and to identify and implement effective risk-control measures. The aims of this work were 1) describe how QRA is used to evaluate the risk for consumers health, 2) address the methodology to obtain models to apply in QMRA; 3) evaluate solutions to mitigate the risk. The application of a QCRA to the Italian milk industry enabled the assessment of Aflatoxin M1 exposure, impact on different population categories, and comparison of risk-mitigation strategies. The results highlighted the most sensitive population categories, and how more stringent sampling plans reduced risk. The application of a QMRA to Spanish fresh cheeses evidenced how the contamination of this product with Listeria monocytogenes may generate a risk for the consumers. Two risk-mitigation actions were evaluated, i.e. reducing shelf life and domestic refrigerator temperature, both resulting effective in reducing the risk of listeriosis. A description of the most applied protocols for data generation for predictive model development, was provided to increase transparency and reproducibility and to provide the means to better QMRA. The development of a linear regression model describing the fate of Salmonella spp. in Italian salami during the production process and HPP was described. Alkaline electrolyzed water was evaluated for its potential use to reduce microbial loads on working surfaces, with results showing its effectiveness. This work showed the relevance of QRA, of predictive microbiology, and of new technologies to ensure food safety on a more integrated way. Filling of data gaps, the development of better models and the inclusion of new risk-mitigation strategies may lead to improvements in the presented QRAs.