Pipeline And Hazardous Materials Safety Administration Research Articles

A comparison of onshore oil and gas transmission pipeline incident statistics in Canada and the United States

This study analyzes the mileage and incident data between 1995 and 2016 corresponding to the onshore oil and natural gas transmission pipelines regulated by the Canada Energy Regulator (CER) and Pipeline and Hazardous Materials Safety Administration (PHMSA) of the United States. The analysis indicates that the material/weld/equipment failure is the leading failure cause for both CER and PHMSA pipeline incidents. The annual average incident rates of the CER and PHMSA pipelines are in the order of 10−3 per km except for the PHMSA gas pipelines, the annual incident rate of which is in the order of 10−4 per km. The annual average rupture rates of the CER and PHMSA pipelines vary from 3.5 × 10−5 to 4.5 × 10−5 per km. The F-N curves for the PHMSA pipelines are developed based on the mileage and incident data to quantify the societal risks posed by the pipeline in general.

Optimizing natural gas pipeline risk assessment using hybrid fuzzy bayesian networks and expert elicitation for effective decision-making strategies

Natural gas pipelines are susceptible to external and internal risk factors, such as corrosion, environmental conditions, external interferences, construction and design faults, and equipment failures. Bayesian Networks (BN) is a promising risk assessment approach widely used to evaluate these risk factors. One of BN's inherent limitations is its inability to accurately capture statistical dependencies and causal relationships, which can be overcome by incorporating expert elicitation into BN. To account for uncertainty and vagueness in assessing pipeline failure risks, fuzzy set theory (FST) can be combined with BN, commonly known as Fuzzy Bayesian Networks (FBN). This study developed an FBN framework that uses linguistic variables to calculate fuzzy probability (FPr) through domain expert elicitation, and crisp probabilities (CPr) are computed using historical incident data from the Pipeline and Hazardous Materials Safety Administration (PHMSA). Based on the findings from the case study of the Midwest region of the USA, external factors, i.e., third-party interference, outside force, and other incidents, significantly impact pipeline performance and reliability. Diagnosis inference indicates that in the Midwest region of the USA, pipeline material and age are critical factors leading to corrosion failure by threatening pipeline integrity. The findings from this study suggested that a targeted risk mitigation strategy is paramount for minimizing the risks associated with pipeline networks.

Underground natural gas storage facility operations and well leakage events in the United States

Federal minimum safety standards for underground natural gas storage (UNGS) operations in the United States (U.S.) were set by the Pipeline and Hazardous Materials Safety Administration (PHMSA) in the aftermath of the 2015 Aliso Canyon well leakage incident. Beginning in 2017, these standards required operators of U.S. UNGS facilities to publicly report: 1) leakage events that meet established criteria for incidents; 2) annual details of well construction, maintenance, and integrity testing activities; and 3) the occurrence of leading indicators of leakage (i.e., safety-related conditions). We reviewed both PHMSA reports and previously published studies to compile a dataset of 53 well leakage events at UNGS facilities in the U.S. that align with the PHMSA reporting requirements. Casings (55.0%) and wellheads (32.5%) were the most common failed well components identified. Human intervention through incorrect operation or outside force damage was the most common (39.3%) cause of well leakage events. Well leakage events caused by corrosion resulted in significantly greater emissions than those with other causes. UNGS annual reports detailed operations at 406 UNGS facilities with 17,993 wells—14,469 were injection and the remainder monitoring. Of these wells, 11,446 (63.6%) were reported to have a design that is potentially susceptible to a single point of failure, which is more than three times the previous estimate. Additional information about the status and construction of individual wells is needed to confirm the number of operational wells with a single-point-of-failure design. These data would help regulators identify single-point-of-failure wells and ensure the elevated risks associated with them are appropriately mitigated by proposed risk management plans. Statistically significant differences in the characteristics of UNGS facilities that have and have not experienced well leakage events were observed among those operating in depleted hydrocarbon reservoirs. Depleted hydrocarbon UNGS facilities that experienced well leakage events were generally larger, which suggests that focusing regulatory inspections and reviews on these facilities may be justified. The UNGS data reported were not sufficient to build a predictive model that forecasts well leakage events. Modeling efforts were limited by the data reporting format, which requires UNGS operators to aggregate data by facility in their annual reports. Gathering and evaluating information for individual wells at UNGS facilities would be valuable and may provide additional insights into well leakage risks to better inform risk management planning efforts.

Predicting Natural Gas Pipeline Failures Caused by Natural Forces: An Artificial Intelligence Classification Approach

Pipeline networks are a crucial component of energy infrastructure, and natural force damage is an inevitable and unpredictable cause of pipeline failures. Such incidents can result in catastrophic losses, including harm to operators, communities, and the environment. Understanding the causes and impact of these failures is critical to preventing future incidents. This study investigates artificial intelligence (AI) algorithms to predict natural gas pipeline failures caused by natural forces, using climate change data that are incorporated into pipeline incident data. The AI algorithms were applied to the publicly available Pipeline and Hazardous Material Safety Administration (PHMSA) dataset from 2010 to 2022 for predicting future patterns. After data pre-processing and feature selection, the proposed model achieved a high prediction accuracy of 92.3% for natural gas pipeline damage caused by natural forces. The AI models can help identify high-risk pipelines and prioritize inspection and maintenance activities, leading to cost savings and improved safety. The predictive capabilities of the models can be leveraged by transportation agencies responsible for pipeline management to prevent pipeline damage, reduce environmental damage, and effectively allocate resources. This study highlights the potential of machine learning techniques in predicting pipeline damage caused by natural forces and underscores the need for further research to enhance our understanding of the complex interactions between climate change and pipeline infrastructure monitoring and maintenance.

Environmental risk of oil pipeline accidents

Oil spills from pipeline accidents, caused by either material degradation or improper operation, can result in long-lasting environmental damage to soil and water. Assessing the potential environmental risks of these accidents is crucial for effective pipeline integrity management. This study calculates the accident rate using Pipeline and Hazardous Materials Safety Administration (PHMSA) data and estimates the environmental risk of pipeline accidents by factoring in the cost of environmental remediation. Results show that crude oil pipelines in Michigan pose the highest environmental risk, while Texas has the highest environmental risk for product oil pipelines. On average, crude oil pipelines have a higher environmental risk (56,533.6 US dollars·times·mile−1·year−1) compared to product oil pipelines (13,395.6 US dollars·times·mile−1·year−1). Factors affecting pipeline integrity management are also analyzed, including diameter, diameter-thickness ratio, and design pressure. The study finds that larger pipelines with higher pressures receive more attention during maintenance and thus pose a lower environmental risk. Furthermore, underground pipelines pose a much higher environmental risk than pipelines in other environments, and pipelines are more vulnerable in the early and mid-stages of operation. The leading causes of environmental risk in pipeline accidents are material failure, corrosion, and equipment failure. By comparing environmental risks, managers can better understand the strengths and weaknesses of their integrity management efforts.

Evaluation protocols for flammable and toxic dispersion models

AbstractThe siting of liquefied natural gas (LNG) facilities requires several types of hazards to be quantified so that the risk to the public and public property in areas surrounding each facility can be properly assessed. In order to quantify the hazards from potential accident scenarios, computational tools must be used. Given the multiplicity of tools available, ranging from empirical models to 3D computational fluid dynamics packages, the agency responsible for reviewing the hazard analysis may not have the methodologies or protocols necessary to determine the suitability of a given model to a certain scenario, its accuracy, and any other setup requirements. The Pipeline and Hazardous Materials Safety Administration (PHMSA) commissioned Blue Engineering and Consulting and the Gas Technology Institute to develop a set of model evaluation protocols (MEPs) that will allow the review of modeling tools for several different hazards, including flammable and toxic dispersion, source terms for dispersion models, vapor cloud explosions, and boiling liquid expanding vapor explosions (BLEVEs). The project will provide PHMSA with the means to properly evaluate modeling tools for these hazards, which are required to be evaluated in an LNG facility siting study. It will also provide clarity to LNG plant developers and their safety consultants on which models may be used and which safety factors need to be applied, and will increase the public's confidence in the regulatory review process of LNG facilities. This article discusses the first two MEPs completed as part of this project, which are focused on evaluating flammable dispersion and toxic dispersion models, respectively. This article describes the evaluation methodology, including the information to be submitted by the model proponents and the review process, and the model validation databases compiled for each protocol.

Too many or not enough? A methodology for evaluating fire and gas detector layouts at LNG facilities

AbstractNFPA 59A Standard for the Production, Storage, and Handling of Liquefied Natural Gas (LNG) requires facilities to have the equipment necessary for the detection and control of fires, leaks and spills of hazardous materials, yet provides no requirements or guidance on the location of the detectors. Literature available in the public domain outlines key factors to consider in developing layouts for flame and gas detectors, but a methodology to use this information in evaluating a hazard detector layout is not clearly defined; instead, generic and non‐quantifiable terminology such as “quick and reliable” is often used. As a result, there is no consistent approach to developing flame and gas detector layouts for land‐based LNG facilities and there is no systematic method for regulators to evaluate these designs. The ability to quantify hazard detector performance and define performance targets are of particular interest to the Department of Transportation (DOT) Pipeline and Hazardous Materials Safety Administration (PHMSA), which regulates numerous LNG facilities in the United States. Blue Engineering and Consulting is working on a DOT‐PHMSA sponsored project to develop a risk‐based approach and criteria for hazard detector layouts at LNG facilities. This project builds upon performance‐based design principles outlined in NFPA 72 National Fire Alarm and Signaling Code and the International Society of Automation (ISA) technical report 84.00.07 Guidance on the Evaluation of Fire, Combustible Gas, and Toxic Gas System Effectiveness. The methodology divides the LNG facility into Detection Areas based on the hazards present and the plant layout, identifies the appropriate hazard scenarios to evaluate the detector layout, establishes performance targets for each Detection Area, and quantifies hazard detector coverage. This paper will describe and demonstrate the proposed methodology. It should be noted that, while performance targets must be chosen for the purposes of the demonstrative included in this paper, these targets should not be interpreted as requirements of DOT‐PHMSA nor as acceptable to them.

Identifying causality and contributory factors of pipeline incidents by employing natural language processing and text mining techniques

The key to learning from the past incidents is to identify the underlying causes and contributory factors of the incidents. A large amount of text data on incident narratives has been accumulated over the years and can be a good learning source, if properly utilized. However, the vast amount and unstructured nature of the text data impedes generating insights on occurring patterns of incidents. This research sets upon applying natural language processing (NLP) and text mining techniques to utilize the resource for understanding contributing factors and causations behind the incidents with pipeline industry as an illustrative example. The 3587 records of incident narratives of the ‘comment’ section in the incident database of Pipeline and Hazardous Materials Safety Administration (PHMSA) are exploited. Two methods of text analytics, K-means clustering and co-occurrence network, are employed to infer latent causality of incidents. The results demonstrate that both methods are capable of identifying contributing factors under specific failure types. The co-occurrence network approach exhibits advantages on extracting dependency among the contributory factors, while K-means clustering is only able to indicate general correlations. The workflow proposed in this paper provides new perspectives of identifying contributing factors and their causal dependency from incident text data for promising applications in risk analysis and accident modeling.

Quantifying Variable Importance in Predicting Critical Span Length and Scour Depth for Failure of Onshore River Crossing Pipelines Using ANN

Onshore oil and gas pipelines are often buried beneath the river bed and channel banks. One of the primary reasons for the exposure of buried pipelines is the scouring mechanism that occurs when shear stress induced on riverbed by flowing water exceeds the resistance of channel bed material. Depending on the free spanning length and watercourse flow velocity, the vortex shedding phenomena may cause interactions resulting in a catastrophic pipeline failure. Accurate estimation of parameters that influence critical span length and scour depth become extremely important to maintain the integrity of the pipeline system and optimize its effective service life. This study is aimed at quantifying the relative importance of input variables used in predicting critical span length and scour depth based on the weights obtained from an Artificial Neural Network (ANN). The Artificial Neural Network model is developed by collecting pipeline accident reports from Pipeline and Hazardous Material Safety Administration (PHMSA) database for accidents that occurred due to Vortex Induced Vibration (VIV) loading during flooding in the last 35 years. It is seen that factors such as internal fluid pressure, dynamic lateral and vertical soil stiffness, reduced velocity and age of pipeline have a significant contribution in terms of model weights and help in accurately assessing the pipeline’s vulnerability to failure.

Analysis of Thermal Runaway Incidents Involving Lithium Batteries in U.S. Commercial Aviation

Thermal runaway incidents involving lithium batteries as cargo, in luggage, or as personal property in the cabin have been associated with fatalities, the destruction of cargo, and even the loss of entire aircraft. This research represents the first examination of the incidence of lithium battery thermal runaway incidents involving a variety of rechargeable lithium-ion and lithium metal batteries on commercial flights in the U.S.A. The objective is to examine the occurrence of these thermal runaway incidents and the circumstances surrounding them from the best available data source, the Pipeline and Hazardous Materials Safety Administration (PHMSA) hazardous material incident database. Using descriptive statistics, the frequency of incidents and the circumstances surrounding these incidents, including incident characteristics, device type, preceding event, activity of device, and location of incident between 1996 and July 2019, are examined. There were records of 274 thermal runaway incidents in U.S. commercial air transportation during the approximately 23-year period., with 76% of these incidents reported since 2015. Fire was the most commonly reported characteristic and loose lithium batteries not otherwise specified were the most common device involved in these thermal runaways. Missing information on the circumstances surrounding incidents among was a common condition, and “Not Specified” represented the largest categorization of preceding events, activity of device and the second largest category of location. The focus of this paper is aviation, but it is expected that some of the insights and lessons learned from incidents in aviation can be extended to other modes of transportation as well.

Towards a causal model from pipeline incident data analysis

Pipeline network facilitates transportation of hazardous materials over long distances and is considered a relatively safer mode of transportation. However, a significant number of incidents occurred over the last few years that has increased the need for development of an accurate predictive model for incidents. Pipeline incident databases have been collecting a wide range of data regarding the incidents including the background operating conditions, the causes contributed to the incident, and the severity of consequences. Most academic studies analyzing these databases have developed predictive failure models focusing only on a narrow range of factors that played a role behind certain categories of incidents. They fail to provide a holistic understanding of how interaction of multiple factors contributing to an incident or how their combined effect eventually leads to failure. The amount of data collected in the databases are however huge. For example, the current reporting format of Pipeline and Hazardous Materials Safety Administration (PHMSA) collects over six hundred datapoints from each incident. Given the large amount of information available and current technologies, it is now possible to look into ways to understand the holistic effect of all contributing factors. The current study looks into how the databases can be utilized to derive such a complete understanding. The study compares the databases of US PHMSA, Canada National Energy Board (NEB), and European Gas Pipeline Incident Data Group (EGIG) to examine the frameworks used to classify the causal factors of the incident data and shows that the background factors, underlying factors and the causal factors identified in the various databases are inter-related and show varying degrees of dependency. This curves the way forward to development of a causal model that will help identify the important factors that needs to be addressed and a prediction of future failure given existing conditions of a pipeline system.

Review of failure trends in the US natural gas pipeline industry: An in-depth analysis of transmission and distribution system incidents

Natural gas (NG) transmission and distribution pipelines play an integral role in the United States (US) energy infrastructure. Various incidents over the past decades have caused growing concern as to the current condition of such pipelines in the US. Significant incidents were analyzed to understand the circumstances and causes to enable one to increase transmission and distribution line safety. Various data sets pertaining to significant US natural gas pipeline failures were analyzed in terms of transmission and distribution (main) pipelines. These categories were individually analyzed to develop an overall understanding of trends. While the report focuses on incidents over the ‘10 – ‘17 timeframe, additional analyses are included in the Appendix for two earlier time periods, ‘97 – ‘01 and ‘02 – ‘09. Only ‘significant’ incidents were included in the analysis, totaling 3000, and categorized in terms of: number of incidents, fatalities; pipe material; release type; ignition/explosion; location of loss; age of pipe; and cause of incident.Four significant incidents within the distribution sets and three significant incidents within the transmission sets were further analyzed as case studies, seven in all. The case studies were developed to provide an in-depth analysis of events leading to failures, providing additional information gathered by the National Transportation Safety Board (NTSB), Pipeline and Hazardous Material Safety Administration (PHMSA), and additional local utility commissions. Finally, recommendations are made for further work in this area, including comparison of the findings of this analysis with on-going steps by the NG pipeline industry to reduce failures.

Risk Assessment of Incidents Response for Downstate New York Natural Gas Distribution Infrastructure

In the United States today, there are thousands of miles of an extended network of natural gas pipelines across the nation. Current pipeline explosions and leaks in several regions have challenged the natural gas industry to re-evaluate efforts and to pursue proactive strategies. Safety and the environmental threat has become a primary concern in the United States and around the world, but mostly in cases where natural gases, oil, and other hazardous wastes are intricate. Thus, a significant point in the natural gas pipeline industry that signifies both the economic and social issue is the unplanned pipeline risk. In this article, a quantitative data analysis was performed for Downstate New York companies, Con Edison and National Grid. There, the data from various natural gas pipelines was observed for the trend regarding failing material, failure cause, aging characteristics, and perform a risk assessment to come up with training and risk checklist that could be crucial for risk handling strategies. The statistical analyses of the natural gas pipeline-related incident data for distribution pipelines between 2012 and 2016, which were composed from Pipeline and Hazardous Material Safety Administration (PHMSA) of the United States Department of Transportation (DOT), are compiled. The total miles in the gas distribution pipelines in downstate New York is approximately 48,539 as of 2016. The equipment failure, other incident cause, other outside force, and excavation damages are the leading causes of the pipe-related incidents, which are responsible for over 20% of the total incidents between 2012 and 2016. As a result, a quantitative research methodology has been developed as the suitable approach to achieve risk assessment. Mainly, this approach aims towards risk management in natural gas industry projects using the maximum likelihood method on 70 rupture incidents between 2012 and 2016, which were collected from the PHMSA pipeline incident database. The hypothetical quantitative risk assessment of the gas distribution pipelines are illustrated by combining the statistics of the pipeline rupture incidents, as well as risk assessment performed in the present study.

Statistical analysis of environmental consequences of hazardous liquid pipeline accidents

Although pipelines are the safest method to transport fuels, they are associated with risks due to failures, leading to significant negative consequences. This paper investigates pipeline accident data provided by PHMSA (Pipeline and Hazardous Material Safety Administration) between 2010 and 2017, with a focus on environmental consequences of hazardous liquid pipeline accidents. The average amount of released product, the average time elapsed between the accident, the emergency response from the oil company, and the average costs of environmental remediation are estimated. The impact on soil, water, and wildlife is investigated for frequency and magnitude, where possible. It was found that, on average, 85% of product released after an accident remained unrecovered, 53% of accidents led to soil contamination, 41% of accidents impacted environmentally sensitive areas, and 92% of water crossing pipelines involved in accidents were uncased. From an annual average total cost of USD 326 million, annual average environmental damage and remediation costs were USD 140 million. This analysis assists in the diagnosis of challenges that might be addressed with improved maintenance and inspection programs, especially for pipelines at higher risk of negative environmental consequences. Finally, the performance of safety management systems should be improved to efficiently respond to emergencies.

Natural gas distribution system: A statistical analysis of accidents data

Natural Gas (NG) distribution is obtained by a really complex system that must ensure safe conditions and avoid human or economic losses. This paper analyzes accidents that occurred between 2004 and 2015 in the United States distribution systems and were recorded in the Pipeline and Hazardous Material Safety Administration (PHMSA) database. Statistical trends are studied; number of accidents, injuries and fatalities are shown and risk indexes are proposed for different accident causes. An average value of 2.09 × 10−5 accidents/km are found in US distribution systems and it is shown that natural events pose the highest risk to distribution systems. Working conditions, such as pressure, pipe diameter and system age are considered in the study, finding that the low pressure and diameter systems account for the greatest number of injuries and fatalities in the case of failure. On the basis of the results, recommendations are given to sector stakeholders.

Risk assessment of class 3 (PG II & III) hazardous materials in transportation

Risks associated with transportation of Class 3 packing group II & III hazardous materials in transport by motor carriers were investigated. Incident data of transportation of Class 3 materials was collected from the Pipeline and Hazardous Materials Safety Administration (PHMSA) database for a period of 10 years (2005–2014). The collected incident data was screened later for small quantities (≤ 8 gallons) and for single component (32,455 incidents). Root causes of the incidents (31,307 incidents) were categorized according to different transportation phases and corresponding frequencies were determined. Using the available consequence data (fatality/injury, financial damage, and quantity released) incident pyramids were prepared and later risk matrices were developed for fatality/injury, financial damage, and quantity released. Analysis found the risk of Class 3 (PG II & III) material in transportation a low consequence‐high frequency phenomenon and also revealed some key issues such as almost two‐third of the total incidents occurred during “unloading” phase of the transportation. Procedural deviation and human error were found as the two most frequently cited categories, and there was no incident resulting in fatality in these ten years. © 2018 American Institute of Chemical Engineers Process Process Saf Prog 37:376–381, 2018

Canada’s federal database is inadequate for the assessment of environmental consequences of oil and gas pipeline failures

In Canada, the National Energy Board (NEB) regulates inter-provincial oil and gas pipelines and maintains historical records that contain data on oil and gas pipeline accidents; these data include information about operators, the accidents’ cause, and the resulting consequences. New inter-provincial pipelines are being built in Canada to transport fuels, but no comprehensive statistical analysis of the risk to environmental receptors exists. This study assesses the quality and quantity of NEB pipeline failure data available in Canada with a focus on environmental consequences and investigates differences between Canada and a more thoroughly studied jurisdiction, the United States, in tracking accident data. The discrepancies in agencies’ jurisdiction and regulated mileage are analyzed, along with reporting criteria and initial recording year. The level of detail provided by the two agencies is compared, identifying deficiencies in data collection. The Pipeline and Hazardous Materials Safety Administration (PHMSA) regulates 76% of pipelines in the United States, whereas the NEB only monitors 9% of pipelines in Canada. PHMSA provides four databases that include accidents from the 1980s for most pipelines and from 2011 for liquefied natural gas facilities; the NEB database includes accident data starting from 2008, which derive primarily from transmission pipelines. Information about environmental consequences is quite detailed in the US database, which reports 21 descriptive fields, whereas in Canada only two NEB database fields describe environmental outcomes. Moreover, dissimilarities in accident reporting criteria prevent the combination of data from the two agencies. Consequently, the NEB database does not allow for statistically robust and system wide analysis of the environmental consequences of pipeline failures in Canada. Furthermore, to calculate failure rates (annual number of accidents per kilometre of pipeline) for regulated pipelines, annual total mileage estimates are required. Mileage per year is provided by PHMSA for gas gathering, transmission, and distribution pipelines starting from 1984, and for hazardous liquid pipelines from 2004; the NEB provides annual mileage from 2010, a shorter period of record. The Canadian federal agencies are encouraged to improve accuracy and consistency in recording past accidents and in collecting pipeline data, with the goal of preventing and minimizing future pipeline failures.

Statistical model and structural reliability analysis for onshore gas transmission pipelines

Abstract The reliability of gas pipelines against rupture can be estimated based on historical failure data and theory of structural reliability. In this study, an integrated model for reliability analysis of failure data is presented jointly with a robust structural reliability model for the purpose of comparison and cross-verification. The statistical model adopts a parametric hybrid empirical hazard model complemented with a robust data processing technique known as the nonlinear quantile regression for reliability analysis and prediction. This model provides inferences on the complete lifecycle reliability of the average pipe segment in the region under study. The structural reliability model is segment based and estimates rupture probabilities due to external metal loss corrosion. The non-homogeneous Poisson process is used to model the generation of new defects and the Poisson square wave process is used to model the growth of defects. The internal pressure load is modelled as a discrete Ferry-Borges stochastic process. Then, an inspection and maintenance plan is incorporated based on ASME B31.8S code of practice, for the service life considered. The probability of detection and measurement error of the inspection tools is also incorporated in the model. A numerical example of these models in an industrial context is presented. Onshore gas transmission pipeline rupture data for the period from 2002 to 2014, was obtained from the United States Department of Transportation Pipeline and Hazardous Materials Safety Administration (PHMSA) database and analysed. The comparative study of the proposed methodologies can assist gas pipeline operators in the informed implementation of optimal maintenance strategies based on risk prioritization.

Revised PREP Guideline Review: What You Should Know?

ABSTRACT No. 2017 – 296 On April 11, 2016 the U.S. Coast Guard (USCG), the Environmental Protection Agency (EPA), the Pipeline and Hazardous Materials Safety Administration (PHMSA), and the Bureau of Safety and Environmental Enforcement (BSEE) released the 2016 National Preparedness for Response Exercise Program (PREP) Guidelines. The new guidelines became effective on June 10, 2016 and replaced the previous guidelines issued in 2002. Established under the Oil Pollution Act of 1990 (OPA 90), the PREP guidelines were developed to provide a mechanism for compliance with response plan drill and exercise requirements under the Act and implementing regulations. Use of the PREP Guidelines is voluntary, however, compliance with the PREP guidelines will satisfy these requirements. The 2016 PREP Guidelines apply to all OPA 90 response plan holders including USCG regulated vessels and marine transportation-related facilities, EPA non-transportation-related onshore and offshore facilities, PHMSA-regulated facilities and pipelines, BSEE-regulated offshore facilities and area on-scene coordinator (OSC) exercises. The guidelines specify that, within a three-year cycle, all elements of the Facility Response Plan (FRP) or Vessel Response Plan (VRP), including the 15 core components, should be exercised in a drill, or series of drills, involving the Owner/Operator, Qualified Individual (QI), Oil Spill Removal Organizations (OSRO) and Salvage and Marine Firefighting (SMFF) resource providers. This paper will provide an overview of the PREP requirements, including plan holder initiated exercises, the remote assessment and consultation exercises (RACE) for vessels, shore-based tabletop exercises, response equipment deployment exercises, and Government Initiated Unannounced Exercises (GUIEs). As the QI, O’Brien’s has designed, conducted, played, and or evaluated well over 1,000 PREP related activities. This paper will discuss the implementation of PREP from the QI’s perspective, and the identification of some lessons learned and best practices that may be applicable more broadly to support the regulated industry and response community with the implementation of PREP.

Learning from Experience: Three Case Studies in International Regulatory Cooperation, A Report Prepared for the European Commission

Since at least 1990 regulators in the United States, Canada and the European Union have been exploring avenues for deeper collaboration in the fields of health, safety, environmental and financial regulation. These efforts have been driven by three main goals: to reduce regulatory costs of compliance for industry, to leverage scarce agency resources, and to steer regulatory standards in a globalizing marketplace in the right direction. Past efforts at transatlantic regulatory collaboration have yielded, at best, mixed results. But they have also generated a trove of valuable experience which can be used to inform the most recent initiative -- the Transatlantic Trade and Investment Partnership (TTIP) between the United States and the European Union -- which is currently is currently in negotiations and has made the promotion of regulatory cooperation a top priority for both sides. What can be learned from past experience to inform ongoing efforts to promote international regulatory cooperation in TTIP and beyond? In this empirical study, sponsored by the European Commission, two administrative law scholars draw on extensive primary research to craft three case studies of transnational regulatory cooperation involving the US Federal Aviation Administration (FAA), the Pipeline and Hazardous Materials Safety Administration (PHMSA), and the Food and Drug Administration (FDA, working with their foreign counterparts to address shared safety risks. The closely-analyzed experience of these three agencies' efforts yields a rich array of insights that should interest both scholars of administrative law and trade negotiators/regulators charged with strengthening international regulatory cooperation in these and other regulatory regimes.