Evaluation and recommendation of sensitivity analysis methods for application to Stochastic Human Exposure and Dose Simulation models

Background:Among nonoccupationally exposed U.S. residents, drinking water and diet are considered primary exposure pathways for inorganic arsenic (iAs). In drinking water, iAs is the primary form of arsenic (As), while dietary As speciation techniques are used to differentiate iAs from less toxic arsenicals in food matrices.Objectives:Our goal was to estimate the distribution of iAs exposure rates from drinking water intakes and rice consumption in the U.S. population and ethnic- and age-based subpopulations.Methods:The distribution of iAs in drinking water was estimated by population, weighting the iAs concentrations for each drinking water utility in the Second Six-Year Review data set. To estimate the distribution of iAs concentrations in rice ingested by U.S. consumers, 54 grain-specific, production-weighted composites of rice obtained from U.S. mills were extracted and speciated using both a quantitative dilute nitric acid extraction and speciation (DNAS) and an in vitro gastrointestinal assay to provide an upper bound and bioaccessible estimates, respectively. Daily drinking water intake and rice consumption rate distributions were developed using data from the What We Eat in America (WWEIA) study.Results:Using these data sets, the Stochastic Human Exposure and Dose Simulation (SHEDS) model estimated mean iAs exposures from drinking water and rice were and , respectively, for the entire U.S. population. The Tribal, Asian, and Pacific population exhibited the highest mean daily exposure of iAs from cooked rice (); the mean exposure rate for children between ages 1 and 2 years in this population is body weight (BW)/day.Conclusions:An average consumer drinking 1.5 L of water daily that contains between 2 and is exposed to approximately the same amount of iAs as a mean Tribal, Asian, and Pacific consumer is exposed to from rice. https://doi.org/10.1289/EHP418

Permethrin is a broad-spectrum pyrethroid insecticide and among the most widely used insecticides in homes and crops. Managing the risks for pesticides such as permethrin depends on the ability to consider diverse exposure scenarios and their relative risks. Physiologically based pharmacokinetic models of delta methrin disposition were modified to describe permethrin kinetics in the rat and human. Unlike formulated deltamethrin which consists of a single stereoisomer, permethrin is formulated as a blend of cis- and trans-diastereomers. We assessed time courses for cis-permethrin and trans-permethrin in several tissues (brain, blood, liver, and fat) in the rat following oral administration of 1 and 10mg/kg permethrin (cis/trans: 40/60). Accurate simulation of permethrin in the rat suggests that a generic model structure is promising for modeling pyrethroids. Human in vitro data and appropriate anatomical information were used to develop a provisional model of permethrin disposition with structures for managing oral, dermal, and inhalation routes of exposure. The human permethrin model was used to evaluate dietary and residential exposures in the U.S. population as estimated by EPA's Stochastic Human Exposure and Dose Simulation model. Simulated cis- and trans-DCCA, metabolites of permethrin, were consistent with measured values in the National Health and Nutrition Examination Survey, indicating that the model holds promise for assessing population exposures and quantifying dose metrics.

Application of Refined Exposure Surrogates in Ambient PM2.5 Epidemiology Studies: Accounting for Temporal/Spatial Variations in Particulate Matter Infiltration

Aquatic herbicides are commonly used to control a wide variety of algae and plants, but they also have the potential to contaminate and affect nontarget organisms. However, the impacts of low-level 2,4-dichlorophenoxyacetic acid (2,4-D) herbicide exposure on larval fish are not well understood. We conducted a series of experiments to determine the effects of low concentrations (0.05, 0.50, and 2.00 ppm) of 2 commercial 2,4-D amine salt herbicide formulations (Weedestroy® AM40 [WAM40] and DMA® 4 IVM [DMA4]) and pure 2,4-D on the development and survival of fathead minnows (Pimephales promelas) at various life cycle stages. Larval survival (30 d post hatch [dph]) was decreased following exposure of eggs and larvae to pure 2,4-D (0.50 ppm; p ≤ 0.001), as well as to WAM40 (0.50 and 2.00 ppm; p ≤ 0.001, p ≤ 0.001) and DMA4 (0.50 and 2.00 ppm; p ≤ 0.001, p ≤ 0.001). The results also narrowed the critical window of exposure for effects on survival to the period between fertilization and 14 dph. Development was not negatively altered by any of the compounds tested, although the commercial formulations increased larval total length and mass at 2.00 ppm. Altogether, the results indicate that the use of 2,4-D herbicides for weed control in aquatic ecosystems at current recommended concentrations (<2 ppm whole lake; <4 ppm spot treatment) could present risks to fathead minnow larval survival. Environ Toxicol Chem 2018;37:2550–2559. © 2018 SETAC

In recent years, environmental lead (Pb) exposure through drinking water has resulted in community public health concerns. To understand potential impacts on blood Pb levels (BLLs) from drinking water Pb reduction actions (i.e., combinations of lead service lines [LSL] and corrosion control treatment [CCT] scenarios), EPA's Stochastic Human Exposure and Dose Simulation (SHEDS)-Multimedia/Integrated Exposure Uptake and Biokinetic (IEUBK) model was applied for U.S. children aged 0 to <6 years. The results utilizing a large drinking water sequential sampling data set from 15 cities to estimate model input concentration distributions demonstrated lowest predicted BLLs for the "no LSLs" with "combined CCT" scenario and highest predicted BLLs for the "yes LSLs" and "no CCT" scenario. Modeled contribution to BLLs from ingestion of residential drinking water ranged from ∼10 to 80%, with the highest estimated for formula-fed infants (age 0 to <1 year). Further analysis using a "bounding" data set spanning a range of realistic water Pb concentrations and variabilities showed BLL predictions consistent with the sequential sampling-derived inputs. Our study illustrates (1) effectiveness of LSL replacement coupled with CCT for reducing Pb in drinking water and children's BLLs, and (2) in some age groups, under realistic local and residential water use conditions, drinking water can be the dominant exposure pathway.

Analysis of the QUESTOR water quality model using a Fourier amplitude sensitivity test (FAST) for two UK rivers

Sensitivity analysis and uncertainty propagation of the time to onset of natural circulation in air ingress accidents

Identifying sensitive sources and key control handles for the reduction of greenhouse gas emissions from wastewater treatment

Simulation of fate and transport mechanisms in the porous systems from contaminant transport models are affected by uncertainty associated with input model parameters. Sensitivity analysis (SA) provides tools to quantify the sources of uncertainty to the variations in the model output metrics. To quantify the uncertainty associated with physical non-equilibrium contaminant transport model, global SA was conducted for the problem mimicking reactive transport in the saturated soil column conditions. Five global SA methods, namely Morris, RSA (Regionalized Sensitivity Analysis), Sobol, FAST (Fourier Amplitude Sensitivity Test), and PAWN, were tested based on the temporal moments of contaminant concentrations for two output metrics: zeroth temporal moment (ZTM) and mean residence time (MRT). The ranking order of ten input model parameters from global SA methods for two output metrics was compared. Morris SA implied that the ZTM at outlet of the soil column is highly sensitive to sorption distribution coefficient in the mobile and immobile regions and less sensitive to dispersion coefficient and degradation rate constant in the immobile region. The mass-transfer coefficient showed highest non-linear interactions with other flow and transport parameters based on the highest value of standard deviation of elementary effects (EEs) for ZTM output metric. The sorption distribution coefficient in the mobile region and mass-transfer coefficient showed highest sensitivity and non-linear effect toward MRT based on the Morris method. The comparison of global SA methods revealed that the top two sensitive parameters affecting ZTM and MRT were the same from all the considered methods. However, large difference in the ranking order of bottom three sensitive parameters was observed. The sorption distribution coefficient of mobile region and mass-transfer coefficient were observed as the most sensitive parameters affecting ZTM and MRT based on the comparison of all five global SA methods. Overall results suggest that the non-linear contaminant transport model should be examined based on multiple sensitivity output metrics via a multi-model approach. The multi-model global SA approach implemented in this study highlighted its significance in quantifying the interplay of non-linear model parameters.

Salt precipitation is generated near the injection well when dry supercritical carbon dioxide (scCO2) is injected into saline aquifers, and it can seriously impair the CO2 injectivity of the well. We used solid saturation (Ss) to map CO2 injectivity. Ss was used as the response variable for the sensitivity analysis, and the input variables included the CO2 injection rate (QCO2), salinity of the aquifer (XNaCl), empirical parameter m, air entry pressure (P0), maximum capillary pressure (Pmax), and liquid residual saturation (Splr and Sclr). Global sensitivity analysis methods, namely, the Morris method and Sobol method, were used. A significant increase in Ss was observed near the injection well, and the results of the two methods were similar: XNaCl had the greatest effect on Ss; the effect of P0 and Pmax on Ss was negligible. On the other hand, with these two methods, QCO2 had various effects on Ss: QCO2 had a large effect on Ss in the Morris method, but it had little effect on Ss in the Sobol method. We also found that a low QCO2 had a profound effect on Ss but that a high QCO2 had almost no effect on the Ss value.

The development of heavy oil reservoirs in China is of great significance to safeguard national energy security, but great challenges are faced due to the complex and heterogeneous reservoir properties. Inter-well connectivity analysis is critical to enhancing the development performance, as it is a good way to interpret fluid flow and provides a theoretical basis for injection-production optimization. Data-driven deep learning methods have been widely used in reservoir development and can be employed to develop surrogate models of injection and production and to infer inter-well connectivity. In this study, the model performance of a recurrent neural network (RNN) and its four variants were evaluated and compared in a temporal production prediction. The comparison results showed that bidirectional gated recurrent unit (Bi-GRU) is the optimal algorithm with the highest accuracy of 0.94. A surrogate model was established to simulate the inter-well connectivity of steam-assisted gravity drainage (SAGD) in the research area by utilizing the Bi-GRU algorithm. A global sensitivity analysis method, Fourier amplitude sensitivity testing (FAST), was introduced and combined with the surrogate model to explain the influence of the input variables on the output variables by quantitatively calculating the sensitivity of each variable. Quantitative results for the inter-well connectivity of SAGD were derived from the sensitivity analysis of the proposed method, which was effectively applied to typical linear patterns and five-spot patterns. Inter-well connectivity varied from 0.1 to 0.58 in test applications, and mutual corroboration with previous geological knowledge can further determine the distribution of the interlayer in the reservoir. The workflow proposed in this study provides a new direction for analyzing and inferring the inter-well connectivity of SAGD in Northeast China heavy oil reservoirs.

Uncertainty quantification has always been an important topic in model reduction and simulation of complex systems. In this aspect, global sensitivity analysis (GSA) methods such as Fourier amplitude sensitivity test (FAST) are well recognized as effective algorithms. Recently, some data-based metamodeler such as Random Forest (RF) also developed their own variable importance selection solutions for parameters with perturbations. This paper proposes a visual comparison of these two uncertainty quantification methods, using datasets retrieved from vibroacoustic models. Their results have a lot in common and are capable to explain many results. The remarkable agreement between methods under fundamentally different definitions can potentially improve their compatibility in various occasions.

The sanitary survey program was created by the US Environmental Protection Agency (EPA) to support state primacy agencies in assessing utility progress with implementing water quality requirements in the Ground Water Rule and the Interim Enhanced Surface Water Treatment Rule. In the spring of 2021, EPA said it was planning to issue a direct file rule to integrate cybersecurity into the existing sanitary survey program. Multiple organizations representing water utilities and state primacy agencies communicated to EPA that using the sanitary survey program for cybersecurity was ill-advised. Even so, on March 3, 2023, EPA issued the “Cyber Rule” directing state primacy agencies to assess cybersecurity of public water systems (PWSs) as part of the sanitary survey program—effective immediately. The new Cyber Rule requires all PWSs (n = 151,606) to determine whether they use “operational technology,” meaning hardware and software that detect or cause a change through the direct monitoring or control of physical devices, processes, and events in the enterprise, per the Internet of Things Cybersecurity Improvement Act of 2020, 15 U.S.C. § 271(3)(6). EPA provided states with three compliance options: (1) self-assessment or third-party assessment by a state-approved entity; (2) state assessment during a sanitary survey; or (3) an alternative, equivalent, state-developed cybersecurity program. The draft guidance for the Cyber Rule includes a checklist of 33 controls that EPA determined are “technically feasible for most PWS[s] to address without significant capital expenditures.” Sixteen of these controls are classified by EPA as potential “significant deficiencies” if not implemented. There are numerous implementation challenges, including the ability of a state official to nonintrusively verify that a control has been implemented. The Cyber Rule interprets the use of operational technology as being part of the equipment or operations examined in the sanitary survey, components used for producing and distributing safe drinking water. This represents a significant expansion of the states’ existing sanitary survey inspection obligations. The details of the rule were never proposed or made available for public review and comment, which is the norm under the Administrative Procedures Act (APA). While EPA did have discussions with states in the summer of 2022, the Association of State Drinking Water Administrators has consistently advised the agency against using the sanitary survey for addressing cybersecurity. Bypassing APA and other regulatory obligations represents a troubling process issue that undermines the integrity of the rule of law. This includes EPA's determination that the regulatory oversight approach set out by Congress in §2013 of America's Water Infrastructure Act (AWIA) of 2018 was, in the administrator's judgment, insufficient. AWIA §2013 amended the Safe Drinking Water Act (SDWA) §1433 to require each community water system serving 3,300 or more people to conduct a risk and resilience assessment (RRA) at least every five years, which explicitly encompass cybersecurity threats to “electronic, computer, or other automated systems.” Further, §2013 requires systems to incorporate the findings of the RRA into emergency response plans, which must address the “strategies and resources to improve the resilience of the system, including the physical security and cybersecurity of the system.” Congress clearly defined a process by which a specific class of PWSs would address cybersecurity. Finally, Congress instructed EPA to directly implement, oversee, and enforce AWIA §2013. Unlike other SDWA requirements, AWIA does not authorize the EPA to delegate implementation to the states. Contrary to congressional direction, the Cyber Rule shifts the burden of oversight to the state. Many of these procedural concerns were shared with EPA in a January 2023 letter from the water community. Undeterred, EPA proceeded with issuing the Cyber Rule. Subsequently, on April 17, the states of Missouri, Arkansas, and Iowa filed a challenge to the Cyber Rule in the US Court of Appeals for the Eighth Circuit, State of Missouri, et al. v. EPA, et al., No. 23-1787 (8th Cir.). AWWA and the National Rural Water Association have filed to intervene on behalf of the states. The intent of the challenge is to hold EPA accountable for going around the checks and balances created to govern the promulgation of regulations. Perhaps watching the “Three Ring Government” episode from Schoolhouse Rock! is in order since it explains the balance of power between the three branches of government. The judiciary is a last resort for accountability; it is unfortunate that the public–private collaboration called for in the National Cybersecurity Strategy was not exercised. Kevin M. Morley is manager of federal relations at the AWWA Government Affairs Office in Washington, D.C. He can be reached at [email protected].

Received for publication September 11, 2000, and accepted for publication September 10, 2001. Abbreviations: CDC, US Centers for Disease Control and Prevention; EPA, US Environmental Protection Agency; FDA, US Food and Drug Administration; NRC, National Research Council. From the US Environmental Protection Agency, Washington, DC. Correspondence to Dr. Lynn Goldman, Johns Hopkins Bloomberg School of Public Health, 615 North Wolfe Street, Suite W8511, Baltimore, MD 21205 (e-mail: lgoldman@jhsph.edu). While epidemiologic evidence and, particularly, results of individual studies is often highly controversial, epidemiologic findings often play a significant role in the development of many environmental standards and regulations. This prominence reflects the direct relevance of epidemiologic evidence to public health, which was a focus for new policy initiatives over the first 5 years of the Clinton administration. Federal environmental statutes state that protection of human health is a major goal in ensuring, for example, clean water, clean air, and responsible management of waste. At times in the past, however, there was less focus on public health and greater reliance on projections of theoretical tools, such as modeling and risk assessment as the basis for selecting among policy options. With the implementation of the Government Performance and Results Act of 1993 (1), a government-wide effort began to identify ways for measuring and tracking outcomes of governmental efforts, including those of the US Environmental Protection Agency (EPA) and other regulatory agencies. At the same time, there is increased appreciation of the relevance of epidemiology in the public policy arena (2). A demand for more surveillance and other epidemiologic data can be anticipated. There are numerous other forces that have pushed regulatory agencies in the direction of relying more on epidemiology. Industry has questioned the applicability of animal toxicology data to human health risk and has wanted human data to be used to validate this practice. Public health advocates have pushed regulatory agencies to look beyond cancer and other diseases that are more readily assessed using animal models to include other diseases (e.g., reproductive, neurologic, and respiratory) where epidemiology studies have indicated there may be additional risks. The National Toxicology Program has recently begun to incorporate more epidemiology information into its cancer assessments for the Report on Carcinogens. Epidemiologists and the findings of epidemiologic studies will probably play a more significant role in environmental regulation in the future. This presentation offers the perspective of a physicianepidemiologist on the role of epidemiologic evidence in the regulatory arena. It draws on selected examples and experiences of the author as a basis for general considerations on epidemiology and regulation. While the presentation is thus based around a particular era of one administration, it offers more general lessons concerning epidemiology and policy. It is hoped that these perspectives will help to promote a greater understanding of the policy process among epidemiologists, and how their data are likely to be used (and misused). It is also hoped to promote a greater understanding and appreciation of the need to incorporate epidemiology among risk assessors (who predominantly are toxicologists).

9 - EPA Screening Levels and Pesticide Status