Geology Reports⌕ Search

SEARCH · Geology Reports

Results for “Applied Sciences”

Search indexed USGS publications on groundwater, aquifers, geologic maps, mineral resources and earthquakes. Explore source records by subject and place.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 559 records · Page 31Linked to original sources
USGS2026

CoralCache: A virtual coral core repository for transparent and reproducible annual growth rate analyses

As science fields enter the Big Data revolution, open-access repositories are essential for addressing larger-scale questions than are possible for single researchers by making data findable, accessible, interoperable, and reusable (FAIR). Furthermore, transparent data and code are increasingly important for reproducible research, especially for data types that inherently require subjective human interpretations. These ideas are applicable to coral sclerochronology, as the field has long been characterized by individual researchers collecting and analyzing coral skeletal cores from their study sites without substantial data sharing or archiving of the core images to meet FAIR principles. Here, we present CoralCache, a virtual coral core repository that not only archives image datasets (i.e., digitized X-rays and computed tomography scans), but also observer interpretations of the density banding patterns. CoralCache is linked to a graphical user interface, CoralCT, which together offer a way forward for coral growth rate analysis that is reproducible and collaborative. The data organization systems presented here could also be readily applied to related archives such as tree rings or bivalve shells.

Earth System Science Data↗
USGS1967

Biodegradation of dichlorodiphenyltrichloroethane: Intermediates in dichlorodiphenylacetic acid metabolism by Aerobacter aerogenes

The final product of dichlorodiphenyltrichloroethane (DDT) degradation by vertebrates is commonly considered to be dichlorodiphenylacetic acid, DDA (J. E. Peterson and W. H. Robison, Toxicol. Appl. Pharmacol. 6:321, 1964). Recently, certain organisms (A. S. Perry, S. Miller, and A. J. Buckner. J. Agr. Food Chem. 11:457, 1963; J. D. Pinto, M. N. Comien, and M. S. Dunn. J. Biol. Chem. 240:2148, 1965) have been found to degrade further DDA to dichlorobenzophenone (DBP), but the possibility that such degradation was due to microbial action could not be excluded. Significantly, dichlorobenzhydrol (DBH), dichlorophenylmethane (DPM), and dichlorodiphenylethylene (DDE) have been tentatively identified in rats fed DDA (Pinto et al., J. Biol. Chem. 240:2148, 1965). Since DDA as well as DDT is degraded by the ubiquitous microorganism Aerobacter aerogenes (G. Wedemeyer, Appl. Microbiol. 15:569, 1967; J. L. Mendel, and M. S. Walton, Science 151:1527, 1966), it seemed reasonable that the intestinal microflora might be involved in DBP formation, DPM and DBH being intermediates in its pathway from DDA. Since DDA is a (3,y-unsaturated acid, ketone formation via an alkene and an alcohol would be expected (S. G. Waley, Mechanisms of Organic and Enzymatic Reactions, Oxford University Press, London, England 1962).

Applied Microbiology↗
USGS1996

Overview of the limnology of crater lake

Crater Lake occupies the collapsed caldera of volcanic Mount Mazama in Crater Lake National Park, Oregon. It is the deepest lake (589 m) in the United States and the 7th deepest lake in the world. The water column mixes to a depth of about 200 m in winter and spring from wind energy and cooling. The deep lake is mixed in winter and early spring each year when relatively cold water near the surface sinks and exchanges positions with water in the deep basins of the lake. The lake becomes thermally stratified in summer and early fall. The metalimnion extends to a depth of about 100 m; thus most of the water column is a cold hypolimnion. Secchi disk clarity measurements typically are in the upper-20-m range to the low-30-m range in summer and early fall. Concentrations of nutrients are low, although conductivity is relatively high owing to the inflow of hydrothermal fluids. Total chlorophyll is low in concentration, but typically maximal at a depth of 120 m during periods of thermal stratification. Primary production also is low, with the maximum levels occurring between the depth of 40 and 80 m. Phytoplankton taxa are spatially segregated from each other within the water column to a depth of 200 m in summer and early fall. The same generalization applies to the Zooplankton taxa. Water level, clarity, concentrations of total chlorophyll, primary production, and abundances of zooplankton and introduced kokanee salmon exhibit long-term fluctuations. Based primarily on a recent 10-year study of the lake, the lake is considered to be pristine, except for the consequences of fish introductions. ?? 1996 by the Northwest Scientific Association. All rights reserved.

Northwest Science↗
USGS2021

Techniques to improve ecological interpretability of black box machine learning models

Statistical modeling of ecological data is often faced with a large number of variables as well as possible nonlinear relationships and higher-order interaction effects. Gradient boosted trees (GBT) have been successful in addressing these issues and have shown a good predictive performance in modeling nonlinear relationships, in particular in classification settings with a categorical response variable. They also tend to be robust against outliers. However, their black-box nature makes it difficult to interpret these models. We introduce several recently developed statistical tools to the environmental research community in order to advance interpretation of these black-box models. To analyze the properties of the tools, we applied gradient boosted trees to investigate biological health of streams within the contiguous USA, as measured by a benthic macroinvertebrate biotic index. Based on these data and a simulation study, we demonstrate the advantages and limitations of partial dependence plots (PDP), individual conditional expectation (ICE) curves and accumulated local effects (ALE) in their ability to identify covariate–response relationships. Additionally, interaction effects were quantified according to interaction strength (IAS) and Friedman’s H 2 "> H 2 statistic. Interpretable machine learning techniques are useful tools to open the black-box of gradient boosted trees in the environmental sciences. This finding is supported by our case study on the effect of impervious surface on the benthic condition, which agrees with previous results in the literature. Overall, the most important variables were ecoregion, bed stability, watershed area, riparian vegetation and catchment slope. These variables were also present in most identified interaction effects. In conclusion, graphical tools (PDP, ICE, ALE) enable visualization and easier interpretation of GBT but should be supported by analytical statistical measures. Future methodological research is needed to investigate the properties of interaction tests. Supplementary materials accompanying this paper appear on-line.

Journal of Agricultural, Biological, and Environme↗
USGS2006

The Model Parameter Estimation Experiment (MOPEX): Its structure, connection to other international initiatives and future directions

The Model Parameter Estimation Experiment (MOPEX) is an international project aimed at developing enhanced techniques for the a priori estimation of parameters in hydrological models and in land surface parameterization schemes connected to atmospheric models. The MOPEX science strategy involves: database creation, a priori parameter estimation methodology development, parameter refinement or calibration, and the demonstration of parameter transferability. A comprehensive MOPEX database has been developed that contains historical hydrometeorological data and land surface characteristics data for many hydrological basins in the United States (US) and in other countries. This database is being continuously expanded to include basins from various hydroclimatic regimes throughout the world. MOPEX research has largely been driven by a series of international workshops that have brought interested hydrologists and land surface modellers together to exchange knowledge and experience in developing and applying parameter estimation techniques. With its focus on parameter estimation, MOPEX plays an important role in the international context of other initiatives such as GEWEX, HEPEX, PUB and PILPS. This paper outlines the MOPEX initiative, discusses its role in the scientific community, and briefly states future directions.

IAHS-AISH Publication↗
USGS2021

Cyprosulfamide: Analysis of the herbicide safener and two of its degradates in surface water and groundwater from the Midwestern United States

Herbicide safeners are commonly included in herbicide formulations to selectively protect crops from herbicide toxicity but are poorly understood in terms of their environmental occurrence and fate. This study established an analytical method for a newer safener, cyprosulfamide, and two of its degradates, cyprosulfamide desmethyl and N -cyclopropyl-4-sulfamoylbenzamide, in water via solid-phase extraction and liquid chromatography with tandem mass spectroscopy. To evaluate the potential for off-field transport and transformation of cyprosulfamide, the method was used to analyze groundwater and surface water samples collected near cornfields in the midwestern United States where cyprosulfamide had been applied. All three compounds were detected in surface water samples ( N = 34); N -cyclopropyl-4-sulfamoylbenzamide was most frequently detected (56%), followed by cyprosulfamide (25%) and cyprosulfamide desmethyl (19%). Maximum concentrations ranged from 22.0 to 5185.9 ng/L, with the highest concentrations and detection rates during the growing season. None of our target analytes were detected in groundwater.

ACS Agricultural Science and Technology↗
USGS2025

An approach to urban waterway assessment using holistic values and reciprocity

Current aquatic ecosystem assessment methods and tools often focus on physical, chemical, and biological indicators of ecosystem health. This approach to ecosystem assessment is not always straightforward to execute in urban environments and ignores potential connectivity between social and environmental outcomes. During a workshop at the Symposium on Urbanization and Stream Ecology in Brisbane, Australia in 2023 (SUSE6), we developed an approach to urban aquatic ecosystem assessment that incorporates a holistic perspective. Specifically, our approach considers both environmental (biological, chemical, and physical integrity) and social (community connection, human safety, resource use) values of urban waterways. This approach is inclusive of Indigenous perspectives, such as the concept of reciprocity, whereby consideration of both the environment and society leads to a healthy ecosystem. To highlight how this holistic assessment approach could be used, we present real-world examples that included assessing both environmental and societal values informed by reciprocity or balanced perspectives. This approach can be broadly applied and adapted to specific aquatic ecosystem conditions and projects, providing an inclusive, community-centered approach for assessing the health of waterways in urban environments.

Freshwater Science↗
USGS2026

An improved empirical model for predicting postfire debris-flow volume in the western United States

Reliable estimates of debris-flow volume can be used to help predict the magnitude of debris-flow hazards following wildfire in the western United States. In this study, we compiled and used a database of 227 postfire debris-flow volumes that were collected across the western United States to develop a multiple linear regression model for predicting postfire debris-flow volume. We explored 36 predictor variables related to rainfall, terrain, and fire characteristics, and selected the model with the combination of variables that yielded the most accurate predictions of debris-flow volume. We evaluated model performance against the entire volume database, as well as against four subsets of volume data from southern California, the Intermountain West, the Southwest, and regions with limited volume data, such as northern California and Washington. We also compared model performance against 3 existing postfire debris-flow volume models that were developed for use in southern California, the Intermountain West, and the Southwest. We demonstrate that the new volume model performs as well as the regional models in the regions for which they were developed and outperforms existing models when applied to volumes from data-limited regions in the western United States. These results indicate that the debris-flow volume model introduced in this study can be used to improve postfire hazard assessments across the western United States, especially outside of southern California.

Arizona, California, Colorado, New Mexico, Utah, W↗
USGS2024

Boundary spanning increases knowledge and action on invasive species in a changing climate

Challenges associated with global change stressors on ecosystems have prompted calls to improve actionable science, including through boundary-spanning activities, which aim to build connections and communication between researchers and natural resource practitioners. By synthesizing and translating research and practitioner knowledge, boundary-spanning activities could support proactive, research-informed conservation practice, but the success of these efforts is rarely evaluated. Using repeat survey data from the Northeast Regional Invasive Species and Climate Change (NE RISCC) Management Network, a boundary-spanning organization, we evaluate whether participating in NE RISCC affected practitioners' knowledge, actions and priorities related to invasive species management under a changing climate. Our survey results suggest that practitioners who participate in NE RISCC have greater knowledge about invasive species and climate change and are incorporating climate change in more ways into their invasive species management. We also found NE RISCC membership affected the perceived usefulness of informational resources, with NE RISCC members more frequently identifying research syntheses and targeted workshops (both are common products used by NE RISCC to translate science into practice and share manager knowledge) as useful compared to non-members. Practitioners who participate in NE RISCC also identified somewhat different research priorities, with non-members and short-term members more frequently identifying range-shifting neonative species and their impacts on native communities as higher priorities compared to long-term NE RISCC members. NE RISCC research activities and outreach materials have consistently framed range-shifting neonative species as comparatively low risk, suggesting that this information has influenced practitioner's perception of risk. Practical implication : Although real-world impacts of applied ecology are notoriously difficult to quantify, this analysis illustrates that if research results are actively translated, they can affect the knowledge and actions of natural resource practitioners. These impacts illustrate the potential for boundary-spanning efforts to address other global change challenges to conservation.

Ecological Solutions and Evidence↗
USGS2021

Predicting water temperature dynamics of unmonitored lakes with meta-transfer learning

Most environmental data come from a minority of well-monitored sites. An ongoing challenge in the environmental sciences is transferring knowledge from monitored sites to unmonitored sites. Here, we demonstrate a novel transfer-learning framework that accurately predicts depth-specific temperature in unmonitored lakes (targets) by borrowing models from well-monitored lakes (sources). This method, meta-transfer learning (MTL), builds a meta-learning model to predict transfer performance from candidate source models to targets using lake attributes and candidates' past performance. We constructed source models at 145 well-monitored lakes using calibrated process-based (PB) modeling and a recently developed approach called process-guided deep learning (PGDL). We applied MTL to either PB or PGDL source models (PB-MTL or PGDL-MTL, respectively) to predict temperatures in 305 target lakes treated as unmonitored in the Upper Midwestern United States. We show significantly improved performance relative to the uncalibrated PB General Lake Model, where the median root mean squared error (RMSE) for the target lakes is 2.52°C. PB-MTL yielded a median RMSE of 2.43°C; PGDL-MTL yielded 2.16°C; and a PGDL-MTL ensemble of nine sources per target yielded 1.88°C. For sparsely monitored target lakes, PGDL-MTL often outperformed PGDL models trained on the target lakes themselves. Differences in maximum depth between the source and target were consistently the most important predictors. Our approach readily scales to thousands of lakes in the Midwestern United States, demonstrating that MTL with meaningful predictor variables and high-quality source models is a promising approach for many kinds of unmonitored systems and environmental variables.

Water Resources Research↗
USGS2001

Aeolian dust in Colorado Plateau soils: Nutrient inputs and recent change in source

Aeolian dust (windblown silt and clay) is an important component in arid-land ecosystems because it may contribute to soil formation and furnish essential nutrients. Few geologic surfaces, however, have been characterized with respect to dust-accumulation history and resultant nutrient enrichment. We have developed a combination of methods to identify the presence of aeolian dust in arid regions and to evaluate the roles of this dust in ecosystem processes. Unconsolidated sandy sediment on isolated surfaces in the Canyonlands region of the Colorado Plateau differs greatly in mineralogical and chemical composition from associated bedrock, mainly aeolian sandstone. Detrital magnetite in the surficial deposits produces moderately high values of magnetic susceptibility, but magnetite is absent in nearby bedrock. A component of the surficial deposits must be aeolian to account for the abundance of magnetite, which formed originally in far-distant igneous rocks. Particle-size analysis suggests that the aeolian dust component is typically as much as 20–30%. Dust inputs have enriched the sediments in many elements, including P, Mg, Na, K, and Mo, as well as Ca, at sites where bedrock lacks calcite cement. Soil-surface biologic crusts are effective dust traps that apparently record a change in dust sources over the past several decades. Some of the recently fallen dust may result from human disturbance of land surfaces that are far from the Canyonlands, such as the Mojave Desert. Some land-use practices in the study area have the potential to deplete soil fertility by means of wind-erosion removal of aeolian silt. Many studies have addressed the presence of aeolian dust in soils and surficial deposits in deserts to provide important geologic and ecologic information bearing on landscape dynamics (1–16). From this body of work, we have improved understanding about: ( i ) current and past sources and flux of dust, hence changing conditions of dust emission; ( ii ) the genesis of desert soils; ( iii ) the influences of aeolian silt and clay on water-infiltration rates in soil; ( iv ) the evolution of desert surfaces (such as desert pavement) relevant to surface stability, as well as the distribution of surface and subsurface water; and ( v ) interrelations among aeolian dust, distribution of plants and soil crust, rain-water runoff, and productivity. Nevertheless, we lack fundamental knowledge about the accumulation history of aeolian dust on most landscapes and about how to discriminate between contributions from parent material and aeolian dust to the biotic system. Although many different methods provide clear evidence for aeolian input into soils (4, 6, 8, 9, 11, 13, 17, 18), ecosystem studies would benefit from rapid assessment of aeolian components in soils. Here we demonstrate that magnetic methods, which characterize the type and distribution of iron oxide minerals, can be applied to detect the presence of aeolian dust in young surficial sediments and soils over large arid-land areas. The magnetic results, combined with geochemical and textural analyses, form a basis for understanding the influence of fine-grained aeolian inputs on soil fertility of the central Colorado Plateau, Utah.

Utah↗
USGS2021

A novel framework to predict relative habitat selection in aquatic systems: Applying machine learning and resource selection functions to acoustic telemetry data from multiple shark species

Resource selection functions (RSFs) have been widely applied to animal tracking data to examine relative habitat selection and to help guide management and conservation strategies. While readily used in terrestrial ecology, RSFs have yet to be extensively used within marine systems. As acoustic telemetry continues to be a pervasive approach within marine environments, incorporation of RSFs can provide new insights to help prioritize habitat protection and restoration to meet conservation goals. To overcome statistical hurdles and achieve high prediction accuracy, machine learning algorithms could be paired with RSFs to predict relative habitat selection for a species within and even outside the monitoring range of acoustic receiver arrays, making this a valuable tool for marine ecologists and resource managers. Here, we apply RSFs using machine learning to an acoustic telemetry dataset of four shark species to explore and predict species-specific habitat selection within a marine protected area. In addition, we also apply this RSF-machine learning approach to investigate predator-prey relationships by comparing and averaging tiger shark relative selection values with the relative selection values derived for eight potential prey-species. We provide methodological considerations along with a framework and flexible approach to apply RSFs with machine learning algorithms to acoustic telemetry data and suggest marine ecologists and resource managers consider adopting such tools to help guide both conservation and management strategies.

Buck Island Reef National Monument, St Croix↗
USGS2015

Downscaling global land-use/land-cover projections for use in region-level state-and-transition simulation modeling

Global land-use/land-cover (LULC) change projections and historical datasets are typically available at coarse grid resolutions and are often incompatible with modeling applications at local to regional scales. The difficulty of downscaling and reapportioning global gridded LULC change projections to regional boundaries is a barrier to the use of these datasets in a state-and-transition simulation model (STSM) framework. Here we compare three downscaling techniques to transform gridded LULC transitions into spatial scales and thematic LULC classes appropriate for use in a regional STSM. For each downscaling approach, Intergovernmental Panel on Climate Change (IPCC) Representative Concentration Pathway (RCP) LULC projections, at the 0.5 × 0.5 cell resolution, were downscaled to seven Level III ecoregions in the Pacific Northwest, United States. RCP transition values at each cell were downscaled based on the proportional distribution between ecoregions of (1) cell area, (2) land-cover composition derived from remotely-sensed imagery, and (3) historic LULC transition values from a LULC history database. Resulting downscaled LULC transition values were aggregated according to their bounding ecoregion and “cross-walked” to relevant LULC classes. Ecoregion-level LULC transition values were applied in a STSM projecting LULC change between 2005 and 2100. While each downscaling methods had advantages and disadvantages, downscaling using the historical land-use history dataset consistently apportioned RCP LULC transitions in agreement with historical observations. Regardless of the downscaling method, some LULC projections remain improbable and require further investigation.

AIMS Environmental Science↗
USGS2003

The Sima de los Huesos hominids date to beyond U/Th equilibrium (>350 kyr) and perhaps to 400-500 kyr: New radiometric dates

The Sima de los Huesos site of the Atapuerca complex near Burgos, Spain contains the skeletal remains of at least 28 individuals in a mud breccia underlying an accumulation of the Middle Pleistocene cave bear (U. deningeri). Earlier dating estimates of 200 to 320 kyr were based on U-series and ESR methods applied to bones, made inaccurate by unquantifiable uranium cycling. We report here on a new discovery within the Sima de los Huesos of human bones stratigraphically underlying an in situ speleothem. U-series analyses of the speleothem shows the lower part to be at isotopic U/Th equilibrium, translating to a firm lower limit of 350 kyr for the SH hominids. Finite dates on the upper part suggest a speleothem growth rate of c. 1 cm/32 kyr. This rate, along with paleontological constraints, place the likely age of the hominids in the interval of 400 to 600 kyr. ?? 2002 Elsevier Science Ltd. All rights reserved.

Journal of Archaeological Science↗
USGS2005

A regional classification scheme for estimating reference water quality in streams using land-use-adjusted spatial regression-tree analysis

Various approaches are used to subdivide large areas into regions containing streams that have similar reference or background water quality and that respond similarly to different factors. For many applications, such as establishing reference conditions, it is preferable to use physical characteristics that are not affected by human activities to delineate these regions. However, most approaches, such as ecoregion classifications, rely on land use to delineate regions or have difficulties compensating for the effects of land use. Land use not only directly affects water quality, but it is often correlated with the factors used to define the regions. In this article, we describe modifications to SPARTA (spatial regression-tree analysis), a relatively new approach applied to water-quality and environmental characteristic data to delineate zones with similar factors affecting water quality. In this modified approach, land-use-adjusted (residualized) water quality and environmental characteristics are computed for each site. Regression-tree analysis is applied to the residualized data to determine the most statistically important environmental characteristics describing the distribution of a specific water-quality constituent. Geographic information for small basins throughout the study area is then used to subdivide the area into relatively homogeneous environmental water-quality zones. For each zone, commonly used approaches are subsequently used to define its reference water quality and how its water quality responds to changes in land use. SPARTA is used to delineate zones of similar reference concentrations of total phosphorus and suspended sediment throughout the upper Midwestern part of the United States. ?? 2006 Springer Science+Business Media, Inc.

Environmental Management↗
USGS2019

Amphibian conservation in the Anthropocene

Research is necessary to identify patterns in nature, to understand how a system functions, and to make predictions about the future state of an ecosystem. Applied research in conservation biology can identify effective strategies to maintain biodiversity, though many papers end with the conclusion that more research is needed. However, more research does not necessarily lead to solutions. We use the ongoing global decline of amphibians as a salient example to highlight limitations in current conservation research, and to focus on finding solutions which are directly relevant for conservation. While research has been conducted since declines were first detected in the 1990s, outside a few specific examples, little progress in conservation has been achieved. We suggest that the case of amphibian declines is relevant to conservation science in general, as the current paradigm for conservation is that management is planned after research is completed; research and management are not effectively (and not directly) connected. This disconnect illustrates the knowledge-action divide which has been identified as a serious deficiency in conservation. Accordingly, we use this introductory paper to the Special Issue (Amphibian conservation in the Anthropocene: Progress and challenges) to describe amphibians as a conservation dilemma, and to make the case for a different, more pragmatic, and more solutions-focused view of conservation research.

Kansas, Oklahoma↗
USGS2002

Ground truth seismic events and location capability at Degelen mountain, Kazakhstan

We utilized nuclear explosions from the Degelen Mountain sub-region of the Semipalatinsk Test Site (STS), Kazakhstan, to assess seismic location capability directly. Excellent ground truth information for these events was either known or was estimated from maps of the Degelen Mountain adit complex. Origin times were refined for events for which absolute origin time information was unknown using catalog arrival times, our ground truth location estimates, and a time baseline provided by fixing known origin times during a joint hypocenter determination (JHD). Precise arrival time picks were determined using a waveform cross-correlation process applied to the available digital data. These data were used in a JHD analysis. We found that very accurate locations were possible when high precision, waveform cross-correlation arrival times were combined with JHD. Relocation with our full digital data set resulted in a mean mislocation of 2 km and a mean 95% confidence ellipse (CE) area of 6.6 km2 (90% CE: 5.1 km2), however, only 5 of the 18 computed error ellipses actually covered the associated ground truth location estimate. To test a more realistic nuclear test monitoring scenario, we applied our JHD analysis to a set of seven events (one fixed) using data only from seismic stations within 40?? epicentral distance. Relocation with these data resulted in a mean mislocation of 7.4 km, with four of the 95% error ellipses covering less than 570 km2 (90% CE: 438 km2), and the other two covering 1730 and 8869 km2 (90% CE: 1331 and 6822 km2). Location uncertainties calculated using JHD often underestimated the true error, but a circular region with a radius equal to the mislocation covered less than 1000 km2 for all events having more than three observations. ?? 2002 Elsevier Science B.V. All rights reserved.

Physics of the Earth and Planetary Interiors↗
USGS2011

Towards identifying the next generation of superfund and hazardous waste site contaminants

Background This commentary evolved from a workshop sponsored by the National Institute of Environmental Health Sciences titled "Superfund Contaminants: The Next Generation" held in Tucson, Arizona, in August 2009. All the authors were workshop participants. Objectives Our aim was to initiate a dynamic, adaptable process for identifying contaminants of emerging concern (CECs) that are likely to be found in future hazardous waste sites, and to identify the gaps in primary research that cause uncertainty in determining future hazardous waste site contaminants. Discussion Superfund-relevant CECs can be characterized by specific attributes: They are persistent, bioaccumulative, toxic, occur in large quantities, and have localized accumulation with a likelihood of exposure. Although still under development and incompletely applied, methods to quantify these attributes can assist in winnowing down the list of candidates from the universe of potential CECs. Unfortunately, significant research gaps exist in detection and quantification, environmental fate and transport, health and risk assessment, and site exploration and remediation for CECs. Addressing these gaps is prerequisite to a preventive approach to generating and managing hazardous waste sites. Conclusions A need exists for a carefully considered and orchestrated expansion of programmatic and research efforts to identify, evaluate, and manage CECs of hazardous waste site relevance, including developing an evolving list of priority CECs, intensifying the identification and monitoring of likely sites of present or future accumulation of CECs, and implementing efforts that focus on a holistic approach to prevention.

Environmental Health Perspectives↗