Economics of place-based monitoring under the safe drinking water act, part I: spatial and temporal patterns of contaminants, and design of screening strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the USA. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Under the Safe Drinking Water Act (SDWA), a common list of over 90 contaminants is analyzed nationwide using EPA-authorized laboratory procedures. National and state-level summaries of SDWA data have shown that not all contaminants occur in all places at all times. This hypothesis is confirmed and extended by showing that only a few (less than seven) contaminants are of concern in any one of 19 Iowa surface water systems studied. These systems collectively serve about 350,000 people and their sizes vary between 1,200 and 120,000. The distributions of contaminants found in these systems are positively skewed, with many non-detect measurements. A screening strategy to identify such contaminants in individual systems is presented. These findings have significant implications not only for the design of alternative monitoring programs, but also in multi-billion-dollar decisions that influence the course of future drinking water infrastructure, repair, and maintenance investments.     

Managing troubled data: coastal data partnerships smooth data integration

Understanding the ecology, condition, and changes of coastal areas requires data from many sources. Broad-scale and long-term ecological questions, such as global climate change, biodiversity, and cumulative impacts of human activities, must be addressed with databases that integrate data from several different research and monitoring programs. Various barriers, including widely differing data formats, codes, directories, systems, and metadata used by individual programs, make such integration troublesome. Coastal data partnerships, by helping overcome technical, social, and organizational barriers, can lead to a better understanding of environmental issues, and may enable better management decisions. Characteristics of successful data partnerships include a common need for shared data, strong collaborative leadership, committed partners willing to invest in the partnership, and clear agreements on data standards and data policy. Emerging data and metadata standards that become widely accepted are crucial. New information technology is making it easier to exchange and integrate data. Data partnerships allow us to create broader databases than would be possible for any one organization to create by itself.     

Marine Birds as Indicators of Arctic Marine Ecosystem Health: Linking the Northern Ecosystem Initiative to Long-Term Studies

Marine birds are sensitive indicators of the condition of marine ecosystems in the Arctic, partly because they feed at the top of the arctic food chain. The Northern Ecosystem Initiative (NEI) recently supported four separate studies that investigated aspects of Arctic marine bird science which simultaneously addressed goals of the NEI to better understand northern ecosystems and their response to environmental stressors. The projects used both scientific and traditional knowledge to examine the relationship between sea-ice, contaminants, and the ecology of marine birds, and to transfer environmental knowledge to students. Results from these investigations confirm that changes are occurring in Arctic environments, and that these are captured through marine bird research. Collectively these studies provided new data that supported NEI objectives of monitoring the health of the Arctic ecosystem, and contributed to Canada's international obligations for Arctic science.     

The impact of government preferences and environmental regulations on green development of China's marine economy

Green development is the fundamental way for high-quality development of marine economy. Achievement of green development goals of marine economy depends on the local government's decision-making preferences and reasonable marine-related environmental regulatory instruments. Based on 2007–2016 panel data of China's coastal provinces, this paper adopts the differential GMM(Gaussian Mixture Model) model to empirically analyze the impact of government preferences and environmental regulations on green development of marine economy. The results indicate that: lag exists in the promotion of environmental regulation on green development of marine economy.The impact of government preferences varies, in which, industrial preferences have a negative effect on green development of marine economy,while environmental preferences have a positive effect.The joint action of industrial preference and environmental preference inhibits green development of marine economy, while that of environmental preference and environmental regulation plays a promotion role. Different government preferences indicate different impacts in different regions. Environmental preference promotes the green development of marine economy in the Bohai Bay region, while industrial preference suppresses it. Both industrial preference and environmental preference in the Yangtze River Delta region have promotion effect, while only environmental preference in the Pan-Pearl River Delta region does so. Therefore, the government should establish a more complete official examination system, improve the marine environmental regulation system, and formulate differentiated green development policies for marine economy.     

Environmental Data in Decision Making in EPA Regional Offices

The mid-Atlantic region of the United States has a wide diversity of natural resources. Human pressures on these natural resources are intense. These factors have resulted in the collection of substantial amounts of environmental information about the region by EPA (both Regional and Research Offices), other governmental agencies, industry, and environmental groups. EPA Regional Offices comprehend first hand the importance of environmental data and are extremely supportive of investments in these data. Environmental data are used prominently in a variety of strategic planning and resource management initiatives. In EPA Region 3, the use of scientifically-sound environmental data is, in fact, one of our strategic programmatic goals. Environmental information is captured and assessed continuously by Regional staff, sometimes working in partnership with other Federal and State agencies, to derive relevant resource management conclusions. The restoration goals for the Chesapeake Bay are based on environmental indicators and resulting data. Attainment of the water quality objectives for streams and coastal estuaries are predicted on monitoring data. Our initiative in the Mid-Atlantic Highlands area uses environmental indicators to measure the condition of forests and streams. Landscape-level indicators will provide unique opportunities for the use of data in planning and management activities in support of the principles of community-based activism and sustainable development. Significant value is added to these data during their use by Regional managers. Regional programs, such as the Chesapeake Bay Program and several National Estuary Programs, are founded in environmental data. Environmental information is used by the Regional program managers to ascertain whether programs are accomplishing their intended objectives. Finally, Regional programs provide a crucial means for disseminating this information to broad segments of the public, so that a better informed and educated client base for effective environmental protection will develop.     

Economics of place-based monitoring under the safe drinking water act, part II: Design and development of place-based monitoring strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the United States. In this three part series, spatial and temporal patterns in water quality data are utilized to develop, compare, and evaluate the economic performance of alternative place-based monitoring approaches to current monitoring practice. Part II: Several factors affect the performance of monitoring strategies, including: measurable objectives, required precision in estimates, acceptable confidence levels of such estimates, available budget for sampling. In this paper, we develop place-based monitoring strategies based on extensive analysis of available historical water quality data (1960-1994) of 19 Iowa community water systems. These systems supply potable water to over 350,000 people. In the context of drinking water, the objective is to protect public health by utilizing monitoring resources to characterize contaminants that are detectable, and are close to exceeding health standards. A place-based monitoring strategy was developed in which contaminants were selected based on their historical occurrence, rather than their appearance on the SDWA contaminant list. In a subset of the water systems, the temporal frequency of monitoring for one ubiquitous contaminant, nitrate, was tailored to patterns in its historical occurrence and concentration. Three sampling allocation models (linear, quadratic, and cubic) based on historic patterns in peak occurrence were developed and evaluated. Random and fixed-interval sampling strategies within the context of such models were also developed and evaluated. Strategies were configured to incorporate a variety of options for frequency and number of samples (depending on budget and the desired precision in estimate of peak concentrations).     

Southern California's marine monitoring system ten years after the National Research Council evaluation

In 1990, the National Research Council (NRC) published two in-depth assessments of marine environmental monitoring effectiveness. The first of these, Managing Troubled Waters: The Role of Marine Environmental Monitoring, provided a national perspective and the second, Monitoring Southern California's Coastal Waters, examined the specifics of monitoring design and implementation in a densely populated, highly urbanized coastal region. The reports include explicit recommendations about the need for greater regionalization of monitoring efforts, supported by greater standardization of field, laboratory, and data analysis methods. They also identified the need for centralized data management and for greater flexibility in the language of standard discharge permits, flexibility that would permit discharge agencies to more readily participate in regional monitoring and research programs. Other recommendations identified a need for EPA and NOAA to focus on creating a national monitoring program structured as a network of coordinated local and regional efforts. Finally, the NRC emphasized the need for better reporting and for periodic review of monitoring's relevance to management concerns. In this paper, we use southern California as a test case to assess progress made in implementing the NRC's recommendations. We review progress made on each recommendation and discuss the features of the regulatory and management climate that contributed to or impeded this progress. We also consider whether, and to what extent, the NRC's recommendations remain relevant in the present context.     

Developing an optimal sampling design. A case study in a coastal marine ecosystem

The development of a sampling design for optimisingsampling site locations collected from a coastalmarine environment has been the purpose of the presentwork; application of statistical analysis and spatialautocorrelation methods have been carried out. Thedataset included data collected from 34 sampling sitesspaced out in the Strait of Lesbos, Greece, arrangedin a 1×1 NM grid. The coastal shallow ecosystem wassubdivided into three zones, an inner one (7stations), a middle one (16 stations) and an offshorezone (11 stations). The standard error of thechlorophyll-a concentrations in each zone hasbeen used as the criterion for the sampling designoptimisation, resulting into reallocation of thesampling sites into the three zones. The positions ofthe reallocated stations have been assessed byestimation of the spatial heterogeneity and anisotropyof chlorophyll-a concentrations usingvariograms. Study of the variance of the initialdataset of the inner zone taking into account spatialheterogeneity, revealed two different sub-areas andtherefore, the number of the inner stations has beenreassessed. The proposed methodology eliminates thenumber of sampling sites and maximises the informationof spatial data from marine ecosystems. It isdescribed as a step-by-step procedure and could bewidely applied in sampling design concerning coastalpollution problems.     

Development of the Coastal Intensive Site Network (CISNET)

The U.S. Environmental Protection Agency (EPA), National Oceanic and Atmospheric Administration (NOAA), and National Aeronautics and Space Administration (NASA) have formed a partnership to establish pilot sites for the development of a network known as the Coastal Intensive Site Network (CISNet). CISNet is composed of intensive, long-term monitoring and research sites around the U.S. marine and Great Lakes coasts. In this partnership, EPA and NOAA are funding research and monitoring programs at pilot sites that utilize ecological indicators and investigate the ecological effects of environmental stressors. NASA is funding research aimed at developing a remote sensing capability that will augment or enhance in situresearch and monitoring programs selected by EPA and NOAA. CISNet has three objectives: 1) to develop a sound scientific basis for understanding ecological responses to anthropogenic stresses in coastal environments, including the interaction of exposure, environment/climate, and biological/ecological factors in the response, and the spatial and temporal nature of these interactions, 2) to demonstrate the value of developing data from selected sites intensively monitored to examine the relationships between changes in environmental stressors, including anthropogenic and natural stresses, and ecological response, and 3) to provide intensively monitored sites for development and evaluation of indicators of change in coastal systems.     

1,4-Dichlorobenzene Marine Risk Assessment with Special Reference to the Osparcom Region: North Sea

This risk assessment on 1,4-dichlorobenzene was carried out for the marine environment, following methodology given in the EU risk assessment Regulation (1488/94) and Guidance Document of the EU New and Existing Substances Regulation (TGD, 1996). Data from analytical monitoring programs in large rivers and estuaries in the North Sea area were collected and evaluated on effects and environmental concentrations. Risk is indicated by the ratio of predicted environmental concentration (PEC) to predicted no-effect concentration (PNEC) for the marine aquatic environment. In total, 17 data for fish, 9 data for invertebrates and 7 data for algae were evaluated. Acute and chronic toxicity studies were taken into account and appropriate assessment factors used to define a final PNEC value of 20 microg/l. Recent monitoring data indicate that 1,4-dichlorobenzene levels in coastal waters and estuaries are below the determination limit of 0.1 microg/l used in monitoring programs. The worst case value recorded in river water is below 0.45 microg/l. Using these values, calculated PEC/PNEC ratios give safety margins of about 40-200, taking no account of dilution in the sea. Environmental fate and bioaccumulation data indicate that current use of 1,4-dichlorobenzene poses no risk to the aquatic environment.     

The challenges and opportunities in cumulative effects assessment

The cumulative effects of increasing human use of the ocean and coastal zone have contributed to a rapid decline in ocean and coastal resources. As a result, scientists are investigating how multiple, overlapping stressors accumulate in the environment and impact ecosystems. These investigations are the foundation for the development of new tools that account for and predict cumulative effects in order to more adequately prevent or mitigate negative effects. Despite scientific advances, legal requirements, and management guidance, those who conduct assessments—including resource managers, agency staff, and consultants—continue to struggle to thoroughly evaluate cumulative effects, particularly as part of the environmental assessment process. Even though 45 years have passed since the United States National Environmental Policy Act was enacted, which set a precedent for environmental assessment around the world, defining impacts, baseline, scale, and significance are still major challenges associated with assessing cumulative effects. In addition, we know little about how practitioners tackle these challenges or how assessment aligns with current scientific recommendations. To shed more light on these challenges and gaps, we undertook a comparative study on how cumulative effects assessment (CEA) is conducted by practitioners operating under some of the most well-developed environmental laws around the globe: California, USA; British Columbia, Canada; Queensland, Australia; and New Zealand. We found that practitioners used a broad and varied definition of impact for CEA, which led to differences in how baseline, scale, and significance were determined. We also found that practice and science are not closely aligned and, as such, we highlight opportunities for managers, policy makers, practitioners, and scientists to improve environmental assessment.     

Distributed process modeling for regional assessment of coastal vulnerability to sea-level rise

Sea-level rise involves increases in the coastal processes of inundation and erosion which are affected by a complex interplay of physical environmental parameters at the coast. Many assessments of coastal vulnerability to sea-level rise have been detailed and localised in extent. There is a need for regional assessment techniques which identify areas vulnerable to sea-level rise. Four physical environmental parameters – elevation, exposure, aspect and slope, are modeled on a regional scale for the Northern Spencer Gulf (NSG) study area using commonly available low-resolution elevation data of 10 m contour interval and GIS-based spatial modeling techniques. For comparison, the same parameters are modeled on a fine-scale for the False Bay area within the NSG using high-resolution elevation data. Physical environmental parameters on the two scales are statistically compared to coastal vulnerability classes as identified by Harvey et al. [1] using the Spearman rank-correlation test and stepwise linear regression. Coastal vulnerability is strongly correlated with elevation and exposure at both scales and this relationship is only slightly stronger for the high resolution False Bay data. The results of this study suggest that regional scale distributed coastal process modeling may be suitable as a first cut in assessing coastal vulnerability to sea-level rise in tide-dominated, sedimentary coastal regions. Distributed coastal process modeling provides a suitable basis for the assessment of coastal vulnerability to sea-level rise of sufficient accuracy for on-ground management and priority-setting on a regional scale.     

Economics of place-based monitoring under the safe drinking water act, part III: performance evaluation of place-based monitoring strategies

The goals of environmental legislation and associated regulations are to protect public health, natural resources, and ecosystems. In this context, monitoring programs should provide timely and relevant information so that the regulatory community can implement legislation in a cost-effective and efficient manner. The Safe Drinking Water Act (SDWA) of 1974 attempts to ensure that public water systems (PWSs) supply safe water to its consumers. As is the case with many other federal environmental statutes, SDWA monitoring has been implemented in relatively uniform fashion across the USA. In this three part series, we present over 30 years of evidence to demonstrate unique patterns in water quality contaminants over space and time, develop alternative place-based monitoring approaches that exploit such patterns, and evaluate the economic performance of such approaches to current monitoring practice. Part III: Place-based (PBA) and current SDWA monitoring approaches were implemented on test datasets (1995-2001) from 19 water systems and evaluated based on the following criteria: percent of total detections, percent detections above threshold values (e.g. 20, 50, 90% of MCL), and cost. The PBA outperformed the current SDWA monitoring requirements in terms of total detections, missed only a small proportion of detections below the MCL, and captured all detections above 50% of the MCL. Essentially the same information obtained from current compliance monitoring requirements can be gained at approximately one-eighth the cost by implementing the PBA. Temporal sampling strategies were implemented on test datasets (1995-2001) from four water systems and evaluated by the following criteria: parameter estimation, percent deviation from "true" 90th, 95th, and 99th percentiles, and number of samples versus accuracy of the estimate. Non event-based (NEB) strategies were superior in estimating percentiles 1-50, but underestimated the higher percentiles. Event-based strategies were superior in estimating 95th and 99th percentiles, and required significantly fewer samples (than NEB strategies) to estimate the "true" 95th and 99th percentiles. Incorporation of place-based information significantly improves the performance of monitoring and temporal sampling strategies in the context of surface-influenced water systems in the state of Iowa. Application of similar methods to other areas and types of water systems would likely produce similar results. Compared to current SDWA monitoring, the place based approach allows for cost-effective, enhanced characterization of local contaminants of concern.     

全国近岸海域水质空间插值算法精度分析

空间插值技术对近海环境数据的分析和表征具有广泛应用价值,但目前针对各类模型适用性和精度比较的研究很少。基于2009年全国近岸海域299个站位的水质监测数据,利用交叉检验法,对3种插值算法13种模型的空间拟合结果进行分析和验证。结果表明,13种模型的模拟值与实测值显著相关(r=0.643~0.750,P0.01,n=299),说明其均适用于近岸海域水质的空间模拟;综合比较模拟结果与实测结果的相关系数、平均误差、平均绝对误差、均方差及偏离程度,排序为IDW(p2)Spline-TensionIDW(p3)IDW(p4)IDW(p1)IDW(p5)IDW(p6)Kriging-GuassianKriging-Spherical,Kriging-CircularKriging-LinearKriging-ExponentialSpline-Regularized,提出IDW(p2)是精度最优的空间插值模型。     

Establishing the Canadian Community Monitoring Network

Community-based ecosystem monitoring activities in Canada are increasing in response to a number of factors including: (i) the needs of decision-makers for timely information on local environmental changes; (ii) limited use of government monitoring data and information by decision makers; (iii) government cuts to monitoring programs; (iv) the increasingly recognized need to include stakeholders in planning and management processes; and (v) the desire of citizens to contribute to environmental protection. To date there has been no network coordination of community based monitoring in Canada. This paper reports on the establishment of the Canadian Community Monitoring Network by Environment Canada's Ecological Monitoring and Assessment Network Coordinating Office and the Canadian Nature Federation. Information on research prepared in support of network establishment is presented along with a discussion of the potential of the network.     

A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.     

Monitoring Long-Term Ecological Changes Through the Ecological Monitoring and Assessment Network: Science-Based and Policy Relevant

Ecological monitoring and its associated research programshave often provided answers to various environmental management issues. In the face of changing environmental conditions, ecological monitoring provides decision-makers with reliable information as they grapple with maintaining a sustainable economy and healthy environment. The EcologicalMonitoring and Assessment Network (EMAN) is a national ecological monitoring network consisting of (1) about 100 casestudy sites across the country characterized by long-term multi-disciplinary environmental work conducted by a multitudeof agencies (142 partners and counting); (2) a variety of lesscomprehensive yet more extensive monitoring sites; (3) a network where core monitoring variables of ecosystem change aremeasured; and (4) geo-referenced environmental observations. Environment Canada is the co-ordinating partner for the network through the EMAN Co-ordinating Office. EMAN's mission is to focus a scientifically-sound, policy-relevant ecosystem monitoring and research network based on (a) stabilizing a network of case-study sites operated by a varietyof partners, and (b) developing a number of cooperative dispersedmonitoring initiatives in order to deliver unique and needed goods and services. These goods and services include: (1) an efficient and cost-effective early warning system which detects,describes and reports on changes in Canadian ecosystems at a national or ecozone scale; and (2) cross-disciplinary and cross-jurisdictional assessments of ecosystem status, trends and processes. The early warning system and assessments of ecosystem status, trends and processes provide Environment Canada and partner organizations with timely information thatfacilitates increasingly adaptive policies and priority setting. Canadians are also informed of changes and trends occurring in Canadian ecosystems and, as a result, are betterable to make decisions related to conservation and sustainability.     

Historical pollution trends in coastal environments of India

Seventeen sediment cores were collected from different coastalecosystems of Tamil Nadu, India that include coastal lagoon (Pulicat), polluted rivers in Chennai (Adyar and Cooum), Coral reef (Gulf of Mannar) and a perennial river (Tamiraparani).Radiometric dating has been used to determine the modern sedimentation rates in these ecosystems. The Pulicat Lake and thepolluted rivers (Adyar and Cooum) yield an average sediment accumulation rate of 12.34 and 7.85 mm yr^-1, respectively. Inthe Gulf of Mannar coral reef, the sedimentation rate averages 17.37 mm yr^-1, while the rate in Tamiraparani River is 11.00 mm yr^-1. In the Tamiraparani River basin, the deposition rates were an order of magnitude higher when compared to the erosion rates, which may be due to bank erosion and the intense human activity. In general high rates of sedimentation observed in the coastal ecosystems not only reflect the capacity of the coastal regions as sinks for trace metals but also denoteincreased input of pollutants into the coastal environments in the recent past. The deposition rates of heavy metals – Fe, Mn,Zn, Cu, Cr and Ni in the depth profiles have been computed using sedimentation rates and their distribution is discussed. It can be seen that the mean deposition rates of all the measured elements in the Tamil Nadu coastal ecosystems are high compared with rates determined for the sediments of the deltaic regions ofIndia and the Bay of Bengal.     

Evaluation of marine outfall with three-dimensional hydrodynamic and water quality modeling

Numerical models are often used to evaluate the potential impact of human alternation of natural water bodies and to help the design of the alternation to mitigate its impacts. In the past decade, three-dimensional hydrodynamic and reactive transport modeling has matured from a research subject to a practical analysis technology. This paper presents a practical study in which a three-dimensional hydrodynamic and water quality model [hydrodynamic eutrophication model (HEM-3D)] was applied to determine the optimal location for treated wastewater discharged from marine outfall system in the Keelung harbor and the adjacent coastal sea. First, model validation was conducted with respect to surface elevation, current, and water quality variables measured in the Keelung harbor station and its coastal sea. The overall performance of the model was in qualitative agreement with the available field data. The model was then used to evaluate several scenarios of the locations from marine outfall system. Based on model simulation results, a location at the northeast of Ho-Ping Island was recommended for adoption because the environmental impact is smaller than any other alternative.

Neural Network Based Automated Interpretation Algorithm for Combined Geophysical Soundings in Coastal Zones

The fresh water availability in coastal aquifers is an important problem faced by a major part of world’s population dwelling there. For in situ and dynamic characterization of seawater encroachment into coastal aquifers, electrical geophysical methods are better suited. However, the resolving power of such data in distinguishing saline sands from moist clays in the subsurface is very poor. To meet this aspect and also the problem of analyzing voluminous data sets, we propose a feed forward back-propagation neural network (BPNN) based approach for the analysis of combined vertical electrical and induced polarization soundings. Our method is tested on synthetic data computed from available geo-electric sections and prevailing subsurface geological information of coastal aquifers of East Coast of India.The synthetic data are comprised of 18 combined soundings spread over five profiles. 15 out of 18 are used for training the BPNN, while 3 are used for testing. The trained BPNN (one node each in each of the input and output layers and 18 hidden nodes) showed 84.85% accuracy in testing phase for distinguishing clays from saline sands.Our method is also tested on real data concerning a shaly aquifer in Bahia, Brazil yielding an overall accuracy of 84.9%, comparable to that of synthetic case; thereby validating our approach.