A disaggregated emissions inventory for Taiwan with uses in hybrid input‐output life cycle analysis (IO‐LCA)

This paper reports on a life‐cycle analysis (LCA) of Taiwan's “agriculture and forestry”, “crude petroleum, coal and natural gas extraction” and “electricity generation” sectors, revealing for the first time Taiwan's CO₂ and CH₄ emissions inventories and matching Taiwan's input‐output sectors. Integrated hybrid input‐output life cycle analysis is used to disaggregate the electricity generation sector into nuclear, hydro, gas, oil and coal, and cogeneration. Results show that the fossil‐fuel‐related electricity sub‐sectors have higher CO₂ emissions intensity than the remaining sectors in the economy and that the “paddy rice” sector is Taiwan's most CH₄‐intensive sector, making rice cultivation an important source of CH₄ emissions. This work is vital to sound policy decisions concerning power generation, coal, and agriculture and forestry at the national level.     

Use of experimental ecosystems in regulatory decision making

Tiered testing for the effects of chemicals on aquatic ecosystems has begun to include tests at the ecosystem level as a component in pesticide regristration. Because such tests are expensive, regulators and industry need to know what additional information they can gain from such tests relative to the costs of the simpler single-species toxicity bioassays. Requirements for ecosystem-level testing have developed because resource managers have not fully understood the implications of potential damage to resources without having evaluations of the predicted impacts under field conditions. We review approaches taken in the use of experimental ecosystems, discuss benefits and limitations of small- and large-scale ecosystem tests, and point to correlative approaches between laboratory and field toxicity testing.Laboratory experimental ecosystems (microcosms) have been successfully used to measure contaminant bioavailability, to determine routes of uptake in moderately complex aquatic systems, and to isolate factors modifying contaminant uptake into the biota. Such factors cannot be as readily studied in outdoor experimental ecosystems because direct cause-and-effect relations are often confounded and difficult to isolate. However, laboratory tests can be designed to quantify the relations among three variables: known concentrations of Stressors; specific sublethal behavioral, biochemical, and physiological effects displayed by organisms; and responses that have been observed in ecosystem-level analyses. For regulatory purposes, the specificity of test results determines how widely they can be applied. Ecotoxicological research should be directed at attempts to identify instances where single-species testing would be the appropriate level of analysis for identifying critical ecological endpoints and for clarifying relationships between ecosystem structure and function, and where it would be inadequate for a given level of analysis.     

Corporate occupational exposure limits: An example of a strategy

Occupational exposure limits (OELs) developed by authorities play a key role in the implementation of programs to protect workers against hazardous chemicals. Unfortunately, many hazardous substances do not have OELs or the OEL could be outdated. To assure the health of the workers, it is therefore useful for companies to develop corporate OELs. An inhouse strategy will be presented hereafter. Expertise in toxicology, industrial hygiene, and occupational health should be available within the company and clear selection criteria for substances are needed. A corporate OEL is only developed for hazardous substances (e.g., carcinogenic or reprotoxic) with a high potential for worker exposure when an appropriate national OEL or threshold limit value is not available. The methodology to calculate corporate OELs is based on the existing methods for national or community OELs and also on the guidance from the European Union's (EU) regulation on the Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH). For carcinogenic substances with a nonthreshold mode of action, there is always a residual chance that a cancer develops even when the exposure of workers is low. To establish an OEL for these substances, the “German traffic light model” is recommended. It is pragmatic, defines an unacceptable, tolerable, and acceptable risk level when workers are exposed to these substances, and determines risk management for exposure reduction. Overall, the professional practice to develop OELs is a good example of corporate leadership to proactively protect the health of workers.     

ASSEMBLY OF MAP‐BASED STREAM NARRATIVES TO FACILITATE STAKEHOLDER INVOLVEMENT IN WATERSHED MANAGEMENT1

ABSTRACT: Watershed stewardship activities throughout North America have evolved into a process that requires more involvement in planning and decision making by community stakeholders. Active involvement of all stakeholders in the process of watershed stewardship is dependent on effective exchange of information among participants, and active involvement of a wide range of stakeholders from “communities of place” as well as those from “communities of interest.” We developed a map‐based stream narrative tool as a means to: (a) assemble a wealth of incompletely documented, “traditional” ecological or natural history observations for rivers or streams; and (b) promote a higher level of active involvement by community stakeholders in contributing to information‐based, watershed management. Creation of stream narratives is intended for use as a tool to actively engage local stakeholders in the development of a more comprehensive information system to improve management for multiple stewardship objectives in watersheds. Completion of map‐based stream narrative atlases provides a valuable supplement to other independent efforts to assemble observations and knowledge about land‐based natural resources covering entire watersheds. We are confident that completion of stream narrative projects will make a valuable addition to the information and decision making tools that are currently available to the public and resource agencies interested in advancing the cause of community‐based approaches to watershed and ecosystem management.     

Ensemble Streamflow Forecast: A GLUE‐Based Neural Network Approach1

Abstract: While training a Neural Network to model a rainfall‐runoff process, generally two aspects are considered: its capability to be able to describe the complex nature of the processes being modeled and the ability to generalize so that novel samples could be mapped correctly. The general conclusion is that, the smallest size network capable of representing the sample distribution is the best choice, as far as generalization is concerned. Oftentimes input variables are selected a priori in what is called an explanatory data analysis stage and are not part of the actual network training and testing procedures. When they are, the final model will have only a “fixed” type of inputs, lag‐space, and/or network structure. If one of these constituents was to change, one would obtain another equally “optimal” Neural Network. Following Beven and others' generalized likelihood uncertainty estimate approach, a methodology is introduced here that accounts for uncertainties in network structures, types of inputs, and their lag‐space relationships by looking at a population of Neural Networks rather than target in getting a single “optimal” network. It is shown that there is a wide array of networks that provide “similar” results, as seen by a likelihood measure, for different types of inputs, lag‐space, and network size combinations. These equally optimal networks expose the range of uncertainty in streamflow predictions and their expected value results in a better performance than any of the single network predictions.     

Sustainable Water Resources Management in a Conflict Resolution Framework1

Abstract: A decision support system for sustainable water resources management in a water conflict resolution framework is developed to identify and evaluate a range of acceptable alternatives for the Geum River Basin in Korea and to facilitate strategies that will result in sustainable water resource management. Working with stakeholders in a “shared vision modeling” framework, sustainable management strategies are created to illustrate system tradeoffs as well as long‐term system planning. A multi‐criterion decision‐making (MCDM) approach using subjective scales is utilized to evaluate the complex water resource allocation and management tradeoffs between stakeholders and system objectives. The procedures used in this study include the development of a “shared vision model,” a simulated decision‐making support system (as a tool for sustainable water management strategies associated with water conflicts, management options, and planning criteria), and the application of MCDM techniques for evaluating alternatives provided by the model. The research results demonstrate the utility of the sustainable water resource management model in aid of MCDM techniques in facilitating flexibility during initial stages of alternative identification and evaluation in a basin suffering from severe water conflicts.     

Growth of the Decision Tree: Advances in Bottom‐Up Climate Change Risk Management

There has recently been a return in climate change risk management practice to bottom‐up, robustness‐based planning paradigms introduced 40 years ago. The World Bank's decision tree framework (DTF) for “confronting climate uncertainty” is one incarnation of those paradigms. In order to better represent the state of the art in climate change risk assessment and evaluation techniques, this paper proposes: (1) an update to the DTF, replacing its “climate change stress test” with a multidimensional stress test; and (2) the addition of a Bayesian network framework that represents joint probabilistic behavior of uncertain parameters as sensitivity factors to aid in the weighting of scenarios of concern (the combination of conditions under which a water system fails to meet its performance targets). Using the updated DTF, water system planners and project managers would be better able to understand the relative magnitudes of the varied risks they face, and target investments in adaptation measures to best reduce their vulnerabilities to change. Next steps for the DTF include enhancements in: modeling of extreme event risks; coupling of human‐hydrologic systems; integration of surface water and groundwater systems; the generation of tradeoffs between economic, social, and ecological factors; incorporation of water quality considerations; and interactive data visualization.     

Approaches to Evaluate Water Quality Model Parameter Uncertainty for Adaptive TMDL Implementation1

Abstract: The National Research Council recommended Adaptive Total Maximum Daily Load implementation with the recognition that the predictive uncertainty of water quality models can be high. Quantifying predictive uncertainty provides important information for model selection and decision‐making. We review five methods that have been used with water quality models to evaluate model parameter and predictive uncertainty. These methods (1) Regionalized Sensitivity Analysis, (2) Generalized Likelihood Uncertainty Estimation, (3) Bayesian Monte Carlo, (4) Importance Sampling, and (5) Markov Chain Monte Carlo (MCMC) are based on similar concepts; their development over time was facilitated by the increasing availability of fast, cheap computers. Using a Streeter‐Phelps model as an example we show that, applied consistently, these methods give compatible results. Thus, all of these methods can, in principle, provide useful sets of parameter values that can be used to evaluate model predictive uncertainty, though, in practice, some are quickly limited by the “curse of dimensionality” or may have difficulty evaluating irregularly shaped parameter spaces. Adaptive implementation invites model updating, as new data become available reflecting water‐body responses to pollutant load reductions, and a Bayesian approach using MCMC is particularly handy for that task.     

Assessment of Endocrine‐Disrupting Chemicals Attenuation in a Coastal Plain Stream Prior to Wastewater Treatment Plant Closure

The U.S. Geological Survey is conducting a combined pre/post‐closure assessment at a long‐term wastewater treatment plant (WWTP) site at Fort Gordon near Augusta, Georgia. Here, we assess select endocrine‐active chemicals and benthic macroinvertebrate community structure prior to closure of the WWTP. Substantial downstream transport and limited instream attenuation of endocrine‐disrupting chemicals (EDCs) was observed in Spirit Creek over a 2.2‐km stream segment downstream of the WWTP outfall. A modest decline (less than 20% in all cases) in surface water detections was observed with increasing distance downstream of the WWTP and attributed to partitioning to the sediment. Estrogens detected in surface water in this study included estrone (E1), 17β‐estradiol (E2), and estriol (E3). The 5 ng/l and higher mean estrogen concentrations observed in downstream locations indicated that the potential for endocrine disruption was substantial. Concentrations of alkylphenol ethoxylate (APE) metabolite EDCs also remained statistically elevated above levels observed at the upstream control site. Wastewater‐derived pharmaceutical and APE metabolites were detected in the outflow of Spirit Lake, indicating the potential for EDC transport to aquatic ecosystems downstream of Fort Gordon. The results indicate substantial EDC occurrence, downstream transport, and persistence under continuous supply conditions and provide a baseline for a rare evaluation of ecosystem response to WWTP closure.     

Consideration of User Needs and Spatial Accuracy in Drought Mapping1

Abstract: The increasing availability of web mapping tools creates new opportunities to bridge decision‐makers’ climate information needs with technical capabilities. These new tools, however, raise familiar, unresolved issues related to cartographic representation. Using an on‐line drought mapping tool, this study seeks to understand which spatial unit best meets the desire drought managers have for “local” information, their comprehension of uncertainties introduced in mapping information at local scales, and their willingness to trade off accuracy for information at a desired unit. We found that the most useful local map information includes regional context and boundaries which present their local area of interest. Even among this experienced, well‐educated, professional group, those who had not taken a GIS or cartography class did not fully recognize the role of interpolation in creating and introducing uncertainty to some drought maps. Those who did recognize the uncertainty introduced by interpolation still strongly favored maps that provided estimated values for all areas vs. station point accuracy. Mapping poses a unique set of challenges to communicating risk and uncertainty. As more decision‐support efforts incorporate web mapping, greater attention is needed to assure that users understand the tradeoffs between accuracy and precision in creating local information, the imprecision of boundaries, as well as the limits of forecasts. Clearly conveying spatial accuracy and uncertainty is a challenge that merits greater attention in using maps to communicate drought and other environmental risk information.     

Streamflow Hydrology Estimate Using Machine Learning (SHEM)

Continuity and accuracy of near real‐time streamflow gauge (streamgage) data are critical for flood forecasting, assessing imminent risk, and implementing flood mitigation activities. Without these data, decision makers and first responders are limited in their ability to effectively allocate resources, implement evacuations to save lives, and reduce property losses. The Streamflow Hydrology Estimate using Machine Learning (SHEM) is a new predictive model for providing accurate and timely proxy streamflow data for inoperative streamgages. SHEM relies on machine learning (“training”) to process and interpret large volumes (“big data”) of historic complex hydrologic information. Continually updated with real‐time streamflow data, the model constructs a virtual dataset index of correlations and groups (clusters) of relationship correlations between selected streamgages in a watershed and under differing flow conditions. Using these datasets, SHEM interpolates estimated discharge and time data for any indexed streamgage that stops transmitting data. These estimates are continuously tested, scored, and revised using multiple regression analysis processes and methodologies. The SHEM model was tested in Idaho and Washington in four diverse watersheds, and the model's estimates were then compared to the actual recorded data for the same time period. Results from all watersheds revealed a high correlation, validating both the degree of accuracy and reliability of the model.     

城轨车辆的试验设施

城轨车辆制造完成后,应按国际电工标准IEC61133进行型式试验与例行试验.本文介绍了国外完成这些试验所具备的试验设施,包括维也纳的车辆环境试验中心,西门子公司的牵引系统试验中心及庞巴迪包岑工厂的车辆试验设施.     

Modeling Connectivity of Non‐floodplain Wetlands: Insights,Approaches, and Recommendations

Representing hydrologic connectivity of non‐floodplain wetlands (NFWs) to downstream waters in process‐based models is an emerging challenge relevant to many research, regulatory, and management activities. We review four case studies that utilize process‐based models developed to simulate NFW hydrology. Models range from a simple, lumped parameter model to a highly complex, fully distributed model. Across case studies, we highlight appropriate application of each model, emphasizing spatial scale, computational demands, process representation, and model limitations. We end with a synthesis of recommended “best modeling practices” to guide model application. These recommendations include: (1) clearly articulate modeling objectives, and revisit and adjust those objectives regularly; (2) develop a conceptualization of NFW connectivity using qualitative observations, empirical data, and process‐based modeling; (3) select a model to represent NFW connectivity by balancing both modeling objectives and available resources; (4) use innovative techniques and data sources to validate and calibrate NFW connectivity simulations; and (5) clearly articulate the limits of the resulting NFW connectivity representation. Our review and synthesis of these case studies highlights modeling approaches that incorporate NFW connectivity, demonstrates tradeoffs in model selection, and ultimately provides actionable guidance for future model application and development.     

Stationarity: Wanted Dead or Alive?1

Lins, Harry F. and Timothy A. Cohn, 2011. Stationarity: Wanted Dead or Alive? Journal of the American Water Resources Association (JAWRA) 47(3):475‐480. DOI: 10.1111/j.1752‐1688.2011.00542.x Abstract: Aligning engineering practice with natural process behavior would appear, on its face, to be a prudent and reasonable course of action. However, if we do not understand the long‐term characteristics of hydroclimatic processes, how does one find the prudent and reasonable course needed for water management? We consider this question in light of three aspects of existing and unresolved issues affecting hydroclimatic variability and statistical inference: Hurst‐Kolmogorov phenomena; the complications long‐term persistence introduces with respect to statistical understanding; and the dependence of process understanding on arbitrary sampling choices. These problems are not easily addressed. In such circumstances, humility may be more important than physics; a simple model with well‐understood flaws may be preferable to a sophisticated model whose correspondence to reality is uncertain.     

Application of a Modified Health Belief Model to the Pro‐Environmental Behavior of Private Well Water Testing

A social cognition model of health behavior, the health belief model, was applied to the pro‐environmental behavior of private well water testing. Conceptualizing environmental behaviors as health behaviors may provide new insight into pro‐environmental behavior change. A groundwater education program was provided to K‐12 children throughout New England. Both child participants and their parents completed surveys pertaining to private well water behavior. Results indicate that perceived barriers and socioeconomic status significantly influenced past well water testing of parent participants. Perceived barriers included: participants' concern related to the cost of treating their water, and how a well water problem would influence their property value. Parent participants also indicated that they would perform future well water testing if they received a reminder cue to action that might include: getting a discount or reminder in the mail, if a well testing program was available, and state or local requirement. Our findings reinforce the need for continued private well water research and parallels to additional environmental behaviors.     

Geographic information systems: a tool for strategic ground water quality management

Geographically‐related information is needed for several elements of an integrated ground water quality management programme, including ground water monitoring planning, prioritization of pollution sources, usage of permits and inspections for source control, and planning and completion of remedial actions. Geographic Information Systems (GISs) can be used to support these elements along with delineating wellhead protection areas (WHPAs), prioritizing existing contaminant sources and evaluating proposed changes in land usage in such areas. Eight case studies of the use of GISs in wellhead protection programmes are summarized, including examples from Rhode Island, Mississippi, New Jersey, New York, Pennsylvania, Kansas, Massachusetts and Texas. Six additional examples are mentioned relative to the use of GISs for evaluating ground water pollution potential, facilitating data analysis for environmental restoration of a large area with numerous waste sites, evaluating trends in ground water nitrate contamination, establishing a national database for ground water vulnerability to agricultural chemicals, simulating water table altitudes from stream and drainage basin locations, and selecting radioactive waste dump sites. The applicability of GISs and their associated advantages in wellhead protection and other ground water management studies are demonstrated via the case studies. The GIS technology provides a unique opportunity for analysing and visualizing spatial data. Contaminant and source prioritization within WHPAs is needed for both extant conditions and in the evaluation of proposed land use changes. The coupling of a GIS with contaminant/source prioritization would provide a strategic tool which could be used to plan targeted ground water monitoring programmes, to identify appropriate management or mitigation measures, minimize introduction of contaminants from existing sources into the subsurface environment, and to evaluate the potential of proposed land use activities for causing ground water contamination. GISs can be useful in providing current information for policy makers, planners and managers engaged in ground water quality decision making.     

Forecasting the Probability of Future Groundwater Levels Declining Below Specified Low Thresholds in the Conterminous U.S.

We present a logistic regression approach for forecasting the probability of future groundwater levels declining or maintaining below specific groundwater‐level thresholds. We tested our approach on 102 groundwater wells in different climatic regions and aquifers of the United States that are part of the U.S. Geological Survey Groundwater Climate Response Network. We evaluated the importance of current groundwater levels, precipitation, streamflow, seasonal variability, Palmer Drought Severity Index, and atmosphere/ocean indices for developing the logistic regression equations. Several diagnostics of model fit were used to evaluate the regression equations, including testing of autocorrelation of residuals, goodness‐of‐fit metrics, and bootstrap validation testing. The probabilistic predictions were most successful at wells with high persistence (low month‐to‐month variability) in their groundwater records and at wells where the groundwater level remained below the defined low threshold for sustained periods (generally three months or longer). The model fit was weakest at wells with strong seasonal variability in levels and with shorter duration low‐threshold events. We identified challenges in deriving probabilistic‐forecasting models and possible approaches for addressing those challenges.     

New perspectives in ecotoxicology

The task of regulating potentially harmful chemicals in the environment is presently hindered by the lack of appropriate concepts and methods for evaluating the effects of anthropogenic chemicals on ecosystems. Toxicity tests at the molecular and physiological levels have been used successfully as indicators of adverse effects on test organisms and have been extrapolated to humans to establish a basis for risk assessment. However, laboratory measurements of effects upon individuals do not translate readily into potential effects upon natural populations, in part because natural populations interact with other populations and with the physical environment. Even more difficult to assess are the deleterious impacts of anthropogenic chemicals on ecosystems, because of effects on species interactions, diversity, nutrient cycling, productivity, climatic changes, and other processes.Effects on ecosystems resulting from chemical stresses are outside the realm of classical toxicology, and an ecosystem-level perspective is essential for the consideration of such effects; but the science that deals with ecosystem-level effects,ecotoxicology, is still developing. This article synthesizes the topics discussed at a workshop on ecotoxicology held by the Ecosystems Research Center at Cornell University. Topics covered include: the regulatory framework in which ecotoxicological research must be applied; ecosystem modification of toxicant fate and transport; how ecosystem composition, structure, and function are influenced by chemicals; methods currently available for predicting the effects of chemicals at the ecosystem level; and recommendations on research needs to enhance the state of the science of ecotoxicology.     

APPLICATION OF ENHANCED ANNEALING TO GROUND WATER REMEDIATION DESIGN1

ABSTRACT: A methodology for ground water remediation design has been developed that interfaces ground water simulation models with an enhanced annealing optimizer. The ground water flow and transport simulators provide the ability to consider site‐specific contamination and geohydrologic conditions directly in the assessment of alternative remediation system designs. The optimizer facilitates analysis of tradeoffs between technical, environmental, regulatory, and financial risks for alternative design and operation scenarios. A ground water management model using an optimization method referred to as “enhanced annealing” (simulated annealing enhanced to include “directional search” and “memory” mechanisms) has been developed and successfully applied to an actual restoration problem. The demonstration site is the contaminated unconfined aquifer referred to as N‐Springs located at Han‐ford, Washington. Results of the demonstration show the potential for improving groundwater restoration system performance while reducing overall system cost.     

Environmental and socioeconomic impacts of cobblestone quarries in Addis Ababa and implication for resource use efficiency,environmental quality,and sustainability of land after‐use

The extraction of construction material in Addis Ababa has been a source of public conflict for many years, especially in terms of quarry operation, displacement of people, rehabilitation of quarry sites, and land after‐use. One of the main reasons for the conflict has been the extraction sector's inability to adjust to the existing laws. This paper reports the findings of a study undertaken to assess the environmental and socioeconomic impacts of quarry mining in Addis Ababa, Ethiopia, and it prescribes interventions that can assist in mitigating the negative impacts of mining. Marked operational, environmental, and socioeconomic impacts have occurred as a result of cobblestone quarrying in Addis Ababa. Improvements in the mitigation of these impacts can be achieved if quarrying operations are planned prior to commencement; resource‐efficient and sustainable mining techniques are employed; stakeholder participation is enhanced; the government provides institutional, organizational, and technical support to the operators; regulations are improved and regulatory implementations receive strict follow‐up; and the provision of the Ethiopian constitution's regarding “rights to development” is respected.