Auditing the quality of effluent discharges

The public and their elected representatives want to see whether they get Value-for-Money from investment in preventing pollution. For many rivers, the achievement of good water quality is a matter of regulating the discharges from wastewater treatment plants. The effective audit of the quality of such discharges is a good basis for measuring progress in controlling pollution. To prove that control is effective, the techniques which underpin the following tasks must be sound and consistent:

- the standards for rivers must be devised so that the environmental objectives are met with the required reliability; the form of the standards will be constrained by the procedures available to monitor compliance;

- the standards worked out for effluents must have the correct mathematical relation with the river targets, and they too must be consistent with the options available for auditing performance;

- the assessment of compliance must be objective; and,

- statistics used to summarise the performance of a region (or a Nation) must be simple, stable, clear, and consistent with the results for individual sites.

     

Macroinvertebrate Regionalisation for use in the Management of Aquatic Ecosystems in Victoria, Australia

The development of a broader, more holistic approach to aquaticecosystem management has been called for in recent years. Physical and chemical objectives alone are no longer consideredsufficient for the protection of aquatic ecosystems and shouldbe supplemented with biological objectives. The ubiquitousand sedentary nature of macroinvertebrates, combined with theirmeasurable response to environmental conditions, favour their use as important indicators in environmental policies. To establish biological objectives, there is a need for a regionalframework to limit the variability between ecosystems. Past studies have demonstrated that an a posteriori regionalisationapproach may be more useful than an a priori approach in explaining single component (e.g. macroinvertebrates) patternsacross ecosystems. This is particularly important as aquaticresource management agencies often focus on one or twocomponents of the ecosystem to assess environmental health. This study uses an a posteriori method to delineate and describebiological regions based on edge and riffle macroinvertebrate data. The regionalisation will provide a framework for settingbiological objectives, based on the range of reference conditionsmeasured within each separate region. The objectives will includeregional checklists for taxa and biotic indices. Predictive modelling in the style of RIVPACS or AUSRIVAS will also be usedwithin each region to develop objectives, incorporating local, regional and systematic features as predictor variables.     

Quantifying the Effects of Forest Management Strategies on the Production of Forest Values: Timber,Carbon, Oxygen,Water, and Soil

Forest management practices alter forest structure quantified with ecosystem characteristics and values. In this paper, we utilized a forest management simulation model to assess the effects of three forest management strategies focusing on timber production, carbon sequestration, oxygen production, soil erosion, and water production of a forest management unit in Turkey. A forest simulation model “ETÇAPSimülasyon” was developed and used to project forest ecosystem development over 100 years under three forest management policies of timber-oriented forest management (TFM), multipurpose forest management (MFM), and no intervention (NI). The results showed that TFM strategy produced more timber and its net present value than MFM and NI strategies did. The amount of carbon sequestration and oxygen production potential was also found to be the highest with TFM strategy than with the MFM and NI strategies. Compared with the other strategies, however, NI strategy produced the highest amount of water production and soil losses over the planning horizon. The effects of a forest management strategy depend mainly on the initial forest structure, the rate of development and the level of forest management interventions. Therefore, forest dynamics under various management strategies should be explained before the final management decision. Understanding long-term effects of any management strategies on forest structure will provide the basis for better reaching the management objectives.     

Framework for designing sampling programs

A general framework for designing sampling programs is described. As part of the sampling program the problem of concern, or reason for sampling, needs to be clearly stated and objectives specified. The development of a conceptual model will assist the clarification of objectives and the choice of indicators to be sampled.Objectives can then be stated as testable hypotheses and decisions made about the samallest difference/changes that are to be detected/observed by the sampling.To allow the collection of representative samples, and the statistical analysis of data to be collected, the potential sources of variability in the data must be considered. Site, selection, frequency and replication must account for the expected variability.Before field collection of samples occurs, the sample collection device needs to be tested as to its efficiency to collect a representative sample. It also will usually be necessary to consider how samples are to be preserved to inhibit biological and chemical change. All sample programs require a quality assurance program to identify, measure and control errors.As well as the above the cost-effectiveness of the program should be evaluated in terms of maximizing the information obtained/cost.     

Spatial variability of salinity and alkalinity of a field having salination risk in semi-arid climate in northern Turkey

Spatial variability of salinity and alkalinity is important for site-specific management since they are the most important factors influencing soil quality and agricultural production. The objectives of this study were to analyze spatial variability in salinity and alkalinity and some soil properties affecting salinity and alkalinity, using classical statistics and geostatistical methods, in an irrigated field with low-quality irrigation water diverted from drainage canals. A field of 5 da was divided into 10 m x 10 m grids (5 lines in the east-west direction and 10 lines in the north-south direction). The soil samples were collected from three depths (0-30, 30-60 and 60-90 cm) at each grid corner. The variation coefficients of OM and sand contents were higher than other soil properties. OM had the maximum variability, with a mean of 1.63% at 0-30 cm depth and 0.71% at 30-60 cm depth. Significant correlations occurred between ESP, EC and each of Ca, Mg, K and CaCO(3) contents of the soils (p<0.01). Experimental semivariograms were fitted to spherical and gaussian models. All geostatistical range values were greater than 36 m. The soil properties had spatial variability at small distances at 60-90 cm depth. EC was variable within short distances at 30-60 cm depth. The nugget effect of ESP increased with soil depth. Kriged contour maps revealed that soils had a salinisation and alkalisation tendency at 60-90 cm depth based on spatial variance structure of the EC and ESP values. Spatial variability in EC and ESP can depend on ground water level, quality of irrigation water, and textural differences.     

环境统计与排污许可衔接的工业源排放核算研究

环境统计面临依据排污许可数据估算工业污染排放总量的挑战.以某市4个行业6类污染物的排放数据为案例,讨论了在非重点源污染排放量估算问题上衔接排污许可和环境统计的可行性和存在的问题.研究结果表明:排污许可重点管理单位与环境统计重点调查单位存在显著差异,不能采用比率估算方法估算工业非重点源排污量;排污许可简化和登记管理单位排...     

Simulating Unstressed Crop Development and Growth Using the Unified Plant Growth Model (UPGM)

Since initial development of the EPIC model in 1989, the EPIC plant growth component has been incorporated into other erosion and crop management models (e.g., WEPS, WEPP, SWAT, ALMANAC, and GPFARM) and subsequently modified to meet research objectives of the model developers. This has resulted in different versions of the same base plant growth component. The objectives of this study are the following: (1) describe the standalone Unified Plant Growth Model (UPGM), initially derived from the WEPS plant growth model, to be used for merging enhancements from other EPIC-based plant growth models; and (2) describe and evaluate new phenology, seedling emergence, and canopy height sub-models derived from the Phenology Modular Modeling System (PhenologyMMS V1.2) and incorporated into UPGM. A 6-year (2005–2010) irrigated maize (Zea mays L.) study from northeast Colorado was used to calibrate and evaluate UPGM running both the original (i.e., based on WEPS) and new phenology, seedling emergence, and canopy height sub-models. Model statistics indicated the new sub-models usually resulted in better simulation results than the original sub-models. For example when comparing original and new sub-models, respectively, for predicting canopy height, the root mean square error (RMSE) was 53.7 and 40.7 cm, index of agreement (d) was 0.84 and 0.92, relative error (RE) was 26.0 and ?1.26 %, and normalized objective function (NOF) was 0.47 and 0.33. The new sub-models predict leaf number (old sub-models do not), with mean values for 4 years of 2.43 leaves (RMSE), 0.78 (d), 18.38 % (RE), and 0.27 (NOF). Simulating grain yield, final above ground biomass, and harvest index showed little difference when running the original or new sub-models. Both the new phenology and seedling emergence sub-models respond to varying water deficits, increasing the robustness of UPGM for more diverse environmental conditions. Future research will continue working to incorporate existing enhancements from other EPIC-based plant growth models to unify them into one model such as multispecies competition and N cycling.     

Quality assurance and quality control in monitoring programs

There are three general characteristics of the data to be collected in a monitoring program that should be met in order to maximize the use and value of the data: the data quality should be known, the data type and quality should be consistent and comparable, and the data should be available and accessible. Potential problems with each of these characteristics are addressed effectively by quality assurance and quality control. One of the most important aspects of quality assurance in a monitoring program is the development of a quality assurance plan, which should identify clearly the quality of the data needed and describe in detail the planned actions to provide confidence that the program will meet its stated objectives.Quality control data, which allow for the quality and suitability of the environmental data to be evaluated and ascertained, should be collected and utilized as an integral part of the QA effort associated with a monitoring program.     

A spatial hierarchical framework for the co-management of ecosystems in Canada and the United States for the upper Great Lakes region

Over the past three decades, considerable effort has been invested in the development of complex and comprehensive ecosystem classifications and inventories in many parts of North America. Paralleling this has been an evolution in those hierarchical frameworks guiding the development and application of classifications. However, resource management agencies continue to grapple with the dilemma of applying multiple classification and inventory templates over large jurisdictions, especially as they attempt to address ecosystem management objectives. Given that Canada and the United States share ecosystems and that commitments have been made by all levels of government to make progress towards ecosystem-based approaches to management, there is a need to provide the proper tools. Comprehensive goals will not be achieved without collaboration and cooperation.This paper outlines the range of ecosystem classification approaches that exist in the Upper Great Lakes region. Canadian and American national hierarchical frameworks are briefly examined. Specific information needs and tasks are outlined which must be followed, independent of national boundaries, for the successful integration of planning and monitoring programs for large regional ecosystems.A general model is proposed for the development and application of an integrated, multi-scale and bi-national ecosystem classification, inventory and information system. This approach would facilitate data sharing and communication across jurisdictional boundaries.     

Monitoring of growth and yield and response to silvicultural treatments

The objectives for monitoring the growth and yield of forests can range from collecting data to validate current management on an ownership to collecting data at a regional level to develop models, measure treatment response, or observe long-term growth trends. Traditional inventory and research data each have drawbacks for observing growth and yield and treatment response. The actual design of a monitoring system should try to minimize these problems, but will depend on the specific objectives. Monitoring of operations may take an inventory-type approach, while gathering regional information to build models requires a design more like research. Each organization must be responsible for monitoring its own operations, however, cooperatives offer a viable and cost effective alternative to gathering regional growth and response data. Monitoring programs will lead to confidence and credibility in management practices and in the use of tested models.     

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.     

Statistical evaluation of data from multi-laboratory testing of a measurement method intended to indicate the presence of dust resulting from the collapse of the World Trade Center

In this paper we describe a statistical analysis of the inter-laboratory data summarized in Rosati et al. (2008) to assess the performance of an analytical method to detect the presence of dust from the collapse of the World Trade Center (WTC) on September 11, 2001. The focus of the inter-lab study was the measurement of the concentration of slag wool fibers in dust which was considered to be an indicator of WTC dust. Eight labs were provided with two blinded samples each of three batches of dust that varied in slag wool concentration. Analysis of the data revealed that three of labs, which did not meet measurement quality objectives set forth prior to the experimental work, were statistically distinguishable from the five labs that did meet the quality objectives. The five labs, as a group, demonstrated better measurement capability although their ability to distinguish between the batches was somewhat mixed. This work provides important insights for the planning and implementation of future studies involving examination of dust samples for physical contaminants. This work demonstrates (a) the importance of controlling the amount of dust analyzed, (b) the need to take additional replicates to improve count estimates, and (c) the need to address issues related to the execution of the analytical methodology to ensure all labs meet the measurement quality objectives.     

Evaluating the environmental sustainability of biomass-based energy strategy: Using an impact matrix framework

A roadmap for a more sustainable energy strategy is complex, as its development interacts critically with the economic, social, and environmental dimensions of sustainable development. This paper applied an impact matrix method to evaluate the environmental sustainability and to identify the desirable policy objectives of biomass-based energy strategy for the case of Alberta. A matrix with the sustainability domains on one axis and areas of environmental impact on the other was presented to evaluate the nexus effect of policy objectives and bioenergy production.As per to our analysis, economic diversification, technological innovation, and resource conservation came up as the desirable policy objectives of sustainable development for Alberta because they demonstrated environmental benefits in all environmental impact categories, namely climate change, human health, and ecosystem. On the other hand, human health and ecosystem impacts were identified as trade-offs when the policy objectives for sustainability were energy security, job creation, and climate change. Thus, bioenergy can mitigate climate change but may impact human health and ecosystem which then in turn can become issues of concern. Energy strategies may result in shifting of risks from one environmental impact category to another, and from one sustainable domain to another if the technical and policy-related issues are not identified.     

Predicting climate change effects on surface soil organic carbon of Louisiana,USA

This study aimed to assess the degree of potential temperature and precipitation change as predicted by the HadCM3 (Hadley Centre Coupled Model, version 3) climate model for Louisiana, and to investigate the effects of potential climate change on surface soil organic carbon (SOC) across Louisiana using the Rothamsted Carbon Model (RothC) and GIS techniques at the watershed scale. Climate data sets at a grid cell of 0.5°?×?0.5° for the entire state of Louisiana were collected from the HadCM3 model output for three climate change scenarios: B2, A2, and A1F1, that represent low, higher, and even higher greenhouse gas emissions, respectively. Geo-referenced datasets including USDA-NRCS Soil Geographic Database (STATSGO), USGS Land Cover Dataset (NLCD), and the Louisiana watershed boundary data were gathered for SOC calculation at the watershed scale. A soil carbon turnover model, RothC, was used to simulate monthly changes in SOC from 2001 to 2100 under the projected temperature and precipitation changes. The simulated SOC changes in 253 watersheds from three time periods, 2001–2010, 2041–2050, and 2091–2100, were tested for the influence of the land covers and emissions scenarios using SAS PROC GLIMMIX and PDMIX800 macro to separate Tukey-Kramer (p?p?p?p?相似文献   

High speed rail comparative strategic assessments in EU member states

This paper explores the role and capacity of strategic level assessments in addressing the strategic dimension of High Speed Rail (HSR) proposals and influencing decision-making processes. The overall research objective was to find out to what extent opportunities for strategic thinking are being undertaken in HSR. Three different cases of high speed rail were compared – High Speed Rail 2 (HS2) in the UK, High Speed Rail Network (RFAV) in Portugal and European Gauge Railway Line Kaunas in the Lithuanian-Latvian Border (Rail Baltica 2). Strategic environmental assessment (SEA) effectiveness literature was reviewed to draw on criteria that could establish a comparative framework to explain how environmental and sustainability assessments were undertaken in the three aforementioned European high speed rail case studies. Research results allow us to conclude that an SEA or a sustainability assessment/appraisal (SA) will be most beneficial if developed before any HSR project to first determine if HSR is really necessary and strategically justifiable to the achievement of both environmental and sustainability objectives. Results achieved suggest that even though the SEA and SA in the three cases studied can be said to have influenced the planning process mostly at project-level decisions, it also shows a missed opportunity to contribute to developing a high level strategy for HSR that addresses several strategic issues, assessing options before they are undertaken.     

Water quality assessment programs in Australia deciding what to measure,and how and where to use bioindicators

Effective water quality assessment programs require the formulation of common objectives between managers who are making decisions and scientists who are obtaining the information on which those decisions are to be made. The data collected must be apropriate for use in the decision making process. After the objectives have been formulated a number of testable hypotheses can be proposed and evaluated in terms of what information is required for decision making.From a management perspective it is important to know if an impact occurs and what management strategy to adopt to reduce or eliminate the impact. When bioaccumulators are used to indicate environmental quality the organisms proposed need to be fully evaluated before being used. Communities, which are often used to assess levels of impact, have the capacity to assimilate pollutants and they will function under pollutant stress. Thus managers need to make value judgements about when a community structure or function has shifted from acceptable to adverse. Bioassays in which the effects of pollutants on growth, biochemistry and behaviour are measured, give an indication of the sub-lethal effects of a pollutant, but it is difficult to set meaningful levels that are not to be exceeded for use by managers.Difficulties in using chemical and biological data mainly arise from a lack of appreciation of environmental heterogeneity. The data obtained must meet the needs for statistically testing hypotheses. Before programs can be designed to meet statistical needs the potential sources of variability must be considered. Once the minimum differences that are seen as important have been determined, the number of replicates needed can be calculated. Data verification is also needed, as if the validity of data is questioned, so will any decisions that have been made based on those data. Finally programs should be designed to minimize the sampling effort/cost to meet the objectives.     

Mapping nitrate leaching to upper groundwater in the sandy regions of The Netherlands, using conceptual knowledge

The European Community asks its Member States to provide a comprehensive and coherent overview of their groundwater chemical status. It is stated that simple conceptual models are necessary to allow assessments of the risks of failing to meet quality objectives. In The Netherlands two monitoring networks (one for agriculture and one for nature) are operational, providing results which can be used for an overview. Two regression models, based upon simple conceptual models, link measured nitrate concentrations to data from remote sensing images of land use, national forest inventory, national cattle inventory, fertiliser use statistics, atmospheric N deposition, soil maps and weather monitoring. The models are used to draw a nitrate leaching map and to estimate the size of the area exceeding the EU limit value in the early 1990s. The 95% confidence interval for the fraction nature and agricultural areas where the EU limit value for nitrate (50 mg/l) was exceeded amounted to 0.77–0.85 while the lower 97.5% confidence limit for the fraction agricultural area where the EU limit value was exceeded amounted to 0.94. Although the two conceptual models can be regarded as simple, the use of the models to give an overview was experienced as complex.     

Urinary nickel concentrations and selected pregnancy outcomes in delivering women and their newborns among arctic populations of Norway and Russia

The two objectives of this study were to compare urinary nickel excretion in pregnant women and their newborns living in the Murmansk and Arkhangelsk Counties of Russia with that in comparable Norwegian populations living in Finnmark and the city of Bergen and to assess the influence on pregnancy outcome of different risk variables, specifically urinary nickel concentrations and questionnaire-based anamnestic information. Life-style information and urine samples were collected from 50 consecutive mother-infant pairs from hospital delivery departments in three Russian and three Norwegian communities. Pregnancy outcomes were verified from medical records. Urinary nickel excretion was significantly higher in the Russian communities, independent of the presence of a nickel refinery as a local environmental source. The birth weight and mean body mass index of the newborn children (BMIC) were significantly lower (p < 0.001) in the Russian groups, with or without adjustment for gestational age. A multivariate linear regression analysis indicated that maternal urinary nickel concentration had no impact on birth weight. The maternal body mass index (BMI) and maternal height were positive explanatory variables; maternal urinary creatinine is suggested as a weak negative factor. Smoking was shown to be a strong negative predictor only in the Norwegian group among whom there was a significantly higher smoking frequency (p = 0.005). The significant contribution of a country factor in the predictive model is interpreted to indicate that a number of important risk factors for low birth weight were not identified.     

Applying mathematical programming to reserve selection

During the last 10–15 years heuristic methods have been developed for problems in optimal reserve selection. Unfortunately, there is no guarantee that heuristics will find optimal solutions. In recognizing this limitation, analysts have formulated reserve selection problems as set covering problems, for which matrix reduction and integer (0/1) programming can be used to find optimal solutions. In this paper we restate the set covering formulation and review solution techniques. A new 0/1 programming model, which is a generalization of the set covering model, is then presented and applied to a hypothetical reserve selection problem. Objectives of minimizing the number of sites selected and maximizing the number of species represented are addressed. Solutions which characterize the tradeoffs between these objectives provide a rich set of information for planners and decision makers. Applications of mathematical programming to related problems in land use planning and forestry are also discussed.