Risk-based standards: integrating top–down and bottom–up approaches

In response to rapidly changing threats posed to increasingly complex socio-technical systems, many in the government and private sector have called for protection through risk-based standards. However, given the nature of these dynamic and uncertain threats, traditional risk assessment techniques may not be sufficient. Instead, there is a critical need for an integrated approach in which decision analytic techniques are used to assess evidence-based data with the values and preferences of decision makers. We point to three examples in the fields of nuclear power regulation, nanotechnology, and cybersecurity, where risk-based approaches (bottom–up) have been combined with decision analysis (top–down) to guide decision makers toward risk management policies that manifest both the best available evidence and the plurality of values within a society.     

Risk and resilience lessons from Venice

In the history of disasters in Venice, there are implications for modern times in terms of complex systems management and emerging threats, in particular from examples of risk management and resilience achieved by the Venetian state during outbreaks of the plague. In fourteenth century Venice, risk assessment the way we practice it today would fail to provide meaningful recommendations to reduce the casualty rate of the plague epidemic because the cause and transmission of the disease was not understood. Instead, a set of systemic actions across the social, economic, and transportation networks of the city taken by officials and doctors eventually slowed and arguably stopped the spread of the disease. These latter actions are an early example of what is now considered resilience management. Resilience management improves a complex system’s ability to prepare, absorb, recover, and adapt to unexpected threats and does so by address the capabilities at a system, rather than component, level. Resilience management can be a guide to addressing current issues of population growth and rising sea level in modern day Venice and across the globe. This paper calls for integration of resilience assessment in comprehensive risk and resilience management framework.     

Climate change mitigation policy paradigms—national objectives and alignments

The aim of this paper is to assess how policy goals in relation to the promotion of green growth, energy security, pollution control and greenhouse gas (GHG) emissions reductions have been aligned in policies that have been implemented in selected countries during the last decades as a basis for discussing how a multi objective policy paradigm can contribute to future climate change mitigation. The paper includes country case studies from Brazil, Canada, China, the European Union (EU), India, Japan, Mexico, Nigeria, South Africa, South Korea and the United States covering renewable energy options, industry, transportation, the residential sector and cross-sectoral policies. These countries and regions together contribute more than two thirds of global GHG emissions. The paper finds that policies that are nationally driven and that have multiple objectives, including climate-change mitigation, have been widely applied for decades in both developing countries and industrialised countries. Many of these policies have a long history, and adjustments have taken place based on experience and cost effectiveness concerns. Various energy and climate-change policy goals have worked together in these countries, and in practice a mix of policies reflecting specific priorities and contexts have been pursued. In this way, climate-change mitigation has been aligned with other policy objectives and integrated into broader policy packages, though in many cases specific attention has not been given to the achievement of large GHG emission reductions. Based on these experiences with policy implementation, the paper highlights a number of key coordination and design issues that are pertinent to the successful joint implementation of several energy and climate-change policy goals.     

Application of non-linear automatic optimization techniques for calibration of HSPF.

Development of TMDLs (total maximum daily loads) is often facilitated by using the software system BASINS (Better Assessment Science Integrating point and Nonpoint Sources). One of the key elements of BASINS is the watershed model HSPF (Hydrological Simulation Program Fortran) developed by USEPA. Calibration of HSPF is a very tedious and time consuming task, more than 100 parameters are involved in the calibration process. In the current research, three non-linear automatic optimization techniques are applied and compared, as well an efficient way to calibrate HSPF is suggested. Parameter optimization using local and global optimization techniques for the watershed model is discussed. Approaches to automatic calibration of HSPF using the nonlinear parameter estimator PEST (Parameter Estimation Tool) with its Gauss-Marquardt-Levenberg (GML) method, Random multiple Search Method (RSM), and Shuffled Complex Evolution method developed at the University of Arizona (SCE-UA) are presented. Sensitivity analysis was conducted and the most and the least sensitive parameters were identified. It was noted that sensitivity depends on number of adjustable parameters. As more parameters were optimized simultaneously--a wider range of parameter values can maintain the model in the calibrated state. Impact of GML, RSM, and SCE-UA variables on ability to find the global minimum of the objective function (OF) was studied and the best variables are suggested. All three methods proved to be more efficient than manual HSPF calibration. Optimization results obtained by these methods are very similar, although in most cases RSM outperforms GML and SCE-UA outperforms RSM. GML is a very fast method, it can perform as well as SCE-UA when the variables are properly adjusted, initial guess is good and insensitive parameters are eliminated from the optimization process. SCE-UA is very robust and convenient to use. Logical definition of key variables in most cases leads to the global minimum.     

Desertification in Russia: Problems and solutions (an example in the Republic of Kalmykia-Khalmg Tangch)

During the second half of the 20th century Kalmykia has undergone severe desertification. Under Soviet rule, rangelands were increasingly devoted to animal production, and pastures were converted to cropland in a campaign to increase crops. Pastures were grazed two to three times their sustainable production, saiga populations and habitat greatly decreased, more than 17 million ha were subjected to wind erosion, 380,000 ha were transformed into moving sands, and 106,000 ha were ruined by secondary salinization and waterlogging. By the 1990s almost 80% of the Republic had undergone desertification, and 13% had been transformed into a true desert. In 1986 the General Scheme of Desertification Control was formulated. The scheme called for rotating pastures, reclaiming blown sand using silviculture, tilling overgrazed pastures and sowing fodder plants, and developing water supplies for pastures. In its early years the scheme has been successful. But the management of restored pastures usually reverts to the same farms responsible for the poor conditions, and there is great apprehension that degradation could reoccur. This case study concludes that the general cattle and agriculture development in Kalmykia is unviable for ecological and economic reasons, that Kalmykia should implement an adaptive policy oriented toward conservation and accommodating the interrelation and variability of land resources, that the desertification problem can be solved only by changing agrarian policy as a whole, and that a desertification control program must become an integral part of economic and social development of the Republic.     

Sources of uncertainty in model predictions: lessons learned from the IAEA Forest and Fruit Working Group model intercomparisons

The International Atomic Energy Agency (IAEA), through the BIOMASS program, has provided a unique international forum for assessing the relative contribution of different sources of uncertainty associated with environmental modeling. The methodology and guidance for dealing with parameter uncertainty have been fairly well developed and quantitative tools such as Monte-Carlo modeling are often recommended. The issue of model uncertainty is still rarely addressed in practical applications and the use of several alternative models to derive a range of model outputs (similar to what was done in IAEA model intercomparisons) is one of a few available techniques. This paper addresses the often overlooked issue of what we call 'modeler uncertainty,' i.e., differences in problem formulation, model implementation and parameter selection originating from subjective interpretation of the problem at hand. This study uses results from the Fruit and Forest Working Groups created under the BIOMASS program (BIOsphere Modeling and ASSessment). The greatest uncertainty was found to result from modelers' interpretation of scenarios and approximations made by modelers. In scenarios that were unclear for modelers, the initial differences in model predictions were as high as seven orders of magnitude. Only after several meetings and discussions about specific assumptions did the differences in predictions by various models merge. Our study shows that the parameter uncertainty (as evaluated by a probabilistic Monte-Carlo assessment) may have contributed over one order of magnitude to the overall modeling uncertainty. The final model predictions ranged between one and three orders of magnitude, depending on the specific scenario. This study illustrates the importance of problem formulation and implementation of an analytic-deliberative process in fate and transport modeling and risk characterization.     

Using the expert model PERPEST to translate measured and predicted pesticide exposure data into ecological risks

An important topic in the registration of pesticides and the interpretation of monitoring data is the estimation of the consequences of a certain concentration of a pesticide for the ecology of aquatic ecosystems. Solving these problems requires predictions of the expected response of the ecosystem to chemical stress. Up until now, a dominant approach to come up with such a prediction is the use of simulation models or safety factors. The disadvantage of the use of safety factors is a crude method that does not provide any insight into the concentration–response relationships at the ecosystem level. On the other hand, simulation models also have serious drawbacks like that they are often very complex, lack transparency, their implementation is expensive and there may be a compilation of errors, due to uncertainties in parameters and processes. In this paper, we present the expert model prediction of the ecological risks of pesticides (PERPEST) that overcomes these problems. It predicts the effects of a given concentration of a pesticide based on the outcome of already performed experiments using experimental ecosystems. This has the great advantage that the outcome is more realistic. The paper especially discusses how this model can be used to translate measured and predicted concentrations of pesticides into ecological risks, by taking data on measured and predicted concentrations of atrazine as an example. It is argued that this model can be of great use to evaluate the outcome of chemical monitoring programmes (e.g. performed in the light of the Water Framework Directive) and can even be used to evaluate the effects of mixtures.     

Clustering of aerosols in atmospheric turbulent flow

A mechanism of formation of small-scale inhomogeneities in spatial distributions of aerosols and droplets associated with clustering instability in the atmospheric turbulent flow is discussed. The particle clustering is a consequence of a spontaneous breakdown of their homogeneous space distribution due to the clustering instability, and is caused by a combined effect of the particle inertia and a finite correlation time of the turbulent velocity field. In this paper a theoretical approach proposed in Elperin et al. (2002) Phys Rev E 66:036302 is further developed and applied to investigate the mechanisms of formation of small-scale aerosol inhomogeneities in the atmospheric turbulent flow. The theory of the particle clustering instability is extended to the case when the particle Stokes time is larger than the Kolmogorov time scale, but is much smaller than the correlation time at the integral scale of turbulence. We determined the criterion of the clustering instability for the Stokes number larger than 1. We discussed applications of the analyzed effects to the dynamics of aerosols and droplets in the atmospheric turbulent flow.     

Advanced oxidation processes in azo dye wastewater treatment.

The chemical degradation of synthetic azo dyes color index (C.I.) Acid Orange 7, C.I. Direct Orange 39, and C.I. Mordant Yellow 10 has been studied by the following advanced oxidation processes: Fenton, Fenton-like, ozonation, peroxone without or with addition of solid particles, zeolites HY, and NH4ZSM5. Spectrophotometric (UV/visible light spectrum) and total organic carbon measurements were used for determination of process efficiency and reaction kinetics. The degradation rates are evaluated by determining their rate constants. The different hydroxyl radical generation processes were comparatively studied, and the most efficient experimental conditions for the degradation of organic azo dyes solutions were determined.     

Water-related problems of central Asia: some results of the (GIWA) International Water Assessment Program

This paper presents results of the research under the program Global International Waters Assessment (GIWA) for the Aral Sea basin (Subregion 24 of the GIWA program). These results show that the detemining factor for the region is freshwater shortage and the main issue is modification of stream flow. According to GIWA assessment estimations, freshwater shortage is responsible for about 70% of the developmental problems in the region. The current economy is developing under conditions of increasing water deficiency. In spite of increasing efforts by the governments of the countries in the region, and by the international community, the situation in regard to water supply and economic objectives in the countries of central Asia remains tense and shows clear tendencies towards aggravation and conflict. The main causes for this sharpening of ecological and socioeconomic conditions in the region are analyzed, and measures to mitigate stress in transboundary water-resources use are presented.