Designating Air Quality Management Areas (AQMAs) in the UK Implications for Securing UK Air Quality Objectives

Across the United Kingdom, the majority of local authoritieshave now completed their first phase of local air qualityreview and assessment work, as required under the AirQuality Strategy for England, Scotland, Wales and NorthernIreland (DETR, 2000a). Emerging from this first phasework is an anticipated suite of over 110 Air QualityManagement Areas (AQMAs). These areas are identifiedlocations where one or more of the national air qualityobjectives are predicted to exceed by specific target dates,and their spatial extent and shape is emerging as highlyvariable. Local authorities are guided to use a variety ofscientific tools to underpin the scientific assessments, anda consideration of uncertainty in both the tools used andsubsequent delineation of AQMAs is likely to affect theemerging management areas significantly. With subsidiarity underpinning the process of local air qualitymanagement (LAQM), local decision-making is anticipated toinfluence the outcome of the LAQM process in its entirety,with the declaration of AQMAs necessitating the preparationand implementation of air quality action plans. UKexperience of the effective management of local air quality,through the designation of AQMAs, demonstrates a valuableframework for other European countries developing mechanismsto manage air quality locally.     

UNCERTAINTY ANALYSIS OF BMP EFFECTWENESS FOR CONTROLLING NITROGEN FROM URBAN NONPOINT SOURCES1

ABSTRACT: The effectiveness of urban Best Management Practices (BMPs) in achieving the No-Net-Increase Policy (NNTP), a policy designed to limit nonpoint nitrogen loading to Long Island Sound (US), is analyzed. A unit loading model is used to simulate annual nitrogen exported from the Norwalk River watershed (Connecticut) under current and future conditions. A probabilistic uncertainty analysis is used to incorporate uncertainty in nitrogen export coefficients and BMP nitrogen removal effectiveness. The inclusion of uncertainty in BMP effectiveness and nitrogen export coefficients implies that additional BMPs, or BMPs with a greater effectiveness in nitrogen removal, will be required to achieve the NNIP. Even though including uncertainty leads to an increase in BMP implementation rates or BMP effectiveness, this type of analysis provides the decision maker with a more realistic assessment of the likelihood that implementing BMPs as a management strategy will be successful. Monte Carlo simulation results indicate that applying BMPs to new urban developments alone will not be sufficient to achieve the NNIP since BMPs are not 100 percent effective in removing the increase in nitrogen caused by urbanization. BMPs must also be applied to selected existing urban areas. BMPs with a nitrogen removal effectiveness of 40–60 percent, probably the highest level of removal that can be expected over an entire watershed, must be applied to at least 75 percent of the existing urban area to achieve the NNIP This high rate of application is not likely to be achieved in urbanized watersheds in the LIS watershed; therefore, additional point source control will be necessary to achieve the NNIP     

UNCERTAINTY IN ESTIMATING BANKFULL CONDITIONS1

ABSTRACT: Bankfull depth and discharge are basic input parameters to stream planform, stream restoration, and highway crossing designs, as well as to the development of hydraulic geometry relationships and the classification of streams. Unfortunately, there are a wide variety of definitions for bankfull that provide a range of values, and the actual selection of bankfull is subjective. In this paper, the relative uncertainty in determining the bankfull depth and discharge is quantified, first by examining the variability in the estimates of bankfull and second by using fuzzy numbers to describe bankfull depth. Fuzzy numbers are used to incorporate uncertainty due to vagueness in the definition of bankfull and subjectivity in the selection of bankfull. Examples are provided that demonstrate the use of a fuzzy bankfull depth in sediment trans. port and in stream classification. Using fuzzy numbers to describe bankfull depth rather than a deterministic value allows the engineer to base designs and decisions on a range of possible values and associated degrees of belief that the bankfull depths take on each value in that range.     

Risk-based optimal operation of hybrid power system using multiobjective optimization

ABSTRACT

This paper solves an optimal generation scheduling problem of hybrid power system considering the risk factor due to uncertain/intermittent nature of renewable energy resources (RERs) and electric vehicles (EVs). The hybrid power system considered in this work includes thermal generating units, RERs such as wind and solar photovoltaic (PV) units, battery energy storage systems (BESSs) and electric vehicles (EVs). Here, the two objective functions are formulated, i.e., minimization of operating cost and system risk, to develop an optimum scheduling strategy of hybrid power system. The objective of proposed approach is to minimize operating cost and system risk levels simultaneously. The operating cost minimization objective consists of costs due to thermal generators, wind farms, solar PV units, EVs, BESSs, and adjustment cost due to uncertainties in RERs and EVs. In this work, Conditional Value at Risk (CVaR) is considered as the risk index, and it is used to quantify the risk due to intermittent nature of RERs and EVs. The main contribution of this paper lies in its ability to determine the optimal generation schedules by optimizing operating cost and risk. These two objectives are solved by using a multiobjective-based nondominated sorting genetic algorithm-II (NSGA-II) algorithm, and it is used to develop a Pareto optimal front. A best-compromised solution is obtained by using fuzzy min-max approach. The proposed approach has been implemented on modified IEEE 30 bus and practical Indian 75 bus test systems. The obtained results show the best-compromised solution between operating cost and system risk level, and the suitability of CVaR for the management of risk associated with the uncertainties due to RERs and EVs.     

Genetically Modified (GM) Crops: Precautionary Science and Conflicts of Interests

Risk governance of GM plants and GMfood products is presently subject to heatedscientific and public controversies. Scientistsand representatives of the biotechnologyindustry have dominated debates concerningsafety issues. The public is suspicious withregard to the motives of scientists, companies,and political institutions involved. Thedilemmas posed are nested, embracing valuequestions, scientific uncertainty, andcontextual issues. The obvious lack of data andinsufficient information concerning ecologicaleffects call for application of thePrecautionary Principle (PP). There are,however, divergent opinions among scientistsabout the relevance of putative hazards,definition of potential ``adverse effects,' andwhether actions should be taken to preventharm. The reliance on the concept ofsubstantial equivalence in safety evaluation ofGM food is equally controversial. Consequently,value assumptions embedded in a scientificframework may be a barrier for employment ofthe PP. One of our major conclusions is thatprecautionary GMP usage requires riskassessment criteria yet undeveloped, as well asbroader and more long-term conceptions of risk,uncertainty, and ignorance. Conflicts ofinterest and public participation are otherissues that need to be taken intoconsideration. GMP governance regimes that arejustifiable from a precautionary and ethicalpoint of view must transcend traditionalscientific boundaries to include alternativescientific perspectives as well as publicinvolvement.     

METHODOLOGIES FOR CALIBRATION AND PREDICTIVE ANALYSIS OF A WATERSHED MODEL1

ABSTRACT: The use of a fitted parameter watershed model to address water quantity and quality management issues requires that it be calibrated under a wide range of hydrologic conditions. However, rarely does model calibration result in a unique parameter set. Parameter nonuniqueness can lead to predictive nonuniqueness. The extent of model predictive uncertainty should be investigated if management decisions are to be based on model projections. Using models built for four neighboring watersheds in the Neuse River Basin of North Carolina, the application of the automated parameter optimization software PEST in conjunction with the Hydrologic Simulation Program Fortran (HSPF) is demonstrated. Parameter nonuniqueness is illustrated, and a method is presented for calculating many different sets of parameters, all of which acceptably calibrate a watershed model. A regularization methodology is discussed in which models for similar watersheds can be calibrated simultaneously. Using this method, parameter differences between watershed models can be minimized while maintaining fit between model outputs and field observations. In recognition of the fact that parameter nonuniqueness and predictive uncertainty are inherent to the modeling process, PEST's nonlinear predictive analysis functionality is then used to explore the extent of model predictive uncertainty.     

Extension of EU Emissions Trading Scheme to Other Sectors and Gases: Consequences for Uncertainty of Total Tradable Amount

Emissions trading in the European Union (EU), covering the least uncertain emission sources of greenhouse gas emission inventories (CO₂ from combustion and selected industrial processes in large installations), began in 2005. During the first commitment period of the Kyoto Protocol (2008–2012), the emissions trading between Parties to the Protocol will cover all greenhouse gases (CO₂, CH₄, N₂O, HFCs, PFCs, and SF₆) and sectors (energy, industry, agriculture, waste, and selected land-use activities) included in the Protocol. In this paper, we estimate the uncertainties in different emissions trading schemes based on uncertainties in corresponding inventories. According to the results, uncertainty in emissions from the EU15 and the EU25 included in the first phase of the EU emissions trading scheme (2005–2007) is ±3% (at 95% confidence interval relative to the mean value). If the trading were extended to CH₄ and N₂O, in addition to CO₂, but no new emissions sectors were included, the tradable amount of emissions would increase by only 2% and the uncertainty in the emissions would range from −4 to +8%. Finally, uncertainty in emissions included in emissions trading under the Kyoto Protocol was estimated to vary from −6 to +21%. Inclusion of removals from forest-related activities under the Kyoto Protocol did not notably affect uncertainty, as the volume of these removals is estimated to be small.     

The Impact of Uncertainty on Banking Behavior: Evidence from the US Sulfur Dioxide Emissions Allowance Trading Program

In this paper, we study empirically whether uncertainty has an influence on trade in the US sulfur dioxide allowances market. In particular, we investigate the role of uncertainty on banking behavior. To do this, we introduce a tractable, structural model of trading permits under uncertainty. The model establishes a relation between banking behavior and risk preferences, especially prudence in the Kimball (1990) sense. We then test this model using data on allowances, for utilities submitted to the US Environmental Protection Agency’s Acid Rain Program, carried over from one year to the next. Evidence is found of imprudence, namely, utilities bank permits in order to favor higher profits. Another finding is that larger utilities do not adopt behavior significantly different from that of smaller ones. This paper was presented at the “International Workshop on Uncertainty in Greenhouse Gas Inventories: Verification, Compliance & Trading” in Warsaw, Poland, September 2004, under the title “Portfolio Management of Emissions Permits and Prudence Behavior.”     

Compliance and Emissions Trading under the Kyoto Protocol: Rules for Uncertain Inventories

A solution is proposed for proving compliance with emission targets and for emissions trading in the event of uncertainties in reported emission inventories. The solution is based on the undershooting concept, from which the mathematical conditions for both proving compliance with a risk α and calculating effective emissions for trading are derived. Based on the reported emission units, the number of permits granted is reduced in proportion to the uncertainty in the inventory. A country whose inventory has higher uncertainty is thereby allotted fewer permits than a country with the same inventory but smaller uncertainty.