Uncertainties. In this subsection the statistical and systematic uncertainties are discussed using the |Hφ | example flight at a middle frequency of f = 55 MHz and a zenith angle bin of (Θ = 42.5±2.5)◦ as mentioned above. This zenith angle is chosen as most events at AERA are reconstructed coming from this direction. While some systematic uncertainties are stable between flights, e.g., measurement of the power injected to the transmitting antenna or the transmitting antenna response pattern, others are flight dependent, e.g., the octocopter position and the measurement of the receiving power at the AUT. The VEL relative uncertainties are listed in table 2. These individual uncertainties are described in detail in the following subsections. The constant systematic uncertainties add quadratically to 6.3% and the flight dependent systematic uncertainty is 6.9%.
Uncertainties. Assess the uncertainty and risks of failing to achieve and maintain the good status objective under various climate change scenarios.
Uncertainties. As for any approach attempting a systematic evaluation of flood impacts and responses at large scale, there are a number of uncertainties emerging from the assumptions made and data used. These assumptions need to be kept in mind when interpreting the final results. The source, effect and brief explanation of these uncertainties are shown in Tab. 8. For a more general discussion on uncertainties, we refer to Sec. 4. We would like to highlight two major sources of uncertainty, namely (i) the maximum asset Figure 14: (a) Land cover, (b) inundation depth and (c) damages for the urban region of Bilbao. The flood depth and damage maps refer to the hypothetical occurrence of a 5 m flood, a value that is close to the 100-year event (Puertos del Estado 2005) in that region. value used to derive economic damages, and (ii) the effect of existing protective measures again flooding. Asset value has been taken from the work of Xxxxxxxx (2007) and refer only to an average (European) economic value for each land-type investigated. Although the average value is then adjusted for countries on the grounds of their economic power, adjustments for spatial scales lower than national level are disregarded. This is relevant in the sense that we are working a the city scale, where disparities in economic performance to country averages are usually observed. Our approach neglects this, and sets a constant maximum value of assets (at the land-use level) for different urban clusters in the same country. Errors in the asset xxxxx can therefore lead to a wrong scaling of damage functions for each cluster. The second source of uncertainty can be traced to the disregard of existing protective measures again flooding in our analysis. In the lack of a realistic global database of coastal protection, some studies made use of limited evidence on existing measures complemented with expert judgement (Xxxxxxxxxx et al. 2013). For the full set of urban clusters investigated such was not feasible. It was therefore assumed that no protective infrastructure exists. This leads to the unavoidable cascade of uncertainty, starting with an over estimation of the flood extent and depth, and propagating to the estimation of economic damages and estimation of protection needs. Despite these uncertainties, this work does constitute, to our knowledge, the first systematic derivation of monetary damage functions and protection needs with regard to coastal flooding for a large number of European cities. Table 8: Uncertai...
Uncertainties. The next three years will present significant economic, political and financial uncertainty in the external environment facing the college and our partners. While these are outwith our control, it is critical that we continue to make a positive impact on the region. The wider political situation in Scotland, the UK and Europe over the next three years is already creating uncertainty. Although the impact, for example, of BREXIT and new arrangements for welfare reform and national bargaining are still largely unknown, such changes will present challenges for the college, our students, communities and employers. Therefore, to deliver this ambitious outcome agreement requires a significant increase in core funding. Financial challenges such as the introduction of a simplified funding model and changes to funding for extended learning support have the potential to put at risk support for students who need it most. For example, in 2015-16 a fifth of the college’s credit activity supported students with a declared disability and 20.5% supported students who lived in SIMD10 areas. Ayrshire College # 193132 2018-01-17 11:55:44 (UTC+00 Regionalisation is likely to remain high on the political agenda, in particular in relation to economic development and education. The outcomes of the consultation on governance arrangements in schools, as well as the review of enterprise and skills agencies, could have far-reaching consequences for schools, local authorities and national agencies. Changes arising from these reviews will require the college to be agile in how we work with national and local partners to ensure that people, communities and the economy in Ayrshire grow and develop through skills. Strategic Plan 2017-20 We will continue to be proactive to changes in the external environment and flexible in our approach to the delivery of learning and services to support our students. By working in collaboration with partners we will maximise the potential outcomes for our students. Our strategic goals for 2017-20 reflect this approach, and support Scottish Funding Council outcomes. These goals are:
Uncertainties. A major issue for the validity of HIA relates to the expression of uncertainties.24 Because the model requires combining two set of CRFS provided with confidence intervals, one can provide the range of uncertainty around the estimate of attributable cases, using Monte Carlo simulations to propagate CRFs uncertainty distributions into the attributable risks.25 However, because there are several other sources of uncertainty that vary across the main assumptions, one needs additional approaches to integrate uncertainties more broadly. Conducting different sets of sensitivity analysis can provide useful information regarding the possible range of the impact caused by the uncertainty in the CRF point estimates. Moreover, stakeholders and expert opinions should be used to further explicit the degree of confidence in assumptions as well as methodological features. Improving Knowledge and Communication for Decision Making on Air Pollution and Health in Europe References
Uncertainties. Following are some elements that can be taken into consideration when discussing uncertainties in HIA. The first issue is to distinguish between the uncertainties that can be reduced using careful design, and the uncertainties that are inherent to the methodology and cannot be avoided. It is essential to communicate both types of uncertainties and do whatever is possible to reduce manageable uncertainties. Among the uncertainties that cannot be reduced is the key assumption that causality exists between exposure to air pollution and health outcomes. The number of cases attributable to air pollution can be estimated only if there are strong arguments for this causality as defined by Hill (Hill, 1965). In the case of air pollution, the most important arguments for this causality are: consistency of epidemiological findings reproduced over different geographic areas, periods and study designs; coherence of the observed effects; biological plausibility strengthened by clinical and toxicological studies; more recently the demonstration through intervention studies that changing the exposure causes a change in the outcome and the analogy found with cigarette smoking (Xxxx, III et al.
Uncertainties. The parties understand and acknowledge that there are uncertainties surrounding the business of the Company and the Company Products, including, but not limited to: (A) the ability to satisfactorily complete the design of the Company Products, (B) the clinical safety of the Company Products, (C) market acceptance of the Company Products, (D) competitive product offerings that may be introduced by third parties, and (E) Intellectual Property owned by third parties. As a result of such uncertainties, the parties agree and acknowledge that Buyer must have flexibility to react to future developments. Buyer is entitled to exercise its discretion with respect thereto subject, however, to the following provisions.
Uncertainties. The Board was notified by the management of certain subsidiaries in the PRC that they were at one stage required to temporarily suspend their business operations as a result of the precautionary and control measures for containing COVID-19 outbreak. As such, the Company was unable to obtain sufficient documents and information in relation to, nor conduct site visit at, the subsidiaries. Therefore, the valuation of fair value measurement on (i) identifiable assets acquired, liabilities assumed and non-controlling interests for a newly acquired subsidiary in the PRC during the year; (ii) investment properties; and (iii) expected credit loss assessment on trade and other receivables, cannot be carried out by the independent valuer before the date of this announcement. In addition, COVID-19 outbreak further slowdown of settlements of trade receivables. If the present situation in respect of the COVID-19 outbreak continues and the restrictions and control measures are prolonged, the Group’s operations and cash flows may be negatively affected. The Group’s financial conditions indicate the existence of material uncertainties which may cast significant doubt about the Group’s ability to continue as a going concern. 2 Summary of significant accounting policies (continued) 2.1 Basis of preparation (continued)
Uncertainties. There are uncertainties in the ability of the lead models to predict blood lead levels for the receptors at the LPRSA. In addition to the uncertainties noted in Appendix G of the HHRA, the HHRA exposure scenarios, while considered reasonable maximum exposures (RME), are at the lower limits of the lead model designs. Exposures were assumed to occur one to three times per week over a 13-week period (i.e., 91-day period). The Technical Review Workgroup for Metals and Asbestos (TRW) Lead Committee “recommends that users not apply the IEUBK model or the ALM to assess exposure frequency less than 1 day per week and of duration shorter than 90 consecutive days... The reliability of these models for predicting PbB concentrations for exposure durations less than 90 consecutive days has not been assessed” (USEPA 2016a). The models may overpredict blood lead concentrations for exposures that are less frequent and of shorter duration than the HHRA RME scenarios. In addition, there is uncertainty in the use of a default soil lead concentration of 200 mg/kg to estimate the time-weighted average. Average urban soil lead concentrations near the LPRSA have not been measured and may be higher or lower than 200 mg/kg. Off-site soil lead concentrations would be associated with sources other than the LPRSA. As noted in USEPA 2016b, Superfund programs do not normally set cleanup levels below natural or anthropogenic background levels. The single measurement of lead in accessible sediment above Dundee Dam, upstream of the LPRSA, was 189 mg/kg. This upstream concentration is just a bit lower than the default soil lead concentration of 200 mg/kg. However, the data is extremely limited and cannot be counted on to characterize background sediment or soil concentrations with any certainty. Conclusions Although the December 2016 memo specifically addresses soil, in order to be protective, CDM Xxxxx reran the IEUBK and ALM modeling for select receptors from the LPRSA HHRA who may be exposed to other media (e.g., sediment, surface water). Using the blood lead level of concern of 5 µg/dL identified in the memo shows that the percentage of children below that target is generally in Refinements to Lead Models for the LPRSA Human Health Risk Assessment May 30, 2017 agreement with the conclusions in Appendix G of the HHRA. Therefore, lead is not considered to be a COC for the LPRSA. References AECOM. 2017. Baseline Human Health Risk Assessment for the Lower Passaic River Study Area, Revised ...
Uncertainties. Cost analyses are marked by considerable uncertainty in the assumptions on the type of cost items to be included and the costs assigned to individual items. As an example we refer to the detailed cost analysis of a well to be used as an injector in the ROAD project, which amounted to €7.6 million, as mentioned in the close-out report on storage. The ROAD well cost, more than twice that assumed in this analysis, is for a specific well and is not necessarily representative of the costs for recompletion of offshore gas production xxxxx for CO2 injection.
