THE EFFECTS OF PARAMETRIC UNCERTAINTIES IN SIMULATIONS OF A REACTIVE PLUME USING A LAGRANGIAN STOCHASTIC MODEL

A combined Lagrangian stochastic model with micro mixing and chemical sub-models is used to investigate a reactive plume of nitrogen oxides (NOx) released into a turbulent grid flow doped with ozone (O3). Sensitivities to the model input parameters are explored for high NOx model scenarios. A wind tunnel experiment is used to provide the simulation conditions for the first case study where photolysis reactions are not included and the main uncertainties occur in the parameters defining the turbulence scales, the source size and the reaction rate of NO (nitric oxide) with O3. Using nominal values of the parameters from previous studies, the model gives a good representation of the radial profile of the conserved scalar [NOx] compared to the experiments, although the width of the simulated profile is slightly smaller, especially at longer distances from the source. For this scenario, the Lagrangian velocity structure function coefficient has the largest impact on simulated [NOx] profiles. At the next stage photolysis reactions are included in a chemical scheme consisting of eight reactions between species NO, O, O3 and NO2. The high dimensional model representation (HMDR) method is used to investigate the effects of uncertainties in the various model inputs resulting from the parameterisation of important physical and chemical processes in the reactive plume model, on the simulation of primary and secondary chemical species concentrations. Both independent and interactive effects of the parameters are studied. In total 22 parameters are assumed to be uncertain, among them the turbulence parameters, temperature dependant rate parameters, photolysis rates, temperature, fraction of NO in total NOx at the source and background concentration of O3. Only uncertainties in the mixing time scale coefficient and the structure function coefficient are responsible for the variance in the [NOx] radial profile. On the other hand, the variance in the [O3] profile is caused by parameters describing both physical and chemical processes

THE EFFECTS OF PARAMETRIC UNCERTAINTIES IN SIMULATIONS OF A REACTIVE PLUME USING A LAGRANGIAN STOCHASTIC MODEL

A combined Lagrangian stochastic model with micro mixing and chemical sub-models is used to investigate a reactive plume of nitrogen oxides (NOx) released into a turbulent grid flow doped with ozone (O3). Sensitivities to the model input parameters are explored for high NOx model scenarios. A wind tunnel experiment is used to provide the simulation conditions for the first case study where photolysis reactions are not included and the main uncertainties occur in the parameters defining the turbulence scales, the source size and the reaction rate of NO (nitric oxide) with O3. Using nominal values of the parameters from previous studies, the model gives a good representation of the radial profile of the conserved scalar [NOx] compared to the experiments, although the width of the simulated profile is slightly smaller, especially at longer distances from the source. For this scenario, the Lagrangian velocity structure function coefficient has the largest impact on simulated [NOx] profiles. At the next stage photolysis reactions are included in a chemical scheme consisting of eight reactions between species NO, O, O3 and NO2. The high dimensional model representation (HMDR) method is used to investigate the effects of uncertainties in the various model inputs resulting from the parameterisation of important physical and chemical processes in the reactive plume model, on the simulation of primary and secondary chemical species concentrations. Both independent and interactive effects of the parameters are studied. In total 22 parameters are assumed to be uncertain, among them the turbulence parameters, temperature dependant rate parameters, photolysis rates, temperature, fraction of NO in total NOx at the source and background concentration of O3. Only uncertainties in the mixing time scale coefficient and the structure function coefficient are responsible for the variance in the [NOx] radial profile. On the other hand, the variance in the [O3] profile is caused by parameters describing both physical and chemical processes

In-street wind direction variability in the vicinity of a busy intersection in central London

We present results from fast-response wind measurements within and above a busy intersection between two street canyons (Marylebone Road and Gloucester Place) in Westminster, London taken as part of the DAPPLE (Dispersion of Air Pollution and Penetration into the Local Environment; www.dapple.org.uk) 2007 field campaign. The data reported here were collected using ultrasonic anemometers on the roof-top of a building adjacent to the intersection and at two heights on a pair of lamp-posts on opposite sides of the intersection. Site characteristics, data analysis and the variation of intersection flow with the above-roof wind direction (θref) are discussed. Evidence of both flow channelling and recirculation was identified within the canyon, only a few metres from the intersection for along-street and across-street roof-top winds respectively. Results also indicate that for oblique rooftop flows, the intersection flow is a complex combination of bifurcated channelled flows, recirculation and corner vortices. Asymmetries in local building geometry around the intersection and small changes in the background wind direction (changes in 15-min mean θref of 5–10 degrees) were also observed to have profound influences on the behaviour of intersection flow patterns. Consequently, short time-scale variability in the background flow direction can lead to highly scattered in-street mean flow angles masking the true multi-modal features of the flow and thus further complicating modelling challenges

Low-cost wind resource assessment for small-scale turbine installations using site pre-screening and short-term wind measurements

A two-stage approach to low-cost wind resource assessment for small-scale wind installations has been investigated in terms of its ability to screen for non-viable sites and to provide accurate wind power predictions at promising locations. The approach was implemented as a case study at ten UK locations where domestic-scale turbines were previously installed. In stage one, sites were pre-screened using a boundary-layer scaling model to predict the mean wind power density, including estimated uncertainties, and these predictions were compared to a minimum viability criterion. Using this procedure, five of the seven non-viable sites were correctly identified without direct onsite wind measurements and none of the viable sites were excluded. In stage two, more detailed analysis was carried out using 3 months onsite wind measurements combined with measure-correlate-predict (MCP) approaches. Using this process, the remaining two non-viable sites were identified and the available wind power density at the three viable sites was accurately predicted. The effect of seasonal variability on the MCPpredicted wind resource was considered and the implications for financial projections were highlighted. The study provides a framework for low-cost wind resource assessment in cases where long-term onsite measurements may be too costly or impractical

Methodology for the assessment of PV capacity over a city region using low-resolution LiDAR data and application to the City of Leeds (UK)

An assessment of roof-mounted PV capacity over a local region can be accurately calculated by established roof segmentation algorithms using high-resolution light detection and ranging (LiDAR) datasets. However, over larger city regions often only low-resolution LiDAR data is available where such algorithms prove unreliable for small rooftops. A methodology optimised for low-resolution LiDAR datasets is presented, where small and large buildings are considered separately. The roof segmentation algorithm for small buildings, which are typically residential properties, assigns a roof profile to each building from a catalogue of common profiles after identifying LiDAR points within the building footprint. Large buildings, such as warehouses, offer a more diverse range of roof profiles but geometric features are generally large, so a direct approach is taken to segmentation where each LiDAR point within the building footprint contributes a separate roof segment. The methodology is demonstrated by application to the city region of Leeds, UK. Validation by comparison to aerial photography indicates that the assignment of an appropriate roof profile to a small building is correct in 81% of cases

Urban case studies : general discussion

Urban case studies: general discussio

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Methodologies for city-scale assessment of renewable energy generation potential to inform strategic energy infrastructure investment

In support of national and international policies to address climate change, local government actors across Europe and Asia are committed to reducing greenhouse gas emissions. Many recognise the contribution that decentralised renewable electricity production can bring towards reducing emissions whilst also generating revenue. However, these actors are often subject to significant financial pressures, meaning a reliable and compelling business case is needed to justify upfront investment. This article develops a method for rapid comparison of initial project viability for multiple city sites and installation options using data from wind and solar resource prediction techniques. In doing so, detailed resource assessments grounded in academic research are made accessible and useful for city practitioners. Long term average wind speeds are predicted using a logarithmic vertical wind profile. This employs detailed three-dimensional building data to estimate aerodynamic parameters for the complex urban surface. Solar resource is modelled using a Geographical Information System-based methodology. This establishes the location and geometry of roof structures to estimate insolation, whilst accounting for shading effects from other buildings and terrain features. Project viability for potential installations is assessed in terms of the net present value over the lifespan of the technology and associated Feed-in Tariff incentive. Discounted return on investment is also calculated for all sites. The methodology is demonstrated for a case study of 6,794 sites owned by Leeds City Council, UK. Results suggest significant potential for small-scale wind and solar power generation across council assets. A number of sites present a persuasive business case for investment, and in all cases, using the generated electricity on site improves financial viability. This indicates that initial installations should be sited at assets with high electricity demands. Overall, the work establishes a 2 methodology that enables large city-level asset holders to make strategic investment decisions across their entire portfolio, which are based on financial assessment of wind and solar generation potential accurate to the individual asset scale. Such tools could facilitate strategic planning within cities and help to ensure that investment in renewable energy is focused at the most viable sites. In addition, the methodology can assist with asset management at the city scale by identifying sites with a higher market value as a result of their potential for renewable energy generation than otherwise might be estimated

Sample-tip interaction of piezoresponse force microscopy in ferroelectric nanostructures

We report on qualitative and quantitative implications of the sample-tip interaction in piezoresponse force microscopy. Our finite-element analysis of adsorbate effects, sample heterogeneities, and tip asymmetries is in agreement with experimental observation of ferroelectric nanostructures. Qualitative discrepancies arise from locally asymmetric tip-sample interaction. Any quantitative determination of field-related material parameters as required for the verification of semiempirical models of the ferroelectric limit typically relies on an overestimated field across the sample. Our findings indicate that adsorbates reduce the actual field across the nanograin by roughly one order of magnitude