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Fluxes of nitrogen oxides (NOx=NO+NO2) and carbon dioxide (CO2) were measured using eddy covariance at the British Telecommunications (BT) Tower in central London during the coronavirus pandemic. Comparing fluxes to those measured in 2017 prior to the pandemic restrictions and the introduction of the Ultra-Low Emissions Zone (ULEZ) highlighted a 73 % reduction in NOx emissions between the two periods but only a 20 % reduction in CO2 emissions and a 32 % reduction in traffic load. Use of a footprint model and the London Atmospheric Emissions Inventory (LAEI) identified transport and heat and power generation to be the two dominant sources of NOx and CO2 but with significantly different relative contributions for each species. Application of external constraints on NOx and CO2 emissions allowed the reductions in the different sources to be untangled, identifying that transport NOx emissions had reduced by >73 % since 2017. This was attributed in part to the success of air quality policy in central London but crucially due to the substantial reduction in congestion that resulted from pandemic-reduced mobility. Spatial mapping of the fluxes suggests that central London was dominated by point source heat and power generation emissions during the period of reduced mobility. This will have important implications on future air quality policy for NO2 which, until now, has been primarily focused on the emissions from diesel exhausts.

Good representation of turbulence in urban canopy models is necessary for accurate prediction of momentum and scalar distribution in and above urban canopies. To develop and improve turbulence closure schemes for one-dimensional multi-layer urban canopy models, turbulence characteristics are investigated here by analyzing existing large-eddy simulation and direct numerical simulation data. A range of geometries and flow regimes are analyzed that span packing densities of 0.0625 to 0.44, different building array configurations (cubes and cuboids, aligned and staggered arrays, and variable building height), and different incident wind directions ($$0^\circ $$ 0 ∘ and $$45^\circ $$ 45 ∘ with regards to the building face). Momentum mixing-length profiles share similar characteristics across the range of geometries, making a first-order momentum mixing-length turbulence closure a promising approach. In vegetation canopies turbulence is dominated by mixing-layer eddies of a scale determined by the canopy-top shear length scale. No relationship was found between the depth-averaged momentum mixing length within the canopy and the canopy-top shear length scale in the present study. By careful specification of the intrinsic averaging operator in the canopy, an often-overlooked term that accounts for changes in plan area density with height is included in a first-order momentum mixing-length turbulence closure model. For an array of variable-height buildings, its omission leads to velocity overestimation of up to $$17\%$$ 17 % . Additionally, we observe that the von Kármán coefficient varies between 0.20 and 0.51 across simulations, which is the first time such a range of values has been documented. When driving flow is oblique to the building faces, the ratio of dispersive to turbulent momentum flux is larger than unity in the lower half of the canopy, and wake production becomes significant compared to shear production of turbulent momentum flux. It is probable that dispersive momentum fluxes are more significant than previously thought in real urban settings, where the wind direction is almost always oblique.

Convective-scale ensemble prediction systems (EPS) are critical tools to accurately forecast damaging surface winds in the short range, capturing the local details of their variability and providing guidance on the associated forecast uncertainty. Due to computational cost, operational convective-scale EPS are atmosphere-only models, which represent ocean and wave effects through sea-state independent parametrizations, and therefore do not account for the impact of an evolving ocean and wave state during the forecast. Benefits of integrating atmosphere, ocean, and wave feedbacks into a single coupled multimodel system have been shown by global-scale deterministic systems and EPS, and convective-scale deterministic systems. These benefits lead to the question of what are the corresponding benefits of coupling in convective-scale EPS. To address this question, we present the first convective-scale regional ensemble coupled system focused on the UK domain and surrounding seas (termed RECS-UK). We demonstrate the robustness of the impact of atmosphere-ocean-wave coupling and stochastic perturbations to model physics parametrizations on forecasts of extratropical cyclone Ciara and quantify the importance of these coupling impacts relative to initial condition error. Coupling to the ocean leads to localised reductions in the 10-m wind speeds due to cooling of sea surface temperatures, which increase the stability in the surface layer. However, these localised impacts on coupling to ocean are not apparent when comparing the ensemble strike probabilities of exceeding a storm wind threshold (set to 20 m s-1) for the atmosphere-ocean-coupled and control (atmosphere-only) ensembles. In contrast, coupling additionally to waves leads to substantial reductions in wind strike probability and consistently reduces, by up to 1 m s-1, the ensemble forecast median and mean of Ciara’s wind speeds at all simulation hours during which Ciara is in the model domain. Each atmosphere-ocean-wave coupled ensemble member simulates the dynamical response of wind speeds to the forced young ocean waves, with maximum reductions in high wind speed regions. The largest 10-m wind speed spread from stochastic and initial condition perturbations is found away from the strongest wind speed regions of Ciara, but the impact of coupling to waves is more enhanced in these strongest wind speed regions, and is also comparable in size there with the largest sensitivity to stochastic and initial condition perturbations. The implications of this work are that the impacts on 10-m wind speed of coupling convective-scale atmospheric models to ocean and wave models can be robust across an ensemble and be of comparable size to those of initial condition and stochastic physics perturbations. However, convection-permitting atmosphere-ocean-wave coupled EPS should be assessed in different meteorological conditions and further tested on longer timescales prior to operational implementation.

Rapid expansion of wind and solar capacity in Great Britain presents challenges for managing electricity systems. One concern is the reduction in system inertia during periods where renewables provide a high proportion of demand which has led to some networks imposing system non-synchronous penetration limits. However, given the lack of operational data, the relationship between renewable generation and demand for the full range of meteorological conditions experienced in Great Britain is poorly understood. This study uses reanalysis datasets to determine the proportion of demand from renewable generation on an hourly resolution for a 36-year period. The days with highest penetration of renewables tend to be sunny, windy weekend days between May and September, when there is a significant contribution of both wind and solar generation and demand is suppressed due to human behaviour. Based on the current distribution of wind and solar capacity, there is very little curtailment for all system non-synchronous penetration limits considered. However, as installed capacity of renewables grows the volume of generation curtailed also increases with a disproportionate volume occurring at weekends. The total volume of curtailment is highly dependent on ratio of wind and solar capacity, with the current blend close to the optimum level.

Façade pressure coefficients are widely used to determine wind-driven ventilation potential for buildings at the design stage. Over nine months we measured façade pressure coefficients under full-scale conditions using the 6 m Silsoe cube in isolation and in a staggered array. Results are compared against a 1:300 wind-tunnel model, a time-dependent computational fluid dynamics (CFD) model at full-scale and to published pressure coefficients in ventilation design guidance for a range of wind angles.\ud \ud Across all wind angles, wind-tunnel, CFD and published models tended to underestimate full-scale experimental pressure coefficients in magnitude but replicated trends well for a single face on the isolated cube. Agreement was weaker for the array; pressure coefficients are asymmetric with wind direction and results sensitive to model set up and measurement strategies. Differences in pressure coefficient across the building compared well in both isolated and array cases, suggesting this is a more robust parameter for models than individual facet data.\ud \ud It is recommended that building symmetry and surrounding areas should be considered when relying on ventilation guidelines. Scale and computational models are effective to support design for more complex cases; however, it is important to ensure measurement locations are representative and that uncertainties are quantified.

Urban climatology: A cloudy picture for hot cities Compared to nearby rural areas, mega-cities can produce an atmosphere that is, paradoxically, drier yet persistently more cloudy. Cities are known to create an “urban heat island”, but a multi-institution team led by Natalie Theeuwes from the University of Reading now shows that the urban fingerprint extends to an increase in cumulus cloud cover. In an analysis of the Paris and London mega-cities, the team finds that afternoon cloud cover during spring and summer is, on average, several percent higher over the urban core than over surrounding rural areas. The results are initially counter-intuitive, because reduced vegetation in cities also tends to dry the atmosphere, which should reduce cloud cover. By probing detailed ground-based observations in and near London, the researchers explain that buildings release their heat throughout the afternoon, enhancing turbulent mixing and thus the delivery of moisture to clouds. The findings illuminate the widening impact of cities on their environment.

The presence of tall buildings in cities affects momentum and scalar exchange within and above the urban canopy. As wake effects can be important over large distances, they are crucial for urban-flow modelling on and across different spatial scales. We explore the aerodynamic effects of tall buildings on the microscale to local scales with a focus on the interaction between the wake structure, canopy and roughness sublayer flow of the surroundings in a realistic urban setting in central London. Flow experiments in a boundary-layer wind tunnel use a 1:200 scale model with two tall buildings (81 m and 134.3 m) for two wind directions. Large changes in mean flow, turbulence statistics and instantaneous flow structure of the wake are evident when tall buildings are part of the complex urban canopy rather than isolated. In the near-wake, the presence of lower buildings displaces the core of the recirculation zone upwards, thereby reducing the vertical depth over which flow reversal occurs. This amplifies vertical shear at the rooftop and enhances turbulent momentum exchange. In the near part of the main wake, lateral velocity fluctuations and hence turbulence kinetic energy are reduced compared to the isolated building case as eddies generated in the urban canopy and roughness sublayer distribute energy down to smaller scales that dissipate more rapidly. Evaluation of a wake model for flow past isolated buildings suggests model refinements are needed to account for such flow-structure changes in tall-building canopies.

With a number of operational centres looking forward to the possibilities of “city scale” NWP and climate modelling it is important to understand the behaviour of order 100m models over cities. A key issue is how to handle the representation of partially resolved turbulence in these models. In this paper we compare the representation of a clear convective boundary layer case in London in 100m and 50m grid-length versions of the Unified Model (MetUM) with observations. Comparison of Doppler lidar observations of the vertical velocity shows that convective overturning in the boundary layer is broadly well represented in terms of its depth and magnitude. The role of model resolution was investigated by comparing a 50m grid-length model with the 100m one. It is found that, although going to 50m grid-length does not greatly change many of the bulk properties (mixing height, heat flux profiles, etc.) the spatial structure of the overturning is significantly different. This is confirmed with spectral analysis which shows that the 50m model resolves significantly more of the energetic eddies, and a length scale analysis that shows the 50m and 100m models produce convective structures 2-3 times larger than observed. We conclude that, for the MetUM, model grid-lengths of order 100m may well be sufficient for predicting many bulk and statistical properties of convective boundary layers however the details of the spatial structures around convective overturning in these situations are likely to be still under-resolved. Spin up artefacts emanating from the inflow boundary of the model are investigated by comparing with a smaller 100m grid-length domain which is more dominated by such effects. These manifest themselves as along wind boundary layer rolls which produce a less realistic comparison with the lidar observations. A stability analysis is presented in order to better understand the formation of these rolls.

Recently there has been a significant change in the distribution of wind farms in Great Britain with the construction of clusters of large offshore wind farms. These clusters can produce large ramping events (i.e. changes in power output) on temporal scales which are critical for managing the power system (30 minute, 60 minute and 4 hours). This study analyses generation data from the Thames Estuary cluster in conjunction with meteorological observations to determine the magnitude and frequency of ramping events and the meteorological mechanism.\ud Over a 4 hour time window, the extreme ramping events of the Thames Estuary cluster were caused by the passage of a cyclone and associated weather fronts. On shorter time scales, the largest ramping events over 30 minute and 60 minute time windows are not associated with the passage of fronts. They are caused by three main meteorological mechanisms; (1) very high wind speeds associated with a cyclone causing turbine cut-out (2) gusts associated with thunderstorms and (3) organised band of convection following a front. Despite clustering offshore capacity, the addition of offshore wind farms has increased the mean separation between capacity and therefore reduced the variability in nationally aggregated generation on high frequency time scales.

Accurate modelling of air–sea surface exchanges is crucial for reliable extreme surface wind-speed forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between the atmosphere, ocean and wave model components. Here, we investigate the sensitivity of extreme surface wind speeds to air–sea exchanges at the kilometre scale using coupled and uncoupled configurations of the Met Office’s UK Regional Coupled Environmental Prediction system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 m s$$^{-1}$$ - 1 over the UK. Compared with the atmosphere-only results, coupling to the ocean decreases the domain-average sea-surface temperature by up to 0.5 K. Inclusion of coupling to waves reduce the 98th percentile 10-m wind speed by up to 2 m s$$^{-1}$$ - 1 as young, growing wind waves reduce the wind speed by increasing the sea-surface aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1 m s$$^{-1}$$ - 1 , due to enhanced boundary-layer turbulence which partially offsets air–sea momentum transfer. Using a new drag parametrization based on the Coupled Ocean–Atmosphere Response Experiment 4.0 parametrization, with a cap on the neutral drag coefficient and reduction for wind speeds exceeding 27 m s$$^{-1}$$ - 1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind-speed skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

Accurate modelling of air-sea surface exchanges is crucial for reliable extreme surface wind forecasts. While atmosphere-only weather forecast models represent ocean and wave effects through sea-state independent parametrizations, coupled multi-model systems capture sea-state dynamics by integrating feedbacks between atmosphere, ocean and wave model components.Here, we present the results of studying the sensitivity of extreme surface wind speeds to air-sea exchanges at kilometre scale using coupled and uncoupled configurations of the Met Office's UK Regional Coupled Environmental Prediction (UKC4) system. The case period includes the passage of extra-tropical cyclones Helen, Ali, and Bronagh, which brought maximum gusts of 36 ms-1 over the UK.Compared to the atmosphere-only results, coupling to ocean decreases the domain-average sea surface temperature by up to 0.5 K. Inclusion of coupling to waves decreases the 98th percentile 10-m wind speed by up to 2 ms-1 as young, growing wind waves decrease wind speed by increasing the sea aerodynamic roughness. Impacts on gusts are more modest, with local reductions of up to 1ms -1, due to enhanced boundary-layer turbulence which partially offsets air-sea momentum transfer.Using a new drag parametrization based on the COARE~4.0 scheme, with a cap on the neutral drag coefficient and decrease for wind speeds exceeding 27 ms-1 , the atmosphere-only model achieves equivalent impacts on 10-m wind speeds and gusts as from coupling to waves. Overall, the new drag parametrization achieves the same 20% improvement in forecast 10-m wind skill as coupling to waves, with the advantage of saving the computational cost of the ocean and wave models.

In urban areas with high air pollution emissions, the boundary layer volume within which gases and particles are diluted is critical to air quality impacts. With advances in ground-based remote sensing technologies and data processing algorithms, observations of layers forming the atmospheric boundary layer (ABL) are becoming increasingly available at high temporal resolution. Here, mixing height (MH) estimates determined from turbulence measurements of Doppler lidars and aerosol-derived mixed layer height (MLH) based on automatic lidar and ceilometer (ALC) observations within the centre of London are assessed. While MH uncertainty increases with shorter duration of vertical stare sampling within the Doppler lidar scan pattern, instrument-related noise of the ALC may result in large MLH errors due to the challenging task of layer attribution. However, when long time series are assessed most of the algorithm- and instrument-related uncertainties average out and therefore become less critical to overall climatological analyses. Systematic differences occur in nocturnal MH from two nearby (3–4 km) sites but MLH estimates at both sites generally agree with MH obtained at the denser urban setting. During daytime, most spatial variations in ABL structure induced by synoptic conditions or land cover heterogeneity at this scale do not exceed measurement uncertainty. Agreement between MH and MLH is clearly affected by ABL aerosol content and cloud conditions. Discrepancies increase with cloud complexity. On average, MH rises ahead of MLH during the morning growth period and peaks earlier in the day. There is a faster afternoon decay of MLH so that MLH and MH converge again around sunset and often have similar nocturnal values. Results demonstrate that turbulence-derived MH and aerosol-derived MLH should not be used inter-changeably for purposes of model evaluation, interpretation of surface air quality observations or initialisation of chemical transport models.

Currently, no clear standards exist for determining urban building natural ventilation rates, especially under varying realistic meteorological conditions. In this study, ventilation rates are determined using tracer gas decay and pressure-based measurements for a full-scale (6 m tall) cube. The cube was either isolated (2 months of observations) or sheltered within a staggered array (7 months), for both single-sided and cross ventilation (openings 0.4 m × 1 m). Wind speeds at cube height ranged between 0.04 m s−1 and 13.1 m s−1. Errors for both ventilation methods are carefully assessed. There is no discernible linear relation between normalised ventilation rates from the two methods, except for cross ventilation in the array case. The ratio of tracer gas and pressure derived ventilation rates is assessed with wind direction. For single-sided (leeward opening) cases it approached 1. For cross ventilation the ratio was closer to 1 but with more scatter. One explanation is that agreement is better when internal mixing is less jet-dominated, i.e. for oblique directions in the isolated case and for all directions for unsteady array flows. Sheltering may reduce the flushing rate of the tracer gas from the cube relative to internal mixing rate. This new dataset provides an extensive range of conditions for numerical model evaluation and for understanding uncertainty of ventilation rates. Knowledge of the latter is critical in building design.

The study of the boundary layer can be most difficult when it is in transition and forced by a complex surface, such as an urban area. Here, a novel combination of ground-based remote sensing and in situ instrumentation in central London, UK, is deployed, aiming to capture the full evolution of the urban boundary layer (UBL) from night-time until the fully-developed convective phase. In contrast with the night-time stable boundary layer observed over rural areas, the night-time UBL is weakly convective. Therefore, a new approach for the detection of the morning-transition and rapid-growth phases is introduced, based on the sharp, quasi-linear increase of the mixing height. The urban morning-transition phase varied in duration between 0.5 and 4 h and the growth rate of the mixing layer during the rapid-growth phase had a strong positive relationship with the convective velocity scale, and a weaker, negative relationship with wind speed. Wind shear was found to be higher during the night-time and morning-transition phases than the rapid-growth phase and the shear production of turbulent kinetic energy near the mixing-layer top was around six times larger than surface shear production in summer, and around 1.5 times larger in winter. In summer under low winds, low-level jets dominated the UBL, and shear production was greater than buoyant production during the night-time and the morning-transition phase near the mixing-layer top. Within the rapid-growth phase, buoyant production dominated at the surface, but shear production dominated in the upper half of the UBL. These results imply that regional flows such as low-level jets play an important role alongside surface forcing in determining UBL structure and growth.

Nine methods to determine local-scale aerodynamic roughness length \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(z_{0})$$\end{document}(z0) and zero-plane displacement \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(z_{d})$$\end{document}(zd) are compared at three sites (within 60 m of each other) in London, UK. Methods include three anemometric (single-level high frequency observations), six morphometric (surface geometry) and one reference-based approach (look-up tables). A footprint model is used with the morphometric methods in an iterative procedure. The results are insensitive to the initial \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{d}$$\end{document}zd and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{0}$$\end{document}z0 estimates. Across the three sites, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{d}$$\end{document}zd varies between 5 and 45 m depending upon the method used. Morphometric methods that incorporate roughness-element height variability agree better with anemometric methods, indicating \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{d}$$\end{document}zd is consistently greater than the local mean building height. Depending upon method and wind direction, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{0}$$\end{document}z0 varies between 0.1 and 5 m with morphometric \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{0}$$\end{document}z0 consistently being 2–3 m larger than the anemometric \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{0}$$\end{document}z0. No morphometric method consistently resembles the anemometric methods. Wind-speed profiles observed with Doppler lidar provide additional data with which to assess the methods. Locally determined roughness parameters are used to extrapolate wind-speed profiles to a height roughly 200 m above the canopy. Wind-speed profiles extrapolated based on morphometric methods that account for roughness-element height variability are most similar to observations. The extent of the modelled source area for measurements varies by up to a factor of three, depending upon the morphometric method used to determine \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{d}$$\end{document}zd and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$z_{0}$$\end{document}z0.

Doppler wind LiDAR (Light Detection And Ranging) makes use of the principle of optical Doppler shift between the reference and backscattered radiations to measure radial velocities at distances up to several kilometers above the ground. Such instruments promise some advantages, including its large scan volume, movability and provision of 3-dimensional wind measurements, as well as its relatively higher temporal and spatial resolution comparing with other measurement devices. In recent decades, Doppler LiDARs developed by scientific institutes and commercial companies have been well adopted in several real-life applications. Doppler LiDARs are installed in about a dozen airports to study aircraft-induced vortices and detect wind shears. In the wind energy industry, the Doppler LiDAR technique provides a promising alternative to in-situ techniques in wind energy assessment, turbine wake analysis and turbine control. Doppler LiDARs have also been applied in meteorological studies, such as observing boundary layers and tracking tropical cyclones. These applications demonstrate the capability of Doppler LiDARs for measuring backscatter coefficients and wind profiles. In addition, Doppler LiDAR measurements show considerable potential for validating and improving numerical models. It is expected that future development of the Doppler LiDAR technique and data processing algorithms will provide accurate measurements with high spatial and temporal resolutions under different environmental conditions.

RationaleAn accumulation of CO2 in occupied indoor spaces is correlated to negative impacts on concentration, sleepiness and aspects of cognitive performance. However, factors such as: (a) the relative effect of CO2 itself compared to other pollutants; (b) the minimum necessary exposure time for cognitive performance to be affected; and (c) the physiological drivers of cognitive performance reductions due to increased indoor CO2 concentrations are not yet clear.MethodA within-subjects counterbalanced study design was used to test cognitive performance, subjective and physiological parameters of 31 volunteers during short (< 60 min) exposures to normal CO2 (830 ppm) and high CO2 (2700 ppm, raised by introducing pure CO2 alongside the occupant generated CO2). The study was conducted in a small naturally ventilated office and EEG was used as an objective indicator of sleepiness.ResultsThe addition of pure CO2 to the room resulted in the absence of an expected learning effect in two cognitive performance test battery components which could not be explained by any of the physiological, psychological, or reported comfort, sick building syndrome and health variables measured. However, participants who had slept less the previous night appeared more susceptible to becoming sleepier as a result of the increased CO2.ContributionsThe results suggest (1) the addition of pure CO2 may influence aspects of cognitive performance after only short exposures (2) these changes occur in the absence of clear physiological drivers, (3) lack of sleep may mediate people's response to higher CO2 concentration.

Drowsiness which can affect work performance, is often elicited through self- reporting. This paper demonstrates the potential to use EEG to objectively quantify changes to drowsiness due to poor indoor air quality. Continuous EEG data was recorded from 23 treatment group participants subject to artificially raised indoor CO2 concentrations (average 2,700 ± 300 ppm) for approximately 10 minutes and 13 control group participants subject to the same protocol without additional CO2 (average 830 ± 70 ppm). EEG data were analysed for markers of drowsiness according neurophysiological methods at three stages of the experiment, Baseline, High CO2 and Post-Ventilation. Treatment group participants’ EEG data yielded a closer approximation to drowsiness than that of control group participants during the High CO2 condition, despite no significant group differences in self-reported sleepiness. Future work is required to determine the persistence of these changes to EEG over longer exposures and to better isolate the specific effect of CO2 on drowsiness compared to other environmental or physiological factors.Practical implicationsThis study introduces EEG as a potential objective indicator of the effect of indoor environmental conditions upon drowsinessParticipants exposed to 2,700 ppm for 10 minutes showed greater evidence of a progression towards drowsiness (as measured by EEG) than that of participants who received the same protocol without additional CO2 (mean 830 ± 70 ppm), despite similar ratings of subjective sleepiness.Subjective and objectively measured indications of drowsiness were reduced following ventilation of the room. Future work could explore the potential of regular ventilation episodes in knowledge work spaces to retain alertness.

The large body of natural ventilation research, rarely addresses the effects of the urban area on ventilation rates. A novel contribution to this gap is made by the REFRESH cube campaign (RCC). During 9 months of observations, the Silsoe cube was both isolated and surrounded by a limited asymmetrical staggered array. A wide range of variables were measured continuously, including: local, reference and internal flow, stability, background meteorological conditions, internal temperature, and ventilation rates (pressure difference techniques for cross ventilated cases). This paper tests the impact of the array on the relation between local and reference wind speeds as modified by wind direction and on cross ventilation rates. The presence of the array causes a 50% to 90% reduction in normalised ventilation rate when the reference wind direction is normal to the cube. The decrease in natural ventilation varies with wind direction with large amounts of scatter for both setups. The relation between local and reference wind speeds for the array case had two characteristic responses, not explained by reference wind (speed or direction) nor sensitive to averaging period, turbulence intensity or temperature differences. Given the singular response of the CIBSE approach, it is unable to capture these conditions.

In recent years there has been a significant change in the distribution of wind farms in Great Britain, with a trend towards very large offshore farms clustered together in zones. However, there are concerns these clusters could produce large ramping events on time scales of less than 6 h as local meteorological phenomena simultaneously impact the production of several farms. This paper presents generation data from the wind farms in the Thames Estuary (the largest cluster in the world) for 2014 and quantifies the high frequency power ramps. Based on a case study of a ramping event which occurred on 3rd November 2014, we show that due to the large capacity of the cluster, a localised ramp can have a significant impact on the cost of balancing the power system on a national level if it is not captured by the forecast of the system operator. The planned construction of larger offshore wind zones will exacerbate this problem. Consequently, there is a need for accurate regional wind power forecasts to minimise the costs of managing the system. This study shows that state-of-the-art high resolution forecast models have capacity to provide valuable information to mitigate this impact.

Thermal generation is a vital component of mature and reliable electricity markets. As the share of renewable electricity in such markets grows, so too do the challenges associated with its variability. Proposed solutions to these challenges typically focus on alternatives to primary generation, such as energy storage, demand side management, or increased interconnection. Less attention is given to the demands placed on conventional thermal generation or its potential for increased flexibility. However, for the foreseeable future, conventional plants will have to operate alongside new renewables and have an essential role in accommodating increasing supply-side variability.\ud \ud This paper explores the role that conventional generation has to play in managing variability through the sub-system case study of Northern Ireland, identifying the significance of specific plant characteristics for reliable system operation. Particular attention is given to the challenges of wind ramping and the need to avoid excessive wind curtailment. Potential for conflict is identified with the role for conventional plant in addressing these two challenges. Market specific strategies for using the existing fleet of generation to reduce the impact of renewable resource variability are proposed, and wider lessons from the approach taken are identified.

The ClearfLo project provides integrated measurements of the meteorology, composition and particulate loading of London's urban atmosphere to improve predictive capability for air quality.Air quality and heat are strong health drivers and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants such as ozone, nitrogen dioxide, and fine and coarse particulate matter in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the ClearfLo project's interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures.Within ClearfLo (www.clearflo.ac.uk), a large multi-institutional project funded by the UK Natural Environment Research Council (NERC), integrated measurements of meteorology, gaseous and particulate composition/loading within London's atmosphere were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, kerbside and rural locations were complemented with high-resolution numerical atmospheric simulations . Combining these (measurement/modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and summer Olympics 2012) focus upon the vertical structure and evolution of the urban boundary layer, chemical controls on nitrogen dioxide and ozone production, in particular the role of volatile organic compounds, and processes controlling the evolution, size, distribution and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

Ambient concentrations of trace elements with 2 h time resolution were measured in PM10–2.5, PM2.5–1.0 and PM1.0–0.3 size ranges at kerbside, urban background and rural sites in London during winter 2012. Samples were collected using rotating drum impactors (RDIs) and subsequently analysed with synchrotron radiation-induced X-ray fluorescence spectrometry (SR-XRF). Quantification of kerb and urban increments (defined as kerb-to-urban and urban-to-rural concentration ratios, respectively), and assessment of diurnal and weekly variability provided insight into sources governing urban air quality and the effects of urban micro-environments on human exposure. Traffic-related elements yielded the highest kerb increments, with values in the range of 10.4 to 16.6 for SW winds (3.3–6.9 for NE) observed for elements influenced by brake wear (e.g. Cu, Sb, Ba) and 5.7 to 8.2 for SW (2.6–3.0 for NE) for other traffic-related processes (e.g. Cr, Fe, Zn). Kerb increments for these elements were highest in the PM10–2.5 mass fraction, roughly twice that of the PM1.0–0.3 fraction. These elements also showed the highest urban increments (~ 3.0), although no difference was observed between brake wear and other traffic-related elements. All elements influenced by traffic exhibited higher concentrations during morning and evening rush hours, and on weekdays compared to weekends, with the strongest trends observed at the kerbside site, and additionally enhanced by winds coming directly from the road, consistent with street canyon effects. Elements related to mineral dust (e.g. Al, Si, Ca, Sr) showed significant influences from traffic-induced resuspension, as evidenced by moderate kerb (3.4–5.4 for SW, 1.7–2.3 for NE) and urban (~ 2) increments and increased concentrations during peak traffic flow. Elements related to regional transport showed no significant enhancement at kerb or urban sites, with the exception of PM10–2.5 sea salt (factor of up to 2), which may be influenced by traffic-induced resuspension of sea and/or road salt. Heavy-duty vehicles appeared to have a larger effect than passenger vehicles on the concentrations of all elements influenced by resuspension (including sea salt) and wearing processes. Trace element concentrations in London were influenced by both local and regional sources, with coarse and intermediate fractions dominated by traffic-induced resuspension and wearing processes and fine particles influenced by regional transport.

In the coming years the geographical distribution of wind farms in Great Britain is expected to change significantly. Following the development of the “round 3” wind zones (circa 2025), most of the installed capacity will be located in large offshore wind farms. However, the impact of this change in wind-farm distribution on the characteristics of national wind generation is largely unknown. This study uses a 34-year reanalysis dataset (Modern-Era Retrospective Analysis for Research and Applications (MERRA) from National Aeronautics and Space Administration, Global Modeling and Assimilation Office (NASA-GMAO)) to produce a synthetic hourly time series of GB-aggregated wind generation based on: (1) the “current” wind farm distribution, and (2) a “future” wind farm distribution scenario. The derived data are used to estimate a climatology of extreme wind power events in Great Britain for each wind farm distribution. The impact of the changing wind farm distribution on the wind-power statistics is significant. The annual mean capacity factor increased from 32.7% for the current wind farm distribution to 39.7% for the future distribution. In addition, there are fewer periods of prolonged low generation and more periods of prolonged high generation. Finally, the frequency and magnitude of ramping in the nationally aggregated capacity factor remains largely unchanged. However, due to the increased capacity of the future distribution, in terms of power output, the magnitude of the ramping increases by a factor of 5.

A Met Office/Natural Environment Research Council Joint Weather and Climate Research Programme workshop brought together 50 key international scientists from the UK and international community to formulate the key requirements for an Urban Meteorological Research strategy. The workshop was jointly organised by University of Reading and the Met Office.

It has long been known that the urban surface energy balance is different to that of a rural surface, and that heating of the urban surface after sunset gives rise to the Urban Heat Island (UHI). Less well known is how flow and turbulence structure above the urban surface are changed during different phases of the urban boundary layer (UBL). This paper presents new observations above both an urban and rural surface and investigates how much UBL structure deviates from classical behaviour. A 5-day, low wind, cloudless, high pressure period over London, UK, was chosen for analysis, during which there was a strong UHI. Boundary layer evolution for both sites was determined by the diurnal cycle in sensible heat flux, with an extended decay period of approximately 4 h for the convective UBL. This is referred to as the “Urban Convective Island” as the surrounding rural area was already stable at this time. Mixing height magnitude depended on the combination of regional temperature profiles and surface temperature. Given the daytime UHI intensity of \(1.5\,^\circ \mathrm{C}\), combined with multiple inversions in the temperature profile, urban and rural mixing heights underwent opposite trends over the period, resulting in a factor of three height difference by the fifth day. Nocturnal jets undergoing inertial oscillations were observed aloft in the urban wind profile as soon as the rural boundary layer became stable: clear jet maxima over the urban surface only emerged once the UBL had become stable. This was due to mixing during the Urban Convective Island reducing shear. Analysis of turbulent moments (variance, skewness and kurtosis) showed “upside-down” boundary layer characteristics on some mornings during initial rapid growth of the convective UBL. During the “Urban Convective Island” phase, turbulence structure still resembled a classical convective boundary layer but with some influence from shear aloft, depending on jet strength. These results demonstrate that appropriate choice of Doppler lidar scan patterns can give detailed profiles of UBL flow. Insights drawn from the observations have implications for accuracy of boundary conditions when simulating urban flow and dispersion, as the UBL is clearly the result of processes driven not only by local surface conditions but also regional atmospheric structure.

As the integration of vertical axis wind turbines in the built environment is a promising alternative to horizontal axis wind turbines, a 2D computational investigation of an augmented wind turbine is proposed and analysed. In the initial CFD analysis, three parameters are carefully investigated: mesh resolution; turbulence model; and time step size. It appears that the mesh resolution and the turbulence model affect result accuracy; while the time step size examined, for the unsteady nature of the flow, has small impact on the numerical results. In the CFD validation of the open rotor with secondary data, the numerical results are in good agreement in terms of shape. It is, however, observed a discrepancy factor of 2 between numerical and experimental data. Successively, the introduction of an omnidirectional stator around the wind turbine increases the power and torque coefficients by around 30–35% when compared to the open case; but attention needs to be given to the orientation of the stator blades for optimum performance. It is found that the power and torque coefficients of the augmented wind turbine are independent of the incident wind speed considered.

As wind generation increases, system impact studies rely on predictions of future generation and effective representation of wind variability. A well-established approach to investigate the impact of wind variability is to simulate generation using observations from 10 m meteorological mast-data. However, there are problems with relying purely on historical wind-speed records or generation histories: mast-data is often incomplete, not sited at a relevant wind generation sites, and recorded at the wrong altitude above ground (usually 10 m), each of which may distort the generation profile. A possible complimentary approach is to use reanalysis data, where data assimilation techniques are combined with state-of-the-art weather forecast models to produce complete gridded wind time-series over an area. Previous investigations of reanalysis datasets have placed an emphasis on comparing reanalysis to meteorological site records whereas this paper compares wind generation simulated using reanalysis data directly against historic wind generation records. Importantly, this comparison is conducted using raw reanalysis data (typical resolution ∼50 km), without relying on a computationally expensive “dynamical downscaling” for a particular target region. Although the raw reanalysis data cannot, by nature of its construction, represent the site-specific effects of sub-gridscale topography, it is nevertheless shown to be comparable to or better than the mast-based simulation in the region considered and it is therefore argued that raw reanalysis data may offer a number of significant advantages as a data source.

Currently there are few observations of the urban wind field at heights other than rooftop level. Remote sensing instruments such as Doppler lidars provide wind speed data at many heights, which would be useful in determining wind loadings of tall buildings, and predicting local air quality. Studies comparing remote sensing with traditional anemometers carried out in flat, homogeneous terrain often use scan patterns which take several minutes. In an urban context the flow changes quickly in space and time, so faster scans are required to ensure little change in the flow over the scan period. We compare 3993 h of wind speed data collected using a three-beam Doppler lidar wind profiling method with data from a sonic anemometer (190 m). Both instruments are located in central London, UK; a highly built-up area. Based on wind profile measurements every 2 min, the uncertainty in the hourly mean wind speed due to the sampling frequency is 0.05–0.11 m s−1. The lidar tended to overestimate the wind speed by ≈0.5 m s−1 for wind speeds below 20 m s−1. Accuracy may be improved by increasing the scanning frequency of the lidar. This method is considered suitable for use in urban areas.

[1] The Weather Research and Forecasting model was applied to analyze variations in the planetary boundary layer (PBL) structure over Southeast England including central and suburban London. The parameterizations and predictive skills of two nonlocal mixing PBL schemes, YSU and ACM2, and two local mixing PBL schemes, MYJ and MYNN2, were evaluated over a variety of stability conditions, with model predictions at a 3 km grid spacing. The PBL height predictions, which are critical for scaling turbulence and diffusion in meteorological and air quality models, show significant intra-scheme variance (> 20%), and the reasons are presented. ACM2 diagnoses the PBL height thermodynamically using the bulk Richardson number method, which leads to a good agreement with the lidar data for both unstable and stable conditions. The modeled vertical profiles in the PBL, such as wind speed, turbulent kinetic energy (TKE), and heat flux, exhibit large spreads across the PBL schemes. The TKE predicted by MYJ were found to be too small and show much less diurnal variation as compared with observations over London. MYNN2 produces better TKE predictions at low levels than MYJ, but its turbulent length scale increases with height in the upper part of the strongly convective PBL, where it should decrease. The local PBL schemes considerably underestimate the entrainment heat fluxes for convective cases. The nonlocal PBL schemes exhibit stronger mixing in the mean wind fields under convective conditions than the local PBL schemes and agree better with large-eddy simulation (LES) studies.

The variability of renewable energy is widely recognised as a challenge for integrating high levels of renewable generation into electricity systems. However, to explore its implications effectively, variability itself should first be clearly understood. This is particularly true for national electricity systems with high planned penetrations of renewables and limited interconnection such as the UK. Variability cannot be considered as a distinct resource property with a single measurable parameter, but is a multi-faceted concept best described by a range of distinct characteristics. This paper identifies relevant characteristics of variability, and considers their implications for energy research. This is done through analysis of wind, solar and tidal current resources, with a primary focus on the Bristol Channel region in the UK. The relationship with electricity demand is considered, alongside the potential benefits of resource diversity. Analysis is presented in terms of persistence, distribution, frequency and correlation between supply and demand. Marked differences are seen between the behaviours of the individual resources, and these give rise to a range of different implications for system integration. Wind shows strong persistence and a useful seasonal pattern, but also a high spread in energy levels at time scales beyond one or two days. The solar resource is most closely correlated with electricity demand, but is undermined by night-time zero values and an even greater spread of monthly energy delivered than wind. In contrast, the tidal resource exhibits very low persistence, but also much greater consistency in energy values assessed across monthly time scales. Whilst this paper focuses primarily on the behaviour of resources, it is noted that discrete variability characteristics can be related to different system impacts. Persistence and predictability are relevant for system balancing, whereas statistical distribution is more relevant when exploring issues of asset utilisation and energy curtailment. Areas of further research are also identified, including the need to assess the value of predictability in relation to other characteristics.

Meteorological (met) station data is used as the basis for a number of influential studies into the impacts of the variability of renewable resources. Real turbine output data is not often easy to acquire, whereas meteorological wind data, supplied at a standardised height of 10 m, is widely available. This data can be extrapolated to a standard turbine height using the wind profile power law and used to simulate the hypothetical power output of a turbine. Utilising a number of met sites in such a manner can develop a model of future wind generation output. However, the accuracy of this extrapolation is strongly dependent on the choice of the wind shear exponent α . This paper investigates the accuracy of the simulated generation output compared to reality using a wind farm in North Rhins, Scotland and a nearby met station in West Freugh. The results show that while a single annual average value for α may be selected to accurately represent the long term energy generation from a simulated wind farm, there are significant differences between simulation and reality on an hourly power generation basis, with implications for understanding the impact of variability of renewables on short timescales, particularly system balancing and the way that conventional generation may be asked to respond to a high level of variable renewable generation on the grid in the future.

Airflow along rivers might provide a key mechanism for ventilation in cities: important for air quality and thermal comfort. Airflow varies in space and time in the vicinity of rivers. Consequently, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D airflow in locations which are difficult to observe with conventional approaches. For three months in the winter and spring of 2011, the airflow above the River Thames in central London was observed using a scanning Doppler lidar, a scintillometer and sonic anemometers. First, an inter-comparison showed that lidar-derived mean wind-speed estimates compare almost as well to sonic anemometers (root-mean-square error (rmse) 0.65-0.68 m s− 1) as comparisons between sonic anemometers (0.35-0.73 m s− 1). Second, the lidar duo-beam operating strategy provided horizontal transects of wind vectors (comparison with scintillometer rmse 1.12-1.63 m s− 1) which revealed mean and turbulent airflow across the river and surrounds; in particular, channelled airflow along the river and changes in turbulence quantities consistent with the roughness changes between built and river environments. The results have important consequences for air quality and dispersion around urban rivers, especially given that many cities have high traffic rates on roads located on riverbanks.

We report on more than 3 years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Mean annual emissions of CO2 in the period 2012–2014 (39.1 ± 2.4 ktons km−2 yr−1) and CO (89 ± 16 tons km−2 yr−1) were consistent (within 1 and 5 % respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 emissions (72 ± 3 tons km−2 yr−1) were over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69 %, and monthly fluxes were strongly anti-correlated with mean air temperature. The winter increment in CO emissions was attributed mainly to vehicle cold starts and reduced fuel combustion efficiency. CO2 fluxes were 33 % higher in winter than in summer and anti-correlated with mean air temperature, albeit to a lesser extent than for CO. This was attributed to an increased demand for natural gas for heating during the winter. CH4 fluxes exhibited moderate seasonality (21 % larger in winter), and a spatially variable linear anti-correlation with air temperature. Differences in resident population within the flux footprint explained up to 90 % of the spatial variability of the annual CO2 fluxes and up to 99 % for CH4. Furthermore, we suggest that biogenic sources of CH4, such as wastewater, which is unaccounted for by the atmospheric emissions inventories, make a substantial contribution to the overall budget and that commuting dynamics in and out of central business districts could explain some of the spatial and temporal variability of CO2 and CH4 emissions. To our knowledge, this study is unique given the length of the data sets presented, especially for CO and CH4 fluxes. This study offers an independent assessment of "bottom-up" emissions inventories and demonstrates that the urban sources of CO and CO2 are well characterized in London. This is however not the case for CH4 emissions which are heavily underestimated by the inventory approach. Our results and others point to opportunities in the UK and abroad to identify and quantify the "missing" sources of urban methane, revise the methodologies of the emission inventories and devise emission reduction strategies for this potent greenhouse gas.

High quality wind measurements in cities are needed for numerous applications including wind engineering. Such data-sets are rare and measurement platforms may not be optimal for meteorological observations. Two years' wind data were collected on the BT Tower, London, UK, showing an upward deflection on average for all wind directions. Wind tunnel simulations were performed to investigate flow distortion around two scale models of the Tower. Using a 1:160 scale model it was shown that the Tower causes a small deflection (ca. 0.5°) compared to the lattice on top on which the instruments were placed (ca. 0–4°). These deflections may have been underestimated due to wind tunnel blockage. Using a 1:40 model, the observed flow pattern was consistent with streamwise vortex pairs shed from the upstream lattice edge. Correction factors were derived for different wind directions and reduced deflection in the full-scale data-set by

We investigate the spatial characteristics of urban-like canopy flow by applying particle image velocimetry (PIV) to atmospheric turbulence. The study site was a Comprehensive Outdoor Scale MOdel (COSMO) experiment for urban climate in Japan. The PIV system captured the two-dimensional flow field within the canopy layer continuously for an hour with a sampling frequency of 30 Hz, thereby providing reliable outdoor turbulence statistics. PIV measurements in a wind-tunnel facility using similar roughness geometry, but with a lower sampling frequency of 4 Hz, were also done for comparison. The turbulent momentum flux from COSMO, and the wind tunnel showed similar values and distributions when scaled using friction velocity. Some different characteristics between outdoor and indoor flow fields were mainly caused by the larger fluctuations in wind direction for the atmospheric turbulence. The focus of the analysis is on a variety of instantaneous turbulent flow structures. One remarkable flow structure is termed 'flushing', that is, a large-scale upward motion prevailing across the whole vertical cross-section of a building gap. This is observed intermittently, whereby tracer particles are flushed vertically out from the canopy layer. Flushing phenomena are also observed in the wind tunnel where there is neither thermal stratification nor outer-layer turbulence. It is suggested that flushing phenomena are correlated with the passing of large-scale low-momentum regions above the canopy.

Urban boundary layers (UBLs) can be highly complex due to the heterogeneous roughness and heating of the surface, particularly at night. Due to a general lack of observations, it is not clear whether canonical models of boundary layer mixing are appropriate in modelling air quality in urban areas. This paper reports Doppler lidar observations of turbulence profiles in the centre of London, UK, as part of the second REPARTEE campaign in autumn 2007. Lidar-measured standard deviation of vertical velocity averaged over 30 min intervals generally compared well with in situ sonic anemometer measurements at 190 m on the BT telecommunications Tower. During calm, nocturnal periods, the lidar underestimated turbulent mixing due mainly to limited sampling rate. Mixing height derived from the turbulence, and aerosol layer height from the backscatter profiles, showed similar diurnal cycles ranging from c. 300 to 800 m, increasing to c. 200 to 850 m under clear skies. The aerosol layer height was sometimes significantly different to the mixing height, particularly at night under clear skies. For convective and neutral cases, the scaled turbulence profiles resembled canonical results; this was less clear for the stable case. Lidar observations clearly showed enhanced mixing beneath stratocumulus clouds reaching down on occasion to approximately half daytime boundary layer depth. On one occasion the nocturnal turbulent structure was consistent with a nocturnal jet, suggesting a stable layer. Given the general agreement between observations and canonical turbulence profiles, mixing timescales were calculated for passive scalars released at street level to reach the BT Tower using existing models of turbulent mixing. It was estimated to take c. 10 min to diffuse up to 190 m, rising to between 20 and 50 min at night, depending on stability. Determination of mixing timescales is important when comparing to physico-chemical processes acting on pollutant species measured simultaneously at both the ground and at the BT Tower during the campaign. From the 3 week autumnal data-set there is evidence for occasional stable layers in central London, effectively decoupling surface emissions from air aloft.

Flow and turbulence above urban terrain is more complex than above rural terrain, due to the different momentum and heat transfer characteristics that are affected by the presence of buildings (e.g. pressure variations around buildings). The applicability of similarity theory (as developed over rural terrain) is tested using observations of flow from a sonic anemometer located at 190.3 m height in London, U.K. using about 6500 h of data. Turbulence statistics—dimensionless wind speed and temperature, standard deviations and correlation coefficients for momentum and heat transfer—were analysed in three ways. First, turbulence statistics were plotted as a function only of a local stability parameter z/Λ (where Λ is the local Obukhov length and z is the height above ground); the σi/u* values (i = u, v, w) for neutral conditions are 2.3, 1.85 and 1.35 respectively, similar to canonical values. Second, analysis of urban mixed-layer formulations during daytime convective conditions over London was undertaken, showing that atmospheric turbulence at high altitude over large cities might not behave dissimilarly from that over rural terrain. Third, correlation coefficients for heat and momentum were analyzed with respect to local stability. The results give confidence in using the framework of local similarity for turbulence measured over London, and perhaps other cities. However, the following caveats for our data are worth noting: (i) the terrain is reasonably flat, (ii) building heights vary little over a large area, and (iii) the sensor height is above the mean roughness sublayer depth.

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 (θ ref ) 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 roof-top 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 θ ref of 5°–10°) 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.

Street-level mean flow and turbulence govern the dispersion of gases away from their sources in urban areas. A suitable reference measurement in the driving flow above the urban canopy is needed to both understand and model complex street-level flow for pollutant dispersion or emergency response purposes. In vegetation canopies, a reference at mean canopy height is often used, but it is unclear whether this is suitable for urban canopies. This paper presents an evaluation of the quality of reference measurements at both roof-top (height = H) and at height z = 9H = 190 m, and their ability to explain mean and turbulent variations of street-level flow. Fast response wind data were measured at street canyon and reference sites during the six-week long DAPPLE project field campaign in spring 2004, in central London, UK, and an averaging time of 10 min was used to distinguish recirculation-type mean flow patterns from turbulence. Flow distortion at each reference site was assessed by considering turbulence intensity and streamline deflection. Then each reference was used as the dependent variable in the model of Dobre et al. (2005) which decomposes street-level flow into channelling and recirculating components. The high reference explained more of the variability of the mean flow. Coupling of turbulent kinetic energy was also stronger between street-level and the high reference flow rather than the roof-top. This coupling was weaker when overnight flow was stratified, and turbulence was suppressed at the high reference site. However, such events were rare (

The paper describes a field study focused on the dispersion of a traffic-related pollutant within an area close to a busy intersection between two street canyons in Central London. Simultaneous measurements of airflow, traffic flow and carbon monoxide concentrations ([CO]) are used to explore the causes of spatial variability in [CO] over a full range of background wind directions. Depending on the roof-top wind direction, evidence of both flow channelling and recirculation regimes were identified from data collected within the main canyon and the intersection. However, at the intersection, the merging of channelled flows from the canyons increased the flow complexity and turbulence intensity. These features, coupled with the close proximity of nearby queuing traffic in several directions, led to the highest overall time-average measured [CO] occurring at the intersection. Within the main street canyon, the data supported the presence of a helical flow regime for oblique roof-top flows, leading to increased [CO] on the canyon leeward side. Predominant wind directions led to some locations having significantly higher diurnal average [CO] due to being mostly on the canyon leeward side during the study period. For all locations, small changes in the background wind direction could cause large changes in the in-street mean wind angle and local turbulence intensity, implying that dispersion mechanisms would be highly sensitive to small changes in above roof flows. During peak traffic flow periods, concentrations within parallel side streets were approximately four times lower than within the main canyon and intersection which has implications for controlling personal exposure. Overall, the results illustrate that pollutant concentrations can be highly spatially variable over even short distances within complex urban geometries, and that synoptic wind patterns, traffic queue location and building topologies all play a role in determining where pollutant hot spots occur.

Profiles of wind and turbulence over an urban area evolve with fetch in response to surface characteristics. Sodar measurements, taken on 22 April 2002 during the Salford Experiment in the UK (Salfex), are here related to upstream terrain. A logarithmic layer up to z = 65m was observed in all half-hour averaged profiles. Above this height the profile showed a different vertical gradient, suggesting a change in surface cover upstream. The drag coefficient varied by a factor of two over only a 20° direction change. Turbulence intensity (σx) for each wind component (x) decreased with height, but the ratio suggested an underestimate of σu compared to previous results. Mean urban and suburban cover fraction within the source area for each height decreased sharply between z = 20 and 50m, increasing slightly above. The near-convergence of cover fractions thus occured for source areas of minimum length ≈ 2,200 m. In comparison, the mean length scale of heterogeneity LP was calculated from surface cover data to be 1,284 m, and the corresponding mean blending height hb was 175 m. Finally, the mean streamline angle, α, was negative and the magnitude decreased with height. An exponential fit to α for z ≤ 65m gave an e-folding height scale of 159 m. A simple relationship between this height scale and LP was assumed, giving LP ≈ 1,080 m, which is in reasonable agreement with the estimate from surface cover type. The results suggest that more emphasis is required on modelling and measuring surface-layer flow over heterogeneous urban canopies.

A wind-tunnel study was conducted to investigate ventilation of scalars from urban-like geometries at neighbourhood scale by exploring two different geometries a uniform height roughness and a non-uniform height roughness, both with an equal plan and frontal density of λ p = λ f = 25%. In both configurations a sub-unit of the idealized urban surface was coated with a thin layer of naphthalene to represent area sources. The naphthalene sublimation method was used to measure directly total area-averaged transport of scalars out of the complex geometries. At the same time, naphthalene vapour concentrations controlled by the turbulent fluxes were detected using a fast Flame Ionisation Detection (FID) technique. This paper describes the novel use of a naphthalene coated surface as an area source in dispersion studies. Particular emphasis was also given to testing whether the concentration measurements were independent of Reynolds number. For low wind speeds, transfer from the naphthalene surface is determined by a combination of forced and natural convection. Compared with a propane point source release, a 25% higher free stream velocity was needed for the naphthalene area source to yield Reynolds-number-independent concentration fields. Ventilation transfer coefficients w T /U derived from the naphthalene sublimation method showed that, whilst there was enhanced vertical momentum exchange due to obstacle height variability, advection was reduced and dispersion from the source area was not enhanced. Thus, the height variability of a canopy is an important parameter when generalising urban dispersion. Fine resolution concentration measurements in the canopy showed the effect of height variability on dispersion at street scale. Rapid vertical transport in the wake of individual high-rise obstacles was found to generate elevated point-like sources. A Gaussian plume model was used to analyse differences in the downstream plumes. Intensified lateral and vertical plume spread and plume dilution with height was found for the non-uniform height roughness.

Trace element measurements in PM10–2.5, PM2.5–1.0 and PM1.0–0.3 aerosol were performed with 2 h time resolution at kerbside, urban background and rural sites during the ClearfLo winter 2012 campaign in London. The environment-dependent variability of emissions was characterized using the Multilinear Engine implementation of the positive matrix factorization model, conducted on data sets comprising all three sites but segregated by size. Combining the sites enabled separation of sources with high temporal covariance but significant spatial variability. Separation of sizes improved source resolution by preventing sources occurring in only a single size fraction from having too small a contribution for the model to resolve. Anchor profiles were retrieved internally by analysing data subsets, and these profiles were used in the analyses of the complete data sets of all sites for enhanced source apportionment. A total of nine different factors were resolved (notable elements in brackets): in PM10–2.5, brake wear (Cu, Zr, Sb, Ba), other traffic-related (Fe), resuspended dust (Si, Ca), sea/road salt (Cl), aged sea salt (Na, Mg) and industrial (Cr, Ni); in PM2.5–1.0, brake wear, other traffic-related, resuspended dust, sea/road salt, aged sea salt and S-rich (S); and in PM1.0–0.3, traffic-related (Fe, Cu, Zr, Sb, Ba), resuspended dust, sea/road salt, aged sea salt, reacted Cl (Cl), S-rich and solid fuel (K, Pb). Human activities enhance the kerb-to-rural concentration gradients of coarse aged sea salt, typically considered to have a natural source, by 1.7–2.2. These site-dependent concentration differences reflect the effect of local resuspension processes in London. The anthropogenically influenced factors traffic (brake wear and other traffic-related processes), dust and sea/road salt provide further kerb-to-rural concentration enhancements by direct source emissions by a factor of 3.5–12.7. The traffic and dust factors are mainly emitted in PM10–2.5 and show strong diurnal variations with concentrations up to 4 times higher during rush hour than during night-time. Regionally influenced S-rich and solid fuel factors, occurring primarily in PM1.0–0.3, have negligible resuspension influences, and concentrations are similar throughout the day and across the regions.