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Characterizing turbulent exchange over a heterogeneous urban landscape
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Much of the world’s population now resides within cities where altered energy use, building distributions, transportation networks, and surface characteristics influence land-atmosphere interactions, energy and water budgets, and carbon cycles, relative to rural areas. Knowledge of the surface properties that affect exchanges of energy and mass, as well as how exchanges change over time, is critical for accurate local weather and climate forecasting, and pollution dispersion modelling. One way of measuring flows of energy and mass over cities is through the use of eddy covariance (EC). This stationary approach has been implemented in many cities globally, and has contributed greatly to knowledge of the exchange between the urban surface and the urban atmosphere. However, EC was developed for ecosystems like forests, where source/sink distributions are horizontally homogeneous; This surface uniformity does not usually pertain to cities, where sources of heat, water, momentum, and trace gases exhibit spatial heterogeneity. Eight years (2008 - 2016) of continuous EC flux measurements over a residential neighbourhood in Vancouver, BC, Canada, were used to characterize the relationship between surface source/sink heterogeneity and the efficiency of turbulent exchange of heat, water vapour, momentum, and carbon dioxide (CO2) (represented by the correlation coefficients r_wT, r_wh, r_uw, and r_wc, respectively). Using a combination of remotely-sensed satellite and light detection and ranging (LiDAR) imagery, geospatially-referenced land cover data, traffic densities, and source area modelling, exchange efficiencies were examined seasonally, diurnally, as a function of atmospheric stability, and in terms of distinct, spatially-variable surface cover attributes. Transport of momentum and scalars exhibited varied dependencies that resulted in dissimilar exchange efficiencies; r_wT was primarily moderated by stability, time of day and year, and surface patchiness, r_uw was mostly affected by stability and surface roughness, and r_wh and r_wc were mostly affected by surface patchiness. As source/sink heterogeneity increased, exchange became less efficient. Competing sources and sinks acting simultaneously on a turbulent entity resulted in an exchange efficiency closer to zero. Under stable conditions, r_wT, r_wh, r_uw, and r_wc depended mostly on stability, while surface heterogeneity contributed more to dissimilarities between momentum and scalar exchange efficiencies under unstable conditions.
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A widely used morphometric method (Macdonald et al. 1998) to calculate the zero-plane displacement (zd) and aerodynamic roughness length (z0) for momentum is further developed to include vegetation. The adaptation also applies to the Kanda et al. (2013) morphometric method which considers roughness-element height variability. Roughness-element heights (mean, maximum and standard deviation) of both buildings and vegetation are combined with a porosity corrected plan area and drag formulation. The method captures the influence of vegetation (in addition to buildings), with the magnitude of the effect depending upon whether buildings or vegetation are dominant and the porosity of vegetation (e.g. leaf-on or leaf-off state). Application to five urban areas demonstrates that where vegetation is taller and has larger surface cover, its inclusion in the morphometric methods can be more important than the morphometric method used. Implications for modelling the logarithmic wind profile (to 100 m) are demonstrated. Where vegetation is taller and occupies a greater amount of space, wind speeds may be slowed by up to a factor of three.
We report on more than three years of measurements of fluxes of methane (CH4), carbon monoxide (CO) and carbon dioxide (CO2) taken by eddy-covariance in central London, UK. Inter-annual variability in the period 2012–2014 ranged from 36.3 to 40.7 ktons km−2 y−1 for CO2, and from 69 to 75 tons km−2 y−1 for CH4. Mean annual emissions of CO2 (39.1 ± 2.4 ktons km−2 y−1) and CO (89 ± 16 tons km−2 y−1) were consistent (within 1 % and 5 % respectively) with values from the London Atmospheric Emissions Inventory, but measured CH4 (72 ± 3 tons km−2 y−1) was over two-fold larger than the inventory value. Seasonal variability was large for CO with a winter to summer reduction of 69 %. Monthly fluxes of CO were strongly anti-correlated with mean air temperature, and the winter emissions accounted for 45 % of the annual budget. 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 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. Seasonality in CH4 fluxes was moderate (21 % larger in winter) and linear correlation with air temperature was only statistically significant for certain wind sectors (N, NE, E and W), which was also the case for CO2. Differences in resident population within the flux footprint explained ca. 90 % variability by wind direction in annual CO2 fluxes and 99 % for CH4 (wind sectors excluded from linear regressions: S for CO2; S, SE and E for CH4). Seasonality and proportionality of emissions with respect to population in the outlying wind sectors (S, SE and E) might be masked by constant sources of CO2 and CH4, perhaps of industrial or biogenic origin. To our knowledge, this study is unique given the long-term, continuous dataset of urban CH4 fluxes analysed.
If one surveys the development of wind engineering, one comes to the conclusion that the challenge of urban climatology is one of the most important remaining tasks for the wind engineers. But what distinguishes wind engineering in urban areas from conventional wind engineering? Principally, the fact that the effects studied are usually unique to a particular situation, requiring consideration of the surroundings of the buildings. In the past, modelling criteria have been developed that make it possible to solve environmental problems with great confidence, and studies validated the models: at least in a neutrally stratified atmosphere.
The approach adopted in the book is that of applied fluid mechanics, since this forms the basis for the evaluation of the urban wind field. Variables for air quality or loads are problem specific, or even random, and methods for studying them are based on risk analysis, which is also presented. Criteria are developed for a systematic approach to urban wind engineering problems, including parameter studies.
The five sections of the book are: Fundamentals of urban boundary layer and dispersion; Forces on complex structures in built-up areas; Air pollution in cities; Numerical solution techniques; and Posters. A subject index is included.
Large-eddy simulations (LES) are used to gain insight into the effects of trees on turbulence, aerodynamic parameters, and momentum transfer rates characterizing the atmosphere within and above a real urban canopy. Several areas are considered that are part of a neighbourhood in the city of Vancouver, BC, Canada where a small fraction of trees are taller than buildings. In this area, eight years of continuous wind and turbulence measurements are available from a 30 m meteorological tower. Data from airborne light detection and ranging (LiDAR) are used to represent both buildings and vegetation at the LES resolution. In the LES algorithm, buildings are accounted through an immersed boundary method, whereas vegetation is parameterized via a location-specific leaf area density. LES are performed including and excluding vegetation from the considered urban areas, varying wind direction and leaf area density. Surface roughness lengths (z0) from both LES and tower measurements are sensitive to the parameter, where LAI is the leaf area index and is the frontal area fraction of buildings characterizing a given canopy. For instance, tower measurements predict a 19% seasonal increase in z0, slightly lower than the 27% increase featured by LES for the most representative canopy (leaves-off leaves-on ). Removing vegetation from such a canopy would cause a dramatic drop of approximately 50% in z0 when compared to the reference summer value. The momentum displacement height (d) from LES also consistently increases as increases, due in large part to the disproportionate amount of drag that the (few) relatively taller trees exert on the flow. LES and measurements both predict an increase in the ratio of turbulent to mean kinetic energy (TKE/MKE) at the tower sampling height going from winter to summer, and LES also show how including vegetation results in a more (positive) negatively skewed (horizontal) vertical velocity distribution – reflecting a more intermittent velocity field which favors sweep motions when compared to ejections. Within the urban canopy, the effects of trees are twofold: on one hand, they act as a direct momentum sink for the mean flow; on the other, they reduce downward turbulent transport of high-momentum fluid, significantly reducing the wind intensity at the heights where people live and buildings consume energy.
This paper provides a comprehensive, critical review of turbulence observations over cities. More than fifty studies are analysed with their experimental conditions summarized in an appendix. The main results are based on 14 high-quality experiments which met criteria based on stringent experimental requirements. The observations are presented as nan-dimensional statistics to facilitate comparison between urban studies and work conducted over other rough, inhomogeneous surfaces. Wake production associated with bluff bodies, and the inhomogeneous distribution of sources and sinks of scalars, result in a roughness sub-layer which for the studies reviewed extends to about 2.5 to 3 times the height of the buildings. It is shown that within this region the basis of several traditional micrometeorological approaches to describe the turbulent exchange is in doubt. There are strong similarities to flow over plant canopies, and many of the turbulence characteristics can be interpreted in the framework of a plane mixing layer. Future field observations should concentrate on the turbulent exchange near the top and within the urban canopy as well as within the urban boundary layer.