The Clean Air for London (ClearfLo) project provides integrated measurements of the meteorology, composition, and particulate loading of the urban atmosphere in London, United Kingdom, to improve predictive capability for air quality. METEOROLOGY, AIR QUALITY, AND HEALTH IN LONDONThe ClearfLo Project Economic and Social Affairs 2013). Urban populations are exposed to stressful environmental conditions, such as local and nonlocal pollutants, that cause poor air quality and microclimates that exacerbate heat stress during heat waves. These are projected to increase in a warming climate. Our cities are therefore nexus points for several environmental health stresses that we currently face (Rydin et al. 2012) and the interacting issues around sustainability and human health.The purpose of this paper is to introduce the Clean Air for London (ClearfLo) project, which investigates the atmospheric science that underpins these health stresses, with a particular focus on the urban increment in atmospheric drivers. We focused on three atmospheric drivers of environmental health stress in cities, namely, heat, gas-phase pollutants, and particulate matter (PM). Health stresses from the urban atmospheric environment.Heat waves have an impact on human health. Populations typically display an optimal temperature range at which the (daily or weekly) mortality rate is lowest. Mortality rates rise as temperatures exceed this optimal range (e.g., Rydin et al. 2012). The 2003 European heat wave (Stedman 2004) in combination with air pollution was responsible for more than 2000 excess deaths in the United Kingdom (Johnson et al. 2005). Under a warming climate, the risks posed by heat stress are predicted to increase (Hacker et al. 2005). People living in urban environments are exposed to higher temperatures than in nonurban regions. Thus, heat-related deaths could be higher within urban areas (Mavrogianni et al. 2011). Hence, ClearfLo is concerned with measuring the factors controlling the urban atmospheric boundary layer, that is, the surface energy balance.The World Health Organization (WHO) reported (WHO 2006) that the strongest effects of air quality 779MAY 2015 AMERICAN METEOROLOGICAL SOCIETY | on health are attributable to PM, followed by ozone (O 3 ) and nitrogen dioxide (NO 2 ). A recent report (Guerreiro et al. 2013) indicates that in 2011 up to 88% of the urban population in Europe was exposed to concentrations exceeding the WHO air quality guidelines for PM 10 (defined as particles that pass through a size-selective inlet with a 50% efficiency cutoff at 10-µm aerodynamic diameter, representative of the inhalable fraction). It is estimated that a reduction of PM 10 to the WHO annual-mean guideline of 20 µg m −3 would reduce attributable deaths per year in Europe by 22,000. Further, this would lead to a substantial improvement in the quality of life for millions with a preexisting respiratory or cardiovascular disease (COMEAP 2010).Epidemiological studies consistently demonstrate an association between the PM mass concentr...
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°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.
Nine methods to determine local-scale aerodynamic roughness length (z 0 ) and zero-plane displacement (z d ) 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 z d and z 0 estimates. Across the three sites, z d 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 z d is consistently greater than the local mean building height. Depending upon method and wind direction, z 0 varies between 0.1 and 5 m with morphometric z 0 consistently being 2-3 m larger than the anemometric z 0 . 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 z d and z 0 .
Abstract. Determining the contribution of wood smoke to air pollution in large cities such as London is becoming increasingly important due to the changing nature of domestic heating in urban areas. During winter, biomass burning emissions have been identified as a major cause of exceedances of European air quality limits. The aim of this work was to quantify the contribution of biomass burning in London to concentrations of PM2.5 and determine whether local emissions or regional contributions were the main source of biomass smoke. To achieve this, a number of biomass burning chemical tracers were analysed at a site within central London and two sites in surrounding rural areas. Concentrations of levoglucosan, elemental carbon (EC), organic carbon (OC) and K+ were generally well correlated across the three sites. At all the sites, biomass burning was found to be a source of OC and EC, with the largest contribution of EC from traffic emissions, while for OC the dominant fraction included contributions from secondary organic aerosols, primary biogenic and cooking sources. Source apportionment of the EC and OC was found to give reasonable estimation of the total carbon from non-fossil and fossil fuel sources based upon comparison with estimates derived from 14C analysis. Aethalometer-derived black carbon data were also apportioned into the contributions from biomass burning and traffic and showed trends similar to those observed for EC. Mean wood smoke mass at the sites was estimated to range from 0.78 to 1.0 μg m−3 during the campaign in January–February 2012. Measurements on a 160 m tower in London suggested a similar ratio of brown to black carbon (reflecting wood burning and traffic respectively) in regional and London air. Peaks in the levoglucosan and K+ concentrations were observed to coincide with low ambient temperature, consistent with domestic heating as a major contributing local source in London. Overall, the source of biomass smoke in London was concluded to be a background regional source overlaid by contributions from local domestic burning emissions. This could have implications when considering future emission control strategies during winter and may be the focus of future work in order to better determine the contributing local sources.
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