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Local urban air quality models must be able to account for complex road geometries if they are to predict near-road concentrations accurately. This includes flyovers, which are often used to improve flow at busy junctions or to take traffic through urban greenspace. We present a new methodology for modelling elevated roads in which the plume is only allowed to grow downwards once it has left the downwind road edge, thus accounting for road shielding. This new approach has been implemented in the operational dispersion model ADMS-Urban. The updated model is validated against monitoring data from two sites located next to busy flyovers—one in London, UK, the other in Antwerp, Belgium. It is shown to perform very well compared with simulations in which the flyovers are modelled at ground level, and slightly better than simulations when the traditional approach to modelling elevated roads (no road shielding) is used. Near-ground concentrations are significantly reduced with road elevation due to (i) increased vertical source-receptor distance, (ii) greater dispersion from the source where wind speeds are higher, and (iii) reduced impact of ground-level plume reflections. Pollutant trapping in street canyons is also minimised in cases where a flyover is elevated above the local building level. A sensitivity analysis is also presented in which multiple road elevations are tested; these results can be used by urban planners when designing new flyovers or by modellers in deciding whether it is important to account for road elevation near sensitive receptors. [ABSTRACT FROM AUTHOR]

Ambient air pollution from PM2.5 is a major risk to human and environmental health, with significant impacts on mortality and morbidity. Mitigation policies—which may be regional or national in extent—need to consider both primary and secondary particles to be effective, balancing within-region emissions and longer-range transport phenomena. The modelling system WRF-CMAQ was used to simulate the impact of emissions reductions in the West Midlands region of the UK, evaluating the change in total PM2.5 and in its primary and secondary components. Domestic combustion, road transport and agriculture emissions were reduced individually or in combination, at a national or at local level. Combined reduction of road transport and agriculture emissions showed the strongest reduction (29%) in average PM2.5 if applied at national level. At the local level, reductions from domestic combustion were shown to be the most effective policy (13.4% on average). Secondary inorganic fractions of PM2.5 are the most abundant, with 25% NO3− 21% SO42− and 13% NH4+ on average. Scenario analysis shows that the contribution of secondary components to the fractional change of PM2.5 dominates for national policies (up to 0.86 for NO3−) when road transport and agriculture activities are reduced, while at the regional level the elemental and organic carbon fractional changes are dominant (up to 0.64 for organic carbon). [ABSTRACT FROM AUTHOR]

Information on the spatiotemporal characteristics of Beijing's urban-rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (~ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both Local Climate Zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ~ 4.5 °C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities. [ABSTRACT FROM AUTHOR]

Byline: John S. Irwin, David Carruthers, Jenny Stocker, James Paumier During the development phase of an air quality dispersion model and in subsequent upgrades, model performance is constantly evaluated. These evaluations generally compare simulation results using simple methods that do not account for the fact that models only predict a portion of the variability seen in the observations. To fill a part of this void, the US Environmental Protection Agency (EPA) developed a standard that has been adopted by the American Society for Testing and Materials (ASTM), designation D6589 Standard Guide for the Statistical Evaluation of Atmospheric Dispersion Model Performance. Within the annex to this standard is an 'example' test method that tests the ability of dispersion models to simulate the average centreline concentration. The method involves grouping observed data into groups or regimes, in which the dispersion is expected to be somewhat similar. The average centerline concentration is then derived for each group using bootstrap resampling. It is this average centreline concentration that is then compared with the modeling results. By this means, the focus is on testing the ability of models to replicate the first moment (the average) of the centreline concentration distribution, which for most operational models is the only feature in the centerline concentration distribution they are capable of simulating. This paper will focus on recent work to further test the ASTM 'example' test method. This work involved the application of the test method to the results from ADMS (version 3.1), AERMOD (versions 98022 and 02161), HPDM (version 4.3, level 920605) and ISCST3 (version 00101). Three atmospheric dispersion field studies are analysed Prairie Grass (in 1956, rural, low level release), Kincaid (1980, rural, elevated release) and Indianapolis (1985, urban, elevated release).

We examine the street-scale variation of NOx, NO2, O3 and PM2.5 concentrations in Beijing during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) winter measurement campaign in November–December 2016. Simulations are performed using the urban air pollution dispersion and chemistry model ADMS-Urban, and an explicit network of road source emissions. Two versions of the gridded Multi-resolution Emission Inventory for China (MEIC v1.3) are used: the standard MEIC v1.3 emissions and an optimised version, both at 3 km resolution. We construct a new traffic emissions inventory by apportioning the transport sector onto a detailed spatial road map. Agreement between mean simulated and measured pollutant concentrations from Beijing's air quality monitoring network and the Institute of Atmospheric Physics (IAP) field site is improved when using the optimised emissions inventory. The inclusion of fast NOx-O3 chemistry and explicit traffic emissions enables the sharp concentration gradients adjacent to major roads to be resolved with the model. However, NO2 concentrations are overestimated close to roads, likely due to the assumption of uniform traffic activity across the study domain. Differences between measured and simulated diurnal NO2 cycles suggest that an additional evening NOx emission source, likely related to heavy duty diesel trucks, is not fully accounted for in the emissions inventory. Overestimates in simulated early evening NO2 are reduced by delaying the formation of stable boundary layer conditions in the model to replicate Beijing's urban heat island. The simulated campaign period mean PM2.5 concentration range across the monitoring network (~ 15 μgm−3) is much lower than the measured range (~ 40 μgm−3). This is likely a consequence of insufficient PM2.5 emissions and spatial variability, neglect of explicit point sources, and assumption of a homogeneous background PM2.5 level. Sensitivity studies highlight that the use of explicit road source emissions, modified diurnal emission profiles, and inclusion of urban heat island effects permit closer agreement between simulated and measured NO2 concentrations. This work lays the foundations for future studies of human exposure to ambient air pollution across complex urban areas, with the APHH-China campaign measurements providing a valuable means of evaluating the impact of key processes on street-scale air quality. [ABSTRACT FROM AUTHOR]

With the aim of developing a forecasting system for the prediction of adverse meteorological conditions in the vicinity of complex terrain for aircraft landing at Hong Kong International Airport, the linearized, quasi‐empirical FLOWSTAR model has been configured to represent a series of eight landing events (2015–2017); half of these events reported significant wind shear and, for two, the landing attempt was aborted. Meteorological data used as input to the model have been derived from Hong Kong Observatory radiosonde measurements; these are the most reliable available despite being recorded at a location distant from the airport and at one or more hours before or after landing events. In general, the model predicts stronger wind shear for cases where adverse conditions have been reported. Analysis of the magnitude of wind shear generated as a result of wind veering and backing helps to quantify the importance of nonlinear flow features such as trapped lee waves. The model is able to represent strong downslope flows and recirculating flow regions (rotors) generated by the mountainous region located upwind of the airport. Comparisons of model predictions against LIDAR traces indicate that the model replicates wind shear for 50% of cases where it was recorded, although the location and magnitude of the wind shear usually differs between the modelled and measured datasets; the lack of agreement is likely to be because the input meteorological conditions are not wholly representative of the upstream conditions and the LIDAR trace does not exactly coincide with the aircraft trajectory. When airports are located in hilly terrain, near‐ground flow features such as wind shear and turbulence periodically cause disruption to aircraft movements. The FLOWSTAR model has been configured to represent favourable and unfavourable landings at Hong Kong International Airport; the model predicts high wind shear at some locations along the flight path (black dotted line). Quantitative analyses of wind shear generated as a result of wind veering and backing demonstrate the importance of flow features such as trapped lee waves. [ABSTRACT FROM AUTHOR]

High-resolution and accurate air quality concentration data are needed for detailed exposure and health effects calculations. Simulating such data numerically requires realistic treatment of both local emissions and background concentrations transported from further afield. This study combines regional and urban scale modelling and uses adjusted emission factors for NOx and NO2 and non-exhaust emission rates of PM10 and PM2.5 to reflect real-world emissions more accurately. Three modelling approaches have been used to simulate air quality in 2012 across London: a regional chemistry-climate model with 5 km horizontal resolution and gridded emissions; a local dispersion and chemistry model with explicit road source emissions; and a coupled regional-to-local modelling system combining the two individual models. The performance of each of the models is assessed against measurements from background and near-road sites in London in terms of annual averages, high hourly average concentrations and diurnal cycles. The regional model shows good agreement compared to measurements for background sites for these metrics but under-predicts concentrations of all pollutants except O3 at near-road sites due to the low resolution of input emissions and calculations. The urban model, using measured concentrations as regional background, and the coupled model show similarly good agreement for most pollutants at both background and near-road sites. Using the coupled model, it is estimated that 13 % of the area of London exceeded the EU limit value of 40 µg m−3 for annual average NO2 in 2012. [ABSTRACT FROM AUTHOR]