ORCID Profile
0000-0002-6935-7177
Current Organisation
University of Leeds
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Publisher: Elsevier BV
Date: 06-2012
Publisher: American Meteorological Society
Date: 05-2015
DOI: 10.1175/BAMS-D-12-00245.1
Abstract: 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 Clean Air for London (ClearfLo www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures. Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, 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, curbside, 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 the Summer Olympics of 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 that 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.
Publisher: Elsevier BV
Date: 06-2012
Publisher: Elsevier BV
Date: 06-2012
Publisher: Copernicus GmbH
Date: 12-06-2013
Abstract: Abstract. This study is conducted in the framework of the Air Quality Modelling Evaluation International Initiative (AQMEII) and aims at the operational evaluation of an ensemble of 12 regional-scale chemical transport models used to predict air quality over the North American (NA) and European (EU) continents for 2006. The modelled concentrations of ozone and CO, along with the meteorological fields of wind speed (WS) and direction (WD), temperature (T), and relative humidity (RH), are compared against high-quality in-flight measurements collected by instrumented commercial aircraft as part of the Measurements of OZone, water vapour, carbon monoxide and nitrogen oxides by Airbus In-service airCraft (MOZAIC) programme. The evaluation is carried out for five model domains positioned around four major airports in NA (Portland, Philadelphia, Atlanta, and Dallas) and one in Europe (Frankfurt), from the surface to 8.5 km. We compare mean vertical profiles of modelled and measured variables for all airports to compute error and variability statistics, perform analysis of altitudinal error correlation, and examine the seasonal error distribution for ozone, including an estimation of the bias introduced by the lateral boundary conditions (BCs). The results indicate that model performance is highly dependent on the variable, location, season, and height (e.g. surface, planetary boundary layer (PBL) or free troposphere) being analysed. While model performance for T is satisfactory at all sites (correlation coefficient in excess of 0.90 and fractional bias ≤ 0.01 K), WS is not replicated as well within the PBL (exhibiting a positive bias in the first 100 m and also underestimating observed variability), while above 1000 m, the model performance improves (correlation coefficient often above 0.9). The WD at NA airports is found to be biased in the PBL, primarily due to an overestimation of westerly winds. RH is modelled well within the PBL, but in the free troposphere large discrepancies among models are observed, especially in EU. CO mixing ratios show the largest range of modelled-to-observed standard deviations of all the examined species at all heights and for all airports. Correlation coefficients for CO are typically below 0.6 for all sites and heights, and large errors are present at all heights, particularly in the first 250 m. Model performance for ozone in the PBL is generally good, with both bias and error within 20%. Profiles of ozone mixing ratios depend strongly on surface processes, revealed by the sharp gradient in the first 2 km (10 to 20 ppb km−1). Modelled ozone in winter is biased low at all locations in the NA, primarily due to an underestimation of ozone from the BCs. Most of the model error in the PBL is due to surface processes (emissions, transport, photochemistry), while errors originating aloft appear to have relatively limited impact on model performance at the surface. Suggestions for future work include interpretation of the model-to-model variability and common sources of model bias, and linking CO and ozone bias to the bias in the meteorological fields. Based on the results from this study, we suggest possible in-depth, process-oriented and diagnostic investigations to be carried out next.
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Charles Chemel.