The influence of surface-atmosphere exchange processes on ozone levels

Transcription

1 The influence of surface-atmosphere exchange processes on ozone levels A. D Allura 1,3, R. De Maria 2, M. Clemente 2, F. Lollobrigida 2, S. Finardi 3, C. Silibello 3 & G. Brusasca 3 1 Dipartimento di Scienze dell'ambiente e del Territorio, Universita' di Milano-Bicocca, Italy 2 ARPA Piemonte, Italy 3 ARIANET srl, Italy Abstract A comprehensive modelling system taking into account emission, transport, dispersion, deposition and chemical transformation processes of gaseous pollutants has been used to simulate an ozone episode over the Piemonte Region in Northern Italy. A meteorological pre-processor (SURFPRO: SURrfaceatmosphere interface PROcessor) has been developed and applied in order to estimate the parameters used to define the status of the lower part of the atmosphere commonly called the Planetary Boundary Layer (PBL). The vertical exchanges between surface and lower atmospheric layers are defined estimating momentum, heat and moisture turbulent fluxes and PBL depth. The capability of the atmosphere to vertically redistribute the pollutants is represented by vertical diffusivities. The influence of different land use areas on diffusivities and other turbulent scaling parameters is shown confirming the importance of adequate descriptions of the surface cover. The effects of terrain slopes and shadow projection on incoming solar radiation and consequently on heat exchanges are also shown. Finally the good agreement between observed and predicted ozone concentration by the Eulerian photochemical model FARM (Flexible Air quality Regional Model) confirms the capability of the modelling system and the meteorological pre-processor to correctly describe chemical and physical processes that lead to the formation and the accumulation of ozone in Northern Italy. Keywords: Land-use, atmospheric turbulence, vertical diffusivity, photochemical models. é Heat Transfer VIII, B. Sund

2 266 Heat Transfer VIII 1 Introduction The Earth-atmosphere system receives energy input from solar radiation. The incoming radiant energy is channelled and stored into different sub-systems, converted exchanged and transported in different forms and modes. The atmospheric circulation is a way to transport energy between sites affected by different energy inputs (e.g. from equatorial regions to polar ones at global scale and between land and sea areas at local scale). The lower layers of the atmosphere are mainly influenced by the energy exchanges with the earth surface, which receives solar radiation and transfer energy back to the atmosphere both through radiation and heat fluxes. This energy exchanges are the main causes of local scale circulation (e.g. sea and mountain breezes) and of the vertical motions of the atmosphere. The direct influence of the surface is limited to a shallow layer known as the planetary boundary layer (PBL). This layer is characterized by turbulent motion generated by the bubbling-up of air parcels from the heated surface and by the surface frictional drag. The PBL turbulent nature determines the atmospheric power to mix and dilute substances emitted by the earth surface (Oke [1]). Air pollutant concentrations, their chemical composition, and their time and space variability are closely dependent on atmospheric boundary layer motion (wind and turbulence)and on underlying emissions. In this context a main topic studying air pollution is the correct understanding and parameterisation of boundary layer physic. The boundary layer flow is described by a set of nonlinear differential equations that can be solved numerically on a 3D mesh. These equations have to be supplemented by parameterisations capable to describe the sub-grid effects related to the energy and momentum exchanges between earth and atmosphere layers, e.g. according to Monin-Obukhov similarity theory (Stull [2]). Prognostic and diagnostic meteorological code have been developed during the last part of the last century to properly model micrometeorology and local scale atmospheric dynamics (Fisher et al. [3]). Meteorological models provide mean and turbulent variables fields, describing the dynamic and thermodynamic status of the atmosphere, that are used as input information by models describing chemical formation and dispersion of ozone and other pollutants (Seinfield [4]). It is well known that central and southern European urban areas are exposed to high ozone concentrations during summertime. The last European directive 2002/3/EC sets out requirements to assess short term episodes taking into account local circumstances, and draw up action plans to avoid health risk for population and vegetation. Nevertheless the approach based only on analysis of information provided by monitoring networks is limited by the spatial representativity of measurements and often insufficient to describe the air quality status on regional basis. This is especially true when complex topography and atmospheric circulation patterns come in to play, as it happens in most of the Italian territory. Today computational resources, improvements in input data availability (meteorological, air quality, emissions), scientific knowledge and a adequate experience on modelling simulations of photochemical pollution

3 Heat Transfer VIII 267 episodes (Silibello et al. [5]) permit one to well implement modelling integrated use of monitoring activities, emission inventories and atmospheric dispersion modeling as the main approach for air quality assessments. In this paper an integrated modelling system was applied to simulate a typical summer ozone episode over Piemonte Region in Northern Italy. A previous study was conducted in the same area but over a smaller urban scale domain during winter time (DeMaria et al. [6]). The model simulations showed that the right description of PBL morning growing trend strongly influenced the results. The studied area characteristics and the modelling system adopted are described in section 2, PBL behaviour and final results are disclosed in section 3. 2 Methodology The simulated episode lasted three days: July 19 th 21 st 1999 (Monday to Wednesday). This period represents a typical summer ozone episode characterized by exceedances of the Italian limits for hourly average concentrations of O 3 (200 µg/m 3 ). The investigated site is centred over Piemonte Region (Fig.1). The domain includes the western part of the Po Valley, closed by the Alpine range on the northern and western side and by the Apennine range on the southern side. The computational mesh is made by 53x69 cells in horizontal and 12 vertical levels, horizontal resolution is 4 Km. Owing to its peculiar topographic features the area is often affected by low winds and air stagnation events that can cause severe polluting episodes. Due to the limited effect of synoptic forcing the atmospheric flow features are frequently determined by meso and local scale phenomenon driven by the steep topographic slopes and differences in surface cover. 2.1 Input data Meteorological data available for pollution modelling purpose included wind and temperature analysed fields from the European Centre for Medium Range Weather Forecast (ECMWF), two radio-sounding and 69 surface stations. CORINE land cover database was used to reconstruct surface features. Emission data were provided by the INEMAR regional emission inventory, based on EU CORINAIR 1999 methodology and referring to year The data from the air quality monitoring network of Piedmont, Valle d Aosta, Liguria, Lombardia Regions, the city of Torino and the European Environment Information and Observation Network (EIONET) have been elaborated to prepare the initial and boundary conditions on the computational domain. 2.2 Integrated modelling The integrated modelling system is based on the regional emission inventory, the data from air quality and meteorological regional monitoring network, and a set of air pollution transport and dispersion models.

4 268 Heat Transfer VIII The MINERVE wind field model The meteorological input data (vertical profiles and near-ground wind and temperature measurements), were employed to reconstruct 3D wind and temperature fields on an hourly basis, using MINERVE diagnostic model (Desiato et al. [7]) The SURFPRO meteorological pre-processor Turbulence fields needed by the dispersion model (surface layer scaling parameters boundary layer height and diffusivities) were estimated by SURFPRO meteorological pre-processor (Finardi et al. [8]). At first the modelling system analyses land-use data providing season based information on surface physical features: albedo, soil moisture, surface roughness, leaf area index. From topography, season, latitude, cloud cover and solar constant, the incoming solar radiation Q (W m -2 ) is computed as gridded 2D field taking into account the presence of water bodies, terrain slopes and solar shading effects. The methods adopted by SURFPRO for the calculation of turbulence scale parameters over land and water surface are largely adapted from those implemented in U.S. EPA METPRO (Paine [9]). These methods consider the following approaches: Over land boundary layer: Sensible heat flux: energy balance method (Holtslag and van Ulden [10]); Surface friction velocity and Monin-Obukhov length: o unstable conditions: Holtslag and van Ulden [10] iterative scheme; o stable conditions: Venkatram [11], Weil and Brower [12] iterative schemes; Mixing height: o daytime convective: modified Carson [13] method; o daytime mechanical (neutral): Venkatram [11]; o nighttime conditions: Venkatram [11]; Convective velocity scale: from mixing height and sensible heat flux; PGT stability: Turner method. Over water boundary layer: Micrometeorological parameters: o profile method, using air-sea temperature difference Hanna et al. [14], and roughness length estimated from wind speed, using Hosker [15]; Mixing height: o neutral barotropic scaling relationship proposed by Blackadar and Tennekes [16]; PGT stability: assigned from Monin-Obukhov length Hanna et al. [14]. Different formulations are available for the calculation of diffusivities, in detail the Lange [17] scheme has been applied to estimate vertical diffusivities while Smagorinsky [18] scheme has been applied to estimate horizontal ones.

5 Heat Transfer VIII The FARM photochemical Eulerian model FARM (Flexible Air quality Regional Model) is a three-dimensional Eulerian model derived from STEM (Carmichael et al. [19]), that accounts for the transport, chemical conversion and deposition of atmospheric pollutants. FARM code produces a file containing 2D and 3D gas-phase time-dependent concentrations of selected species and two files, containing respectively timedependent dry and wet deposition fluxes. 3 Model results The heterogeneous landscape that characterises the computational domain allowed to set in evidence the effect of some topographic and land use features on the earth atmosphere interface fluxes and on the boundary layer turbulence MILAN 5000 TURIN Figure 1: Computational domain area. Depicted here are urban areas (in white), the squared area zoomed in Fig.2 and the dashed line which the cross sections in Fig.5 are referred to. The influence of terrain slope and of topography shadow projection on total radiation field is showed in Fig.2, referred to a mountain region located in the north-east area of the domain (see Fig.1). The effects of different land use on the sensible heat flux (H 0 ) field is depicted in Fig. 3/a. The presence of rice-field areas (see the circled region) decreases H 0 values due to the energy absorbed by water evaporation, that gives rise to large values of latent heat flux. Built-up and

6 270 Heat Transfer VIII urban areas account for opposite behaviour, that can be clearly observed for Turin and Milan urban areas. The time evolution of boundary layer turbulence is showed by the convective scale velocity (w * ) trends over different terrain types (Fig. 4). w * is an index of free convection movements due to heated Earth s surface during daytime (the magnitude of the vertical velocity fluctuations in thermals is of the same order of magnitude as w * ). The water bodies, not affected by diurnal heating cycle, give rise to very limited buoyancy effects depending on water - surface layer air temperature gradient, that show a daily cycle nearly opposite to that showed by land areas. On the other hand atmospheric turbulence is generated by surface friction drag, that gives rise to wind shear. The Monin- Obukhov length is an atmospheric stability parameter and an index of turbulence intensity. The Monin-Obukhov length can be seen as the height above the surface at which buoyant (w * ) and mechanical (u * ) factors are balanced. Above scale parameters are taken into account to compute the mixed layer height (fig.3/b). During summer daytime, the PBL can grow even over 2000 m before collapsing at sunset. During the whole length of the studied period persisting clear sky whether caused the strong convective forcing whose effects are described by model simulation results. Fig. 3/a-b show very similar patterns and point out the clear predominance of convective conditions Figure 2: Total radiation (W/m 2 )field referred to the north-east mountain area in the domain, 20/07/ :00 (squared area in Fig.1). The values of vertical diffusivities depend on values of turbulence scaling parameters, in particular depth of the layer affected by relevant mixing effects is determined by the value of the mixing height (Fig.5/a). Diffusivities, together with mean variables fields (wind, temperature and humidity) provide the photochemical model the necessary information to estimate the own volume in

7 Heat Transfer VIII 271 which pollutants are dispersed and the efficiency of turbulent diffusion. The effect of the reconstructed turbulence fields on the ozone concentrations is illustrated, in Fig. 5/b by a vertical cross section of ozone concentrations, that can be compared with the analogous cross section showed in Fig. 5/a for vertical diffusivity. a) b) MILAN MILAN 5000 TURIN TURIN Figure 3: a) H0 (W/m2)field, b) Mixed layer height (Hmix), 20/07/ :00. convective scale velocity Urban 0.00 Lake Rice-field Bare-rock Figure 4: 19-21/07/1999 hourly convective scale velocity w*(m/s) values for four different land use sits. Evaluating similarities and differences it has to be taken into account that concentration fields are heavily influenced by emission distribution, wind field and chemical reactions. Higher concentration areas correspond to the position of

8 272 Heat Transfer VIII Milan urban area. Weak wind conditions limited transport effects and allowed to highlight buoyancy dominated mixing effects. Model simulation results have been verified comparing computed ozone concentrations with measurements at different sites (see Fig. 6). Good agreement has been obtained in both urban and rural stations. Comparing computed and measured values, it has to be taken into account on one and the limited space representativity of measurements and, on the other hand, the limited space resolution of modelled concentration fields, representative of 4x4 km 2 grid cells. a) Hmix z+hmix b) Figure 5: Section along x for constant y (5035 Km), see dashed line in Fig.1, 20/07/ :00. a) Vertical diffusivities (m/s) where the thick line is Hmix above the ground level and the squared one is Hmix a.s.l. b) Ozone concentration (ppb).

9 Heat Transfer VIII Figure 6: Comparison between computed (continuous line) and measured (squares) O3 concentrations (ppb) at different sites.the left one Torino-Lingotto urban background station; the right Cogne (Valle D Aosta) background station in mountain area. 4 Conclusions An integrated modelling system has been tested in order to verify its capability to compute boundary layer parameters in the Piemonte Region and neighbouring areas, characterised by complex topography. The test concerned a period of three days, characterized by strong convective conditions, during which a large number of exceedances for O 3 occurred. The components of the system that have been tested are a meteorological pre-processor (SURFPRO), driven by a massconsistent wind model (MINERVE) and the land use data from CORINE Land Cover database, linked with an Eulerian three-dimensional photochemical dispersion model (FARM). Turbulent fields computed by SURFPRO highlight the influence of land use coverage and topographic features on turbulent parameters and local scale circulation within studied area. Moreover the analysis of diffusivities and ozone concentration patterns confirm the role of vertical diffusion on ozone distribution. Finally, the comparison between computed and observed O 3 concentrations at urban and rural sites evidence the capability of the modelling system to reproduce measured levels and indirectly confirm the correctness of assumptions used to reproduce surface-atmosphere exchange processes. Acknowledgements The authors wish to acknowledge Drs. S. Bovo, R. Pelosini, M. Muraro and S. Bande from Regional Weather Service for providing meteorological data and technical support regarding the meteorological characterisation of the simulated period, and Drs. G.Pession, G. Agnesod and M.Zublena from ARPA Valle d Aosta for providing data from the air quality monitoring network, and Drs. C. Contardi, A. Benedetti, G. Arduino, F. Sordi. and G. Truffo from Environmental Protection Regional Department for providing emission inventory. References [1] Oke T.R., Boundary Layer Climates, Routledge, 1987.

10 274 Heat Transfer VIII [2] Stull R.B., An introduction to Boundary Layer Meteorology (Chapter 9). Similarity Theory, Kluwer Academic Publishers, pp , [3] Fisher B.E.A., Erbrink J.J, Finardi S., Jeannet P., Joffre S., Morselli M.G., Pechinger U., Seibert P., Thomson D.J. (Editors), Harmonisation of the Pre-processing of Meteorological Data for Atmospheric Dispersion Models. COST Action 710 Final Report, EUR 18195, [4] Seinfield J.H.,Ozone air quality models a Critical Review, JAPCA, 38(5), pp , [5] Silibello C.,Calori G.,Brusisca G.,Catenacci G.,Finzi G., Application of photochemical grid model to Milan metropolitan area. Atmospheric Environment, 32(11), pp , [6] R.De Maria, M.Clemente, F.Lollobrigida, G.Calori, S.Finardi, G.Tinarelli, Air quality integrated assessment in tourin urban area using atmospheric transport and dispersion models. Proc. of the 4th Int. Conf. On Urban Air Quality, pp , [7] Desiato F., Finardi S., Brusasca G. and Morselli M.G., TRANSALP 1989 Experimental Campaign - Part I: Simulation of 3-D Flow with Diagnostic Wind Field Models, Atmospheric Environment, 32(7), pp , [8] Finardi S., Morselli M.G., Brusasca G., Tinarelli G., A 2D meteorological pre-processor for real-time 3D ATD Models, International Journal of Environmental Pollution, 8, pp , [9] Paine R.J. User's Guide to the CTDM Meteorological Preprocessor (METPRO) Program. US-EPA Report EPA/600/8-88/004, [10] Holtslag A.A.M. and van Ulden A.P. A simple scheme for daytime estimates of the surface fluxes from routine weather data. J. of Climate and Applied Meteorology 22, pp , [11] Venkatram A. Estimating the Monin-Obukhov length in the stable boundary layer for dispersion calculations. Boundary Layer Meteorology 19, pp , [12] Weil J.C., Brower R.P. Estimating convective boundary layer parameters for diffusion application. Draft report Environmental Center, Martin Marietta Corp. for Maryland Dept. of Natural Resources, Annapolis MD., [13] Carson D.J. The development of a dry inversion-capped convecticely unstable boundary layer. Q. J. R. Met. Soc. 99, pp , [14] Hanna S.R., Shulman L.L., Paine R.J., Pleim J.E., Baer M. Development and evaluation of the Offshore and Coastal Dispersion Model., JAPCA 35, pp , [15] Hosker R.P. A comparison of estimation procedures for overwater plume dispersion. Proc. of Symposium on Atmospheric Diffusion and Air Pollution, American Meteorological Society, Boston, MA, [16] Blackadar A.K. and Tennekes H. Asymptotic similarity in neutral barotropic planetary boundary layer. J. Atmos. Sci., 25, pp , 1968.

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