MarcoPolo. Monitoring and Assessment of Regional air quality in China using space Observations. Project Of Long-term sino-european co-operation

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1 Project no MarcoPolo Monitoring and Assessment of Regional air quality in China using space Observations. Project Of Long-term sino-european co-operation Type of funding scheme: Collaborative Project - Small or medium-scale focused research project Work programme topics addressed: SPA : Cooperation with third countries Deliverable D 5.3 (PU/Other) metropolitan areas of Shanghai, Version: 2.0 Due date of final deliverable: project month 38 Actual submission date: project month 39 Organisation name of lead contractor for this deliverable: Danish Meteorological Institute (DMI)

2 PAGE : 2 of 20 Document Status sheet Lead Author Contributing Authors Alexander Mahura (DMI), Mikhail Sofiev (FMI) Bjarne Amstrup, Roman Nuterman, Xiaohua Yang, Claus Petersen, Rostislav Kouznetsov Reviewed by Distribution list Project partners and EC Document Change Record Date Issue Pages affected Description 15 Jun Content & Chapter 1 Outline for content/ structure of report/ Introduction background 10 Dec Chapter 2 High resolution modelling for metropolitan areas with downscaling approach 15 Jan Chapter 3 Models setup and operational runs / service: Enviro-HIRLAM / SILAM; Setups for Shanghai (semi-oper), Beijing and Perl River Delta case study mode/ runs 25 Dec Chapter 3 Setup for Shanghai metropolitan area operational mode; Concluding remarks; References 25 Feb Chapter 3 Updating section 3.3. with the most recent output of the Enviro-HIRLAM operation run for downscaling to Shanghai metropolitan area 26 Feb Acknowledgements Final version of report

3 PAGE : 3 of 20 Table of Contents 1. Introduction background High resolution modelling for metropolitan areas with downscaling approach Models setup and operational runs / service Enviro-HIRLAM - HIgh Resolution Limited Area Model SILAM - System for Integrated modelling of Atmospheric composition Setup for Shanghai metropolitan area operational mode Setup for Beijing metropolitan area case study mode Setup for Perl River Delta case study mode Concluding remarks Acknowledgements References... 18

4 PAGE : 4 of Introduction background Urban air pollution is a serious problem in megacities and major industrial agglomerations of China. Therefore, air quality information is important for public. Due to strong economic growth in the past decades, air pollution became a serious problem in megacities and major industrial agglomerations of China. So, information on air quality in these urbanized areas is important for population. In particular, the metropolitan areas of Shanghai, are well known as main regions with serious air pollution issues. In this study the Enviro-HIRLAM (Environment - HIgh Resolution Limited Area Model) is applied for seamless/ on-line integrated meteorology and atmospheric composition forecasting for the Shanghai region (in operational mode) of China as well as other selected metropolitan areas (in research/ case study mode). The model setup includes the urban Building Effects Parameterization module, describing different types of urban districts with its own morphological and aerodynamical characteristics. The model is running in downscaling chain from regional-to-urban/city scales. 2. High resolution modelling for metropolitan areas with downscaling approach The most serious air pollution events occur in cities where there is a combination of high population density and air pollution. The pollutants can lead to serious human health problems. However, European-scale air quality models are not well suited for urban forecasts, as their grid-cell is typically of the order of 5-10 km and they generally lack detailed representation of urban effects. Due to constantly increasing supercomputer power modern nested numerical meteorological and air pollution models realize model nesting/down-scaling from the global to urban scale and approach the necessary horizontal and vertical resolutions to provide weather and air quality forecasts for urban scales. This will bring a strong support for continuous improvement of the forecast modelling systems for weather and air quality in Europe, and underline clear perspectives for the future multi-scale air quality core-downstream services for end-users. The downscaling chain for on-line/ semless integrated meteorology-chemistry-aerosols Enviro-HIRLAM model for weather and environmental applications is shown in Figure 2.1. The model can be run independently or as a part of the ensemble. The generated model output (for meteorology and chemistry/aerosols) for model runs at different resolutions can be used for assessment studies on environment and population when it is necessary.

5 MarcoPolo REF ISSUE DATE PAGE : D5.3 : 1.0 : 28 Feb 2017 : 5 of 20 Figure 2.1: Downscaling chain for on-line integrated meteorology-chemistry/aerosols EnviroHIRLAM (Environment High Resolution Limited Area Model) model for weather and environmental applications. Figure 2.2: Model domains (C15-C05-C02 with horizontal resolutions of km), ur-ban cells in domains, and Shanghai metropolitan area (Google-Earth) & /C15 370x226 (nlon x nlat) grids, 300 sec; C05 650x370 grids, 240 sec; and both C02 CTRL&URB runs: 496x334 grids, 90 sec/.

6 MarcoPolo REF ISSUE DATE PAGE : D5.3 : 1.0 : 28 Feb 2017 : 6 of 20 In the MarcoPolo project the model downscaling chain was setup for area covering almost the entire China (C15), East China (C05) and the Shanghai metropolitan area (C02; as the testbed) as shown in Figure 2.2. In the chain the horizontal resolution is improving from 15 to 2.5 km. At the beginning the selected model domains (C15-C05C02 with horizontal resolutions of km) were tested. The size of domains and time step are varying: C15 370x226 (nlon x nlat) grids, 300 sec; C05 650x370 grids, 240 sec; and C02 496x334 grids, 90 sec/. For the later domain, both the reference and urbanized runs were initially tested to show importance of urban effects for finer resolution runs and especially in the large metropolitan areas of China. Examples of variability of PM10 on a diurnal cycle for regional, sub-regional and urban/city scale runs are shown in Figure 2.3. Figure 2.3: Enviro-HIRLAM downscaling chain for operational runs over the enclosed Chinese domains (top plate C15 middle C05 bottom C02) from regional subregional urban/city scales (at km resolutions): example of modelled PM10 (ppb) concentration fields on 15 Jul 2010 at 06 (left column), 12 (middle), and 18 (right) UTCs. 3. Models setup and operational runs / service 3.1 Enviro-HIRLAM - HIgh Resolution Limited Area Model The Environment HIgh Resolution Limited Area Model (Enviro-HIRLAM) is developed as a fully online integrated numerical weather prediction (NWP) and atmospheric chemical transport (ACT) model for research and forecasting of joint meteorological, chemical and biological weather at multi-scales (latest model overview

7 PAGE : 7 of 20 publication by Baklanov et al., ). The components of the system such as gas-phase chemistry, emissions, deposition, aerosols are shown in Figure and the Structure of the modelling system is shown in Figure Note that emissions used will depend on the needs of the research project. Figure 3.1.1: Components (gas-phase chemistry, emissions, deposition, aerosols) of the Enviro- HIRLAM modelling system. The NWP part developed by HIRLAM consortium (Unden et al., 2002) is used for operational weather forecasting. The Enviro-components were mainly developed by DMI and NBI/UoC with partners from European countries (Korsholm, 2009; Baklanov et al., 2008). It consists of gas-phase chemistry CBMZ (Zaveri & Peters, 1999) and aerosol microphysics M7 (Vignati et al., 2004), which includes sulfate, mineral dust, sea-salt, black and organic carbon. There are modules of urbanization for land surface scheme, natural and anthropogenic emissions, nucleation, coagulation, condensation, dry and wet deposition, and sedimentation of aerosols. The Savijarvi radiation scheme (Savijärvi, 1990) has been improved to account explicitly for aerosol radiation interactions for 10 aerosol subtypes. The aerosol activation scheme (Abdul-Razzak & Ghan, 2000) was also implemented in STRACO condensation-convection scheme. The nucleation is dependent on aerosol properties and the ice-phase processes are reformulated in terms of classical

8 PAGE : 8 of 20 nucleation theory. Model Setup includes: period to be studied; boundaries of modeling domain; selected projection; horizontal & vertical resolutions; chemical & meteorological initial & boundary conditions; emissions (anthropogenic for EU domain - TNO-MACC for year 2009, biogenic (IS4FIRES by FMI), natural (interactive sea-salt Zakey et al. (2008) and mineral dust Zakey et al. (2006) emission modules); chemical & aerosol modules. Enviro-HIRLAM includes two-way feedbacks between air pollutants and meteorological processes. Different parts of Enviro-HIRLAM were evaluated versus ETEX-1 experiment, Chernobyl accident, urban case studies for several European metropolitan areas. Figure 3.1.2: Structure of the seamless/ on-line coupled integrated meteorology-chemistryaerosols Enviro-HIRLAM (Environment High Resolution Limited Area Model) for weather and atmospheric composition modelling.

9 PAGE : 9 of SILAM - System for Integrated modelling of Atmospheric composition The System for Integrated modelling of Atmospheric composition SILAM v.5.5 (Sofiev et al, 2015) is a Eulerian chemical transport model with the transport module based on advection scheme of Galperin (2000) refined by Sofiev et al (2015) and adaptive vertical diffusion algorithm of Sofiev (2002). Apart from the transport and physico-chemical cores described below, SILAM includes a set of supplementary tools including a meteorological pre-processor, input-output converters, grid transformers, interpolation routines, etc. The SILAM Eulerian transport core (Sofiev et al, 2015) is based on the coupled developments: refined advection scheme of Galperin (2000) and vertical diffusion algorithm of Sofiev (2002) and Kouznetsov & Sofiev, (2012). The vertical diffusivity parameterization follows the approach suggested by Genikhovich et al. (2004), as described in Sofiev et al, (2010). The procedure diagnoses all the similarity theory parameters using the profiles of the basic meteorological quantities: wind, temperature and humidity. Dry deposition parameterization follows the standard resistive analogy of Wesely (1989). Deposition velocity for aerosols are evaluated using the original (Kouznetsov & Sofiev, 2012) algorithm. Wet deposition parameterization is based on the scavenging coefficient after Sofiev (2000) for gas species and a new deposition scheme for aerosols following the generalised formulations of (Kouznetsov & Sofiev, 2012). The main gas-phase chemical mechanism is CBM-4. The heterogeneous scheme is an updated version of the DMAT model scheme (Sofiev, 2000). It incorporates the formations pathways of secondary inorganic aerosols. SILAM model for Asian domain has been set up on a 639x375-size lon-lat grid with a cell size of 0.125x0.125 degree, with a bounding box of E, 8-60N, covering India, China, Korean peninsula and Japan. Following Sofiev (2002), SILAM uses multi-vertical approach with the meteorology-resolving grid corresponding to the tropospheric part of the IFS vertical: hybrid levels from 69 to 137. The chemical transformations and vertical fluxes are computed on the basis of 12 thick staggered sigma-pressure layers, with the thickness increasing from about 25 m for the lowest layer to m in the free troposphere. Within the thick layers, the sub-grid information is used to evaluate the weighted averages of the high-resolution meteorological parameters and effective diffusion coefficients. Meteorological forcing is the ECMWF IFS operational forecasts taken from the 12UTC forecast of the previous day. Thus, the forecast length of the meteorology fields is from +12 hr till +132 hr. The meteo fields are taken from the operational dissemination procedure of ECMWF in lon-lat coordinates system with 0.1 resolution. Boundary conditions are taken from the global SILAM simulations. The hourly fields are imported; in-between, the linear interpolation is applied.

10 PAGE : 10 of 20 Emission fields are based on the PanHAM inventory for CO, SO2, NO2, NH3, PM2.5. and PM Emissions of biogenic VOCs and sea salt and wind-blown dust are computed in the corresponding SILAM dynamic modules. The bio-voc computations follow the Poupkou et al. (2010) model and provide isoprene and mono-terpene emissions (currently, only isoprene emission is used in the CB-4 mechanism). The sea salt emission parameterization is the original development generally based on Sofiev et al (2011) with refinements and spume formation mechanism. The original wind-blown dust emission model is used. Example of the SILAM model output is shown in Figure Figure Example of the output (on the global and China areas scales) generated by the System for Integrated modelling of Atmospheric composition (SILAM). 3.3 Setup for Shanghai metropolitan area operational mode In this study, modelling of atmospheric composition with downscaling ( km) from regional (15 km horizontal resolution; C15 domain) to sub-regional (5 km; C05 domain) to urban/city (2.5 km) scale had been realized for the Shanghai metropolitan area (C02 domain; in the operational mode), and Beijing and Pearl River Delta metropolitan areas (B02 and P02 domains, respectively; in the research mode with testing for winter and summer months of 2010). Geographical coverage of these domains is shown in Figure The seamless / on-line integrated meteorology-chemistry-aerosols multi-scale modelling system Enviro-HIRLAM was adapted for China. Preparatory steps included selection of model domains (for downscaling domain shown in figure) and model setup for China; testing of chemical CBM-Z and aerosol HAM-M7 schemes; assigning of land-use/cover data for selected domains; classifying urban districts and attributing urban related characteristics; develop pre-processing emission

11 PAGE : 11 of 20 data for model domains; making test-runs with downscaling for selected studies (meteorology and atmospheric composition with focus on aerosols) for China for Jan and Jul Figure 3.3.1: Geographical coverage of model domains Enviro-HIRLAM-C15-C05-C02 (&B02 for Beijing, P02 for Perl River Delta metropolitan areas) with horizontal resolutions of km, respectively. The pre-operational runs (with 24 h forecast length) for the Shanghai metropolitan areas for the downscaling chain (at DMI s CRAY-XT5 supercomputer) had started in Fal 2015, and then later the migration (including scripting update to new environment and recompilation of the code) of the entire system to new HPC CRAY-XT30 (Iceland) started mid-dec 2015 and finished by summer The operational runs at new HPC have extended forecast length up to 48 hours for all 3 subsequent by resolution model runs. In downscaling to urban/ city scale for the Shanghai metropolitan area as a test bed the simulations are important for monitoring of air quality and meteorology and for evaluation/ improvement of online coupled air pollution-meteorology model. Examples of operational downscaling forecasts are shown for meteorology such as air temperature at 2m, relative humidity at 2m, wind speed at 10m (Figures ) and aerosols such as PM2.5 (Figure 3.3.5). For convenience and easer interpretation of changes in the pollutant concentrations the meteorological fields can be also used (in addition the wind direction and mean sea level pressure are also included in plots.

12 PAGE : 12 of 20 Enviro-HIRLAM-C15 at 12 hour FL Enviro-HIRLAM-C05 at 12 hour FL Enviro-HIRLAM-C02 at 12 hour FL Enviro-HIRLAM-C02 at 24 hour FL Enviro-HIRLAM-C02 at 36 hour FL Enviro-HIRLAM-C02 at 48 hour FL Figure Example of the operational Enviro-HIRLAM-C02 model output for air temperature field at 12, 24, 36, and 48 hour forecast length for the Shanghai metropolitan area and surroundings.

13 MarcoPolo REF ISSUE DATE PAGE : D5.3 : 1.0 : 28 Feb 2017 : 13 of 20 Enviro-HIRLAM-C15 at 12 hour FL Enviro-HIRLAM-C05 at 12 hour FL Enviro-HIRLAM-C02 at 12 hour FL Enviro-HIRLAM-C02 at 24 hour FL Enviro-HIRLAM-C02 at 36 hour FL Enviro-HIRLAM-C02 at 48 hour FL Figure Example of the operational Enviro-HIRLAM-C02 model output for relative humidity field at 12, 24, 36, and 48 hour forecast length for the Shanghai metropolitan area and surroundings.

14 PAGE : 14 of 20 Enviro-HIRLAM-C15 at 12 hour FL Enviro-HIRLAM-C05 at 12 hour FL Enviro-HIRLAM-C02 at 12 hour FL Enviro-HIRLAM-C02 at 24 hour FL Enviro-HIRLAM-C02 at 36 hour FL Enviro-HIRLAM-C02 at 48 hour FL Figure Example of the operational Enviro-HIRLAM-C02 model output for wind speed at 12, 24, 36, and 48 hour forecast length for the Shanghai metropolitan area and surroundings.

15 PAGE : 15 of 20 Enviro-HIRLAM-C15 at 12 hour FL Enviro-HIRLAM-C05 at 12 hour FL Enviro-HIRLAM-C02 at 12 hour FL Enviro-HIRLAM-C02 at 24 hour FL Enviro-HIRLAM-C02 at 36 hour FL Enviro-HIRLAM-C02 at 48 hour FL Figure Example of the operational Enviro-HIRLAM-C02 model output for PM2.5 concentration field at 12, 24, 36, and 48 hour forecast length for the Shanghai metropolitan area and surroundings.

16 PAGE : 16 of Setup for Beijing metropolitan area case study mode The Enviro-HIRLAM model was also setup in a research mode (case study mode) for the Beijing metropolitan area with a numerical setup including 496 vs. 334 grid point along longitude vs. latitude, time step of 90 sec., horizontal resolution of deg /appx. 2.5 km/, with a domain placed within 22 deg south deg north deg west deg east in the rotated system of coordinates. The runs (for Jan and Jul 2010) in a research mode and their analysis showed a reliable quality of the forecasts for both meteorological and aerosols patterns. Examples (for PM2.5) of the model runs on a diurnal cycle are shown in Figure Figure Enviro-HIRLAM-B02 model output for PM2.5 concentration field for the Beijing metropolitan area and surroundings. 3.5 Setup for Perl River Delta case study mode Similarly to the Beijing MA, the Enviro-HIRLAM model was setup for the Perl River Delta metropolitan areas with a similar numerical setup (including number of grids along latitude vs. longitude, time step, horizontal resolution, etc.). The runs (for Jan and Jul 2010) in a research mode or a case study mode and their analysis showed reliable quality of the forecasts for both meteorological and aerosols patterns. Examples (for PM2.5) of the model runs on a diurnal cycle are shown in Figure First of all, reflecting geographical positioning of sources of emissions where the concentrations are generally higher and mostly these areas are heavily populated. Second, due to domination of maritime conditions in this geographical region, existing sea-breeze circulation, and corresponding precipitation patterns, the concentrations of pollutants had shown clear dependencies on these factors. This led to redistribution of pollution patterns, when the rapid reduction of concentrations was observed due to passage of the fronts, excessive removal due to wet deposition.

17 PAGE : 17 of 20 Figure Enviro-HIRLAM-P02 model output for PM2.5 concentration field for the Beijing metropolitan area and surroundings. 4. Concluding remarks Summarizing activities realized during the project by years, it should be mentioned that during 2014, the downscaling of online integrated meteorology-chemistry-aerosols Enviro-HIRLAM (Environment - HIgh Resolution Limited Area Model) model was used to study effects of Chinese megacities composed of different urban districts on formation and development of meteorological and chemical fields through chain of runs at km resolutions and taking into account urban effects. Comparing urbanized and reference runs it was found (Mahura et al., 2015) that the boundary layer height is increased during evening-late night hours for urban areas compared with rural areas; surface temperature increased - evening-night; wind speed increased - evening-late night; relative humidity decreased - evening-late night; air temperature increased, except noon; Urban Heat Island (UHI) urban effect is the strongest during evening-late night; Urban footprint can be extended far away from urban area; as for anthropogenic heat flux (AHF) differences between reference and urbanized runs for meteorological parameters became larger with increasing value of the flux. During 2015, the downscaling of the Enviro-HIRLAM model was adapted to study effects of Chinese megacities composed of different urban districts on formation and development of meteorological and chemical (with focus on aerosols) fields through chain of regional-subregional-urban/city runs ( km) and taking into account urban effects. Testing and semi-operational runs (with focus on Shanghai Metropolitan Area, MA) at HPC CRAY-XT5 showed good model performance for winter vs. summer months (Jan and Jul 2010) (Mahura et al., 2016). Similar setup was realized for the Beijing and Perl River Delta MAs. It was expected that operational Enviro-HIRLAM runs at CRAY-XC30 (new supercomputer at DMI) will provide atmospheric composition and meteorology (air temperature, relative humidity, wind characteristics, and cloud cover) forecast for Air Quality Service at for FP7 EU MarcoPolo & Panda projects. In late Fall 2015, corresponding steps were taken

18 PAGE : 18 of 20 for transferring (it took place until spring 2016) the system to new HPC and adapting corresponding scripts. During 2016, the Enviro-HIRLAM model adapted for China and selected megacities was applied for forecasting of weather and atmospheric composition (with focus on aerosols). The model system is running in downscaling chain from regional to urban/city scales at subsequent horizontal resolutions of km. The model setup includes also the urban Building Effects Parameterization module, describing different types of urban districts (industrial commercial, city center, high density and residential) with its own morphological and aerodynamical characteristics. The effects of urbanization are important for atmospheric transport, dispersion, deposition, and chemical transformations, in addition to better quality emission inventories for China and selected urban areas. Starting Fall 2016, the Enviro-HIRLAM system provides meteorology and air quality forecasts at regional-subregional-urban scales (China - East China Shanghai metropolitan area) (Mahura et al., 2017). The system is running twice per day at 00 and 12 UTC in a subsequent mode (e.g. output generated from the outer run is used for inner run) with the forecast length up to 48 hours. The system is also run at 06 and 18 UTCs, but at the shorter forecast length of 9 hours and these runs are used in order to keep the assimilation of meteorological data at mid-term for smoother and more continuous fields of meteorological and aerosol patterns. In particular, such forecasting is important for metropolitan areas, where formation and development of meteorological and chemical/aerosol patterns are especially complex. It also provides information for evaluation impact on selected megacities of China as well as for investigation relationship between air pollution and meteorology. 5. Acknowledgements Thanks to DMI Computer Department for technical support and advice. Thanks to DMI colleagues for useful comments. The CRAY-XT5/XC-30 supercomputing facilities, ECMWF boundary conditions were used in this study. The research is supported by the funding from the FP7 EU MarcoPolo project. 5. References Abdul-Razzak, H., and S. J. Ghan (2000), A parameterization of aerosol activation: 2. Multiple aerosol types, J. Geophys. Res., 105(D5), , doi: /1999jd Allen, L, Lindberg, F & Grimmond, S (2011), 'Global to city scale model for anthropogenic heat flux: Model and variability' Int J of Clim, vol 31, no. 13, pp. Baklanov A., A. Mahura, R. Sokhi (Eds) (2010): Integrated Systems of Meso-Meteorological and Chemical Transport Models, Springer, 192p. Baklanov A., S. Grimmond, A. Mahura, M. Athanassiadou (Eds) (2009): Meteorological and Air Quality Models for Urban Areas. Springer, 185p. Baklanov A., U. Korsholm, A. Mahura, C. Petersen, A. Gross, (2008): Enviro-HIRLAM: on-line coupled modelling of urban meteorology & air pollution. Adv. Sci. Res., 2,

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