WP-I1: Urban air quality module

Goals of the project:

Air pollution and heat stress are the two most important environmental issues for people living in cities, leading to an increased burden of disease and ultimately premature death. The World Health Organization (WHO) estimates that air pollution alone is responsible for seven million premature deaths worldwide each year. Air quality policy framework and consequent mitigation strategies play a vital role in improving air quality of urban areas.

Hence, assessment of the current local air pollution mitigation measures is one of the central applications of PALM-4U, which receives a large amount of scientific and political attention. Chemistry modeling is in many aspects more complex than urban meteorology modeling, as the chemistry depends on more variables (including highly fluctuating emission forcing in space and time) and processes. Evaluation is also more challenging, as chemistry processes are less well understood than physical fundamentals (that is, the skill of meteorological models is better than for chemistry). Relevant air pollutants are nitrogen oxides (NOx), ozone (O3), anthropogenic and biogenic organic compounds, as well as aerosols, which are complex mixtures of coarse (< 10 μm), fine (< 2.5 μm) and ultrafine (< 0.1 μm) primary and secondary particulate matters. Aerosol composition (e.g. black carbon) and water uptake are the key variables for future investigations into the urban radiation budget and cloud/rain formation.

In the first phase of MOSAIK, PALM has been extended by an atmospheric gas phase chemistry module to allow air quality related studies with PALM-4U. Although large-eddy simulation (LES) studies with chemistry were carried out already in the past, PALM-4U is the first LES model that can simulate chemical transformation, advection and deposition of air pollutants for larger and realistically shaped urban areas (see Figure 1 and Figure 2 below). The implementation based on the KPP preprocessor allows for the flexible generation and selection of gas phase chemistry mechanisms (see Figure 3). Furthermore, dry deposition processes and modules for photolysis and emission input have been implemented in PALM-4U within MOSAIK phase I. The goal within MOSAIK II is to improve urban chemistry module in terms of biogenic emissions, enhanced aerosol description including ultra fine particles, pollen emissions and transport, and advanced emissions, and wet deposition of pollutants.

Figure 1: Preliminary results of the chemistry module for an LES of a diurnal cycle for an area around Ernst-Reuter-Platz in Berlin, Germany. Solely traffic emissions were considered which were parameterised depending on the street type classes from 'OpenStreetMap'. Shown are exemplary instantaneous xy-cross sections of (a) NO2 and (d) O3 at 1330 UTC as well as yz-sections (b)–(c) NO2 and (e)–(f) O3 during nighttime (0530 UTC, (b) and (e)) and in the afternoon (1330 UTC, (c) and (f)), together with vertical velocity as contour lines. The line a’ in (a) indicates the location where the yz-sections were taken (Figure taken from Maronga et al., 2019).

Figure 2: Horizontal cross-sections of near surface NO2 concentration on 21 July 2013, at 1700 CET, for the area around Ernst-Reuter-Platz, Berlin, Germany, based on three different chemical mechanisms: PHSTAT (left), SMOG (center), CBM4 (right).

Figure 3: CPU time requirement for a PALM run using the different provided mechanisms (listed in the corresponding colors below the graph) relative to a meteorology only run. The bars in the front show the increase time if only the transport of the chemical compounds is considered.

Tasks of the project:

WP-I1.1: Description of BVOC-related processes

WP-I1.2: Description of pollen emissions, atmospheric transport and deposition

WP-I1.3: Explore the feasibility of using PALM-4U output to quantify urban greenhouse gas budgets

WP-I1.4: Extend the emissions description, options and handling for use in idealised studies

WP-I1.5 Enhanced aerosol description for PALM-4U

WP-I1.6: Wet deposition

WP-I1.7: Model evaluation and code optimisation

WP-I1.8: Support to new PALM-4U users

Structure of the project:

This WP is conducted by KIT and FU Berlin in close collaboration with LUH

Deliverables:

DL1: BVOC emissions, transport and chemical mechanism implemented

DL2: Including default emissions from residential heating and default point source information

DL3: Pollen emission, transport and deposition implemented

DL4: UFPs size fractions and coagulation loss functions in PALM-4U

DL5: Workflow for inverse modelling of CO2 emissions

DL6: Wet deposition in PALM-4U

DL7: Optimisation and evaluation of new components‘ codes

Progress so far:

We prepared a contribution to the publication describing the implementation of the chemistry model in the PALM model system 6.0 (Khan, et al., 2021). A case study has also been included comparing four different chemical mechanisms.

Figure 4: Modelled concentrations of near-surface nitrogen dioxide (a) and ozone (b) at 09:00 CEST on 17th July 2017 for a 6.7 km x 6.7 km sub-area of ​​Berlin around Ernst-Reuter-Platz. The simulation was carried out with the chemical mechanism CBM4 and a horizontal grid width of 10 m.

The development of a biogenic emission model is in progress (WP-I1.1). The code development is completed, however, the model code needs to be ported to the recently introduced data structure that provides a two stage interface for all current and future emission modules. The rationale behind the new code structure remains convenience, code elegance and computational efficiency. A publication is in preparation.

The architecture for the development of a new module for the introduction of volume sources from different emission sectors or modes such as domestic heating, aviation and biogenic emissions is presented in Figure 5 (WP-I1.4). So far only emissions have been implemented as surface fluxes.

Figure 5:Architecture of the new module for the generalised volume sources, e.g. here for traffic emissions or biogenic emissions.

The development of a graphics-based algorithm for chimney position location (see example in Figure 6) is based on the geometric centre of each connected building according to an approach following Struschka and Li (2019, internal report in the line of a subcontract in MOSAIK phase 1) (WP-I1.4).

Figure 6:Exemplary representation of the chimney position location (orange) on the respective buildings (yellow)

We cooperate and exchange data with WP-I2 (TUB) on dynamic traffic-related emissions for the pollutant dispersion calculation in PALM-4U (WP-I1.4)

A Python based dynamic driver has been developed to provide realistic mesoscale forcings from WRF output data to PALM-4U. A journal paper, Lin et al.,(2020), has been accepted for publication in Geoscientific Model Development (WP-I1.7).

With the available nco-cdo based tool, output from WRF-Chem will be used to provide mesoscale chemistry forcing for PALM-4U chemistry simulations (WP-I1.7).

A publication is in preparation including a comprehensive evaluation of the chemistry model in PALM-4U. For this purpose, nested model runs for different domains were set up (see one example in Figure 7), which are to be evaluated on the basis of available measurement data (WP-I1.7).

Figure 7:Nested PALM simulation. Parent domain (left panel, grid resolution of 10m) and child domain (right panel, grid resolution of 1m)

Technical support and advice for the chemistry model in relation to PALM-4U evaluation runs is being provided as and when required (WP-I1.8).

Chemistry model training and support is provided in PALM Seminar in February and September 2020, and also in February 2021.

References:

Barbaro, E., Krol, M.C., Vilá-Guerau de Arellano, J., 2015 Numerical simulation of the interaction between ammonium nitrate aerosol and convective boundary-layer dynamics, Atmo. Env., 105, 202-211, https://doi.org/10.1016/j.atmosenv.2015.01.048.

Bergström, R., Hallquist, M., Simpson, D., Wildt, J., Mentel, T.F., 2014, Biotic stress: A significant contributor to organic aerosol in Europe? Atmos. Chem. Phys., 14, 13643-13660.

D'Amato, G., Cecchi, L., Bonini, S., Nunes, C., Annesi-Maesano, I., Behrendt, H., Liccardi, G., Popov, T., Van Cauwenberge, P., 2007, Allergenic pollen and pollen allergy in Europe, Allergy, 62, 976-990.

Emberlin, J., Smith, M., Close, R., Adams-Groom, B., 2007, Changes in the pollen seasons of the early flowering trees Alnus spp. and Corylus spp. in Worcester, United Kingdom, 1996-2005. Int. J. Biometeorol., 51, 181-191.

Ghirardo, A., Xie, J., Zheng, X., Wang, Y., Grote, R., Block, K., Wildt, J., Mentel, T., Kiendler-Scharr, A., Hallquist, M., Butterbach-Bahl, K., Schnitzler, J.P. 2016, Urban stress-induced biogenic VOC emissions and SOA-forming potentials in Beijing, Atmos. Chem. Phys., 16, 2901-2920.

Grote, R., Niinemets, Ü., 2008, Modeling volatile isoprenoid emissions - A story with split ends, Plant Biol. 10, 8-28.

Grote, R., Monson, R., Niinemets, Ü., 2013, Leaf-level Models of Constitutive and Stress-Driven Volatile Organic Compound Emissions, In: Niinemets, Ü., Monson, R.K. (Eds.), Biology, Controls and Models of Tree Volatile Organic Compound Emission, Springer Netherlands, 315-355.

Jeon, W., Choi, Y., Roy, A., Pan, S., Price, D., Hwang, M.-K., Kim, K.R., Oh, I., 2018, Investigation of Primary Factors Affecting the Variation of Modeled Oak Pollen Concentrations: A Case Study for Southeast Texas in 2010, Asia-Pacific Journal of Atmospheric Sciences 54, 33-41.

Khan, B., Banzhaf, S., Chan, E. C., Forkel, R., Kanani-Sühring, F., Ketelsen, K., Kurppa, M., Maronga, B., Mauder, M., Raasch, S., Russo, E., Schaap, M., Sühring, M., 2021, Development of an atmospheric chemistry model coupled to the PALM model system 6.0: implementation and first applications, Geoscientific Model Development, 1-34., 14(2), 1171-1193, https://doi.org/10.5194/gmd-14-1171-2021, 2021.

Lenshow, D.H., Gurarie, D:, Patton , E.G., 2016, Modeling the diurnal cycle of conserved and reactive species in the convective boundary layer using SOMCRUS. Geosci. Model Dev., 9, 979-996, https://doi.org/10.5194/gmd-9-979-2016.

Lin, D., Khan, B., Katurji, M., Bird, L., Faria, R., Revell, L. E., 2020, WRF4PALM v1. 0: A Mesoscale Dynamical Driver for the Microscale PALM Model System 6.0, Geoscientific Model Development Discussions, 1-37.

Linkosalo, T., Ranta, H., Oksanen, A., Siljamo, P., Luomajoki, A., Kukkonen, J., Sofiev, M., 2010, A double-threshold temperature sum model for predicting the flowering duration and relative intensity of Betula pendula and B. pubescens, Agric. Forest Meteorol. 150, 1579-1584.

Maronga, B., Gross, G., Raasch, S., Banzhaf, S., Forkel, R., Heldens, W., Kanani-Sühring, F., Matzarakis, A., Mauder, M., Pavlik, D., Pfafferott, J., Schubert, S., Seckmeyer, G., Sieker, H., Winderlich, K., 2018, Development of a new urban climate model based on the model PALM – Project overview, planned work, and first achievements, Meteorol. Z., 28, 121–138, https://doi.org/10.1127/metz/2019/0909.

Monson, R.K., Holland, E.A., 2001, Biospheric trace gas fluxes and their control over tropospheric chemistry, Annual Review of Ecology and Systematics 32, 547-576.

Tseng, Y.-T., Kawashima, S., Kobayashi, S., Takeuchi, S., Nakamura, K.,2018, Algorithm for forecasting the total amount of airborne birch pollen from meteorological conditions of previous years, Agric. Forest Meteorol. 249, 35-43.

Zink, K., Vogel, H., Vogel, B., Magyar, D., Kottmeier, c., 2012, Modeling the dispersion of Am-brosia artemisiifolia L. pollen with the model system COSMO-ART Int. J. Biometeorol. 56, 669-680.

Contacts:

matthias.mauder[at]kit.edu,

renate.forkel[at]kit.edu,

sabine.banzhaf[at]met.fu-berlin.de

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