European WRF-Chem User Workshop 2019
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European WRF-Chem User Workshop 2019
7 - 8 May 2019
Room D0.30, Pettenkoferstr. 12, 80336 Munich, Germany
Organising committee:
Christoph Knote (LMU Munich), Tim Butler (IASS Potsdam), Hüseyin Toros (ITU Istanbul),
Renate Forkel (KIT Garmisch-Partenkirchen)
last updated May 6, 2019European WRF-Chem User Workshop 2019
Tuesday, May 7 Wednesday, May 8
9 00 Coffee and registration 9 00 Haselsteiner, Magdalena Driving WRF-Chem with meteorological data from the AROME model
20 Welcome 20 Hilboll, Andreas To nudge or not to nudge: a WRF-Chem perspective
40 Abdi, Amir Hossein An Investigation on mesoscale variability of atmospheric methane over Africa using WRF-Chem 40 Thiam, Mamadou Lamine Study of the impact of temporal variability of surface wind downstream of mountains on PM10
concentration in West Africa
10 00 Botia, Santiago Atmospheric transport of greenhouse gases in the Amazon region 10 00 Coffee
20 Galkowski, Michal Simulations of greenhouse gases with WRF-GHG for the CoMet 1.0 campaign 20 Silver, Ben Using WRF-Chem to Examine the Drivers of Recent Trends in Chinese Air Quality
40 Marshall, Julia The development of an Ensemble Kalman Filter regional inversion system with WRF-Chem to 40 Lupascu, Aurelia Unraveling the impact of different sources of NOx precursors to O3 concentrations during a heat
constrain European carbon dioxide fluxes wave period
11 00 Coffee 11 00 Mogno, Caterina Quantifying the role of the transport sector on observed variations of PM2.5 over the National
Capital Region of Delhi, India.
20 Zhao, Xinxu Analysis for Total Column CO2 and CH4 combining WRF-GHG Model with Differential Column 20 Karlický, Jan The impact of urban emission reduction on meteorological variables during summer and winter
Methodology (DCM) episodes
40 Eckl, Maximilian Quantifying nitrous oxide emissions from agriculture in the mid-west of the U.S. 40 Sibiya, Behki Modelling the effect of traffic emission on urban air quality in different scenarios: A case of
Berlin-Brandenburg region
12 00 Pillai, Dhanyalekshmi Towards designing a high-resolution atmospheric CO2 modeling system over India using WRF- 12 00 Coffee
Chem
20 20
Open discussions
40 40
13 00 Lunch 13 00 Adjourn
20
40
14 00 Kiely, Laura New Constraint on particulate emissions from Indonesian peat fires 14 00 Excursion to the Meteorological Institute
20 Ferrari, Francesco The role of the natural aerosol on the flash-floods in the Liguria region
40 Baró, Rocío Simulating the 2011 Grímsvötn eruption with a new volcanic module implementation in WRF- Sessions
Chem
15 00 Ünal, Zeynep Feriha A Case Study for Dust Transportation over Istanbul GHG Greenhouse gases
20 Morichetti, Mauro The influence of biogenic emissions on trace gases: MEGAN sensitivity study NATURAL Natural emissions
40 AQ FCST Air quality studies and forecasting
Coffee
16 00 MET/TECH Meteorology and technical issues
20 Marelle, Louis Simulating Arctic boundary layer ozone depletion events in WRF-Chem 4.0 ANTHRO Anthropogenic emissions
40 Thorp, Tom Evaluation of Siberian tropospheric ozone using satellite, surface measurements and a regional
model
17 00 Dinç, Umur Air Pollution Forecasting with Machine Learning by using WRF-Chem Model Output Room D0.30, LMU Munich, Pettenkoferstr. 12, 80336 Munich, Germany
20 Visser, Auke OMI-derived European NOx emissions in WRF-Chem: effects on summertime surface ozone https://wrfchem2019.meteo.physik.uni-muenchen.de
40 Garcia-Reynoso, Jose Agustin Evaluation of WRF-chem-urban in Mexico Megacity
19 30 DinnerUseful information
Transportation
Public transport: https://www.mvv-muenchen.de
Wireless internet
Option 1: BayernWLAN
Free, open, unsecured WLAN offered by the Bavarian State. SSID: @BayernWLAN
Option 2: eduroam
Available for those affiliated with a university. Get your certificate and username before the
workshop at your home institution. SSID: eduroam
Option 3: WRF-Chem 2019 conference WLAN
European WRF-Chem User Workshop 2019Presenter information
Each presenter is allocated a 20 minute time slot, out of which 5 minutes should be allowed for
questions and discussion. A laptop will be provided with Microsoft Powerpoint (Windows) and
Acrobat Reader installed, so we can accomodate presentations in .pdf, .ppt, .pptx formats, as
well as any self-contained formation like web pages. Internet access from the presentation laptop
is likely, but not guaranteed. Please upload your presentation before your session starts, either
by bringing it on a USB stick or uploading it to https://owncloud.physik.uni-muenchen.
de/index.php/s/RSDkHYbAstWoM2S.
Abstracts
Tuesday, 09:40: An Investigation on mesoscale variability of atmo-
spheric methane over Africa using WRF-Chem (WITHDRAWN)
Abdi, Amir Hossein1 , Marshall, Julia1 , Gerbig, Christoph1
1
Max Planck Institute for Biogeochemistry
Africa, as a significant source of methane (CH4 ), has a remarkable contribution in the global
methane budget. For better understanding the mesoscale variability of atmospheric methane
over Africa, a high-resolution Eulerian model, Weather Research and Forecasting model with
chemistry supporting passive tracer transport of methane (WRF-Chem), is run over Africa
with 30 hours spin up time from January to December, 2012 for two domains: a parent domain
covering the whole continent on 50 km horizontal resolution , and the nested domain which
consists of a part of central African countries on 10 km resolution. Emissions Database for
Global Atmospheric Research (EDGAR v4.3.2) and Global Fire Assimilation System (GFAS
v1.2) are used as anthropogenic and biomass burning emission inventories respectively. Fur-
thermore, a global wetland methane emissions and uncertainty dataset (WetCHARTs v1.0),
Sanderson model for termite, and Ridgewell et al. model for soil uptake are applied to calcu-
late biospheric CH4 fluxes. The results are compared to Greenhouse Gases Observing Satellite
(GOSAT) retrievals in order to assess the robustness of the simulation.
Tuesday, 10:00: Atmospheric transport of greenhouse gases in the
Amazon region
Botia, Santiago1 , Gerbig, Christoph1 , Marshall, Julia1 , Lavric, Jost1
1
Max Planck Institute for Biogeochemistry
At the Amazon Tall Tower Observatory (ATTO) a 6-year record of concentrations of methane,
carbon dioxide and carbon monoxide provides a good basis for validating atmospheric trans-
port at different temporal scales. Using WRF-GHG and emission inventories such as GFED4
for biomass burning, WetCHARTs for wetland emissions, the online VPRM model for vegeta-
tion and EDGARv4.2 for anthropogenic emissions, we performed a 15-day simulation during
September 2014. The objective of this simulation is twofold: 1. We want to assess the contribu-
tion of different tracers to the observed concentrations at ATTO but also 2. to analyze the effect
of terrain heterogeneity, mainly during nighttime in tracer transport. For these purposes we
used a one-way-nested 4-domain set up, reaching a resolution of 1km in the innermost domain.
European WRF-Chem User Workshop 2019Our results suggest a good agreement with observations, and also an interesting nighttime
accumulation of tracers in the lower parts of the terrain adjacent to ATTO.
Tuesday, 10:20: Simulations of greenhouse gases with WRF-GHG for
the CoMet 1.0 campaign
Galkowski, Michal1 , Marshall, Julia1 , Gerbig, Christoph1 , Koch, Frank-Thomas1 , Chen,
Jinxuan1 , Baum, Stephan1
1
Max Planck Institute for Biogeochemistry, Jena, Germany
During May and June 2018, an intensive campaign took place (CoMet: Carbon dioxide and
Methane mission) that made atmospheric measurements of greenhouse gases over Europe.
CoMet aimed at characterising the distribution of CH4 and CO2 over significant regional sources
with the use of a fleet of research aircraft, equipped in state-of-the-art in-situ and remote sensing
instruments. Most detailed measurements were performed over the Upper Silesian Coal Basin
(USCB), one of the strongest methane-emitting regions, responsible for emissions between 0.4
Tg and 1.5 Tg CH4 annually.
In order to link the observations to emission sources, high-resolution simulations with WRF-
GHG (10 km x10 km Europe + nested 2 km x 2 km domain over USCB), driven by short-term
meteorological forecasts from the ECMWF IFS model and chemical forecasts from CAMS
MACC for initial and lateral tracer boundary conditions were performed. Biogenic fluxes of
CO2 were calculated online using the VPRM model driven by MODIS indices. Anthropogenic
emissions over Europe were taken from the database of TNO (available at 7 km x 7 km resolution
for area sources, with point sources stored separately), and from the internal emission database
of CoMet.
Detailed information about the location and strength of the most important point sources
within the USCB allowed for tagged tracer simulations for selected sources to be performed
by expanding the tracer list available in the WRF-Chem GHG module. The results of source
partitioning of the predicted signals are presented and compared against observations performed
during the campaign.
Tuesday, 10:40: The development of an Ensemble Kalman Filter re-
gional inversion system with WRF-Chem to constrain European car-
bon dioxide fluxes
Marshall, Julia1 , Gerbig, Christoph1 , Gałkowski, Michał1 , Koch, Frank-Thomas1
1
Max Planck Institute for Biogeochemistry
Atmospheric measurements of carbon dioxide (CO2 ) can be used, together with a transport
model and inverse statistical methods, to constrain the fluxes of CO2 at the surface. This is
known as “top-down” modeling or flux inversion. This presentation describes the implemen-
tation of such a method using the WRF-Chem model, making use of tools from the Data
Assimilation Research Testbed (DART). An ensemble of flux realizations, spanning the range
of uncertainty in our prior flux estimate, is advected by WRF-Chem, treating them as a large
array of passive tracers. The mixing ratios produced by these fluxes are confronted by in-situ
European WRF-Chem User Workshop 2019measurements, and an Ensemble Kalman Filter is used to select those flux realizations that are
most consistent with the available measurements. The model is tested for 2015, and the results
are compared to previous semi-operational inversions using a Lagrangian model for consistency.
The application to satellite measurements, which is not easily feasible with a Lagrangian ap-
proach, is explored. The impact of transport uncertainty on the ensemble is tested by varying
physics options in WRF is explored.
Tuesday, 11:20: Analysis for Total Column CO2 and CH4 combining
WRF-GHG Model with Differential Column Methodology (DCM)
Zhao, Xinxu1 , Marshall, Julia2 , Hachinger, Stephan3 , Gerbig, Christoph2 , Chen, Jia1
1
Electrical and Computer Engineering, Technische Unversität München, 80333 Munich, Germany
2
Max Plank Institute of Biogeochemistry, 07745 Jena, Germany
3
Leibniz Supercomputering Center (Leibniz-Rechenzenturm, LRZ) of Bavarian Academy of Sciences and Hu-
manities, Bolzmannstr. 1, 85748 Garching, Germany
The share of greenhouse gas (GHG) released from urban areas has continued increasing since
the pre-industrial era. Quantitative methods for accurately assessing the amount of urban GHG
emissions and identifying the respective sources have thus become an essential subject of study.
The Weather Research and Forecasting model (WRF) coupled with GHG modules (WRF-GHG)
developed for mesoscale atmospheric GHG transport, can predict column-averaged abundances
of CO2 and CH4 (XCO2 and XCH4 ) and calculate emission fluxes for certain sources. To assess
the precision of WRF- GHG and provide insights on how to detect and understand sources of
GHGs within urban areas, the uptake and emission of atmospheric GHGs in Berlin is simulated
using WRF-GHG at a high spatial resolution of 1 km, with an appropriate workflow set-up [1].
The simulated wind and concentration fields were compared with the measurements from a
campaign performed around Berlin in 2014 [2]. The simulated wind fields and XCO2 mostly
agree well with the measurements. On the contrary, a bias of around 2.7% in the simulated
XCH4 is found, caused by relatively high initialization values for the background concentra-
tion field. Differential column methodology (DCM) [3], which is independent on such biases,
e.g., caused by initialization conditions, is then highlighting different contributions to simulated
CO2 and CH4 concentrations. The diurnal variation of concentration components from different
emission tracers is discussed. The biogenic component plays a pivotal role in the variations of
XCO2 , while the impact from anthropogenic emission sources is weaker. DCM helps to high-
light that the XCO2 signal within the inner Berlin urban area is dominated by anthropogenic
emissions. The XCH4 enhancement is highly dependent on human activities.
We conclude that WRF-GHG can be a suitable mesoscale model for precise GHG transport
analysis in urban areas. DCM is an effective method, not only for comparing models to ob-
servations independently of biases caused, e.g., by initial conditions, but also for detecting and
understanding sources of GHG emissions quantitatively in urban areas. Now we are using
WRF-GHG for Munich and plan to compare with the most up-to-date measurement data, such
that local sources (e.g., Oktoberfest) and the related transport features can be quantitatively
studied. In future work, more urban cases are suggested for running WRF-GHG, and the
mesoscale WRF-GHG framework can also be combined with micro-scale atmospheric transport
models such that essential details of transport patterns and emission sources are studied.
[1] Zhao, X., Marshall, J., Hachinger, S., Gerbig, C., and Chen, J.: Analysis of Total Column CO2 and CH4
European WRF-Chem User Workshop 2019Measurements in Berlin with WRF-GHG, Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acp-2018-
1116, in review, 2019.
[2] Hase, F., Frey, M., Blumenstock, T., Groß, J., Kiel, M., Kohlhepp, R., Mengistu Tsidu, G., Schäfer, K., Sha,
M., and Orphal, J.: Application of portable FTIR spectrometers for detecting greenhouse gas emissions of the
major city Berlin, Atmospheric Measurement Techniques, 8, 3059–3068, https://doi.org/10.5194/amt-8-3059-
2015, 2015.
[3] Chen, J., Viatte, C., Hedelius, J. K., Jones, T., Franklin, J. E., Parker, H., Gottlieb, E. W., Wennberg, P. O.,
Dubey, M. K., and Wofsy, S. C.:Differential column measurements using compact solar-tracking spectrometers,
Atmospheric Chemistry and Physics, 16, 8479–8498, https://doi.org/10.5194/acp-16-8479-2016, 2016.
Tuesday, 11:40: Quantifying nitrous oxide emissions from agriculture
in the mid-west of the U.S.
Eckl, Maximilian1 , Roiger, Anke1 , Kostinek, Julian1 , Huntrieser, Heidi1 , Knote, Christoph2 ,
Barley, Zachary3 , Davis, Kenneth3
1
German Aerospace Center (DLR), Institute of Atmospheric Physics, 82234 Oberpfaffenhofen, Germany
2
Ludwig-Maximilians-University (LMU), Meteorological Institute, 80333 Munich, Germany
3
The Pennsylvania State University, Department of Meteorology and Atmospheric Science, University Park,
PA 16802, USA
Atmospheric nitrous oxide (N2 O) is, after carbon dioxide and methane, the third most im-
portant long-lived anthropogenic greenhouse gas in terms of radiative forcing. Anthropogenic
emissions of N2 O, mainly from agricultural activity, contribute considerably to the rising trend
in atmospheric concentrations. Attempts to quantify and constrain those emissions suffer from
sparse observational constraints and poor model estimates. Only few studies on top-down ap-
proaches in the U.S. exist, mainly using Lagrangian models and ground-based measurements.
They all suggest a significant underestimation of anthropogenic emission sources in established
inventories, such as the Global Emissions InitiAtive (GEIA) and the Emissions Database for
Global Atmospheric Research (EDGAR). In this study we quantify anthropogenic N2 O emis-
sions in the mid-west of the U.S., an area of high agricultural activity. In the course of the
Atmospheric Carbon and Transport – America (ACT-America) campaign in fall 2017 we con-
ducted in-situ aircraft-based N2 O measurements in this region in the lower and middle tro-
posphere with a Quantum-Cascade-Laser-Spectrometer (QCLS) onboard the NASA-C130. To
investigate the influence of regional agricultural N2 O emissions on the spatial characteristics
of atmospheric N2 O mixing ratios, the Eulerian Weather Research and Forecasting model with
chemistry enabled (WRF-Chem) was used. The numerical simulations enable potential surface
emission distributions to be evaluated with respect to our airborne measurements including
quantification of sources. These results are then compared to emission rates in the GEIA and
EDGAR inventory.
Tuesday, 12:00: Towards designing a high-resolution atmospheric CO2
modeling system over India using WRF-Chem
Pillai, Dhanyalekshmi1 , Marshall, Julia2 , Gerbig, Christoph2 , Heimann, Martin2
1
Indian Institute of Science Education and Research Bhopal India
2
Max Planck Institute for Biogeochemistry, Jena Germany
European WRF-Chem User Workshop 2019The current estimates of regional carbon budget over India possess significant uncertainties
due to many factors including erroneous emission inventories and improper accounting of com-
plex biogeochemical mechanisms. The objective of this study is to optimally design a regional
greenhouse gas modeling framework over India using WRF-Chem as a core modeling compo-
nent. This approach takes into account the fine scale transport and flux variability, which
results in significant reduction of biases in the estimates, but are not resolved in current mod-
eling approaches over Indian subcontinent. The study focuses on designing and implementing
a dedicated modeling system for generating high-resolution GHG simulations over India at a
spatial scale of 10 km. A set of prior flux models and inventories are needed for implementing
the modeling system. The first set of WRF-GHG simulations will be presented along with the
preliminary analysis of the fine-scale variability of the atmospheric CO2 mixing ratio.
Tuesday, 14:00: New Constraint on particulate emissions from Indone-
sian peat fires
Kiely, Laura1 , Spracklen, Dominick1 , Arnold, Stephen1 , Marsham, John1 , Reddington, Carly1 ,
Conibear, Luke1 , Knote, Christoph2 , Kuwata, Mikinori3 , Budisulistiorini, Sri Hapsari3 , Wied-
inmyer, Christine4 , Latif, Talib5
1
School of Earth and Environment, University of Leeds, UK
2
Ludwig-Maximilians University, Munich, Germany
3
Nanyang Technological University, Singapore
4
University of Colorado, USA
5
University Kebangsaan Malaysia
Indonesia contains large areas of peatland which are being drained and cleared of natural veg-
etation, making them susceptible to burning. Peat fires emit considerable amounts of carbon
dioxide, particulate matter and other trace gases, contributing to climate change and causing
regional air quality issues. However emissions from peat fires are still very uncertain. We used
WRF-chem and extensive measurements of particulate matter concentrations to constrain par-
ticulate emissions from Indonesian fires, and include them in FINN. We also tested the effect
of the injection height of emissions in the model, by comparing simulated PM2.5 when emis-
sions are injected at the surface, and when they are injected through the boundary layer. We
estimate PM2.5 emissions from Indonesian fires were 7.33 Tg in 2015, a factor 3.5 greater than
those in FINNv1.5, which does not include peat burning. We estimate similar dry fuel con-
sumption and CO2 emissions to those in GFED4s, but a factor 1.8 greater PM2.5 emissions, due
to updated PM2.5 emission factors. Through comparing simulated and measured PM concen-
trations, our work provides an independent confirmation of these updated field based emission
factors. We estimate peat burning contributes 71% of total PM2.5 emissions from fire in In-
donesia during September-October 2015. Overall, our work suggests that peat fires in Indonesia
produce substantially more particulate emissions than estimated in current emission datasets,
with implications for the predicted air quality impacts of peat burning.
European WRF-Chem User Workshop 2019Tuesday, 14:20: The role of the natural aerosol on the flash-floods in
the Liguria region (WITHDRAWN)
Ferrari, Francesco1 , Cassola, Federico2 , Mazzino, Andrea1 , Morichetti, Mauro3 , Passerini,
Giorgio3 , Miglietta, Marcello Mario4 , Rizza, Umberto3
1
University of Genoa, Department of Civil, Chemical and Environmental Engineering (DICCA)
2
ARPAL - Centro Funzionale Meteo-Idrologico di Protezione Civile della Regione Liguria
3
University Polytechnic of Marche, Department of Industrial Engineering and Mathematics Sciences (DIISM),
Ancona, Italy
4
CNR/ISAC, Unit of Lecce, Lecce, Italy
The aim of the present work is to investigate the potential effects of dust aerosol and sea
salt spray on the structure of some severe rainfall events in Liguria (north-west of Italy).
These events are typically associated with intense southerly or southwesterly flows from South-
ern Mediterranean and Northern Africa and are also often associated with both mineral dust
plumes and relevant amounts of marine spray generated under strong wind conditions. The
former ones are usually generated in the Northern Sahara while the latter are due to the in-
teraction between the strong southerly flows and the sea surface. In particular the flooding
event occurred in Vernazza (Cinque Terre) on October 25, 2011, is analyzed here. For this
purpose several simulations are performed with the Weather Research and Forecasting model
online coupled with chemistry (WRF-Chem v. 4.0) in order to simulate the formation of the
convective storm and its feedback with dust aerosol. In particular, in the first part of this work,
the capability of the model to generate and transport aerosol from Sahara to the northern part
of the Mediterranean basin was analyzed. Then, the effect of aerosol in enhancing/reducing
the phenomena associated to the flood event are studied by means of three sets of simulations,
in which (a) the mineral dust does not interact with clouds and/or radiation, (b) the dust
transport is considered and only aerosols direct effects are accounted for, and finally (c) both
aerosols direct and indirect effects are considered.
Tuesday, 14:40: Simulating the 2011 Grímsvötn eruption with a new
volcanic module implementation in WRF-Chem
Baró, Rocío1 , Hirtl, Marcus1 , Scherllin-Pirscher, Barbara1 , Stuefer, Martin2
1
Zentralanstalt für Meteorologie und Geodynamik, Vienna, Austria
2
University of Alaska Fairbanks, Fairbanks, Alaska
Studying volcanic eruptions is important since the dispersion of the ash and SO2 clouds have
a strong influence on our environment. They affect air traffic, causing large economic impacts,
and ground touching plumes can influence soil, water and also affect/deteriorate air quality.
This study reveals the first results obtained with a new implementation of the volcanic module
within the WRF-Chem version 3.9.1. The source properties of ash and SO2 of the volcanic
eruption can be processed with this new version separately, and without intermediate pre-
processing steps. The new implementation provides the opportunity of considering vertical
profiles of emissions and furthermore, it is linked to the source term provided by the FLEXPART
model. The new module is evaluated for eruption of the Icelandic Grímsvötn volcano, which
took place in May 2011. It was simulated using ECMWF data as meteorological initial and
boundary conditions. Vertically-resolved ash and SO2 emission data were provided by the
European WRF-Chem User Workshop 2019FLEXPART model. This special case was chosen because the ash and SO2 plumes were ejected
in different heights and the vertical wind shear caused a clear separation of the volcanic ash
and SO2 plumes.
Comparisons with satellite data from ash and SO2 show that the new volcano implementation
is able to properly simulate the dispersion of the volcanic ash and SO2 plumes during this
particular Grímsvötn episode.
Tuesday, 15:00: A Case Study for Dust Transportation over Istanbul
Ünal, Zeynep Feriha1 , Dinç, Umur1 , Toros, Hüseyin1 , Kurşun, İlayda1
1
Meteorological Engineering Department, Istanbul Technical University, Istanbul, Turkey
The determination of air quality and the associated air pollution forecasting for near future are
remarkably important for all living creatures today. After years of the almost accurate weather
forecast, it has been possible to work on the almost accurate forecast of air pollution for the near
future. Dust transportation is the one of the biggest concern in air pollution forecasting. The
dust transportation from the source regions as North&South Africa and the Arabian Peninsula
increases the dust amount in the target area with the help of southern flow to the area and
moving pressure centers in Mediterranean region. Prediction for dust events like this event can
provide taking prevention for the socio-economic results like public health issues. WRF-Chem
model for air pollution forecasting is the one succesful model of atmospheric models & systems
for air quality forecasting. In this study, time interval is five days, GFS data sets are used for
WRF-Chem. Mud precipitation in Istanbul on 26.01.2019 and the sudden rise of PM2.5 & PM10
on the same day were modelled, the estimated data of this event and actual station data were
compared for consistency and error percentages were calculated. In this study, it is aimed to
show how effective WRF-Chem can be for air pollution estimation for the future.
Tuesday, 15:20: The influence of biogenic emissions on trace gases:
MEGAN sensitivity study
Morichetti, Mauro1 , Barth, Mary2 , Wiedinmyer, Christine3 , Madronich, Sasha2 , Passerini,
Giorgio1 , Bevilacqua, Diletta1 , Rizza, Umberto4
1
Department of Industrial Engineering and Mathematical Science, University of Polytechnic of Marche, An-
cona, Italy
2
National Center for Atmospheric Research, Boulder, Colorado, USA
3
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, Boulder, Col-
orado, USA
4
Institute of Atmospheric Sciences and Climate, National Research Council of Italy, Unit of Lecce, Italy
Natural gases, produced by the Earth’s ecosystem, include mostly biogenic volatile organic
compounds (BVOCs). Their emission flux has been consistently included in a regional chemi-
cal transport models (i.e. Model of Emissions of Gases and Aerosols from Nature, MEGAN).
The application includes the examination and test of a set of updates made to the MEGAN
model by integrating the algorithm into the existing MEGAN v2.04 embedded into the Weather
Research and Forecasting model coupled with chemistry (WRF-Chem v3.9). Two different test
cases are studied, the first is for a European domain, and the second for a United States domain.
European WRF-Chem User Workshop 2019Our study includes four simulations for each test case, the first is the control run: the database
has been used without any change (Megan_V2.04); the second simulation has modified activity
factors following MEGAN version 2.10 (Megan_Gamma); the third simulation adds the plant
functional type (PFT) emission factor changes to the activity factors (Megan_GammaPFT);
the last simulation calculates the isoprene emission factor within the MEGAN module, instead
of reading it directly from the input database (Megan_GammaPFTISO). For the Europe re-
gion, simulations are applied to an intense ozone event that took place over central Italy in
August 13th, 2015. The comparison of WRF-Chem results for the European domain with the
AIRBASE (European Environment Agency air quality network) showed that the temporal and
spatial distribution of ozone are well represented. However, comparing the updated MEGAN
emission simulations with the control run (Megan_V2.04), ozone concentrations increased sub-
stantially (by up to 10%). Results from the U.S. domain are compared with the NOMADSS
(Nitrogen, Oxidants, Mercury and Aerosol Distributions, Sources and Sinks) field campaign
data (from June 1th 00:00 UTC to June 15th 00:00 UTC, 2013), the WRF-Chem isoprene
mixing ratios are found to over-estimate observed isoprene mixing ratios considerably (up to a
factor of 5).
Tuesday, 16:20: Simulating Arctic boundary layer ozone depletion
events in WRF-Chem 4.0
Marelle, Louis1 , Thomas, Jennie L.2
1
Laboratoire Atmosphères, Milieux et Observations Spatiales, Université Pierre et Marie Curie, 4 place Jussieu,
75252 Paris CEDEX 05, France
2
Université Grenoble Alpes, CNRS, IRD, Grenoble-INP, IGE, 38000 Grenoble, France
Arctic ozone depletion events in WRF-Chem 4.0 Halogen chemistry in the Arctic is very ac-
tive, especially after polar sunrise, and can cause almost total loss of boundary layer ozone.
Release of reactive halogens to the Arctic troposphere is poorly understood, and is influenced
by complex heterogeneous processes on snow and aerosols. Halogen chemistry and emissions
are not included in most atmospheric models, and as a result there are important discrepancies
between modeled and observed ozone during the Arctic Spring. In order to improve predictions
of Arctic ozone, we implement in WRF-Chem 4.0 a description of chlorine and bromine gas-
phase chemistry, as well as simplified parameterizations representing bromine emissions over
snow and bromine recycling on snow and aerosols. We show that these developments signifi-
cantly improve model predictions of ozone during the Arctic Spring. This improved model will
be used to better understand the processes influencing Arctic ozone depletion events, and the
response of Arctic ozone to climate change and anthropogenic ozone precursor emissions.
Tuesday, 16:40: Evaluation of Siberian tropospheric ozone using satel-
lite, surface measurements and a regional model
Thorp, Tom1 , Arnold, Stephen1 , Spracklen, Dominick1 , Pope, Richard1 , Conibear, Luke1 ,
Knote, Christoph2 , Arshinov, Mikhail3 , Belan, Boris3 , Skorokhod, Andrey4
1
Institute of Climate and Atmospheric Science, University of Leeds, United Kingdom
2
Lehrstuhl Experimentelle Meteorologie - Fakultät für Physik, Ludwig-Maximilians-Universität München, Ger-
many
European WRF-Chem User Workshop 20193
V.E Zuev Institute of Atmospheric Optics, Russian Academy of Sciences, Siberian Branch, Tomsk, Russia.
4
A.M Obukhov Institute of Atmospheric Physics, Russian Academy of Sciences, Moscow, Russia.
The Arctic has warmed disproportionately relative to mid-latitudes over recent decades. This
warming is predominantly controlled by radiative forcing from well-mixed greenhouse gases,
amplified by efficient Arctic climate feedbacks. However, warming from changes in short-lived
climate pollutants (SLCPs), such as tropospheric ozone and aerosols, have been shown to con-
tribute substantially to Arctic warming. Arctic SLCP abundances are controlled by long-range
transport from mid-latitudes, and by local sources within the Arctic. At present, high latitude
emissions of SLCPs and ozone precursors are poorly quantified, particularly in Russia, where
there is a paucity of in-situ observations. A full understanding of the impact of SLCPs on
the Arctic is partly hampered by poor knowledge of processes controlling SLCPs in northern
Siberia, which is home to large sources of anthropogenic and natural emissions. This region
is also a key route for import of SLCPs to the Arctic lower troposphere from lower latitude
northern Europe and Asia.
In this study we use the regional chemistry transport model WRF-Chem, in conjunction with
observations from surface sites and the Ozone Monitoring Instrument (OMI) satellite instru-
ment, to evaluate processes controlling the regional distribution of tropospheric ozone over
Western Siberia during spring and summer. We assess the influence of NOx source sectors on
ozone over Siberia and the Russian Arctic, including comparison between anthropogenic sources
and wildfires. Model comparisons with OMI NO2 observations are used to highlight potential
emission biases in the region. We also assess the sensitivity of ozone deposition to different land
cover types in Siberia, to gain a better understanding of an important ozone sink in this region.
Our study provides insight into the relative importance of anthropogenic emissions compared
with natural biosphere processes in controlling Siberian tropospheric ozone.
Tuesday, 17:00: Air Pollution Forecasting with Machine Learning by
using WRF-Chem Model Output
Dinç, Umur1 , Ünal, Zeynep Feriha1 , Toros, Hüseyin1
1
Meteorological Engineering Department, Istanbul Technical University, Istanbul, Turkey
Since the frequent usage of coal for Industrial Revolution during 18th and 19th centuries,
air pollution has become more important day by day due to its fatal effects on living creatures
and hazardous effects on the environment such as acid rains, climate change and ozone increase.
Apparently, the reason behind the air pollution problem is mostly human activities and at that
point, forecasting air pollution is important as preventing air pollution sources. Air pollution
forecasting already has a wide variety of useful methods and machine learning method is one
of these methods. In this study, it is focused on the machine learning method due to being
able to train the model with temporal-spatial data from the past and to consider these data to
forecast air pollution for future more accurate than other common models. Our study method
is using NOAA’s GFS data for WRF-Chem model then using WRF-Chem output parameters
like temperature, pressure, moisture, wind speed and direction, particular matters and also
observed particular matters are used as our new input to train machine learning model. In the
end, WRF-Chem results and machine learning results are compared with actual observed data
separately. In this work, it can be seen the machine learning method with WRF-Chem output
have satisfying results comparing to the usage of WRF-Chem model only.
European WRF-Chem User Workshop 2019Tuesday, 17:20: OMI-derived European NOx emissions in WRF-Chem:
effects on summertime surface ozone
Visser, Auke1 , Boersma, K Folkert2 , Ganzeveld, Laurens3 , Krol, Maarten4
1
Meteorology and Air Quality department, Wageningen University, Wageningen, the Netherlands
2
Wageningen University, Royal Netherlands Meteorological Institute (KNMI)
3
Wageningen University
4
Wageningen University, Utrecht University
Several studies have reported that simulated peak summertime ozone concentrations in WRF-
Chem are underestimated. The formation of ozone in European summers critically depends
on nitrogen oxides, which catalyze the oxidation of reactive hydrocarbons that leads to ozone
production. We hypothesize that uncertainties in NOx emissions contribute to the under-
estimation of peak ozone concentrations in European summers. To test this, we calculated
satellite-constrained NOx emissions for July 2015 based on differences between WRF-Chem-
simulated NO2 columns and those observed by the Ozone Monitoring Experiment (OMI). This
resulted in 67% higher emissions across Europe compared to the prior emission estimate in
WRF-Chem. A first-order source attribution suggests that this increase can for a large part
be attributed to (agricultural) soil NOx emissions, which seem underestimated in the model.
Our results show that implementation of these OMI-inferred NOx emissions in WRF-Chem
leads to improvements in simulated NO2 and O3 when compared to independent AirBase in
situ measurements. Overall, our findings demonstrate that assessments of European summer
ozone air quality benefit from constraining surface NOx emissions estimates by satellite NO2
columns.
Tuesday, 17:40: Evaluation of WRF-chem-urban in Mexico Megacity
Garcia-Reynoso, Jose Agustin1 , Noyola, Miguel1
1
Centro de Ciencias de la Atmosfera, UNAM, Ciudad de Mexico, Mexico
Air quality depends on emissions and meteorological patterns, by using Air quality models
is possible to identify population exposure and environmental effect from secondary pollutants.
Depending on the compound emissions inventories can have a large uncertainty in some cases
there are overestimation or underestimation. Also meteorological filed can have an impor-
tant role in the pollutant dispersion and dilution, stronger winds can lead a larger dilution
than weaker. In the case of Mexico City, the wind measured over the city stations has lower
intensity than the model, in order to enhance the pollutant concentrations, the use of the WRF-
chem-urban model was used. In this model there are several urban categories that can lead
an increase in the surface length roughness that can lead a better wind intensity description.
An evaluation of the WRF-chem vs WRF-chem-urban is presented for air quality modeling in
Mexico.
European WRF-Chem User Workshop 2019Wednesday, 09:00: Driving WRF-Chem with meteorological data from
the AROME model
Haselsteiner, Magdalena1 , Flandorfer, Claudia1 , Scherllin-Pirscher, Barbara1 , Wittmann,
Christoph1 , Schneider, Stefan1 , Weidle, Florian1 , Hirtl, Marcus1
1
Zentralanstalt für Meteorologie und Geodynamik (ZAMG)
This study aims to improve air quality forecasts over complex terrain by us- ing high-resolution
meteorological data as initial and boundary conditions for WRF-Chem. In Europe many me-
teorological offices operationally perform high-resolution runs of limited area models to obtain
high-resolution meteorological data. These data, however, are often available in non-standard
data format, which cannot be processed by WRF (Weather Research and Forecasting Model)
or WPS (WRF Pre-processing System). An overview will be provided on how to pre-process
non-standard data to a WPS readable format, using data from the Austrian AROME model
as an example. AROME stands for ‘Application of Research to Operations at Mesoscale’ and
provides data in a format called FA, introduced by Météo-France. The AROME model and
its data format are used by many meteorological offices worldwide. In addition, case studies of
driving WRF with global data from the IFS (Integrated Forecasting System) (0.1°) and data
from AROME (2.5km) will be compared. The focus will be on wind and temperature, because
many other fields e.g. concentrations of air pollutants depend on them. The significant dif-
ference in temperature fields will be discussed in contrast to the non-differing accuracy of the
wind fields.
Wednesday, 09:20: To nudge or not to nudge: a WRF-Chem perspec-
tive (WITHDRAWN)
Hilboll, Andreas1 , Kalisz Hedegaard, Anna Beata2 , Daskalakis, Nikos1 , Vrekoussis, Mihalis1
1
Institute of Environmental Physics, University of Bremen, Bremen, Germany
2
Institute of Atmospheric Physics, German Aerospace Center (DLR), Wessling, Germany
Simulation of atmospheric chemistry requires accurate knowledge of the prevailing meteoro-
logical conditions, as these influence, in some cases strongly, the reaction rates governing the
chemical transformation of trace species. In order to facilitate such simulations at high spatial
resolution, one common approach is the tight integration of a meteorological with a chemical
model, i.e., the meteorology is simulated on the same spatial grid as the chemical processes,
using large-scale meteorological fields as initial and boundary conditions.
As meteorological simulations tend to drift away from the large-scale fields driving them, this
can introduce biases in the simulated trace gas concentrations. This is especially important
in modeling setups where the area of interest is far away from the domain boundaries, e.g., in
cases where a number of sequentially nested domains is needed to down-scale coarse-resolution
chemical boundary conditions to the target resolution. To overcome this problem, the meteo-
rology can be "nudged" to the driving fields, i.e., Newtonian relaxation terms are added to the
model predictive equations, forcing the simulated meteorology in the direction of the driving
fields.
While the nudging method is well-established for meteorological simulations, many studies
of atmospheric chemistry seem to not make use of it. In this presentation, we investigate
the effects of nudging the model meteorology to ECMWF’s new ERA5 reanalysis, using the
European WRF-Chem User Workshop 2019Weather Research and Forecasting model coupled with Chemistry, WRF-Chem (version 4.0.2).
In particular, we present the effects of nudging on both a) meteorological key parameters
(temperature, wind, humidity) and b) key tracers like ozone and nitrogen dioxide.
Wednesday, 09:40: Study of the impact of temporal variability of sur-
face wind downstream of mountains on PM10 concentration in West
Africa (WITHDRAWN)
Thiam, Mamadou Lamine1 , Gueye, Moussa2 , Senghor, Habib1 , Gaye, Amadou Thierno1
1
Laboratory of Atmosphere Physics and Ocean Simeon Fongang, University Cheikh Anta Diop, Dakar, Senegal
2
Department of Meteorology, Pennsylvania State University, University Park, 16802, PA, USA
Most of the dust emitted in West Africa is mainly generated in the downstream regions of
the mountains (Evan et al., 2016), where a large population evolves and is exposed to poor air
quality due to dust transport. We analyzed the temporal variability of surface wind and PM10
concentration over three downstream from mountains such as Tibesti (Chad), to the south and
west of the Hoggar Mountains (Algeria), during dust periods from 01 to 04 January 2012 and
from January 18 to 23, 2012 in West Africa, using the WRF-Chem with horizontal resolutions
of 18, 50 and 100 km. Both dust events were observed using the MODIS radiometer to measure
AOD. We find that the WRF-Chem has captured the dust events by showing that the dust
episode from 01 to 04 January 2012 was initiated in Bodélé and that from 18 to 23 January
2012 was generated in southern Algeria. Our results show that the 100 km resolution shows
low values of PM10 concentration with a large deviation from the other two resolutions in the
mountainous region (Tibesti) near the main source Bodele. On the other hand, in the moun-
tainous regions (south and west of the Hoggar Mountains) near the main source in southern
Algeria, the resolution of 100 km indicates well the high values of PM10 simulated at these
regions compared to the other two resolutions. This shows that horizontal resolutions below
100 km are more appropriate to simulate dust in West Africa, especially in Bodélé which is one
of the most active dust sources in West Africa. Our results suggest that the use of WRF-Chem
with 50 km would be important to better simulate the air quality in these areas at the foot of
the mountains where the consequences for health are greater.
Wednesday, 10:20: Using WRF-Chem to Examine the Drivers of Re-
cent Trends in Chinese Air Quality
Silver, Ben1 , Reddington, Carly1 , Arnold, Steve1 , Conibear, Luke1 , Knote, Christoph2 , Spracklen,
Dominick1 , Li, Meng3 , Zhang, Qiang4
1
Institute for Climate and Atmospheric Science, University of Leeds
2
Meteorologisches Institut, Ludwig-Maximilians-Universität München
3
Max-Planck Institute for Chemistry, Mainz
4
Department of Earth System Science, Tsinghua University
China’s rapid industrialisation and urbanisation has led to serious air pollution, resulting in over
one million premature deaths per year. The Chinese government have responded by introducing
regulations to reduce emissions and setting ambitious targets for ambient PM2.5 concentrations.
European WRF-Chem User Workshop 2019Our previous study uses data from over 1600 monitoring stations in China and Taiwan to quan-
tify the trend in PM2.5 , SO2 , NO2 , and O3 during 2015 – 2017. We found that while PM2.5 and
SO2 decreased significantly across China, O3 has increased during the same period, and there
was no overall trend in NO2 . However, due to the lack of monitoring data before 2014, it is
unclear whether recent trends are driven primarily by changes in emissions, or by inter-annual
meteorological variability. In this work, we will use the WRF-Chem model, with the latest Chi-
nese emission inventories (MEIC), to establish the main drivers for the observed trends. Our
proposed methodology is to perform counterfactual simulations to isolate the effects of changes
in emissions from inter-annual meteorological variation. We will simulate 2015 – 2017 using a
30km domain that covers China and Taiwan. We will perform one counterfactual run using
constant emissions but inter-annually varying meteorology, and another where meteorological
conditions are repeated, but emissions vary. These will be compared to a control run that will
attempt to simulate real conditions, which we can validate using the monitoring network. I
will present early results from this work, including validation of 2015 runs using the monitoring
network, and the effects of introducing a diurnal cycle into WRF-Chem emissions.
Wednesday, 10:40: Unraveling the impact of different sources of NOx
precursors to O3 concentrations during a heat wave period
Lupascu, Aurelia1 , Butler, Tim1
1
Institute for Advanced Sustainability Studies, Potsdam, Germany
The increased concentration of air pollutants in the ambient air could cause adverse effect
on humans. The heat wave effect combined to the high ozone episodes is associated with an
increase in mortality. In Germany, the heat wave definitions describe periods of at least 48 h, in
which temperatures exceed 32° Celsius. High temperatures were measured in Germany during
June 29 - July 6, 2015, and new temperature records were established on July 5, 2015 reaching
39.7° C at Bad Duerkheim, and a new national record of 40.3 C was observed at Kitzingen.
Moreover, the European legislation suggests that the maximum daily 8-hour average (MDA8)
should have a threshold of 120 µg/m3 which should not be exceeded on more than 25 days
averaged over 3 years and this limit was exceeded during the heat wave episodes. However,
the contribution of the different sources of precursors to O3 formation within each country is
still to be understood. Our study use an O3 source apportionment method implemented in
the WRF-Chem model to understand and quantify the origin of MDA8 O3 peak over the heat
wave period. The method tags both O3 and its gas precursor emissions from source regions
and types within one simulation and each tagged species is subject to the typical physical and
chemical processes. Thus, by the means of the tagging method, we are able to quantify the
contribution of the NOx local and remote sources to the O3 concentration and to understand
the origin of peak O3 event during June 29 - July 6, 2015 period.
Wednesday, 11:00: Quantifying the role of the transport sector on
observed variations of PM2.5 over the National Capital Region of Delhi,
India.
Mogno, Caterina1 , Palmer, Paul1 , Wallington, Timothy J.2
European WRF-Chem User Workshop 20191
School of Geosciences, The University of Edinburgh - Edinburgh, UK
2
Research and Advanced Engineering, Ford Motor Company, Dearborn, MI, 48121-2053, USA
According to the World Health Organisation (WHO), particulate matter less than 2.5 mi-
crons in diameter (PM2.5 ) now affect people more than any other pollutant as they pose a great
risk to human health. Moreover, as reported by the WHO, Delhi in India is one of the most
polluted megacity in the world, with annual median PM2.5 values over 100 µgm-3 (cfr annual
median of 5 µgm-3 in Edinburgh, UK, 2015). The transport sector is proven to be one of the
largest primary sources ( 30%) of PM2.5 in Delhi. The aim of this PhD project is to quantify
the role of the transport sector on PM2.5 over Delhi, combining a recent source apportionment
inventory of PM2.5 prepared for the Indian Ministry of Heavy Industries with WRF-chem. We
will map out PM2.5 across Delhi, and assess the sensitivity of results to different assumptions
about atmospheric chemistry, taking into account also different boundary conditions. Moreover
we will perform a sensitive analysis on different assumption on the transport sector emissions.
We will quantify the exposure to PM2.5 due to transport on a spatial basis and on a temporal
basis, under environmental conditions indicative of Delhi in different seasons of the year as well
as under anomalous conditions (e.g. heatwaves).
Wednesday, 11:20: The impact of urban emission reduction on meteo-
rological variables during summer and winter episodes
Karlický, Jan1
1
Department of Atmospheric Physics, Faculty of Mathematics and Physics, Charles University, Prague, Czech
Republic
The WRF-Chem model was used for modelling of three different 14-day periods during 2016–2017,
specifically for summer high-level ozone episode, summer convective episode and winter episode
with high concentrations of aerosol pollutants. Simulations were run on 2 km domain covering
the centre of Czech Republic with the capital Prague, which was nested into 10 km domain
covering the centre of Europe. For the investigation of meteorological impact of the reduc-
tion of urban induced emissions, two model simulations were performed for every episode; one
simulation with full anthropogenic emissions and second one with reduced emissions of Prague
urban area to a background level. Differences between the simulations are significant for sur-
face concentrations of primary gas pollutants, but less distinct for ozone and aerosol pollutants.
Differences of total column characteristics such as AOD (Aerosol Optical Depth) and also of
meteorological variables such as downward solar radiation, temperature, boundary level height
and rainfall are not statistically significant.
Wednesday, 11:40: Modelling the effect of traffic emission on urban air
quality in different scenarios: A case of Berlin-Brandenburg region
Sibiya, Bheki1 , Butler, Tim1 , Schaap, Martijn2 , Lupascu, Aura1 , Leitao, Joana1
1
Institute for Advanced Sustainability Studies, Potsdam, Germany
2
Freie Universität, Fachbereich Geowissenschaften, Institut für Meteorologie, Berlin, Germany
European WRF-Chem User Workshop 2019The emissions from traffic sector are a major environmental problem in most countries, partic-
ularly in the urban areas of developed countries. Due to the rapid increase in the number of
vehicles and their dependency on petroleum based fuel, road transport has emerged to be the
largest source of urban pollution. Vehicles are associated with high levels of particulate and
gaseous pollutants e.g particulate matter (PM) and oxides of nitrogen (NOx ). The amount and
type of fuel (e.g. petrol or diesel) used as well as the operating conditions of the engine largely
influence the composition of the emitted species. Diesel-powered vehicles have been recognised
as one of the important emitters of NOx and PM in European urban areas (Degraeuwe et al.,
2017). Both PM and NOx annual limit values are regularly exceed over large areas of the Euro-
pean continent. European Environmental Agency (EEA, 2016) also highlights that Germany is
among the largest emitters of NOx . Consequently, the Berlin-Brandenburg Region (BBMR) in
Germany is one of the urban areas with critical load of vehicle emissions. In combination with
the WRF-Chem modelling system, this study uses a recent emission inventory with high reso-
lution traffic emission data for the Berlin city in order to investigate the contribution of traffic
emissions to the state of air quality in the BBMR region and further test possible mitigation
options for improving air quality in the area.
European WRF-Chem User Workshop 2019Poster: Assessment of the land-atmosphere exchange of CO2 in a
GHGs forecast system using airborne measurement
Chen, Jinxuan1 , Gerbig, Christoph1 , Marshall, Julia1 , Gałkowski, Michał1 , Totsche, Kai
Uwe2
1
Max Planck Institute for Biogeochemistry, Jena, Germany
2
Friedrich Schiller University Jena, Jena, Germany
A regional forecast system for atmospheric CO2 and CH4 has been developed in order to
support the CoMet campaign (Carbon dioxide and Methane mission). The forecasting system
is developed using the WRF-GHG v3.9.1.1 model, with 10km x 10km spatial resolution over
European domain and nested 2km x 2km subdomain over Berlin and Upper Silesian Coal Basin.
The CAMS chemical forecast is used as the initial and boundary conditions for tracers while the
anthropogenic emission comes from the TNO database and an internal CH4 emission database.
An essential part of the forecast model is the land-atmosphere exchange of CO2 , as the vege-
tation plays an important role in the variation of CO2 in diurnal to synoptic time scales. The
exchange is due to photosynthesis and respiration of vegetation, and the magnitude depends on
the environmental condition (Shortwave radiation, temperature etc.) as well as the vegetation
states. In the forecast system the light-use-efficiency model VPRM (the Vegetation Photosyn-
thesis Respiration Model) is used to forecast the future CO2 flux by predicting VPRM’s input.
Errors are potentially involved from five error sources, which are using near-real-time MODIS
product, applying extrapolation on MODIS data, lacking constrain from future MODIS data,
using forecast shortwave radiation and using forecast air temperature. An assessment of the
VPRM flux prediction has been done offline in flux space (J. Chen et. al., in preparation). In
this research we further assess the biospheric model within the forecast system in concentration
space. Six biospheric flux scenarios are implemented in the forecasting system, in which errors
from different sources are contained in each flux scenario. Hindcast is then made by the forecast
model with each scenario, and the comparison between the modeled CO2 vs. the measurement
from the CoMet campaign has been taken to quantify the error from different source.
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