This dataset contains the input and output files for LES simulations performed for the study described in journal article "Large-eddy simulation of the optimal street-tree layout for pedestrian-level aerosol particle concentrations – A case study from a city-boulevard" (Karttunen et al., 2020, https://doi.org/10.1016/j.aeaoa.2020.100073) using the PALM model system version 6.0, revision 3698. Each simulation run has its own dedicated folder. The folder naming scheme is includes the scenario identifier (eg. S2A) and the wind direction. Please refer to the original journal article for information on the simulation setup and runs. Note that running the scenario runs requires the binary output from the precursor run. Please refer to PALM documentation on how the binary input mechanism can be used. File formats and descriptions (file name suffix "_N02" corresponds to data from the nested subdomain): CPU_MEASURES (ascii): CPU statistics from the run. DATA_1D_PR_NETCDF (netCDF4): Profile data averaged horizontally over whole domain. DATA_1D_TS_NETCDF (netCDF4): Time series data averaged over whole domain. DATA_2D_XY_AV_NETCDF (netCFF4): Temporally averaged data at height levels. DATA_MASK_NETCDF_N02_M01 (netCDF4): Masked 3-dimensional wind data from the nested subdomain. DATA_MASK_NETCDF_N02_M02 (netCDF4): Masked 3-dimensional bin-wise aerosol number concentrations from the nested subdomain. ENVPAR (netCDF4): Environment variables for PALM. HEADER (ASCII): Detailed simulation setup and data input-output descriptions. PARIN (ASCII): Simulation and data input-output setups. PIDS_SALSA (netCDF4): The SALSA aerosol module input data. PIDS_STATIC(netCDF4): Static data inputs for the PALM model system, excluding the aerosol module. PROGRESS (ASCII): Run progress status. RUN_CONTROL (ASCII): Diagnostic simulation run log. For more details about data sampling and averaging, please refer to the corresponding HEADER file. The PALM model documentation (https://palm.muk.uni-hannover.de) has detailed documentation on the input files and variables.

2020