Data sets and simulation codes for the work: Radiative cooling in New York/New Jersey metropolitan areas by wildfire particulate matter emitted from the Canadian wildfires of 2023
DOI: 10.4121/963d23da-9d1d-4771-ab30-8b41de423c95
Datacite citation style
Dataset
Excel file with data sets for particle mass concentrations (Fig. 1b & S5), size distributions (Fig. 1c), concentrations of polycyclic aromatic hydrocarbons (PAHs; Fig. 1d), absorption coefficients (Fig. 2a and S4a), scattering coefficients (Fig. S2b and S4b), mass absorption cross-sections (Fig. S2c), single scattering albedos (Fig. S2d) and observed mean daily temperatures (Fig. 4). These data are part of a field sampling campaign that took place on June 7 and 8, 2023 at Piscataway, NJ to characterize the wildfire particulate matter that was transported from Quebec, Canada to northeast US. The background aerosols were also characterized on June 12, 2023, a reference smoke-free day. More details regarding the sampling campaign can be found in the Methods section of this work.
MATLAB files with Mie theory code used to estimate light absorption and scattering of wildfire particulate matter (Figs. 2c, 2d, S7, S8). Details regarding the input values used in the MATLAB code can be found in the Methods section of this work.
A text file with the wavelength (first column), real (second column) and imaginary (third column) refractive index parts is used as an input to run the uploaded MATLAB files and is also provided here.
History
- 2025-03-17 first online, published, posted
Publisher
4TU.ResearchDataFormat
2 MATLAB files *.m, 1 Text file *.txt, 1 Excel file *.xlsxOrganizations
TU Delft, Faculty of Aerospace Engineering, Department of Flow Physics and Technology;Environmental and Occupational Health Sciences Institute, School of Public Health, Rutgers University, Piscataway, USA
DATA
Files (5)
- 1,745 bytesMD5:
510b584d0ab054229151c452a26d012a
README.txt - 1,523 bytesMD5:
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CB_OCTC_958c.txt - 1,467,515 bytesMD5:
708792a8c8ed265fa287e2af64a77adb
Data_All_Figures_Kelesidis_et_al_COMMSENV_2025.xlsx - 5,569 bytesMD5:
241662e9fdb7f2040dc8a736b408d78d
mie.m - 2,600 bytesMD5:
be1fd6bba277866f7fac09b4c8f541de
Mie_Theory_Code.m -
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