API Reference¶

Functions Module¶

aerosol.functions.air_density(temp, pres)[source]¶

Calculate air density

Parameters:

tempfloat or series of lenght n: absolute temperature (K)
presfloat or series of length n: absolute pressure (Pa)

Returns:

float or series of length n: air density (kg/m3)

aerosol.functions.beta(dp, temp, pres, diffusivity, molar_mass)[source]¶

Calculate Fuchs Sutugin correction factor

Sutugin et al. (1971): https://doi.org/10.1016/0021-8502(71)90061-9

Parameters:

dpfloat or series of lenght m: aerosol particle diameter(s), unit: m
tempfloat or series of lenght n: temperature, unit: K
presfloat or series of lenght n: pressure, unit: Pa
diffusivityfloat or series of length n: diffusivity of the gas that is condensing, unit: m2/s
molar_massfloat: molar mass of the condensing gas, unit: g/mol

Returns:

float or dataframe of shape (n,m): Fuchs Sutugin correction factor for each particle diameter and temperature/pressure unit: m2/s

aerosol.functions.binary_diffusivity(temp, pres, Ma, Mb, Va, Vb)[source]¶

Binary diffusivity in a mixture of gases a and b

Fuller et al. (1966): https://doi.org/10.1021/ie50677a007

Parameters:

tempfloat or series of length n: temperature, unit: K
presfloat or series of length n: pressure, unit: Pa
Mafloat: relative molecular mass of gas a, unit: dimensionless
Mbfloat: relative molecular mass of gas b, unit: dimensionless
Vafloat: diffusion volume of gas a, unit: dimensionless
Vbfloat: diffusion volume of gas b, unit: dimensionless

Returns:

float or series of length n: binary diffusivity, unit: m2 s-1

aerosol.functions.calc_bin_edges(dp)[source]¶

Calculate bin edges given bin centers

Parameters:

dppandas series of lenght n: bin center diameters

Returns:

pandas series of lenght n+1: log bin edges

aerosol.functions.calc_coags(df, dp, temp=293.15, pres=101325.0, dp_start=None)[source]¶

Calculate coagulation sink

Kulmala et al (2012): doi:10.1038/nprot.2012.091

Parameters:

dfdataframe: Aerosol number size distribution
dpfloat or series of length m: Particle diameter(s) for which you want to calculate the CoagS, unit: m
tempfloat or series indexed by DatetimeIndex: Ambient temperature corresponding to the data, unit: K If single value given it is used for all data
presfloat or series indexed by DatetimeIndex: Ambient pressure corresponding to the data, unit: Pa If single value given it is used for all data
dp_startfloat or None: The smallest size that you consider as part of the coagulation sink If None (default) then the smallest size is from dp

Returns:

float or dataframe: Coagulation sink for the given diamater(s), unit: s-1

aerosol.functions.calc_conc(df, dmin, dmax, frac=0.5)[source]¶

Calculate particle number concentration from aerosol number-size distribution by adding whole bins

Parameters:

dfdataframe: Aerosol number-size distribution
dminfloat or series of length n: Size range lower diameter(s), unit: m
dmaxfloat or series of length n: Size range upper diameter(s), unit: m
fracfloat: Minimum fraction of available data when calculating a concentration point

Returns:

dataframe: Number concentration in the given size range(s), unit: cm-3

aerosol.functions.calc_conc_interp(df, dmin, dmax, threshold=0.0)[source]¶

Calculate particle number concentration from aerosol number-size distribution using integration and linear approximation

Parameters:

dfdataframe: Aerosol number-size distribution
dminfloat: Size range lower diameter, unit: m
dmaxfloat: Size range upper diameter, unit: m
thresholdfloat: fraction of nans accepted per row

Returns:

series: Number concentration in the given size range, unit: cm-3 in the index of the original dataframe

aerosol.functions.calc_cs(df, temp=293.15, pres=101325.0)[source]¶

Calculate condensation sink, assuming that the condensing gas is sulfuric acid in air with aerosol particles.

Kulmala et al (2012): doi:10.1038/nprot.2012.091

Parameters:

dfpandas.DataFrame: aerosol number size distribution (dN/dlogDp)
temppandas.Series or float: Ambient temperature corresponding to the data, unit: K If single value given it is used for all data
prespandas.Series or float: Ambient pressure corresponding to the data, unit: Pa If single value given it is used for all data

Returns:

pandas.Series: condensation sink, unit: s-1

aerosol.functions.calc_formation_rate(df, dp1, dp2, gr, sink_term)[source]¶

Calculate particle formation rate

Kulmala et al (2012): doi:10.1038/nprot.2012.091

Parameters:

dfDataframe (m rows): Aerosol particle number size distribution Unit cm-3
dp1float or series of length n: Lower diameter of the size range(s) Unit m
dp2float or series of length n: Upper diameter of the size range(s) Unit m
grfloat or Dataframe (n columns, m rows): Growth rates unit nm/h
sink_termDataframe (n columns, m rows): Flux of particles out of size range due to sink Unit: cm-3 s-1

Returns:

dict: Particle formation rate, dN/dt terms, sink terms and GR terms for the diameter range(s) Unit cm-3 s-1

aerosol.functions.calc_ion_formation_rate(df_particles, df_negions, df_posions, dp1, dp2, gr_negions, gr_posions, sink_term_negions, sink_term_posions)[source]¶

Calculate ion formation rate

Kulmala et al (2012): doi:10.1038/nprot.2012.091

Parameters:

df_particlesdataframe with m rows: Aerosol particle number size distribution
df_negionsdataframe with m rows: Negative ion number size distribution
df_posionsdataframe with m rows: Positive ion number size distribution
dp1float or series of length n: Lower diameter of the size range(s), unit: m
dp2float or series of length n: Upper diameter of the size range(s), unit: m
gr_negionsFloat or DataFrame (n columns and m rows): The negative ion GRs unit nm h-1
gr_posionsFloat or DataFrame (n columns and m rows): The positive ion GRs unit nm h-1
sink_term_negionsDataframe (n columns and m rows): Flux of negative ions out of the size range due to coagulation Unit: cm-3 s-1
sink_term_posionsDataframe (n columns and m rows): Flux of positive ions out of the size range due to coagulation Unit: cm-3 s-1

Returns:

dict: Negative ion formation rate, dN/dt terms, sink terms, GR terms, attachment terms and recombination terms for the diameter range(s) Unit cm-3 s-1
dict: Positive ion formation rate, dN/dt terms, sink terms, GR terms, attachment terms and recombination terms for the diameter range(s) Unit cm-3 s-1

aerosol.functions.calc_ion_production_rate(clus_ion_conc, dp_clus, cs)[source]¶

Calculate the ion production rate from sink and ion concentration

Parameters:

clus_ion_concseries of length n: Cluster ion concentration from negative or positive polarity in cm-3
dp_clusfloat: Cluster ion diameter in nm
csseries of length n: Particle number size distribution unit cm-3

Returns:

series of lenght n: Ion production rate in cm-3 s-1

Notes

Assume balance between cluster ion polarities

aerosol.functions.calc_ldsa(df)[source]¶

Calculate total LDSA from number size distribution data

ICRP, 1994. Human respiratory tract model for radiological protection. A report of a task group of the international commission on radiological protection. Ann. ICRP 24 (1-3), 1-482

Parameters:

dfpandas.DataFrame: Aerosol number-size distribution

Returns:

pandas.DataFrame: Total LDSA for alveoli (“al”), trachea/bronchi (“tb”) head-airways (“ha”) and all combiend (“tot”) unit: um2 cm-3

aerosol.functions.calc_lung_df(dp)[source]¶

Calculate lung deposition fractions for particle diameters

ICRP, 1994. Human respiratory tract model for radiological protection. A report of a task group of the international commission on radiological protection. Ann. ICRP 24 (1-3), 1-482

Parameters:

dppandas.Series: aerosol particle diameters unit: m

Returns:

pandas.DataFrame: Lung deposition fractions for alveoli (“DF_al”), trachea/bronchi (“DF_tb”) head-airways (“DF_ha”) and all combiend (“DF_tot”)

aerosol.functions.coagulation_coef(dp1, dp2, temp=293.15, pres=101325.0, gas='air')[source]¶

Calculate Brownian coagulation coefficient (Fuchs)

Parameters:

dp1float: first particle diameter, unit: m
dp2float or series of lenght m: second particle diameter, unit: m
tempfloat or series of lenght n: air temperature, unit: K
presfloat or series of lenght n: air pressure, unit: Pa
gasstr: air (default) or nitrogen

Returns:

float or dataframe of shape (n,m)

Brownian coagulation coefficient (Fuchs),

If dataframe is returned the columns correspond to diameter pairs (dp1,dp2) and are labeled by elements in dp2.

unit m3 s-1

aerosol.functions.cross_corr_gr(df, dmin, dmax, median_filter_window=None, smoothing_window=None, tau_limit=12.0, number_of_divisions=1, nan_threshold=0.0, data_reso=1.0, gamma=0.25, verbose=False)[source]¶

Calculate GR using cross-correlation method

Parameters:

dfpandas dataframe: Aerosol number size distribution
dminfloat: Lower size limit for GR
dmaxfloat: Upper size limit for GR
median_filter_windowfloat: Window length used in median filter in hours (for spike removal) If None, no median filtering
smoothing_windowfloat: Window length used in smoothing the data in hours If None, no smoothing is applied
tau_limitfloat: Range of time lags used in hours
number_of_divisionsint: The number of divisions applied to the size range
nan_thresholdfloat: Maximum fraction of NaNs present in any of the size channels
data_resofloat: Data resolution in hours
verboseboolean: If True then GR, lags and cross correlations are returned If False then only GR is returned

Returns:

dictionary

If verbose is True

gr: total growth rate in nm/h
gr_incr: growth rates in each increment
tau_max_incr: tau_max in each increment
lag: lags in seconds for each increment
corr: cross correlations for each increment
t: interpolated timestamps (seconds)
n1: Interpolated unnormalized concs in lower channels
n2: Interpolated unnormalized concs in upper channels

If verbose is False

gr: total growth rate in nm/h

References

Lampilahti et al. (2025): https://doi.org/10.5194/ar-3-637-2025

aerosol.functions.cs2coags(cs, dp, m=-1.6)[source]¶

Estimate coagulation sink from condensation sink

Parameters:

cspandas.Series: The condensation sink time series: unit s-1
dpfloat: Particle diameter for which CoagS is calculated, unit: nm
mfloat: Exponent in the equation

Returns:

coagspandas.Series: Coagulation sink time series for size dp

References

Kulmala et al (2012), doi:10.1038/nprot.2012.091

aerosol.functions.datenum2datetime(datenum)[source]¶

Convert from matlab datenum to python datetime

Parameters:

datenumfloat or int: A serial date number representing the whole and fractional number of days from 1-Jan-0000 to a specific date (MATLAB datenum)

Returns:

pandas.Timestamp

aerosol.functions.datetime2datenum(dt)[source]¶

Convert from python datetime to matlab datenum

Parameters:

dtdatetime object

Returns:

float: A serial date number representing the whole and fractional number of days from 1-Jan-0000 to a specific date (MATLAB datenum)

aerosol.functions.dndlogdp2dn(df)[source]¶

Convert from normalized number concentrations to unnormalized number concentrations.

Parameters:

dfdataframe: Aerosol number-size distribution (dN/dlogDp)

Returns:

dataframe: Aerosol number size distribution (dN)

aerosol.functions.gas_viscosity(temp, gas='air')[source]¶

Calculate gas viscosity using Enskog-Chapman theory

Parameters:

tempfloat or series of length n: air temperature, unit: K
gasstr: Either air (default) or nitrogen

Returns:

float or series of length n: viscosity of gas, unit: m2 s-1

aerosol.functions.ions2particles(neg_ions, pos_ions, temp=293.15, mob_ratio=1.0)[source]¶

Estimate particle number size distribution from ions using Li et al. (2022)

Parameters:

neg_ionspandas dataframe of shape (n,m): negative ion number size distribution
pos_ionspandas dataframe of shape (n,m): positive ion number size distribution
tempfloat or series of length n: ambient temperature in K
mob_ratiofloat: mobility ratio to be used default 1.0

Returns:

pandas dataframe of shape (n,m): estimated particle number size distribution

References

Li et al. (2022), https://doi.org/10.1080/02786826.2022.2060795

aerosol.functions.mean_free_path(temp, pres, gas='air')[source]¶

Calculate mean free path in air

Parameters:

tempfloat or series of length n: air temperature, unit: K
presfloat or series of length n: air pressure, unit: Pa
gasstr: air (default) or nitrogen

Returns:

float or series of length n: mean free path in gas, unit: m

aerosol.functions.nanoranking(conc, nan_threshold=0, include_concs=False)[source]¶

Simplified method of calculating the nanorank

Parameters:

concpandas series: number concentration time series in the diameter range of interst
nan_thresholdfloat: maximum fraction of nans when calculating the number concentartion for each day
include_concsboolean: Include the background removed concentrations for each day in the results or not

Returns:

dictionary

the result dictionary has the following keys:

norm_conc: Concentration with removed background (if include_concs = True)

rank: Value of the peak normalized concentration

rank_time: Time where the peak occurs

Notes

The nanorank is calculated for one day. See Aliaga et al 2023

aerosol.functions.particle_diffusivity(dp, temp=293.15, pres=101325.0, gas='air')[source]¶

Particle brownian diffusivity in air

Parameters:

dpfloat or series of lenght m: particle diameter, unit: m
tempfloat or series of lenght n: air temperature, unit: K
presfloat or series of lenght n: air pressure, unit: Pa
gasstr: air (default) or nitrogen

Returns:

float or dataframe of shape (n,m): Particle Brownian diffusivity in air unit m2 s-1

aerosol.functions.particle_mean_free_path(dp, temp=293.15, pres=101325.0, gas='air')[source]¶

Particle mean free path in air

Parameters:

dpfloat or series of length m: particle diameter, unit: m
tempfloat or series of length n: air temperature, unit: K
presfloat or series of length n: air pressure, unit: Pa
gasstr: air (default) or nitrogen

Returns:

float or dataframe of shape (n,m): Particle mean free path, unit: m

aerosol.functions.particle_thermal_speed(dp, temp)[source]¶

Particle thermal speed

Parameters:

dpfloat or series: particle diameter, unit: m
tempfloat or series: air temperature, unit: K

Returns:

float or dataframe: Particle thermal speed point, unit: m s-1

aerosol.functions.sample_from_dist(x, y, n)[source]¶

Draw n samples from empirical distribution defined by points (x,y)

Parameters:

xnumpy array: x-data points
ynumpy array: y-data points
nint: number of samples to draw

Returns:

numpy array: samples drawn

aerosol.functions.slipcorr(dp, temp=293.15, pres=101325.0, gas='air')[source]¶

Slip correction factor in gas

Parameters:

dpfloat or series of lenght m: particle diameter, unit m
tempfloat or series of length n: air temperature, unit K
presfloat or series of lenght n: air pressure, unit Pa
gasstr: air (default) or nitrogen

Returns:

float or dataframe fo shape (n,m): For dataframe the index is taken from temperature or pressure series. Columns are particle diameters. unit dimensionless

Notes

Correction is done according to Mäkelä et al. (1996)

aerosol.functions.surf_dist(df)[source]¶

Calculate the aerosol surface area size distribution

Parameters:

dfpandas.DataFrame: Aerosol number-size distribution

Returns:

pandas.DataFrame: Aerosol surface area-size distribution unit: m2 cm-3

aerosol.functions.utc2solar(utc_time, lon, lat)[source]¶

Convert utc time to solar time (solar maximum occurs at noon)

Parameters:

utc_timepandas Timestamp
lonfloat: Location’s longitude
latfloat: Location’s latitude

Returns:

pandas Timestamp: solar time

aerosol.functions.vol_dist(df)[source]¶

Calculate the aerosol volume size distribution

Parameters:

dfpandas.DataFrame: Aerosol number-size distribution

Returns:

pandas.DataFrame: Aerosol volume-size distribution unit: m3 cm-3

Plotting Module¶

aerosol.plotting.generate_log_ticks(min_exp, max_exp, minor=False)[source]¶

Generate ticks and ticklabels for log axis

Parameters:

min_expint: The exponent in the smallest power of ten
max_expint: The exponent in the largest power of ten

Returns:

numpy.array: minor tick values
numpy.array: major tick values
list of strings: major tick labels (powers of ten)

aerosol.plotting.generate_timeticks(t_min, t_max, minortick_interval, majortick_interval, ticklabel_format)[source]¶

Parameters:

t_minpandas timestamp
t_maxpandas timestamp
majortick_intervalpandas date frequency string: See for all options here: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
minortick_intervalpandas date frequency string
ticklabel_formatpython date format string: See for all options here: https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-code

Returns:

pandas DatetimeIndex: minor tick values
pandas DatetimeIndex: major tick values
pandas Index containing strings: major tick labels

aerosol.plotting.plot_aerosol_dist(v, ax, norm='log', clim=None, cmap='turbo', xmajortick_interval=None, xminortick_interval=None, xticklabel_format='%Y-%m-%d %H:%M')[source]¶

Plot aerosol particle number-size distribution surface plot

Parameters:

vpandas.DataFrame or list of pandas.DataFrames: Aerosol number size distribution (continuous index)
axaxes object: axis on which to plot the data
normstring: Define how to normalize the colors. “linear” or “log”
climlist with two elements or None: Minimum and maximum value in colorbar, None calculates automatic limits
xminortick_intervalpandas date frequency string: See for all options here: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
xmajortick_intervalpandas date frequency string
xticklabel_formatstr: See for all options here: https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-code

Returns:

image handle
colorbar handle

aerosol.plotting.plot_one_to_one_line(ax=None, color='black', linestyle='--', linewidth=1, shade_frac=0.1, shade_color='grey', shade_alpha=0.3)[source]¶

Plot a 1:1 reference line and a shaded fractional deviation region.

The function plots a line corresponding to y = x within the overlapping visible axis range and optionally shades a symmetric fractional interval around the line (e.g. ±10%).

Parameters:

axmatplotlib.axes.Axes, optional: Matplotlib axes object on which to draw the line and shaded region. If None, the current axes returned by matplotlib.pyplot.gca() are used.
colorstr, default=’black’: Color of the 1:1 reference line.
linestylestr, default=’–’: Line style of the 1:1 reference line.
linewidthfloat, default=1: Width of the 1:1 reference line.
shade_fracfloat, default=0.10: Fractional deviation used for the shaded region around the 1:1 line. For example, 0.10 corresponds to a ±10% region.
shade_colorstr, default=’grey’: Fill color of the shaded fractional deviation region.
shade_alphafloat, default=0.3: Alpha transparency value for the shaded region.

Returns:

line_handlematplotlib.lines.Line2D: Handle to the plotted 1:1 line.
shade_handlematplotlib.collections.FillBetweenPolyCollection: Handle to the shaded fractional deviation region.

Notes

The original axis limits are restored after plotting to avoid modifying the current view extent.

Examples

>>> fig, ax = plt.subplots()
>>> ax.scatter(x, y)
>>> plot_one_to_one_line(ax=ax, shade_frac=0.2)

aerosol.plotting.rotate_xticks(ax, degrees)[source]¶

Parameters:

axmatplotlib axes
degreesint or float: number of degrees to rotate the xticklabels

aerosol.plotting.show_matrix_values(ax, matrix, text_format='%d', text_color='white')[source]¶

Plot numerical values on top of the cells when visualizing a matrix with imshow()

Parameters:

axmatplotlib.axes
matrixnumpy 2d-array
text_formatstr
text_colorstr

aerosol.plotting.subplot_aerosol_dist(vlist, grid, norm='log', vmin=10, vmax=10000, xminortick_interval='1H', xmajortick_interval='2H', xticklabel_format='%H:%M', keep_inner_ticklabels=False, hspace_padding=None, vspace_padding=None, subplot_labels=None, label_color='black', label_size=10, column_titles=None, fill_order='row', **kwargs)[source]¶

Plot aerosol size distributions (subplots)

Parameters:

vlistlist of pandas.DataFrames: Aerosol size distributions (continuous index)
gridtuple (rows,columns): define number of rows and columns
normstring: Define how to normalize the colors. “linear” or “log”
vminfloat or int: Minimum value in colorbar
vmaxfloat or int: Maximum value in colorbar
xminortick_intervalstr: A pandas date frequency string. See for all options here: https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#offset-aliases
xmajortick_intervalstr: A pandas date frequency string
xticklabel_formatstr: Date format string. See for all options here: https://docs.python.org/3/library/datetime.html#strftime-and-strptime-format-code
keep_inner_ticklabelsbool: If True, use ticklabels in all subplots. If False, use ticklabels only on outer subplots.
subplot_paddingnumber or None: Adjust space between subplots
subplot_labelslist of str or None: The labels to put to labels the subplots with
label_colorstr
label_sizefloat
column_titleslist of strings or None
fill_orderstr: “rows” fills the subplots row by row “columns” fills the subplots column by column
**kwargsoptional parameters passed to matplotlib imshow()

Returns:

figure object
array of axes objects
list of image handles
colorbar handle

Fitting Module¶

aerosol.fitting.fit_multimode(x, y, timestamp=None, n_modes=1, n_samples=10000)[source]¶

Fit multimodal Gaussian to aerosol number-size distribution

Parameters:

x1d numpy array: log10 of bin diameters in nm.
y1d numpy array: Number size distribution
timestamppandas Timestamp or None: timestamp associated with the number size distributions
n_modesint: number of modes to fit
n_samplesint: Number of samples to draw from the distribution during the fitting process.

Returns:

dictionary:: Fit results

aerosol.fitting.fit_multimodes(df, n_modes=1, n_samples=10000)[source]¶

Fit multimodal Gaussian to a aerosol number size distribution (dataframe)

Parameters:

dfpandas DataFrame: Aerosol number size distribution
n_modesint: Number of modes to fit
n_samplesint: Number of samples to draw from the distribution during the fitting process.

Returns:

list:: List of fit results

Lab Module¶

aerosol.lab.calc_equiv_loss_tube_length(q, l_ref, q_ref)[source]¶

Calculate tube length to match losses for different flow rates

Parameters:

qfloat: Flow rate in the tube
l_reffloat: Length of the reference tube
q_reffloat: Flow rate in the reference tube

Returns:

float: Length of the tube

aerosol.lab.calc_peg_dp(m_peg)[source]¶

Calculate mobility diameter for PEG molecule of a given mass

Parameters:

m_pegfloat: PEG mass in g/mol

Returns:

float: PEG mobility diameter in nm

References

See https://pubs.acs.org/doi/10.1021/ac034138m

aerosol.lab.calc_peg_mob(m_peg)[source]¶

Calculate mobility for PEG molecule of a given mass

Parameters:

m_pegfloat: PEG mass in g/mol

Returns:

float: PEG mobility in cm2 V-1 s-1

References

See https://pubs.acs.org/doi/10.1021/ac034138m

aerosol.lab.calc_tube_residence_time(tube_diam, tube_length, flowrate)[source]¶

Calculate residence time in a circular tube

Parameters:

tube_diamfloat or series of length m: Inner diameter of the tube (m)
tube_lengthfloat or series of length m: Length of the tube (m)
flowratefloat or series of length n: Volumetric flow rate (lpm)

Returns:

float or dataframe of shape (n,m): Average residence time in seconds

aerosol.lab.conical_dma_mob2volts(Q, R1_max, R2, L, alpha, Z)[source]¶

Conical DMA voltage corresponding to mobility

Parameters:

Qfloat: sheath flow rate, unit lpm
R1_maxfloat: inner electrode radius at outlet at distance L, unit m
R2float: outer electrode radius, unit m
Lfloat: effective electrode length, unit m
alphafloat: tapering angle, unit degrees
Zfloat: mobility, unit cm2 s-1 V-1

Returns:

float: DMA voltage, unit V

aerosol.lab.det_eff_fit(diams, det_effs)[source]¶

Fit activation curve to detection efficiency data

The below function is used in the fit:

\[\eta (d_p) = \eta_{\infty}\times \left( 1 - \exp \left( -\frac{d_p - d_{p50}}{d_{p50} - d_{p0}} \right) \times \log 2 \right) \]

Parameters:

diams1-d array: Selected diameters in nm
det_effs1-d array: Measured detection efficiencies

Returns:

list

Fitted parameters

Plateau detection efficiency
dp50
dp0

list

parameter standard deviations

aerosol.lab.diam2mob(dp, temp=293.15, pres=101325.0, ne=1, gas='air')[source]¶

Convert electrical mobility diameter to electrical mobility in gas

Parameters:

dpfloat: particle diameter(s), unit : nm
tempfloat: ambient temperature default 20 C unit: K
presfloat: ambient pressure, default 1 atm unit: Pa
neint: number and polarity of charges on the aerosol particle default 1
gasstr: air (default) or nitrogen

Returns:

float: particle electrical mobility, unit: cm2 s-1 V-1

aerosol.lab.dma_mob2volts(Q, R1, R2, L, Z)[source]¶

Cylindrical DMA voltage corresponding to mobility

Parameters:

Qfloat: sheath flow rate, unit lpm
R1float: inner electrode radius, unit m
R2float: outer electrode radius, unit m
Lfloat: effective electrode length, unit m
Zfloat: mobility, unit cm2 s-1 V-1

Returns:

float: DMA voltage, unit V

aerosol.lab.dma_volts2mob(Q, R1, R2, L, V)[source]¶

Theoretical selected mobility from cylindrical DMA

Parameters:

Qfloat: sheath flow rate, unit lpm
R1float: inner electrode radius, unit m
R2float: outer electrode radius, unit m
Lfloat: effective electrode length, unit m
Vfloat or series: applied voltage, unit V

Returns:

float or series: selected mobility, unit cm2 s-1 V-1

aerosol.lab.eq_charge_frac(dp, N)[source]¶

Calculate equilibrium charge fraction using Wiedensohler (1988) approximation

Parameters:

dpfloat: Particle diameter (m)
Nint: Amount of elementary charge in range [-2,2]

Returns:

float: Fraction of particles of diameter dp having N elementary charges

aerosol.lab.flow_velocity_in_pipe(tube_diam, flowrate)[source]¶

Calculate fluid speed from the flow rate in circular tube

Parameters:

tube_diamfloat or series of lenght m: Diameter of circular tube (m)
flowratefloat or series of lenght n: Volumetric flow rate (lpm)

Returns:

float or dataframe of shape (n,m): Speed of fluid (m/s)

aerosol.lab.mob2diam(Zp, temp=293.15, pres=101325.0, ne=1, tol=0.001, maxiter=100, gas='air')[source]¶

Convert electrical mobility to electrical mobility diameter in gas

Parameters:

Zpfloat: particle electrical mobility or mobilities, unit: cm2 s-1 V-1
tempfloat: ambient temperature, unit: K
presfloat: ambient pressure, unit: Pa
neinteger: number and polarity of elementary charges on the aerosol particle
gasstr: air (default) or nitrogen

Returns:

float: particle diameter, unit: m

aerosol.lab.pipe_reynolds(tube_diam, flowrate, temp=293.15, pres=101325.0)[source]¶

Calculate Reynolds number in a tube

Parameters:

tube_diamfloat or series of length m: Inner diameter of the tube (m)
flowratefloat or series of lenght n: Volumetric flow rate (lpm)
tempfloat or series of length n: Temperature in K
presfloat or series of length n: Pressure in Pa

Returns:

float or dataframe of shape (n,m): Reynolds number

aerosol.lab.refmob_dp2volts(ref_voltage, dp, gas='air', ref_mobility=0.97)[source]¶

Convert particle diameters to DMA voltages

Parameters:

ref_voltagefloat

Voltage at the reference mobility peak (V)

dpfloat or series

Particle diameters (nm)

gasstr

air (default) or nitrogen

ref_mobilityfloat

Reference mobility (cm2 V-1 s-1)

Default is the THA+ monomer as STP (0.97 cm2 V-1 s-1)

Returns:

float or series:: DMA voltage (V) corresponding to dp

aerosol.lab.refmob_volts2dp(ref_voltage, dma_voltage, gas='air', ref_mobility=0.97)[source]¶

Convert DMA voltages to particle diameters

Parameters:

ref_voltagefloat

Voltage at the reference mobility peak (V)

dma_voltagefloat

DMA voltage (V)

gasstr

air (default) or nitrogen

ref_mobilityfloat

Reference mobility (cm2 V-1 s-1)

Default is the THA+ monomer at STP (0.97 cm2 V-1 s-1)

Returns:

float:: particle diameter corresponding to DMA voltage (nm)

aerosol.lab.tubeloss(diam, flowrate, tubelength, temp=293.15, pres=101325.0)[source]¶

Calculate diffusional particle losses to walls of straight cylindrical tube assuming a laminar flow regime

Parameters:

diamfloat or series of length m: Particle diameters for which to calculate the losses, unit: m
flowratefloat or series of length n: unit: L/min
tubelengthfloat: Length of the cylindrical tube unit: m
tempfloat or series of length n: temperature unit: K
presfloat or series of lenght n: air pressure unit: Pa

Returns:

float or dataframe of shape (n,m): Fraction of particles passing through. Each column represents diameter and each each row represents different temperature pressure and flowrate value

aerosol.lab.tubeloss_turbulent(diam, flowrate, tube_length, tube_diam, temp=293.15, pres=101325.0)[source]¶

Calculate particle losses to walls of a straight cylindrical tube assuming a turbulent flow regime and air as the carrier gas.

Parameters:

diamfloat or series of length m: Particle diameters for which to calculate the losses, unit: m
flowratefloat or series of length n: unit: L/min
tube_lengthfloat: Length of the cylindrical tube unit: m
tube_diamfloat: Diameter of the cylindrical tube unit: m
tempfloat or series of length n: temperature unit: K
presfloat or series of lenght n: air pressure unit: Pa

Returns:

float or dataframe of shape (n,m): Fraction of particles passing through. Each column represents diameter and each each row represents different temperature pressure and flowrate value