Ambient aerosol particles

[maxicloco]

Hello, I am using pycontails to not only simulate contrails due to Jet A-1 or SAF but also liquid hydrogen combustion. Since there are no additional nvPM Emissions due to LH2 the ambient aerosol concentration becomes more important. At the moment a "min_ice_particle_number_nvpm_ei_n" is defined to account for ambient aerosol particles in case the nvPM are below this threshhold. Unfortunatly the ice particle number is thereafter calculated with the fuel per segment length
("return fuel_dist * np.maximum(nvpm_ei_n_activated, min_ice_particle_number_nvpm_ei_n) * f_surv").
This is unproblematic for Jet A-1 and SAF but the fuel consumption for LH2 is only about 30 %. In order to simulate LH2 it would probably be better to take a ambient aerosol concentration not dependent on the fuel consumption. If I have made a mistake please let me know and thank you in advance! I am using pycontrails V0.49.0

[thabbott]

Thanks for starting this discussion, @maxicloco. We're taking a look at this and will follow up soon!

[thabbott]

I think you bring up a good point, @maxicloco. min_ice_particle_number_nvpm_ei_n is currently used to represent activation of secondary aerosols produced by engine emissions and ambient aerosols:

pycontrails/pycontrails/models/cocip/contrail_properties.py

Lines 204 to 218 in 2c35205

	def ice_particle_number(
	nvpm_ei_n: npt.NDArray[np.float_],
	fuel_dist: npt.NDArray[np.float_],
	iwc: npt.NDArray[np.float_],
	iwc_1: npt.NDArray[np.float_],
	air_temperature: npt.NDArray[np.float_],
	T_crit_sac: npt.NDArray[np.float_],
	min_ice_particle_number_nvpm_ei_n: float,
	) -> npt.NDArray[np.float_]:
	"""Calculate the initial number of ice particles per distance after the wake vortex phase.
	The initial number of ice particle per distance is calculated from the black
	carbon number emissions index ``nvpm_ei_n`` and fuel burn per distance ``fuel_dist``.
	Note that a lower bound for ``nvpm_ei_n`` is set at ``1e13`` :math:`kg^{-1}` to account
	for the activation of ambient aerosol particles and organic volatile particles.

Scaling by fuel consumption seems like the right thing to do for secondary aerosols, since they form from combustion byproducts. As you point out, it's probably not the ideal way to represent ambient aerosols.

We could think about separating min_ice_particle_number_nvpm_ei_n into two parameters: one that represents activation of secondary aerosols by setting a floor for nvpm_ei_n, and a second parameter that enters the ice particle number calculation independently from fuel_dist and represents activation of ambient aerosols. The details might be tricky, though. Converting an ambient aerosol number concentration (dimensions of number per volume) to an ice particle number (dimensions of number per distance) would require knowing the plume area at time of nucleation, which isn't something we have to worry about in the current ice particle number calculation.

If we did this, we'd also want to make the floor for nvpm_ei_n dependent on fuel type, since only certain fuels produce secondary aerosols.

@zebengberg and @trdean1, what do you think about moving this to an issue? (I would classify it as a feature request rather than a bug fix. Our current approach seems fine for Jet-A and SAF, but figuring out a way to better represent nucleation on ambient aerosols might be more appropriate for LH2.)

[roger-teoh]

Hi @maxicloco , thank you for your question. We have previously used pycontrails to perform an exploratory study to evaluate the effects of liquid hydrogen (LH2) on the change in persistent contrail formation, properties, and climate forcing. We had to resolve these similar questions and came up with the following workaround that is consistent with what was proposed by @thabbott :

• You are right that the lower calorific value of LH2 is higher than Jet A, and therefore, the fuel consumption per flight distance flown should be smaller than conventional fuels. We assume that the fuel consumption for LH2 scales as a ratio of the lower calorific value of the Jet A divided by the LH2 fuel.
• As we do not know the exact ambient aerosol concentration, we reverted to a sensitivity analysis and assume a fixed "nvPM" EIn of 10^13, 10^14, and 10^15 particles/kg at all flight waypoints to approximate for the potential differences in the activation of ambient aerosols. This EIn range was informed by Fig. 3 of Karcher et al. (2018) Formation and radiative forcing of contrail cirrus

We acknowledge that this solution is not ideal, but it should provide a quick workaround to the issues you are facing. We agree that the global spatiotemporal variability in ambient aerosol concentration is important for the simulation of LH2, and are currently working on incorporating this feature into pycontrails. Depending on development priorities, we expect this feature to be integrated in pycontrails within two months.

[maxicloco]

Hello @thabbott and @roger-teoh , thanks to both of you for the detailed updates and information! Thanks @roger-teoh for your solution for the problem. I am really looking forward to the coming updates! I would end the discussion as resolved.