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Ice nucleating particles (INPs) are a rare subset of particles that can have an outsized impact relative to their prevalence. To simulate INP variability, models require parameterizations for the most important sources of INPs. Most parameterizations in the literature were developed from laboratory experiments that used proxies for ambient particles. Whether these laboratory models effectively represent ambient aerosol is still not well understood and parameterizations developed from field measurements may be more atmospherically relevant. Expanding on previous work in which we used an ice chamber and a single‐particle mass spectrometer (SPMS) to characterize INP composition, we calculate heterogeneous ice nucleation rate coefficients for ambient particles. We find good agreement between our dust and previous measurements of airborne dust. We also use a Monte Carlo approach to assess the relative contribution of each measurement to the uncertainty and find that the biggest source is the sampling efficiency of the SPMS. Plain Language Summary: Ice nucleation activity is typically parameterized using results from laboratory experiments. However, whether these parameterizations accurately represent the ice nucleation activity of ambient aerosol is not well understood. In this work, we develop a novel framework for deriving ice nucleation rate coefficients from ambient measurements, and apply these methods to an ambient data set using a Monte Carlo approach. Key Points: An integrated CFDC and ATOFMS were used to derive particle‐type specific heterogeneous ice nucleation rate coefficients for ambient aerosolDust ice nucleation rate coefficients were within 2–5‐fold of previous estimatesThese are the first published measurements of nucleation rate coefficients for sea spray aerosol [ABSTRACT FROM AUTHOR]