We demonstrate that the thermodynamic properties of a single liquid aerosol droplet can be explored through the combination of a single-beam gradient force optical trap with Raman spectroscopy. A single aqueous droplet, 2-6 microm in radius, can be trapped in air indefinitely and the response of the particle to variations in relative humidity investigated. The Raman spectrum provides a unique fingerprint of droplet composition, temperature, and size. Spontaneous Raman scattering is shown to be consistent with that from a bulk phase sample, with the shape of the OH stretching band dependent on the concentration of sodium chloride in the aqueous phase and on the polarization of the scattered light. Stimulated Raman scattering at wavelengths commensurate with whispering gallery modes is demonstrated to provide a method for determining the size of the trapped droplet with nanometer precision and with a time resolution of 1 s. The polarization dependence of the stimulated scatter is consistent with the dependence observed for the spontaneous scatter from the droplet. By characterizing the spontaneous and stimulated Raman scattering from the droplet, we demonstrate that it is possible to measure the equilibrium size and composition of an aqueous droplet with variation in relative humidity. For this benchmark study we investigate the variation in equilibrium size with relative humidity for a simple binary sodium chloride/aqueous aerosol, a typical representative inorganic/aqueous aerosol that has been studied extensively in the literature. The measured equilibrium sizes are shown to be in excellent agreement with the predictions of Köhler theory. We suggest that this approach could provide an important new strategy for characterizing the thermodynamic properties and kinetics of transformation of aerosol particles.

Abstract. Warm and dry climatological conditions favour the occurrence of forest fires. These fires then become a significant emission source to the atmosphere. Despite this global importance, fires are a local phenomenon and are difficult to represent in large-scale Earth system models (ESMs). To address this, the INteractive Fire and Emission algoRithm for Natural envirOnments (INFERNO) was developed. IN-FERNO follows a reduced complexity approach and is intended for decadal-to centennial-scale climate simulations and assessment models for policy making. Fuel flammability is simulated using temperature, relative humidity (RH) and fuel load as well as precipitation and soil moisture. Combining flammability with ignitions and vegetation, the burnt area is diagnosed. Emissions of carbon and key species are estimated using the carbon scheme in the Joint UK Land Environment Simulator (JULES) land surface model. JULES also possesses fire index diagnostics, which we document and compare with our fire scheme. We found INFERNO captured global burnt area variability better than individual indices, and these performed best for their native regions. Two meteorology data sets and three ignition modes are used to validate the model. INFERNO is shown to effectively diagnose global fire occurrence (R = 0.66) and emissions (R = 0.59) through an approach appropriate to the complexity of an ESM, although regional biases remain.

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