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Abstract. Waters impounded behind dams (i.e., reservoirs) areimportant sources of greenhouses gases (GHGs), especially methane (CH4), butemission estimates are not well constrained due to high spatial and temporalvariability, limitations in monitoring methods to characterize hot spot andhot moment emissions, and the limited number of studies that investigatediurnal, seasonal, and interannual patterns in emissions. In this study, weinvestigate the temporal patterns and biophysical drivers of CH4emissions from Acton Lake, a small eutrophic reservoir, using a combinationof methods: eddy covariance monitoring, continuous warm-season ebullitionmeasurements, spatial emission surveys, and measurements of key drivers ofCH4 production and emission. We used an artificial neural network togap fill the eddy covariance time series and to explore the relativeimportance of biophysical drivers on the interannual timescale. We combinedspatial and temporal monitoring information to estimate annualwhole-reservoir emissions. Acton Lake had cumulative areal emission rates of45.6 ± 8.3 and 51.4 ± 4.3 g CH4 m−2 in 2017 and 2018,respectively, or 109 ± 14 and 123 ± 10 Mg CH4 in 2017 and2018 across the whole 2.4 km2 area of the lake. The main differencebetween years was a period of elevated emissions lasting less than 2 weeksin the spring of 2018, which contributed 17 % of the annual emissions inthe shallow region of the reservoir. The spring burst coincided with aphytoplankton bloom, which was likely driven by favorable precipitation andtemperature conditions in 2018 compared to 2017. Combining spatiallyextensive measurements with temporally continuous monitoring enabled us toquantify aspects of the spatial and temporal variability in CH4emission. We found that the relationships between CH4 emissions andsediment temperature depended on location within the reservoir, and we observed a clearspatiotemporal offset in maximum CH4 emissions as a function ofreservoir depth. These findings suggest a strong spatial pattern in CH4biogeochemistry within this relatively small (2.4 km2) reservoir. Inaddressing the need for a better understanding of GHG emissions fromreservoirs, there is a trade-off in intensive measurements of one water bodyvs. short-term and/or spatially limited measurements in many waterbodies. The insights from multi-year, continuous, spatially extensivestudies like this one can be used to inform both the study design andemission upscaling from spatially or temporally limited results,specifically the importance of trophic status and intra-reservoirvariability in assumptions about upscaling CH4 emissions. 

Abstract. Acidity, defined as pH, is a central component of aqueouschemistry. In the atmosphere, the acidity of condensed phases (aerosolparticles, cloud water, and fog droplets) governs the phase partitioning ofsemivolatile gases such as HNO3, NH3, HCl, and organic acids andbases as well as chemical reaction rates. It has implications for theatmospheric lifetime of pollutants, deposition, and human health. Despiteits fundamental role in atmospheric processes, only recently has this fieldseen a growth in the number of studies on particle acidity. Even with thisgrowth, many fine-particle pH estimates must be based on thermodynamic modelcalculations since no operational techniques exist for direct measurements.Current information indicates acidic fine particles are ubiquitous, butobservationally constrained pH estimates are limited in spatial and temporalcoverage. Clouds and fogs are also generally acidic, but to a lesser degreethan particles, and have a range of pH that is quite sensitive toanthropogenic emissions of sulfur and nitrogen oxides, as well as ambientammonia. Historical measurements indicate that cloud and fog droplet pH haschanged in recent decades in response to controls on anthropogenicemissions, while the limited trend data for aerosol particles indicateacidity may be relatively constant due to the semivolatile nature of thekey acids and bases and buffering in particles. This paper reviews andsynthesizes the current state of knowledge on the acidity of atmosphericcondensed phases, specifically particles and cloud droplets. It includesrecommendations for estimating acidity and pH, standard nomenclature, asynthesis of current pH estimates based on observations, and new modelcalculations on the local and global scale.