Lakes are considered the second largest natural source of atmospheric methane (CH4). However, current estimates are still uncertain and do not account for diel variability of CH4 emissions. In this study, we performed high-resolution measurements of CH4 flux from several lakes, using an automated and sensor-based flux measurement approach (in total 4,580 measurements), and demonstrated a clear and consistent diel lake CH4 flux pattern during stratification and mixing periods. The maximum of CH4 flux were always noted between 10:00 and 16:00, whereas lower CH4 fluxes typically occurred during the nighttime (00:00–04:00). Regardless of the lake, CH4 emissions were on an average 2.4 higher during the day compared to the nighttime. Fluxes were higher during daytime on nearly 80% of the days. Accordingly, estimates and extrapolations based on daytime measurements only most likely result in overestimated fluxes, and consideration of diel variability is critical to properly assess the total lake CH4 flux, representing a key component of the global CH4 budget. Hence, based on a combination of our data and additional literature information considering diel variability across latitudes, we discuss ways to derive a diel variability correction factor for previous measurements made during daytime only.

This is of the same order of magnitude as the CO 2 emissions from land use change, or the carbon transport from continents to the ocean (Ciais et al., 2013), making CO 2 emissions from lakes important in the global carbon cycle. Lakes are concentrated in boreal regions, which contain roughly 30% of global lakes (Downing et al., 2006;Verpoorter et al., 2014), and together with the arctic region contribute 17% of global lake CO 2 emissions (Aufdenkampe et al., 2011). Potential climate change effects in boreal lakes, including increased runoff (Larsen et al., 2011;Weyhenmeyer et al., 2015) and increased carbon mineralization rates (Bergström Abstract Lakes are generally supersaturated in carbon dioxide (CO 2 ) and emitters of CO 2 to the atmosphere. However, estimates of CO 2 flux ( CO 2 E F ) from lakes are seldom based on direct flux measurements and usually do not account for nighttime emissions, yielding risk of biased assessments.Here, we present direct CO 2 E F measurements from automated floating chambers collected every 2-3 hr and spanning 115 24 hr periods in three boreal lakes during summer stratification and before and after autumn mixing in the most eutrophic lake of these. We observed 40%-67% higher mean CO 2 E F in daytime during periods of surface water CO 2 supersaturation in all lakes. Day-night differences in wind speed were correlated with the day-night CO 2 E F differences in the two larger lakes, but in the smallest and most wind-sheltered lake peaks of CO 2 E F coincided with low-winds at night. During stratification in the eutrophic lake, CO 2 was near equilibrium and diel variability of CO 2 E F insignificant, but after autumn mixing CO 2 E F was high with distinct diel variability making this lake a net CO 2 source on an annual basis.We found that extrapolating daytime measurements to 24 hr periods overestimated CO 2 E F by up to 30%, whereas extrapolating measurements from the stratified period to annual rates in the eutrophic lake underestimated CO 2 E F by 86%. This shows the importance of accounting for diel and seasonal variability in lake CO 2 emission estimates.Plain Language Summary Considerable carbon cycling occurs within lakes, and carbon inputs from the catchment can be processed internally, stored in sediment and biomass or transported downstream. Additionally, carbon is exchanged with the atmosphere, resulting in lake uptake or atmospheric emission of carbon dioxide. Carbon dioxide exchanges from lakes have globally significant implications, but may be highly variable in time in ways that are not yet accounted for in emission estimates. Here, we estimated carbon dioxide exchange during multiple days and nights in three lakes with different nutrient levels during summer and autumn. For the most nutrient rich lake we also covered the period of water column mixing in autumn, which constitutes a critical time for carbon exchange. When carbon dioxide emission exceeded uptake, we found 40%-67% higher average exchange rates during daytime than nighttime. In contrast, the most nutrient...

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Methane (CH4) is an important component of the carbon (C) cycling in lakes. CH4 production enables carbon in sediments to be either reintroduced to the food web via CH4 oxidation or emitted as a greenhouse gas making lakes one of the largest natural sources of atmospheric CH4. Large stable carbon isotopic fractionation during CH4 oxidation makes changes in 13C:12C ratio (δ13C) a powerful and widely used tool to determine the extent to which lake CH4 is oxidized, rather than emitted. This relies on correct δ13C values of original CH4 sources, the variability of which has rarely been investigated systematically in lakes. In this study, we measured δ13C in CH4 bubbles in littoral sediments and in CH4 dissolved in the anoxic hypolimnion of six boreal lakes with different characteristics. The results indicate that δ13C of CH4 sources is consistently higher (less 13C depletion) in littoral sediments than in deep waters across boreal and subarctic lakes. Variability in organic matter substrates across depths is a potential explanation. In one of the studied lakes available data from nearby soils showed correspondence between δ13C-CH4 in groundwater and deep lake water, and input from the catchment of CH4via groundwater exceeded atmospheric CH4 emissions tenfold over a period of 1 month. It indicates that lateral hydrological transport of CH4 can explain the observed δ13C-CH4 patterns and be important for lake CH4 cycling. Our results have important consequences for modelling and process assessments relative to lake CH4 using δ13C, including for CH4 oxidation, which is a key regulator of lake CH4 emissions.

Large greenhouse gas emissions occur via the release of carbon dioxide (CO 2 ) and methane (CH 4 ) from the surface layer of lakes. Such emissions are modeled from the air− water gas concentration gradient and the gas transfer velocity (k). The links between k and the physical properties of the gas and water have led to the development of methods to convert k between gases through Schmidt number normalization. However, recent observations have found that such normalization of apparent k estimates from field measurements can yield different results for CH 4 and CO 2 . We estimated k for CO 2 and CH 4 from measurements of concentration gradients and fluxes in four contrasting lakes and found consistently higher (on an average 1.7 times) normalized apparent k values for CO 2 than CH 4 . From these results, we infer that several gas-specific factors, including chemical and biological processes within the water surface microlayer, can influence apparent k estimates. We highlight the importance of accurately measuring relevant air−water gas concentration gradients and considering gas-specific processes when estimating k.