Trends in source gases

Source gases are defined as those gases that, by their breakdown, introduce into the stratosphere halogen, hydrogen, and nitrogen compounds that are important in stratospheric ozone destruction. Given here is an update of the existing concentration time series for chlorocarbons, nitrous oxide, and methane. Also reviewed is information on halogen containing species and the use of these data for establishing trends. Also reviewed is evidence on trends in trace gases that influence tropospheric chemistry and thus the tropospheric lifetimes of source gases, such as carbon dioxide, carbon monoxide, or nitrogen oxides. Much of the information is given in tabular form

Impact of changes in barometric pressure on landfill methane emission

Citation: Xu, Liukang, Xiaomao Lin, Jim Amen, Karla Welding, and Dayle McDermitt. “Impact of Changes in Barometric Pressure on Landfill Methane Emission.” Global Biogeochemical Cycles 28, no. 7 (2014): 679–95. https://doi.org/10.1002/2013GB004571.Landfill methane emissions were measured continuously using the eddy covariance method from June to December 2010. The study site was located at the Bluff Road Landfill in Lincoln, Nebraska, USA. Our results show that landfill methane emissions strongly depended on changes in barometric pressure; rising barometric pressure suppressed the emission, while falling barometric pressure enhanced the emission, a phenomenon called barometric pumping. There was up to a 35-fold variation in day-to-day methane emissions due to changes in barometric pressure. Wavelet coherence analysis revealed a strong spectral coherency between variations of barometric pressure and methane emission at periodicities ranging from 1 day to 8 days. Power spectrum and ogive analysis showed that at least 10 days of continuous measurements was needed in order to capture 90% of the total variance in the methane emission time series at our landfill site. From our results, it is clear that point-in-time measurements taken at monthly or longer time intervals using techniques such as the trace plume method, the mass balance method, or the closed-chamber method will be subject to large variations in measured emission rates because of the barometric pumping phenomenon. Estimates of long-term integrated methane emissions from landfills based on such measurements could yield uncertainties, ranging from 28.8% underestimation to 32.3% overestimation. Our results demonstrate a need for continuous measurements to quantify annual total landfill emissions. This conclusion may apply to the study of methane emissions from wetlands, peatlands, lakes, and other environmental contexts where emissions are from porous media or ebullition. Other implications from the present study for hazard gas monitoring programs are also discussed

Methane and carbon monoxide emissions from asphalt pavement: Measurements and estimates of their importance to global budgets

We measured emissions of methane from asphalt surfaces used in pavement for roadways. Maximum emissions were 22 mg/m2/yr for 1- to 4-week-old pavement during maximum sunlight intensity. Emissions were much smaller at low sunlight intensity and dropped off to negligible amounts at night. Smaller emissions were observed for asphalt pavement of 2.5 to 3 years approximate age under similar conditions. Companion measurements of carbon monoxide emissions resulted in maximum emissions of about 2.6 mg/m2/hr for 1-wk-old pavement. These findings indicate that emissions of CH4 and CO are a function of both sunlight and temperature. Based on our results, methane emissions from asphalt pavement cannot be a significant source of atmospheric methane. -from Author

Statistical inference of OH concentrations and air mass dilution rates from successive observations of non-methane hydrocarbons in single air masses

Bayesian inference has been used to determine rigorous estimates of hydroxyl radical concentrations () and air mass dilution rates (K) averaged following air masses between linked observations of nonmethane hydrocarbons (NMHCs) spanning the North Atlantic during the Intercontinental Transport and Chemical Transformation (ITCT)-Lagrangian-2K4 experiment. The Bayesian technique obtains a refined (posterior) distribution of a parameter given data related to the parameter through a model and prior beliefs about the parameter distribution. Here, the model describes hydrocarbon loss through OH reaction and mixing with a background concentration at rate K. The Lagrangian experiment provides direct observations of hydrocarbons at two time points, removing assumptions regarding composition or sources upstream of a single observation. The estimates are sharpened by using many hydrocarbons with different reactivities and accounting for their variability and measurement uncertainty. A novel technique is used to construct prior background distributions of many species, described by variation of a single parameter . This exploits the high correlation of species, related by the first principal component of many NMHC samples. The Bayesian method obtains posterior estimates of , K and following each air mass. Median values are typically between 0.5 and 2.0 × 106 molecules cm−3, but are elevated to between 2.5 and 3.5 × 106 molecules cm−3, in low-level pollution. A comparison of estimates from absolute NMHC concentrations and NMHC ratios assuming zero background (the “photochemical clock” method) shows similar distributions but reveals systematic high bias in the estimates from ratios. Estimates of K are ∼0.1 day−1 but show more sensitivity to the prior distribution assumed

Methane fluxes during the initiation of a large-scale water table manipulation experiment in the Alaskan Arctic tundra

Much of the 191.8 Pg C in the upper 1 m of Arctic soil of Arctic soil organic mater is, or is at risk of, being released to the atmosphere as CO2 and/or CH4. Global warming will further alter the rate of emission of these gases to the atmosphere. Here we quantify the effect of major environmental variables affected by global climate change on CH4 fluxes in the Alaskan Arctic. Soil temperature best predicts CH4 fluxes and explained 89% of the variability in CH4 emissions. Water table depth has a nonlinear impact on CH4 efflux. Increasing water table height above the surface retards CH4 efflux. Decreasing water table depth below the surface has a minor effect on CH4 release once an aerobic layer is formed at the surface. In contrast with several other studies, we found that CH4 emissions are not driven by net ecosystem exchange (NEE) and are not limited by labile carbon supply