ALBERT

Description: [1]  Several regions within California have significant air quality issues. Transport of pollutants emitted in one region to another region may add to the impact of local emissions. In this work, Lagrangian particle dispersion model simulations show the amounts of tracers that are transported within and among four regions, Southern California, the San Francisco Bay Area, the Central Valley, and the rest of the state. The simulations cover May and June of 2010, the CalNex experiment period. Tracers of automobile emissions and one type of agricultural emissions are used. Tracer mixing ratios are compared to airborne and ground-based measurements. The age of tracers in each location is also presented. Vertical profiles and diurnal cycles help to clarify the transport process. As is well known, Southern California emissions are transported to the east and affect the desert areas, and Bay Area automobile emissions are an important source of pollutants in the San Joaquin Valley. A novel result is that the Southern California Bight is filled with a mixture of well-aged carbon monoxide tracer from Southern California and the Bay Area. Air over the Bight is also affected by the agricultural emissions represented by the agricultural tracer, dominantly from the Central Valley where its sources are largest. There is no indication of transport from Southern California to the Central Valley. Emissions from the Central Valley do make their way to Southern California, as shown by the agricultural tracer, but automobile emissions from the Valley are insignificant in Southern California.

Description: [1]  The contemporary global carbon cycle is dominated by perturbations from anthropogenic CO 2 emissions. One approach to identify, quantify, and monitor anthropogenic emissions is to focus on intensely emitting urban areas. In this study, we compare the ability of different CO 2 observing systems to constrain anthropogenic flux estimates in the Los Angeles megacity. We consider different observing system configurations based on existing observations and realistic near-term extensions of the current ad hoc network. We use a high-resolution regional model (STILT-WRF) to simulate different observations and observational network designs within and downwind of the Los Angeles basin. A Bayesian inverse method is employed to quantify the relative ability of each network to improve constraints on flux estimates. Ground-based column CO 2 observations provide useful complementary information to surface observations due to lower sensitivity to localized dynamics, but column CO 2 observations from a single site do not appear to provide sensitivity to emissions from the entire LA megacity. Surface observations from remote, down-wind sites contain weak, sporadic urban signals and are complicated by other source/sink impacts, limiting their usefulness for quantifying urban fluxes in LA. We find a network of 8 optimally located in-city surface observation sites provides the minimum sampling required for accurate monitoring of CO 2 emissions in LA, and present a recommended baseline network design. We estimate that this network can distinguish fluxes on 8 week time-scales and 10 km spatial scales to within ~12 g C m -2 d -1 (~10% of average peak fossil CO 2 flux in the LA domain).

Description: [1]  Nitrous oxide (N 2 O) is an important gas for climate and for stratospheric chemistry, with a lifetime exceeding 100 years. Global concentrations have increased steadily since the 18 th century, apparently due to human-associated emissions, principally from the application of nitrogen fertilizers. However, quantitative studies of agricultural emissions at large spatial scales are lacking, inhibited by the difficulty of measuring small enhancements in atmospheric concentration. Here we derive regional emission rates for N 2 O in the agricultural heartland of California, based on analysis of in-situ airborne atmospheric observations collected using a new quantum cascade laser spectrometer. The data were obtained on board the NOAA WP-3 research aircraft during the CalNex (California Research at the Nexus of Air Quality and Climate Change) program in late spring, 2010. We coupled the WRF (Weather Research and Forecasting) model, a meso-scale meteorology model, with the STILT (Stochastic Time-Inverted Lagrangian Transport) model, a Lagrangian particle dispersion model, to link our in-situ airborne observations to surface emissions. We then used a variety of statistical methods to identify source areas and to optimize emission rates. Our results are consistent with the view that fertilizer application is the largest source of N 2 O in the Central Valley. The spatial distribution of surface emissions, based on California land use and activity maps, was very different than indicated in the leading emissions inventory (EDGAR 4.0). Our estimated total emission flux of N 2 O for California in May and June was 3–4 times larger than the annual mean given for the state by EDGAR and other inventories, indicating a strong seasonal variation. We estimated the statewide total annual emissions of N 2 O to be 0.042 ± 0.011 Tg N/yr, roughly equivalent to inventory values if we account for seasonal variations using observations obtained in the Midwestern United States. This state total N 2 O emission is 20.5 Tg CO 2 equivalent (100-year global warming potential (GWP) = 310 CO 2 eq/g N 2 O), accounting for approximately 4% of the state total greenhouse gas emissions.