This study quantitatively estimates the spatial distribution of anthropogenic methane sources in the United States by combining comprehensive atmospheric methane observations, extensive spatial datasets, and a high-resolution atmospheric transport model. Results show that current inventories from the US Environmental Protection Agency (EPA) and the Emissions Database for Global Atmospheric Research underestimate methane emissions nationally by a factor of ∼1.5 and ∼1.7, respectively. Our study indicates that emissions due to ruminants and manure are up to twice the magnitude of existing inventories. In addition, the discrepancy in methane source estimates is particularly pronounced in the south-central United States, where we find total emissions are ∼2.7 times greater than in most inventories and account for 24 ± 3% of national emissions. The spatial patterns of our emission fluxes and observed methane–propane correlations indicate that fossil fuel extraction and refining are major contributors (45 ± 13%) in the south-central United States. This result suggests that regional methane emissions due to fossil fuel extraction and processing could be 4.9 ± 2.6 times larger than in EDGAR, the most comprehensive global methane inventory. These results cast doubt on the US EPA’s recent decision to downscale its estimate of national natural gas emissions by 25–30%. Overall, we conclude that methane emissions associated with both the animal husbandry and fossil fuel industries have larger greenhouse gas impacts than indicated by existing inventories.

Surface ecophysiology at five sites in tropical South America across vegetation and moisture gradients is investigated. From the moist northwest (Manaus) to the relatively dry southeast (Pe de Gigante, state of Sao Paulo) simulated seasonal cycles of latent and sensible heat, and carbon flux produced with the Simple Biosphere Model (SiB3) are confronted with observational data. In the northwest, abundant moisture is available, suggesting that the ecosystem is light-limited. In these wettest regions, Bowen ratio is consistently low, with little or no annual cycle. Carbon flux shows little or no annual cycle as well; efflux and uptake are determined by high-frequency variability in light and moisture availability. Moving downgradient in annual precipitation amount, dry season length is more clearly defined. In these regions, a dry season sink of carbon is observed and simulated. This sink is the result of the combination of increased photosynthetic production due to higher light levels, and decreased respiratory efflux due to soil drying. The differential response time of photosynthetic and respiratory processes produce observed annual cycles of net carbon flux. In drier regions, moisture and carbon fluxes are in-phase; there is carbon uptake during seasonal rains and efflux during the dry season. At the driest site, there is also a large annual cycle in latent and sensible heat flux.

We investigated the seasonal patterns of Amazonian forest photosynthetic activity, and the effects thereon of variations in climate and land-use, by integrating data from a network of ground-based eddy flux towers in Brazil established as part of the ‘Large-Scale Biosphere Atmosphere Experiment in Amazonia’ project. We found that degree of water limitation, as indicated by the seasonality of the ratio of sensible to latent heat flux (Bowen ratio) predicts seasonal patterns of photosynthesis. In equatorial Amazonian forests (5° N–5° S), water limitation is absent, and photosynthetic fluxes (or gross ecosystem productivity, GEP) exhibit high or increasing levels of photosynthetic activity as the dry season progresses, likely a consequence of allocation to growth of new leaves. In contrast, forests along the southern flank of the Amazon, pastures converted from forest, and mixed forest-grass savanna, exhibit dry-season declines in GEP, consistent with increasing degrees of water limitation. Although previous work showed tropical ecosystem evapotranspiration (ET) is driven by incoming radiation, GEP observations reported here surprisingly show no or negative relationships with photosynthetically active radiation (PAR). Instead, GEP fluxes largely followed the phenology of canopy photosynthetic capacity (Pc), with only deviations from this primary pattern driven by variations in PAR. Estimates of leaf flush at three non-water limited equatorial forest sites peak in the dry season, in correlation with high dry season light levels. The higher photosynthetic capacity that follows persists into the wet season, driving high GEP that is out of phase with sunlight, explaining the negative observed relationship with sunlight. Overall, these patterns suggest that at sites where water is not limiting, light interacts with adaptive mechanisms to determine photosynthetic capacity indirectly through leaf flush and litterfall seasonality. These mechanisms are poorly represented in ecosystem models, and represent an important challenge to efforts to predict tropical forest responses to climatic variations.

To better understand how forest management, phenology, vegetation type, and actual and simulated climatic change affect seasonal and inter-annual variations in soil respiration (R_s), we analyzed more than 100,000 individual measurements of soil respiration from 23 studies conducted over 22 years at the Harvard Forest in Petersham, Massachusetts, USA. We also used 24 site-years of eddy-covariance measurements from two Harvard Forest sites to examine the relationship between soil and ecosystem respiration (R_e).

R_s was highly variable at all spatial (respiration collar to forest stand) and temporal (minutes to years) scales of measurement. The response of R_s to experimental manipulations mimicking aspects of global change or aimed at partitioning R_s into component fluxes ranged from −70% to +52%. The response appears to arise from variations in substrate availability induced by changes in the size of soil C pools and of belowground C fluxes or in environmental conditions. In some cases (e.g., logging, warming), the effect of experimental manipulations on R_s was transient, but in other cases the time series were not long enough to rule out long-term changes in respiration rates. Inter-annual variations in weather and phenology induced variation among annual R_s estimates of a magnitude similar to that of other drivers of global change (i.e., invasive insects, forest management practices, N deposition). At both eddy-covariance sites, aboveground respiration dominated R_e early in the growing season, whereas belowground respiration dominated later. Unusual aboveground respiration patterns—high apparent rates of respiration during winter and very low rates in mid-to-late summer—at the Environmental Measurement Site suggest either bias in R_s and R_e estimates caused by differences in the spatial scale of processes influencing fluxes, or that additional research on the hard-to-measure fluxes (e.g., wintertime R_s, unaccounted losses of CO₂ from eddy covariance sites), daytime and nighttime canopy respiration and its impacts on estimates of R_e, and independent measurements of flux partitioning (e.g., aboveground plant respiration, isotopic partitioning) may yield insight into the unusually high and low fluxes. Overall, however, this data-rich analysis identifies important seasonal and experimental variations in R_s and R_e and in the partitioning of R_e above- vs. belowground.

Measurements of the isotopic composition of the net ecosystem–atmosphere exchange of CO₂ (NEE) have been desired as a means to probe ecosystem carbon cycling and in particular to partition NEE into gross ecosystem photosynthesis and respiration. Several attempts at such measurements have combined eddy covariance (EC) measurements of the total net CO₂ flux with flask measurements of the isotopic composition of CO₂ in ambient air – an indirect method that has never been validated. Direct EC measurements of the isotopic composition of NEE (i.e. of the net exchanges of ¹²C¹⁶O₂, ¹³C¹⁶O₂, and ¹⁸O¹²C¹⁶O) have been made only twice, in short-term (2-month and 1-month) campaigns.

Here we present a full growing season of direct EC measurements of the isotopic composition of NEE in a temperate deciduous forest, and we use these data: (1) to rigorously assess their limiting sources of error, (2) to test the indirect EC/flask method, and (3) to give an indication of the potential for ecological analyses. We describe the method and instrumentation, including the new cryogen-free, continuous-wave, quantum cascade laser spectrometer, which can determine δ¹³C and δ¹⁸O in ambient CO₂ with unprecedented noise levels of ±0.02‰ and ±0.03‰ (1 standard deviation), respectively, for a 100 s integration time and a 1-h calibration interval. We find: (1) that precision is jointly limited by the instrumentation and by horizontal ecosystem or landscape heterogeneity, so that there is little to be gained by further improvements to instrument performance; (2) that the isotopic composition of NEE obtained by the EC/flask method can be biased, on a monthly timescale, by 2‰; and (3) that the present measurements are precise enough to elucidate biological mechanisms controlling the ecosystem-scale carbon balance.

Seasonal variations of atmospheric carbon dioxide (CO₂) in the Northern Hemisphere have increased since the 1950s, but sparse observations have prevented a clear assessment of the patterns of long-term change and the underlying mechanisms. We compare recent aircraft-based observations of CO₂ above the North Pacific and Arctic Oceans to earlier data from 1958 to 1961 and find that the seasonal amplitude at altitudes of 3 to 6 km increased by 50% for 45° to 90°N but by less than 25% for 10° to 45°N. An increase of 30 to 60% in the seasonal exchange of CO₂ by northern extratropical land ecosystems, focused on boreal forests, is implicated, substantially more than simulated by current land ecosystem models. The observations appear to signal large ecological changes in northern forests and a major shift in the global carbon cycle.

Mid-upper tropospheric methane (CH₄), as an operational product at NOAA's (National Oceanic and Atmospheric Administration) Comprehensive Large Array-data Stewardship System (CLASS), has been retrieved from the Infrared Atmospheric Sounding Interferometer (IASI) since 2008. This paper provides a description of the retrieval method and the validation using 596 CH₄ vertical profiles from aircraft measurements by the HIAPER Pole-to-Pole Observations (HIPPO) program over the Pacific Ocean. The number of degrees of freedom for the CH₄ retrieval is mostly less than 1.5, and it decreases under cloudy conditions. The retrievals show greatest sensitivity between 100–600 hPa in the tropics and 200–750 hPa in the mid- to high latitude. Validation is accomplished using aircraft measurements (convolved by applying the monthly mean averaging kernels) collocated with all the retrieved profiles within 200 km and on the same day, and the results show that, on average, a larger error of CH₄ occurs at 300–500 hPa. The bias in the trapezoid of 374–477 hPa is −1.74% with a residual standard deviation of 1.20%, and at layer 596–753 hPa the bias is −0.69% with a residual standard deviation of 1.07%. The retrieval error is relatively larger in the high northern latitude regions and/or under cloudy conditions. The main reasons for this negative bias include the uncertainty in the spectroscopy near the methane Q branch and/or the empirical bias correction, plus residual cloud contamination in the cloud-cleared radiances. It is expected for NOAA to generate the CH₄ product for 20 + years using a similar algorithm from three similar thermal infrared sensors: Atmospheric Infrared Sounder (AIRS), IASI and the Cross-track Infrared Sounder (CrIS). Such a unique product will provide a supplementary to the current ground-based observation network, particularly in the Arctic, for monitoring the CH₄ cycle, its transport and trend associated with climate change.

We present a novel spectral method to measure atmospheric carbon dioxide (CO₂) with high precision and stability without resorting to calibration tanks during long-term operation. This spectral null method improves precision by reducing spectral proportional noise associated with laser emission instabilities. We employ sealed quartz cells with known CO₂ column densities to serve as the permanent internal references in the null method, which improve the instrument's stability and accuracy. A prototype instrument – ABsolute Carbon dioxide (ABC) is developed using this new approach. The instrument has a one-second precision of 0.02 ppm, which averages down to 0.007 ppm within one minute. Long-term stability of within 0.1 ppm is achieved without any calibrations for over a one-month period. These results have the potential for eliminating the need for calibration cylinders for high accuracy field measurements of carbon dioxide.

Changes in atmospheric CO₂ variability during the twenty-first century may provide insight about ecosystem responses to climate change and have implications for the design of carbon monitoring programs. This paper describes changes in the three-dimensional structure of atmospheric CO₂ for several representative concentration pathways (RCPs 4.5 and 8.5) using the Community Earth System Model–Biogeochemistry (CESM1-BGC). CO₂ simulated for the historical period was first compared to surface, aircraft, and column observations. In a second step, the evolution of spatial and temporal gradients during the twenty-first century was examined. The mean annual cycle in atmospheric CO₂ was underestimated for the historical period throughout the Northern Hemisphere, suggesting that the growing season net flux in the Community Land Model (the land component of CESM) was too weak. Consistent with weak summer drawdown in Northern Hemisphere high latitudes, simulated CO₂ showed correspondingly weak north–south and vertical gradients during the summer. In the simulations of the twenty-first century, CESM predicted increases in the mean annual cycle of atmospheric CO₂ and larger horizontal gradients. Not only did the mean north–south gradient increase due to fossil fuel emissions, but east–west contrasts in CO₂ also strengthened because of changing patterns in fossil fuel emissions and terrestrial carbon exchange. In the RCP8.5 simulation, where CO₂ increased to 1150 ppm by 2100, the CESM predicted increases in interannual variability in the Northern Hemisphere midlatitudes of up to 60% relative to present variability for time series filtered with a 2–10-yr bandpass. Such an increase in variability may impact detection of changing surface fluxes from atmospheric observations.

Measurements of carbonyl sulfide (OCS) have been proposed to provide a unique constraint on carbon assimilation by the biosphere that is independent of the influence of plant and soil respiration of CO₂, but this constraint depends on a comprehensive understanding of the processes controlling OCS in the biosphere. We conducted a high-resolution temporal and spatial survey of OCS and CO₂ mixing ratios during the California Nexus Experiment research cruise along the coast of California (U.S.) and into the Sacramento River Delta using a newly constructed compact quantum cascade laser spectrometer (precision for OCS of <8 pptv (pmol/mol) at 1 Hz). The temporal and spatial resolution of the measurements revealed a number of specific processes related to known sources and sinks. The observations demonstrate OCS uptake during daytime photosynthetic uptake of CO₂, OCS depletion during nighttime forest respiration of CO₂, and OCS emission from a freshwater marsh. OCS emission was observed in one anthropogenically influenced plume, but, overall, no correlation was observed between OCS and SO₂, and the use of scaled SO₂ emission fields in global budgets of OCS should be reconsidered for areas with strict sulfur emission controls, such as California. The observations show that, in a homogeneous ecosystem on a local scale, OCS may be a proxy for CO₂ uptake. However, at larger scales that span heterogeneous environments, in order to confidently quantify any single process, competing processes must be either relatively small or well quantified.

The causes of renewed growth in the atmospheric CH₄ burden since 2007 are still poorly understood and subject of intensive scientific discussion. We present a reanalysis of global CH₄ emissions during the 2000s, based on the TM5-4DVAR inverse modeling system. The model is optimized using high-accuracy surface observations from NOAA ESRL's global air sampling network for 2000–2010 combined with retrievals of column-averaged CH₄ mole fractions from SCIAMACHY onboard ENVISAT (starting 2003). Using climatological OH fields, derived global total emissions for 2007–2010 are 16–20 Tg CH₄/yr higher compared to 2003–2005. Most of the inferred emission increase was located in the tropics (9–14 Tg CH₄/yr) and mid-latitudes of the northern hemisphere (6–8 Tg CH₄/yr), while no significant trend was derived for Arctic latitudes. The atmospheric increase can be attributed mainly to increased anthropogenic emissions, but the derived trend is significantly smaller than estimated in the EDGARv4.2 emission inventory. Superimposed on the increasing trend in anthropogenic CH₄ emissions are significant inter-annual variations (IAV) of emissions from wetlands (up to ±10 Tg CH₄/yr), and biomass burning (up to ±7 Tg CH₄/yr). Sensitivity experiments, which investigated the impact of the SCIAMACHY observations (versus inversions using only surface observations), of the OH fields used, and of a priori emission inventories, resulted in differences in the detailed latitudinal attribution of CH₄ emissions, but the IAV and trends aggregated over larger latitude bands were reasonably robust. All sensitivity experiments show similar performance against independent shipboard and airborne observations used for validation, except over Amazonia where satellite retrievals improved agreement with observations in the free troposphere.

Methane (CH₄), carbon dioxide (CO₂), carbon monoxide (CO), and C₂–C₅ alkanes were measured throughout the Los Angeles (L.A.) basin in May and June 2010. We use these data to show that the emission ratios of CH₄/CO and CH₄/CO₂ in the L.A. basin are larger than expected from population-apportioned bottom-up state inventories, consistent with previously published work. We use experimentally determined CH₄/CO and CH₄/CO₂ emission ratios in combination with annual State of California CO and CO₂ inventories to derive a yearly emission rate of CH₄ to the L.A. basin. We further use the airborne measurements to directly derive CH₄ emission rates from dairy operations in Chino, and from the two largest landfills in the L.A. basin, and show these sources are accurately represented in the California Air Resources Board greenhouse gas inventory for CH₄. We then use measurements of C₂–C₅ alkanes to quantify the relative contribution of other CH₄ sources in the L.A. basin, with results differing from those of previous studies. The atmospheric data are consistent with the majority of CH₄ emissions in the region coming from fugitive losses from natural gas in pipelines and urban distribution systems and/or geologic seeps, as well as landfills and dairies. The local oil and gas industry also provides a significant source of CH₄ in the area. The addition of CH₄ emissions from natural gas pipelines and urban distribution systems and/or geologic seeps and from the local oil and gas industry is sufficient to account for the differences between the top-down and bottom-up CH₄ inventories identified in previously published work.

Atmospheric methane (CH₄) concentration in the mid-to-upper troposphere has been retrieved using atmospheric infrared sounder (AIRS) data on NASA EOS/AQUA. By selecting the AIRS strong CH₄ absorption channels near 1306 cm^-1, severe CH₄ depletion was mapped during a stratospheric intrusion event on 27 March 2010. The areas with depleted CH₄ mixing ratio are collocated with enhanced ozone (O₃) and low tropopause height. Aircraft measurements observed the depleted CH₄ and enhanced O₃ down to 550 hPa. An estimate of the depleted CH₄ amount which resulted from stratospheric intrusion is -54 to -67 Tg yr^-1. This study suggests that the AIRS and/or other thermal infrared sounders can provide an observation of CH₄ variation associated with stratospheric intrusion, a key unknown in CH₄ budget, and this data set will be also useful for studying the stratosphere-troposphere exchange (STE).

We present top-down estimates of anthropogenic CO, NO_x and CO₂ surface fluxes at mesoscale using a Lagrangian model in combination with three different WRF model configurations, driven by data from aircraft flights during the CALNEX campaign in southern California in May–June 2010. The US EPA National Emission Inventory 2005 (NEI 2005) was the prior in the CO and NO_x inversion calculations. The flux ratio inversion method, based on linear relationships between chemical species, was used to calculate the CO₂ inventory without prior knowledge of CO₂ surface fluxes. The inversion was applied to each flight to estimate the variability of single-flight-based flux estimates. In Los Angeles (LA) County, the uncertainties on CO and NO_x fluxes were 10% and 15%, respectively. Compared with NEI 2005, the CO posterior emissions were lower by 43% in LA County and by 37% in the South Coast Air Basin (SoCAB). NO_x posterior emissions were lower by 32% in LA County and by 27% in the SoCAB. NO_x posterior emissions were 40% lower on weekends relative to weekdays. The CO₂ posterior estimates were 183 Tg yr⁻¹ in SoCAB. A flight during ITCT (Intercontinental Transport and Chemical Transformation) in 2002 was used to estimate emissions in the LA Basin in 2002. From 2002 to 2010, the CO and NO_x posterior emissions decreased by 41% and 37%, respectively, in agreement with previous studies. Over the same time period, CO₂ emissions increased by 10% in LA County but decreased by 4% in the SoCAB, a statistically insignificant change. Overall, the posterior estimates were in good agreement with the California Air Resources Board (CARB) inventory, with differences of 15% or less. However, the posterior spatial distribution in the basin was significantly different from CARB for NO_x emissions. WRF-Chem mesoscale chemical-transport model simulations allowed an evaluation of differences in chemistry using different inventory assumptions, including NEI 2005, a gridded CARB inventory and the posterior inventories derived in this study. The biases in WRF-Chem ozone were reduced and correlations were increased using the posterior from this study compared with simulations with the two bottom-up inventories, suggesting that improving the spatial distribution of ozone precursor surface emissions is also important in mesoscale chemistry simulations.

The California Research at the Nexus of Air Quality and Climate Change (CalNex) field study was conducted throughout California in May, June, and July of 2010. The study was organized to address issues simultaneously relevant to atmospheric pollution and climate change, including (1) emission inventory assessment, (2) atmospheric transport and dispersion, (3) atmospheric chemical processing, and (4) cloud-aerosol interactions and aerosol radiative effects. Measurements from networks of ground sites, a research ship, tall towers, balloon-borne ozonesondes, multiple aircraft, and satellites provided in situ and remotely sensed data on trace pollutant and greenhouse gas concentrations, aerosol chemical composition and microphysical properties, cloud microphysics, and meteorological parameters. This overview report provides operational information for the variety of sites, platforms, and measurements, their joint deployment strategy, and summarizes findings that have resulted from the collaborative analyses of the CalNex field study. Climate-relevant findings from CalNex include that leakage from natural gas infrastructure may account for the excess of observed methane over emission estimates in Los Angeles. Air-quality relevant findings include the following: mobile fleet VOC significantly declines, and NO_x emissions continue to have an impact on ozone in the Los Angeles basin; the relative contributions of diesel and gasoline emission to secondary organic aerosol are not fully understood; and nighttime NO₃ chemistry contributes significantly to secondary organic aerosol mass in the San Joaquin Valley. Findings simultaneously relevant to climate and air quality include the following: marine vessel emissions changes due to fuel sulfur and speed controls result in a net warming effect but have substantial positive impacts on local air quality.

Thermal infrared radiances from the Tropospheric Emission Spectrometer (TES) between 10 and 15 μm contain significant carbon dioxide (CO₂) information, however the CO₂ signal must be separated from radiative interference from temperature, surface and cloud parameters, water, and other trace gases. Validation requires data sources spanning the range of TES CO₂ sensitivity, which is approximately 2.5 to 12 km with peak sensitivity at about 5 km and the range of TES observations in latitude (40° S to 40° N) and time (2005–2011). We therefore characterize Tropospheric Emission Spectrometer (TES) CO₂ version 5 biases and errors through comparisons to ocean and land-based aircraft profiles and to the CarbonTracker assimilation system. We compare to ocean profiles from the first three Hiaper Pole-to-Pole Observations (HIPPO) campaigns between 40° S and 40° N with measurements between the surface and 14 km and find that TES CO₂ estimates capture the seasonal and latitudinal gradients observed by HIPPO CO₂ measurements. Actual errors range from 0.8–1.8 ppm, depending on the campaign and pressure level, and are approximately 1.6–2 times larger than the predicted errors. The bias of TES versus HIPPO is within 1 ppm for all pressures and datasets; however, several of the sub-tropical TES CO₂ estimates are lower than expected based on the calculated errors. Comparisons to land aircraft profiles from the United States Southern Great Plains (SGP) Atmospheric Radiation Measurement (ARM) between 2005 and 2011 measured from the surface to 5 km to TES CO₂ show good agreement with an overall bias of −0.3 ppm to 0.1 ppm and standard deviations of 0.8 to 1.0 ppm at different pressure levels. Extending the SGP aircraft profiles above 5 km using AIRS or CONTRAIL measurements improves comparisons with TES. Comparisons to CarbonTracker (version CT2011) show a persistent spatially dependent bias pattern and comparisons to SGP show a time-dependent bias of −0.2 ppm yr⁻¹. We also find that the predicted sensitivity of the TES CO₂ estimates is too high, which results from using a multi-step retrieval for CO₂ and temperature. We find that the averaging kernel in the TES product corrected by a pressure-dependent factor accurately reflects the sensitivity of the TES CO₂ product.

Validation results are reported for the MOPITT (Measurements of Pollution in the Troposphere) “Version 5” (V5) product for tropospheric carbon monoxide (CO) and are compared to results for the “Version 4” product. The V5 retrieval algorithm introduces (1) a method for reducing retrieval bias drift associated with long-term instrumental degradation, (2) a more exact representation of the effects of random errors in the radiances and, for the first time, (3) the use of MOPITT's near-infrared (NIR) radiances to complement the thermal-infrared (TIR) radiances. Exploiting TIR and NIR radiances together facilitates retrievals of CO in the lowermost troposphere. V5 retrieval products based (1) solely on TIR measurements, (2) solely on NIR measurements and (3) on both TIR and NIR measurements are separately validated and analyzed. Actual retrieved CO profiles and total columns are compared with equivalent retrievals based on in situ measurements from (1) routine NOAA aircraft sampling mainly over North America and (2) the “HIAPER Pole to Pole Observations” (HIPPO) field campaign. Particular attention is focused on the long-term stability and geographical uniformity of the retrieval errors. Results for the retrieved total column clearly indicate reduced temporal bias drift in the V5 products compared to the V4 product, and do not exhibit a positive bias in the Southern Hemisphere, which is evident in the V4 product.

A recent National Research Council report highlighted the potential utility of atmospheric observations and models for detecting trends in concentrated emissions from localized regions, such as urban areas. The Salt Lake City (SLC), Utah, area was chosen for a pilot study to determine the feasibility of using ground-based sensors to identify trends in anthropogenic urban emissions over a range of time scales (from days to years). The Weather Research and Forecasting model (WRF) was combined with a Lagrangian particle dispersion model and an emission inventory to model carbon dioxide (CO₂) concentrations that can be compared with in situ measurements. An accurate representation of atmospheric transport requires a faithful modeling of the meteorological conditions. This study examines in detail the ability of different configurations of WRF to reproduce the observed local and mesoscale circulations, and the diurnal evolution of the planetary boundary layer (PBL) in the SLC area. Observations from the Vertical Transport and Mixing field experiment in 2000 were used to examine the sensitivity of WRF results to changes in the PBL parameterization and to the inclusion of an urban canopy model (UCM). Results show that for urban locations there is a clear benefit from parameterizing the urban canopy for simulation of the PBL and near-surface conditions, particularly for temperature evolution at night. Simulation of near-surface CO₂ concentrations for a 2-week period in October 2006 showed that running WRF at high resolution (1.33 km) and with a UCM also improves the simulation of observed increases in CO₂during the early evening.

Nitrous oxide (N₂O) is an important gas for climate and for stratospheric chemistry, with a lifetime exceeding 100 years. Global concentrations have increased steadily since the 18th 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 N₂O 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 N₂O 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 emission inventory (EDGAR 4.0). Our estimated total emission flux of N₂O 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 N₂O to be 0.042 ± 0.011 Tg N/year, roughly equivalent to inventory values if we account for seasonal variations using observations obtained in the midwestern United States. This state total N₂O emission is 20.5 Tg CO₂ equivalent (100 year global warming potential = 310 CO₂ eq/g N₂O), accounting for approximately 4% of the state total greenhouse gas emissions.

Monitoring the global distribution and long-term variations of CO₂ sources and sinks is required for characterizing the global carbon budget. Total column measurements are useful for estimating regional-scale fluxes; however, model transport remains a significant error source, particularly for quantifying local sources and sinks. To improve the capability of estimating regional fluxes, we estimate lower tropospheric CO₂ concentrations from ground-based near-infrared (NIR) measurements with space-based thermal infrared (TIR) measurements. The NIR measurements are obtained from the Total Carbon Column Observing Network (TCCON) of solar measurements, which provide an estimate of the total CO₂ column amount. Estimates of tropospheric CO₂ that are co-located with TCCON are obtained by assimilating Tropospheric Emission Spectrometer (TES) free tropospheric CO₂ estimates into the GEOS-Chem model. We find that quantifying lower tropospheric CO₂ by subtracting free tropospheric CO₂ estimates from total column estimates is a linear problem, because the calculated random uncertainties in total column and lower tropospheric estimates are consistent with actual uncertainties as compared to aircraft data. For the total column estimates, the random uncertainty is about 0.55 ppm with a bias of −5.66 ppm, consistent with previously published results. After accounting for the total column bias, the bias in the lower tropospheric CO₂ estimates is 0.26 ppm with a precision (one standard deviation) of 1.02 ppm. This precision is sufficient for capturing the winter to summer variability of approximately 12 ppm in the lower troposphere; double the variability of the total column. This work shows that a combination of NIR and TIR measurements can profile CO₂ with the precision and accuracy needed to quantify lower tropospheric CO₂ variability.