We present the first estimate of the global distribution of CO₂surface fluxes from 14 stations of the Total Carbon Column Observing Network (TCCON). The evaluation of this inversion is based on 1) comparison with the fluxes from a classical inversion of surface air-sample-measurements, and 2) comparison of CO₂mixing ratios calculated from the inverted fluxes with independent aircraft measurements made during the two years analyzed here, 2009 and 2010. The former test shows similar seasonal cycles in the northern hemisphere and consistent regional carbon budgets between inversions from the two datasets, even though the TCCON inversion appears to be less precise than the classical inversion. The latter test confirms that the TCCON inversion has improved the quality (i.e., reduced the uncertainty) of the surface fluxes compared to the assumed or prior fluxes. The consistency between the surface-air-sample-based and the TCCON-based inversions despite remaining flaws in transport models opens the possibility of increased accuracy and robustness of flux inversions based on the combination of both data sources and confirms the usefulness of space-borne monitoring of the CO₂ column.

The mass concentrations of black carbon (BC) were measured continuously at Miyun, a rural site near Beijing, concurrently with some trace gases (CO, CO₂, NO_y, SO₂) during the nonheating seasons of 2010 (April to October). The average concentration of BC was 2.26 ± 2.33 μg m⁻³. About 70%–100% of the air masses arriving at the site from June to September were from the source region of Beijing and the North China Plain (NCP), while in the spring, 40% were of continental background origin. BC had moderate to strong positive correlations with CO (R² = 0.51), NO_y (R² = 0.58), and CO₂ (nonsummer, R² = 0.54), but not with SO₂ (R² < 0.1). The observed ΔBC/ΔCO ratio was 0.0050 ± 0.0001 μg m⁻³/ppbv for the regional air masses (excluding the influence of biomass burning). This ratio increased by 68% to 0.0084 ± 0.0004 μg m⁻³/ppbv after excluding the influence of wet deposition. Accounting further for the impact of atmospheric processes on the observation, we derived an average top-down BC/CO emission ratio of 0.0095 ± 0.002 μg m⁻³/ppbv for the source region of Beijing and NCP that is 18%–21% lower than the average emission ratio from the bottom-up inventory of Zhang et al. (2009), whereas the difference is substantially lower than the uncertainty of emissions for either species. The difference between the mean bottom-up and top-down emission ratios is most likely to be attributed to the residential sector, which needs to have a lower share in the total emissions of BC or a much lower BC/CO emission ratio. The industry and transportation sectors are found to be dominant sources of BC from Beijing and the NCP rather than from the residential sector as suggested by the bottom-up inventory.

Seasonal dynamics of atmospheric carbonyl sulfide (OCS) at regional and continental scales and plant OCS exchange at the leaf level have shown a close relationship with those for CO₂. CO₂ has both sinks and sources within terrestrial ecosystems, but the primary terrestrial exchange for OCS is thought to be leaf uptake, suggesting potential for OCS uptake as a proxy for gross primary production (GPP). We explored the utility of OCS uptake as a GPP proxy in micrometeorological studies of biosphere-atmosphere CO₂ exchange by applying theoretical concepts from earlier OCS studies to estimate GPP. We partitioned measured net ecosystem exchange (NEE) using the ratio of measured vertical mole fraction gradients of OCS and CO₂. At the Harvard Forest AmeriFlux site, measured CO₂ and OCS vertical gradients were correlated and were related to NEE and GPP, respectively. Estimates of GPP from OCS-based NEE partitioning were similar to those from established environmental regression techniques, providing evidence that OCS uptake can potentially serve as a GPP proxy. Measured vertical CO₂ mole fraction gradients at five other AmeriFlux sites were used to project anticipated vertical OCS mole fraction gradients to provide indication of potential OCS signal magnitudes at sites where no OCS measurements were made. Projected OCS gradients at sites with short canopies were greater than those in forests, including measured OCS gradients at Harvard Forest, indicating greater potential for OCS uptake as a GPP proxy at these sites. This exploratory study suggests that continued investigation of linkages between OCS and GPP is warranted.

Deforestation in mid- to high latitudes is hypothesized to have the potential to cool the Earth’s surface by altering biophysical processes^1,2,3. In climate models of continental-scale land clearing, the cooling is triggered by increases in surface albedo and is reinforced by a land albedo–sea ice feedback^4,5. This feedback is crucial in the model predictions; without it other biophysical processes may overwhelm the albedo effect to generate warming instead⁵. Ongoing land-use activities, such as land management for climate mitigation, are occurring at local scales (hectares) presumably too small to generate the feedback, and it is not known whether the intrinsic biophysical mechanism on its own can change the surface temperature in a consistent manner^6,7. Nor has the effect of deforestation on climate been demonstrated over large areas from direct observations. Here we show that surface air temperature is lower in open land than in nearby forested land. The effect is 0.85 ± 0.44 K (mean ± one standard deviation) northwards of 45° N and 0.21 ± 0.53 K southwards. Below 35° N there is weak evidence that deforestation leads to warming. Results are based on comparisons of temperature at forested eddy covariance towers in the USA and Canada and, as a proxy for small areas of cleared land, nearby surface weather stations. Night-time temperature changes unrelated to changes in surface albedo are an important contributor to the overall cooling effect. The observed latitudinal dependence is consistent with theoretical expectation of changes in energy loss from convection and radiation across latitudes in both the daytime and night-time phase of the diurnal cycle, the latter of which remains uncertain in climate models⁸.

Atmospheric emissions of gas and particulate matter from a large ocean-going container vessel were sampled as it slowed and switched from high-sulfur to low-sulfur fuel as it transited into regulated coastal waters of California. Reduction in emission factors (EFs) of sulfur dioxide (SO₂), particulate matter, particulate sulfate and cloud condensation nuclei were substantial (≥90%). EFs for particulate organic matter decreased by 70%. Black carbon (BC) EFs were reduced by 41%. When the measured emission reductions, brought about by compliance with the California fuel quality regulation and participation in the vessel speed reduction (VSR) program, are placed in a broader context, warming from reductions in the indirect effect of SO₄ would dominate any radiative changes due to the emissions changes. Within regulated waters absolute emission reductions exceed 88% for almost all measured gas and particle phase species. The analysis presented provides direct estimations of the emissions reductions that can be realized by California fuel quality regulation and VSR program, in addition to providing new information relevant to potential health and climate impact of reduced fuel sulfur content, fuel quality and vessel speed reductions.

We evaluated an idealized boundary layer (BL) model with simple parameterizations using vertical transport information from community model outputs (NCAR/NCEP Reanalysis and ECMWF Interim Analysis) to estimate regional-scale net CO₂ fluxes from 2002 to 2007 at three forest and one grassland flux sites in the United States. The BL modeling approach builds on a mixed-layer model to infer monthly average net CO₂ fluxes using high-precision mixing ratio measurements taken on flux towers. We compared BL model net ecosystem exchange (NEE) with estimates from two independent approaches. First, we compared modeled NEE with tower eddy covariance measurements. The second approach (EC-MOD) was a data‐driven method that upscaled EC fluxes from towers to regions using MODIS data streams.

Measurements of atmospheric N₂O spanning altitudes from the surface to 14 km, and latitudes from 67°S to 85°N, show high concentrations in the tropics and subtropics, with strong maxima in the middle and upper troposphere. The pattern varies significantly over time scales of a few weeks. Global simulations do not accurately capture observed distributions with latitude, altitude, or time. Inversion results indicate strong, episodic inputs of nitrous oxide from tropical regions (as large as 1 Tg N-N₂O over 9 weeks) are necessary to produce observed vertical and latitudinal distributions. These findings highlight strong tropical sources of N₂O with high temporal variability, and the necessity of using full vertical profile observations in deriving emissions from atmospheric measurements.

The Alternative Aviation Fuel Experiment (AAFEX), conducted in January of 2009 in Palmdale, California, quantified aerosol and gaseous emissions from a DC-8 aircraft equipped with CFM56-2C1 engines using both traditional and synthetic fuels. This study examines the emissions of nitrous acid (HONO) and nitrogen oxides (NO_x = NO + NO₂) measured 145 m behind the grounded aircraft. The fuel-based emission index (EI) for HONO increases approximately 6-fold from idle to takeoff conditions but plateaus between 65 and 100% of maximum rated engine thrust, while the EI for NO_x increases continuously. At high engine power, NO_x EI is greater when combusting traditional (JP-8) rather than Fischer–Tropsch fuels, while HONO exhibits the opposite trend. Additionally, hydrogen peroxide (H₂O₂) was identified in exhaust plumes emitted only during engine idle. Chemical reactions responsible for emissions and comparison to previous measurement studies are discussed.

Given the predicted growth of aviation and the recent developments of alternative aviation fuels, quantifying methane (CH₄) and nitrous oxide (N₂O) emission ratios for various aircraft engines and fuels can help constrain projected impacts of aviation on the Earth’s radiative balance. Fuel-based emission indices for CH₄ and N₂O were quantified from CFM56–2C1 engines aboard the NASA DC-8 aircraft during the first Alternative Aviation Fuel Experiment (AAFEX-I) in 2009. The measurements of JP-8 fuel combustion products indicate that at low thrust engine states (idle and taxi, or 4% and 7% maximum rated thrusts, respectively) the engines emit both CH₄ and N₂O at a mean ±1σ rate of 170 ± 160 mg CH₄ (kg Fuel)⁻¹ and 110 ± 50 mg N₂O (kg Fuel)⁻¹, respectively. At higher thrust levels corresponding to greater fuel flow and higher engine temperatures, CH₄ concentrations in engine exhaust were lower than ambient concentrations. Average emission indices for JP-8 fuel combusted at engine thrusts between 30% and 100% of maximum rating were −54 ± 33 mg CH₄ (kg Fuel)⁻¹ and 32 ± 18 mg N₂O (kg Fuel)⁻¹, where the negative sign indicates consumption of atmospheric CH₄ in the engine. Emission factors for the synthetic Fischer–Tropsch fuels were statistically indistinguishable from those for JP-8.

Estimating the current sources and sinks of carbon and projecting future levels of CO₂ and climate require biospheric carbon models that cover the landscape. Such models inevitably suffer from deficiencies and uncertainties. This paper addresses how to quantify errors in modeled carbon fluxes and then trace them to specific input variables. To date, few studies have examined uncertainties in biospheric models in a quantitative fashion that are relevant to landscape-scale simulations. In this paper, we introduce a general framework to quantify errors in biospheric carbon models that “unmix” the contributions to the total uncertainty in simulated carbon fluxes and attribute the error to different variables. To illustrate this framework we apply and use a simple biospheric model, the Vegetation Photosynthesis and Respiration Model (VPRM), in boreal forests of central Canada, using eddy covariance flux measurement data from two main sites of the Canadian Carbon Program (CCP). We explicitly distinguish between systematic errors (“biases”) and random errors and focus on the impact of errors present in biospheric parameters as well as driver data sets (satellite indices, temperature, solar radiation, and land cover). Biases in downward shortwave radiation accumulated to the most significant amount out of the driver data sets and accounted for a significant percentage of the annually summed carbon uptake. However, the largest cumulative errors were shown to stem from biospheric parameters controlling the light-use efficiency and respiration-temperature relationships. This work represents a step toward a carbon model-data fusion system because in such systems the outcome is determined as much by uncertainties as by the measurements themselves.

The HIAPER Pole-to-Pole Observations (HIPPO) programme has completed three of five planned aircraft transects spanning the Pacific from 85° N to 67° S, with vertical profiles every approximately 2.2° of latitude. Measurements include greenhouse gases, long-lived tracers, reactive species, O2/N2 ratio, black carbon (BC), aerosols and CO2 isotopes. Our goals are to address the problem of determining surface emissions, transport strength and patterns, and removal rates of atmospheric trace gases and aerosols at global scales and to provide strong tests of satellite data and global models. HIPPO data show dense pollution and BC at high altitudes over the Arctic, imprints of large N2O sources from tropical lands and convective storms, sources of pollution and biogenic CH4 in the Arctic, and summertime uptake of CO2 and sources for O2 at high southern latitudes. Global chemical signatures of atmospheric transport are imaged, showing remarkably sharp horizontal gradients at air mass boundaries, weak vertical gradients and inverted profiles (maxima aloft) in both hemispheres. These features challenge satellite algorithms, global models and inversion analyses to derive surface fluxes. HIPPO data can play a crucial role in identifying and resolving questions of global sources, sinks and transport of atmospheric gases and aerosols.

Fluxes of biogenic volatile organic compounds, including isoprene, monoterpenes, and oxygenated VOCs measured above a mixed forest canopy in central Massachusetts during the 2005 and 2007 growing seasons are reported. Mixing ratios were measured using proton transfer reaction mass spectrometry (PTR-MS) and fluxes computed by the disjunct eddy covariance technique. Isoprene was by far the predominant BVOC emitted at this site, with summer mid-day average fluxes of 5.3 and 4.4 mg m⁻² hr⁻¹ in 2005 and 2007, respectively. In comparison, mid-day average fluxes of monoterpenes were 0.21 and 0.15 mg m⁻² hr⁻¹ in each of these years. On short times scales (days), the diel pattern in emission rate compared well with a standard emission algorithm for isoprene. The general shape of the seasonal cycle and the observed decrease in isoprene emission rate in early September was, however, not well captured by the model. Monoterpene emission rates exhibited dependence on light as well as temperature, as determined from the improved fit to the observations obtained by including a light-dependent term in the model. The mid-day average flux of methanol from the canopy was 0.14 mg m⁻² hr⁻¹ in 2005 and 0.19 mg m⁻² hr⁻¹ in 2007, but the maximum flux was observed in spring (29 May 2007), when the flux reached 1.0 mg m⁻² hr⁻¹. This observation is consistent with enhanced methanol production during leaf expansion. Summer mid-day fluxes of acetone were 0.15 mg m⁻² hr⁻¹ during a short period in 2005, but only 0.03 mg m⁻² h⁻¹ averaged over 2007. Episodes of negative fluxes of oxygenated VOCs, particularly acetone, were observed periodically, especially in 2007. Thus, deposition within the canopy could help explain the low season-averaged flux of acetone in 2007. Fluxes of species of biogenic origin at mass-to-charge ($m/z$) ratios of 73 (0.05 mg m⁻² hr⁻¹ in 2005; 0.03 mg m⁻² hr⁻¹ in 2007) and 153 (5 μg m⁻² hr⁻¹ in 2007), possibly corresponding to methyl ethyl ketone and an oxygenated terpene or methyl salicylate, respectively, were also observed.

Hourly measurements of O₃, NO, NO₂, PAN, HNO₃ and NO_y concentrations, and eddy-covariance fluxes of O₃ and NO_y over a temperate deciduous forest from June to November, 2000 were used to evaluate the dry deposition velocities (V_d) estimated by the WRF-Chem dry deposition module (WDDM), which adopted Wesely (1989) scheme for surface resistance (R_c), and the Noah land surface model coupled with a photosynthesis-based Gas-exchange Evapotranspiration Model (Noah-GEM). Noah-GEM produced better V_d(O₃) variations due to its more realistically simulated stomatal resistance (R_s) than WDDM. V_d(O₃) is very sensitive to the minimum canopy stomatal resistance (R_i) which is specified for each seasonal category assigned in WDDM. Treating Sep-Oct as autumn in WDDM for this deciduous forest site caused a large underprediction of V_d(O₃) due to the leafless assumption in ‘autumn’ seasonal category for which an infinite R_i was assigned. Reducing R_i to a value of 70 s m⁻¹, the same as the default value for the summer season category, the modeled and measured V_d(O₃) agreed reasonably well. HNO₃ was found to dominate the NO_y flux during the measurement period; thus the modeled V_d(NO_y) was mainly controlled by the aerodynamic and quasi-laminar sublayer resistances (R_a and R_b), both being sensitive to the surface roughness length (z₀). Using an appropriate value for z₀ (10% of canopy height), WDDM and Noah-GEM agreed well with the observed daytime V_d(NO_y). The differences in V_d(HNO₃) between WDDM and Noah-GEM were small due to the small differences in the calculated R_a and R_b between the two models; however, the differences in R_c of NO₂ and PAN between the two models reached a factor of 1.1–1.5, which in turn caused a factor of 1.1–1.3 differences for V_d. Combining the measured concentrations and modeled V_d, NO_x, PAN and HNO₃ accounted for 19%, 4%, and 70% of the measured NO_y fluxes, respectively.

The Hudson Bay Lowlands (HBL) is the second largest boreal wetland ecosystem in the world and an important natural source of global atmospheric methane. We quantify the HBL methane emissions by using the GEOS-Chem chemical transport model to simulate aircraft measurements over the HBL from the ARCTAS and pre-HIPPO campaigns in May–July 2008, together with continuous 2004–2008 surface observations at Fraserdale (southern edge of HBL) and Alert (Arctic background). The difference in methane concentrations between Fraserdale and Alert is shown to be a good indicator of HBL emissions, and implies a sharp seasonal onset of emissions in late May (consistent with the aircraft data), a peak in July–August, and a seasonal shut-off in September. The model, in which seasonal variation of emission is mainly driven by surface temperature, reproduces well the observations in summer but its seasonal shoulders are too broad. We suggest that this reflects the suppression of emissions by snow cover and greatly improve the model simulation by accounting for this effect. Our resulting best estimate for HBL methane emissions is 2.3 Tg a⁻¹, several-fold higher than previous estimates (Roulet et al., 1994; Worthy et al., 2000).

The Hudson Bay Lowlands (HBL) is the second largest boreal wetland ecosystem in the world and an important natural source of global atmospheric methane. We quantify the HBL methane emissions by using the GEOS-Chem chemical transport model to simulate aircraft measurements over the HBL from the ARCTAS and pre-HIPPO campaigns in May–July 2008, together with continuous 2004–2008 surface observations at Fraserdale (southern edge of HBL) and Alert (Arctic background). The difference in methane concentrations between Fraserdale and Alert is shown to be a good indicator of HBL emissions, and implies a sharp seasonal onset of emissions in late May (consistent with the aircraft data), a peak in July–August, and a seasonal shut-off in September. The model, in which seasonal variation of emission is mainly driven by surface temperature, reproduces well the observations in summer but its seasonal shoulders are too broad. We suggest that this reflects the suppression of emissions by snow cover and greatly improve the model simulation by accounting for this effect. Our resulting best estimate for HBL methane emissions is 2.3 Tg a⁻¹, several-fold higher than previous estimates (Roulet et al., 1994; Worthy et al., 2000).

We used eddy covariance and ecological measurements to investigate the effects of reduced impact logging (RIL) on an old-growth Amazonian forest. Logging caused small decreases in gross primary production, leaf production, and latent heat flux, which were roughly proportional to canopy loss, and increases in heterotrophic respiration, tree mortality, and wood production. The net effect of RIL was transient, and treatment effects were barely discernable after only 1 y. RIL appears to provide a strategy for managing tropical forest that minimizes the potential risks to climate associated with large changes in carbon and water exchange.

We describe an approach for evaluating the representativeness of eddy covariance flux measurements and assessing sensor location bias (SLB) based on footprint modelling and remote sensing. This approach was applied to the 12 main sites of the Fluxnet-Canada Research Network (FCRN)/Canadian Carbon Program (CCP) located along an east-west continental-scale transect, covering grassland, forest, and wetland biomes. For each site, monthly and annual footprint climatologies (i.e. monthly or annual cumulative footprints) were calculated using the Simple Analytical Footprint model on Eulerian coordinates (SAFE). The resulting footprint climatologies were then overlaid on to images of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) derived from LANDSAT Thematic Mapper (TM) imagery, which were used as surrogates of land surface fluxes to estimate SLB. Results indicate that (i) the sizes of annual footprint climatology increased exponentially with increasing cumulative footprint percentages and, for a given percentage of footprint climatology, the footprint areas were significantly different among the sites. Typically, the 90% annual footprint climatology areas varied from 1.1 km² to 5.0 km²; (ii) using either NDVI or EVI as the flux surrogate, the SLB was less than 5% for most sites with respect to the reference area of interest (A_r) at 90% annual footprint climatology (scenario A) and a circular area with radius of 1 km centred at the individual tower (scenario B), with several exceptions; (iii) the SLB decreased with increasing size of footprint climatology for all sites for both scenarios A and B; (iv) out of 12, eight flux towers represented most of the ecosystem surrounding the towers for an area of 0.3 km² up to 10 km² with a satisfactorily low bias of <5%, whereas four towers represented areas ranging from only 0.75 to 4 km²; and (v) the seasonal differences in monthly SLB using NDVI as a flux surrogate were about 1–4% for most sites for both scenarios A and B.

More accurate projections of future carbon dioxide concentrations in the atmosphere and associated climate change depend on improved scientific understanding of the terrestrial carbon cycle. Despite the consensus that U.S. terrestrial ecosystems provide a carbon sink, the size, distribution, and interannual variability of this sink remain uncertain. Here we report a terrestrial carbon sink in the conterminous U.S. at 0.63 pg C yr⁻¹ with the majority of the sink in regions dominated by evergreen and deciduous forests and savannas. This estimate is based on our continuous estimates of net ecosystem carbon exchange (NEE) with high spatial (1 km) and temporal (8-day) resolutions derived from NEE measurements from eddy covariance flux towers and wall-to-wall satellite observations from Moderate Resolution Imaging Spectroradiometer (MODIS). We find that the U.S. terrestrial ecosystems could offset a maximum of 40% of the fossil-fuel carbon emissions. Our results show that the U.S. terrestrial carbon sink varied between 0.51 and 0.70  pg C yr⁻¹ over the period 2001–2006. The dominant sources of interannual variation of the carbon sink included extreme climate events and disturbances. Droughts in 2002 and 2006 reduced the U.S. carbon sink by ∼20% relative to a normal year. Disturbances including wildfires and hurricanes reduced carbon uptake or resulted in carbon release at regional scales. Our results provide an alternative, independent, and novel constraint to the U.S. terrestrial carbon sink.

Nitrous acid (HONO) is important as a significant source of hydroxyl radical (OH) in the troposphere and as a potent indoor air pollutant. It is thought to be generated in both environments via heterogeneous reactions involving nitrogen dioxide (NO₂). In order to enable fast-response HONO detection suitable for eddy-covariance flux measurements and to provide a direct method that avoids interferences associated with derivatization, we have developed a 2-channel tunable infrared laser differential absorption spectrometer (TILDAS) capable of simultaneous high-frequency measurements of HONO and NO₂. Beams from two mid-infrared continuous-wave mode quantum cascade lasers (cw-QCLs) traverse separate 210 m paths through a multi-pass astigmatic sampling cell at reduced pressure for the direct detection of HONO (1660 cm⁻¹) and NO₂ (1604 cm⁻¹). The resulting one-second detection limits (S/N=3) are 300 and 30 ppt (pmol/mol) for HONO and NO₂, respectively. Our HONO quantification is based on revised line-strengths and peak positions for cis-HONO in the 6-micron spectral region that were derived from laboratory measurements. An essential component of ambient HONO measurements is the inlet system and we demonstrate that heated surfaces and reduced pressure minimize sampling artifacts.

abstract