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The provinces of Alberta and Saskatchewan account for 70% of Canada's methane emissions from the oil and gas sector. In 2018, the Government of Canada introduced methane regulations to reduce emissions from the sector by 40-45% from the 2012 levels by 2025. Complementary to inventory accounting methods, the effectiveness of regulatory practices to reduce emissions can be assessed using atmospheric measurements and inverse models. Total anthropogenic (oil and gas, agriculture, and waste) emission rates of methane from 2010 to 2017 in Alberta and Saskatchewan were derived using hourly atmospheric methane measurements over a six-month winter period from October to March. Scaling up the winter estimate to annual indicated an anthropogenic emission rate of 3.7 ± 0.7 MtCH4/year, about 60% greater than that reported in Canada's National Inventory Report (2.3 MtCH4). This discrepancy is tied primarily to the oil and gas sector emissions as the reported emissions from livestock operations (0.6 MtCH4) are well substantiated in both top-down and bottom-up estimates and waste management (0.1 MtCH4) emissions are small. The resulting estimate of 3.0 MtCH4 from the oil and gas sector is nearly twice that reported in Canada's National Inventory (1.6 MtCH4).

Extremely high levels of column-averaged dry-air mole fractions of atmospheric methane (XCH4) were detected in August and September 2013 over northeast Asia (∼ 20 ppb above the averaged summertime XCH4 over 2009–2012, after removing a long-term trend), as being retrieved from the Short-Wavelength InfraRed (SWIR) spectral data observed with the Thermal And Near-infrared Sensor for carbon Observation – Fourier Transform Spectrometer (TANSO-FTS) onboard Greenhouse Gases Observing Satellite (GOSAT). Similar enhancements of XCH4 were also observed by the ground-based measurements at two Total Carbon Column Observing Network (TCCON) sites in Japan. The analysis of surface CH4 concentrations observed at three monitoring sites around the Japan archipelago suggest that the extreme increase of XCH4 has occurred in a limited area. The model analysis was conducted to investigate this anomalously high XCH4 event, using an atmospheric transport model. The results indicate that the extreme increase of XCH4 is attributed to the anomalous atmospheric pressure pattern over East Asia during the summer of 2013, which effectively transported the CH4-rich air to Japan from the strong CH4 source areas in east China. The two Japanese TCCON sites, ∼ 1000 km east–west apart each other, coincidentally located along the substantially CH4-rich air flow from east China. This analysis demonstrates the capability of GOSAT to monitor an XCH4 event on a synoptic scale. We anticipate that the synoptic information of XCH4 from GOSAT data contributes to improve our understanding of regional carbon cycle and the regional flux estimation.

The Canadian Arctic (> 60 ∘ N, 60–141 ∘ W) may undergo drastic changes if the Arctic warming trend continues. For methane ( CH4 ), Arctic reservoirs are large and widespread, and the climate feedbacks from such changes may be potentially substantial. Current bottom-up and top-down estimates of the regional CH4 flux range widely. This study analyzes the recent observations of atmospheric CH4 from five arctic monitoring sites and presents estimates of the regional CH4 fluxes for 2012–2015. The observational data reveal sizeable synoptic summertime enhancements in the atmospheric CH4 that are distinguishable from background variations, which indicate strong regional fluxes (primarily wetland and biomass burning CH4 emissions) around Behchoko and Inuvik in the western Canadian Arctic. Three regional Bayesian inversion modelling systems with two Lagrangian particle dispersion models and three meteorological datasets are applied to estimate fluxes for the Canadian Arctic and show relatively robust results in amplitude and temporal variations across different transport models, prior fluxes, and subregion masking. The estimated mean total CH4 flux for the entire Canadian Arctic is 1.8±0.6 Tg CH4 yr −1 . The flux estimate is partitioned into biomass burning of 0.3±0.1 Tg CH4 yr −1 and the remaining natural (wetland) flux of 1.5±0.5 Tg CH4 yr −1 . The summer natural CH4 flux estimates clearly show inter-annual variability that is positively correlated with surface temperature anomalies. The results indicate that years with warmer summer conditions result in more wetland CH4 emissions. More data and analysis are required to statistically characterize the dependence of regional CH4 fluxes on the climate in the Arctic. These Arctic measurement sites will aid in quantifying the inter-annual variations and long-term trends in CH4 emissions in the Canadian Arctic.

A regional greenhouse gas flux inversion system (REFIST v1.0) is described. This paper provides a comprehensive evaluation of REFIST for three provinces in Canada that include Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using year 2009 fossil fuel CO2 CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, inversion time span, prior flux distribution, region definition and the atmospheric transport model, as well as their interactions. The posterior fluxes were estimated by two different optimisation methods, the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. Increasing the number of sub-regions (unknowns) beyond "optimality" can produce unstable and unrealistic fluxes for some sub-regions, and does not yield significantly different flux estimates overall. The two optimisation methods can provide comparable, stable and realistic flux results when the transport model error is small (prior R2~0.8 with synthetic observations), but both methods present difficulty when the transport model error is large (prior R2~0.3). Stable and realistic sub-regional and monthly flux estimates for the western region of AB+SK can be obtained, but not for the eastern region of ON without excluding a poorly simulated station. This indicates a real observation-based inversion will likely work for the western region for tracers with similar temporal and spatial emission characteristics to fossil fuel CO2 [e.g. wintertime CH4 in Canada]. However, improvements are needed with the current inversion setup before a real inversion is performed for the eastern region.

We describe an assimilation system for atmospheric methane (CH4), CarbonTracker-CH4, and demonstrate the diagnostic value of global or zonally averaged CH4 abundances for evaluating the results. We show that CarbonTracker-CH4 is able to simulate the observed zonal average mole fractions and capture inter-annual variability in emissions quite well at high northern latitudes (53–90° N). In contrast, CarbonTracker-CH4 is less successful in the tropics where there are few observations and therefore misses significant variability and is more influenced by prior flux estimates. CarbonTracker-CH4 estimates of total fluxes at high northern latitudes are about 81 ± 7 Tg CH4 yr−1, about 12 Tg CH4 yr−1 (13%) lower than prior estimates, a result that is consistent with other atmospheric inversions. Emissions from European wetlands are decreased by 30%, a result consistent with previous work by Bergamaschi et al. (2005); however, unlike their results, emissions from wetlands in boreal Eurasia are increased relative to the prior estimate. Although CarbonTracker-CH4 does not estimate an increasing trend in emissions from high northern latitudes for 2000 through 2010, significant inter-annual variability in high northern latitude fluxes is recovered. Exceptionally warm growing season temperatures in the Arctic occurred in 2007, a year that was also anonymously wet. Estimated emissions from natural sources were greater than the decadal average by 4.4 ± 3.8 Tg CH4 yr−1 in 2007. CarbonTracker-CH4 estimates for temperate latitudes are only slightly increased over prior estimates, but about 10 Tg CH4 yr−1 is redistributed from Asia to North America. This difference exceeds the estimated uncertainty for North America (±3.5 Tg CH4 yr−1). We used time invariant prior flux estimates, so for the period from 2000 to 2006, when the growth rate of global atmospheric CH4 was very small, the assimilation does not produce increases in natural or anthropogenic emissions in contrast to bottom-up emission data sets. After 2006, when atmospheric CH4 began its recent increases, CarbonTracker-CH4 allocates some of the increases to anthropogenic emissions at temperate latitudes, and some to tropical wetland emissions. For temperate North America the prior flux increases by about 4 Tg CH4 yr−1 during winter when biogenic emissions are small. Examination of the residuals at some North American observation sites suggests that increased gas and oil exploration may play a role since sites near fossil fuel production are particularly hard for the inversion to fit and the prior flux estimates at these sites are apparently lower and lower over time than what the atmospheric measurements imply. The tropics are not currently well resolved by CarbonTracker-CH4 due to sparse observational coverage and a short assimilation window. However, there is a small uncertainty reduction and posterior emissions are about 18% higher than prior estimates. Most of this increase is allocated to tropical South America rather than being distributed among the global tropics. Our estimates for this source region are about 32 ± 4 Tg CH4 yr−1, in good agreement with the analysis of Melack et al. (2004) who obtained 29 Tg CH4 yr−1 for the most productive region, the Amazon Basin.

The global methane (CH4) budget is becoming an increasingly important component for managing realistic pathways to mitigate climate change. This relevance, due to a shorter atmospheric lifetime and a stronger warming potential than carbon dioxide, is challenged by the still unexplained changes of atmospheric CH4 over the past decade. Emissions and concentrations of CH4 are continuing to increase, making CH4 the second most important human-induced greenhouse gas after carbon dioxide. Two major difficulties in reducing uncertainties come from the large variety of diffusive CH4 sources that overlap geographically, and from the destruction of CH4 by the very short-lived hydroxyl radical (OH). To address these difficulties, we have established a consortium of multi-disciplinary scientists under the umbrella of the Global Carbon Project to synthesize and stimulate research on the methane cycle, and producing regular (similar to biennial) updates of the global methane budget. This consortium includes atmospheric physicists and chemists, biogeochemists of surface and marine emissions, and socio-economists who study anthropogenic emissions. Following Kirschke et al. (2013), we propose here the first version of a living review paper that integrates results of top-down studies (exploiting atmospheric observations within an atmospheric inverse-modelling framework) and bottom-up models, inventories and data-driven approaches (including process-based models for estimating land surface emissions and atmospheric chemistry, and inventories for anthropogenic emissions, data-driven extrapolations). For the 2003-2012 decade, global methane emissions are estimated by top-down inversions at 558 TgCH(4) yr(-1), range 540-568. About 60% of global emissions are anthropogenic (range 50-65 %). Since 2010, the bottom-up global emission inventories have been closer to methane emissions in the most carbon-intensive Representative Concentrations Pathway (RCP8.5) and higher than all other RCP scenarios. Bottom-up approaches suggest larger global emissions (736 TgCH(4) yr(-1), range 596-884) mostly because of larger natural emissions from individual sources such as inland waters, natural wetlands and geological sources. Considering the atmospheric constraints on the top-down budget, it is likely that some of the individual emissions reported by the bottom-up approaches are overestimated, leading to too large global emissions. Latitudinal data from top-down emissions indicate a predominance of tropical emissions (similar to 64% of the global budget, amp;lt;30 degrees N) as compared to mid (similar to 32 %, 30-60 degrees N) and high northern latitudes (similar to 4 %, 60-90 degrees N). Top-down inversions consistently infer lower emissions in China (similar to 58 TgCH(4) yr(-1), range 51-72, -14 %) and higher emissions in Africa (86 TgCH(4) yr(-1), range 73-108, + 19 %) than bottom-up values used as prior estimates. Overall, uncertainties for anthropogenic emissions appear smaller than those from natural sources, and the uncertainties on source categories appear larger for top-down inversions than for bottom-up inventories and models. The most important source of uncertainty on the methane budget is attributable to emissions from wetland and other inland waters. We show that the wetland extent could contribute 30-40% on the estimated range for wetland emissions. Other priorities for improving the methane budget include the following: (i) the development of process-based models for inland-water emissions, (ii) the intensification of methane observations at local scale (flux measurements) to constrain bottom-up land surface models, and at regional scale (surface networks and satellites) to constrain top-down inversions, (iii) improvements in the estimation of atmospheric loss by OH, and (iv) improvements of the transport models integrated in top-down inversions. The data presented here can be downloaded from the Carbon Dioxide Information Analysis Center (http://doi.org/10.3334/CDIAC/GLOBAL_METHANE_BUDGET_2016_V1.1) and the Global Carbon Project. Funding Agencies|Swiss National Science Foundation; NASA [NNX14AF93G, NNX14AO73G]; National Environmental Science Program - Earth Systems and Climate Change Hub; European Commission [283576, 633080]; ESA Climate Change Initiative Greenhouse Gases Phase 2 project; US Department of Energy, BER [DE-AC02-05CH11231]; FAO member countries; Environment Research and Technology Development Fund of the Ministry of the Environment, Japan [2-1502]; ERC [322998]; NERC [NE/J00748X/1]; Swedish Research Council VR; Research Council of Norway [244074]; NSF [1243232, 1243220]; National Science and Engineering Research Council of Canada (NSERC); Chinas QianRen Program; CSIRO Australia; Australian Bureau of Meteorology; Australian Institute of Marine Science; Australian Antarctic Division; NOAA USA; Meteorological Service of Canada; National Aeronautic and Space Administration (NASA) [NAG5-12669, NNX07AE89G, NNX11AF17G, NNX07AE87G, NNX07AF09G, NNX11AF15G, NNX11AF16G]; Department of Energy and Climate Change (DECC, UK) [GA01081]; Commonwealth Scientific and Industrial Research Organization (CSIRO Australia); Bureau of Meteorology (Australia); Joint DECC/Defra Met Office Hadley Centre Climate Programme [GA01101]

[1] Arctic regional climate is influenced by the radiative impact of aerosol black carbon (BC) both in the atmosphere and deposited on the snow and ice covered surfaces. The NIES (National Institute for Environmental Studies) global atmospheric transport model was used, with BC emissions from mid-latitude fossil fuel and biomass burning source regions, to simulate BC concentrations with 16 year period. The model-simulated BC agreed well with the BC observations, including the trends and seasonality, at three Arctic sites: Alert (Nunavut, Canada), Barrow (Alaska, USA), and Zepplin, Ny-Alesund (Svalbard, Norway). The equivalent black carbon (EBC, absorption inferred BC) observations at the three Arctic locations showed an overall decline of 40% from 1990 to 2009; with most change occurring during early 1990s. Model simulations confirmed declining influence on near surface BC contribution by 70% , and atmospheric BC burden by one half from the Former Soviet Union (FSU) BC source region over 16 years. In contrast, the BC contribution from the East Asia (EA) region has little influence at the surface but atmospheric Arctic BC burden increased by 3 folds. Modelled dry deposition is dominant in the Arctic during wintertime, while wet deposition prevails at all latitudes during summer. Sensitivity analyses on the dry and wet deposition schemes indicate that parameterizations need to be refined to improve on the model performance. There are limitations in the model due to simplified parameterizations and remaining model uncertainties, which requires further exploration of source region contributions, especially from growing EA source region to Arctic BC levels in the future is warranted.

Increasing atmospheric carbon dioxide (CO2) is the principal driver of anthropogenic climate change. Asia is an important region for the global carbon budget, with 4 of the world's 10 largest national emitters of CO2. Using an ensemble of seven atmospheric inverse systems, we estimated land biosphere fluxes (natural, land-use change and fires) based on atmospheric observations of CO2 concentration. The Asian land biosphere was a net sink of −0.46 (−0.70–0.24) PgC per year (median and range) for 1996–2012 and was mostly located in East Asia, while in South and Southeast Asia the land biosphere was close to carbon neutral. In East Asia, the annual CO2 sink increased between 1996–2001 and 2008–2012 by 0.56 (0.30–0.81) PgC, accounting for ∼35% of the increase in the global land biosphere sink. Uncertainty in the fossil fuel emissions contributes significantly (32%) to the uncertainty in land biosphere sink change., Land biosphere uptake of carbon is important in mitigating the anthropogenic increase in atmospheric CO2 and its climate forcing. Here, the authors show that land biosphere uptake of carbon in Asia has increased substantially since the mid 1990s, likely owing to reforestation and regional climate change.

Independent verification of bottom-up greenhouse gas (GHG) emission inventories is crucial for a reliable reporting of Kyoto gases to the United Nations Framework Convention on Climate Change. Here, we use a pseudo-data experiment to test if our improved version of the well-known Radon tracer method (RTM) is able to quantitatively retrieve regional GHG fluxes. Using in-situ observations in Egbert, Canada, from 2006 to 2009 for the RTM, we derive night-time fluxes of CH4 and N2O in southern Ontario. The N2O fluxes found have a inter-quartile range of 7.6–31.2 μgN2O/(m2h) with an overall mean of 24.4 ± 5.6 μgN2O/(m2h). Comparison with the EDGAR4.1 inventory revealed an underestimation by a factor of 1.7 ± 0.4 in the inventory, which is explainable by missing natural sources and a missing seasonal cycle in the inventory. Our RTM-based fluxes of CH4 with a inter-quartiles range of 0.19–0.49 mgCH4/(m2h) and a mean of 0.36 ± 0.08 mgCH4/(m2h) lie significantly below the inventory-based estimates of 0.79 ± 0.06 m...

Inversion models can use atmospheric concentration measurements to estimate surface fluxes. This study is an evaluation of the errors in a regional flux inversion model for different provinces of Canada, Alberta (AB), Saskatchewan (SK) and Ontario (ON). Using CarbonTracker model results as the target, the synthetic data experiment analyses examined the impacts of the errors from the Bayesian optimisation method, prior flux distribution and the atmospheric transport model, as well as their interactions. The scaling factors for different sub-regions were estimated by the Markov chain Monte Carlo (MCMC) simulation and cost function minimization (CFM) methods. The CFM method results are sensitive to the relative size of the assumed model-observation mismatch and prior flux error variances. Experiment results show that the estimation error increases with the number of sub-regions using the CFM method. For the region definitions that lead to realistic flux estimates, the numbers of sub-regions for the western region of AB/SK combined and the eastern region of ON are 11 and 4 respectively. The corresponding annual flux estimation errors for the western and eastern regions using the MCMC (CFM) method are -7 and -3 % (0 and 8 %) respectively, when there is only prior flux error. The estimation errors increase to 36 and 94 % (40 and 232 %) resulting from transport model error alone. When prior and transport model errors co-exist in the inversions, the estimation errors become 5 and 85 % (29 and 201 %). This result indicates that estimation errors are dominated by the transport model error and can in fact cancel each other and propagate to the flux estimates non-linearly. In addition, it is possible for the posterior flux estimates having larger differences than the prior compared to the target fluxes, and the posterior uncertainty estimates could be unrealistically small that do not cover the target. The systematic evaluation of the different components of the inversion model can help in the understanding of the posterior estimates and percentage errors. Stable and realistic sub-regional and monthly flux estimates for western region of AB/SK can be obtained, but not for the eastern region of ON. This indicates that it is likely a real observation-based inversion for the annual provincial emissions will work for the western region whereas; improvements are needed with the current inversion setup before real inversion is performed for the eastern region.

Seasonal and inter-annual variations of atmospheric CO 2 for the period from 1961 to 1997 have been simulated using a global tracer transport model driven by a new version of the Biome BioGeochemical Cycle model (Biome-BGC). Biome-BGC was forced by daily temperature and precipitation from the NCEP reanalysis dataset, and the calculated monthly-averaged CO 2 fluxes were used as input to the global transport model. Results from an inter-comparison with the Carnegie–Ames–Stanford Approach model (CASA) and the Simulation model of Carbon cYCle in Land Ecosystems (Sim-CYCLE) model are also reported. The phase of the seasonal cycle in the Northern Hemisphere was reproduced generally well by Biome-BGC, although the amplitude was smaller compared to the observations and to the other biosphere models. The CO 2 time series simulated by Biome-BGC were compared to the global CO 2 concentration anomalies from the observations at Mauna Loa and the South Pole. The modeled concentration anomalies matched the phase of the inter-annual variations in the atmospheric CO 2 observations; however, the modeled amplitude was lower than the observed value in several cases. The result suggests that a significant part of the inter-annual variability in the global carbon cycle can be accounted for by the terrestrial biosphere models. Simulations performed with another climate-based model, Sim-CYCLE, produced a larger amplitude of inter-annual variability in atmospheric CO 2, making the amplitude closer to the observed range, but with a more visible phase mismatch in a number of time periods. This may indicate the need to increase the Biome-BGC model sensitivity to seasonal and inter-annual changes in temperature and precipitation. DOI: 10.1034/j.1600-0889.2003.00044.x

Variations of δ^C in atmospheric CO_2 were reconstructed for the period of 1724 to 1961 by analyzing a high-accumulation ice core drilled at H15,Antarctica. Measured values of δ^C were corrected for the gravitational enrichment which occurred in the firn, on the basis of the analytical results of δ^N in N_2 in the core. From the vertical profile of δ^N calculated using a diffusion model for the firn, it was suggested that the air in the layer shallower than 17m depth was mixed well with the atmosphere over the firn surface. The average value of δ^C during the period 1724-1775 was found to be -6.67±0.11‰. δ^C decreased secularly from this value to -7.33‰ in 1961,and its trend was enhanced especially after the late 19th century, corresponding to the long-term increase of the CO_2 concentration. CO_2 fluxes estimated by deconvolution analysis of the reconstructed CO_2 concentrations with the box-diffusion model accounted for the observed variations of δ^C fairly well. It was also suggested that a dip of δ^C found at the end of the 18th century was attributable to terrestrial biospheric CO_2 emissions enhanced under high air temperatures.

Digital filtering and harmonic regression curve fitting techniques are applied to CO2 flask data from four stations in North America (Pt. Barrow, Alert, Sable Island and Cape St. James) to evaluate these two different methodologies in terms of growth rate and seasonal cycle in the atmospheric CO2 concentration. Both methods agree relatively well in producing long-term atmospheric CO2 trend at each of the monitoring stations, as well as in capturing relatively large interannual variations in the annual growth rate. Furthermore, they both agree in indicating the dependency of the variation in the seasonal amplitude on the seasonal minimum concentration. The digital filtering technique is able to capture the local temporal variation in CO2 measurements much better than the harmonic regression method, although in some cases this variability is exaggerated in the digital filtering approach. The harmonic regression approach tends to smooth out the data, with much of the power in the very long period oscillations. Also, the timing of the occurrence of the seasonal minimum calculated by the digital filtering method tends to be earlier than that calculated by the harmonic regression method, although both methods do not indicate any major secular change in the timing. The overall assessment of the two methods applied to the CO2 flask data underscores the importance of using more than one curve fitting method before any conclusions can be drawn from the flask data about the interannual variability in the trend and seasonal cycle of the atmospheric CO2 concentration. © 1997 John Wiley & Sons, Ltd.

Northern Eurasia is one of the largest terrestrial carbon reservoirs on the Earth's surface. However, since the coverage of surface CO2 observations is still limited, the response to the climate variability remains uncertain. We estimated monthly CO2 fluxes for three sub-regions in Northern Eurasia (north of ~60?N), Northeastern Europe, Western Siberia and Eastern Siberia, using CO2 retrievals from the Japanese Greenhouse Gases Observing SATellite (GOSAT). The variations of estimated CO2 fluxes were examined in terms of the regional climate variability, for the three consecutive growing seasons of 2009?2011. The CO2 fluxes estimated using GOSAT data are highly correlated with the surface temperature anomalies in July and August (r?>?0.8) while no correlation is found in the CO2 fluxes estimated only using surface observations. The estimated fluxes from GOSAT data exhibit high negative correlations with one-month lagged positive precipitation anomalies in late summer (r?>??0.7) through surface temperature and the Normalized Difference Vegetation Index (NDVI). The results indicate that GOSAT data reflects the changes in terrestrial biospheric processes responding to climate anomalies. In 2010, a large part of Eurasia experienced an extremely hot and dry summer, while cold and wet weather conditions were recorded in Western Siberia. The CO2 fluxes estimated from GOSAT data showed a reduction of net CO2 uptake in Northeastern Europe and Eastern Siberia, but the enhancement of net CO2 uptake in Western Siberia. These opposite sub-regional flux anomalies can be explained by the different climate anomalies on a sub-regional scale in Northern Eurasia. Thus, this study demonstrates that space-based observations by GOSAT compensate for the lack of ground-based observational coverage so as to better capture the inter-annually varying atmosphere-terrestrial biosphere CO2 exchange on a regional scale.

The recent decline in sea ice cover in the Arctic Ocean could affect the regional radiative forcing via changes in sea ice-atmosphere exchange of dimethyl sulfide (DMS) and biogenic aerosols formed from its atmospheric oxidation, such as methanesulfonic acid (MSA). This study examines relationships between changes in total sea ice extent north of 70 degrees N and atmospheric MSA measurement at Alert, Nunavut, during 1980-2009; at Barrow, Alaska, during 1997-2008; and at Ny-Alesund, Svalbard, for 1991-2004. During the 1980-1989 and 1990-1997 periods, summer (July-August) and June MSA concentrations at Alert decreased. In general, MSA concentrations increased at all locations since 2000 with respect to 1990 values, specifically during June and summer at Alert and in summer at Barrow and Ny-Alesund. Our results show variability in MSA at all sites is related to changes in the source strengths of DMS, possibly linked to changes in sea ice extent as well as to changes in atmospheric transport patterns. Since 2000, a late spring increase in atmospheric MSA at the three sites coincides with the northward migration of the marginal ice edge zone where high DMS emissions from ocean to atmosphere have previously been reported. Significant negative correlations are found between sea ice extent and MSA concentrations at the three sites during the spring and June. These results suggest that a decrease in seasonal ice cover influencing other mechanisms of DMS production could lead to higher atmospheric MSA concentrations.

[1] Sunlit and shaded leaf separation proposed by Norman (1982) is an effective way to upscale from leaf to canopy in modeling vegetation photosynthesis. The Boreal Ecosystem Productivity Simulator (BEPS) makes use of this methodology, and has been shown to be reliable in modeling the gross primary productivity (GPP) derived from CO2flux and tree ring measurements. In this study, we use BEPS to investigate the effect of canopy architecture on the global distribution of GPP. For this purpose, we use not only leaf area index (LAI) but also the first ever global map of the foliage clumping index derived from the multiangle satellite sensor POLDER at 6 km resolution. The clumping index, which characterizes the degree of the deviation of 3-dimensional leaf spatial distributions from the random case, is used to separate sunlit and shaded LAI values for a given LAI. Our model results show that global GPP in 2003 was 132 ± 22 Pg C. Relative to this baseline case, our results also show: (1) global GPP is overestimated by 12% when accurate LAI is available but clumping is ignored, and (2) global GPP is underestimated by 9% when the effective LAI is available and clumping is ignored. The clumping effects in both cases are statistically significant (p < 0.001). The effective LAI is often derived from remote sensing by inverting the measured canopy gap fraction to LAI without considering the clumping. Global GPP would therefore be generally underestimated when remotely sensed LAI (actually effective LAI by our definition) is used. This is due to the underestimation of the shaded LAI and therefore the contribution of shaded leaves to GPP. We found that shaded leaves contribute 50%, 38%, 37%, 39%, 26%, 29% and 21% to the total GPP for broadleaf evergreen forest, broadleaf deciduous forest, evergreen conifer forest, deciduous conifer forest, shrub, C4 vegetation, and other vegetation, respectively. The global average of this ratio is 35%.

A nested inverse modelling system was developed for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Monthly inverse modelling was conducted using CO2 concentration measurements of 3 yr (2001–2003) at 88 sites. Inversion results show that in 2003 the global carbon sink is −2.76 ± 0.55 Pg C. Oceans and lands are responsible for 88.5% and 11.5% of the sink, respectively. Northern lands are the largest sinks with North America contributing a sink of −0.97 ± 0.21 Pg C in 2003, of which Canada's sink is −0.34 ± 0.14 Pg C. For Canada, the inverse results show a spatial pattern in agreement, for the most part, with a carbon source and sink distribution map previously derived through ecosystem modelling. However, discrepancies in the spatial pattern and in flux magnitude between these two estimates exist in certain regions. Numerical experiments with a full covariance matrix, with the consideration of the error structure of the a priori flux field based on meteorological variables among the 30 North America regions, resulted in a small but meaningful improvement in the inverted fluxes. Uncertainty reduction analysis suggests that new observation sites are still needed to further improve the inversion for these 30 regions in North America.DOI: 10.1111/j.1600-0889.2006.00235.x

Using discrete air sampling, values of δ13C and δ18O in atmospheric CO2, as well as its concentration, were measured in a forest in the central part of the main island of Japan during the period from June 1994 to June 1996 to examine the biospheric contribution to their temporal variations. δ13C shows a prominent diurnal variation with high values in the daytime and low values in the nighttime, especially during the warm season. δ13C also vary seasonally, showing a maximum in summer and a minimum in spring. The diurnal and seasonal variations of δ13C are opposite in phase with those of the CO2 concentration. The rate of change in δ13C with respect to the CO2 concentration is found to be approximately -0.05‰/ppmv. This suggests that the diurnal and seasonal variations of the CO2concentration are produced primarily by diurnally- and seasonally-dependent photosynthetic-respiratory processes of the biosphere near the observation site, respectively. In the warm season, δ18O also increases in the daytime and decreased in the nighttime, which is similar to the diurnal variation of δ13C, but opposite to that of the CO2 concentration. The diurnal δ18O variation is thought to be caused by the release of isotopically heavy CO2during photosynthesis, and light CO2 during respiration. However, an interpretation of the seasonal δ18O variation is found to be much more difficult than those of δ13C and the CO2 concentration. This is likely due to complicated combinations of different seasonally varying fluxes of biospheric CO2 into the atmosphere, as well as to various weather-dependent factors governing the δ18O composition in CO2.DOI: 10.1034/j.1600-0889.49.issue4.3.x

[1] The rate of increase in global atmospheric methane (CH4) abundance has steadily declined since the late 1980s with near zero increase from 1999 through 2006. At the Canadian Baseline Observatory at Alert, Canada (82°28′N, 62°30′W), continuous measurements of methane (CH4) and carbon dioxide (CO2) have been made since 1987. During winter, both gases are frequently highly correlated during well-defined episodes lasting from 2 to 5 days. We observe a gradual decrease in the ratios of CH4/CO2 during these episodes from ∼16 ppb CH4 (ppm CO2)−1 to ∼12 ppb CH4 (ppm of CO2)−1 over the entire record. An atmospheric transport model with prescribed CO2 and CH4 source distributions is used to partition simulated CH4 events into contributions by region. We show that anthropogenic emissions from Europe and Siberia account for more than 85% of the CO2 and CH4 enhancements simulated at Alert, but without a change in CH4 emissions, modeled CH4/CO2 ratios remain constant. To reproduce the observed trend in the ratio of CH4/CO2, the model requires a reduction in emissions of CH4 on the order of 30 Tg (13.6 to 33.4 Tg) in Europe and Siberia over the observational period. This is about twice the drop reported by the Emission Database for Global Atmospheric Research (EDGAR) emissions inventory and large enough to account for the leveling off of the global atmospheric CH4 burden observed over the past 20 years.

[1] In atmospheric transport models, the covariation of the atmospheric transport and annually neutral biospheric CO2 flux is usually evident as the annual zonal mean surface CO2 concentration gradient. Using the NIES transport model and CO2 flux from the Biome-BGC model, the covariations of different transport mechanisms and CO2 flux were examined and quantified. Including the covariation of the total transport (processes included in the NIES model) and CO2 flux, the annual average pole to pole CO2 concentration gradient is 3.5 ppm and interhemispheric difference of the average extratropical surface concentration is 2.5 ppm. The conventional covariation mechanism of the seasonal variation of planetary boundary layer mixing height and CO2 flux accounts for approximately 45% of the CO2 concentration gradient. Another important contribution to the CO2 concentration gradient in this model is the covariation of the extratropical anomaly transport (mainly by cyclones and anticyclones) and the biospheric flux, which accounts for about 55%. This alternate physical mechanism is the association of stronger meridional (north–south) anomaly transport (under strong baroclinic instability condition) with higher CO2 concentration from soil respiration in the winter and weaker anomaly transport (weak baroclinic instability condition) with lower CO2 concentration from photosynthetic uptake in the summer. The net result of the meridional transport and flux covariation is a north–south annual zonal mean CO2 concentration gradient.

[1] The atmosphere-land-ocean fluxes of CO2 were derived for 64 partitioned areas of the globe (22 over the ocean and 42 over the land) using a time-dependent inverse (TDI) model for the period of January 1988 to December 2001. The model calculation partially follow the TransCom-3 protocol, and is constrained by atmospheric CO2 concentration data from 87 stations and fully time-dependent atmospheric transport model simulations. The air-to-land and air-to-sea fluxes averaged over the 1990s are estimated at 1.15 ± 0.74 and 1.88 ± 0.53 Pg-C yr−1, respectively. These estimates, however, remain uncertain owing to sampling biases arising from the sparse distribution of atmospheric CO2 data, are compared with other estimates by various methods. The sensitivity analysis indicates that the differences in fluxes and flux variability caused by the choices of initial conditions for the TDI model are smaller compared to those due to the selection of measurement networks. Our model results capture interannual variations in global and regional CO2 fluxes realistically. The estimated oceanic CO2 flux anomalies appear to be closely related to prominent climate modes such as El Nino–Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the Pacific Decadal Oscillation (PDO). The results from the correlation analyses show that the oceanic CO2 flux in the tropics is strongly influenced by the ENSO dynamical cycle, and that in the sub-polar regions by upwelling of sub-surface waters in the winter and plankton blooms in the spring.

lower than those estimated from TDI model results, by about 1.0 Pg-C yr � 1 for the periods and regions of intense fire. The correlation and principal component analyses suggest that changes in meteorology (i.e., rainfall and air temperature) associated with the

[1] In order to examine the role of terrestrial biospheric activity in the seasonal variation of δ18O of atmospheric CO2, we measured δ18O values of CO2 and H2O in the soil and the canopy air in a temperate forest in the northern part of the main island of Japan for the period August 2000–December 2001. It was found that the δ18O value of the soil water near the surface varied seasonally almost in phase with that of precipitation, except for spring. On the other hand, its seasonal variation at 70 cm depth showed a 3-month delay compared to those at 10 and 40 cm depths, owing to slow penetration of precipitation into the soil. The measured δ18O values of CO2 in the soil air at 10, 40, and 70 cm depths agreed well with the results calculated under the assumption that CO2 in the soil air was isotopically equilibrated with its surrounding soil water. On the basis of the measurement results, we derived the seasonally varying oxygen isotopic discrimination factors for respiration and photosynthesis processes. Using these discrimination factors as well as biospheric CO2 fluxes estimated by employing an ecosystem model, we calculated the seasonal variation of δ18O of atmospheric CO2 in the forest canopy. The result showed a good agreement with the observation, indicating that the isotopic contribution of photosynthesis to the atmospheric δ18O was strong in spring and fall, while that of respiration was dominant in summer and winter.

We present analysis of the temporal variation of atmospheric CO 2 in the subtropical region of East Asia, obtained aboard a ferry between Ishigaki Island and Hateruma Island, Japan for the period June 1993–April 2005. The annual mean CO 2 concentration increases from 360.1 ppmv in 1994 to 378.4 ppmv in 2004, showing an average growth rate of 1.8 ppmv yr -1 . The growth rate shows interannual variations with high values during ENSO events. The average seasonal CO 2 cycle reaches the maximum in early April and the minimum in mid-September, with a peak-to-peak amplitude of 8.5 ppmv. Numerical simulations using a three-dimensional atmospheric transport model show interannual variations of the CO 2 growth rate similar to the observation, but the amplitude of the seasonal cycle is larger, with maximum concentration appearing earlier than the observation by 1 month. Low CO 2 values observed during the spring of 1998 are likely associated with the 1997/1998 ENSO event. A backward trajectory analysis suggests that they were due to changes in atmospheric transport whereby maritime air masses from the Pacific Ocean dominated over polluted air masses from the Asian Continent. Extreme values (either high or low) of CO 2 are also occasionally observed. A comparison of backward trajectories of air parcels with CO 2 concentration fields calculated using the atmospheric transport model shows that these unusual CO 2 concentrations result from the transport of air affected not only by anthropogenic CO 2 emissions but also by terrestrial biospheric activities mainly in China. DOI: 10.1111/j.1600-0889.2007.00288.x

A nested inverse modelling system was developed for estimating carbon fluxes of 30 regions in North America and 20 regions for the rest of the globe. Monthly inverse modelling was conducted using CO 2 concentration measurements of 3 yr (2001–2003) at 88 sites. Inversion results show that in 2003 the global carbon sink is −2.76 ± 0.55 Pg C. Oceans and lands are responsible for 88.5% and 11.5% of the sink, respectively. Northern lands are the largest sinks with North America contributing a sink of −0.97 ± 0.21 Pg C in 2003, of which Canada's sink is −0.34 ± 0.14 Pg C. For Canada, the inverse results show a spatial pattern in agreement, for the most part, with a carbon source and sink distribution map previously derived through ecosystem modelling. However, discrepancies in the spatial pattern and in flux magnitude between these two estimates exist in certain regions. Numerical experiments with a full covariance matrix, with the consideration of the error structure of the a priori flux field based on meteorological variables among the 30 North America regions, resulted in a small but meaningful improvement in the inverted fluxes. Uncertainty reduction analysis suggests that new observation sites are still needed to further improve the inversion for these 30 regions in North America. DOI: 10.1111/j.1600-0889.2006.00235.x

Atmospheric CO 2 measurements show strong synoptic variability. To understand the contribution of the synoptic signals on atmospheric CO 2 inversion, we simulate the cases of biospheric fluxes with and without synoptic variations (referred to as ‘Synoptic’ and ‘Reference’, respectively) using an atmospheric transport model, and then perform inversion analyses with these biospheric CO 2 concentration fields. Results show the monthly and annually averaged CO 2 concentration anomalies (Synoptic–Reference) are functions of the distance from the continental biospheric source regions. Remote sites (like Mauna Loa) show averaged monthly amplitude of ∼0.2 ppm, while continental sites show averaged monthly amplitudes of 1–2 ppm with maximum monthly amplitudes up to 7 ppm. Spatial scales of these monthly mean synoptic anomaly patterns may exceed 1000 km. These CO 2 concentration patterns are the results of the interaction of the synoptic CO 2 flux field and atmospheric transport, and may be referred to as the synoptic Rectifier Effect. Inversion CO 2 fluxes for 1992–1995 are obtained using biospheric background fields with and without synoptic biospheric flux variations. The maximum magnitude differences in estimated monthly flux for land and ocean regions are ∼0.4 and ∼0.2 GtC month −1 , respectively. The average land sink increases by 0.19 GtC yr −1 while the average ocean sink decreases by 0.30 GtC yr −1 . DOI: 10.1111/j.1600-0889.2006.00219.x

From around 1993 to 1997, the NOAA-CU δ 18 O measurements at Pt. Barrow, Mauna Loa, Cape Kumukahi, Cape Grim and the South Pole show a decrease in atmospheric CO 2 δ 18 O of about 0.5‰. Recently,Gillon and Yakir (2001) have attributed this decrease to a conversion of C3 forests to C4 grasslands through anthropogenic land-use change. However, their explanation can account for only about 0.02‰ yr −1 decrease rate. In this paper we offer a viable alternative explanation. We have used a multi-box model of the global carbon cycle and its δ 18 O to show that an increase in biospheric respiration (CO 2 flux from plant with lower-than-atmosphere δ 18 O ), combined with a decrease in the amount of CO 2 (with higher-than-atmosphere δ 18 O ) diffusing back from plant leaves before being assimilated as part of the gross primary production (GPP), could produce the observed decline in the atmospheric CO 2 δ 18 O . This decrease in the CO 2 back diffusion out of leaves could be interpreted as an overall increase in both biospheric activities of photosynthesis and respiration. Change in the metabolic activities of the biosphere as a possible cause for the observed decrease in δ 18 O is a reasonable hypothesis, since isotopic fractionations that occur during CO 2 exchange processes (photosynthesis and respiration) between the atmosphere and the biosphere contribute significantly to the observed variations in atmospheric CO 2 δ 18 O , while contribution from the net air-sea CO 2 exchange is negligible. DOI: 10.1034/j.1600-0889.2002.201312.x

Using discrete air sampling, values of δ 13 C and δ 18 O in atmospheric CO 2 , as well as its concentration, were measured in a forest in the central part of the main island of Japan during the period from June 1994 to June 1996 to examine the biospheric contribution to their temporal variations. δ 13 C shows a prominent diurnal variation with high values in the daytime and low values in the nighttime, especially during the warm season. δ 13 C also vary seasonally, showing a maximum in summer and a minimum in spring. The diurnal and seasonal variations of δ 13 C are opposite in phase with those of the CO 2 concentration. The rate of change in δ 13 C with respect to the CO 2 concentration is found to be approximately -0.05‰/ppmv. This suggests that the diurnal and seasonal variations of the CO 2 concentration are produced primarily by diurnally- and seasonally-dependent photosynthetic-respiratory processes of the biosphere near the observation site, respectively. In the warm season, δ 18 O also increases in the daytime and decreased in the nighttime, which is similar to the diurnal variation of δ 13 C, but opposite to that of the CO 2 concentration. The diurnal δ 18 O variation is thought to be caused by the release of isotopically heavy CO 2 during photosynthesis, and light CO 2 during respiration. However, an interpretation of the seasonal δ 18 O variation is found to be much more difficult than those of δ 13 C and the CO 2 concentration. This is likely due to complicated combinations of different seasonally varying fluxes of biospheric CO 2 into the atmosphere, as well as to various weather-dependent factors governing the δ 18 O composition in CO 2 . DOI: 10.1034/j.1600-0889.49.issue4.3.x

The ongoing development of the Global Carbon Project (GCP) global methane (CH4 ) budget shows a continuation of increasing CH4 emissions and CH4 accumulation in the atmosphere during 2000-2017. Here, we decompose the global budget into 19 regions (18land and 1 oceanic) and five key source sectors to spatially attribute the observed global trends. A comparison of top-down (TD) (atmospheric and transport model-based) and bottom-up (BU) (inventory- and process model-based) CH4 emission estimates demonstrates robust temporal trends with CH4 emissions increasing in 16 of the 19 regions. Five regions-China, Southeast Asia, USA, South Asia, and Brazil-account for >40% of the global total emissions (their anthropogenic and natural sources together totaling >270Tg CH4 yr-1 in 2008-2017). Two of these regions, China and South Asia, emit predominantly anthropogenic emissions (>75%) and together emit more than 25% of global anthropogenic emissions. China and the Middle East show the largest increases in total emission rates over the 2000 to 2017 period with regional emissions increasing by >20%. In contrast, Europe and Korea and Japan show a steady decline in CH4 emission rates, with total emissions decreasing by ~10% between 2000 and 2017. Coal mining, waste (predominantly solid waste disposal) and livestock (especially enteric fermentation) are dominant drivers of observed emissions increases while declines appear driven by a combination of waste and fossil emission reductions. As such, together these sectors present the greatest risks of further increasing the atmospheric CH4 burden and the greatest opportunities for greenhouse gas abatement.