ALBERT

Description: At present, global CO2 emission inventories are mainly based on bottom-up estimates that rely, for example, on reported fossil fuel consumptions and fuel types1,2. The associated uncertainties propagate into the CO2-to-NOx emission ratios that are used in pollution prediction and monitoring3, as well as into biospheric carbon fluxes derived by inverse models4. Here we analyse simultaneous and co-located satellite retrievals from SCIAMACHY (ref. 5; SCanning Imaging Absorption SpectroMeter for Atmospheric CHartographY) of the column-average dry-air mole fraction of CO2 (refs 6,7) and NO2 (refs 8-10) for the years 2003-2011 to provide a top-down estimate of trends in emissions and in the ratio between CO2 and NOx emissions. Our analysis shows that the CO2-to-NOcx emission ratio has increased by 4.2 ± 1.7%yr-1 in East Asia. In this region, we find a large positive trend of CO2 emissions (9.8 ± 1.7%yr-1), which we largely attribute to the growing Chinese economy. This trend exceeds the positive trend of NOx emissions (5.8±0.9%yr-1). Our findings suggest that the recently installed and renewed technology in East Asia, such as power plants, transportation and so on, is cleaner in terms of NOx emissions than the old infrastructure, and roughly matches relative emission levels in North America and Europe. © 2014 Macmillan Publishers Limited. All rights reserved.

Description: Current knowledge about the European terrestrial biospheric carbon sink, from the Atlantic to the Urals, relies upon bottom-up inventory and surface flux inverse model estimates (e.g., 0.27 ± 0.16 Gt C a−1 for 2000–2005 5 (Schulze et al., 2009), 0.17 ± 0.44 Gt C a−1 for 2001–2007 (Peters et al., 2010), 0.45 ± 0.40 Gt C a−1 for 2010 (Chevallier et al., 2014), 0.40 ± 0.42 Gt C a−1 for 2001–2004 (Peylin et al., 2013). Inverse models assimilate in situ CO2 atmospheric concentrations measured by surface-based air sampling networks. The intrinsic sparseness of these networks is one reason for the relatively large flux uncertainties (Peters et al., 2010; Bruhwiler et al., 2011). Satellite-based CO2 measurements have the potential to reduce these uncertainties (Miller et al., 2007; Chevallier et al., 2007). Global inversion experiments using independent models and independent GOSAT satellite data products consistently derived a considerably larger European sink (0.9–1.2 Gt C a−1 for September 2009–August 2010 (Basu et al., 2013), 1.2–1.8 Gt C a−1 in 2010, Chevallier et al., 2014). However, these results have been considered unrealistic due to potential large scale retrieval biases and/or long-range transport errors (Chevallier et al., 2014) or have not been discussed at all (Basu et al., 2013; Takagi et al., 2014). Here we show that the satellite-derived European terrestrial carbon sink is indeed much larger (1.02 ± 0.30 Gt C a−1 in 2010) than previously expected. Our analysis comprises a regional inversion approach using STILT (Gerbig et al., 2003; Lin et al., 2003) short range (days) particle dispersion modelling, rendering it insensitive to large scale retrieval biases and less sensitive to long-range transport errors. The highest gain in information is obtained during the growing season when satellite observation conditions are advantageous and a priori uncertainties are largest. The consistency among an ensemble of five different inversion set-ups and five independent satellite retrievals (BESD (Reuter et al., 2011) 2003–2010, ACOS (O’Dell et al., 2012) 2010, UoL-FP (Cogan et al., 2012) 2010, RemoTeC C (Butz et al., 2011) 2010, and NIES (Yoshida et al., 2013) 2010) using data from two different instruments (SCIAMACHY, Bovensmann et al., 1999 and GOSAT, Kuze et al., 2009) provides evidence that our current understanding of the European carbon sink has to be revisited.

Description: Column-averaged dry-air mole fractions of carbon dioxide and methane have been retrieved from spectra acquired by the TANSO-FTS (Thermal And Near-infrared Sensor for carbon Observations-Fourier Transform Spectrometer) and SCIAMACHY (Scanning Imaging Absorption Spectrometer for Atmospheric Cartography) instruments on board GOSAT (Greenhouse gases Observing SATellite) and ENVISAT (ENVIronmental SATellite), respectively, using a range of European retrieval algorithms. These retrievals have been compared with data from ground-based high-resolution Fourier transform spectrometers (FTSs) from the Total Carbon Column Observing Network (TCCON). The participating algorithms are the weighting function modified differential optical absorption spectroscopy (DOAS) algorithm (WFMD, University of Bremen), the Bremen optimal estimation DOAS algorithm (BESD, University of Bremen), the iterative maximum a posteriori DOAS (IMAP, Jet Propulsion Laboratory (JPL) and Netherlands Institute for Space Research algorithm (SRON)), the proxy and full-physics versions of SRON's RemoTeC algorithm (SRPR and SRFP, respectively) and the proxy and full-physics versions of the University of Leicester's adaptation of the OCO (Orbiting Carbon Observatory) algorithm (OCPR and OCFP, respectively). The goal of this algorithm inter-comparison was to identify strengths and weaknesses of the various so-called round- robin data sets generated with the various algorithms so as to determine which of the competing algorithms would proceed to the next round of the European Space Agency's (ESA) Greenhouse Gas Climate Change Initiative (GHG-CCI) project, which is the generation of the so-called Climate Research Data Package (CRDP), which is the first version of the Essential Climate Variable (ECV) "greenhouse gases" (GHGs). For XCO2, all algorithms reach the precision requirements for inverse modelling (〈 8 ppm), with only WFMD having a lower precision (4.7 ppm) than the other algorithm products (2.4–2.5 ppm). When looking at the seasonal relative accuracy (SRA, variability of the bias in space and time), none of the algorithms have reached the demanding 〈 0.5 ppm threshold. For XCH4, the precision for both SCIAMACHY products (50.2 ppb for IMAP and 76.4 ppb for WFMD) fails to meet the 〈 34 ppb threshold for inverse modelling, but note that this work focusses on the period after the 2005 SCIAMACHY detector degradation. The GOSAT XCH4 precision ranges between 18.1 and 14.0 ppb. Looking at the SRA, all GOSAT algorithm products reach the 〈 10 ppm threshold (values ranging between 5.4 and 6.2 ppb). For SCIAMACHY, IMAP and WFMD have a SRA of 17.2 and 10.5 ppb, respectively.

Description: The terrestrial biosphere is currently acting as a net carbon sink on the global scale, exhibiting significant interannual variability in strength. To reliably predict the future strength of the land sink and its role in atmospheric CO2 growth, the underlying biogeochemical processes and their response to a changing climate need to be well understood. In particular, better knowledge of the impact of key climate variables such as temperature or precipitation on the biospheric carbon reservoir is essential. It is demonstrated using nearly a decade of SCIAMACHY (SCanning Imaging Absorption spectroMeter for Atmospheric CHartographY) nadir measurements that years with higher temperatures during the growing season can be robustly associated with larger growth rates in atmospheric CO2 and smaller seasonal cycle amplitudes for northern mid-latitudes. We find linear relationships between warming and CO2 growth as well as seasonal cycle amplitude at the 98% significance level. This suggests that the terrestrial carbon sink is less efficient at higher temperatures during the analysed time period. Unless the biosphere has the ability to adapt its carbon storage under warming conditions in the longer term, such a temperature response entails the risk of potential future sink saturation via a positive carbon-climate feedback. Quantitatively, the covariation between the annual CO2 growth rates derived from SCIAMACHY data and warm season surface temperature anomaly amounts to 1.25 ± 0.32 ppm yr−1 K−1 for the Northern Hemisphere, where the bulk of the terrestrial carbon sink is located. In comparison, this relationship is less pronounced in the Southern Hemisphere. The covariation of the seasonal cycle amplitudes retrieved from satellite measurements and temperature anomaly is −1.30 ± 0.31 ppm K−1 for the north temperate zone. These estimates are consistent with those from the CarbonTracker data assimilated CO2 data product, indicating that the temperature dependence of the model surface fluxes is realistic.

Description: Current knowledge about the European terrestrial biospheric carbon sink, from the Atlantic to the Urals, relies upon bottom-up inventory and surface flux inverse model estimates (e.g. 0.27±0.16 GtC a−1 for 2000–2005 (Schulze et al., 2009), 0.17±0.44 GtC a−1 for 2001–2007 (Peters et al., 2010), 0.45±0.40 GtC a−1 for 2010 (Chevallier et al., 2014), 0.40±0.42 GtC a−1 for 2001–2004 (Peylin et al., 2013)). Inverse models assimilate in situ CO2 atmospheric concentrations measured by surface-based air sampling networks. The intrinsic sparseness of these networks is one reason for the relatively large flux uncertainties (Peters et al., 2010; Bruhwiler et al., 2011). Satellite-based CO2 measurements have the potential to reduce these uncertainties (Miller et al., 2007; Chevallier et al., 2007). Global inversion experiments using independent models and independent GOSAT satellite data products consistently derived a considerably larger European sink (1.0–1.3 GtC a−1 for 09/2009–08/2010 (Basu et al., 2013), 1.2–1.8 GtC a−1 in 2010 (Chevallier et al., 2014)). However, these results have been considered unrealistic due to potential retrieval biases and/or transport errors (Chevallier et al., 2014) or have not been discussed at all (Basu et al., 2013; Takagi et al., 2014). Our analysis comprises a regional inversion approach using STILT (Gerbig et al., 2003; Lin et al., 2003) short-range (days) particle dispersion modelling, rendering it insensitive to large-scale retrieval biases and less sensitive to long-range transport errors. We show that the satellite-derived European terrestrial carbon sink is indeed much larger (1.02±0.30 GtC a−1 in 2010) than previously expected. This is qualitatively consistent among an ensemble of five different inversion set-ups and five independent satellite retrievals (BESD (Reuter et al., 2011) 2003–2010, ACOS (O’Dell et al., 2012) 2010, UoL-FP (Cogan et al., 2012) 2010, RemoTeC (Butz et al., 2011) 2010, and NIES (Yoshida et al., 2013) 2010) using data from two different instruments (SCIAMACHY (Bovensmann et al., 1999) and GOSAT (Kuze et al., 2009)). The difference to in situ based inversions (Peylin et al., 2013), whilst large with respect to the mean reported European carbon sink (0.4 GtC a−1 for 2001–2004), is similar in magnitude to the reported uncertainty (0.42 GtC a−1). The highest gain in information is obtained during the growing season when satellite observation conditions are advantageous, a priori uncertainties are largest, and the surface sink maximises; during the dormant season, the results are dominated by the a priori. Our results provide evidence that the current understanding of the European carbon sink has to be revisited.