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Many global environmental agendas, including halting biodiversity loss, reversing land degradation, and limiting climate change, depend upon retaining forests with high ecological integrity, yet the scale and degree of forest modification remains poorly quantified and mapped. By integrating data on direct and indirect forest pressures and lost forest connectivity, we generate the first globally-consistent, continuous index of forest condition as determined by degree of anthropogenic modification, which we term ‘forest health’. Globally, only 17.4 million km 2 of forest (40.5%) can be considered in high health (mostly found in Canada, Russia, the Amazon, Central Africa and New Guinea) and only 27% of this area is found in nationally-designated protected areas. Of all the world’s forests found within protected areas, only 56% can be considered in high health. Ambitious policies that prioritize the retention of forest health are now urgently needed alongside current efforts aimed at restoring the health of forests globally.

International audience; The University of Toronto Atmospheric Observatory and Environment Canada's Centre for Atmospheric Research Experiments each has over a decade of ground-based Fourier transform infrared (FTIR) spectroscopy measurements in southern Ontario. We present the Toronto area FTIR time series from 2002 to 2013 of two tropospheric trace gases—ozone and carbon monoxide—along with surface in situ measurements taken by government monitoring programs. We interpret their variability with the GEOS-Chem chemical transport model and determine the atmospheric conditions that cause pollution events in the time series. Our analysis includes a regionally tagged O3 model of the 2004–2007 time period, which quantifies the geographical contributions to Toronto area O3. The important emission types for 15 pollution events are then determined with a high-resolution adjoint model. Toronto O3, during pollution events, is most sensitive to southern Ontario and U.S. fossil fuel NOx emissions and natural isoprene emissions. The sources of Toronto pollution events are found to be highly variable, and this is demonstrated in four case studies representing local, short-, middle-, and long-range transport scenarios. This suggests that continental-scale emission reductions could improve air quality in the Toronto region. We also find that abnormally high temperatures and high-pressure systems are common to all pollution events studied, suggesting that climate change may impact Toronto O3. Finally, we quantitatively compare the sensitivity of the surface and column measurements to anthropogenic NOx emissions and show that they are remarkably similar. This work thus demonstrates the usefulness of FTIR measurements in an urban area to assess air quality.

National audience

The 2006 Canadian Arctic ACE (Atmospheric Chemistry Experiment) Validation Campaign collected measurements at the Polar Environment Atmospheric Research Laboratory (PEARL, 80.05° N, 86.42° W, 610 m above sea level) at Eureka, Canada from 17 February to 31 March 2006. Two of the ten instruments involved in the campaign, both Fourier transform spectrometers (FTSs), were operated simultaneously, recording atmospheric solar absorption spectra. The first instrument was an ABB Bomem DA8 high-resolution infrared FTS. The second instrument was the Portable Atmospheric Research Interferometric Spectrometer for the Infrared (PARIS-IR), the ground-based version of the satellite-borne FTS on the ACE satellite (ACE-FTS). From the measurements collected by these two ground-based instruments, total column densities of seven stratospheric trace gases (O3, HNO3, NO2, HCl, HF, NO, and ClONO2 were retrieved using the optimal estimation method and these results were compared. Since the two instruments sampled the same portions of atmosphere by synchronizing observations during the campaign, the biases in retrieved columns from the two spectrometers represent the instrumental differences. These differences were consistent with those seen in previous FTS intercomparison studies. Partial column results from the ground-based spectrometers were also compared with partial columns derived from ACE-FTS version 2.2 (including updates for O3, HDO and N2O5 profiles and the differences found were consistent with the other validation comparison studies for the ACE-FTS version 2.2 data products. Column densities of O3, HCl, ClONO2, and HNO3 from the three FTSs were normalized with respect to HF and used to probe the time evolution of the chemical constituents in the atmosphere over Eureka during spring 2006.

For the first time, vertical column measurements of (HNO3) above the Arctic Stratospheric Ozone Observatory (AStrO) at Eureka (80N, 86W), Canada, have been made during polar night using lunar spectra recorded with a Fourier Transform Infrared (FTIR) spectrometer, from October 2001 to March 2002. AStrO is part of the primary Arctic station of the Network for the Detection of Stratospheric Change (NDSC). These measurements were compared with FTIR measurements at two other NDSC Arctic sites: Thule, Greenland (76.5N, 68.8W) and Kiruna, Sweden (67.8N, 20.4E). The measurements were also compared with two atmospheric models: the Canadian\ud Middle Atmosphere Model (CMAM) and SLIMCAT. This is the first time that CMAM HNO3 columns have been compared with observations in the Arctic. Eureka lunar measurements are in good agreement with solar ones made with the same instrument. Eureka and Thule HNO3 columns are consistent within measurement error. Differences among HNO3 columns measured at Kiruna and those measured at Eureka and Thule can be explained on the basis of the available sunlight hours and the polar vortex location. The comparison of CMAM HNO3 columns with Eureka and Kiruna data shows good agreement, considering CMAM small inter-annual variability. The warm 2001/02 winter with almost no Polar Stratospheric Clouds (PSCs) makes the comparison of the warm climate version of CMAM with these observations a good test for CMAM under no PSC conditions. SLIMCAT captures the magnitude of HNO3 columns at Eureka, and the day-to-day variability, but generally reports higher HNO3 columns than the CMAM climatological mean columns.

Atmospheric CO2 concentrations, retrieved from spectral measurements made in the near infrared (NIR) by the SCIAMACHY instrument, using Full Spectral Initiation Weighting Function Modified Differential Optical Absorption Spectroscopy (FSI WFM-DOAS), are compared to ground based Fourier Transform Infrared (FTIR) data and to the output from a global chemistry-transport model. Analysis of the FSI WFM-DOAS retrievals with respect to the ground based FTIR instrument, located at Egbert, Canada, show good agreement with an average negative bias of approximately -4.0% with a standard deviation of similar to 3.0%. This bias which exhibits an apparent seasonal trend, is of unknown origin, though slight differences between the averaging kernels of the instruments and the limited temporal coverage of the FTIR data may be the cause. The relative scatter of the retrieved vertical column densities is larger than the spread of the FTIR measurements. Normalizing the CO2 columns using the surface pressure does not affect the magnitude of this bias although it slightly decreases the scatter of the FSI data. Comparisons of the FSI retrievals to the TM3 global chemistry-transport model, performed over four selected Northern Hemisphere scenes show reasonable agreement. The correlation, between the time series of the SCIAMACHY and model monthly scene averages, are similar to 0.7 or greater, demonstrating the ability of SCIAMACHY to detect seasonal changes in the CO2 distribution. The amplitude of the seasonal cycle, peak to peak, observed by SCIAMACHY however, is larger by a factor of 2-3 with respect to the model, which cannot be explained. The yearly means detected by SCIAMACHY are within 2% of those of the model with the mean difference between the CO2 distributions also approximately 2.0%. Additionally, analysis of the retrieved CO2 distributions reveals structure not evident in the model fields which correlates well with land classification type. From these comparisons, it is estimated that the overall bias of the CO2 columns retrieved by the FSI algorithm is < 4.0% with the precision of monthly 1 degrees x1 degrees gridded data close to 1.0%. [References: 41]

International audience; Total column amounts of CO, CH4, CO2 and N2O retrieved from SCIAMACHY nadir observations in its near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.5 for CO and CH4 and version 0.4 for CO2 and N2O), IMAP-DOAS (version 1.1 and 0.9 (for CO)) and IMLM (version 6.3) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The present results indicate that the individual SCIAMACHY data obtained with the actual versions of the algorithms have been significantly improved, but that the quality requirements, for estimating emissions on regional scales, are not yet met. Nevertheless, possible directions for further algorithm upgrades have been identified which should result in more reliable data products in a near future.

International audience; Total column amounts of CO, CH4, CO2 and N2O retrieved from SCIAMACHY nadir observations in its near-infrared channels have been compared to data from a ground-based quasi-global network of Fourier-transform infrared (FTIR) spectrometers. The SCIAMACHY data considered here have been produced by three different retrieval algorithms, WFM-DOAS (version 0.4, 0.41 for CH4), IMAP-DOAS (version 0.9) and IMLM (version 5.5) and cover the January to December 2003 time period. Comparisons have been made for individual data, as well as for monthly averages. To maximize the number of reliable coincidences that satisfy the temporal and spatial collocation criteria, the SCIAMACHY data have been compared with a temporal 3rd order polynomial interpolation of the ground-based data. Particular attention has been given to the question whether SCIAMACHY observes correctly the seasonal and latitudinal variability of the target species. The ensemble of comparisons, discussed in this paper, demonstrate the capability of SCIAMACHY, using any of the three algorithms, to deliver products for the target species under consideration, which are already useful for qualitative geophysical studies on a global scale. It is expected that the remaining uncertainties in the data products will decrease in future versions of the algorithm to also allow more quantitative investigations on a regional scale.