Low growth rates of atmospheric CO₂ were observed following the 1991 Pinatubo (Luzon) volcanic eruption. One hypothesis for this CO₂ anomaly is that since diffuse light is more efficiently used by forests than direct light, the increase in the diffuse fraction of sunlight due to scattering by volcanic sulfur aerosol in the years following the eruption substantially increased forest net primary production (NPP). However, other observations suggest a decrease in northern forest NPP because of the cooler conditions following the eruption. Here we used a global database of dated tree ring widths (which correlate with forest NPP) to test this hypothesis. Ice core records of sulfur deposition allowed us to identify the timing and magnitude of 23 Pinatubo-scale eruptions since 1000 CE. We found a significant decrease in ring width for trees in middle to high northern latitudes (north of 45°N) following eruption sulfur peaks. Decreases in tree ring widths were in the range of 2–8% and persisted for ∼8 years following sulfur peaks, with minima at around 4–6 years. Ring width changes at lower latitudes in the Northern Hemisphere (30°N to 45°N) and in the Southern Hemisphere (30°S to 56°S) were not significant. In the tropics (30°N to 30°S) the paucity of tree ring records did not permit the evaluation of NPP changes. Given that elevated aerosol levels and summer cooling last only ∼2–3 years after an eruption, the persistence of declines in northern tree growth for up to 8 years after eruptions implies some additional mechanism that links these shorter-lived global eruption effects to sustained changes in tree physiology, biogeochemistry, or microclimate. At least for this sample of trees, the beneficial effect of aerosol light scattering appears to be entirely offset by the deleterious effect of eruption-induced climate change.

Recent inverse analyses constraining carbon fluxes using atmospheric CO₂ observations have assumed that the CO₂ source from atmospheric oxidation of reduced carbon is released at the surface rather than distributed globally in the atmosphere. This produces a bias in the estimates of surface fluxes. We used a three-dimensional (3D) atmospheric chemistry model (GEOS-CHEM) to evaluate the magnitude of this effect on modeled concentrations and flux estimates. We find that resolving the 3D structure of the atmospheric CO₂ source, as opposed to emitting this reduced carbon as CO₂ at the surface, yields a decrease in the modeled annual mean interhemispheric gradient (N-S) of 0.21 ppm. Larger adjustments (up to −0.6 ppm) are apparent on a regional basis in and downwind of regions of high reduced carbon emissions. We used TransCom3 annual mean simulations from three transport models to evaluate the implications for inversion estimates. The main impacts are systematic decreases in estimates of northern continental land uptake (i.e., by 0.22 to 0.26 Pg C yr⁻¹), and reductions in tropical land carbon efflux with smaller changes over oceans and in the Southern Hemisphere. These adjustments represent a systematic bias in flux estimates, accounting for changes of 9 to 27% in the estimated northern land CO₂ sink for the three models evaluated here. Our results highlight the need for a realistic description of reduced carbon emission and oxidation processes in deriving inversion estimates of CO₂ surface fluxes.

Estimating CO₂ fluxes from the pattern of atmospheric CO₂ concentrations with atmospheric transport models is an ill-posed inverse problem, whose solution is stabilized using prior information. Weights assigned to prior information and to CO₂ concentrations at different locations are quantified by parameters that are not well known, and differences in the choice of these parameters contribute to differences among published estimates of the regional partitioning of CO₂ fluxes. Following the TransCom 3 protocol to estimate CO₂ fluxes for 1992–1996, we find that the partitioning of the CO₂ sink between land and oceans and between North America and Eurasia depends on parameters that quantify the relative weight given to prior flux estimates and the extent to which CO₂ concentrations at different stations are differentially weighted. Parameter values that minimize an estimated prediction error can be chosen by generalized cross-validation (GCV). The GCV parameter values yield fluxes in northern regions similar to those obtained with the TransCom parameter values, but the GCV fluxes are smaller in the poorly constrained equatorial and southern regions.

Radiocarbon levels in annual plants provide a means to map out regional and continental-scale fossil fuel plumes in surface air. We collected corn (Zea mays) across North America during the summer of 2004. Plants from mountain regions of western North America showed the smallest influence of fossil fuel-derived CO₂ with a mean Δ¹⁴C of 66.3‰ ±1.7‰. Plants from eastern North America and from the Ohio-Maryland region showed a larger fossil fuel influence with a mean Δ¹⁴C of 58.8‰ ± 3.9‰ and 55.2‰ ± 2.3‰, respectively, corresponding to 2.7 ppm ± 1.5 ppm and 4.3 ppm ± 1.0 ppm of added fossil fuel CO₂ relative to the mountain west. A model–data comparison suggests that surveys of annual plant Δ¹⁴C can provide a useful test of atmospheric mixing in transport models that are used to estimate the spatial distribution of carbon sources and sinks.

Radiocarbon levels in annual plants provide a means to map out regional and continental-scale fossil fuel plumes in surface air. We collected corn (Zea mays) across North America during the summer of 2004. Plants from mountain regions of western North America showed the smallest influence of fossil fuel-derived CO₂ with a mean Δ¹⁴C of 66.3‰ ±1.7‰. Plants from eastern North America and from the Ohio-Maryland region showed a larger fossil fuel influence with a mean Δ¹⁴C of 58.8‰ ± 3.9‰ and 55.2‰ ± 2.3‰, respectively, corresponding to 2.7 ppm ± 1.5 ppm and 4.3 ppm ± 1.0 ppm of added fossil fuel CO₂ relative to the mountain west. A model–data comparison suggests that surveys of annual plant Δ¹⁴C can provide a useful test of atmospheric mixing in transport models that are used to estimate the spatial distribution of carbon sources and sinks.