The Use of Satellite-Measured Aerosol Optical Depth to Constrain Biomass Burning Emissions Source Strength in a Global Model GOCART

Small particles in the atmosphere, called "atmospheric aerosol" have a direct effect on Earth climate through scattering and absorbing sunlight, and also an indirect effect by changing the properties of clouds, as they interact with solar radiation as well. Aerosol typically stays in the atmosphere for several days, and can be transported long distances, affecting air quality, visibility, and human health not only near the source, but also far downwind. Smoke from vegetation fires is one of the main sources of atmospheric aerosol; other sources include anthropogenic pollution, dust, and sea salt. Chemistry transport models (CTMs) are among the major tools for studying the atmospheric and climate effects of aerosol. Due to the considerable variation of aerosol concentrations and properties on many temporal and spatial scales, and the complexity of the processes involved, the uncertainties in aerosol effects on climate are large, as is featured in the latest report of Intergovernmental Panel on Climate Change (IPCC) in 2007. Reducing this uncertainty in the models is very important both for predicting future climate scenarios and for regional air quality forecasting and mitigation. During vegetation fires, also called biomass burning (BB) events, complex mixture of gases and particles is emitted. The amount of BB emissions is usually estimated taking into account the intensity and size of the fire and the properties of burning vegetation. These estimates are input into CTMs to simulate BB aerosol. Unfortunately, due to large variability of fire and vegetation properties, the quantity of BB emissions is very difficult to estimate and BB emission inventories provide numbers that can differ by up to the order of magnitude in some regions. Larger uncertainties in data input make uncertainties in model output larger as well. A powerful way to narrow the range of possible model estimates is to compare model output to observations. We use satellite observations of aerosol properties, specifically aerosol optical depth, which is directly proportional to the amount of aerosol in the atmosphere, and compare it to the model output. Assuming the model represents aerosol transport and particle properties correctly, the amount of BB emissions determines the simulated aerosol optical depth. In this study, we explore the regional performance of 13 commonly used emission estimates. These are each input to global Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. We then evaluate how well each emission estimate reproduces the smoke aerosol optical depth measured by the MODIS instrument. We compared GOCART-simulate aerosol optical depth with that measured from the satellite for 124 fire cases around the world during 2006 and 2007. We summarize the regional performance of each emission inventory and discuss reasons for their differences by considering the assumptions made during their development. We also show that because stronger wind disperses smoke plumes more readily, in cases with stronger wind, a larger increase in emission amount is needed to increase aerosol optical depth. In quiet, low-wind-speed environments, BB emissions produce a more significant increase in aerosol optical depth, other things being equal. Using the region-specific, quantitative relationships derived in our paper, together with the wind speed obtained from another source for a given fire case, we can constrain the amount of emission required in the model to reproduce the observations. The results of this paper are useful to the developers of BB emission inventories, as they show the strengths and weaknesses of individual emission inventories in different regions of the globe, and also for modelers who use these inventories and wish to improve their model results

Perspectives for biocatalytic lignin utilization: cleaving 4-O-5 and C??-C?? bonds in dimeric lignin model compounds catalyzed by a promiscuous activity of tyrosinase

Background: In the biorefinery utilizing lignocellulosic biomasses, lignin decomposition to value-added phenolic derivatives is a key issue, and recently biocatalytic delignification is emerging owing to its superior selectivity, low energy consumption, and unparalleled sustainability. However, besides heme-containing peroxidases and laccases, information about lignolytic biocatalysts is still limited till date. Results: Herein, we report a promiscuous activity of tyrosinase which is closely associated with delignification requiring high redox potentials (>1.4 V vs. normal hydrogen electrode [NHE]). The promiscuous activity of tyrosinase not only oxidizes veratryl alcohol, a commonly used nonphenolic substrate for assaying ligninolytic activity, to veratraldehyde but also cleaves the 4-O-5 and C??-C?? bonds in 4-phenoxyphenol and guaiacyl glycerol-??-guaiacyl ether (GGE) that are dimeric lignin model compounds. Cyclic voltammograms additionally verified that the promiscuous activity oxidizes lignin-related high redox potential substrates. Conclusion These results might be applicable for extending the versatility of tyrosinase toward biocatalytic delignification as well as suggesting a new perspective for sustainable lignin utilization. Furthermore, the results provide insight for exploring the previously unknown promiscuous activities of biocatalysts much more diverse than ever thought before, thereby innovatively expanding the applicable area of biocatalysis

Influence of anthropogenic aerosol on cloud optical depth and albedo shown by satellite measurements and chemical transport modeling

The Twomey effect of enhanced cloud droplet concentration, optical depth, and albedo caused by anthropogenic aerosols is thought to contribute substantially to radiative forcing of climate change over the industrial period. However, present model-based estimates of this indirect forcing are highly uncertain. Satellite-based measurements would provide global or near-global coverage of this effect, but previous efforts to identify and quantify enhancement of cloud albedo caused by anthropogenic aerosols in satellite observations have been limited, largely because of strong dependence of albedo on cloud liquid water path (LWP), which is inherently highly variable. Here we examine satellite-derived cloud radiative properties over two 1-week episodes for which a chemical transport and transformation model indicates substantial influx of sulfate aerosol from industrial regions of Europe or North America to remote areas of the North Atlantic. Despite absence of discernible dependence of optical depth or albedo on modeled sulfate loading, examination of the dependence of these quantities on LWP readily permits detection and quantification of increases correlated with sulfate loading, which are otherwise masked by variability of LWP, demonstrating brightening of clouds because of the Twomey effect on a synoptic scale. Median cloud-top spherical albedo was enhanced over these episodes, relative to the unperturbed base case for the same LWP distribution, by 0.02 to 0.15

The performance of a global and mesoscale model over the central Arctic Ocean during late summer

Measurements of turbulent fluxes, clouds, radiation, and profiles of mean meteorological parameters, obtained over an ice floe in the central Arctic Ocean during the Arctic Ocean Experiment 2001, are used to evaluate the performance of U.K. Met Office Unified Model (MetUM) and Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS) in the lower atmosphere during late summer. Both the latest version of the MetUM and the version operational in 2001 are used in the comparison to gain an insight as to whether updates to the model have improved its performance over the Arctic region. As with previous model evaluations over the Arctic, the pressure, humidity, and wind fields are satisfactorily represented in all three models. The older version of the MetUM underpredicts the occurrence of low-level Arctic clouds, and the liquid and ice cloud water partitioning is inaccurate compared to observations made during SHEBA. In the newer version, simulated ice and liquid water paths are improved, but the occurrence of low-level clouds are overpredicted. Both versions overestimate the amount of radiative heat absorbed at the surface, leading to a significant feedback of errors involving the surface albedo, which causes a large positive bias the surface temperature. Cloud forcing in COAMPS produces similar biases in the downwelling shortwave and longwave radiation fluxes to those produced by UM(G25). The surface albedo parameterization is, however, more realistic, and thus, the total heat flux and surface temperature are more accurate for the majority of the observation period