ALBERT

Description: The Mass Absorption Cross section (MAC) and Absorption Ångström Exponent (AAE) have been commonly estimated for ambient aerosols but rarely for black carbon (BC) or organic aerosol (OA) alone in the ambient conditions. Here, we provide estimates of BC (and OA) MAC and AAE in East Asian outflow, by analyzing field data collected at the Gosan ABC super site. At this site, EC (and OC) carbon mass, the aerosol absorption coefficient at 7 wavelengths and PM mass density were continuously measured from October 2009 to June 2010. We remove the absorption data with significant dust influence using the mass ratio of PM10 to PM2.5. The remaining data shows an AAE of about 1.27, which we suggest represent the average carbonaceous aerosol (CA) AAE at Gosan. We find a positive correlation between the mass ratio of OC to EC and CA AAE, and successfully increase the correlation by filtering out data associated with weak absorption signal. After the filtering, absorption coefficient is regressed on OC and EC mass densities. BC and OA MACs are found to be 5.1 (3.8–6.1) and 1.4 (0.8–2.0) m2 g−1 at 520 nm respectively. From the estimated BC and OA MAC, we find that OA contributes about 45% to CA absorption at 520 nm. BC AAE is found to be 0.7–1.0, and is probably even lower considering the instrument bias. OA AAE is found to be 1.6–1.8. Compared with a previous estimate of OA MAC and AAE near biomass burning, our estimates at Gosan strongly suggest that the strongly-absorbing so-called brown carbon spheres are either unrelated to biomass burning or absent near the emission source.

Description: Evaluating surface fluxes of CH4 using total column data requires models to accurately account for the transport and chemistry of methane in the free-troposphere and stratosphere, thus reducing sensitivity to the underlying fluxes. Vertical profiles of methane have increased sensitivity to surface fluxes because lower tropospheric methane is more sensitive to surface fluxes than a total column. Resolving the free troposphere from the lower-troposphere also helps to evaluate the impact of transport and chemistry uncertainties on estimated surface fluxes. Here we demonstrate the potential for estimating lower tropospheric CH4 concentrations through the combination of free-tropospheric methane measurements from the Aura Tropospheric Emission Spectrometer (TES) and XCH4 (dry-mole air fraction of methane) from the Greenhouse Gases Observing Satellite Thermal And Near Infrared for Carbon Observations (GOSAT TANSO, herein GOSAT for brevity). The mean precision of these estimates are calculated to be ~ 23 ppb for a monthly average on a 4 × 5 latitude/longitude degree grid making these data suitable for evaluating lower-tropospheric methane concentrations. Smoothing error is approximately 10 ppb or less. The accuracy is primarily determined by knowledge error of XCO2, used to estimate XCH4 from the GOSAT CH4/CO2 "proxy" retrieval. For example, we use different XCO2 fields to quantify XCH4 from the GOSAT CH4/CO2 retrieval, one from Carbontracker and another from the NASA Carbon Monitoring System, and find that differences of up to approximately 60 ppb are possible with a mean value of approximately 35 ppb or less for any given latitude for these lower-tropospheric methane estimates using these two different XCO2 distributions. We show that these lower-tropospheric concentrations are more directly sensitive to the underlying fluxes than a total column using the GEOS-Chem model. In particular, we compare these lower-tropospheric methane estimates with those from the GEOS-Chem model for July 2009 to determine if these data can capture methane enhancements associated with the high-latitude methane fluxes because both TES and GOSAT separately do not show much sensitivity to methane from these sources. We find that the spatial patterns and magnitude of lower tropospheric methane concentrations from GEOS-Chem over Northern European and Siberian wetland fluxes are consistent with these data but modeled concentrations are much larger than measured over Canadian wetland fluxes. Transport of methane significantly affects lower-tropospheric methane concentrations over S.E. Asia as both data and model show methane enhancements that are shifted away from their sources. A possible new finding is that there is no representation of a strong source between the Black and Caspian seas.

Description: PM1.0, PM2.5, and PM10 were sampled at Gosan ABC Superstation on Jeju Island from August 2007 to September 2008. The carbonaceous aerosols were quantified with the thermal/optical reflectance (TOR) method, which produced five organic carbon (OC) fractions, OC1, OC2, OC3, OC4, and pyrolyzed organic carbon (OP), and three elemental carbon (EC) fractions, EC1, EC2, and EC3. The mean mass concentrations of PM1.0, PM2.5, and PM10 were 13.7 μg m−3, 17.2 μg m−3, and 28.4 μg m−3, respectively. The averaged mass fractions of OC and EC were 23.0% and 10.4% for PM1.0, 22.9% and 9.8% for PM2.5, and 16.4% and 6.0% for PM10. Among the OC and EC sub-components, OC2 and EC2+3 were enriched in the fine mode, but OC3 and OC4 in the coarse mode. The filter-based PM1.0 EC agreed well with black carbon (BC) measured by an Aethalometer, and PM10 EC was higher than BC, implying less light absorption by larger particles. EC was well correlated with sulfate, resulting in good relationships of sulfate with both aerosol scattering coefficient measured by Nephelometer and BC concentration. Our measurements of EC confirmed the definition of EC1 as char-EC emitted from smoldering combustion and EC2+3 as soot-EC generated from higher-temperature combustion such as motor vehicle exhaust and coal combustion (Han et al., 2010). In particular, EC1 was strongly correlated with potassium, a traditional biomass burning indicator, except during the summer, when the ratio of EC1 to EC2+3 was the lowest. We also found the ratios of major chemical species to be a useful tool to constrain the main sources of aerosols, by which the five air masses were well distinguished: Siberia, Beijing, Shanghai, Yellow Sea, and East Sea types. Except Siberian air, the continental background of the study region, Beijing plumes showed the highest EC1 (and OP) to sulfate ratio, which implies that this air mass had the highest net warming by aerosols of the four air masses. Shanghai-type air, which was heavily influenced by southern China, showed the highest sulfate enhancement. The highest EC2+3/EC1 ratio was found in aged East Sea air, demonstrating a significant influence of motor vehicle emissions from South Korea and Japan and less influence from industrial regions of China. The high ratio results from the longer residence time and less sensitivity to wet scavenging of EC2+3 compared to EC1, indicating that soot-EC could have greater consequence in regional-scale warming.

Description: Tropical fires represent a highly uncertain source of atmospheric methane (CH4) because of the variability of fire emissions and the dependency of the fire CH4 emission factors (g kg−1 dry matter burned) on fuel type and combustion phase. In this paper we use new observations of CH4 and CO in the free troposphere from the Aura Tropospheric Emission Sounder (TES) satellite instrument to place constraints on the role of tropical fire emissions versus microbial production (e.g. in wetlands and livestock) during the (October) 2006 El Niño, a time of significant fire emissions from Indonesia. We first compare the global CH4 distributions from TES using the GEOS-Chem model. We find a mean bias between the observations and model of 26.3 ppb CH4 that is independent of latitude between 50° S and 80° N, consistent with previous validation studies of TES CH4 retrievals using aircraft measurements. The slope of the distribution of CH4 versus CO as observed by TES and modeled by GEOS-Chem is consistent (within the TES observation error) for air parcels over the Indonesian peat fires, South America, and Africa. The CH4 and CO distributions are correlated between R = 0.42 and R = 0.46, with these correlations primarily limited by the TES random error. Over Indonesia, the observed slope of 0.13 (ppb ppb−1) ±0.01, as compared to a modeled slope of 0.153 (ppb ppb−1) ±0.005 and an emission ratio used within the GEOS-Chem model of approximately 0.11 (ppb ppb−1), indicates that most of the observed methane enhancement originated from the fire. Slopes of 0.47 (ppb ppb−1) ±0.04 and 0.44 (ppb ppb−1) ±0.03 over South America and Africa show that the methane in the observed air parcels primarily came from microbial-generated emissions. Sensitivity studies using GEOS-Chem show that part of the observed correlation for the Indonesian observations and most of the observed correlations over South America and Africa are a result of transport and mixing of the fire and nearby microbial-generated emissions into the observed air parcels. Differences between observed and modeled CH4 distributions over South America and southern Africa indicate that the magnitude of the methane emissions for this time period are inconsistent with observations even if the relative distribution of fire versus biotic emissions are consistent. This study shows the potential for estimation of CH4 emissions over tropical regions using joint satellite observations of CH4 and CO.

Description: Previous controversial studies on the hygroscopic behavior of NaNO3 aerosols and our frequent observation of crystalline NaNO3-containing ambient aerosol particles prompted this extensive hygroscopic study on NaNO3 aerosol particles. In this work, the hygroscopic behavior of individual NaNO3 particles of 2.5–4.0 μm in diameter is investigated on a single-particle basis using an optical microscopy technique. Quite different hygroscopic behaviors between particles generated by the nebulization of NaNO3 solution and powdery particles were observed; i.e., most of generated particles continuously grew and shrank during humidifying and dehydration processes, respectively, and yet all the individual powdery particles had reproducible deliquescence and efflorescence relative humidities (DRHs and ERHs). The different behaviors of the two NaNO3 systems are due to the different nucleation mechanisms. Our hygroscopic studies of NaNO3 particles generated from aqueous NaNO3 solutions indicate that they nucleate via homogeneous nucleation, but the time scale for the nucleation to occur is too long to be atmospherically relevant. And thus no efflorescence of the particles has been observed in the laboratory measurements. However, when chemical species acting as heterogeneous nuclei are present, then efflorescence occurs which can explain the observation of ambient crystalline NaNO3 particles. It is imperative to work with heterogeneous nucleation systems which are more relevant to the real world.

Description: PM1.0, PM2.5, and PM10 were sampled at Gosan ABC Superstation on Jeju Island from August 2007 to September 2008. The carbonaceous aerosols were quantified with the thermal/optical reflectance (TOR) method, which produced five organic carbon (OC) fractions, OC1, OC2, OC3, OC4, and pyrolyzed organic carbon (OP), and three elemental carbon (EC) fractions, EC1, EC2, and EC3. The mean mass concentrations of PM1.0, PM2.5, and PM10 were 13.72 μg m−3, 17.24 μg m−3, and 28.37 μg m−3, respectively. The averaged mass fractions of OC and EC were 23.0 % and 10.4 % for PM1.0, 22.9 % and 9.8 % for PM2.5, and 16.4 % and 6.0 % for PM10. Among the OC and EC sub-components, OC2 and EC2+3 were enriched in the fine mode, but OC3 and OC4 in the coarse mode. The filter-based PM1.0 EC agreed well with black carbon (BC) measured by an Aethalometer, and PM10 EC was higher than BC, implying less light absorption by larger particles. EC was well correlated with sulfate, resulting in good relationships of sulfate with both aerosol scattering coefficient measured by Nephelometer and BC concentration. Our measurements of EC confirmed the definition of EC1 as char-EC emitted from smoldering combustion and EC2+3 as soot-EC generated from higher-temperature combustion such as motor vehicle exhaust and coal combustion. In particular, EC1 was strongly correlated with potassium, a traditional biomass burning indicator, except during the summer, when the ratio of EC1 to EC2+3 was the lowest. We also found the ratios of major chemical species to be a useful tool to constrain the main sources of aerosols, by which the five air masses were well distinguished: Siberia, Beijing, Shanghai, Yellow Sea, and East Sea types. Except Siberian air, the continental background of the study region, Beijing plumes showed the highest EC1 (and OP) to sulfate ratio, which implies that this air mass had the highest net warming by aerosols of the four air masses. Shanghai-type air, which was heavily influenced by southern China, showed the highest sulfate enhancement. The highest EC2+3/EC1 ratio was found in aged East Sea air, demonstrating a significant influence of motor vehicle emissions from South Korea and Japan and less influence from industrial regions of China. The high ratio results from the longer residence time and less sensitivity to wet scavenging of EC2+3 compared to EC1, indicating that soot-EC could have greater consequence in regional-scale warming.

Description: We developed a~process model LM3-TAN to assess the combined effects of direct human influences and climate change on Terrestrial and Aquatic Nitrogen (TAN) cycling. The model was developed by expanding NOAA's Geophysical Fluid Dynamics Laboratory land model LM3V-N of coupled terrestrial carbon and nitrogen (C-N) cycling and including new N cycling processes and inputs such as a~soil denitrification, point N sources to streams (i.e. sewage), and stream transport and microbial processes. Because the model integrates ecological, hydrological, and biogeochemical processes, it captures key controls of transport and fate of N in the vegetation-soil-river system in a comprehensive and consistent framework which is responsive to climatic variations and land use changes. We applied the model at 1/8° resolution for a study of the Susquehanna River basin. We simulated with LM3-TAN stream dissolved organic-N, ammonium-N, and nitrate-N loads throughout the river network, and we evaluated the modeled loads for 1986–2005 using data from 15 monitoring stations as well as a reported budget for the entire basin. By accounting for inter-annual hydrologic variability, the model was able to capture inter-annual variations of stream N loadings. While the model was calibrated with the stream N loads only at the last downstream station Marietta (40.02° N, 76.32° W), it captured the N loads well at multiple locations within the basin with different climate regimes, land use types, and associated N sources and transformations in the sub-basins. Furthermore, the calculated and previously reported N budgets agreed well at the level of the whole Susquehanna watershed. Here we illustrate how point and non-point N sources contribute to the various ecosystems are stored, lost, and exported via the river. Local analysis for 6 sub-basins showed combined effects of land use and climate on the soil denitrification rates, with the highest rates in the Lower Susquehanna sub-basin (extensive agriculture; Atlantic coastal climate) and the lowest rates in the West Branch Susquehanna sub-basin (mostly forest; Great Lakes and Midwest climate). In the re-growing secondary forests, most of the N from non-point sources was stored in the vegetation and soil, but in the agricultural lands most N inputs were removed by soil denitrification indicating that anthropogenic N applications could drive substantial increase of N2O emission, an intermediate of the denitrification process.

Description: With the current expansion of wind power as a renewable energy source, wind turbines increasingly extract kinetic energy from the atmosphere, thus impacting its energy resource. Here, we present a simple, physics-based model (the Kinetic Energy Budget of the Atmosphere; KEBA) to estimate wind energy resource potentials that explicitly account for this removal effect. The model is based on the regional kinetic energy budget of the atmospheric boundary layer that encloses the wind farms of a region. This budget is shaped by horizontal and vertical influx of kinetic energy from upwind regions and the free atmosphere above, as well as the energy removal by the turbines, dissipative losses due to surface friction and wakes, and downwind outflux. These terms can be formulated in a simple yet physical way, yielding analytic expressions for how wind speeds and energy yields are reduced with increasing deployment of wind turbines within a region. We show that KEBA estimates compare very well to the modelling results of a previously published study in which wind farms of different sizes and in different regions were simulated interactively with the Weather Research and Forecasting (WRF) atmospheric model. Compared to a reference case without the effect of reduced wind speeds, yields can drop by more than 50 % at scales greater than 100 km, depending on turbine spacing and the wind conditions of the region. KEBA is able to reproduce these reductions in energy yield compared to the simulated climatological means in WRF (n=36 simulations; r2=0.82). The kinetic energy flux diagnostics of KEBA show that this reduction occurs because the total yield of the simulated wind farms approaches a similar magnitude as the influx of kinetic energy. Additionally, KEBA estimates the slowing of the region's wind speeds, the associated reduction in electricity yields, and how both are due to the depletion of the horizontal influx of kinetic energy by the wind farms. This limits typical large-scale wind energy potentials to less than 1 W m−2 of surface area for wind farms with downwind lengths of more than 100 km, although this limit may be higher in windy regions. This reduction with downwind length makes these yields consistent with climate-model-based idealized simulations of large-scale wind energy resource potentials. We conclude that KEBA is a transparent and informative modelling approach to advance the scientific understanding of wind energy limits and can be used to estimate regional wind energy resource potentials that account for the depletion of wind speeds.

Description: Severe tropical storms play an important role in triggering phytoplankton blooms, but the extent to which such storms influence carbon flux from the euphotic zone is unclear. In 2008, typhoon Fengwong provided a unique opportunity to study the in situ biological responses including phytoplankton blooms and particulate organic carbon fluxes associated with a severe storm in the southern East China Sea (SECS). After passage of the typhoon, the sea surface temperature (SST) in the SECS was markedly cooler (~25 to 26 °C) than before typhoon passage (~28 to 29 °C). The POC flux 5 days after passage of the typhoon was 265 ± 14 mg-C m−2 d−1, which was ~1.7-fold that (140–180 mg-C m−2 d−1) recorded during a period (June–August, 2007) when no typhoons occurred. A somewhat smaller but nevertheless significant increase in POC flux (224–265 mg-C m−2 d−1) was detected following typhoon Sinlaku which occurred approximately 1 month after typhoon Fengwong, indicating that typhoon events can increase biogenic carbon flux efficiency in the SECS. Remarkably, phytoplankton uptake accounted for only about 5% of the nitrate injected into the euphotic zone by typhoon Fengwong and it is likely that phytoplankton population growth was presumably constrained by a combination of light limitation and grazing pressure. Modeled estimates of new/export production were remarkably consistent with the average of new and export production following typhoon Fengwong. The same model suggested that during non-typhoon conditions approximately half of the export of organic carbon occurs via convective mixing of dissolved organic carbon, a conclusion consistent with earlier work at comparable latitudes in the open ocean.