ALBERT

Description: The influence of aerosols, both natural and anthropogenic, remains a major area of uncertainty when predicting the properties and behaviour of clouds and their influence on climate. In an attempt to better understand warm cloud formation in a tropical marine environment, a period of intensive measurements took place in December 2004 in Puerto Rico, using some of the latest developments in online instrumentation such as aerosol mass spectrometers, cloud condensation nuclei counters and a hygroscopicity tandem differential mobility analyser. Simultaneous online measurements of aerosol size distributions, composition, hygroscopicity and optical properties were made near the lighthouse of Cape San Juan in the north-eastern corner of the island and at the top of East Peak mountain (1040 m a.s.l.), the two sites separated by 17 km. Additional measurements of the cloud droplet residual and interstitial aerosol properties were made at the mountain site, accompanied by measurements of cloud droplet size distributions, liquid water content and the chemical composition of cloud and rain water samples. Both aerosol composition and cloud properties were found to be sensitive to wind sector. Air from the east-northeast (ENE) was mostly free of anthropogenic influences, the submicron fraction being mainly composed of non-sea salt sulphate, while that from the east-southeast (ESE) was found to be moderately influenced by populated islands upwind, adding smaller (

Description: Detailed investigations of the chemical and microphysical properties of rural continental aerosols were performed during the HAZE2002 experiment, which was conducted in May 2002 at the Meteorological Observatory Hohenpeissenberg (DWD) in Southern Germany. Online measurements included: Size-resolved chemical composition of submicron particles; total particle number concentrations and size distributions over the diameter range of 3 nm to 9 μm; gas-phase concentration of monoterpenes, CO, O3, OH, and H2SO4. Filter sampling and offline analytical techniques were used to determine: Fine particle mass (PM2.5), organic, elemental and total carbon in PM2.5 (OC2.5, EC2.5, TC2.5), and selected organic compounds (dicarboxylic acids, polycyclic aromatic hydrocarbons, proteins). Overall, the non-refractory components of submicron particles detected by aerosol mass spectrometry (PM1, 6.6±5.4 μg m−3, arithmetic mean and standard deviation) accounted for ~62% of PM2.5 determined by filter gravimetry (10.6±4.7 μg m−3). The relative proportions of non-refractory submicron particle components were: (23±39)% ammonium nitrate, (27±23)% ammonium sulfate, and (50±40)% organics (OM1). OM1 was closely correlated with PM1 (r2=0.9) indicating a near-constant ratio of non-refractory organics and inorganics. The average ratio of OM1 to OC2.5 was 2.1±1.4, indicating a high proportion of heteroelements in the organic fraction of the sampled rural aerosol. This is consistent with the high ratio of oxygenated organic aerosol (OOA) over hydrocarbon-like organic aerosol (HOA) inferred from the AMS results (4:1), and also with the high abundance of proteins (~3%) indicating a high proportion of primary biological material (~30%) in PM2.5. This finding was confirmed by low abundance of PAHs (

Description: Detailed investigations of the chemical and microphysical properties of rural continental aerosols were performed during the HAZE2002 experiment, which was conducted in May 2002 at the Meteorological Observatory Hohenpeissenberg (DWD) in Southern Germany. The online measurement data and techniques included: size-resolved chemical composition of submicron particles by aerosol mass spectrometry (AMS); total particle number concentrations and size distributions over the diameter range of 3 nm to 9 μm (CPC, SMPS, OPC); monoterpenes determined by gas chromatography- ion trap mass spectrometry; OH and H2SO4 determined by atmospheric pressure chemical ionization mass spectrometry (CIMS). Filter sampling and offline analytical techniques were used to determine: fine particle mass (PM2.5), organic, elemental and total carbon in PM2.5 (OC2.5, EC2.5, TC2.5), and selected organic compounds (dicarboxylic acids, polycyclic aromatic hydrocarbons, proteins). Overall, the non-refractory components of submicron particles detected by aerosol mass spectrometry (PM1, 6.6±5.4 μg m−3, arithmetic mean and standard deviation) accounted for ~62% of PM2.5 determined by filter gravimetry (10.6±4.7 μg m−3). The relative proportions of non-refractory submicron particle components were: 11% ammonium, 19% nitrate, 20% sulfate, and 50% organics (OM1). In spite of strongly changing meteorological conditions and absolute concentration levels of particulate matter (3–13 μg m−3 PM1), OM1 was closely correlated with PM1 (r2=0.9) indicating a near-constant ratio of non-refractory organics and inorganics. In contrast, the ratio of nitrate to sulfate was highly dependent on temperature (14–32°C) and relative humidity (20–100%), which could be explained by thermodynamic model calculations of NH3/HNO3/NH4NO3 gas-particle partitioning. From the combination of optical and other sizing techniques (OPC, AMS, SMPS), an average refractive index of 1.40–1.45 was inferred for the measured rural aerosol particles. The average ratio of OM1 to OC2.5 was 2, indicating a high proportion of heteroelements in the organic fraction of the sampled rural aerosol. This is consistent with the high ratio of oxygenated organic aerosol (OOA) over hydrocarbon-like organic aerosol (HOA) inferred from the AMS results (4:1), and also with the high abundance of proteins (~3%) indicating a high proportion of primary biological material (~30%) in PM2.5. Moreover, the low abundance of PAHs (

Description: During the measurement campaign FROST (FReezing Of duST), LACIS (Leipzig Aerosol Cloud Interaction Simulator) was used to investigate the immersion freezing behavior of coated and uncoated Arizona Test Dust (ATD) particles with a mobility diameter of 300 nm. Particles were coated with succinic acid (C4H6O4), sulfuric acid (H2SO4, two different coating conditions), and ammonium sulfate ((NH4)2SO4). Ice fractions at temperatures between 233.15 K and 240.65 K were determined for all types of particles acting as IN (Ice Nuclei). In this temperature range, uncoated particles and those coated with C4H6O4 or small amounts of H2SO4 started to act as IN at higher temperatures compared to particles with larger amounts of H2SO4 or (NH4)2SO4 coatings. Although the latter two showed similar hygroscopic growth and droplet activation behavior, they differed in their ability to act as IN. ATD particles coated with (NH4)2SO4 were the most inefficient IN. The ability of the investigated particles to act as IN was found not to be related to water activity for the freezing process investigated, however, in LACIS, the supercooled droplets were activated and highly diluted before the freezing occurred. Applying the measurement results, a parameterization, based on a simplified CNT (Classical Nucleation Theory) type nucleation rate expression, was developed. The simplified theory allows us to determine that thermodynamic changes at the surface are dominating the change in nucleating ability, rather than changes in surface area or kinetic effects.

Description: The influence of aerosols, both natural and anthropogenic, remains a major area of uncertainty when predicting the properties and behaviour of clouds and their influence on climate. In an attempt to better understand warm cloud formation in a tropical marine environment, a period of intensive measurements using some of the latest developments in online instrumentation took place in December 2004 in Puerto Rico. Simultaneous online measurements of aerosol size distributions, composition, hygroscopicity and optical properties were made near the lighthouse of Cape San Juan in the north-eastern corner of the island and at the top of East Peak mountain (1040 m a.s.l.), the two sites separated by 17 km. Additional measurements of the cloud droplet residual and interstitial aerosol properties were made at the mountain site, accompanied by measurements of cloud droplet size distributions, liquid water content and the chemical composition of cloud and rain water samples. Both aerosol composition and cloud properties were found to be sensitive to wind sector. Air from the east-northeast (ENE) was mostly free of anthropogenic influences, the submircron fraction being mainly composed of non-sea salt sulphate, while that from the east-southeast (ESE) was found to be moderately influenced by populated islands upwind, adding smaller (

Description: Accurate determination of carbon balances in heterogeneous ecosystems often requires the extrapolation of point based measurements. The ground resolution (pixel size) of the extrapolation base, e.g. a land-cover map, might thus influence the calculated carbon balance, in particular if biogeochemical hot spots are small in size. In this paper, we test the effects of varying ground resolution on the calculated carbon balance of a boreal peatland consisting of hummocks (dry), lawns (intermediate) and flarks (wet surfaces). The generalizations in lower resolution imagery led to biased area estimates for individual micro-site types. While areas of lawns and hummocks were stable below a threshold resolution of ~60 cm, the maximum of the flark area was located at resolutions below 25 cm and was then decreasing with coarsening resolution. Using a resolution of 100 cm instead of 6 cm led to an overestimation of total CO2 uptake of the studied peatland area (approximately 14 600 m2) of ~6% and an underestimation of total CH4 emission of ~11%. To accurately determine the surface area of scattered and small-sized micro-site types in heterogeneous ecosystems (e.g. flarks in peatlands), a minimum ground resolution appears necessary. In our case this leads to a recommended resolution of 25 cm, which can be derived by conventional airborne imagery. The usage of high resolution imagery from commercial satellites, e.g. Quickbird, however, is likely to underestimate the surface area of biogeochemical hot spots. It is important to note that the observed resolution effect on the carbon balance estimates can be much stronger for other ecosystems than for the investigated peatland where the relative hot spot area of the flarks is very small and their hot spot characteristics with respect to CH4 and CO2 fluxes is rather modest.

Description: Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach was justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatland sites in Finland and a tundra site in Siberia. The flux measurements were performed using transparent chambers on vegetated surfaces and opaque chambers on bare peat surfaces. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes and even lower for longer closure times. The degree of underestimation increased with increasing CO2 flux strength and is dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.

Description: Accurate determination of carbon balances in heterogeneous ecosystems often requires the extrapolation of point based measurements. The ground resolution (pixel size) of the extrapolation base, e.g. a land-cover map, might thus influence the calculated carbon balance, in particular if biogeochemical hot spots are small in size. In this paper, we test the effects of varying ground resolution on the calculated carbon balance of a boreal peatland consisting of hummocks (dry), lawns (intermediate) and flarks (wet surfaces). The generalizations in lower resolution imagery led to biased area estimates for individual micro-site types. While areas of lawns and hummocks were stable below a threshold resolution of ~60 cm, the maximum of the flark area was located at resolutions below 25 cm and was then decreasing with coarsening resolution. Using a resolution of 100 cm instead of 6 cm led to an overestimation of total CO2 uptake of the studied peatland area (approximately 14 600 m2) of ~5% and an underestimation of total CH4 emission of ~6%. To accurately determine the surface area of scattered and small-sized micro-site types in heterogeneous ecosystems (e.g. flarks in peatlands), a minimum ground resolution appears necessary. In our case this leads to a recommended resolution of 25 cm, which can be derived by conventional airborne imagery. The usage of high resolution imagery from commercial satellites, e.g. Quickbird, however, is likely to underestimate the surface area of biogeochemical hot spots. It is important to note that the observed resolution effect on the carbon balance estimates can be much stronger for other ecosystems than for the investigated peatland. In the investigated peatland the relative hot spot area of the flarks is very small and their hot spot characteristics with respect to CH4 and CO2 fluxes is rather modest.

Description: Real-time measurements of non-refractory submicron aerosols (NR-PM1) were conducted within the greater Alpine region (Switzerland, Germany, Austria, France and Liechtenstein) during several week-long field campaigns in 2002–2009. A large variety of sites was covered including urban backgrounds, motorways, rural, remote, and high-Alpine stations, and also mobile on-road measurements were performed. Inorganic and organic aerosol (OA) fractions were determined by means of aerosol mass spectrometry (AMS). The average mass concentration of NR-PM1 for the different campaigns typically ranged between 10 and 30 μg m−3. Overall, the organic portion was most abundant, ranging from 36% to 81% of NR-PM1. Other main constituents comprised ammonium (5–15%), nitrate (8–36%), sulfate (3–26%), and chloride (0–5%). These latter anions were, on average, fully neutralized by ammonium. The OA was further divided (based on factor analysis, FA) into its underlying components, such as oxygenated (mostly secondary) organic aerosol (OOA), hydrocarbon-like and freshly emitted organic aerosol (HOA), as well as primary OA from biomass burning (P-BBOA). OOA was ubiquitous, ranged between 36% and 94% of OA, and could be separated into a low-volatility and a semi-volatile fraction (LV-OOA and SV-OOA) for all summer campaigns at low sites. Primary wood combustion (P-BBOA) accounted for a considerable fraction during wintertime (17–49% OA). HOA/OA ratios were comparatively low for all campaigns (6–16%) with the exception of on-road, mobile measurements (23%).

Description: Closed (non-steady state) chambers are widely used for quantifying carbon dioxide (CO2) fluxes between soils or low-stature canopies and the atmosphere. It is well recognised that covering a soil or vegetation by a closed chamber inherently disturbs the natural CO2 fluxes by altering the concentration gradients between the soil, the vegetation and the overlying air. Thus, the driving factors of CO2 fluxes are not constant during the closed chamber experiment, and no linear increase or decrease of CO2 concentration over time within the chamber headspace can be expected. Nevertheless, linear regression has been applied for calculating CO2 fluxes in many recent, partly influential, studies. This approach has been justified by keeping the closure time short and assuming the concentration change over time to be in the linear range. Here, we test if the application of linear regression is really appropriate for estimating CO2 fluxes using closed chambers over short closure times and if the application of nonlinear regression is necessary. We developed a nonlinear exponential regression model from diffusion and photosynthesis theory. This exponential model was tested with four different datasets of CO2 flux measurements (total number: 1764) conducted at three peatlands sites in Finland and a tundra site in Siberia. Thorough analyses of residuals demonstrated that linear regression was frequently not appropriate for the determination of CO2 fluxes by closed-chamber methods, even if closure times were kept short. The developed exponential model was well suited for nonlinear regression of the concentration over time c(t) evolution in the chamber headspace and estimation of the initial CO2 fluxes at closure time for the majority of experiments. However, a rather large percentage of the exponential regression functions showed curvatures not consistent with the theoretical model which is considered to be caused by violations of the underlying model assumptions. Especially the effects of turbulence and pressure disturbances by the chamber deployment are suspected to have caused unexplainable curvatures. CO2 flux estimates by linear regression can be as low as 40% of the flux estimates of exponential regression for closure times of only two minutes. The degree of underestimation increased with increasing CO2 flux strength and was dependent on soil and vegetation conditions which can disturb not only the quantitative but also the qualitative evaluation of CO2 flux dynamics. The underestimation effect by linear regression was observed to be different for CO2 uptake and release situations which can lead to stronger bias in the daily, seasonal and annual CO2 balances than in the individual fluxes. To avoid serious bias of CO2 flux estimates based on closed chamber experiments, we suggest further tests using published datasets and recommend the use of nonlinear regression models for future closed chamber studies.