Search Results
Organic aerosol components derived from 25 AMS data sets across Europe using a consistent ME-2 based source apportionment approach
2014, Crippa, M., Canonaco, F., Lanz, V.A., Äijälä, M., Allan, J.D., Carbone, S., Capes, G., Ceburnis, D., Dall'Osto, M., Day, D.A., DeCarlo, P.F., Ehn, M., Eriksson, A., Freney, E., Hildebrandt Ruiz, L., Hillamo, R., Jimenez, J.L., Junninen, H., Kiendler-Scharr, A., Kortelainen, A.-M., Kulmala, M., Laaksonen, A., Mensah, A.A., Mohr, C., Nemitz, E., O'Dowd, C., Ovadnevaite, J., Pandis, S.N., Petäjä, T., Poulain, L., Saarikoski, S., Sellegri, K., Swietlicki, E., Tiitta, P., Worsnop, D.R., Baltensperger, U., Prévôt, A.S.H.
Organic aerosols (OA) represent one of the major constituents of submicron particulate matter (PM1) and comprise a huge variety of compounds emitted by different sources. Three intensive measurement field campaigns to investigate the aerosol chemical composition all over Europe were carried out within the framework of the European Integrated Project on Aerosol Cloud Climate and Air Quality Interactions (EUCAARI) and the intensive campaigns of European Monitoring and Evaluation Programme (EMEP) during 2008 (May–June and September–October) and 2009 (February–March). In this paper we focus on the identification of the main organic aerosol sources and we define a standardized methodology to perform source apportionment using positive matrix factorization (PMF) with the multilinear engine (ME-2) on Aerodyne aerosol mass spectrometer (AMS) data. Our source apportionment procedure is tested and applied on 25 data sets accounting for two urban, several rural and remote and two high altitude sites; therefore it is likely suitable for the treatment of AMS-related ambient data sets. For most of the sites, four organic components are retrieved, improving significantly previous source apportionment results where only a separation in primary and secondary OA sources was possible. Generally, our solutions include two primary OA sources, i.e. hydrocarbon-like OA (HOA) and biomass burning OA (BBOA) and two secondary OA components, i.e. semi-volatile oxygenated OA (SV-OOA) and low-volatility oxygenated OA (LV-OOA). For specific sites cooking-related (COA) and marine-related sources (MSA) are also separated. Finally, our work provides a large overview of organic aerosol sources in Europe and an interesting set of highly time resolved data for modeling purposes.
Extreme events in gross primary production: A characterization across continents
2014, Zscheischler, J., Reichstein, M., Harmeling, S., Rammig, A., Tomelleri, E., Mahecha, M.D.
Climate extremes can affect the functioning of terrestrial ecosystems, for instance via a reduction of the photosynthetic capacity or alterations of respiratory processes. Yet the dominant regional and seasonal effects of hydrometeorological extremes are still not well documented and in the focus of this paper. Specifically, we quantify and characterize the role of large spatiotemporal extreme events in gross primary production (GPP) as triggers of continental anomalies. We also investigate seasonal dynamics of extreme impacts on continental GPP anomalies. We find that the 50 largest positive extremes (i.e., statistically unusual increases in carbon uptake rates) and negative extremes (i.e., statistically unusual decreases in carbon uptake rates) on each continent can explain most of the continental variation in GPP, which is in line with previous results obtained at the global scale. We show that negative extremes are larger than positive ones and demonstrate that this asymmetry is particularly strong in South America and Europe. Our analysis indicates that the overall impacts and the spatial extents of GPP extremes are power-law distributed with exponents that vary little across continents. Moreover, we show that on all continents and for all data sets the spatial extents play a more important role for the overall impact of GPP extremes compared to the durations or maximal GPP. An analysis of possible causes across continents indicates that most negative extremes in GPP can be attributed clearly to water scarcity, whereas extreme temperatures play a secondary role. However, for Europe, South America and Oceania we also identify fire as an important driver. Our findings are consistent with remote sensing products. An independent validation against a literature survey on specific extreme events supports our results to a large extent.
A concept of an automated function control for ambient aerosol measurements using mobility particle size spectrometers
2014, Schladitz, A., Merkel, M., Bastian, S., Birmili, W., Weinhold, K., Löschau, G., Wiedensohler, A.
An automated function control unit was developed to regularly check the ambient particle number concentration derived from a mobility particle size spectrometer as well as its zero-point behaviour. The function control allows unattended quality assurance experiments at remote air quality monitoring or research stations under field conditions. The automated function control also has the advantage of being able to get a faster system stability response than the recommended on-site comparisons with reference instruments. The method is based on a comparison of the total particle number concentration measured by a mobility particle size spectrometer and a condensation particle counter while removing diffusive particles smaller than 20 nm in diameter. In practice, the small particles are removed by a set of diffusion screens, as traditionally used in a diffusion battery. Another feature of the automated function control is to check the zero-point behaviour of the ambient aerosol passing through a high-efficiency particulate air (HEPA) filter. The performance of the function control is illustrated with the aid of a 1-year data set recorded at Annaberg-Buchholz, a station in the Saxon air quality monitoring network. During the period of concern, the total particle number concentration derived from the mobility particle size spectrometer slightly overestimated the particle number concentration recorded by the condensation particle counter by 2 % (grand average). Based on our first year of experience with the function control, we developed tolerance criteria that allow a performance evaluation of a tested mobility particle size spectrometer with respect to the total particle number concentration. We conclude that the automated function control enhances the quality and reliability of unattended long-term particle number size distribution measurements. This will have beneficial effects for intercomparison studies involving different measurement sites, and help provide a higher data accuracy for cohort health and climate research studies.
Schneefernerhaus as a mountain research station for clouds and turbulence
2015, Risius, S., Xu, H., Di Lorenzo, F., Xi, H., Siebert, H., Shaw, R.A., Bodenschatz, E.
Cloud measurements are usually carried out with airborne campaigns, which are expensive and are limited by temporal duration and weather conditions. Ground-based measurements at high-altitude research stations therefore play a complementary role in cloud study. Using the meteorological data (wind speed, direction, temperature, humidity, visibility, etc.) collected by the German Weather Service (DWD) from 2000 to 2012 and turbulence measurements recorded by multiple ultrasonic sensors (sampled at 10 Hz) in 2010, we show that the Umweltforschungsstation Schneefernerhaus (UFS) located just below the peak of Zugspitze in the German Alps, at a height of 2650 m, is a well-suited station for cloud–turbulence research. The wind at UFS is dominantly in the east–west direction and nearly horizontal. During the summertime (July and August) the UFS is immersed in warm clouds about 25 % of the time. The clouds are either from convection originating in the valley in the east, or associated with synoptic-scale weather systems typically advected from the west. Air turbulence, as measured from the second- and third-order velocity structure functions that exhibit well-developed inertial ranges, possesses Taylor microscale Reynolds numbers up to 104, with the most probable value at ~ 3000. In spite of the complex topography, the turbulence appears to be nearly as isotropic as many laboratory flows when evaluated on the "Lumley triangle".
Gravity wave influence on NLC: Experimental results from ALOMAR, 69° N
2013, Wilms, H., Rapp, M., Hoffmann, P., Fiedler, J., Baumgarten, G.
The influence of gravity waves on noctilucent clouds (NLC) at ALOMAR (69° N) is analysed by relating gravity wave activity to NLC occurrence from common-volume measurements. Gravity wave kinetic energies are derived from MF-radar wind data and filtered into different period ranges by wavelet transformation. From the dataset covering the years 1999–2011, a direct correlation between gravity wave kinetic energy and NLC occurrence is not found, i.e., NLC appear independently of the simultaneously measured gravity wave kinetic energy. In addition, gravity wave activity is divided into weak and strong activity as compared to a 13 yr mean. The NLC occurrence rates during strong and weak activity are calculated separately for a given wave period and compared to each other. Again, for the full dataset no dependence of NLC occurrence on relative gravity wave activity is found. However, concentrating on 12 h of NLC detections during 2008, we do find an NLC-amplification with strong long-period gravity wave occurrence. Our analysis hence confirms previous findings that in general NLC at ALOMAR are not predominantly driven by gravity waves while exceptions to this rule are at least possible.
Identifying environmental controls on vegetation greenness phenology through model-data integration
2014, Forkel, M., Carvalhais, N., Schaphoff, S., v. Bloh, W., Migliavacca, M., Thurner, M., Thonicke, K.
Existing dynamic global vegetation models (DGVMs) have a limited ability in reproducing phenology and decadal dynamics of vegetation greenness as observed by satellites. These limitations in reproducing observations reflect a poor understanding and description of the environmental controls on phenology, which strongly influence the ability to simulate longer-term vegetation dynamics, e.g. carbon allocation. Combining DGVMs with observational data sets can potentially help to revise current modelling approaches and thus enhance the understanding of processes that control seasonal to long-term vegetation greenness dynamics. Here we implemented a new phenology model within the LPJmL (Lund Potsdam Jena managed lands) DGVM and integrated several observational data sets to improve the ability of the model in reproducing satellite-derived time series of vegetation greenness. Specifically, we optimized LPJmL parameters against observational time series of the fraction of absorbed photosynthetic active radiation (FAPAR), albedo and gross primary production to identify the main environmental controls for seasonal vegetation greenness dynamics. We demonstrated that LPJmL with new phenology and optimized parameters better reproduces seasonality, inter-annual variability and trends of vegetation greenness. Our results indicate that soil water availability is an important control on vegetation phenology not only in water-limited biomes but also in boreal forests and the Arctic tundra. Whereas water availability controls phenology in water-limited ecosystems during the entire growing season, water availability co-modulates jointly with temperature the beginning of the growing season in boreal and Arctic regions. Additionally, water availability contributes to better explain decadal greening trends in the Sahel and browning trends in boreal forests. These results emphasize the importance of considering water availability in a new generation of phenology modules in DGVMs in order to correctly reproduce observed seasonal-to-decadal dynamics of vegetation greenness.
Application of linear polarized light for the discrimination of frozen and liquid droplets in ice nucleation experiments
2013, Clauss, T., Kiselev, A., Hartmann, S., Augustin, S., Pfeifer, S., Niedermeier, D., Wex, H., Stratmann, F.
We report on the development and test results of the new optical particle counter TOPS-Ice (Thermo-stabilized Optical Particle Spectrometer for the detection of Ice). The instrument uses measurements of the cross-polarized scattered light by single particles into the near-forward direction (42.5° ± 12.7°) to distinguish between spherical and non-spherical particles. This approach allows the differentiation between liquid water droplets (spherical) and ice particles (non-spherical) having similar volume-equivalent sizes and therefore can be used to determine the fraction of frozen droplets in a typical immersion freezing experiment. We show that the numerical simulation of the light scattered on non-spherical particles (spheroids in random orientation) considering the actual scattering geometry used in the instrument supports the validity of the approach, even though the cross-polarized component of the light scattered by spherical droplets does not vanish in this scattering angle. For the separation of the ice particle mode from the liquid droplet mode, we use the width of the pulse detected in the depolarization channel instead of the pulse height. Exploiting the intrinsic relationship between pulse height and pulse width for Gaussian pulses allows us to calculate the fraction of frozen droplets even if the liquid droplet mode dominates the particle ensemble. We present test results obtained with TOPS-Ice in the immersion freezing experiments at the laminar diffusion chamber LACIS (Leipzig Aerosol Cloud Interaction Simulator) and demonstrate the excellent agreement with the data obtained in similar experiments with a different optical instrument. Finally, the advantages of using the cross-polarized light measurements for the differentiation of liquid and frozen droplets in the realistic immersion freezing experiments are discussed.
Four-dimensional distribution of the 2010 Eyjafjallajökull volcanic cloud over Europe observed by EARLINET
2013, Pappalardo, G., Mona, L., D'Amico, G., Wandinger, U., Adam, M., Amodeo, A., Ansmann, A., Apituley, A., Alados Arboledas, L., Balis, D., Boselli, A., Bravo-Aranda, J.A., Chaikovsky, A., Comeron, A., Cuesta, J., De Tomasi, F., Freudenthaler, V., Gausa, M., Giannakaki, E., Giehl, H., Giunta, A., Grigorov, I., Groß, S., Haeffelin, M., Hiebsch, A., Iarlori, M., Lange, D., Linné, H., Madonna, F., Mattis, I., Mamouri, R.-E., McAuliffe, M.A.P., Mitev, V., Molero, F., Navas-Guzman, F., Nicolae, D., Papayannis, A., Perrone, M.R., Pietras, C., Pietruczuk, A., Pisani, G., Preißler, J., Pujadas, M., Rizi, V., Ruth, A.A., Schmidt, J., Schnell, F., Seifert, P., Serikov, I., Sicard, M., Simeonov, V., Spinelli, N., Stebel, K., Tesche, M., Trickl, T., Wang, X., Wagner, F., Wiegner, M., Wilson, K.M.
The eruption of the Icelandic volcano Eyjafjallajökull in April–May 2010 represents a "natural experiment" to study the impact of volcanic emissions on a continental scale. For the first time, quantitative data about the presence, altitude, and layering of the volcanic cloud, in conjunction with optical information, are available for most parts of Europe derived from the observations by the European Aerosol Research Lidar NETwork (EARLINET). Based on multi-wavelength Raman lidar systems, EARLINET is the only instrument worldwide that is able to provide dense time series of high-quality optical data to be used for aerosol typing and for the retrieval of particle microphysical properties as a function of altitude. In this work we show the four-dimensional (4-D) distribution of the Eyjafjallajökull volcanic cloud in the troposphere over Europe as observed by EARLINET during the entire volcanic event (15 April–26 May 2010). All optical properties directly measured (backscatter, extinction, and particle linear depolarization ratio) are stored in the EARLINET database available at http://www.earlinet.org. A specific relational database providing the volcanic mask over Europe, realized ad hoc for this specific event, has been developed and is available on request at http://www.earlinet.org. During the first days after the eruption, volcanic particles were detected over Central Europe within a wide range of altitudes, from the upper troposphere down to the local planetary boundary layer (PBL). After 19 April 2010, volcanic particles were detected over southern and south-eastern Europe. During the first half of May (5–15 May), material emitted by the Eyjafjallajökull volcano was detected over Spain and Portugal and then over the Mediterranean and the Balkans. The last observations of the event were recorded until 25 May in Central Europe and in the Eastern Mediterranean area. The 4-D distribution of volcanic aerosol layering and optical properties on European scale reported here provides an unprecedented data set for evaluating satellite data and aerosol dispersion models for this kind of volcanic events.
Modeling the global emission, transport and deposition of trace elements associated with mineral dust
2015, Zhang, Y., Mahowald, N., Scanza, R.A., Journet, E., Desboeufs, K., Albani, S., Kok, J.F., Zhuang, G., Chen, Y., Cohen, D.D., Paytan, A., Patey, M.D., Achterberg, E.P., Engelbrecht, J.P., Fomba, K.W.
Trace element deposition from desert dust has important impacts on ocean primary productivity, the quantification of which could be useful in determining the magnitude and sign of the biogeochemical feedback on radiative forcing. However, the impact of elemental deposition to remote ocean regions is not well understood and is not currently included in global climate models. In this study, emission inventories for eight elements primarily of soil origin, Mg, P, Ca, Mn, Fe, K, Al, and Si are determined based on a global mineral data set and a soil data set. The resulting elemental fractions are used to drive the desert dust model in the Community Earth System Model (CESM) in order to simulate the elemental concentrations of atmospheric dust. Spatial variability of mineral dust elemental fractions is evident on a global scale, particularly for Ca. Simulations of global variations in the Ca / Al ratio, which typically range from around 0.1 to 5.0 in soils, are consistent with observations, suggesting that this ratio is a good signature for dust source regions. The simulated variable fractions of chemical elements are sufficiently different; estimates of deposition should include elemental variations, especially for Ca, Al and Fe. The model results have been evaluated with observations of elemental aerosol concentrations from desert regions and dust events in non-dust regions, providing insights into uncertainties in the modeling approach. The ratios between modeled and observed elemental fractions range from 0.7 to 1.6, except for Mg and Mn (3.4 and 3.5, respectively). Using the soil database improves the correspondence of the spatial heterogeneity in the modeling of several elements (Ca, Al and Fe) compared to observations. Total and soluble dust element fluxes to different ocean basins and ice sheet regions have been estimated, based on the model results. The annual inputs of soluble Mg, P, Ca, Mn, Fe and K associated with dust using the mineral data set are 0.30 Tg, 16.89 Gg, 1.32 Tg, 22.84 Gg, 0.068 Tg, and 0.15 Tg to global oceans and ice sheets.
Calibration of Raman lidar water vapor profiles by means of AERONET photometer observations and GDAS meteorological data
2018, Dai, Guangyao, Althausen, Dietrich, Hofer, Julian, Engelmann, Ronny, Seifert, Patric, Bühl, Johannes, Mamouri, Rodanthi-Elisavet, Wu, Songhua, Ansmann, Albert
We present a practical method to continuously calibrate Raman lidar observations of water vapor mixing ratio profiles. The water vapor profile measured with the multiwavelength polarization Raman lidar PollyXT is calibrated by means of co-located AErosol RObotic NETwork (AERONET) sun photometer observations and Global Data Assimilation System (GDAS) temperature and pressure profiles. This method is applied to lidar observations conducted during the Cyprus Cloud Aerosol and Rain Experiment (CyCARE) in Limassol, Cyprus. We use the GDAS temperature and pressure profiles to retrieve the water vapor density. In the next step, the precipitable water vapor from the lidar observations is used for the calibration of the lidar measurements with the sun photometer measurements. The retrieved calibrated water vapor mixing ratio from the lidar measurements has a relative uncertainty of 11 % in which the error is mainly caused by the error of the sun photometer measurements. During CyCARE, nine measurement cases with cloud-free and stable meteorological conditions are selected to calculate the precipitable water vapor from the lidar and the sun photometer observations. The ratio of these two precipitable water vapor values yields the water vapor calibration constant. The calibration constant for the PollyXT Raman lidar is 6.56 g kg−1 ± 0.72 g kg−1 (with a statistical uncertainty of 0.08 g kg−1 and an instrumental uncertainty of 0.72 g kg−1). To check the quality of the water vapor calibration, the water vapor mixing ratio profiles from the simultaneous nighttime observations with Raman lidar and Vaisala radiosonde sounding are compared. The correlation of the water vapor mixing ratios from these two instruments is determined by using all of the 19 simultaneous nighttime measurements during CyCARE. Excellent agreement with the slope of 1.01 and the R2 of 0.99 is found. One example is presented to demonstrate the full potential of a well-calibrated Raman lidar. The relative humidity profiles from lidar, GDAS (simulation) and radiosonde are compared, too. It is found that the combination of water vapor mixing ratio and GDAS temperature profiles allow us to derive relative humidity profiles with the relative uncertainty of 10–20 %.