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In the present work, three different techniques are used to separate ice-nucleating particles (INP) and ice particle residuals (IPR) from non-ice-active particles: the Ice Selective Inlet (ISI) and the Ice Counterflow Virtual Impactor (Ice-CVI), which sample ice particles from mixed phase clouds and allow for the analysis of the residuals, as well as the combination of the Fast Ice Nucleus Chamber (FINCH) and the Ice Nuclei Pumped Virtual Impactor (IN-PCVI), which provides ice-activating conditions to aerosol particles and extracts the activated ones for analysis. The collected particles were analyzed by scanning electron microscopy and energy-dispersive X-ray microanalysis to determine their size, chemical composition and mixing state. Samples were taken during January/February 2013 at the High Alpine Research Station Jungfraujoch. All INP/IPR-separating techniques had considerable abundances (median 20–70%) of contamination artifacts (ISI: Si-O spheres, probably calibration aerosol; Ice-CVI: Al-O particles; FINCH + IN-PCVI: steel particles). Also, potential measurement artifacts (soluble material) occurred (median abundance < 20%). After removal of the contamination particles, silicates and Ca-rich particles, carbonaceous material and metal oxides were the major INP/IPR particle types separated by all three techniques. Minor types include soot and Pb-bearing particles. Sea-salt and sulfates were identified by all three methods as INP/IPR. Lead was identified in less than 10% of the INP/IPR. It was mainly present as an internal mixture with other particle types, but also external lead-rich particles were found. Most samples showed a maximum of the INP/IPR size distribution at 400 nm geometric diameter. In a few cases, a second super-micron maximum was identified. Soot/carbonaceous material and metal oxides were present mainly in the submicron range. ISI and FINCH yielded silicates and Ca-rich particles mainly with diameters above 1 μm, while the Ice-CVI also sampled many submicron particles. Probably owing to the different meteorological conditions, the INP/IPR composition was highly variable on a sample to sample basis. Thus, some part of the discrepancies between the different techniques may result from the (unavoidable) non-parallel sampling. The observed differences of the particles group abundances as well as the mixing state of INP/IPR point to the need of further studies to better understand the influence of the separating techniques on the INP/IPR chemical composition.
Increasing atmospheric CO2 stimulates photosynthesis which can increase net primary production (NPP), but at longer timescales may not necessarily increase plant biomass. Here we analyse the four decade-long CO2-enrichment experiments in woody ecosystems that measured total NPP and biomass. CO2 enrichment increased biomass increment by 1.05 ± 0.26 kg C m−2 over a full decade, a 29.1 ± 11.7% stimulation of biomass gain in these early-secondary-succession temperate ecosystems. This response is predictable by combining the CO2 response of NPP (0.16 ± 0.03 kg C m−2 y−1) and the CO2-independent, linear slope between biomass increment and cumulative NPP (0.55 ± 0.17). An ensemble of terrestrial ecosystem models fail to predict both terms correctly. Allocation to wood was a driver of across-site, and across-model, response variability and together with CO2-independence of biomass retention highlights the value of understanding drivers of wood allocation under ambient conditions to correctly interpret and predict CO2 responses.
We combined biostratigraphical analyses, archaeological surveys, and Glacial Isostatic Adjustment (GIA) models to provide new insights into the relative sea-level evolution in the northeastern Aegean Sea (eastern Mediterranean). In this area, characterized by a very complex tectonic pattern, we produced a new typology of sea-level index point, based on the foraminiferal associations found in transgressive marine facies. Our results agree with the sea-level history previously produced in this region, therefore confirming the validity of this new type of index point. The expanded dataset presented in this paper further demonstrates a continuous Holocene RSL rise in this portion of the Aegean Sea. Comparing the new RSL record with the available geophysical predictions of sea-level evolution indicates that the crustal subsidence of the Samothraki Plateau and the North Aegean Trough played a major role in controlling millennial-scale sea-level evolution in the area. This major subsidence rate needs to be taken into account in the preparation of local future scenarios of sea-level rise in the coming decades.
We apply seismic full waveform inversion to SH‐ and Love‐wave data for investigating the near‐surface lithology at an archaeological site. We evaluate the resolution of the applied full waveform inversion algorithm through ground truthing in the form of an excavation and sediment core studies. Thereby, we investigate the benefits of full waveform inversion in comparison with other established methods of near‐surface prospecting in terms of resolution capabilities and interpretation security. The study is performed in a presumed harbour area of the ancient Thracian city of Ainos. The exemplary target is the source of a linear magnetic anomaly oriented perpendicular to the coast, which was found in a previous magnetic gradiometry survey, suggesting a mole. The SH‐wave full waveform inversion recovered a subsurface SH‐wave velocity model with submeter resolution showing lateral and vertical velocity variation between 40 and 150 m/s. To tame the non‐linearity of the full waveform inversion, a sequential inversion of frequency bands has to be combined with time‐windowing in order to separate the Love wave from the reflected SH wavefield. We compare the full waveform inversion results with multichannel analysis of surface waves, standard seismic reflection imaging, electrical resistivity tomography and electromagnetic induction. It turns out that the respective depth sections are correlated to a certain degree with the full waveform inversion results. However, the structural resolution of the other geophysical methods is significantly lower than for the full waveform inversion. An exception is the reflection seismic imaging, which shows the same resolution as full waveform inversion but can only be interpreted together with the full waveform inversion–based velocity model. An archaeological excavation as well as coring data allows ground truthing and a direct understanding of the geophysical structures. The results show that the target was a sort of near‐surface trench of about 3–4 m width and 0.8 m to 1.0 m depth, filled with silty sediment, which differs from the layered surrounding in colour and composition. The ground truthing revealed that only SH‐wave full waveform inversion and seismic reflection imaging could image the trench and sediment structure with satisfying lateral and depth resolution. We emphasize that the velocity distribution from SH‐wave full waveform inversion agrees closely with the excavated subsurface structures, and that the discovered changes in seismic velocity correlate with changes in the sand content in the respective sediment facies sequences. The study demonstrated that SH‐wave full waveform inversion is capable to image structural and lithological changes in the near subsurface at scales as low as 0.5 m, thus providing the high resolution needed for archaeological and geoarchaeological prospection.
This paper presents results from the "INUIT-JFJ/CLACE 2013" field campaign at the high alpine research station Jungfraujoch in January/February 2013. The chemical composition of ice particle residuals (IPR) in a size diameter range of 200–900 nm was measured in orographic, convective and non-convective clouds with a single particle mass spectrometer (ALABAMA) under ambient conditions characterized by temperatures between −28 and −4 °C and wind speed from 0.1 to 21 km h−1. Additionally, background aerosol particles in cloud free air were investigated. The IPR were sampled from mixed-phase clouds with two inlets which selectively extract small ice crystals in-cloud, namely the Counterflow Virtual Impactor (Ice-CVI) and the Ice Selective Inlet (ISI). The IPR as well as the aerosol particles were classified into seven different particle types: (1) black carbon, (2) organic carbon, (3) black carbon internally mixed with organic carbon, (4) minerals, (5) one particle group (termed "BioMinSal") that may contain biological particles, minerals, or salts, (6) industrial metals, and (7) lead containing particles. For any sampled particle population it was determined by means of single particle mass spectrometer how many of the analyzed particles belonged to each of these categories. Accordingly, between 20 and 30% of the IPR and roughly 42% of the background particles contained organic carbon. The measured fractions of minerals in the IPR composition varied from 6 to 33%, while the values for the "BioMinSal" group were between 15 and 29%. Four percent to 31% of the IPR contained organic carbon mixed with black carbon. Both inlets delivered similar results of the chemical composition and of the particle size distribution, although lead was found only in the IPR sampled by the Ice-CVI. The results show that the ice particle residual composition varies substantially between different cloud events, which indicates the influence of different meteorological conditions, such as origin of the air masses, temperature and wind speed.
The Tarim River Basin, located in Xinjiang, NW China, is the largest endorheic river basin of China and one of the largest in whole Central Asia. Due to the extremely arid climate with an annual precipitation of less than 100 mm, the water supply along the Aksu and Tarim River solely depends on river water. This applies for anthropogenic activities (e.g. agriculture) as well as for the natural ecosystems so that both compete for water. The on-going increase of water consumption by agriculture and other human activities in this region has been enhancing the competition for water between human needs and nature. Against this background, 11 German and 6 Chinese universities and research institutes formed the consortium SuMaRiO (www.sumario.de), which aims at gaining a holistic picture of the availability of water resources in the Tarim River Basin and the impacts on anthropogenic activities and natural ecosystems caused by the water distribution within the Tarim River Basin. The discharge of the Aksu River, which is the major tributary to the Tarim, has been increasing over the past 6 decades due to enhanced glacier melt. Alone from 1989 to 2011, the area under agriculture more than doubled. Thereby, cotton became the major crop and there was a shift from small-scale farming to large-scale intensive farming. The major natural ecosystems along the Aksu and Tarim River are riparian ecosystems: Riparian (Tugai) forests, shrub vegetation, reed beds, and other grassland. Within the SuMaRiO Cluster the focus was laid on the Tugai forests, with Populus euphratica as dominant tree, because the most productive and species-rich natural ecosystems can be found among those forests. On sites with groundwater distance of less than 7.5 m the annual increments correlated with river runoffs of the previous year. But, the further downstream along the Tarim River, the more the natural river dynamics ceased, which impacts on the recruitment of Populus euphratica. Household surveys revealed that there is a considerable willingness to pay for conservation of those riparian forests with the mitigation of dust and sandstorms considered as the most important ecosystem service. This interdisciplinary project will result in a decision support tool (DST), build on the participation of regional stakeholders and models based on results and field experiments. This DST finally shall assist stakeholders in balancing the water competition acknowledging the major external effects of any water allocation.
The Tarim River basin, located in Xinjiang, NW China, is the largest endorheic river basin in China and one of the largest in all of Central Asia. Due to the extremely arid climate, with an annual precipitation of less than 100 mm, the water supply along the Aksu and Tarim rivers solely depends on river water. This is linked to anthropogenic activities (e.g., agriculture) and natural and semi-natural ecosystems as both compete for water. The ongoing increase in water consumption by agriculture and other human activities in this region has been enhancing the competition for water between human needs and nature. Against this background, 11 German and 6 Chinese universities and research institutes have formed the consortium SuMaRiO (Sustainable Management of River Oases along the Tarim River; http://www.sumario.de), which aims to create a holistic picture of the availability of water resources in the Tarim River basin and the impacts on anthropogenic activities and natural ecosystems caused by the water distribution within the Tarim River basin. On the basis of the results from field studies and modeling approaches as well as from suggestions by the relevant regional stakeholders, a decision support tool (DST) will be implemented that will then assist stakeholders in balancing the competition for water, acknowledging the major external effects of water allocation to agriculture and to natural ecosystems. This consortium was formed in 2011 and is funded by the German Federal Ministry of Education and Research. As the data collection phase was finished this year, the paper presented here brings together the results from the fields from the disciplines of climate modeling, cryology, hydrology, agricultural sciences, ecology, geoinformatics, and social sciences in order to present a comprehensive picture of the effects of different water availability schemes on anthropogenic activities and natural ecosystems along the Tarim River. The second objective is to present the project structure of the whole consortium, the current status of work (i.e., major new results and findings), explain the foundation of the decision support tool as a key product of this project, and conclude with application recommendations for the region. The discharge of the Aksu River, which is the major tributary of the Tarim, has been increasing over the past 6 decades. From 1989 to 2011, agricultural area more than doubled: cotton became the major crop and there was a shift from small-scale to large-scale intensive farming. The ongoing increase in irrigated agricultural land leads to the increased threat of salinization and soil degradation caused by increased evapotranspiration. Aside from agricultural land, the major natural and semi-natural ecosystems are riparian (Tugai) forests, shrub vegetation, reed beds, and other grassland, as well as urban and peri-urban vegetation. Within the SuMaRiO cluster, focus has been set on the Tugai forests, with Populus euphratica as the dominant tree species, because these forests belong to the most productive and species-rich natural ecosystems of the Tarim River basin. At sites close to the groundwater, the annual stem diameter increments of Populus euphratica correlated with the river runoffs of the previous year. However, the natural river dynamics cease along the downstream course and thus hamper the recruitment of Populus euphratica. A study on the willingness to pay for the conservation of the natural ecosystems was conducted to estimate the concern of the people in the region and in China's capital. These household surveys revealed that there is a considerable willingness to pay for conservation of the natural ecosystems, with mitigation of dust and sandstorms considered the most important ecosystem service. Stakeholder dialogues contributed to creating a scientific basis for a sustainable management in the future.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations as well as hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a one-year period and full seasonal cycle (March 2014 - February 2015). The presented measurements provide a climatology of CCN properties for a characteristic central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The observed mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), elevated values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter κ exhibits remarkably little temporal variability: no pronounced diurnal cycles, weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modelling purposes, we compare different approaches of predicting CCN number concentration and present a novel parameterization, which allows accurate CCN predictions based on a small set of input data.
Size-resolved long-term measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a 1-year period and full seasonal cycle (March 2014–February 2015). The measurements provide a climatology of CCN properties characteristic of a remote central Amazonian rain forest site.
The CCN measurements were continuously cycled through 10 levels of supersaturation (S = 0.11 to 1.10 %) and span the aerosol particle size range from 20 to 245 nm. The mean critical diameters of CCN activation range from 43 nm at S = 1.10 % to 172 nm at S = 0.11 %. The particle hygroscopicity exhibits a pronounced size dependence with lower values for the Aitken mode (κAit = 0.14 ± 0.03), higher values for the accumulation mode (κAcc = 0.22 ± 0.05), and an overall mean value of κmean = 0.17 ± 0.06, consistent with high fractions of organic aerosol.
The hygroscopicity parameter, κ, exhibits remarkably little temporal variability: no pronounced diurnal cycles, only weak seasonal trends, and few short-term variations during long-range transport events. In contrast, the CCN number concentrations exhibit a pronounced seasonal cycle, tracking the pollution-related seasonality in total aerosol concentration. We find that the variability in the CCN concentrations in the central Amazon is mostly driven by aerosol particle number concentration and size distribution, while variations in aerosol hygroscopicity and chemical composition matter only during a few episodes.
For modeling purposes, we compare different approaches of predicting CCN number concentration and present a novel parametrization, which allows accurate CCN predictions based on a small set of input data.
Size-resolved measurements of atmospheric aerosol and cloud condensation nuclei (CCN) concentrations and hygroscopicity were conducted at the remote Amazon Tall Tower Observatory (ATTO) in the central Amazon Basin over a full seasonal cycle (Mar 2014–Feb 2015). In a companion part 1 paper, we presented an in-depth CCN characterization based on annually as well as seasonally averaged time intervals and discuss different parametrization strategies to represent the Amazonian CCN cycling in modelling studies (M. Pöhlker et al., 2016b). The present part 2 study analyzes the aerosol and CCN variability in original time resolution and, thus, resolves aerosol advection and transformation for the following case studies, which represent the most characteristic states of the Amazonian atmosphere:
1. Near-pristine (NP) conditions, defined as the absence of detectable black carbon (< 0.01 µg m−3), showed their highest occurrence (up to 30 %) in the wet season (i.e., Mar–May). On average, the NP episodes are characterized by a bimodal aerosol size distribution (strong Aitken mode: DAit = 70 nm, NAit = ~ 200 cm−3 vs. weaker accumulation mode: Dacc = 170 nm, Nacc = ~ 60 cm−3), a mostly organic particle composition, and relatively low hygroscopicity levels (κAit = 0.12 vs. κacc = 0.18). The NP CCN efficiency spectrum shows that the CCN population is sensitive to changes in supersaturation (S) over a wide S range.
2. Long-range transport (LRT) conditions frequently mix Saharan dust, African combustion smoke, and sea spray aerosols into the Amazonian wet season atmosphere. The LRT episodes (i.e., Feb–Apr) are characterized by an accumulation mode dominated size distribution (DAit = 80 nm, NAit = 120 cm−3 vs. Dacc = 180 nm, Nacc = 300 cm−3), a clearly increased abundance of dust and salt compounds, and relatively high hygroscopicity levels (κAit = 0.18, κacc = 0.34). The LRT CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
3. Biomass burning (BB) conditions dominate the Amazonian dry season. A selected characteristic BB episode shows a very strong accumulation mode (DAit = 70 nm, NAit = ~ 140 cm−3 vs. Dacc = 170 nm, Nacc = ~ 3400 cm−3), particles with very high organic fractions (> 90 %), and correspondingly low hygroscopicity levels (κAit = 0.14, κacc = 0.17). The BB CCN efficiency spectrum shows that the CCN population is highly sensitive to changes in S in the low S regime.
4. Mixed pollution conditions show the superposition of African (i.e., volcanic) and Amazonian (i.e., biomass burning) aerosol emissions during the dry season. The African aerosols showed a broad monomodal distribution (D = 130 nm, N = ~ 1300 cm−3), with very high sulfate fractions (20 %), and correspondingly high hygroscopicity (κAit = 0.14, κacc = 0.22). This was superimposed by fresh smoke from nearby fires with one strong mode (D = 113 nm, Nacc = ~ 2800 cm−3), an organic-dominated aerosol, and sharply decreased hygroscopicity (κAit = 0.10, κacc = 0.20). These conditions underline the rapidly changing pollution regimes with clear impacts on the aerosol and CCN properties.
Overall, this study provides detailed insights into the CCN cycling in relation to aerosol-cloud interaction in the vulnerable and climate-relevant Amazon region. The detailed analysis of aerosol and CCN key properties and particularly the extracted CCN efficiency spectra with the associated fit parameters provide a basis for an in-depth analysis of aerosol-cloud interaction in the Amazon and beyond.