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Simulation of global temperature variations and signal detection studies using neural networks
(1998)
The concept of neural network models (NNM) is a statistical strategy which can be used if a superposition of any forcing mechanisms leads to any effects and if a sufficient related observational data base is available. In comparison to multiple regression analysis (MRA), the main advantages are that NNM is an appropriate tool also in the case of non-linear cause-effect relations and that interactions of the forcing mechanisms are allowed. In comparison to more sophisticated methods like general circulation models (GCM), the main advantage is that details of the physical background like feedbacks can be unknown. Neural networks learn from observations which reflect feedbacks implicitly. The disadvantage, of course, is that the physical background is neglected. In addition, the results prove to be sensitively dependent from the network architecture like the number of hidden neurons or the initialisation of learning parameters. We used a supervised backpropagation network (BPN) with three neuron layers, an unsupervised Kohonen network (KHN) and a combination of both called counterpropagation network (CPN). These concepts are tested in respect to their ability to simulate the observed global as well as hemispheric mean surface air temperature annual variations 1874 - 1993 if parameter time series of the following forcing mechanisms are incorporated : equivalent CO2 concentrations, tropospheric sulfate aerosol concentrations (both anthropogenic), volcanism, solar activity, and ENSO (all natural). It arises that in this way up to 83% of the observed temperature variance can be explained, significantly more than by MRA. The implication of the North Atlantic Oscillation does not improve these results. On a global average, the greenhouse gas (GHG) signal so far is assessed to be 0.9 - 1.3 K (warming), the sulfate signal 0.2 - 0.4 K (cooling), results which are in close similarity to the GCM findings published in the recent IPCC Report. The related signals of the natural forcing mechanisms considered cover amplitudes of 0.1 - 0.3 K. Our best NNM estimate of the GHG doubling signal amounts to 2.1K, equilibrium, or 1.7 K, transient, respectively.
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.
Invasive plant species are increasingly altering species composition and the functioning of ecosystems from a local to a global scale. The grass species Pennisetum setaceum has recently raised concerns as an invader on different archipelagos worldwide. Among these affected archipelagos are the Canary Islands, which are a hotspot of endemism. Consequently, conservation managers and stakeholders are interested in the potential spreading of this species in the archipelago. We identify the current extent of the suitable habitat for P. setaceum on the island of La Palma to assess how it affects island ecosystems, protected areas (PAs), and endemic plant species richness. We recorded in situ occurrences of P. setaceum from 2010 to 2018 and compiled additional ones from databases at a 500 m × 500 m resolution. To assess the current suitable habitat and possible distribution patterns of P. setaceum on the island, we built an ensemble model. We projected habitat suitability for island ecosystems and PAs and identified risks for total as well as endemic plant species richness. The suitable habitat for P. setaceum is calculated to cover 34.7% of the surface of La Palma. In open ecosystems at low to mid elevations, where native ecosystems are already under pressure by land use and human activities, the spread of the invader will likely lead to additional threats to endemic plant species. Forest ecosystems (e.g., broadleaved evergreen and coniferous forests) are not likely to be affected by the spread of P. setaceum because of its heliophilous nature. Our projection of suitable habitat of P. setaceum within ecosystems and PAs on La Palma supports conservationists and policymakers in prioritizing management and control measures and acts as an example for the potential threat of this graminoid invader on other islands.
Following votes in the Coniacian Working Group, the Cretaceous Subcommission and the International Commission on Stratigraphy, on May 1st, 2021, the International Union of Geological Sciences voted unanimously to ratify the Global Stratotype Section and Point (GSSP) proposal for the base of the Coniacian Stage of the Upper Cretaceous Series and Cretaceous System. The lower boundary of the Coniacian Stage is placed at the base of Bed 46 of the Salzgitter-Salder section in northern Germany. The boundary is defined by the first appearance of the inoceramid bivalve species Cremnoceramus deformis erectus (Meek) and complemented by the Navigation carbon isotope event. Additional data include the bivalve genus Didymotis, foraminifera, ammonite, nannofossil and organic-walled dinoflagellate cyst events. Three auxiliary sections (Słupia Nadbrzeżna, central Poland; Střeleč, Czech Republic; El Rosario, NE Mexico) supplement the details of the boundary record in various facies, and in differing geographic and biogeographic contexts.
The formation of secondary particles in the atmosphere accounts for more than half of global cloud condensation nuclei. Experiments at the CERN CLOUD (Cosmics Leaving OUtdoor Droplets) chamber have underlined the importance of ions for new particle formation, but quantifying their effect in the atmosphere remains challenging. By using a novel instrument setup consisting of two nano-particle counters, one of them equipped with an ion filter, we were able to further investigate the ion-related mechanisms of new particle formation. In autumn 2015, we carried out experiments at CLOUD on four systems of different chemical compositions involving monoterpenes, sulfuric acid, nitrogen oxides, and ammonia. We measured the influence of ions on the nucleation rates under precisely controlled and atmospherically relevant conditions. Our results indicate that ions enhance the nucleation process when the charge is necessary to stabilize newly formed clusters, i.e. in conditions where neutral clusters are unstable. For charged clusters that were formed by ion-induced nucleation, we were able to measure, for the first time, their progressive neutralization due to recombination with oppositely charged ions. A large fraction of the clusters carried a charge at 1.2 nm diameter. However, depending on particle growth rates and ion concentrations, charged clusters were largely neutralized by ion–ion recombination before they grew to 2.2 nm. At this size, more than 90 % of particles were neutral. In other words, particles may originate from ion-induced nucleation, although they are neutral upon detection at diameters larger than 2.2 nm. Observations at Hyytiälä, Finland, showed lower ion concentrations and a lower contribution of ion-induced nucleation than measured at CLOUD under similar conditions. Although this can be partly explained by the observation that ion-induced fractions decrease towards lower ion concentrations, further investigations are needed to resolve the origin of the discrepancy.
A new method for size-resolved chemical analysis of nucleation mode aerosol particles (size range from ∼10 to ∼30 nm) is presented. The Thermal Desorption Differential Mobility Analyzer (TD-DMA) uses an online, discontinuous principle. The particles are charged, a specific size is selected by differential mobility analysis and they are collected on a filament by electrostatic precipitation. Subsequently, the sampled mass is evaporated in a clean carrier gas and analyzed by a chemical ionization mass spectrometer. Gas-phase measurements are performed with the same mass spectrometer during the sampling of particles. The characterization shows reproducible results, with a particle size resolution of 1.19 and the transmission efficiency for 15 nm particles being slightly above 50 %. The signal from the evaporation of a test substance can be detected starting from 0.01 ng and shows a linear response in the mass spectrometer. Instrument operation in the range of pg m−3 is demonstrated by an example measurement of 15 nm particles produced by nucleation from dimethylamine, sulfuric acid and water.
A new method for size resolved chemical analysis of nucleation mode aerosol particles (size range from ~10 to ~30 nm) is presented. The Thermal Desorption Differential Mobility Analyzer (TD-DMA) uses an online, discontinuous principle. The particles are charged, a specific size is selected by differential mobility analysis and they are collected on a filament by electrostatic precipitation. Subsequently, the sampled mass is evaporated in a clean carrier gas and analyzed by a chemical ionization mass spectrometer. Gas phase measurements are performed with the same mass spectrometer during the sampling of particles. The characterization shows reproducible results, with a particle size resolution of 1.19 and the transmission efficiency for 15 nm particles being slightly above 50 %. The signal from the evaporation of a test substance can be detected starting from 0.01 ng and shows a linear response in the mass spectrometer. Instrument operation in the range of pg/m3 is demonstrated by an example measurement of 15 nm particles produced by nucleation from dimethylamine, sulfuric acid and water.
We present a study characterizing aerosol particles resulting from a skyscraper blasting. High mass concentrations with a maximum of 844.9 μg m-3 were present for a short time period of approximately 15 minutes. They result in a day mean of 32.6 μg m-3 compared to a 27.6 μg m-3 background not exceeding the 50 μg m-3 EU maximum permissive value. The increase in particle number concentration was less pronounced with a maximum concentration of 6.9 ⋅ 104 cm-3 compared to the local background value of 1.8 ⋅ 104 cm-3. The size-resolved number concentration shows a single mode of ultrafine particles at approximately 93 nm. The spatial distribution of deposited dust was investigated with Bergerhoff glass collection vessels, showing a decrease with distance. In the deposited dust samples the concentrations of twelve metals was determined, non of them exceeded the regional background concentrations significantly. The chemical composition of individual particles emitted by the demolition was studied by Scanning Electron Microscopy. They were mainly concrete and steel particles, with 60% calcium carbonates, 19% calcium sulfates, 19% silicates and 2% steel. In energy-dispersive X-Ray Spectroscopy, no fibers like asbestos were observed. Using a broad spectrum of instruments and methods, we obtain comprehensive characterization of the particles emitted by the demolition.
Atmospheric nanoaerosols have extensive effects on the Earth’s climate and human health. This cumulative work focuses on the development and characterization of instrumentation for measuring various parameters of atmospheric nanoaerosols, and its use to understand new particle formation from organic precursors. The principal research question is, how the chemical composition of nanoaerosol particles can be measured and how atmospheric chemistry influences aerosol processes, especially new particle formation and growth. Therefore, nanoaerosols are investigated under various aspects. More specifically, an instrument is developed to analyze nanoparticles, and field as well as chamber studies are conducted.
The main project is the instrument development of the Thermal Desorption Differential Mobility Analyzer (TD-DMA, project 1, Wagner et al. (2018)). This instrument analyzes the chemical composition of small aerosol particles. By characterization and testing in chamber experiments, it is proven to be suitable for the analysis of freshly nucleated particles.
The second project (Wagner et al. (2017)) applies a broad spectrum of aerosol measurement instruments for the characterization of aerosol particles produced by a skyscraper blasting. A comprehensive picture of the particle population emitted by the demolition is obtained.
Project 3 (K¨urten et al. (2016)) is also an ambient aerosol measurement, focusing of new particle formation in a rural area in central Germany, and the ability of a negative nitrate CI-APi-TOF to detect various substances in atmosphere. Project 4 (Heinritzi et al. (2016)) is a characterization of the negative nitrate CI-APi-TOF used in projects 1, 3, 5, 6, 7 and 8. The following projects focus on understanding new particle formation from atmospherically abundant organic precursors. Key instruments comprise the negative nitrate CI-APiTOF for gas-phase measurements of the nucleating species, and various sizing and counting instruments for quantifying the particle formation and growth. Project 5 (Kirkby et al. (2016)) shows that biogenic organic compounds formed from alpha-pinene can nucleate on their own without the influence of e.g. sulfuric acid. Project 6 (Tr¨ostl et al. (2016)) describe the subsequent growth of these particles. Project 7 (Stolzenburg et al. (2018)) covers the temperature dependence of this growth and in project 8 (Heinritzi et al. (2018)), the suppressing influence of isoprene on the new particle formation is assessed.