ALBERT

Description: Many local governments in Germany aim to reach Renewable Energy Self-Sufficiency (RESS) in their municipalities. In this context, ambitious time horizons for reaching this goal make it necessary to address the question of how less absolute energy can be consumed. The topic of energy conservation in scientific literature is very controversially discussed and in fact it is not clear which measures in the long term contribute to real reductions in energy demand. Therefore, in this paper, we do not determine how energy conservation should be achieved. Instead, we reconstruct, through an inductive longitudinal study, why energy conservation was integrated into the general principles of a municipality that wished to reach “RESS” by the year 2020 and considerably reduce energy demand. At the same time, we looked at the question of how energy conservation was conceptualized by local actors and which strategies, instruments, and activities were used to reach the goal. We found that environmentally concerned citizens brought the idea of energy conservation into the political arena. However, it was not until energy prices rose, regulations developed on a national level, subsidies for energy conservation emerged, and actions addressing the issue were seen by many local actors as adding value to the unique character the municipality gained by their RESS activities, that the actual subject was considered relevant in the municipality.

Description: The change of conventional energy systems to a system mainly based on renewable energies is occurring in many parts of the world. A processual analysis of three case studies from regions in Germany that are moving towards renewable energy self-sufficiency were conducted in order to better understand this process of socio-technical change. This paper scrutinizes the role of actors and their activities, which are driving the change of the local energy system. Three discrete distinguishable phases of this change were found: pioneer phase, pivotal network phase, and extended network and emerging market dynamic phase. Each phase can be characterized by the type of actor, their specific activities, artifacts involved, and their underlying motives. We suggest using the phase model as a heuristic instrument to identify the elements which shape socio-technical change.

Description: The change of conventional energy systems to a system mainly based on renewable energies is occurring in many parts of the world. A processual analysis of three case studies from regions in Germany that are moving towards renewable energy self-sufficiency were conducted in order to better understand this process of socio-technical change. This paper scrutinizes the role of actors and their activities, which are driving the change of the local energy system. Three discrete distinguishable phases of this change were found: pioneer phase, pivotal network phase, and extended network and emerging market dynamic phase. Each phase can be characterized by the type of actor, their specific activities, artifacts involved, and their underlying motives. We suggest using the phase model as a heuristic instrument to identify the elements which shape socio-technical change.

Description: The transformation of the present energy system into a sustainable one is discussed worldwide. This is also mirrored in a vivid debate in the scientific literature [1–3]. Self-sufficiency attained with the help of electricity, heat, and fuel from renewable energy (RE) in combination with energy saving is seen as one way to establish a sustainable energy system, e.g., [4,5]. Many communities and regions in different countries are facing the challenge of such a transformation of their energy system, and have taken up the objective of achieving energy self-sufficiency through the use of renewables [4,6–8]. [...]

Description: An estimated 0.5–1 billion people globally have inadequate intakes of selenium (Se), due to a lack of bioavailable Se in agricultural soils. Deposition from the atmosphere, especially through precipitation, is an important source of Se to soils. However, very little is known about the atmospheric cycling of Se. It has therefore been difficult to predict how far Se travels in the atmosphere and where it deposits. To answer these questions, we have built the first global atmospheric Se model by implementing Se chemistry in an aerosol–chemistry–climate model, SOCOL-AER (modeling tools for studies of SOlar Climate Ozone Links – aerosol). In the model, we include information from the literature about the emissions, speciation, and chemical transformation of atmospheric Se. Natural processes and anthropogenic activities emit volatile Se compounds, which oxidize quickly and partition to the particulate phase. Our model tracks the transport and deposition of Se in seven gas-phase species and 41 aerosol tracers. However, there are large uncertainties associated with many of the model's input parameters. In order to identify which model uncertainties are the most important for understanding the atmospheric Se cycle, we conducted a global sensitivity analysis with 34 input parameters related to Se chemistry, Se emissions, and the interaction of Se with aerosols. In the first bottom-up estimate of its kind, we have calculated a median global atmospheric lifetime of 4.4 d (days), ranging from 2.9 to 6.4 d (2nd–98th percentile range) given the uncertainties of the input parameters. The uncertainty in the Se lifetime is mainly driven by the uncertainty in the carbonyl selenide (OCSe) oxidation rate and the lack of tropospheric aerosol species other than sulfate aerosols in SOCOL-AER. In contrast to uncertainties in Se lifetime, the uncertainty in deposition flux maps are governed by Se emission factors, with all four Se sources (volcanic, marine biosphere, terrestrial biosphere, and anthropogenic emissions) contributing equally to the uncertainty in deposition over agricultural areas. We evaluated the simulated Se wet deposition fluxes from SOCOL-AER with a compiled database of rainwater Se measurements, since wet deposition contributes around 80 % of total Se deposition. Despite difficulties in comparing a global, coarse-resolution model with local measurements from a range of time periods, past Se wet deposition measurements are within the range of the model's 2nd–98th percentiles at 79 % of background sites. This agreement validates the application of the SOCOL-AER model to identifying regions which are at risk of low atmospheric Se inputs. In order to constrain the uncertainty in Se deposition fluxes over agricultural soils, we should prioritize field campaigns measuring Se emissions, rather than laboratory measurements of Se rate constants.

Description: We developed the pycraf Python package, which provides functions and procedures for various tasks related to spectrum-management compatibility studies. This includes an implementation of ITU-R Rec. P.452 (ITU-R, 2015), which allows to calculate the path attenuation arising from the distance and terrain properties between an interferer and the victim service. A typical example would be the calculation of interference levels at a radio telescope produced from a radio broadcasting tower. Furthermore, pycraf provides functionality to calculate atmospheric attenuation as proposed in ITU-R Rec. P.676 (ITU-R, 2013).Using the rich ecosystem of scientific Python libraries and our pycraf package, we performed a large number of compatibility studies. Here, we will highlight a recent case study, where we analysed the potential harm that the next-generation cell-phone standard 5G could bring to observations at a radio observatory. For this we implemented a Monte-Carlo simulation to deal with the quasi-statistical spatial distribution of base stations and user devices around the radio astronomy station.

Description: The rewetting of drained peatlands alters peat geochemistry and often leads to sustained elevated methane emission. Although this methane is produced entirely by microbial activity, the distribution and abundance of methane-cycling microbes in rewetted peatlands, especially in fens, is rarely described. In this study, we compare the community composition and abundance of methane-cycling microbes in relation to peat porewater geochemistry in two rewetted fens in northeastern Germany, a coastal brackish fen and a freshwater riparian fen, with known high methane fluxes. We utilized 16S rRNA high-throughput sequencing and quantitative polymerase chain reaction (qPCR) on 16S rRNA, mcrA, and pmoA genes to determine microbial community composition and the abundance of total bacteria, methanogens, and methanotrophs. Electrical conductivity (EC) was more than 3 times higher in the coastal fen than in the riparian fen, averaging 5.3 and 1.5 mS cm−1, respectively. Porewater concentrations of terminal electron acceptors (TEAs) varied within and among the fens. This was also reflected in similarly high intra- and inter-site variations of microbial community composition. Despite these differences in environmental conditions and electron acceptor availability, we found a low abundance of methanotrophs and a high abundance of methanogens, represented in particular by Methanosaetaceae, in both fens. This suggests that rapid (re)establishment of methanogens and slow (re)establishment of methanotrophs contributes to prolonged increased methane emissions following rewetting.

Description: An estimated 0.5–1 billion people globally have inadequate intakes of selenium (Se), due to a lack of bioavailable Se in agricultural soils. Deposition from the atmosphere, especially through precipitation, is an important source of Se to soils. However, very little is known about the atmospheric cycling of Se. It has therefore been difficult to predict how far Se travels in the atmosphere and where it deposits. To answer these questions, we have built the first global atmospheric Se model by implementing Se chemistry into an aerosol–chemistry–climate model, SOCOL-AER. In the model, we include information from the literature about the emissions, speciation, and chemical transformation of atmospheric Se. Natural processes and anthropogenic activities emit volatile Se compounds, which oxidize quickly and partition to the particulate phase. Our model tracks the transport and deposition of Se in 7 gas-phase species and 41 aerosol tracers. However, there are large uncertainties associated with many of the model's input parameters. In order to identify which model uncertainties are the most important for understanding the atmospheric Se cycle, we conducted a global sensitivity analysis with 34 input parameters related to Se chemistry, Se emissions, and the interaction of Se with aerosols. In the first bottom-up estimate of its kind, we have calculated a median global atmospheric lifetime of 4.4 d (days), ranging from 2.9–6.4 d (2nd–98th percentile) given the uncertainties of the input parameters. The uncertainty in the Se lifetime is mainly driven by the uncertainty in the carbonyl selenide (OCSe) oxidation rate and the lack of tropospheric aerosol species other than sulfate aerosols in SOCOL-AER. In contrast to uncertainties in Se lifetime, the uncertainty in deposition flux maps are governed by Se emission factors, with all four Se sources (volcanic, marine biosphere, terrestrial biosphere, and anthropogenic emissions) contributing equally to the uncertainty in deposition over agricultural areas. We evaluated the simulated Se wet deposition fluxes from SOCOL-AER with a compiled database of rainwater Se measurements, since wet deposition contributes around 80 % of total Se deposition. Despite difficulties in comparing a global, coarse resolution model with local measurements from a range of time periods, past Se wet deposition measurements are within the range of the model's 2nd–98th percentile at 79 % of background sites. This agreement validates the application of the SOCOL-AER model to identifying regions which are at risk of low atmospheric Se inputs. In order to constrain the uncertainty in Se deposition fluxes over agricultural soils we should prioritize field campaigns measuring Se emissions, rather than laboratory measurements of Se rate constants.

Description: SOCOL-AERv1 was developed as an aerosol–chemistry–climate model to study the stratospheric sulfur cycle and its influence on climate and the ozone layer. It includes a sectional aerosol model that tracks the sulfate particle size distribution in 40 size bins, between 0.39 nm and 3.2 µm. Sheng et al. (2015) showed that SOCOL-AERv1 successfully matched observable quantities related to stratospheric aerosol. In the meantime, SOCOL-AER has undergone significant improvements and more observational datasets have become available. In producing SOCOL-AERv2 we have implemented several updates to the model: adding interactive deposition schemes, improving the sulfate mass and particle number conservation, and expanding the tropospheric chemistry scheme. We compare the two versions of the model with background stratospheric sulfate aerosol observations, stratospheric aerosol evolution after Pinatubo, and ground-based sulfur deposition networks. SOCOL-AERv2 shows similar levels of agreement as SOCOL-AERv1 with satellite-measured extinctions and in situ optical particle counter (OPC) balloon flights. The volcanically quiescent total stratospheric aerosol burden simulated in SOCOL-AERv2 has increased from 109 Gg of sulfur (S) to 160 Gg S, matching the newly available satellite estimate of 165 Gg S. However, SOCOL-AERv2 simulates too high cross-tropopause transport of tropospheric SO2 and/or sulfate aerosol, leading to an overestimation of lower stratospheric aerosol. Due to the current lack of upper tropospheric SO2 measurements and the neglect of organic aerosol in the model, the lower stratospheric bias of SOCOL-AERv2 was not further improved. Model performance under volcanically perturbed conditions has also undergone some changes, resulting in a slightly shorter volcanic aerosol lifetime after the Pinatubo eruption. With the improved deposition schemes of SOCOL-AERv2, simulated sulfur wet deposition fluxes are within a factor of 2 of measured deposition fluxes at 78 % of the measurement stations globally, an agreement which is on par with previous model intercomparison studies. Because of these improvements, SOCOL-AERv2 will be better suited to studying changes in atmospheric sulfur deposition due to variations in climate and emissions.

Description: The interface between climate and ecosystem structure and function is incompletely understood, partly because few ecological records start before the recent warming phase. Here, we analyse an exceptional 100-yr long record of the great tit (Parus major) population in Switzerland in relation to climate and habitat phenology. Using structural equation analysis, we demonstrate an uninterrupted cascade of significant influences of the large-scale atmospheric circulation (North-Atlantic Oscillation, NAO, and North-sea – Caspian Pattern, NCP) on habitat and breeding phenology, and further on fitness-relevant life history traits within great tit populations. We then apply the relationships of this analysis to reconstruct the circulation-driven component of fluctuations in great tit breeding phenology and productivity on the basis of new seasonal NAO and NCP indices back to 1500 AD. According to the structural equation model, the multi-decadal oscillation of the atmospheric circulation likely led to substantial variation in habitat phenology, productivity and consequently, tit population fluctuations with minima during the "Maunder Minimum" (∼ 1650–1720) and the Little Ice Age Type Event I (1810–1850). The warming since 1975 was not only related with a quick shift towards earlier breeding, but also with the highest productivity since 1500, and thus, the impact of the NAO and NCP has contributed to an unprecedented increase of the population. A verification of the structural equation model against two independent data series (1970–2000 and 1750–1900) corroborates that the retrospective model reliably depicts the major long-term NAO/NCP impact on ecosystem parameters. The results suggest a complex cascade of climate effects beginning at a global scale and ending at the level of individual life histories. This sheds light on how large-scale climate conditions substantially affect major life history parameters within a population, and thus influence key ecosystem parameters at the scale of centuries.