Augustins dogmatische formulierung der trinitatslehre und die theologischen voraussetzungen seines ansatzes zur erkenntnis dertrinitat

This thesis is based on a careful reading and analysis of St. Augustine's "De Trinitate". Concentrating on the interpretation of essential passages much more than on the evaluation and discussion of secondary material, it deals with St. Augustines doctrine of the trinity with regard to the following two aspects: On the one hand, it tries to understand St. Augustine's attempt to formulate the doctrine of the trinity as it was presented to him in the orthodox teaching of his church (i.e. the Nicene Creed). His main problems were how to relate unity and trinity in God to each other as well as how to combine the innertrinitarian and the extratrinitarian aspect. The author comes to the conclusion that the contents of St. Augustin's teaching is drawn from the extratrinitarian aspect, i.e. from the way how God reveals himself to man in the course of the history of salvation, much more than one would generally think of a theologian of the Western Church (Ch. 2). On the other hand, looking at the second half of "De Trinitate" (book VIII-XV), the thesis considers the important fact that St. Augustine did not only want to formulate a dogmatical issue but also to show the possibility of man to understand, and thus draw nearer to, the trinity in a personal and existential act of knowing. To explain this, some main lines of St. Augustine's theology had to be considered in their relation to this topic: his teaching of God as the supreme being and creator of the world (Ch. 3), his teaching of man as the supreme of God's creatures, as "imago dei", and as the sinner who is unconsciously dependent on God's preserving grace (Ch. 4), and, finally, some aspects of his christology (Ch, 5), These two parts of the thesis are preceded by an introductory chapter (Ch, 1) which looks at St. Augustine from the point of view of his biography, of the history of doctrine, and of his philosophical and theological preconditions

Climate and air quality impacts due to mitigation of non-methane near-term climate forcers

It is important to understand how future environmental policies will impact both climate change and air pollution. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone, and precursor gases, should improve air quality, NTCF reductions will also impact climate. Prior assessments of the impact of NTCF mitigation on air quality and climate have been limited. This is related to the idealized nature of some prior studies, simplified treatment of aerosols and chemically reactive gases, as well as a lack of a sufficiently large number of models to quantify model diversity and robust responses. Here, we quantify the 2015-2055 climate and air quality effects of non-methane NTCFs using nine state-of-the-art chemistry-climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with weak (SSP3-7.0) versus strong (SSP3-7.0-lowNTCF) levels of air quality control measures. As SSP3-7.0 lacks climate policy and has the highest levels of NTCFs, our results (e.g., surface warming) represent an upper bound. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface fine particulate matter (PM2:5) and ozone (O3) decrease by 2:20:32 ugm3 and 4:60:88 ppb, respectively (changes quoted here are for the entire 2015-2055 time period; uncertainty represents the 95% confidence interval), over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0:250:12K and 0:030:012mmd1, respectively. Similarly, increases in extreme weather indices, including the hottest and wettest days, also occur. Regionally, the largest warming and wetting occurs over Asia, including central and north Asia (0:660:20K and 0:030:02mmd1), south Asia (0:470:16K and 0:170:09mmd1), and east Asia (0:460:20K and 0:150:06mmd1). Relatively large warming and wetting of the Arctic also occur at 0:590:36K and 0:040:02mmd1, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet climate mitigation goals. © Author(s) 2020. This work is distributed under the Creative Commons Attribution 4.0 License

Evaluation of global simulations of aerosol particle and cloud condensation nuclei number, with implications for cloud droplet formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24 % and -35 % for particles with dry diameters > 50 and > 120 nm, as well as -36 % and -34 % for CCN at supersaturations of 0.2 % and 1.0 %, respectively. However, they seem to behave differently for particles activating at very low supersaturations (<0.1 %) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N-3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2 % (CCN0.2) compared to that for N-3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120 nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40 % during winter and 20 % in summer. In contrast to the large spread in simulated aerosol particle and CCN number concentrations, the CDNC derived from simulated CCN spectra is less diverse and in better agreement with CDNC estimates consistently derived from the observations (average NMB -13 % and -22 % for updraft velocities 0.3 and 0.6 m s(-1), respectively). In addition, simulated CDNC is in slightly better agreement with observationally derived values at lower than at higher updraft velocities (index of agreement 0.64 vs. 0.65). The reduced spread of CDNC compared to that of CCN is attributed to the sublinear response of CDNC to aerosol particle number variations and the negative correlation between the sensitivities of CDNC to aerosol particle number concentration (partial derivative N-d/partial derivative N-a) and to updraft velocity (partial derivative N-d/partial derivative w). Overall, we find that while CCN is controlled by both aerosol particle number and composition, CDNC is sensitive to CCN at low and moderate CCN concentrations and to the updraft velocity when CCN levels are high. Discrepancies are found in sensitivities partial derivative N-d/partial derivative N-a and partial derivative N-d/partial derivative w; models may be predisposed to be too "aerosol sensitive" or "aerosol insensitive" in aerosol-cloud-climate interaction studies, even if they may capture average droplet numbers well. This is a subtle but profound finding that only the sensitivities can clearly reveal and may explain intermodel biases on the aerosol indirect effect.Peer reviewe

Aerosol indirect effects

Aerosol indirect effects continue to constitute one of the most important uncertainties for anthropogenic climate perturbations. Within the international AEROCOM initiative, the representation of aerosol-cloud-radiation interactions in ten different general circulation models (GCMs) is evaluated using three satellite datasets. The focus is on stratiform liquid water clouds since most GCMs do not include ice nucleation effects, and none of the model explicitly parameterises aerosol effects on convective clouds. We compute statistical relationships between aerosol optical depth (tau a) and various cloud and radiation quantities in a manner that is consistent between the models and the satellite data. cloud droplet number concentration (N d) compares relatively well to the satellite data at least over the ocean. The relationship between (tau a) and liquid water path is simulated much too strongly by the models. This suggests that the implementation of the second aerosol indirect effect mainly in terms of an autoconversion parameterisation has to be revisited in the GCMs. A positive relationship between total cloud fraction (fcld) and tau a as found in the satellite data is simulated by the majority of the models, albeit less strongly than that in the satellite data in most of them. In a discussion of the hypotheses proposed in the literature to explain the satellite-derived strong fcld–tau a relationship, our results indicate that none can be identified as a unique explanation. Relationships similar to the ones found in satellite data between tau a and cloud top temperature or outgoing long-wave radiation (OLR) are simulated by only a few GCMs. The GCMs that simulate a negative OLR - tau a relationship show a strong positive correlation between tau a and fcld. The short-wave total aerosol radiative forcing as simulated by the GCMs is strongly influenced by the simulated anthropogenic fraction of tau a, and parameterisation assumptions such as a lower bound on Nd. Nevertheless, the strengths of the statistical relationships are good predictors for the aerosol forcings in the models. An estimate of the total short-wave aerosol forcing inferred from the combination of these predictors for the modelled forcings with the satellite-derived statistical relationships yields a global annual mean value of −1.5±0.5Wm−2. In an alternative approach, the radiative flux perturbation due to anthropogenic aerosols can be broken down into a component over the cloud-free portion of the globe (approximately the aerosol direct effect) and a component over the cloudy portion of the globe (approximately the aerosol indirect effect). An estimate obtained by scaling these simulated clearand cloudy-sky forcings with estimates of anthropogenic tau a and satellite-retrieved Nd–tau a regression slopes, respectively, yields a global, annual-mean aerosol direct effect estimate of −0.4±0.2Wm−2 and a cloudy-sky (aerosol indirect effect) estimate of −0.7±0.5Wm−2, with a total estimate of −1.2±0.4Wm−2

Evaluation of Global Simulations of Aerosol Particle and Cloud Condensation Nuclei Number, with Implications for Cloud Droplet Formation

A total of 16 global chemistry transport models and general circulation models have participated in this study; 14 models have been evaluated with regard to their ability to reproduce the near-surface observed number concentration of aerosol particles and cloud condensation nuclei (CCN), as well as derived cloud droplet number concentration (CDNC). Model results for the period 2011-2015 are compared with aerosol measurements (aerosol particle number, CCN and aerosol particle composition in the submicron fraction) from nine surface stations located in Europe and Japan. The evaluation focuses on the ability of models to simulate the average across time state in diverse environments and on the seasonal and short-term variability in the aerosol properties. There is no single model that systematically performs best across all environments represented by the observations. Models tend to underestimate the observed aerosol particle and CCN number concentrations, with average normalized mean bias (NMB) of all models and for all stations, where data are available, of -24% and -35% for particles with dry diameters > 50 and > 120nm, as well as -36% and -34% for CCN at supersaturations of 0.2% and 1.0%, respectively. However, they seem to behave differently for particles activating at very low supersaturations (< 0.1%) than at higher ones. A total of 15 models have been used to produce ensemble annual median distributions of relevant parameters. The model diversity (defined as the ratio of standard deviation to mean) is up to about 3 for simulated N3 (number concentration of particles with dry diameters larger than 3 nm) and up to about 1 for simulated CCN in the extra-polar regions. A global mean reduction of a factor of about 2 is found in the model diversity for CCN at a supersaturation of 0.2% (CCN(0.2)) compared to that for N3, maximizing over regions where new particle formation is important. An additional model has been used to investigate potential causes of model diversity in CCN and bias compared to the observations by performing a perturbed parameter ensemble (PPE) accounting for uncertainties in 26 aerosol-related model input parameters. This PPE suggests that biogenic secondary organic aerosol formation and the hygroscopic properties of the organic material are likely to be the major sources of CCN uncertainty in summer, with dry deposition and cloud processing being dominant in winter. Models capture the relative amplitude of the seasonal variability of the aerosol particle number concentration for all studied particle sizes with available observations (dry diameters larger than 50, 80 and 120nm). The short-term persistence time (on the order of a few days) of CCN concentrations, which is a measure of aerosol dynamic behavior in the models, is underestimated on average by the models by 40% during winter and 20% in summer

Climate and air quality impacts due to mitigation of non-methane near-term climate forcers

Over the next few decades, policies that optimally address both climate change and air quality are essential. Although targeting near-term climate forcers (NTCFs), defined here as aerosols, tropospheric ozone and precursor gases (but not methane), should improve air quality, NTCF reductions will also impact climate. How future policies affect the abundance of NTCFs and their impact on climate and air quality remains uncertain. Here, we quantify the 2015–2055 climate and air quality effects of non-methane NTCFs using state-of-the-art chemistry-climate model simulations conducted for the Aerosol and Chemistry Model Intercomparison Project (AerChemMIP). Simulations are driven by two future scenarios featuring similar increases in greenhouse gases (GHGs) but with weak versus strong levels of air quality control measures. Unsurprisingly, we find significant improvements in air quality under NTCF mitigation (strong versus weak air quality controls). Surface ozone (O3) and fine particulate matter (PM2.5) decrease by −15 % and −25 %, respectively, over global land surfaces, with larger reductions in some regions including south and southeast Asia. Non-methane NTCF mitigation, however, leads to additional climate change due to the removal of aerosol which causes a net warming effect, including global mean surface temperature and precipitation increases of 0.24 K and 1.1 %, respectively, with similar increases in extreme weather indices. Regionally, the largest warming and wetting trends occur over Asia, including central and north Asia (0.56 K and 2.1 %), south Asia (0.48 K and 4.6 %) and east Asia (0.44 K and 4.7 %). Relatively large warming and wetting of the Arctic also occurs at 0.41 K and 2.1 %, respectively. Similar surface warming occurs in model simulations with aerosol-only mitigation, implying weak cooling due to ozone reductions. Our findings suggest that future policies that aggressively target non-methane NTCF reductions will improve air quality, but will lead to additional surface warming, particularly in Asia and the Arctic. Policies that address other NTCFs including methane, as well as carbon dioxide emissions, must also be adopted to meet mitigation goals

Soot microphysical effects on liquid clouds, a multi-model investigation

We use global models to explore the microphysical effects of carbonaceous aerosolson clouds. Although absorption of solar radiation by soot warms the atmosphere, sootmay cause climate cooling due to its contribution to cloud condensation nuclei (CCN)and therefore cloud brightness. Six global models conducted three soot experiments; four of the models had detailed aerosol microphysical schemes. The average cloudradiative response to biofuel soot (black and organic carbon), including both indirectand semi-direct effects, is−0.11 Wm−2, comparable in size but opposite in sign tothe respective direct effect. In a more idealized fossil fuel black carbon experiment,some models calculated a positive cloud response because soot provides a deposition sink for sulfuric and nitric acids and secondary organics, decreasing nucleation andevolution of viable CCN. Biofuel soot particles were also typically assumed to be largerand more hygroscopic than for fossil fuel soot and therefore caused more negativeforcing, as also found in previous studies. Diesel soot (black and organic carbon)experiments had relatively smaller cloud impacts with five of the models<±0.06 Wm−2 from clouds. The results are subject to the caveats that variability among models,and regional and interrannual variability for each model, are large. This comparisontogether with previously published results stresses the need to further constrain aerosolmicrophysical schemes. The non-linearities resulting from the competition of opposingeffects on the CCN population make it difficult to extrapolate from idealized experiments to likely impacts of realistic potential emission changes.ISSN:1680-7375ISSN:1680-736

Soot microphysical effects on liquid clouds, a multi-model investigation

We use global models to explore the microphysical effects of carbonaceous aerosols on liquid clouds. Although absorption of solar radiation by soot warms the atmosphere, soot may cause climate cooling due to its contribution to cloud condensation nuclei (CCN) and therefore cloud brightness. Six global models conducted three soot experiments; four of the models had detailed aerosol microphysical schemes. The average cloud radiative response to biofuel soot (black and organic carbon), including both indirect and semi-direct effects, is −0.11 Wm−2, comparable in size but opposite in sign to the respective direct effect. In a more idealized fossil fuel black carbon experiment, some models calculated a positive cloud response because soot provides a deposition sink for sulfuric and nitric acids and secondary organics, decreasing nucleation and evolution of viable CCN. Biofuel soot particles were also typically assumed to be larger and more hygroscopic than for fossil fuel soot and therefore caused more negative forcing, as also found in previous studies. Diesel soot (black and organic carbon) experiments had relatively smaller cloud impacts with five of the models <±0.06 Wm−2 from clouds. The results are subject to the caveats that variability among models, and regional and interrannual variability for each model, are large. This comparison together with previously published results stresses the need to further constrain aerosol microphysical schemes. The non-linearities resulting from the competition of opposing effects on the CCN population make it difficult to extrapolate from idealized experiments to likely impacts of realistic potential emission changes.ISSN:1680-7375ISSN:1680-736

Soot microphysical effects on liquid clouds, a multi-model investigation

We use global models to explore the microphysical effects of carbonaceous aerosols on liquid clouds. Although absorption of solar radiation by soot warms the atmosphere, soot may cause climate cooling due to its contribution to cloud condensation nuclei (CCN) and therefore cloud brightness. Six global models conducted three soot experiments; four of the models had detailed aerosol microphysical schemes. The average cloud radiative response to biofuel soot (black and organic carbon), including both indirect and semi-direct effects, is −0.11Wm−2, comparable in size but opposite in sign to the respective direct effect. In a more idealized fossil fuel black carbon experiment, some models calculated a positive cloud response because soot provides a deposition sink for sulfuric and nitric acids and secondary organics, decreasing nucleation and evolution of viable CCN. Biofuel soot particles were also typically assumed to be larger and more hygroscopic than for fossil fuel soot and therefore caused more negative forcing, as also found in previous studies. Diesel soot (black and organic carbon) experiments had relatively smaller cloud impacts with five of the models <±0.06Wm−2 from clouds. The results are subject to the caveats that variability among models, and regional and interrannual variability for each model, are large. This comparison together with previously published results stresses the need to further constrain aerosol microphysical schemes. The non-linearities resulting from the competition of opposing effects on the CCN population make it difficult to extrapolate from idealized experiments to likely impacts of realistic potential emission changes

Soot microphysical effects on liquid clouds, a multi-model investigation

We use global models to explore the microphysical effects of carbonaceous aerosols on liquid clouds. Although absorption of solar radiation by soot warms the atmosphere, soot may cause climate cooling due to its contribution to cloud condensation nuclei (CCN) and therefore cloud brightness. Six global models conducted three soot experiments; four of the models had detailed aerosol microphysical schemes. The average cloud radiative response to biofuel soot (black and organic carbon), including both indirect and semi-direct effects, is −0.11Wm−2, comparable in size but opposite in sign to the respective direct effect. In a more idealized fossil fuel black carbon experiment, some models calculated a positive cloud response because soot provides a deposition sink for sulfuric and nitric acids and secondary organics, decreasing nucleation and evolution of viable CCN. Biofuel soot particles were also typically assumed to be larger and more hygroscopic than for fossil fuel soot and therefore caused more negative forcing, as also found in previous studies. Diesel soot (black and organic carbon) experiments had relatively smaller cloud impacts with five of the models <±0.06Wm−2 from clouds. The results are subject to the caveats that variability among models, and regional and interrannual variability for each model, are large. This comparison together with previously published results stresses the need to further constrain aerosol microphysical schemes. The non-linearities resulting from the competition of opposing effects on the CCN population make it difficult to extrapolate from idealized experiments to likely impacts of realistic potential emission changes