TY  - GEN
A1  - Murawski, Aline
A1  - Bürger, Gerd
A1  - Vorogushyn, Sergiy
A1  - Merz, Bruno
T1  - Can local climate variability be explained by weather patterns?
BT  - a multi-station evaluation for the Rhine basin
T2  - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe
N2  - To understand past flood changes in the Rhine catchment and in particular the role of anthropogenic climate change in extreme flows, an attribution study relying on a proper GCM (general circulation model) downscaling is needed. A downscaling based on conditioning a stochastic weather generator on weather patterns is a promising approach. This approach assumes a strong link between weather patterns and local climate, and sufficient GCM skill in reproducing weather pattern climatology. These presuppositions are unprecedentedly evaluated here using 111 years of daily climate data from 490 stations in the Rhine basin and comprehensively testing the number of classification parameters and GCM weather pattern characteristics. A classification based on a combination of mean sea level pressure, temperature, and humidity from the ERA20C reanalysis of atmospheric fields over central Europe with 40 weather types was found to be the most appropriate for stratifying six local climate variables. The corresponding skill is quite diverse though, ranging from good for radiation to poor for precipitation. Especially for the latter it was apparent that pressure fields alone cannot sufficiently stratify local variability. To test the skill of the latest generation of GCMs from the CMIP5 ensemble in reproducing the frequency, seasonality, and persistence of the derived weather patterns, output from 15 GCMs is evaluated. Most GCMs are able to capture these characteristics well, but some models showed consistent deviations in all three evaluation criteria and should be excluded from further attribution analysis.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 525 
KW  - athmospheric circulation patterns
KW  - stochastic rainfall model
KW  - within-type variability
KW  - river Rhine
KW  - precipitation
KW  - temperature
KW  - trends
KW  - classification
KW  - Europe
KW  - scenarios
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-410155
SN  - 1866-8372
IS  - 525
ER  - 
TY  - JOUR
A1  - Wang, Hao
A1  - Wang, Xue-jiang
A1  - Wang, Wei-shi
A1  - Yan, Xiang-bo
A1  - Xia, Peng
A1  - Chen, Jie
A1  - Zhao, Jian-fu
T1  - Modeling and optimization of struvite recovery from wastewater and reusing for heavy metals immobilization in contaminated soil
JF  - Journal of chemical technology & biotechnology
N2  - BACKROUND: Few studies have been carried out to connect nutrients recovery from wastewater and heavy metals immobilization in contaminated soil. To achieve the goal, ammonia nitrogen (AN) and phosphorus (P) were recovered from rare-earth wastewater by using the formation of struvite, which was used as the amendment with plant ash for copper, lead and chromium immobilization. RESULTS: AN removal efficiency and residual P reached 95.32 +/- 0.73% and 6.14 +/- 1.72mgL(-1) under optimal conditions: pH= 9.0, n(Mg): n(N): n(P)= 1.2: 1: 1.1, which were obtained using response surface methodology (RSM). The minimum available concentrations of Cu, Pb and Cr (CPC) separately reduced to 320.82 mg kg(-1), 190.77 mg kg(-1) and 121.46 mg kg(-1) with increasing immobilization time at the mass ratio of phosphate precipitate (PP)/plant ash (PA) of 1: 3. Humic acid (HA) and fulvic acid (FA) were beneficial to immobilize Cu, both of which showed no effect or even a negative effect on Pb and Cr immobilization.
KW  - precipitation
KW  - experimental design
KW  - immobilization
KW  - heavy metals
KW  - environmental remediation
Y1  - 2016
U6  - https://doi.org/10.1002/jctb.4931
SN  - 0268-2575
SN  - 1097-4660
VL  - 91
SP  - 3045
EP  - 3052
PB  - Wiley-Blackwell
CY  - Hoboken
ER  -