scholarly journals Stock Model Based Bottom-up Accounting for Washing Machines: Worldwide Energy, Water and Greenhouse Gas Saving Potentials 2010–2030

2016 ◽  
Vol 53 (5) ◽  
pp. 410-416 ◽  
Author(s):  
Thomas Götz ◽  
Lena Tholen
Keyword(s):  
Greenhouse Gas ◽  
Bottom Up ◽  
Model Based ◽  
Washing Machines ◽  
Stock Model

scholarly journals Smells Like Teen Spirit—A Model to Generate Laundry-Associated Malodour In Vitro

2021 ◽  
Vol 9 (5) ◽  
pp. 974
Author(s):  
Marc-Kevin Zinn ◽  
Marco Singer ◽  
Dirk Bockmühl
Keyword(s):  
Volatile Compounds ◽  
Micrococcus Luteus ◽  
Dimethyl Disulfide ◽  
Bacterial Strains ◽  
Dimethyl Trisulfide ◽  
Model Based ◽  
Washing Machines ◽  
Staphylococcus Hominis

Although malodour formation on textiles and in washing machines has been reported to be a very relevant problem in domestic laundry, the processes leading to bad odours have not been studied intensively. In particular, the smell often described as “wet-and-dirty-dustcloth-like malodour” had not been reproduced previously. We developed a lab model based on a bacterial mixture of Micrococcus luteus, Staphylococcus hominis, and Corynebacterium jeikeium, which can produce this odour type and which might allow the detailed investigation of this problem and the development of counteractions. The model uses bacterial strains that have been isolated from malodourous textiles. We could also show that the three volatile compounds dimethyl disulfide, dimethyl trisulfide, and indole contribute considerably to the “wet-fabric-like” malodour. These substances were not only found to be formed in the malodour model but have already been identified in the literature as relevant malodourous substances.

A model-based approach to measuring denitrification and greenhouse gas production in lakes

2021 ◽  
Author(s):  
Juliet Falco Ajambo-Doherty
Keyword(s):  
Greenhouse Gas ◽  
Atmospheric Pressure ◽  
Schmidt Number ◽  
Spatial Scales ◽  
Gas Production ◽  
System Model ◽  
Biogeochemical Processes ◽  
Model Based ◽  
Temporal And Spatial ◽  
System Metabolism

An existing whole-system model based on changes in dissolved N₂ concentration was modified for lentic systems. Field validations carried out at Christie Lake in Dundas, ON and Turtle Pond in Stoney Creek, ON (Canada). New model inputs included air temperature, atmospheric pressure, relative humidity, wind velocity, and Schmidt number. Mont Carlo analysis was integrated into the model to better constrain error in model estimates of denitrification, whole-system metabolism, and greenhouse gas production. Denitrification rates ranged from -419-4415 µmol N.m-².h-¹ in Christie Lake and from 10-74 µmol N.m-².h-¹ in Turtle Pond. N₂O production ranged from 915-10,635 nmol N.m-².h-¹ in Christie Lake and from -344-131 nmol N.m-².h-¹ in Turtle Pond. The whole-system model allows for the examination of biogeochemical processes at ecologically significant temporal and spatial scales.

scholarly journals A bottom-up dynamic building stock model for residential energy transition: A case study for the Netherlands

2022 ◽  
Vol 306 ◽  
pp. 118060
Author(s):  
Xining Yang ◽  
Mingming Hu ◽  
Arnold Tukker ◽  
Chunbo Zhang ◽  
Tengfei Huo ◽  
...  
Keyword(s):  
The Netherlands ◽  
Energy Transition ◽  
Residential Energy ◽  
Building Stock ◽  
Bottom Up ◽  
Stock Model

scholarly journals Model-based analysis of greenhouse gas emission reduction potential through farm-scale digestion

2019 ◽  
Vol 181 ◽  
pp. 157-172 ◽  
Author(s):  
Tine L.I. Vergote ◽  
Wouter J.C. Vanrolleghem ◽  
Caroline Van der Heyden ◽  
Anke E.J. De Dobbelaere ◽  
Jeroen Buysse ◽  
...  
Keyword(s):  
Greenhouse Gas ◽  
Emission Reduction ◽  
Reduction Potential ◽  
Greenhouse Gas Emission ◽  
Gas Emission ◽  
Model Based ◽  
Emission Reduction Potential ◽  
Farm Scale ◽  
Greenhouse Gas Emission Reduction ◽  
Model Based Analysis

scholarly journals Logic Grammars for Diagnosis and Repair

2003 ◽  
Vol 12 (03) ◽  
pp. 227-248 ◽  
Author(s):  
Henning Christiansen ◽  
Veronica Dahl
Keyword(s):  
Natural Language ◽  
Error Detection ◽  
Specific Problem ◽  
Constraint Handling ◽  
Proof Of Concept ◽  
Top Down ◽  
Bottom Up ◽  
Model Based ◽  
Logic Grammars

We propose an abductive model based on Constraint Handling Rule Grammars (CHRGs) for detecting and correcting errors in problem domains that can be described in terms of strings of words accepted by a logic grammar. We provide a proof of concept for the specific problem of detecting and repairing natural language errors, in particular, those concerning feature agreement. Our methodology relies on grammar and string transformation in accordance with a user-defined dictionary of possible repairs. This transformation also serves as top-down guidance for our essentially bottom-up parser. With respect to previous approaches to error detection and repair, including those that also use constraints and/or abduction, our methodology is surprisingly simple while far-reaching and efficient.

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