scholarly journals A bottom-up spatially explicit methodology to estimate the space heating demand of the building stock at regional scale

2020 ◽  
Vol 206 ◽  
pp. 109581 ◽  
Author(s):  
Valentina D'Alonzo ◽  
Antonio Novelli ◽  
Roberto Vaccaro ◽  
Daniele Vettorato ◽  
Rossano Albatici ◽  
...  
Keyword(s):  
Regional Scale ◽  
Space Heating ◽  
Spatially Explicit ◽  
Building Stock ◽  
Bottom Up

Analysis of space heating demand in the Swiss residential building stock: Element-based bottom-up model of archetype buildings

2019 ◽  
Vol 184 ◽  
pp. 300-322 ◽  
Author(s):  
Kai Nino Streicher ◽  
Pierryves Padey ◽  
David Parra ◽  
Meinrad C. Bürer ◽  
Stefan Schneider ◽  
...  
Keyword(s):  
Residential Building ◽  
Space Heating ◽  
Building Stock ◽  
Bottom Up ◽  
Residential Building Stock

A stochastic bottom-up model for space heating and domestic hot water load profiles for German households

2016 ◽  
Vol 124 ◽  
pp. 120-128 ◽  
Author(s):  
David Fischer ◽  
Tobias Wolf ◽  
Johannes Scherer ◽  
Bernhard Wille-Haussmann
Keyword(s):  
Hot Water ◽  
Space Heating ◽  
Bottom Up ◽  
Water Load ◽  
Domestic Hot Water

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

Development of An Exposure Model for Bridge Structures in Northern Algeria

2018 ◽  
Author(s):  
Andrés Abarca ◽  
Ricardo Monteiro
Keyword(s):  
Risk Assessment ◽  
Large Scale ◽  
Risk Mitigation ◽  
Regional Scale ◽  
Mitigation Measures ◽  
Exposure Model ◽  
Building Stock ◽  
Earthquake Scenarios ◽  
Northern Algeria ◽  
Bridge Structures

In recent years, the use of large scale seismic risk assessment has become increasingly popular to evaluate the fragility of a specific region to an earthquake event, through the convolution of hazard, exposure and vulnerability. These studies tend to focus on the building stock of the region and sometimes neglect the evaluation of the infrastructure, which has great importance when determining the ability of a social group to attend to a disaster and to eventually resume normal activities. This study, developed within the scope of the EU-funded project ITERATE (Improved Tools for Disaster Risk Mitigation in Algeria), focuses on the proposal of an exposure model for bridge structures in Northern Algeria. The proposed model was developed using existing national data surveys, as well as satellite information and field observations. As a result, the location and detailed characterization of a significant share of the Algeria roadway bridge inventory was developed, as well as the definition of a taxonomy that is able to classify the most common structural systems used in Algerian bridge construction. The outcome of this study serves as input to estimate the fragility of the bridge infrastructure inventory and, furthermore, to the overall risk assessment of the Northern Algerian region. Such fragility model will, in turn, enable the evaluation of earthquake scenarios at a regional scale and provide valuable information to decision makers for the implementation of risk mitigation measures.

A review of bottom-up building stock models for energy consumption in the residential sector

2010 ◽  
Vol 45 (7) ◽  
pp. 1683-1697 ◽  
Author(s):  
M. Kavgic ◽  
A. Mavrogianni ◽  
D. Mumovic ◽  
A. Summerfield ◽  
Z. Stevanovic ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Building Stock ◽  
Bottom Up ◽  
Residential Sector

scholarly journals EXPLUME v1.0: a model for personal exposure to ambient O<sub>3</sub> and PM<sub>2.5</sub>

2020 ◽  
Vol 13 (3) ◽  
pp. 1075-1094 ◽  
Author(s):  
Myrto Valari ◽  
Konstandinos Markakis ◽  
Emilie Powaga ◽  
Bernard Collignan ◽  
Olivier Perrussel
Keyword(s):  
Regional Scale ◽  
Personal Exposure ◽  
Exposure Model ◽  
Population Exposure ◽  
Population Mobility ◽  
Building Stock ◽  
Annual Average ◽  
Time Activity ◽  
Road Tunnels ◽  
Pm2.5 Exposure

Abstract. This paper presents the first version of the regional-scale personal exposure model EXPLUME (EXposure to atmospheric PolLUtion ModEling). The model uses simulated gridded data of outdoor O3 and PM2.5 concentrations and several population and building-related datasets to simulate (1) space–time activity event sequences, (2) the infiltration of atmospheric contaminants indoors, and (3) daily aggregated personal exposure. The model is applied over the greater Paris region at 2 km×2 km resolution for the entire year of 2017. Annual averaged population exposure is discussed. We show that population mobility within the region, disregarding pollutant concentrations indoors, has only a small effect on average daily exposure. By contrast, considering the infiltration of PM2.5 in buildings decreases annual average exposure by 11 % (population average). Moreover, accounting for PM2.5 exposure during transportation (in vehicle, while waiting on subway platforms, and while crossing on-road tunnels) increases average population exposure by 5 %. We show that the spatial distribution of PM2.5 and O3 exposure is similar to the concentration maps over the region, but the exposure scale is very different when accounting for indoor exposure. We model large intra-population variability in PM2.5 exposure as a function of the transportation mode, especially for the upper percentiles of the distribution. Overall, 20 % of the population using bicycles or motorcycles is exposed to annual average PM2.5 concentrations above the EU target value (25 µg m−3), compared to 0 % for people travelling by car. Finally, we develop a 2050 horizon projection of the building stock to study how changes in the buildings' characteristics to comply with the thermal regulations will affect personal exposure. We show that exposure to ozone will decrease by as much as 14 % as a result of this projection, whereas there is no significant impact on exposure to PM2.5.

Top-down Support of Swiss non-CO2 Greenhouse Gas Emissions Reporting to UNFCCC

2020 ◽  
Author(s):  
Stephan Henne ◽  
Martin K. Vollmer ◽  
Martin Steinbacher ◽  
Markus Leuenberger ◽  
Frank Meinhardt ◽  
...  
Keyword(s):  
Nitrous Oxide ◽  
Radiative Forcing ◽  
Dispersion Model ◽  
Regional Scale ◽  
Particle Dispersion ◽  
Mitigation Measures ◽  
Ratio Method ◽  
Top Down ◽  
Bottom Up ◽  
Halogenated Compound

&lt;p&gt;Globally, emissions of long-lived non-CO&lt;sub&gt;2&lt;/sub&gt; greenhouse gases (GHG; methane, nitrous oxide and halogenated compounds) account for approximately 30 % of the radiative forcing of all anthropogenic GHG emissions. In industrialised countries, &amp;#8216;bottom-up&amp;#8217; estimates come with relatively large uncertainties for anthropogenic non-CO&lt;sub&gt;2&lt;/sub&gt; GHGs when compared with those of anthropogenic CO&lt;sub&gt;2&lt;/sub&gt;. 'Top-down' methods on the country scale offer an independent support tool to reduce these uncertainties and detect biases in emissions reported to the UNFCCC. Based on atmospheric concentration observations these tools are also able to detect the effectiveness of emission mitigation measures on the long term.&lt;/p&gt;&lt;p&gt;Since 2012 the Swiss national inventory reporting (NIR) contains an appendix on 'top-down' studies for selected halogenated compound. Subsequently, this appendix was extended to include methane and nitrous oxide. Here, we present these updated (2020 submission) regional-scale (~300 x 200 km&lt;sup&gt;2&lt;/sup&gt;) atmospheric inversion studies for non-CO&lt;sub&gt;2&lt;/sub&gt; GHG emission estimates in Switzerland, making use of observations on the Swiss Plateau (Berom&amp;#252;nster tall tower) as well as the neighbouring mountain-top sites Jungfraujoch and Schauinsland.&lt;/p&gt;&lt;p&gt;We report spatially and temporally resolved Swiss emissions for CH&lt;sub&gt;4&lt;/sub&gt; (2013-2019), N&lt;sub&gt;2&lt;/sub&gt;O (2017-2019) and total Swiss emissions for hydrofluorocarbons (HFCs) and SF&lt;sub&gt;6&lt;/sub&gt; (2009-2019) based on a Bayesian inversion system and a tracer ratio method, respectively. Both approaches make use of transport simulations applying the high-resolution (7 x 7 km&lt;sup&gt;2&lt;/sup&gt;) Lagrangian particle dispersion model (FLEXPART-COSMO). We compare these 'top-down' estimates to the 'bottom-up' results reported by Switzerland to the UNFCCC. Although we find good agreement between the two estimates for some species (CH&lt;sub&gt;4&lt;/sub&gt;, N&lt;sub&gt;2&lt;/sub&gt;O), emissions of other compounds (e.g., considerably lower 'top-down' estimates for HFC-134a) show larger discrepancies. Potential reasons for the disagreements are discussed. Currently, our 'top-down' information is only used for comparative purposes and does not feed back into the 'bottom-up' inventory.&lt;/p&gt;

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