Urban Water Demand Simulation in Residential and Non-Residential Buildings Based on a CityGML Data Model

Humans’ activities in urban areas put a strain on local water resources. This paper introduces a method to accurately simulate the stress urban water demand in Germany puts on local resources on a single-building level, and scalable to regional levels without loss of detail. The method integrates building geometry, building physics, census, socio-economy and meteorological information to provide a general approach to assessing water demands that also overcome obstacles on data aggregation and processing imposed by data privacy guidelines. Three German counties were used as validation cases to prove the feasibility of the presented approach: on average, per capita water demand and aggregated water demand deviates by less than 7% from real demand data. Scenarios applied to a case region Ludwigsburg in Germany, which takes the increment of water price, aging of the population and the climate change into account, show that the residential water demand has the change of −2%, +7% and −0.4% respectively. The industrial water demand increases by 46% due to the development of economy indicated by GDP per capita. The rise of precipitation and temperature raise the water demand in non-residential buildings (excluding industry) of 1%

A Method for Assessing Regional Bioenergy Potentials Based on GIS Data and a Dynamic Yield Simulation Model

The assessment of regional bioenergy potentials from different types of natural land cover is an integral part of simulation tools that aim to assess local renewable energy systems. This work introduces a new workflow, which evaluates regional bioenergy potentials and its impact on water demand based on geographical information system (GIS)-based land use data, satellite maps on local crop types and soil types, and conversion factors from biomass to bioenergy. The actual annual biomass yield of crops is assessed through an automated process considering the factors of local climate, crop type, soil, and irrigation. The crop biomass yields are validated with historic statistical data, with deviation less than 7% in most cases. Additionally, the resulting bioenergy potentials yield between 10.7 and 12.0 GWh/ha compared with 13.3 GWh/ha from other studies. The potential contribution from bioenergy on the energy demand were investigated in the two case studies, representing the agricultural-dominant rural area in North Germany and suburban region in South Germany: Simulation of the future bioenergy potential for 2050 shows only smaller effects from climate change (less than 4%) and irrigation (below 3%), but the potential to cover up to 21% of the transport fuels demand in scenario supporting biodiesel and bioethanol for transportation

A GIS-Based Simulation Method for Regional Food Potential and Demand

A quantitative assessment of food-water-energy interactions is important to assess pathways and scenarios towards a holistically sustainable regional development. While a range of tools and methods exist that assess energetic demands and potentials on a regional scale, the same is not true for assessments of regional food demand and potential. This work introduces a new food simulation workflow to address local food potential and demand at the regional level, by extending an existing regional energy-water simulation platform. The goal of this work is to develop a GIS-based bottom-up approach to simulate regional food demand that can be linked to similarly GIS-based workflows assessing regional water demands and energetic demands and potentials. This allows us to study food-water-energy issues on a local scale. For this, a CityGML land use data model is extended with a feed and animal potential raster map as well as a soil type map to serve as the main inputs. The workflow simulates: (1) the vegetal and animal product food potentials by taking climate, crop type, soil type, organic farming, and food waste parameters into account; (2) the food demand of vegetal and animal products influenced by population change, body weight, age, human development index, and other indicators. The method is tested and validated in three German counties with various land use coverages. The results show that restricting land used exclusively for energy crop production is the most effective way to increase annual food production potential. Climate change by 2050 is expected to result in annual biomass yield changes between −4% and 2% depending on the region. The amount of animal product consumption is expected to rise by 16% by 2050, while 4% fewer vegetal products are excepted to be consumed

Urban Water Demand Simulation in Residential and Non-Residential Buildings Based on a CityGML Data Model

Humans’ activities in urban areas put a strain on local water resources. This paper introduces a method to accurately simulate the stress urban water demand in Germany puts on local resources on a single-building level, and scalable to regional levels without loss of detail. The method integrates building geometry, building physics, census, socio-economy and meteorological information to provide a general approach to assessing water demands that also overcome obstacles on data aggregation and processing imposed by data privacy guidelines. Three German counties were used as validation cases to prove the feasibility of the presented approach: on average, per capita water demand and aggregated water demand deviates by less than 7% from real demand data. Scenarios applied to a case region Ludwigsburg in Germany, which takes the increment of water price, aging of the population and the climate change into account, show that the residential water demand has the change of −2%, +7% and −0.4% respectively. The industrial water demand increases by 46% due to the development of economy indicated by GDP per capita. The rise of precipitation and temperature raise the water demand in non-residential buildings (excluding industry) of 1%

Urban Water Demand Simulation in Residential and Non-Residential Buildings Based on a CityGML Data Model

Humans’ activities in urban areas put a strain on local water resources. This paper introduces a method to accurately simulate the stress urban water demand in Germany puts on local resources on a single-building level, and scalable to regional levels without loss of detail. The method integrates building geometry, building physics, census, socio-economy and meteorological information to provide a general approach to assessing water demands that also overcome obstacles on data aggregation and processing imposed by data privacy guidelines. Three German counties were used as validation cases to prove the feasibility of the presented approach: on average, per capita water demand and aggregated water demand deviates by less than 7% from real demand data. Scenarios applied to a case region Ludwigsburg in Germany, which takes the increment of water price, aging of the population and the climate change into account, show that the residential water demand has the change of −2%, +7% and −0.4% respectively. The industrial water demand increases by 46% due to the development of economy indicated by GDP per capita. The rise of precipitation and temperature raise the water demand in non-residential buildings (excluding industry) of 1%

A GIS-Based Simulation Method for Regional Food Potential and Demand

A quantitative assessment of food-water-energy interactions is important to assess pathways and scenarios towards a holistically sustainable regional development. While a range of tools and methods exist that assess energetic demands and potentials on a regional scale, the same is not true for assessments of regional food demand and potential. This work introduces a new food simulation workflow to address local food potential and demand at the regional level, by extending an existing regional energy-water simulation platform. The goal of this work is to develop a GIS-based bottom-up approach to simulate regional food demand that can be linked to similarly GIS-based workflows assessing regional water demands and energetic demands and potentials. This allows us to study food-water-energy issues on a local scale. For this, a CityGML land use data model is extended with a feed and animal potential raster map as well as a soil type map to serve as the main inputs. The workflow simulates: (1) the vegetal and animal product food potentials by taking climate, crop type, soil type, organic farming, and food waste parameters into account; (2) the food demand of vegetal and animal products influenced by population change, body weight, age, human development index, and other indicators. The method is tested and validated in three German counties with various land use coverages. The results show that restricting land used exclusively for energy crop production is the most effective way to increase annual food production potential. Climate change by 2050 is expected to result in annual biomass yield changes between −4% and 2% depending on the region. The amount of animal product consumption is expected to rise by 16% by 2050, while 4% fewer vegetal products are excepted to be consumed

A Method for Assessing Regional Bioenergy Potentials Based on GIS Data and a Dynamic Yield Simulation Model

The assessment of regional bioenergy potentials from different types of natural land cover is an integral part of simulation tools that aim to assess local renewable energy systems. This work introduces a new workflow, which evaluates regional bioenergy potentials and its impact on water demand based on geographical information system (GIS)-based land use data, satellite maps on local crop types and soil types, and conversion factors from biomass to bioenergy. The actual annual biomass yield of crops is assessed through an automated process considering the factors of local climate, crop type, soil, and irrigation. The crop biomass yields are validated with historic statistical data, with deviation less than 7% in most cases. Additionally, the resulting bioenergy potentials yield between 10.7 and 12.0 GWh/ha compared with 13.3 GWh/ha from other studies. The potential contribution from bioenergy on the energy demand were investigated in the two case studies, representing the agricultural-dominant rural area in North Germany and suburban region in South Germany: Simulation of the future bioenergy potential for 2050 shows only smaller effects from climate change (less than 4%) and irrigation (below 3%), but the potential to cover up to 21% of the transport fuels demand in scenario supporting biodiesel and bioethanol for transportation

Using 3D CityGML for the modeling of the food waste and wastewater generation — A case study for the city of Montréal

The paper explains a workflow to simulate the food energy water (FEW) nexus for an urban district combining various data sources like 3D city models, particularly the City Geography Markup Language (CityGML) data model from the Open Geospatial Consortium, Open StreetMap and Census data. A long term vision is to extend the CityGML data model by developing a FEW Application Domain Extension (FEW ADE) to support future FEW simulation workflows such as the one explained in this paper. Together with the mentioned simulation workflow, this paper also identifies some necessary FEW related parameters for the future development of a FEW ADE. Furthermore, relevant key performance indicators are investigated, and the relevant datasets necessary to calculate these indicators are studied. Finally, different calculations are performed for the downtown borough Ville-Marie in the city of Montréal (Canada) for the domains of food waste (FW) and wastewater (WW) generation. For this study, a workflow is developed to calculate the energy generation from anaerobic digestion of FW and WW. In the first step, the data collection and preparation was done. Here relevant data for georeferencing, data for model set-up, and data for creating the required usage libraries, like food waste and wastewater generation per person, were collected. The next step was the data integration and calculation of the relevant parameters, and lastly, the results were visualized for analysis purposes. As a use case to support such calculations, the CityGML level of detail two model of Montréal is enriched with information such as building functions and building usages from OpenStreetMap. The calculation of the total residents based on the CityGML model as the main input for Ville-Marie results in a population of 72,606. The statistical value for 2016 was 89,170, which corresponds to a deviation of 15.3%. The energy recovery potential of FW is about 24,024 GJ/year, and that of wastewater is about 1,629 GJ/year, adding up to 25,653 GJ/year. Relating values to the calculated number of inhabitants in Ville-Marie results in 330.9 kWh/year for FW and 22.4 kWh/year for wastewater, respectively

The Application of CityGML Food Water Energy ADE to Estimate the Biomass Potential for a Land Use Scenario

Cities are undergoing rapid urbanisation throughout the globe. A common challenge amongst them is to provide food, water, and energy (FWE) supplies under sustainable and economically productive conditions. As a result, new tools and techniques must be developed to support domain experts and decision-makersto understand, simulate and visualise the nexus impact on the sustainable supply of the FWE resources. A critical part of such a development process is to eliminate data silos and move towards an integrated FWE based data model, which can then be used to connect domain-specific urban simulation tools to simulate FWE nexus scenarios based on changes in landuse, population, and climatic conditions.This paper demonstrates the CityGML FWE Application Domain Extension (ADE) application as a central data exchange format to connect different urban simulation tools. First, it gives an insight into the ongoing development of the FWE ADE to the standardised open city information data model of CityGML. Secondly, it demonstrates the role of the CityGML FWE ADE in exchanging datasets between a FWE based landuse simulator built with UD_InfraSim and an urban energy simulator SimStadt to estimate the biomass potential for a landuse scenario of Vienna based on its future population and climatic changes

A Method for Assessing Regional Bioenergy Potentials Based on GIS Data and a Dynamic Yield Simulation Model

The assessment of regional bioenergy potentials from different types of natural land cover is an integral part of simulation tools that aim to assess local renewable energy systems. This work introduces a new workflow, which evaluates regional bioenergy potentials and its impact on water demand based on geographical information system (GIS)-based land use data, satellite maps on local crop types and soil types, and conversion factors from biomass to bioenergy. The actual annual biomass yield of crops is assessed through an automated process considering the factors of local climate, crop type, soil, and irrigation. The crop biomass yields are validated with historic statistical data, with deviation less than 7% in most cases. Additionally, the resulting bioenergy potentials yield between 10.7 and 12.0 GWh/ha compared with 13.3 GWh/ha from other studies. The potential contribution from bioenergy on the energy demand were investigated in the two case studies, representing the agricultural-dominant rural area in North Germany and suburban region in South Germany: Simulation of the future bioenergy potential for 2050 shows only smaller effects from climate change (less than 4%) and irrigation (below 3%), but the potential to cover up to 21% of the transport fuels demand in scenario supporting biodiesel and bioethanol for transportation