scholarly journals AI-Based Campus Energy Use Prediction for Assessing the Effects of Climate Change

2020 ◽  
Vol 12 (8) ◽  
pp. 3223 ◽  
Author(s):  
Soheil Fathi ◽  
Ravi S. Srinivasan ◽  
Charles J. Kibert ◽  
Ruth L. Steiner ◽  
Emre Demirezen

In developed countries, buildings are involved in almost 50% of total energy use and 30% of global annual greenhouse gas emissions. The operational energy needs of buildings are highly dependent on various building physical, operational, and functional characteristics, as well as meteorological and temporal properties. Besides physics-based energy modeling of buildings, Artificial Intelligence (AI) has the capability to provide faster and higher accuracy estimates, given buildings’ historic energy consumption data. Looking beyond individual building levels, forecasting building energy performance can help city and community managers have a better understanding of their future energy needs, and to plan for satisfying them more efficiently. Focusing at an urban scale, this research develops a campus energy use prediction tool for predicting the effects of long-term climate change on the energy performance of buildings using AI techniques. The tool comprises four steps: Data Collection, AI Development, Model Validation, and Model Implementation, and can predict the energy use of campus buildings with 90% accuracy. We have relied on energy use data of buildings situated in the University of Florida, Gainesville, Florida (FL). To study the impact of climate change, we have used climate properties of three future weather files of Gainesville, FL, developed by the North American Regional Climate Change Assessment Program (NARCCAP), represented based on their impact: median (year 2063), hottest (2057), and coldest (2041).

2021 ◽  
Author(s):  
Moshe Gophen

AbstractPart of the Kinneret watershed, the Hula Valley, was modified from wetlands – shallow lake for agricultural cultivation. Enhancement of nutrient fluxes into Lake Kinneret was predicted. Therefore, a reclamation project was implemented and eco-tourism partly replaced agriculture. Since the mid-1980s, regional climate change has been documented. Statistical evaluation of long-term records of TP (Total Phosphorus) concentrations in headwaters and potential resources in the Hula Valley was carried out to identify efficient management design targets. Significant correlation between major headwater river discharge and TP concentration was indicated, whilst the impact of external fertilizer loads and 50,000 winter migratory cranes was probably negligible. Nevertheless, confirmed severe bdamage to agricultural crops carried out by cranes led to their maximal deportation and optimization of their feeding policy. Consequently, the continuation of the present management is recommended.


2012 ◽  
pp. 91-120 ◽  
Author(s):  
Andrew Clarke ◽  
David K. A. Barnes ◽  
Thomas J. Bracegirdle ◽  
Hugh W. Ducklow ◽  
John C. King ◽  
...  

2010 ◽  
Vol 27 ◽  
pp. 57-64 ◽  
Author(s):  
M. Wegehenkel ◽  
U. Heinrich ◽  
H. Jochheim ◽  
K. C. Kersebaum ◽  
B. Röber

Abstract. Future climate changes might have some impacts on catchment hydrology. An assessment of such impacts on e.g. ground water recharge is required to derive adaptation strategies for future water resources management. The main objective of our study was an analysis of three different regional climate change scenarios for a catchment with an area of 2415 km2 located in the Northeastern German lowlands. These data sets consist of the STAR-scenario with a time period 1951–2055, the WettReg-scenario covering the period 1961–2100 and the grid based REMO-scenario for the time span 1950–2100. All three data sets are based on the SRES scenario A1B of the IPCC. In our analysis, we compared the meteorological data for the control period obtained from the regional climate change scenarios with corresponding data measured at meteorological stations in the catchment. The results of this analysis indicated, that there are high differences between the different regional climate change scenarios regarding the temporal dynamics and the amount of precipitation. In addition, we applied a water balance model using input data obtained from the different climate change scenarios and analyzed the impact of these different input data on the model output groundwater recharge. The results of our study indicated, that these regional climate change scenarios due to the uncertainties in the projections of precipitation show only a limited suitability for hydrologic impact analysis used for the establishment of future concrete water management procedures in their present state.


2020 ◽  
pp. 1-12
Author(s):  
Moshe Gophen

The long-term record of River Jordan-Lake Kinneret ecosystem indicates some significant climate condition changes: water temperature increase, decline in rainfall, and diminishing river discharges and lake water inflows accompanied by a reduction in nitrogen and a slight increase in phosphorus in the Lake upper layers (Epilimnion). Lake Water level decreased, Prolongation of Residence Time was documented, nutrient inputs and dynamics modifications resulting water quality deterioration. As a result of temperature elevation and nitrogen deficiency, the biomass of Peridinium spp significantly reduced and was replaced by Cyanobacterial biomass enhancement. Dryness trend expressed as enhanced frequency of drought seasons initiated an elevation of lake water salinity. It has been suggested that these changes in the phytoplankton community structure are caused by regional climate change. This study evaluates a multi-annual respective approach although the summer is the most critical. The objective of this research is evaluate the background of the ecosystem structure modification aimed at define future potential management design.


Author(s):  
Theodore G. Shepherd

Climate science seeks to make statements of confidence about what has happened, and what will happen (conditional on scenario). The approach is effective for the global, thermodynamic aspects of climate change, but is ineffective when it comes to aspects of climate change related to atmospheric circulation, which are highly uncertain. Yet, atmospheric circulation strongly mediates climate impacts at the regional scale. In this way, the confidence framework, which focuses on avoiding type 1 errors (false alarms), raises the prospect of committing type 2 errors (missed warnings). This has ethical implications. At the regional scale, however, where information on climate change has to be combined with many other factors affecting vulnerability and exposure—most of which are highly uncertain—the societally relevant question is not ‘What will happen?’ but rather ‘What is the impact of particular actions under an uncertain regional climate change?’ This reframing of the question can cut the Gordian knot of regional climate change information, provided one distinguishes between epistemic and aleatoric uncertainties—something that is generally not done in climate projections. It is argued that the storyline approach to climate change—the identification of physically self-consistent, plausible pathways—has the potential to accomplish precisely this.


2018 ◽  
Vol 99 (10) ◽  
pp. 2093-2106 ◽  
Author(s):  
Ambarish V. Karmalkar

AbstractTwo ensembles of dynamically downscaled climate simulations for North America—the North American Regional Climate Change Assessment Program (NARCCAP) and the Coordinated Regional Climate Downscaling Experiment (CORDEX) featuring simulations for North America (NA-CORDEX)—are analyzed to assess the impact of using a small set of global general circulation models (GCMs) and regional climate models (RCMs) on representing uncertainty in regional projections. Selecting GCMs for downscaling based on their equilibrium climate sensitivities is a reasonable strategy, but there are regions where the uncertainty is not fully captured. For instance, the six NA-CORDEX GCMs fail to span the full ranges produced by models in phase 5 of the Coupled Model Intercomparison Project (CMIP5) in summer temperature projections in the western and winter precipitation projections in the eastern United States. Similarly, the four NARCCAP GCMs are overall poor at spanning the full CMIP3 ranges in seasonal temperatures. For the Southeast, the NA-CORDEX GCMs capture the uncertainty in summer but not in winter projections, highlighting one consequence of downscaling a subset of GCMs. Ranges produced by the RCMs are often wider than their driving GCMs but are sensitive to the experimental design. For example, the downscaled projections of summer precipitation are of opposite polarity in two RCM ensembles in some regions. Additionally, the ability of the RCMs to simulate observed temperature trends is affected by the internal variability characteristics of both the RCMs and driving GCMs, and is not systematically related to their historical performance. This has implications for adequately sampling the impact of internal variability on regional trends and for using model performance to identify credible projections. These findings suggest that a multimodel perspective on uncertainties in regional projections is integral to the interpretation of RCM results.


Author(s):  
Pieter de Jong ◽  
Tarssio B. Barreto ◽  
Clemente.A.S. Tanajura ◽  
Karla P. Oliveira-Esquerre ◽  
Asher Kiperstok ◽  
...  

2012 ◽  
Vol 12 (3) ◽  
pp. 7705-7726 ◽  
Author(s):  
J. Langner ◽  
M. Engardt ◽  
C. Andersson

Abstract. The impact of climate change and changes in ozone precursor emissions on summer surface ozone in Europe were studied using a regional CTM over the period 1990 to 2100. Two different climate simulations under the SRES A1B scenario together with ozone precursor emission changes from the RCP4.5 scenario were used as model input. In southern Europe regional climate change leads to increasing surface ozone concentrations during April–September, but projected emission reductions in Europe have a stronger effect, resulting in net reductions of surface ozone concentrations. In northern Europe regional climate change decreases surface O3 and reduced emissions acts to further strengthen this trend also when including increasing hemispheric background concentrations, although on the British Isles the combined effect is an increase. Due to substantial decadal variability in the simulations it is important to study averages over sufficiently long time periods in order to be able to extract robust signals of climate change impacts on surface O3 concentrations.


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