Data Mining Climate Variability as an Indicator of U.S. Natural Gas

doi:10.3389/fdata.2019.00020

The City of Portland (City) and Multnomah County 2015 Climate Action Plan targets a 40 percent reduction in carbon emissions below 1990 levels by 2030. To reach this goal, the plan includes a key objective to reduce the total energy use of existing buildings by 25 percent. Buildings are responsible for one-half of carbon emissions in Portland, Oregon, U.S., and improving their performance is critical to achieving the City’s climate goals. As part of its climate action planning, the City passed an ordinance on April 22, 2015, requiring commercial buildings 20,000 ft2 and larger to benchmark and disclose annual energymore » performance metrics through ENERGY STAR® Portfolio Manager® (ESPM), including greenhouse gas emissions, building energy use intensity (EUI) and ENERGY STAR scores. Twenty-five cities in the U.S. have adopted similar policies requiring energy benchmarking. These policies are generating a treasure trove of data about the drivers of building performance, but practitioners are only beginning to link benchmarking data to other datasets to produce actionable insight into improving building performance. In 2016, the City received a financial assistance award from the U.S. Department of Energy (DOE) through the Cities Leading through Energy Analysis and Planning project (Award Number DE-0007737). Portland’s project evaluated the application of the DOE Building Energy Asset Score Tool and rating system developed by Pacific Northwest National Laboratory (PNNL) to commercial buildings that report to the City. The City used building construction permit history to develop Asset Scores for a set of office buildings that reported energy performance for 2015 – the first year the City mandated energy benchmarking and reporting for commercial buildings 50,000 ft2 and larger. The primary project objective was to link energy benchmarking data and commercial building permit data to analyze commercial buildings systems that present the best, specific opportunities to improve energy performance. Integrating these datasets from two City departments, the Bureau of Development Services and the Bureau of Planning and Sustainability, could expand Portland’s use of analytics to inform climate policy decisions and strategic targeting of financial incentives for building owners and managers who are best positioned to improve the performance of their buildings. The project began with the commercial benchmarking data received for 340 commercial buildings that submitted calendar year 2015 energy reports. The City retained Research Into Action and Energy 350 (RIA team) to evaluate this self-reported benchmarking data. Based on a survey of 53 building managers, the RIA team found that most respondents used the City’s compliance tools, including a How-to Guide and Help Desk, and found access to utility data to be straightforward. However, almost one-third of the respondents encountered challenges when estimating the gross floor area (GFA), and some experienced confusion regarding the input of property use types and details into ESPM. Based on the RIA team’s recommendations, the City refined its How-to Guide, created online answers to frequently asked questions, and hosted office hour sessions to help building managers accurately characterize their building’s physical characteristics and operations in ESPM. Concurrently with the RIA team’s evaluation, the City worked with PNNL to estimate DOE Asset Score Preview (Preview) scores for 181 of the 340 commercial buildings that submitted ESPM reports to the City. Asset Score Tool is a web-based tool developed by PNNL for DOE to evaluate and rate the as-built energy efficiency of a building. Asset Score Tool’s full analysis capability runs a detailed energy model based on building geometry, age, envelope, lighting and mechanical systems using standard operating assumptions to give the building a score, similar to a miles per gallon rating for a car. Preview, a simplified deployment of the full Asset Score Tool, provides a preliminary score range using only seven data points, six of which are readily available in the ESPM benchmarking data. Analysis of the combined Preview scores and the operational ESPM scores identified buildings with a high potential for energy improvements through either retro-commissioning and retuning of existing operations or capital investments into building systems. The City contracted Whole Building Solutions (WBS) to mine building permit history and develop full Asset Scores for a subset of 26 office buildings that were eligible for both ENERGY STAR scores and Asset Scores. WBS researched permits and building plans to identify mechanical, lighting and envelope systems and other building characteristics necessary to complete Asset Scores. This historical data was recorded using the web-based Asset Score Tool, which evaluates the as designed energy efficiency of existing buildings. Much of this City information was available online after 2010; however, WBS had to search through microfiche files and the City’s database to obtain permit and plan history prior to 2010. Although building geometry, mechanical system type and basic envelope information was consistently identifiable, WBS found permit data gaps that prevented complete and accurate Asset Scores for most of the office buildings. If the City decides to develop Asset Scores based on building permit information in the future, WBS recommended requiring lighting plans, control diagrams and as-built drawings that reflect how the buildings are actually constructed. In addition, WBS recommended uploading plans and permits from microfiche storage into a more comprehensive, searchable database consistent with the City’s current online permit information. To identify the actual lighting types, WBS and City staff conducted site visits of all 26 office buildings. As part of managing the flow of ESPM and Asset Score data for the project, Earth Advantage, a sub-recipient of the Cities-LEAP award, created a DOE Standard Energy Efficiency Data (SEED) (USDOE 2018) instance for the City and used Asset Score’s Application Programming Interface (API) (Asset Score 2018) capabilities to develop two new features in the SEED Platform™: (1) automated Asset Score Preview ranges calculated based on benchmarking data and the City’s estimate of number of building floors; and (2) storage of full Asset Score information. Leveraging the construction permit history and site visit information for the 26 office buildings, The Cadmus Group (Cadmus) analyzed benchmarking data and Asset Score information to identify opportunities and drivers to improve performance. Correlation and regression analysis of the combined dataset was completed to determine whether building operations or specific systems – mechanical, lighting or envelope – present the best opportunities to improve energy performance. The central outcome of this project was Cadmus’ detailed analysis of the richer dataset that was created by combining the City of Portland’s commercial building permit activity and building-specific energy performance information based on metrics from ESPM and Asset Score Tool. Some of their findings collaborate with well-known facts, such as buildings with less efficient lighting systems are good targets for efficiency improvements through lighting upgrades. This analysis also helped identify that individual heating, ventilation, and air conditioning (HVAC) equipment efficiency does not necessarily correlate with building performance. However, overall HVAC system performance, as measured with the Total System Performance Ratio (TSPR) metric, is a better indicator of building performance (Goel et al. 2014). As a metric, TSPR considers whole system performance that includes equipment efficiency and system controls, such as resets for static pressure and chilled water setpoints, which can be more effective and financially feasible options for improving building performance. Given the high cost associated with envelope retrofits, opportunities to upgrade envelope insulation are likely to be limited. However, buildings with single-pane and non-thermal break windows are good candidates for window replacements, such as upgrading to double-pane windows with thermal breaks. This research project determined that developing Asset Scores based on site visits is preferable to mining City building permit data. In addition, the use of benchmarking data to develop Asset Score Preview Scores is recommended as a first step in engaging building managers to develop full Asset Scores. Asset Score Tool outputs can help building managers quickly identify opportunities for improvement and then work with the utility incentive administrator and energy service providers to develop their retrofit plan. Where full Asset Scores are available, analysis using a quadrant matrix with ENERGY STAR scores is recommended to identify buildings that present the best opportunities for operational-behavioral improvements versus ones with opportunities for upgrades to physical building systems. This workflow and the tools will help cities, utility incentive administrators, building portfolio managers and energy service providers develop energy programs and strategies for screening and analysis of buildings with the greatest energy savings potential. This report describes the project approach and research results to inform future coordination of ESPM and Asset Score data, including the use of benchmarking data to generate Preview scores. Given better awareness of energy performance, building managers can make more informed decisions to reduce energy consumption and carbon emissions. With cities, states and jurisdictions adopting benchmarking and auditing ordinances, there are substantial amounts of data submitted to cities that could be used to inform investments in energy efficiency.

Title: Data Mining Climate Variability as an Indicator of U.S. Natural Gas

Citation Formats

More-Persistent Weak Stratospheric Polar Vortex States Linked to Cold Extremes
journal, January 2018

ENSO and meridional modes: A null hypothesis for Pacific climate variability: ENSO AND MM PACIFIC DECADAL VARIABILITY
journal, November 2015

Pacific sea surface temperature and the winter of 2014: SST and 2014 Winter
journal, March 2015

Increasing precipitation volatility in twenty-first-century California
journal, April 2018

The North American winter ‘dipole’ and extremes activity: a CMIP5 assessment: Amplification of North American dipole
journal, February 2015

Extreme Fire Season in California: A Glimpse Into the Future?
journal, December 2015

The Pacific Decadal Oscillation, Revisited
journal, June 2016

Different ENSO teleconnections and their effects on the stratospheric polar vortex
journal, January 2008

Uncertainty in climate change projections: the role of internal variability
journal, December 2010

Distinguishing coupled ocean–atmosphere interactions from background noise in the North Pacific
journal, January 2001

California from drought to deluge
journal, June 2017

Estimating economic damage from climate change in the United States
journal, June 2017

ENSO, Pacific Decadal Variability, and U.S. Summertime Precipitation, Drought, and Stream Flow
journal, May 2001

Trends in atmospheric patterns conducive to seasonal precipitation and temperature extremes in California
journal, April 2016

Weakening of the stratospheric polar vortex by Arctic sea-ice loss
journal, September 2014

The seasonal relationship between intraseasonal tropical variability and ENSO in CMIP5
journal, January 2018

Role of the Gulf Stream and Kuroshio–Oyashio Systems in Large-Scale Atmosphere–Ocean Interaction: A Review
journal, June 2010

Probable causes of the abnormal ridge accompanying the 2013-2014 California drought: ENSO precursor and anthropogenic warming footprint: DIAGNOSING CALIFORNIA DROUGHT 2013-14
journal, May 2014

Seasonal Evolutions of Atmospheric Response to Decadal SST Anomalies in the North Pacific Subarctic Frontal Zone: Observations and a Coupled Model Simulation
journal, January 2012

Title: Data Mining Climate Variability as an Indicator of U.S. Natural Gas

Citation Formats

More-Persistent Weak Stratospheric Polar Vortex States Linked to Cold Extremes journal, January 2018

ENSO and meridional modes: A null hypothesis for Pacific climate variability: ENSO AND MM PACIFIC DECADAL VARIABILITY journal, November 2015

Pacific sea surface temperature and the winter of 2014: SST and 2014 Winter journal, March 2015

Increasing precipitation volatility in twenty-first-century California journal, April 2018

The North American winter ‘dipole’ and extremes activity: a CMIP5 assessment: Amplification of North American dipole journal, February 2015

Extreme Fire Season in California: A Glimpse Into the Future? journal, December 2015

The Pacific Decadal Oscillation, Revisited journal, June 2016

Different ENSO teleconnections and their effects on the stratospheric polar vortex journal, January 2008

Uncertainty in climate change projections: the role of internal variability journal, December 2010

Distinguishing coupled ocean–atmosphere interactions from background noise in the North Pacific journal, January 2001

California from drought to deluge journal, June 2017

Estimating economic damage from climate change in the United States journal, June 2017

ENSO, Pacific Decadal Variability, and U.S. Summertime Precipitation, Drought, and Stream Flow journal, May 2001

Trends in atmospheric patterns conducive to seasonal precipitation and temperature extremes in California journal, April 2016

Weakening of the stratospheric polar vortex by Arctic sea-ice loss journal, September 2014

The seasonal relationship between intraseasonal tropical variability and ENSO in CMIP5 journal, January 2018

Role of the Gulf Stream and Kuroshio–Oyashio Systems in Large-Scale Atmosphere–Ocean Interaction: A Review journal, June 2010

Probable causes of the abnormal ridge accompanying the 2013-2014 California drought: ENSO precursor and anthropogenic warming footprint: DIAGNOSING CALIFORNIA DROUGHT 2013-14 journal, May 2014

Seasonal Evolutions of Atmospheric Response to Decadal SST Anomalies in the North Pacific Subarctic Frontal Zone: Observations and a Coupled Model Simulation journal, January 2012