Category: Energy & Environmental Policy

Spatial Energy Efficiency Patterns in New York and Implications for Energy Demand and the Rebound Effect

The confluence of the threat of global climate change, increasing energy prices, and widespread adoption of low-carbon technologies have been cited as key drivers of the energy transition. Two of the scenarios exemplified by future rates of uptake of energy transition based on expectations of change in demand, and socially incremental choices that define the transition in terms of energy consumption and consumer behavior illustrate potential results under the current business-as-usual paradigm. An important area that has been overlooked is how spatial diffusion of energy-efficiency policies or complementarities across policy mixes can yield direct measurable benefits that improve overall energy policy design and performance measurement.

In our new paper (co-authored with Dr. John Byrne) titled Spatial Energy Efficiency Patterns in New York and Implications for Energy Demand and the Rebound Effect, published in Energy Sources, Part B: Economics Planning and Policy, we posit the inquiry of how to address this quandary as one of spatial dynamism in policy design: promoting spatial sensitivity in technology-or sector-specific energy-efficiency policies to support increased diffusion, information sharing, and accelerating the adoption rates of energy efficiency measures.

In this study, we applied the spatial modeling (i.e., spatial Durbin error model-SDEM) approach to analyze adoption trends for residential energy-efficiency measures. To do so, we evaluated the potential for local socioeconomic and building performance variables which influence the effectiveness of energy efficiency policies and diffusion patterns in each location in the long-term. We investigated this potential for New York state at a ZIP code level to show the ubiquitous promise and potential of this conceptualization to improve urban energy planning and management. To arrive at a practical strategy, we investigated the policy implications for energy demand and the rebound effect.

Our study shows the significant influence of the built environment and jurisdictional boundaries and their effect on energy transition capacities. As such, the paper makes a compelling case for a fundamental reconsideration of energy policy design in New York and target setting to account for specific conditions in the built environment that may constrain the uptake of energy-efficient technologies in a given jurisdiction.

As the payoff from investment in advanced-analytics management and big data revolution becomes real, the art and science of delivery is on the upswing as institutions share knowledge, tools and experience in problem solving. For instance, public policy institutions are full of good ideas on how to solve complex social problems, improve STEM pedagogy and student learning, cure diseases, and produce energy (at scale, efficiently, and sustainably). But what has been missing in this process is the ability to implement simple, pragmatic and scalable solutions to effect positive social change. This seems to be changing, pretty fast, however, as organizations integrate their stovepipes of data across operations and sectors to provide powerful insights.

Speaking at this year’s annual meeting plenary session, World Bank Group President Jim Yong Kim addressed the facts and processes germaine to the next frontier in advancing the science of delivery. “Effective delivery demands context-specific knowledge. It requires constant adjustments, a willingness to take smart risks, and a relentless focus on the details of implementation,” he observed.

https://www.youtube.com/watch?feature=player_embedded&v=cGz8gBctezo

McKinsey has also developed an anthology of leading delivery models by social thinkers and practitioners in health care, smart energy, financial services, governance, and food security to improve development outcomes.

Steven Johnson opened Emergence, his searing 2001 book on how complex systems manifest from simple rules and are driven by bottom-up behaviour, with a fascinating rhetoric:

“How does a lively neighbourhood evolve out of a disconnected association of shopkeepers, bartenders and real estate developers?” he asked. “How does a media event take on a life of its own? How will new software programs create an intelligent worldwide web?”

It’s an interesting question. Emergence examines how simple, interconnected elements – such as amoeba-like slime mould cells, neurons or the individual members of an insect colony – self-organise to form more intelligent and sophisticated systems by coalescing with thousands of their neighbours.

But how does this happen? And how is it relevant for cities?

Consider that when it comes to control over processes such as how long it should take for traffic lights to change, or the amount of energy consumed in each household, or how many times in a week garbage is collected, every city model falls somewhere along a continuum.

At one end are highly controlled, top-down hierarchical systems being engineered by a master planner. Someone – at the control room of a Pacific Gas and Electric Company, or a Southern California Edison, or a British Gas – monitors how much energy is coming in and how much is being consumed at any given moment.

And at the other end are self-organising components, where no individual exerts control over the processes. These components are, in essence, far more than the sum of their residents and get their orders from below.

In all leading cities today, we talk about sustainability as both a big-picture goal and in terms of what individual residents can do – those who are looking through various processes with an environmental lens, whether it be a shorter commute to work, an affordable fuel-efficient car with better miles per gallon, the replacement of incandescent light bulbs with energy saving bulbs, a weatherised home, liveable and healthier neighbourhoods, etc.

Each decision has competing tradeoffs. Yet those random personal and local decisions combine – and self-organise – to form the macro-behaviour of homes, boroughs, regions and cities, leading to global patterns.

And with this self-organisation, new pockets of success emerge: monthly home energy bills are reduced, waste and expenses associated with inefficient processes are slashed, air pollution is fixed, and equilibrium is restored. In essence, it is neighbourhoods in cities solving problems that would otherwise appear insurmountable – without any of those cities realising it.

IBM’s Smarter Cities initiative equips city managers with tools and technology that enable them to drive sustainable growth and prosperity by analysing efforts among agencies and sectors as they happen, thus helping them anticipate issues rather than react to them. New York, Rio de Janeiro and Memphis, to name a few, are using IBM tools to coordinate emergency response units and strengthen crime fighting, while Singapore is working with IBM on a range of issues such as congestion charging in order to reduce traffic and air pollution.

“The majority of us live in cities, and the percentage is growing,” says IBM. “As centres of business, culture and life, cities are logical places to integrate many of the Smarter Planet principles and innovations: smarter transportation, policing, emergency response, governance and smart grid that links power and water systems, to name a few. By using these tested approaches, cities can manage growth and development in a sustainable way that minimises disruptions and helps increase prosperity for everyone.”

However, with budget cuts and slower economic growth, many cities are facing a tough challenge. Their populations are growing at a time when their revenues are shrinking. More than half of the world’s population now lives in cities. Moreover, this figure is estimated to grow to 80 percent by the year 2050.

These new realities have led people to ask some searching questions. What will happen to monthly energy costs in the coming years? How clean is the water supply? What adaptation and mitigation strategies will climate change require us to model? How can we replace fossil fuels with sustainable energy sources in our mass-transit systems in the urban environment? And how can we increase the vitality and competitiveness of our urban environments with solutions that optimise the entire city?

Consider one million people will have moved into the world’s cities by the end of this week. For the foreseeable future, cities may have to do more with less, and they may have to find new ways to manage complexity, to increase efficiency, to reduce overheads and still build liveable and healthier neighbourhoods and improve quality of life.

By eliminating operational silos, enlisting forward-thinking leaders and adopting self-organising smarts, cities can remain prosperous and sustainable in the face of unprecedented competing interests, and take the first steps toward creating more liveable neighbourhoods.

This article first appeared  in PMI Global Sustainability Practice

Sign up and subscribe to our newsletter

We respect your privacy and do not tolerate spam