There’s a shift afoot in the world of corporate sustainability, and especially the clean energy slice of the corporate sustainability pie. A growing number of companies are taking a fresh, hard look at their efforts and asking how they can better leverage their energy-related investments to achieve a low-carbon future faster.

In practice, that has meant going above and beyond blindly procuring renewable energy, whether through the purchase of renewable energy certificates (RECs), installing on-site solar, and/or signing long-term contracts such as various flavors of power purchase agreements (PPAs). Now, corporations are increasingly also taking a look at their bottom-line impacts: How can they more aggressively reduce their greenhouse gas (GHG) emissions?

It’s here that blockchain—and better data—have a key role to potentially play.

From renewable energy to emissions reductions

Walmart presents an excellent case-in-point demonstrating the shift from a renewables-heavy focus to one that also includes a complementary focus on emissions reductions.

The company is one of the nationwide renewable energy leaders when it comes to installed rooftop solar capacity on its stores and distribution centers across the country. And while Walmart has lost its #1 ranking (Target surpassed it in installed rooftop solar capacity), last year Walmart announced it would install solar on another 120 stores, alongside also participating in Georgia Power’s green tariff program and announcing that it would also buy Midwest wind energy to help support its renewable energy goals.

This commendable, multi-pronged renewable energy strategy is what the market has largely come to expect from a leader like Walmart. But what comes next is what has caught our attention here at WattTime.

Two years ago Walmart announced its Project Gigaton, which has recently gained major traction. The initiative aims to prevent one gigaton (1 billion metric tons) of GHG emissions across the company’s global supply chain over a 15-year span. Though it launched in Spring 2017, Project Gigaton landed back in the headlines just recently when Walmart announced that 1,000 suppliers had joined the carbon-reduction push and that the company had already conserved 93 million metric tons of emissions through energy efficiency practices, renewable energy purchases, and sustainable packaging projects.

It might feel easy to dismiss these kind of achievements as only something a mega-company like Walmart can achieve. But blockchain—paired with new and better sources of data, insights, and full productized software solutions—just might be the way to help this approach scale across far more of the corporate sustainability world.

Four ways blockchain enhances corporate sustainability

Blockchain is a distributed ledger system that is proving its merits far beyond the world of cryptocurrencies such as Bitcoin. As a secure, auditable, immutable, and decentralized database, it’s finding favor in industries from healthcare and banking to, yes, energy and sustainability.

In the corporate sustainability context, blockchain appeals in at least four ways:

• Integrity: Thanks to the validation process by which blocks of data get added to a blockchain, shareholders and customers alike can have greater confidence in corporate sustainability claims.
• Granularity: By “tokenizing” data and/or assets with a digital twin, as well as simply getting more granular with existing data sets, blockchain can facilitate market entry for smaller players, not to mention open the door to further deal aggregation.
• Integration: By marrying two traditionally complementary but separate data streams—renewable energy generation and real-time carbon offsets—blockchain can help corporations better track the emissions impact of their efforts.
• Automation: Thanks to how blockchain can disintermediate and make transparent previously opaque parts of the market, along with automating traditionally manual back-office processes, blockchain has the potential to streamline corporate sustainability reporting.

Blockchains still need better data to start with

The data stored on a blockchain may be highly secure, immutable, and auditable, but it’s still only as good as the data you add to the blockchain in the first place. The source and type of data matters.

When it comes to emissions data, that means going beyond business-as-usual long-term average emissions rates. For example, here at WattTime we leverage historical, real-time, and predictive data—alongside sophisticated algorithms and machine learning—to develop highly accurate location- and time-specific emissions rates.

We use this insight to power software solutions such as Automated Emissions Reduction (AER), which allows energy users large and small to do a simple software upgrade to their smart devices (e.g., building energy management systems, electric vehicle charging stations) so that they adjust their timing to use more clean energy and avoid dirty energy.

But that data and those insights can feed into other solutions as well, such as blockchain-based approaches.

Partnering with Swytch to unlock blockchain’s potential

Swytch is a blockchain platform committed to making our planet a little cleaner and greener. In their work with corporate customers, Swytch verifies the carbon reduction impact of renewable energy purchases and other actions and awards Swytch tokens (via a digital wallet) to users based on the results. Earlier this year, Swytch and WattTime announced an exciting partnership.

Swytch’s oracle now connects to WattTime’s API as one of its key sources of emissions data. Swytch is then able to provide its customers with the insight to make more informed and strategic energy decisions, from the development of renewable energy assets to the adoption of IoT devices like energy storage and EVs.

Our joint work is illustrating how blockchain and credible data can ensure that energy users have a more complete and accurate picture of their energy use and associated impact than they’ve ever had before. In this case and many others, the blockchain solution doesn’t work nearly as well without a strong foundation of data to leverage.

We now have a sightline to a world in which it’s arguably never been easier to make emissions reductions a central and direct focus of corporate sustainability efforts. Emissions-focused work need not be overly complicated, nor relegated to sophisticated teams like those at Walmart. With WattTime-powered data and blockchain-based solutions like that of Swytch, we’re excited to see many more corporations add an emissions lens to their great work.

As the end of 2018 draws nearer, headlines are once again starting to crop up about the U.S. Environmental Protection Agency (EPA)—under the current White House administration—considering significant rollbacks of the Mercury and Air Toxics Standards (MATS) regulations, possibly even setting the stage for a full repeal.

This could be an unmitigated tragedy. In its short life—announced in 2011, implemented in 2012, and compliance required by 2015/2016—MATS has emerged as one of the single most-effective regulations in American history for protecting human health and the environment, especially from the ravages of mercury exposure.

Over the past half century, myriad regulations have been heralded for their role drastically reducing the harmful effects from known toxic pollutants: removing lead from gasoline and paint, removing arsenic from drinking water. MATS is of a similar echelon when it comes to drastically reducing mercury pollution from coal-fired power plants.

The resounding success of MATS: 86% mercury emissions reductions

An analysis by the Center for American Progress (CAP) found a 65% nationwide reduction in annual power plant mercury emissions during the three-year period 2014–2017. Since 2011, CAP finds an 82% drop.

WattTime also crunched the numbers for eight states throughout the Great Lakes region across a similar time period (2014–2018) and found even more striking results: an 86% reduction in mercury emissions. Perhaps just as importantly, these significant emissions reductions were not via a gradual decline over those years. Mercury emissions essentially fell off a cliff. Pre-MATS and post-MATS mercury emissions were night and day. In other words, the regulations were highly effective.

A victory for human health and the environment is at risk

Mercury’s profoundly negative health effects are well-known: it ranks on the World Health Organization’s top 10 list of chemicals that pose a major public health concern. It’s the economic tally of those health effects—and their subsequent impact on the U.S. economy—partly at the heart of the MATS controversy.

Environmental regulations like MATS are generally evaluated on the cost for industry to comply with the regulation vs. the dollar-value benefit (e.g., healthcare costs, economic productivity) the regulation delivers. Mercury emissions-reducing technology is not cheap. It costs the electric utility industry an estimated $9.6 billion per year to comply, prompting the New York Times to label it “the most expensive clean air regulation ever put forth by the federal government.” Some proponents of MATS argue that the cost of compliance is actually far less than the $9.6 billion estimate. But regardless, MATS compliance is relatively expensive.

On the other side of the coin is the economic value of the human health and environmental benefits MATS delivers. Original federal estimates put the direct mercury-reduction benefits at less than $10 million annually. Such meager numbers have generally been widely debunked. Harvard University’s School of Public Health notes that “mercury-related benefits from MATS are orders of magnitude larger than previously estimated,” on the scale of several billion dollars per year. Meanwhile, both the original federal estimates and subsequent third-party review estimate indirect co-benefits at a whopping $24–$80 billion annually, since mercury-related MATS-compliance technologies also reduce other harmful pollutants such as sulfur dioxide and nitrogen oxide.

If MATS is significantly weakened or repealed, mercury emissions are at risk of jumping up

Whether the true cost to run MATS compliance technology is $9.6 billion or something else, the fact is there remains a cost associated with the tech. Part of that expense is sunk upfront capital cost to install the technologies in the first place and part is ongoing operational costs to keep MATS-compliance technologies running.

Many utilities and other stakeholders have argued that the electricity sector broadly has already invested in these technologies, so there’s no sense going back to a pre-MATS world. To a degree, that’s true. But undoubtedly, coal-fired generators will have economic incentives to turn off their mercury emissions-reducing tech in a bid to reduce costs and stay more price-competitive.

If they do, the grid’s mercury emissions could rocket back up closer to their pre-MATS levels. For our part, WattTime will be watching. With our unique algorithms and near-real-time insights into grid emissions, we’ll be one of the first to know.

Possible pathways in a MATS (or post-MATS) future

There’s of course a big fork in the road looming just ahead, obscured by the fog of EPA uncertainty: either MATS continues in existence largely resembling its current form or MATS shrinks to a shadow of its former self, possibly disappearing entirely. If the latter—and legal challenges to its dissolution not withstanding—all is not necessarily lost.

WattTime’s Automated Emissions Reduction (AER) technology could potentially step in to do what an eviscerated MATS couldn’t. AER focuses in particular on marginal generators, those power plants “on the margin” of the dispatch curve that turn on or off in response to rising and falling electricity demand.

For customers passively using electricity, that all happens invisibly in the background of grid operations. But with smart devices controlling flexible electricity loads—thermostats, batteries, electric vehicles, electric water heaters, etc.—customers can start shifting the timing of their electricity demand to proactively turn marginal generators on or off, like a light switch for the electricity grid. And if we knew which power plants were on the margin when, we could start applying customer-driven criteria to the smart devices to effect specific outcomes, such as using more renewable energy and avoiding more fossil-fueled energy, or reducing marginal carbon and other GHG emissions, or—in the case of MATS—avoiding those generators with higher mercury emissions.

AER is the solution that delivers on this promise. In a (hopefully hypothetical) post-MATS world, AER could prove a powerful tool for avoiding mercury emissions in two critical ways:

First, direct implementation of AER on smart devices could shift electricity demand to avoid marginal generators with high mercury emissions rates and use more electricity during times when marginal generators are mercury emissions-free. According to WattTime analysis, attacking marginal mercury emissions in this way could reduce annual energy-related mercury emissions in the Great Lakes region by a meaningful 16% if AER were adopted at scale.

Second, broad customer adoption of AER could provide a strong market signal for fossil-fueled power plants to keep their MATS-compliance technologies running. With the United States’ merit order dispatch stack for electricity generators, a given power plant only provides power—and, importantly, only gets paid—if it’s part of the dispatch stack. Thus there’s strong incentive to stay in the stack.

Meanwhile, AER gives customers the power to help decide who’s in or out of the stack based on criteria such as emissions. If large numbers of customers leverage AER software to avoid power plants that have higher mercury emissions, those power plants will have a good reason to keep their MATS-compliance technologies running. That outcome would help reduce mercury emissions whenever those power plants are running, and not just when they’re on the margin.

Of course, here at WattTime we’re rooting for MATS to survive. Either way, however, AER remains a compelling tool that gives customers the power to choose clean energy—and, if need be, avoid what could be a lamentable increase in mercury emissions.

By Jamie Mandel and Gavin McCormick. Originally posted on RMI Outlet.

Carbon emissions are arguably the most important thing for our society to learn how to manage in the coming years. The largest single source of U.S. carbon emissions is our electricity system. And yet, we do not measure emissions from our electricity use correctly, meaning we cannot manage our emissions effectively.

But now, thanks to a new technology that accurately measures moment-to-moment carbon emissions on our electricity system, we can unlock a whole host of new opportunities to manage emissions creatively and with less effort. With new software that automatically tracks the actual emissions impacts associated with specific actions on the electricity system, both in real time and ahead of time, we can now use our appliances at times when our electricity is the cleanest.

End-use flexibility

Many uses of electricity have inherent flexibility—that is, the timing can be changed by small or large amounts without impacting the quality of the service that device is providing. As Rocky Mountain Institute explored in The Economics of Demand Flexibility, harnessing this flexibility can save consumers and companies money while lowering grid costs.

The same is true of carbon emissions—harnessing the flexibility of end-use devices can make them run, on average, 15 percent cleaner than a “dumb” device, at no cost or quality impacts for the end-user.

Millions of people and thousands of corporations try every day to manage their carbon emissions. Unfortunately, much of this effort occurs without measuring these emissions correctly. Personal and corporate efforts to manage carbon emissions from electricity typically happen in one of two ways:

1) Wthout any measurement, by focusing on efforts that are generally associated with reduced emissions. For example, many corporations invest in things like efficiency, solar PV, and grid-sourced clean energy, but do not attempt to quantify the emissions savings associated with specific investments.

2) With coarse measurement of average emissions intensity, primarily by using eGrid historical data to estimate averages for electricity-related emissions. For example, a corporation might deliberately site a data center at a location on the grid that is, on average, cleaner than other options and claim some associated carbon emissions savings.

Thanks to new technology, it is now possible instead to know the actual emissions impacts associated with specific actions at a specific place on the electricity system, in real time—and even ahead of time through predictive algorithms. More importantly, it is now possible to assess future decisions based on marginal—rather than average—emissions factors, which, according to most economists, is the correct way to properly understand emissions impacts.

The emissions hidden in the margins

The difference between average and marginal emissions factors can be very large, and quite important. An average factor refers to the amount of emissions generated over a given time, divided by the amount of energy produced in that time. For example, the U.S. Pacific Northwest gets most of its electricity from hydropower, a low-emissions energy resource, and thus its average emissions factor is very low.

A marginal emissions factor refers to rate at which emissions would change with a small change to electricity load. Continuing the simplified Pacific Northwest example, imagine a time when hydropower is providing 75 percent of the region’s power and gas-fired power plants are providing the remaining 25 percent. This means that the average emissions factor of power in the Pacific Northwest would be very clean, at 25 percent the emissions intensity of natural gas (approximately 210 lbs. CO2 per megawatt-hour (MWh)). So at first glance, a great way to reduce a company’s or a person’s carbon footprint would be to move to the Pacific Northwest, where the electricity is very clean.

Yet in many cases, natural gas is the marginal resource, meaning that if a new kilowatt-hour of electricity is needed at a certain time, it will be provided by natural gas. So a company or an individual moving to the Pacific Northwest would increase carbon emissions at a rate equal to 100 percent of natural gas (840 lbs. CO2 per MWh)—a very big difference! Thinking in marginal rather than average carbon emissions can dramatically affect a company’s or a person’s choice of optimal environmental impact.

Estimating emissions impacts based on average emissions factors can have these types of effects on a recurring basis, across the U.S. This is because the portfolio of generators dispatching energy into the grid changes every five to 15 minutes, changing the marginal resource. For example, Midwest utilities mostly burn coal at night; if you own an electric vehicle there, you would have lower CO2 emissions if you deliberately charged it during the day. On the other hand, California’s electricity market has more efficient gas plants on the margin at night than during the day, so you should charge your electric vehicle (EV) in the evening to minimize your CO2 emissions. And with an Internet-connected EV charger, you can cut emissions even further with micro-timing. For example, you can time the EV charging to shut down when less-efficient peaking plants briefly kick on (say when the wind subsides or a cloud passes over), and turn it back on five minutes later when the wind returns or the cloud moves on and the marginal generator is cleaner.

Things you can do when you account for carbon emissions correctly

Accounting for carbon emissions correctly unlocks a whole host of new emissions-management opportunities. You can:

• Change the timing of energy use: As noted above, this is likely the easiest and largest source of untapped savings since it doesn’t take any additional investments or impact end-use quality. It simply takes advantage of emerging controls technology associated with Internet-connected devices. Thermostats, EV chargers, commercial-scale HVAC units, and demand-response programs, for example, can all run with lower emissions rates with just a few lines of computer code.
• Change the location of both electricity use and generation: By locating energy generating (or consuming) facilities in a particular place, you can affect which power plants they take offline or use. Each MWh produced by a wind farm in West Virginia reduces twice as much carbon as a MWh from an identical farm in California. Yet today, a corporate buyer of renewable energy would view these two wind projects identically. To help buyers start to understand these effects, RMI’s Business Renewables Center has begun to track emissions intensity—the differences in emissions reduction from different renewables projects.
• Value different energy conservation measures based on their actual carbon reduction potential: Today, all so-called negawatts, or avoided energy generation, are valued equally. But negawatts should have different values, as the Ohio and Texas examples show. A negawatt that displaces a kilowatt of coal power does more good to the planet than a negawatt that displaces a kilowatt of natural gas, wind, or hydropower. Valuing on-site energy conservation measures and distributed generation based on actual emissions reduction potential can support better decision-making.
• Price carbon markets correctly: If we do move to a world in which carbon emissions have a price, it would be great if it has the right price. Currently, renewable energy credits (RECs) and carbon offsets are priced, but only on average carbon impacts. Differentiating highly carbon-reducing RECs will lead to more cost-effective emissions reduction.

RMI and WattTime are working together to measure carbon emissions correctly and reduce them cost-effectively.

WattTime is a California-based nonprofit that has developed software to accurately forecast carbon emissions on the margin, in real time. This data can be used to control the timing of device charging, apply carbon emissions data to the models that renewable energy developers use to site projects, provide strategic advice to corporations on how to most cost-effectively reduce emissions, and provide more accurate reporting and verification of emissions.

RMI is using this new technological tool to unlock new markets for carbon reduction, and to maximize the value of these reductions. This technology can be used to improve the profitability of distributed energy resource companies and retail energy providers by lowering customer acquisition costs, accelerating corporate sustainability efforts, and improving the way that carbon emissions are measured and, ultimately, priced.

For example, 240 EV customers nationwide are charging their EVs with cleaner energy than their neighbors. Thousands of thermostat customers in Chicago are learning that cooling their houses with fewer carbon emissions is as easy as pushing a button. By using WattTime, millions of independent devices can be seamlessly checking the emissions content of the grid and making small decisions about the timing of electricity use to lower carbon emissions.

A key founding principle at RMI is that people don’t want raw kilowatt-hours. They want hot showers, cold beer, and illumination. Similarly, the planet doesn’t care how many kilowatt-hours we reduce. It cares how much we reduce CO2 emissions. So why not start measuring them directly? Together, we will help people and companies easily reduce their carbon emissions to help create a world that’s thriving, verdant, and secure, for all, for ever.

What’s the problem?

WattTime analyzes power grid data in real time from dozens of open data sources. Because the data is used to optimize the behavior of smart devices in real time, it is very important that we always have the most accurate up-to-date data. This means that we have had to tackle a classic engineering problem: building a highly reliable system out of less reliable components.

There are two main sources of unreliability in our data ingestion system. First, any of our incoming data sources can go down for a period of time without warning, creating a gap in our data record. Second, our cluster of worker servers may not run the data scraping jobs for any number of reasons, deepening the potential gaps. You can see how we’re in a tricky predicament of always needing the most accurate data and yet having a number of reasons for something to go wrong.

As the saying goes, if you can’t measure it, you can’t manage it. Today’s post explains how we built a monitoring and alerting system to detect gaps in our data ingestion pipeline using Librato.

Designing the Solution

Here are the primary characteristics we wanted in a monitoring and alerting system:

1. The solution needs to run 24/7. We want to provide our end-users with cleanest available energy, and whether the current energy supply is clean can change every five minutes. If our data is not up-to-date, then the energy supply can change without our knowledge, and we might miss an opportunity to give our users a choice to save carbon.

1. The solution needs to run in a way that's isolated/decoupled from how the data scraping tasks normally get run. We don’t want our monitoring system to be dependent on the system it’s supposed to be monitoring! This means that we’d either have to spin up our own separate monitoring service (and maybe a monitor for the monitor…) or use a reliable third-party SaaS tool.

1. The solution needs to have a way to identify any new gaps in our data as soon as possible, so we can triage and fix the problem before it gets worse. If we’re using a third-party tool, that means we need to give it a way to hook into our data pipeline.

1. The solution needs to have a way to send us alert messages when a problem occurs. We like the workflow of Slack, but email would be ok as a fallback.

1. The solution should make it easy to configure the frequency and thresholds for triggering alerts. Overly noisy alerting systems get ignored, so we thought it was a good idea that any system we implemented didn’t bombarded us with notifications, just sending the important actionable ones.

The WattTime API is currently running on Heroku, a popular cloud platform-as-a-service provider. Heroku has a great ecosystem of high-quality third-party “add-ons” that we can trust to have good uptime (satisfying criterion #1), even if something bad happens on our end (satisfying criterion #2). We decided to start by surveying Heroku’s add-ons to see which ones would help us satisfy our other design criteria: data pipeline integration (#3), Slack integration (#4), and configurability (#5).

After some doc hunting, we established that many add-ons had Slack integration, so that didn’t narrow our solution space very far. Instead, we decided to make our choice primarily based on the mechanism of integrating with our data pipeline. There was a wide range of options here: some add-ons would collect data from us if we printed it to our logs, others would collect data if we raised an exception, etc. Exception-based add-ons would be a great fit for detecting failed requests during data ingestion, but they wouldn’t help us monitor failures in our worker cluster overall. A sufficiently configurable log-based add-on, on the other hand, would be able to send alerts either if a problematic value appeared in the logs, or if the log stream stopped getting updated altogether. If such an add-on existed, it would allow us to meet all five design criteria.

And it does: Librato! Librato is a service for visualizing and creating alerts based on metrics. The Heroku add-on comes preconfigured to read metrics from Heroku log streams. In fact, we were already using Librato to visualize dyno performance metrics that Heroku printed to our log stream—but we hadn’t tried configuring any alerts. Reading Librato’s docs on alerts, we discovered that it supports both kinds of alert triggers we wanted. This made it a great choice for a monitoring service that we can configure to watch our data and alert us if something unexpected happens.

Step 1: Logging data quality

Librato is organized around the concept of a “metric.” A Librato metric can be any kind of time series data: something that can be graphed with a time stamp on the x axis and a number on the y axis. When the metric hasn’t been reporting or hasn’t logged a new datapoint within a certain period of time, visualizations like this can help us clearly see what is going on.

We chose “lag time” as the metric to track. We define lag time as the age of the most recently ingested data point of a particular type. Lag time serves as a good metric because it helps us get to the heart of the problem. If our goal is to have the most accurate up-to-date data, we’d like to know when our gaps start and for how long they occurred for.

To implement data quality logging, every time we collect data, we figure out how old the newest data point is, and print that number of minutes to the logs in Librato’s specific format. Here’s a screenshot of what the output looks like in our Papertrail logs:

Step 2: Setting up alerts

We have several ways to detect if something has gone wrong with our data collecting. If a new datapoint has not been added within an acceptable amount of time, then we may want to get alerted and see if there is anything we can do on our end. To do this, we set “condition type” to “goes above” when creating an alert:

We can also check if our metric stops reporting entirely. In that case, we set “condition type” to “stops reporting”. Both alerts serve to inform us as quickly as possible if something were to go wrong.

Step 3: Receiving alerts

To set up Slack integration, Librato requires you retrieving the Webhook URL for your Slack channel. In the Slack desktop app, go to the top left and click on Apps & Integration. This will take you to a directory of different apps that can integrate with Slack. Search for "Incoming WebHooks."

From there, go to "add configurations" and you should be able to find the webhook URL.

Once you have the URL, you can go to Librato’s Integrations tab and click “add configuration” on the Slack tab. Paste in the URL and give it a title you’ll be familiar with.

Then whenever an alert is triggered, you’ll receive a Slack message showing you why the alert was triggered and other relevant information. 

What we're thinking about next

While it’s really nice for our system to alert us whenever anything goes wrong, we thought that maybe it would be even better practice if our system was self-healing. As it stands, our system sends us an alert, and from there a living breathing human being has to take time out of what they’re doing and investigate. So for our next step, we will create a system to patch up data holes as they happen. In this way we can be more sure that we have the most accurate up-to-date data at any time.

Do you manage a large commercial or industrial facility? Perhaps a university, apartment complex, or hotel? Today we're pleased to share that, thanks to WattTime's newest partnership with Building Clouds, you can now cut your emissions through WattTime-enabled technology in nearly any equipment.

Facility managers everywhere have learned that not all equipment manufacturers play nice with each other and that interoperability is a major problem. What we love about Building Clouds Strati-Fi(TM) controllers is that they allow for remarkably quick and cost effective monitoring and control of most equipment types in commercial or industrial scale HVAC equipment. So whatever your building currently runs on, you can now WattTime-enable it by giving Building Clouds a call.

We've been working with Building Clouds for over a year to pilot this technology and work out all the kinks. Our first project began with Sutardja Hall, which became the first building in the world to optimize its HVAC package's energy loads in real time to cut carbon emissions. Building Clouds President Bob Wallace met with us on the rooftop of Sutardja Dai Hall and demonstrated the technology installation, which took place in under an hour. We were able to collect data almost immediately and automatically started cutting carbon less than a week later.

The implementation and results of this went over so well with UC Berkeley that we recently agreed upon a second project for the Residential and Student Services Building (RSSB). This deal included connecting the Strati-Fi(TM) controllers to WattTime-enable two sixty-ton air handlers. Both projects have successfully achieved absolutely zero increase in the building's energy bill or on occupant comfort. In fact, as a mischievous test, we did not announce the project until one month after installation, during which no building occupants were even aware of any change.

After over a year of successful pilots, we're delighted to share that WattTime and Building Clouds are scaling up our partnership to release our technology to the broader market. If you're looking for cost-effective building automation solutions that also cut emissions, please take a look at buildingclouds.com or WattTime's own Shop page.

We are thrilled to announce that WattTime has received a substantial grant from the Great Lakes Protection Fund to lead a coalition of nonprofits and companies in reducing mercury pollution from coal plants. The project will be a collaboration between WattTime, Rocky Mountain Institute, National Wildlife Federation, Delta Institute, Energy Emissions Intelligence, and several corporate partners.

In 2008, a Federal court struck down the national Clean Air Mercury Rule that required coal-fired power plants to limit dangerous mercury emissions. With repeated attempts to replace the rule continuing to face uncertain political futures, badly-needed efforts to return to safe mercury levels in the Great Lakes have stalled.

Right now if you're using the power grid near the Great Lakes, you're dumping mercury in the water.

But a core WattTime value is choice. Whether it's mercury, carbon dioxide, or any other pollutant, we believe nobody should be allowed to make you pollute without your consent.

So in collaboration with this powerhouse team of leading names in environmental activism and technology, WattTime will be developing and deploying technology to make it possible for people in the area to tune their smart devices to “just say no” to drawing power from the dirtiest mercury-spewing coal plants. You can read more about the project here.

Would your smart home or smart building technology company like to showcase your eco-friendly credentials and join our pilot? There's still time to get involved: contact us to learn more.

WattTime yesterday joined the University of California Carbon Neutrality Summit [link] as one of two featured startups for the Entrepreneurs forum [video]. At the conference, Governor Jerry Brown and UC President Janet Napolitano both spoke about the urgent need for more innovative climate change solutions.

Many speakers focused on Napolitano’s vow to turn the ten UC campuses into “living laboratories” to generate solutions that can be adopted on state, national and global levels.

“Climate change impacts issues as varied as disease management, food security, the preservation of water resources, the stability of fragile governments, and transportation infrastructure,” Napolitano said. “Addressing these challenges, and reducing our carbon footprint, is a moral imperative.” [source]

To address these challenges, the UC Climate Solutions Group presented 10 scalable solutions to move the world towards carbon neutrality. The group, comprised of 50 experts from 10 UC campuses and national laboratories, stressed the moral implications of climate change in the executive summary of their report: "Bending the Curve: Ten scalable solutions for carbon neutrality and climate stability.”

“15 percent of us contribute 60 percent of the pollution. We’re leaving behind a planet of uncertain future for our children, grandchildren and generations unborn,” said Veerabhadran Ramanathan, chair of the UC Climate Solutions Group.

As part of the Entrepreneurs forum, WattTime Executive Director Gavin McCormick spoke in particular of the importance of the UC’s “living laboratories” concept. Panelists agreed that the concept has been invaluable for helping ideas take off by allowing university facilities to be used to test innovative new ideas early on. McCormick remarked that early adoption of new WattTime technologies at UC Merced and UC Berkeley was a crucial factor in WattTime’s ability to calibrate our new carbon saving technology [link] to the daily operating needs of users.

“This is a call to action. We put all of our best minds in California on this — a very formidable force. Nothing less than that is required,” said Brown.