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BreezoMeter, which powers air quality in Apple’s Weather app, launches Wildfire Tracker

BreezoMeter has been on a mission to make environmental health hazard information accessible to as many people as possible. Through its air quality index (AQI) calculations, the Israel-based company can now identify the quality of air down to a few meters in dozens of countries. A partnership with Apple to include its data into the iOS Weather app along with its own popular apps delivers those metrics to hundreds of millions of users, and an API product allows companies to tap into its data set for their own purposes.

Right on the heels of a $30 million Series C round a few weeks ago, the company is radially expanding its product from air quality into the real-time detection of wildfire perimeters with its new product, Wildfire Tracker.

The new product will take advantage of the company’s fusion of sensor data, satellite imagery and local eyewitness reports to be able to identify the edges of wildfires in real time. “People expect accurate wildfire information just as they expect accurate weather or humidity data,” Ran Korber, CEO and co-founder, said. “It has an immediate effect on their life.” He added further that BreezoMeter wants to “try to connect the dots between climate tech and human health.”

Fire danger zones will be indicated with polygonal boundaries marked in red, and as always, air quality data will be viewable in these zones and in surrounding areas.

BreezoMeter’s air quality maps can show the spread of wildfire pollution. Image Credits: BreezoMeter.

Korber emphasized that getting these perimeters accurate across dozens of countries was no easy feat. Sensors can be sparse, particularly in the forests where wildfires ignite. Meanwhile, satellite data that focuses on thermal imaging can be fooled. “We’re looking for abnormalities … many of the times you have these false positives,” Korber said. He gave an example of a large solar panel array which can look very hot with thermal sensors, but obviously isn’t a fire.

The identified fire perimeters will be available for free to consumers on BreezoMeter’s air quality map website, and will shortly come to the company’s apps as well. Later this year, these perimeters will be available from the company’s APIs for commercial customers. Korber hopes the API endpoints will give companies like car manufacturers the ability to forewarn drivers that they are approaching a conflagration.

The new feature is just a continuation of BreezoMeter’s longtime expansion of its product. “When we started, it was just air quality … and only forecasting air pollution in Israel,” Korber said. “Almost every year since then, we expanded the product portfolio to new environmental hazards.” He pointed to the addition of pollen in 2018 and the increasingly global nature of the app.

Wildfire detection is an, ahem, hot area these days for VC investors. For example, Cornea is a startup focused on helping firefighters identify and mitigate blazes, while Perimeter wants to help identify boundaries of wildfires and give explicit evacuation instructions, complete with maps. As Silicon Valley’s home state of California and much of the world increasingly become a tinderbox for fires, expect more investment and products to enter this area.

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a16z leads investment in Firemaps, a marketplace for home hardening against wildfires

Wildfires are burning in countries all around the world. California is dealing with some of the worst wildfires in its history (a superlative that I use essentially every year now) with the Caldor fire and others blazing in the state’s north. Meanwhile, Greece and other Mediterranean nations have been fighting fires for weeks to bring a number of massive blazes under control.

With the climate increasingly warming, millions of homes just in the United States alone are sitting in zones at high risk for wildfires. Insurance companies and governments are putting acute pressure on homeowners to invest more in defending their homes in what is typically dubbed “hardening,” or ensuring that if fires do arrive, a home has the best chance to survive and not spread the disaster further.

SF-based Firemaps has a bold vision for rapidly scaling up and solving the problem of home hardening by making a complicated and time-consuming process as simple as possible.

The company, which was founded just a few months ago (in March), sends out a crew with a drone to survey a homeowner’s house and property if it is in a high-risk fire zone. Within 20 minutes, the team will have generated a high-resolution 3D model of the property down to the centimeter. From there, hardening options are identified and bids are sent out to trade contractors to perform the work on the company’s marketplace.

Once the drone scans a house, Firemaps can create a full CAD model of the structure and the nearby property. Image Credits: Firemaps.

While early, it’s already gotten traction. In addition to hundreds of homeowners who have signed up on its website and a few dozen that have been scanned, Andrew Chen of a16z has led a $5.5 million seed round into the business (the Form D places the round sometime around April). Uber CEO Dara Khosrowshahi and Addition’s Lee Fixel also participated.

Firemaps is led by Jahan Khanna, who co-founded it along with his brother, who has a long-time background in civil engineering, and Rob Moran. Khanna was co-founder and CTO of early ridesharing startup Sidecar, where Moran joined as one of the company’s first employees. The trio spent cycles exploring how to work on climate problems, while staying focused on helping people in the here and now. “We have crossed certain thresholds [with the climate] and we need to get this problem under control,” Khanna said. “We are one part of the solution.”

Over the past few years Khanna and his brother explored opening a solar farm or a solar-powered home in California. “What was wild, whenever we talked to someone, is they said you cannot build anything in California since it will burn down,” Khanna said. “What is kind of the endgame of this?” As they explored fire hardening, they realized that millions of homeowners needed faster and cheaper options, and they needed them sooner rather than later.

While there are dozens of options to harden a home to fire, some popular options include constructing an ember-free zone within a few feet of a home, often by placing gravel made of granite on the ground, as well as ensuring that attic vents, gutters and siding are fireproof and can withstand high temperatures. These options can vary widely in cost, although some local and state governments have created reimbursement programs to allow homeowners to recoup at least some of the expenses of these improvements.

A Firemaps house in 3D model form with typical hardening options and associated prices. Image Credits: Firemaps.

The company’s business model is simple: vetted contractors pay Firemaps to be listed as an option on its platform. Khanna believes that because its drone offers a comprehensive model of a home, contractors will be able to bid for contracts without doing their own site visits. “These contractors are getting these shovel-ready projects, and their acquisition costs are basically zero,” Khanna said.

Long-term, “our operating hypothesis is that building a platform and building these models of homes is inherently valuable,” Khanna said. Right now, the company is launched in California, and the goal for the next year is to “get this model repeatable and scalable and that means doing hundreds of homes per week,” he said.

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With more cash and a launch, Vannevar Labs is reconnecting Silicon Valley to its defense industry roots

Silicon Valley was once one of the most productive regions in the country for the defense industry, churning out chips and technologies that helped the United States overtake the Soviet Union during the Cold War. Since then, the region has been known far less for silicon and defense than for the consumer internet products of Google, Facebook and Netflix.

A small number of startups, though, are attempting to revitalize that important government-industry nexus as the rise of China pushes more defense planners in Washington to double down on America’s technical edge. Vannevar Labs is one of this new crop, and it has hit some new milestones in its quest to displace traditional defense contractors with Silicon Valley entrepreneurial acumen.

I last chatted with the company just as it was debuting in late 2019, having raised a $4.5 million seed. The company has been quiet and heads down the past two years as it developed a product and traction within the defense establishment. Now it’s ready to reveal a bit more of what all that work has culminated in.

First, the company officially launched its Vannevar Decrypt product in January of this year. It’s focused on foreign language natural language processing, organizing overseas data and resources that are collected by the intelligence community and then immediately translating and interpreting those documents for foreign policy decisionmakers. CEO and co-founder Brett Granberg said that the product “went from one deployment to a dozen adoptions.”

Second, the company raised a $12 million Series A investment in May from Costanoa Ventures and Point72, with General Catalyst participating. Costanoa and GC co-led the startup’s seed round.

Finally, the company has been on a hiring spree. The team has grown into a crew of 20 employees, and the firm last week brought on Scott Sanders to lead business development. Sanders was one of the earliest employees at Anduril, and had spent several years at the company. Vannevar also added to its board John Doyle, a long-time Palantir employee who was head of its national security business, according to Granberg. Today, the team is equally split between national security folks and technologists, and he says that the team is set to double this year.

Vannevar Labs

Co-founders Nini Moorhead and Brett Granberg of Vannevar Labs. Photo via Vannevar Labs.

With a few years of hindsight, Granberg says that he has refined what he considers the best model for defense tech startups to break into the hardscrabble market at the Pentagon and across Northern Virginia.

First, there needs to be incredible focus on getting access to actual end users and learning their work. The functions that defense and intelligence personnel perform are completely different from operations in the commercial economy, and trying to translate what works at a large corporation into defense is a fool’s errand. “You need to have both the DNA of understanding new technology and the DNA of deeply understanding a lot of different use cases within DoD,” Granberg said, referencing the Department of Defense.

That has directly informed how Decrypt has developed over time. “We started focusing on the counter-terrorism space, and as the government moved away from counter-terrorism, we started moving to the foreign actors that were important,” he said. “Once we have our first couple of deployments, we are able to iterate very, very quickly.”

He also strongly eschews a popular view in defense procurement circles that there are “dual-use” technologies that can be used equally well in commercial and defense applications. “Some of the most important mission problems where the government spends the most money and has the most interest,” he explained, are also contexts where commercial off-the-shelf products (dubbed COTS in the industry parlance) are least useful. He says startups targeting defense simply cannot split their bandwidth by also trying to learn commercial use cases.

In fact, he went so far to predict that “you are going to see a lot of companies that have raised a lot of money that will fizzle out in the coming years” because they just can’t nail the dual-use model well.

Second, he argues that defense tech startups need to move beyond the model that each company should work on one platform, and instead move to an organizational model where a company offers multiple products to reach scale. Each product has the potential to reach “a couple of hundred million in revenue,” according to Granberg, but it is hard to expand a company’s size if it doesn’t parallelize product development.

To that end, Granberg said that he pushes Vannevar Labs to always be exploring new product lines for growth. “Decrypt is our first product [but]10% of our energy is in new product efforts,” he said. “I can imagine when we are three to four years down the line… it might be nine-10 products.” He said that the one platform approach might have worked for Palantir, which ironically, is the major winner in the defense tech space the last few years. But newer companies like Anduril and Shield AI have been designed around product line expansion.

Finally, noting those other companies, Granberg believes there is something of a collective benefit as each startup makes headway in the defense sector. “There is this theory in our space that we don’t view ourselves as competitors — if one of us does well, we all do well,” he said. Given the varied mission requirements of different agencies and the absolute massive scale of budgets in this field, startups actually have a lot of independent terrain to explore, even if they come up against the big legacy defense contractors on a regular basis.

As for Vannevar Labs, its next goal is to turn its Decrypt product into a program of record, which would guarantee it a certain level of sales and revenue for potentially years into the future. That’s a huge bar to leap, but would be a turning point in the company’s long-term trajectory.

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The tough calculus of emissions and the future of EVs

Investors and politicians embracing a vision of an all-electric car future believe that path will significantly reduce global carbon dioxide emissions. That’s far from clear.

A growing body of research points to the likelihood that widespread replacement of conventional cars with EVs would likely have a relatively small impact on global emissions. And it’s even possible that the outcome would increase emissions.

The issue is not primarily about the emissions resulting from producing electricity. Instead, it’s what we know and don’t know about what happens before an EV is delivered to a customer, namely, the “embodied” emissions arising from the labyrinthine supply chains to obtain and process all the materials needed to fabricate batteries.

All products entail embodied emissions that are ‘hidden’ upstream in production processes, whether it’s a hamburger, a house, a smartphone, or a battery. To see the implications at the macro level, credit France’s High Climate Council for a study issued last year. The analysis found that France’s claim of achieving a national decline in carbon dioxide emissions was illusory. Emissions had in fact increased and were some 70% higher than reported once the embodied emissions inherent in the country’s imports were counted.

Embodied emissions can be devilishly difficult to accurately quantify, and nowhere are there more complexities and uncertainties than with EVs. While an EV self-evidently emits nothing while driving, about 80% of its total lifetime emissions arise from the combination of the embodied energy in fabricating the battery and then in ‘fabricating’ electricity to power the vehicle. The remaining comes from manufacturing the non-fuel parts of the car. That ratio is inverted for a conventional car where about 80% of lifecycle emissions come directly from fuel burned while driving, and the rest comes from the embodied energy to make the car and fabricate gasoline.

Virtually every feature of the fuel-cycle for conventional cars is well-understood and narrowly bounded, significantly monitored if not tightly regulated, and largely assumption-free. That’s not the case for EVs.

For example, one review of fifty academic studies found estimates for embodied emissions to fabricate a single EV battery ranged from a low of about eight tons to as high as 20 tons of CO2. Another recent technical analysis put the range at about four to 14 tons. The high end of those ranges is nearly as much CO2 as is produced by the lifetime of fuel burned by an efficient conventional car. Again, that’s before the EV is delivered to a customer and driven its first mile.

The uncertainties come from inherent—and likely unresolvable—variabilities in both the quantity and type of energy used in the battery fuel cycle with factors that depend on geography and process choices, many often proprietary. Analyses of the embodied energy show a range from two to six barrels of oil (in energy-equivalent terms) is used to fabricate a battery that can store the energy-equivalent of one gallon of gasoline. Thus, any calculation of embodied emissions for an EV battery is an estimate based on myriad assumptions. The fact is, no one can measure today’s or predict tomorrow’s EV carbon dioxide ‘mileage.’

As more dollars flood into government programs and climate-tech funds — 2021 is on track to blow past record 2020 climate-tech investments, with three firms alone, BlackRock, General Atlantic and TPG, each announcing new $4 to $5 billion cleantech funds — we’re overdue for paying serious attention to embodied emissions of EVs and other presumed technological panaceas for reducing carbon dioxide emissions. As we will see shortly, the attention may not reveal the expected outcomes.

Data (on) mining

The goal for any vehicle is to have the fuel system take as small a share of total weight as possible, leaving room for passengers or cargo. Lithium batteries, as revolutionary and Nobel-prize worthy as they are, still constitute a distant second place in the metric of merit for powering untethered machines: energy density.

The inherent energy density of lithium-class chemicals (i.e., not a battery cell, but the raw chemical) can be theoretically as high as about 700 watt-hours per kilogram (Wh/kg). While that’s roughly five-fold greater than the energetics of lead-acid battery chemistry, it’s still a small fraction of the 12,000 Wh/kg available in petroleum.

To achieve the same driving range as 60 pounds of gasoline, an EV battery weighs about 1,000 pounds. Not much of that gap is closed by the lower weight of an electric versus gasoline motor because the former is typically only about 200 pounds lighter than the latter.

Manufacturers offset some of a battery’s weight penalty by lightening the rest of the EV using more aluminum or carbon-fiber instead of steel. Unfortunately, those materials are respectively 300% and 600% more energy intensive per pound to produce than steel. Using a half ton of aluminum, common in many EVs, adds six tons of CO2 to the non-battery embodied emissions (a factor most analyses ignore.) But it’s with all the other elements, the ones needed to fabricate the battery itself, where the emissions accounting gets messy.

There are many combinations of elements possible for lithium battery chemistries. Choices are dictated by compromises to meet a battery’s mix of performance metrics: safety, density, charge rate, lifespan, etc. Depending on the specific formulation chosen, the embodied energy associated with the key battery chemicals themselves can vary by as much as 600%.

Consider the key elements in the widely used nickel-cobalt formulation. A typical 1,000-pound EV battery contains about 30 pounds of lithium, 60 pounds of cobalt, 130 pounds of nickel, 190 pounds of graphite, and 90 pounds of copper. (The balance of the weight is with steel, aluminum, and plastic.)

Uncertainties in the embodied energy begin with the ore grade, or share of rock that contains each target mineral. Ore grades can range from a few percent to as little as 0.1 percent depending on the mineral, the mine, and over time. Using today’s averages, the quantity of ore mined—necessarily using energy-intensive heavy equipment—for one single EV battery is about: 10 tons of lithium brines to get to the 30 pounds of lithium; 30 tons of ore to get 60 pounds of cobalt; 5 tons for the 130 pounds of nickel; 6 tons for the 90 pounds of copper; and about one ton of ore for the 190 pounds of graphite.

Aerial view of trucks loading brine from the evaporation pools of the new state-owned lithium extraction complex, in the southern zone of the Uyuni Salt Flat, Bolivia, on July 10, 2019. Image Credits: PABLO COZZAGLIO/AFP via Getty Images

Then, one must add to that tonnage the “over-burden,” the amount of earth that’s first removed in order to access the mineral-bearing ore. That quantity also varies widely, depending on ore type and geology, typically from about three to seven tons excavated to access one ton of ore. Putting all the factors together, fabricating a single half-ton EV battery can entail digging up and moving a total of about 250 tons of earth. After that, an aggregate total of roughly 50 tons of ore are transported and processed to separate out the targeted minerals.

Embodied energy is also impacted by a mine’s location, something that is in theory knowable today but is a guessing-game regarding the future. Remote mining sites typically involve more trucking and depend on more off-grid electricity, the latter commonly supplied by diesel generators. As it stands today, the mineral sector alone accounts for nearly 40% of global industrial energy use. And over one-half of the world’s batteries or the key battery chemicals are produced in Asia with its coal-dominated electric grids. Despite hopes for more factories in Europe and North America, every forecast sees Asia utterly dominating that supply chain for a long time.

The wide variability of power grids and batteries

Most analyses of EV emissions don’t ignore the embodied carbon debt in batteries. But that factor is typically, and simplistically, assigned a single value in order to calculate the variabilities arising from using EVs on different electric grids.

A recent analysis from the International Council on Clean Transportation (ICCT) is usefully illustrative. The ICCT, using a fixed carbon debt for a battery, focused on how the EV carbon footprint varies depending on where it’s driven in Europe. The calculations showed that, compared to a fuel-efficient conventional car, an EV’s lifecycle emissions can range from as much as 60% lower when driven in Norway or France, to about 25% lower when driven in the U.K., to tiny emissions reduction if driven in Germany. (Germany’s grid has roughly the same average carbon emissions per kilowatt-hour as does America’s.)

Their analysis used average grid emissions data that don’t necessarily represent emissions that occur when plugged in. But the specific time, not the average, determines the actual source of electricity used for ‘fueling.’ No such ambiguities attend to the location and time of gasoline use; it’s always the same anytime and anywhere on the planet. While the EV time factor has minimal variability in Norway and France where most electricity comes around the clock from hydro and nuclear respectively, it can vary wildly elsewhere from, say, 100% solar to 100% coal depending on the time of day, month and location.

The lignite-fired power station of Boxberg in Germany. The region of Lusatia in the east of Germany and its economic infrastructure is heavily dependent on the coal-fired power plants in Jaenschwalde, Schwarze Pumpe and Boxberg. Image Credits: Florian Gaertner/Photothek via Getty Images

Another recent ICCT analysis also used annualized grid averages and calculated that, compared to an average car, lifecycle emissions reductions range from about 25% for EVs in India to 70% in Europe. But, as with the similar exercise for intra-European comparisons, a single, fixed carbon debt for battery fabrication was assumed, and a low value at that.

There is good reason to consider the implications of the range of embodied battery emissions, rather than a single, low average value, because the IEA (amongst others) reports that most mineral production today entails processes at the higher end of emissions “intensity.” Adjusting the ICCT outcomes for that reality lowers the calculated lifecycle EV emissions savings to about 40% (instead of 60%) driving in Norway, to little or no reduction in the U.K. or the Netherlands, and about a 20% increase for EVs driven in Germany.

That’s not the end of the real-world uncertainties. The ICCT, again typical of many similar analyses, made calculations based on batteries 30% to 60% smaller than the size required to replicate the 300-mile range needed for widespread replacement of conventional cars. The larger batteries are common on high-end EVs today. Doubling the size of the battery leads to a straightforward doubling of its carbon debt which, in turn, dramatically erodes or eliminates lifecycle emissions savings in many, maybe most places.

Similarly problematic, one finds forecasts of future emissions savings often explicitly assume that the future battery supply chain will be located in the country where the EVs operate. One widely cited analysis assumed aluminum demand for U.S. EVs would be met by domestic smelters and powered mainly from hydro dams. While that may be theoretically possible, it doesn’t reflect reality. The United States, for example, produces just 6% of global aluminum. If one assumes instead the industrial processes are located in Asia, the calculated lifecycle emissions are 150% higher.

For EV carbon accounting, the problem is that there are no reporting mechanisms or standards even remotely equivalent to the transparency with which petroleum is obtained, refined, and consumed. The challenges in having accurate data are not lost on the researchers, even if those concerns don’t percolate up into executive summaries and media claims. In the technical literature one often finds cautionary statements such as a “greater understanding of the energy required to manufacture Li-ion battery cells is crucial for properly assessing the environmental implications of a rapidly increasing use of Li-ion batteries.” Or in another recent research paper: “Unfortunately, industry data for the rest of the battery materials remain meager to nonexistent, forcing LCA [lifecycle analysis] researchers to resort to engineering calculations or approximations to fill the data gaps.”

Those “data gaps” become chasms when it comes to expanding the world’s mineral supply chain to support the production of tens of millions of more EVs.

Turning up the volume

Perhaps the most important wildcard is the expected rise in energy costs associated with obtaining the necessary quantities of “energy transition minerals,” (ETMs) as the International Energy Agency (IEA) terms them.

Earlier this year, the agency issued a major report on the challenges of supplying ETMs to build batteries as well as solar and wind machines. The report reinforces what others have earlier pointed out. Compared to conventional cars, EVs require using, overall, about 500% more critical minerals per vehicle. Thus, the IEA concludes that current plans for EVs, along with plans for wind and solar, will require a 300% to 4,000% increase in global mine output for the necessary suite of key minerals.

The fact that an EV uses, for example, about 300 to 400% more copper than a conventional car has yet to impact global supply chain because EVs still account for less than 1% of the total global auto fleet. Producing EVs at scale, along with plans for grid batteries as well as for wind and solar machines, will push the “clean energy” sector up to consuming over half of all global copper (from today’s 20% level). For nickel and cobalt, to note two other relevant minerals, “transition” aspirations will push clean energy use of those two metals to 60% and 70%, respectively of global demand, up from a negligible share today.

Tesla Inc. vehicles in a parking lot after arriving at a port in Yokohama, Japan, on Monday, May 10, 2021. Image Credits: Toru Hanai/Bloomberg via Getty Images

To illustrate the ultimate scale of demand that EV mandates alone will place on mining, consider that a world with 500 million electric cars—which would still constitute under half of all vehicles—would require mining a quantity of energy minerals sufficient to build batteries for about 3 trillion smartphones. That’s equal to over 2,000 years of mining and production for the latter. For the record, that many EVs would eliminate only about 15% of world oil use.

Set aside the environmental, economic, and geopolitical implications of such a staggering expansion of global mining. The World Bank cautions about “a new suite of challenges for the sustainable development of minerals and resources.” Such an increase in mining has direct relevance for predictions about the future carbon intensity for minerals because acquiring raw materials already accounts for nearly one half of the life-cycle carbon dioxide emissions for EVs.

As the IEA report also observes, ETMs not only have a “high emissions intensity,” but trends show that the energy-use-per-pound mined has been rising because of long-standing declines in ore grades. If mineral demands accelerate, miners will necessarily chase ever lower grade ores, and increasingly in more remote locations. The IEA sees, for example, a 300% to 600% increase in emissions to produce each pound of lithium and nickel respectively.

Nickel mine, Thio, New Caledonia, French Overseas Collectivity, France. Image Credits: DeAgostini/Getty Images

Trends with copper are illustrative of the challenge. From 1930 to 1970, advances in the post-mining chemical processes led to a 30% drop in energy use to produce a ton of copper even though ore grades slowly declined. But those were one-time gains as optimized processes approached physics limits. Thus, during the four decades after 1970, as ore grade continued to decline, energy use per ton of copper increased, and returned to the same level as in 1930. That will be the pattern for the near future as ore grades continue to decline for other minerals.

Nonetheless, the IEA, like others, uses today’s putative average supply-chain emissions intensity to assert that EVs in the future will reduce emissions. But the data in the IEA’s own report point to rising embodied emissions for ETMs. Add to this the implications of far more solar and wind construction, which the IEA notes require 500% to 700% more minerals compared to building a natural gas power plant, and we’ll see even more pressure on the mining supply chain — which, in the commodity world, points to a dramatic rise in prices.

If the EV share of vehicles rises from today’s less than 1% and begins to approach a 10% share, the resource experts at Wood Mackenzie see untenable material demands: “Unless battery technology can be developed, tested, commercialised, manufactured and integrated into EVs and their supply chains faster than ever before, it will be impossible for many EV targets and ICE (internal combustion engine) bans to be achieved – posing issues for current EV adoption rate projections.”

There’s no evidence of capabilities to accelerate industry-class chemical development and manufacturing, or mining, in the short time-periods common in policy aspirations. Nearly three decades passed after the discovery of lithium battery chemistry before the first Tesla sedan.

Chasing carbon efficiencies in the battery supply chains

There are, of course, ways to ameliorate some of the factors that are dragging the world toward a future with increasing EV supply-chain emissions: better battery chemistry (reducing materials needed per kilowatt-hour of stored energy), more efficient chemical processes, electrifying mining equipment, and recycling. All of these are often offered as “inevitable” or “necessary” solutions. But none can have a significant impact in the time frames contemplated for rapid EV expansion.

Even though popular news stories frequently claim some “breakthrough,” there are no commercially viable alternative battery chemistries that significantly change the order-of-magnitude of the physical materials needed per electric-vehicle-mile. In most cases, changing chemistry formulations merely shifts burdens.

For example, reducing the use of cobalt is generally achieved by increasing nickel content. As for chemistries that eliminate the use of energetic atoms of, say, carbon or nickel, using instead, for example, more prosaic and low-energy-intensity elements like iron (e.g., the lithium-iron-phosphate battery), such formulations have lower energy density. The latter means a bigger, heavier battery is needed to maintain vehicle range. Still, it is reasonable to imagine the eventual discovery of a foundationally superior classes of battery chemistries. But once validated, it then takes many years to safely scale-up industrial chemical systems. Batteries put into cars today, and for the near future, will necessarily use technologies available now and not theoretically available someday.

Then there’s the prospect for improving the efficiency of the various chemical processes used in the mineral refining and conversion processes. Improvements there are inevitable, in no small part because that’s what engineers always do, and in the digital era they will more often find success. But there are no known “step function” changes on the horizon in the well-trod field of physical chemistry where processes already operate near physics limits. Put differently, lithium batteries are now well past the early stages where one sees rapid improvements in process (and cost) efficiencies and have entered the stage of incremental gains.

As for electrifying mining trucks and equipment, Caterpillar, Deere and Case (and others) all have such projects, and even a few production machines for sale. Promising designs are on the horizon for a few specific applications, but batteries are not up to the 24×7 performance demands to power heavy equipment in most uses. Moreover, the turnover rate in mining and industrial equipment is measured in decades. Mines will use a lot of oil-fired equipment for a very long time.

Finally, there’s recycling, commonly proposed to mitigate new demands. Even if all batteries were entirely recycled, it couldn’t come close to meeting the enormous increase in demand that will arise from the proposed (or mandated) growth path for EVs. In any case, there are unresolved technical challenges regarding the efficacy and economics of recycling critical minerals from complex machines, especially batteries. While one might imagine someday having automated recycling capabilities, nothing like that exists now. And given the variety of present and future battery designs, there’s no clear path to such capabilities in the timeframes policymakers and EV proponents have in mind.

Legal chaos and EV emissions credits

The unavoidable fact is that there are so many assumptions, guesses, and ambiguities that any claims of EV emissions reductions will be subject to manipulation if not fraud. Much of the necessary data may never be collectable in any normal regulatory fashion given the technical uncertainties, the variety and opacity of geographic factors, as well as the proprietary nature of many of the processes. Even so, the Securities and Exchange Commission is apparently considering such disclosure requirements. The uncertainties in the EV ecosystem could lead to legal havoc if European and U.S. regulators enshrine “green disclosures” in legally binding ways, or enforce “responsible” ESG metrics regarding carbon dioxide emissions.

For policymakers eager to reduce automotive oil use, engineers have already invented an easier and more certain way to achieve that goal while awaiting revolutions in battery chemistry and mining. Commercially viable combustion engines already exist that can cut fuel use by as much as 50%. Capturing just half that potential by providing incentives for consumers to purchase more efficient engines would be cheaper, faster—and transparently verifiable—than adding 300 million EVs to the world’s roads.

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FloodMapp wants to predict where water goes before it washes away your home

Floods are devastating. They rip asunder communities, wipe out neighborhoods, force the evacuation of thousands of people every year and recovering from them can take years — assuming recovery is possible at all. The U.S. government estimates that floods in recent decades (exclusive of hurricanes and tropical storms) have caused an estimated $160 billion in damage and killed hundreds of people.

One would think that we should have a real-time model for where water is and where it is going around the world, what with all of those sensors on the ground and satellites in orbit. But we mostly don’t, instead relying on antiquated models that fail to take into account the possibilities of big data and big compute.

FloodMapp, a Brisbane, Australia-based startup, is aiming to wash out the old approaches to hydrology and predictive analytics and put in place a much more modern approach to help emergency managers and citizens know when the floods are coming — and what to do.

CEO and co-founder Juliette Murphy has spent a lifetime in the water resources engineering field, and saw firsthand the heavy destruction that water can cause. In 2011, she watched as her friend’s home was submerged in the midst of terrible flooding. The “water went right over the peak of her house,” she said. Two years later in Calgary, she saw the same situation again: floods and fear as friends tried to determine whether and how to evacuate.

Those memories and her own professional career led her to think more about how to build better tools for disaster managers. She ultimately synced up with CTO and co-founder Ryan Prosser to build FloodMapp in 2018, raising $1.3 million AUD along with a matching grant.

The company’s premise is simple: We have the tools to build real-time flooding models today, but we just have chosen not to take advantage of them. Water follows gravity, which means that if you know the topology of a place, you can predict where the water will flow to. The challenge has been that calculating second-order differential equations at high resolution remains computationally expensive.

Murphy and Prosser decided to eschew the traditional physics-based approach that has been popular in hydrology for decades for a completely data-based approach that takes advantage of widely available techniques in machine learning to make those calculations much more palatable. “We do top down what used to be bottoms up,” Murphy said. “We have really sort of broken the speed barrier.” That work led to the creation of DASH, the startup’s real-time flood model.

FloodMapp’s modeling of the river flooding in Brisbane. Image Credits: FloodMapp

Unlike typical tech startups though, FloodMapp isn’t looking to be its own independent platform. Instead, it interoperates with existing geographic information systems (GIS) like ESRI’s ArcGIS by offering a data layer that can be combined with other data streams to provide situational awareness to emergency response and recovery personnel. Customers pay a subscription fee for access to FloodMapp’s data layer, and so far, the company is working with the Queensland Fire and Emergency Services in Australia as well as the cities of Norfolk and Virginia Beach in Virginia.

But it’s not just emergency services the startup is ultimately hoping to attract. Any company with physical assets, from telcos and power companies to banks and retail chains with physical stores could potentially be a customer of the product. In fact, FloodMapp is betting that the SEC will mandate further climate change financial disclosures, which could lead to a … flood of new business (I get one flood pun, okay, I get one).

FloodMapp’s team has expanded from its original two founders to a whole crop of engineering and sales personnel. Image Credits: FloodMapp

Murphy notes that “we are still in our early stages” and that the company is likely to raise further financing early next year as it gets through this year’s flood season and onboards several new customers. She hopes that ultimately, FloodMapp will “not only help people, but help our country change and adapt in the face of a changing climate.”

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A close look at Singapore’s thriving startup ecosystem

Singapore is home to fewer than six million people, making it one of the smallest ASEAN countries, in terms of population. It is a young country as well — having gained independence in 1963 — and resides in a neighborhood with far larger economies, including China, Indonesia, and Vietnam. When the country first became independent, its mandate was to simply survive rather than thrive.

So how does a country evolve from a position of relative uncertainty, with comparatively few resources, to one that leads the ASEAN region in venture capital investment and has been home to 10 unicorns?

Countries around the world examine Singapore’s ecosystem from a distance, hoping to learn from, and emulate, its story. The World Bank Group recently published a report, The Evolution and State of Singapore’s Start-up Ecosystem, documenting the country’s experience in building its startup ecosystem and the challenges facing it.

This article presents an overview of the report’s key findings and offers a few key recommendations on what other countries can learn from Singapore’s experience, as well as what Singapore itself can do to maintain progress.

A glimpse into Singapore’s current startup ecosystem

As of 2019, Singapore had over $19 billion in PE and VC assets under management, more than twice that of neighboring Indonesia, Philippines, Vietnam, Malaysia, and Thailand combined. In that same year, the country was home to an estimated 3,600 tech startups and nearly 200 different intermediary and supporting organizations (accelerators, co-working spaces, coding academies, etc.) – some which have a multinational presence, such as Blk71, whose Singapore headquarters has been referred to as “the world’s most tightly packed entrepreneurial ecosystem.”

While assessing the size and strength of startup ecosystems is an evolving method, Start-up Genome priced Singapore’s ecosystem at over $25 billion, five times the global median.

Arguably, the most eye-catching hallmark of this ecosystem is its population of current and former unicorns. Collectively, Singapore has been home to ten unicorns, three of which have offered an IPO (Nanofilm, Razer and Sea) and two of which have been acquired – one by giant Alibaba (Lazada) and one by Chinese streaming powerhouse YY (Bigo Live). The remaining five are Trax, Acronis, JustCo, PatSnap, and Grab – the ASEAN region’s largest unicorn to date.

 

The education sector is also prominent in Singapore’s ecosystem. Universities like the National University of Singapore (NUS) and Nanyang Technological University (NTU) are deeply embedded into this ecosystem, helping with R&D commercialization linkages, incubation, talent/knowledge transfer, and other areas.

So, how did Singapore’s startup ecosystem come to be?

Numerous factors have contributed to building Singapore’s startup ecosystem, with government intervention and leadership being the dominant driving forces. The government has spent more than USD60 billion over the past several decades to enhance the country’s R&D infrastructure, create VC funds, and launch accelerators and other support organizations.

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Following the IPCC’s report, we need more technology to respond to more disasters

This week, the Intergovernmental Panel on Climate Change released its major sixth assessment report on the physical science of climate change. The details are grim, if getting more precise, as better and more comprehensive data becomes available. As my colleague Mike Butcher summarized yesterday, it’s “stern and blunt in its conclusions.”

While many of the themes of the report will be familiar to any person not living under (an ever increasingly hot) rock, one part jumped out at me as I was perusing the documents. The working group assessed that regardless of mitigation and adaptation strategies, many of the negative changes happening to Earth will continue unabated in all future scenarios. From the summary report:

Many changes due to past and future greenhouse gas emissions are irreversible for centuries to millennia, especially changes in the ocean, ice sheets and global sea level. […] Mountain and polar glaciers are committed to continue melting for decades or centuries (very high confidence). Loss of permafrost carbon following permafrost thaw is irreversible at centennial timescales (high confidence) …

In short, there is already momentum toward a warmer and more chaotic world, and we have limited tools to stop many of these trends.

There has been a rush of initiatives, investments and startups bubbling around the theme of climate tech, with projects focused on everything from improving the yields and decreasing the emissions of agriculture and food production, to improving the power grid, and to reducing the emissions from air conditioning in buildings. Those initiatives are fine and important, but they don’t get at one of the toughest challenges facing us this century: that disasters are here, they are coming and they are going to continue to get more intense as the century rolls on.

Just this past week, we have seen the second-largest fire in California’s state history with the Dixie Fire, currently blazing across hundreds of thousands of acres in the northern reaches of the state. Meanwhile in Greece, hundreds of wildfires are causing an unprecedented crisis in that country. Droughts, floods, hurricanes, typhoons and more are intensifying and ravaging ever more billions of people across every continent.

One response to solving this problem is improving resilience — building up cities and structures as well as food and water systems that are fortified against these natural calamities. Many of those projects though are costly and also time-consuming, measured over the course of decades rather than months.

Instead, we need a more immediate push to develop better disaster response technology today. I’ve covered a wide segment of these companies over the past few months. There’s RapidSOS, which is adding more data into emergency calls to make responses faster and more efficient. There’s Qwake, which raised $5.5 million to build hardware and cloud services to allow firefighters to visualize their environments in smoky conditions. Meanwhile, YC-backed Gridware has also raised more than $5 million to create sensors to identify failures in the power grid faster.

In short, there are a growing crop of disaster tech startups — but more are going to be needed to fight the panoply of disasters that will strike in the years ahead.

There’s so much to do: better mental health resources for victims and first responders, easier access to recovery funds to heal lives, higher-quality sensors and data analyses to identify disasters earlier, faster logistics to evacuate people out of harm’s way. In fact, there are quite literally dozens of fields that need more investment and founder attention.

It’s not an easy market, as I pointed out in an analysis of sales cycles. Budgets are tight, disasters are random, and technology is often an afterthought. In some ways though, that friction is a font of creativity — how to build these next-generation of services and how to sell them is the risk that leads to the potential high return.

As the IPCC’s report made clear this week, the chaotic weather and intense disasters we’ve seen the past few decades aren’t going to abate any time soon. But with ingenuity, we can respond better to the disasters that are already on their way, and save lives and treasure in the process.

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China roundup: Games are opium, algorithms need scrutiny

Hello and welcome back to TechCrunch’s China roundup, a digest of recent events shaping the Chinese tech landscape and what they mean to people in the rest of the world.

The question for the tech news cycle in China these days has become: Who is Beijing’s next target? Regulatory clampdowns are common in China’s tech industry but the breadth of the recent moves has been unprecedented. No major tech giant is exempted and everyone is being attacked from a slightly different angle, but Beijing’s message is clear: Tech businesses are to align themselves with the interests and objectives of Beijing.

Education curbs hit tech giants

The government’s motivation isn’t always ideological. It could lead to policies that rein in the unruly private tutoring sector in the hope of easing pressure on students and parents. Recent orders from Beijing have strictly limited after-school tutoring, though they also sparked a wave of sympathy for public school teachers who work at lucrative tutoring centers to compensate for their meager salaries.

The effects of the education crackdown are also trickling down to internet companies. For the past few years, ByteDance had been aggressively building an online education business through a hiring and acquisition spree in part to diversify an ad-based video business. Its plan seems to be in shambles as it reportedly plans to lay off staff in its education department following recent the clampdown.

The restraints are also hitting American companies. Duolingo, the language learning app, was removed from several app stores in China. While it’s not immediately clear whether the action was the result of any policy change, the government recently, along with its restraints on extra-curriculum, barred foreign curricula in schools from K-9.

Games are opium

It could be tricky to read the top leaders’ minds because their messages could come through various government departments or state-affiliated media outlets, carrying different weights.

This week, Tencent is in the authorities’ crosshairs. About $60 billion of its market cap was wiped after the Economic Information Daily, an economic paper supervised by China’s major state news agency Xinhua, published an article (which was taken down shortly) describing video games as “spiritual opium” and cited the major role Tencent plays in the industry. Shares of Tencent’s smaller rival NetEase were also battered.

This certainly isn’t the first time Tencent and the gaming industry overall were slammed by the government for their impact on underage players. Tencent has been working to appease the authorities by introducing protections for young players, for instance, by tightening age checks several times.

Tencent, which has a sprawling online empire of social networks, payments and music on top of games, has also promised to “do [more social] good” through its products. And following the recent op-ed from the state paper, Tencent further restricted the amount of time and money children can spend inside games. But after all, the company still depends largely on addictive game mechanics that lure players to open loot boxes.

Tencent share prices over the past six months. Image Credits: Google Finance

Fix the algorithms

The other camp of tech companies feeling the heat is those dependent on machine learning algorithms to distribute content. The Propaganda Department of the Chinese Communist Party, the country’s watchdog of public expressions, along with several other government organs, issued an advisory to “strengthen the study and guidance of online algorithms and carry out oversight over algorithmic recommendations.”

The government’s goal is to assert more control over how algorithmic black boxes affect what information people receive. Shares of Kuaishou, TikTok’s archrival in China, tanked on the news. Since its blockbuster initial public offering in February, Kuaishou’s stock price has tumbled as much as 70%. Meanwhile, the Beijing-based short video firm is shuttering one of its overseas apps called Zynn, which has caused controversy over plagiarism. But its overseas user base is also rapidly growing, crystalizing in one billion monthly users worldwide recently.

End of “two-choose-one”

The week hasn’t ended. On Friday morning, The Wall Street Journal reported that the country’s antitrust regulator is preparing to fine Meituan, China’s major food delivery platform, $1 billion for allegedly abusing its market dominance. In 2020, Meituan earned 114.8 billion yuan or $17.7 billion in revenue.

Until recently, forcing suppliers to pick sides had been a common practice in China’s e-commerce world. Alibaba did so by forbidding sellers to list on rivaling platforms, a practice that resulted in a $2.75 billion antitrust penalty in April. We will see where the government will act next as it continues to curb the power of its tech darlings.

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RapidSOS learned that the best product design is sometimes no product design

Sometimes, the best missions are the hardest to fund.

For the founders of RapidSOS, improving the quality of emergency response by adding useful data, like location, to 911 calls was an inspiring objective, and one that garnered widespread support. There was just one problem: How would they create a viable business?

The roughly 5,700 public safety answering points (PSAPs) in America weren’t great contenders. Cash-strapped and highly decentralized, 911 centers already spent their meager budgets on staffing and maintaining decades-old equipment, and they had few resources to improve their systems. Plus, appropriations bills in Congress to modernize centers have languished for more than a decade, a topic we’ll explore more in part four of this EC-1.

Who would pay? Who was annoyed enough with America’s antiquated 911 system to be willing to shell out dollars to fix it?

People obviously desire better emergency services — after all, they are the ones who will dial 911 and demand help someday. Yet, they never think about emergencies until they actually happen, as RapidSOS learned from the poor adoption of its Haven app we discussed in part one. People weren’t ready to pay a monthly subscription for these services in advance.

So, who would pay? Who was annoyed enough with America’s antiquated 911 system to be willing to shell out dollars to fix it?

Ultimately, the company iterated itself into essentially an API layer between the thousands of PSAPs on one side and developers of apps and consumer devices on the other. These developers wanted to include safety features in their products, but didn’t want to engineer hundreds of software integrations across thousands of disparate agencies. RapidSOS’ business model thus became offering free software to 911 call centers while charging tech companies to connect through its platform.

It was a tough road and a classic chicken-and-egg problem. Without call center integrations, tech companies wouldn’t use the API — it was essentially useless in that case. Call centers, for their part, didn’t want to use software that didn’t offer any immediate value, even if it was being given away for free.

This is the story of how RapidSOS just plowed ahead against those headwinds from 2017 onward, ultimately netting itself hundreds of millions in venture funding, thousands of call agency clients, dozens of revenue deals with the likes of Apple, Google and Uber, and partnerships with more software integrators than any startup has any right to secure. Smart product decisions, a carefully calibrated business model and tenacity would eventually lend the company the escape velocity to not just expand across America, but increasingly across the world as well.

In this second part of the EC-1, I’ll analyze RapidSOS’ current product offerings and business strategy, explore the company’s pivot from consumer app to embedded technology and take a look at its nascent but growing international expansion efforts. It offers key lessons on the importance of iterating, how to secure the right customer feedback and determining the best product strategy.

The 411 on a 911 API

It became clear from the earliest stages of RapidSOS’ journey that getting data into the 911 center would be its first key challenge. The entire 911 system — even today in most states — is built for voice and not data.

Karin Marquez, senior director of public safety at RapidSOS, who we met in the introduction, worked for decades at a PSAP near Denver, working her way up from call taker to a senior supervisor. “When I started, it was a one-man dispatch center. So, I was working alone, I was answering 911 calls, non-emergency calls, dispatching police, fire and EMS,” she said.

RapidSOS senior director of public safety Karin Marquez. Image Credits: RapidSOS

As a 911 call taker, her very first requirement for every call was figuring out where an emergency is taking place — even before characterizing what is happening. “Everything starts with location,” she said. “If I don’t know where you are, I can’t send you help. Everything else we can kind of start to build our house on. Every additional data [point] will help to give us a better understanding of what that emergency is, who may be involved, what kind of vehicle they’re involved in — but if I don’t have an address, I can’t send you help.”

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ActiveFence comes out of the shadows with $100M in funding and tech that detects online harm, now valued at $500M+

Online abuse, disinformation, fraud and other malicious content is growing and getting more complex to track. Today, a startup called ActiveFence is coming out of the shadows to announce significant funding on the back of a surge of large organizations using its services. ActiveFence has quietly built a tech platform to suss out threats as they are being formed and planned to make it easier for trust and safety teams to combat them on platforms.

The startup, co-headquartered in New York and Tel Aviv, has raised $100 million, funding that it will use to continue developing its tools and to continue expanding its customer base. To date, ActiveFence says that its customers include companies in social media, audio and video streaming, file sharing, gaming, marketplaces and other technologies — it has yet to disclose any specific names but says that its tools collectively cover “billions” of users. Governments and brands are two other categories that it is targeting as it continues to expand. It has been around since 2018 and is growing at around 100% annually.

The $100 million being announced today actually covers two rounds: Its most recent Series B led by CRV and Highland Europe, as well as a Series A it never announced led by Grove Ventures and Norwest Venture Partners. Vintage Investment Partners, Resolute Ventures and other unnamed backers also participated. It’s not disclosing valuation but I understand it’s over $500 million.

“We are very honored to be ActiveFence partners from the very earliest days of the company, and to be part of this important journey to make the internet a safer place and see their unprecedented success with the world’s leading internet platforms,” said Lotan Levkowitz, general partner at Grove Ventures, in a statement.

The increased presence of social media and online chatter on other platforms has put a strong spotlight on how those forums are used by bad actors to spread malicious content. ActiveFence’s particular approach is a set of algorithms that tap into innovations in AI (natural language processing) and to map relationships between conversations. It crawls all of the obvious, and less obvious and harder-to-reach parts of the internet to pick up on chatter that is typically where a lot of the malicious content and campaigns are born — some 3 million sources in all — before they become higher-profile issues. It’s built both on the concept of big data analytics as well as understanding that the long tail of content online has a value if it can be tapped effectively.

“We take a fundamentally different approach to trust, safety and content moderation,” Noam Schwartz, the co-founder and CEO, said in an interview. “We are proactively searching the darkest corners of the web and looking for bad actors in order to understand the sources of malicious content. Our customers then know what’s coming. They don’t need to wait for the damage, or for internal research teams to identify the next scam or disinformation campaign. We work with some of the most important companies in the world, but even tiny, super niche platforms have risks.”

The insights that ActiveFence gathers are then packaged up in an API that its customers can then feed into whatever other systems they use to track or mitigate traffic on their own platforms.

ActiveFence is not the only company building technology to help platform operators, governments and brands have a better picture of what is going on in the wider online world. Factmata has built algorithms to better understand and track sentiments online; Primer (which also recently raised a big round) also uses NLP to help its customers track online information, with its customers including government organizations that used its technology to track misinformation during election campaigns; Bolster (formerly called RedMarlin) is another.

Some of the bigger platforms have also gotten more proactive in bringing tracking technology and talent in-house: Facebook acquired Bloomsbury AI several years ago for this purpose; Twitter has acquired Fabula (and is working on a bigger efforts like Birdwatch to build better tools), and earlier this year Discord picked up Sentropy, another online abuse tracker. In some cases, companies that more regularly compete against each other for eyeballs and dollars are even teaming up to collaborate on efforts.

Indeed, it may well be that ultimately there will exist multiple efforts and multiple companies doing good work in this area, not unlike other corners of the world of security, which might need more than one hammer thrown at problems to crack them. In this particular case, the growth of the startup to date, and its effectiveness in identifying early warning signs, is one reason investors have been interested in ActiveFence.

“We are pleased to support ActiveFence in this important mission,” commented Izhar Armony, a general partner at CRV, in a statement. “We believe they are ready for the next phase of growth and that they can maintain leadership in the dynamic and fast-growing trust and safety market.”

“ActiveFence has emerged as a clear leader in the developing online trust and safety category. This round will help the company to accelerate the growth momentum we witnessed in the past few years,” said Dror Nahumi, general partner at Norwest Venture Partners, in a statement.

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