agriculture
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Researchers at Carnegie Mellon University have discovered a new method for delivering key nutrients to plant roots – without having to ensure they’re present in the soil where the plants are growing.
The landmark study greatly increases the efficiency of surface delivery of nutrients and pesticides to plants. Currently, when crops are sprayed with stuff that’s supposed to help them grow faster or better, the vast majority of that (up to 95 percent, according to CMU’s engineering blog) will just end up either as concentrated deposits in the surrounding soil, or dissolving into ground water. In both cases, accumulation over time can have negative knock-on effects, in addition to being terribly inefficient at their primary task.
This method, described by researchers in detail in a new academic paper, would manage to improve efficiency to nearly 100% absorption of nutrients and pesticides delivered as nanoparticles (particles smaller than 50 nanometers across – a human hair is about 75,000 nanometers wide, for context) sprayed onto the leaves of plants, which then make their way through the plant’s internal vascular system all the way down into the root system.
Using this method, agricultural professionals could also greatly improve delivery of plant antibiotics, making it easier and more cost-effective to treat plant diseases affecting crop yields. It would be cheaper to delivery all nutrients and pesticides, too, because the big bump in efficiency of uptake by the plants means you can use much less of anything you want to deliver to achieve your desired effect.
This research could have huge impact in terms of addressing growing global food supply needs while making the most existing agricultural land footprint and decreasing the need for potentially damaging expansion of the same.
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Roughly $165 billion worth of wholesale produce is bought and sold every year in the U.S. And while that number is expected to go up to $1 trillion by 2025, the business of agribusiness remains unaffected by technology advancements that have reshaped almost every other industry.
Now Silo, a company that recently raised $3 million from investors led by Garry Tan and Alexis Ohanian’s Initialized Capital and including Semil Shah from Haystack Ventures, angel investors Kevin Mahaffey and Matt Brezina and The Penny Newman Grain Company, an international grain and feed marketplace, is looking to change that.
Silo’s chief executive, Ashton Braun, spent years working in commodities marketplaces as a coffee trader in Singapore and moved to California after business school. As part of the founding team at Kite with Adam Smith, Braun worked on getting off the ground Kite’s software to automate computer programming, but he’d never let go of creating a tool that could help farmers and buyers better communicate and respond to demand signals, Braun says.
“I was a super young, green, bright-eyed potential entrepreneur,” says Braun. Eventually, Braun took the opportunity to develop the software that had been on his mind for four-and-a-half years.*
He’d seen the technology work in another industry closer to home. Growing up in Boston, Braun had seen how technology was used to update the fishing industry, giving ships a knowledge of potential buyers of their catch while they were still out in ocean waters.
“When you’re moving a product that’s worth tens of thousands of dollars and has a shelf life of a few days there’s literally no room for error and there’s a lot you need to do,” says Braun. It’s a principle that applies not only to seafood but to the hundreds of millions of dollars of produce and meat that comes from farms in places like California. “What we want to do is we want communication and data to live in the right places at the right time.”
Braun says there’s limited data coming in to farmers to let them know what demand for certain produce looks like, so they’re making guesses that have real financial outcomes with very little data.
Silo’s software vets and supports buyers and suppliers to give farmers a window into demand and potential buyers a view into available supply and quality.
“What Silo is building has the potential to make marketing and distribution of agriculture incredibly more efficient, which is a win both for the suppliers and buyers. We’re excited to support and assist this team as they work to move agriculture forward,” said Eric Woersching, general partner at Initialized Capital, in a statement.
Silo is using the new financing to make a hiring push and develop new products and services to support liquidity in its perishable goods marketplace.
While an earlier generation of agribusiness software focused on increasing productivity on farms, a new crop of companies is targeting the business of farming itself. Companies like AgriChain and GrainChain also offer supply chain management software for farming, and WorldCover is creating insurance products for small farmowners in emerging markets.
The penetration of technology through near ubiquitous mobile devices, coupled with sensing technologies and machine learning-enhanced predictive software, is transforming one of the world’s oldest industries.
“I’ve come across quite a few marketplace platforms attempting to serve different segments of the agriculture supply chain, and none of which have come close to impressing me to the degree Silo has in their tech-forward approach to reducing the friction that comes with managing all aspects of the supply chain on their platform. Silo’s deployment of machine learning streamlines the process, requiring little to no change in their users’ workflow, and removes many barriers of their platform reaching critical mass,” said Matthew Nicoletti, commodity trader at The Penny Newman Grain Company.
*An earlier version of this story referenced Kite’s sale to Microsoft . The company remains independent.
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WorldCover, a New York and Africa-based climate insurance provider to smallholder farmers, has raised a $6 million Series A round led by MS&AD Ventures.
Y Combinator, Western Technology Investment and EchoVC also participated in the round.
WorldCover’s platform uses satellite imagery, on-ground sensors, mobile phones and data analytics to create insurance options for farmers whose crop yields are affected adversely by weather events — primarily lack of rain.
The startup currently operates in Ghana, Uganda and Kenya . With the new funding, WorldCover aims to expand its insurance offerings to more emerging market countries.
“We’re looking at India, Mexico, Brazil, Indonesia. India could be first on an 18-month timeline for a launch,” WorldCover co-founder and chief executive Chris Sheehan said in an interview.
The company has served more than 30,000 farmers across its Africa operations. Smallholder farmers are those earning all or nearly all of their income from agriculture, farming on 10-20 acres of land and earning around $500 to $5,000, according to Sheehan.
Farmers connect to WorldCover by creating an account on its USSD mobile app. From there they can input their region and crop type and determine how much insurance they would like to buy and use mobile money to purchase a plan. WorldCover works with payments providers such as M-Pesa in Kenya and MTN Mobile Money in Ghana.
The service works on a sliding scale, where a customer can receive anywhere from 5x to 15x the amount of premium they have paid. If there is an adverse weather event, namely lack of rain, the farmer can file a claim via mobile phone. WorldCover then uses its data-analytics metrics to assess it, and, if approved, the farmer will receive an insurance payment via mobile money.
Common crops farmed by WorldCover clients include maize, rice and peanuts. It looks to add coffee, cocoa and cashews to its coverage list.
For the moment, WorldCover only insures for events such as rainfall risk, but in the future it will look to include other weather events, such as tropical storms, in its insurance programs and platform data analytics.
The startup’s founder clarified that WorldCover’s model does not assess or provide insurance payouts specifically for climate change, though it does directly connect to the company’s business.
“We insure for adverse weather events that we believe climate change factors are exacerbating,” Sheehan explained. WorldCover also resells the risk of its policyholders to global reinsurers, such as Swiss Re and Nephila.
On the potential market size for WorldCover’s business, he highlights a 2018 Lloyd’s study that identified $163 billion of assets at risk, including agriculture, in emerging markets from negative, climate change-related events.
“That’s what WorldCover wants to go after…These are the kind of micro-systemic risks we think we can model and then create a micro product for a smallholder farmer that they can understand and will give them protection,” he said.
With the round, the startup will look to possibilities to update its platform to offer farming advice to smallholder farmers, in addition to insurance coverage.
WorldCover investor and EchoVC founder Eghosa Omoigui believes the startup’s insurance offerings can actually help farmers improve yield. “Weather-risk drives a lot of decisions with these farmers on what to plant, when to plant, and how much to plant,” he said. “With the crop insurance option, the farmer says, ‘Instead of one hector, I can now plant two or three, because I’m covered.’ ”
Insurance technology is another sector in Africa’s tech landscape filling up with venture-backed startups. Other insurance startups focusing on agriculture include Accion Venture Lab-backed Pula and South Africa based Mobbisurance.

With its new round and plans for global expansion, WorldCover joins a growing list of startups that have developed business models in Africa before raising rounds toward entering new markets abroad.
In 2018, Nigerian payment startup Paga announced plans to move into Asia and Latin America after raising $10 million. In 2019, South African tech-transit startup FlexClub partnered with Uber Mexico after a seed raise. And Lagos-based fintech startup TeamAPT announced in Q1 it was looking to expand globally after a $5 million Series A round.
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The days when you could simply grow a basil plant from a seed by placing it on your windowsill and watering it regularly are gone — there’s no point now that machine learning-optimized hydroponic “cyber-agriculture” has produced a superior plant with more robust flavors. The future of pesto is here.
This research didn’t come out of a desire to improve sauces, however. It’s a study from MIT’s Media Lab and the University of Texas at Austin aimed at understanding how to both improve and automate farming.
In the study, published today in PLOS ONE, the question being asked was whether a growing environment could find and execute a growing strategy that resulted in a given goal — in this case, basil with stronger flavors.
Such a task is one with numerous variables to modify — soil type, plant characteristics, watering frequency and volume, lighting and so on — and a measurable outcome: concentration of flavor-producing molecules. That means it’s a natural fit for a machine learning model, which from that variety of inputs can make a prediction as to which will produce the best output.
“We’re really interested in building networked tools that can take a plant’s experience, its phenotype, the set of stresses it encounters, and its genetics, and digitize that to allow us to understand the plant-environment interaction,” explained MIT’s Caleb Harper in a news release. The better you understand those interactions, the better you can design the plant’s lifecycle, perhaps increasing yield, improving flavor or reducing waste.
In this case the team limited the machine learning model to analyzing and switching up the type and duration of light experienced by the plants, with the goal of increasing flavor concentration.
A first round of nine plants had light regimens designed by hand based on prior knowledge of what basil generally likes. The plants were harvested and analyzed. Then a simple model was used to make similar but slightly tweaked regimens that took the results of the first round into account. Then a third, more sophisticated model was created from the data and given significantly more leeway in its ability to recommend changes to the environment.
To the researchers’ surprise, the model recommended a highly extreme measure: Keep the plant’s UV lights on 24/7.
Naturally this isn’t how basil grows in the wild, since, as you may know, there are few places where the sun shines all day long and all night strong. And the arctic and antarctic, while fascinating ecosystems, aren’t known for their flavorful herbs and spices.
Nevertheless, the “recipe” of keeping the lights on was followed (it was an experiment, after all), and incredibly, this produced a massive increase in flavor molecules, doubling the amount found in control plants.
“You couldn’t have discovered this any other way,” said co-author John de la Parra. “Unless you’re in Antarctica, there isn’t a 24-hour photoperiod to test in the real world. You had to have artificial circumstances in order to discover that.”
But while a more flavorful basil is a welcome result, it’s not really the point. The team is more happy that the method yielded good data, validating the platform and software they used.
“You can see this paper as the opening shot for many different things that can be applied, and it’s an exhibition of the power of the tools that we’ve built so far,” said de la Parra. “With systems like ours, we can vastly increase the amount of knowledge that can be gained much more quickly.”
If we’re going to feed the world, it’s not going to be done with amber waves of grain, i.e. with traditional farming methods. Vertical, hydroponic, computer-optimized — we’ll need all these advances and more to bring food production into the 21st century.
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Venture investors are pouring billions of dollars into feeding their hunger for food and agriculture startups. Whether that trend line is due to enthusiasm for the sector or just broader heavy investing in the VC space is much less clear.
According to a recent report published by AgFunder – a VC and investing marketplace focused on the agriculture and food sectors – the “AgriFood” space is booming. Using data from Crunchbase and several other data partners, the organization published its “2018 AgriFood Tech Investing Report” this morning, finding that investment in AgriFood companies increased 43% year-over-year, reaching $16.9 billion in 2018.
AgFunder classifies AgriFood tech as “the small but growing segment of the startup and venture capital universe that’s aiming to improve or disrupt the global food and agriculture industry.” Their definition is intentionally broad, encompassing everything from crop and livestock biotech, property management systems, and payments, to biomaterials and meat alternatives, all the way up to tech platforms for restaurants, grocers, deliveries and at-home cooks.
While some of the AgriFood tech categories – such as delivery or restaurant software – have long been popular destinations for venture capital, we’re now seeing a more diverse array of startups innovating across the entire food supply chain. According to the report, expansion in AgriFood is fairly consistent across upstream (agricultural and farming) subsectors to downstream (more consumer-facing) subsectors, with each group growing roughly 44% and 42% year-over-year respectively.
The data also shows growth occurring across almost all deal stages. AgriFood saw huge increases in the average deal size and total investment for late-stage companies in particular, as venture-backed startups have grown to global scale. And penetrating and attracting capital from international markets seems more feasible than ever. AgriFood investing, which traditionally has been largely US-centric, is rapidly becoming a global phenomenon, with more than half of total funding – and some of the largest rounds – now coming from companies and investors outside the US.
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The Green New Deal has burst onto the American stage, spurring more conversation about – and aspiration for – ambitious climate policy than at any point in at least a decade.
I’m glad to see it. Suddenly, climate is on the agenda, and ambitions for climate policy are higher than perhaps at any point in US history.
The Green New Deal is a resolution right now. It’s a statement of intent. It hasn’t yet progressed to the point of detailed policy proposals or legislation, which means now is the time to help craft its details.
For the last decade I’ve written about and publicly spoken about innovation in clean technology and ways to address climate change. I’ve helped to lead a climate-fighting citizen ballot initiative in my home state of Washington, invested in clean energy startups, and advised on climate and clean energy policies of other nations.
In that time, my views on what sort of climate policies have the most impact and have the greatest chances of winning over voters have changed. Policies that I thought were foolish a decade ago have revealed themselves to have been farsighted and effective. Policies I thought were powerful and elegant have, on closer inspection, revealed themselves to be far less effective than I believed. And the history of climate and energy legislation and attitudes in the US has demonstrated a path to getting new and more ambitious policies passed.
What I’ve learned over time is that good climate policy has 3 key traits:
All of that is compatible with a Green New Deal. Here’s what it could look like.
The conventional wisdom on climate policy is straightforward. Every nation uses its policies to reduce its own emissions. This conventional wisdom is wrong. Carbon dioxide doesn’t honor national boundaries. Climate change is global. And the best climate policies have a global impact as well.
The US, overwhelmingly, is the country most responsible for climate change. The carbon dioxide and other greenhouse gases we’ve emitted over the past decades are largely still in the atmosphere, still warming the planet. The world’s present and future emissions, though, are increasingly elsewhere. The US now accounts for just 15% of the world’s annual greenhouse gas emissions from fossil fuels. And because the developing world is rising in energy consumption far faster than the US, American emissions will be an ever-smaller share each year.

That means that, despite the fact that the US is the largest overall contributor to climate change thus far, the US could completely eliminate its carbon emissions and barely affect the future course of climate.
This means we need a different strategy. It’s not enough to eliminate the US’s carbon emissions alone. Our goal has to be to drive down the whole world’s emissions.
The Most Effective Climate Policy in the World
How can the US drive down the emissions of other countries? We can do it by making clean technologies irresistible to the entire world. And there we can take a lesson from the most effective climate policy of all time – Germany’s early subsidies of solar and wind.
Solar panels and electricity-producing wind farms have been around for decades. Yet, for most of that time, they’ve been a far more expensive way to produce electricity than burning coal or natural gas. Germany changed that. Starting in 2010, Germany’s Energiewende legislation heavily subsidized solar and wind. That, in turn, drove utilities and home owners and corporations to purchase solar and wind. And that, in turn, made the technology cheaper. As prices fell, other nations – first European nations, then the US, and then China – jumped into the fray, enacting more ambitious policies that further brought down the price of solar and wind (and now batteries and electric cars).
Why did subsidies bring down the price of technology? Because industry scale leads to industry learning and innovation, and that, in turn, leads to lower cost ways to manufacture, deploy, and manage new technologies. We’ve seen this for a century. Almost all technologies improve via Wright’s Law, often referred to as the learning curve or the experience curve. In the late 1930s, Theodore Paul Wright, an aeronautical engineer, observed that every doubling of production of US aircraft brought down prices by 13%. Since then, a similar effect has been found in nearly every technology area, going back to the Ford Model T.

Electricity from solar power, meanwhile, drops in cost by 25-30% for every doubling in scale. Battery costs drop around 20-30% per doubling of scale. Wind power costs drop by 15-20% for every doubling. Scale leads to learning, and learning leads to lower costs.
Germany began subsidizing solar and wind when they were extremely small scale industries, and their costs were quite high. Those subsidies drove German utilities, businesses, and home owners to purchase clean energy. That created a market. That, in turn, led solar and wind manufacturers to leap into the market, competing ruthlessly against one another to bring down their prices faster, offering the best product at the best price to customers.
By scaling the clean energy industries, Germany lowered the price of solar and wind for everyone, worldwide, forever.
The International Renewable Energy Agency finds that, between 2010 and 2019, the price of solar power, worldwide, has dropped by more than a factor of 5. The price of offshore wind power has dropped by a factor of three.

In just the past decade, solar power has gone from being uneconomical anywhere on earth without subsidies, to being cheaper than any fossil fuel electricity in the sunniest parts of the world. Building new solar is now cheaper than building new fossil fuel electricity plants in India, Chile, Mexico, Spain, and in sunny US states like Arizona, Nevada, Colorado, and Texas.
And because, in general, businesses, utilities, and consumers all around the world will deploy the cheapest energy they can, solar is now the fastest growing energy source around the world.
Happy? Good. Thank policy makers in Germany, and the US, and China – all of whom took action to bootstrap markets for solar and wind before they were cost-competitive.
The lesson for US climate policy is clear: The biggest impact we can have is by driving down the cost of technologies that reduce carbon emissions, to the point that clean technologies are cheapest way to provide the energy, food, and transportation that everyone around the world desires, and then spreading those technologies to the world. That means a mix of early-stage government R&D, government incentives to scale deployment in the private sector, and a very healthy dollop of private sector competition.

1 – As solar volume has grown, prices have dropped, leading to more growth.
Would the Green New Deal drive down the cost of clean technologies in a way that scales to the rest of the world? The current resolution is vague on exactly how the rapid decarbonization in the US would happen. One reason for concern is that the now-retracted Green New Deal FAQ released by Representative Alexandria Ocasio-Cortez specifically dismissed the idea that the private sector – even with government incentives – could pull off this decarbonization, and explicitly says that “Merely incentivizing the private sector doesn’t work”.
I agree in one sense – basic government R&D is a high-value investment, especially when the technologies we need to invent don’t even exist yet. The government has a vital role to play. At the same time, the incredible, unprecedented decline in cost of solar power, wind power, batteries, and electric cars has happened both because of early government R&D, and because private sector companies, incentivized by governments, have brought these technologies to market and been forced to compete with one another to provide the best technology at the lowest price. Ignoring this is to ignore what brought us the very best progress we’ve seen in cleaning up the way we produce energy.
The FAQ I reference has been retracted. The Green New Deal hasn’t yet become a detailed roadmap or legislation. As it does, I urge you, Green New Deal legislators and architects: Craft policies that create incentives to build and deploy clean technologies. Then use the market for what it’s good at: fierce competition that delivers ever-better products at ever-lower prices.
The Green New Deal resolution is really quite comprehensive. It touches on almost every source of US emissions.
Even so, there’s a tendency for climate and energy wonks – and legislators – to focus on electricity and cars when discussing climate policy.
Electricity and cars aren’t our hardest problems. They’re both big chunks of our carbon emissions, yes. And they both need more policy to drive them home. (More on that down below.) They’re also the areas where we’ve made the most progress, with incredible declines in the price of clean electricity and electric vehicles that put us at the edge of a tipping point. We aren’t over the hump yet, but the solutions are here – and if we continue to push them with policy, we can decarbonize electricity and cars.
Our hardest climate problems – the ones that are both large and lack obvious solutions – are agriculture (and deforestation – its major side effect) and industry. Together these are 45% of global carbon emissions. And solutions are scarce.
Agriculture and land use account for 24% of all human emissions. That’s nearly as much as electricity, and twice as much all the world’s passenger cars combined.
Industry – steel, cement, and manufacturing – account for 21% of human emissions – one and a half times as much as all the world’s cars, trucks, ships, trains, and planes combined.
Add industry, agriculture, and land use together and you have a very sticky, very difficult-to-improve 45% of carbon emissions.
By contrast, electricity and transportation are 39% of global emissions – nearly as big. The good news is that in electricity and transportation, we have momentum.
We do NOT have momentum in reducing the carbon emissions of industry and agriculture.
Decarbonizing Agriculture and Industry
The Green New Deal does, happily, mention these sectors. In agriculture, though, it avoids the biggest chunk of the problem: Livestock.
Livestock around the world – specifically cows, pigs, and other mammals – consume a tremendous amount of the world’s agriculture output. They drive the bulk of the deforestation around the world (which itself releases carbon into the atmosphere, and reduces forest land that could absorb carbon instead). And cows and pigs belch methane – a greenhouse gas that’s causes tremendously more warming than CO2 – about 100 times more in the first year, and 30 times more over the course of a century. Livestock in total produce about 15% of the world’s carbon emissions, as much as all transportation on land, air, and sea combined.
And the world’s appetite for meat is rapidly growing, with consumption expected to double in the next 40 or so years.

Cows should scare you more than coal.
In industry, meanwhile, steel and cement production both remain incredibly carbon intensive. We’ve learned to recycle steel using electricity, but making new steel from ore still involves the use of a tremendous amount of coal. (Theoretical ways to make steel without coal exist, but aren’t expected to be commercially viable for another 20 years.) We’re closer to technologies that could make cement without carbon emissions, but those technologies are still young, expensive, and haven’t been deployed to any significant degree. And the rest of industry – from manufacturing finished goods to making petrochemical products like plastics and lubricants – remains extremely carbon intensive.
These two sectors – agriculture and industry – are on path to be the two largest sources of carbon emissions in the world. And they’re the ones we have the fewest and least developed solutions for. The Green New Deal – or any serious climate policy – ought to focus first and foremost on R&D to develop methods for clean agriculture and clean construction and manufacturing; and then on incentives to deploy those clean methods, which will initially be extremely expensive, until they hit the scale to compete directly with dirty methods on cost alone.
What would a climate policy for agriculture and industry look like? Let’s take a page from energy, where we have a one-two punch: 1) Agencies like the Department of Energy’s Advanced Research Projects Agency for Energy, ARPA-E, that funds early stage energy science and technology R&D; and 2) A breadth of state and national subsidies and incentives that help those technologies reach higher scale and lower costs.
This one-two punch first invents technology (ARPA-E is modeled after the original ARPA, which created the foundations of the internet, originally called ARPANET), and then scales technology to the point that the new clean technology is cheaper than the alternatives.
We can use that one-two punch in agriculture and industry, by creating:
In several of these areas some options exist today, but a need for more innovation and more fundamental research – that the federal government is uniquely equipped to fund – still exists.

2-ARPA-I would fund research to decarbonize industry, starting with the largest industrial sources – steel, cement, and petrochemicals.
As with solar and wind in Germany, scaling use of these methods in industry would bring their prices down, with a target of beating the price of existing, carbon-heavy methods.
All of the above is compatible with Green New Deal language. It’s just a matter of emphasis. We need to double down on these two areas – agriculture and industry – that are soon to be the largest sources of global carbon emissions, and the ones we have the least progress in solving.
Perhaps the most important question about the Green New Deal is this – what can we actually pass?
The Green New Deal has already moved the Overton window, by elevating the conversation about climate. At the state level, in progressive states like California and New York, Democrats have solid majorities and could pass large parts of the Green New Deal that are applicable at a state level. As I argued just after Donald Trump’s election, the States are where we can most effectively push for climate action.
What about at the Federal level? Maybe the Green New Deal, by motivating the base, will lead to more electoral victories for Democrats in 2020. Or maybe it will hurt in red states like Alabama, where Democrats are defending a Senate seat. It’s far too early to say.
Democrats don’t have any chance of reaching 60 Senate seats in 2020. They do have the option, if they win a majority and the Presidency, of eliminating the legislative filibuster (using the so-called “nuclear option”), in which case a simple majority of the House and Senate could pass as much of the Green New Deal as Democrats could achieve consensus on, without the need for any Republican legislators.
What if none of the above occurs? What if Democrats don’t get a Senate majority at all? Or do get a majority, but are unwilling to eliminate the legislative filibuster? Could any parts of the Green New Deal pass with some Republican support?
Bipartisan Climate Policy is Possible. In Fact, It’s Here Now
Yes. Recent history shows that, while climate is a highly divisive issue in the US, clean energy and innovation have massive support on both sides of the aisle.
Consider the following:
Wait. Don’t Republicans hate clean energy?
Nope. Not at all. Americans on both sides of the aisle love solar and wind. Solar is the most popular energy source in the US, with 76% of Americans saying that their utility should get more energy from solar. Wind is a close second, at 71%. The third choice, natural gas, is 24 points behind solar, at 52%. And a meager 30% of Americans want more coal.

It helps that clean energy is literally everywhere in America. Solar and wind have been built out in every state. Wind power, especially, is booming in rural districts in red states. Representatives from these districts, and Republican Senators from red states like Iowa and Texas that have deployed a tremendous amount of solar and wind, have every reason to support policies that benefit clean energy.

What’s more, Americans – on both sides of the aisle – wildly support research into new technologies that can improve their lives. A whopping 85% of Americans support funding more research into renewable energy sources. Ready for the real shocker? Solid majorities in virtually every county and every congressional district in the US support more funding of research into clean energy.
Nearly as many Americans – 82% – support tax breaks for Americans who purchase energy-efficient vehicles or solar panels. And again, the support isn’t limited to blue states or blue districts. It’s overwhelmingly national.

So Americans don’t just love innovation and R&D spending. They also support incentives to deploy clean technology faster. And, in fact, those two policy levers – more research funding, and incentives to deploy clean technology – get both the most support in poll after poll, the most bipartisan support, and the most geographically consistent support. If you want a policy proposal that that will work in red or purple states, or that can win over some Republican Senators and Representatives, clean technology research and clean technology deployment incentives are the two most likely to garner support.
What Bipartisan Policy Would Look Like
If Democrats do get both the White House a filibuster-proof congressional majority – one way or another – and get enough internal consensus, they can drive forward whatever GND policy they wish. Right now, that seems unlikely to me.
In the event that we have a Congress without that filibuster-proof majority, or with enough moderate democrats who balk at the entirety of the Green New Deal, there are still extremely effective climate policies that Congress can put in place.
First, in industry and agriculture, the four policies we mentioned already:
Those policies in agriculture and industry have an excellent chance of getting bipartisan support. They follow a pattern of Americans being willing to invest in new science and technology R&D. And, because they benefit industrial and agricultural states and districts, by giving carrots for deploying clean industry and clean agriculture, they’re a benefit to politicians from those – often red – states that have the greatest concentration of farms and factories. That’s the exact opposite of a policy that penalized farmers or factories for their carbon emissions. You’d have a hard time getting much bipartisan support for that. Make the policy an incentive that helps farms and industry thrive, and helps them get an edge over their global competitors, and the politics completely change.
In electricity, transportation, and buildings, there are also policies – some of them counter-intuitive – that would accelerate us towards a clean future :

3- A nation-sized grid increases the amount of energy we can use from solar and wind, and reduces the overall cost. Source – Nature Climate Change
Long-range transmission is also remarkably efficient and low cost. High-voltage DC transmission lines can send power 2,000 miles with only 10% losses and a small additional cost. That means solar power plants in Texas could be powering New York City…an hour after the sun has gone down in New York. China understands this, and is building the world’s largest high voltage power grid, moving power from the sunniest and windiest areas in the west to the coastal population centers 3,000 km (1,860 miles) east. In the US, meanwhile, it’s nearly impossible to build new long-range transmission – largely because of NIMBY. Congress should make it easier to get the necessary permissions to build transmission, paving the way for a grid with more and cheaper clean energy.
4- China’s Ultra High Voltage Grid moves clean energy 2,000 miles from the sunny and windy interior to the population centers on the eastern coast. The US has nothing similar.

5-29 US States have Renewable Portfolio Standards
The solution is for Congress to mandate a Renewable Portfolio Standard nationally, dragging the laggard states up to the standard of the rest. How high should that mandate be? The Green New Deal goal of 100% carbon free electricity by 2030 is incredibly ambitious. And it pushes us into the unknown. Beyond 70 or 80 or 90% of electricity from renewables, integration becomes increasingly difficult as periods of bad weather nation-wide cause serious problems. The technical challenges there can be overcome – perhaps through nuclear, or next-generation carbon-capturing natural-gas plants, or long-term energy storage technologies (which are being funded by ARPA-E).
Those challenges are still real enough that even a clean energy optimist like me gets nervous. A goal of 50% of electricity from carbon free sources in every state by 2030, then 80% by 2040, and 100% by 2050 would be in-line with what scientific models say we need to achieve in order to stay below 1.5 degrees Celsius of warming. And by scaling both clean energy and the technology to integrate it to high percentages of the total grid, it would drive those technologies down in price for the rest of the world, and pave the way for cleaner grids everywhere.
First, for individually owned vehicles, Congress should improve the federal electric vehicle tax credit. Today’s $7,500 federal tax credit is capped at 200,000 electric vehicles per manufacturer. That’s an absurdly low number in a country that has 260 million cars on the road. General Motors CEO Mary Barra recently called for the cap to be removed. Congress ought to put electric vehicles on the same footing as solar, wind, and batteries: A 30% tax credit – like the solar ITC – with no limit on the number of vehicles its applied to would be simple, clear, and consistent. For individuals buying their own vehicles, that tax credit ought to be structured so it can be taken off the purchase price of the vehicle directly, rather than waiting for tax season.
Second, the same tax credit ought to apply to fleet operators who buy or build electric vehicles to offer rides to consumers. While the pace at which consumers buy new cars is slow, the pace at which they switch miles of transport can be far faster, as they switch some of their travel to fleets like Uber, Lyft, and whatever comes after. Those fleets, today, are mostly gasoline engine vehicles of hybrids. As electric vehicles increasingly become the cheapest per mile, those app-based transport fleets will go electric. And a typical taxi drives 70,000 miles a year, or roughly 4 times the 13,500 miles per year of a typical individually-owned car. That means each electric vehicle deployed as a taxi can have the impact of four individually owned vehicles.
Finally, Congress ought to accelerate the deployment of autonomous cars on the nation’s roads. Why? Because an autonomous vehicle, by taking out the cost of the driver, can cut the cost per mile by half. Some calculations show that an autonomous electric taxi, by 2025, could cost 35 cents per mile. That’s 1/10th of what a taxi costs, 1/5th of what a Lyft or UberX costs today, and half the cost of owning and operating your own car. That lower cost would cause even more rapid switching to electric transport fleets, as currently-owned gasoline vehicles increasingly sat unused, or saved for long-distance trips or other scenarios. Some studies find that, even at twice that price, as much as 40% of miles driven would switch to these electric fleets.

6 – Autonomous Electric Taxis could be half the cost per mile of owning and operating a gasoline car – if autonomous vehicles arrive.
Getting to those costs absolutely depends on autonomy. Today, however, autonomous driving is regulated by a hodge-podge of different laws at the State level. Congress should step in and act to standardize safety testing, unify laws between states, and accelerate the deployment of safe, cheap, efficient, electric autonomous taxi services. Congress almost did so in 2018. It’s time to try again.
These three actions would both accelerate the deployment of electric vehicles in the US, and drive innovation in a sector where US companies are currently in the lead, and where they could be global leaders in trillion-dollar industries for decades to come.

7 – Electric vehicles with smart chargers could charge when solar and wind are most abundant on the grid, increasing the amount of renewable energy we can use.
Wait, but what about?
So I didn’t list your favorite technology, policy, or issue? Here:

8 – The cheapest ways to capture carbon are on the bottom of this chart – in soils and forests.
What About Climate Justice?
The Green New Deal advances a plan to fight climate change and to ensure that we do so through a just transition. Here, I think a few principles clearly apply.
All of that is fully in alignment with the Green New Deal resolution. The GND goes further, though, making the case for universal healthcare, universal higher education, universal housing, a job guarantee for all people in the United States, strengthening unions, reducing discrimination in the workplace, respect for Native American rights and sovereignty, and stopping the transfer of jobs overseas.
Many of those policies are ones I support, or at least where I support the motivations behind them. Yet I am not at all certain those policies should be coupled with climate action. Coupling a long list of liberal priorities with climate action would seem to make it harder to get the bipartisan support we’ll probably need to enact these climate policies. That said, the Green New Deal resolution is a high level map, not a specific bill. The original New Deal wasn’t one piece of legislation – it was made up of more than 30 separate bills. Democrats should approach the Green New Deal the same way. They ought to embrace the idea that the overall effort may take multiple years and multiple Congresses to enact, and that it’s perfectly acceptable to support some parts of the Green New Deal and not others. They ought to embrace alliances and assistance – including bipartisan alliances – to pass parts of the Green New Deal where they can.
(Photo by Ira L. Black/Corbis via Getty Images)
Climate Action is the Ultimate Climate Justice
Even more importantly, though, acting on climate change itself creates a more just world. Climate change is a slow, insidious, and massive threat to human well-being. It’s also profoundly unjust. Americans may only emit 15% of carbon emissions today, but all the CO2 we’ve emitted in the past will linger in the atmosphere for roughly a century from when it was released. Add up all the carbon the US has emitted over time, and the US remains the largest cumulative emitter of greenhouse gases on the planet. We Americans are more responsible for climate change than any other nation, even those with many times our population.
Meanwhile, two billion people live in countries that have emitted the least carbon dioxide over history – the poorest countries on planet earth – which are also the countries where people are likely to suffer the most from climate change. Climate change itself is a deep inequity. The most just thing we can do is to address climate change as rapidly as possible, and to produce and spread the tools that also boost climate resilience around the developing world. Indeed, most of the benefits of fighting climate change don’t go to Americans at all. Americans do benefit. But the largest benefits of fighting climate change go to the billions around the world who have the fewest resources and who live in the nations with the greatest vulnerability.
Lower income Americans also stand to suffer more from climate change than do wealthier Americans. A lower-income American in Detroit isn’t as vulnerable as a subsistence farmer in Botswana – not by a long shot. At the same time, it’s hard to deny that Katrina, for example, hit the poor of New Orleans harder than it did the rich. Wealthier Americans can relocate more easily, can pay energy bills more easily, can rebuild from climate disasters more easily. And here again, the most just thing we can do is to act on climate, as rapidly as possible.
Should we find ways to use the fight against climate change to also address the long history of inequality and injustice, and the differences in wealth and income that exist in the US? If so, should we stop there? Climate change is global. Carbon emissions and the harm they cause know no national borders. The harm of American (and European, and more recently Chinese) carbon emissions will fall most heavily on the poor of the developing world. Should climate policy aim to decarbonize the world as rapidly as possible? Or should it aim to decarbonize and address other global ills?
For me, the answer is clear. Climate change itself is so unjust, so lopsided in who has benefited from burning fossil fuels and who will suffer the most from that combustion, that addressing climate change is, itself, to help undo an injustice – one that threatens billions of people around the world.
Let’s tackle all the world’s other problems too. As we do so, let’s keep in mind that addressing climate change, even if we don’t succeed at everything else, is a major, vital, and necessary step towards a more just world.
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SeeTree, a Tel Aviv-based startup that uses drones and artificial intelligence to bring precision agriculture to their groves, today announced that it has raised an $11.5 million Series A funding round led by Hanaco Ventures, with participation from previous investors Canaan Partners Israel, Uri Levine and his investors group, iAngel and Mindset. This brings the company’s total funding to $15 million.
The idea behind the company, which also has offices in California and Brazil, is that in the past, drone-based precision agriculture hasn’t really lived up to its promise and didn’t work all that well for permanent crops like fruit trees. “In the past two decades, since the concept was born, the application of it, as well as measuring techniques, has seen limited success — especially in the permanent-crop sector,” said SeeTree CEO Israel Talpaz. “They failed to reach the full potential of precision agriculture as it is meant to be.”
He argues that the future of precision agriculture has to take a more holistic view of the entire farm. He also believes that past efforts didn’t quite offer the quality of data necessary to give permanent crop farmers the actionable recommendations they need to manage their groves.

SeeTree is obviously trying to tackle these issues and it does so by offering granular per-tree data based on the imagery gathered from drones and the company’s machine learning algorithms that then analyze this imagery. Using this data, farmers can then decide to replace trees that underperform, for example, or map out a plan to selectively harvest based on the size of a tree’s fruits and its development stages. They can then also correlate all of this data with their irrigation and fertilization infrastructure to determine the ROI of those efforts.
“Traditionally, farmers made large-scale business decisions based on intuitions that would come from limited (and often unreliable) small-scale testing done by the naked eye,” said Talpaz. “With SeeTree, farmers can now make critical decisions based on accurate and consistent small and large-scale data, connecting their actions to actual results in the field.”
SeeTree was founded by Talpaz, who like so many Israeli entrepreneurs previously worked for the country’s intelligence services, as well as Barak Hachamov (who you may remember from his early personalized news startup my6sense) and Guy Morgenstern, who has extensive experience as an R&D executive with a background in image processing and communications systems.
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For the last two and a half years, Iron Ox has been working on perfecting its agricultural robots to tend its indoor farms. After first testing its systems on a small scale, the company is opening its first fully autonomous production farm, with plans to start selling its produce soon.
The farm is currently growing a number of leafy greens, including romaine, butterhead and kale, in addition to basil, cilantro and chives. The robots tending these plants are Angus, a 1,000-pound machine that can lift and move the large hydroponic boxes in which the produce is growing, and Iron Ox’s robotic arm for harvesting the produce.
As Iron Ox co-founder and CEO Brandon Alexander told me, the current setup can produce about 26,000 plants per year and is equivalent to a one-acre outdoor farm — though this one is obviously indoors and far more densely packed.

Alexander noted that he and his co-founder Jon Binney decided to get into indoor farming after working at a number of other robotics companies — for Alexander, that includes a stint at Google X — where the focus was often more on building cool technologies and not on how those robots could be used. “We’d seen lots of novelty robotics stuff and wanted to avoid that,” he told me. And while the founding team considered getting into warehouse logistics or drones, they eventually settled on farming because, as Alexander tells it, they didn’t just want to build a good business but also one that would create social good.
Today, the majority of leafy greens (the kind of produce that Iron Ox focuses on) in the U.S. are grown in California and Arizona — especially during the winter months when it’s colder in the rest of the country. That means a romaine lettuce that’s sold on the East Coast in January has often traveled more than 2,000 miles to get there. “That’s why we switched to indoors,” Alexander said. “We can decentralize the farm.”

It also helps that an indoor hydroponic farm can achieve 30 times the yield of an outdoor farm over the course of a year, yet uses far less space.
To get to this point where Iron Ox can operate an autonomous farm, though, took plenty of work and engineering chops. The hardest challenge, Alexander told me, was to get the robotic arm to look at the plants through its stereo cameras and then plan the pickup operation to harvest the produce, which isn’t always uniform. And to run this operation autonomously, it obviously has to do so reliably.
Angus, the larger robot that picks up the 800-pound pallets the produce is grown in and brings them to the robotic arm, also took some time to get right. You don’t want to move those pallets too quickly, after all, or you’ll have plenty of water to mop up.

All of that, including the system that monitors the plants, their growth, the sensors that watch over them and the hydroponics system, is then controlled from a cloud-based service that tells the robots when it’s time to harvest and which operations to perform. The robots themselves, though, then perform those tasks autonomously.
One thing that came as something of a surprise to the team, though, was that running an indoor farm solely with LED lighting still results in electricity bills that are simply too expensive to make the operation profitable. So going forward, Iron Ox is actually betting on more traditional greenhouses that are augmented by high-efficiency LED lighting.
That means the team can’t build these autonomous farms right in the city, though, because you can’t exactly stack a number of greenhouses on top of each other. But as Alexander noted, even if you have to be 20 miles outside of the city, that’s still far better than shipping produce to a supermarket that is thousands of miles away.

As Alexander stressed, the team spent a lot of time talking to both farmers and chefs to figure out what they needed. Farmers, it turned out, were mostly complaining about their inability to find labor. And that’s no surprise. The labor shortage in the agricultural industry is starting to become a major issue for farmers, especially in states like California. As for the chefs, what they were mostly looking for was quality, of course, but also predictability and consistent quality.
The plan now is to start selling the produce from the first farm and then scale to more and larger locations over time. Iron Ox now has the money to do so, given that it has raised more than $5 million in total, including a $3 million round it announced earlier this year.

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Demand for sustainable coffee is growing, a boon for socially conscious coffee lovers — but many small growers are missing out because they lack the ability to verify that their coffee beans are grown using fair labor and eco-friendly practices. In fact, verification is often accessible only to large coffee estates or cooperatives. Enveritas wants to change that. The nonprofit, which recently completed Y Combinator’s accelerator program, uses geospatial analysis to make the process more efficient, enabling it to offer free verification to small farms.
Enveritas’ goal is to end poverty in the coffee sector by 2030. Before founding Enveritas in 2016, CEO David Browning and head of operations Carl Cervone worked at TechnoServe, a nonprofit that serves businesses in developing economies. Browning led TechnoServe’s global coffee practice, while Cervone advised coffee growers in Africa, Asia and Latin America about sustainability trends.
Browning tells TechCrunch that TechnoServe’s coffee team spent a lot of time working with small farmers, many of whom don’t have access to sustainability verification because their farms are too remote or small. The typical coffee grower served by Enveritas has less than two hectares of land, lives on less than $2 a day and relies on cash crops for their family’s income.
“The existing solutions work well for large estates and it can also be effective for farmers organized into cooperatives, but many of the world’s coffee farmers are smaller farmers and not organized into estates,” Browning explains. “For those farmers, the existing solutions can be more difficult to access.”
Part of the reason is because many verification solutions rely on field workers who visit farms and track sustainability standards using pen and paper, a time-consuming and costly process.

To develop a more efficient and scalable system, Enveritas uses geospatial and machine learning to identify coffee farms through satellite imagery and monitor for issues like deforestation. Though it still relies on local partners to visit farms and confirm that sustainability standards are being followed, its technology enables Enveritas to provide verification services for free.
Enveritas checks for 30 standards, which it divides into three categories: social, environmental and economic. “Social” includes no child labor and workers’ rights; “environmental” checks for problems like deforestation, pollution or banned pesticides; and “economic” covers fair wages, ethical business practices and transparent pricing, among other standards.
The organization currently operates in 10 countries, including Uganda, Indonesia, Ethiopia, Nicaragua and Costa Rica, with plans to expand into more markets.
Sustainable coffee isn’t just in demand by caffeine lovers with a penchant for social justice. Many of the world’s biggest coffee companies, including Illy and Starbucks, have launched sustainability initiatives as part of their corporate responsibility measures. Offering coffee grown using fair labor or environmentally friendly practices also helps differentiate their products in a crowded marketplace. Research by the National Coffee Association, an American trade group, recently found that many millennials prefer sustainable coffee, with up to two-thirds of 19 to 24-year-olds surveyed said they pick their coffee based on whether it was grown using environmentally friendly practices and fair labor.
While coffee is currently its main focus, Browning says Enveritas’ system can be applied to other agricultural products that need more visibility in their supply chains. For example, it also can be used to verify the sustainability of cocoa, cotton and palm oil.
As a nonprofit, Enveritas faces different funding challenges from other tech startups. Browning says it is currently at the equivalent of being ready for a Series A. Much of its backing comes from coffee companies (Enveritas can’t disclose which ones) that hope to benefit from Enveritas’ solutions.
“One of the advantages of this system is that it reduces the cost for coffee companies relative to the traditional pen and paper system, but it’s also simultaneously free for farmers,” Browning says. “That’s one of the most compelling innovations, so it’s a win-win for both.”
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GV (formerly Google Ventures) is leading a $10 million investment in Abundant Robotics, a company building apple-picking robots that could eventually be adapted to harvest other fruits. Joining GV in the round were BayWa AG and Tellus Partners, along with the company’s earlier backers Yamaha Motor Company, KPCB Edge and Comet Labs. Read More
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