We need a taxonomy for principles

When you start collecting principles, a natural question arises: how to organize these principles? Clear organization is not just useful for quicker access but — when the collecting is crowd-sourced — critical to ensuring that the database of principles grows healthily and sustainably. We need a balance between the extremes of hairballs and orphan principles.

Now, there are books written on this subject, knowledge management (I promise, it's not nearly as dull (or settled) a subject as you might think). That said, one thing at a time. In this post, all I want to do is propose a few dimensions I think might be useful for classifying principles in the future.

Here they are:

  • Normative vs. Descriptive
  • Universal vs. Situational (or "First" and "Derived")
  • Deterministic vs. Stochastic

Normative and Descriptive.

There's a big difference between principles that tell you how the world *is* and how it (or you) *should be*. The former are the domain of the traditional sciences. It's what we mean when we talk about principles and postulates in physics. The latter are the domain of decision theory/philosophy/etc.

There's a bridging principle between the two in that accomplishing any normative goals requires you to have an accurate descriptive view of how the world is. Still, in general, we can make a pretty clean break between these categories.

Universal and Situational ("First" and "Derived")

The universe looks different at different length scales: the discrete, quantum atoms in Angströms give rise to continuous, classical fluids at meter scales and might yet contain continuous strings at Planck-lengths.

Physics gives us a formal way to linking the descriptive principles of one length scale to those of another—the "the Renormalization Group". This is a (meta-)principled approach to constructing "coarse-grained", higher order principles out of base principles. In this way, the postulates of quantum gravity would give rise to those of classical mechanics, but also those of chemistry, in turn biology, psychology, etc.

The same is true on the normative end. "Do no harm" can look very different in different situations, and the 2 Areas/Principles/Aphorisms & Platitudes/Golden Rule has more subtleties and gradations than I can count.

In general, the "first principles" in these chains of deduction tend to be more universal (and apply across a wider range of phenomena). Evolution doesn't just apply to biological systems but to any replicators, be it cultures, cancers, or memes. 1

Final Project — Anthropology of Science and Tech through …|700

Deterministic and Stochastic

One of the main failure modes of a "principles-driven approach" is becoming overly rigid—seeing principles as ironclad laws that never change or break.

I believe one of the main reasons for this is error that we tend to think of principles as deterministic "rules". We tend to omit qualifiers like "usually", "sometimes", "occasionally" from our principles because they sound weaker. But randomness has a perfectly important role in description (the quantum randomness of measurement or the effective randomness of chaotic systems) and in prescription (e.g., divination rituals may have evolved as a randomizing device to improve decision-making).

So we shouldn't shy away from statements like "play tit-for-tat with 5% leakiness". But also less precise statements like "avoid refined sugars, but, hey, it's okay if you have a cheat day every once in a while because hey you also deserve to take it easy on yourself."

A Few Examples

Using these classifications, we can make more thorough sense of the initial set of Open Principles divisions:

"Generic"/"situational" principles and "mental models" are descriptive principles that differ in how universal they are. "Values" and "virtues" are universal normative principles with "habits" as their derived counterparts. "Biases" are a specific type of derived descriptive principle reserved to the domain of agents.

A few more examples:


Call to Action

A few things that might help us keep the Open Principles healthy:

Cheers, Jesse


  1. This isn't always true: the real world is not very quantum mechanic. But it's probably a good enough starting point for now.

Introduction to Atomic Workflows

An ongoing trend in the tech-productivity space is productivity gurus sharing their workflows.


Superficially, these digital crib-tours act as a reference for an audience that wants to implement similar workflows.

The Expectations Are Too High

But the tours risk setting too high a target for the beginner. Rather than take these examples as inspiration, the beginner interprets them as instruction: "in order to be 'productive,' you have to use this tool in this way."

In their defense, these tours really can be a source of motivation and insight. But the workflows themselves are often too complex and time-intensive for the budding productivitist to copy exactly. And when the beginner sets too high a target, they are less likely to persist and realize a lasting routine.

We need a more structured approach to building workflows. In this article, I'll suggest an approach I call "atomic workflows" (after James Clear's 2 Areas/3 Notes/3 Sciences/9 Psychology & Psychiatry/Atomic Habits).

Let's take a step back. What are habits and what are workflows?

🗿 1 Projects/Rationalia/LW/Concepts/Habits are behavioral routines that usually operate subconsciously. In contrast with workflows, habits are behaviorally monolithic: they involve single (or very similar) actions with clear outcomes.


  • 🚲 You bike to the gym.
  • 📖 You read at night in bed.
  • 💅 You bite your nails raw.
  • 🚬 You smoke your lungs black.

🎡 Workflows also involve behavioral routines that may (or may not) operate subconsciously. What sets workflows apart from habits is that workflows are orchestrated collections of interdependent habits. They involve habits that would not function in isolation, and they are "orchestrated" in that workflows require the executive ability to choose the right habits at the right times.


  • 🗃 The Zettelkasten is a workflow for writing. Its habits include finding and reading content, taking and managing notes, and drafting and editing texts.
  • 📥 Getting Things Done (GTD)is a workflow for managing time. Its habits include adding tasks to the inbox, processing the inbox, and reviewing your progress.
  • 📈 Spaced Repetition Systems (SRS) are a workflow for memorizing. Its habits include acquiring content, forming questions, creating notes, and reviewing cards.
  • 🏷 Scrum (along with other agile frameworks) is a workflow for managing teams in product development. Its habits include meeting together, writing "stories", and managing time.

The asymmetry of habit-formation

Good habits are hard enough to develop as they are.

Because workflows involve multiple habits that can depend intricately on each other, good workflows are even harder to develop.

Clear gave us the answer to forming habits in 2 Areas/3 Notes/3 Sciences/9 Psychology & Psychiatry/Atomic Habits. His process combines first-principles thinking with the precision of a surgeon: (1) Strip a habit to its minimum set of activities, and (2) build it up from there.


  • 🚲 Gym: Start by regularly biking to the gym, but don't do anything else. Then, add two minutes of jumping jacks. Move on to a five minute core routine. Etc.
  • 📖 Reading: Read one page before lights out every night, then 2, then 4…

So too, Clear's insight offers the answer to forming workflows: "atomic workflows". This adds one additional starting step: (1) Strip a workflow to its minimum set of habits, (2) strip those habits to their minimum sets of activities, and (3) build them up from there.


  • 1 Projects/Writing/02 Series/Atomic Workflows/Atomic Zettelkasten:
    • Taking literature notes: Unless you already have a strict note-taking practice, begin by taking literature notes in the margins of your texts. Disallow yourself literal quoting. This will force you to be sufficiently concise. It will also shorten the time you need before you write which is the end goal and the source of feedback.
    • Taking permanent notes: Give yourself a consistent time in the day to add at least 5 notes.
    • Writing (drafting + editing): The most essential habit. Keep yourself to short blog articles so you keep the feedback present.
    • Organizing your notes: Imposing a top-level structure is non-essential. Defer this until later.
    • Only when this is running smoothly, expand your literature note-taking, spend more time pruning and organizing your Zettelkasten, and let a top-level structure emerge organically.
  • Atomic GTD:
    • Processing the inbox (daily): start with a simple daily to-do list on a sheet of scrap paper.
    • Managing an inbox: use the other side of your daily to-do list to note tasks for the next day.
    • Reviewing your progress: start with a daily transfer session.
    • Gradually level up to an additional weekly to-do list, then monthly, etc.; At the same time, add some form of priority labels and time estimates.
  • 1 Projects/Writing/02 Series/Atomic Workflows/Atomic SRS:
    • Reviewing cards: This is the most essential activity. Start with someone else's deck.
    • Gathering content: Find something simple like a list of vocabulary words and filter for the words you don't know.
    • Making cards: Start with simple uniand bidirectional notes (containing only a pair of a word and a picture plus definition).
    • When this feels comfortable, explore making cloze cards and your own note templates. Then, consider larger projects (that require multiple kinds of notes), like learning a language.
  • Atomic Scrum:
    • Reviewing the sprint: Choose a simple retrospective structure and stick to it religiously (for a while).
    • Planning the sprint (writing cards): skip the user story (when you're early on in development, the AC usually stand on their own), and skip the HTD (trusting that your founding team are all A-players).
    • Keeping each other up-to-pubDate: Choose a time (or several) and get in the habit of standing-up even if you have nothing pressing to share.
    • As complexity and manpower increase, add ideas like a user story and HTD back in. Introduce longer-term review sessions and new review formats. Adopt stricter asynchronous communication guidelines.

12. Be radically honest and transparent

12. Be Radically Honest and Transparent

"One sincere and honest move will cover over dozens of dishonest ones. Open-hearted gestures of honesty and generosity bring down the guard of even the most suspicious people. Once your selective honesty opens a hole in their armor, you can deceive and manipulate them at will. A timely gift—a Trojan horse—will serve the same purpose." — The 48 Laws of Power (2 Areas/3 Notes/3 Sciences/0 Mathematics/AM3D Axioms, postulates/48 Laws of Power/12. Use selective honesty and generosity to disarm your victim)

In the upside-down world of the 48 Laws of Power, even honesty becomes a tool of the dishonest—just another weapon to deceive the insufficiently cynical. To prove his point, Greene shares how Count Victor Lustig conned Al Capone. One day, Lustig approached Capone with a dubious money-making proposal. Give him two months, Lustig promised, and he would double Capone's $50,000 investment. Smooth talker as he was, Lustig secured the money and promptly locked it in a safety box where it remained untouched for the full two months.

Lustig returned to Capone appearing contrite and humbled. The plan had failed, he admitted. But before Capone had time to flay Lustig alive (or to inflict whatever method he preferred for slow, torturous death), the con artist pulled out the original $50,000 and returned it penny for penny. Capone was shocked. Honest men did not cross his threshold often.

Lustig had correctly calculated that Capone would soften at a display of honesty. After returning the money, Lustig secured a smaller gift of $5,000—the true aim of his con all along.

It's a pretty story and apt anecdote. The only problem1 in viewing it as lesson material is that it assumes you want to spend time in the company of ruthless criminals. If you want to have a constructive impact on society, there are easier paths.

Creative power requires a different kind of honesty—not selective and Trojan but radical and unrelenting.

"I'm talking about a specific extra type of integrity that is not lying, but bending over backwards to show how you're maybe wrong, that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen" — Richard Feynman

I'm talking about Feynman's kind of honesty—the radical honesty underpinning the scientific project that led us out of the dark ages. Whether you are a pollyannaish progress worshipper or climate-fearing progress denier, we need the very same honesty to wage an effective climate dialogue—all that stands between us and a prompt return to the dark ages.

But there's no reason to restrict this boon to only scientists. More generally, radical honesty is our responsibility as citizens, colleagues, and children, as partners, parents, and people of the Earth. It builds more resilient, trusting, and happier companies and communities.

Observance of the Law #1

Perhaps the best example of this principle in practice is Bridgewater, one of the world's most successful investment management firm. When asked, founder Ray Dalio often cites "radical transparency" as the most important factor in his company's culture.

As Dalio writes in his Principles:

"Provide people with as much exposure as possible to what’s going on around them. Allowing people direct access lets them form their own views and greatly enhances accuracy and the pursuit of truth. Winston Churchill said, “There is no worse course in leadership than to hold out false hopes soon to be swept away.” The candid question-and-answer process allows people to probe your thinking. You can then modify your thinking to get at the best possible answer, reinforcing your confidence that you’re on the best possible path."

Radical transparency is not easy. Newcomers typically need 18 months to adjust to the new expectations, and many never complete the transition—turnover at Bridgewater is survivorship bias, which is almost double the average. But those that remain, Dalio might say, are stronger for it. They have survived the hazing and excised their deceitful tendencies to become more productive coworkers and business people.

Interpretation # 1

The main purpose of radical transparency at Bridgewater is to foster clearer communication. In our information age, conflict stems less frequently from resource scarcity—the usual cause in premodern societies—than from simple misunderstanding.

Large corporations like Bridgewater are liable to fracture into bureaucratically isolated strata. As a result, information ends up taking painfully convoluted paths to get from A and B. It's a game of telephone sure to corrupt the original message.

Which is why Elon Musk advocates against overly hierarchical company structures:

"A major source of issues is poor communication between depts. The way to solve this is allow free flow of information between all levels. If, in order to get something done between depts, an individual contributor has to talk to their manager, who talks to a director, who talks to a VP, who talks to another VP, who talks to a director, who talks to a manager, who talks to someone doing the actual work, then super dumb things will happen. It must be ok for people to talk directly and just make the right thing happen."

It's a straightforward consequence of the Information Inequality:

I(X)I(f(X)).I(X)\geq I(f(X)).

The information, II, contained in a signal, XX , is always less than or equal to the information contained in any function/modification of that signal, f(x)f(x) . By reducing the number of interlocutors, fif_i, we can more tightly hug the upper bound:

I(X)I(f1(X))I(f2(f1(X))))I(f3(f2(f1(X))))).I(X) \geq I(f_1(X)) \geq I(f_2(f_1(X)))) \geq I(f_3(f_2(f_1(X)))))\geq \dots.

A different approach is to make the modification functions fif_i less lossy. Every additional filter we impose on the signal—our sense of what is decent, what will offend people, what is or is not relevant, etc.—makes us a worse conveyor of information. The solution, then, is to strip out as many filters as possible to make fif_i more conservative: i.e., to adopt radical transparency.2

“By lying, we deny others a view of the world as it is. Our dishonesty not only influences the choices they make, it often determines the choices they can make—and in ways we cannot always predict. Every lie is a direct assault upon the autonomy of those we lie to.” — Sam Harris

Observance #2

Another company celebrated for its culture of radical transparency is Netflix. Here's a 25% over the first 18 months:

“In most situations, both social and work, those who consistently say what they really think about people are quickly isolated and banished. We work hard to get people to give each other professional, constructive feedback—up, down and across the organization—on a continual basis. Leaders demonstrate that we are all fallible and open to feedback. People frequently ask others, ‘What could I be doing better?’ and themselves, ‘What feedback have I not yet shared?’”

Yet more concisely, co-CEO Reed Hastings wrote in a memo:

”You only say things about fellow employees you say to their face.”

This is also the company famous for its "Keeper Test"—managers regularly ask themselves which of their employees they would fight to keep if those employees were preparing to leave for another company. Anyone who doesn't make the cut is promptly fired with a considerable severance package. Better to buy off detractors and free room for star players than slowly decline into the sunk-cost fallacy swamp. "Adequate performance gets a generous severance package".

Despite the continual risk of being fired and at-times brutal peer reviews (or, who knows, maybe because of), Netflix is consistently ranked as one of the tech world's favorite places to work—among the release from the company. Maybe radical transparency works.

Interpretation #2

For Netflix, radical "candor" is less about clarity in communication than making room for personal growth and trust. Most of us tend towards stagnation because we surround ourselves with people unwilling to critique us. Perhaps it comes from a good place: our friends don't want to hurt us. Perhaps it comes from a more nefarious place: we self-select an entourage of yes-men to feel better about ourselves. Whatever the cause, the end result is complacency at best and spiritual death at worst. Honest third-party feedback is the fuel of personal development.

If for no other reason, we should strive towards radical honesty because honest people are more pleasant to be around. On the long run, one sincere and consistently honest person will outweight a dozen potentially hurtful feedbacks.

“Honest people are a refuge: You know they mean what they say; you know they will not say one thing to your face and another behind your back; you know they will tell you when they think you have failed—and for this reason their praise cannot be mistaken for mere flattery.” — Sam Harris


With both Bridgewater and Netflix, the work culture probably isn't all that the press mythologizes it to be.

Bridgewater's radical transparency has a number of rather creepy corollaries. For one, almost every encounter is recorded on video, so it can potentially serve as training material in the future. This leads to a near-Orwellian surveillance state with "Truespeak" substituted for Orwell's original "Newspeak"—Big Brother butts in only when its subjects become too conventional and self-moderating.

The problem with this particular incarnation of radical transparency is that trust needs autonomy to flourish (top 10 or 20 American companies on GlassDoor). Constant surveillance breeds suspicion.

In addition, Dalio's adherence to his principles trust to be trusted:

Each day, employees are tested and graded on their knowledge of the Principles. They walk around with iPads loaded with the rules and an interactive rating system called “dots” to evaluate peers and supervisors. The ratings feed into each employee’s permanent record, called the “baseball card.”

Two dozen Principles “captains” are responsible for enforcing the rules. Another group, “overseers,” some of whom report to Mr. Dalio, monitor department heads.

Maybe this really is something you can get used to after 18 months of living it. But I'm inclined to think that this period serves more to select for those people already distrusting enough that they can tolerate a work culture so clearly inspired by the Stasi.

Another risk is that Bridgewater's notorious public condemnations are almost universally less effective than private feedback. As radically transparent as you think your culture is, human nature is more receptive to feedback when it is delivered in a small, private setting than when you are surrounded by a tribe of coworkers.

Netflix's variety of radical candor has can get near cultish. In particular, the willingness to fire has leld to a pervasive fear of dismissal. After asking a group of people how many of them feared being fired, Karen Barragan doubled down with the declaration that it was "[g]ood, because fear drives you.”

Within limits, Ms. Barragan, within limits. It definitely isn't good when it leads to a situation like the following:

One former employee remembers seeing a woman who was just fired crying, packing up her boxes, while the rest of her team shied away from the scene without offering any support. They feared that “helping her would put a target on their back,” the employee said. “I just couldn’t believe it.”

Radical candor should not have to mean emotional blunting, but it requires active work to keep the two apart. Every strategy has its pitfalls.

Like any, radical honesty is no perfect decision. There will always be cases where omitting information is the best course of action—or even actively lying (if the Nazis are at the door asking for the location of the family you are hiding). That said, in general, not lying comes pretty close to perfect.

“Lying is, almost by definition, a refusal to cooperate with others. It condenses a lack of trust and trustworthiness into a single act. It is both a failure of understanding and an unwillingness to be understood. To lie is to recoil from relationship.” — Sam Harris



  1. There are actually other problems. Many of them. Like, if Lustig had calculated incorrectly, he would be dead, and we likely would not have heard it. Always factor in the its own downsides.

  2. Ok this needs a bit more rigor since human beings are not quite well-behaved functions f(x)f(x) (we can spit out different results for the same answers and might introduce information of our own). Really, this should be expressed in terms of mutual information: H(X)=I(X;X)I(X;f(x))H(X) = I(X; X) \geq I(X; f(x)) — the entropy (average information) contained in XX (equal to the average amount of information about XX contained in XX) is always less than the average information about XX contained in a function of XX.

The Green Mortgage

The Green Mortgage

1. Introduction

Note: This is a living document. I'm still actively adding sources, updating text, and creating figures and animations.

In this series, I'd like to shamelessly promote an idea I have stolen (as far as I can trace it) from Saul Griffith: the Green Mortgage.

Griffith credits much of our modern world to credit (the financial kind). The car loan (invented in the 1920s) and the 25-year mortgage (1940s) lifted a large chunk of Americans into the middle class and ignited the conflagration known as modern finance (for good or bad).

In the 2020s, he argues, we need a climate loan. The most environmentally impactful decisions on the individual level are irregular, once-a-decade decisions—things like putting solar on the roof, electric cars in the garage, energy efficient washers and dryers in the house, an electric heat pump in the basement, etc. We need new financing instruments to make it easier to make the right choice when these decisions come our way.

At these crossroad moments, our primary imperative is to electrify. Even if our electricity comes from fossil fuels, large power plants are typically more efficient than small car engines and residential furnaces. Electrifying sets us up to fully abandon fossil fuels in the future. A green mortgage is primarily an electrification mortgage

In this series, I would like to explore what a green mortgage actually looks like at different income levels and housing/family situations, what to include in the package, and how much it will cost. It's to rank different interventions by emissions saved and address complications like "when is the optimal time to replace a still-functioning gas-powered car with an electric one?"

Best of all, I'm using a new tool I've designed to make more interactive documents. This will let you play around with the parameters to see, for example, how the conclusions change as the grid becomes cleaner, or to see what the green mortgage might look like for your own home.

Start with the Rich

The rich are disproportionately responsible for climate change. This is true for countries as well as for individuals. For example, the rich tend to live in single-family detached homes, which account for 60% of all housing units (in 2000) [1] but three quarters of total residential energy use [2]. They drive further to work, own more (and larger) cars, take regular flights, maintain more lifeless, larger lawns1, and so on.

So if we're talking about getting the most bang for our buck, we have to start by rehabilitating the rich. It also make sense because they have more money to put towards initiatives like these. It's the Tesla approach of building uberexpensive Roadster's before "more affordable" Model S's before almost affordable Model 3's.

First though, I need to make an important point—one that the wealthy are not particularly keen to hear. Before anything else (i.e., before electrification), we need to decrease our consumption. Even if we fully electrify and convert to 100% renewable resources, it is impossible to scale the American dream of McMansions, ATVs, and 24/7 steaks to every person without guaranteeing the demise of the natural world.2

Which we don't want.

So if you currently occupy one of these 350+ square meter behemoths (3800+ square feet), stop being an entitled asshole, and begin by downsizing.3 That also means you, Bill4.

With this caveat, let us sketch what the green mortgage might look like for a lower upperclass US household (top 80%-95% of household incomes). This is a household with an income of roughly $100,000—300,000 a year (still falls into the "lower" category because wealth is so unbelievably unevenly distributed at the upper end[^5]).

[^5] The 96th to 99th percentiles take about twice as much in annual income as the average over the 80th to 95th percentiles, the top one percent takes four times as much as that, the top 0.01 percent takes 20 times on top of those multipliers, and so on.

2. The Financial Costs

We begin by computing the one-time installation costs of a full green renewal—electrifying everything that we could conceivably electrify. Later on, we can look at whether each of these interventions actually makes environmental sense, how quickly the investments pay for themselves, and how best to schedule the electrification.

For the sake of example, we will work with a hypothetical family of =family.size living in a =home.area, =home.num_rooms:"%i{-room}" home (valued at =home.value) with =cars.num—the "Andersons".

// Family 
family.size: `%n {people}` = NUMBER(1, 10) ?? 4

// Home
home.area: "%i m2" = NUMBER(0, 500, 10) ?? 250
home.value_per_m2: `$%i/m2 ` = NUMBER(10, 1000, 10) ?? 500
home.m2_per_room: `%i m2{/room}` = NUMBER(5, 50, 5) ?? 20
home.num_rooms: {one: `%n {room}`, other: `%n {rooms}`} = home.area / home.m2_per_room
home.value: "$%i," = home.area * home.value_per_m2 

// Cars
cars.num: "%n {cars}" = NUMBER(0, 5) ?? 2

Note 1: We'll be ignoring tax-incentives and other programs that effectively lower the price.

Note 2: See the values in green? These are our first interactive elements. Try clicking on them and dragging left or right. As a result, you'll see the values in blue start to change.

🌞 The Roof (=solar.cost)

First up on our list of interventions is the roof.

=solar.area:"{Estimating we have} %i m2 {of roof available for solar}", we can manage up to a system (=solar.kw_multiple the =solar.kw_avg_resid: "{size of the average residential installation}"). At =solar.cost_per_kw This will probably cost =solar.cost to install (I invite you to play around with Google's Project Sunroof). At a conversion factor of solar.kwh_per_day_per_kw (which depends on altitude, cloudiness, shade from trees, etc.), this installation provides the Andersons an average of solar.kwh_per_day.

home.num_stories: "%i {average stories}" = NUMBER(0.5, 5, .5) ?? 2

roof.slant: "%i deg" = NUMBER(0, 75) ?? 30
roof.area: "%i m2" = home.area/home.num_stories/COS(roof.slant)
roof.available: "%p%" = NUMBER(0, 1, .01) ?? .8

solar.area: "%i m2" = roof.area * roof.available
solar.kw_per_m2: "%f.2 kW/m2" = NUMBER(0, 1, .01) ?? .15 "%i kW/" = FLOOR(solar.area * solar.kw_per_m2)

solar.kw_avg_resid = 6
solar.kw_multiple: "%ix" = / solar.kw_avg_residential = "[@fu2016]"

solar.cost_per_kw: "$%d,/kW" = NUMBER(0, 3000, 100) ?? 1500
solar.cost: "$%d," = * solar.cost_per_kw

solar.kwh_per_day_per_kw: "%f.2 kWh {actual}/d/(kW {capacity})" = NUMBER(0, 10, 0.1) ?? 3.5
solar.kwh_per_day: "%d kWh/d" = * solar.kwh_per_day_per_kw

🚗 The Cars ($90,000)

Our family goes for an extended range Tesla Model 3 at 50,000.AndtheygetaChevyBoltfor50,000. And they get a Chevy Bolt for 35,000. Together with two level two charging stations (~$5,000), electrifying the Anderson transportation fleet will cost around $90,000.

🔋 The Battery ($20,000)

A fair number of American home-owners already experiences regular power outages. In my childhood home in New York State, I remember (with something nearing fondness) 2011's hurricane Sandy knocking us out of power for nine days.

Climate change is going to increase the frequency and intensity of extreme weather, thus also the likelihood of regular grid outgage, so—if only for adaptation purposes—the Andersons need some batteries.

Tesla recommends one Powerwall for every 7.6 kW AC of solar installed, so our family gets two Powerwalls. That's 15,000forthebatteriesthemselves,15,000 for the batteries themselves, 1,000 for a coupling device called a "Gateway" and 3,000forinstallationcosts.Letsroundupandcallitaneven3,000 for installation costs. Let's round up and call it an even 20,000.

Between these two batteries, the family gets 27 kWh of storage capacity in addition to the capacity of the cars. That's 82 kWh for the extended range Model 3, and 65kWh for the Chevy Bolt. So, in total, the family has up to 175 kWh of storage available.

Depending on how much electricity they need for heating, whether their solar panels are obscured by a layer of snow or not, and how much they need to drive, our family should be able to outlast most storms. In order to make that statement just a little more precise, we turn to heating next.

🧦 Insulation ($45,000—60,000)

The Andersons live in an older house, so before going crazy with electric heating, they stand much to gain from investing in humble insulation (they are far enough enough North for cold winters).

  • 🪟Windows: The Andersons have between 30 and 40 square meters of glass across 50 windows1. For the sake of example, suppose all windows are single pane, and we want to upgrade everything (rather than retrofitting existing windows with an add-on glaze). The Andersons end up going for double pane rather than triple pane windows at an [average cost of 750perwindow](,whichcomestoatotalof750 per window](, which comes to a total of 37,500. Windows are not cheap, especially on older homes.
  • 🧱 Walls: Fortunately, the Andersons' home has cavity walls, which are easier to retroactively insulate than solid walls. They go with a polyurethane foam option, which costs around [25persquaremeter](,ofwhichnoteverythingisinsulable,thetotalcomesinsomewherebetween25 per square meter]( With somewhere between 300 and 500 square meters of walls, of which not everything is insulable, the total comes in somewhere between 5,000 and $10,000.
  • 🛖 Loft: With easy access to the loft, the Andersons go for a fiberglass insulating option at a very comparable price to the foam (~25persquaremeter).Thepriceforthis,usingtheroofareawecomputedforthesolarpanels,aresomewherebetween25 per square meter). The price for this, using the roof area we computed for the solar panels, are somewhere between 3,750 and $5,000
  • 🪵 Suspended floor: Another lucky strike for the Andersons: their floors are easily accessible from underneath via the basement. That means inserting new insulation isn't going to require them to tear up the floor boards. Still, it doesn't come free, 125 square meters of floor boards come to roughly $3,000 in insulation.

🌡 Heating and Cooling ($50,000)

The most straightforward electric heating solution is the heat pump, a device that transfers heat between your house and an external heat reservoir much as a fridge does. Perhaps the best feature of a heat pump is that it can pump in both directions, so it solves both heating and cooling.

Most common is the air-source heat pump, in which the reservoir is the air outside your home. But the Andersons decide to go further. They opt in for a ground-based system where the reservoir is a fluid—some kind of antifreeze—that is pumped underground (by a separate circulation pump). The more constant temperature below ground means the heat pump can work more efficiently.

The Andersons go for the larger five-ton heat pump, which by itself—at around 2,500pertonhasapricetagof2,500 per ton—has a price tag of 12,500. The costs of digging a vertical closed loop system have a roughly equal price tag.

But then there's the fact that the Anderson's live in an older house that previously got its heating via radiators. Their geothermal system is air-to-fluid, which means they will need to install ductwork throughout their house. All in all, this retrofitting costs another $20,000.

Let's round up again (to account for things like a new smart thermometer, unforeseen installation costs, etc.), and we estimate the total costs at around $50,000.

It still requires some electricity to run the fan that circulates the hot air and to keep the circulation pump going, but the Andersons have almost fully relinquished their direct dependence on oil.

🍃 Lawn ($500—5,000)

To fully rid the Andersons of their addiction to oil, we have to take a look in their garage and outside their house. The gas-powered lawn-mower, weed-wacker, chainsaw, and leaf-blower all have to go.

Now, you could electrify all these for less than $500 (as long as you choose a smaller lawn-mower). But that would spare the Anderson's an important learning opportunity.

Occupying 40 million acres of land in the continental US, lawns are America's number one crop. They're also incredibly water-, pesticide-, and time-intensive, utterly devoid of biodiversity, and let's admit it, sterile and pathetic-looking. The Andersons' lawn has to go.

That's going to be difficult for Mr. Anderson who has grown up equating lawns with success. It might be years and many sessions of psychotherapy before he shakes this more insidious, personally involving addiction, before he can suppress the urge to go blasting his leaf blower at six in the morning on a Sunday. But he has to give it up—the natural world can no longer maintain the terror of lawns.

Enough of my rant, what all this means practically is that the Green Mortgage is an opportunity for landowners to "rewild" their lawns. One-time services run upwards of $5,000, not including recurring landscaping work thereafter. Fortunately, nature-friendly landscaping tends to be less labor-intensive than conventional lawns once up and running. Since the Anderson's are already spending ridiculous amounts on landscaping crews to come by weekly, they stand to save money relatively quickly.

🍳 Appliances ($3,000—8,000)

After oil and lawns, next to go is the Anderson's dependency on propane, which they still use for their stove and hot water.

Water Heater ($2,000) Let's start with water. Their heat pump already gets them part of the way there—the Andersons opted for a small add-on module that preheats water before it enters the boiler, but to go 100%, they need to transition to electric.

In fact, since they no longer need a boiler to heat their radiators, they can downsize to a 50 gallon electric water heater. With installation fees, this ends up costing the Anderson's $2,000.

The Oven (1,0004,000)Aftergettinganenergyefficientelectricovenforjustover1,000—4,000) After getting an energy-efficient electric oven for just over 1,000, the Andersons have officially cut out their direct consumption of fossil fuels. They feel pretty good about it.

Well, there is one thing left—the grill. For an avid grillmaster like Mr. Anderson, this is probably the single most controversial item on the list. How is he to make his delicious burgers without his beloved propane grill?2 Tough luck man. You can either shell out another $1,000—3,000 or abandon the grill altogether.

Thus, we have gotten through all the changes essential to electrification. Depending on how old their other large appliances are, the Andersons might consider getting a more efficient model. According to the EPA, average annual energy for these appliances are (in decreasing order):

  • The Dryer (769 kWh/year)
  • The Fridge (596 kWh/year)
  • The Washing Machine (590 kWh/year)
  • The Dishwasher (206 kWh/year)

The most efficient modern models are, in most cases, radically better:

Replacing the entire set with the best new models, all in all, would not put the Andersons back more than $5,000, thereby completing the transformation.3

Total Costs ($233,000—260,000)

Let's tally up the costs in order of decreasing costs:

  • $90,000 (Cars)
  • $45,000—60,000 (Insulation)
  • $50,000 (Geothermal)
  • $20,000—25,000 (Solar Roof)
  • $20,000 (Batteries)
  • $5,000 (Lawn)
  • $3,000—12,000 (Appliances)

For a total of 233,000260,000,aboutaquarterofthehomesvalue.Fortherestoftheseries,wewillworkwith233,000—260,000, about a quarter of the home's value. For the rest of the series, we will work with 250,000 as the baseline.

Amortizement ($900—1,900/month)

With a 30 year amortizement period, 50,000downpayment,andthestandard3.250,000 down payment, and the standard 3.2% APR for home mortgages, the green mortgage, on its own, would [add]( 110,000 in interest at a monthly price of 900.Ashorter15yearmortgageataninterestrateof2.43900. A shorter 15-year mortgage at an interest rate of 2.43% would add only 40,000 in interest fees for a total of about 1,300amonth.Finally,a10yearmortgageat2.381,300 a month. Finally, a 10-year mortgage at 2.38% APR would cost 25,000 in interest at almost $1,900 a month.

Property Tax and Insurance ($500/month)

If you add $250,000 in renovations to your house, your home value will increase, and, with it, the amount you spend on property taxes. How much will depend entirely on where you live—annual property taxes range from the permils (0.1%) to almost 3%.

Again, our example concerns a lower upper class family, so we assume they live in a county that takes towards the higher end—let's say 2%. We add 5,000totheannualcost(abitover5,000 to the annual cost (a bit over 400 a month).

Lastly, the Andersons, responsible home owners as they are, need to insure the new goods. An increase in home value of 250,000meanssomethinglike[a250,000 means something like [a 75 increase in monthly payments]( or $900 a year. That said, some of these improvements, such as better insulation, might decrease premiums.


With a longer duration 30-year mortgage, the Andersons are looking at a price tag of aboout 1,400amonth.Withtheshorter10yearmortage,thisjumpsupto1,400 a month. With the shorter 10-year mortage, this jumps up to 2,400 a month. (With $500/month persisting even after the mortgages are paid off).

But really, this is not the right way to make this calculation, because in most cases the Anderson's almost immediately save on their monthly bills. So in the next chapter, we'll factor in these savings to compute the actual "effective" monthly cost.

3. The Financial Payback

In the last instalment in this series, we determined that a complete electric overhaul—solar roof, batteries, electric vehicles, geothermal, better insulation, etc.—will cost the average lower upper-class family (the "Andersons") between 200250,000upfront.Afteramortizement,propertytaxes,andinsurance,theyrelookingatamonthlyfeeof200-250,000 up front. After amortizement, property taxes, and insurance, they're looking at a monthly fee of 1,400 (30-year mortgage) to $2,400 (10-year mortgage).

But really that figure is misleading: almost all of the changes included in the green mortgage immediately lower the Andersons' monthly utility bills. What really matters is the net change in monthly costs. In this installment we'll compute how much the Andersons save and, in turn, the effective monthly cost of their green mortgage.


Most of these calculations depend wholly on how much the Andersons were paying for electricity, gas, oil, and propane before electrification.

Let's fix these prices beforehand. For consistency, we assume we're somewhere in the NY metropolitan area.

🌞 The Roof (+$300/month)

If we assume panels with 15% efficiency (including conversion losses), then 4.25 kWh/m^2/day of Solar Irradiance (see image below) times 75 square meters of panels yields more than 17,000 kWh a year, almost 1,500 kWh a month.

Compared to the roughly 20¢/kWh standard electricity rate we fixed above, the Andersons are saving $300 a month. Not bad.

If we compare this to the $20-25,000 price tag, a solar roof will pay itself off in only five to seven years.

categorical imperative

🚗 The Cars (+$100-200/month)

New York drivers cover, on average about 12,000 miles a year.

With 360 miles of range on an 82 kWh battery, the Long Range Model 3 gets 4.4 miles per kWh. With 259 miles on a 65 kWh battery, the Chevy Bolt gets 4 miles per kWh. If the Anderson's two drivers split their miles evenly between them and their vehicles, they will need about 5,700 kWh/year for transportation. That's a little under 480 kWh/month or about 100$/month.

If their two previous cars are had an average fuel economy of 33 miles per gallon (the average from a decade ago), they would have been consuming around 730 gallons of gas a year—almost $200 a month.

So all other things being equal, the Anderson's have cut their monthly transportation energy costs in half. This is probably still conservative. For one, we've ignored the fact that EVs usually charge at night when electricity is cheaper. In balance, the Anderson's occasionally have to splurge on a supercharger (at 0.28¢/kWh, only about 20per"tank").WevealsoignoredgenerousEVsubsidiesandtheoccasionalfreechargingstation.Next,maintenancecosts:EVmaintenancecostsabout[3¢permile,internalcombustionvehiclesabout6¢permile]( per "tank"). We've also ignored generous EV subsidies and the occasional free charging station. Next, maintenance costs: EV maintenance costs about [3¢ per mile, internal combustion vehicles about 6¢ per mile]( This saves the Andersons an additional 60 a month.

Putting it all together, the Anderson's are saving somewhere in the range of $100-200.

🔋 The Battery (+$0-120/month)

The main financial benefits of the battery are secondary to those of the solar roof. It allows you to access free electricity outside sunny hours. We have effectively already priced this into the solar roof.

There is a second, more direct benefit: managing grid outages. Here, I had a hard time finding good figures for the frequency and duration of suburban blackout events. It's easy to find this information on a per-state basis, but this gives an inaccurate picture since it conflates cities (with infrequent, shorter duration blackouts) and suburbs/rural areas (where blackouts are more frequent and longer-lasting). Based on my own childhood in NY exurbia, I'd estimate the Andersons lose power 1-5 days a year.

To deal with these outages, many families resort to generators, which can tally up to substantial expense. Let's look at an example: this 20 kW system consumes 3.5 gallons per hour of liquid propane or 84 gallons a day. Neglecting the upfront costs, the Anderson's are saving 2901,400ayearduringblackouts,290—1,400 a year during blackouts, 24—120 a month.1 The battery ( $20,000) pays for itself after 70 days of power outs.

Of course, the Anderson's did not need to buy a generator and could have braved the outage in the dark (so we'll set a lower limit to the savings of $0).

🧦 Insulation (+$30-80/month)

This is probably the hardest to measure accurately since it varies so much from home to home. Still, using of $5,000 for the upper-end models, we estimate that the Andersons save between 15% and 20% on heating and cooling from better insulation.

The 10,000 hours. Considering that about half of that bill goes to heating and cooling and that the Anderson's live in a larger, older house, let's assume that their heating and cooling cost somewhere in the range of $200-400 per month before electrification.

So better insulation is saving the Anderson's are saving 3080amonth.Consideringthatinsulationcost30-80 a month. Considering that insulation cost 45-60,000, this investment will take 50 to 170 years to pay for itself. That sounds bad until you realize that these prices neglect fossil fuel's external costs. It does suggest that we might more effectively redirect government subsidies from solar roofs (which are already a good investment on their own) to insulation.

🌡 Heating and Cooling (+$60-180/month)

Fortunately for me, someone has already done this calculation. EnergyStar's reference for climate zone 4-5. Using the figures from above, that's an additional $60-180 a month.

In other words, the $50,000 investment pays for itself in some 25 to 70 years. At the lower end, that's an okay investment. At the higher end, not so much. That is, as long as you neglect the quality of life improvements associated to geothermal. Speaking from experience, geothermal is a much more pleasant and responsive heating and cooling solution than radiators and window-mounted AC units. These less quantifiable benefits are sure to save off a few years.

🍃 Lawn (+$0-450/month)

Many upperclass families hire regular landscaping services—once a week for 100200atime,alandscapingcrewwillcometowreckhavoconyourlocalecosystem.Thisracksupquickly,andyouresoonspending100-200 a time, a landscaping crew will come to wreck havoc on your local ecosystem. This racks up quickly, and you're soon spending 400-900 a month to keep your lawn perfectly sterile and your neighbors perfectly ticked off at the non-stop drone of the air-quality-annihilating leaf blowers.

The alternatives to the lawn are not just aesthetically more appealing but cheaper to maintain and much better for local biodiversity. Whereas a lawn requires a weekly trio of lawn-mower, weed-whacker, and leaf-blower, the meadow requires only a biweekly visit by a weed-whacker to trim a small area and remove the clippings, and maybe a biannual spot treatment of invasives.2 You'll easily save half in landscaping costs, and you will save it immediately.

Unfortunately, this is probably one of the harder ones to convince people, so I'm removing the lower cap.

🍳 Appliances (+$30-50/month)

First, our replacements for formerly propane-powered appliances:

  • Water Heater: I believe this is already factored into the geothermal-related savings above.
  • The Range (180-360 gallons propane → 180-1,200 kWh / year3): Savings of 40-50% or $5-20 a month. (I'm ignoring the grill which only gets used a few times per year anyway).

Next, the gains we get from switching to more energy efficient appliances:

  • The Dryer: 769 → 125 kWh/year (-84%)
  • The Fridge: 596 → 186 kWh/year (-69%)
  • The Washing Machine: 590 →120 kWh/year (-80.%)
  • The Dishwasher: 206 →196 kWh/year (-4.9%)

For a total savings of 1,530 kWh/year or 25 per month. At the lower investment amount (\3,000), it pays for itself in a decade.

Summary of Financial Payback

Let's tally up the monthly savings in decreasing order:

  • $300 (Solar Roof)
  • $100-200 (Cars)
  • $60-180 (Geothermal)
  • $30-80 (Insulation)
  • $30-50 (Appliances)
  • $0-450 (Lawn)
  • $0-120 (Batteries)

In total, the Andersons are saving $500-1,400 a month.

Let's pull up the costs we calculated in the previous chapter.

  • $900-1,900 (Green Mortgage, 30 year — 10 year)
  • $500 (Property tax & insurance)

So we come to the striking conclusion that a more sustainable, electrified home almost entirely pays for itself. In the best case, it pays for itself in full4. In the worst case, you're spending 800amonthoverthirtyyearsor800 a month over thirty years or 1,800 a month over ten—saving 20 to 40% off of the sticker price. Not bad for a home that's more pleasant to live in, look at (well, alright, maybe this will have to wait for the solar roof), and share a planet with.

4. The Environmental Costs

In the past chapters of this series, we've seen that the green mortgage makes resounding financial sense. But we've failed to address the more pressing question: does the green mortgage make environmental sense—is it actually green?

The answer, we'll see, is that it depends. It depends on how much of the Andersons' electricity consumption they can fulfill with their roof. It depends on the source of electricity in their grid. It depends on how old the appliances and vehicles the Andersons are replacing, their efficiency ratings, the efficiency ratings of their replacements, and the embedded emissions contained in manufacturing and transporting these goods. Because it depends on so much, the final answer is that it's complicated.

But that's no reason not to try to give an answer.

Note: For the sake of sanity, I'll focus exclusively on emissions costs (in terms of median 2000-square-foot NY house incurs an average of $400 in utility costs per month). This means I'll neglect important non-emissions improvements (for example, delawning has an important role in promoting biodiversity and decreasing fresh water consumption) as well as hidden costs (for example, mining lithium, cobalt, etc. are fresh-water-intensive, toxic-chemical-releasing, and human-rights-abuses-accompanying—a topic for another day). Safe to say, there are no perfect decisions1.

🌞 The Roof (Dandelion Energy (an admittedly biased party in favor of geothermal) estimates that a typical 2,500 square foot home in the greater NY area saves around 50% on their average heating and cooling costs)

First, let's calculate the lifecycle emissions involved in manufacturing, installing, and decommissioning a solar roof. At far too much about sustainable landscaping for photovoltaics (in a range of 30-220 g/kWh; 1-3 kW for electric), the Andersons' 1 gallon of propane per hour (see last chapter) solar roof costs them CO2-100-year-equivalents.

If we asssume that their grid was sourcing its electricity from coal at -1.4 ton CO2e/month (cf. natural gas at 500 g CO2e/kWh; 40 g CO2e/kWh), the Andersons are saving source.

Subtracting the embedded costs, the Andersons are saving 1500 kWh/month.

🚗 The Cars (-60 kg CO2e/month)

A favorite claim of the anti-EV lobby is that switching to EVs doesn't matter if your electricity comes from fossil fuels. This is wrong. First, power plants tend to burn more efficiently than car-scale combustion engines. You need less fuel (thus also emissions) for the same miles (see below). Second, switching to an EV makes it easier to decarbonize in the future when your utility does make the switch to clean energy. New infrastructure rarely saturates immediately.

Still, we'd be amiss to ignore the emissions associated to our EVs. Unfortunately, every tangible good in the modern world has a carbon price tag.

First, let us compute the the emissions associated with the old vehicles that are being replaced before they would normally have expired. If the Andersons sold these cars second-hand, we could ignore these costs—they'd be passed down to the purchaser. But if the vehicles are scrapped, then we have to transfer these embedded costs to the new electric vehicles.

Pasted image 20211016091556.png

(1 kg CO2e/kWh)

At an expected lifetime of source (1.5 ton CO2e/month, pg. 27) and a manufacturing cost of 1.4 ton CO2e/month (see graph), a lower medium segment internal combustion vehicle (ICV) costs 590 kg CO2e/month to make. An equivalent EV, at a more expensive manufacturing cost of source meanwhile costs 320000 km to make.

If the Anderson's previous cars had source of their lifetime remaining and they scrapped both of their 25 g CO2e/km previous cars, they would transfer 8 tons CO2e to the replacement vehicles. That's effectively a 40 g CO2e/km increase in emissions per km. Comparing the more than 13 tons CO2e costs for fuel and electricity in the gasoline-powered ICV to the 25% for fuel in a grid-mix-powered EV, the early decomission is well worth it.

We see that the other favorite anti-EV argument—that EVs are so much more environmentally costly to manufacture that it's not worth it—is bunk. Even if the previous vehicles had been brand new, it would still be worth it to scrap the cars and take on electric vehicles. This would add only 2 per vehicle. The EV is still three to four times less emitting.

Let's put it altogether. At an average of 4 tons CO2e, the Andersons are now emitting only 6 g CO2e/km/car compared to their previous emissions of 235 g CO2e/km, for a savings of 30g CO2e/km.

And, really, that's probably conservative. Rather than scrap old cars, the Andersons could sell these second-hand. So long as their mileage beat the mileage of the purchaser's previous vehicle, this would be an improvement on its own.

To leave you with a nugget of practical advice: if you're buying a new car, you should be buying electric. I'll grant you a little slack if you're going second-hand (as long as it significantly improves on your previous vehicle's mileage), but really we have no time to dawdle when we need to get to decarbonize by 2050. Especially when car lifetimes are now regularly above 15 years. Stop your pathetic complaining about "oh what if I need to make a long trip somewhere" and suck it up. You can afford to spend an hour every 300 kilometers to charge—it's probably even good for your physical health, road-trip sanity, and safety on the road.

🔋 The Battery (24 g CO2e/km)

I couldn't find any figures specifically for the Tesla Powerwall, but 1600 km /month/car estimates 240 kg CO2e/month as the lifetime emissions for a Lithium-ion Nickel Manganese Cobalt battery (the most common chemistry out there). With 830 kg CO2e/month of capacity, this amounts to 590 kg CO2e/month of total emissions. Across a -103 kg CO2e/month lifetime, this amortizes to this paper.

The most important emissions "savings" for batteries are really already factored into the solar roof (just as the financial savings in the previous chapter).

Less significant are the savings accrued during power outages (as compared to using a generator). With 72.9 kg CO2e/kWh and a generator that uses 28 kWh the Anderson's would have been consuming 2.0 tons CO2e. At 10 year (17 kg CO2e/month), this comes out to 3 blackout days/year.

(I'm skipping the manufacturing/maintenance/decommissioning costs for the generator. If you're interested, you can use the 10 to 15% rate for car fuel to non-fuel emissions as an upper limit.)

In total, then, the battery costs 84 gallons propane/day.

Of course, if your model family was hardy enough to survive without a generator, there would be no emissions on this front. (You can incorporate this by setting 252 gallons liquid propane/year to zero.)

🧦 Insulation (-5.72 kg CO2e/gallon of liquid propane)

In the last chapter, we estimated that the Andersons could save source on heating and cooling from better insulation. To see how much this saves, we first have to estimate the Andersons' total heating and cooling related emissions.

Assume that the Andersons were consuming 120 kg CO2e/month (-103 kg CO2e/month). At num_blackout_days (66 kg CO2e/month), their heating-related emissions total 15%.

Meanwhile, suppose they were using 900 gallons of electricity for air conditioning (source)2. With grid-sourced electricity emitting 10. kg CO2e/gallon heating oil (reminder: this is the figure for dirtier coal-sourced electricity), this would have meant annual cooling-related emissions of source.

Altogether, their heating and cooling emissions would have totaled 9 tons CO2e/year before the green mortgage. The 2750 kWh/year insulation-related reduction in fuel use would mean savings of source.

As mentioned, this is a living document—I'll come back to factor in the embedded costs of the glass of the windows, insulation materials, and installation at a later date.

🌡 Heating and Cooling (-1 kg CO2e/kWh)

Moving to geothermal means we get rid of the remaining 85% of the fossil-fuel-related emissions (2.8 tons CO2e/year) for heating.

But, in turn, we've increased our heating-and-cooling-related electricity consumption to a total of 1. ton CO2e/month3, or (at 15%), 150 kg CO2e/month.

Altogether, this yields a net improvement of 310 kg CO2e/month. At first glance, it may appear that geothermal isn't quite as green as first promised. We're reducing our heating and cooling related emissions by only 640 kg CO2e/month. But, just as with the vehicles, this neglects the fact that heat pumps make future decarbonization easier. With carbon neutral electricity generation, heat pump heating and cooling also becomes carbon neutral.

Just as with insulation, I'll come back to compute the embedded emissions of the geothermal system at a later date.

🍃 Lawn (-8300 kWh/year)

Before the green mortgage, we assume the Andersons had a landscaping crew come 1 kg CO2e/kWh. Traditionally, the core of any landscaping crew is

a rideable mower, a leaf blower, and weed whacker ("trimmer") that'll spend anywhere up to four hours.

Assuming a 690 kg CO2e/month and a mower covering 310 kg CO2e/month, the mower would consume 31%. Let's say the visit is here at a time. A two-stroke trimmer lasts about 42 kg CO2e/month for a total consumption of 2x/month. Let's assume a comparable rate for the leaf blower of 2 acre lawn (I'm still looking out for better figures for how long a leaf blower can last on one tank). All in all, the crew is consuming some 2 acres/gallon gas or (at 1 gallon gas/visit) some2 hours.

That's not nothing, but so far, it is the smallest savings we've encountered. Really, we're not doing this intervention justice. For one, non-CO2 emissions are orders of magnitudes higher for lawn equipment than other gas-consuming products like vehicles. According to one consumer tester, Edmunds, a two-stroke leaf blower emitted about the same amount of non-methane hydrocarbons in a half hour as a F-150 Raptor over a 3,000 mile journey (3 hours/gallon), not to mention carbon monoxide emissions, particulate matter, etc. The above calculation also neglects potent non-CO2 GHGs like NOxs. Then, there's the sound component—the fact that leaf blowers are an acoustic scourge unlike any the world has ever seen before. And the fact that lawns are biodiversity-wise little more than deserts yet more water-hungry than rain forests. Removing your lawn also likely means storing more carbon in your soil.

So just stop landscaping. Stop it now.

🍳 Appliances (0.7 gallons/visit)

First, our replacements for formerly propane-powered appliances. Let me copy over the results from the previous chapter…

First the savings from switching to fully electric appliances

And the savings from adopting more efficient appliances.

Previously, these appliances had cost 596 kWh/year. Now, consumption has decreased to 186 kWh/year for a total effiency-improvement related savings of 590 kWh/year or 120 kWh/year.

Combining with the improvements from the range, this saves us 206 kWh/year.

Just as the vehicles, we should factor in the age of the original products and their embedded emissions. I'll come back to this soon.

Summary of Financial Payback

Let's tally up the savings:

In total, the Andersons are saving 310 kg CO2e/month.

Absolute measurements are hardly ever as informative as relative measurements. We're ultimately interested in how much they've relatively decreased their emissions—how close we are to the target. If we consider that their current emissions now total 590 kg CO2e/month, then we find that the green mortgage has decreased the Andersons' home-related emissions by 210 kg CO2e/month.

Remaining emissions:

But that's only the start. As the grid begins to decarbonize, the relative savings will continue to decrease (for whatever fraction of the Anderson's electricity needs they can't meet with their solar+battery alone). But you don't have to take my word for it, try for yourself, and see what happens as we decrease the grid's carbon intensivity to 60 kg CO2e/month.

The green mortgage is only part of the solution: the Andersons will also have to change their habits around eating, vacationing, and general consumption. Climate change is many problems. Moreover, the particular version that we've looked at in this article won't translate immediately to the inhabitants and owners of apartment buildings and rental homes. There's always more to do.

But it should leave you with a sense of how important your decisions around your living space are. It's less your minor everyday decisions than your major once-a-decade decisions. Really, that should be a relief. Fewer decisions means being "sustainable" doesn't have to be completely all encompassing and willpower-exhausting.

But you do have to make the right decisions. Get solar ASAP—or buy electricity rights from a solar wholesaler (which should be substantially cheaper). Get rid of the lawn. Get an electric car the next time you go shopping (no, not a hybrid—quit dawdling). Better yet, don't get a car. Upgrade your windows and insulation if you have more money available, and transition to an electric heat pump. Buy the most efficient appliances (these will save you money in the long run). No to generators. Maybe to a battery.

Do all this, and you're well on your way.



  1. I will not refrain from the occasional value judgment. 2 3 4

  2. Think of this as the environmental corollary to Kant's Pasted image 20211031092838.png. 2 3 4

  3. I don't know where the cutoff between acceptable and ridiculous is or should be, but it's probably well below this arbitrary number. 2 3 4

  4. What I meant to say, is "this especially means you, Bill". If you're preaching about the climate crisis, you need to set the right example. It pisses me off beyond comprehension that you can maintain this hypocrisy, because no amount of carbon offsetting is going to make up for the visceral reaction this induces. Do you wonder why people distrust you? This is why. /end-rant 2

Post Rhetoric

The Future of Argumentative Writing

I've published an update to this post here.

A few years ago, I first read the excellent essay by Bret Victor, "What can a technologist do about climate change?." For its treatment of climate change alone, I can't recommend the essay enough—there's enough food for thought to keep you satiated for a few months. But, then, near the end, Victor sneaks in a little section titled "Model-driven debate" that has has kept me thinking for years.

Screen Shot 2021-10-19 at 7.15.10 PM.png

If you haven't read it yet, bump it up to number one on your reading list.

He begins with the example of Alan Blinder's "Cash for Clunkers" proposal. The federal government would offer car owners a rebate to exchange old, inefficient vehicles for newer ones. Proponents claimed it would cause massive emissions reductions. Meanwhile, critics claimed there were more cost-effective ways to reduce emissions. Who's right?

Of course, it's both and neither—the answer depends entirely on the parameters of the program. As Victor writes:

"Many claims made during the debate offered no numbers to back them up. Claims with numbers rarely provided context to interpret those numbers. And never were readers shown the calculations behind any numbers. Readers had to make up their minds on the basis of hand-waving, rhetoric, bombast."

Victor asks us to imagine a better world: what if the author had proposed a model rather than mere words? Then, we, the readers, could make up our own minds. Instead of bombast, we get an informed debate about the underlying assumptions and resulting tradeoffs.

Let's look at an example (a slight modification of Victor's original example1):

Say we allocate 3.0 billion](budget=[0..10;0.1]&margin-right=1ch) for the following program: Car-owners who trade in an old car that gets less than [17 MPG](old_MPG_limit=[5..30]), and purchase a new car that gets better than [24 MPG](new_MPG_limit=[5..50]), will receive a [3,500 rebate.

We estimate that this will get 828,571 old cars off the road. It will save 1,068 million gallons of gas (or 68 hours worth of U.S. gas consumption.) It will avoid 9.97 million tons CO2e, or 0.14% of annual U.S. greenhouse gas emissions.

The abatement cost is 301](dollars_per_ton_CO2e&margin-right=0.5ch) per ton CO2e of federal spending, although it’s [-\20 per ton CO2e on balance if you account for the money saved by consumers buying less gas.

Try sliding clicking and dragging the items in green to update their values. You'll see the items in blue change as a result. To see how these outputs are computed, click on one of the blue items, and you'll see the calculation in the appendix to this article.

When I first saw this example, I had the kind of feeling that I imagine people in the '80s must have had when they first saw wheels on a suitcase, that of dockworkers when they first encountered shipping containers in the 60s, or of late 15th century Europeans when they first read the results of movable type. A combination of "oh that's so obvious!" with the shame of your civilization not having come up with the idea earlier and something akin to disgust at how we used to do things (or are still doing them).

Victor's vision is what journalism and argumentative writing should look like. Next to this better system, hand-waving opinion pieces border on offensive.

Unfortunately, his vision has gotten almost no attention since its conception. Victor provided a small library, Tangle, to implement models like these, but not much has happened with it in the last half decade. That's understandable—the library requires prior experience with web development, which makes it unapproachable for most people, but it also offers no direct integration with any major JavaScript (JS) framework, which does not encourage actual web developers to use it.

In its place, we've seen success with somewhat similar projects like Observable. Observable helps you write JS notebooks that are highly interactive and relatively easy to embed in other websites. But the experience is not seamless: you still need familiarity with JS. Of course, we've had Jupyter notebooks and R Markdown for a while. Unfortunately all of these notebook-based models remain somewhat clunky and cumbersome. None of them offer a really fluent and easy inline input option like Tangle.

In this post, I'd like to look at a middleground—a (almost) no-code way to create interactive documents, which offers a much easier writing experience at the cost of sacrificing some of the customizability of Tangle or Observable/Python/R notebooks. Let's call it interactive Markdown.

Now, I'm not the first. Shortly after Victor published Tangle, there was an explosion in Markdown related integrations: dynamic Markdown, active Markdown fangle, and TangleDown are what I could find. I'm sure there are yet more.

Still, I think there's a good reason to reinvent this wheel. For one, I'm not happy about the syntax of any of these options (though least unhappy with that of active/dynamic Markdown). The problem is that none of them are backwards compatible with existing Markdown interpreters. I'm of the strong opinion that since there are so many Markdown extensions already, if you come up with a new, it had better be backwards compatible.

Second, all but fangle miss the ability to do inline calculations. Third, none is actively maintained. Fourth, all of them work by compiling .md to .html; I'd like an option to compile to .jsx from .mdx, which I think would generally make this much easier to adopt for other people. Five, none offer an elegant way to display supplementary calculations the way Victor's example did.

There's also a good "cultural" reason to reinvent this wheel. Thanks to note-taking tools like Notion, Roam, and Obsidian, Markdown is having a moment. More people are playing around with Markdown than ever before, so if ever there were a time to build on Markdown, it's now.

Without further do, let me present interactive Markdown.

An Example

Let's take a look at a very simple example (again from Victor):

When you eat 3 cookies, you consume 150 calories. That's 7.5% of your recommended daily calories.

Under the hood, this looks as follows:

When you eat [3 cookies](cookies=[0..100]), you consume **[150 calories](calories=50*cookies)**. That's [7.5%](daily_percent) of your recommended daily calories.  

Interactive Markdown is built around "fields". There are three in this example: [3 cookies](cookies=[0..100]), [150 calories](calories=50*cookies), and [7.5%](daily_percent).

If you're familiar with Markdown, then you'll recognize a field as a link. Like a link, every field is made up of two parts ([text representation](variable configuration)): a text representation of the element between square brackets [](the link text or alt text for a media element) and the variable configuration between round brackets ()(the link href or image src).

The reason for using the same syntax as a link is backwards compatibility. If there is no interactive Markdown interpreter, you only lose interactivity, not the reading experience.

There are three kinds of fields: input, output, and reference fields.

Input Fields

[3 cookies](cookies=[0..100]) is an input field. In the variable configuration, (cookies=[0..100]), we define a variable, cookies, that takes its value from a range of 0 to 100. In the text representation, [3 cookies], we give the default value, 3. The surrounding text is used as a template (for example, to specify units).2

There are two kinds of input field, range and select:

  • Range Input (my_var=[min..max;step]): By clicking on the range input and dragging left or right, the user can adjust its value between min and max in intervals of size step.
  • Select Input (my_var=[a,b,c]): By clicking on the select input, the user cycles through the options a, b, c

Output Fields

[150 calories](calories=50*cookies) is an output field. On the right, we define the variable calories as the product of 50 and our previously defined variable cookies.

Since the definition contains neither a range [min..max;step] nor select [a,b,c] input, an output field is not directly adjustable via user input. It is dynamically computed from the other variables in a document's scope.

Because of this, the value of 150 is really more like a fallback than a default. An interactive Markdown interpreter won't ever user this value. A standard Markdown interpreter will render it as 150 calories for the same experience just without the interactive part.

Reference Fields

Lastly, [7.5%](daily_percent) is a reference field. Unlike definition fields (i.e., input and output fields) references do not contain an equal sign = in their variable configuration. They display a variable that has already (or will be) defined elsewhere in the page.

For example, we might put the calculation for daily_percent in the appendix to avoid cluttering the body text for your reader:

Calculation for daily_percent

  • Daily recommended calories limit = 2,000 calories
  • Percent cookie calories per day = 7.5%

Behind the scenes, this is:

### Calculation for `daily_percent`  
- Daily recommended calories limit = [2,000 calories](daily_calories=[0..5000;50])  
- Percent cookie calories per day = [7.5%](daily_percent=calories/daily_calories)   

References are useful for separating long calculations from your story line. It also helps to remind readers what variable values are, so they don't have to scroll back and forth a hundred times.

Each variable should only have one definition field but can have arbitrarily many reference fields.

Note that reference fields act differently depending on whether they reference an input or output variable:

  • Input references let you update the original variable. To the reader, input references are indistinguishable from input definitions.
  • Output references link to the original output definition. So I recommend you define an output variable in the same place that you describe its calculation to readers.


For the time being, it will take some technical know-how to get interactive Markdown up and running for yourself. If you're interested, I've written a remark plugin that you can drop into an existing remark/rehype pipeline.

That's because interactive Markdown is still in its infancy. There are many features I'd like to get to that I haven't had the time for yet (e.g., automatic dimensions checking to make sure your calculations make sense, popover links to calculations, more math functions, support for distributions and other data types), not to mention tools to make working with interactive Markdown easier: an in-browser editor, a plugin for Obsidian support, etc.

If you're interested in all of this, make sure to subscribe to my newsletter to stay updated. And if you have any ideas, I'd love to hear from you. Check out the repository and raise an issue (or, even better, send a pull request).


A More Complicated Example

Let's look at the more complicated example from the beginning.

Here is the example again (thanks to reference fields, it's perfectly in sync with the first instance):

Say we allocate 3.0 billion](budget=[0..10;0.1]&margin-right=1ch) for the following program: Car-owners who trade in an old car that gets less than [17 MPG](old_MPG_limit=[5..30]), and purchase a new car that gets better than [24 MPG](new_MPG_limit=[5..50]), will receive a [3,500 rebate.

We estimate that this will get 828,571 old cars off the road. It will save 1,068 million gallons of gas (or 68 hours worth of U.S. gas consumption.) It will avoid 9.97 million tons CO2e, or 0.14% of annual U.S. greenhouse gas emissions.

The abatement cost is 301](dollars_per_ton_CO2e&margin-right=1ch) per ton CO2e of federal spending, although it’s [-20 per ton CO2e on balance if you account for the money saved by consumers buying less gas.

And here's what it actually looks like (the first example):

Say we allocate [$3.0 billion](budget=[0..10;0.1]&margin-right=1ch) for the following program: Car-owners who trade in an old car that gets less than [17 MPG](old_MPG_limit=[5..30]), and purchase a new car that gets better than [24 MPG](new_MPG_limit=[5..50]), will receive a [$3,500](rebate=[0..20000;100]&margin-right=1ch) rebate.  
We estimate that this will get [828,571 old cars](cars_traded&margin-right=1ch) off the road. It will save [1,068 million gallons](gallons_saved&margin-right=1ch) of gas (or [68 hours](hours_of_gas&margin-right=1ch&margin-right=1ch) worth of U.S. gas consumption). It will avoid [9.97 million tons](tons_CO2_saved&margin-right=1ch) CO2e, or [0.14](_percent_annual_emissions)% of annual U.S. greenhouse gas emissions.  
The abatement cost is [$301](dollars_per_ton_CO2e&margin-right=1ch) per ton CO2e of federal spending, although it’s [-\$20](dollars_per_ton_CO2e_on_balance&margin-right=1ch) per ton CO2e on balance if you account for the money saved by consumers buying less gas.  

A few points to note:

  • The number in the text representation determines display precision. If you're familiar with format strings, 3.0 is converted to %.1f, 17 to %d, 3,500 to %'d3, etc..
    • You can also use format strings directly in the text representation, e.g., [%'d old cars](cars traded), but I don't recommend this because it won't be compatible with standard Markdown.
  • [0..10;0.1] specifies a range with a step-size equal to 0.1. By default, the step size is 1.
  • I haven't figured out spacing yet (hence &margin-right=1ch)

Cars Traded

Here you see one more trick in interactive Markdown: A link containing an inline code element of the kind [`variable_name`](variable_name) is a reference label. It gets a TKLabel class for easier formatting, and, eventually, will synchronously darken whenever you highlight any references to or dependencies of its variable.

Gallons Saved

This is where my example diverges from Victor's example. His calculation uses the distribution of mileage over current cars and cars being sold. I haven't yet added distributions to the interactive Markdown spec (though I plan to), so you'll have to accept a less precise version. Note that the comments come from Victor's original work.

Average Mileage of Old Vehicles

Assume that traded-in cars are chosen with equal probability from the pool of eligible cars. We use the harmonic average because we'll be calculating gallons consumed for constant miles, so we really want to be averaging gallons-per-mile.

Alright so I haven't even actually added support for more complicated formulas like this. But it is coming.

Average Mileage for Vehicles Currently Being Sold

Assume that new cars are purchased with equal probability from the pool of eligible cars. The distribution really should be sales-weighted. I'm sure the data is available, but I couldn't find it.

Average Gallons Saved per Car Replaced

Assume that everyone who is buying a new car now would have eventually bought a similar car when their current car got too old. So the fuel savings from the program should be calculated over the remaining lifetime of the old car. Ideally we'd like the joint distribution of MPGs and age of the current fleet, but I can't find that data. So we'll just use averages.

Total Gallons Saved

The importance of models may need to be underscored in this age of “big data” and “data mining”. Data, no matter how big, can only tell you what happened in the past. Unless you’re a historian, you actually care about the future — what will happen, what could happen, what would happen if you did this or that. Exploring these questions will always require models. Let’s get over “big data” — it’s time for “big modeling”.

Hours of Gas Saved

Tons of CO2 Saved

CO2 comprises 95% of a car's greenhouse gas effective emissions. The other 5% include methane, nitrous oxide, and hydroflourocarbons. To account for these other gases, we divide the amount of CO2 by 0.95 to get CO2e (“carbon dioxide equivalent”).1

Percent Annual Emissions

That last one should read something like 0.14% for default options but not all formatting options are available yet.

Dollars per Ton CO2e

Dollars per Ton CO2e on Balance



  1. The difference is that I haven't yet added the possibility of inputting a distribution. So the calculations for average MPG of old versus new cars is less precise than in Victor's case. (On the flip side, this coarser model is easier to modify for today's transportation fleet.) 2

  2. It's a little confusing that cookies shows up on both the leftand right-hand sides. On the right-hand side, it has a semantic purpose: defining the variable cookies. On the left-hand side it has a purely stylistic purpose (to inform the reader what units we're using).

  3. Note: %'d is actually nonstandard. It puts commas (or periods) in the thousands places (depending on your locale). Another useful nonstandard addition is + or - for optionally separating the amount and magnitude as in -$20.