Short trips in cars

April 9, 2014

Discussions about replacing car trips with bicycle trips often focus on commutes, and whether those are too long or too unpleasant/unsafe. However, it turns out that commuting trips are only about a quarter of all trips, and also disproportionately not-short, so this makes cycling look less practical than it actually can be. Here are bar charts, taken from data from ORNL about vehicle use in 2009, where the heights of the charts were chosen to (1) be roughly in proportion and (2) split evenly into four parts on the cumulative-amount scale. Each pair of bars shows the number of trips of a particular length in miles (blueish bar), together with the sum of all trips that long or shorter (reddish bar). The first chart, with height to scale, shows how this is distributed for commuting vehicle trips only, the second chart shows how this is distributed for all vehicle trips.

Thus, it’s easy to see that half of all vehicle trips are five miles or less long, versus commuting, where the median trip distance appears to be closer to 8 miles (extrapolating on the 5-9 scale). Note also that there are more “all trips” that are three or fewer miles long and not commutes (76.5 billion total, comprising 11.4 billion commuting trips and 64.1 non-commuting trips) than all commuting trips combined (60.8 billion).



Short trips, however, don’t amount to that many road miles. Putting people on bikes may make cities quieter, cleaner, and safer, and their riders healthier, but it won’t put that big a dent in fuel use.



Excel version of the spreadsheet used to make the charts.

Original spreadsheets from ORNL.gov.

This does not count carbon taxes (ought to be 25 cents per gallon) or pollution taxes (in the range of $1 to $1.50 per gallon, based on location) or noise taxes or crash risk to others (in theory insurance captures this, but insurance may not pay out if a smashed pedestrian or cyclist was “at fault” — but without the speed and bulk of the car, harm would have been smaller) or congestion costs. This is just the cost to build and maintain the roads. The images links to the spreadsheet containing all data and links to documents from which it was obtained; these are all government sources, either EIA, FHWA, or Federal Reserve.

No, bicycles do not tear up roads, nor do they pollute or make noise. Their crash risk to others is many times lower, and because they take up so much less space their congestion costs are correspondingly lower.

In a comment exchange on some random liberal blog, a transit advocate was mysteriously opposed to bicycles-as-transit. He never completely explained why, but I think he was making assumptions about road damage and congestion that assumed a linear relationship to weight. However, that’s just not so. Damage-per-wheel is at least proportional to the cube of the weight on the wheel, if not the fourth power. It’s very non-linear, and non-intuitively a heavy vehicle with many wheels can do less road damage than a lighter vehicle with just a few.

Turns out, a city bus can do a LOT of damage, and per-passenger, it does over twice the damage of even a single-occupancy SUV. A plan-loaded city bus is almost as bad for roads as a fully loaded semi truck, and a crush-loaded city bus is worse. Whether you calculate it as marginal damage per passenger, or average damage per passenger, a bus passenger is hundreds of times more damaging to the road than even a fully-loaded cargo bike, and thousands of times more damaging than someone merely carrying themselves on a bicycle. Even the marginal road-damage cost of the first passenger to board a bus is a little bit worse than the road-damage cost of a single-occupancy SUV.

I’m not at all sure that these costs are rolled into the published “costs” of transit. Note that these are not the only costs; there are congestion costs, parking space costs, fuel costs, risk-to-others costs, risks-to-rides costs. But the road damage costs are really large.
(And if someone knows more about this than I do, do please check my math, I am working from published sources and conservative estimates. This was surprising to me.) Read the rest of this entry »

US Density blobs

November 10, 2013

Standard US anti-cycling claim: “We’re too spread out, not like those dense European countries.”

Here’s the copy-and-paste from Calca:

density(area, population) = population/area

NYCMetro_area = 13,318
NYCMetro_population = 23,508,600
density(NYCMetro_area, NYCMetro_population) => 1,765.175


Netherlands_area = 16,039
Netherlands_population = 16,819,595
density(Netherlands_area, Netherlands_population) => 1,048.6686


Massachusetts_area = 10,555
Massachusetts_population = 6,646,144
density(Massachusetts_area, Massachusetts_population) => 629.6678


Denmark_area = 16,562.1
Denmark_population = 5,602,536
density(Denmark_area, Denmark_population) => 338.2745

And if you notice, there’s a whole lot of Western Massachusetts that’s relatively empty (and also relatively hilly), but that works against the “we’re spread out” claim; if the west is sparse, then the east must be even denser.

And no, we do not have a uniform transit policy across the nation — how many subways are there in Montana or Alaska? We do what’s locally appropriate.

Among our excuses for not riding bicycles is that America is too spread out. This explains why we don’t ride cross country very often, but not why we don’t ride to the grocery store. In fact, a whole lot of us live in places that are quite dense. I attempted to graph this before using 2000 Census data and “50K areas” but I was unhappy with the result, both because of my errors and because 50K area leaves out a lot (I live in a town of 25000, for example).

Happily, with new data, organized by non-overlapping zipcode, I can solve both those problems. One sixth of us (52 million people) live in places denser than 5362 per square mile; the next sixth, denser than 2786 per square mile, the next sixth, denser than 1292 per square mile (that’s the median density for our population; half of us live in zipcodes less dense than that, too). With all the zipcodes included it’s clear that many of us live in plenty-dense places.

I’ve tagged the graph with densities of towns and cities near Boston, mostly inside 128, plus all of Boston, and also plus three European cities known for their relatively high bike trip share. I added some other US cities for comparison.

This graph is cumulative, meaning that the Y axis is the sum of all the people living in zipcodes with a density of X or more. For example, about 30 million people live in places with 8000 or more people per square mile.


“Democrat math”

December 13, 2012

Also known as “math”.

Apparently some conservatives and other deluded souls believe that our appallingly low life expectancy is not a healthcare result, but is instead caused by excess (misclassified, not health-related) infant mortality and excess violence. This, like many conservative beliefs, is bullshit. Proof:

Suppose we have a “true” life expectancy, but two subpopulations that die early for non-medical reasons and drag it down. The “misclassified infant death” subpopulation dies at age 0, and accounts for about 0.003 of our deaths (that is, the excess US infant mortality rate is about 3 per 1000). The “murder death” subpopulation dies at an average age of 25 (a guess), and accounts for 15,000 deaths per year out of a total of 2,500,000 or 0.006 of our deaths. The reported US life expectancy is 78.37 years, and this is equal to the adjusted life expectancy * 0.991 + 25 * 0.006 + 0 * 0.003.

That is, adjusted = (78.37 – 25 * 0.006) / 0.991 = 78.93.

Without adjusting ANY OTHER COUNTRIES (Portugal’s infant mortality rate is better than ours, but not first-class) for worse-than-hoped infant mortality or murders, we move all the way from #49 to #44. That’s not much to brag about.

Update, the claim is it’s traffic accidents

Because I am feeling lazy and generous, I’ll assume average age 30, erase ALL of them, the death rate is 33,808/2,500,000 = 0.0135.

adjusted = (78.37 – 25 * 0.006 – 30 * 0.0135) / 0.9775 = 79.6.

That’s #37 in the list. USA! USA! USA!

That figure is overly generous and should not be relied on, because there are other countries between #49 and #37 with relatively high traffic death rates that would also be “corrected” upwards in the same way, among them Belgium and South Korea.

Further update — what if we try to factor in the exercise that we don’t get because we drive cars to excess?

That might matter. The years-of-life penalty is estimated to be 2-5 years, though it can be made up with other forms of exercise. +2 years takes us out of the embarrassing weeds, and up into the top ranks. However, again, one-must-apply-the-correction-equally; even in the Netherlands, even in Denmark, many people do drive automobiles to excess (how do you think they were able to do these studies in the first place?)

You may have noticed the news that there’s less ice in the arctic this summer than at any time in recorded history.

What’s interesting is that back in 2007, a researcher at the Naval Postgraduate School came pretty close to predicting this — he suggested an ice-free summer as early as 2013. And then, conventional wisdom was ice-free somewhere between 2040 and 2100.

But look at what simple extrapolations of ice cap volume get us now, five years later:

And see how the extrapolations have changed over time:

That is, a simple fit back in 2007 would have predicted ice-free in 2019, and since then the predicted ice-free year has moved 2 years earlier.

What does this mean? One somewhat-modeled prediction is slower Rossby waves, which means that what ever weather we get (hot, cold, dry, wet), we’ll get it in longer-lasting doses. But the big official predictions (e.g., the IPCC reports) don’t incorporate any of this news; they’re still based on the assumption that there is some amount of Arctic ice cap for decades.

My personal prediction is that this next winter, or the next, when some large hunk of the US gets stuck under a long-lasting blob of cold Arctic air, that some head-in-the-sand moron will say “this proves that there is no global warming”.

Relevant links:

Estimated changes in albedo

Calculations of consequence of albedo change (LARGE).

Arctic Sea Ice blog (Good source of data, discussion, links)

And again, none of the “official” conservative models include this effect, because they assume the arctic ice cap persists for another 40 years, and not fewer than 4. This is a big warming change.