So they are not comparing clean air neighborhoods to highly polluted neighborhoods, but the same neighborhood on different days.
https://www.sciencedaily.com/releases/2019/10/191003114007.h...
'Exposure to' makes me think it's more prolonged, and over time the effect is[...] but actually it's suggesting that it has a reversible, quickly reacting/short-term impact, which (naively) I find much more surprising.
Relevant excerpt:
> They find that a 10% increase in same-day exposure to PM2.5 (particulate matter less than 2.5 microns in diameter) is associated with a 0.14% increase in violent crimes, such as assault. An equivalent increase in exposure to ozone, an air pollutant, is associated with a 0.3% jump in such crimes. Pollution levels can easily rise by much more than that.
Reading the title, I was expecting this to be a long-term relationship, and to happen at extremely high levels of air pollution. Particularly since the study on China last year showing that exposure to PM2.5 has lasting cognitive effects, which found variation at levels far higher than anything found in the US. And ozone at approved levels (but not PM2.5) has been linked to long-term cognitive decline.
Instead, this is claiming day-to-day variation based on that PM2.5 levels that are 25% of the EPA 24-hour exposure threshold, and even below the annual EPA standard. If you told me that air pollution below the EPA safe thresholds had a noticeable impact on cancer or emphysema rates, I wouldn't be surprised at all. But this is wild - a 5% increase in violent crime based on a day of pollution! For reference, one violent crime study I just checked finds that violent crime is about 10% higher in the summer than the winter in a cold city, and late-night crime (past midnight) is about 5% higher on weekends than weekdays. So 15 micrograms of PM2.5 is about as impactful as "people stay up late and get drunk on weekends".
It's an effect so bizarrely strong that my first reaction is to assume the study is bad or confounded. Except... all the obvious patterns don't work, and the controls look solid. Unpleasant weather keeps people inside and reduces (outdoor) crime. Shared causes like high human activity should have raised property crime rates. The effect looks stable across all kinds of temperature and crime subsets. If there is a confounder, it's presumably something strong and interesting.
> Pollution levels can easily rise by much more than that.
Very true, although I note that the effect doesn't seem to continue across the whole range studied. I wonder why effect falls off, and what happens in places that are always this polluted?
Pun intended? If so, this was brilliant IMO!
And even excluding road rage as the mechanism for violence, 10% more people doing actions all over the place can also just cause violence.
density causes more interaction which causes more conflict.
I see this all the time at meetup tech talks and it infuriates me!
It is related to arguement from ignorance and Dunning-Kreuger effect in that it often assumes their comprehended issues are the end of all problems and that the objections may already be implicitly handled. Listing everything explicitly in exhaustive detail technically addresses it but would be both inefficient and bad communication from how overloaded it would get.
That said assuming uncovered issues are implicitly covered is itself a fallacious inference. It may be dickish pedantry that is wrong based upon incomplete information but not illogical given what is known and communicated.
This seems pretty extensive and serious
There is likely less violent crimes on rainy days, just because more people stay home.
To do this properly, they would have to do a controlled experiment with people in rooms with or without air pollution. And measure how sanguine they get or something of that nature.
"Pollution and crime rates may have common correlations with location and time-varying unobservables. For example, PM2.5 or ozone levels and crime rates may be correlated with county-level covariates such as traffic density, population density, demographics, and industrial activity. Failing to control for such covariates will lead to biased estimates of γPM and γo.
Our identification strategy explicitly addresses omitted variable bias in several ways.
First, we show that endogeneity with respect to violent crimes and pollution can be addressed by including a series of high-dimensional fixed effects. In our primary specification, we include county-by-year-by-month-by-day of the week fixed effects to control for county level unobservables that are either constant over time, such as state and county-level policies, or that are time-variant, such as changes in population density, demographic composition, seasonal variation in pollution or crime, or changes in state and county-level policies that limit pollution or crime enforcement. These fixed effects also control for cyclical within-week, within-county variation in pollution and crime. Thus, our data allows us to compare for example, the effect of changes in pollution within a series of Mondays within a given county within a given month. We argue that changes in pollution across a series of Mondays within a county-month, conditional on weather controls, is random and thus exogenous to crime.
Second, crime has been shown to respond to changes in temperature, and temperature is generally correlated with air pollution (Field 1992; Jacob et al. 2007; Ranson 2014). Thus, failure to adequately control for temperature, and weather more generally, will lead to biased estimates. To address this concern, we include temperature and precipitation splines in our primary specification, we provide robustness checks with alternative functions of temperature, and in Section 5.3 we perform a series of tests to show that our results are not confounded by unaccounted for variation between temperature and air pollution. For example, we show that effect of PM2.5 on violent crime is larger at lower temperatures, opposite of the effect of temperature alone."
This sort of thing has happened before. Lead was removed in the late 70's, and, lo, 20ish years later, crime rates dropped -- perhaps, for the reason there are fewer neurological impacts growing up without airborne lead.
Don't get me wrong, any savings is an improvement, but EVs are not the 'green' transport revolution the industry wants to picture them as, just an incremental step.
https://www.researchgate.net/publication/297889793_Non-exhau...
Sometimes you can use common sense to infer a causal relationship (violent crime linked to emergency room visits), but it seems like a leap here, especially as they're on a bit of a fishing expedition with multiple types of pollution and multiple types of crime.
The authors are aware of this and attempt to control, mainly by assuming that all confounding effects are either constant or cyclical:
"We include county-by-year-by-month-by-day of the week fixed effects to control for county level unobservables that are either constant over time, such as state and county-level policies, or that are time-variant, such as changes in population density, demographic composition, seasonal variation in pollution or crime, or changes in state and county-level policies that limit pollution or crime enforcement. These fixed effects also control for cyclical within-week, within-county variation in pollution and crime. Thus, our data allows us to compare for example, the effect of changes in pollution within a series of Mondays within a given county within a given month. We argue that changes in pollution across a series of Mondays within a county-month, conditional on weather controls, is random and thus exogenous to crime."
I'm not at all convinced this holds true, however - lots of systems with humans in it are chaotic rather than cyclical. I imagine if you did a plot of population over time, it would be very noisy. All it takes is a bit of aperiodic noise in the population, and tight correlations between population/crime and population/pollution, and their effect is rendered void.
People should just stop doing this kind of studies, we are just not equipped with powerful enough mathematical tools yet to deal with this kind of highly entangled phenomenons (and we often don't have the data either, collecting and curating it would be an interesting and useful research topic by itself).
Perhaps simply not drawing false conclusions from them would be better.
Exposure to air pollution seems to my intuition like it lowers a persons level of consciousness, and the lower a persons level of consciousness (the further down The Spiral Dynamics model they are) the more prone they are to violence.
Nobody in the field of people publishing this kind of studies has the required skill-set to develop the needed tools. This is the job of mathematicians. I'm not meaning it pejoratively, it's just a totally different job. (I wouldn't trust a mathematician to build a house, you shouldn't trust an economist, a biologist, or anyone to build statistics tooling).
> maybe thats what the intent behind "collecting and curating" was?)
Most of the time the data behind this kind of studies isn't easily available. Sometimes you can shoot an email to the author, sometimes it comes from some publicly available data needing a lot of preprocessing before being consumable, and I wish we had a centralized database of well-formed data.
I would be more convinced if ozone/pollution was released by the scientists in an area and they found the same effect.
This doesn't mean it is impossible, as rain might e.g. still be correlated with less traffic. The nature of a hidden variable is exactly that its indirect correlations would be not pinpoint-able in the data.
But IMHO this paper does a decent job of trying to account for lots of dimensions, and trying identify the existence of dominant hidden variables from the data at hand.
This is far from a rush job or a 'spurious correlation' piece of work, and its results most certainly are interesting and a very good basis for further investigation into an important observation. I'd even go further and say that these results warrant societal value systems that subscribe to the precautionary principle to take this on board in further decisions about pollution in populated areas.
Is that 'million' a typo? I imagine $1.1m amounts to something like one homicide a year.
What if, in this case, pollution has a delayed effect? How would their methodology deal with that (it wouldn't)?
Personally, I think what happened here is the author started with a prior belief: ""Several years ago, Fort Collins experienced a fairly severe wildfire season," Burkhardt said. "The smoke was so bad that after a few days, I started to get frustrated, and I wondered if frustration and aggression would show up in aggregate crime data.""
and then they conducted a study that supported their belief, possibly making methodological errors along the way , generating a scientific narrative to support their belief.
Edit: found a copy of the paper that wasn't paywalled, read the whole thing, and found their attempts to correct for bias wanting (section 4.2).
" Overall, our heterogeneity results indicate the most important explanatory factor in the relationship between pollution and crime is age, and the results are not ameliorated by higher incomes."
uh, ok. if you want to defend this paper go ahead but I've already read enough to know these folks started with a biased belief, carelessly analzyed the data in a way that supported their beliefs, and escalated the results into something that sounded far more significant and certain than their data shows.
An interesting result, to be sure, but correlation does not imply causation.
The researchers were careful to correct for other possible explanations, including weather, heat waves, precipitation, or more general, county-specific confounding factors."
https://www.sciencedaily.com/releases/2019/10/191003114007.h...
The paper's abstract says "The results suggest that a 10% reduction in daily PM2.5 and ozone could save $1.4 billion in crime costs per year, a previously overlooked cost associated with pollution." In my opinion this is a statement of a causal relationship, not merely a correlation.
I wonder why they didn't reverse that relationship, too, and propose that violent crime increases pollution.
I would love to read the actual paper, but it's only available to people with money.
Probably because you can easily rule out that possibility using common sense, whereas causation in the other direction is at least thinkable and worth investigating further.
more activity -> more pollution -> more crime
more activity -> more crime
Say what? You should write these scientists and explain, I'm sure they've never heard of this concept!