Scientists suspect that, in general, air pollution affects psychologically, and that a dirty air due to industrialization, coal combustion and motor vehicles has become a burden for the welfare of those who live in Chinese cities. But these effects are difficult to measure.
And that's where it comes in Weibo, the Chinese version of Twitter. An international team of researchers analyzed entries made between March 1 and November 30, 2014 and geo-tagged in 144 different Chinese cities.
They used a specific program of semantic analysis to evaluate the sentiment expressed in each Weibo entry and then analyzed the daily happiness index on a scale of 1 to 100 for each city. The researchers have published their results in Nature Human Behavior.
Weibo users expressed significantly more happiness in their entries on good news days, such as when Beijing hosted the Asia-Pacific Economic Cooperation Summit, and less happiness on the days when bad news was published, such as the collapse of flight 370 Malaysia Airlines. This reinforces the argument that this method allows the detection of short-term changes in the happiness of a population.
And how does it influence pollution? The researchers collected data on the daily pollution levels in each city, and introduced them in equations to establish models of how pollution affects the level of happiness expressed in the entrances to social networks. The details of these analyzes are designed to maximize the probability of detecting causal relationships.
The researchers analyzed Weibo entries in relation to the total air quality index (ICA) of a city, as well as a variety of individual pollutants. They focused especially on the fine particles in suspension (PM2.5), which can damage lung health and especially concern the Chinese population, as indicated by the searches in Baidu-com, the most popular search engine in China. During the period covered by the study, PM2.5 was the main pollutant in 60% of the days with high contamination.
When the total contamination measured by the ICA drops one standard deviation, the happiness index increases a standard deviation of 0.046. Similarly, the reduction of one standard deviation in the concentration of PM2.5 is associated with an increase of 0.043 of the standard deviation in the happiness index. These happiness changes correspond to approximately one-tenth of those observed during the three days of May Day holidays. This suggests that the effect of pollution on happiness is small but real.
"There is evidence to conclude that high levels of air pollution decrease the levels of happiness manifested by the urban population," the scientists say.
Pollution depresses the population more on weekends and holidays than working days. Atmospheric pollution affects people's happiness more on cloudy days than sunny days, and more on days that are too hot or cold than those where the temperature is more pleasant. Women are affected psychologically more than men. And the people who live in both the cleanest and the dirtiest cities are the ones who experience major mood swings in response to air pollution.
"Given that the subjects are not aware that their opinions are being analyzed, these data can offer a vision without filters of daily life in a very polluted country," the scientists say.
One drawback of the study is that Weibo users do not represent a random sample of the Chinese population. For example, older people are less likely to use social networks, but they are more vulnerable to air pollution.
However, this lack of representativeness could in fact be an advantage when it comes to combating pollution in China. Users of social networks tend to be younger and academically better prepared than the average, a demographic segment that the Chinese Government considers especially important. Scientists say that the fact that air pollution erodes the well-being and psychological health of that segment could lead authorities to better monitor compliance with environmental regulations.
Source: Zheng S. et al. "Air pollution lowers Chinese urbanites' expressed happiness on social media" Nature Human Behavior 2019
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