The study, published in the journal Nature Human Behaviour, found that higher levels of pollution are associated with a decrease in people’s happiness levels. Despite an annual economic growth rate of 8%, satisfaction levels amongst China’s urban population have not risen as much as would be expected, researchers said. Alongside inadequate public services, soaring house prices, and concerns over food safety, air pollution — caused by the country’s industrialisation, coal burning, and increasing use of cars — has had a significant impact on quality of life in urban areas.
Research has previously shown that air pollution is damaging to health, cognitive performance, labour productivity, and educational outcomes. However, air pollution also has a broader impact on people’s social lives and behaviour, according to Siqi Zheng, an associate professor at MIT. “Pollution also has an emotional cost. People are unhappy, and that means they may make irrational decisions,” Zheng said.
On polluted days, people have been shown to be more likely to engage in impulsive and risky behaviour that they may later regret, possibly as a result of short-term depression and anxiety, according to Zheng. “So we wanted to explore a broader range of effects of air pollution on people’s daily lives in highly polluted Chinese cities,” she said.
The researchers, including those from the Chinese Academy of Sciences and Shanghai University of Finance and Economics, used real-time data from social media to track how changing daily pollution levels impact people’s happiness in 144 Chinese cities.
“Social media gives a realtime measure of people’s happiness levels and also provides a huge amount of data, across a lot of different cities,” Zheng said. The researchers used information on urban levels of ultrafine particulate matter — PM 2.5 concentration — from the daily air quality readings released by China’s ministry of environmental protection.
To measure daily happiness levels for each city, the team applied a machine-learning algorithm to analyse the 210 million geotagged tweets from China’s largest microblogging platform, Sina Weibo.
The tweets cover a period from March to November 2014. For each tweet, the researchers applied the machine-trained sentiment analysis algorithm to measure the sentiment of the post. They then calculated the median value for that city and day, the so-called expressed happiness index, ranging from 0 to 100, with 0 indicating a very negative mood, and 100 a very positive one. Finally, the researchers merged this index with the daily PM2.5 concentration and weather data.
They found a significantly negative correlation between pollution and happiness levels. Women were more sensitive to higher pollution levels than men, as were those on higher incomes. When the researchers looked at the type of cities that the tweets originated from, they found that people from the very cleanest and very dirtiest cities were the most severely affected by pollution levels. PTI