A product of decades of industrialization, urbanization, and motorization, chronic severe air pollution is now a global phenomenon. Today, 90 percent of the world’s people live in places that do not meet World Health Organization (WHO) air quality standards. The consequences for human health have been grave. Each year, air pollution causes 5 to 9 million premature deaths and many more cases of bronchitis, asthma, and other cardiopulmonary illnesses.
The global south is the epicenter of this problem, accounting for more than 90 percent of the deaths and illnesses attributed to air pollution. Although indoor air pollution from the use of wood fuel is a major contributor, most deaths and illnesses are caused by outdoor pollution. Moreover, in most developing countries, outdoor air pollution is getting worse, not better.
Unfortunately, it will be difficult to address this problem by significantly improving outdoor air quality in the short-to-medium-term. A lack of political will and shortages of human and financial capital all curb the effectiveness of environmental regulation.
Therefore, perhaps the most practical and cost-effective strategy for reducing illness and death caused by air pollution in the short to medium term is to reduce exposure by encouraging people to avoid outdoor activities, close windows, and engage in other avoidance behaviors on days when air pollution is severe. And that, in turn, requires disseminating timely and accurate information about air quality, along with recommendations about how to avoid exposure. Information and communication technologies (ICTs) are a logical means of providing such information.
Recently, smartphone apps that display real-time information on air quality have become available. For example, the U.S. Environmental Protection Agency’s AirNow app provides historical, real-time, and predicted data for most cities in the United States. Sameer, Air Quality China, and AirRater provide similar data for cities in India, China, and Australia. And apps like AirVisual and IQAir compile this information for cities around the world. However, the extent to which these apps actually affect avoidance behavior, environmental attitudes, and other outcomes is not clear: to our knowledge, the effects of air quality smartphone app on such outcomes have never been studied.
A recent IDB Working Paper, “Breathe Easy, There’s an App for That: Using Information and Communication Technology to Avoid Air Pollution in Bogotá,” helps fill that gap. The paper summarizes the results of a randomized controlled trial that evaluated the effect of training university students in Bogotá, Colombia—a city with chronic severe air pollution—to use Aire Bogotá, an air quality smartphone app developed by the municipal government.
The study randomly assigned a sample of 578 university students to either a control group or a treatment group that received an information session—on air pollution, avoidance behaviors, and the Aire Bogotá app—along with an invitation to participate in a six-week interactive email campaign designed to habituate them to using the app. A baseline survey, which was administered in person in March 2020 just before the information session, and an endline survey, which was administered remotely three months later, collected information on sociodemographic characteristics and a range of behavioral and attitudinal outcomes.
We find that the training boosted participants’ acquisition of information about air quality, their knowledge about avoidance behavior, their actual avoidance behavior and their concern about other environmental issues. With regard to the acquisition of information about air quality, the training increased by 84 percentage points the probability of having the air quality app installed a device and by 29 percentage points the probability of using the app to search for air quality information.
As for knowledge about avoidance behavior, the training increased by 3 percentage points the probability of knowing that changing some aspect of one’s behavior can reduce the adverse health effects of air pollution and it increased by 9 to 31 percentage points the probability of knowing about specific avoidance behaviors.
Regarding actual avoidance behavior, the training increased by 9 percentage points the probability of changing of having changed any behavior in the past two weeks as a result of poor air quality. It increased by 5 percentage points the probability of having worn a mask with a filter in response to poor air quality and by 7 percentage point the probability of having closed windows.
The treatment also enhanced participants’ concerns about other environmental issues. It increased their level of concern about hazardous waste by 0.19 Likert points [0–4 scale], boosted their concern about water pollution by 0.14 Likert points [0–4 scale] and cut by 8 percentage points the probability that they believed that pollution was a necessary trade-off for fostering economic growth.
Finally, the effects of the training were moderated by participant characteristics. In particular, among students who were also job holders, it was less effective in increasing use of the air quality app, actual avoidance behavior, and air quality warnings.
These findings have useful policy implications. They confirm that training in the use of air quality smartphone apps may be an effective means of reducing adverse health effects of severe air pollution in developing countries, where air pollution has the most effects on human health and where prospects for reducing emissions in the short to medium term are arguably most limited. In addition, they suggest that training in the use of such apps can have spillover effects on people’s attitudes about other types of pollution and environmental quality in general.