A professor at the Harvard T.H. Chan School of Public Health Dominici presents the Henry W. Kendall Memorial Lecture at MIT. She reveals how leveraging huge amounts of data in the United States affects air pollution levels on human health.
For providing a data-driven foundation, their efforts are critical to building environmental regulations as well as human health policy. But they say that the results will be excellent when they use data science and evidence to notify policy.
How Data Science to Gather Air Pollution Insights
In the past 20 years, air pollution is dramatically dropping in nationwide. Dominici says on average, we all are breathing clean air. But some research also shows that even with relatively low air pollution levels, it may be harmful to health.
In addition, current patterns of diminishing air pollution left some geographic areas worse off than others. In the various studies, Dominici hone on some specific type of harmful air pollution called fine particulate matter.
These tiny particles are less than 2.5 microns in width. They come from multiple sources like industrial facilities that burn fossil fuel and vehicle emissions.
These particulate matters can go in very deep into the lungs and then get into your blood. Further, it can lead to cardiovascular disease, systemic inflammation, and a weak immune system.
To examine the risk PM2.5 poses on human health, Dominici made data about people and the environment they experience. One dataset provides information for more than 60 million Americans who sign up for Medicare. It includes not only their health history but also other factors, including Zip code and socioeconomic status.
On the other side, a team of Joel Schwartz, who is a professor of environmental epidemiology, combines satellite data on weather. This data also includes air pollution, land use and unite them with air quality data from the EPA’s national network.
This helps them to create a model that offers a daily level of PM2.5 for every square kilometer. In this way, they can assign people’s daily exposure to PM2.5 who registers themselves in the Medicare system.
For acquiescing several findings, it is vital to combine and analyze these datasets. On the basis of present NAAQS for PM2.5, levels which are less than 12 micrograms per cubic meter are safe.
Dominici’s team also says that even levels less than standard may possess a higher risk of death. Further, they say by reducing the standard to 10 micrograms per cubic meter, the air quality becomes more rigorous. It will help to save approximately 140,000 lives over a decade.
During the Covid-19 pandemic, problems regarding both environmental injustice and air pollution are at harsh relief. They also say that how long-term exposure increases the risk of dying from Covid-19.
Data scientist is the best way to find all those factors that are influencing serious environmental policy decisions. Moreover, this pandemic can also provide an additional source to control emissions regarding fossil fuels. In this way, scientists are using data science to gather air pollution insights.