MIT researchers have shared promising environmental news: human-induced mercury emissions have decreased over the past two decades, contrary to global emission inventories that suggest otherwise.
In a recent study, the researchers examined data from all available monitoring stations in the Northern Hemisphere and found that atmospheric mercury concentrations dropped by about 10% between 2005 and 2020.
They employed two distinct modeling methods to identify the causes of this trend, both of which pointed to a reduction in human-related mercury emissions as the most likely reason.
Conversely, global inventories have shown opposite trends. These inventories estimate atmospheric emissions using models that incorporate average emission rates from polluting activities and the scale of these activities worldwide.
"Our work highlights the importance of learning from real-world data to improve our models and emission estimates. This is crucial for policy-making because if we cannot accurately estimate past mercury emissions, how can we predict future mercury pollution trends?" says Ari Feinberg, a former postdoc at the Institute for Data, Systems, and Society (IDSS) and lead author of the study.
The new findings could assist scientists engaged in a global collaborative effort to assess pollution models and develop a deeper understanding of what influences global atmospheric mercury concentrations.
However, due to the lack of data from global monitoring stations and limited scientific understanding of mercury pollution, the researchers could not pinpoint the definitive reason for the discrepancy between inventories and recorded measurements.
"It seems that mercury emissions are moving in the right direction and may continue to do so, which is encouraging. But that’s all we could ascertain with mercury. We need to keep measuring and advancing the science," adds co-author Noelle Selin, a professor at MIT in the IDSS and the Department of Earth, Atmospheric, and Planetary Sciences (EAPS).
Feinberg and Selin, his postdoctoral advisor at MIT, collaborated on this paper with an international team of researchers who contributed atmospheric mercury measurement data and statistical methods. The research is published this week in the Proceedings of the National Academy of Sciences.
Mercury Mismatch
The Minamata Convention is a global treaty aimed at reducing human-induced mercury emissions, a potent neurotoxin released into the atmosphere from sources like coal-fired power plants and small-scale gold mining.
The treaty, signed in 2013 and effective from 2017, is reviewed every five years. Its first conference coincided with discouraging reports that global mercury emission inventories, partially compiled from national inventory data, had increased despite international reduction efforts.
This was puzzling news for environmental scientists like Selin. Monitoring station data showed a decline in atmospheric mercury concentrations over the same period.
Bottom-up inventories combine emission factors, such as the amount of mercury entering the atmosphere when coal from a specific region is burned, with estimates of polluting activities, like the amount of coal burned in power plants.
"The big question we wanted to answer was: what is actually happening to mercury in the atmosphere, and what does it tell us about anthropogenic emissions over time?" says Selin.
Modeling mercury emissions is particularly challenging. Firstly, mercury is the only metal that is liquid at room temperature, giving it unique properties. Additionally, mercury removed from the atmosphere by sinks like the ocean or land can be re-emitted later, complicating the identification of primary emission sources.
At the same time, mercury is harder to study in the lab than many other atmospheric pollutants, partly due to its toxicity. Scientists thus have a limited understanding of all the chemical reactions mercury can undergo. There is also a much smaller network of mercury monitoring stations compared to other pollutants like methane and nitrous oxide.
"One of the challenges of our study was to develop statistical methods capable of bridging these data gaps, as available measurements come from different periods and measurement networks," explains Feinberg.
Multifaceted Models
The researchers compiled data from 51 stations in the Northern Hemisphere. They used statistical techniques to group data from nearby stations, helping them fill data gaps and assess regional trends.
By combining data from 11 regions, their analysis indicated that atmospheric mercury concentrations in the Northern Hemisphere decreased by about 10% between 2005 and 2020.
Next, the researchers used two modeling methods—biogeochemical box modeling and chemical transport modeling—to explore possible causes for this decline. Box modeling was used to run hundreds of thousands of simulations to evaluate a wide range of emission scenarios. Chemical transport modeling is more computationally intensive but allows researchers to assess the impacts of meteorology and spatial variations on trends in selected scenarios.
For example, they tested a hypothesis that there might be an additional environmental sink removing more mercury from the atmosphere than previously thought. The models would indicate the feasibility of such an unknown sink.
"By systematically examining each hypothesis, we were quite surprised to actually identify the reduction in anthropogenic emissions as the most likely cause," explains Selin.
Their work underscores the importance of long-term mercury monitoring stations, adds Feinberg. Many stations evaluated by the researchers are no longer operational due to a lack of funding.
Although their analysis couldn’t determine exactly why emission inventories don’t match real data, they have some hypotheses.
One possibility is that global inventories lack key information about certain countries. For example, the researchers resolved some discrepancies using a more detailed regional inventory of China. But there remains a gap between observations and estimates.
They also suspect that this gap could result from changes in two major sources of mercury that are particularly uncertain: emissions from small-scale gold mining and mercury-containing products.
Small-scale gold mining involves using mercury to extract gold from the ground and is often carried out in remote regions of developing countries, making it difficult to estimate. Yet, small-scale gold mining contributes to about 40% of human-induced emissions.
Additionally, it’s challenging to determine how long it takes for the pollutant to be released into the atmosphere from discarded products like thermometers or scientific equipment.
"We haven’t yet determined which source is truly responsible for this gap," says Feinberg.
In the future, researchers from several countries, including MIT, will collaborate to study and improve the models they use to estimate and assess emissions. This research will help advance mercury monitoring, he says.
This research was funded by the Swiss National Fund, the U.S. National Science Foundation, and the U.S. Environmental Protection Agency.
