Climate predictions require increasingly accurate information on atmospheric particles

Although knowledge of the mechanisms and dynamics of atmospheric nanoparticle growth has increased dramatically in the 21st century, comprehensive models predicting climate change do not yet take into account with sufficient accuracy the effect of nanoparticles on cloud formation and, consequently, on the radiative balance of the soil.

This is evident from a review published in the Reviews of Modern Physics magazine, in which researchers from the University of Helsinki, TU Wien, Stockholm University and the Finnish Meteorological Institute collected research on atmospheric nanoparticles, or aerosol particles, conducted over the past twenty years.

In particular, the researchers investigated how the formation and growth of aerosol particles less than 25 nanometers in size are linked to predicting cloud droplet formation and how aerosol data can be used increasingly more effectively in climate predictions.

Particles influence the reflection of clouds

Aerosol particles affect the climate in two ways: first, by directly affecting how much sunlight reaches the Earth’s surface, and second, through the formation of clouds.

Clouds consist of small droplets, which are formed by the condensation of water on the surface of aerosol particles in the air. Without aerosol particles, cloud droplets would not form without an ultrahigh saturation ratio.

The quantity and composition of the aerosol particles determine the properties of the cloud cover, including the amount of sunlight reflected back into space by the clouds. If the amount of water in the air is constant, large amounts of aerosol particles result in a smaller cloud droplet size but a larger total droplet area. This also results in brighter clouds that spread light more effectively.

Sulfur dioxide, ammonia, certain oxygen-rich hydrocarbons and other emissions caused by human activities also generate new particles in the atmosphere. The formation of these particles increases atmospheric particle concentrations above levels typical of any human activity. These particles also grow large enough to influence cloud formation and ultimately climate.

The growth of aerosol particles is a sensitive process influenced by meteorological conditions, the gases, vapors and particles in the air. Usually the formation and growth of new particles in the atmosphere is observed on clear, sunny days. Related to this, certain types of vapor molecules form clusters on which other vapors can condense, creating particles large enough to contribute to cloud formation.

In the review article, the researchers’ goal was to bridge the gap between experimental research and modeling, minimize uncertainty related to particle growth, and provide tools for better climate modeling.

An example of uncertainty associated with particle growth is the precise experimental determination of their growth rate at various measurement locations around the world. This especially applies to particles smaller than 5 nanometers. Moreover, uncertainty is caused by the more detailed physical and chemical description of particle growth in global climate models.

“The latest experimental results provide much better insight into the formation and growth of different particles, but they cannot be applied as effectively as possible in climate models, because their precise modeling requires too much computing power. Incorporating these experimental findings into models can better predict how human activity affects air quality and climate. Once the models become more accurate, they will better predict the interconnected effects of various human perturbations on the climate system,” says postdoctoral researcher Runlong Cai from the Institute for Atmospheric and Earth System Research INAR at the University of Helsinki.

“Next, it will be crucial to determine the role of the different vapors involved in particle growth, and to model these vapors and growth mechanisms more accurately in climate models,” says university researcher Juha Kangasluoma from INAR.