Impacts of artificial cloud seeding on surface PM_2.5 and PM₁₀ scavenging in the Yangtze River Delta

Artificial cloud seeding, as a direct intervention to enhance precipitation and an indirect method to reduce the ground particulate matter (PM) concentrations, has gained increasing attention in recent years for its potential applications in improving air quality. Our analysis of PM observations in the north of Yangtze River Delta (Xuzhou and Suqian) during 2022-2023 showed that PM wet removal efficiency increases linearly with rainfall intensity above threshold values, while the scavenging efficiency of gaseous pollutants showed no precipitation-dependent. In an aircraft seeding experiment in Suqian during the 2023 Shanghai Expo, AgI-induced ice nucleation triggered deposition growth of ice crystals, releasing latent heat that strengthened local updrafts and promoted subsequent riming and melting. Post-seeding observations (3-hour period) observed precipitation rates of 0.1-0.3 mm/h with PM₁₀ and PM_2.5 reductions of 25 %-29 % and 10 %-16 %, respectively, despite low wind speed indicating seeding-influenced precipitation improved PM scavenging. Model simulations combined with observational scavenging rates showed the domain-wide impacts over an area of ∼9000 km² area and an enhanced rainfall of 90,000 tons. However, PM reductions were modest (<1 %) across the entire domain. Regions with strong updrafts (> 0.5 Pa/s) showed higher scavenging efficiencies with PM reductions of 1 % over 900 km², 4 %-5 % over 100 km², and > 10 % in localized areas (40 km²). These results highlight that targeted cloud seeding can improve the surface rainfall and PM wet deposition, with the effectiveness of the process driven by microphysical-dynamical feedbacks.