Characteristics of seasonal variation of ambient nanoparticles in Kanazawa

Dr. Linfa Bao(Japan*, Mitsuhiko Hata, Masami Furuuchi, Kanazawa University)

*Project officer /Postdoctoral fellow,

Environment / Eco-technical Special Course,

College of Science and Engineering, Kanazawa University

Atmospheric nanoparticles, defined as particles with spherical equivalent diameters smaller than 100 nm, are either directly emitted from combustion sources, or are formed in the atmosphere by a process called nucleation. They then quickly grow by the condensation of gas monomers or clusters, or by coagulation with other particles, to become a critical participant in a number of important atmospheric processes such as heterogeneous chemistry, cloud formation, precipitation, and the scatter and absorption of solar radiation (1). An understanding of nanoparticles has increased dramatically in recent years because of significant advances in instrumentation to detect, size, and determine their chemical composition.

Two developed samplers based on the inertial filter technology were carried in the field measurements of ambient particles, compared with currently available samplers such as a LPI, a low volume air sampler with PM2.5 (LV) as well as a high volume air sampler with TSP (HV). This study focuses on mass concentration, size distribution and chemical components such as ionic compositions in sized particles to understand the seasonal variation of ambient nanoparticles in Kanazawa as well as its sources.

Mass concentration and fraction of nanoparticles in airborne particulates were found to have seasonal variations with peaks in May during the yellow dust season. Results is included: (1) evaluation of chemicals in nanoparticles such as OC, EC, WSOC and PAHs, (2) discussion on differences between Nanosampler, ANIF and LPI focusing on influence of pressure drop on measured particle mass and chemicals, (3) discussion on possible sources and formation mechanisms of nanoparticles (including the influence of yellow dust).

Title

Jianghong Shi

Beijing Normal University

State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University

Abstract