Abstract
Smog is one of the most important environmental problems in China. Scientists have attempted to explain the causes from chemistry, physics, atmosphere and other perspectives. Many meteorologists believe that meteorology is a crucial reason. In this paper we present a new multi-view approach to visual analytics of the recent smog problems in China. This approach integrates four interrelated visualizations, each specialized in a different analysis task. To reveal the relationship between smog and meteorological attributes, we design a Correlation Detection View that simultaneously visualizes the air quality change patterns across multiple cities and related meteorological attributes. Component Trend View is used to show the variation patterns of six air components, while Aggregation View can reveal the regional overall pollution situations. A case study has been conducted using the China Air Quality Observation Data and European Centre for Medium-Range Weather Forecasts re-analysis data to verify the effectiveness of the proposed approach. By visually analyzing the meteorological data of Beijing and other major cities, we have found several interesting patterns, which prove the validity of our work in identifying sources of smog.
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