JoVE Visualize What is visualize?
Stop Reading. Start Watching.
Advanced Search
Stop Reading. Start Watching.
Regular Search
Find video protocols related to scientific articles indexed in Pubmed.
Spatial distribution and source apportionment of atmospheric dust fall at Beijing during spring of 2008-2009.
Environ Sci Pollut Res Int
PUBLISHED: 05-22-2014
Show Abstract
Hide Abstract
Beijing is a megacity, where atmospheric dust fall amount is great, and its resultant air pollution is serious. So, analyzing the chemical elements in atmospheric dust fall and revealing its various sources can provide a scientific basis for taking effective measures to improve atmospheric environmental quality. In this paper, we investigated the spatial and temporal distribution of dust fall in Beijing, based on the dust samples collected in the spring of 2008 and 2009 at 18 observation sites laid out in Beijing and then analyzed the sources of atmospheric dust fall based on the test of samples, adopting enrichment factor and factor analysis methods. Our results found that the dust fall quantity in the observation periods was respectively 33.6230 t km(-2) and 28.7130 t km(-2); the dust fall quantity varied significantly in different months in the spring, but the variation trend was similar at the sites. There were two centers of large quantity in Beijing; one was in the southwest of downtown, and the other was in the northeast of downtown. The spatial distribution of dust fall generally showed a structural feature of three loops; the northwestern mountainous area was a small quantity belt; the plain area around the downtown was a large quantity belt, and the central downtown was a center of small quantity. Soil dust, construction dust, coal dust, and vehicle exhaust were the four major sources of dust fall in spring of Beijing, respectively, accounting for 38.50, 22.25, 14.06, and 20.82 % of the total dust fall quantity.
Related JoVE Video

What is Visualize?

JoVE Visualize is a tool created to match the last 5 years of PubMed publications to methods in JoVE's video library.

How does it work?

We use abstracts found on PubMed and match them to JoVE videos to create a list of 10 to 30 related methods videos.

Video X seems to be unrelated to Abstract Y...

In developing our video relationships, we compare around 5 million PubMed articles to our library of over 4,500 methods videos. In some cases the language used in the PubMed abstracts makes matching that content to a JoVE video difficult. In other cases, there happens not to be any content in our video library that is relevant to the topic of a given abstract. In these cases, our algorithms are trying their best to display videos with relevant content, which can sometimes result in matched videos with only a slight relation.