English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

The goal of the study is to investigate elemental concentrations and source signatures of particulate matter at a selected receptor site in an urban area Navi Mumbai which is one of the hot spots of India with heavy industrialization. To achieve the objective, particulate matter samples were collected from 2008-2010 using Gent sampler with the automatic dichotomous size segregation unit. It was observed that the three year average concentrations of coarse ((PM_(10-2.5μm)) and fine (PM_(2.5μm)) fractions of PM were 89.92 (μg m^(-3)) and 42.25 (μg m^(-3)) respectively which were higher than the national standards prescribed by Central Pollution Control Board (CPCB), India. Subsequent elemental analysis of air filters using INAA and EDXRF showed marginally higher levels of anthropogenic derived elements. Furthermore, in the present study potentially contributing sources of coarse and fine PM were identified using two different receptor model techniques Factor Analysis (FA) and Positive Matrix Factorization (PMF). Six possible contributing sources of coarse fraction and seven probable sources of fine PM were identified by both the techniques. Further, sources identified by the receptor techniques and the comparability between the two techniques were also evaluated.

Comparison of Two Receptor Model Techniques for the Size Fractionated Particulate Matter Source Apportionment