Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Acta Geophysica

1 2023

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: positive matrix factorization

Sortuj według:

Ogranicz wyniki do:

Chemical and morphological characterization of PM2.5 samples collected over an urban industrial region Raipur, Chhattisgarh

Khobragade Pallavi Pradeep, Ahirwar Ajay Vikram

Acta Geophysica

2023

Vol. 71, no. 6

3057--3076

Estimating the direct radiative forcing (DRF) by air particles is challenging because of uncertainty in the morphology (shape and size), mixing states, and chemical properties of fine particulates. To improve numerically estimated optical and radiative properties, a region-specific database of the aforementioned physico-chemical properties (at individual particle level) is required. PM2.5 samples were examined using scanning electron microscopy-energy-dispersive X-ray spectroscopy (SEM-EDS). SEM-EDS was utilized to investigate the differences in forms, morphology, and elemental composition of PM2.5 particles, as well as to relate them to a potential source as a cause of pollution and pollution emissions and transit from various polluted places. SEM micrographs identified a wide range of PM morphologies, including spherical, irregular, angular, cluster, flaky, rod-like, crystalline, and agglomerate structures, indicating natural and anthropogenic causes and creation. The sources of PM2.5 pollution episodes in Raipur were identified employing observed pollution levels and meteorological data, backward air mass trajectories, correlation, and PMF analysis. In addition, positive matrix factorization has been used to source-apportion the data and five significant source/pollution types including industrial emissions (37%), vehicular exhaust (13.8%), coal combustion (12.4%), ionic factor (11.3%), and crustal dust (25.5%) were detected. Using a backward trajectory analysis, the influence of air pollutant transmission on regional particle pollution was investigated. A significant connection between Fe-Mn, Mn-Ni, Ni-Al, and Cl- and NH4+ indicates that the contaminants share a similar source. It was revealed that unfavorable climatic circumstances, such as low wind speed, low humidity, low temperature, and surface layer inversions, increase the risk of large PM2.5 concentrations in the region.