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New study to help accurate estimation of black carbon over Himalayas

Scientists have made extensive observations of black carbon and elemental carbon

1-himalayas

Scientists have made extensive observations of black carbon and elemental carbon and estimated monthly and wavelength-dependent values of mass absorption cross-section (MAC) over the central Himalayan region for the first time.

An accurate estimation of black carbon (BC), the second-most important global warming pollutant after carbon dioxide, will now be possible using optical instruments in the Himalayan region, thanks to a parameter called MAC specific to the region that scientists have estimated.

It will also improve the performance of numerical weather prediction and climate models.

"Scientists at the Aryabhatta Research Institute of Observational Sciences (ARIES), an autonomous institute under the Department of Science & Technology (DST), in collaboration with scientists from the University of Delhi, IIT Kanpur and Space Physics Laboratory, ISRO, have made extensive observations of black carbon and elemental carbon and estimated monthly and wavelength-dependent values of MAC over the central Himalayan region for the first time," the DST said in a statement.

The researchers have derived the values of MAC, an essential parameter which is used for obtaining black carbon mass concentrations.

In a study published in the 'Asia-Pacific Journal of Atmospheric Sciences', Priyanka Srivastava and her PhD supervisor Manish Naja have calculated the annual mean value of MAC and found it to be significantly lower than the constant value used earlier.

These lower values are a result of transport of processed (not fresh) air pollution emissions at this otherwise clean site.

It is found that these changes are caused by the seasonal variability of biomass burning, air mass variation, and meteorological parameters.

According to the ARIES team, these higher resolution multi-wavelength and long-term observations used in calculating MAC will help improve the performance of numerical weather prediction and climate models in estimating the warming effects caused by BC emissions.

The precise knowledge on BC at various wavelengths will help in source apportionment studies done to constrain the sources of BC emissions. This can thus serve as important information to form the mitigation policies, it added.