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Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling

[Image: see text] Black carbon (BC) aerosols perturb climate and impoverish air quality/human health—affecting ∼1.5 billion people in South Asia. However, the lack of source-diagnostic observations of BC is hindering the evaluation of uncertain bottom-up emission inventories (EIs) and thereby also m...

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Autores principales: Dasari, Sanjeev, Andersson, August, Stohl, Andreas, Evangeliou, Nikolaos, Bikkina, Srinivas, Holmstrand, Henry, Budhavant, Krishnakant, Salam, Abdus, Gustafsson, Örjan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2020
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586323/
https://www.ncbi.nlm.nih.gov/pubmed/32885963
http://dx.doi.org/10.1021/acs.est.0c02193
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author Dasari, Sanjeev
Andersson, August
Stohl, Andreas
Evangeliou, Nikolaos
Bikkina, Srinivas
Holmstrand, Henry
Budhavant, Krishnakant
Salam, Abdus
Gustafsson, Örjan
author_facet Dasari, Sanjeev
Andersson, August
Stohl, Andreas
Evangeliou, Nikolaos
Bikkina, Srinivas
Holmstrand, Henry
Budhavant, Krishnakant
Salam, Abdus
Gustafsson, Örjan
author_sort Dasari, Sanjeev
collection PubMed
description [Image: see text] Black carbon (BC) aerosols perturb climate and impoverish air quality/human health—affecting ∼1.5 billion people in South Asia. However, the lack of source-diagnostic observations of BC is hindering the evaluation of uncertain bottom-up emission inventories (EIs) and thereby also models/policies. Here, we present dual-isotope-based (Δ(14)C/δ(13)C) fingerprinting of wintertime BC at two receptor sites of the continental outflow. Our results show a remarkable similarity in contributions of biomass and fossil combustion, both from the site capturing the highly populated highly polluted Indo-Gangetic Plain footprint (IGP; Δ(14)C-f(biomass) = 50 ± 3%) and the second site in the N. Indian Ocean representing a wider South Asian footprint (52 ± 6%). Yet, both sites reflect distinct δ(13)C-fingerprints, indicating a distinguishable contribution of C(4)-biomass burning from peninsular India (PI). Tailored-model-predicted season-averaged BC concentrations (700 ± 440 ng m(–3)) match observations (740 ± 250 ng m(–3)), however, unveiling a systematically increasing model-observation bias (+19% to −53%) through winter. Inclusion of BC from open burning alone does not reconcile predictions (f(biomass) = 44 ± 8%) with observations. Direct source-segregated comparison reveals regional offsets in anthropogenic emission fluxes in EIs, overestimated fossil-BC in the IGP, and underestimated biomass-BC in PI, which contributes to the model-observation bias. This ground-truthing pinpoints uncertainties in BC emission sources, which benefit both climate/air-quality modeling and mitigation policies in South Asia.
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spelling pubmed-75863232020-10-27 Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling Dasari, Sanjeev Andersson, August Stohl, Andreas Evangeliou, Nikolaos Bikkina, Srinivas Holmstrand, Henry Budhavant, Krishnakant Salam, Abdus Gustafsson, Örjan Environ Sci Technol [Image: see text] Black carbon (BC) aerosols perturb climate and impoverish air quality/human health—affecting ∼1.5 billion people in South Asia. However, the lack of source-diagnostic observations of BC is hindering the evaluation of uncertain bottom-up emission inventories (EIs) and thereby also models/policies. Here, we present dual-isotope-based (Δ(14)C/δ(13)C) fingerprinting of wintertime BC at two receptor sites of the continental outflow. Our results show a remarkable similarity in contributions of biomass and fossil combustion, both from the site capturing the highly populated highly polluted Indo-Gangetic Plain footprint (IGP; Δ(14)C-f(biomass) = 50 ± 3%) and the second site in the N. Indian Ocean representing a wider South Asian footprint (52 ± 6%). Yet, both sites reflect distinct δ(13)C-fingerprints, indicating a distinguishable contribution of C(4)-biomass burning from peninsular India (PI). Tailored-model-predicted season-averaged BC concentrations (700 ± 440 ng m(–3)) match observations (740 ± 250 ng m(–3)), however, unveiling a systematically increasing model-observation bias (+19% to −53%) through winter. Inclusion of BC from open burning alone does not reconcile predictions (f(biomass) = 44 ± 8%) with observations. Direct source-segregated comparison reveals regional offsets in anthropogenic emission fluxes in EIs, overestimated fossil-BC in the IGP, and underestimated biomass-BC in PI, which contributes to the model-observation bias. This ground-truthing pinpoints uncertainties in BC emission sources, which benefit both climate/air-quality modeling and mitigation policies in South Asia. American Chemical Society 2020-09-04 2020-10-06 /pmc/articles/PMC7586323/ /pubmed/32885963 http://dx.doi.org/10.1021/acs.est.0c02193 Text en This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Dasari, Sanjeev
Andersson, August
Stohl, Andreas
Evangeliou, Nikolaos
Bikkina, Srinivas
Holmstrand, Henry
Budhavant, Krishnakant
Salam, Abdus
Gustafsson, Örjan
Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
title Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
title_full Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
title_fullStr Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
title_full_unstemmed Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
title_short Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
title_sort source quantification of south asian black carbon aerosols with isotopes and modeling
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7586323/
https://www.ncbi.nlm.nih.gov/pubmed/32885963
http://dx.doi.org/10.1021/acs.est.0c02193
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