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Information on the origin of pollution constitutes an essential step of air quality management as it helps identifying measures to control air pollution. In this work, we review the most widely used source-apportionment methods for air quality management. Using theoretical and real-case datasets we study the differences among these methods and explain why they result in very different conclusions to support air quality planning. These differences are a consequence of the intrinsic assumptions that underpin the different methodologies and determine/limit their range of applicability. We show that ignoring their underlying assumptions is a risk for efficient/successful air quality management as these methods are sometimes used beyond their scope and range of applicability. The simplest approach based on increments (incremental approach) is often not suitable to support air quality planning. Contributions obtained through mass-transfer methods (receptor models or tagging approaches built in air quality models) are appropriate to support planning but only for specific pollutants. Impacts obtained via “brute-force” methods are the best suited but it is important to assess carefully their application range to make sure they reproduce correctly the prevailing chemical regimes.
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Source Quantification of South Asian Black Carbon Aerosols with Isotopes and Modeling
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 (Δ14C/δ13C) 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; Δ14C-fbiomass = 50 ± 3%) and the second site in the N. Indian Ocean representing a wider South Asian footprint (52 ± 6%). Yet, both sites reflect distinct δ13C-fingerprints, indicating a distinguishable contribution of C4-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 (fbiomass = 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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Source regions of some persistent organic pollutants measured in the atmosphere at Birkenes, Norway.
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Source-receptor and inverse modelling to quantify urban PARTiculate emissions (SRIMPART). TemaNord, 2009:552
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We combine observations from Western USA and inverse modelling to constrain global atmospheric emissions of microplastics (MPs) and microfibers (MFs). The latter are used further to model their global atmospheric dynamics. Global annual MP emissions were calculated as 9.6 ± 3.6 Tg and MF emissions as 6.5 ± 2.9 Tg. Global average monthly MP concentrations were 47 ng m-3 and 33 ng m-3 for MFs, at maximum. The largest deposition of agricultural MPs occurred close to the world’s largest agricultural regions. Road MPs mostly deposited in the East Coast of USA, Central Europe, and Southeastern Asia; MPs resuspended with mineral dust near Sahara and Middle East. Only 1.8% of the emitted mass of oceanic MPs was transferred to land, and 1.4% of land MPs to ocean; the rest were deposited in the same environment. Previous studies reported that 0.74–1.9 Tg y-1 of land-based atmospheric MPs/MFs (
2022