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2022 ◽  
Author(s):  
Hitoshi Matsui ◽  
Tatsuhiro Mori ◽  
Sho Ohata ◽  
Nobuhiro Moteki ◽  
Naga Oshima ◽  
...  

Abstract. Black carbon (BC) particles in the Arctic contribute to rapid warming of the Arctic by heating the atmosphere and snow and ice surfaces. Understanding the source contributions to Arctic BC is therefore important, but they are not well understood, especially those for atmospheric and snow radiative effects. Here we estimate simultaneously the source contributions of Arctic BC to near-surface and vertically integrated atmospheric BC mass concentrations (MBC_SRF and MBC_COL), BC deposition flux (MBC_DEP), and BC radiative effects at the top of the atmosphere and snow surface (REBC_TOA and REBC_SNOW), and show that the source contributions to these five variables are highly different. In our estimates, Siberia makes the largest contribution to MBC_SRF, MBC_DEP, and REBC_SNOW in the Arctic (defined as > 70° N), accounting for 70 %, 53 %, and 43 %, respectively. In contrast, Asia’s contributions to MBC_COL and REBC_TOA are largest, accounting for 38 % and 45 %, respectively. In addition, the contributions of biomass burning sources are larger (24−34 %) to MBC_DEP, REBC_TOA, and REBC_SNOW, which are highest from late spring to summer, and smaller (4.2−14 %) to MBC_SRF and MBC_COL, whose concentrations are highest from winter to spring. These differences in source contributions to these five variables are due to seasonal variations in BC emission, transport, and removal processes and solar radiation, as well as to differences in radiative effect efficiency (radiative effect per unit BC mass) among sources. Radiative effect efficiency varies by a factor of up to 4 among sources (1465−5439 W g–1) depending on lifetimes, mixing states, and heights of BC and seasonal variations of emissions and solar radiation. As a result, source contributions to radiative effects and mass concentrations (i.e., REBC_TOA and MBC_COL, respectively) are substantially different. The results of this study demonstrate the importance of considering differences in the source contributions of Arctic BC among mass concentrations, deposition, and atmospheric and snow radiative effects for accurate understanding of Arctic BC and its climate impacts.


Geosphere ◽  
2021 ◽  
Author(s):  
Tanya Furman ◽  
Barry B. Hanan ◽  
Megan Pickard Sjoblom ◽  
Biltan Kürkcüoğlu ◽  
Kaan Sayit ◽  
...  

We present new Sr-Nd-Pb-Hf isotopic data on mafic lavas from the Sivas, Develidağ, Erciyes, and Erkilet volcanic complexes in central Turkey and Tendürek in eastern Turkey to evaluate the mantle sources for volcanism in the context of the geodynamic evolution of the Anatolian microplate. Early Miocene through Quaternary volcanism in Western Anatolia and latest Miocene through Quaternary activity in Central Anatolia were dominated by contributions from two distinct source regions: heterogeneous metasomatized or subduction-modified lithosphere, and roughly homogeneous sublithospheric ambient upper mantle; we model the source contributions through mixing between three end members. The sublithospheric mantle source plots close to the Northern Hemisphere reference line (NHRL) with radiogenic 206Pb/204Pb of ~19.15, while the other contributions plot substantially above the NHRL in Pb isotope space. The lithospheric source is heterogeneous, resulting from variable pollution by subduction-related processes likely including direct incorporation of sediment and/or mélange; its range in radiogenic isotopes is defined by regional oceanic sediment and ultrapotassic melts of the subcontinental lithospheric mantle. The geochemical impact of this contribution is disproportionately large, given that subduction-modified lithosphere and/or ocean sediment dominates the Pb isotope signatures of mafic Anatolian lavas. Subduction of the Aegean or Tethyan seafloor, associated with marked crustal shortening, took place throughout the region until ca. 16–17 Ma, after which time broad delamination of the thickened lower crust and/or the Tethyan slab beneath Central Anatolia allowed for sediment and/or mélange and slab-derived fluids to be released into the overlying evolving modified mantle. Aggregation of melts derived from both mantle and lithospheric domains was made possible by upwelling of warm asthenospheric material moving around and through the complexly torn younger Aegean-Cyprean slab that dips steeply to the north beneath southern Anatolia.


2021 ◽  
Vol 921 (1) ◽  
pp. 45
Author(s):  
I. Bartos ◽  
D. Veske ◽  
M. Kowalski ◽  
Z. Márka ◽  
S. Márka

Geoderma ◽  
2021 ◽  
Vol 398 ◽  
pp. 115112
Author(s):  
Hong Chen ◽  
Gang Liu ◽  
Xunchang Zhang ◽  
Hongqiang Shi ◽  
Hairu Li

2021 ◽  
Vol 14 (8) ◽  
pp. 5809-5821
Author(s):  
Blake Actkinson ◽  
Katherine Ensor ◽  
Robert J. Griffin

Abstract. Mobile monitoring is becoming increasingly popular for characterizing air pollution on fine spatial scales. In identifying local source contributions to measured pollutant concentrations, the detection and quantification of background are key steps in many mobile monitoring studies, but the methodology to do so requires further development to improve replicability. Here we discuss a new method for quantifying and removing background in mobile monitoring studies, State-Informed Background Removal (SIBaR). The method employs hidden Markov models (HMMs), a popular modeling technique that detects regime changes in time series. We discuss the development of SIBaR and assess its performance on an external dataset. We find 83 % agreement between the predictions made by SIBaR and the predetermined allocation of background and non-background data points. We then assess its application to a dataset collected in Houston by mapping the fraction of points designated as background and comparing source contributions to those derived using other published background detection and removal techniques. The presented results suggest that the SIBaR-modeled source contributions contain source influences left undetected by other techniques, but that they are prone to unrealistic source contribution estimates when they extrapolate. Results suggest that SIBaR could serve as a framework for improved background quantification and removal in future mobile monitoring studies while ensuring that cases of extrapolation are appropriately addressed.


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