SearcharxivSearch

arXiv · 1309.1836

Transboundary secondary organic aerosol in western Japan indicated by stable carbon isotope ratio of low volatile water-soluble organic carbon and signal at m/z 44 in organic aerosol mass spectra

Abstract

Field studies were conducted in the winter of 2010 at two rural sites and an urban site in western Japan, and filter samples of total suspended particulate matter were collected every 24-h and analyzed for concentration and stable carbon isotope ratio (delta13C) of low volatile water-soluble organic carbon (LV-WSOC). Concentration of major chemical species in fine aerosol (<1.0 micron) was also measured in real time by Aerodyne aerosol mass spectrometers. Oxidation state of organic aerosol was evaluated using the proportion of signal at m/z 44 (fragment ions of carboxyl group) to the sum of all m/z signals of organic mass spectra (f44). Analyses show a high correlation between LV-WSOC and m/z 44 concentrations, suggesting that the LV-WSOC is likely associated with water soluble carboxylic acids in the fine aerosol. Plots of delta13C of LV-WSOC versus f44 exhibit systematic trends at the rural sites and random variation at the urban site. The systematic trends qualitatively agree with a simple binary mixture model of secondary organic aerosol and background LV-WSOC that has delta13C of -17 permil or higher and f44 of approximately 0.06, respectively. Comparison with references suggests that the source of background LV-WSOC is likely biomass burning of C4 plants.

Explore related subjects

Keep this discovery

BibTeXRIS

Satoshi Irei, Akinori Takami, Masahiko Hayashi, Yasuhiro Sadanaga, Keiichiro Hara, Naoki Kaneyasu, Kei Sato, Takemitsu Arakaki, Shiro Hatakeyama, Hiroshi Bandow, Toshihide Hikida, Akio Shimono. 2014-05-20. Transboundary secondary organic aerosol in western Japan indicated by stable carbon isotope ratio of low volatile water-soluble organic carbon and signal at m/z 44 in organic aerosol mass spectra. https://doi.org/10.1021/es405362y

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related papers

Windowed Envelope Statistics for Time-Domain Significant Wave Height Estimation From HF Radar

Significant wave height (SWH) retrieval from high-frequency (HF) radar typically relies on a weak second-order Doppler continuum that is sensitive to noise, interference, and spectral leakage. This letter presents a Windowed Envelope Statistics Estimator (WESE) that operates directly on beam-formed time-domain voltages. A second-order term obtained from a Neumann expansion of the rough-surface field equation motivates quadratic compensation of localized radar features. WESE extracts the mean, standard deviation, or variance from overlapping windows of the in-phase, quadrature, or envelope-magnitude sequence, followed by quadratic compensation, rank ordering, least-squares regression, and causal smoothing. Evaluation used 335 synchronized hourly observations from a 13.385 MHz, 12-element WERA system at Argentia, Newfoundland and Labrador. The optimal configuration used quadrature variance, a 16-sample window, 896 retained chronological samples, and 30-h smoothing, achieving an RMSE of 0.152 m and a Pearson correlation of 0.978. This represents RMSE reductions of 32.1% and 18.7% relative to previously reported linear and second-order compensated ordered-statistics models, respectively. The results demonstrate robust time-domain SWH estimation without explicit Doppler-spectrum construction.

physics.ao-ph

KiloDA: Reconstructing kilometer-scale near-surface wind states from sparse station observations

Accurate kilometer-scale near-surface winds are important for understanding atmospheric processes over complex terrain, yet remain difficult to reconstruct from sparse and unevenly distributed observations. Here we introduce KiloDA, a diffusion framework for hourly kilometer-scale wind reconstruction from surface stations. KiloDA learns the statistical distribution and spatial structure of wind fields from historical 3-km Weather Research and Forecasting (WRF) model forecasts. At each reconstruction time, no contemporaneous WRF field is used. Instead, station observations provide the only constraints on the current atmospheric state and guide posterior sampling from the learned prior. In idealized WRF experiments, KiloDA recovers localized wind structures when only 0.24% of grid cells are observed and shows an overall advantage over conventional interpolation across terrain conditions and wind speed regimes. This capability largely transfers to real observations. In a fully withheld region, KiloDA reduces the median wind speed root mean square error (RMSE) by 19% relative to ERA5 reanalysis, using only observations outside the region, with the largest improvements over high-elevation and high-relief terrain. A random station holdout further confirms that this advantage extends across different complex-terrain locations and holdout configurations. These results show that historical model archives can provide useful structural knowledge for reconstructing kilometer-scale wind fields from sparse observations without requiring an accurate model estimate of the current atmospheric state.

physics.ao-ph