Primary Sulfate Is the Dominant Source of Particulate Sulfate during Winter in Fairbanks, Alaska.

Within and surrounding high-latitude cities, poor air quality disturbs Arctic ecosystems, influences the climate, and harms human health. The Fairbanks North Star Borough has wintertime particulate matter (PM) concentrations that exceed the Environmental Protection Agency's (EPA) threshold for public health. Particulate sulfate (SO4 2-) is the most abundant inorganic species and contributes approximately 20% of the total PM mass in Fairbanks, but air quality models underestimate observed sulfate concentrations. Here we quantify sulfate sources using size-resolved δ34S(SO4 2-), δ18O(SO4 2-), and Δ17O(SO4 2-) of particulate sulfate in Fairbanks from January 18th to February 25th, 2022 using a Bayesian isotope mixing model. Primary sulfate contributes 62 ± 12% of the total sulfate mass on average. Most primary sulfate is found in the size bin with a particle diameter < 0.7 µm, which contains 90 ±5% of total sulfate mass and poses the greatest risk to human health. Oxidation by all secondary formation pathways combined contributes 38 ± 12% of total sulfate mass on average, indicating that secondary sulfate formation is inefficient in this cold, dark environment. On average, the dominant secondary sulfate formation pathways are oxidation by H2O2 (13 ± 6%), O3 (8 ± 4%), and NO2 (8 ± 3%). These findings will inform mitigation strategies to improve air quality and public health in Fairbanks and possibly other high-latitude urban areas during winter.

Optimization of the Photon Path Length Probability Density Function-Simultaneous (PPDF-S) Method and Evaluation of CO2 Retrieval Performance Under Dense Aerosol Conditions.

The photon path length probability density function-simultaneous (PPDF-S) algorithm is effective for retrieving column-averaged concentrations of carbon dioxide (XCO2) and methane (XCH4) from Greenhouse gases Observing Satellite (GOSAT) spectra in Short Wavelength InfraRed (SWIR). Using this method, light-path modification attributable to light reflection/scattering by atmospheric clouds/aerosols is represented by the modification of atmospheric transmittance according to PPDF parameters. We optimized PPDF parameters for a more accurate XCO2 retrieval under aerosol dense conditions based on simulation studies for various aerosol types and surface albedos. We found a more appropriate value of PPDF parameters referring to the vertical profile of CO2 concentration as a measure of a stable solution. The results show that the constraint condition of a PPDF parameter that represents the light reflectance effect by aerosols is sufficiently weak to affect XCO2 adversely. By optimizing the constraint, it was possible to obtain a stable solution of XCO2. The new optimization was applied to retrieval analysis of the GOSAT data measured in Western Siberia. First, we assumed clear sky conditions and retrieved XCO2 from GOSAT data obtained near Yekaterinburg in the target area. The retrieved XCO2 was validated through a comparison with ground-based Fourier Transform Spectrometer (FTS) measurements made at the Yekaterinburg observation site. The validation results showed that the retrieval accuracy was reasonable. Next, we applied the optimized method to dense aerosol conditions when biomass burning was active. The results demonstrated that optimization enabled retrieval, even under smoky conditions, and that the total number of retrieved data increased by about 70%. Furthermore, the results of the simulation studies and the GOSAT data analysis suggest that atmospheric aerosol types that affected CO2 analysis are identifiable by the PPDF parameter value. We expect that we will be able to suggest a further improved algorithm after the atmospheric aerosol types are identified.

A global database of water vapor isotopes measured with high temporal resolution infrared laser spectroscopy.

The isotopic composition of water vapour provides integrated perspectives on the hydrological histories of air masses and has been widely used for tracing physical processes in hydrological and climatic studies. Over the last two decades, the infrared laser spectroscopy technique has been used to measure the isotopic composition of water vapour near the Earth's surface. Here, we have assembled a global database of high temporal resolution stable water vapour isotope ratios (δ18O and δD) observed using this measurement technique. As of March 2018, the database includes data collected at 35 sites in 15 Köppen climate zones from the years 2004 to 2017. The key variables in each dataset are hourly values of δ18O and δD in atmospheric water vapour. To support interpretation of the isotopologue data, synchronized time series of standard meteorological variables from in situ observations and ERA5 reanalyses are also provided. This database is intended to serve as a centralized platform allowing researchers to share their vapour isotope datasets, thus facilitating investigations that transcend disciplinary and geographic boundaries.