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This study investigated the spatiotemporal variabilities in nitrogen dioxide (NO2), formaldehyde (HCHO), ozone (O3), and light-absorbing aerosols within the Greater Tokyo Area, Japan, the most populous metropolitan area in the world. The analysis was based on total column, partial column, and in situ observations retrieved from multiple platforms and additional information obtained from reanalysis and box model simulations. This study mainly covers the 2013--2020 period, focusing on 2020, when air quality was influenced by the coronavirus disease 2019 (COVID-19) pandemic. In 2020 overall, NO2 concentrations were reduced by about 10% annually, with reductions exceeding 40% in some areas during the pandemic state of emergency. Light-absorbing aerosol levels were also reduced for most of 2020, while smaller fluctuations in HCHO and O3 were observed. Moreover, the degree of weekly cycling of NO2, HCHO, and light-absorbing aerosol levels was significantly enhanced in urban areas during 2020. The latter changes were unprecedented in recent years and potentially related to coincident reduced mobility in Japan, which, in contrast to other countries, was anomalously low on weekends in 2020. This finding suggests that, despite the lack of strict legal restrictions in Japan, widespread adherence to recommendations designed to limit the spread of the pandemic caused modification of common habits, resulting in unique air quality changes. [ABSTRACT FROM AUTHOR]

We developed a high-resolution surface flux inversion system based on the global Lagrangian-Eulerian coupled tracer transport model composed of National Institute for Environmental Studies Transport Model (NIES-TM) and FLEXible PARTicle dispersion model (FLEXPART). The inversion system is named NTFVAR (NIES-TM-FLEXPART-variational) as it applies variational optimisation to estimate surface fluxes. We tested the system by estimating optimized corrections to natural surface CO2 fluxes to achieve best fit to atmospheric CO2 data collected by the global in-situ network, as a necessary step towards capability of estimating anthropogenic CO2 emissions. We employ the Lagrangian particle dispersion model (LPDM) FLEXPART to calculate the surface flux footprints of CO2 observations at a 0.1° × 0.1° spatial resolution. The LPDM is coupled to a global atmospheric tracer transport model (NIES-TM). Our inversion technique uses an adjoint of the coupled transport model in an iterative optimization procedure. The flux error covariance operator is being implemented via implicit diffusion. Biweekly flux corrections to prior flux fields were estimated for the years 2010-2012 from in-situ CO2 data included in the Observation Package (ObsPack) dataset. High-resolution prior flux fields were prepared using Open-Data Inventory for Anthropogenic Carbon dioxide (ODIAC) for fossil fuel combustion, Global Fire Assimilation System (GFAS) for biomass burning, the Vegetation Integrative SImulator for Trace gases (VISIT) model for terrestrial biosphere exchange and Ocean Tracer Transport Model (OTTM) for oceanic exchange. The terrestrial biospheric flux field was constructed using a vegetation mosaic map and separate simulation of CO2 fluxes at daily time step by the VISIT model for each vegetation type. The prior flux uncertainty for terrestrial biosphere was scaled proportionally to the monthly mean Gross Primary Production (GPP) by the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD17 product. The inverse system calculates flux corrections to the prior fluxes in the form of a relatively smooth field multiplied by high-resolution patterns of the prior flux uncertainties for land and ocean, following the coastlines and vegetation productivity gradients. The resulting flux estimates improve fit to the observations at continuous observations sites, reproducing both the seasonal variation and short-term concentration variability, including high CO2 concentration events associated with anthropogenic emissions. The use of high-resolution atmospheric transport in global CO2 flux inversion has the advantage of better resolving the transport from the mix of the anthropogenic and biospheric sources in densely populated continental regions and shows potential for better separation between fluxes from terrestrial ecosystems and strong localised sources such as anthropogenic emissions and forest fires. Further improvements in the modelling system are needed as the posterior fit is better than that by the National Oceanic and Atmospheric Administration (NOAA) CarbonTracker only for a fraction of the monitoring sites, mostly at coastal and island locations experiencing mix of background and local flux signals. [ABSTRACT FROM AUTHOR]

A three-dimensional simulation of gravitational separation, defined as the process of atmospheric molecule separation under gravity according to their molar masses, is performed for the first time in the upper troposphere and lower stratosphere. We analyze distributions of two isotopes with a small difference in molecular mass (13C16O2 (Mi = 45) and 12C16O2 (Mi = 44)) simulated by the National Institute for Environmental Studies (NIES) chemical transport model with a parameterization of molecular diffusion. The NIES model employs global reanalysis and an isentropic vertical coordinate and uses optimized CO2 fluxes. This study includes a comparison with measurements recorded by cryogenic balloon-borne samplers in the lower stratosphere and two-dimensional model simulations. The benefits of the NIES TM simulations are discussed. We investigate the processes affecting gravitational separation by a detailed estimation of terms in the molecular diffusion equation. At the same time, we study the age of air derived from the tracer distributions. We find a strong relationship between age of air and gravitational separation for the main climatic zones. The advantages and limitations of using age of air and gravitational separation as indicators of the variability in the stratosphere circulation are discussed. [ABSTRACT FROM AUTHOR]