Measurements Of Atmospheric Concentrations Research Articles

Potential of 14C-based vs. ΔCO-based ΔffCO2 observations to estimate urban fossil fuel CO2 (ffCO2) emissions

Abstract. Atmospheric transport inversions are a powerful tool for independently estimating surface CO2 fluxes from atmospheric CO2 concentration measurements. However, additional tracers are needed to separate the fossil fuel CO2 (ffCO2) emissions from non-fossil CO2 fluxes. In this study, we focus on radiocarbon (14C), the most direct tracer of ffCO2, and the continuously measured surrogate tracer carbon monoxide (CO), which is co-emitted with ffCO2 during incomplete combustion. In the companion paper by Maier et al. (2024), we determined discrete 14C-based and continuous ΔCO-based estimates of the ffCO2 excess concentration (ΔffCO2) compared with a clean-air reference for the urban Heidelberg observation site in southwestern Germany. The ΔCO-based ΔffCO2 concentration was calculated by dividing the continuously measured ΔCO excess concentration by an average 14C-basedΔCO/ΔffCO2 ratio. Here, we use the CarboScope inversion framework adapted for the urban domain around Heidelberg to assess the potential of both types of ΔffCO2 observations to investigate ffCO2 emissions and their seasonal cycle. We find that, although they are more precise, 14C-based ΔffCO2 observations from almost 100 afternoon flask samples collected in the 2 years of 2019 and 2020 are not well suited for estimating robust ffCO2 emissions in the main footprint of this urban area, which has a very heterogeneous distribution of sources including several point sources. The benefit of the continuous ΔCO-based ΔffCO2 estimates is that they can be averaged to reduce the impact of individual hours with an inadequate model performance. We show that the weekly averaged ΔCO-based ΔffCO2 observations allow for a robust reconstruction of the seasonal cycle of the area source ffCO2 emissions from temporally flat a priori emissions. In particular, the distinct COVID-19 signal – with a steep drop in emissions in spring 2020 – is clearly present in these data-driven a posteriori results. Moreover, our top-down results show a shift in the seasonality of the area source ffCO2 emissions around Heidelberg in 2019 compared with the bottom-up estimates from the Netherlands Organization for Applied Scientific Research (TNO). This highlights the huge potential of ΔCO-based ΔffCO2 to validate bottom-up ffCO2 emissions at urban stations if the ΔCO/ΔffCO2 ratios can be determined without biases.

Stochastic assessment of temperature-CO2 causal relationship in climate from the Phanerozoic through modern times.

As a result of recent research, a new stochastic methodology of assessing causality was developed. Its application to instrumental measurements of temperature (T) and atmospheric carbon dioxide concentration ([CO2]) over the last seven decades provided evidence for a unidirectional, potentially causal link between T as the cause and [CO2] as the effect. Here, I refine and extend this methodology and apply it to both paleoclimatic proxy data and instrumental data of T and [CO2]. Several proxy series, extending over the Phanerozoic or parts of it, gradually improving in accuracy and temporal resolution up to the modern period of accurate records, are compiled, paired, and analyzed. The extensive analyses made converge to the single inference that change in temperature leads, and that in carbon dioxide concentration lags. This conclusion is valid for both proxy and instrumental data in all time scales and time spans. The time scales examined begin from annual and decadal for the modern period (instrumental data) and the last two millennia (proxy data), and reach one million years for the most sparse time series for the Phanerozoic. The type of causality appears to be unidirectional, T→[CO2], as in earlier studies. The time lags found depend on the time span and time scale and are of the same order of magnitude as the latter. These results contradict the conventional wisdom, according to which the temperature rise is caused by [CO2] increase.

Characterizing the Atmospheric Mn Cycle and Its Impact on Terrestrial Biogeochemistry

AbstractThe role of manganese (Mn) in ecosystem carbon (C) biogeochemical cycling is gaining increasing attention. While soil Mn is mainly derived from bedrock, atmospheric deposition could be a major source of Mn to surface soils, with implications for soil C cycling. However, quantification of the atmospheric Mn cycle, which comprises emissions from natural (desert dust, sea salts, volcanoes, primary biogenic particles, and wildfires) and anthropogenic sources (e.g., industrialization and land‐use change due to agriculture), transport, and deposition, remains uncertain. Here, we use compiled emission data sets for each identified source to model and quantify the atmospheric Mn cycle by combining an atmospheric model and in situ atmospheric concentration measurements. We estimated global emissions of atmospheric Mn in aerosols (<10 μm in aerodynamic diameter) to be 1,400 Gg Mn year−1. Approximately 31% of the emissions come from anthropogenic sources. Deposition of the anthropogenic Mn shortened Mn “pseudo” turnover times in 1‐m‐thick surface soils (ranging from 1,000 to over 10,000,000 years) by 1–2 orders of magnitude in industrialized regions. Such anthropogenic Mn inputs boosted the Mn‐to‐N ratio of the atmospheric deposition in non‐desert dominated regions (between 5 × 10−5 and 0.02) across industrialized areas, but that was still lower than soil Mn‐to‐N ratio by 1–3 orders of magnitude. Correlation analysis revealed a negative relationship between Mn deposition and topsoil C density across temperate and (sub)tropical forests, consisting with atmospheric Mn deposition enhancing carbon respiration as seen in in situ biogeochemical studies.

Measuring The Spatio-Temporal Distribution of Sulfur Dioxide (SO2) with Copernicus Sentinel-5P Near Real Time in Medan City

This study aims to monitor the impact of sulfur dioxide (SO2), a significant contributor to atmospheric corrosion and associated with air pollution, in urban and industrial areas through empirical models of spatial distribution and temporal estimation in Medan. Datasets of Sentinel 5P NRTI are worth using to monitor the formation of sulfate aerosols or SO2 emissions from natural sources and anthropogenic origin in near real-time from 2019 until 2023 on the local scale, Medan. The source dataset covers 1,11 km of spatial image resolution on orbital in daily revisit time with a spectral bound between the ultraviolet and the shortwave infrared. The measurement of atmospheric SO2 concentrations is generated by enumerating the SO2 vertical column density technique at the soil surface with the cloud-based platform The Earth Engine (EE) Code Editor to handle large data sizes and produce interactive mapping. Based on the availability of auxiliary results, the number of spreading SO2 concentrations fell from 0,92 mmol/m2 in 2019 to 0,41 mmol/m2 in 2023, a reduction of 49.98 percent. The average of SO2 concentrations has decreased substantially over the years. Consequently, these pollutants have recorded long-term health and meteorological parameters impact that substances can rise or reduce acid rain.Keywords: Air pollution, Meteorological parameters, Sentinel 5P NRTI, SO2

Large‐Scale Summertime Variability of Carbonate Chemistry Across the East Siberian Sea: Primary Production Versus Ikaite Dissolution

AbstractSea‐ice dynamics can affect carbon cycling in polar oceans, with sea‐ice ikaite acting as a potentially important carbon pump. However, there is no large‐scale direct field evidence to support this. Here we used a unique data set that combined continuous measurements of atmospheric and water CO2 concentrations with water chemistry data collected over 1,200 km along the East Siberian Sea, the widest Arctic shelf sea. Our results reveal large spatial heterogeneity of sea‐ice ikaite contents, which directly interact with carbonate chemistry in the water column. Our findings demonstrate that the CO2 drawdown by sea‐ice ikaite dissolution could be as important as that by primary production. We suggest that the role of ikaite in regulating the seasonal carbon cycle on a regional scale could be more important than we previously thought. Effects of the warmer climate on sea ice loss might also play a role in the ikaite inventory.

Evaluation of the GRAMM/GRAL model for high-resolution wind fields in Heidelberg, Germany

Independent verification of mitigation efforts for climate and air quality action in cities relies on inferring emissions from atmospheric concentration measurements. As emissions are dispersed in the atmosphere before they reach an instrument, the quantitative estimation of emissions requires an understanding of the atmospheric transport and associated uncertainties. In this study, we analyse the catalogue of steady-state flow fields generated by the Graz Mesoscale Model (GRAMM) coupled to the Graz Lagrangian Model (GRAL) for an entire year in Heidelberg, Germany. We use a loss function for the wind field selection, which assigns a best-matching catalogue entry to any given hour by exploiting observation data. We introduce a new loss function which finds an optimal balance between differences in wind speed and wind direction. We evaluate the performance of the model based on 15 meteorological measurement sites, of which 14 are in the inner high-resolution and building-resolving GRAL domain (12.5 km × 12.5 km, 10 m resolution). Performance metrics include mean bias (MB) and root mean square errors (RMSEs) of simulated and observed wind speed and wind direction for all individual stations. On average, we find a mean underestimation of wind speed of 0.14 ms−1 corresponding to about 7 % of the mean wind speed and a mean RMSE of 1.03 ms−1. For wind direction, a mean overall bias smaller than 1° is achieved, but individual stations show larger biases (mean absolute bias: 37°), especially at stations where wind speeds are low on average. Evaluation benchmarks for mean biases of wind direction and wind speed of mesoscale models provided by the European Environmental Agency (EEA) are met at 11 and 14 out of 15 stations at low measurement heights, respectively. Recently suggested extended benchmarks for complex terrain are met at almost all stations. Additionally, for the first time, we analyse the model's ability to simulate the vertical wind profile and we analyse the benefit of implementing a wind profile measurement into the process. We find that the model does not fully capture the vertical profile in our setting. We further study the required measurement network size and find that a high number (> 6) of meteorological stations improves the selection of flow fields over the entire GRAL domain substantially. The conducted comprehensive analysis of the wind fields in the GRAL domain are the basis for detailed quantitative analysis of greenhouse gas and air pollutant emissions using the GRAMM/GRAL modelling framework.

NO2 Concentration Estimation at Urban Ground Level by Integrating Sentinel 5P Data and ERA5 Using Machine Learning: The Milan (Italy) Case Study

The measurement of atmospheric NO2 pollution concentrations has become a critical topic due to its impact on human health. Ground sensors are the most popular method for measuring atmospheric pollution, but they can be expensive to purchase, install, and maintain. In contrast, satellite technology offers global coverage but typically provides concentration estimates at the tropospheric level, not at the ground level where most human activities take place. This work presents a model that can be used to estimate NO2 ground-level concentrations in metropolitan areas using Sentinel-5P satellite images and ERA5 meteorological data. The primary goal is to offer a cost-effective solution for Low- and Medium-Income Countries (LMICs) to assess air quality, thereby addressing the air quality measurement constraints. To validate the model’s accuracy, study points were selected in alignment with the Regional Agency for the Environment Protection (ARPA) NO2 sensor network in the Metropolitan City of Milan. The results showed that the RMSE of the model estimations was significantly lower than the standard deviation of the real measurements. This work fills the gaps in the literature by providing an accurate estimation model of NO2 in the Metropolitan City of Milan using both satellite data and ERA5 meteorological data. This work presents as an alternative to ground sensors by enabling more regions to assess their air quality effectively.

Assessing the variability of tissue-free water tritium and non-exchangeable organically bound tritium in pine needles in Fukushima using atmospheric titrated water vapor

When conducting environmental tritium monitoring at nuclear and fusion facilities, it is important to understand how tritium concentrations vary within the soil-plant-atmosphere continuum. Past measurements of organically bound tritium (OBT) concentrations have been conducted from the standpoint of ascertaining the persistence of tritium in terrestrial vegetation, and it has been reported that OBT concentrations fluctuate depending on the influence of atmospheric sources and meteorological conditions. The present study provides information on the variability of tritium concentrations in vegetation growing close to atmospheric sources of tritiated water (HTO) in Japan. We conducted measurements of tissue-free water tritium (TFWT) and non-exchangeable OBT (NE-OBT) in pine needles collected from locations near the Tokyo Electric Power Company's Fukushima Daiichi Nuclear Power Plant from 2018 to 2021. The results we obtained indicate that TFWT concentrations fluctuate in response to short-term changes in atmospheric HTO vapor concentrations and that NE-OBT concentrations vary primarily in response to the time-averaged TFWT concentration during the pine needle growing season, which is in turn mainly determined by atmospheric HTO vapor concentrations. Although it is difficult to ascertain the time-averaged TFWT concentration during the growing season by measuring plant materials, our results show that the measurement of atmospheric HTO vapor concentrations provides an effective alternative method of doing this. We believe our findings can lead to better understanding of the potential impact on the terrestrial environment associated with the atmospheric discharge of HTO and can contribute to improving the strategy of environmental tritium monitoring.

Novel Compact Polarized Martian Wind Imaging Interferometer

The Mars Atmospheric Wind Imaging Interferometer offers several advantages, notably its high throughput, enabling the acquisition of precise and high vertical resolution data on the temperature and wind fields in the Martian atmosphere. Considering the current absence of such an Interferometer, this paper introduces a novel Mars wind field imaging interferometer. In analyzing the photochemical model of O2 (a1Δg) 1.27 μm molecular airglow radiation in the Martian atmosphere and considering the impact of instrument signal-to-noise ratio (SNR), we have chosen an optical path difference (OPD) of 8.6 cm for the interferometer. The all-solid-state polarized wind imaging interferometer is miniaturized by incorporating two arm glasses as the compensation medium in its construction, achieving the effects of field-widening and temperature compensation. Additionally, an F-P Etalon is designed to selectively filter the desired three spectral lines of O2 dayglow, and its effect is evaluated through simulations. The accuracy of the proposed compact Mars polarized wind imaging interferometer for detecting Mars’ wind field and temperature field has been validated through rigorous theoretical derivation and comprehensive computer simulations. The interferometer boasts several advantages, including its compact and small size, static stability, minimal stray light, and absence of moving parts. It establishes the theoretical, technological, and instrumental engineering foundations for future simultaneous static measurement of Martian global atmospheric wind fields, temperature fields, and ozone concentrations from spacecraft, thereby significantly contributing to the dataset for investigating Martian atmospheric dynamics.

OH measurements in the coastal atmosphere of South China: possible missing OH sinks in aged air masses

Abstract. The hydroxyl radical (OH) is the main atmospheric oxidant responsible for the removal of many reduced trace gases and the formation of secondary air pollutants. However, due to technical difficulties in measuring OH, the existing measurements of atmospheric OH concentrations are limited, and its sources and sinks are not well understood under low-nitrogen-oxide (NOx) conditions. In this study, we observed the OH concentrations using chemical ionization mass spectrometry at a coastal site in Hong Kong from October to November 2020. The average noontime OH concentration over the study period was measured at 4.9±2.1×106 cm−3. We found that a box model with comprehensive observational constraints reproduced the observed daytime OH concentrations when air parcels originated from the continental regions. However, this model overpredicted the observed daytime OH concentrations for coastal air parcels by 142 % on average. Unaccounted-for OH sinks in the model are proposed to be the cause of this overprediction. A missing OH reactivity, which is defined as the pseudo-first-order rate coefficient for OH loss by unmeasured trace gases, was estimated as 5.0±2.6 s−1 (lower limit) in the coastal air, and the missing reactivity increased with decreasing concentrations of NOx and volatile organic compounds (VOCs). Further studies are needed to find out the exact cause of the model overestimation and to identify the suspected unmeasured chemical species that contribute to the OH budget, in order to better quantify the formation of secondary air pollutants.

Concurrent measurements of atmospheric ammonia concentrations in the megacities of Beijing and Shanghai by using cavity ring-down spectroscopy

Ammonia (NH3) is a vital precursor of secondary aerosols, which play an important role in urban air pollution. The passive observation of NH3 in the urban atmosphere showed higher concentrations than conventionally believed; however, the NH3 dynamics remain limited due to the paucity of active measurements with fast response instruments. In this study, intensive online measurements of ambient NH3 were conducted using cavity ring-down spectroscopy in late spring and early summer 2020 at the megacities of Beijing and Shanghai in northern and southern China. The results show that the average NH3 concentration in Beijing (23.1 ± 10.3 ppb) was nearly double that in Shanghai (12.0 ± 5.0 ppb). This spatial difference was confirmed by satellite column observations and bottom-up emission patterns. In addition, there was a significant increase in NH3 concentrations during the morning in our study. This special diurnal profile was a universal feature, with an occurrence frequency exceeding 50% in both cities. These frequent morning increases were mainly caused by motor vehicle emissions, with an additional contribution from the residual layer breakup for one-quarter of the days in the morning increase. On these days, the NH3 concentration increased by approximately 20% due to the downward mixing of the residual layer rupture. The unique data observed here could be used to validate the chemistry and transport models at a higher time resolution and improve the understanding of the current status of NH3 pollution in the urban atmosphere.

Mobile measurements of atmospheric pollutant concentrations in the pollutant plume of BER airport

Recent research has demonstrated that airports are important emission sources for ultrafine particles (UFP) which may largely contribute to regional UFP number concentrations. However, in areas where multiple particle sources are present, the differentiation and the quantification of the contribution of aircraft emissions to ambient UFP is challenging. We present the results from a car-based mobile measurement campaign in the vicinity of the recently opened Berlin-Brandenburg airport (BER) in Germany. Total particle number concentrations (TNC), CO2, particle mass (PM) and equivalent black carbon (eBC) concentrations were measured downwind from the airport. TNC roughly followed an exponential decline with increasing distance to the airport, which was more pronounced during the measurement campaign in the fall than in the subsequent summer. Cluster analysis showed that airport emissions are dominated by elevated TNC concentrations (median elevation by 59%), while particle emissions from vehicle traffic coincided with increased CO2 and eBC concentrations. The airport emission cluster could be found up to approx. 7000 m distance to the central terminal building of the airport during the fall campaign. The real-world emission factors derived from the measurements indicate that aircrafts emit roughly eight times the number of particles per kg fuel than vehicle traffic. Overall, our study presents the effects of airport-related emissions onto the regional air quality downwind from the airport. To get further insights into the contribution percentage of airports to ambient UFP, studies on aerosol dispersion and dynamics modelling are needed.

Advanced Pressure Compensation in High Accuracy NDIR Sensors for Environmental Studies

Measurements of atmospheric gas concentrations using of NDIR gas sensors requires compensation of ambient pressure variations to achieve reliable result. The extensively used general correction method is based on collecting data for varying pressures for a single reference concentration. This one-dimensional compensation approach is valid for measurements carried out in gas concentrations close to reference concentration but will introduce significant errors for concentrations further away from the calibration point. For applications, requiring high accuracy, collecting, and storing calibration data at several reference concentrations can reduce the error. However, this method will cause higher demands on memory capacity and computational power, which is problematic for cost sensitive applications. We present here an advanced, but practical, algorithm for compensation of environmental pressure variations for relatively low-cost/high resolution NDIR systems. The algorithm consists of a two-dimensional compensation procedure, which widens the valid pressure and concentrations range but with a minimal need to store calibration data, compared to the general one-dimensional compensation method based on a single reference concentration. The implementation of the presented two-dimensional algorithm was verified at two independent concentrations. The results show a reduction in the compensation error from 5.1% and 7.3%, for the one-dimensional method, to -0.02% and 0.83% for the two-dimensional algorithm. In addition, the presented two-dimensional algorithm only requires calibration in four reference gases and the storing of four sets of polynomial coefficients used for calculations.

Estimating Daily NO2 Ground Level Concentrations Using Sentinel-5P and Ground Sensor Meteorological Measurements

Environmental and health deterioration due to the increasing presence of air pollutants is a pressing topic for governments and organizations. Institutions such as the European Environment Agency have determined that more than 350,000 premature deaths can be attributed to atmospheric pollutants. The measurement of trace gas atmospheric concentrations is key for environmental agencies to fight against the decreased deterioration of air quality. NO2, which is one of the most harmful pollutants, has the potential to cause diseases such as Chronic Obstructive Pulmonary Disease (COPD). Unfortunately, not all countries have local atmospheric pollutant monitoring networks to perform ground measurements (especially Low- and Middle-Income Countries). Although some alternatives, such as satellite technologies, provide a good approximation for tropospheric NO2, these do not measure concentrations at the ground level. In this work, we aim to provide an alternative to ground sensor measurements. We used a combination of ground meteorological measurements with satellite Sentinel-5P observations to estimate ground NO2. For this task, we used state-of-the-art Machine Learning models, linear regression models, and feature selection algorithms. From the results obtained, we found that a Multi-layer Perceptron Regressor and Kriging in combination with a Random Forest feature selection algorithm achieved the lowest RMSE (2.89 µg/m3). This result, in comparison with the real data standard deviation and the models using only satellite data, represented an RMSE decrease of 55%. Future work will focus on replacing the use of meteorological ground sensors with only satellite-based data.

A twenty year record of greenhouse gases in the Eastern Mediterranean atmosphere

Twenty years of CO2, CH4 and CO greenhouse gas atmospheric concentration measurements at Finokalia station on Crete in the Eastern Mediterranean region are presented. This dataset is the longest in the Eastern Mediterranean, based on bi-weekly grab sampling since 2002 and continuous observations since June 2014. CO2 concentrations increase by 2.4 ppm·y−1 since 2002, in agreement with the general north hemisphere trend as derived by worldwide NOAA observations. CH4 showed a mean increasing trend of 7.5 ppb·y−1 since 2002, a rate that has accelerated since 2018 (12.4 ppb·y−1). In contrast, CO has decreased by 1.6 ppb·y−1 since 2002, which resulted from a strong decrease until 2017 (2.5 ppb·y−1), followed by a small increase in the last 3 years (0.2 ppb·y−1). Both CO2 and CH4 present maxima during winter and minima during summer, in general agreement with the observations at the ICOS stations in Europe. CO also presents the highest values in winter and the lowest values in summer during June, while a secondary maximum is seen in August, which can be attributed to open fires that often occur in the area during this period. The mean summertime diurnal cycles of CH4 and CO agree with a 24-h mean OH radical concentration of the order of 0.3–1 × 107 molecules·cm−3 over the region, in general agreement with the only existing in-situ observations at Finokalia for 2001.

Assessment of the nocturnal boundary layer height based on long-term atmospheric radon measurements

The article presents the results of statistical analyzes of meteorological and atmospheric radon concentration measurements carried out in Krakow in the years 2004–2013. Based on the diurnal variability, an estimation of the height of the nocturnal boundary layer was performed and compared with the ERA5 data. The average concentration of radon in the air of that period in Kraków was equal to (5.262 ± 0.017) Bqm−3. The diurnal and seasonal variability of radon concentration was found. The correlation of meteorological parameters calculated based on hourly mean data was analyzed. The correlations obtained were statistically significant, for wind speed (r= -0.38, p<0.001), and air humidity (r=0.33, p<0.001). The possibility of determining of the nocturnal boundary layer height on the basis of radon measurements has been confirmed; however, the calculation model needs to be refined.

The first simultaneous and continuous underway measurements of atmospheric gaseous elemental mercury, carbon dioxide and methane in the marine boundary layer: Results of cruise study in the Sea of Japan in May 2018

This paper presents the results of the first simultaneous measurements of gaseous elemental mercury (GEM) and greenhouse gases (CH4 and CO2) in the marine boundary layer over the Sea of Japan. Continuous underway measurements of atmospheric GEM, CH4 and CO2 concentrations were carried out aboard the R/V Akademik M.A. Lavrentiev from 4 to May 26, 2018. GEM concentrations (range: 0.4–1.6 ng/m3; mean ± standard deviation (SD): 1.0 ± 0.2 ng/m3; N = 938) were lower than both the atmospheric background and previously observed values in this area. Concentrations of CH4 (range: 1922.6–2010.6 ppb; mean ± SD: 1942.2 ± 10.8 ppb) and CO2 (range: 408.9–436.1 ppm; mean ± SD: 412.5 ± 2.5 ppm) were higher than both the average global atmospheric concentrations in May, and the average annual values. Concentration-weighted trajectory (CWT) analysis highlighted the Korean peninsula, northeastern China, southern Primorsky Krai (Russia) and the southwestern coast of Hokkaido (Japan) as potential source areas influencing atmospheric GEM, CH4 and CO2 concentrations during the cruise. Vertical distribution of the CWT values for all the measured gaseous species identified the lower atmosphere up to 1000 m as source layer. The same layer was also characterized by lower CWT values for CH4 and CO2, which were associated with atmospheric transport from the central part of the Sea of Japan. With increasing altitude, the CWT values for GEM and CH4 decreased, while the CO2 values began to rise from 2000 m reflecting the respiration of terrestrial ecosystems and, possibly, atmospheric transport from fires in western Russia.The study shows potential source regions influencing GEM, CH4 and CO2 concentrations in the atmosphere over the Sea of Japan in May 2018.

Measurements of Atmospheric Water Vapor by a 1.316 μm Optical Fiber Laser Heterodyne Radiometer

A passive optical fiber laser heterodyne radiometer prototype with a semiconductor laser near 1.316 μm as the local oscillator was built, parameters of the prototype have been optimized. Using the prototype, the water vapor concentration in the atmospheric column was measured with a spectral resolution of 0.009 cm−1 in late October and early November of 2020, the collection time was approximately 3 min, and the signal-to-noise ratio was better than 120. The water vapor column concentration and profiles were inversed based on the optimal estimation method. Compared with the measurement of the Fourier transform spectrometer (EM27/SUN) which was performed simultaneously, the inversion results deviated by less than 14%, and the variation trend of the water vapor concentration showed good consistency. It is demonstrated that the 1.316 μm optical fiber laser heterodyne radiometer possesses good stability and accuracy in the field measurement of atmospheric water vapor concentration.

Carbon Monoxide Emissions from the Washington, DC, and Baltimore Metropolitan Area: Recent Trend and COVID-19 Anomaly.

We analyze airborne measurements of atmospheric CO concentration from 70 flights conducted over six years (2015-2020) using an inverse model to quantify the CO emissions from the Washington, DC, and Baltimore metropolitan areas. We found that CO emissions have been declining in the area at a rate of ≈-4.5 % a-1 since 2015 or ≈-3.1 % a-1 since 2016. In addition, we found that CO emissions show a "Sunday" effect, with emissions being lower, on average, than for the rest of the week and that the seasonal cycle is no larger than 16 %. Our results also show that the trend derived from the NEI agrees well with the observed trend, but that NEI daytime-adjusted emissions are ≈50 % larger than our estimated emissions. In 2020, measurements collected during the shutdown in activity related to the COVID-19 pandemic indicate a significant drop in CO emissions of 16 % relative to the expected emissions trend from the previous years, or 23 % relative to the mean of 2016 to February 2020. Our results also indicate a larger reduction in April than in May. Last, we show that this reduction in CO emissions was driven mainly by a reduction in traffic.

The Variability of Air-sea O2 Flux in CMIP6: Implications for Estimating Terrestrial and Oceanic Carbon Sinks

The measurement of atmospheric O2 concentrations and related oxygen budget have been used to estimate terrestrial and oceanic carbon uptake. However, a discrepancy remains in assessments of O2 exchange between ocean and atmosphere (i.e. air-sea O2 flux), which is one of the major contributors to uncertainties in the O2-based estimations of the carbon uptake. Here, we explore the variability of air-sea O2 flux with the use of outputs from Coupled Model Intercomparison Project phase 6 (CMIP6). The simulated air-sea O2 flux exhibits an obvious warming-induced upward trend (∼1.49 Tmol yr−2) since the mid-1980s, accompanied by a strong decadal variability dominated by oceanic climate modes. We subsequently revise the O2-based carbon uptakes in response to this changing air-sea O2 flux. Our results show that, for the 1990–2000 period, the averaged net ocean and land sinks are 2.10±0.43 and 1.14±0.52 GtC yr−1 respectively, overall consistent with estimates derived by the Global Carbon Project (GCP). An enhanced carbon uptake is found in both land and ocean after year 2000, reflecting the modification of carbon cycle under human activities. Results derived from CMIP5 simulations also investigated in the study allow for comparisons from which we can see the vital importance of oxygen dataset on carbon uptake estimations.