Spatial heterogeneity in global atmospheric CO during the COVID-19 lockdown: Implications for global and regional air quality policies

The COVID-19 lockdown (LD) provided a unique opportunity to examine the changes in regional and global air quality. Changes in the atmospheric carbon monoxide (CO) during LD warrant a thorough analysis as CO is a major air pollutant that affects human health, ecosystem and climate. Our analysis reveals a decrease of 5-10% in the CO column during LD (April-May 2020) compared to the pre-lockdown (PreLD, March 2020) periods in regions with high anthropogenic activity, such as East China (EC), Indo-Gangetic Plain (IGP), North America, parts of Europe and Russia. However, this reduction did not occur in the regions of frequent and intense wildfires and agricultural waste burning (AWB). We find high heterogeneity in the CO column distributions, from regional to city scales during the LD period. To determine the sources of CO emissions during LD, we examined the ratios of nitrogen dioxide (NO2), sulfur dioxide (SO2) to CO for major cities in the world. This facilitated the identification of contributions from different sources; including vehicles, industries and biomass burning during LD. The comparison between CO levels during the LD and PreLD periods indicates a notable reduction in the global tropospheric CO, but no significant change in the stratosphere. It is found that CO emissions decreased during LD in the hotspot regions, but rebounded after the LD restrictions were lifted. This study, therefore, highlights the importance of policy decisions and their implementations in the global and regional scales to improve the air quality, and thus to protect public health and environment.

The first balloon-borne sample analysis of atmospheric carbonaceous components reveals new insights into formation processes

Atmospheric aerosol optical, physical, and chemical properties play a fundamental role in the Earth's climate system. A better understanding of the processes involved in their formation, evolution, and interaction with radiation and the water cycle is critical. We report the analysis of atmospheric molecules/particles collected with a new sampling system that flew under regular weather balloons for the first time. The flight took place on January 18, 2022 from Reims (France). The samples were subsequently analyzed by high-resolution mass spectrometry (Orbitrap) to specifically infer hundreds of organic components present in 4 different layers from the troposphere to the stratosphere (up to 20 km). Additional measurements of O₃, CO, and aerosol concentrations a few hours before this flight took place to contextualize the sampling. After separating common species found on each filter that might be common to atmospheric layers or residuals for contaminations, we found that each sample yields significant differences in the number and size of organic species detected that should reflect the unique composition of atmospheric layers. While tropospheric samples yield significantly oxidized and saturated components, with carbon numbers below 30 that might be explained by complex organics chemistry from local and distant source emissions, the upper tropospheric and stratospheric samples were associated with increased carbon numbers (C > 30), with a significantly reduced unsaturation number for the stratosphere, that might be induced by strong UV radiations. The multimodal distributions of carbon numbers in chemical formulas observed between 15 and 20 km suggest that oligomerization and growth of organic molecules may take place in aged air masses of tropical origin that are known to carry organic compounds even several km above the tropopause where their lifetime significantly increases. In addition, the presence of organics may also reflect the extended influence of wildfires smoke injected during the spring and summer in the NH hemisphere before the in situ observations and their long-lifetime in the upper troposphere and stratosphere.

Characteristics of elevated aerosol layer over the Indian east coast, Kattankulathur (12.82oN, 80.04°E): A northeast monsoon region

The elevated aerosol layer (EAL) plays a vital role in weather and climate by modifying the Earth's radiation budget. In the present study, the EAL occurrence and its characteristics in the pre-monsoon season using micropulse lidar (MPL) observations during 2016-2018 and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) during 2007-2018 over Kattankulathur is being reported. We have collected 147 days (101 cases) of MPL (CALIPSO) observations during clear sky conditions in the pre-monsoon 2016-2018 (2007-2018), out of which EAL is observed for 56 days (61 cases). The EAL width is generally found to be ~2.0 km and occurs between ~1.0 km and 5.0 km. Three different types of EALs are categorized based on their altitudinal occurrence using the zero-crossing method. The EALs with their base at ~1.0-1.5 km, ~1.5-2.0 km, and ~ 2.0-3.0 km are taken as types I, II, and III, which occur for 9, 20, and 27 days, respectively. The EAL significantly modifies the total columnar aerosol optical depth (AOD). It is found that AOD, in total, within ABL and EAL, are ~0.72 (0.61), 0.28 (0.25), and 0.45 (0.36) using MPL (CALIPSO), respectively. The aerosols within ABL contribute ~38 % (41 %) while EAL ~ 62 % (59 %) to the total AOD obtained using MPL (CALIPSO). We observed that the ABL and EAL are characterized by different aerosol subtypes, such as dust marine (31 %) and smoke (~ 27 %) aerosols. Other aerosol subtypes, such as dust and polluted dust, commonly occur within the ABL (54 %) and EAL (52 %).

Occurrence, latitudinal gradient and potential sources of perchlorate in the atmosphere across the hemispheres (31°N to 80°S)

Perchlorate (ClO₄^-) is harmful to human health, and knowledge on the levels and sources of natural ClO₄^- in different environments remains rather limited. Here, we investigate ClO₄^- in aerosol samples collected along a cross-hemisphere ship cruise between China and Antarctica and on a traverse between coastal East Antarctica and the ice sheet summit (Dome Argus). Perchlorate concentrations range from a few to a few hundred pg m^-3. A clear latitudinal trend is found, with elevated ClO₄^- concentrations near populated areas and in the southern mid-high latitudes. Spatial patterns of atmospheric ClO₄^- over oceans near the landmasses support that terrestrial ClO₄^- is not transported efficiently over long distances. In the southern mid-latitudes, higher ClO₄^- concentrations in March than in November-December may be caused by significant stratospheric inputs in March. Perchlorate concentrations appear to be higher in the warm half than in the cold half of the year in the southern high latitudes, suggesting seasonal difference in main atmospheric sources. ClO₄^- may be formed in the reactions between chlorine free radical (Cl·) and ozone (O₃) in the stratosphere when Antarctic ozone hole occurs during September-October. And the stratosphere-produced ClO₄^- is moved to the boundary layer in several months and may be responsible for the high ClO₄^- concentrations in the warm half of the year. Perchlorate produced by photochemical reactions between O₃ and Cl· in the Antarctic stratosphere is likely responsible for the higher ClO₄^- concentrations in Antarctica than in Arctic.

Lithosphere atmosphere ionosphere coupling associated with the 2019 Mw 7.1 California earthquake using GNSS and multiple satellites

Global Navigation Satellite System (GNSS)-based Earthquake (EQ) anomalies in the ionosphere and troposphere provide explicit evidences to study the coupling between seismic events, atmosphere, and ionosphere in epicentral breeding regions consequent to the EQ day in the preparation period. EQs are still not predicted, but the space-based EQ anomalies aid in the development of monitoring pre- and post-seismic precursors around the seismogenic zone and associated fault lineament regions. In this paper, tropospheric and ionospheric anomalies are investigated for the July 06, 2019, M_w 7.1 California EQ from GNSS tropospheric delays and Total Electron Content (TEC), respectively. We noticed that atmospheric and ionospheric anomalies from GNSS stations within 5-10 days before the main shock and storm-induced ionospheric variations occur beyond the 5th day after the EQ. Similarly, synchronized and collocated lower atmospheric anomalies are also recorded in the long-term temporal values of SO₂ and SO₄ within 1-month before and after July 2019, which validates the existence of Lithosphere-Atmosphere-Ionosphere Coupling (LAIC) over the EQ epicenter. On the other hand, EQ anomalies occur during quiet geomagnetic storm activity (Kp < 3; Dst < - 20 nT) and geomagnetic storm triggered high-intensity ionospheric variations during Kp > 3. All these atmospheric and ionospheric perturbations support the development in EQ precursors with satellite measurements, which are indispensable towards the forecasting of future EQ.

Hydroxyl, hydroperoxyl free radicals determination methods in atmosphere and troposphere

The hydroxyl radical (•OH) has a crucial function in the oxidation and removal of many atmospheric compounds that are harmful to health. Nevertheless, high reactivity, low atmospheric abundance, determination of hydroxyl, and hydroperoxyl radical's quantity is very difficult. In the atmosphere and troposphere, hydroperoxyl radicals (HO₂) are closely demanded in the chemical oxidation of the troposphere. But advances in technology have allowed researchers to improve the determination methods on the research of free radicals through some spectroscopic techniques. So far, several methods such as laser-induced fluorescence (LIF), high-performance liquid chromatography (HPLC), and chemical ionization mass spectroscopy have been identified and mostly used in determining the quantity of hydroxyl and hydroperoxyl radicals. In this systematic review, we have advised the use of scavenger as an advance for further researchers to circumvent some of these problems caused by free radicals. The primary goal of this review is to deepen our understanding of the functions of the most critical free radical (•OH, HO₂) and also understand the currently used methods to quantify them in the atmosphere and troposphere.

VMF3o: the Vienna Mapping Functions for optical frequencies

The troposphere is considered as one of the major error sources in space geodetic techniques. Thus, accurate troposphere delay models are essential to provide high-quality products, such as reference frames, satellite orbits, or Earth rotation parameters. In this paper, a new troposphere delay model for satellite laser ranging, the Vienna Mapping Functions 3 for optical frequencies (VMF3o), is introduced. The model parameters are derived from ray-traced delays generated by an in-house ray-tracing software. VMF3o comprises not only zenith delays and mapping functions, but also linear horizontal gradients, which are not part of the standard SLR analysis yet. The model parameters are dedicated to a signal wavelength of 532 nm. Since some SLR stations operate also with other wavelengths, VMF3o provides a correction formula to transform the model parameters to any requested wavelength between 350 and 1064 nm. A test demonstrates that the correction formula approximates slant delays calculated at different wavelengths very accurately. The remaining error for slant delays at a wavelength of 1064 nm adds up to only a few millimetres at 10 ∘ elevation angle. A comparison study of the modelled delays that are derived from VMF3o and ray-traced delays was carried out to examine the quality of the model approach. The remaining differences of modelled and ray-traced delays are expressed as mean absolute error. At 5 ∘ elevation angle, the mean absolute error is only a few millimetres. At 10 ∘ elevation angle, it is at the 1 mm level. The results of the comparison also reveal that introducing linear horizontal gradients reduces the mean absolute error by more than 80% for low elevation angles.

Refined discrete and empirical horizontal gradients in VLBI analysis

Missing or incorrect consideration of azimuthal asymmetry of troposphere delays is a considerable error source in space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). So-called horizontal troposphere gradients are generally utilized for modeling such azimuthal variations and are particularly required for observations at low elevation angles. Apart from estimating the gradients within the data analysis, which has become common practice in space geodetic techniques, there is also the possibility to determine the gradients beforehand from different data sources than the actual observations. Using ray-tracing through Numerical Weather Models (NWMs), we determined discrete gradient values referred to as GRAD for VLBI observations, based on the standard gradient model by Chen and Herring (J Geophys Res 102(B9):20489-20502, 1997. 10.1029/97JB01739) and also for new, higher-order gradient models. These gradients are produced on the same data basis as the Vienna Mapping Functions 3 (VMF3) (Landskron and Böhm in J Geod, 2017. 10.1007/s00190-017-1066-2), so they can also be regarded as the VMF3 gradients as they are fully consistent with each other. From VLBI analyses of the Vienna VLBI and Satellite Software (VieVS), it becomes evident that baseline length repeatabilities (BLRs) are improved on average by 5% when using a priori gradients GRAD instead of estimating the gradients. The reason for this improvement is that the gradient estimation yields poor results for VLBI sessions with a small number of observations, while the GRAD a priori gradients are unaffected from this. We also developed a new empirical gradient model applicable for any time and location on Earth, which is included in the Global Pressure and Temperature 3 (GPT3) model. Although being able to describe only the systematic component of azimuthal asymmetry and no short-term variations at all, even these empirical a priori gradients slightly reduce (improve) the BLRs with respect to the estimation of gradients. In general, this paper addresses that a priori horizontal gradients are actually more important for VLBI analysis than previously assumed, as particularly the discrete model GRAD as well as the empirical model GPT3 are indeed able to refine and improve the results.

VMF3/GPT3: refined discrete and empirical troposphere mapping functions

Incorrect modeling of troposphere delays is one of the major error sources for space geodetic techniques such as Global Navigation Satellite Systems (GNSS) or Very Long Baseline Interferometry (VLBI). Over the years, many approaches have been devised which aim at mapping the delay of radio waves from zenith direction down to the observed elevation angle, so-called mapping functions. This paper contains a new approach intended to refine the currently most important discrete mapping function, the Vienna Mapping Functions 1 (VMF1), which is successively referred to as Vienna Mapping Functions 3 (VMF3). It is designed in such a way as to eliminate shortcomings in the empirical coefficients b and c and in the tuning for the specific elevation angle of 3 ∘ . Ray-traced delays of the ray-tracer RADIATE serve as the basis for the calculation of new mapping function coefficients. Comparisons of modeled slant delays demonstrate the ability of VMF3 to approximate the underlying ray-traced delays more accurately than VMF1 does, in particular at low elevation angles. In other words, when requiring highest precision, VMF3 is to be preferable to VMF1. Aside from revising the discrete form of mapping functions, we also present a new empirical model named Global Pressure and Temperature 3 (GPT3) on a5 ∘ × 5 ∘ as well as a1 ∘ × 1 ∘ global grid, which is generally based on the same data. Its main components are hydrostatic and wet empirical mapping function coefficients derived from special averaging techniques of the respective (discrete) VMF3 data. In addition, GPT3 also contains a set of meteorological quantities which are adopted as they stand from their predecessor, Global Pressure and Temperature 2 wet. Thus, GPT3 represents a very comprehensive troposphere model which can be used for a series of geodetic as well as meteorological and climatological purposes and is fully consistent with VMF3.

Atmospheric fate of hydrofluoroolefins, CxF2x+1CHCH2 (x = 1,2,3,4 and 6): Kinetics with Cl atoms and products

Rate coefficients for the gas-phase reactions of C_xF_2x+1CHCH₂ (x = 1, 2, 3, 4 and 6) with Cl atoms were determined at (298 ± 2) K and (710 ± 5) Torr of air using a relative rate technique. Two experimental setups with simulation chambers were employed with Fourier Transform Infrared (FTIR) spectroscopy and Gas Chromatography coupled to Mass Spectrometry (GC-MS) as detection techniques. The Cl-rate coefficients obtained were (in 10^-10 cm³ molecule^-1 s^-1): (0.85 ± 0.11) for CF₃CHCH₂, (1.11 ± 0.08) for C₂F₅CHCH₂, (1.12 ± 0.18) for C₃F₇CHCH₂, (0.97 ± 0.09) for C₄F₉CHCH₂, and (0.99 ± 0.08) for C₆F₁₃CHCH₂. Additionally, the gas-phase products were identified and quantified, when possible, by FTIR spectroscopy or GC-MS. The main reaction product was reported to be C_xF_2x+1C(O)CH₂Cl. The fluorinated species, C_xF_2x+1CHO and C_xF_2x+1C(O)CH₂Cl, were identified. CF₃C(O)CH₂Cl and CF₃CHO were found to be formed with molar yield of (69 ± 5)% and (9 ± 1)%, respectively. The global lifetime of the investigated C_xF_2x+1CHCH₂ due to their Cl-reaction is more than 100 days so this route does not compete with the removal by OH radicals. This lifetime is long enough for C_xF_2x+1CHCH₂ to be transported to remote areas where they can be degraded. However, at a local scale, in marine regions at dawn the removal of C_xF_2x+1CHCH₂ is expected to occur in ca. 1 day. The atmospheric degradation of these hydrofluoroolefins by Cl atoms is not expected to be a source of bioaccumulative perfluorinated carboxylic acids, C_xF_2x+1C(O)OH. Additionally, the UV absorption cross sections of CF₃C(O)CH₂Cl were determined together with the rate coefficient of the OH reaction by an absolute kinetic method at room temperature.

Selective sensing of ozone and the chemically active gaseous species of the troposphere by using the C20 fullerene and graphene segment

OZONE is a key species in forming a layer in the atmosphere of earth that brings vita for our planet and supports the complex life. This three-atom molecule in the ozone-layer, is healing the earth's ecosystem by protecting it from dangerous rays of the sun. Until this molecule is in the stratosphere, it would support the natural order of the life; but, when it appears in our environment, damages will begin against us. In this project, we have tried to find a new way for beaconing ozone species in our environment via physical adsorption by the C₂₀ fullerene and graphene segment as a sensor. To find the selectivity of this nano-sized segment in sensing ozone (O₃), compared to the usual chemically active gasses of the troposphere like O₂, N₂, CO₂, H₂O, CH₄, H₂, and CO, the density of state (DOS) plots were analyzed, for each interacting species. The results showed that ozone could significantly change the electrical conductivity of C₂₀ fullerene, for each adsorption step. Thus, this fullerene could clearly sense ozone in different adsorption steps; while, the graphene segment could do this only at the second step adsorption (/ΔE_g-B/=0.016eV) (at the first adsorption step the /ΔE_g-A/ is 0.00eV).

Analysis of surface ozone using a recurrent neural network

Hourly concentrations of ozone (O₃) and nitrogen dioxide (NO₂) have been measured for 16 years, from 1998 to 2013, in a seaside town in central Italy. The seasonal trends of O₃ and NO₂ recorded in this period have been studied. Furthermore, we used the data collected during one year (2005), to define the characteristics of a multiple linear regression model and a neural network model. Both models are used to model the hourly O₃ concentration, using, two scenarios: 1) in the first as inputs, only meteorological parameters and 2) in the second adding photochemical parameters at those of the first scenario. In order to evaluate the performance of the model four statistical criteria are used: correlation coefficient, fractional bias, normalized mean squared error and a factor of two. All the criteria show that the neural network gives better results, compared to the regression model, in all the model scenarios. Predictions of O₃ have been carried out by many authors using a feed forward neural architecture. In this paper we show that a recurrent architecture significantly improves the performances of neural predictors. Using only the meteorological parameters as input, the recurrent architecture shows performance better than the multiple linear regression model that uses meteorological and photochemical data as input, making the neural network model with recurrent architecture a more useful tool in areas where only weather measurements are available. Finally, we used the neural network model to forecast the O₃ hourly concentrations 1, 3, 6, 12, 24 and 48 h ahead. The performances of the model in predicting O₃ levels are discussed. Emphasis is given to the possibility of using the neural network model in operational ways in areas where only meteorological data are available, in order to predict O₃ also in sites where it has not been measured yet.

Can artificial neural networks be used to predict the origin of ozone episodes?

Tropospheric ozone is a secondary pollutant having a negative impact on health and environment. To control and minimize such impact the European Community established regulations to promote a clean air all over Europe. However, when an episode is related with natural mechanisms as Stratosphere-Troposphere Exchanges (STE), the benefits of an action plan to minimize precursor emissions are inefficient. Therefore, this work aims to develop a tool to identify the sources of ozone episodes in order to minimize misclassification and thus avoid the implementation of inappropriate air quality plans. For this purpose, an artificial neural network model - the Multilayer Perceptron - is used as a binary classifier of the source of an ozone episode. Long data series, between 2001 and 2010, considering the ozone precursors, (7)Be activity and meteorological conditions were used. With this model, 2-7% of a mean error was achieved, which is considered as a good generalization. Accuracy measures for imbalanced data are also discussed. The MCC values show a good performance of the model (0.65-0.92). Precision and F1-measure indicate that the model specifies a little better the rare class. Thus, the results demonstrate that such a tool can be used to help authorities in the management of ozone, namely when its thresholds are exceeded due natural causes, as the above mentioned STE. Therefore, the resources used to implement an action plan to minimize ozone precursors could be better managed avoiding the implementation of inappropriate measures.