Predicting the climate impact of aviation for en-route emissions: the algorithmic climate change function submodel ACCF 1.0 of EMAC 2.53

Using climate-optimized flight trajectories is one essential measure to reduce aviation's climate impact. Detailed knowledge of temporal and spatial climate sensitivity for aviation emissions in the atmosphere is required to realize such a climate mitigation measure. The algorithmic Climate Change Functions (aCCFs) represent the basis for such purposes. This paper presents the first version of the Algorithmic Climate Change Function submodel (ACCF 1.0) within the European Centre HAMburg general circulation model (ECHAM) and Modular Earth Submodel System (MESSy) Atmospheric Chemistry (EMAC) model framework. In the ACCF 1.0, we implement a set of aCCFs (version 1.0) to estimate the average temperature response over 20 years (ATR20) resulting from aviation CO2 emissions and non-CO2 impacts, such as NOx emissions (via ozone production and methane destruction), water vapour emissions, and contrail cirrus. While the aCCF concept has been introduced in previous research, here, we publish a consistent set of aCCF formulas in terms of fuel scenario, metric, and efficacy for the first time. In particular, this paper elaborates on contrail aCCF development, which has not been published before. ACCF 1.0 uses the simulated atmospheric conditions at the emission location as input to calculate the ATR20 per unit of fuel burned, per NOx emitted, or per flown kilometre.In this research, we perform quality checks of the ACCF 1.0 outputs in two aspects. Firstly, we compare climatological values calculated by ACCF 1.0 to previous studies. The comparison confirms that in the Northern Hemisphere between 150–300 hPa altitude (flight corridor), the vertical and latitudinal structure of NOx-induced ozone and H2O effects are well represented by the ACCF model output. The NOx-induced methane effects increase towards lower altitudes and higher latitudes, which behaves differently from the existing literature. For contrail cirrus, the climatological pattern of the ACCF model output corresponds with the literature, except that contrail-cirrus aCCF generates values at low altitudes near polar regions, which is caused by the conditions set up for contrail formation. Secondly, we evaluate the reduction of NOx-induced ozone effects through trajectory optimization, employing the tagging chemistry approach (contribution approach to tag species according to their emission categories and to inherit these tags to other species during the subsequent chemical reactions). The simulation results show that climate-optimized trajectories reduce the radiative forcing contribution from aviation NOx-induced ozone compared to cost-optimized trajectories. Finally, we couple the ACCF 1.0 to the air traffic simulation submodel AirTraf version 2.0 and demonstrate the variability of the flight trajectories when the efficacy of individual effects is considered. Based on the 1 d simulation results of a subset of European flights, the total ATR20 of the climate-optimized flights is significantly lower (roughly 50 % less) than that of the cost-optimized flights, with the most considerable contribution from contrail cirrus. The CO2 contribution observed in this study is low compared with the non-CO2 effects, which requires further diagnosis.

Aerosol demasking enhances climate warming over South Asia.

Anthropogenic aerosols mask the climate warming caused by greenhouse gases (GHGs). In the absence of observational constraints, large uncertainties plague the estimates of this masking effect. Here we used the abrupt reduction in anthropogenic emissions observed during the COVID-19 societal slow-down to characterize the aerosol masking effect over South Asia. During this period, the aerosol loading decreased substantially and our observations reveal that the magnitude of this aerosol demasking corresponds to nearly three-fourths of the CO2-induced radiative forcing over South Asia. Concurrent measurements over the northern Indian Ocean unveiled a ~7% increase in the earth's surface-reaching solar radiation (surface brightening). Aerosol-induced atmospheric solar heating decreased by ~0.4 K d-1. Our results reveal that under clear sky conditions, anthropogenic emissions over South Asia lead to nearly 1.4 W m-2 heating at the top of the atmosphere during the period March-May. A complete phase-out of today's fossil fuel combustion to zero-emission renewables would result in rapid aerosol demasking, while the GHGs linger on.

Two years of volatile organic compound online in situ measurements at the Site Instrumental de Recherche par Télédétection Atmosphérique (Paris region, France) using proton-transfer-reaction mass spectrometry

Volatile organic compounds (VOCs) have direct influences on air quality and climate. They indeed play a key role in atmospheric chemistry as precursors of secondary pollutants, such as ozone (O3) and secondary organic aerosols (SOA). In this respect, long-term datasets of in situ atmospheric measurements are crucial for characterizing the variability of atmospheric chemical composition, its sources, and trends. The ongoing establishment of the Aerosols, Cloud, and Trace gases Research InfraStructure (ACTRIS) allows implementation of the collection and provision of such high-quality datasets. In this context, online and continuous measurements of O3, nitrogen oxides (NOx), and aerosols have been carried out since 2012 at the SIRTA (Site Instrumental de Recherche par Télédétection Atmosphérique) observatory, located in the Paris region, France. Within the last decade, VOC measurements were conducted offline at SIRTA, until the implementation of real-time monitoring which started in January 2020 using a proton-transfer-reaction quadrupole mass spectrometer (PTR-Q-MS).The dataset acquired during the first 2 years of online VOC measurements provides insights into their seasonal and diurnal variabilities. The additional long-term datasets obtained from co-located measurements (NOx, aerosol physical and chemical properties, meteorological parameters) are used to better characterize the atmospheric conditions and to further interpret the obtained results. Results also include insights into VOC main sources and the influence of meteorological conditions and air mass origin on their levels in the Paris region. Due to the COVID-19 pandemic, the year 2020 notably saw a quasi-total lockdown in France in spring and a lighter one in autumn. Therefore, the focus is placed on the impact of these lockdowns on the VOC variability and sources. A change in the behaviour of VOC markers for anthropogenic sources was observed during the first lockdown, reflecting a change in human activities. A comparison with gas chromatography data from the Paris city centre consolidates the regional representativity of the SIRTA station for benzene, while differences are observed for shorter-lived compounds with a notable impact of their local sources. This dataset could be further used as input for atmospheric models and can be found at 10.14768/f8c46735-e6c3-45e2-8f6f-26c6d67c4723 (Simon et al., 2022a).

Smart Device for CO2 Measuring and Supplementing with O2 Using IOT

Globally, atmospheric carbon dioxide (CO2) concentration is rising due to rising carbon-based fuel consumption and ongoing deforestation. As carbon dioxide levels grow due to the warming trend, the atmosphere's temperature is predicted to climb. Increased fatigue, headaches, and tinnitus are just a few health issues that high CO2 concentrations in the atmosphere can cause. The electrical activities of the brain, the heart, and the lungs have all been demonstrated to change significantly after a brief exposure to 0.1 percent CO2. Continuous measurements of the atmospheric CO2 content have recently been shown to help evaluate the ventilation conditions in buildings or rooms. Additionally, it prevents the development of the severe acute respiratory syndrome coronavirus 2 (Severe acute respiratory). The coronavirus, known as a powerful acute respiratory, can make people ill. This has grown to be a significant concern in emergency medicine. © 2022 IEEE.

Coarse particulate matter air quality in East Asia: implications for fine particulate nitrate

Air quality network data in China and South Korea show very high year-round mass concentrations of coarse particulate matter (PM), as inferred by the difference between PM10 and PM2.5. Coarse PM concentrations in 2015 averaged 52 µg m-3 in the North China Plain (NCP) and 23 µg m-3 in the Seoul Metropolitan Area (SMA), contributing nearly half of PM10. Strong daily correlations between coarse PM and carbon monoxide imply a dominant source from anthropogenic fugitive dust. Coarse PM concentrations in the NCP and the SMA decreased by 21 % from 2015 to 2019 and further dropped abruptly in 2020 due to COVID-19 reductions in construction and vehicle traffic. Anthropogenic coarse PM is generally not included in air quality models but scavenges nitric acid to suppress the formation of fine particulate nitrate, a major contributor to PM2.5 pollution. GEOS-Chem model simulation of surface and aircraft observations from the Korea–United States Air Quality (KORUS-AQ) campaign over the SMA in May–June 2016 shows that consideration of anthropogenic coarse PM largely resolves the previous model overestimate of fine particulate nitrate. The effect is smaller in the NCP which has a larger excess of ammonia. Model sensitivity simulations for 2015–2019 show that decreasing anthropogenic coarse PM directly increases PM2.5 nitrate in summer, offsetting 80 % the effect of nitrogen oxide and ammonia emission controls, while in winter the presence of coarse PM increases the sensitivity of PM2.5 nitrate to ammonia and sulfur dioxide emissions. Decreasing coarse PM helps to explain the lack of decrease in wintertime PM2.5 nitrate observed in the NCP and the SMA over the 2015–2021 period despite decreases in nitrogen oxide and ammonia emissions. Continuing decrease of fugitive dust pollution means that more stringent nitrogen oxide and ammonia emission controls will be required to successfully decrease PM2.5 nitrate.

Methane emissions are predominantly responsible for record-breaking atmospheric methane growth rates in 2020 and 2021

The global atmospheric methane growth rates reported by NOAA for 2020 and 2021 are the largest since systematic measurements began in 1983. To explore the underlying reasons for these anomalous growth rates, we use newly available methane data from the Japanese Greenhouse gases Observing SATellite (GOSAT) to estimate methane surface emissions. Relative to baseline values in 2019, we find that a significant global increase in methane emissions of 27.0 ± 11.3 and 20.8 ± 11.4 Tg is needed to reproduce observed atmospheric methane in 2020 and 2021, respectively, assuming fixed climatological values for OH. We see the largest annual increases in methane emissions during 2020 over Eastern Africa (14 ± 3 Tg), tropical Asia (3 ± 4 Tg), tropical South America (5 ± 4 Tg), and temperate Eurasia (3 ± 3 Tg), and the largest reductions are observed over China (-6 ± 3 Tg) and India (-2 ± 3 Tg). We find comparable emission changes in 2021, relative to 2019, except for tropical and temperate South America where emissions increased by 9 ± 4 and 4 ± 3 Tg, respectively, and for temperate North America where emissions increased by 5 ± 2 Tg. The elevated contributions we saw in 2020 over the western half of Africa (-5 ± 3 Tg) are substantially reduced in 2021, compared to our 2019 baseline. We find statistically significant positive correlations between anomalies of tropical methane emissions and groundwater, consistent with recent studies that have highlighted a growing role for microbial sources over the tropics. Emission reductions over India and China are expected in 2020 due to the Covid-19 lockdown but continued in 2021, which we do not currently understand. To investigate the role of reduced OH concentrations during the Covid-19 lockdown in 2020 on the elevated atmospheric methane growth in 2020–2021, we extended our inversion state vector to include monthly scaling factors for OH concentrations over six latitude bands. During 2020, we find that tropospheric OH is reduced by 1.4 ± 1.7 % relative to the corresponding 2019 baseline value. The corresponding revised global growth of a posteriori methane emissions in 2020 decreased by 34 % to 17.9 ± 13.2 Tg, relative to the a posteriori value that we inferred using fixed climatological OH values, consistent with sensitivity tests using the OH climatology inversion using reduced values for OH. The counter statement is that 66 % of the global increase in atmospheric methane during 2020 was due to increased emissions, particularly from tropical regions. Regional flux differences between the joint methane–OH inversion and the OH climatology inversion in 2020 are typically much smaller than 10 %. We find that OH is reduced by a much smaller amount during 2021 than in 2020, representing about 10 % of the growth of atmospheric methane in that year. Therefore, we conclude that most of the observed increase in atmospheric methane during 2020 and 2021 is due to increased emissions, with a significant contribution from reduced levels of OH.

Global Atmospheric Composition Needs from Future Ultraviolet–Visible–Near-Infrared (UV–Vis–NIR) NOAA Satellite Instruments

Presentations spanned a range of applications: the public health impacts of poor air quality and environmental justice;greenhouse gas measuring, monitoring, reporting, and verification (GHG MMRV);stratospheric ozone monitoring;and various applications of satellite observations to improve models, including data assimilation in global Earth system models. The combination of methane (CH4), carbon dioxide (CO2), carbon monoxide (CO), and NO2 retrievals can improve confidence in emissions inventories and model performance, and together these data products would be of use in future air quality management tools. The ability to retrieve additional trace gases (e.g., ethane, isoprene, and ammonia) in the thermal IR along with those measured in the UV–Vis–NIR region would be extremely useful for air quality applications, including source apportionment analysis (e.g., for oil/natural gas extraction, biogenic, and agricultural sources). Ground-level ozone is one of six criteria pollutants for which the EPA sets National Ambient Air Quality Standards (NAAQS) to protect against human health and welfare effects.

Investigation of Changes in Atmospheric Pollutants due to the Cessation of Anthropogenic Activities: Spatial Heterogeneity and Complex Atmospheric Chemistry

The current study examines the air quality trends in response to Covid-19-induced lockdowns at various locations in Delhi. The primary pollutants like NO2, CO, and PM10 have shown reductions during the lockdown phase, but the magnitude varied significantly in different places. Also, during the lockdown, air quality in some areas of Delhi exceeded National Ambient Air Quality Standards. Secondary pollutants like O3 have shown mixed trends due to complex atmospheric processes and dependence on relative proportions of VOC and NOx levels. A total of six sites, including traffic, industrial, and residential sites, have been studied. The diurnal behavior of pollutants also differed significantly around different places. During the lockdown, Ashok Vihar, a traffic-influenced area, showed a decrease in O3 (~ 40%), while at DTU (Traffic site), O3 levels increased (~ 48%). The industrial sites Okhla and Wazirpur also showed different trends during the lockdown;O3 in Wazirpur decreased by 50%, whereas Okhla increased by 25%. NOx concentration was lesser in 2020 at all the stations compared to 2019, indicating the positive impact of the lockdown on air pollution due to vehicular emissions. The Approximate Envelope Method estimates the secondary fraction of PM2.5. This fraction of PM is dominated in the lockdown year in the residential site, while it remains unchanged in the traffic site and increased by 11% in the industrial area. Despite being not so far from each other, these sites show very different patterns of pollutants during lockdown episodes. © 2023, The Author(s) under exclusive licence to Institute of Earth Environment, Chinese Academy Sciences.

Nearly five-year continuous atmospheric measurements of black carbon over a suburban area in central France

Atmospheric black carbon (BC) concentration over a nearly 5 year period (mid-2017–2021) was continuously monitored over a suburban area of Orléans city (France). Annual mean atmospheric BC concentration were 0.75 ± 0.65, 0.58 ± 0.44, 0.54 ± 0.64, 0.48 ± 0.46 and 0.50 ± 0.72 μg m−3, respectively, for the year of 2017, 2018, 2019, 2020 and 2021. Seasonal pattern was also observed with maximum concentration (0.70 ± 0.18 μg m−3) in winter and minimum concentration (0.38 ± 0.04 μg m−3) in summer. We found a different diurnal pattern between cold (winter and fall) and warm (spring and summer) seasons. Further, fossil fuel burning contributed >90 % of atmospheric BC in the summer and biomass burning had a contribution equivalent to that of the fossil fuel in the winter. Significant week days effect on BC concentrations was observed, indicating the important role of local emissions such as car exhaust in BC level at this site. The behavior of atmospheric BC level with COVID-19 lockdown was also analyzed. We found that during the lockdown in warm season (first lockdown: 27 March–10 May 2020 and third lockdown 17 March–3 May 2021) BC concentration were lower than in cold season (second lockdown: 29 October–15 December 2020), which could be mainly related to the BC emission from biomass burning for heating. This study provides a long-term BC measurement database input for air quality and climate models. The analysis of especially weekend and lockdown effect showed implications on future policymaking toward improving local and regional air quality as well. © 2022 Elsevier B.V.

How Partial Anonymity May Reduce Students' Anxiety During Remote Active Learning─A Case Study Using Clubhouse

Active learning, a common practice in higher education, has been shown to promote higher order thinking and skills. Class discussions have been chosen to be the medium to incorporate active learning in schools‘ curriculum. However, the rate of class participation could be low for certain courses. Literature has shown that the fear of negative evaluation from peers is the most common reason as to why students choose not to partake in class discussions. Anonymity via clickers or applications such as Kahoot! has shown to be useful in reducing students' anxiety and increasing class participations. However, this is not a viable method to employ if vocal discussion is required for the course. Here, partial anonymity (voice only), Speak Your Mind, was applied into an environmental chemistry course with 20 students in the National University of Singapore (NUS) to study its correlation with students‘ anxiety and class participation. Participants survey results suggested that a reason for not participating in class discussions was the fear of being judged by their peers. Remote learning was conducted due to COVID-19 and partial anonymity was obtained by a proxy application: Clubhouse. This application allowed students to partake in a podium discussion while maintaining psychological safety via partial anonymity. Participants survey responses indicated that partial anonymity reduced their anxiety (Cohen's d = 0.58) and slightly increased their self-reported class participation rate (Cohen's d = 0.21);it was noted that partial anonymity did not have much effect on their fears of being judged if they provided the wrong answer (Cohen's d = 0.11). © 2023 American Chemical Society and Division of Chemical Education, Inc.

Unwanted Indoor Air Quality Effects from Using Ultraviolet C Lamps for Disinfection

Ultraviolet germicidal irradiation (UVGI) is known to inactivate various viruses and bacteria, including SARS-CoV-2, and is widely applied especially in medical facilities. This inactivation results from the high photon energies causing molecular bonds to break, but when nonpathogen molecules are affected, unwanted effects may occur. Here, we explored the effect of a commercial high-intensity (∼2 kW) UVC disinfection device on the composition and concentration of gases and particles in indoor air. We find that the UVC (254 nm) caused dramatic increases in particle number concentrations, and nearly all (∼1000) monitored gas phase species also increased. These responses were unsurprising when considering the typical impacts of UVC on atmospheric chemistry. High particle concentrations are associated with adverse health effects, suggesting that the impact of UVGI devices on indoor air quality (IAQ) should be studied in much more detail. The high-intensity device in this study was intended for short durations in unoccupied rooms, but lower-intensity devices for continuous use in occupied rooms are also widely applied. This makes further studies even more urgent, as the potential IAQ effects of these approaches remain largely unexplored. © 2023 The Authors. Published by American Chemical Society.

Mechanisms and Pathways for Coordinated Control of Fine Particulate Matter and Ozone.

Purpose of Review: Fine particulate matter (PM2.5) and ground-level ozone (O3) pose a significant risk to human health. The World Health Organization (WHO) has recently revised healthy thresholds for both pollutants. The formation and evolution of PM2.5 and O3 are however governed by complex physical and multiphase chemical processes, and therefore, it is extremely challenging to mitigate both pollutants simultaneously. Here, we review mechanisms and discuss the science-informed pathways for effective and simultaneous mitigation of PM2.5 and O3. Recent Findings: Global warming has led to a general increase in biogenic emissions, which can enhance the formation of O3 and secondary organic aerosols. Reductions in anthropogenic emissions during the COVID-19 lockdown reduced PM2.5; however, O3 was enhanced in several polluted regions. This was attributed to more intense sunlight due to low aerosol loading and non-linear response of O3 to NO x . Such contrasting physical and chemical interactions hinder the formulation of a clear roadmap for clean air over such regions. Summary: Atmospheric chemistry including the role of biogenic emissions, aerosol-radiation interactions, boundary layer, and regional-scale transport are the key aspects that need to be carefully considered in the formulation of mitigation pathways. Therefore, a thorough understanding of the chemical effects of the emission reductions, changes in photolytic rates and boundary layer due to perturbation of solar radiation, and the effect of meteorological/seasonal changes are needed on a regional basis. Statistical emulators and machine learning approaches can aid the cumbersome process of multi-sector multi-species source attribution.

Two years of Volatile Organic Compounds online in-situ measurements at SIRTA (Paris region, France) using Proton-Transfer-Reaction Mass Spectrometry

Volatile Organic Compounds (VOCs) have direct influences on air quality and climate. They indeed play a key role in atmospheric chemistry, as precursors of secondary pollutants, such as ozone (O3) and secondary organic aerosols (SOA). To this respect, long-term datasets of in-situ atmospheric measurements are crucial to characterize the variability of atmospheric chemical composition, its sources and trends. The on-going establishment of the Aerosols, Cloud, and Trace gases Research InfraStructure (ACTRIS) allows implementing the collection and provision of such high-quality datasets. In this context, online and continuous measurements of O3, nitrogen oxides (NOX) and aerosols have been carried out since 2012 at the SIRTA observatory, located in the Paris region, France. Within the last decade, VOC measurements have been conducted offline at SIRTA, until the implementation of a real-time monitoring which started in January 2020, using a Proton-Transfer-Reaction Quadrupole Mass-Spectrometer (PTR-Q-MS). The dataset acquired during the first two years of online VOC measurements provides insights on their seasonal and diurnal variabilities. The additional long-term datasets obtained from co-located measurements (NOX, aerosol physical and chemical properties, meteorological parameters) are used to better characterize the atmospheric conditions and to further interpret the obtain results. Results also include insights on VOC's main sources and the influence of meteorological conditions and air mass origin on their levels, in the Paris region. Due to the COVID-19 pandemic, the year 2020 notably comprised a quasi-total lockdown in France in Spring, and a lighter one in Autumn. Therefore, a focus is made on the impact of these lockdowns on the VOC variability and sources. A change in the behaviour of VOC markers for anthropogenic sources was observed during the first lockdown, reflecting a change in human activities. This dataset could be further used as input for atmospheric models and can be found under https://doi.org/10.14768/f8c46735-e6c3-45e2-8f6f-26c6d67c4723 (Simon et al, 2022). [ FROM AUTHOR]

Integrating “Impacts of Covid-19 pandemic on air quality” in STEM courses and internships for undergraduate students

Air pollution is a global public health concern and has led to millions of premature deaths worldwide. In overpopulated cities, particulate matter such PM2.5, nitrogen dioxide (NO2), and ozone (O3) in the troposphere have deleterious effects on human health leading to cardiovascular and respiratory diseases. The students in two undergraduate courses (Principles of Biology for Honors students and Ecology) and one graduate course (Teaching STEM at the K-12 schools) at the University of Maryland Eastern Shore;and summer-exchange undergraduate engineering interns learnt about the positive and negative effects of Covid-19 pandemic on air quality for some of the selected overpopulated cities in the world that witnessed lockdowns from March 2020 through spring 2021. The STEM students as well as the interns had the opportunity to learn how to analyze the real-time and historical air quality data from the Environmental Protection's Agency's centralized data system, AirNow, as well as from the Air Quality Open Data Platform (https://aqicn.org/data-platform/covid19) Worldwide Covid-19 dataset. For the above-mentioned courses, the materials pertaining to Covid-19 and air quality were taught in the form of modules (two for each course) with lectures;discussions and class debates;video materials;simulations with real-time data;and a project centering on that theme. The engineering students who worked as summer interns worked on analyzing data from five of the major cities in the world. Besides analyzing the effects of the pandemic on PM2.5, NO2, and O3 in the selected populated cities, the students also studied whether any correlations existed among the air quality parameters or not. The students' learning outcomes included honing content knowledge in atmospheric chemistry and physics of particulate matter;environmental sciences and engineering;public health and policies;research skills with respect to data analysis and problem-solving;as well as presentation and writing skills. The students and interns in the courses and internships also addressed and debated on the various issues of sustainability, which encompasses social, environmental, economic considerations along with policies. The crisis of the pandemic on climate change is dependent on the policies of the governments towards which directions the economies need to head. When the governments prioritize to shift from fossil fuels to cleaner energy such as wind, solar, geothermal, biofuels, then the mitigation efforts of climate change could come to fruition. It is anticipated that with more ongoing collaborations across disciplines, the authors will be able to permanently integrate these diverse components in other STEM courses such as Statistics for Engineers, Big Data Analytics, and enhance multidisciplinary learning for all majors. This integration of research findings in STEM courses is a reflection of the KDB (Know, Do, Be) framework, as the interns and the students honed their skills not only in content knowledge through inquiry, but felt responsible in taking action towards mitigation efforts of climate change. © American Society for Engineering Education, 2022

HazeL: A Low-Cost Learning Platform for Aerosol Measurements

The switch to online instruction during the COVID-19 pandemic forced educators to adapt hands-on environmental engineering experiments to a remote curriculum previously conducted in a laboratory using expensive analytical instruments (> $2000 per device). Here, we describe how we developed a low-cost (<$200) aerosol sensor platform as a successful solution for supporting remote laboratories on air quality for environmental engineering courses in Spring 2021, and continued for in-person classes in Spring 2022. This sensor platform, called HazeL (Haze Laser Sensor), consists of an externally mounted aerosol sensor, a GPS receiver, and temperature and pressure sensors coupled to an Arduino MKR WiFi 1010 microcontroller connected via a Grove system. Using a project-based learning approach and implementing the scientific method, students worked asynchronously to design experiments, collect aerosol measurements, and analyze and visualize data using the R programming language. Students generated hypotheses regarding factors affecting air pollution, measured >= 0.3 mu m particles in different locations, tested differences between samples, and rejected the null hypothesis if appropriate. HazeL was also used for projects on data processing and statistical inference in an upper-level computational course. We present an instructional guide on manufacturing the HazeL platform and using it as a teaching tool for enhancing student experiential learning, participation, and engagement.

Black carbon aerosol reductions during COVID-19 confinement quantified by aircraft measurements over Europe

The abrupt reduction in human activities during the first lockdown of the COVID-19 pandemic created unprecedented atmospheric conditions. To quantify the changes in lower tropospheric air pollution, we conducted the BLUESKY aircraft campaign and measured vertical profiles of black carbon (BC) aerosol particles over western and southern Europe in May and June 2020. We compared the results to similar measurements of the EMeRGe EU campaign performed in July 2017 and found that the BC mass concentrations (MBC) were reduced by about 48%. For BC particle number concentrations, we found comparable reductions. Based on ECHAM/MESSy Atmospheric Chemistry (EMAC) chemistry-transport model simulations, we found differences in meteorological conditions and flight patterns responsible for about 7% of the MBC reductions. Accordingly 41% of MBC reductions can be attributed to reduced anthropogenic emissions. Our results reflect the strong and immediate positive effect of changes in human activities on air quality and the atmospheric role of BC aerosols as a major air pollutant in the Anthropocene.

Disentangling drivers of air pollutant and health risk changes during the COVID-19 lockdown in China.

The COVID-19 restrictions in 2020 have led to distinct variations in NO2 and O3 concentrations in China. Here, the different drivers of anthropogenic emission changes, including the effects of the Chinese New Year (CNY), China's 2018-2020 Clean Air Plan (CAP), and the COVID-19 lockdown and their impact on NO2 and O3 are isolated by using a combined model-measurement approach. In addition, the contribution of prevailing meteorological conditions to the concentration changes was evaluated by applying a machine-learning method. The resulting impact on the multi-pollutant Health-based Air Quality Index (HAQI) is quantified. The results show that the CNY reduces NO2 concentrations on average by 26.7% each year, while the COVID-lockdown measures have led to an additional 11.6% reduction in 2020, and the CAP over 2018-2020 to a reduction in NO2 by 15.7%. On the other hand, meteorological conditions from 23 January to March 7, 2020 led to increase in NO2 of 7.8%. Neglecting the CAP and meteorological drivers thus leads to an overestimate and underestimate of the effect of the COVID-lockdown on NO2 reductions, respectively. For O3 the opposite behavior is found, with changes of +23.3%, +21.0%, +4.9%, and -0.9% for CNY, COVID-lockdown, CAP, and meteorology effects, respectively. The total effects of these drivers show a drastic reduction in multi-air pollutant-related health risk across China, with meteorology affecting particularly the Northeast of China adversely. Importantly, the CAP's contribution highlights the effectiveness of the Chinese government's air-quality regulations on NO2 reduction.

Impact of COVID-19 Pandemic Preventing Measures and Meteorological Conditions on the Atmospheric Air Composition in Moscow in 2020

Changes in the atmospheric composition during different periods of 2020 in Moscow which were associated with the COVID-19 pandemic preventing measures as well as corresponding pollutant emission reduction, are investigated. Surface concentrations of nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3), aerosol fraction (PM10), and meteorological parameters during different periods of 2020 were compared with similar data for the previous five years. The analysis of ground-based measurements, as well as of high-resolution satellite distributions of CO and NO2 indicated that the concentration of major pollutants and its spatial distribution in the Moscow region were significantly affected by both restrictive measures and abnormal meteorological conditions in 2020.

Diesel passenger vehicle shares influenced COVID-19 changes in urban nitrogen dioxide pollution

Diesel-powered vehicles emit several times more nitrogen oxides than comparable gasoline-powered vehicles, leading to ambient nitrogen dioxide (NO2) pollution and adverse health impacts. The COVID-19 pandemic and ensuing changes in emissions provide a natural experiment to test whether NO2 reductions have been starker in regions of Europe with larger diesel passenger vehicle shares. Here we use a semi-empirical approach that combines in-situ NO2 observations from urban areas and an atmospheric composition model within a machine learning algorithm to estimate business-as-usual NO2 during the first wave of the COVID-19 pandemic in 2020. These estimates account for the moderating influences of meteorology, chemistry, and traffic. Comparing the observed NO2 concentrations against business-as-usual estimates indicates that diesel passenger vehicle shares played a major role in the magnitude of NO2 reductions. European cities with the five largest shares of diesel passenger vehicles experienced NO2 reductions ∼2.5 times larger than cities with the five smallest diesel shares. Extending our methods to a cohort of non-European cities reveals that NO2 reductions in these cities were generally smaller than reductions in European cities, which was expected given their small diesel shares. We identify potential factors such as the deterioration of engine controls associated with older diesel vehicles to explain spread in the relationship between cities’ shares of diesel vehicles and changes in NO2 during the pandemic. Our results provide a glimpse of potential NO2 reductions that could accompany future deliberate efforts to phase out or remove passenger vehicles from cities.

Stereoscopic Monitoring: A Promising Strategy to Advance Diagnostic and Prediction of Air Pollution

Monitoring and modeling/predicting air pollution are crucial to understanding the links between emissions and air pollution levels, to supporting air quality management, and to reducing human exposure. Yet, current monitoring networks and modeling capabilities are unfortunately inadequate to understand the physical and chemical processes above ground and to support attribution of sources. We highlight the need for the development of an international stereoscopic monitoring strategy that can depict three-dimensional (3D) distribution of atmospheric composition to reduce the uncertainties and to advance diagnostic understanding and prediction of air pollution. There are three reasons for the implementation of stereoscopic monitoring: 1) current observation networks provide only partial view of air pollution, and this can lead to misleading air quality management actions;2) satellite retrievals of air pollutants are widely used in air pollution studies, but too often users do not acknowledge that they have large uncertainties, which can be reduced with measurements of vertical profiles;and 3) air quality modeling and forecasting require 3D observational constraints. We call on researchers and policymakers to establish stereoscopic monitoring networks and share monitoring data to better characterize the formation of air pollution, optimize air quality management, and protect human health. Future directions for advancing monitoring and modeling/predicting air pollution are also discussed.