ABSTRACT
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.
ABSTRACT
The COVID-19 pandemic has posed a challenge for maintaining an engaging learning environment while using remote laboratory formats. In this work, we describe a Student Choice Project (SCP) in an undergraduate instrumental analysis course that was adapted for remote learning without sacrificing research-based learning goals. We discuss the implementation and assessment of this SCP, selected student results, and student feedback. Students were provided handheld carbon dioxide monitors and charged with designing and implementing an investigation centered on COVID-19 airborne transmission. The real-time monitors provided experience with a new analytical tool that demanded considerations and analysis not common to other methods discussed in the course. Students were motivated by the ability to design their own projects and by the real-world implications of their findings. They performed well for all assessments, reported a positive experience, and recommended these monitors be added to the typical repertoire of instrumentation for the course.
ABSTRACT
The outbreak of COVID-19 promoted strict restrictions to human activities in China, which led to a dramatic decrease in most air pollutant concentrations (e.g., PM2.5, PM10, NOx, SO2 and CO). However, an obvious increase in ozone (O3) concentrations was found during the lockdown period in most urban areas of China. In this study, we conducted field measurements targeting ozone and its key precursors by utilizing a novel proton transfer reaction time-of-flight mass spectrometer (PTR-TOF-MS) in Changzhou, which is representative of the Yangtze River Delta (YRD) city cluster of China. We further applied the integrated methodology including machine learning, an observation-based model (OBM) and sensitivity analysis to obtain insights into the reasons causing the obvious increase in ozone. Major findings include the following: (1) by deweathered calculation, we found changes in precursor emissions contributed 1.46 ppbv to the increase in the observed O3 during the full-lockdown period in 2020, while meteorology constrained 3.0 ppbv of O3 in the full-lockdown period of 2019. (2) By using an OBM, we found that although a significant reduction in O3 precursors was observed during the full-lockdown period, the photochemical formation of O3 was stronger than that during the pre-lockdown period. (3) The NOx/VOC ratio dropped dramatically from 1.84 during the pre-lockdown to 0.79 in the full-lockdown period, which switched O3 formation from a VOC-limited regime to the boundary of a NOx- and VOC-limited regime. Additionally, box model results suggested that the decrease in the NOx/VOC ratio during the full-lockdown period could increase the mean O3 by 2.4 ppbv. Results of this study give insights into the relationship between O3 and its precursors in urban area and demonstrate reasons for the obvious increase in O3 in most urban areas of China during the COVID-19 lockdown period. This study also underlines the necessity of controlling anthropogenic oxygenated volatile organic compounds (OVOCs), alkenes and aromatics in the sustained campaign of reducing O3 pollution in China.
ABSTRACT
The COVID-19 outbreak in 2020 prompted strict lockdowns, reduced human activity, and reduced emissions of air pollutants. We measured volatile organic compounds (VOCs) using a proton-transfer-reaction mass spectrometry instrument in Changzhou, China from 8 January through 27 March, including periods of pre-lockdown, strict measures (level 1), and more relaxed measures (level 2). We analyze the data using positive matrix factorization and resolve four factors: textile industrial emissions (62 ± 10% average reduction during level 1 relative to pre-lockdown), pharmaceutical industrial emissions (40 ± 20%), traffic emissions (71 ± 10%), and secondary chemistry (20 ± 20%). The two industrial sources showed different responses to the lockdown, so emissions from the industrial sector should not be scaled uniformly. The quantified changes in VOCs due to the lockdowns constrain emission inventories and inform chemistry-transport models, particularly for sectors where activity data are sparse, as the effects of lockdowns on air quality are explored.
ABSTRACT
The COVID-19 global pandemic and associated government lockdowns dramatically altered human activity, providing a window into how changes in individual behavior, enacted en masse, impact atmospheric composition. The resulting reductions in anthropogenic activity represent an unprecedented event that yields a glimpse into a future where emissions to the atmosphere are reduced. Furthermore, the abrupt reduction in emissions during the lockdown periods led to clearly observable changes in atmospheric composition, which provide direct insight into feedbacks between the Earth system and human activity. While air pollutants and greenhouse gases share many common anthropogenic sources, there is a sharp difference in the response of their atmospheric concentrations to COVID-19 emissions changes, due in large part to their different lifetimes. Here, we discuss several key takeaways from modeling and observational studies. First, despite dramatic declines in mobility and associated vehicular emissions, the atmospheric growth rates of greenhouse gases were not slowed, in part due to decreased ocean uptake of CO2 and a likely increase in CH4 lifetime from reduced NO x emissions. Second, the response of O3 to decreased NO x emissions showed significant spatial and temporal variability, due to differing chemical regimes around the world. Finally, the overall response of atmospheric composition to emissions changes is heavily modulated by factors including carbon-cycle feedbacks to CH4 and CO2, background pollutant levels, the timing and location of emissions changes, and climate feedbacks on air quality, such as wildfires and the ozone climate penalty.