Observation-Based Diagnostics of Reactive Nitrogen Recycling through HONO Heterogenous Production: Divergent Implications for Ozone Production and Emission Control.

Understanding of nitrous acid (HONO) production is crucial to photochemical studies, especially in polluted environments like eastern China. In-situ measurements of gaseous and particulate compositions were conducted at a rural coastal site during the 2018 spring Ozone Photochemistry and Export from China Experiment (OPECE). This data set was applied to investigate the recycling of reactive nitrogen through daytime heterogeneous HONO production. Although HONO levels increase during agricultural burning, analysis of the observation data does not indicate more efficient HONO production by agricultural burning aerosols than other anthropogenic aerosols. Box and 1-D modeling analyses reveal the intrinsic relationships between nitrogen dioxide (NO2), particulate nitrate (pNO3), and nitric acid (HNO3), resulting in comparable agreement between observed and simulated HONO concentrations with any one of the three heterogeneous HONO production mechanisms, photosensitized NO2 conversion on aerosols, photolysis of pNO3, and conversion from HNO3. This finding underscores the uncertainties in the mechanistic understanding and quantitative parametrizations of daytime heterogeneous HONO production pathways. Furthermore, the implications for reactive nitrogen recycling, ozone (O3) production, and O3 control strategies vary greatly depending on the HONO production mechanism. On a regional scale, the conversion of HONO from pNO3 can drastically enhance O3 production, while the conversion from NO2 can reduce O3 sensitivity to NOx changes in polluted eastern China.

Chemical Production of Oxygenated Volatile Organic Compounds Strongly Enhances Boundary-Layer Oxidation Chemistry and Ozone Production.

Photolysis of oxygenated volatile organic compounds (OVOCs) produces a primary source of free radicals, including OH and inorganic and organic peroxy radicals (HO2 and RO2), consequently increasing photochemical ozone production. The amplification of radical cycling through OVOC photolysis provides an important positive feedback mechanism to accelerate ozone production. The large production of OVOCs near the surface helps promote photochemistry in the whole boundary layer. This amplifier effect is most significant in regions with high nitrogen oxides (NOx) and VOC concentrations such as Wangdu, China. Using a 1-D model with comprehensive observations at Wangdu and the Master Chemical Mechanism (MCM), we find that OVOC photolysis is the largest free-radical source in the boundary layer (46%). The condensed chemistry mechanism we used severely underestimates the OVOC amplifier effect in the boundary layer, resulting in a lower ozone production rate sensitivity to NOx emissions. Due to this underestimation, the model-simulated threshold NOx emission value, below which ozone production decreases with NOx emission decrease, is biased low by 24%. The underestimated OVOC amplifier effect in a condensed mechanism implies a low bias in the current 3-D model-estimated efficacy of NOx emission reduction on controlling ozone in polluted urban and suburban regions of China.

COVID-19 Impact on the Concentration and Composition of Submicron Particulate Matter in a Typical City of Northwest China.

In this study, we evaluated the variations of air quality in Lanzhou, a typical city in Northwestern China impacted by the COVID-19 lockdown. The mass concentration and chemical composition of non-refractory submicron particulate matter (NR-PM1) were determined by a high-resolution aerosol mass spectrometer during January-March 2020. The concentration of NR-PM1 dropped by 50% from before to during control period. The five aerosol components (sulfate, nitrate, ammonium, chloride, and organic aerosol [OA]) all decreased during the control period with the biggest decrease observed for secondary inorganic species (70% of the total reduction). Though the mass concentration of OA decreased during the control period, its source emissions varied differently. OA from coal and biomass burning remained stable from before to during control period, while traffic and cooking related emissions were reduced by 25% and 50%, respectively. The low concentration during the control period was attributed to the lower production rate for secondary aerosols.

Comprehensive evaluations of diurnal NO2 measurements during DISCOVER-AQ 2011: effects of resolution-dependent representation of NO x emissions.

Nitrogen oxides (NO x =NO+NO2) play a crucial role in the formation of ozone and secondary inorganic and organic aerosols, thus affecting human health, global radiation budget, and climate. The diurnal and spatial variations in NO2 are functions of emissions, advection, deposition, vertical mixing, and chemistry. Their observations, therefore, provide useful constraints in our understanding of these factors. We employ a Regional chEmical and trAnsport model (REAM) to analyze the observed temporal (diurnal cycles) and spatial distributions of NO2 concentrations and tropospheric vertical column densities (TVCDs) using aircraft in situ measurements and surface EPA Air Quality System (AQS) observations as well as the measurements of TVCDs by satellite instruments (OMI: the Ozone Monitoring Instrument; GOME-2A: Global Ozone Monitoring Experiment - 2A), ground-based Pandora, and the Airborne Compact Atmospheric Mapper (ACAM) instrument in July 2011 during the DISCOVER-AQ campaign over the Baltimore-Washington region. The model simulations at 36 and 4 km resolutions are in reasonably good agreement with the regional mean temporospatial NO2 observations in the daytime. However, we find significant overestimations (underestimations) of model-simulated NO2 (O3) surface concentrations during night-time, which can be mitigated by enhancing nocturnal vertical mixing in the model. Another discrepancy is that Pandora-measured NO2 TVCDs show much less variation in the late afternoon than simulated in the model. The higher-resolution 4 km simulations tend to show larger biases compared to the observations due largely to the larger spatial variations in NO x emissions in the model when the model spatial resolution is increased from 36 to 4 km. OMI, GOME-2A, and the high-resolution aircraft ACAM observations show a more dispersed distribution of NO2 vertical column densities (VCDs) and lower VCDs in urban regions than corresponding 36 and 4 km model simulations, likely reflecting the spatial distribution bias of NO x emissions in the National Emissions Inventory (NEI) 2011.

Modeling Reading Ability Gain in Kindergarten Children during COVID-19 School Closures.

By 15 April 2020, more than 1.5 billion students worldwide experienced school closures in an effort to slow the spread of a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), during the worldwide coronavirus disease 2019 (COVID-19) pandemic. These interruptions in formal in-person educational experiences caused adverse consequences on school-age children's academic outcomes. Using a pre-existing database, we calculated changes in children's reading ability without formal education (i.e., the summer months). The resultant models predicted that the rate of reading ability gain in kindergarten children during COVID-19 school closures without formal in-person education will decrease 66% (2.46 vs. 7.17 points/100 days), compared to the business-as-usual scenario, resulting in a 31% less reading ability gain from 1 January 2020 to 1 September 2020. Additionally, the model predicted that kindergarten children who have books read to them daily would have 2.3 points less loss (42%) compared to those who do not, who are predicted to have a 5.6-point loss during the same time period. Even though reading books to children will not substitute the critical role of formal education in teaching children how to read, families, educators, and policy makers can promote this simple strategy to facilitate and maintain reading ability gain during school closures, which may be a common occurrence as nations see the public health benefits of physical distancing for the current and future pandemic outbreaks.

Quantifying methane emissions from the largest oil-producing basin in the United States from space.

Using new satellite observations and atmospheric inverse modeling, we report methane emissions from the Permian Basin, which is among the world's most prolific oil-producing regions and accounts for >30% of total U.S. oil production. Based on satellite measurements from May 2018 to March 2019, Permian methane emissions from oil and natural gas production are estimated to be 2.7 ± 0.5 Tg a-1, representing the largest methane flux ever reported from a U.S. oil/gas-producing region and are more than two times higher than bottom-up inventory-based estimates. This magnitude of emissions is 3.7% of the gross gas extracted in the Permian, i.e., ~60% higher than the national average leakage rate. The high methane leakage rate is likely contributed by extensive venting and flaring, resulting from insufficient infrastructure to process and transport natural gas. This work demonstrates a high-resolution satellite data-based atmospheric inversion framework, providing a robust top-down analytical tool for quantifying and evaluating subregional methane emissions.