Identifying the contributions of chemistry and transport to observed ozone pollution using regional-to-global models relies on accurate representation of ozone dry deposition. We use a recently developed configuration of the NOAA GFDL chemistry-climate model -in which the atmosphere and land are coupled through dry deposition-to investigate the influence of ozone dry deposition on ozone pollution over northern midlatitudes. In our model, deposition pathways are tied to dynamic terrestrial processes, such as photosynthesis and water cycling through the canopy and soil. Small increases in winter deposition due to more process-based representation of snow and deposition to surfaces reduce hemispheric-scale ozone throughout the lower troposphere by 5-12 ppb, improving agreement with observations relative to a simulation with the standard configuration for ozone dry deposition. Declining snow cover by the end of the 21st-century tempers the previously identified influence of rising methane on winter ozone. Dynamic dry deposition changes summer surface ozone by −4 to +7 ppb. While previous studies emphasize the importance of uptake by plant stomata, new diagnostic tracking of depositional pathways reveals a widespread impact of nonstomatal deposition on ozone pollution. Daily variability in both stomatal and nonstomatal deposition contribute to daily variability in ozone pollution. Twenty-first century changes in summer deposition result from a balance among changes in individual pathways, reflecting differing responses to both high carbon dioxide (through plant physiology versus biomass accumulation) and water availability. Our findings highlight a need for constraints on the processes driving ozone dry deposition to test representation in regional-to-global models.

Preliminary analysis of satellite measurements from around the world showed drops in nitrogen dioxide (NO2) with lockdowns due to the COVID-19 pandemic. 1 A number of studies have found these drops to be correlated with local decreases in transportation and/or industry. None of these studies, however, has rigorously quantified the statistical significance of these drops relative to natural meteorological variability and other factors that influence pollutant levels during similar time periods in previous years. Here, we develop a novel statistical testing framework that accounts for seasonal variability, transboundary influences, and new factors such as COVID-19 restrictions in explaining trends in several pollutant levels at 16 ground-based measurement sites in Southern Ontario, Canada. We find statistically significant and temporary drops in NO2 (11 out 16 sites) and CO (all 4 sites) in April-June 2020, with pollutant levels 20% lower than in the previous three years.Much fewer sites (2-3 out of 16) experienced statistically significant drops in O3 and PM2.5. The statistical testing framework developed here is the first of its kind applied to air quality data, and highlights the need for rigorous assessment of statistical significance, should analyses of pollutant level changes post COVID-19 lockdowns be used to inform policy decisions in Ontario, Canada.

The Region of Waterloo is the third fastest growing region in Southern Ontario in Canada with a population of 619,000 as of 2019. However, only one air quality monitoring station, located in a city park in Kitchener, Ontario, is currently being used to assess the air quality of the region. In September 2020, a network of AQMesh Multisensor Mini Monitoring Stations (pods) were installed near elementary schools in Kitchener located near different types of emission source. Data analysis using a custom-made long-distance scaling software showed that the levels of nitrogen oxides (NO and NO2), ground level ozone (O3), and fine particulate matter (PM2.5) were traffic related. These pollutants were used to calculate the Air Quality Health Index-Plus (AQHI+) at each location, highlighting the inability of the provincial air quality monitoring station to detect hotspot areas in the city. The case study presented here quantified the impact of the 2021 summer wildfires on the local air quality at a high time resolution (15-min). The findings in this article show that these multisensor pods are a viable alternative to expensive research-grade equipment. The results highlight the need for networks of local scale air quality measurements, particularly in fast-growing cities in Canada.

Thiocyanate ion (SCN-) levels were determined for the hypocotyl-root region of Raphanus sativus. Root tissue of plants grown on organic soil yielded a higher quantity of thiocyanate ion than those grown on loam soil. Also, roots of those plants seeded in early spring yielded a higher quantity of thiocyanate ion than roots of those plants seeded at a later date.

Isothiocyanate levels were determined for the hypocotyl-root region of Raphanus sativus, grown under two daylengths and in three different soil types. Under a short photoperiod (8.5 h) radishes grown in loam soil had the highest isothiocyanate concentration but under a longer photoperiod (15 h) radishes grown in organic soil had the highest isothiocyanate concentration.