Surface ozone and carbon monoxide levels observed at Oki, Japan: regional air pollution trends in East Asia

A Geo-AI-based ensemble mixed spatial prediction model with fine spatial-temporal resolution for estimating daytime/nighttime/daily average ozone concentrations variations in Taiwan

High levels of ground level ozone (O₃) are associated with detrimental health concerns. Most of the studies only focused on daily average and daytime trends due to the presence of sunlight that initiates its formation. However, atmospheric chemical reactions occur all day, thus, nighttime concentrations should be given equal importance. In this study, geospatial-artificial intelligence (Geo-AI) which combined kriging, land use regression (LUR), machine learning, an ensemble learning, was applied to develop ensemble mixed spatial models (EMSMs) for daily, daytime, and nighttime periods. These models were used to estimate the long-term O₃ spatio-temporal variations using a two-decade worth of in-situ measurements, meteorological parameters, geospatial predictors, and social and season-dependent factors. From the traditional LUR approach, the performance of EMSMs improved by 60% (daytime), 49% (nighttime), and 57% (daily). The resulting daily, daytime, and nighttime EMSMs had a high explanatory power with and adjusted R² of 0.91, 0.91, and 0.88, respectively. Estimation maps were produced to examine the changes before and during the implementation of nationwide COVID-19 restrictions. These results provide accurate estimates and its diurnal variation that will support pollution control measure and epidemiological studies.

Unexpected rise of ozone in urban and rural areas, and sulfur dioxide in rural areas during the coronavirus city lockdown in Hangzhou, China: implications for air quality

The outbreak of coronavirus named COVID-19, initially identified in Wuhan, China in December 2019, has spread rapidly at the global scale. Most countries have rapidly stopped almost all activities including industry, services and transportation of goods and people, thus decreasing air pollution in an unprecedented way, and providing a unique opportunity to study air pollutants. While satellite data have provided visual evidence for the global reduction in air pollution such as nitrogen dioxide (NO₂) worldwide, precise and quantitative information is missing at the local scale. Here we studied changes in particulate matter (PM_2.5, PM₁₀), carbon monoxide (CO), NO₂, sulfur dioxide (SO₂) and ozone (O₃) at 10 urban sites in Hangzhou, a city of 7.03 million inhabitants, and at 1 rural site, before city lockdown, January 1-23, during city lockdown, January 24-February 15, and during resumption, February 16-28, in 2020. Results show that city lockdown induced a sharp decrease in PM_2.5, PM₁₀, CO, and NO₂ concentrations at both urban and rural sites. The NO₂ decrease is explained by reduction in traffic emissions in the urban areas, and by lower regional transport in rural areas during lockdown, as expected. SO₂ concentrations decreased from 6.3 to 5.3 μg m^-3 in the city, but increased surprisingly from 4.7 to 5.8 μg m^-3 at the rural site: this increase is attributed both to higher coal consumption for heating and emissions from traditional fireworks of the Spring Eve and Lantern Festivals during lockdown. Unexpectedly, O₃ concentrations increased by 145% from 24.6 to 60.6 μg m^-3 in the urban area, and from 42.0 to 62.9 μg m^-3 in the rural area during the lockdown. This finding is explained by the weakening of chemical titration of O₃ by NO due to reductions of NO_x fresh emissions during the non-photochemical reaction period from 20:00 PM to 9:00 AM (local time). During the lockdown, compared to the same period in 2019, the daily average concentrations in the city decreased by 42.7% for PM_2.5, 47.9% for PM₁₀, 28.6% for SO₂, 22.3% for CO and 58.4% for NO₂, which is obviously explained by the absence of city activities. Overall, we observed not only the expected reduction in some atmospheric pollutants (PM, SO₂, CO, NO₂), but also unexpected increases in SO₂ in the rural areas and of ozone (O₃) in both urban and rural areas, the latter being paradoxically due to the reduction in nitrogen oxide levels. In other words, the city lockdown has improved air quality by reducing PM_2.5, PM₁₀, CO, and NO₂, but has also decreased air quality by augmenting O₃ and SO₂.

Spatiotemporal Distribution of PM2.5 and O3 and Their Interaction During the Summer and Winter Seasons in Beijing, China

This study analyzed the spatiotemporal variations in PM2.5 and O3, and explored their interaction in the summer and winter seasons in Beijing. To this aim, hourly PM2.5 and O3 data for 35 air quality monitoring sites were analyzed during the summer and winter of 2016. Results suggested that the highest PM2.5 concentration and the lowest O3 concentration were observed at traffic monitoring sites during the two seasons. A statistically significant (p < 0.05) different diurnal variation of PM2.5 was observed between the summer and winter seasons, with higher concentrations during daytime summer and nighttime winter. Diurnal variations of O3 concentrations during the two seasons showed a single peak, occurring at 16:00 and 15:00 in summer and winter, respectively. PM2.5 presented a spatial pattern with higher concentrations in southern Beijing than in northern areas, particularly evident during wintertime. On the contrary, O3 concentrations presented a decreasing spatial trend from the north to the south, particularly evident during summer. In addition, we found that PM2.5 concentrations were positively correlated (p < 0.01, r = 0.57) with O3 concentrations in summer, but negatively correlated (p < 0.01, r = −0.72) with O3 concentrations in winter.

Seasonal trends, meteorological impacts, and associated health risks with atmospheric concentrations of gaseous pollutants at an Indian coastal city

This study presents surface ozone (O3) and carbon monoxide (CO) measurements conducted at Bhubaneswar from December 2010 to November 2012 and attempts for the very first time a health risk assessment of the atmospheric trace gases. Seasonal variation in average 24 h O3 and CO shows a distinct winter (December to February) maxima of 38.98 ± 9.32 and 604.51 ± 145.91 ppbv, respectively. O3 and CO characteristics and their distribution were studied in the form of seasonal/diurnal variations, air flow patterns, inversion conditions, and meteorological parameters. The observed winter high is likely due to higher regional emissions, the presence of a shallower boundary layer, and long-range transport of pollutants from the Indo-Gangetic Plain (IGP). Large differences between daytime and nighttime O3 values during winter compared to other seasons suggest that photochemistry is much more active on this site during winter. O3 and CO observations are classified in continental and marine air masses, and continental influence is estimated to increase O3 and CO by up to 20 and 120 ppbv, respectively. Correlation studies between O3 and CO in various seasons indicated the role of CO as one of the O3 precursors. Health risk estimates predict 48 cases of total premature mortality in adults due to ambient tropospheric O3 during the study period. Comparatively low CO concentrations at the site do not lead to any health effects even during winter. This study highlights the possible health risks associated with O3 and CO pollution in Bhubaneswar, but these results are derived from point measurements and should be complemented either with regional scale observations or chemical transport models for use in design of mitigation policies.