Surface Ozone Concentration and Its Relationship with UV Radiation, Meteorological Parameters and Radon on the Eastern Coast of the Baltic Sea

Jasaitis, Dainius; Vasiliauskienė, Vaida; Chadyšienė, Renata; Pečiulienė, Milda

doi:10.3390/atmos7020027

Cited by 34 publications

(16 citation statements)

References 42 publications

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“…With the exception of NO 2 which is likely bimodal in its AM-PM concentration distribution, pollutant levels trended higher in the later hours of the day (after 12 PM) aligning with previous studies as it relates to traffic pollution [83][84][85]. Diurnal significance would however diminish in constructed models.…”

Section: Discussionsupporting

confidence: 85%

Ambient air pollution per specific land use types and activities in an urbanizing Eastern Caribbean Country, St. Kitts and Nevis

Whittaker

Deziel

Zhang

et al. 2020

Environ. Res. Commun.

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Urban development can have negative impacts on the environment through various mechanisms. While many air quality studies have been carried out in more developed nations, Eastern Caribbean (EC) countries remain understudied. This study aims to estimate the concentrations of air pollutants in the EC nation of St. Kitts and Nevis. Transport, recreation and construction sites were selected randomly using local land use records. Pollutant levels were measured repeatedly for numerous 1-hour intervals in each location between October 2015 and November 2018. Weather trends and land use characteristics were collected concurrent to sampling. Across 27 sites, mean NO 2 , O 3 , SO 2 , PM 10 and PM 2.5 levels were 26.61 ppb (range: 0-306 ppb), 11.94 ppb (0-230 ppb), 27.9 ppb (0-700 ppb), 52.9 μg m −3 (0-10,400 μg m −3 ) and 29.8 μg m −3 (0-1556 μg m −3 ), respectively. Pollutants were elevated in high urban areas and generally significantly positively correlated with each other, with the exception of PM 10 . NO 2 levels in construction areas were generally comparable to those in transportation areas and higher than in recreation areas. O 3 levels were lower in construction than recreation and transport areas. SO 2 concentrations were lower in construction and recreation compared to transport sites. Construction and recreation PM 10 levels exceeded transport sites, while PM 2.5 was highest in construction areas. Additional bivariate and multivariate analysis were conducted to assess whether various meteorological, temporal and land use factors including rain, tour season and urban features explained variability in air pollutant concentrations. Tourist season and specific months, more than any other factors, contributed most to variability in pollutant concentrations. These new measurements of air pollution concentrations in an understudied nation may have important implications for health outcomes among exposed EC residents, and provide critical data for future exposure and epidemiologic research and environmental policy.

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Section: Discussionsupporting

confidence: 85%

Ambient air pollution per specific land use types and activities in an urbanizing Eastern Caribbean Country, St. Kitts and Nevis

Whittaker

Deziel

Zhang

et al. 2020

Environ. Res. Commun.

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Section: Introductionmentioning

confidence: 94%

“…The effects of global radiation (GR) on ground-level O 3 through the photochemical reaction have already been established in another work by the author[4]. Other studies have also established GR-O 3 correlation, which ranges from 0.4 to 0.6 (R 2 )[23,24].In recent years there has been a further NO 2 reduction with the increase of EV adherence, such as pure electric battery electric vehicles (BEV) and plug-in hybrid electric vehicles (PHEV), and the application of European emission standards for road transport and internal combustion engine vehicles (ICEV).EV adherence can affect pollutant dynamics and its influence on air quality is seen as beneficial due to the reduced, or nonexistent, combustion of fuel for these types of vehicles while circulating. Therefore, fleet electrification and the stringiest emission regulations, should contribute to the decrease of ground-level O 3 .…”

mentioning

confidence: 96%

Urban Ground-Level O3 Trends: Lessons from Portuguese Cities, 2010–2018

et al. 2021

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Big datasets of air-quality pollutants and weather data allow us to review trends of NO2, NO, O3, and global radiation (GR), for Lisbon, Porto and Coimbra, with regard to the historical period of 2010–2018. GR is expected to have a considerable impact on photochemical reactions of the O3 formation mechanism. We aim to characterize daily, monthly, and yearly trends. We explore Weekday (WD) versus weekend (WE), and seasonality of O3 and NO2. We are interested to know these pollutant peak concentration variations over the years and investigate if parallels can be drawn between urban mobility indicators and these pollutants. For this purpose, economic data, European emission standards, and car stock data (fuel, age, and number of vehicles) are cross-analyzed. How are they correlated? Has it impacted NO2 and O3 variations? How do different air-quality monitoring stations (AQMS), traffic and non-traffic, compare? How is Lisbon NOx-O3 correlated? What are its implications for future scenarios? Results show that urban mobility trends and economic events are correlated with NO2 and O3 variability. Weekend effect has a partial relationship with urban mobility trends and economy as it is relatively well correlated for Lisbon but not for Porto and Coimbra. Nonetheless, weekend effect for the period of 2010–2018 is overall trending upwards for all cities. In Lisbon and Coimbra, O3 concentrations also trend upwards during the same 2010–2018 period but for Porto they do not. Regardless, for the period of 2015–2018, after the economic recession, the upwards trends of both weekend effect and overall O3 concentrations are clear for all AQMS. For AQMS peak values comparison, Lisbon traffic AQMS registered an annual averaged 8-hour daily max O3 concentration of 34.4 ppb while Lisbon non-traffic AQMS presented 39.1 ppb. Altogether, annual 8-hour daily maximum values for 2010–2018 traffic AQMS in Lisbon show an inverse relationship with fuel sales, and have concentrations fluctuating between 28–35 ppb, which is slightly higher than the 2001–2010 historical European range of 27–31 ppb. Lastly, for the 8 years data in Lisbon, it has been shown that a negative NOx-O3 correlation exists, and the study location might be VOC–sensitive. This means that as NOx concentrations decrease, O3 concentrations become exponentially higher. Further research into VOCs with better data availability is required to make more concise claims. Regardless, it can be inferred that in a future scenario where mitigation continues to escalate, through O3 emission standards and an aggressive shift of car stock to electric vehicles, achieving unprecedented rises in O3 concentrations could be observed.

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“…Among them, f trI (s, t) is the quantity of entering cellular pollutants by migration, f trO (s, t) is the quantity of exit cellular pollutants by migration, and the pollutants migration of CA(s, t) is related to the local meteorological W mete 34 and terrain G terr…”

Section: Swarm Intelligence Based Air Pollution Spatiotemporal Evolution Modelmentioning

confidence: 99%

Spatiotemporal Evolution Analysis of NO 2 Column Density before and after COVID-19 Pandemic in Henan Province Based on SI-APSTE Model

Liu,

Zhao,

Song

et al. 2021

Preprint

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Air pollution is the result of comprehensive evolution of a dynamic and complex system composed of emission sources, topography, meteorology and other environmental factors. The establishment of spatiotemporal evolution model is of great significance for the study of air pollution mechanism, trend prediction, identification of pollution sources and pollution control. In this paper, the air pollution system is described based on cellular automata and restricted agents, and a Swarm Intelligence based Air Pollution SpatioTemporal Evolution (SI-APSTE) model is constructed. Then the spatiotemporal evolution analysis method of air pollution is studied. Taking Henan Province before and after COVID-19 pandemic as an example, the NO2 products of TROPOMI and OMI were analysed based on SI-APSTE model. The tropospheric NO2 Vertical Column Densities (VCDs) distribution characteristics of spatiotemporal variation of Henan province before COVID-19 pandemic were studied. Then the tropospheric NO2 VCDs of TROPOMI was used to study the pandemic period, month-on-month and year-on-year in 18 urban areas of Henan Province. The results show that SI-APSTE model can effectively analyse the spatiotemporal evolution of air pollution by using environmental big data and swarm intelligence, and also can establish a theoretical basis for pollution source identification and trend prediction.

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Surface Ozone Concentration and Its Relationship with UV Radiation, Meteorological Parameters and Radon on the Eastern Coast of the Baltic Sea

Cited by 34 publications

References 42 publications

Ambient air pollution per specific land use types and activities in an urbanizing Eastern Caribbean Country, St. Kitts and Nevis

Ambient air pollution per specific land use types and activities in an urbanizing Eastern Caribbean Country, St. Kitts and Nevis

Urban Ground-Level O3 Trends: Lessons from Portuguese Cities, 2010–2018

Spatiotemporal Evolution Analysis of NO 2 Column Density before and after COVID-19 Pandemic in Henan Province Based on SI-APSTE Model

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