Air Quality Analysis in the European Union

Huete-Morales, María Dolores; Quesada-Rubio, José Manuel; Navarrete-Álvarez, Esteban; Rosales-Moreno, María Jesús; Del-Moral-Ávila, María José

doi:10.15244/pjoes/67530

Cited by 4 publications

(2 citation statements)

References 12 publications

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“…Air pollution as a consequence of smog in big cities was discussed and modeled in [36][37][38][39][40]. The broad impact of different pollutants on the health of living organisms in different places of the world was discussed in [41][42][43][44][45][46]. The wide spectrum of modeling was discussed in [47], taking into consideration aspects of chemistry and meteorology as well different timescales with seasonal variation.…”

Section: Models Of Air Pollution Propagationmentioning

confidence: 99%

Models of Air Pollution Propagation in the Selected Region of Katowice

2021

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The paper deals with issues related to analyzing the spread of air pollution and pollutants in large urban agglomerations, specifically, the search for causality between meteorological conditions and the concentrations of particular substances. The pollutants SO2 and PM10 were selected for analysis, which, in addition to NOx, CO, CO2 and PM2.5, contribute to smog, especially during the heating seasons. This analysis is particularly important because Polish environmental standards are more lenient than those in western EU states. Industrial activity, transport and heating systems based on coal-burning are still a big problem in Poland, and each year their gaseous and particulate emissions exceed air-quality limits. This paper presents a statistical analysis of data recorded at the air-quality monitoring station on Kossuth Street in Katowice concerning the heating seasons from 2013–2016. The verification of proposed parabolic models containing concentrations from previous time periods and statistically significant meteorological conditions was conducted for individual heating seasons as well for the whole set of data, which included the influence of wind speed and temperature. The models obtained proved that the selected form of a model is statistically significant, and its use may produce satisfactory forecast results and permit various environmental applications. The specified model might be used both for forecasting (verification and possibly updating coefficients to increase forecast accuracy) and analyzing the factors influencing pollution values. Such statistical analysis may be helpful in assessing the impact of measures adopted to reduce air pollution, particularly in large Polish cities.

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Section: Models Of Air Pollution Propagationmentioning

confidence: 99%

Models of Air Pollution Propagation in the Selected Region of Katowice

2021

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“…Epidemiological studies have shown that longterm exposure to ambient air pollution is harmful to human health [1][2][3][4]. Population exposure to air pollutants especially the fine particulate matter (PM 2.5 ), will lead to significant adverse impacts on morbidity and mortality [5,6].…”

Section: Introductionmentioning

confidence: 99%

High-Resolution Population Exposure to PM<sub>2.5</sub> in Nanchang Urban Region Using Multi-Source Data

Yang¹,

Guo²,

Leng³

2021

Pol. J. Environ. Stud.

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Long-term exposure to PM 2.5 can lead to great adverse health effect on human health. To better guide public policies that aim to reduce PM 2.5 population exposure, this work combined multi-source data to realize high-resolution PM 2.5 exposure risk assessment in Nanchang urban region. The land use regression (LUR) model was used to simulate the seasonal-spatial variations of PM 2.5 concentrations at 100-m resolution, and building information extracted from IKONOS image was applied to spatialize population at 100-m resolution. An improved piece-wise population exposure approach was introduced to evaluate the exposure risk, and results were compared with two classical approaches. In all seasons, results by the absolute concentration approach are very different from the other two, showing obvious spatial smoothing effect. Results by population-weighted and piece-wise exposure approaches are similar in spring and autumn, and different in summer and winter. In winter, the area and population percentages divided to severity level 7 by population-weighted exposure approach are 5.21% and 2.35% lower than that by piece-wise exposure approach. When in summer, the area and population percentages divided to severity level 7 by population-weighted exposure approach are 6.77% and 24.79% higher than that by piece-wise exposure approach. The absolute concentration approach is disadvantageous for the identification of high-risk areas, the population-weighted exposure approach would underestimate or overestimate the population exposure when air is seriously polluted or remarkably clean, and the proposed piece-wise exposure approach would be more reasonable. The integrated methodology is effective in exposure risk assessment and can be applied to other regions and pollutants.

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