Analysis of Air quality in Poland from the period 2013 to 2022

Eng. Rojadasan Rajendran, B.E. BE (mechanical)

Master's thesis

Abstract:

Abstract The thesis "Analysis of Air Quality in Poland from 2013 to 2022" seeks to provide a comprehensive overview of Poland's air quality situation over the selected time period. The study will concentrate on essential components of air pollution, such as industrial emissions, transportation, home heating, and coal burning. Particulate matter (PM2.5 and PM10), nitrogen oxides (NOx), nitrogen dioxide (NO2), sulphur dioxide (SO2), and ozone (O3) are among the primary pollutants being addressed. The first part of the study sets up a solid method for combining data from many sources, such as national air quality tracking networks, satellite observations, meteorological datasets, emission inventories, and health statistics. This also assesses the effectiveness of environmental policies, regulatory measures, and technological interventions made throughout the study period to reduce air pollution and enhance air quality in Poland. It involves assessing how emission reduction plans, fuel quality standards, car emission norms, industry emissions regulations, urban planning policies, green programmes, and renewable energy transitions affect air quality trends. At the end of the thesis, there are suggestions based on data that will help Poland improve its strategies for managing air quality, reducing pollution, and promoting sustainable development. The suggestions include ways to encourage cleaner transportation, switch to renewable energy sources, support green technologies, raise public knowledge, and make it easier for agencies to work together and involve stakeholders. Methodology Methodology is a planned approach that combines different types of data, study methods, and analytical techniques. First, the study will gather past data on air quality from reliable sources like the European Environment Agency (EEA), state environmental agencies, and monitoring stations all over Poland. Important air pollution like PM2.5, PM10, NO2, NOx, SO2, and O3 will be measured, along with weather conditions like temperature, humidity, wind speed, and atmospheric pressure. After validating the data, the study will utilise statistical analytic methods including time series analysis, trend analysis, correlation analysis, and regression modelling to investigate temporal patterns, seasonal changes, and connections between air pollutants and factors that influence them. The data will be summarised and visualised using descriptive statistics, graphical representations such as charts, graphs, and maps, as well as statistical tests. These methods will aid in the identification of trends, outliers, and deviations, ultimately leading to the generation of useful insights. In addition to qualitative analysis, the thesis will use qualitative research methods such as literature reviews, case studies and policy document analysis in order to explain the qualitative findings, better understand the broader environmental and socioeconomic context, and assess the impact of environmental policies and interventions on air quality. Furthermore, the study will use a comparative approach to analyse air quality trends and levels among regions, urban versus rural areas, industrialised zones versus residential areas, and predetermined time periods within the study period. This comparison analysis will aid in identifying regional disparities, pollution sources, and the effectiveness of pollution control approaches across diverse environments. Conclusion To sum up, the regression model's economic verification has illuminated a number of variables affecting air quality and their possible financial effects. Though the statistical significance of the correlations varies, the coefficient analysis shows interesting relationships between economic indicators and air pollution levels. Though more research is necessary due to the lack of statistical significance, the positive correlation between GDP per capita and the Air Quality Index (AQI) raises the possibility of a connecti

Abstract:

on between economic prosperity and air pollution. In a similar vein, the weak correlation and negligible p-value found between GDP per capita and air quality highlight the necessity of examining more variables in order to fully comprehend the relationship between the two. However, the negative coefficients linked to motor vehicles especially passenger cars highlight the adverse effect that vehicle emissions have on air quality, and their statistical significance indicates the pressing need for policy changes. Air pollution may be mitigated by policies that support alternative modes of transportation and lower vehicle emissions. In addition, the marginal increase in air pollution linked to energy use emphasises how critical it is to investigate energy-efficient technologies and renewable energy sources. The coefficient pertaining to industrial emissions suggests that there is a noteworthy influence on air quality, underscoring the necessity of stricter regulations and more environmentally friendly production methods to tackle industrial pollution. Furthermore, the existence of multicollinearity among explanatory variables demands that model interpretation and refinement be done with great care. Strategies like variable selection, transformation, or regularisation can improve the model's interpretability and stability, which will increase the model's accuracy in forecasting air quality results. In conclusion, the results highlight the intricate relationship that exists between environmental sustainability and economic development, which highlights the need for integrated urban planning techniques. Societies can work towards striking a healthy balance between environmental preservation and economic growth by addressing the detrimental effects on air quality through focused policies and interventions.

Keywords

Emissions, Pollutants, Climate change, Health impacts, Pandemic

Jazyk práce: English

Datum vytvoření / odevzdání či podání práce: 31. 3. 2024

Obhajoba závěrečné práce

• Vedúci: doc. Ing. Petr Procházka, MSc Ph.D.
• Oponent: Vladimír Hönig, externi

Czech University of Life Sciences Prague

Faculty of Economics and Management

Master programme:
Economics and Management