The Impact of the COVID-19 Pandemic on Gaseous and Solid Air Pollutants Concentrations and Emissions in the EU, with Particular Emphasis on Poland

Rybak, Aurelia

doi:10.3390/en14113264

Cited by 5 publications

(3 citation statements)

References 35 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Based on the calculation of sensitivity analysis, this section proposes a self-organizing LSTM. The algorithm flow is explained in Algorithm 1: Before training, the hidden layer neurons numbers and network parameters are initialized randomly [36][37][38][39]. Then, the network continuously performs iterative training until the maximum iteration is reached and the output of the loss function has not reached the set threshold ζ(t) = t −0.65 .…”

Section: Prediction Algorithm Based On Self-organizing Lstmmentioning

confidence: 99%

Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China

Yu,

Guan,

Zhu

et al. 2023

Sustainability

View full text Add to dashboard Cite

Urban road green belts, an essential component of Urban Green Space (UGS) planning, are vital in improving the urban environment and protecting public health. This work chooses Long Short-Term Memory (LSTM) to optimize UGS planning and design methods in urban road green belts. Consequently, sensitivity-based self-organizing LSTM shows a Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) of 1.75, 1.12, and 6.06, respectively. These values are superior to those of LSTM, XGBoost, and SVR. Furthermore, we configure three typical plant community models using the improved LSTM model and found that different plant community configurations have distinct effects on reducing PM 2.5 concentrations. The experimental results show that other plant community configuration models have specific effects on reducing PM 2.5 concentrations, and the multi-layered green space with high canopy density in the community has a better impact on PM 2.5 reduction than the single-layer green space model with low canopy density. We also assess the reduction function of green road spaces on PM 2.5, which revealed that under zero pollution or slight pollution (PM 2.5 < 100 μg.m−3), the green space significantly reduces PM 2.5. In UGS planning, the proposed model can help reveal UGS spatial morphology indicators that significantly impact PM 2.5 reduction, thereby facilitating the formulation of appropriate green space planning strategies. The finding will provide primary data for selecting urban road green space plant configuration.

show abstract

Section: Prediction Algorithm Based On Self-organizing Lstmmentioning

confidence: 99%

Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China

Yu,

Guan,

Zhu

et al. 2023

Sustainability

View full text Add to dashboard Cite

show abstract

“…A study in Poland monitored emissions during pandemic phases by defining a heat map, i.e., a graphical illustration of the value of the tested characteristic, depending on its concentration level and size, presented with a selected color palette [36].…”

Section: Literature Review On Vehicular Pollutant Emission Pre and Post Pandemicmentioning

confidence: 99%

Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey

et al. 2021

View full text Add to dashboard Cite

As in other countries of the world, the Turkish government is implementing many preventive partial and total lockdown practices against the virus’s infectious effect. When the first virus case has been detected, the public authorities have taken some restriction to reduce people and traffic mobility, which has also turned into some positive affect in air quality. To this end, the paper aims to examine how this pandemic affects traffic mobility and air quality in Istanbul. The pandemic does not only have a human health impact. This study also investigates the social and environmental effects. In our analysis, we observe, visualize, compare and discuss the impact of the post- and pre-lockdown on Istanbul’s traffic mobility and air quality. To do so, a geographic information system (GIS)-based approach is proposed. Various spatial analyses are performed in GIS with the statistical data used; thus, the environmental effects of the pandemic can be better observed. We test the hypothesis that this has reduced traffic mobility and improved air quality using traffic density cluster set and air monitoring stations (five air pollutant parameters) data for five months. The results shows that there are positive changes in terms of both traffic mobility and air quality, especially in April–May. PM10, SO2, CO, NO2 and NOx parameter values improved by 21.21%, 16.55%, 18.82%, 28.62% and 39.99%, respectively. In addition, there was a 7% increase in the average traffic speed. In order for the changes to be permanent, it is recommended to integrate e-mobility and sharing systems into the current transportation network.

show abstract

“…Moreover, Rybak and Rybak studied the impact of the COVID-19 pandemic on gaseous and solid air pollutant concentrations and emissions in Poland [47]. Bielecki et al studied the impact of the COVID-19 pandemic on electricity use by residential users [48].…”

Section: Literature Reviewmentioning

confidence: 99%

Determinants of Managerial Competences Transformation in the Polish Energy Industry

Pilipczuk¹

2021

Energies

View full text Add to dashboard Cite

Different technological, socio-economic, geopolitical, and demographic factors have a significant influence on labor markets. Currently, due to COVID-19, the global economy is in a challenging situation, and millions of people from different countries have lost their jobs. The employee’s mental health and well-being are in risk conditions. In the coming years, the Polish energy sector will face several transformations. Emerging technologies are intended to deal with the problems in energy management. One of the main industry forces is human capital, people who will be able to project and manage the innovative technologies. Thus, this paper examines the determinants of managerial competences transformation in the energy industry from the labor market perspective. The paper fulfills the research gap in the energy manager profession’s transformation in Poland. The aim of the paper was to present the current state of the energy manager profession in Poland. Two methodological approaches were used: the theoretical and practical approaches. Descriptive statistics are provided to present the labor market research results. The findings of the research can contribute to the literature and practice by applying them in the process of developing energy manager competency models, as well as in education programs and training courses for enterprises and universities.

show abstract

The Impact of the COVID-19 Pandemic on Gaseous and Solid Air Pollutants Concentrations and Emissions in the EU, with Particular Emphasis on Poland

Cited by 5 publications

References 35 publications

Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China

Artificial Intelligence and Urban Green Space Facilities Optimization Using the LSTM Model: Evidence from China

Evaluation of Air Quality Index by Spatial Analysis Depending on Vehicle Traffic during the COVID-19 Outbreak in Turkey

Determinants of Managerial Competences Transformation in the Polish Energy Industry

Contact Info

Product

Resources

About