Fine particulate matter (PM2.5) affects climate change and human health. Therefore, the prediction of PM2.5 level is particularly important for regulatory planning. The main objective of the study is to predict PM2.5 concentration employing an artificial neural network (ANN). The annual change in PM2.5 in Liaocheng from 2014 to 2021 shows a gradual decreasing trend. The air quality in Liaocheng during lockdown and after lockdown periods in 2020 was obviously improved compared with the same periods of 2019. The ANN employed in the study contains a hidden layer with 6 neurons, an input layer with 11 parameters, and an output layer. First, the ANN is used with 80% of data for training, then with 10% of data for verification. The value of correlation coefficient (R) for the training and validation data is 0.9472 and 0.9834, respectively. In the forecast period, it is demonstrated that the ANN model with Bayesian regularization (BR) algorithm (trainbr) obtained the best forecasting performance in terms of R (0.9570), mean absolute error (4.6 μg/m3), and root mean square error (6.6 μg/m3), respectively. The ANN model has produced accurate results. These results prove that the ANN is effective in monthly PM2.5 concentration predicting due to the fact that it can identify nonlinear relationships between the input and output variables.

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Prediction of Monthly PM2.5 Concentration in Liaocheng in China Employing Artificial Neural Network

Transformation of road transport sector through replacing of internal combustion vehicles with zero-emission technologies is among key challenges to achievement of climate neutrality by 2050. In a constantly developing economy, the demand for transport services increases to ensure continuity in the supply chain and passenger mobility. Deployment of electric technologies in the road transport sector involves both businesses and households, its pace depends on the technological development of zero-emission vehicles, presence of necessary infrastructure and regulations on emission standards for new vehicles entering the market. Thus, this study attempts to estimate how long combustion vehicles will be in use and what the state of the fleet will be in 2050. For obtainment of results the TR3E partial equilibrium model was used. The study simulates the future fleet structure in passenger and freight transport. The results obtained for Poland for the climate neutrality (NEU) scenario show that in 2050 the share of vehicles using fossil fuels will be ca. 30% in both road passenger and freight transport. The consequence of shifts in the structure of the fleet is the reduction of CO2 emissions ca. 80% by 2050 and increase of the transport demand for electricity and hydrogen.

How Long Will Combustion Vehicles Be Used? Polish Transport Sector on the Pathway to Climate Neutrality

This paper addresses the issue of incorporating rail transport into an urban delivery system. Its main purpose was to identify the possibilities of utilising rail transport in a Zero-emission Urban Delivery System (ZUDS) by applying Light Freight Railway (LFR) electric trains. The study applied the following research methods: literature review, observation, case study, and mathematical computations. In order to estimate the volume of transport external costs reduction resulting from shifting urban deliveries from road to rail transport in the city of Szczecin, the EU methodology was applied to specify the amounts of external costs generated by individual modes and means of transport. The research study showed that application of LFR electric trains makes it possible to significantly reduce external costs generated by transport. Moreover, this solution may have an impact on developing Clean Transport Zones (CTZs) and may also contribute to expansion of the ZUDS. The research study results also provide grounds to conclude that application of the LFR system makes it possible to reduce negative effects generated by Urban Freight Transport (UFT) and to achieve a coherent zero-emission system for handling cargo and passenger flows in cities, which consequently contributes to achieving electromobility goals in transport.

Effects of Incorporating Rail Transport into a Zero-Emission Urban Deliveries System: Application of Light Freight Railway (LFR) Electric Trains

Zooming into mobility to understand cities: A review of mobility-driven urban studies

Circular homes – An energy-water-materials nexus for community climate engagement and action at grassroots level in the built environment

The research focus was on analysing evacuation using data on the process in a selected area located within the boundaries of the Polish capital, Warsaw. The simulations were conducted to determine the consequences of private vehicle evacuation on the load of the road network, and enabled observations at the scale of the entire set of junctions, while also taking into account factor whose impact on the transport system cannot be captured by any systematic measurements (evacuation). The research procedure comprised three major stages. First, the evacuation documentation for Warsaw was reviewed. Due to the lack of detailed guidelines within the documentation, the data essential for the construction of traffic models had to be acquired (stage two), and the evacuation process was modelled in various scenarios (stage three), based on the Vissim software. The study considered five evacuation scenarios and zero variant for the two transport peaks. Thus, the total number of simulations, amounted to twelve. The results of the analysis revealed that although the deterioration of overall traffic conditions is particularly evident in Scenario 5, the evacuation process itself is still most efficient in this scenario. The traffic simulations conducted prove that it is impossible for an effective evacuation to be conducted without a disturbance to the normal traffic flow, and the ensuing accumulation may be detrimental for all road users. 

Effectiveness of the policy for organising self-evacuation by private vehicle transport, as verified in microsimulations

Spatial Dimension of Transport Exclusion Related to Statutory Trade Restriction—The Use of ITS Tools in Studies of Sustainable Urban Development

How transport shapes the landscape of large-format food retail trade? Retail geography in Poland – An interactive measure

The article examines the popularity of Uniejow and other small towns and spa resorts with a similar profile within the boundaries of the voivodeship of Łodź. The popularity was measured by the number of searches for each of these towns via the Google search engine. In addition, an analysis was made of season-connected changes in looking up Uniejow on the Internet, and the results were compared with promotional actions implemented by the Municipal Office. The findings indicate that Uniejow is the best known settlement in the group of small towns of Łodź region and, considering its potential and length of functioning, a major spa resort.

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Popularność Uniejowa na tle małych miast regionu łódzkiego oraz konkurujących z nim uzdrowisk

This article presents the variety of electoral choices of Uniejow municipality inhabitants in 2019 elections, which had a supranational (European Parliament) as well as a national (Polish Parliament) dimension The electoral decisions that were taken into account in this study included support for the different parties and voter turnout

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Paulina Kurzyk

Papers

Effectiveness of the policy for organising self-evacuation by private vehicle transport, as verified in microsimulations

Spatial Dimension of Transport Exclusion Related to Statutory Trade Restriction—The Use of ITS Tools in Studies of Sustainable Urban Development

How transport shapes the landscape of large-format food retail trade? Retail geography in Poland – An interactive measure

Popularność Uniejowa na tle małych miast regionu łódzkiego oraz konkurujących z nim uzdrowisk

Heterogeniczność przestrzenna postaw wyborczych mieszkańców gminy Uniejów w wyborach europejskich i parlamentarnych w 2019 roku