Search Results (55)

This study analyzes air pollution time-series big data to assess stationarity, seasonal patterns, and the performance of machine learning models in forecasting PM2.5 concentrations. Fifty-two low-cost sensors (LCS) were deployed across Krakow city and its surroundings (Poland), collecting hourly air quality data and generating nearly 20,000 observations per month. The network captured both spatial and temporal variability. The Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test confirmed trend-based non-stationarity, which was addressed through differencing, revealing distinct daily and 12 h cycles linked to traffic and temperature variations. Additive seasonal decomposition exhibited time-inconsistent residuals, leading to the adoption of multiplicative decomposition, which better captured pollution outliers associated with agricultural burning. Machine learning models—Ridge Regression, XGBoost, and LSTM (Long Short-Term Memory) neural networks—were evaluated under high spatial and temporal variability (winter) and low variability (summer) conditions. Ridge Regression showed the best performance, achieving the highest $R^2$ (0.97 in winter, 0.93 in summer) and the lowest mean squared errors. XGBoost showed strong predictive capabilities but tended to overestimate moderate pollution events, while LSTM systematically underestimated PM2.5 levels in December. The residual analysis confirmed that Ridge Regression provided the most stable predictions, capturing extreme pollution episodes effectively, whereas XGBoost exhibited larger outliers. The study proved the potential of low-cost sensor networks and machine learning in urban air quality forecasting focused on rare smog episodes (RSEs). Full article

Air pollution, largely driven by car traffic, poses significant challenges in many cities, including Košice, Slovakia. As the city explores micromobility as a part of its smart city initiatives and sustainable alternative to individual car use, understanding its spatial dynamics becomes essential. Despite the growing adoption of shared micromobility systems, research on their spatial patterns in Central Europe is still limited. This study analyzes over 900,000 trips made between 2019 and 2022 using bicycles, e-bikes, e-scooters, and e-mopeds in Košice’s dockless system. Using spatial analysis, we identified key hubs near public transport stops, pedestrian zones, and universities, highlighting how micromobility addresses the first/last mile transport challenge. A notable shift from bicycles to e-scooters was observed, enabling wider adoption in areas with fragmented terrain and neighborhoods farther from the city center. Our findings show a significant demand for shared micromobility, indicating its potential to reduce urban car dependency and support smart and sustainable urban transport. However, winter months remain a challenge, with high smog levels but near-zero demand for shared micromobility. Full article

Air pollution is a serious public health issue in Pakistan’s metropolitan cities, including Lahore, Karachi, Faisalabad, Islamabad, and Rawalpindi. Pakistan’s urban areas are vulnerable due to air pollution drivers such as industrial activities, vehicular emissions, burning processes, emissions from brick kilns, urbanization, and other human activities that have resulted in significant human health issues. The purpose of this study was to examine the impact of air pollutants and smog, as well as their causes and effects on human health. The PRISMA technique was used to assess the impact of environmental contaminants on human health. This study looked at air pollution sources and pollutants such as PM_2.5, PM₁₀, CO₂, CO, SO_X, and NO_x from waste combustion and agriculture. The population included people of all ages and sexes from both urban and rural areas of Pakistan. Data were retrieved and analyzed using SRDR⁺ software and Microsoft Excel spreadsheets. The data suggested that Karachi and Lahore had the highest levels of air pollution and disease prevalence, which were attributed to heavy industrial activity and traffic emissions. Smog was a serious concern in Lahore during winter, contributing to the spread of several diseases. Other cities, including Islamabad, Rawalpindi, Jhang, Sialkot, Faisalabad, and Kallar Kahar, were impacted by agricultural operations, industrial pollutants, brick kilns, and urbanization. Due to these drivers of air pollution, some diseases such as respiratory and cardiovascular diseases had notably higher incidences in these cities. Other diseases were connected with air pollution exposure, asthma, eye and throat problems, allergies, lung cancer, morbidities, and mortalities. To reduce air pollution’s health effects, policies should focus on reducing emissions, supporting cleaner technologies, and increasing air quality monitoring. Full article

The rapid urbanization and growing number of factories, human population, and motor vehicles have led to a drastic increase in the concentration of air pollutants. This smog is one of the most important disturbances in city planning. Urban trees play a vital role in the improvement of air quality. The selection of high-potential trees to capture air pollutants provides an attractive route for the mitigation of urban smog. The current study explored the air purification potential of the four most abundant trees, i.e., white mulberry (Morus alba L.), plane tree (Platanus orientalis L.), European ash (Fraxinus excelsior L.), and Tehran pine (Pinus eldarica Ten.)], as phytoremediators grown in three parks located in regions with low, moderate, and high levels of air pollution in Tehran on the mitigation of four urban hazardous gases (O₃, NO₂, CO, and SO₂) and in altering the content of respiratory gases (CO₂ and O₂). The measurement of gas levels was carried out in September–October, from 1.30 to 1.50 m above the ground. The concentration of gases was measured by an ambient gas assessment device (Aeroqual). Broad-leaf deciduous species had a greater ability to mitigate O₃, NO₂, CO, CO₂, and SO₂ concentrations than needle-leaf evergreen species. The lowest levels of O₃ and CO were found around P. orientalis (0.035 and 0.044 ppm, respectively), whereas the content of O₂ was the highest in the atmosphere of this tree (20.80 ppm). The lowest content of NO₂ (0.081 ppm) and SO₂ (0.076 ppm) was determined in the vicinity of M. alba and F. excelsior, respectively. Among the studied species, P. orientalis proved to be the best for air phytoremediation, effectively mitigating hazardous gases more than the other species. Conversely, P. eldarica is not recommended for air phytoremediation in urban green spaces. Future research should focus on exploring a wider range of tree species and their potential for air pollution mitigation in diverse urban settings across different seasons and climatic conditions. Full article

Sustainable urban development in the era of energy and digital transformation is crucial from a societal perspective. Utilizing modern techniques for analyzing large datasets, including machine learning and artificial intelligence, enables a deeper understanding of historical data and the efficient prediction of future events based on data from IoT sensors. This study conducted a multidimensional historical analysis of air pollution to investigate the impacts of energy transformation and environmental policy and to determine the long-term environmental implications of certain actions. Additionally, machine learning (ML) techniques were employed for air pollution prediction, taking spatial factors into account. By utilizing multiple low-cost air sensors categorized as IoT devices, this study incorporated data from various locations and assessed the influence of neighboring sensors on predictions. Different ML approaches were analyzed, including regression models, deep neural networks, and ensemble learning. The possibility of implementing such predictions in publicly accessible IT mobile systems was explored. The research was conducted in Krakow, Poland, a UNESCO-listed city that has had long struggle with air pollution. Krakow is also at the forefront of implementing policies to prohibit the use of solid fuels for heating and establishing clean transport zones. The research showed that population growth within the city does not have a negative impact on PMx concentrations, and transitioning from coal-based to sustainable energy sources emerges as the primary factor in improving air quality, especially for PMx, while the impact of transportation remains less relevant. The best results for predicting rare smog events can be achieved using linear ML models. Implementing actions based on this research can significantly contribute to building a smart city that takes into account the impact of air pollution on quality of life. Full article

Volatile organic compounds (VOCs) are major ingredients of photochemical smog. It is essential to know the spatial and temporal variation of VOC emissions. In this study, we used the Positive Matrix Factorization (PMF) model for VOC source apportionment in Mexico City. We first analyzed a data set collected during the ozone season from March–May 2016. It includes 33 VOCs, nitrogen oxide (NO), nitrogen dioxide (NO₂), the sum of nitrogen oxides (NO_x), carbon monoxide (CO), sulfur dioxide (SO₂) and particle matter with a diameter < 1 μm (PM₁). Another PMF analysis focused only on VOC data obtained in the month of May between the years 2016, 2017, 2018, 2021, and 2022 to gain insights into interannual variations. While the use of fossil fuel through combustion and evaporation continues to be major fraction in Mexico City, additional sources could be identified. Apart from biogenic sources which become more important closer to the end of the ozone season, a second natural emission factor termed “geogenic”, was identified. Overall, anthropogenic sources range between 80–90%. Diurnal plots and bivariate plots show the relative importance of these emission source factors on different temporal and spatial scales, which can be applied in emission control policies for Mexico City. Full article

High-rise buildings represent technological, urban, and life-style trends of the modern urban landscape, yet there are limited data regarding their embodied carbon and environmental impacts, particularly when compared to low- or mid-rise buildings. Given that the projected growth of the global urban population by 2050 requires cities with higher density and potentially a greater number of high-rise buildings, it is crucial to develop a clear understanding of the embodied carbon and environmental impacts of high-rise buildings. The primary structural materials used in high-rise buildings are reinforced concrete and structural steel. As of today, over 99% of tall buildings’ structures are built from those two materials. This article utilizes a building information modeling (BIM)-based life cycle assessment (LCA) in Revit and Tally to examine the embodied carbon and environmental impacts of an actual high-rise building structure case study in Chicago that uses a hybrid concrete steel structure. The results show that the embodied carbon and environmental impacts of the high-rise building structure are dominated by the impacts of the product stage in the building’s life cycle and by concrete being the main structural material. Specifically, this study reveals that concrete constitutes a substantial 91% share of the total mass of the building structure, with a 74% contribution to the life cycle global warming potential, 53% to the acidification potential, 74% to the eutrophication potential, 74% to the smog formation potential, and 68% to the non-renewable energy usage. On the other hand, steel accounts for 9% of the building’s structure mass, estimated to constitute 26% of the global warming potential, 47% of the acidification potential, 26% of the eutrophication potential, 26% of the smog formation potential, and 32% of the non-renewable energy usage. Full article

The problem of poor air quality in urban areas has a negative impact on the health of residents. This is especially important during periods of smog. In Poland, as in other countries, the problem of poor air quality, especially during the winter season, is associated with a high concentration of particulate pollutants in ambient air (PM₁₀, PM_2.5). Sources of particulate emissions, in addition to solid-fuel boilers, include means of transportation, especially those equipped with diesel engines. In turn, during periods of strong sunshine (spring and summer), the problem of photochemical smog, whose precursors are nitrogen oxides NO_X, arises in urban areas. Their main sources of emissions are internal combustion engines. Therefore, to improve air quality in urban areas, changes are being made in the transport sector, among which is upgrading the fleet of urban transport vehicles to low- or zero-emission vehicles, which are more environmentally friendly. In addition, measures that reduce the harmfulness of the transportation sector to air quality include the introduction of clean transportation zones, as well as park-and-ride (P&R) systems. The purpose of this article is to present the results in terms of PM₁₀, PM_2.5, and NOx emission reductions, implemented over a period of two years (2021–2022) in the area of the Rzeszow agglomeration, related to the modernization of the suburban bus fleet and the implementation of a P&R system for passenger cars. The results of the study were compared with the value of estimated emissions from coal-fired boilers used for residential heating and hot water, which also contribute to smog. Thanks to the implementation of the project, i.e., the replacement of 52 old buses with new buses of the Euro VI emission class and the construction of new P&R spaces, the total average annual reduction in emissions amounted to approximately 703.6 kg of PM₁₀, approximately 692.7 kg of PM_2.5, and a reduction of approximately 10.4 tons of NO_X. Full article

Air pollution is prevalent throughout the entire world due to the release of various gases such as NO_x, PM, SO₂, tropospheric ozone (O₃), etc. Ground-stage ozone is the predominant issue in smog and is the product of the interplay between sunlight and emissions. The destructive impact on the health of the populace might also still occur in cities with noticeably clean air and where ozone levels hardly ever exceed safe limits. Therefore, the findings of small variations in air quality and the technique of regulating air contamination are thought-provoking. The study employs various techniques to effectively observe and assess strategies for detecting and eliminating outliers in ozone emissions from pollution episodes. This technique helps to describe the sources and exceedance values and enhance the value of monitoring the data. In this study, the data have some missing observations. The method of imputation, the classical statistical technique, the statistical process control (SPC) technique, functional data analysis (FDA), and functional process control help to fill in the data and detect outliers, trend deviations, and changes in ozone concentration at ground level. A comparison study is carried out using these three techniques: classical analysis, SPC, and FDA, and the results show how the statistical process control and functional data methods performed better than the classical technique for the detection of outliers and also in what way this methodology can enable an additional, comprehensive method of defining air pollution control measures and water pollution control measures. Full article

Contemporary problems related to the consequences of climate change and exposure to changing investment and implementation conditions are prompting the development of programmes adapting to climate change. Issues of adaptation and actions in relation to climate change are being discussed in the architectural, urban planning, and governmental communities. Models are being developed for shaping the functional and spatial structure, buildings and infrastructure in the city in relation to the projected climate change. Multi-criteria and interdisciplinary research is being carried out and solutions are being implemented for retaining water, minimising the heat island effect, reducing emissions and environmental impact by analysing the carbon footprint and introducing circular economy principles. The research is focused on the analysis of design and implementation conditions for multi-family housing projects in Poland, and the development of design guidelines enabling adaptation and mitigation of the negative effects of climate change, including heat island effects, smog, overheating, drought, and flooding in housing. Conclusions from the overview of the indicated documents and legal provisions for the implementation of sustainable development principles and adaptation to climate change in the investments under preparation (urban and architectural projects) enable the forecasting of development directions and ideological assumptions for shaping urbanised areas, providing the basis for shaping the resilience of the functional and spatial structure and the natural system in urban areas subject to transformation. Issues of implementing pro-environmental technologies and developing new urban planning standards disseminate the solutions of compact cities in which the development of multifunctional building complexes with public spaces equipped with greenery linked to the buildings are realised. Full article

This paper assessed the impacts of environmental smog early-warning signals on road traffic deaths. For an accurate assessment, we used the daily traffic death data from 2016 to 2020 in 295 Chinese cities and constructed a rigorous Regression Discontinuity Design (RDD) strategy to identify the causality and adopted the high-dimensional fixed-effect method to deal with the interference of meteorological factors. The results indicate that light smog and moderate smog early warnings decreased road fatalities by about 3.6% and 4.3%, respectively. Surprisingly, the heavy smog early-warning signal had no significant effect, possibly because of the self-consciousness mechanism instead of the early-warning signal mechanism. Further heterogeneity analysis showed that women drivers, highly-educated drivers, older drivers (over 60 years), two-wheeled vehicle drivers, and drivers on country roads and freeways are more sensitive to smog early-warning signals. Full article

Biodegradable waste from households, companies, and gastronomy is not utilized in large Polish agglomerations for the production of biogas. Determining the biogas production potential in a selected agglomeration will enable the implementation of circular economy goals and sustainable development objectives. Once appropriate odor neutrality standards are met, biogas plants could be constructed around large cities, supplying both energy and heating systems to nearby housing estates or production facilities. This article aims to assess the potential of biodegradable municipal waste collected in a large city for the production of energy in specialized municipal biogas plants. The following analytical study focuses on Krakow and its surrounding municipalities. Because of its geographical location, Krakow is exposed to smog, and every action limiting the usage of carbon-based materials for heating will have a positive impact on the air quality. A biogas plant powered by municipal waste would present a viable opportunity to limit urban smog. It is also crucial that a biogas plant can store energy as it is equipped with methane tanks. Both renewable and other energy sources are still awaiting functional technical solutions that would allow for optimal energy storage. Full article

Polish smog is a specific type of air pollution present in Eastern Poland, which may cause particularly adverse cardiovascular effects. It is characterized primarily by high concentrations of particulate matter (PM) and different favorable conditions of formation. Our study aimed to assess whether PM and nitrogen dioxide (NO₂) have a short-term impact on mortality due to acute coronary syndrome (ACS) and ischemic stroke (IS). The study covered the years 2016–2020, a total of 6 million person-years from five main cities in Eastern Poland. To evaluate the association between air pollution and cause-specific mortality, a case-crossover study design with conditional logistic regression was used at days with LAG from 0 to 2. We recorded 87,990 all-cause deaths, including 9688 and 3776 deaths due to ACS and IS, respectively. A 10 μg/m³ increase in air pollutants was associated with an increase in mortality due to ACS (PM_2.5 OR = 1.029, 95%CI 1.011–1.047, p = 0.002; PM₁₀ OR = 1.015, 95%CI 1–1.029, p = 0.049) on LAG 0. On LAG 1 we recorded an increase in both IS (PM_2.5 OR = 1.03, 95%CI 1.001–1.058, p = 0.04) and ACS (PM_2.5 OR = 1.028, 95%CI 1.01–1.047, p = 0.003; PM₁₀ OR = 1.026, 95%CI 1.011–1.041, p = 0.001; NO₂ OR = 1.036, 95%CI 1.003–1.07, p = 0.04). There was a strong association between air pollution and cause-specific mortality in women (ACS: PM_2.5 OR = 1.032, 95%CI 1.006–1.058, p = 0.01; PM₁₀ OR = 1.028, 95%CI 1.008–1.05, p = 0.01) and elderly (ACS: PM_2.5 OR = 1.03, 95%CI 1.01–1.05, p = 0.003; PM₁₀ OR = 1.027, 95% CI 1.011–1.043, p < 0.001 and IS: PM_2.5 OR = 1.037, 95%CI 1.007–1.069, p = 0.01; PM₁₀ OR = 1.025, 95%CI 1.001–1.05, p = 0.04). The negative influence of PMs was observed on mortality due to ACS and IS. NO₂ was associated with only ACS-related mortality. The most vulnerable subgroups were women and the elderly. Full article

With the aim of understanding the impact of air pollution on human health and ecosystems in the tropical Andes region (TAR), we aim to couple the Weather Research and Forecasting Model (WRF) with the chemical transport models (CTM) Long-Term Ozone Simulation and European Operational Smog (LOTOS–EUROS), at high and regional resolutions, with and without assimilation. The factors set for WRF, are based on the optimized estimates of climate and weather in cities and urban heat islands in the TAR region. It is well known in the weather research and forecasting field, that the uncertainty of non-linear models is a major issue, thus making a sensitivity analysis essential. Consequently, this paper seeks to quantify the performance of the WRF model in the presence of disturbances to the initial conditions (IC), for an arbitrary set of state-space variables (pressure and temperature), simulating a disruption in the inputs of the model. To this aim, we considered three distributions over the error term: a normal standard distribution, a normal distribution, and an exponential distribution. We analyze the sensitivity of the outputs of the WRF model by employing non-parametric and robust statistical techniques, such as kernel distribution estimates, rank tests, and bootstrap. The results show that the WRF model is sensitive in time, space, and vertical levels to changes in the IC. Finally, we demonstrate that the error distribution of the output differs from the error distribution induced over the input data, especially for Gaussian distributions. Full article

The balance between smog pollution (SP) control and economic growth (EG) is currently a major problem facing China’s development. Green technology innovation (GTI) is an effective way to promote ecological civilization and realize green development. Thus, whether GTI can facilitate a win–win situation of SP control and stable EG is an important issue of academic concerns. In this paper, the mechanisms of the role of GTI, SP and EG were systematically demonstrated. The corresponding research hypotheses were proposed. Based on the data book of 278 Chinese cities from 2008 to 2020, the effects of GTI on SP and EG were systematically investigated using the econometric estimation method of dynamic spatial panel simultaneous equations. The results show that GTI can reduce SP directly, or indirectly by promoting EG. Although GTI can promote EG, EG may be inhibited due to GTI-induced SP reduction. Inter-regional SP showed significant spatial agglomeration characteristics. EG had significant spatial correlation effects. GTI in neighboring regions can also facilitate local SP control. Further analysis shows that compared with green utility model innovation (GUMI), green invention and innovation (GII) had a more significant effect on reducing SP and promoting EG. In addition, the analysis of the comprehensive effect of GTI on SP and EG shows that GTI can achieve the overall balanced development of SP prevention and EG regardless of GTI types. Full article