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9 pages, 1436 KB

Open AccessProceeding Paper

Insights into Air Quality Index (AQI) Variability with Explainable Machine Learning Techniques

by Claudio Andenna and Roberta Valentina Gagliardi

Environ. Earth Sci. Proc. 2025, 34(1), 1; https://doi.org/10.3390/eesp2025034001 - 5 Aug 2025

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In this study, a combined approach joining the machine learning model Extreme Gradient Boosting (XGBoost) with Shapley Additive Explanation (SHAP) is adopted to simulate the temporal pattern of the air quality index (AQI) and subsequently explore the key factors affecting AQI variability. Based [...] Read more.

In this study, a combined approach joining the machine learning model Extreme Gradient Boosting (XGBoost) with Shapley Additive Explanation (SHAP) is adopted to simulate the temporal pattern of the air quality index (AQI) and subsequently explore the key factors affecting AQI variability. Based on the analysis of air pollutants and meteorological data acquired from two air quality monitoring stations in Rome (Italy), over the 2018–2022 period, the results demonstrate the effectiveness of the proposed methodological approach in elucidating the role of the main factors driving AQI evolution, and their interaction effects. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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7 pages, 337 KB

Open AccessProceeding Paper

Exposure to PM_2.5 While Walking in the City Center

by Anna Mainka, Witold Nocoń, Aleksandra Malinowska, Julia Pfajfer, Edyta Komisarczyk and Pawel Wargocki

Environ. Earth Sci. Proc. 2025, 34(1), 2; https://doi.org/10.3390/eesp2025034002 - 6 Aug 2025

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Abstract

This study investigates personal exposure to fine particulate matter (PM_2.5) during walking commutes in Gliwice, Poland—a city characterized by elevated levels of air pollution. Data from a low-cost air quality sensor were compared with a municipal monitoring station and the Silesian [...] Read more.

This study investigates personal exposure to fine particulate matter (PM_2.5) during walking commutes in Gliwice, Poland—a city characterized by elevated levels of air pollution. Data from a low-cost air quality sensor were compared with a municipal monitoring station and the Silesian University of Technology laboratory. PM_2.5 concentrations recorded by the low-cost sensor (7.3 µg/m³) were lower than those reported by the stationary monitoring sites. The findings suggest that low-cost sensors may offer valuable insights into short-term peaks in PM_2.5 exposure to serve as a practical tool for increasing public awareness of personal exposure risks to protect respiratory health. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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10 pages, 1061 KB

Open AccessProceeding Paper

Effect of Nitrogen Oxide Concentration Levels and Meteorological Variables on Ozone (O₃) Formation in the Petrochemical Industry Area in the Monterrey Metropolitan, Mexico

by Jailene Marlen Jaramillo-Perez, Bárbara A. Macías-Hernández, Edgar Tello-Leal and René Ventura-Houle

Environ. Earth Sci. Proc. 2025, 34(1), 3; https://doi.org/10.3390/eesp2025034003 - 8 Aug 2025

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Abstract

The petrochemical industry emits large amounts of nitrogen oxides (NOx). It is the second source of volatile organic compounds (VOCs), which, through photochemical reactions, can form tropospheric ozone (O₃) and, together with geographic and meteorological conditions, influence the spatial and temporal [...] Read more.

The petrochemical industry emits large amounts of nitrogen oxides (NOx). It is the second source of volatile organic compounds (VOCs), which, through photochemical reactions, can form tropospheric ozone (O₃) and, together with geographic and meteorological conditions, influence the spatial and temporal behavior of pollution. The objective of this study is to assess the influence of air pollutants NOx, NO₂, and NO, as well as meteorological factors on O₃ concentration levels in the city of Cadereyta, Nuevo Leon, which is characterized by its petrochemical industry as part of the metropolitan area of Monterrey, Mexico. The data were analyzed using the Spearman’s correlation coefficient, identifying a weak-to-moderate negative association between NOx and NO₂ with O₃ in the spring season and a null relationship in the summer. However, the autumn and winter seasons observed a moderate to strong negative relationship. Subsequently, a multiple linear regression analysis determined the influence of air pollutants NOx, NO₂, and NO, as well as meteorological factors on O₃ concentration levels. In this sense, when the concentration levels of NOx and NO₂ decrease, the concentration of O₃ will increase proportionally according to the season of the year. The prediction model obtains a coefficient of determination (R²) of 0.60 and a root-mean-square error (RMSE) value of 0.0096 ppm. In the prediction model, all variables presented a significant effect on the interpretation of the dependent variable. The independent variables that provided the most significant variation in the concentration levels of O₃ were NOx and NO₂. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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7 pages, 2820 KB

Open AccessProceeding Paper

Significance of Summertime Heat Low over the Northern Part of the Indian Subcontinent in the Changing Climate

by Prashant Singh

Environ. Earth Sci. Proc. 2025, 34(1), 4; https://doi.org/10.3390/eesp2025034004 - 8 Aug 2025

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Abstract

The Indian heat low, a strong atmospheric circulation pattern marked by low pressure and high temperatures, significantly influences weather patterns over Pakistan and northern India. Understanding how terrestrial heating patterns changes over time is crucial for understanding climate change. Such changes can profoundly [...] Read more.

The Indian heat low, a strong atmospheric circulation pattern marked by low pressure and high temperatures, significantly influences weather patterns over Pakistan and northern India. Understanding how terrestrial heating patterns changes over time is crucial for understanding climate change. Such changes can profoundly affect large-scale systems such as the heat low and monsoon. The evolving characteristics of the heat low area over the Indian subcontinent from 1940 to 2020 are investigated using a decadal analysis of reanalysis data (ERA5). The results indicate an eastward shift in the heat low over the historical period. Furthermore, ensembles of CMIP5 Global Climate Models (GCMs) under RCP6.0 and RCP8.5 scenarios project a continued eastward shift in this heat low pattern between 2050 and 2100. The eastward shift in the heat low pattern significantly influences the monsoon circulation system, potentially leading to substantial changes in rainfall distribution across the Indian subcontinent, as projected under RCP6.0 and RCP8.5 scenarios—with some differences between them. The results from the GCMs support the idea of an eastward shift in rainfall, indicating the potential for altered precipitation distribution in the future. Furthermore, the study emphasizes the possible drying of the western Indian subcontinent, including Pakistan and western India, because of the altering heat low trend. These findings highlight the necessity of considering changing atmospheric circulation patterns in climate change assessments and the need for a better understanding of the associated implications for regional climate dynamics. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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11 pages, 2553 KB

Open AccessProceeding Paper

Evaluation of an Integrated Low-Cost Pyranometer System for Application in Household Installations

by Theodore Chinis, Spyridon Mitropoulos, Pavlos Chalkiadakis and Ioannis Christakis

Environ. Earth Sci. Proc. 2025, 34(1), 5; https://doi.org/10.3390/eesp2025034005 - 21 Aug 2025

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Abstract

The climatic conditions of a region are a constant object of study, especially now that climate change is clearly affecting quality of life and the way we live. The study of the climatic conditions of a region is conducted through meteorological data. Meteorological [...] Read more.

The climatic conditions of a region are a constant object of study, especially now that climate change is clearly affecting quality of life and the way we live. The study of the climatic conditions of a region is conducted through meteorological data. Meteorological installations include a set of sensors to monitor the meteorological and climatic conditions of an area. Meteorological data parameters include measurements of temperature, humidity, precipitation, wind speed, and direction, as well as tools such as an oratometer and a pyranometer, etc. Specifically, the pyranometer is a high-cost instrument, which has the ability to measure the intensity of the sunshine on the surface of the earth, expressing the measurement in Watt/m². Pyranometers have many applications. They can be used to monitor solar energy in a given area, in automated systems such as photovoltaic system management, or in automatic building shading systems. In this research, both the implementation and the evaluation of an integrated low-cost pyranometer system is presented. The proposed pyranometer device consists of affordable modules, both microprocessor and sensor. In addition, a central server, as the information system, was created for data collection and visualization. The data from the measuring system is transmitted via a wireless network (Wi-Fi) over the Internet to an information system (central server), which includes a database for collecting and storing the measurements, and visualization software. The end user can retrieve the information through a web page. The results are encouraging, as they show a satisfactory degree of determination of the measurements of the proposed low-cost device in relation to the reference measurements. Finally, a correction function is presented, aiming at more reliable measurements. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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5 pages, 749 KB

Open AccessProceeding Paper

A Holistic Approach for the Minimization of Nitrous Oxide (N₂O) Emissions from Brewery Wastewater Treatment Using Malt Sprout Derived Biochar

by Pelin Soyertaş Yapıcıoğlu

Environ. Earth Sci. Proc. 2025, 34(1), 6; https://doi.org/10.3390/eesp2025034006 - 1 Sep 2025

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Abstract

This study investigated the minimization of the N₂O emissions related to brewery wastewater treatment by malt-sprout-derived biochar. The biochar was derived using slow pyrolysis (300 (B1), 400 (B2), and 550 °C (B3)). The correspondence between the N₂O emission and [...] Read more.

This study investigated the minimization of the N₂O emissions related to brewery wastewater treatment by malt-sprout-derived biochar. The biochar was derived using slow pyrolysis (300 (B1), 400 (B2), and 550 °C (B3)). The correspondence between the N₂O emission and wastewater treatment quality was investigated by Monte Carlo simulation. An average of 25.6% of minimization in N₂O emissions was reported by malt-sprout-derived biochar. The simulation results showed that the Total Kjeldahl Nitrogen (TKN) and ammonium (NH₄-N) had the highest correspondence with N₂O emissions. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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10 pages, 2820 KB

Open AccessProceeding Paper

Evaluation of Modelling and Remote Sensing Tools for Improving Air Quality in Surroundings of Open Pit Mines

by Raúl Arasa Agudo, Óscar Hernández, Elisa Etzkorn, Milagros Herrera, David Fuertes, Eliot Llopis, Ana Sánchez de la Campa, Francisco Alejandro and Emilio Sanjuán

Environ. Earth Sci. Proc. 2025, 34(1), 7; https://doi.org/10.3390/eesp2025034007 - 15 Sep 2025

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Abstract

In this contribution, three techniques related to modelling and remote sensing were tested to answer questions and satisfy requirements from air quality managers in the mining sector: (1) What are appropriate emission factors for blasting operations in copper mines? (2) How can we [...] Read more.

In this contribution, three techniques related to modelling and remote sensing were tested to answer questions and satisfy requirements from air quality managers in the mining sector: (1) What are appropriate emission factors for blasting operations in copper mines? (2) How can we know the concentration of particulate matter in the next few hours in advance? (3) How can we generate a heat map of the particulate matter levels over the mine and nearby populations? These techniques were evaluated for one of the most relevant open pit mines in southern Europe, the Riotinto Mine, Huelva (Spain). The results obtained suggest that these techniques can efficiently improve the management of air quality in mining activities. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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8 pages, 2456 KB

Open AccessProceeding Paper

Modelling the Outdoor Thermal Benefit of Urban Trees: A Case Study in Lecce, Italy

by Francesco Giangrande, Gianluca Pappaccogli, Rita Cesari, Antonio Esposito, Rohinton Emmanuel, Fabio Ippolito and Riccardo Buccolieri

Environ. Earth Sci. Proc. 2025, 34(1), 8; https://doi.org/10.3390/eesp2025034008 - 16 Sep 2025

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Abstract

Urban vegetation plays a key role in mitigating thermal stress in cities, particularly in Mediterranean climates increasingly affected by urban heat. This study evaluates the impact of vegetation on outdoor thermal comfort in Piazzetta San Michele Arcangelo, a square in Lecce (Southern Italy), [...] Read more.

Urban vegetation plays a key role in mitigating thermal stress in cities, particularly in Mediterranean climates increasingly affected by urban heat. This study evaluates the impact of vegetation on outdoor thermal comfort in Piazzetta San Michele Arcangelo, a square in Lecce (Southern Italy), using the ENVI-met microclimate model. Two scenarios were simulated: the current configuration and a hypothetical one without trees. Results show that vegetation reduces air temperature during the hottest hours (up to −0.52 °C on average) and improves thermal comfort, as indicated by the Universal Thermal Climate Index (UTCI), with reductions in “very strong heat stress” up to 43% at peak times. At night, tree canopies limit radiative cooling, leading to slight temperature increases. The findings confirm the crucial role of urban greening in enhancing outdoor thermal comfort and provide quantitative support for sustainable urban planning strategies in Mediterranean contexts. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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13 pages, 1031 KB

Open AccessProceeding Paper

Building Envelope Renovation for Energy Efficiency in Maputo, Mozambique: Expanded Polystyrene Insulation and Double-Glazed Windows

by Samuel Aires Master Lazaro, Xiangyu Li and Vanessa Fathia Baba

Environ. Earth Sci. Proc. 2025, 34(1), 9; https://doi.org/10.3390/eesp2025034009 - 17 Sep 2025

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Abstract

This study examines the impact of envelope renovation using Expanded Polystyrene (EPS) insulation and double glazing on reducing CO₂ emissions and energy consumption in low-income residential buildings in Mozambique’s tropical climate. Conducted in Maputo over 12 months (2023–2024), it targets urban households, [...] Read more.

This study examines the impact of envelope renovation using Expanded Polystyrene (EPS) insulation and double glazing on reducing CO₂ emissions and energy consumption in low-income residential buildings in Mozambique’s tropical climate. Conducted in Maputo over 12 months (2023–2024), it targets urban households, addressing high energy use and emissions caused by inefficient building envelopes and limited access to sustainable technologies. The study uses DesignBuilder’s validated EnergyPlus engine to evaluate energy savings and financial viability within cultural and economic contexts. Results show a 42.16% reduction in energy consumption (from 5392.04 to 3118.69 kWh) and a 42.20% decrease in CO₂ emissions (from 3.27 × 10³ to 1.89 × 10³ kg) compared to conventional designs. With an 11.75% discount rate accounting for inflation and opportunity costs, the retrofit achieves a payback period of 6.9 years, confirming its financial viability. These findings offer policymakers, architects, and low-income communities a cost-effective retrofit model, advocating for policy integration of low-U-value materials to improve environmental and economic sustainability. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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9 pages, 3996 KB

Open AccessProceeding Paper

Analyzing the Relationship Between Vegetation and Temperature Changes in the Sylhet Region

by Sk. Tanjim Jaman Supto

Environ. Earth Sci. Proc. 2025, 34(1), 10; https://doi.org/10.3390/eesp2025034010 - 22 Sep 2025

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Abstract

As global temperatures continue to rise, understanding the relationship between climate and vegetation is crucial for agriculture and for mitigating and adapting to environmental changes. The complex interaction between vegetation and climate becomes even more significant as temperatures increase, making it essential to [...] Read more.

As global temperatures continue to rise, understanding the relationship between climate and vegetation is crucial for agriculture and for mitigating and adapting to environmental changes. The complex interaction between vegetation and climate becomes even more significant as temperatures increase, making it essential to comprehend these changes in the environment. This study investigates vegetation dynamics in the Sylhet region of northeastern Bangladesh between 1988 and 2025, focusing on how long-term temperature changes have influenced vegetation cover. The research utilizes Landsat-derived Normalized Difference Vegetation Index (NDVI) datasets from 1988, 1995, 2005, 2015, and 2025, alongside monthly temperature records from NOAA’s NCEI. The temperature data was analyzed using Pearson’s correlation and descriptive statistical method to examine the relationship between vegetation and climate. The results show that dense vegetation declined sharply, with an estimated net loss of ~12.9 km² converting to sparse vegetation and ~1.5 km² converting to urban/barren land between 1988 and 2025. At the same time, sparse vegetation expanded, while urban area/barren land areas increased substantially. Water bodies also showed reductions. Over the same period, the mean annual temperature rose by +0.32 °C. These findings highlight the region’s ecological vulnerability to combined climatic and anthropogenic pressures, underscoring the urgent need for sustainable land management and adaptive strategies. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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7 pages, 1212 KB

Open AccessProceeding Paper

Effect of the Form of the Error Correlation Functions on Uncertainty in the Estimation of Atmospheric Aerosol Distribution When Using Spatial-Temporal Optimal Interpolation

by Natallia Miatselskaya, Andrey Bril and Anatoly Chaikovsky

Environ. Earth Sci. Proc. 2025, 34(1), 11; https://doi.org/10.3390/eesp2025034011 - 22 Sep 2025

Abstract

Spatial-temporal optimal interpolation (STOI) is a data assimilation method based on minimizing the error in an estimate. Error correlations can be modeled with analytical functions. We investigated the effect of the form of the error correlation functions on the uncertainty in an estimate. [...] Read more.

Spatial-temporal optimal interpolation (STOI) is a data assimilation method based on minimizing the error in an estimate. Error correlations can be modeled with analytical functions. We investigated the effect of the form of the error correlation functions on the uncertainty in an estimate. We applied STOI to the estimation of aerosol distribution over Europe using the results of GEOS-Chem chemical transport model simulations and observations from a ground-based radiometric Aerosol Robotic Network. We used exponential functions to model correlation curves. The results show that a ±15–25% change in the argument of the constructed exponential functions has little effect on the mean square error in the estimate in regions where observations are dense. STOI estimates are sensitive to the form of the correlation curves in regions where observations are sparse. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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10 pages, 3980 KB

Open AccessProceeding Paper

Warming Projections of Eastern Mediterranean in CMIP6 Simulations According to SSP2-4.5 and SSP5-8.5 Scenarios

by Ioannis Logothetis, Kleareti Tourpali and Dimitrios Melas

Environ. Earth Sci. Proc. 2025, 34(1), 12; https://doi.org/10.3390/eesp2025034012 - 23 Sep 2025

Abstract

This study investigates the future temperature changes in the climate-vulnerable region of the Eastern Mediterranean. The results from seventeen (17) CMIP6 (6th Phase of Coupled Model Intercomparison Project) model simulations are analyzed. The analysis is focused on the SSP2-4.5 and SSP5-8.5 scenarios. The [...] Read more.

This study investigates the future temperature changes in the climate-vulnerable region of the Eastern Mediterranean. The results from seventeen (17) CMIP6 (6th Phase of Coupled Model Intercomparison Project) model simulations are analyzed. The analysis is focused on the SSP2-4.5 and SSP5-8.5 scenarios. The ERA5 reanalysis is used as a reference dataset to investigate the performance of CMIP6 simulations to accurately reproduce the mean temperature in the Eastern Mediterranean region. The results show that CMIP6 model simulations vary regarding their efficiency for capturing the mean temperature. Future projections show that significant warming is shown during the last period of the 21st century. The continental Balkan and Turkish regions are recognized as the most affected areas regarding future warming. The increase in temperature spatially ranges (in local scale) from 1.5 °C to 4.5 °C for the SSP2-4.5 scenario and from 3.0 °C to 8.0 °C for the SSP5-8.5 scenario. Finally, the seasonal analysis indicates that summer (JJA) shows the maximum temperature increase compared with the other seasons. Full article

(This article belongs to the Proceedings of The 7th International Electronic Conference on Atmospheric Sciences (ECAS-7))

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