Spatial decision-making for urban flood vulnerability: A geomatics approach applied to Al-Ain City, UAE

Urban Climate, Journal Year: 2025, Volume and Issue: 59, P. 102297 - 102297

Published: Jan. 31, 2025

Language: Английский

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A comprehensive spatiotemporal approach to mapping air quality distribution and prediction in desert region

Urban Climate, Journal Year: 2024, Volume and Issue: 58, P. 102137 - 102137

Published: Sept. 30, 2024

Language: Английский

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Do Meteorological Variables Impact Air Quality Differently Across Urbanization Gradients? A Case Study of Kaohsiung, Taiwan, China

Heliyon, Journal Year: 2025, Volume and Issue: 11(2), P. e41694 - e41694

Published: Jan. 1, 2025

Air pollution has become a major challenge to global urban sustainable development, necessitating urgent solutions. Meteorological variables are key determinants of air quality; however, research on their impact across different gradients remains limited, and mechanisms largely unexplored. This study investigates the dynamic effects meteorological quality under varying levels urbanization using Kaohsiung City, Taiwan, as case study. pollutant data from monitoring stations in Kaohsiung, for year 2023 were collected analyzed. The Quality Index (AQI) was used quantify levels, Granger causality tests Vector Autoregression (VAR) models employed analyze relationships between AQI. results revealed that: (1) Suburban areas exhibited significantly better than near-urban areas, with annual AQI values 59.58 Meinong (outskirts), 67.86 Renwu (suburbs area), 76.73 Qianjin (urban showing progressive improvement suburban primarily due lower abundant forest resources; (2) Temperature relative humidity emerged influencing AQI, indicating that temperature affects especially areas. Impulse response analysis had notable positive negative correlation effect over lagged periods, while wind speed showed gradually shifting time; (3) Variance decomposition indicated largest particularly cumulative lag effects, main provides scientific evidence future planning environmental management, supporting development more effective strategies promote development.

Language: Английский

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Spatiotemporal dynamics of urban heat island effect and air pollution in Bengaluru and Hyderabad: implications for sustainable urban development

Discover Sustainability, Journal Year: 2025, Volume and Issue: 6(1)

Published: Feb. 25, 2025

Language: Английский

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Analysis and Prediction of Atmospheric Environmental Quality Based on the Autoregressive Integrated Moving Average Model (ARIMA Model) in Hunan Province, China

Sustainability, Journal Year: 2024, Volume and Issue: 16(19), P. 8471 - 8471

Published: Sept. 29, 2024

Based on the panel data of atmospheric environmental pollution in Hunan Province from 2016 to 2023, autoregressive integrated moving average model (ARIMA) is introduced evaluate and predict current status quality China, constructed ARIMA has an excellent prediction effect Province. The following conclusions are obtained through analysis based model: (1) shows a year-on-year improvement trend; (2) method reliable effective can accurately analyze concentrations air pollutants (PM2.5, PM10, SO2, CO) quality, results show that outdoor will improve gradually each year 2024 2028; (3) this study contributes better understanding ambient during 2016–2023 provides good forecasting for period 2024–2028.

Language: Английский

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Improving Air Quality Data Reliability through Bi-Directional Univariate Imputation with the Random Forest Algorithm

Sustainability, Journal Year: 2024, Volume and Issue: 16(17), P. 7629 - 7629

Published: Sept. 3, 2024

Forecasting the future levels of air pollution provides valuable information that holds importance for general public, vulnerable populations, and policymakers. High-quality data are essential precise reliable forecasts investigations pollution. Missing observations arise when sensors utilized assessing quality parameters experience malfunctions, which result in erroneous measurements or gaps dataset hinder quality. This research paper presents a novel approach imputing missing values univariate approach. The algorithm employs random forest (RF) to impute bi-directional (forward reverse time) manner (particulate matter less than 2.5 μm (PM2.5)) from Republic Serbia. was evaluated against simple methods, such as mean median imputation over durations 24, 48, 72 h. results indicate our yielded comparable error rates method all periods PM2.5 data. Ultimately, algorithm’s higher computational complexity proved itself not justified considering minimal decrease it achieved compared with simpler methods. However, improvement, additional is needed, utilizing low-code machine learning libraries time-series forecasting techniques.

Language: Английский

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Study on the Influencing Factors of the Competitive Network Pattern of Cobalt Industry Chain Trade in the Context of Big Data Analysis

Applied Mathematics and Nonlinear Sciences, Journal Year: 2024, Volume and Issue: 9(1)

Published: Jan. 1, 2024

Abstract The article proposes a time series model to explore the influencing factors of cobalt industry chain trade competition network pattern. By analyzing current situation evolution network, relevant variables are selected. data described based on overview algorithmic research model. Finally, is empirically tested. unit root verified be in an unsteady state by first-order differencing, and p-values all have probability accepting original hypothesis greater than 0. After second-order differencing ADF test, smooth them monotonic. cointegration it was found that residual at 5% critical level, there relationship.

Language: Английский

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