Search Results (9)

Among the challenges the human population needs to address are threats of global pandemics, increasing socioeconomic inequality, especially in developing countries, and anthropogenic climate change. The latter’s effect has been amplified with the arrival of 2023/24 El Niño, causing an exceptional drought in the Amazon basin, significantly affecting fire conditions and hydroelectric power production in several South American countries, including Ecuador. This study analyzes five criteria pollutants—carbon monoxide (CO), nitrogen dioxide (NO₂), sulfur dioxide (SO₂), ozone (O₃), and particulate matter ≤ 2.5 µm (PM_2.5)—during 2019–2024 in Quito, Ecuador, a high-elevation tropical metropolis. Despite long-term efforts to regulate emissions, air pollution levels continue to rise, driven by overlapping crises, including energy shortages, political unrest, and extreme weather events. The persistent failure to improve air quality underscores the vulnerability of developing nations to climate change-induced energy instability and the urgent need for adaptive, diversified, and resilient future energy planning. Without immediate shifts in climate adaptation policies, cities like Quito will continue to experience worsening air quality, with severe implications for public health and environmental sustainability. Full article

The Bayesian approach offers a flexible, interpretable and powerful framework for statistical analysis, making it a valuable tool to help in making optimal decisions under uncertainty. It incorporates prior knowledge or beliefs about the parameters, which can lead to more accurate and informative results. Also, it offers credible intervals as a measure of uncertainty, which are often more interpretable than confidence intervals. Hence, the Bayesian approach is utilized to estimate the parameters, reliability function, hazard rate function and reversed hazard rate function of a new competing risks model. A squared error loss function as a symmetric loss function and a linear exponential loss function as an asymmetric loss function are employed to derive the Bayesian estimators. Credible intervals of the parameters, reliability function, hazard rate function and reversed hazard rate function are obtained. Predicting future observations is important in many fields, from finance and weather forecasting to healthcare and engineering. Thus, two-sample prediction (as a special case of the multi-sample prediction) for future observation is considered. An adaptive Metropolis algorithm is applied to conduct a simulation study to evaluate the performance of the Bayes estimates and predictors. Moreover, two applications of medical and engineering data sets are used to test and validate the theoretical results, ensuring that they are accurate, applicable to real-world scenarios and contribute to the understanding of the world and inform decision-making. Full article

This study sought to explore the determinants of adopting urban tree planting as a method of reducing climate change in the metropolis of Enugu. The 823 respondents were chosen using a multistage random selection process. Logistic regression and descriptive statistics were employed in analysing the data. The study results indicated that the majority (53%) of the respondents were male, with an average age of 36 years. The majority of the households were aware of climate change, since they perceived extreme weather events like drought, a decrease in rainfall, and a rise in temperature. Moreover, the majority of the households experienced a decline in agricultural productivity, a reduction in farm returns, and a rise in unemployment during peak seasons. The mitigation strategy adopted by households for climate change is urban tree planting, and this contributes positively to livelihood improvement. Furthermore, the study results showed that the price of the tree, access to information on the changing climate, access to water, use and access of trees, and occupation positively influenced households’ decisions in adopting urban tree planting. Therefore, we recommend that stakeholders such as governments must promote the delivery of agricultural extension and advisory services by improving their climate information systems, among other strategies to boost their all-inclusive adaptation to the effects of climate change. Full article

In urban environments, radiation energy from the sun becomes a heat load on the human body. The radiation energy can be divided into visible, near-infrared, and far-infrared wavelengths. Far-infrared radiation is re-emitted from structures that have been warmed by the sun. On the other hand, visible and near-infrared light comes directly or reflected from structures. However, previous studies have measured environmental changes using only far-infrared cameras to study urban heat island (UHI) countermeasures. Therefore, it is important to measure the environmental radiation energy at each wavelength region to properly discuss the cause of the heat load. To conduct the measurements, we used three cameras operating at different wavelengths: visible, near-infrared, and far-infrared. In addition, the measurements were conducted in different urban locations, seasons, and weather conditions in the Tokyo area of Japan, an urban metropolis. The results for far-infrared wavelengths show that, in summer when the temperature is high, all structures except the sky have a positive heat load on the human body, while, in winter or cloudy weather when the temperature is low, the heat load on the human body is negative. The results of heat load measurements at visible and near-infrared wavelengths show that the heat load varies greatly depending on the proportion of sky, plants, and buildings, despite the proportion of ground area being the same. These results indicate that the differences in radiation wavelengths need to be considered when considering reducing the heat load on the human body in urban environments. Therefore, the proposed method could contribute to the development of more effective UHI countermeasures by measuring in a various environments and countries. Full article

Background: Neighborhood-scale air pollution sampling methods have been used in a range of settings but not in low air pollution airsheds with extreme weather events such as volatile precipitation patterns and extreme summer heat and aridity—all of which will become increasingly common with climate change. The desert U.S. metropolis of Tucson, AZ, has historically low air pollution and a climate marked by volatile weather, presenting a unique opportunity. Methods: We adapted neighborhood-scale air pollution sampling methods to measure ambient NO₂, NO_x, and PM_2.5 and PM₁₀ in Tucson, AZ. Results: The air pollution concentrations in this location were well below regulatory guidelines and those of other locations using the same methods. While NO₂ and NO_x were reliably measured, PM_2.5 measurements were moderately correlated with those from a collocated reference monitor (r = 0.41, p = 0.13), potentially because of a combination of differences in inlet heights, oversampling of acutely high PM_2.5 events, and/or pump operation beyond temperature specifications. Conclusion: As the climate changes, sampling methods should be reevaluated for accuracy and precision, especially those that do not operate continuously. This is even more critical for low-pollution airsheds, as studies on low air pollution concentrations will help determine how such ambient exposures relate to health outcomes. Full article

This paper studies surface air temperature inversions and their impact on air pollution under the background of meteorological conditions in southern Poland. The relationship of temperature gradients and air quality classes with weather conditions in the most urbanized and polluted part of Poland as represented by the Upper Silesia region (USR) within the administrative boundaries of the Górnośląsko-Zagłębiowska Metropolis (GZM) is presented. Based on probability analysis this study hierarchized the role of the selected weather elements in the development of surface-based temperature inversion (SBI) and air quality (AQ). The thresholds of weather elements for a rapid increase in the probability of oppressive air pollution episodes were distinguished. Although most SBI occurred in summer winter SBIs were of great importance. In that season a bad air quality occurred during >70% of strong inversions and >50% of moderate inversions. Air temperature more strongly triggered AQ than SBI development. Wind speed was critical for SBI and significant for AQ development. A low cloudiness favored SBI occurrence altered air quality in winter and spring during SBI and favored very bad AQ5 (>180 µg/m³) occurrence. The probability of high air pollution enhanced by SBI rapidly increased in winter when the air temperature dropped below −6 °C the wind speed decreased below 1.5 m/s and the sky was cloudless. Changes in the relative humidity did not induce rapid changes in the occurrence of bad AQ events during SBI Full article

Since 1990 the Hanoi capital region (or Hanoi metropolitan area) in Vietnam has undergone rapid development, which has gone together with increasing socio-economic growth and prosperity. However, the environmental degradation that has accompanied urban development has raised considerable concern from the public in recent years. This research investigates the effects of urban development on urban sprawl, urban heat island (UHI), and metropolitan weather phenomena that are related to the quality of urban life in the period from 1999–2016. To achieve these objectives, remote sensing technologies were applied to satellite images at three time points (i.e., 1999, 2009, and 2016) that were associated with the meteorological dataset from ground-based stations. The spatial distribution evolution was examined for the land use/land cover changes while using the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). The increasing impact of urban sprawl on UHI intensity is determined based on the land surface temperature (LST) in multi-temporal forms. Increasing urbanization with the development of gradual outward and northward expansion from the city centre intensified the correlation analysis shows that the UHI. The potential formation of new UHI areas in the near future is also indicated. Furthermore, more than 30% of the metropolitan area is decaying in ecological quality according to an assessment of the urban thermal field variance index (UTFVI). With respect to metropolitan weather, the urbanization in Hanoi affected the observation of meteorological parameters revealed that the relative humidity, total rainfall, temperature, and wind speed over both urban and rural areas. The overall results imply that urban development and its environmental effects and impacts have imposed pressing issues and new challenges to sustainable development in the Hanoi metropolitan area. Full article

Optimal Quantitative Precipitation Estimation (QPE) of rainfall is crucial to the accuracy of hydrological models, especially over urban catchments. Small-to-medium size towns are often equipped with sparse rain gauge networks that struggle to capture the variability in rainfall over high spatiotemporal resolutions. X-band Local Area Weather Radars (LAWRs) provide a cost-effective solution to meet this challenge. The Clermont Auvergne metropolis monitors precipitation through a network of 13 rain gauges with a temporal resolution of 5 min. 5 additional rain gauges with a 6-minute temporal resolution are available in the region, and are operated by the national weather service Météo-France. The LaMP (Laboratoire de Météorologie Physique) laboratory’s X-band single-polarized weather radar monitors precipitation as well in the region. In this study, three geostatistical interpolation techniques—Ordinary kriging (OK), which was applied to rain gauge data with a variogram inferred from radar data, conditional merging (CM), and kriging with an external drift (KED)—are evaluated and compared through cross-validation. The performance of the inverse distance weighting interpolation technique (IDW), which was applied to rain gauge data only, was investigated as well, in order to evaluate the effect of incorporating radar data on the QPE’s quality. The dataset is comprised of rainfall events that occurred during the seasons of summer 2013 and winter 2015, and is exploited at three temporal resolutions: 5, 30, and 60 min. The investigation of the interpolation techniques performances is carried out for both seasons and for the three temporal resolutions using raw radar data, radar data corrected from attenuation, and the mean field bias, successively. The superiority of the geostatistical techniques compared to the inverse distance weighting method was verified with an average relative improvement of 54% and 31% in terms of bias reduction for kriging with an external drift and conditional merging, respectively (cross-validation). KED and OK performed similarly well, while CM lagged behind in terms of point measurement QPE accuracy, but was the best method in terms of preserving the observations’ variance. The correction schemes had mixed effects on the multivariate geostatistical methods. Indeed, while the attenuation correction improved KED across the board, the mean field bias correction effects were marginal. Both radar data correction schemes resulted in a decrease of the ability of CM to preserve the observations variance, while slightly improving its point measurement QPE accuracy. Full article

Urban morphology and increasing building density play a key role in the overall use of energy and promotion of environmental sustainability. The urban environment causes a local increase of temperature, a phenomenon known as Urban Heat Island (UHI). The purpose of this work is the study of the possible formation of an UHI and the evaluation of its magnitude, in the context of a small city, carried out with the ENVI-met^® software. For this purpose, a simulation was needed, and this simulation is preparatory for a monitoring campaign on site, which will be held in the immediate future. ENVI-met^® simulates the temporal evolution of several thermodynamics parameters on a micro-scale range, creating a 3D, non-hydrostatic model of the interactions between building-atmosphere-vegetation. The weather conditions applied simulate a typical Italian summer heat wave. Three different case-studies have been analyzed: Base Case, Cool Case and Green Case. Analysis of the actual state in the Base Case shows how even in an area with average building density, such as the old town center of a small city, fully developed UHI may rise with strong thermal gradients between built areas and open zones with plenty of vegetation. These gradients arise in a really tiny space (few hundreds of meters), showing that the influence of urban geometry can be decisive in the characterization of local microclimate. Simulations, carried out considering the application of green or cool roofs, showed small relevant effects as they become evident only in large areas heavily built up (metropolis) subject to more intense climate conditions. Full article