Atmósfera (Journal)
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Spatiotemporal analysis of different vegetation indices and relation to meteorological parameters over a tropical urban location and its surroundings
Full text linkThe paper investigates the long-term spatiotemporal characteristics of various satellite-derived vegetation indices (VI), such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), as well as Gross Primary Productivity (GPP) and Sun-induced Chlorophyll Fluorescence (SIF) over the Kolkata conurbation and its surrounding areas from 2003 to 2016. Additionally, it analyzes the correlation between these vegetation indices and atmospheric parameters like rainfall, soil moisture (SM), evapotranspiration (ET), and land surface temperature (LST). Monthly variations of these parameters are observed, and inter-annual variability is examined using linear regression techniques. The study also observes the time average spatial correlation between vegetation indices and weather parameters. Moreover, it investigates the time-lag effect (0, 1, 2, and 3 months) using Pearson correlation coefficient analysis between VI and other meteorological parameters. NDVI and EVI exhibit maximum correlation with rainfall, SM, ET, and LST within specific lag periods. NDVI and EVI show a slow response rate to rainfall, and their sensitivity depends on SM and ET. A positive correlation is observed between NDVI and ET, indicating that NDVI increases with vaporized water in the atmosphere. A negative correlation is noted between NDVI and LST in the region studied. The study’s insights are valuable for predicting future vegetation index characteristics based on meteorological parameters in tropical urban areas like Kolkata and its surroundings. This predictive capability can aid in mitigating adverse weather effects on vegetation
Assessment of organic contaminants at a paint manufacturing site: Implications for health risks and source identification
Full text linkThe daily variation of organic contaminants, both gaseous and associated with suspended particulate matter (PM), was investigated within the estate of the National Company of Paintings in Lakhdaria, Algeria, spanning the period 2014-2015. The research emphasizes the chemical characterization of suspended PM, analyzing a range of organic compounds, including n-alkanes, polycyclic aromatic hydrocarbons (PAHs), and highly polar organics (HPOC), such as phthalate esters and heterocyclic compounds. Vapors of PAHs and polychlorobiphenyls (PCBs) were also analyzed. Low molecular weight compounds were primarily associated with the gas phase (two-ring PAHs, approximately 95%; three-ring PAHs, around 70%), while high molecular weight congeners were mainly associated with the particle phase (six-ring PAHs, 55%). The concentrations of PCBs (ranging from 0.6 to 42 ng m–3) were higher than those reported in other cities in Algeria and Europe. The source reconciliation of organic contaminants through principal component analysis (PCA) demonstrated that the primary sources were petroleum combustion, industrial manufacturing, tobacco smoking, and vehicular traffic. The significance of tobacco smoke was further confirmed by the analysis of PAH diagnostic ratios. Differences in the rates of diagnostic ratios between gaseous and particulate PAHs were attributed to distinct contributions from sources such as industrial processes. Health risks for workers exposed to PAHs and PCBs in PM < 10 μm (PM10) were quantitatively assessed in terms of benzo[a]pyrene equivalent concentration and incremental lifetime cancer risk (ILCR). The ILCR presents novel findings showcasing heightened risks among workers exposed to specific PAHs within production areas, whereas those related to PCBs suggested a high potential of health risks for laboratory workers
Indoor dust composition of university laboratories and potential health risks in Pahang, Malaysia
Full text linkDust pollution poses a significant risk to human health and natural systems, and has a substantial impact on the overall quality of both outdoor and indoor air. Dust also plays a crucial role in transporting metal elements in an indoor environment. This study examines the levels of specific metals (Al, Fe, Cu, Pb, Zn) present in dust samples collected from two laboratories in UiTM Cawangan Pahang, Malaysia. The analysis focuses on assessing pollution levels and potential impacts on human health. The concentrations of metal were significantly higher in Lab 2. Moderate enrichment of Zn was found in the indoor dust samples. Both laboratories showed that the major route of exposure to metals posing health risks was ingestion, followed by skin contact and inhalation, for individuals of all age groups, including adults and children. Zn and Pb exhibited higher potential non-cancer risk than Fe and Cu. The hazard index (HI) and lifetime cancer risk (LCR) were within acceptable thresholds (HI < 1 and 10–6 < LCR < 10–4) in both laboratories
Comparison of COSMO and ICON-LAM high-resolution numerical forecast for Romanian territory: Case studies and evaluation
Full text linkThis paper aims to offer the first detailed inter-comparison of the performance from the numerical weather prediction models Consortium for Small-scale Modeling (COSMO) and Icosahedral Nonhydrostatic General Circulation Model, Limited Area Mode (ICON-LAM), integrated for the Romanian territory at the horizontal resolution of 2.8 km. As the ICON numerical model is set to replace COSMO, a comparison is carried out between the operational configurations of the two models. First, two cases with severe weather (strong atmospheric instability, observed heavy precipitation, and strong wind) are analyzed: February 3-6, 2020 (heavy precipitation [snow] and very strong wind) and May 3-5, 2020 (heavy precipitation). This is followed by a statistical inter-comparison between the two models for the summer of 2020 (June, July, August). A statistical evaluation of the forecast quality from the two models is performed objectively, through statistical scores computed using surface observations from all available meteorological stations on the Romanian territory. Stratifications depending on station altitude and location are carried out, with emphasis on stations of particular interest, depending on the evolution of the synoptic situation. Following the statistical evaluation, results for the precipitation forecast do not show significant improvement in favor of either model. However, ICON-2.8 km mostly outperforms COSMO-2.8 km for surface parameters
Studies on airborne microbiota in Mexico, a review
Full text linkAirborne microbiota has garnered increasing interest in recent decades, not only because of its role as carrier of pathogenic microorganisms and its involvement in the deterioration of man-made objects, buildings, and food but also because of its participation in atmospheric processes and its content of microorganisms important for biogeochemical cycles in different ecosystems. In order to understand and comprehensively analyze existing studies on airborne microbiota in Mexico, a systematic review was conducted utilizing Web of Science and Google Scholar as search tools. The information found in the 35 identified publications was systematically organized, including title, study location, sampling method, laboratory approach, identification method, and organisms found. This information was then ordered into three sections: bibliometric analysis, employed methodologies, and main findings. Through this work, it was revealed that the studies were carried out in 14 out of the 32 states of Mexico, with Mexico City standing out with 17 articles. Three methodological approaches were identified: microbial cultures (77% of the studies), microscopy (11.5%), and metagenomics (11.5%). The studies predominantly focused on state capitals or densely populated cities, making the identification of potentially pathogenic organisms from humans, animals, and plants, of particular interest. This comprehensive review lays the foundation for proposing compelling avenues of future research, aimed at advancing our comprehension of airborne microbiota in Mexico
Enhancing geostatistical precipitation estimations for the Santiago River basin, Mexico
Full text linkAccurate precipitation estimation is crucial for understanding the hydrological cycle, its applications in basin-specific planning, and outliers event prediction. Multivariate geostatistics leverage correlated variables, such as terrain elevation and shoreline distance, to reduce estimation error uncertainty. However, the distinct characteristics of humid and dry seasons demand specific estimation approaches. Precise precipitation estimation poses a challenge in the vast and diverse Santiago River basin (SRB) along Mexico’s west coast. This study assessed precipitation estimates for dry and humid seasons using ordinary kriging and ordinary cokriging with altitude and shoreline distance as auxiliary variables. Evaluation of error metrics revealed superior results incorporating shoreline distance as a covariable in the wet month of July, especially after logarithmic transformation, yielding a 17% improvement in average standardized error compared to the univariate approach. Conversely, optimal results were achieved for the dry month (February) using ordinary kriging excluding outliers’ values, effectively reducing the average squared error
Orinoco revisited: Comprehensive analysis of the Orinoco River basin present and future hydroclimate
Full text linkThe Orinoco River basin, ranked as South America’s third-largest catchment, is pivotal in contributing to the Atlantic Ocean’s water volume. This study provides a comprehensive update on the basin’s surface water balance, examining trends using gridded precipitation and total evaporation datasets. We also explore projected changes in precipitation until the end of the 21st century, focusing on the RCP8.5 climate change scenario. To achieve this, we utilize data from regional climate models designed by the CORDEX-CORE experiment, selecting an ensemble that excels in performance across South America and Central America. We estimate the accuracy of reference datasets in capturing water balance dynamics. We identify increasing trends in precipitation and total evaporation across most of the basin, enhancing our understanding of its long-term hydrological balance. Notably, the Andean and Guianese sectors of the basin contribute equally to half of the mean surface runoff, although the latter encompasses only 30% of the total area. This underscores the key role of the Guianese shield sub-basins. In regional climate modeling, despite some underestimation, the model runs for the CORDEX South America domain simulate effectively the precipitation across the basin. Regarding climate scenarios, our analysis using the RCP8.5 scenario projects an average annual precipitation reduction of around 45% for the entire basin. These findings emphasize the urgency of adopting measures to mitigate potential adverse effects on the Orinoco River basin’s hydrological sustainability in response to evolving climate patterns
Severe winter conditions in the Citlaltepetl-Cofre de Perote mountain range, 2021-2022
Full text linkThe central border that divides the states of Puebla and Veracruz is characterized by being the highest territorial limit in Mexico; it is composed of three of the highest mountains in the country. This border reaches a length of 100 km, forming a watershed that continuously exceeds 3000 m in altitude. Due to its elevation, winter freezing conditions are frequent; however, due to changing climate patterns, in recent winter seasons, severe frosts and snowfalls have occurred at elevations well below the main peaks, affecting the health of thousands of vulnerable residents of both states surrounding this mountain range. Because the 2021-2022 winter season was one of the most intense in all North America, with severe impacts in Mexico as a result of freezing temperatures and snowfall, this work analyzes the winter conditions in 2021-2022 through the monitoring of frontal systems and the analysis of data from automatic meteorological stations near the study area. From the records, the lower limit of surface freezing was estimated for each arrival of cold air masses; the occurrence of snowfall was determined by remote sensing, and the area of snow cover was also calculated. At the same time, the population affected by freezing weather conditions was estimated. The surface freezing starts at elevations as low as 2259 m, covering an area of up to 2949 km2, which corresponds to the entire study region, affecting 139 towns in Veracruz and 163 in Puebla
The effects of climate warming on large-scale atmospheric systems of the Northern Hemisphere
Full text linkIn the present study, we examine the impact of climate warming on the variability of the main climatic drivers in the northern hemisphere, using 40 years (1979-2018) of ERA-Interim reanalysis data. We applied Sen’s slope estimator and the Mann-Kendall significance test to identify regions with significant variability of 500-1000 hPa thickness. The findings reveal that climate warming is particularly pronounced at latitudes ranging from 80º to 90º and also in subtropical regions. The increase in thickness is most notable in mid-latitudes during the summer season, owing to climate warming. The steeper trend slope observed in autumn indicates a faster warming rate compared to other seasons. Moreover, despite climate warming, significant trends in large-scale atmospheric circulation systems demonstrate the strengthening of the Siberian high-pressure in winter and autumn. Additionally, a segment of the core of the Azores high-pressure system has also experienced strengthening during winter. Conversely, the monsoon and Aleutian low-pressure systems have weakened in spring and winter, respectively. The subtropical high-pressure system exhibits a positive and significant trend in winter, spring, and summer, aligning with the positive significant trends observed in atmospheric thickness, thereby confirming the effects of climate warming
Comparison of different drought monitoring indices in different climatic conditions in Iran
Full text linkThis study evaluates drought in different climate zones (Rasht, Shiraz, and Birjand) in Iran, using meteorological, agricultural, and remote sensing drought indices. For this purpose, NDVI, SAVI, and SR were extracted from Landsat images for 2002 and 2014-2020. Then, these indices were compared with the SPI, SPEI, and PDSI. The results indicate an increase in drought and a decrease in vegetation cover in the study area. In Rasht, where the vegetation cover is high, NDVI and SAVI were equal. In Shiraz and Birjand, where the soil effect is more significant, the distance between these two indices increased, which shows that SAVI performs better than NDVI for Shiraz and Birjand. The results also show that the drought severity could grow with decreasing rainfall and more water demand due to temperature increases, according to SPI, SPEI, and PDSI criteria. The comparison of drought indices showed that the highest correlations were between NDVI plus SAVI and SPI in Rasht, SR and SPEI in Shiraz, and NDVI and SPEI in Birjand. Based on the results of the Mann-Kendall test, the increasing trend of drought in the studied area is confirmed based on the SPI, SPEI, and PDSI. Therefore, it is suggested that remote sensing techniques combined with drought indices can be considered a suitable tool for optimal management of water resources, land use planning, and reduction of costs due to drought