Hasil untuk "Meteorology. Climatology"

Rubia Truppel, Anderson D’Oliveira, Laura Canale et al.

This review investigates and analyzes the state of the art on scientific evidence related to educational interventions to improve air quality indoors and outdoors through a mapping review. The review followed proposed guidelines for mapping reviews in environmental sciences and the steps described in the Template for a Mapping Study Protocol. The search was conducted in PubMed, Web of Science, Embase, Cinahl, and Google Scholar with no language restrictions, and was completed in January 2025. Three filters were applied: search, selection with inclusion and exclusion criteria (PECOS strategy), and data extraction. Two independent reviewers assessed article eligibility, and disagreements were resolved by a third researcher. Twenty-four studies that met the eligibility criteria were included. Five research questions were answered. Studies published between 1977 and 2024 were included, totaling 7289 participants aged 12 to 85. The geographic distribution was concentrated in China (five studies) and the United States (four studies), followed by South Korea, India, Australia, and other countries, with fewer publications. The methodological predominance was experimental studies; observational studies were also analyzed, although less frequently. The period with the greatest increase in the number of publications was between 2020 and 2024. The educational methods most commonly used in the studies were lectures and the delivery of information leaflets. Particulate matter with diameters of 2.5 μm and 10 μm (PM_2.5 and PM₁₀) were the most widely investigated pollutants in the studies. From our analyses, it was observed that the educational interventions to improve air quality, adopted in the selected studies, resulted in the acquisition of knowledge about the environmental effects and the importance of individual actions. The changes in behavior included the adoption of more sustainable practices and an improvement in air quality in the environment, with a significant reduction in pollutant emissions. We conclude that interventions through environmental education demonstrate great potential to improve air quality. Based on the mapped evidence, governments and global policymakers can use this information to develop new strategies or improve existing ones to reduce air pollution in affected environments and regions.

Angela Maria de Arruda, Luana Nunes Centeno, André Becker Nunes

This study analyzed the correlation between climate indices—El Niño–Southern Oscillation (NINO34), Southern Oscillation Index (SOI), Antarctic Oscillation (AOC), Sea Surface Temperature in the southwestern Atlantic (ISSTRG2 + RG3), South Atlantic Subtropical High (SASH), Pacific Decadal Oscillation (PDO), and Madden–Julian Oscillation (MJO)—and precipitation in Rio Grande do Sul (RS) during 45-day subseasonal periods from 2006 to 2022. Precipitation data from 670 rain gauges were categorized into three clusters: cluster 1, located in western RS, displayed the lowest precipitation variation; cluster 2, in eastern RS, exhibited the greatest variability; and cluster 3, situated in northern RS. ENSO demonstrated the strongest positive correlation with precipitation during spring in clusters 1 and 3 (0.65–0.79), while PDO also correlated positively, especially in summer and spring. AOC exhibited negative correlations, most pronounced in spring. Significant inter-index correlations were identified, including a high positive correlation between SASH and AOC (0.7) and a high negative correlation between NINO34 and SOI (−0.73). Within clusters, NINO34 and PDO showed low positive correlations with precipitation (0.24–0.32), while SOI demonstrated low negative correlations (−0.21 to −0.30). Seasonal analysis revealed that NINO34 influenced summer and spring precipitation, correlating with above-average rainfall during El Niño events. SASH and PDO also showed positive correlations with summer and spring rainfall, with PDO’s positive phase associated with a 25% increase in precipitation. These findings provide valuable insights into the complex interactions between global climatic indices and regional precipitation patterns, enhancing the understanding of subseasonal climate variability in RS and supporting the development of more accurate climate prediction models for the region.

Pham Quy Giang, Rajendra Khanal

Vietnam is a coastal country with a coastline stretching more than 3,260 km. Marine resources are important for the development of Vietnam. In Vietnamese seas, there are about 20 typical ecosystems spreading over 1 million square kilometers in the East Sea consisting of mangrove forests, coral reefs, lagoons, seagrasses in intertidal areas and estuaries, and living species in 155,000 hectares, 1,300 square kilometers, 500 square kilometers, 16,000 hectares, and 11,000 living species, respectively. At present, the impact of climate change, socio-economic development, and environmental pollution are considered as the main causes of degradation of Vietnam’s marine ecosystems. This paper presents and discusses the pressure of socio-economic activities including industry, tourism, marine transportation and services, aquaculture and fishery on marine ecosystems. In Vietnam, compared to the early 2000s a total of 12% of coral reefs, and 48% of other coral reefs are vulnerable to degradation. So far, about 100 species of marine life in Vietnam are at risk of being threatened due to over-exploitation and fishing. The seagrass-bed ecosystem is currently being degraded with only over 5,580 ha remaining. In some areas, such as Cat Ba, Ha Long, and Quang Nam, seagrass beds have almost no chance to recover naturally due to serious impacts from tourism and aquaculture activities. From the findings, orientations that aim at effective management and protection of marine ecosystems to cope with adverse impacts of anthropogenic activities, climate change, and the pressure of socioeconomic development were proposed.

Vassilis Amiridis, Stelios Kazadzis, Antonis Gkikas et al.

The Mediterranean, and particularly its Eastern basin, is a crossroad of air masses advected from Europe, Asia and Africa. Anthropogenic emissions from its megacities meet over the Eastern Mediterranean, with natural emissions from the Saharan and Middle East deserts, smoke from frequent forest fires, background marine and pollen particles emitted from ocean and vegetation, respectively. This mixture of natural aerosols and gaseous precursors (Short-Lived Climate Forcers—SLCFs in IPCC has short atmospheric residence times but strongly affects radiation and cloud formation, contributing the largest uncertainty to estimates and interpretations of the changing cloud and precipitation patterns across the basin. The SLCFs’ global forcing is comparable in magnitude to that of the long-lived greenhouse gases; however, the local forcing by SLCFs can far exceed those of the long-lived gases, according to the Intergovernmental Panel on Climate Change (IPCC). Monitoring the spatiotemporal distribution of SLCFs using remote sensing techniques is important for understanding their properties along with aging processes and impacts on radiation, clouds, weather and climate. This article reviews the current state of scientific know-how on the properties and trends of SLCFs in the Eastern Mediterranean along with their regional interactions and impacts, depicted by ground- and space-based remote sensing techniques.

Robert G. Fovell, Matthew J. Brewer

This study investigates the predictability of downslope windstorms located in Santa Barbara County, California, locally referred to as Sundowner winds, from both observed relationships and a high-resolution, operational numerical weather prediction model. We focus on April 2022, during which the Sundowner Winds Experiment (SWEX) was conducted. We further refine our study area to the Montecito region owing to some of the highest wind measurements occurring at or near surface station MTIC1, situated on the coast-facing slope overlooking the area. Fires are not uncommon in this area, and the difficulty of egress makes the population particularly vulnerable. Area forecasters often use the sea-level pressure difference (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mo>Δ</mo></semantics></math></inline-formula>SLP) between Santa Barbara Airport (KSBA) and locations to the north such as Bakersfield (KBFL) to predict Sundowner windstorm occurrence. Our analysis indicates that <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mo>Δ</mo></semantics></math></inline-formula>SLP by itself is prone to high false alarm rates and offers little information regarding downslope wind onset, duration, or magnitude. Additionally, our analysis shows that the high-resolution rapid refresh (HRRR) model has limited predictive skill overall for forecasting winds in the Montecito area. The HRRR, however, skillfully predicts KSBA-KBFL <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mo>Δ</mo></semantics></math></inline-formula>SLP, as does GraphCast, a machine learning weather prediction model. Using a logistic regression model we were able to predict the occurrence of winds exceeding 9 m <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><msup><mi mathvariant="normal">s</mi><mrow><mo>−</mo><mn>1</mn></mrow></msup></semantics></math></inline-formula> with a high probability of detection while minimizing false alarm rates compared to other methods analyzed. This provides a refined and easily computed algorithm for operational applications.

Sheau Tieh Ngai, Srivatsan V. Raghavan, Jing Xiang Chung et al.

To address the gap in understanding precipitation changes in Southeast Asia and to enhance the reliability of climate projections for the region through moisture budget analysis, this study examines the differences among six multi-model ensembles of CMIP6 simulated precipitation in term of moisture budget analysis. It investigates the relative contributions of thermodynamic and dynamic components to seasonal precipitation changes over Southeast Asia under the highest emission scenario, SSP5-8.5. The comparison between ensembles indicates that Good performance model ensembles slightly outperform the combination of all resolution and all category ensembles in reducing the biases. There is no strong evidence showing that good category ensembles outperform the combination of all model ensemble groups in simulating the spatial pattern of historical seasonal precipitation. From the perspective of moisture budget, regions receiving seasonal high rainfall intensity are mainly influenced by the moisture convergence during the monsoon seasons: northeast monsoon (December‒January‒February) and southwest monsoon (June–July–August). By the late 21st century (2081–2100), all model ensemble projections show an increase in December‒January‒February precipitation over the northern Southeast Asia and decreased June‒July‒August rainfall in the southern regions. The moisture budget analysis explained that the seasonal mean rainfall change in Southeast Asia is largely influenced by evaporation and followed by moisture flux convergence. The changes in moisture flux convergence are contributed by both the dynamic and thermodynamic components. Greater inter-model uncertainty was found in the precipitation dynamic component compared to the thermodynamic component suggesting the existence of large discrepancy between the various approaches used by GCMs in describing atmospheric dynamics. The study highlights that the Good model ensemble with middle to low resolution is able to narrow the inter-model uncertainties in terms of the moisture budget analysis compared to the combination of all Good model ensembles.

J. Tacza, G. Li, J.‐P. Raulin

Abstract The suppression of high‐energy cosmic rays, known as Forbush decreases (FDs), represents a promising factor in influencing the global electric circuit (GEC) system. Researchers have delved into these effects by examining variations, often disruptive, of the potential gradient (PG) in ground‐based measurements taken in fair weather regions. In this paper, we aim to investigate deviations observed in the diurnal curve of the PG, as compared to the mean values derived from fair weather conditions, during both mild and strong Forbush decreases. Unlike the traditional classification of FDs, which are based on ground level neutron monitor data, we classify FDs using measurements of the Alpha Magnetic Spectrometer (AMS‐02) on the International Space Station. To conduct our analysis, we employ the superposed epoch method, focusing on PGs collected between January 2010 and December 2019 at a specific station situated at a low latitude and high altitude: the Complejo Astronómico El Leoncito (CASLEO) in Argentina (31.78°S, 2,550 m above sea level). Our findings reveal that for events associated with FDs having flux amplitude (A) decrease ≤10%, no significant change in the PG is observed. However, for FDs with A > 10%, a clear increase in the PG is seen. For these A > 10% events, we also find a good correlation between the variation of Dst and Kp indices and the variation of PG.

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Christos Mourgelas, Evangelia Micha, Emmanouil Chatzistavrakis et al.

Nikki Choudhary, Akansha Rai, Jagdish Chandra Kuniyal et al.

This study presents the source apportionment of coarse-mode particulate matter (PM₁₀) extracted by 3 receptor models (PCA/APCS, UNMIX, and PMF) at semi-urban sites of the Indian Himalayan region (IHR) during August 2018–December 2019. In this study, water-soluble inorganic ionic species (WSIIS), water-soluble organic carbon (WSOC), carbon fractions (organic carbon (OC) and elemental carbon (EC)), and trace elements of PM₁₀ were analyzed over the IHR. Nainital (62 ± 39 µg m⁻³) had the highest annual average mass concentration of PM₁₀ (average ± standard deviation at 1 σ), followed by Mohal Kullu (58 ± 32 µg m⁻³) and Darjeeling (54 ± 18 µg m⁻³). The annual total ∑WSIIS concentration order was as follows: Darjeeling (14.02 ± 10.01 µg m⁻³) > Mohal-Kullu (13.75 ± 10.21 µg m⁻³) > Nainital (10.20 ± 6.30 µg m⁻³), contributing to 15–30% of the PM₁₀ mass. The dominant secondary ions (NH₄⁺, SO₄²⁻, and NO₃⁻) suggest that the study sites were strongly influenced by anthropogenic sources from regional and long-range transport. Principal component analysis (PCA) with an absolute principal component score (APCS), UNMIX, and Positive Matrix Factorization (PMF) were used for source identification of PM₁₀ at the study sites of the IHR. All three models showed relatively similar results of source profiles for all study sites except their source number and percentage contribution. Overall, soil dust (SD), secondary aerosols (SAs), combustion (biomass burning (BB) + fossil fuel combustion (FFC): BB+FFC), and vehicular emissions (VEs) are the major sources of PM₁₀ identified by these models at all study sites. Air mass backward trajectories illustrated that PM₁₀, mainly attributed to dust-related aerosols, was transported from the Thar Desert, Indo-Gangetic Plain (IGP), and northwestern region of India (i.e., Punjab and Haryana) and Afghanistan to the IHR. Transported agricultural or residual burning plumes from the IGP and nearby areas significantly contribute to the concentration of carbonaceous aerosols (CAs) at study sites.

Zhanling Li, Wen Li, Zhanjie Li et al.

Understanding the impact of climate change on runoff and its extremes is of great significance for water resource assessment and adaptation strategies, especially in water-scarce regions. This study aims to analyze the impact of future climate change on runoff and its extremes in the upper reaches of the Heihe River basin in northwest China. The projected runoff was derived using the Soil Water Assessment Tool with climate data from the CSIRO-MK-3-6-0 model under the scenario of RCP4.5, and a frequency analysis of runoff was performed by generalized extreme value distribution. The results indicate that, compared with the baseline period of 1961 to 2000, the minimum and maximum temperatures in the period 2031 to 2070 were predicted to increase by 2.5 °C on average. The precipitation in most months was also predicted to increase, with an average rise of 16.5%. The multi-year average runoff was projected to increase by 8%. The annual mean and extreme flows were also expected to rise under future climate change at different return periods, and the low flow was expected to increase the most.

P. Mangala C.S. De Silva, E.M.D.V. Ekanayake, T.D.K.S.C. Gunasekara et al.

Aim: Chronic kidney disease of uncertain aetiology (CKDu) is an emerging health concern in tropical farming communities. The role of occupational heat exposure as a potential driver of CKDu remains debated. Our study examines occupational heat exposure and kidney health in three occupational groups in Sri Lanka. Methodology: We recruited participants from three occupational groups from three climatic zones; fisherfolk from the dry and intermediate zones (N = 225), paddy farmers from the intermediate zone (N = 180) and tea plantation workers from the wet zone (N = 70). Serum creatinine, cystatin-C, urea and uric acid, estimated glomerular filtration rate and urinary albumin-creatinine ratio were used as diagnostic criteria of impaired renal function. Results: CKDu susceptibility was at the highest among farmers (13.33 %), with a significant difference compared to the fisherfolk (5.36 %; p = 0.0003). Among the plantation workers, CKDu susceptibility was 5.71 %, and it was not significantly different compared to the farmers (p = 0.087) and the fisherfolk (p = 0.427). Despite higher exposure to heat stress and dehydration, as indicated by the highest simplified wet bulb globe temperature (sWBGT) in the work environments, fisherfolk reported the lowest CKDu susceptibility, while farmers and workers with low to moderate heat exposure showed an increased incidence of abnormal renal function. Further, a multivariable regression analysis identified a significant effect of occupation (p = 0.005), agrochemical exposure (p = 0.001) and age (p = 0.001) on the likelihood of CKDu susceptibility while the sWBGT in the working environments showed no significant effect (p = 0.227). Conclusion: With the evidence from our findings, heat exposure alone does not appear to be the leading driver of CKDu in Sri Lanka, suggesting that the nephropathy is more likely to be associated with occupational risks such as agrochemical exposures.

Fatwa Ramdani, Putri Setiani

Abstract The global pandemic of COVID‐19 has been insisted by many countries in the world to implement social distancing, including Indonesia. This research measured the environmental impact before and during the COVID‐19 pandemic in Indonesia. Variables, such as nitrogen dioxide (NO2) of Sentinel‐5P Tropospheric Monitoring Instrument (Tropomi), nighttime light condition of Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) and land surface temperature (LST) of Thermal InfraRed Sensor (TIRS) of Landsat‐8 Operational Land Imager (OLI), were monitored using the cloud‐based computing platform of Google Earth Engine (GEE). This study found that all monitored variables decreased during the period of the COVID‐19 pandemic compared to the period before the pandemic. However, the pattern of reduction of NO2 concentration and nighttime light was not observed to be coherent with large‐scale social distancing regulation enforced by the government. This study found that the reduction has begun 2 months earlier than the official regulation enforced by the government. The lower LST shown in both the time‐series map and the graph demonstrated changes before and during the pandemic. The hypothesis was tested using the t‐test method, and the statistical results show the significant difference between two groups of observed variables (e.g. before and during the pandemic) with the lower p‐values and higher Cohen's d. Results of this study indicate that it should be feasible to monitor the environmental impact of the COVID‐19 pandemic using the combination of NO2 concentration, nighttime light and LST information as a proxy.

T. Kuzmina, Yu. Kuzmin, O. Salganskiy et al.

Helminth community of the Antarctic black rockcod, Notothenia coriiceps, was examined using the fish samples collected in 2014—2015 (106 specimens) and 2020—2021 (78 specimens) in the water area of the Argentine Islands, West Antarctica. In total, 30,951 helminth specimens were collected and identified. We analyse the helminth infra- and component communities and investigate possible changes in the main parameters of helminth communities of N. coriiceps during the six-year period. Thirty species of helminths from five taxonomic groups were recorded: one species of Monogenea, 5 of Nematoda, 4 of Cestoda, 9 of Trematoda, and 11 of Acanthocephala. Notothenia coriiceps was found to be the definitive host of 18 helminth species; 12 species parasitize it in the larval stage using N. coriiceps as the second intermediate or paratenic host. The proportion of larval helminths in the samples was lower in 2014—2015 (73.4%) than in 2020—2021 (81.4%). The number of dominant helminth species (infection prevalence >50%) increased from seven in 2014—2015 to nine in 2020—2021. In helminth infracommunities, the species richness was similar in two samples. On the other hand, we found significantly higher helminth abundance in the infracommunities from the sample collected in 2020—2021. In the helminth component community, the diversity indices (Shannon, Simpson, Pielou, Berger-Parker) evidenced higher evenness and lower domination in the sample collected in 2014—2015 compared to the sample collected in 2020—2021. Lower evenness in 2020—2021 was due to the larger relative abundance of larval Pseudoterranova sp. and Corynosoma spp. We suggest a deeper investigation of the role of separate helminth species in the component community changes, as well as further monitoring of component community parameters as prospective directions for future studies of helminth communities of N. coriiceps in West Antarctica.

Magda Claeys, Willy Maenhaut

In this review, we cover selected research on secondary organic aerosol (SOA) formation from isoprene, from the beginning of research, about two decades ago, to today. The review begins with the first observations of isoprene SOA markers, i.e., 2-methyltetrols, in ambient fine aerosol and focuses on studies dealing with molecular characterization, speciation, formation mechanisms, and source apportionment. A historic account is given on how research on isoprene SOA has developed. The isoprene SOA system is rather complex, with different pathways being followed in pristine and polluted conditions. For SOA formation from isoprene, acid-catalyzed hydrolysis is necessary, and sulfuric acid enhances SOA by forming additional nonvolatile products such as organosulfates. Certain results reported in early papers have been re-interpreted in the light of recent results; for example, the formation of C₅-alkene triols. Attention is given to mass spectrometric and separation techniques, which played a crucial role in molecular characterization. The unambiguous structural characterization of isoprene SOA markers has been achieved, owing to the preparation of reference compounds. Efforts have also been made to use air quality data to estimate the influence of biogenic and pollution aerosol sources. This review examines the use of an organic marker-based method and positive matrix factorization to apportion SOA from different sources, including isoprene SOA.

Elisa M. Murillo, Cameron R. Homeyer

Udo Dorian RECKERTH, Eugen Marian Nicolae MIHULEȚ, Gabriela Victoria HARPA et al.

The purpose of this study is the identification of the areas with an increased frequency of convective developments, especially those affected by hail. All convective cells accompanied by hail, developed in the 2019 warm season in Bobohalma WSR-98D coverage radius were analyzed, in order to determine their areas of action in May-September 2019, as well as the mesocyclones detected. With the help of a soft created in Python programming language and developed within South - Transylvania Regional Forecast Center – Sibiu, all the signals with hail larger than 0.5 inches (1.27 cm) were extracted from the hail algorithms generated by the Principal User Processor (PUP).

Cari Rand, Brent M. Goehring

We quantify the magnitude of millennial-scale glacial erosion at Engabreen, a temperate glacier in coastal northern Norway, using the in situ cosmogenic nuclides carbon-14 (14C) and beryllium-10 (10Be) in bedrock exposed recently by glacial retreat. Nuclide concentrations show no dependence on distance down or across the valley. As such, resulting Holocene erosion depths along two transects perpendicular to glacier flow are highly variable with no systematic distribution, ranging from 0.10 to 2.95 m. We observed 14C–10Be ratios elevated above the production ratio in samples of abraded bedrock, which is counter to the expectation for surfaces covered during the Holocene and exposed only recently. Muon reactions produce nuclides at greater depths than do spallation reactions and 14C at production rates at higher than those of 10Be, resulting in 14C–10Be ratios that increase with depth. Therefore, elevated 14C–10Be ratios indicate that sampled sites were deeply plucked during recent cover, the Little Ice Age in this case, and then rapidly abraded prior to retreat. Our results suggest that, while glacial erosion can generate a u-shaped valley profile over long periods of time (e.g., 105–107 years), the discontinuous nature of glacial plucking produces spatially variable patterns of erosion over shorter millennial timescales.

Masamichi Oura, Ryohji Ohba, Alan Robins et al.

For more than fifty years, atmospheric dispersion predictions based on the joint use of a Gaussian plume model and wind tunnel experiments have been applied in both Japan and the U.K. for the evaluation of public radiation exposure in nuclear safety analysis. The effective source height used in the Gaussian model is determined from ground-level concentration data obtained by a wind tunnel experiment using a scaled terrain and site model. In the present paper, the concentrations calculated by this method are compared with data observed over complex terrain in the field, under a number of meteorological conditions. Good agreement was confirmed in near-neutral and unstable stabilities. However, it was found to be necessary to reduce the effective source height by 50% in order to achieve a conservative estimation of the field observations in a stable atmosphere.

Junjie Li, Xiao-Bing Li, Bai Li et al.

In recent years, road space rationing policies have been increasingly applied as a traffic management solution to tackle congestion and traffic emission problems in big cities. Existing studies on the effect of traffic policy on air quality have mainly focused on the odd&ndash;even day traffic restriction policy or one-day-per-week restriction policy. There are few studies paying attention to the effect of nonlocal license plate restrictions on air quality in Shanghai. Restrictions toward nonlocal vehicles usually prohibit vehicles with nonlocal license plates from entering certain urban areas or using certain subsets of the road network (e.g., the elevated expressway) during specific time periods on workdays. To investigate the impact of such a policy on the residents&rsquo; exposure to pollutants, CO concentration and Air Quality Index (AQI) were compared during January and February in 2015, 2016 and 2017. Regression discontinuity (RD) was used to test the validity of nonlocal vehicle restriction on mitigating environmental pollution. Several conclusions can be made: (1) CO concentration was higher on ground-level roads on the restriction days than those in the nonrestriction days; (2) the extension of the restriction period exposed the commuters to high pollution for a longer time on the ground, which will do harm to them; and (3) the nonlocal vehicle restriction policy did play a role in improving the air quality in Shanghai when extending the evening rush period. Additionally, some suggestions are mentioned in order to improve air quality and passenger health and safety.