Meteorological Effects Research Articles

Cleaner Pandemic Air Led to Reduced Lightning Strikes Worldwide

As people stayed home during the COVID-19 lockdowns, air quality improved. But the improvement was accompanied by an unusual meteorological side effect: a decrease in lightning.

Evaluating the Meteorological Effects on the Urban Form-Air Quality Relationship Using Mobile Monitoring.

Predictive models based on mobile measurements have been increasingly used to understand the spatiotemporal variations of intraurban air quality. However, the effects of meteorological factors, which significantly affect the dispersion of air pollution, on the urban-form-air-quality relationship have not been understood on a granular level. We attempt to fill this gap by developing predictive models of particulate matter (PM) in the Bronx (New York City) using meteorological and urban form parameters. The granular PM data was collected by mobile low-cost sensors as the ground truth. To evaluate the effects of meteorological factors, we compared the performance of models using the urban form within fixed and wind-sensitive buffers, respectively. We find better predictive power in the wind-sensitive group (R = 0.85) for NC10 (number concentration for particles with diameters of 1 μm-10 μm) than the control group (R = 0.01), and modest improvements for PM2.5 (R = 0.84 for the wind sensitive group, R = 0.77 for the control group), indicating that incorporating meteorological factors improved the predictive power of our models. We also found that urban form factors account for 62.95% of feature importance for NC10 and 14.90% for PM2.5 (9.99% and 4.91% for 3-D and 2-D urban form factors, respectively) in our Random Forest models. It suggests the importance of incorporating urban form factors, especially for the uncommonly used 3-D characteristics, in estimating intraurban PM. Our method can be applied in other cities to better capture the influence of urban context on PM levels.

Variations and Source Apportionment of PM2.5 and PM10 Before and During COVID-19 Lockdown Phases in Delhi, India

Major cities across the globe including megacity Delhi have experienced considerable lower levels of air pollutants including particulate matter (PM) during COVID-19 lockdown. This study explores pre-lockdown and during lockdown air quality changes in PM2.5, PM10, PM2.5/PM10 ratio along with meteorological effects. Selected sites with different pollution signatures in Delhi including Alipur (residential), Okhla (industrial) and Pusa Road (traffic) have experienced mean (S.D.) PM2.5 as 87.56(± 54.06), 124.45(± 73.49) and 62.14(± 58.64) µg/m3 and PM10 as 163.01(± 77.37), 217.71(± 93.94) and 135.15(± 77.90) µg/m3 before lockdown (BL), while for Lockdown 1 (L1), PM2.5 concentrations decreased drastically as 39.26(± 16.31), 38.01(± 15.16) and 31.03(± 12.79) µg/m3 and for PM10 as 100.76(± 43.71), 79.47(± 30.97) and 66.53(± 22.78) µg/m3, respectively, with gradual increase in both pollutants during successive lockdown phase—Lockdown 2, Lockdown 3, Lockdown 4 and Unlock phase 1. The percentage (%) decrease in PM2.5 (69.46%) and PM10 (63.49%) during lockdown was found well correlated with people mobility (Google and Apple mobility reports), as outdoor activities showed 70–80% decrease in L1 from BL phase. Source apportionment studies suggested both local and regional pollution contribution in Delhi. Comparison of PM2.5 and PM10 concentrations for the year 2020 with that of 2018 and 2019 and study on diurnal variations of PM2.5 and PM10 have been discussed.

Airborne Environmental Threats to Health & Wellness-An Integrated Overview

Background: The environmental pollution is a growing world problem specifically in developed & developing countries. In these areas G.I.T disorders & diarrheal diseases have replaced by airborne environmental disorders.Methods: Literatures was reviewed on the subject to find out the knowledge regarding Environmental threats of air pollution & its effects on the health of human body. Data and details have been located, selected, extracted and synthesized from different national & international Journals, websites, Proceedings, books, google scholar etc.Result & Conclusion: Changes are taking place in air regularly. Different pollutants are being created from different sources. Indoor air pollution is common among underdeveloped & developing nations. To improve health situation different professional, have to play their roles. Effects of air pollution are sometimes general in nature otherwise may be immediate or delayed. Leading causes of death is cardiovascular diseases like IHD are now being declared as airborne. Emergent airborne diseases are more than 30 like COVID 19 only result in 43.6 lakhs death so far. Toxic & hazardous chemicals are present in air in the form of allergens, neurotoxin, mutagen, carcinogen etc. Air pollutants are carbon monoxide, nitrogen oxides, Benzene, Ozone, Lead, sulphates, SPM etc. Meteorological effects on health are also related with air including season, atmospheric pressure, heat, cold etc. Indoor air pollutants have also specific health effects.

Effects of the COVID-19 shutdown on spatial and temporal patterns of air pollution in New York City

Using spatially- and temporally-resolved data from the New York City Community Air Survey (NYCCAS) and the New York State (NYS) Department of Environmental Conservation (DEC) network, we characterized changes in fine particulate matter (PM2.5) and nitrogen dioxide (NO2) following the COVID-19 shutdown in NYC (3/20/20 – 6/7/20). Difference-in-difference analysis of PM2.5 and NO2 measured at 93 sites were used to estimate the change in citywide pollution attributable to the shutdown. We also quantified how these pollutant changes varied among different demographic groups using difference-in-difference analyses stratified by neighborhood poverty levels and rates of PM2.5-attributable health outcomes. Spatial patterns of PM2.5 and NO2 were interpolated across NYC by fitting land-use regression models to measurements at the 93 sites. Weather conditions and emission source trends were analyzed to determine the potential effects of meteorology and specific emission sources on the observed pollution changes. We estimate that citywide average PM2.5 and NO2 decreased by approximately 25% and 29%, respectively, due to the shutdown. Weather readings show little evidence that meteorology biased our results in the direction of our findings. Data on major sources of PM2.5 and NO2 pollution suggests that decreased vehicle traffic and commercial cooking contributed to declines in air pollution during this period. Pollution reductions occurred disproportionately in the city's central business district (CBD), with smaller changes in other areas of the city, such as those with the highest burden of air pollution-related health impacts. These findings emphasize the need to target pollution sources in communities that suffer the greatest from pollution exposure in the design of equitable environmental health policy.

Simulation of the impact of the atmospheric weather state on the efficiency of functioning of solar thermal and power plants

THE PURPOSE. Determine the impact of the meteorological state of the atmosphere on the efficiency of the functioning of solar thermal and power plants. Modeling the molecular absorption of solar radiation by the atmosphere. Modeling the optical characteristics of the gaseous components of the atmosphere, atmospheric aerosol and clouds.METHODS. A method for numerical modeling of incoming solar radiation fluxes their functioning to determine the efficiency of solar thermal and power plants. The solar fluxes are calculated by stacking layers in a multi-stream approximation, taking into account the multi-tiered cloud cover and the probability of overlapping the sky with clouds. The absorption of radiation by the gaseous phase of the atmosphere is taken into account by the method of equivalent mass in an inhomogeneous atmosphere. The optical characteristics of the dispersed phase of the atmosphere are calculated using the Mie theory.RESULTS. An electronic database has been created on the optical characteristics of the gaseous components of the atmosphere, the optical characteristics of atmospheric aerosol and clouds. The effect of anthropogenic impact on the flux of solar radiation falling on the underlying surface is taken into account. The developed modeling takes into account the effect of humidity on the optical characteristics of atmospheric aerosol and its multicomponent composition, depending on the location of the power plant.CONCLUSION. The information necessary for numerical modeling of meteorological effects on the functioning of solar thermal and power plants is generalized. When calculating solar radiation fluxes, direct illumination of the light-receiving surface by solar radiation, scattered radiation by atmospheric aerosol and clouds are taken into account.

A city-level analysis of PM2.5 pollution, climate and COVID-19 early spread in Spain.

PurpuseThe COVID-19 outbreak has escalated into the worse pandemic of the present century. The fast spread of the new SARS-CoV-2 coronavirus has caused devastating health and economic crises all over the world, with Spain being one of the worst affected countries in terms of confirmed COVID-19 cases and deaths per inhabitant. In this situation, the Spanish Government declared the lockdown of the country.MethodsThe variations of air pollution in terms of fine particulate matter (PM2.5) levels in seven representative cities of Spain are analyzed here considering the effect of meteorology during the national lockdown. The possible associations of PM2.5 pollution and climate with COVID-19 accumulated cases were also analyzed.ResultsWhile the epidemic curve was flattened, the results of the analysis show that the 4-week Spanish lockdown significantly reduced the PM2.5 levels in only one city despite the drastically reduced human activity. Furthermore, no associations between either PM2.5 exposure or environmental conditions and COVID-19 transmission were found during the early spread of the pandemic.ConclusionsA longer period applying human activity restrictions is necessary in order to achieve significant reductions of PM2.5 levels in all the analyzed cities. No effect of PM2.5 pollution or weather on COVID-19 incidence was found for these pollutant levels and period of time.Graphical abstract Supplementary InformationThe online version contains supplementary material available at 10.1007/s40201-022-00786-2.

Meteorological factors' effects on COVID-19 show seasonality and spatiality in Brazil

The meteorological conditions may affect COVID-19 transmission. However, the roles of seasonality and macro-climate are still contentious due to the limited time series for early-stage studies. We studied meteorological factors' effects on COVID-19 transmission in Brazil from February 25 to November 15, 2020. We aimed to explore whether this impact showed seasonal characteristics and spatial variations related to the macro-climate. We applied two-way fixed-effect models to identify the effects of meteorological factors on COVID-19 transmission and used spatial analysis to explore their spatial-temporal characteristics with a relatively long-time span. The results showed that cold, dry and windless conditions aggravated COVID-19 transmission. The daily average temperature, humidity, and wind speed negatively affected the daily new cases. Humidity and temperature played a dominant role in this process. For the time series, the influences of meteorological conditions on COVID-19 had a periodic fluctuation of 3–4 months (in line with the seasons in Brazil). The turning points of this fluctuation occurred at the turn of seasons. Spatially, the negative effects of temperature and humidity on COVID-19 transmission clustered in the northeastern and central parts of Brazil. This is consistent with the range of arid climate types. Overall, the seasonality and similar climate types should be considered to estimate the spatial-temporal COVID-19 patterns. Winter is a critical time to be alert for COVID-19, especially in the northern part of Brazil.

Association of air pollution with acute ischemic stroke risk in Singapore: a time-stratified case-crossover study.

Air quality is an important determinant of cardiovascular health such as ischemic heart disease and acute ischemic stroke (AIS) with substantial mortality and morbidity reported across the globe. However, associations between air quality and AIS in the current literature remain inconsistent, with few studies undertaken in cosmopolitan cities located in the tropics. We evaluated the associations between individual ambient air pollutants and AIS. We performed a nationwide, population-based, time-stratified case-crossover analysis on all AIS cases reported to the Singapore Stroke Registry from 2009 to 2018. We estimated the incidence rate ratio (IRR) of AIS across different concentrations of each pollutant by quartiles (referencing the 25th percentile), in single-pollutant conditional Poisson models adjusted for time-varying meteorological effects. We stratified our analysis by predetermined subgroups deemed at higher risk. A total of 51,675 episodes of AIS were included. Ozone (O3) (IRR4th quartile: 1.05, 95% confidence interval (CI): 1.01-1.08) and carbon monoxide (CO) (IRR2nd quartile: 1.05, 95% CI: 1.02-1.08, IRR3rd quartile: 1.07, 95% CI: 1.04-1.10, IRR4th quartile: 1.07, 95% CI: 1.04-1.11) were positively associated with AIS incidence. The increased incidence of AIS due to O3 and CO persisted for 5 days after exposure. Those under 65 years of age were more likely to experience AIS when exposed to CO. Individuals with atrial fibrillation (AF) were more susceptible to exposure from O3, CO, and PM10. Current/ex-smokers were more vulnerable to the effect of O3. Air pollution increases the incidence of AIS, especially in those with AF and in those who are current or ex-smokers.

Harnessing the Meteorological Effect for Predicting the Retail Price of Rice in Bangladesh

Harnessing the Meteorological Effect for Predicting the Retail Price of Rice in Bangladesh

Meteorological Effects of Green Infrastructure on a Developing Medium Latin American City: A Numerical Modeling Assessment

Meteorological Effects of Green Infrastructure on a Developing Medium Latin American City: A Numerical Modeling Assessment

Harnessing the meteorological effect for predicting the retail price of rice in Bangladesh

Harnessing the meteorological effect for predicting the retail price of rice in Bangladesh

Spatio-temporal prediction and factor identification of urban air quality using support vector machine

Accurate air quality prediction can provide better supervision and reference for management policies. Due to difficulties in data acquisition, combined spatio-temporal prediction is still inconclusive. This study utilizes the support vector machine (SVM) method to predict air quality of unknown space and time. Extracted from a geographic information system (GIS), geographic features such as population, land use, economy, pollution sources, and terrain parameters were added to a time series. Temporal prediction was first executed in the reference stations, and the predicted air quality index (AQI) was then used to spatially infer the future AQI of unknown locations. Verification indicated high accuracy for short-term temporal prediction. Various meteorological and climatic effects were observed to be influential in seasonal difference. In the spatial inference stage, urbanization and city types were spatial features that appeared to impact air quality. Agriculture and forest use, transportation use, residential use, and economic factors were clearly correlated to AQIs, whereas population and labor force were not. This study establishes a prediction framework in northern Taipei based on SVM. Other locations can build their own models based on local actual data to achieve better decision-making, urban planning, or other applications.

Convection Initiation at a Coastal Rainfall Hotspot in South China: Synoptic Patterns and Orographic Effects

AbstractThis study documents the detailed features and processes of convection initiation (CI) at a coastal rainfall hotspot in South China, with emphasis on the typical meteorological conditions and effects of small‐scale orography. The CI occurrences are identified using high‐quality radar mosaics during 7‐year warm seasons. They tend to maximize in low‐lying areas adjacent to coastal small‐scale mountains rather than on the windward slopes of major mountains as previously expected. The genesis of the coastal convection exhibits a remarkable diurnal peak in the early afternoon and mostly occurs on the days of low‐level southwesterlies with a jet‐nose structure in offshore region. These onshore flows enhance the low‐level moistening and convergence on coasts. The characteristic synoptic patterns become common after the onset of summer monsoon, suggesting the key role of monsoonal flows in triggering coastal convection. Driven by the atmospheric conditions of the dominant synoptic pattern, quasi‐idealized numerical simulations demonstrate that the coastal small‐scale mountains disturb the low‐level onshore flow and produce multiple enhanced convergent zones downstream of the mountains. The induced local variations in upward motion and moisture pooling explain the CI occurrences that are located close to these small‐scale mountains. When these mountains are artificially removed in the simulation, convection preferentially initiates on the windward slopes of major mountains as expected. The findings suggest that the small‐scale orography can strongly regulate the local patterns of CI hotspot through disturbing low‐level onshore flow. An explicit resolving of the small‐scale coastal orography is warranted to improve the modeling of local severe weather.

Semi-empiric noise modeling of a Cargo eVTOL UAV by means of system identification from flight noise measurement data

This publication shows the semi-empiric noise modeling of an electric-powered vertical takeoff and landing (eVTOL) unmanned aerial vehicle (UAV) by means of system identification from flight noise measurement data. This work aims to provide noise models with a compact analytical ansatz for horizontal and vertical flight which are suited for integration into a geographical information system. Therefore, flight noise measurement campaigns were conducted and evaluated. An existing noise model ansatz is adapted to the eVTOL UAV under consideration and noise models are computed from the measurement data using the output error method. The resulting models are checked for plausibility by comparing them to technical literature. The horizontal flight noise model is subjected to a correlation analysis and the influence of meteorological effects are examined. To achieve a higher level of accuracy in future noise modelings, an optimization of the microphone positions as well as the flight trajectory is carried out.

Recent Developments of Noise Attenuation Using Acoustic Barriers for a Specific Edge Geometry

The aim of this research is to provide a better prediction for noise attenuation using thin rigid barriers. In particular, the paper presents an analysis on four methods of computing the noise attenuation using acoustic barriers: Maekawa-Tatge formulation, Kurze and Anderson algorithm, Menounou formulation, and the general prediction method (GPM-ISO 9613). Accordingly, to improve the GPM, the prediction computation of noise attenuation was optimized for an acoustic barrier by considering new effects, such as attenuation due to geometrical divergence, ground absorption-reflections, and atmospheric absorption. The new method, modified GPM (MGPM), was tested for the optimization of an y-shape edge geometry of the noise barrier and a closed agreement with the experimental data was found in the published literature. The specific y-shape edge geometry of the noise barrier contributes to the attenuation due to the diffraction phenomena. This aspect is based on the Kirchhoff diffraction theory that contains the Huygens-Fresnel theory, which is applied to a semi-infinite acoustic barrier. The new method MGPM of predicting the noise attenuation using acoustic barriers takes into consideration the next phenomena: The effect of the relative position of the receiver, the effect of the proximity of the source or receiver to the midplane of the barrier, the effect of the proximity of the receiver to the shadow boundary, the effect of ground absorption-reflections, the effect of atmospheric absorption, and the meteorological effect due to downwind. The conclusion of the paper reveals the optimization of the method for computing the noise attenuation using acoustic barriers, including the necessary corrections for ISO-9613 and the Sound PLAN software, as well as the optimization on a case study of a specific geometry of the edge barrier.

A spatial land use clustering framework for investigating the role of land use in mediating the effect of meteorology on urban air quality

Air pollution in urban areas is driven by emission sources and modulated by local meteorology, including the effects of urban form on wind speed and ventilation, and thus varies markedly in space and time. Recently, mobile measurement campaigns have been conducted in urban areas to measure the spatial distribution of air pollutant concentrations. While the main focus of these studies has been revealing spatial patterns in mean (or median) concentrations, they have mostly ignored the temporal aspects of air pollution. However, assessing the temporal variability of air pollution is essential in understanding the integrated exposure of individuals to pollutants above critical thresholds. Here, we examine the role of urban land use in mediating the effect of regional meteorology on Nitrogen Dioxide (NO 2 ) concentrations measured in different regions of Oakland, CA. Inspired by Land Use Regression (LUR) models, we cluster 30-m road segments in the urban area based on their land use. The concentration data from the resulting clusters are stratified based on seasonality and conditionally averaged based on concurrent wind speeds. The clustering analysis yielded 7 clusters, with 4 of them chosen for further statistical analysis due to their large sample sizes. Two of the four clusters demonstrated in winter a strong negative linear relationship between NO 2 concentration and wind speed ( R 2 > 0.87) with a slope of approximately 3 ppb/m s -1 . A weaker correlation and flatter slope was found for the cluster representing road segments belonging to interstate highways ( R 2 > 0.73 and slope < 2 ppb/m s -1 ). No significant relationship was found during the summer season. These findings are consistent with the concept of strong vertical mixing due to highway traffic and increased surface heat fluxes during summer weakening the relationship between wind speed and NO 2 concentrations. In summary, the clustering analysis framework presented here provides a novel tool for use with large-scale mobile measurements to reveal the effect of urban land form on the temporal dynamics of pollutant concentrations and ultimately human exposure. • Clustering framework developed for spatio-temporal analysis of mobile measurements. • Domain-related procedure for selecting number of clusters in k-means is presented. • Effect of meteorology on pollutant levels as mediated by land-use is investigated. • Wind speed is only effective in reducing pollutant levels in some urban regions.

Stratospheric X‐Rays Detected at Midlatitudes With a Miniaturized Balloon‐Borne Microscintillator‐PiN Diode System

AbstractA miniaturized scintillator (“microscintillator”), was flown on a meteorological radiosonde to observe energetic particles in the lower atmosphere. A PiN diode was used to measure the light from the microscintillator to count rates and energies of ionizing radiation from the ground up to the stratosphere (32 km). The flight, over the southern UK on August 27, 2018, occurred during a geomagnetic storm. Low‐energy (50–150 keV) particles in the stratosphere were detected in addition to the usual signal from higher‐energy cosmic rays. Unusually for these miniaturized radiosonde systems, which are designed to be disposable, the payload was retrieved. This allowed for re‐calibration of the microscintillator, which confirmed the low‐energy particle detection. Laboratory tests excluded thermal effects on the microscintillator instrument as the origin of the signal. Data from the NOAA POES spacecraft offer the explanation that the microscintillator detected bremstrahhlung X‐rays from energetic electron precipitation (EEP). EEP events may affect weather and climate through a range of physical mechanisms, and this midlatitude observation, well away from the auroral oval, extends the region over which meteorological effects of EEPs need to be assessed. Our findings underline the value of balloon measurements in providing rapid response to space weather events. The energy‐discriminating and altitude‐sensitive capability of the microscintillator augments spacecraft observations from below.

Long-term characteristics of water quality around the Guangdong-Hong Kong-Macau Greater Bay Area: Spatiotemporal variations and meteorological effects

Monitoring the coastal water quality (CWQ) and determining the effects of meteorological factors (MF) on the long-term CWQ adjacent to urban agglomerations are key topics in coastal monitoring and management. This study used satellite-derived data to study the long-term CWQ around the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) with indicators of chlorophyll-a concentration (Chla) and diffuse attenuation coefficient for downwelling irradiance at 490 nm (Kd(490)). The sea surface temperature (SST) and total precipitation accumulation (TPA) of the waters around the GBA were also studied from 2003 to 2019. Furthermore, statistical analysis was conducted to identify the impact of the MF on CWQ by quantifying trends and relationships of CWQ & MF. The results showed that (1) An increasing trend of annual Chla, Kd(490), and TPA were observed, whereas a decreasing trend of SST has been recorded from 2003 to 2019. Both CWQ indicators and meteorological variables showed significant differences among seasons, and the values of Chla, Kd(490), and SST were found higher in the coastal area but lower in the open waters area. (2) SST was the crucial factor of the high values of CWQ indicators in summer: the highest values of Chla and Kd(490) in summer are likely to be attributed to the proper SST (r = 0.87; r = 0.83) and higher TPA in spring (r = 0.95; r = 0.93). The precipitation played an uncertain role in driving the CWQ (r > 0.9 and r < −0.9 in spring and winter, respectively). A significant increase in TPA was associated with the decrease of SST in the coming year. (3) Due to the relatively stable change of natural environment and human activities, the trends of Chla, Kd(490), and TPA remained broadly consistent with those of the past 17 years. However, SST indicates a slight downward trend. In summary, the TPA and SST-driven patterns were essential in the management of water quality indicators in the GBA area. This study can improve our comprehensive understanding of the water quality status in the coastal regions of the GBA and provide references to the coastal zone and marine management, as well as the sustainable development of the GBA.

Digging out intersexual and meteorological effects on cicada emergence using 10‐year citizen monitoring

Abstract Understanding the mechanisms determining the emergence timing of herbivorous insects is ecologically important. However, little is known about the effect of climatic factors and the presence of conspecific individuals on their emergence in the field. In particular, it is challenging to investigate the seasonal emergence of cicadas because these insects have a long life‐cycle and subterranean larval stages. We assembled a time‐series dataset that consists of daily counts of emerging cicadas together with meteorological factors, using long‐term collection of cicada exuviae by elementary and junior‐high‐school students. We then performed a non‐linear time‐series analysis, empirical dynamic modelling, to identify factors behind the timing of cicada emergence. Our findings are three‐fold: (1) emergence of individuals of the opposite sex constitute a major driver of the number of individuals emerging per day, and this effect is stronger in males than in females, (2) as in other insect species, air temperature consistently affects cicada emergence, but its effects are relatively weak and (3) precipitation and humidity were causally related to emergence. These results are consistent with the theory of sexual selection as well as the fact that it is hard for the subterranean cicada larvae to use information about air temperature. Significantly, the findings are based on long‐term field data collected by non‐expert citizens.