Meteorological parameters modulate transmission of the SARS-Cov-2 virus, the causative agent related to coronavirus disease-2019 (COVID-19) development. However, findings across the globe have been inconsistent attributed to several confounding factors. The aim of the present study was to investigate the relationship between reported meteorological parameters from July 1 to October 31, 2020, and the number of confirmed COVID-19 cases in 4 Brazilian cities: São Paulo, the largest city with the highest number of cases in Brazil, and the cities with greater number of cases in the state of Parana during the study period (Curitiba, Londrina and Maringa). The assessment of meteorological factors with confirmed COVID-19 cases included atmospheric pressure, temperature, relative humidity, wind speed, solar irradiation, sunlight, dew point temperature, and total precipitation. The 7- and 15-day moving averages of confirmed COVID-19 cases were obtained for each city. Pearson's correlation coefficients showed significant correlations between COVID-19 cases and all meteorological parameters, except for total precipitation, with the strongest correlation with maximum wind speed (0.717, <0.001) in São Paulo. Regression tree analysis demonstrated that the largest number of confirmed COVID-19 cases was associated with wind speed (between ≥0.3381 and <1.173 m/s), atmospheric pressure (<930.5mb), and solar radiation (<17.98e). Lower number of cases was observed for wind speed <0.3381 m/s and temperature <23.86°C. Our results encourage the use of meteorological information as a critical component in future risk assessment models.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1080/15287394.2021.1969304 | DOI Listing |
Sci Rep
January 2025
College of New Energy and Environment, Jilin University, Changchun, 130012, China.
Land use and land cover changes (LULCC) alter local surface attributes, thereby modifying energy balance and material exchanges, ultimately impacting meteorological parameters and air quality. The North China Plain (NCP) has undergone rapid urbanization in recent decades, leading to dramatic changes in land use and land cover. This study utilizes the 2020 land use and land cover data obtained from the MODIS satellite to replace the default 2001 data in the Weather Research and Forecasting-Community Multiscale Air Quality (WRF-CMAQ) model.
View Article and Find Full Text PDFMethodsX
June 2025
Department of Royal Rainmaking and Agricultural Aviation, Bangkok 10900, Thailand.
Rainfall prediction is a crucial aspect of climate science, particularly in monsoon-influenced regions where accurate forecasts are essential. This study evaluates rainfall prediction models in the Eastern Thailand by examining an optimal lag time associated with the Oceanic Niño Index (ONI). Five deep learning models-RNN with ReLU, LSTM, GRU (single-layer), LSTM+LSTM, and LSTM+GRU (multi-layer)-were compared using mean absolute error (MAE) and root mean square error (RMSE).
View Article and Find Full Text PDFChemosphere
January 2025
Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, Gansu Province, 730000, China; Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China.
Peroxyacetyl Nitrate (CHC(O)ONO, PAN), a typical secondary product of photochemical reactions, is well known to be a better photochemical indicator due to the only secondary photochemical source in the troposphere. Studies on PAN pollution are sparse in northwest China, resulting in a limited understanding of photochemical pollution in recent years. Herein, the measurement of PAN, O, volatile organic compounds (VOCs), NO, other related species, and meteorological parameters were conducted from May 1 to August 31, 2022, at an urban site in Lanzhou.
View Article and Find Full Text PDFSci Total Environ
January 2025
Center for Environmental Radioactivity (CERAD) CoE, Norwegian University of Life Sciences, P.O. Box 5003, N-1432 Ås, Norway; Faculty of Environmental Sciences and Natural Resource Management, Norwegian University of Life Sciences (NMBU), P.O.Box 5003, NO-1432 Ås, Norway.
Numerical transport models are important tools for nuclear emergency decision makers in that they rapidly provide early predictions of dispersion of released radionuclides, which is key information to determine adequate emergency protective measures. They can also help us understand and describe environmental processes and can give a comprehensive assessment of transport and transfer of radionuclides in the environment. Transport of radionuclides in air and ocean is affected by a number of different physico-chemical processes.
View Article and Find Full Text PDFMedicina (Kaunas)
November 2024
Institute of Allied Health Sciences, College of Medicine, National Cheng Kung University, Tainan 701, Taiwan.
: The incidence of hip fractures is increasing, and there have been reports linking cold weather to a higher risk of fractures. This study aimed to evaluate clinical variables in hip fracture patients who may predispose them to such fractures under different temperatures. : This is a cross-sectional study conducted at a single medical center, enrolling older adults (≥60 years) who had experienced a hip fracture.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!