The roles of meteorological variables, demographic factors, and policy response measures in the variation of COVID-19 daily cases: Evidence from different climate zones DOI Creative Commons

Yiran Lyu,

Yu Wang, Chao Jiang

и другие.

Research Square (Research Square), Год журнала: 2023, Номер unknown

Опубликована: Янв. 6, 2023

Abstract It is widely considered that weather conditions affect the spread of COVID-19, but to date, collective influence demographic factors and government policy response measures have hardly been considered. The objective this study utilize a machine learning method assess corresponding roles meteorological variables, factors, in daily new cases COVID-19 among multiple climate zones at city/county level. overall model showed good performance with validated R 2 0.86, as satisfactory individual zone models. Population density ranked most important factor, followed by variables measures. Ultraviolet radiation temperature dominated association seemed be inconsistent different zones. Implementing stricter could help effectively contain did so lagged effect, typical lockdown might not applicable all conditions. This preliminarily analyzed certain transmission provided practical evidence for developing an early health warning system global pandemics leveraging big data technology sourced fusion.

Язык: Английский

The influence of meteorological factors and terrain on air pollution concentration and migration: a geostatistical case study from Krakow, Poland DOI Creative Commons
Tomasz Danek, Elżbieta Węglińska, Mateusz Zaręba

и другие.

Scientific Reports, Год журнала: 2022, Номер 12(1)

Опубликована: Июнь 30, 2022

Abstract Despite the very restrictive laws, Krakow is known as city with highest level of air pollution in Europe. It has been proven that, due to its location, pollutants are transported this from neighboring municipalities. In study, a complex geostatistical approach for spatio-temporal analysis particulate matter (PM) concentrations was applied. For background noise reduction, data were recorded during COVID-19 lockdown using 100 low-cost sensors and validated based on indications reference stations. Standardized Geographically Weighted Regression, local Moran’s I spatial autocorrelation analysis, Getis–Ord Gi* statistic hot-spot detection Kernel Density Estimation maps used. The results indicate relation between topography, meteorological variables, PM concentrations. main factors wind speed (even if relatively low) terrain elevation. study PM2.5/PM10 ratio allowed detailed migration, including source differentiation. This research indicates that Krakow’s unfavorable location makes it prone accumulating neighborhood. investigated period solid fuel heating outside city. shows importance variability analyzed factors’ influence inflow outflow

Язык: Английский

Процитировано

51

Air pollution seasons in urban moderate climate areas through big data analytics DOI Creative Commons
Mateusz Zaręba, Elżbieta Węglińska, Tomasz Danek

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 6, 2024

Abstract High particulate matter (PM) concentrations have a negative impact on the overall quality of life and health. The annual trends PM can vary greatly depending factors such as country’s energy mix, development level, climatic zone. In this study, we aimed to understand cycle in moderate climate zone using dense grid low-cost sensors located central Europe (Krakow). Over one million unique records PM, temperature, humidity, pressure wind speed observations were analyzed gain detailed, high-resolution understanding yearly fluctuations. comprehensive big-data workflow was presented with statistical analysis meteorological factors. A big data-driven approach revealed existence two main seasons (warm cold) Europe’s zone, which do not correspond directly traditional four (Autumn, Winter, Spring, Summer) side periods (early spring early winter). Our findings also highlighted importance time space data for sustainable spatial planning. allowed distinguishing whether source air pollution is related coal burning heating cold period or agricultural lands during warm period.

Язык: Английский

Процитировано

13

Impact Assessment of Aerosol Optical Depth on Rainfall in Indian Rural Areas DOI Open Access
Sneha Gautam,

Janette Elizabeth,

Alok Sagar Gautam

и другие.

Aerosol Science and Engineering, Год журнала: 2022, Номер 6(2), С. 186 - 196

Опубликована: Март 29, 2022

Язык: Английский

Процитировано

35

Air pollution in five Indian megacities during the Christmas and New Year celebration amidst COVID-19 pandemic DOI Open Access
Roshini Praveen Kumar, Cyril Samuel, Shanmathi Rekha Raju

и другие.

Stochastic Environmental Research and Risk Assessment, Год журнала: 2022, Номер 36(11), С. 3653 - 3683

Опубликована: Апрель 2, 2022

Язык: Английский

Процитировано

24

A Comparative Study in Black Carbon Concentration and its Emission Sources in Tribal Area DOI
Balram Ambade, Tapan Kumar Sankar, Mansi Gupta

и другие.

Water Air & Soil Pollution, Год журнала: 2023, Номер 234(3)

Опубликована: Март 1, 2023

Язык: Английский

Процитировано

11

Fidelity of WRF model in simulating heat wave events over India DOI Creative Commons
Priyanshu Gupta, Sunita Verma, P. Mukhopadhyay

и другие.

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 1, 2024

Abstract The evaluation of Weather Research and Forecasting (WRF) model has been performed for simulating episodic Heat Wave (HW) events 2015 2016 with varied horizontal resolutions 27 km the entire India (d01), 9 North West (NW (d02)) South East (SE (d03)) domain. Study compares maximum temperature (T max ) simulated by WRF model, using six different combination parameterization schemes, observations from Meteorological Department (IMD) during HW events. Among experiments, Exp2 (i.e., WSM6 microphysics (MP) together radiation CAM, Yonsei (PBL), NOAH land surface Grell-3D convective schemes) is found closest to in reproducing temperature. exhibits an uncertainty ± 2 °C both regions, suggesting regional influenced location complex orography. Overall, statistical results reveal that best performance achieved Exp2. Further, understand dynamics rising intensity, two case studies days along influencing parameters like T , RH prevailing wind distribution have simulated. Model reaches up 44 NW SE part India. In 2016, more towards NW, while region upto 34–38 high (60–85%). comparative research made it abundantly evident these are unique terms duration geographical spread which can be used assess future projections HW.

Язык: Английский

Процитировано

3

Black Carbon vs Carbon Monoxide: Assessing the Impact on Indian Urban Cities DOI
Balram Ambade, Tapan Kumar Sankar, Sneha Gautam

и другие.

Water Air & Soil Pollution, Год журнала: 2023, Номер 234(11)

Опубликована: Ноя. 1, 2023

Язык: Английский

Процитировано

9

Atmospheric pollutants response to the emission reduction and meteorology during the COVID-19 lockdown in the north of Africa (Morocco) DOI Open Access
Salah Eddine Sbai,

Farida Bentayeb,

Hao Yin

и другие.

Stochastic Environmental Research and Risk Assessment, Год журнала: 2022, Номер 36(11), С. 3769 - 3784

Опубликована: Апрель 23, 2022

Язык: Английский

Процитировано

12

Impact of short-term ambient air pollution exposure on the risk of severe COVID-19 DOI Open Access
Baihuan Feng, Jiangshan Lian, Fei Yu

и другие.

Journal of Environmental Sciences, Год журнала: 2022, Номер 135, С. 610 - 618

Опубликована: Окт. 11, 2022

Язык: Английский

Процитировано

12

Validation and Spatial–Temporal Variability of Particulate Matter in Urban area Using WRF-Chem with Local and Global Emission Inventories DOI
Yagni Rami, Anurag Kandya, Abha Chhabra

и другие.

Water Air & Soil Pollution, Год журнала: 2024, Номер 235(11)

Опубликована: Окт. 8, 2024

Язык: Английский

Процитировано

2