scholarly journals Correlation and Causation Analysis Between COVID-19 and Environmental Factors in China

2021 ◽  
Vol 3 ◽  
Author(s):  
Zuofang Zheng ◽  
Junxia Dou ◽  
Conglan Cheng ◽  
Hua Gao
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Regional Climate ◽  
Climate Impact ◽  
Control Measures ◽  
Specific Humidity ◽  
Human Society ◽  
Causality Test ◽  
Low Wind Speed ◽  
Causation Analysis

Coronavirus disease 2019 (COVID-19) is seriously threatening and altering human society. Although prevention and control measures play an important role in preventing the transmission of severe acute respiratory syndrome coronavirus, signals of climate impact can still be detected globally. In this paper, the data of 265 cities in China were analyzed. The results show that the correlations between COVID-19 and air quality index (AQI) and PM2.5 concentration were very weak and that the correlations between COVID-19 and meteorological factors were significantly different in different climate backgrounds. So, a fixed model is not enough to describe the correlations. Overall, high humidity, low wind speed, and relatively lower air temperature are conducive to the spread of COVID-19. The climate background suitable for the spread of COVID-19 in China is air temperature 0~15°C, specific humidity <3 g kg−1, and wind speed <3 m s−1. The Granger causality test shows that there is a causal relationship between daily average air temperature and the number of COVID-19 confirmed cases in some cities of China, and air temperature is indicative of the number of confirmed cases the next day. However, this phenomenon is not universal due to regional climate differences.

scholarly journals A physically based method for correcting temperature data measured by naturally ventilated sensors over snow

2001 ◽  
Vol 47 (159) ◽  
pp. 665-670 ◽  
Author(s):  
Martin Arck ◽  
Dieter Scherer
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Measurement Errors ◽  
Correction Method ◽  
Temperature Data ◽  
Heat Fluxes ◽  
Shortwave Radiation ◽  
Low Wind Speed ◽  
Snowmelt Period ◽  
Physically Based

AbstractDuring the snowmelt period in 1998, air-temperature data were acquired at 1 min intervals using different measurement systems as part of a field campaign in the Kärkevagge, Swedish Lapland. A comparison reveals that temperatures from naturally ventilated sensors exceed temperatures from aspirated sensors by as much as 6.2 K. Errors in temperature are closely connected to high values of upwelling shortwave radiation and are larger in periods of low wind speed. Measurement errors result from the instantaneous radiation conditions and propagate over the next measurements due to slow response time of the naturally ventilated sensor. A physically based method is developed for correcting temperature data influenced by radiation errors, which requires additional measurements of wind speed and upwelling shortwave radiation. Coefficients of the correction formula are automatically determined from the erroneous temperature data, so the method is independent of accurate air-temperature measurements. The high quality of the correction method could be validated by accurate psychrometer measurements. One of the most important applications is the computation of sensible-heat fluxes from snow-covered surfaces during the snowmelt period using the bulk-aerodynamic method, which is greatly improved by the new correction method.

scholarly journals Multiparameter Spatiotemporal Anomalies with Some of the Strong Earthquakes (M > 6:0) in 2018 around the World

2019 ◽  
Author(s):  
Azad Rasul
Keyword(s):  
Wind Speed ◽  
Surface Temperature ◽  
Air Temperature ◽  
Land Surface ◽  
Earthquake Forecasting ◽  
Specific Humidity ◽  
Negative Anomaly ◽  
Positive Anomaly ◽  
The World ◽  
Before And After

One of the most destructive natural disasters is the earthquake which brings enormous risks to humankind. The objective of the current study was to determine the Earthquake’s remote sensing multiparameter (i.e. land surface temperature (LST), air temperature, specific humidity, precipitation and wind speed) spatiotemporal anomaly of many earthquake samples occurred during 2018 around the world. In this research 11 earthquake (M > 6:0) studied (4 samples selected in a land with transparent sky situations, 3 samples in land within cloudy situations and 4 samples in marine earthquakes). The interquartile range (IQR) and mean ± 2σ methods utilized to improve the efficiency of anomalous differences. As a result, based on the IQR method, negative anomaly before the event detected during the daytime in Mexico and during the nighttime in Afghanistan. In addition, a negative outlier of brightness temperature (BT) detected in Alaska before, after and during the event. In contrast, based on IQR and mean ± 2σ positive anomaly detected in precipitation before and after the event in all investigated examples. According to mean ± 2σ, negative anomaly LST, specific humidity, sea surface temperature (SST_100) and wind detected in most examined earthquake samples. In contrast, positive SST_0 anomaly observed in Fiji and Honduras after the earthquake. Our results suggested in marine earthquakes, for earthquake forecasting we can merge a prior negative anomaly in the wind speed and SST_100. Regarding the in land cloudy sky earthquakes, merging anomaly parameters could be the negative prior anomaly in BT, skin temperature, in contrast, a positive anomaly in precipitation. In land transparent sky earthquake, usually negative prior anomalies in air temperature, specific humidity and LST.

scholarly journals Influence of SST Anomalies on Winter Turbulent Heat Fluxes in the Eastern Kuroshio–Oyashio Confluence Region

2014 ◽  
Vol 27 (24) ◽  
pp. 9349-9358 ◽  
Author(s):  
Shusaku Sugimoto
Keyword(s):  
Wind Speed ◽  
Air Temperature ◽  
Surface Wind ◽  
Surface Air Temperature ◽  
Surface Wind Speed ◽  
Heat Fluxes ◽  
Specific Humidity ◽  
Turbulent Heat ◽  
Confluence Region ◽  
Sst Anomalies

Abstract Variations in the turbulent heat flux (THF; the sum of the sensible and latent heat fluxes) in the eastern Kuroshio–Oyashio confluence region (EKOCR; 36°–40°N, 155°–160°E) were investigated over a period of 27 consecutive winters (December–February) from 1985/86 to 2011/12. The THF was calculated from a bulk formula using daily variables [surface wind speed, surface air specific humidity, surface air temperature, and sea surface temperature (SST)] of the objectively analyzed air–sea fluxes (OAFlux) dataset and bulk coefficients based on the Tropical Ocean and Global Atmosphere Coupled Ocean–Atmosphere Response Experiment (TOGA COARE) bulk flux algorithm 3.0. The winter THF over the EKOCR showed low-frequency variations, with larger THF values in the early 2000s and smaller values in the late 1990s and late 2000s. The heat release in the early 2000s was up to ~40% greater than that in the late 1990s and late 2000s. By performing experiments using combinations of daily raw data values and daily climatological data, the relative contributions of SST, surface air specific humidity, surface air temperature, and surface wind speed were quantitatively assessed in determining the THF over the EKOCR. Results showed that SST predominantly determines the THF: large amounts of heat are released during times of positive SST anomalies. By using Argo float (temperature–salinity) profiles of 2003–12 and a satellite altimetry dataset of 1992–2012, it was found that the warm–salty water transported by an occurrence of the Kuroshio bifurcation was responsible for the generation of positive SST anomalies in the EKOCR.

scholarly journals Observing Local-Scale Variability of Near-Surface Temperature and Humidity Using a Wireless Sensor Network

2012 ◽  
Vol 51 (1) ◽  
pp. 30-41 ◽  
Author(s):  
Katharina Lengfeld ◽  
Felix Ament
Keyword(s):  
Wireless Sensor Network ◽  
Wind Speed ◽  
Surface Temperature ◽  
Sensor Network ◽  
Air Temperature ◽  
Surface Air Temperature ◽  
Specific Humidity ◽  
Wireless Sensor ◽  
Near Surface ◽  
Single Station

AbstractIn this paper the influence of surface type, wind speed, and other environmental conditions on near-surface air temperature, specific humidity, and surface temperature is studied. A wireless sensor network consisting of 13 low-cost meteorological stations was set up as a 2.3-km-long double transect in western Germany during the Fluxes and Patterns in the Soil–Vegetation–Atmosphere Scheme (FLUXPAT2009) campaign. This deployment covered various surface types, including a small river. It was found that the air temperature was mainly influenced by the distance to the river and that its variability is controlled by the wind speed. During the night, a pool of cold air formed in the valley close to the water. The specific humidity is also governed by proximity to the river, especially during the night and for low wind speeds. In contrast, the differences in surface temperature were caused by different land cover. These results can be confirmed by a cluster analysis. Setting up 13 stations in a relatively small area is not always feasible. In this study, an estimation of the error that is made by considering the effect of a reduced number of stations is given. Use of only a single station results in an error of 0.86 K in air temperature, 0.67 g kg−1 in specific humidity, and 1.4 K in surface temperature.

Two mechanisms for accelerated diffusion of COVID-19 outbreaks in regions with high intensity of population and polluting industrialization: the air pollution-to-human and human-to-human transmission dynamics (Preprint)

2020 ◽  
Author(s):  
Mario Coccia
Keyword(s):  
Air Pollution ◽  
Wind Speed ◽  
Critical Role ◽  
Meteorological Condition ◽  
Meteorological Conditions ◽  
Lessons Learned ◽  
Transmission Dynamics ◽  
Critical Threshold ◽  
Viral Infectivity ◽  
Low Wind Speed

BACKGROUND Coronavirus disease 2019 (COVID-19) is viral infection that generates a severe acute respiratory syndrome with serious pneumonia that may result in progressive respiratory failure and death. OBJECTIVE This study has two goals. The first is to explain the main factors determining the diffusion of COVID-19 that is generating a high level of deaths. The second is to suggest a strategy to cope with future epidemic threats with of accelerated viral infectivity in society. METHODS Correlation and regression analyses on on data of N=55 Italian province capitals, and data of infected individuals at as of April 2020. RESULTS The main results are: o The accelerate and vast diffusion of COVID-19 in North Italy has a high association with air pollution. o Hinterland cities have average days of exceeding the limits set for PM10 (particulate matter 10 micrometers or less in diameter) equal to 80 days, and an average number of infected more than 2,000 individuals as of April 1st, 2020, coastal cities have days of exceeding the limits set for PM10 equal to 60 days and have about 700 infected in average. o Cities that average number of 125 days exceeding the limits set for PM10, last year, they have an average number of infected individual higher than 3,200 units, whereas cities having less than 100 days (average number of 48 days) exceeding the limits set for PM10, they have an average number of about 900 infected individuals. o The results reveal that accelerated transmission dynamics of COVID-19 in specific environments is due to two mechanisms given by: air pollution-to-human transmission and human-to-human transmission; in particular, the mechanisms of air pollution-to-human transmission play a critical role rather than human-to-human transmission. o The finding here suggests that to minimize future epidemic similar to COVID-19, the max number of days per year in which cities can exceed the limits set for PM10 or for ozone, considering their meteorological condition, is less than 50 days. After this critical threshold, the analytical output here suggests that environmental inconsistencies because of the combination between air pollution and meteorological conditions (with high moisture%, low wind speed and fog) trigger a take-off of viral infectivity (accelerated epidemic diffusion) with damages for health of population, economy and society. CONCLUSIONS Considering the complex interaction between air pollution, meteorological conditions and biological characteristics of viral infectivity, lessons learned for COVID-19 have to be applied for a proactive socioeconomic strategy to cope with future epidemics, especially an environmental policy based on reduction of air pollution mainly in hinterland zones of countries, having low wind speed, high percentage of moisture and fog that create an environment that can damage immune system of people and foster a fast transmission of viral infectivity similar to the COVID-19. CLINICALTRIAL not applicable

scholarly journals Fine Dust and Sustainable Supply Chain Management in Port Operations: Focus on the Major Cargo Handled at the Dry Bulk Port

2020 ◽  
Vol 8 (7) ◽  
pp. 530
Author(s):  
Jeho Hwang ◽  
Sihyun Kim
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Local Community ◽  
Local Level ◽  
Green Technology ◽  
Control Measures ◽  
Fine Dust ◽  
Causality Test ◽  
Sustainable Operations ◽  
Port Operations

Local residents living adjacent to ports are directly affected by the fine dust generated from the port operations. There is a need to prepare detailed measures according to cargo type given the high correlation between the types of dust-producing cargo primarily managed at ports and local industries. This study attempts to establish the attributes of the cargo handled at ports and the relationship between supply chains built for local key industries and the air quality of the local community. It aims to ascertain which cargo needs managing preemptively at the local level, based on the major cargo types handled in a port. A correlation analysis and Granger causality test were performed to investigate the causality between the factor of cargo and fine dust concentrations. The results in this study indicate the necessity for intensive management of scrap metal cargo among the major cargo handled at the target port, which confirms the large effect of management on fine dust reduction, as well as on reduction efficiency. The results suggest requirements to expand the regulations on the emissions of supply chains by cargo type, not by industry type. Additionally, it is required to minimize the blind spots of management and form an eco-friendly supply chain by introducing green technology. The preparation of emission control measures is also necessary. The findings provide useful insights for the sustainable operations of the local supply chain around the target port and will help the strategic agenda for future improvement.

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