A wind speed threshold for increased outdoor transmission of coronavirus: an ecological study

Abstract Background To examine whether outdoor transmission may contribute to the COVID-19 epidemic, we hypothesized that slower outdoor wind speed is associated with increased risk of transmission when individuals socialize outside. Methods Daily COVID-19 incidence reported in Suffolk County, NY, between March 16th and December 31st, 2020, was the outcome. Average wind speed and maximal daily temperature were collated by the National Oceanic and Atmospheric Administration. Negative binomial regression was used to model incidence rates while adjusting for susceptible population size. Results Cases were very high in the initial wave but diminished once lockdown procedures were enacted. Most days between May 1st, 2020, and October 24th, 2020, had temperatures 16–28 °C and wind speed diminished slowly over the year and began to increase again in December 2020. Unadjusted and multivariable-adjusted analyses revealed that days with temperatures ranging between 16 and 28 °C where wind speed was < 8.85 km per hour (KPH) had increased COVID-19 incidence (aIRR = 1.45, 95% C.I. = [1.28–1.64], P < 0.001) as compared to days with average wind speed ≥ 8.85 KPH. Conclusion Throughout the U.S. epidemic, the role of outdoor shared spaces such as parks and beaches has been a topic of considerable interest. This study suggests that outdoor transmission of COVID-19 may occur by noting that the risk of transmission of COVID-19 in the summer was higher on days with low wind speed. Outdoor use of increased physical distance between individuals, improved air circulation, and use of masks may be helpful in some outdoor environments where airflow is limited.

Download Full-text

Outdoor transmission of COVID-19: Analysis of windspeed

10.1101/2021.02.05.21251179 ◽

2021 ◽

Author(s):

Sean A. P. Clouston ◽

Olga Morozova ◽

Jaymie R. Meliker

Keyword(s):

Population Size ◽

Negative Binomial ◽

Negative Binomial Regression ◽

Daily Temperature ◽

Susceptible Population ◽

Initial Wave ◽

Outdoor Transmission ◽

Increased Risk ◽

Binomial Regression ◽

Very High

AbstractBackgroundTo examine whether outdoor exposures may contribute to the COVID-19 epidemic, we hypothesized that slower outdoor windspeed is associated with increased risk of transmission when individuals socialize outside.MethodsDaily COVID-19 incidence reported between 3/16/2020-12/31/2020 was the outcome. Average windspeed and maximal daily temperature were derived from the National Oceanic and Atmospheric Administration. Negative binomial regression was used to model incidence, adjusting for susceptible population size.ResultsCases were very high in the initial wave but diminished quickly once lockdown procedures were enacted. Unadjusted and multivariable-adjusted analyses revealed that warmer days with windspeed <5.5 MPH had increased COVID-19 incidence (aIRR=1.50, 95% C.I.=[1.25-1.81], P<0.001) as compared to days with average windspeed ≥5.5 MPH.ConclusionThis study suggests that outdoor transmission of COVID-19 may occur by noting that the risk of transmission of COVID-19 in the summer was highest on days when wind was reduced.

Download Full-text

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

Alternative Energy and Ecology (ISJAEE) ◽

10.15518/isjaee.2018.22-24.028-050 ◽

2018 ◽

pp. 28-50

Author(s):

S. G. Ignatiev ◽

S. V. Kiseleva

Keyword(s):

Energy Storage ◽

Wind Speed ◽

Wind Energy ◽

Wind Turbine ◽

Wind Turbines ◽

Energy Demand ◽

Diesel Generator ◽

Average Wind Speed ◽

Wind Speeds ◽

Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

Download Full-text

Analysis of Performance of the Wind-Driven Pulverizing Aerator Based on Average Wind Speeds in the Conditions of Góreckie Lake

Energies ◽

10.3390/en14102796 ◽

2021 ◽

Vol 14 (10) ◽

pp. 2796

Author(s):

Andrzej Osuch ◽

Ewa Osuch ◽

Stanisław Podsiadłowski ◽

Piotr Rybacki

Keyword(s):

Mathematical Model ◽

Wind Speed ◽

Water Pump ◽

Average Wind Speed ◽

Flow Rates ◽

Wind Speeds ◽

Average Wind ◽

Flow Through ◽

Analysis Of Performance ◽

Research Period

In the introduction to this paper, the characteristics of Góreckie lake and the construction and operation of the wind-driven pulverizing aerator are presented. The purpose of this manuscript is to determine the efficiency of the pulverizing aerator unit in the windy conditions of Góreckie Lake. The efficiency of the pulverization aerator depends on the wind conditions at the lake. It was necessary to conduct thorough research to determine the efficiency of water flow through the pulverization segment (water pump). It was necessary to determine the rotational speed of the paddle wheel, which depended on the average wind speed. Throughout the research period, measurements of hourly average wind speed were carried out. It was possible to determine the efficiency of the machine by developing a dedicated mathematical model. The latest method was used in the research, consisting of determining the theoretical volumetric flow rates of water in the pulverizing aerator unit, based on average hourly wind speeds. Pulverization efficiency under the conditions of Góreckie Lake was determined based on 6600 average wind speeds for spring, summer and autumn, 2018. Based on the model, the theoretical efficiency of the machine was calculated, which, under the conditions of Góreckie Lake, amounted to 75,000 m3 per year.

Download Full-text

Some statistical characteristics of monthly average wind speed at various heights

Renewable and Sustainable Energy Reviews ◽

10.1016/j.rser.2007.01.014 ◽

2008 ◽

Vol 12 (6) ◽

pp. 1712-1724 ◽

Cited By ~ 64

Author(s):

Károly Tar

Keyword(s):

Wind Speed ◽

Statistical Characteristics ◽

Average Wind Speed ◽

Monthly Average ◽

Average Wind

Download Full-text

HAND-FOOT-AND-MOUTH DISEASE EPIDEMIOLOGICAL STATUS AND RELATIONSHIP WITH METEOROLOGICAL VARIABLES IN GUANGZHOU, SOUTHERN CHINA, 2008-2012

Revista do Instituto de Medicina Tropical de São Paulo ◽

10.1590/s0036-46652014000600014 ◽

2014 ◽

Vol 56 (6) ◽

pp. 533-539 ◽

Cited By ~ 21

Author(s):

Tiegang Li ◽

Zhicong Yang ◽

Xiangyi Liu ◽

Yan Kang ◽

Ming Wang

Keyword(s):

Negative Binomial ◽

Southern China ◽

Foot And Mouth Disease ◽

Negative Binomial Regression ◽

Incidence Rates ◽

Mouth Disease ◽

Meteorological Variables ◽

High Morbidity ◽

Weather Factors ◽

Foot And Mouth

Hand-foot-and-mouth disease (HFMD) is becoming one of the extremely common airborne and contact transmission diseases in Guangzhou, southern China, leading public health authorities to be concerned about its increased incidence. In this study, it was used an ecological study plus the negative binomial regression to identify the epidemic status of HFMD and its relationship with meteorological variables. During 2008-2012, a total of 173,524 HFMD confirmed cases were reported, 12 cases of death, yielding a fatality rate of 0.69 per 10,000. The annual incidence rates from 2008 to 2012 were 60.56, 132.44, 311.40, 402.76, and 468.59 (per 100,000), respectively, showing a rapid increasing trend. Each 1 °C rise in temperature corresponded to an increase of 9.47% (95% CI 9.36% to 9.58%) in the weekly number of HFMD cases, while a one hPa rise in atmospheric pressure corresponded to a decrease in the number of cases by 7.53% (95% CI -7.60% to -7.45%). Similarly, each one percent rise in relative humidity corresponded to an increase of 1.48% or 3.3%, and a one meter per hour rise in wind speed corresponded to an increase of 2.18% or 4.57%, in the weekly number of HFMD cases, depending on the variables considered in the model. These findings revealed that epidemic status of HFMD in Guangzhou is characterized by high morbidity but low fatality. Weather factors had a significant influence on the incidence of HFMD.

Download Full-text

Trends in Opioid Prescribing Among Hemodialysis Patients, 2007–2014

American Journal of Nephrology ◽

10.1159/000495353 ◽

2018 ◽

Vol 49 (1) ◽

pp. 20-31 ◽

Cited By ~ 4

Author(s):

Matthew Daubresse ◽

G. Caleb Alexander ◽

Deidra C. Crews ◽

Dorry L. Segev ◽

Mara A. McAdams-DeMarco

Keyword(s):

Low Income ◽

Negative Binomial ◽

Negative Binomial Regression ◽

The United States ◽

Incidence Rates ◽

Opioid Prescription ◽

Opioid Prescribing ◽

Hispanic Patients ◽

Estimate Annual Incidence ◽

National Trends

Background: Hemodialysis (HD) patients frequently experience pain. Previous studies of HD patients suggest increased opioid prescribing through 2010. It remains unclear if this trend continued after 2010 or declined with national trends. Methods: Longitudinal cohort study of 484,745 HD patients in the United States Renal Data System/Medicare data. We used Poisson/negative binomial regression to estimate annual incidence rates of opioid prescribing between 2007 and 2014. We compared prescribing rates with the general US population using IQVIA’s National Prescription Audit data. Outcomes included the following: percent of HD patients receiving an opioid prescription, rate of opioid prescriptions, quantity, days supply, morphine milligram equivalents (MME) dispensed per 100 person-days, and prescriptions per person. Results: In 2007, 62.4% of HD patients received an opioid prescription. This increased to 63.2% in 2010 then declined to 53.7% by 2014. Opioid quantity peaked in 2011 at 73.5 pills per 100 person-days and declined to 62.6 pills per 100 person-days in 2014. MME peaked between 2010 and 2012 then declined through 2014. In 2014, MME rates were 1.8-fold higher among non-Hispanic patients and 1.6-fold higher among low-income patients. HD patients received 3.2-fold more opioid prescriptions per person compared to the general US population and were primarily prescribed oxycodone and hydrocodone. Between 2012 and 2014, HD patients experienced greater declines in opioid prescriptions per person (18.2%) compared to the general US population (7.1%). Conclusion: Opioid prescribing among HD patients declined between 2012 and 2014. However, HD patients continue receiving substantially more opioids than the general US population.

Download Full-text

Formation and distribution of sea-surface microlayers

Biogeosciences Discussions ◽

10.5194/bgd-7-5719-2010 ◽

2010 ◽

Vol 7 (4) ◽

pp. 5719-5755 ◽

Cited By ~ 4

Author(s):

O. Wurl ◽

E. Wurl ◽

L. Miller ◽

K. Johnson ◽

S. Vagle

Keyword(s):

Wind Speed ◽

Primary Production ◽

Sea Surface ◽

Surface Microlayer ◽

Average Wind Speed ◽

Wind Speeds ◽

Average Wind ◽

The Pacific ◽

Sea Surface Microlayer ◽

Natural Surfactants

Abstract. Results from a study of surfactants in the sea-surface microlayer (SML) in different regions of the ocean (subtropical, temperate, polar) suggest that this interfacial layer between the ocean and atmosphere covers the ocean's surface to a significant extent. Threshold values at which primary production acts as a significant source of natural surfactants have been derived from the enrichment of surfactants in the SML relative to underlying water and local primary production. Similarly, we have also derived a wind speed threshold at which the SML is disrupted. The results suggest that surfactant enrichment in the SML is typically greater in oligotrophic regions of the ocean than in more productive waters. Furthermore, the enrichment of surfactants persisted at wind speeds of up to 10 m s−1 without any observed depletion above 5 m s−1. This suggests that the SML is stable enough to exist even at the global average wind speed of 6.6 m s−1. Global maps of primary production and wind speed are used to estimate the ocean's SML coverage. The maps indicate that wide regions of the Pacific and Atlantic Oceans between 30° N and 30° S are more significantly affected by the SML than northern of 30° N and southern of 30° S due to higher productivity (spring/summer blooms) and wind speeds exceeding 12 m s−1 respectively.

Download Full-text

Remaining Useful Life Estimation of Wind Turbine Blades under Variable Wind Speed Conditions Using Particle Filters

Annual Conference of the PHM Society ◽

10.36001/phmconf.2018.v10i1.481 ◽

2018 ◽

Vol 10 (1) ◽

Author(s):

Bhavana Valeti ◽

Shamim N. Pakzad

Keyword(s):

Wind Speed ◽

Wind Turbine ◽

Turbine Blades ◽

Remaining Useful Life ◽

Structural Components ◽

Wind Turbine Blades ◽

Average Wind Speed ◽

Average Wind ◽

Useful Life ◽

Variable Wind

Rotor blades are the most complex structural components in a wind turbine and are subjected to continuous cyclic loads of wind and self-weight variation. The structural maintenance operations in wind farms are moving towards condition based maintenance (CBM) to avoid premature failures. For this, damage prognosis with remaining useful life (RUL) estimation in wind turbine blades is necessary. Wind speed variation plays an important role influencing the loading and consequently the RUL of the structural components. This study investigates the effect of variable wind speed between the cutin and cut-out speeds of a typical wind farm on the RUL of a damage detected wind turbine blade as opposed to average wind speed assumption. RUL of wind turbine blades are estimated for different initial crack sizes using particle filtering method which forecasts the evolution of fatigue crack addressing the non-linearity and uncertainty in crack propagation. The stresses on a numerically simulated life size onshore wind turbine blade subjected to the above wind speed loading cases are used in computing the crack propagation observation data for particle filters. The effects of variable wind speed on the damage propagation rates and RUL in comparison to those at an average wind speed condition are studied and discussed.

Download Full-text

The super-turbine wind power conversion paradox: using machine learning to reduce errors caused by Jensen's inequality

Wind Energy Science ◽

10.5194/wes-4-343-2019 ◽

2019 ◽

Vol 4 (2) ◽

pp. 343-353 ◽

Cited By ~ 1

Author(s):

Tyler C. McCandless ◽

Sue Ellen Haupt

Keyword(s):

Machine Learning ◽

Standard Deviation ◽

Wind Speed ◽

Wind Power ◽

Power Conversion ◽

Jensen’S Inequality ◽

Jensen's Inequality ◽

Average Wind Speed ◽

Wind Speeds ◽

Average Wind

Abstract. Wind power is a variable generation resource and therefore requires accurate forecasts to enable integration into the electric grid. Generally, the wind speed is forecast for a wind plant and the forecasted wind speed is converted to power to provide an estimate of the expected generating capacity of the plant. The average wind speed forecast for the plant is a function of the underlying meteorological phenomena being predicted; however, the wind speed for each turbine at the farm is also a function of the local terrain and the array orientation. Conversion algorithms that assume an average wind speed for the plant, i.e., the super-turbine power conversion, assume that the effects of the local terrain and array orientation are insignificant in producing variability in the wind speeds across the turbines at the farm. Here, we quantify the differences in converting wind speed to power at the turbine level compared with a super-turbine power conversion for a hypothetical wind farm of 100 2 MW turbines as well as from empirical data. The simulations with simulated turbines show a maximum difference of approximately 3 % at 11 m s−1 with a 1 m s−1 standard deviation of wind speeds and 8 % at 11 m s−1 with a 2 m s−1 standard deviation of wind speeds as a consequence of Jensen's inequality. The empirical analysis shows similar results with mean differences between converted wind speed to power and measured power of approximately 68 kW per 2 MW turbine. However, using a random forest machine learning method to convert to power reduces the error in the wind speed to power conversion when given the predictors that quantify the differences due to Jensen's inequality. These significant differences can lead to wind power forecasters overestimating the wind generation when utilizing a super-turbine power conversion for high wind speeds, and indicate that power conversion is more accurately done at the turbine level if no other compensatory mechanism is used to account for Jensen's inequality.

Download Full-text