Search

Objectives: We aim to assess the impact of temperature and relative humidity on the transmission of COVID-19 across communities after accounting for community-level factors such as demographics, socioeconomic status and human mobility status., Design: A retrospective cross-sectional regression analysis via the Fama-MacBeth procedure is adopted., Setting: We use the data for COVID-19 daily symptom-onset cases for 100 Chinese cities and COVID-19 daily confirmed cases for 1005 US counties., Participants: A total of 69 498 cases in China and 740 843 cases in the USA are used for calculating the effective reproductive numbers., Primary Outcome Measures: Regression analysis of the impact of temperature and relative humidity on the effective reproductive number ( R value)., Results: Statistically significant negative correlations are found between temperature/relative humidity and the effective reproductive number ( R value) in both China and the USA., Conclusions: Higher temperature and higher relative humidity potentially suppress the transmission of COVID-19. Specifically, an increase in temperature by 1°C is associated with a reduction in the R value of COVID-19 by 0.026 (95% CI (-0.0395 to -0.0125)) in China and by 0.020 (95% CI (-0.0311 to -0.0096)) in the USA; an increase in relative humidity by 1% is associated with a reduction in the R value by 0.0076 (95% CI (-0.0108 to -0.0045)) in China and by 0.0080 (95% CI (-0.0150 to -0.0010)) in the USA. Therefore, the potential impact of temperature/relative humidity on the effective reproductive number alone is not strong enough to stop the pandemic., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Measuring vertical profiles of the particle light absorption coefficient by using absorption photometers may face the challenge of fast changes in relative humidity. These absorption photometers determine the particle light absorption coefficient due to a change in light attenuation through a particle-loaded filter. The filter material, however, takes up or releases water with changing relative humidity (rh in %), influencing thus the light attenuation. A sophisticated set of laboratory experiments was therefore conducted to investigate the effect of fast rh changes (drh/dt) on the particle light absorption coefficient (σabs in Mm-1) derived with two absorption photometers. The rh dependency was examined based on different filter types and filter loadings with respect to loading material and loading areal density. Different filter material was used in the two examined instruments. The Single Channel Tri-Color Absorption Photometer (STAP; Brechtel Manufacturing Inc, 1789 Addison Way, Hayward, CA 94544, USA) relies on quartz-fiber filter (PALL LifeScience, Pallflex Membrane Filters Type E70-2075W) and the microAeth® MA200 (AethLabs, 1640 Valencia St, Suite 2C, San Francisco, CA 94110, USA) is based on a Polytetrafluoroethylene (PTFE) filter band. Furthermore, three cases were investigated: clean filter, filter loaded with black carbon (BC) and filter loaded with ammonium sulfate. The filter loading areal densities (ρ*) ranged from 3.1 to 99.6 mg m-2 in the case of the STAP and ammonium sulfate, 1.2 to 37.6 mg m-2 considering the MA200. Investigating BC loaded cases, ρ*BC was in the range of 2.9 to 43.0 and 1.1 to 16.3 mg m-2 for the STAP and MA200, respectively. In addition, the effect of a silica-bead based diffusion on the rh effect was investigated. Both instruments revealed opposing responses to relative humidity changes (Δrh) with different amplitudes. Whereas the STAP shows a linear dependence to relative humidity changes, the MA200 is characterized by an exponential recovery after its filter was exposed to relative humidity changes. At a wavelength of 624 nm and for the default 60 second average output, the STAP reveals an absolute change in σabs per absolute change of rh (Δσabs/Δrh) of 0.14 Mm-1 %-1 in the clean case, 0.29 Mm-1 %-1 in the case of BC loaded filters, and 0.21 Mm-1 %-1 considering filters loaded with ammonium sulfate. The 60-second running average of the particle light absorption coefficient at 625 nm measured with the MA200 revealed response of around -0.4 Mm-1 %-1 for all three cases. Whereas the response of the STAP varies over the different loading materials in contrast the MA200 was quite stable. The minimum and maximum response was for the STAP 0.17 Mm-1 %-1 and 0.24 Mm-1 %-1 considering ammonium sulfate loading and in the BC loaded case 0.17 Mm-1 %-1 and 0.62 Mm-1 %-1, respectively. The minimum response shown by the MA200 was -0.42 Mm-1 %-1 and -0.36 Mm-1 %-1 at maximum for ammonium sulfate and -0.42 Mm-1 %-1 and -0.37 Mm-1 %-1 in case of BC loading, respectively. Using the aerosol dryer upstream, the STAP did not change the behavior, but the amplitude of the observed effect was reduced by a factor of up to three. A linear correction function for the STAP was developed here. It is provided by correlating recalculated particle light absorption coefficients at 1 Hz time resolution against the change rate of rh. The linear response is estimated with 10.08 Mm-1 s-1 %-1 and can be used to correct for bias induced to rh changes at this time resolution. A correction approach for the MA200 is also provided, however, the behavior of the MA200 is more complex. Further research and multi-instrument measurements have to be conducted to fully understand the underlying processes, since the correction approach resulted in different correction parameters across various experiments. However, the exponential recovery after the filter of the MA200 experienced a rh change could be reproduced. Due to our findings, we recommend to use an aerosol dryer upstream of absorption photometers to reduce the rh effect significantly. Furthermore, when absorption photometers are used in vertical measurements, the ascending or descending speed through layers of large rh gradients has to be low to minimize the observed rh effect. Additionally, recording the rh of the sample stream allows correcting for the bias during post processing of the data. This data correction leads to reasonable results, according the given example in this study. [ABSTRACT FROM AUTHOR]

Abstract: Forest amphibians, especially salamanders, prefer forests with shaded, cool, and moist forest floors. Timber harvesting opens the forest canopy and exposes the forest floor to direct sunlight, which can increase forest floor temperatures and reduce soil moisture. These microclimatic changes can potentially degrade the harvested stand for amphibian habitat or affect other biotic resources or ecological processes at the forest floor and in the understory. The degree of forest floor disturbance is directly related to the intensity of harvesting, however, the duration of this effect is unknown. We conducted a study of forest floor temperature and relative humidity over a 12-year chronosequence (1993–2004) of timber harvests. We compared simultaneous, paired measurements of temperature and relative humidity at three positions (soil, forest floor, air) in harvested and control sites over three seasonal survey sessions. Vegetation composition and structure were measured at each survey location. Ambient weather conditions were recorded at three open-field locations across the study area. We recorded over 23,000 paired measures of temperature and relative humidity at all 12 harvested and control sites during each survey session. While we found significant effects of time-since-harvesting on differences in temperature between harvested and uncut sites, the average differences were generally small (<1°C). We observed no temporal pattern in temperatures with time-since-harvest in the harvested sites compared to uncut conditions. Time-since-harvest had no effect on differences in relative humidity between cut and uncut sites. The variation in forest floor microclimate among sites was large, likely due to small-scale differences in cutting intensity (retained canopy), understory vegetation growth, and microtopography or aspect. We conclude that timber harvesting, within the range of intensities assessed in this study, would have only minimal and short-term effects on forest floor microclimate. We suggest that the small differences we observed in forest floor temperatures and moisture between cut and uncut forest parcels would likely have minor effects on climatic aspects of forest amphibian habitat, and on climatic influences on other forest floor biota and ecological processes. [Copyright &y& Elsevier]

The effects of relative humidity (RH) and temperature on tomato powdery mildew (Leveillula taurica) were studied in controlled environments to define conditions that affect disease development in fresh market tomatoes in California. Gradients of RH (20–90%) at constant temperatures (20–30°C) were generated in single growth chambers to determine their effect on mildew development on mature tomato plants. Temperatures of 30°C and above were deleterious for spore germination, germ tube elongation, and disease development. Lesion growth and rate of disease progress were significantly higher at 20°C than at 25°C. Low RH levels (20–40%) reduced spore germination and lesion growth, accelerated host tissue death and reduced disease progress. Intermediate RH levels (50–70%) increased spore germination and optimized disease development, provided temperatures were maintained within favorable limits. High RH levels (80–90%) were favorable for spore germination but continued exposure to these conditions led to a limited lesion growth and disease progress. Short daily periods (two or three daily exposures of at least 2 h) of high temperatures (35°C) suppressed disease development by 70–92%. [Copyright &y& Elsevier]

The Southeastern Aerosol and Visibility Study (SEAVS) was undertaken to characterize the size-dependent composition, thermodynamic properties, and optical characteristics of the ambient atmospheric particles in the southeastern United States. The field portion of the study was carried out from July 15 to August 25, 1995. As part of the study a relative humidity controlled inlet was built to raise or lower the relative humidity to predetermined levels before the aerosol was passed into an integrating nephelometer or particle-sizing device. Five other integrating nephelometers were operated in various configurations, two of which were fitted with a 2.5 µm inlet. Fine particle < 2.5 µm) samplers were operated to measure concentrations of sulfate, nitrate, and ammonium ions, organic and elemental carbon, and fine soil. Mass size distributions were measured with an eight-stage, single orifice cascade impactor. Four different strategies for estimating scattering were used. First, an externally mixed model with constant specific scattering coefficients, sulfate ion mass interpreted as ammonium bisulfate, and ammonium bisulfate growth as a function of relative humidity, is assumed. Second, an externally mixed aerosol model, assuming constant dry specific scattering but with sulfate ammoniation and associated composition-dependent hygroscopicity explicitly accounted for, is used. Third, an externally mixed aerosol model, but with sulfate ammoniation, associated growth as a function of relative humidity, and sulfate size distributions, is applied. Fourth, an internally mixed aerosol model with measured sulfur size distributions and estimated size distributions for other species is used with the growth characteristics of the mixture being estimated using the Zdanovskii-Stokes-Robinson (ZSR) assumptions. Only ionic species were considered to be hygroscopic. The second, third, and fourth approaches yield similar results with reconstructed scattering comparing... [ABSTRACT FROM AUTHOR]

In the United States, approximately 600,000 ha of pine trees are fertilized with urea each year, with NH3 volatilization losses ranging from < 1% to > 50% depending on environmental conditions. Previous work showed that the timing of rainfall after urea application plays a significant role in controlling NH3 loss, but the effect of other environmental variables is not well understood. We conducted 10 29-d studies under different environmental conditions during 2 yr to identify important variables controlling NH3 loss from urea applied to loblolly pine (Pinus taeda L.) at 200 kg N ha-1. Ammonia loss was measured with dynamic chambers that adjusted the rate of air flow through the system based on wind speed at 1 cm above the soil surface. Regression analysis indicated that a variable related to the initial water content of the forest floor and a variable related to the relative humidity (RH) during the study explained 85 to 94% of the observed variability in NH3 loss. Relatively high initial water content followed by consistently high RH led to large NH3 losses. In contrast, low initial water contents resulted in slow rates of NH3 loss, which increased when elevated RH led to an increase in the water content of the forest floor. These results indicate that RH can play a significant role in NH3 loss by accelerating urea dissolution and by increasing or decreasing the water content of the forest floor, which in turn can affect the rate of urea hydrolysis. [ABSTRACT FROM AUTHOR]

Fusarium head blight (FHB) is one of the most important cereal diseases in the world and has caused major losses to the grain industry. The principal pathogen causing FHB in North America is Gibberella zeae (anamorph Fusarium graminearum). Information on survival and the conditions under which ascospores remain viable once released from perithecia may assist in refining disease forecasting models. This study measured germination of ascospores after exposure to different temperatures, 15, 20, and 30°C, and levels of relative humidity (RH), 30, 60, and 90% for 4, 24, or 48 h periods. Viability was tested by germination on water agar. Germination rates fell with increasing temperatures at all observation times and at all humidity levels. At 15 and 20°C after 48 h, germination ranged from 74 to 85%, and 52 to 72%, respectively. At 30°C, germination ranged from 36 to 59% after 24 h and from 13 to 47% after 48 h. Germination was highest at 90% RH, except at 30°C after 48 h, and lowest at 60% RH. Successful germination, even under extreme conditions, suggests that ascospores are sufficiently robust to constitute a source of inoculum under most environmental conditions encountered during the growing season. [ABSTRACT FROM AUTHOR]

Since the World Health Organization has declared the current outbreak of the novel coronavirus (COVID-19) a global pandemic, some have been anticipating that the mitigation could happen in the summer like seasonal influenza, while medical solutions are still in a slow progress. Experimental studies have revealed a few evidences that coronavirus decayed quickly under the exposure of heat and humidity. This study aims to carry out an epidemiological investigation to establish the association between meteorological factors and COVID-19 in high risk areas of the United States (U.S.). We analyzed daily new confirmed cases of COVID-19 and seven meteorological measures in top 50 U.S. counties with the most accumulative confirmed cases from March 22, 2020 to April 22, 2020. Our analyses indicate that each meteorological factor and COVID-19 more likely have a nonlinear association rather than a linear association over the wide ranges of temperature, relative humidity, and precipitation observed. Average temperature, minimum relative humidity, and precipitation were better predictors to address the meteorological impact on COVID-19. By including all the three meteorological factors in the same model with their lagged effects up to 3 days, the overall impact of the average temperature on COVID-19 was found to peak at 68.45 °F and decrease at higher degrees, though the overall relative risk percentage (RR %) reduction did not become significantly negative up to 85 °F. There was a generally downward trend of RR % with the increase of minimum relative humidity; nonetheless, the trend reversed when the minimum relative humidity exceeded 91.42%. The overall RR % of COVID-19 climbed to the highest level of 232.07% (95% confidence interval = 199.77, 267.85) with 1.60 inches of precipitation, and then started to decrease. When precipitation exceeded 1.85 inches, its impact on COVID-19 became significantly negative. Our findings alert people to better have self-protection during the pandemic rather than expecting that the natural environment can curb coronavirus for human beings. [ABSTRACT FROM AUTHOR]

Canada and the United States export coniferous lumber and wood chips to Scandinavia and other countries, in 1984, Finnish authorities found the pinewood nematode (PWN) Bursaphelenchus xylophzlus in coniferous wood chips imported from Canada and the United States. The fact that pine-wilt disease, caused by the PWN, is a serious problem in Japan, gave Finland occasion to ban importation of all raw softwood materials from countries where the PWN occurs and, in 1986, other Scandinavian countries followed suit. The Scandinavian ban has affected North American forest exports.

Vapor pressure deficit (VPD) is the difference between saturation and actual water vapor pressures and is driven by interactions between air temperature and humidity. Globally, VPD observations indicate drying of the atmosphere, while air temperature (T) and relative humidity (RH) have changed asymmetrically during daytime versus nighttime. However, whether daytime or nighttime T (Tday and Tnight, respectively) and RH (RHday and RHnight, respectively) have been more important to VPD change is unknown, and so is the seasonal variation of this importance. This research determines the relative contribution of Tday, Tnight, RHday, and RHnight to VPD change observed during 1981–2021 across the conterminous United States. Tday contributed 41% to driving a VPD increase of 2.1 standard deviations (SD), followed by contributions of 25%, 22%, and 12% from RHday, RHnight, and Tnight, respectively. Regions with significant VPD increase have seen increase in Tday (by 1 SD) and Tnight (by 0.9 SD) and a decrease in RHday (by 1 SD) and RHnight (by 3.4 SD). Diurnal asymmetry in warming and drying trends was true for most months, with greater rates of change during the nighttime than daytime. Tday was the dominant driver of the annual mean VPD rise for 70% of the counties, followed by RHday (18%), RHnight (11%), and Tnight (1%). We conclude that warming and drying during the days and nights together explain increased VPD across the US croplands and that climate stressors during days and nights should be viewed independently due to their crop‐specific impacts that vary spatially and seasonally. Core Ideas: Vapor pressure deficit (VPD) has increased by 2.1 standard deviations during 1981–2021 in conterminous United States.Daytime or daily maximum air temperature (Tday), daytime or daily minimum relative humidity (RHday), nighttime or daily maximum relative humidity (RHnight), and nighttime or daily minimum air temperature contributed 41%, 25%, 22%, and 12% to annual mean VPD trend.Strong asymmetric warming and drying, that is, greater trends during daytime than nighttime.Relative contribution of drivers toward VPD trends changed substantially during the year.VPD rise during July and August was attributed equally to Tday, RHday, and RHnight. [ABSTRACT FROM AUTHOR]

Infant bronchiolitis is primarily due to infection by respiratory syncytial virus (RSV), which is highly seasonal. The goal of the study is to understand how circulation of RSV is impacted by fluctuations in temperature and humidity in order to inform prevention efforts. Using data from the Military Health System (MHS) Data Repository (MDR), we calculated rates of infant bronchiolitis for the contiguous US from July 2004 to June 2013. Monthly temperature and relative humidity were extracted from the National Climate Data Center. Using a spatiotemporal generalized linear model for binomial data, we estimated bronchiolitis rates and the effects of temperature and relative humidity while allowing them to vary over location and time. Our results indicate a seasonal pattern that begins in the Southeast during November or December, then spreading in a Northwest direction. The relationships of temperature and humidity were spatially heterogeneous, and we find that climate can partially account for early onset or longer epidemic duration. Small changes in climate may be associated with larger fluctuations in epidemic duration. [ABSTRACT FROM AUTHOR]

The article reports on the impact of humidity on wood. Wood has an affinity for water in both vapor and liquid form. The range of moisture content of wood in live trees is from over 30 percent to more than 200 percent. The equilibrium moisture content (EMC) for wood used outdoors differ by geographical region and month within the continental U.S. because the EMC depends on the interplay of relative humidity and temperature. INSETS: The Rittenhouse Hygrometer;The Weatherstick.

Triple oxygen isotope ratios (∆′17O) offer new opportunities to improve reconstructions of past climate by quantifying evaporation, relative humidity, and diagenesis in geologic archives. However, the utility of ∆′17O in paleoclimate applications is hampered by a limited understanding of how precipitation ∆′17O values vary across time and space. To improve applications of ∆′17O, we present δ18O, d‐excess, and ∆′17O data from 26 precipitation sites in the western and central United States and three streams from the Willamette River Basin in western Oregon. In this data set, we find that precipitation ∆′17O tracks evaporation but appears insensitive to many controls that govern variation in δ18O, including Rayleigh distillation, elevation, latitude, longitude, and local precipitation amount. Seasonality has a large effect on ∆′17O variation in the data set and we observe higher seasonally amount‐weighted average precipitation ∆′17O values in the winter (40 ± 15 per meg [± standard deviation]) than in the summer (18 ± 18 per meg). This seasonal precipitation ∆′17O variability likely arises from a combination of sub‐cloud evaporation, atmospheric mixing, moisture recycling, sublimation, and/or relative humidity, but the data set is not well suited to quantitatively assess isotopic variability associated with each of these processes. The seasonal ∆′17O pattern, which is absent in d‐excess and opposite in sign from δ18O, appears in other data sets globally; it showcases the influence of seasonality on ∆′17O values of precipitation and highlights the need for further systematic studies to understand variation in ∆′17O values of precipitation. Key Points: Precipitation δ′18O‐δ′17O slopes often differ from the 0.528 reference valuePrecipitation ∆′17O values are typically higher in the winter and lower in the summerDifferent controls on ∆′17O and δ18O mean that ∆′17O provides new information for paleoclimate reconstructions [ABSTRACT FROM AUTHOR]

Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US. Plain Language Summary: Fire danger index (FDI), a measure used to assess the risk and severity, relies on a combination of weather and fuel conditions. Multiple FDIs have been frequently used to predict and manage the risk of wildfire. However, it is unclear how well these indices work at different scales, causing uncertainty in predicting the likelihood of fire ignition and the potential size of a fire. Here, we analyzed four commonly used FDIs and conducted sensitivity analysis (SA) to determine their most important drivers. SA results indicate that daily minimum relative humidity, precipitation, and wind speed as the most important drivers. In addition, FDIs highly correlate with total fire size at annual and conterminous United States (CONUS) scale and such correlation decreases at finer spatial and temporal scales. We also used a regional climate model simulation to derive FDIs for current and future climate conditions. Our results suggest an overall increase in fire potential and a prolonged wildfire season in the future climate. Moreover, the enhanced fire frequency is projected to occur in spring and summer over the southwest US whereas in summer and fall over the northern and eastern CONUS. Key Points: The correlation between fire danger indices (FDIs) and observed wildfire size are scale dependentSensitivity analysis indicates that the daily minimum relative humidity and wind speed are the most important drivers of fire dangerCoupling FDIs with regional climate model simulation show higher fire potential in US in future climate [ABSTRACT FROM AUTHOR]

We investigate the climatic influence on COVID-19 transmission risks in 228 cities globally across three climatic zones. The results, based on the application of a Boosted Regression Tree algorithm method, show that average temperature and average relative humidity explain significant variations in COVID-19 transmission across temperate and subtropical regions, whereas in the tropical region, the average diurnal temperature range and temperature seasonality significantly predict the infection outbreak. The number of positive cases showed a decrease sharply above an average temperature of 10°C in the cities of France, Turkey, the US, the UK, and Germany. Among the tropical countries, COVID-19 in Indian cities is most affected by mean diurnal temperature, and those in Brazil by temperature seasonality. The findings have implications on public health interventions, and contribute to the ongoing scientific and policy discourse on the complex interplay of climatic factors determining the risks of COVID-19 transmission. [ABSTRACT FROM AUTHOR]

Anhydrous ammonia is transported via ship, rail, and road everyday in the United States as a refrigerated liquid at ambient pressure. As a result, unintential release of a large amount of anhydrous ammonia could result from an accident during transportation. The aim of this paper is to provide a better understanding of the evaporation of anhydrous ammonia from porous media. In our investigation, laboratory‐scale concrete coupons were used as a surrogate for a larger concrete pad that could be present in an event involving an unintentional release of liquid anhydrous ammonia. Concrete coupons sized 5 cm × 5 cm × 1.9 cm were saturated in liquid anhydrous ammonia, and measurements of the subsequent evaporation from the coupons were made in an environmental chamber. The ambient air temperature within the chamber varied from 5 to 45°C, and the relative humidity varied from 5% to 75%. Mass‐difference calculation and Berthelot's reaction were used to determine the average evaporation rate from a concrete coupon across all trials, which was found to be 6.5 ± 1.9 mg/s. To validate these evaporation rates, the remaining ammonia in the concrete coupon was measured for each trial. We found that the time‐integrated calculated evaporation rates correlated well with the total mass of ammonia that was lost from the coupons. In addition, it was found that ambient air temperature and relative humidity had little influence on anhydrous ammonia evaporation from the concrete coupons. [ABSTRACT FROM AUTHOR]

Copyright of Canadian Journal of Plant Pathology is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The Ogallala Aquifer, a primary irrigation water source in the High Plains region of the United States, is declining, thereby necessitating new water conservation strategies. This paper investigates the impact of mixed wettability on the evaporation dynamics of a 10-µl sessile water droplet placed within simulated soil pores comprised of hydrophobic Teflon beads (CA ∼ 108°) and hydrophilic glass (CA ∼ 41°) beads with 2.38-mm diameters, where homogeneous and heterogenous (i.e., mixed hydrophobicity and hydrophilicity) wettability configurations were investigated. Experiments were performed in an environmental chamber where the relative humidity and temperature were 60% ± 0.1% RH and 20 ± 0.4 °C, respectively. Wettability influenced evaporation times, with homogeneous hydrophobic pores (i.e., three Teflon beads) and heterogenous one glass, two Teflon pores having the longest average evaporation times of 40 and 39 min, respectively. Homogeneous hydrophilic pores (i.e., three glass beads) and heterogenous two glass, one Teflon pores exhibited evaporation times of 34 min. Evaporation times for heterogenous combinations trended based on the predominant wettability. Contact angles and the projected length of contact were analyzed from videos to capture pinning and depinning during evaporation. For many cases including hydrophobicity, contact angles were less than 90°, and in some configurations, water would be pinned on a Teflon bead, whereas depinning (i.e., moving) on a glass bead. Stick-slip evaporation was observed, where the evaporating droplet switched between constant contact radius and constant contact area evaporative modes to minimize droplet surface energy. The results suggest wettability alterations in agricultural settings may reduce evaporation. [ABSTRACT FROM AUTHOR]

Introduction: Vector-borne diseases (VBDs) are an increasingly important global health concern in the face of climate change. Understanding the ecology and evolution of vector species is critical to predicting and combating VBD. Vectorial capacity models, used to forecast disease transmission, traditionally assume traits are constant among populations, and little is known about whether different vector populations vary in thermal tolerance. To test for geographic variation in upper thermal tolerance, we determined the critical thermal maximum (CTmax) of Aedes albopictus, a globally distributed mosquito and competent vector for many viruses including West Nile, chikungunya, and dengue. Methods: We studied CTmax for eight different populations spanning four climate zones across the Eastern United States using common garden experiments to isolate genetic variation. To explore potential drivers of this variation we then tested the relationship between climatic variables measured near each population source and CTmax. Results: We found significant differences across populations for both adults and larvae, and these differences were more pronounced for adults. Larvae had higher CTmax values compared to adults. Several climatic variables improved models of CTmax for both adults and larvae including mean and max seasonal temperature, annual precipitation, and relative humidity. Annual precipitation appears to be particularly important and has a positive linear relationship with CTmax. Discussion: The differences between life stages likely result from different selection pressures experienced in their terrestrial and aquatic habitats. Importantly, the assumption that mosquito populations within a species have the same upper thermal limits does not hold in this case, thus it is important to use population-specific CTmax values, among other important physiological parameters that may vary, to more accurately model and forecast VBDs. [ABSTRACT FROM AUTHOR]

Climate change is escalating the threat of heat stress to global public health, with the majority of humans today facing increasingly severe and prolonged heat waves. Accurate weather data reflecting the complexity of measuring heat stress is crucial for reducing the impact of extreme heat on health worldwide. Previous studies have employed Heat Index (HI) and Wet Bulb Globe Temperature (WBGT) metrics to understand extreme heat exposure, forming the basis for heat stress guidelines. However, systematic comparisons of meteorological and climate data sets used for these metrics and the related parameters, like air temperature, humidity, wind speed, and solar radiation crucial for human thermoregulation, are lacking. We compared three heat measures (HImax, WBGTBernard, and WBGTLiljegren) approximated from gridded weather data sets (ERA5‐Land, PRISM, Daymet) with ground‐based data, revealing strong agreement from HI and WBGTBernard (R2 0.76–0.95, RMSE 1.69–6.64°C). Discrepancies varied by Köppen‐Geiger climates (e.g., Adjusted R2 HImax 0.88–0.95, WBGTBernard 0.79–0.97, and WBGTLiljegren 0.80–0.96), and metrological input variables (Adjusted R2Tmax 0.86–0.94, Tmin 0.91–0.94, Wind 0.33, Solarmax 0.38, Solaravg 0.38, relative humidity 0.51–0.74). Gridded data sets can offer reliable heat exposure assessment, but further research and local networks are vital to reduce measurement errors to fully enhance our understanding of how heat stress measures link to health outcomes. Plain Language Summary: Extreme heat threatens human health. Rising intensity and duration of heat days expose more to hot environments. To understand how extreme heat affects human health, it is important to use accurate weather information and measures that reflect people's actual experience of the heat. Heat Index (HI) and Wet Bulb Globe Temperature (WBGT) are commonly used heat stress metrics that are widely used to set exposure guidelines and policies. However, there have been limited comparisons between daily heat measures and weather variables. In this study, we compared three heat measures (HI, WBGTBernard, and WBGTLiljegren) derived from three widely used gridded weather data sets (ERA5‐Land, PRISM, and Daymet) with ground‐based weather observations. The heat measures calculated from both the gridded weather data and the station data showed a reasonably strong agreement. However, the differences varied depending on the climate types. Gridded weather data sets can provide a reliable approach to assessing heat exposure and impacts based on meteorological variables to produce heat measures. However, further research and the establishment of local ground station networks are necessary to reduce measurement errors in exposure and improve accuracy. This will help us better understand the relationship between heat measures and their impact on health outcomes. Key Points: Compared heat stress measures using gridded data sets and in situ data from 17 institutions across 42 states in the contiguous USObserved variations in heat measures and weather variables align with Köppen‐Geiger climate classificationsInstalling more Wet Bulb Globe Temperature‐measuring stations in diverse microclimates is key to better heat exposure prevention strategies [ABSTRACT FROM AUTHOR]

We perform a statistical climatological study of the synoptic- to meso-scale weather conditions favoring significant tornado occurrence to empirically investigate the existence of long term temporal trends. To identify environments that favor tornadoes, we apply an empirical orthogonal function (EOF) analysis to temperature, relative humidity, and winds from the Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA-2) dataset. We consider MERRA-2 data and tornado data from 1980 to 2017 over four adjacent study regions that span the Central, Midwestern, and Southeastern United States. To identify which EOFs are related to significant tornado occurrence, we fit two separate groups of logistic regression models. The first group (LEOF models) estimates the probability of occurrence of a significant tornado day (EF2-EF5) within each region. The second group (IEOF models) classifies the intensity of tornadic days either as strong (EF3-EF5) or weak (EF1-EF2). When compared to approaches using proxies such as convective available potential energy, our EOF approach is advantageous for two main reasons: first, the EOF approach allows for the discovery of important synoptic- to mesoscale variables previously not considered in the tornado science literature; second, proxy-based analyses may not capture important aspects of three-dimensional atmospheric conditions represented by the EOFs. Indeed, one of our main novel findings is the importance of a stratospheric forcing mode on occurrence of significant tornadoes. Other important novel findings are the existence of long-term temporal trends in the stratospheric forcing mode, in a dry line mode, and in an ageostrophic circulation mode related to the jet stream configuration. A relative risk analysis also indicates that changes in stratospheric forcings are partially or completely offsetting increased tornado risk associated with the dry line mode, except in the eastern Midwest region where tornado risk is increasing. [ABSTRACT FROM AUTHOR]

Prescribed burning is a critical tool for managing wildfire risks and meeting ecological objectives, but its safe and effective application requires that specific meteorological criteria (a 'burn window') are met. Here, we evaluate the potential impacts of projected climatic change on prescribed burning in the south-eastern United States by applying a set of burn window criteria that capture temperature, relative humidity and wind speed to projections from an ensemble of Global Climate Models under two greenhouse gas emission scenarios. Regionally, the percentage of suitable days for burning changes little during winter but decreases substantially in summer owing to rising temperatures by the end of the 21st century compared with historical conditions. Management implications of such changes for six representative land management units include seasonal shifts in burning opportunities from summer to cool-season months, but with considerable regional variation. We contend that the practical constraints of rising temperatures on prescribed fire activities represent a significant future challenge and show that even meeting basic burn criteria (as defined today) will become increasingly difficult over time, which speaks to the need for adaptive management strategies to prepare for such changes. Given a set of suitable weather conditions within which prescribed burning may occur, we use projections from Global Climate Models to explore the potential effects of climate change on prescribed fire management in the south-eastern US. Results indicate substantial reductions in the number of available burning days during late spring and summer months, which would restrict burn window opportunities to cool-season months in many parts of the region. [ABSTRACT FROM AUTHOR]

Large wildfires (>125 hectares) in the United States account for over 95% of the burned area each year. Predicting large wildfires is imperative; however, current wildfire predictive models are region-based and computationally intensive. Using a scalable model based on easily available environmental and atmospheric data, this research aims to accurately predict whether large wildfires will develop across the United States. The data used in this study include 2109 wildfires over 20 years, representing 14 million hectares burned. Remote sensing environmental data (Normalized Difference Vegetation Index—NDVI; Enhanced Vegetation Index—EVI; Leaf Area Index—LAI; Fraction of Photosynthetically Active Radiation—FPAR; Land Surface Temperature during the Day—LST Day; and Land Surface Temperature during the Night—LST Night) consisting of 1.3 billion satellite observations was used. Atmospheric reanalysis data (u component of wind, v component of wind, relative humidity, temperature, and geopotential) at four pressure levels (300, 500, 700, and 850 Ha) were also factored in. Six machine learning classification models (Logistic Regression, Decision Tree, Random Forest, eXtreme Gradient Boosting, K-Nearest Neighbors, and Support Vector Machine) were created and tested on the resulting dataset to determine their accuracy in predicting large wildfires. Model validation tests and variable importance analysis were performed. The eXtreme Gradient Boosting (XGBoost) classification model performed best in predicting large wildfires, with 90.44% accuracy, a true positive rate of 0.92, and a true negative rate of 0.88. Furthermore, towards environmental justice, an analysis was performed to identify disadvantaged communities that are also vulnerable to wildfires. This model can be used by wildfire safety organizations to predict large wildfires with high accuracy and prioritize resource allocation to employ protective safeguards for impacted socioeconomically disadvantaged communities. [ABSTRACT FROM AUTHOR]

Monitoring and understanding the variability of heat within cities is important for urban planning and public health, and the number of studies measuring intraurban temperature variability is growing. Recognizing that the physiological effects of heat depend on humidity as well as temperature, measurement campaigns have included measurements of relative humidity alongside temperature. However, the role the spatial structure in humidity, independent from temperature, plays in intraurban heat variability is unknown. Here we use summer temperature and humidity from networks of stationary sensors in multiple cities in the United States to show spatial variations in the absolute humidity within these cities are weak. This variability in absolute humidity plays an insignificant role in the spatial variability of the heat index and humidity index (humidex), and the spatial variability of the heat metrics is dominated by temperature variability. Thus, results from previous studies that considered only intraurban variability in temperature will carry over to intraurban heat variability. Also, this suggests increases in humidity from green infrastructure interventions designed to reduce temperature will be minimal. In addition, a network of sensors that only measures temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location, allowing for lower-cost heat monitoring networks. SIGNIFICANCE STATEMENT: Monitoring the variability of heat within cities is important for urban planning and public health. While the physiological effects of heat depend on temperature and humidity, it is shown that there are only weak spatial variations in the absolute humidity within nine U.S. cities, and the spatial variability of heat metrics is dominated by temperature variability. This suggests increases in humidity will be minimal resulting from green infrastructure interventions designed to reduce temperature. It also means a network of sensors that only measure temperature is sufficient to quantify the spatial variability of heat across these cities when combined with humidity measured at a single location. [ABSTRACT FROM AUTHOR]

Phyllachora maydis is a fungal pathogen causing tar spot of corn (Zea mays L.), a new and emerging, yield-limiting disease in the United States. Since being first reported in Illinois and Indiana in 2015, P. maydis can now be found across much of the corn growing regions of the United States. Knowledge of the epidemiology of P. maydis is limited but could be useful in developing tar spot prediction tools. The research presented here aims to elucidate the environmental conditions necessary for the development of tar spot in the field and the creation of predictive models to anticipate future tar spot epidemics. Extended periods (30-day windowpanes) of moderate mean ambient temperature (18–23 °C) were most significant for explaining the development of tar spot. Shorter periods (14- to 21-day windowpanes) of moisture (relative humidity, dew point, number of hours with predicted leaf wetness) were negatively correlated with tar spot development. These weather variables were used to develop multiple logistic regression models, an ensembled model, and two machine learning models for the prediction of tar spot development. This work has improved the understanding of P. maydis epidemiology and provided the foundation for the development of a predictive tool for anticipating future tar spot epidemics. [ABSTRACT FROM AUTHOR]

Globally, insects have been impacted by climate change, with bumble bees in particular showing range shifts and declining species diversity with global warming. This suggests heat tolerance is a likely factor limiting the distribution and success of these bees. Studies have shown high intraspecific variance in bumble bee thermal tolerance, suggesting biological and environmental factors may be impacting heat resilience. Understanding these factors is important for assessing vulnerability and finding environmental solutions to mitigate effects of climate change. In this study, we assess whether geographic range variation in bumble bees in the eastern United States is associated with heat tolerance and further dissect which other biological and environmental factors explain variation in heat sensitivity in these bees. We examine heat tolerance by caste, sex, and rearing condition (wild/lab) across six eastern US bumble bee species, and assess the role of age, reproductive status, body size, and interactive effects of humidity and temperature on thermal tolerance in Bombus impatiens. We found marked differences in heat tolerance by species that correlate with each species' latitudinal range, habitat, and climatic niche, and we found significant variation in thermal sensitivity by caste and sex. Queens had considerably lower heat tolerance than workers and males, with greater tolerance when queens would first be leaving their natal nest, and lower tolerance after ovary activation. Wild bees tended to have higher heat tolerance than lab reared bees, and body size was associated with heat tolerance only in wild‐caught foragers. Humidity showed a strong interaction with heat effects, pointing to the need to regulate relative humidity in thermal assays and consider its role in nature. Altogether, we found most tested biological conditions impact thermal tolerance and highlight the stages of these bees that will be most sensitive to future climate change. [ABSTRACT FROM AUTHOR]

Accurate estimation of evapotranspiration (ET) is a prerequisite for water management in arid regions. Field based methods estimate point-wise ET accurately, but the challenge is in estimating ET over a region with high accuracies. Machine learning based approaches were taken to estimate ET over a large spatial scale using the Bowen Ratio Energy Balance (BREB) technique. The BREB method depends on terrestrial energy balance equations to estimate ET. Thus, remote sensing-based parameters representing variables in the energy balance equation, and vegetation index representing plant health conditions were used in the model. The study was conducted in the arid areas of the southwestern United States, where dense patches of Salt cedar consume water from the primary water source. The preliminary model used enhanced vegetation index (EVI), global horizontal irradiance (GHI), surface temperature (TS), and relative humidity (RH) as parameters. The k-nearest neighbor method consistently generated poor accuracies. When all the parameters were used, accuracies of the other models varied within 90–94%. When one predictor parameter was dropped, the best model produced accuracies between 90 to 93%, which dropped to 87–92% when a second variable was dropped. Random forest and support vector machine with radial kernel consistently produced the best predictive accuracies. [ABSTRACT FROM AUTHOR]

Introduction: Operating room air quality can be affected by several factors including temperature, humidity, and airborne particle burden. Our study examines the role of operating room (OR) size on air quality and airborne particle (ABP) count in primary total knee arthroplasty (TKA). Materials and methods: We analyzed all primary, elective TKAs performed within two ORs measuring 278 sq ft. (small) and 501 sq ft. (large) at a single academic institution in the United States from April 2019 to June 2020. Intraoperative measurements of temperature, humidity, and ABP count were recorded. p values were calculated using t test for continuous variables and chi-square for categorical values. Results: 91 primary TKA cases were included in the study, with 21 (23.1%) in the small OR and 70 (76.9%) in the large OR. Between-groups comparisons revealed significant differences in relative humidity (small OR 38.5% ± 7.24% vs. large OR 44.4% ± 8.01%, p = 0.002). Significant percent decreases in ABP rates for particles measuring 2.5 μm (− 43.9%, p = 0.007) and 5.0 μm (− 69.0%, p = 0.0024) were found in the large OR. Total time spent in the OR was not significantly different between the two groups (small OR 153.09 ± 22.3 vs. large OR 173 ± 44.6, p = 0.05). Conclusions: Although total time spent in the room did not differ between the large and small OR, there were significant differences in humidity and ABP rates for particles measuring 2.5 μm and 5.0 μm, suggesting the filtration system encounters less particle burden in larger rooms. Larger studies are required to determine the impact this may have on OR sterility and infection rates. [ABSTRACT FROM AUTHOR]

Widespread wildfires struck the western United States in 2020, damaging properties and threating human lives. Meanwhile, the COVID‐19 pandemic spread across the globe, which disrupted human activities. Here, we investigate the effects of the emissions reductions during the pandemic on fire weather in 2020 over the western United States by using an earth system model together with observations. We show that reductions in aerosols dominate the increases in wildfire risks, whereas greenhouse gas decrease counteracts this influence. The aerosol emissions reductions increased surface air temperature and decreased precipitation and relative humidity due to a weakened moisture transport, which explains one‐third of the observed increase in wildfire risks during August–November over the western United States in 2020. This study suggests that COVID‐19‐related emissions reductions have an unexpected influence on wildfires, highlighting a different but important role of human activities in affecting wildfire risks. Plain Language Summary: Widespread wildfires struck the western United States in 2020 and caused devastating damage on the environment and society. Due to the COVID‐19 pandemic, human activities were restricted and resulted in reductions in anthropogenic emissions. Based on climate model and observational data, our results show that the COVID‐19 emissions reductions in particular matter increased surface air temperature and decreased precipitation and relative humidity, which explains one‐third of the observed increase in the risk of wildfires over the western United States in 2020. Key Points: The impacts of COVID‐19 emissions reductions on weather conditions for wildfire over the western United States in 2020 were investigatedThe COVID‐19 emissions reductions increased surface air temperature and decreased precipitation and relative humidityReductions in aerosols explain one‐third of the observed wildfire risk increase, whereas greenhouse gas decrease counteracts this influence [ABSTRACT FROM AUTHOR]

Simple Summary: Ixodes scapularis, also known as the blacklegged tick or deer tick, is the vector of the bacteria that causes Lyme disease in humans, the most common vector-borne disease in the United States. Synthetic chemical pesticides are used to control ticks. Environmentally friendly, new methods are needed to manage chemical pesticide resistance. We evaluated the efficacy of the industrial mineral, Celite 610, an amorphous silica, against unfed I. scapularis nymphs. Celite is found in nature and has a mechanical, non-toxic mode of action. Dipping ticks into Celite for 1–2 s resulted in 90% mortality in as little as 69 min. Scanning electron microscopy suggested that one mode of action could be the physical obstruction of respiration. We developed another industrial mineral made from volcanic glass, ImergardTM WP, for mosquito and filth fly control. In studies here, Imergard had similar activity as Celite against the deer tick. This research, although needing further study, suggests that industrial minerals could be a new, safe ("found in toothpaste") and persistent ("it's rock") alternative to chemical pesticides to control ticks. Cases of Lyme disease in humans are on the rise in the United States and Canada. The vector of the bacteria that causes this disease is the blacklegged tick, Ixodes scapularis. Current control methods for I. scapularis mainly involve chemical acaricides. Unfortunately, ticks are developing resistance to these chemicals, and more and more, the public prefers non-toxic alternatives to chemical pesticides. We discovered that volcanic glass, ImergardTM WP, and other industrial minerals such as Celite 610 were efficacious mechanical insecticides against mosquitoes, filth flies, and agricultural pests. In this report, when 6–10- and 50–70-day old unfed I. scapularis nymphs were dipped for 1–2 s into Celite, the time to 50% mortality (LT50) was 66.8 and 81.7 min, respectively, at 30 °C and 50% relative humidity (RH). The LT50 was actually shorter at a higher 70% RH, 43.8 min. Scanning electron microscopy showed that the ticks were coated over most of their body surface, including partial to almost total coverage of the opening to their respiratory system. The other mechanical insecticide, Imergard, had similar efficacy against blacklegged unfed nymphs with an LT50 at 30 °C and 50% RH of 70.4 min. Although more research is needed, this study suggests that industrial minerals could be used as an alternative to chemical pesticides to control ticks and Lyme disease. [ABSTRACT FROM AUTHOR]

The impact of water consumption bolus volume and frequency on hydration biomarkers during work in the heat is unknown. In a randomized, crossover fashion, eight males consumed either 500 mL of water every 40 min or 237 mL of water every 20 min during 2 hr of continuous walking at 6.4 kph, 1.0% grade in a 34 °C/30% relative humidity environment, followed by 2 hr of rest. Hydration biomarkers and variables were assessed pre-work, post-work, and after the 2 hr recovery. There were no differences in body mass between trials at any time point (all p > 0.05). Percent change in plasma volume during work was not different when 237 mL of water was repeatedly consumed (−1.6 ± 8.2%) compared to 500 mL of water (−1.3 ± 3.0%, p = 0.92). Plasma osmolality was maintained over time (p = 0.55) with no difference between treatments (p = 0.21). When consuming 500 mL of water repeatedly, urine osmolality was lower at recovery (205 ± 108 mOsmo/L) compared to pre-work (589 ± 95 mOsmo/L, p < 0.01), different from repeatedly consuming 237 mL of water which maintained urine osmolality from pre-work (548 ± 144 mOsmo/L) through recovery (364 ± 261 mOsmo/L, p = 0.14). Free water clearance at recovery was greater with repeated consumption of 500 mL of water (1.2 ± 1.0 mL/min) compared to 237 mL of water (0.4 ± 0.8 mL/min, p = 0.02). Urine volume was not different between treatments post-work (p = 0.62), but greater after 2 hr of recovery when repeatedly consuming 500 mL of water compared to 237 mL (p = 0.01), leading to greater hydration efficiency upon recovery with repeated consumption of 237 mL of water (68 ± 12%) compared to 500 mL (63 ± 14%, p = 0.01). Thirst and total gastrointestinal symptom scores were not different between treatments at any time point (all p > 0.05). Body temperatures and heart rate were not different between treatments at any time point (all p > 0.05). Drinking larger, less frequent water boluses or drinking smaller, more frequent water boluses are both reasonable strategies to promote adequate hydration and limit changes in body mass in males completing heavy-intensity work in the heat. [ABSTRACT FROM AUTHOR]

Certain occupations are associated with greater risk of triggering a sudden cardiac event because of high levels of physical exertion and extreme thermal environments in which they occur. The extent to which sports officials––particularly high school (HS) American football referees––experience these conditions is unknown. Forty-six male HS officials (72% White/Caucasian; age = 48 ± 12 years, body mass index = 31.7 ± 6.6 kg·m−2) were studied to quantify the physiological strain and physical demands of officiating. Referee demographics (e.g., experience, habitual exercise), pre-game urine specific gravity (USG), thermal (peak core temperature [Tcore]) and cardiovascular (average heart rate [HR]) strain, kinematic activity (e.g., total distance, speed, mechanical intensity), and environmental conditions were measured during 10 regular season varsity HS football games (≈2.5 h each) in the Southeastern United States (average wet bulb globe temperature and relative humidity: 18.9 ± 6.0 °C and 78.2% ± 12.1%). Analyses included descriptive statistics, bivariate correlations, and linear regression. Referees covered 5.2 ± 1.2 km per game, eliciting average HR and peak Tcore of 71.5% ± 8.0% HRmax and 38.3 ± 0.5 °C, respectively; 38% began games dehydrated (USG = 1.026 ± 0.004). Multiple regression analyses revealed that obesity (β = 0.34), not participating in regular exercise (β = −0.36), and officiating at lower mechanical intensity (β = −0.33) predicted greater cardiovascular strain (all p ≤ 0.03). White/Caucasian race/ethnicity (β = 0.59), younger age (β = −0.46), and obesity (β = 0.28) predicted greater thermal strain (all p ≤ 0.01). HS football referees experienced elevated levels of physiological strain while officiating, with individual factors modulating the magnitude of strain. Strategies aimed at reducing obesity, increasing exercise participation, and improving cardiovascular health should be emphasized to mitigate strain and prevent cardiac events. [ABSTRACT FROM AUTHOR]

This work examines how environmental variables previously shown to be correlated with dust emissions (temperature, vapor pressure deficit, relative humidity, precipitation, soil moisture, wind speed, and leaf area index [LAI]) explain historical variability in observed fine dust concentrations in the southwestern United States. We quantify fine dust concentrations in the U.S. Southwest dust season, March through July 1995 through 2015, using fine iron measurements from the Interagency Monitoring of Protected Visual Environments network as a dust proxy. We use Coupled Model Intercomparison Project Phase 5 (CMIP5) output to estimate how environmental variables that drive dust concentrations may change in the future. The majority of CMIP5 models that simulate LAI, a quantity anticorrelated with dust concentrations, show increasing LAI in the Southwest United States in the 21st century. Based on linear estimates of how dust concentrations respond to changes in LAI, increases in LAI could result in reduced dust concentrations in the future. However, when environmental variables are selected objectively using lasso regression, LAI is not selected in favor of other variables. When using a linear combination of objectively selected environmental variables, we estimate that future Southwest dust season concentrations will increase by 0.24 μg m−3 (12%) by the end of the 21st century for RCP 8.5. This estimated increase in fine dust concentration is driven by decreases in relative humidity, precipitation, and soil moisture and buffered by decreased wind speeds. Plain Language Summary: Airborne dust can alter atmospheric composition and negatively impact human health. Recent work has suggested that dust concentrations in the Southwest United States may be increasing. This work examines how environmental conditions that drive fine dust concentrations in the southwestern United States may change in the future and what these changes imply for future dust concentrations. We show that estimates of future fine dust concentrations in the Southwest are sensitive to the choice of environmental variables used to make the estimate and that the differences in estimates based on different environmental conditions can be larger than the differences observed between a climate scenario where carbon emissions slow and one where they continue to increase throughout the 21st century. When using a linear combination of objectively selected environmental variables, we estimate that future Southwest dust season concentrations will increase by 12% by the end of the 21st century for a climate scenario where greenhouse gas emissions continue to increase. This estimated increase in fine dust concentration is driven by decreases in relative humidity, precipitation, and soil moisture and buffered by decreased wind speeds. Key Points: Future dust concentration estimates are sensitive to the environmental conditions used to explain historical variabilityFuture fine dust concentrations will likely increase by the end of the 21st century for a climate scenario with high carbon emissionsIncreased dust concentrations are due to decreased relative humidity, precipitation, and soil moisture and buffered by decreased wind speeds [ABSTRACT FROM AUTHOR]

Analyses of wildfire‐climate relationships in North America were conducted using diverse independent observation and reanalysis data sets for the period 1984–2014. Results show that the western United States (WUS) has experienced the most robust increase in burned area, even though Alaska and western‐central Canada have comparable warming trends. In addition to warming, the WUS has been under the influence of multi‐decadal trends in tropospheric relative humidity deficit, reduced cloudiness, increased surface net insolation, and enhanced adiabatic warming and drying from increased tropospheric subsidence, as well as drying from enhanced offshore low‐level flow. These trends are found to be associated with a widening of the descending branch of the Hadley circulation, consistent with climate model projections under greenhouse gases warming. Due to the relative short (~30 years) data record, the aforementioned trend signals are likely also be affected by phase changes of natural interdecadal variability during the data period. Plain Language Summary: The increase in wildfires in the western United States (WUS) has been attributed to numerous factors, such as enhanced warming, drying, and ignitions by humans or nature and possibly amplified by a regional climate feedback. However, the mechanisms of the feedback are not well understood. Our observational analyses show that the increase in wildfires in the WUS is likely linked to a multi‐decadal drying trend in the subtropical troposphere associated with the expansion of the Hadley circulation under greenhouse‐gas warming. This circulation change induces a regional climate feedback, involving reduced relative humidity, fewer clouds, more downward surface insolation, warmer land surfaces, enhanced subsidence, and stronger offshore low‐level winds. This results in accelerated and sustained tropospheric warming and drying, exacerbating wildfires in the WUS. Results suggest that if actions to combat climate change are not taken soon, the WUS wildfire situation will likely worsen quickly. Key Points: Tropospheric warming and drying, induced by a regional climate feedback spurred on by the expansion of the Hadley circulation under global warming, enhance and sustain the recent long‐term increasing trend in large wildfires in the western United StatesDue to its unique climatology, western United States has the most robust long‐term large wildfire increasing trend in North America during 1984–2014Warming and drying by adiabatic compression of sinking air, and increased low level offshore, downslope winds play key roles [ABSTRACT FROM AUTHOR]

Presents a list of cities in the United States with the worst combination of both daytime and nighttime heat and humidity. Heat Index created by R.J. Steadman, a matrix that provides the `apparent temperature' for certain combinations of dry-air temperature and relative humidity; Summer Simmer Index, an equivalent temperature that expresses how hot a particular condition would feel in ten percent relative humidity.

As of 2023, the use of prescribed fire to manage ecosystems accounts for more than 50% of area burned annually across the United States. Prescribed fire is carried out when meteorological conditions, including temperature, humidity, and wind speed are appropriate for its safe and effective application. However, changes in these meteorological variables associated with future climate change may impact future opportunities to conduct prescribed fire. In this study, we combine climate projections with information on prescribed burning windows for ecoregions across the contiguous United States (CONUS) to compute the number of days when meteorological conditions allow for the safe and effective application of prescribed fire under present-day (2006–2015) and future climate (2051–2060) conditions. The resulting projections, which cover 57% of all vegetated area across the CONUS, indicate fewer days with conditions suitable for prescribed burning across ecoregions of the eastern United States due to rising maximum daily temperatures, but opportunities increase in the northern and northwestern United States, driven primarily by rising minimum temperatures and declining wind speeds. [ABSTRACT FROM AUTHOR]

Pecan is a major specialty crop produced in the United States. Sensory evaluation and chemical analyses of pecan nutmeats are integral components of shelf life and have been employed to investigate changes during storage, but there remains a lack of knowledge regarding storage stability. Specifically, the association between shelf life and chemical characteristics has not been investigated. We aimed to investigate the chemical changes in pecan nuts during a range of storage treatments (temperature, relative humidity, packaging material, and modified atmosphere). The results of the chemical analyses were used to build a volatile compound‐based sensory prediction model. The work has utility as a rapid method to measure lipid oxidation in pecan, which is of value to the pecan industry. The research also determined a possible association between pecan nut volatile compounds and sensory attributes of pecans, and their perception by human subjects. Building a sensory‐based prediction model would reduce dependency on expensive and time‐consuming sensory methods. [ABSTRACT FROM AUTHOR]

This article explains that nature asserts its power in many ways, including tornadoes, hurricanes, and blizzards--each capable of causing highly visible destruction and death. But nature also flexes its muscles in quieter ways. One silent entity, extreme heat, claims 1,500 lives in the U.S. each year. Worldwide, the number of heat fatalities is staggering, with a death toll estimated to exceed 20,000, especially in regions where people are not acclimated to prolonged periods of excessive heat. This scenario was tragically highlighted during the August 2003 European heat wave, which was estimated to have caused nearly 15,000 deaths in Paris alone, and up to 40,000 deaths across Western Europe. It explains why such a devastating killer attract such little discussion.

Heat acclimation (HA) is the foremost method of preventing exertional heat illness during exercise in hot and humid environments. However, the prevalence of HA training and its associated knowledge is not currently known in recreational running populations. The purpose of this study was to determine the knowledge of recreational runners toward HA. A survey consisting of 38 questions that required approximately 10–15 min to complete was disseminated to running clubs throughout the Southeastern United States. Questions were designed to collect data on participant demographics, yearly training habits, and HA knowledge. Recreational runners (N = 125) demonstrated a lack of knowledge toward proper HA training and its associated benefits. Participants largely received HA advice from their peers (31.2%) and reported no professional guidance in their training (79.2%). Finally, participants' beliefs toward proper HA training differed among training groups with moderate and high groups perceiving greater frequency, miles/wk, and min/wk as appropriate for HA compared to the low group (p ≤ 0.05). Due to the warmer temperatures and higher relative humidity experienced in the southeastern, southwestern, and mid-Atlantic locations of the United States and throughout certain regions of the European Union, governing bodies in sport and exercise science should develop more educational initiatives to convey the importance and advantages of HA, especially when runners are training for major marathons that are typically held in the late spring and early fall seasons. [ABSTRACT FROM AUTHOR]

Heat index (HI) provides a proven indicator of heat stress and discomfort for the general public. The index takes the integrated effects of both temperature and humidity into account, and both factors are regulated by large-scale circulation patterns. This study examines the impacts of the North Atlantic Subtropical High (NASH) on HI over the conterminous United States (CONUS). The analysis suggests that the HI is primarily controlled by surface air temperature over the CONUS; but is negatively correlated with relative humidity in the western and Central US north of 40°N. In addition, winds contribute to the variation of HI in the Midwest and the southeastern US. By regulating these meteorological parameters, the movement of the NASH western ridge significantly impacts HI over the US, especially the Southeast. When the NASH western ridge is located northwest (NW) of its climatological mean position, abnormally high temperatures are observed due to fewer clouds and a precipitation deficit, leading to positive HI anomalies over the southeastern US. In contrast, when the western ridge is located in the southwest (SW), temperature decreases and HI anomaly becomes negative over the Southeast, even though relative humidity increases east of 100°W. NASH has a weaker impact on the HI when it is far from the North American continent, especially during southeast (SE) ridge years. In the future, CMIP5 models project an increase in HI over the entire CONUS, while NASH-induced HI will be weakened during the NW, SE and NE ridge years but strengthened when its ridge moves to the SW quadrant. These results suggest that future increases in heat stress are likely caused by climatological warming and NASH intensification. [ABSTRACT FROM AUTHOR]

Background Lyme borreliosis (LB) is the most commonly reported vector-borne disease in north temperate regions worldwide, affecting an estimated 300,000 people annually in the United States alone. The incidence of LB is correlated with human exposure to its vector, the blacklegged tick (Ixodes scapularis). To date, attempts to model tick encounter risk based on environmental parameters have been equivocal. Previous studies have not considered (1) the differences between relative humidity (RH) in leaf litter and at weather stations, (2) the RH threshold that affects nymphal blacklegged tick survival, and (3) the time required below the threshold to induce mortality. We clarify the association between environmental moisture and tick survival by presenting a significant relationship between the total number of tick adverse moisture events (TAMEs - calculated as microclimatic periods below a RH threshold) and tick abundance each year. Methods We used a 14-year continuous statewide tick surveillance database and corresponding weather data from Rhode Island (RI), USA, to assess the effects of TAMEs on nymphal populations of I. scapularis. These TAMEs were defined as extended periods of time (>8 h below 82% RH in leaf litter). We fit a sigmoid curve comparing weather station data to those collected by loggers placed in tick habitats to estimate RH experienced by nymphal ticks, and compiled the number of historical TAMEs during the 14-year record. Results The total number of TAMEs in June of each year was negatively related to total seasonal nymphal tick densities, suggesting that sub-threshold humidity episodes >8 h in duration naturally lowered nymphal blacklegged tick abundance. Furthermore, TAMEs were positively related to the ratio of tick abundance early in the season when compared to late season, suggesting that lower than average tick abundance for a given year resulted from tick mortality and not from other factors. Conclusions Our results clarify the mechanism by which environmental moisture affects blacklegged tick populations, and offers the possibility to more accurately predict tick abundance and human LB incidence. We describe a method to forecast LB risk in endemic regions and identify the predictive role of microclimatic moisture conditions on tick encounter risk. [ABSTRACT FROM AUTHOR]

Plastic shrinkage cracking of concrete bridge decks occurs when the water evaporation rate at the surface exceeds the bleeding rate of the freshly placed concrete. Also, the rate of early drying shrinkage after the concrete hardens is related to water evaporation rate due to weather conditions over a prolonged period of time. Thus, water evaporation rate values are of great interest when placing and curing concrete bridge decks. The American Concrete Institute (ACI) has published a water evaporation chart that aids in deciding if weather conditions will cause plastic shrinkage at the time of concrete placement. The chart, although developed for plastic concrete and plastic shrinkage, could be used in conjunction with relative humidity, temperature, and wind velocity data for different locations, times during a day, and times of the year, to provide an improved guideline for indicating appropriate weather-related curing requirements for bridge decks. This study identifies typical temperature, relative humidity, and wind-weather exposure conditions in Alabama for various months/seasons of the year and times of the day; it also evaluates, via the ACI 305 Surface Evaporation Chart, concrete-surface water evaporation rates for these typical Alabama weather exposure conditions. Based on these data and results, tentative bridge-deck curing requirement categories appropriate for Alabama are identified. [ABSTRACT FROM AUTHOR]

To bridge the knowledge gap between (a) our (instantaneous-to-seasonal-scale) process understanding of plants and water and (b) our projections of long-term coupled feedbacks between the terrestrial water and carbon cycles, we must uncover what the dominant dynamics are linking fluxes of water and carbon. This study uses the simplest empirical dynamical systems models-two-dimensional linear models-and observation-based data from satellites, eddy covariance towers, weather stations, and machine-learning-derived products to determine the dominant sub-annual timescales coupling carbon uptake and (normalized) evaporation fluxes. We find two dominant modes across the Contiguous United States: (1) a negative correlation timescale on the order of a few days during which landscapes dry after precipitation and plants increase their carbon uptake through photosynthetic upregulation. (2) A slow, seasonal-scale positive covariation through which landscape drying leads to decreased growth and carbon uptake. The slow (positively correlated) process dominates the joint distribution of local water and carbon variables, leading to similar behaviors across space, biomes, and climate regions. We propose that vegetation cover/leaf area variables link this behavior across space, leading to strong emergent spatial patterns of water/carbon coupling in the mean. The spatial pattern of local temporal dynamics-positively sloped tangent lines to a convex long-term mean-state curve-is surprisingly strong, and can serve as a benchmark for coupled Earth System Models. We show that many such models do not represent this emergent mean-state pattern, and hypothesize that this may be due to lack of water-carbon feedbacks at daily scales., (© 2024 The Author(s). Global Change Biology published by John Wiley & Sons Ltd.)

Nothopassalora personata is one of the most economically severe pathogens of peanut in the United States. The fungus primarily relies on wind and rain for dispersal, which has been documented up to 10 m from an inoculum source. Spore traps have been used in a wide variety of pathosystems to study epidemiology, document detection, develop alert systems, and guide management programs. The objective of this study was to use spore traps and N. personata-specific qPCR primers to quantitatively evaluate dispersal of N. personata conidia at distances up to 70 m from an infected peanut field and to examine relationships between quantities captured and weather variables. Impaction spore samplers were placed at 4, 10, 30, 50, and 70 m from peanut fields at the Edisto Research and Education Center (six fields) and commercial peanut fields in Barnwell and Bamberg counties (one field each) from 2020 to 2022. Following initial detection, samples were collected at a 48-, 48-, 72-h interval until harvest. N. personata conidia were detected at all locations and distances, documenting dispersal up to 70 m from an inoculum source. This result is a reminder that volunteer management is crucial when rotating peanut in nearby fields. A model for predicting log spore quantities was developed using temperature and humidity variables. Temperature variables associated with observed sampling periods had a negative correlation with N. personata quantities, whereas parameters of relative humidity and mean windspeed were positively correlated. [ABSTRACT FROM AUTHOR]

Existing precipitation-type algorithms have difficulty discerning the occurrence of freezing rain and ice pellets. These inherent biases are not only problematic in operational forecasting but also complicate the development of model-based precipitation-type climatologies. To address these issues, this paper introduces a novel light gradient-boosting machine (LightGBM)-based machine learning precipitation-type algorithm that utilizes reanalysis and surface observations. By comparing it with the Bourgouin precipitation-type algorithm as a baseline, we demonstrate that our algorithm improves the critical success index (CSI) for all examined precipitation types. Moreover, when compared with the precipitation-type diagnosis in reanalysis, our algorithm exhibits increased F1 scores for snow, freezing rain, and ice pellets. Subsequently, we utilize the algorithm to compute a freezing-rain climatology over the eastern United States. The resulting climatology pattern aligns well with observations; however, a significant mean bias is observed. We interpret this bias to be influenced by both the algorithm itself and assumptions regarding precipitation processes, which include biases associated with freezing drizzle, precipitation occurrence, and regional synoptic weather patterns. To mitigate the overall bias, we propose increasing the precipitation cutoff from 0.04 to 0.25 mm h−1, as it better reflects the precision of precipitation observations. This adjustment yields a substantial reduction in the overall bias. Finally, given the strong performance of LightGBM in predicting mixed precipitation episodes, we anticipate that the algorithm can be effectively utilized in operational settings and for diagnosing precipitation types in climate model outputs. Significance Statement: Freezing rain can have significant impacts on transportation and infrastructure, making accurate prediction of precipitation types crucial. In this study, we use a machine learning method known as LightGBM to predict precipitation types. We show that the new algorithm performs better than the existing methods for all precipitation types examined. Additionally, we compute a freezing-rain climatology over the eastern United States. Although the resulting climatology pattern corresponds well to observations, the algorithm overpredicts freezing-rain occurrence. We argue that this bias can be substantially reduced by increasing the precipitation cutoff from 0.04 to 0.25 mm h−1. Overall, this work highlights the potential of the LightGBM algorithm for both weather forecasting and diagnosing precipitation types in climate models. [ABSTRACT FROM AUTHOR]

Observed links between parasites, such as ticks, and climate change have aroused concern for human health, wildlife population dynamics, and broader ecosystem effects. The one‐host life history of the winter tick (Dermacentor albipictus) links each annual cohort to environmental conditions during three specific time periods when they are predictably vulnerable: spring detachment from hosts, summer larval stage, and fall questing for hosts. We used mixed‐effects generalized linear models to investigate the drivers of tick loads carried by moose (Alces alces) relative to these time periods and across 750 moose, 10 years, and 16 study areas in the western United States. We tested for the effects of biotic factors (moose density, shared winter range, vegetation, migratory behavior) and weather conditions (temperature, snow, humidity) during each seasonal period when ticks are vulnerable and off‐host. We found that warm climatic regions, warm seasonal periods across multiple partitions of the annual tick life cycle, and warm years relative to long‐term averages each contributed to increased tick loads. We also found important effects of snow and other biotic factors such as host density and vegetation. Tick loads in the western United States were, on average, lower than those where tick‐related die‐offs in moose populations have occurred recently, but loads carried by some individuals may be sufficient to cause mortality. Lastly, we found interannual variation in tick loads to be most correlated with spring snowpack, suggesting this environmental component may have the highest potential to induce change in tick load dynamics in the immediate future of this region. [ABSTRACT FROM AUTHOR]

The responses of secondary organic aerosols (SOA) to emission controls remain uncertain due to the limited continuous long‐term measurements. Measurements of detailed carbonaceous aerosol composition in the New York City metropolitan region during the summers of 2001, 2009, 2011, and 2018 provide a look at the changes in summertime SOA over the past two decades when significant pollution reduction and emission controls occurred in the northeastern United States. Here, we show that the averaged nighttime SOA, especially the fresh local SOA, extreme mass concentrations resulted from anthropogenic volatile organic compounds reductions, while there is a little trend for the regional aged SOA. Meanwhile, these fresh SOA extremes occurred most often under conditions of high relative humidity during nighttime. The analysis presented here provides a comprehensive evaluation of the evolution of the increasingly important organic component of the submicron ambient aerosols in this major metropolitan area. Plain Language Summary: Particulate matter air pollution is a major health hazard and the largest driver of air pollution's burden of disease worldwide. Organic compounds constitute the largest fraction of mass for particulate matter in most locations. This study examines trends in organic aerosol in the New York City area and the relationship of this pollutant with the emissions of anthropogenically and biogenically produced and emitted volatile organic compounds. Extreme high values of organic aerosol, which are the most impactful episodes with regard to adverse health effects, were observed to occur preferentially in summertime high humidity conditions and during nighttime. The insights into organic aerosol formation mechanisms and concentration levels will assist scientists and regulators to control this important pollutant. Key Points: Local formed secondary organic aerosols (SOA) nighttime extremes reflect the reduction of anthropogenic volatile organic compoundsA flat multiyear trend is observed for the regional‐aged SOAThe regional aged SOA is becoming increasingly decoupled from highly oxidized particle sulfate [ABSTRACT FROM AUTHOR]