peak summer
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MAUSAM ◽  
2021 ◽  
Vol 57 (4) ◽  
pp. 653-662
Author(s):  
JAYANTA SARKAR ◽  
V. K. SONI ◽  
A. S. GADGIL ◽  
A. K. MUKHERJEE

lkj & bl 'kks/k i= esa 1981 ls 1996 rd dh vof/k esa ukxiqj esa gqbZ o"kkZ ds ikuh esa jklk;fud rRoksa dh miyC/krk dk v/;;u fd;k x;k gSA bl v/;;u ls ;g irk pyk gS fd ukxiqj esa o"kkZ _rq esa ckj&ckj xtZ ds lkFk vkus okys rwQkuksa ds dkj.k o"kkZ ds ikuh esa Na+ vkSj Cl- ds lkanz.kksa esa leqnz dk izHkko de gSA ;gk¡ ij ekulwu _rq ds vkxeu ls igys ds eghuksa esa vkSj iwjh ekulwu _rq ds nkSjku NO3&  esa cgqr  vf/kd lkanzrk fjdkWMZ dh xbZ gSA ekulwu _rq ds nkSjku K+ dks NksM+dj o"kkZ ds ikuh ds lHkh ?kVdksa dh vxLr rd lkanzrk de gksrh tkrh gSA rFkkfi] flracj esa lHkh ?kVdksa dh lkanzrk esa o`f} ikbZ xbZ gSA Cl- vkSj Na+ ds fu{ksi.k eku rVh; dsanzksa dh rqyuk esa dkQh de ik, x, gSaA SO4&2 ds fu{ksi.k ekuksa dh rqyuk     ;w- ,l- ,l- vkj- ds dqN Hkkxksa esa ik, x, ekuksa ls dh tk ldrh gSA o"kkZ ds ikuh ds fofHkUu ?kVdksa ds chp vuqikrksa dk v/;;u djus vkSj leqnz ds ikuh ds vuqikrksa ds lkFk mudh rqyuk djus ls irk pyk gS fd ukxiqj esa o"kkZ ds ikuh esa Na+ dh vf/kdrk dk dkj.k leqnz ds ikuh ds vykok vU; lzksr Hkh gSaA pH ekuksa esa cgqr vf/kd fofHkUurk ikbZ xbZ gSA ekulwu esa] twu ds ]ckn pH de gksrk tkrk gS vkSj flracj rd cgqr de gks tkrk gSA bldk dkj.k o"kkZ ds ikuh }kjk ewy dSVk;uksa dk i`Fkd djuk ekuk tk ldrk gSA vizSy vkSj ebZ ds lcls rst xehZ ds eghuksa esa pH dh vf/kd ek=k dk dkj.k okrkoj.k esa /kwy d.kksa dh ek=k] ftlesa eq[;r% ewy dSVk;u gksrs gSa] dks ekuk tk ldrk gSA ekulwu _rq ds izR;sd ekg ds pH ds v/;;u ls irk pyk gS fd twu vkSj tqykbZ esa o"kkZ dk Lo:i  lokZf/kd ekSfyd gS tcfd vxLr vkSj flracj esa ukxiqj esa vEyh; o"kkZ dh dqN ?kVuk,¡ ns[kh xbZ gSaA tc ekpZ vkSj fnlcaj ds nks eghuksa esa pH dk eku 5-0 ls uhps fxj tkrk gS rc vEyh; o"kkZ dh leL;k cgqr vf/kd fodV gksrh gSA ekulwu iwoZ _rq ds nkSjku mPp lapkydrk ekuksa dk dkj.k bl vof/k esa okrkoj.k esa /kwy d.kksa dh vf/kd lkanzrk dks ekuk tk ldrk gSA ?kVdksa vkSj o"kkZ ds chp  ds :Ik esa foijhr laca/k ik;k x;k gSA In this paper rainwater chemistry of Nagpur for the period 1981-1996, has been studied. The analysis reveals that at Nagpur rain water there is less marine influence on the concentrations of Na+ and Cl-. Pre-monsoon months, as well as the season as a whole, record higher NO3- concentration which could be attributed to frequent thunderstorm activities in this season. During monsoon months, concentration of all the constituents of rainwater, except K+, goes on decreasing till August. However, in September increase in concentration is observed for all the constituents. Deposition values of Cl- and Na+ are found to be quite low in comparison to that at coastal stations.   SO4-2 deposition value is comparable to the values reported in some parts of USSR. Study of ratios between various constituents and a comparison with sea water ratios reveals that rainwater at Nagpur gets enriched in terms of Na+ from other sources besides sea water. pH values exhibited large variation.  In monsoon, June onwards pH goes on decreasing and lowest value is obtained in September.  This could be attributed to the preferential removal of basic cations by rainwater.  In the peak summer of April and May higher values of pH could be attributed to the abundant prevalence of dust particles in the atmosphere chiefly consisting of basic cations. pH of individual months of monsoon season reveals that in June and July rainfall is predominantly basic in nature while in August and September some instances of acid rain has been observed at Nagpur. Acid rain problem seems to be more acute in the month of March and December when pH in these two months falls below 5.0. High conductivity values during pre-monsoon season could be attributed to higher dust concentrations in the atmosphere during this period. An inverse relationship of form Y = AR-B has been found between the constituents and rainfall.


2021 ◽  
Vol 37 (4) ◽  
pp. 263-270
Author(s):  
Michael B. Boehmler

ABSTRACT In an effort to reduce Aedes taeniorhynchus numbers in the northernmost community of Key Largo, FL (known as Ocean Reef), during the peak summer months, Florida Keys Mosquito Control District (FKMCD) has utilized a bifenthrin-based barrier application (Wisdom TC Flowable®) for several years. The FKMCD conducted a study comparing whether 2 aftermarket wetting/sticking adjuvants could improve the efficacy of the barrier treatments used to control Ae. taeniorhynchus. Maximum label rate was used for 3 separate solutions: Wisdom TC Flowable (1 fl oz/gal [7.81 ml/liter] water) with no additives (Wisdom), Wisdom with Lesco Spreader-Sticker® (0.08 fl oz [2.37 ml]), and Wisdom with Xtended Performance® (2.56 fl oz [75.71 ml]). All solutions were applied to 100-ft (approximately 3 m) sections of tree-lined roadways in Key Largo, FL, using a SR 420® Mistblower backpack sprayer (Stihl Corp.). Leaves were collected from each application area for 8 consecutive weeks. Leaves were used to perform leaf bioassays against local populations of Ae. taeniorhynchus adults, and mortality was recorded at 1, 4, and 24 h postexposure. This process was replicated 3 times. Treatments had variable mortality rates at 1, 4, and 24 h postexposure across 7 wk following application. Mortality rates for all mixtures decreased for all exposure times throughout the study. Overall, the Lesco Spreader-Sticker solution was the only combination with a positive significant difference in adult mortality after 24 h.


2021 ◽  
Vol 13 (7) ◽  
pp. 3607-3689
Author(s):  
Kyle B. Delwiche ◽  
Sara Helen Knox ◽  
Avni Malhotra ◽  
Etienne Fluet-Chouinard ◽  
Gavin McNicol ◽  
...  

Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions due to quasi-continuous and high-temporal-resolution CH4 flux measurements, coincident carbon dioxide, water, and energy flux measurements, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we (1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first open-source global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4-community-product/, last access: 7 April 2021). FLUXNET-CH4 includes half-hourly and daily gap-filled and non-gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we (2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands which are a substantial source of total atmospheric CH4 emissions; and (3) we provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20∘ S to 20∘ N) the spring onset of elevated CH4 emissions starts 3 d earlier, and the CH4 emission season lasts 4 d longer, for each degree Celsius increase in mean annual air temperature. On average, the spring onset of increasing CH4 emissions lags behind soil warming by 1 month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). FLUXNET-CH4 is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle, and future additions of sites in tropical ecosystems and site years of data collection will provide added value to this database. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4672601 (Delwiche et al., 2021). Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/ (last access: 7 April 2021), and a complete list of the 79 individual site data DOIs is provided in Table 2 of this paper.


2021 ◽  
Vol 143 (5) ◽  
Author(s):  
Saboor Shaik ◽  
Manvendra Bhardwaj ◽  
Somya Agarwal ◽  
Raja Sekhar Yendaluru ◽  
Md. Hasanuzzaman ◽  
...  

Abstract The energy gain of domestic solar water heating systems is determined by solar to thermal energy conversion and glazing optical efficiency. For this study, solar transmission properties of different transparent glazing materials such as acrylic, low-iron, medium-iron, and high-iron glasses were measured. The collector thermal efficiency under natural convection mode was compared for different transparent covers determined by numerical simulation using the Hottel–Whillier–Bliss equation. The low-iron glass (LiG-12 mm) has 16.3% and 20% higher thermal efficiency than medium- (MiG-12 mm) and high-iron glasses (HiG-12 mm), respectively, for a peak summer day. The effect of glass thickness on thermal performance is noteworthy in glasses than in acrylic glass sheets. Low-iron content glass with 6 mm thickness has the highest thermal and optical efficiency of 63.2% and 75.65%, respectively, for the collector optimum tilt for Vellore city in Tamil Nadu, India. The results are useful in the selection of glass covers for energy-efficient solar flat plate collectors.


Author(s):  
C. Valli ◽  
P. Anuradha

Background: Feed additives are being used to counteract production losses in lactating cattle arising due to heat stress. In this context a study was conducted to study the impact of supplementing ADDONTM - Rumen support on in vitro rumen fermentation, production and health of lactating cattle during summer. Methods: To a total mixed ration (TMR), ADDONTM Rumen support was supplemented at three levels viz., No ADDONTM -RS, ADDONTM -RS at 0.07g/100g TMR and ADDONTM -RS at 0.15 g/100g TMR and subjected to in vitro rumen fermentation studies using the Rumen Simulation Technique. Eighteen lactating dairy cattle at early lactation, were randomly divided into three treatment groups: T1 - No ADDONTM -RS, T2 - ADDONTM -RS at 7 g/animal/day and T3 - ADDONTM -RS at 15 g/animal/day and their body condition score, body weight, milk yield, fat and SNF content were studied during peak summer. Conclusion: Supplementation of ADDONTM -RS @ 0.15g/100g of TMR helped in regulating in vitro ruminal pH, significantly (p less than 0.05) reduced total gas and carbon dioxide production at 12 hours of incubation and methane production at 12 and 36 hours of incubation. ADDONTM -RS supplementation at both levels (0.07g/100g TMR and 0.15g/100g TMR) resulted in significant (p less than 0.05) increase in in vitro microbial biomass production at 12 hours of incubation. In spite of peak summer, ADDONTM -RS supplementation in lactating dairy cattle prevented changes in body condition score, weight loss and resulted in significantly (p less than 0.05) higher milk yield without compromising on milk fat and SNF content and decreased somatic cell count in milk and improved manure quality. 


2021 ◽  
Author(s):  
Kyle B. Delwiche ◽  
Sara Helen Knox ◽  
Avni Malhotra ◽  
Etienne Fluet-Chouinard ◽  
Gavin McNicol ◽  
...  

Abstract. Methane (CH4) emissions from natural landscapes constitute roughly half of global CH4 contributions to the atmosphere, yet large uncertainties remain in the absolute magnitude and the seasonality of emission quantities and drivers. Eddy covariance (EC) measurements of CH4 flux are ideal for constraining ecosystem-scale CH4 emissions, including their seasonality, due to quasi-continuous and high temporal resolution of flux measurements, coincident measurements of carbon, water, and energy fluxes, lack of ecosystem disturbance, and increased availability of datasets over the last decade. Here, we 1) describe the newly published dataset, FLUXNET-CH4 Version 1.0, the first global dataset of CH4 EC measurements (available at https://fluxnet.org/data/fluxnet-ch4- community-product/). FLUXNET-CH4 includes half-hourly and daily gap-filled and non gap-filled aggregated CH4 fluxes and meteorological data from 79 sites globally: 42 freshwater wetlands, 6 brackish and saline wetlands, 7 formerly drained ecosystems, 7 rice paddy sites, 2 lakes, and 15 uplands. Then, we 2) evaluate FLUXNET-CH4 representativeness for freshwater wetland coverage globally, because the majority of sites in FLUXNET-CH4 Version 1.0 are freshwater wetlands and because freshwater wetlands are a substantial source of total atmospheric CH4 emissions; and 3) provide the first global estimates of the seasonal variability and seasonality predictors of freshwater wetland CH4 fluxes. Our representativeness analysis suggests that the freshwater wetland sites in the dataset cover global wetland bioclimatic attributes (encompassing energy, moisture, and vegetation-related parameters) in arctic, boreal, and temperate regions, but only sparsely cover humid tropical regions. Seasonality metrics of wetland CH4 emissions vary considerably across latitudinal bands. In freshwater wetlands (except those between 20° S to 20° N) the spring onset of elevated CH4 emissions starts three days earlier, and the CH4 emission season lasts 4 days longer, for each degree C increase in mean annual air temperature. On average, the onset of increasing CH4 emissions lags soil warming by one month, with very few sites experiencing increased CH4 emissions prior to the onset of soil warming. In contrast, roughly half of these sites experience the spring onset of rising CH4 emissions prior to the spring increase in gross primary productivity (GPP). The timing of peak summer CH4 emissions does not correlate with the timing for either peak summer temperature or peak GPP. Our results provide seasonality parameters for CH4 modeling, and highlight seasonality metrics that cannot be predicted by temperature or GPP (i.e., seasonality of CH4 peak). The FLUXNET-CH4 dataset provides an open-access resource for CH4 flux synthesis, has a range of applications, and is unique in that it includes coupled measurements of important CH4 drivers such as GPP and temperature. Although FLUXNET-CH4 could certainly be improved by adding more sites in tropical ecosystems and by increasing the number of site-years at existing sites, it is a powerful new resource for diagnosing and understanding the role of terrestrial ecosystems and climate drivers in the global CH4 cycle. All seasonality parameters are available at https://doi.org/10.5281/zenodo.4408468. Additionally, raw FLUXNET-CH4 data used to extract seasonality parameters can be downloaded from https://fluxnet.org/data/fluxnet-ch4-community-product/, and a complete list of the 79 individual site data DOIs is provided in Table 2 in the Data Availability section of this document.


Author(s):  
Qasim Bukhari ◽  
Joseph M. Massaro ◽  
Ralph B. D’Agostino ◽  
Sheraz Khan

The novel coronavirus (SARS-CoV-2) has spread globally and has been declared a pandemic by the World Health Organization. While influenza virus shows seasonality, it is unknown if COVID-19 has any weather-related affect. In this work, we analyze the patterns in local weather of all the regions affected by COVID-19 globally. Our results indicate that approximately 85% of the COVID-19 reported cases until 1 May 2020, making approximately 3 million reported cases (out of approximately 29 million tests performed) have occurred in regions with temperature between 3 and 17 °C and absolute humidity between 1 and 9 g/m3. Similarly, hot and humid regions outside these ranges have only reported around 15% or approximately 0.5 million cases (out of approximately 7 million tests performed). This suggests that weather might be playing a role in COVID-19 spread across the world. However, this role could be limited in US and European cities (above 45 N), as mean temperature and absolute humidity levels do not reach these ranges even during the peak summer months. For hot and humid countries, most of them have already been experiencing temperatures >35 °C and absolute humidity >9 g/m3 since the beginning of March, and therefore the effect of weather, however little it is, has already been accounted for in the COVID-19 spread in those regions, and they must take strict social distancing measures to stop the further spread of COVID-19. Our analysis showed that the effect of weather may have only resulted in comparatively slower spread of COVID-19, but not halted it. We found that cases in warm and humid countries have consistently increased, accounting for approximately 500,000 cases in regions with absolute humidity >9 g/m3, therefore effective public health interventions must be implemented to stop the spread of COVID-19. This also means that ‘summer’ would not alone stop the spread of COVID-19 in any part of the world.


2020 ◽  
Author(s):  
Emma S. Choi ◽  
Erik T. Saberski ◽  
Tom Lorimer ◽  
Cameron Smith ◽  
Unduwap Kandage-don ◽  
...  

AbstractWe find a startling correlation (Pearson ρ > 0.97) between a single event in daily sea surface temperatures each spring, and peak fish egg abundance measurements the following summer, in 7 years of approximately weekly fish egg abundance data collected at Scripps Pier in La Jolla California. Even more surprising is that this event-based result persists despite the large and variable number of fish species involved (up to 46), and the large and variable time interval between trigger and response (up to ~3 months). To mitigate against potential over-fitting, we make a true out-of-sample prediction for the peak summer egg abundance that will be observed at Scripps Pier this year.


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