956 resultados para air temperature and relative humidity


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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Viruses are the major cause of lower respiratory tract infections in childhood and the main viruses involved are Human Respiratory Syncytial Virus (HRSV), Human Metapneumovirus (HMPV), Influenzavirus A and B (FLUA and FLUB), Human Parainfluenza Virus 1, 2 and 3 (HPIV1, 2 and 3) and Human Rhinovirus (HRV). The purposes of this study were to detect respiratory viruses in hospitalized children younger than six years and identify the influence of temperature and relative air humidity on the detected viruses. Samples of nasopharyngeal washes were collected from hospitalized children between May/2004 and September/2005. Methods of viral detection were RT-PCR, PCR and HRV amplicons were confirmed by hybridization. Results showed 54% (148/272) of viral positivity. HRSV was detected in 29% (79/272) of the samples; HRV in 23.1% (63/272); HPIV3 in 5.1% (14/272); HMPV in 3.3% (9/272); HPIV1 in 2.9% (8/272); FLUB in 1.4% (4/272), FLUA in 1.1% (3/272), and HPIV2 in 0.3% (1/272). The highest detection rates occurred mainly in the spring 2004 and in the autumn 2005. It was observed that viral respiratory infections tend to increase as the relative air humidity decreases, showing significant association with monthly averages of minimal temperature and minimal relative air humidity. In conclusion, viral respiratory infections vary according to temperature and relative air humidity and viral respiratory infections present major incidences it coldest and driest periods.

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Viruses are the major cause of lower respiratory tract infections in childhood and the main viruses involved are Human Respiratory Syncytial Virus (HRSV), Human Metapneumovirus (HMPV), Influenzavirus A and B (FLUA and FLUB), Human Parainfluenza Virus 1, 2 and 3 (HPIV1, 2 and 3) and Human Rhinovirus (HRV). The purposes of this study were to detect respiratory viruses in hospitalized children younger than six years and identify the influence of temperature and relative air humidity on the detected viruses. Samples of nasopharyngeal washes were collected from hospitalized children between May/2004 and September/2005. Methods of viral detection were RT-PCR, PCR and HRV amplicons were confirmed by hybridization. Results showed 54% (148/272) of viral positivity. HRSV was detected in 29% (79/272) of the samples; HRV in 23.1% (63/272); HPIV3 in 5.1% (14/272); HMPV in 3.3% (9/272); HPIV1 in 2.9% (8/272); FLUB in 1.4% (4/272), FLUA in 1.1% (3/272), and HPIV2 in 0.3% (1/272). The highest detection rates occurred mainly in the spring 2004 and in the autumn 2005. It was observed that viral respiratory infections tend to increase as the relative air humidity decreases, showing significant association with monthly averages of minimal temperature and minimal relative air humidity. In conclusion, viral respiratory infections vary according to temperature and relative air humidity and viral respiratory infections present major incidences it coldest and driest periods.

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The health impacts of exposure to ambient temperature have been drawing increasing attention from the environmental health research community, government, society, industries, and the public. Case-crossover and time series models are most commonly used to examine the effects of ambient temperature on mortality. However, some key methodological issues remain to be addressed. For example, few studies have used spatiotemporal models to assess the effects of spatial temperatures on mortality. Few studies have used a case-crossover design to examine the delayed (distributed lag) and non-linear relationship between temperature and mortality. Also, little evidence is available on the effects of temperature changes on mortality, and on differences in heat-related mortality over time. This thesis aimed to address the following research questions: 1. How to combine case-crossover design and distributed lag non-linear models? 2. Is there any significant difference in effect estimates between time series and spatiotemporal models? 3. How to assess the effects of temperature changes between neighbouring days on mortality? 4. Is there any change in temperature effects on mortality over time? To combine the case-crossover design and distributed lag non-linear model, datasets including deaths, and weather conditions (minimum temperature, mean temperature, maximum temperature, and relative humidity), and air pollution were acquired from Tianjin China, for the years 2005 to 2007. I demonstrated how to combine the case-crossover design with a distributed lag non-linear model. This allows the case-crossover design to estimate the non-linear and delayed effects of temperature whilst controlling for seasonality. There was consistent U-shaped relationship between temperature and mortality. Cold effects were delayed by 3 days, and persisted for 10 days. Hot effects were acute and lasted for three days, and were followed by mortality displacement for non-accidental, cardiopulmonary, and cardiovascular deaths. Mean temperature was a better predictor of mortality (based on model fit) than maximum or minimum temperature. It is still unclear whether spatiotemporal models using spatial temperature exposure produce better estimates of mortality risk compared with time series models that use a single site’s temperature or averaged temperature from a network of sites. Daily mortality data were obtained from 163 locations across Brisbane city, Australia from 2000 to 2004. Ordinary kriging was used to interpolate spatial temperatures across the city based on 19 monitoring sites. A spatiotemporal model was used to examine the impact of spatial temperature on mortality. A time series model was used to assess the effects of single site’s temperature, and averaged temperature from 3 monitoring sites on mortality. Squared Pearson scaled residuals were used to check the model fit. The results of this study show that even though spatiotemporal models gave a better model fit than time series models, spatiotemporal and time series models gave similar effect estimates. Time series analyses using temperature recorded from a single monitoring site or average temperature of multiple sites were equally good at estimating the association between temperature and mortality as compared with a spatiotemporal model. A time series Poisson regression model was used to estimate the association between temperature change and mortality in summer in Brisbane, Australia during 1996–2004 and Los Angeles, United States during 1987–2000. Temperature change was calculated by the current day's mean temperature minus the previous day's mean. In Brisbane, a drop of more than 3 �C in temperature between days was associated with relative risks (RRs) of 1.16 (95% confidence interval (CI): 1.02, 1.31) for non-external mortality (NEM), 1.19 (95% CI: 1.00, 1.41) for NEM in females, and 1.44 (95% CI: 1.10, 1.89) for NEM aged 65.74 years. An increase of more than 3 �C was associated with RRs of 1.35 (95% CI: 1.03, 1.77) for cardiovascular mortality and 1.67 (95% CI: 1.15, 2.43) for people aged < 65 years. In Los Angeles, only a drop of more than 3 �C was significantly associated with RRs of 1.13 (95% CI: 1.05, 1.22) for total NEM, 1.25 (95% CI: 1.13, 1.39) for cardiovascular mortality, and 1.25 (95% CI: 1.14, 1.39) for people aged . 75 years. In both cities, there were joint effects of temperature change and mean temperature on NEM. A change in temperature of more than 3 �C, whether positive or negative, has an adverse impact on mortality even after controlling for mean temperature. I examined the variation in the effects of high temperatures on elderly mortality (age . 75 years) by year, city and region for 83 large US cities between 1987 and 2000. High temperature days were defined as two or more consecutive days with temperatures above the 90th percentile for each city during each warm season (May 1 to September 30). The mortality risk for high temperatures was decomposed into: a "main effect" due to high temperatures using a distributed lag non-linear function, and an "added effect" due to consecutive high temperature days. I pooled yearly effects across regions and overall effects at both regional and national levels. The effects of high temperature (both main and added effects) on elderly mortality varied greatly by year, city and region. The years with higher heat-related mortality were often followed by those with relatively lower mortality. Understanding this variability in the effects of high temperatures is important for the development of heat-warning systems. In conclusion, this thesis makes contribution in several aspects. Case-crossover design was combined with distribute lag non-linear model to assess the effects of temperature on mortality in Tianjin. This makes the case-crossover design flexibly estimate the non-linear and delayed effects of temperature. Both extreme cold and high temperatures increased the risk of mortality in Tianjin. Time series model using single site’s temperature or averaged temperature from some sites can be used to examine the effects of temperature on mortality. Temperature change (no matter significant temperature drop or great temperature increase) increases the risk of mortality. The high temperature effect on mortality is highly variable from year to year.

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BACKGROUND: The psocid Liposcelis bostrychophila Badonnel, is a widespread, significant pest of stored commodities, has developed strong resistance to phosphine, the major grain disinfestant. The aim was to develop effective fumigation protocols to control this resistant pest. RESULTS: Time to population extinction of all life stages (TPE) in days was evaluated at a series of phosphine concentrations and temperatures at two relative humidities. Regression analysis showed that temperature, concentration and relative humidity all contributed significantly to describing TPE (P < 0.001, R2 = 0.95), with temperature being the dominant variable, accounting for 74.4% of the variation. Irrespective of phosphine concentration, TPE was longer at lower temperatures and high humidity (70% RH) and shorter at higher temperatures and low humidity (55% RH). At any concentration of phosphine, a combination of higher temperature and lower humidity provides the shortest fumigation period to control resistant L. bostrychophila. For example, 19 and 11 days of fumigation are required at 15 °C and 70% RH at 0.1 and 1.0 mg L-1 of phosphine respectively, whereas only 4 and 2 days are required at 35 °C and 55% RH for the same respective concentrations. CONCLUSIONS: The developed fumigation protocols will provide industry with flexibility in application of phosphine.

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The problem with the adequacy of radial basis function neural networks to model the inside air temperature as a function of the outside air temperature and solar radiation, and the inside relative humidity in an hydroponic greenhouse is addressed.

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A real-time parameter estimator for the climate discrete-time dynamic models of a greenhouse located at the North of Portugal are presented. The experiments showed that the second order models identified for the air temperature and humidity achieve a close agreement between simulated and experimantal data.

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Objective: To assess the indoor environment of two different types of dental practices regarding VOCs, PM2.5, and ultrafine particulate concentrations and examine the relationship between specific dental activities and contaminant levels. Method: The indoor environments of two selected dental settings (private practice and community health center) will were assessed in regards to VOCs, PM 2.5, and ultrafine particulate concentrations, as well as other indoor air quality parameters (CO2, CO, temperature, and relative humidity). The sampling duration was four working days for each dental practice. Continuous monitoring and integrated sampling methods were used and number of occupants, frequency, type, and duration of dental procedures or activities recorded. Measurements were compared to indoor air quality standards and guidelines. Results: The private practice had higher CO2, CO, and most VOC concentrations than the community health center, but the community health center had higher PM2.5 and ultrafine PM concentrations. Concentrations of p-dichlorobenzene and PM2.5 exceeded some guidelines. Outdoor concentrations greatly influenced the indoor concentration. There were no significant differences in contaminant levels between the operatory and general area. Indoor concentrations during the working period were not always consistently higher than during the nonworking period. Peaks in particulate matter concentration occurred during root canal and composite procedures.^

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Indoor air quality (IAQ) parameters in 73 primary classrooms in Porto were examined for the purpose of assessing levels of volatile organic compounds (VOCs), aldehydes, particulate matter, ventilation rates and bioaerosols within and between schools, and potential sources. Levels of VOCs, aldehydes, PM2.5 , PM10 , bacteria and fungi, carbon dioxide (CO2 ), carbon monoxide, temperature and relative humidity were measured indoors and outdoors and a walkthrough survey was performed concurrently. Ventilation rates were derived from CO2 and occupancy data. Concentrations of CO2 exceeding 1000 ppm were often encountered, indicating poor ventilation. Most VOCs had low concentrations (median of individual species <5 μg/m(3) ) and were below the respective WHO guidelines. Concentrations of particulate matter and culturable bacteria were frequently higher than guidelines/reference values. The variability of VOCs, aldehydes, bioaerosol concentrations, and CO2 levels between schools exceeded the variability within schools. These findings indicate that IAQ problems may persist in classrooms where pollutant sources exist and classrooms are poorly ventilated; source control strategies (related to building location, occupant behavior, maintenance/cleaning activities) are deemed to be the most reliable for the prevention of adverse health consequences in children in schools.

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The main aim of the research project "On the Contribution of Schools to Children's Overall Indoor Air Exposure" is to study associations between adverse health effects, namely, allergy, asthma, and respiratory symptoms, and indoor air pollutants to which children are exposed to in primary schools and homes. Specifically, this investigation reports on the design of the study and methods used for data collection within the research project and discusses factors that need to be considered when designing such a study. Further, preliminary findings concerning descriptors of selected characteristics in schools and homes, the study population, and clinical examination are presented. The research project was designed in two phases. In the first phase, 20 public primary schools were selected and a detailed inspection and indoor air quality (IAQ) measurements including volatile organic compounds (VOC), aldehydes, particulate matter (PM2.5, PM10), carbon dioxide (CO2), carbon monoxide (CO), bacteria, fungi, temperature, and relative humidity were conducted. A questionnaire survey of 1600 children of ages 8-9 years was undertaken and a lung function test, exhaled nitric oxide (eNO), and tear film stability testing were performed. The questionnaire focused on children's health and on the environment in their school and homes. One thousand and ninety-nine questionnaires were returned. In the second phase, a subsample of 68 children was enrolled for further studies, including a walk-through inspection and checklist and an extensive set of IAQ measurements in their homes. The acquired data are relevant to assess children's environmental exposures and health status.

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This short paper presents a numerical method for spatial and temporal downscaling of solar global radiation and mean air temperature data from global weather forecast models and its validation. The final objective is to develop a prediction algorithm to be integrated in energy management models and forecast of energy harvesting in solar thermal systems of medium/low temperature. Initially, hourly prediction and measurement data of solar global radiation and mean air temperature were obtained, being then numerically downscaled to half-hourly prediction values for the location where measurements were taken. The differences between predictions and measurements were analyzed for more than one year of data of mean air temperature and solar global radiation on clear sky days, resulting in relative daily deviations of around -0.9±3.8% and 0.02±3.92%, respectively.

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Background: In sub-tropical and tropical Queensland, a legacy of poor housing design,minimal building regulations with few compliance measures, an absence of post-construction performance evaluation and various social and market factors has led to a high and growing penetration of, and reliance on, air conditioners to provide thermal comfort for occupants. The pervasive reliance on air conditioners has arguably impacted on building forms, changed cultural expectations of comfort and social practices for achieving comfort, and may have resulted in a loss of skills in designing and constructing high performance building envelopes. Aim: The aim of this paper is to report on initial outcomes of a project that sought to determine how the predicted building thermal performance of twenty-five houses in subtropical and tropical Queensland compared with objective performance measures and comfort performance as perceived by occupants. The purpose of the project was to shed light on the role of various supply chain agents in the realisation of thermal performance outcomes. Methodology: The case study methodology embraced a socio-technical approach incorporating building science and sociology. Building simulation was used to model thermal performance under controlled comfort assumptions and adaptive comfort conditions. Actual indoor climate conditions were measured by temperature and relative humidity sensors placed throughout each house, whilst occupants’ expectations of thermal comfort and their self-reported behaviours were gathered through semi-structured interviews and periodic comfort surveys. Thermal imaging and air infiltration tests, along with building design documents, were analysed to evaluate the influence of various supply chain agents on the actual performance outcomes. Results: The results clearly show that in the housing supply chain – from designer to constructor to occupant – there is limited understanding from each agent of their role in contributing to, or inhibiting, occupants’ comfort.

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This project was conducted at Lithgow Correctional Centre (LCC), NSW, Australia. Air quality field measurements were conducted on two occasions (23-27 May 2012, and 3-8 December 2012), just before and six months after the introduction of smoke free buildings policies (28 May 2012) at the LCC, respectively. The main aims of this project were to: (1) investigate the indoor air quality; (2) quantify the level of exposure to environmental tobacco smoke (ETS); (3) identify the main indoor particle sources; (4) distinguish between PM2.5 / particle number from ETS, as opposed to other sources; and (5) provide recommendations for improving indoor air quality and/or minimising exposure at the LCC. The measurements were conducted in Unit 5.2A, Unit 5.2B, Unit 1.1 and Unit 3.1, together with personal exposure measurements, based on the following parameters: -Indoor and outdoor particle number (PN) concentration in the size range 0.005-3 µm -Indoor and outdoor PM2.5 particle mass concentration -Indoor and outdoor VOC concentrations -Personal particle number exposure levels (in the size range 0.01-0.3 µm) -Indoor and outdoor CO and CO2 concentrations, temperature and relative humidity In order to enhance the outcomes of this project, the indoor and outdoor particle number (PN) concentrations were measured by two additional instruments (CPC 3787) which were not listed in the original proposal.

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Though increased particulate air pollution has been consistently associated with elevated mortality, evidence regarding whether diminished particulate air pollution would lead to mortality reduction is limited. Citywide air pollution mitigation program during the 2010 Asian Games in Guangzhou, China, provided such an opportunity. Daily mortality from non-accidental, cardiovascular and respiratory diseases was compared for 51 intervention days (November 1–December 21) in 2010 with the same calendar date of baseline years (2006–2009 and 2011). Relative risk (RR) and 95% confidence interval (95% CI) were estimated using a time series Poisson model, adjusting for day of week, public holidays, daily mean temperature and relative humidity. Daily PM10 (particle with aerodynamic diameter less than 10 μm) decreased from 88.64 μg/m3 during the baseline period to 80.61 μg/m3 during the Asian Games period. Other measured air pollutants and weather variables did not differ substantially. Daily mortality from non-accidental, cardiovascular and respiratory diseases decreased from 32, 11 and 6 during the baseline period to 25, 8 and 5 during the Games period, the corresponding RR for the Games period compared with the baseline period was 0.79 (95% CI: 0.73–0.86), 0.77 (95% CI: 0.66–0.89) and 0.68 (95% CI: 0.57–0.80), respectively. No significant decreases were observed in other months of 2010 in Guangzhou and intervention period in two control cities. This finding supports the efforts to reduce air pollution and improve public health through transportation restriction and industrial emission control.

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The effects of temperature and relative humidity on the rate of drying of split open fish and salted fish in a tunnel dryer have been studied at a constant air velocity. By a judicious combination of these two, the rate of drying could be considerably accelerated, 10 to 12 hours only being required for drying to moisture levels below 30% in the case of mackerel, lactarius, otolithes and kilimeen (Nemipterus japonicus)