Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

A hybrid commodity price-forecasting model applied to the sugar-alcohol sector

Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.

Forecasting fuel ethanol consumption in Brazil by time series models: 2006-2012

This article analysed scenarios for Brazilian consumption of ethanol for the period 2006 to 2012. The results show that if the country`s GDP sustains a 4.6% a year growth, domestic consumption of fuel ethanol could increase to 25.16 billion liters in this period, which is a volume relatively close to the forecasted gasoline consumption of 31 billion liters. At a lower GDP growth of 1.22% a year, gasoline consumption would be reduced and domestic ethanol consumption in Brazil would be no higher than 18.32 billion liters. Contrary to the current situation, forecasts indicated that hydrated ethanol consumption could become much higher than anhydrous consumption in Brazil. The former is being consumed in cars moved exclusively by ethanol and flex-fuel cars, successfully introduced in the country at 2003. Flex cars allow Brazilian consumers to choose between gasoline and hydrated ethanol and immediately switch to whichever fuel presents the most favourable relative price.

The association between air pollution and blood pressure in traffic controllers in Santo Andre, Sao Paulo, Brazil

Background: Urban air pollutants are associated with cardiovascular events. Traffic controllers are at high risk for pollution exposure during outdoor work shifts. Objective: The purpose of this study was to evaluate the relationship between air pollution and systemic blood pressure in traffic controllers during their work shifts. Methods: This cross-sectional study enrolled 19 male traffic controllers from Santo Andre city (Sao Paulo, Brazil) who were 30-60 years old and exposed to ambient air during outdoor work shifts. Systolic and diastolic blood pressure readings were measured every 15 min by an Ambulatory Arterial Blood Pressure Monitoring device. Hourly measurements (lags of 0-5 h) and the moving averages (2-5 h) of particulate matter (PM(10)), ozone (O(3)) ambient concentrations and the acquired daily minimum temperature and humidity means from the Sao Paulo State Environmental Agency were correlated with both systolic and diastolic blood pressures. Statistical methods included descriptive analysis and linear mixed effect models adjusted for temperature, humidity, work periods and time of day. Results: Interquartile increases of PM(10) (33 mu g/m(3)) and O(3) (49 mu g/m(3)) levels were associated with increases in all arterial pressure parameters, ranging from 1.06 to 2.53 mmHg. PM(10) concentration was associated with early effects (lag 0), mainly on systolic blood pressure. However, O(3) was weakly associated most consistently with diastolic blood pressure and with late cumulative effects. Conclusions: Santo Andre traffic controllers presented higher blood pressure readings while working their outdoor shifts during periods of exposure to ambient pollutant fluctuations. However, PM(10) and O(3) induced cardiovascular effects demonstrated different time courses and end-point behaviors and probably acted through different mechanisms. (C) 2011 Elsevier Inc. All rights reserved.

Forecasting regional crop production using SOI phases: an example for the Australian peanut industry

Using peanuts as an example, a generic methodology is presented to forward-estimate regional crop production and associated climatic risks based on phases of the Southern Oscillation Index (SOI). Yield fluctuations caused by a highly variable rainfall environment are of concern to peanut processing and marketing bodies. The industry could profitably use forecasts of likely production to adjust their operations strategically. Significant, physically based lag-relationships exist between an index of ocean/atmosphere El Nino/Southern Oscillation phenomenon and future rainfall in Australia and elsewhere. Combining knowledge of SOI phases in November and December with output from a dynamic simulation model allows the derivation of yield probability distributions based on historic rainfall data. This information is available shortly after planting a crop and at least 3-5 months prior to harvest. The study shows that in years when the November-December SOI phase is positive there is an 80% chance of exceeding average district yields. Conversely, in years when the November-December SOI phase is either negative or rapidly falling there is only a 5% chance of exceeding average district yields, but a 95% chance of below average yields. This information allows the industry to adjust strategically for the expected volume of production. The study shows that simulation models can enhance SOI signals contained in rainfall distributions by discriminating between useful and damaging rainfall events. The methodology can be applied to other industries and regions.

Alcohol-related traffic accidents with fatal outcomes in the city of Sao Paulo

Aims: The aims of the present study were to characterize fatal traffic accident victims in a major urban center in Brazil and their association with alcohol consumption. Methods: Cross-sectional study of 907 fatal traffic accident victims in Sao Paulo, in 2005. Results: Adult males between the ages of 25 and 54 represented the majority of cases with positive blood alcohol concentrations (BAC). Overall, males had a higher proportional BAC and mean BAC than females. Pedestrians, particularly those with no detectable BAC, were typically older than other victims. Most accidents (total and BAC-positive) happened on weekends between midnight and 6 a.m. Considering all victims, 39.4% were positive (BAC over 0.1 g/l). When only drivers (automobile, motorcycle and bicycle) were evaluated. 42.3% had BAC over the legal limit (0.6 g/l). Conclusions: Alcohol is associated with nearly half of all traffic accident deaths in the city of Sao Paulo. especially for days and times associated with parties and bars (weekends between 12 a.m. and 6 a.m.). (C) 2010 Elsevier Ltd. All rights reserved.

Chronic exposure to fine particulate matter emitted by traffic affects reproductive and fetal outcomes in mice

Air pollution is an important environmental health risk factor that can result in many different gestational and reproductive negative outcomes. In this study, we have investigated the effects of two different times of exposure (before conception and during pregnancy) to urban ambient particulate matter on reproductive and pregnancy outcomes in mice. Using exposure chambers receiving filtered (F) and non-filtered (NF) air, we observed that exposed females exhibited changes in the length of estrus cycle and extended estrus and, therefore, a reduction in the number of cycles during the studied period (F2.6 +/- 0.22 and NF 1.2 +/- 0.29, p = 0.03). The mean number of antral follicles declined by 36% (p = 0.04) in NF mice (75 +/- 35.2) compared to F mice (118.6 +/- 18.4). our results further indicate a significant increase in time necessary for mating and decreased fertility and pregnancy indices (p = 0.003) in NF couples. Mean post-implantation loss rates were increased by 70% (p <= 0.005) in the NF2 group (exposed before and during pregnancy to NF air) compared to the F1 group (exposed before and during pregnancy to F air) and were influenced by both pre-gestational (p < 0.004) and gestational (p < 0.01) period exposure. Fetal weight was significantly higher in the F1 group when compared with the other groups (p < 0.001), at a 20% higher weight in the F1 group (0.86 +/- 0.18 g) than in the NF2 group (0.68 +/- 0.10g). Furthermore, fetal weight was influenced by both pre-gestational and gestational period exposure, and a significant interaction between these two factors was found (p < 0.001). This study demonstrated that exposure to ambient levels of urban traffic-generated particulate matter negatively affects different functions and stages of the reproductive process. Our results also reinforce the idea that maternal exposure to air pollution is linked to negative pregnancy outcomes, even if the exposure occurs only before conception. (C) 2009 Elsevier Inc. All rights reserved.

Comparative respiratory toxicity of particles produced by traffic and sugar cane burning

The impact of particle emissions by biomass burning is increasing throughout the world. We explored the toxicity of particulate matter produced by sugar cane burning and compared these effects with equivalent mass of traffic-derived particles. For this purpose, BALB/c mice received a single intranasal instillation of either distilled water (C) or total suspended particles (15 mu g) from an urban area (SP group) or biomass burning-derived particles (Bio group). Lung mechanical parameters (total, resistive and viscoelastic pressures, static elastance, and elastic component of viscoelasticity) and histology were analyzed 24h after instillation. Trace elements and polycyclic aromatic hydrocarbons (PAHs) metabolites of the two sources of particles were determined. All mechanical parameters increased similarly in both pollution groups compared with control, except airway resistive pressure, which increased only in Bio. Both exposed groups showed significantly higher fraction area of alveolar collapse, and influx of polymorphonuclear cells in lung parenchyma than C. The composition analysis of total suspended particles showed higher concentrations of PAHs and lower concentration of metals in traffic than in biomass burning-derived particles. In conclusion, we demonstrated that a single low dose of ambient particles, produced by traffic and sugar cane burning, induced significant alterations in pulmonary mechanics and lung histology in mice. Parenchymal changes were similar after exposure to both particle sources, whereas airway mechanics was more affected by biomass-derived particles. Our results indicate that biomass particles were at least as toxic as those produced by traffic. (C) 2008 Elsevier Inc. All rights reserved.

The effects of chronic exposure to traffic derived air pollution on the ocular surface

Objectives: The purpose of this study was to explore the clinical relevance of chronic exposure to ambient levels of traffic derived air pollution on the ocular surface. Methods: A panel study involving 55 volunteers was carried out in Sao Paulo, Brazil. We measured the mean individual levels of nitrogen dioxide (NO(2)) exposure for 7 days. All subjects answered the Ocular Symptom Disease Index (OSDI) and a symptoms inventory. Subsequently, subjects underwent Schirmer I test, biomicroscopy, vital staining and tear breakup time (TOUT) assessment. Subject`s mean daily exposure to NO(2) was categorized in quartiles. Statistical analysis was performed using one-way ANOVA, Tukey HSD and Chi-Square tests. Results: A dose-response pattern was detected between OSDI scores and NO(2) quartiles (p < 0.05). There was a significant association between NO(2) quartiles and reported ocular irritation (X(2) = 9.2, p < 0.05) and a significant negative association between TBUT and NO(2) exposure (p < 0.05, R = -0.316. Spearman`s correlation). There was a significant increase in the frequency of meibomitis in subjects exposed to higher levels of NO(2) (p < 0.05). Conclusions: Subjects exposed to higher levels of traffic derived air pollution reported more ocular discomfort symptoms and presented greater tear film instability, suggesting that the ocular discomfort symptoms and tear breakup time could be used as convenient bioindicators of the adverse health effects of traffic derived air pollution exposure. (C) 2010 Elsevier Inc. All rights reserved.

Effects of ambient levels of air pollution generated by traffic on birth and placental weights in mice

Objective: To examine whether there is an association between fetal and/or placental weight and exposure to ambient levels of air pollution in mice. Design: Chronic experiments on mice that were exposed to polluted vs. clean air. Setting: Environmental exposure to atmospheric pollution. Animal(S): Female Swiss mice (n = 70) were maintained at different stages of gestation in an exposure chamber located at an intersection with heavy traffic in a major city in Brazil. Control mice were maintained in a similar chamber, located adjacent to the exposure chamber but equipped with filters for particles and reactive gases. Intervention(s): Animals were divided into six groups as follows: no exposure, exposure to a polluted chamber throughout gestation, exposure to a polluted chamber during the 1st week of pregnancy, exposure to a polluted chamber during the 2nd and 3rd weeks, exposure to a polluted chamber during the 1st and 2nd week, and exposure to a polluted chamber during the 3rd week. Main Outcome Measure(S): At the end of the gestational period, the determination of fetal and placental weight was performed after cesarean section. Result(s): Exposure to air pollution during the 1st week of pregnancy promoted a significant reduction in fetal weight. Mice exposed to polluted air, in any phase of gestation, presented with lower placental weight in comparison to mice maintained in clean chambers. Conclusion(s): Exposure to ambient levels of traffic pollution at early phases of gestation is a determinant for decreased final fetal weight. Placental weight is reduced with exposure to air pollution at any phase of gestation. (Fertil Steril (R) 2008;90:1921-4. (C)2008 by American Society for Reproductive Medicine.)

Impact of a program for the prevention of traffic accidents in a Southern Brazilian city: a model for implementation in a developing country

Background: Traffic accidents constitute the main cause of death in the first decades of life. Traumatic brain injury is the event most responsible for the severity of these accidents. The SBN started an educational program for the prevention of traffic accidents, adapted from the American model ""Think First"" to the Brazilian environment, since 1995, with special effort devoted to the prevention of TBI by using seat belts and motorcycle helmets. The objective of the present study was to set up a traffic accident prevention program based on the adapted Think First and to evaluate its impact by comparing epidemiological variables before and after the beginning of the program. Methods: The program was executed in Maringa city, from September 2004 to August 2005, with educational actions targeting the entire population, especially teenagers and young adults. The program was implemented by building a network of information facilitators and multipliers inside the organized civil society, with widespread population dissemination. To measure the impact of the program, a specific software was developed for the storage and processing of the epidemiological variables. Results: The results showed a reduction of trauma severity due to traffic accidents after the execution of the program, mainly TBI. Conclusions: The adapted Think First was systematically implemented and its impact measured for the first time in Brazil, revealing the usefulness of the program for reducing trauma and TBI severity in traffic accidents through public education and representing a standardized model of implementation in a developing country. (C) 2009 Elsevier Inc. All rights reserved.