The environmental cost of broiler production and carbon sequestration potential of eucalyptus plantations around farms in Mato Grosso do Sul, Brazil.

The present study aimed to evaluate the environmental cost of the production process of broilers from the approach of emergy accounting and carbon sequestration potential for broiler farms. The study assessed a standard farm of the conventional system containing ten houses in 19 ha. We evaluated the following indices solar transformity (Tr), renewability (%R), emergy yield ratio (EYR), emergy investment ratio (EIR), environmental loading ratio (ELR), emergy sustainability index (ESI), and emergy exchange ratio (EER) and carbon sequestration potential of eucalyptus plantation. The total emergy input was 2.79E-06 seJ ha-1 y-1 for the broiler growth process. The highest investment in the production process was related to materials, which came from feeding and electricity. The renewability index indicated the low sustainability of the system with increased consumption of economical materials and equipment, with a low proportion of the emergy use of renewable resources. High investment in broilers production in the conventional system generates an environmental loading ratio that indicates high environmental degradation. Planting trees in the surrounding areas of the farm facilities can minimize the externalities of the production system with the plantation carbon sequestration potential.

A Heuristic and Data Mining Model for Predicting Broiler House Environment Suitability.

The proper combination of environment and flock-based variables plays a critical role in broiler production. However, the housing environment control is mainly focused on temperature monitoring during the broiler growth process. The present study developed a novel predictive model to predict the broiler (Gallus gallus domesticus) rearing conditions' suitability using a data-mining process centered on flock-based and environmental variables. Data were recorded inside four commercial controlled environment broiler houses. The data analysis was conducted in three steps. First, we performed an exploratory and descriptive analysis of the environmental data. In the second step, we labeled the target variable that led to a specific broiler-rearing scenario depending on the age of the birds, the environmental dry-bulb temperature and relative humidity, the ammonia concentration, and the ventilation rate. The output (final rearing condition) was discretized into four categories ('Excellent', 'Good', 'Moderate', and 'Inappropriate'). In the third step, we used the dataset to develop tree models using the data-mining process. The random-tree model only presented accuracy for predicting the 'Excellent' and 'Moderate' rearing conditions. The decision-tree model had high accuracy and indicated that broiler age, relative humidity, and ammonia concentration play a critical role in proper rearing conditions. Using a large amount of data allows the data-mining approach to building up 'if-then' rules that indicate suitable environmental control decision-making by broiler farmers.

Estimating the urban environmental impact of gasoline-ethanol blended fuels in a passenger vehicle engine.

A large portion of urban emissions in developing countries come from old gasoline vehicles driven in metropolitan areas. The present study aimed to develop models to estimate the environmental impact of different contents of gasoline and ethanol mixtures (pure gasoline; 25, 50, 75% ethanol blended to gasoline; and 100% ethanol) in a flex-fuel engine. We tested the blended fuel using three different speeds and recorded the GHG emissions and engine output data. The data mining approach was used to develop environmental impact predictive models. The ethanol content in gasoline; the engine rotational speed 900, 2000, and 3000 rpm; and λ were used as attributes. The classification target was the environmental impact concerning the CO2 emission ("low," "average," and "high"). We employed the Random forest algorithm to develop predictive models. The mean values of CO2 concentrations for all studied fuel content were above 2.47% of the volume. The trees' models (accuracy 73%, κ =0.61) showed three alternatives for predicting the environmental impact based on the ethanol blend, the engine rotation, λ, and the air-fuel ratio. Such models might help policymakers develop educational campaigns to reduce short- and medium-term urban commuter traffic pollution in countries that lack suitable urban transportation.