A variability of soil elements has been studied by environmental modeling techniques using geostatistics. This can be an essential tool for the development of projects related to interpolation methods and statistical methodologies to validate the correlation between soil characteristics. In this perspective, this work aims to model the natural chem...
We propose a robust and efficient method for multiview triangulation and uncertainty estimation. Our contribution is threefold: First, we propose an outlier rejection scheme using two-view RANSAC with the midpoint method. By prescreening the two-view samples prior to triangulation, we achieve the state-of-the-art efficiency. Second, we compare diff...
The growth of the world population has led to the expansion of agricultural areas to produce food that meets world demand, making it necessary to increase productivity and maintain environmental sustainability in these areas. Seeking sustainable food production, the agricultural use of soil must be assessed in view of optimal use or land as natural resource, as well as minimize the effects of global warming related to land use and land cover (LULC). We hypothesize that different LULC affects Amazonian soil attributes. In this study, the effect of different LULC in the southern Brazilian Amazon, namely, native forest, pasture, and rice and soybean crops, on the spatial variability of soil fertility and texture was assessed, seeking to obtain information that will guide farmers in the near future to better exploit their areas and contribute to a more sustainable agriculture. Descriptive statistical analysis was performed for the pH, H + Al, Al, Ca, Mg, P, K, Cu, Fe, Mn, Zn, V, m, organic matter, clay, silt, and sand values from soil samples under different LULC. To verify the data normality, the Shapiro–Wilk test at 5% significance was performed. Outlier analysis using boxplot graphics, principal component analysis (PCA), and cluster analysis was performed. Data were submitted to geostatistical analysis to verify the spatial dependence degree of the variables through semivariograms for interpolated kriging maps. Except for silt, all variables were well represented in the factor map. PCA revealed that the data variability can be explained mainly by pH, V, Ca, K, and Zn values, which are inversely proportional to m, P, and sand. Through geostatistical analysis, spatial dependence ranging from moderate to strong was observed, generating reliability in the prediction of most attributes in pasture, rice, and soybean areas. Yet, a spatial dependence ranging from moderate to strong was found, generating reliability in the prediction of most attributes in pasture, rice, and soybean areas. Our findings reveal a lower fertility and higher acidity in forest areas, whereas crop areas presented the opposite result.
Municipal Solid Waste Management with the material disposal in landfills is a widely adopted practice in Brazil. The environmental performance quantification in MSWM supports the proposition of optimized practices. The Life Cycle Assessment was applied to evaluate 1 ton of material in the Municipal Solid Waste Management of Feira de Santana, state of Bahia, Brazil. The system boundary of the Municipal Solid Waste Management in this study included the material managed in collection, transportation, treatment, disposal and leachate handling stages. The material disposal in sanitary landfill was evaluated in the base scenario of Municipal Solid Waste Management and the resource recovery options for material (recycling and composting) and energy (sanitary landfill and anaerobic digestion with biogas collection) in the proposed scenarios of Municipal Solid Waste Management. The foreground inventory used representative data for the evaluated scenarios, while the background inventory used the ecoinvent™ database in the Simapro® software with the Cumulative Energy Demand and Intergovernmental Panel on Climate Change 2013 with 100 years global warming potential methods. Cumulative Energy Demand was 215 MJ·t⁻¹ and Greenhouse Gas emissions were 449 kg CO2eq·t⁻¹ in the base scenario. The largest contribution in the base scenario was the collection and transportation stage in Cumulative Energy Demand and the sanitary landfill in Greenhouse Gas. The proposed scenarios with resource recovery showed a potential to reduce the Cumulative Energy Demand and Greenhouse Gas emissions in Municipal Solid Waste Management, along with supporting the transition to a circular economy. Keywords: life cycle assessment; zero waste; resource recovery; reverse logistics