Geochemical soil dynamics on a bimodal post-collisional intrusive complex.

The importance of environmental quality for global social and ecological development, including soil degradation, cannot be overstated. Trace elements dispersed in the environment due to anthropogenic or geogenic activities can result in ecotoxicological impacts, negatively influencing environmental quality. The reference values for soil quality concerning trace elements are primarily based on geological, geomorphological, and pedological patterns. However, intrinsic geological factors may diverge some concentration levels from established norms. Therefore, conducting comprehensive surveys of environmental quality reference values becomes imperative, incorporating geological, geomorphological, and pedological patterns. A deeper understanding of the distribution of these elements is also required. Multivariate analysis proves crucial in compartmentalizing the most relevant factors, particularly in regions marked by bimodal magmatism arising from post-collisional distensional processes, such as the Santa Angélica intrusive suite in southeast Brazil. This study collected soil samples from pastures and natural grasslands with minimal anthropogenic intervention at two depths. These samples underwent various chemical and physical analyses. Statistical techniques such as correlation analysis, principal component analysis, hierarchical clustering, and geostatistics were utilized to interpret the data. The analysis revealed a correlation between the clay fraction and trace elements, demonstrating that clustering is an effective methodology for ascertaining landscape distribution patterns of these components. When compared to quality reference values, it was observed that most soil content levels exceeded both global and local standards. This study suggests that the presence of barium (Ba) in the soil might be due to the isomorphic replacement of feldspathic minerals in acidic and intermediate rocks, whereas molybdenum (Mo) seems to be associated with soils in the domain of porphyritic allanite granite. However, additional research is warranted to determine the concentration factor of Mo in this scenario accurately.

Optimized allocation of forest restoration zones to minimize soil losses in watersheds.

Increase of water erosion is one of the main problems in watersheds all over the world and directly affects soil and water resources, causing economic and environmental losses. We proposed a combination of Genetic Algorithm and Erosion/Deposition modelling to allocate vegetation zones in order to reduce soil losses within watersheds. In this study, we have used Unit Stream Power Based Erosion Deposition (USPED) model to predict the spatial distribution of erosion and sediment deposition. Based on USPED estimates, Genetic Algorithm optimize site as well size of forest restoration zones in order to reduce soil losses. Proposed approach considered watershed entirely, in a cell-level optimization, to find the best possible arrangement of forest zones. For initial scenario, soil loss estimate was 2.045,55 ton. ha-1. year-1 and after optimization we achieved 52% reduction. Optimized forest zones formed connected and compacted patches, which enable field implementation. Methodology is also applicable to other watersheds around world.

Relation of El Niño and La Niña phenomena to precipitation, evapotranspiration and temperature in the Amazon basin.

Weather phenomena El Niño and La Niña are observed by meteorological variables, which allows you to track climate change and its possible effects in certain regions. The objective of this study was to analyze the behavior of rainfall, temperature and evapotranspiration in the Amazon river basin (Latitudes 5° N to 20° S and Longitudes 50° W to 80° W), comparing them with the occurrence of El Niño and La Niña phenomena, from January 2000 to December 2016. The values referring to the meteorological variables were obtained from the TRMM and MODIS orbital sensors. After data pre-processing, the data were separated into monthly and annual scales and per period according to the presence or absence of El Niño and La Niña phenomena. Based on the results obtained, it was observed that the studied variables were affected by modification of both phenomena. The modifications are more noticeable in the distinction between the more and less rainy periods. Among the variables studied, the evapotranspiration was severely affected in the rainiest months, the La Niña phenomenon, and the least rainy months, El Niño. Thus, it was possible to conclude that, in general, the presence of La Niña increased precipitation values in comparison to the Neutral period, but the inverse occurs in the presence of El Niño. The methodology applied in the present study was adequate for the analysis of the modifications of the meteorological variables coming from the El Niño and La Niña phenomena, being able to be adapted to other variables and regions.

Environmental risk assessment for sustainable pesticide use in coffee production.

The extensive use of pesticides in agricultural practices has been associated with human health problems and environmental contamination worldwide. Brazil is the largest consumer of pesticides in the world and Espírito Santo State stands out as the second Brazilian producer of coffee. However, there is no information about environmental impact of coffee producing at Itapemirim River Basin (IRB) region, Espírito Santo State, Brazil; hence a simple and quick method using open access softwares (AGROSCRE and ARAquá Web) to estimate surface entrainment and pesticide leaching potential was carried out. AGROSCRE evaluates the contamination risk of superficial and groundwater by Active Ingredients (AIs), using GOSS Method, GUS index and US EPA criteria, while ARAquá Web estimates AI concentrations in water resources, indicating their suitability based on water quality requirements for different uses. Regarding pesticides used in coffee plantations, there is 44.7% chance of surface water and 23.7% chance of groundwater contamination. Results showed that ametryne, cyproconazole, diuron, epoxiconazole, flutriafol, triadimenol and triazophos pose contamination risk to both surface water and groundwater in the IRB region. Of these, 10.5% of the total AIs are triazoles and fall under environmental classes II and III (Product Very/Dangerous to the Environment). The AIs ametryne, thiamethoxam, iprodione, flutriafol, triazophos, endosulfan, triadimenol, cyproconazole, diuron, pendimethalin, chlorpyrifos, copper II hydroxide, etion, epoxiconazole and paraquat dichloride, were found to be potentially toxic, presenting environmental concentrations ranging from 123.40 µg L-1 to 0.14 µg L-1, which are higher than the safety standard for potable water (0.1 µg L-1). With respect to these AIs, chlorpyrifos, ethion and triazophos showed concentrations higher than EC50 values for aquatic invertebrates and ametryne and diuron for algae. Thus, local residents and environment may be at high risk of pesticide exposure, when these AIs are used in coffee plantations next to surface water or groundwater.

Prognoses of diameter and height of trees of eucalyptus using artificial intelligence.

Models of individual trees are composed of sub-models that generally estimate competition, mortality, and growth in height and diameter of each tree. They are usually adopted when we want more detailed information to estimate forest multiproduct. In these models, estimates of growth in diameter at 1.30m above the ground (DBH) and total height (H) are obtained by regression analysis. Recently, artificial intelligence techniques (AIT) have been used with satisfactory performance in forest measurement. Therefore, the objective of this study was to evaluate the performance of two AIT, artificial neural networks and adaptive neuro-fuzzy inference system, to estimate the growth in DBH and H of eucalyptus trees. We used data of continuous forest inventories of eucalyptus, with annual measurements of DBH, H, and the dominant height of trees of 398 plots, plus two qualitative variables: genetic material and site index. It was observed that the two AIT showed accuracy in growth estimation of DBH and H. Therefore, the two techniques discussed can be used for the prognosis of DBH and H in even-aged eucalyptus stands. The techniques used could also be adapted to other areas and forest species.

A new methodology for royalties distribution of the Itaipu hydroelectric plant: The hydrographic basin as the unit of analysis.

Over the past few years, many sectors such as energy generation, industry, domestic supply, and agriculture have encountered serious environmental problems due to the lack of rainfall. Thus, the purpose of this paper is to review the current methodology of royalties distribution from Itaipu hydroelectric plant. In the proposed approach, two criteria were considered to establish the division of Itaipu royalties: (1) the relative percentage of the water flow in the generation of electricity and, (2) the relative percentage of the drop in the height of water. 62 hydroelectric plants were evaluated in this study. In 52 plants the water flow was the factor that most contributed to the generation of electricity. In 2013, 346 municipalities benefited the Itaipu royalties. With the proposed methodology, 1,327 municipalities will receive the resource, what would increase the revenue of each of these municipalities by, on average, US$ 87,436.91 per year. The methodology presented herein proposes a reduction in the environmental disparity that now exists in Brazil, through improvement to Government instruments and environmental policies. The distribution of royalties throughout the watershed can provide additional resources to support payment programs for environmental services at the state and municipality levels.

Spatial and temporal distribution of urban heat islands.

The formation of an urban heat island (UHI) is one of the most common impacts of the urbanization process. To mitigate the effects of UHI, the planning of urban forests (e.g., creation of parks, forests and afforestation streets) has been the major tool applied in this context. Thus, the aim of this study is to evaluate the spatial and temporal distribution of heat islands in Vila Velha, ES, Brazil using the mono-window algorithm. The study followed these methodological steps: 1) mapping of urban green areas through a photointerpretation screen; 2) application of the mono-window algorithm to obtain the spatial and temporal patterns of land surface temperature (LST); 3) correlation between LST and the normalized difference vegetation index (NDVI) and normalized difference build-up index (NDBI); 4) application of ecological evaluation index. The results showed that the mean values of LST in urban areas were at least 2.34 to 7.19°C higher than undeveloped areas. Moreover, the positive correlation between LST and NDBI showed an amplifying effect of the developed areas for UHI, while areas with a predominance of vegetation attenuated the effect of UHI. Urban centers, clustered in some parts of the city, received the worst ecological assessment index. Finally, the adoption of measures to guide the urban forest planning within urban centers is necessary to mitigate the effect of heat islands and provide thermal comfort in urban areas.

Fuzzy logic applied to prospecting for areas for installation of wood panel industries.

Prospecting for suitable areas for forestry operations, where the objective is a reduction in production and transportation costs, as well as the maximization of profits and available resources, constitutes an optimization problem. However, fuzzy logic is an alternative method for solving this problem. In the context of prospecting for suitable areas for the installation of wood panel industries, we propose applying fuzzy logic analysis for simulating the planting of different species and eucalyptus hybrids in Espírito Santo State, Brazil. The necessary methodological steps for this study are as follows: a) agriclimatological zoning of different species and eucalyptus hybrids; b) the selection of the vector variables; c) the application of the Euclidean distance to the vector variables; d) the application of fuzzy logic to matrix variables of the Euclidean distance; and e) the application of overlap fuzzy logic to locate areas for installation of wood panel industries. Among all the species and hybrids, Corymbia citriodora showed the highest percentage values for the combined very good and good classes, with 8.60%, followed by Eucalyptus grandis with 8.52%, Eucalyptus urophylla with 8.35% and Urograndis with 8.34%. The fuzzy logic analysis afforded flexibility in prospecting for suitable areas for the installation of wood panel industries in the Espírito Santo State can bring great economic and social benefits to the local population with the generation of jobs, income, tax revenues and GDP increase for the State and municipalities involved. The proposed methodology can be adapted to other areas and agricultural crops.

Applying GIS to develop a model for forest fire risk: A case study in Espírito Santo, Brazil.

A forest fire risk map is a basic element for planning and protecting forested areas. The main goal of this study was to develop a statistical model for preparing a forest fire risk map using GIS. Such model is based on assigning weights to nine variables divided into two classes: physical factors of the site (terrain slope, land-use/occupation, proximity to roads, terrain orientation, and altitude) and climatic factors (precipitation, temperature, water deficit, and evapotranspiration). In regions where the climate is different from the conditions of this study, the model will require an adjustment of the variables weights according to the local climate. The study area, Espírito Santo State, exhibited approximately 3.81% low risk, 21.18% moderate risk, 30.10% high risk, 41.50% very high risk, and 3.40% extreme risk of forest fire. The areas classified as high risk, very high and extreme, contemplated a total of 78.92% of heat spots.

GIS applied to agriclimatological zoning and agrotoxin residue monitoring in tomatoes: A case study in Espírito Santo state, Brazil.

Searches related to global warming have provided important insights into the response of terrestrial ecosystems, but few have examined the impacts on agricultural crops, particularly those associated with the monitoring of agrotoxin residues. In this context, the agriclimatological zoning is an important tool in the planning and consolidation of crops and should be considered in any initiative that involves such planning. This tool is particularly important in the analysis of agrotoxin residues and may be applied by the Program Analysis of Agrotoxin Residues in Food (PARA) created by the National Health Vigilance Agency of Brazil (ANVISA), which enables greater food security and contributes to the improvement of human health. The aim of this study was to elaborate the current and future agriclimatological zoning for the tomato crop, relating it with the monitoring of samples collected by PARA in Espírito Santo State, Brazil. The results indicate that a temperature increase of 5 °C creates a decrease in apt areas from 37.3% to 4.3%, for a total reduction of 33 percentage points (-88.5%). It is noted that of the 41 producing municipalities, only 26 have apt areas greater than 50%, highlighting the municipalities with apt areas greater than 90%, represented by Mantenópolis (100%), Guaçuí (98.5%), São José do Calçado (97.8%), Irupi (94.4%), Santa Teresa (92.3%), and Marechal Floriano (91.4%). The veracity of agriclimatological zoning is proved by a Kendall rank correlation coefficient of 0.876, indicating that the distribution of the variables of apt areas and productivity are similar at the significance level of 0.05 with a confidence interval 95%. After validation of the agriclimatological zoning for the tomato crop, it is recommended that the PARA should monitor 36 municipalities rather than the current 18, representing an increase of 100%. The methodology can be adjusted to agricultural crops of other countries.

Influence of relief on permanent preservation areas.

Many countries have environmental legislation to protecting natural resources on private property. In Brazil, the Brazilian Forestry Code determines specific areas to maintain with natural vegetation cover, known as areas of permanent preservation (APP). Currently, there are few studies that relate topographic variables on APP. In this context, we sought to evaluate the influence of relief on the conservation of areas of permanent preservation (APP) in the areas surrounding Caparaó National Park, Brazil. By using the chi-squared statistical test, we verified that the presence of forest cover is closely associated with altitude. The classes of APP in better conservation status are slopes in addition to hilltops and mountains, whereas APP streams and springs are among the areas most affected by human activities. The most deforested areas are located at altitudes below 1100.00 m and on slopes less than 45°. All orientations of the sides were significant for APP conservation status, with the southern, southeastern, and southwestern sides showing the lower degrees of impact. The methodology can be adjusted to environmental legislation to other countries.