Publicações

O acesso a novas fontes de energia, principalmente renováveis, requer níveis específicos de dados para sua classificação correta. As estações de coleta capturam informações em um espaço curto de tempo com uma precisão estável, executando o tratamento das informações coletadas. O controle de qualidade é um aspecto principal em qualquer sistema de tratamento de dados, para garantir confiabilidade e permitir a comparação com outras amostras. O Instituto Nacional de Pesquisas Espaciais (INPE), com base nesses conceitos, implementou a rede SONDA para prover dados meteorológicos e solarimétricos com a finalidade de suporte ao setor de energia no Brasil. Este trabalho consiste na continuação da implementação do algoritmo de validação das informações anemométricas e solarimétricas coletadas na rede SONDA, consistindo em adaptar, em seu último estágio, dois modelos de céu claro propostos por Muhammad Iqbal e Dumortier. Para dar continuidade a este projeto de Iniciação Científica estão programadas as atividades: Revisão bibliográfica e escolha dos principais modelos de céu claro; reestruturação do algoritmo implementando novos testes de qualidade para o aumento de confiabilidade das análises; Validação de modelos computacionais utilizados no levantamento destes recursos; implementação do modelo de céu claro baseado no proposto por Muhammad Iqbal; implementação do modelo de céu claro baseado no proposto por Dumortier, e agregá-los ao conjunto de validação de dados solarimétricos na rede SONDA.

Software Ecosystem (SECO) is a consolidated research area in software engineering, emerging as a paradigm for understanding dynamics and relationships among software systems that collaborate with each other to achieve their goals. Understanding the ecosystem and how its elements interact is essential for software evolution, especially for those that provide functions and services for other systems, such as software APIs. Once an API is being used by different software, future changes need to be made in a systematic and appropriate manner, considering the whole ecosystem. However, there is a lack of formal and effective ways for APIs evaluation in the context of SECO. Thus, in this paper, we present Ecolyzer, a prototype tool that aims to support the analysis of API usage considering its ecosystem through interactive visualization. To demonstrate the feasibility of our tool, we conducted a proof of concept (PoC) using an open-source platform API. The results obtained with Ecolyzer are useful and show that the prototype meets the goals described for the accomplishment of this work.

Physical concepts based on the Clausius-Clapeyron relation and on the thermodynamics and aerosol characteristics associated with updrafts, global climate models assuming different parametrizations and lightning-related output variables, and lightning-related data (thunderstorm days) are being used to infer the lightning incidence in a warmer planet, motivated by the global warming observed. In all cases, there are many gaps to be overcome making the lightning response to the global temperature increase still unpredicted. Values from almost 0% (no increase) to 100% have been estimated, being 10% the most common value. While the physical concepts address only part of the problem and the global climate models need to make many simple assumptions, lightning-relate data have strong time and space limitations. In this context, any new evidence should be considered as an important contribution to better understand how will be the lightning incidence in the future. In this article, we described new results about the occurrence of thunderstorms from 1850 to 2010 (a period of 160 years) in the city of Rio de Janeiro, in the Southeast of Brazil. During this period thunderstorm days were recorded in the same location, making this time series one of the longest series of this type available worldwide. The data support an increase of 21% in the mean annual thunderstorm days during the period, while surface temperature increased by 0.6°C during the period. Considering that the mean annual number of thunderstorm in the beginning of this period was 29, we found an increase of one thunderstorm day per 0.1°C of increase in the surface temperature. Assuming that the number of lightning flashes per thunderstorm remains approximately constant during the period, this number corresponds to an increase in the lightning flash rate of approximately 35% per °C of increase of temperature. In addition, considering that the increase of the global temperature during the period was almost the same that observed in Rio de Janeiro, we can conclude that this increase in the lightning flash rate is due to the global warming with no effect of urban activity. Finally, we found that monthly thunderstorm days and monthly mean surface temperature show a linear correlation with a coefficient of 0.9 along the period.

The social and human sciences have had a minor role in the studies of climate change. There remains a signifcant gap in our knowledge and understanding of the many facets of this theme. The educational sector has been neglected in the climate change scientifc debate, although it is acknowledged as a key sector. This article aims to understand how teachers are dealing with the climate change topic: what they think, learn and teach about it. It is focused on teachers at elementary schools (614 years old) in São José dos Campos, São Paulo State, Brazil. This type of social research is important for developing countries such as Brazil, where the sociological research on climate change is emergent. The identifcation of teachers perceptions on climate change is an important step in fnding ways to listen to and engage with them in the formulation of climate change adaptation plans, especially because they will be among the people responsible for preparing the younger generations of citizens. The survey of teachers knowledge and perception about climate change provides two main approaches: (1) It supports better planning of future school activities, training, and updating knowledge and (2) It suggests how children are being prepared to understand and deal with this contemporary problem of climate change.

Habitat loss is a leading cause of extinctions, which may occur even before species are recorded or formally described. On the other hand, limitations in species distribution data and sampling biases can hamper inferences about patterns of species richness that form the basis of conservation strategies. Insects, despite their crucial roles in terrestrial ecosystems, are still largely neglected when dealing with biological inventories. Among insects, ants are of unique importance because of their species richness, widespread distribution, and due to their key ecosystem functions such as seed dispersal, soil nutrient cycling, predation, and biological control. In this study, we prioritize different Brazilian biomes and ecoregions for new ant surveys based on information on the distribution of occurrence records and two estimates of habitat loss for the period between 2000 and 2016. We compiled nearly 8000 ant occurrence records, including a total of 1170 species. The Caatinga was the biome showing the greatest urgency for new inventories, whereas the Atlantic Forest had the lowest urgency. However, there were considerable differences of priority between ecoregions belonging to each biome, thus underscoring the need to pay special attention to these geographical units and their characteristic associated with ant species. The prioritization of poorly studied sites with an imminent risk of habitat loss can be a valuable starting point for filling knowledge gaps and can help in formulating new strategies of conservation. The dataset provided here may also be useful in studies on the distribution of ant diversity in Brazil.

Aircraft atmospheric profiling is a valuable technique for determining greenhouse gas fluxes at regional scales (104106 km2 ). Here, we describe a new, simple method for estimating the surface influence of air samples that uses backward trajectories based on the Lagrangian model Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT). We determined regions of influence on a quarterly basis between 2010 and 2018 for four aircraft vertical profile sites: SAN and ALF in the eastern Amazon, and RBA and TAB or TEF in the western Amazon. We evaluated regions of influence in terms of their relative sensitivity to areas inside and outside the Amazon and their total area inside the Amazon. Regions of influence varied by quarter and less so by year. In the first and fourth quarters, the contribution of the region of influence inside the Amazon was 8393% for all sites, while in the second and third quarters, it was 5775%. The interquarter differences are more evident in the eastern than in the western Amazon. Our analysis indicates that atmospheric profiles from the western sites are sensitive to 4252.2% of the Amazon. In contrast, eastern Amazon sites are sensitive to only 10.925.3%. These results may help to spatially resolve the response of greenhouse gas emissions to climate variability over Amazon.

Forest degradation is widespread around the world, due to multiple factors such as unsustainable logging, agriculture, invasive species, fire, fuelwood gathering, and livestock grazing. In the Brazilian Amazon forest degradation from August 2006 to July 2016 reached 1,1 869 800 ha. The processes of forest degradation are still poorly understood, being a missing component in anthropogenic CO(2)emission estimates in tropical forests. In this work, we analyzed temporal trajectories of forest degradation from August 2006 to July 2016 in the Brazilian Amazon and assessed their impact on the regional carbon balance. We combined the degradation process with deforestation-related processes (clear-cut deforestation and secondary vegetation dynamics), using the spatially-explicit INPE-EM carbon emission model. The trajectory analysis showed that 13% of the degraded area ended up being cleared and converted in the period and 61% of the total degraded area experienced only one event of degradation throughout the whole period. Net emissions added up to 5.4 GtCO(2), considering the emissions from forest degradation and deforestation, absorption from degraded forest recovery, and secondary vegetation dynamics. The results show an increase in the contribution of forest degradation to net emissions towards the end of the period, related to the decrease in clear-cut deforestation rates, decoupled from the forest degradation rates. The analysis also indicates that the regeneration of degraded forests absorbed 1.8 GtCO2 from August 2006 and July 2016-a component typically overlooked in the regional carbon balance.

The Brazilian Amazon has the highest concentration of indigenous peoples in the world. Recently, the Brazilian government sent a bill to Congress to regulate commercial mining in indigenous lands. This work analyzes the risks of the proposed mining bill to Amazonian indigenous peoples and their lands. To evaluate the possible impact of the new mining bill, we consider all mining license requests registered in Brazils National Mining Agency that overlap indigenous lands as potential mining areas in the future. The existing mining requests cover 176 000 km2 of indigenous lands, a factor 3000 more than the area of current illegal mining. Considering only these existing requests, about 15% of the total area of ILs in the region could be directly affected by mining if the bill is approved. Ethnic groups like Yudj´a, Kayapo, Apalaí, Wayana, and Katuena may have between ´ 47% and 87% of their lands impacted. Gold mining, which has previously shown to cause mercury contamination, death of indigenous people due to diseases, and biodiversity degradation, accounts for 64% of the requested areas. We conclude that the proposed bill is a significant threat to Amazonian indigenous peoples, further exposing indigenous peoples to rural violence, contamination by toxic pollutants, and contagious diseases. The obligation of the government is to enforce existing laws and regulations that put indigenous rights and livelihoods above economic consideration and not to reduce such protections.

Several studies have presented morphometric analysis as the key to understanding hydrological behavior or support tool for the assessment of natural resources and environmental risks in a river basin. The Rio Grande Basin has great socioeconomic and environmental relevance for Brazil; however, its morphometric characterization is not widely known. Therefore, we present the morphometric characteristics of the Rio Grande Basin (BHRG), from the geometric, relief, and drainage variables. Data processing was carried out using the Geographic Information System (GIS), from the Digital Elevation Model (DEM). The results indicate that the BHRG is of the ffth order, presenting a dendritic drainage pattern, low susceptibility to fooding under normal precipitation conditions, sinuous watercourses, and an undulating relief. In addition, the BHRG is permeable, poorly drained, and displays low capacity to generate and maintain drainage tracts. The fndings can contribute to a better understanding of hydrological behavior on a river basin and support integrated water resource plans.

Several studies show the effects of lake breezes on cloudiness over natural lakes and large rivers, but only few contain information regarding large flooded areas of hydroelectric dams. Most Brazilian hydropower plants have large water reservoirs that may induce significant changes in the local environment. In this work, we describe the prevailing breeze mechanism in a Brazilian tropical hydropower reservoir to assess its impacts on local cloudiness and incoming surface solar irradiation. GOES-16 visible imagery, ISCCP database products, and ground measurement sites operated by INMET and LABREN/INPE provided data for the statistical analysis. We evaluate the cloudiness frequency assuming two distinct perspectives: spatial distribution by comparing cloudiness over the water surface and areas nearby its shores, and time analysis by comparing cloudiness prior and after reservoir completion. We also evaluated the solar irradiance enhancement over the water surface compared to the border and land areas surrounding the hydropower reservoir. The results pointed out daily average cloudiness increases moving away from the reservoir in any of the four cardinal directions. When looking at the afternoon-only cloudiness (14 h to 16 h local time), 4% fewer clouds were observed over the flooded area during summer (DJF). This difference reaches 8% during autumn (MAM) and spring (SON). Consequently, the irradiance enhancement at the water surface compared to external areas was around 1.75% for daily average and 4.59% for the afternoon-only average. Our results suggest that floating solar PV power plants in hydropower reservoirs can be an excellent option to integrate both renewable energy resources into a hybrid power generation due to the high solar irradiance in Brazilian territory combined with the prevailing breeze mechanism in large tropical water reservoirs.

The tropical savanna in Brazil known as the Cerrado covers circa 23% of the Brazilian territory, but only 3% of this area is protected. High rates of deforestation and degradation in the woodland and forest areas have made the Cerrado the second-largest source of carbon emissions in Brazil. However, data on these emissions are highly uncertain because of the spatial and temporal variability of the aboveground biomass (AGB) in this biome. Remote-sensing data combined with local vegetation inventories provide the means to quantify the AGB at large scales. Here, we quantify the spatial distribution of woody AGB in the Rio Vermelho watershed, located in the centre of the Cerrado, at a high spatial resolution of 30 metres, with a random forest (RF) machine-learning approach. We produced the first high-resolution map of the AGB for a region in the Brazilian Cerrado using a combination of vegetation inventory plots, airborne light detection and ranging (LiDAR) data, and multispectral and radar satellite images (Landsat 8 and ALOS-2/PALSAR-2). A combination of random forest (RF) models and jackknife analyses enabled us to select the best remote-sensing variables to quantify the AGB on a large scale. Overall, the relationship between the ground data from vegetation inventories and remote-sensing variables was strong (R2 = 0.89), with a root-mean-square error (RMSE) of 7.58 Mg ha-1 and a bias of 0.43 Mg ha-1.

Emissions of nitrous oxide (N2O) over croplands are a major source of greenhouse gases to the atmosphere. The precise accounting of sources of N2O is essential to national and global budgets, as well as the understanding of the spatial and temporal relationships with environmental variables such as rainfall, air and soil temperature, and soil moisture. The objective of this work was to investigate the temporal correlations of N2O fluxes with soil and air temperatures, as well as soil moisture. N2O fluxes were measured over four biofuel crops in Central Illinois during their establishment phase. Measurements were carried out from 2009 to 2011 using a trace gas analyzer (TGA) with tunable laser technology. Measurements of concentrations of N2O and CO(2)were taken at the center of four plots of maize/soybean rotation, miscanthus (Miscanthus x giganteus), switchgrass (Panicum virgatum) and a mixture of native prairie plants. Cumulative fluxes indicate an average emission of nitrogen via N2O fluxes on the order of 1.5 kg N ha(-1) year(-1), in agreement with chamber measurements previously reported for the site. N2O fluxes were associated with peaks in soil and air temperature, and soil moisture, particularly during spring and winter thaws. Cross-wavelet analysis was used to investigate the correlation between N2O fluxes and those variables. Results indicate that N2O fluxes and meteorological variables have significant covariance in time scales ranging from 4 to 32 days. In addition, temporal delays of 1-8 days were found in those relationships. Cross-wavelet patterns were similar when relating N2O fluxes with soil temperature, air temperature and soil moisture. The temporal patterns of fluxes and environmental variables reported here support the modeling of emissions and highlight the importance of considering the timing of fluxes in relation to trends in meteorological variables.