Publicações

A geração de energia através da queima de combustíveis, acelerada pela forte urbanização do último século promoveu a alteração significativa da composição química da atmosfera global e, em particular dos centros urbanos. Para compreender os processos de emissão, transformação e contaminação da atmosfera por poluentes, é importante obter amostras ao longo do tempo e em diferentes situações climáticas em regiões sob influência de atividades antropogênicas. O material particulado inalável (MPI), devido à sua composição química complexa e às suas propriedades físicas, pode causar sérios danos ao sistema respiratório e à vegetação. Este estudo teve como objetivo comparar o material particulado inalável (MPI) e suas frações fina (MP≤ 2,5) e grossa (MP2,5-10) em três regiões com atmosferas distintas: São José dos Campos (região urbana de médio porte), Cachoeira Paulista (área rural) e São Paulo (zona urbana densamente povoada). Para tal, com um coletor do tipo dicotômico, foi coletado material particulado com frequência semanal nos três locais entre (03/2013-11/2014). Comparando os resultados obtidos nos três pontos de estudo, observou-se um gradiente de concentração maior para menor entre o local com intensa urbanização (São Paulo) e a zona rural (Cachoeira Paulista) conforme mostrado na Tabela 1. Tabela 1: Média aritmética das concentrações do particulado em MP≤ 2,5 e MP2,5-10 em ng.m-3, correspondente ao período total. Na+ K+ Mg+2 Ca+2 NH4 + Cl- NO3 – SO4-2 SP FF 109,395 113,882 0,001 373,256 597,758 204,569 1056,05 1432,264 SP FG 232,407 288,743 80,862 508,181 211,422 448,831 1168,774 712,075 SJC FF 167,412 140,732 42,595 369,928 304,393 169,682 532,499 617,053 SJC FG 248,034 628,917 66,167 477,69 186,875 300,363 728,375 341,912 CP FF 67,41 88,606 17,342 176,104 262,305 91,184 513,744 660,157 CP FG 114,815 1231,128 35,233 245,467 122,663 179,357 475,864 226,749.

Approximately 57 % of the Brazilian northeast region is recognized as semi-arid land and has been undergoing intense land use processes in the last decades, which have resulted in severe degradation of its natural assets. Therefore, the objective of this study is to identify the areas that are susceptible to desertification in this region based on the 11 influencing factors of desertification (pedology, geology, geomorphology, topography data, land use and land cover change, aridity index, livestock density, rural population density, fire hot spot density, human development index, conservation units) which were simulated for two different periods: 2000 and 2010. Each indicator were assigned weights ranging from 1 to 2 (representing the best and the worst conditions), representing classes indicating low, moderate and high susceptibility to desertification. The results indicate that 94 % of the Brazilian northeast region is under moderate to high susceptibility to desertification. The areas that were susceptible to soil desertification increased by approximately 4.6 % (83.4 km2) from 2000 to 2010. The implementation of the methodology provides the technical basis for decisionmaking that involves mitigating actions and the first comprehensive national assessment within the United Nations Convention to Combat Desertification framework.

Human activities have been driven land cover, provoking acceleration of the erosive process and alteration on the soil characteristics. To explore the effects of human disturbance, we investigated the influences of natural and anthropogenic features on soil quality and soil erosion indicators (EI) within a Brazilian rural watershed located in Bauru Municipality, State of Sao Paulo. A pre-established set of soil EI was used to evaluate the influence of anthropogenic land cover categories on the presence and severity of erosion, related with spatial variations of soil attributes. On-site visits were carried out to measure the occurrence and the intensity of eleven separate EI values and to collect undisturbed topsoil samples for subsequent analyses. We registered 17 occurrences of EIs, distributed in ten locals. Occurrence and intensity of EIs were related to degree of sheet erosion. The EI qualities were more strongly associated with land cover management practices than to local topographic features. The occurrence of EIs and characteristics of soil and soil organic matter (SOM) were not significantly self-correlated. Although land cover class seems to influence soil properties and SOM attributes, we observed that the granulometric composition of the soils also contributes to the structural characteristics of the soil and consequently to the dynamic loss and gain of soil carbon. Sites covered with natural remnant vegetation (NRV) store 96.5 Mg ha-1 of C and grassy and tilled soils stored more C than NRV, 100.1 and 142.4 Mg ha-1 , respectively. Due to the influence of soil texture over the soil C dynamic, we observe that in Bauru, pastured areas have high potential for sequestration of C if factors such as fire and/or erosion were avoided or effectively controlled. Results from this study show that human disturbance substantially affects soil properties within of southeastern region of Brazil.

Brazilian strategic interest in the Madeira River basin, one of the most important of the southern Amazon tributaries, includes the development of hydropower to satisfy the countrys growing energy needs and new waterways to boost regional trade and economic development. Because of evidences that climate change impacts the hydrological regime of rivers, the aim of this study was to assess how global climate change and regional land cover change caused by deforestation could affect the rivers hydrological regime. To achieve this goal, we calibrated a large-scale hydrological model for the period from 19701990 and analyzed the ability of the model to simulate the present hydrological regime when climate model simulations were used as input. Climate change projections produced by climate models were used in the hydrological model to generate scenarios with and without regional land-use and land-cover changes induced by forest conversion to pasture for the period from 20112099. Although results show variability among models, consensus scenarios indicated a decrease in the low-flow regime. When the simulations included forest conversion to pasture, climate change impacts on low flows were reduced in the upper basin, while, in the lower basin, discharges were affected along the whole year due to the more vigorous land-use conversion in the Brazilian region of the basin.

Land cover is of fundamental importance to many environmental applications and serves as critical baseline information for many large scale models e.g. in developing future scenarios of land use and climate change. Although there is an ongoing movement towards the development of higher resolution global land cover maps, medium resolution land cover products (e.g. GLC2000 and MODIS) are still very useful for modelling and assessment purposes. However, the current land cover products are not accurate enough for many applications so we need to develop approaches that can take existing land covers maps and produce a better overall product in a hybrid approach. This paper uses geographically weighted regression (GWR) and crowdsourced validation data from Geo-Wiki to create two hybrid global land cover maps that use medium resolution land cover products as an input. Two different methods were used: (a) the GWR was used to determine the best land cover product at each location; (b) the GWR was only used to determine the best land cover at those locations where all three land cover maps disagree, using the agreement of the land cover maps to determine land cover at the other cells. The results show that the hybrid land cover map developed using the first method resulted in a lower overall disagreement than the individual global land cover maps. The hybrid map produced by the second method was also better when compared to the GLC2000 and GlobCover but worse or similar in performance to the MODIS land cover product depending upon the metrics considered. The reason for this may be due to the use of the GLC2000 in the development of GlobCover, which may have resulted in areas where both maps agree with one another but not with MODIS, and where MODIS may in fact better represent land cover in those situations. These results serve to demonstrate that spatial analysis methods can be used to improve medium resolution global land cover information with existing products.

It has been discussed in past papers if a positive leader propagates in a stepped fashion or not. Some studies state that, in some positive cloud-to-ground flashes, the electric field pulses observed just before the connection of the positive leader to ground could be a manifestation of the stepping of the leader. Some authors say, however, that it may be due to the stepping of the negative upward connecting leader during its ascension toward the downward positive leader. In this work we present a well-documented case of a positive cloud-to-ground flash that shows that the pulses observed in the electric field preceding the return stroke are due solely to the upward propagation of a negative connecting leader. This flash was recorded simultaneously by a fast electric field sensor and a high-speed camera in July 2012 in the Black Hills area of South Dakota.

An innovative data mining approach is presented and applied to investigate the climatic causes of extreme climatic events. Our approach comprises two main steps of knowledge extraction, applied successively in order to reduce the complexity of the original data set. The goal is to identify a much smaller subset of climatic variables that might still be able to describe or even predict the extreme events. The first step applies a class comparison technique. The second step consists of a decision tree learning algorithm used as a predictive model to map the set of statistically most significant climate variables identified in the previous step to classes of precipitation intensity. The methodology is employed to the study the climatic causes of two extreme events occurred in Brazil the last decade: the Santa Catarina 2008 extreme rainfall tragedy and the Amazon droughts of 2005 and 2010. In both cases, our results are in good agreement with analyses published in the literature.

Dynamic global vegetation models (DGVMs) simulate surface processes such as the transfer of energy, water, CO2, and momentum between the terrestrial surface and the atmosphere, biogeochemical cycles, carbon assimilation by vegetation, phenology, and land use change in scenarios of varying atmospheric CO2 concentrations. DGVMs increase the complexity and the Earth system representation when they are coupled with atmospheric global circulation models (AGCMs) or climate models. However, plant physiological processes are still a major source of uncertainty in DGVMs. The maximum velocity of carboxylation (Vcmax), for example, has a direct impact over productivity in the models. This parameter is often underestimated or imprecisely defined for the various plant functional types (PFTs) and ecosystems. Vcmax is directly related to photosynthesis acclimation (loss of response to elevated CO2), a widely known phenomenon that usually occurs when plants are subjected to elevated atmospheric CO2 and might affect productivity estimation in DGVMs. Despite this, current models have improved substantially, compared to earlier models which had a rudimentary and very simple representation of vegetation-atmosphere interactions. In this paper, we describe this evolution through generations of models and the main events that contributed to their improvements until the current state-of-the-art class of models. Also, we describe some main challenges for further improvements to DGVMs.

Several years with extreme floods or droughts in the past decade have caused human suffering in remote communities of the Brazilian Amazon. Despite documented local knowledge and practices for coping with the high seasonal variability characteristic of the regions hydrology (e.g., 10 m change in river levels between dry and flood seasons), and despite civil defense interventions by various levels of government, the more extreme years seem to have exceeded the coping capacity of the community. In this paper, we explore whether there is a real increase in variability, whether the community perceives that recent extreme events are outside the experience which shapes their responses to normal levels of variability, and what science-based policy could contribute to greater local resilience. Hydrological analyses suggest that variability is indeed increasing, in line with expectations from future climate change. However, current measures of hydrological regimes do not predict years with social hardship very well. Interviewees in two regions are able to express their strategies for dealing with normal variability very well, but also identify ways in which abnormal years exceed their ability to cope. Current civil defense arrangements struggle to deliver emergency assistance in a sufficiently timely and locally appropriate fashion. Combining these insights in the context of socialecological change, we suggest how better integration of science, policy and local knowledge could improve resilience to future trends, and identify some contributions science could make into such an arrangement.

The HAND (Height Above the Nearest Drainage), a quantitative topographic descriptor, is used to classify terrain in a manner that is related to local soil water conditions, providing hydrological meaning to the SRTM DEM. In this paper, we compare performance of using the HAND grid instead of the SRTM DEM for classifying, at regional scale (19 000 000 km2), drainage conditions of terra firme environment (plateau, slope, ecotone and waterlogged) in the Eastern Amazon, Brazil. Additionally, we emphasize the need to attenuate the canopy effects of the SRTM DEM for the boundary between forested and deforested areas, in order to produce coherent data for hydrological modeling.