Publicações

The expansion of agricultural activities in Brazil resulted in a loss of approximately 50% of the native vegetation of the Cerrado biome, mainly to the north of the biome in a region known as MATOPIBA. Besides contributing to accelerate climate change, the removal of native vegetation is associated with increase soil degradation. In this study, we used the decision tree method to predict degradation using as indicators Normalized Difference Vegetation Index (NDVI) derived indices over the period 19852018. Results showed that approximately 4677 km2 (0.63%) of MATOPIBA region is under strong signs of degradation, mostly on pasture and grasslands areas, commonly used for grazing. Although the percentage of degraded areas is relatively small, the mapping indicated that the majority of degradation patches are concentrated not only in areas of low resilience, e.g., areas dominated by weakly structured sandy soils, but also where highly stable latosols dominate. More importantly, these areas were frequently affected by fire over the study period. This finding suggests that the combination of unsustainable traditional land management practices, such as fire, the replacement of forest by pasture, and anthropic activities such as inadequate road planning, are the main factor that trigger degradation processes in this Brazilian region. The study results are important for decision makers for defining investment priorities for conservation and for the recovery of degraded areas.

Brazil is currently the largest contributor of land use and land cover change (LULCC) carbon dioxide net emissions worldwide, representing 17%-29% of the global total. There is, however, a lack of agreement among different methodologies on the magnitude and trends in LULCC emissions and their geographic distribution. Here we perform an evaluation of LULCC datasets for Brazil, including those used in the annual global carbon budget (GCB), and national Brazilian assessments over the period 2000-2018. Results show that the latest global HYDE 3.3 LULCC dataset, based on new FAO inventory estimates and multi-annual ESA CCI satellite-based land cover maps, can represent the observed spatial variation in LULCC over the last decades, representing an improvement on the HYDE 3.2 data previously used in GCB. However, the magnitude of LULCC assessed with HYDE 3.3 is lower than estimates based on MapBiomas. We use HYDE 3.3 and MapBiomas as input to a global bookkeeping model (bookkeeping of land use emission, BLUE) and a process-based Dynamic Global Vegetation Model (JULES-ES) to determine Brazil’s LULCC emissions over the period 2000-2019. Results show mean annual LULCC emissions of 0.1-0.4 PgC yr(-1), compared with 0.1-0.24 PgC yr(-1) reported by the Greenhouse Gas Emissions Estimation System of land use changes and forest sector (SEEG/LULUCF) and by FAO in its latest assessment of deforestation emissions in Brazil. Both JULES-ES and BLUE now simulate a slowdown in emissions after 2004 (-0.006 and -0.004 PgC yr(-2) with HYDE 3.3, -0.014 and -0.016 PgC yr(-2) with MapBiomas, respectively), in agreement with the Brazilian INPE-EM, global Houghton and Nassikas book-keeping models, FAO and as reported in the 4th national greenhouse gas inventories. The inclusion of Earth observation data has improved spatial representation of LULCC in HYDE and thus model capability to simulate Brazil’s LULCC emissions. This will likely contribute to reduce uncertainty in global LULCC emissions, and thus better constrains GCB assessments.

Amazonia hosts the Earth’s largest tropical forests and has been shown to be an important carbon sink over recent decades(1-3). This carbon sink seems to be in decline, however, as a result of factors such as deforestation and climate change(1-3). Here we investigate Amazonia’s carbon budget and the main drivers responsible for its change into a carbon source. We performed 590 aircraft vertical profiling measurements of lower-tropospheric concentrations of carbon dioxide and carbon monoxide at four sites in Amazonia from 2010 to 2018(4). We find that total carbon emissions are greater in eastern Amazonia than in the western part, mostly as a result of spatial differences in carbon-monoxide-derived fire emissions. Southeastern Amazonia, in particular, acts as a net carbon source (total carbon flux minus fire emissions) to the atmosphere. Over the past 40 years, eastern Amazonia has been subjected to more deforestation, warming and moisture stress than the western part, especially during the dry season, with the southeast experiencing the strongest trends(5-9). We explore the effect of climate change and deforestation trends on carbon emissions at our study sites, and find that the intensification of the dry season and an increase in deforestation seem to promote ecosystem stress, increase in fire occurrence, and higher carbon emissions in the eastern Amazon. This is in line with recent studies that indicate an increase in tree mortality and a reduction in photosynthesis as a result of climatic changes across Amazonia(1,10). Aircraft observations of atmospheric carbon dioxide and monoxide concentrations in Brazil show higher carbon emissions in eastern Amazonia than in the western part, which are linked to increased ecosystem stress and fire occurrence.

Non-structural carbohydrates (NSC) are major substrates for plant metabolism and have been implicated in mediating drought-induced tree mortality. Despite their significance, NSC dynamics in tropical forests remain little studied. We present leaf and branch NSC data for 82 Amazon canopy tree species in six sites spanning a broad precipitation gradient. During the wet season, total NSC (NSCT) concentrations in both organs were remarkably similar across communities. However, NSCT and its soluble sugar (SS) and starch components varied much more across sites during the dry season. Notably, the proportion of leaf NSCT in the form of SS (SS:NSCT) increased greatly in the dry season in almost all species in the driest sites, implying an important role of SS in mediating water stress in these sites. This adjustment of leaf NSC balance was not observed in tree species less-adapted to water deficit, even under exceptionally dry conditions. Thus, leaf carbon metabolism may help to explain floristic sorting across water availability gradients in Amazonia and enable better prediction of forest responses to future climate change.

Global Environmental Assessments (GEAs) are in a unique position to influence environmental decision-making in the context of sustainability challenges. To do this effectively, however, new methods are needed to respond to the needs of decision-makers for a more integrated, contextualized and goal-seeking evaluation of different policies, geared for action from global to local. While scenarios are an important tool for GEAs to link short-term decisions and medium and long-term consequences, these current information needs cannot be met only through deductive approaches focused on the global level. In this paper, we argue that a more diverse set of futures tools operating at multiple scales are needed to improve GEA scenario development and analysis to meet the information needs of policymakers and other stakeholders better. Based on the literature, we highlight four challenges that GEAs need to be able to address in order to contribute to global environmental decision-making about the future: 1. anticipate unpredictable future conditions; 2. be relevant at multiple scales, 3. include diverse actors, perspectives and contexts; and 4. leverage the imagination to inspire action. We present a toolbox of future-oriented approaches and methods that can be used to effectively address the four challenges currently faced by GEAs.

We relate the spatial and temporal distribution of lightning flash rates and cloud top brightness temperature (CTBT) to concentric atmospheric gravity wave (CGW) events observed at the Southern Space Observatory (SSO) in São Martinho da Serra (29.44°S, 53.82°W, 488.7m) in southern Brazil. The selected identified cases from 2017 to 2018 were observed by a hydroxyl (OH) all-sky imager. Backward ray tracing shows that the time of gravity wave excitation agrees with the highest values of lightning flash rates (indicating lightning jump) as well as the coldest brightness temperatures that indicate the time of convective overshoot. Radiosonde measurements show high convective available potential energy (CAPE), associated with a maximum updraft velocity just prior to the wave events. We find that these possible source locations correspond to the positions and times that convective plumes overshot the tropopause (seen in GOES-16 CTBT images). We also show that higher spatial lightning density (i.e., number of lightning flashes at a given longitude and latitude) agree with the overshoot locations from the GOES satellite. We also find that the overshoot times from the GOES-16 satellite agree with the times lightning jumps were observed in the lightning flash rate. Finally, we find that the periodicities in the lightning flash rate agree with the periods of the observed CGWs, which further strengthens the result that the CGWs were excited by the deep convective systems determined from backward ray tracing.

With the inclusion of demographic characteristics of the population living in vulnerable areas, a combination of empirical and climate models was used to project changes to climate and in hydro-geo-meteorological disasters in Brazil. This study investigated the effect of extreme rainfall changes and the risk of floods and landslides under 1.5, 2.0, and 4.0◦ C global warming levels (GWLs). Projections from a large ensemble of pre-CMIP6 models and different warming levels show a remarkable change in heavy precipitation. As a result, with increasing warming this enhances the risk of landslides and flash floods in the context of climate change. Comparisons of vulnerability and change in potential impacts of landslides and floods show that three regions, highly densely populated areas, are the most exposed to landslides and floods. The Southern and Southeastern of Brazil stand out, including metropolitan regions with high economic development and densely populated, which may be those where disasters can intensify both in terms of frequency and magnitude. The eastern portion of the Northeast is also signaled as one of the affected regions due to its high vulnerability and exposure since the present period, although the projections of future climate do not allow conclusive results regarding the intensification of extreme rainfall events in scenarios below 4◦C. The main metropolitan regions and tourist resorts, and key infrastructure in Brazil are located in those regions. This study highlights the importance of environmental policies to protect human lives and minimize financial losses in the coming decades and reinforces the need for decision-making, monitoring, and early warning systems to better manage disasters as part of disaster risk reduction risk management.

Low-density peats from many countries have long been studied by many authors. They are mostly forest and moss peats. Different peat types, from different locations in the world, may present degradation behavior that differs significantly. Bulk density, which is one the most important physical parameters governing the smoldering dynamics of solid fuels, varies among countries’ peatlands. This work compares experimental data for low (200 kg m(-3)) and high (450 kg m(-3)) bulk density peat smoldering in a test bench. Peat sam-ples with different densities, organic matter contents, and particle sizes were considered in this work. The physicochemical characterization included ultimate analysis, ash composition, the density of the solid, and thermogravimetric and differential thermogravimetric analysis. The influences of the organic matter content, as well as the bulk surface area to volume ratio on peat burning, are also discussed. It is showed that, for the same organic matter and bulk surface area to volume ratio, the high bulk density peat burning rate is as low as one-third of the low bulk density peat burning rate. Once the High Heating Value of both peats is found similar, this lower burning rate is related to chemical kinetics, which shows higher oxidation temperature, around 500 degrees C for the high bulk density peat, and 300 degrees C for the low bulk density peat. For the high bulk density peat, the higher the bulk surface area to volume ratio the higher both horizontal and vertical smoldering spread rates.

O aquecimento global torna necessário o benchmarking do tecido urbano para desenvolver políticas que possam promover a resiliência urbana ao calor. O objetivo desta pesquisa é identificar padrões do tecido urbano que produzem a retroalimentação negativa do sistema climático urbano naturalmente. O método contempla o uso de imagens Landsat-8, para estimar e mapear a temperatura das superfícies e suas características espectrais (albedo, emissividade, fração de cobertura de vegetação e índice de umidade por diferença normalizada), a integração dos dados em um espaço celular georreferenciado, análises de correlação, autocorrelação e de clusters, e identificação de zonas climáticas locais. A área de estudos é São José dos Campos, SP, Brasil, onde a zona climática local 3, com construções compactas de pequeno porte, é predominante. A maior diferença de temperatura de superfície entre clusters foi 12 °C e ocorreu entre áreas verdes e permeáveis e áreas áreas plenamente impermeabilizadas com extensas construções. As análises permitiram inferir a dependência espacial da temperatura da superfície, apesar da variabilidade sazonal, indicando que ela pode ser utilizada para identificar fatores que influenciam processos de retroalimentação do sistema climático urbano, zonas climáticas locais, e auxiliar no desenvolvimento de políticas de adaptação e resiliência urbana ao calor.

The United Nations Sustainable Development Goals (SDGs) are described as integrated and indivisible, where sustainability challenges must be addressed across sectors and scales to achieve global-level sustainability. However, SDG monitoring mostly focuses on tracking progress at national-levels, for each goal individually. This approach ignores local and cross-border impacts of national policies and assumes that global-level progress is the sum of national, sector-specific gains. In this study, we investigate effects of reforestation programs in China on countries supplying forest and agricultural commodities to China. Using case studies of rubber and palm oil production in Southeast Asian countries, soy production in Brazil and logging in South Pacific Island states, we investigate cross-sector effects of production for and trade to China in these exporting countries. We use a three-step multi-method approach. 1) We identify distal trade flows and the narratives used to justify them, using a telecoupling framework; 2) we design causal loop diagrams to analyse social-ecological processes of change in our case studies driven by trade to China and 3) we link these processes of change to the SDG framework. We find that sustainability progress in China from reforestation is cancelled out by the deforestation and cross-sectoral impacts supporting this reforestation abroad. Narratives of economic development support commodity production abroad through unrealised aims of benefit distribution and assumptions of substitutability of socio-ecological forest systems. Across cases, we find the analysed trade supports unambiguous progress on few SDGs only, and we find many mixed effects where processes that support the achievement of SDGs exist, but are overshadowed by counterproductive processes. Our study represents a useful approach for tracking global-level impacts of national sustainability initiatives and provides cross-scale and cross-sectoral lenses through which to identify drivers of unsustainability that can be addressed in the design of effective sustainability policies.

Reservoirs of hydropower plants (HPP) can amend water, energy, and food security in semi-arid regions. However, during severe droughts, the priority of energy demand leads to critical conditions of water availability. To reduce water use for energy, one possible measure is the adoption of solar power, an abundant energy source in semi-arid regions. This study assessed the influence of adding floating photovoltaic power (PV) in the largescale reservoir of Sobradinho HPP, located in the S ao Francisco River (SFR), in Brazil, from 2009 to 2018. The simulated scenarios varied the installed PV power capacity from 50 to 1000 MW. For each scenario, water allocation was modified based on the solar-hydro equivalence that restrained the historical outflow of Sobradinho to maintain water in the reservoir. Besides, a diverse operation rule for the reservoirs in cascade of SFR was adopted to avoid ecological impacts of low streamflow. The scenarios were assessed in water security, solarhydro electricity output, capacity factor of the powerplant, water and energy losses by evaporation and spilled water. Results show that a PV system starting from 250 MW was necessary to improve water security during the severe drought, reserving 0.72.3 of the annual water demand. In addition, the capacity factor was optimized from 29% to 3447%. However, as the HPPs installed at SFR work as one system, the constrain of the river flow reduced the hydroelectricity by 4.4% for 750 MW. We concluded that PV significantly influenced water security and ecological conditions of SFR, with benefits in the range of 250750 MW. The research provides assessment on substituting hydro for solar power on the operation of reservoirs in cascade and identifies the correlated benefits in social and ecological aspects. This information can support decisions of water and energy supply system operators and public policies focused on integrated resources management in semi-arid regions.

Large volumes of water are released to the atmosphere through evaporation from soil and transpiration from vegetation, constituting evapotranspiration (ET). Estimating the water consumption in vegetated areas is important for the management and rational use of this resource. For this study were processed orbital images which correspond to Quixeré-CE, with interest at the Frutacor Farm, where there is predominance the banana crop. The main objective of this study was to assess the accuracy and applicability of S-SEBI and SSEB algorithms with regard to SEBAL to estimate the actual daily evapotranspiration ETa) of a semi-arid region of Northeast Brazil, containing areas of banana orchard, native vegetation (caatinga) and bare soil. SSEBI. The SSEB and SSEB algorithms showed strong correlation (r > 0.93) with statistical significance of 5%. The S-SEBI exhibited errors less than 12% in the orchard and caatinga and SSEB exhibited greater errors at 22%, though for the bare soil, both models showed large discrepancies when compared with SEBAL, with errors greater than 36%. Therefore, among the two algorithms compared with SEBAL, S-SEBI had a better performance in ETa estimation with lower deviations.