Publicações

In this work, we evaluate the environmental and economic sustainability dimensions of a run-of-river hydroelectric plant operation regarding environmental impacts and potential direct and indirect effects of climate change. Results suggest the generation of a vicious cycle of clean generation and dirty generation, enhanced by a positive feedback with climate change impacts. This cycle is triggered by the tradeoffs between environmental protection policies and the socioeconomic pressure for energy production, embedded in an energy production matrix that prioritizes fossil fuel-based production as responses to peak energy demand. The climate projections were generated by the Eta Regional Climate Model from the National Institute for Space Research. They were forced by the atmospheric simulations of the Interdisciplinary Climate Research Model (MIROC5) and the Hadley Center Global Environmental Model (HadGEM2-ES) under the RCP4.5 and RCP 8.5 emission scenarios. The MHD-INPE Distributed Hydrological Model was used to generate streamflow projections. Environmental impacts were assessed by accounting for carbon stock and sequestration, greenhouse gas emissions, and energy cost. Climate projections indicated reduced precipitation and increased temperature. The streamflow will present progressively reductions of the flow volume until the end of the century, which undermines the plant’s ability to ensure firm energy and induce thermal plants’ activation to supply the demand. This activation will lead to an increase in greenhouse gas emissions and an increase in the price of energy, which may lower the benefits in carbon stock associated with a run-of-river hydropower plant and negatively influence the reduction commitments assumed by Brazil.

To achieve regional and international large-scale restoration goals with minimum costs, several restoration commitments rely on natural regeneration, a passive and inexpensive strategy. However, natural regeneration potential may vary within the landscape, mainly due to its historical context. In this work, we use spatially explicit restoration scenarios to explore how and where, within a given region, multiple restoration commitments could be combined to achieve cost-effectiveness outcomes. Our goal is to facilitate the elaboration of forest restoration plans at the regional level, taking into consideration the costs for active and passive restoration methods. The approach includes (1) a statistical analysis to estimate the natural regeneration potential for a given area based on alternative sets of biophysical, land cover, and/or socioeconomic factors and (2) the use of a land change allocation model to explore the cost-effectiveness of combining multiple restoration commitments in a given area through alternative scenarios. We test our approach in a strategic region in the Brazilian Atlantic Forest Biome, the Paraiba Valley in São Paulo State. Using the available data for 2011, calibrated for 2015, we build alternative scenarios for allocating natural regeneration until 2025. Our models indicate that the natural regeneration potential of the region is actually very low, and the cost-effectiveness outcomes are similar for all scenarios. We believe our approach can be used to support the regional-level decision-making about the implementation of multiple commitments aiming at the same target area. It can also be combined with other approaches for more refined analysis (e.g., optimization models).

Humanity is on a deeply unsustainable trajectory. We are exceeding planetary boundaries and unlikely to meet many international sustainable development goals and global environmental targets. Until recently, there was no broadly accepted framework of interventions that could ignite the transformations needed to achieve these desired targets and goals. As a component of the IPBES Global Assessment, we conducted an iterative expert deliberation process with an extensive review of scenarios and pathways to sustainability, including the broader literature on indirect drivers, social change and sustainability transformation. We asked, what are the most important elements of pathways to sustainability? Applying a social-ecological systems lens, we identified eight priority points for intervention (leverage points) and five overarching strategic actions and priority interventions (levers), which appear to be key to societal transformation. The eight leverage points are: (1) Visions of a good life, (2) Total consumption and waste, (3) Latent values of responsibility, (4) Inequalities, (5) Justice and inclusion in conservation, (6) Externalities from trade and other telecouplings, (7) Responsible technology, innovation and investment, and (8) Education and knowledge generation and sharing. The five intertwined levers can be applied across the eight leverage points and more broadly. These include: (A) Incentives and capacity building, (B) Coordination across sectors and jurisdictions, (C) Pre-emptive action, (D) Adaptive decision-making and (E) Environmental law and implementation. The levers and leverage points are all non-substitutable, and each enables others, likely leading to synergistic benefits. Transformative change towards sustainable pathways requires more than a simple scaling-up of sustainability initiatives-it entails addressing these levers and leverage points to change the fabric of legal, political, economic and other social systems. These levers and leverage points build upon those approved within the Global Assessment’s Summary for Policymakers, with the aim of enabling leaders in government, business, civil society and academia to spark transformative changes towards a more just and sustainable world.

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.

Este relatório descreve as atividades de campo realizadas na região do Baixo Tocantins, microrregião de Cametá no estado do Pará, nos anos de 2018 e 2019, pela equipe de pesquisa do Laboratório de Investigação em Sistemas Socioambientais (LiSS) do Instituto Nacional de Pesquisas Espaciais (INPE). Essas atividades tiveram como objetivo coletar dados para caracterizar a região em dois aspectos. O primeiro aspecto diz respeito às diferentes formas de uso e ocupação do solo e aos principais métodos de produção associados às atividades extrativas agrícolas e agroflorestais. O segundo aspecto é a distribuição e o tipo de infraestrutura urbana, bem como o acesso aos serviços nos centros populacionais. Em particular, o segundo aspecto foca na validação do uso do sensor Visible Infrared Imaging Radiometer Suite Day/Night-Band (VIIRS/DNB) na detecção de níveis estáveis de radiância de luzes visíveis durante a noite ao longo do ano. Os levantamentos de campo foram realizados por meio de registros fotográficos, registros de observações e descrições da região, além de entrevistas com moradores, representantes de instituições e de localidades, bem como com responsáveis pelos estabelecimentos rurais. Também foram coletadas fotografias aéreas usando um Veículo Aéreo Não Tripulado (VANT). Foram também coletados dados de produção para 21 estabelecimentos rurais. Observou-se que 95% desses estabelecimentos coletam, cultivam e comercializam frutos de açaí, sendo que 76% dos estabelecimentos também cultivam outros produtos agrícolas. Imagens de VANT foram coletadas em 48 áreas. Essas imagens serão usadas para selecionar amostras rotuladas de classes de uso e cobertura da terra para processos de classificação de imagens, bem como para qualificar a infraestrutura urbana e ajudar a descrever as categorias de produção. Em relação à análise das luzes estáveis visíveis durante a noite, observou-se que 61% delas pertenciam a áreas particulares não relacionadas aos serviços de iluminação pública, enquanto 19% das luzes externas identificadas no campo não foram mapeadas como luzes estáveis. Esse resultado indica a necessidade de mais estudos para avaliar o potencial do uso de dados VIIRS/DNB como indicador de infraestrutura na Amazônia. Além disso, foram identificadas áreas de expansão urbana em Cametá e Mocajuba, das quais 26 foram visitadas e coletadas informações sobre educação, saúde, infraestrutura e condições de vida. Estas informações serão utilizadas para caracterizar, classificar e analisar a conectividade das localidades visitadas.

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.

Reducing the impacts of agriculture on the environment is one of the greatest challenges of this century. In Brazil, it is often argued that more land use change is needed to achieve food security. However, analyses seeking to understand the dynamics between agricultural production for exports and food intended for the Brazilian population have not approached the question if national agriculture is sufficient to provide Brazilians with the necessary nutrients, according to nutritional recommendations. In this sense, we sought to combine supply and dietary requirements for food (calories and nutrients) to assess trends in nutrient production and how future population projections and possible changes in diets would affect land necessity for nutritional security. We use sub-national data on agricultural production, population, Food Balance Sheets from FAO, and a compilation of nutritional information on the Brazilian agricultural production. Our results show that, in the last three decades, Brazil produced enough food calories to feed on average 115% of its population. We found that the agricultural land in 2017, without any expansion, is sufficient to feed, at least, 105% of projected population in 2060, considering the same productivity and dietary patterns. In a vegan diet scenario, less than 10% of the land dedicated to agricultural production in the past 30 years would be required. Despite limitations on supplying certain micro-nutrients, a vegan diet would require even less land in the future. We conclude that Brazilian agriculture could deliver enough food to meet Brazilians nutritional needs without further land expansion. Food production is compatible with environmental conservation in Brazil, especially if meat consumption is reduced.

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.