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• The 2019 wildfires raised global concern about wildfires, their causes and effects. • Fire has distinct roles in fire-prone and fire-sensitive ecosystems. • In fire-prone ecosystems, we need to overcome taboos regarding the use of fire. • In fire-sensitive systems, strategies to reduce fires are urgent. • Climate-change and increasing human impact change fire regimes. In the recent past, wildfires have received much attention both by science and by the media, especially in relation to deforestation, degradation and climate change and when affecting fire-sensitive ecosystems. On the other hand, fire is a natural process in many ecosystems, in particular those to be considered fire-dependent; here, maintaining natural fire regimes is important to maintain biodiversity and ecosystem services. In many regions of the world we are still in the need for a better understanding of fire effects on plant populations, communities and ecosystems. For instance, responses of individuals and populations to heat and fire can differ among distinct fire-prone ecosystems, and community level responses often vary depending on historical disturbance regimes or the fire regime as such. Effects on ecosystem processes, e.g. on carbon cycles, can vary greatly in scale and are even more difficult to predict. This adds up to uncertainties regarding appropriate fire management strategies, both in fire-prone and fire-sensitive ecosystems. Here, we introduce a set of opinion papers on fires in Brazil and a forthcoming Virtual Special Issue of Flora – Morphology, Distribution, Functional Ecology of Plants on "Fire and vegetation", with contributions expected from a broad range of topics related to fire, plants, and vegetation. This special issue will contribute to the development not only of more knowledge on fire effects on plants and vegetation, but also to advances in fire management policies in different ecosystems around the world. The main issue, after all, is to go beyond simple classification of fires as 'good' or 'bad', but rather to develop strategies to deal with changing fire regimes and their effects in a dynamic world increasingly modified by human actions. [ABSTRACT FROM AUTHOR]

Countries have pledged to different national and international environmental agreements, most prominently the climate change mitigation targets of the Paris Agreement. Accounting for carbon stocks and flows (fluxes) is essential for countries that have recently adopted the United Nations System of Environmental-Economic Accounting - ecosystem accounting framework (UNSEEA) as a global statistical standard. In this paper, we analyze how spatial carbon fluxes can be used in support of the UNSEEA carbon accounts in five case countries with available in-situ data. Using global multi-date biomass map products and other remotely sensed data, we mapped the 2010–2018 carbon fluxes in Brazil, the Netherlands, the Philippines, Sweden and the USA using National Forest Inventory (NFI) and local biomass maps from airborne LiDAR as reference data. We identified areas that are unsupported by the reference data within environmental feature space (6–47% of vegetated country area); cross-validated an ensemble machine learning (RMSE=9–39 Mg C ha - 1 and R 2 =0.16–0.71) used to map carbon fluxes with prediction intervals; and assessed spatially correlated residuals (<5 km) before aggregating carbon fluxes from 1-ha pixels to UNSEEA forest classes. The resulting carbon accounting tables revealed the net carbon sequestration in natural broadleaved forests. Both in plantations and in other woody vegetation ecosystems, emissions exceeded sequestration. Overall, our estimates align with FAO-Forest Resource Assessment and national studies with the largest deviations in Brazil and USA. These two countries used highly clustered reference data, where clustering caused uncertainty given the need to extrapolate to under-sampled areas. We finally provide recommendations to mitigate the effect of under-sampling and to better account for the uncertainties once carbon stocks and flows need to be aggregated in relatively smaller countries. These actions are timely given the global initiatives that aim to upscale UNSEEA carbon accounting. [ABSTRACT FROM AUTHOR]

Countries have pledged to different national and international environmental agreements, most prominently the climate change mitigation targets of the Paris Agreement. Accounting for carbon stocks and flows (fluxes) is essential for countries that have recently adopted the United Nations System of Environmental-Economic Accounting - ecosystem accounting framework (UNSEEA) as a global statistical standard. In this paper, we analyze how spatial carbon fluxes can be used in support of the UNSEEA carbon accounts in five case countries with available in-situ data. Using global multi-date biomass map products and other remotely sensed data, we mapped the 2010–2018 carbon fluxes in Brazil, the Netherlands, the Philippines, Sweden and the USA using National Forest Inventory (NFI) and local biomass maps from airborne LiDAR as reference data. We identified areas that are unsupported by the reference data within environmental feature space (6–47% of vegetated country area); cross-validated an ensemble machine learning (RMSE=9–39 Mg C ha - 1 and R 2 =0.16–0.71) used to map carbon fluxes with prediction intervals; and assessed spatially correlated residuals (<5 km) before aggregating carbon fluxes from 1-ha pixels to UNSEEA forest classes. The resulting carbon accounting tables revealed the net carbon sequestration in natural broadleaved forests. Both in plantations and in other woody vegetation ecosystems, emissions exceeded sequestration. Overall, our estimates align with FAO-Forest Resource Assessment and national studies with the largest deviations in Brazil and USA. These two countries used highly clustered reference data, where clustering caused uncertainty given the need to extrapolate to under-sampled areas. We finally provide recommendations to mitigate the effect of under-sampling and to better account for the uncertainties once carbon stocks and flows need to be aggregated in relatively smaller countries. These actions are timely given the global initiatives that aim to upscale UNSEEA carbon accounting. [ABSTRACT FROM AUTHOR]

Numerical models have been developed to investigate and understand responses of biogeochemical cycle to global changes. Steady state, when a system is in dynamic equilibrium, is generally required to initialize these model simulations. However, the spin‐up process that is used to achieve steady state pose a great burden to computational resources, limiting the efficiency of global modeling analysis on biogeochemical cycles. This study introduces a new Semi‐Analytical Spin‐Up (SASU) to tackle this grand challenge. We applied SASU to Community Land Model version 5 and examined its computational efficiency and accuracy. At the Brazil site, SASU is computationally 7 times more efficient than (or saved up to 86% computational cost in comparison with) the traditional native dynamics (ND) spin‐up to reach the same steady state. Globally, SASU is computationally 8 times more efficient than the accelerated decomposition spin‐up and 50 times more efficient than ND. In summary, SASU achieves the highest computational efficiency for spin‐up on site and globally in comparison with other spin‐up methods. It is generalizable to wide biogeochemical models and thus makes computationally costly studies (e.g., parameter perturbation ensemble analysis and data assimilation) possible for a better understanding of biogeochemical cycle under climate change. Plain Language Summary: Land carbon cycle models, a critical component of earth system models, have been developed to investigate and understand ecological responses to global changes. However, the model spin‐up process to achieve steady state are usually time‐consuming and pose great computational burden. The spin‐up problem hinders our ability to study some key issues in land carbon cycle modeling, such as sensitivity analysis. This paper applies a new SASU framework to accelerate spin‐up of Community Land Model matrix version 5. Compared with traditional native dynamic approach, SASU speeds up the spin‐up by approximately 50 times, achieving the fastest spin‐up speed than all the previously recorded methods. Our SASU method is applicable to biogeochemical models and, therefore, liberates the models for computationally costly studies, such as parameter perturbation ensemble analysis and data assimilation. Key Points: A new semi‐analytical spin‐up (SASU) framework combines the default accelerated spin‐up method and matrix analytical algorithmSASU accelerates CLIM5 spin‐up by tens of times, becoming the fastest method to our knowledgeSASU is applicable to most biogeochemical models and enables computationally costly study, for example, sensitivity analysis [ABSTRACT FROM AUTHOR]

This paper performs Fourier cointegration and causality tests to analyze the effect of renewable energy generation, globalization, and agricultural activities on ecological footprint and carbon dioxide (CO 2) emissions in BRIC countries for the period 1971–2016. The Fourier ADL cointegration test supports a long-run relationship between the considered variables in Brazil and China. The long-term elasticities indicate that globalization increases the pollution indicators, while renewable energy generation significantly reduces environmental pressure in China. Moreover, globalization increases CO 2 emissions, while renewable energy generation improves environmental quality in Brazil. The causality results show the existence of bidirectional causality between agriculture and environmental degradation; unidirectional relationships from globalization to the ecological footprint and CO 2 emissions; and renewable energy generation to the ecological indicators. Overall, these findings reveal the importance of renewable energy in combating environmental degradation. Based on the above results, renewable energy generation can significantly reduce environmental pollution in Brazil and China. However, renewable energy does not affect environmental pressure in Russia and India. Therefore, these countries should differentiate the current renewable energy generation policies to achieve their sustainable development goals. [ABSTRACT FROM AUTHOR]

Abstract: The purpose of this paper is to describe the benefits of sugar cane ethanol in Brazil, appointing the productivity of this type of fuel based on hectares of plantation, its carbon dioxide cycle and the contribution to reduce the greenhouse effect. In the following step the uses of ethanol for hydrogen production by steam reforming is analyzed and some comparison with natural gas steam reforming is performed. The sugar cane industry in Brazil, in a near future, in the hydrogen era, could be modified according to our purpose, since besides the production of sugar, and ethylic and anhydric alcohol, Brazilian sugar cane industry will also be able to produce biohydrogen. Fuel cells appear like a promising technology for energy generation. Among several technologies in the present, the PEMFC (proton exchange membrane fuel cell) is the most appropriate for vehicles application, because it combines durability, high power density, high efficiency, good response and it works at relatively low temperatures. Besides that it is easy to turn it on and off and it is able to support present vibration in vehicles. A PEMFC''s problem is the need of noble catalysts like platinum. Another problem is that CO needs to be in low concentration, requiring a more clean hydrogen to avoid fuel cell deterioration. One part of this paper was developed in Stockholm, where there are some buses within the CUTE (clean urban transport for Europe) project that has been in operation with FC since January 2004. Another part was developed in Guaratinguetá, Brazil. Brazil intends to start up a program of FC buses. As conclusion, this paper shows the economical analysis comparing buses moved by fuel cells using hydrogen by different kinds of production. Electrolyze with wind turbine, natural gas steam reforming and ethanol steam reforming. [Copyright &y& Elsevier]

An accurate estimate of carbon fluxes associated with tropical deforestation from the last two decades is needed to balance the global carbon budget. Several studies have already estimated carbon emissions from tropical deforestation, but the estimates vary greatly and are difficult to compare due to differences in data sources, assumptions, and methodologies. In this paper, we review the different estimates and datasets, and the various challenges associated with comparing them and with accurately estimating carbon emissions from deforestation. We performed a simulation study over legal Amazonia to illustrate some of these major issues. Our analysis demonstrates the importance of considering land-cover dynamics following deforestation, including the fluxes from reclearing of secondary vegetation, the decay of product and slash pools, and the fluxes from regrowing forest. It also suggests that accurate carbon-flux estimates will need to consider historical land-cover changes for at least the previous 20 years. However, this result is highly sensitive to estimates of the partitioning of cleared carbon into instantaneous burning vs. Long-timescale slash pools. We also show that carbon flux estimates based on ‘committed flux’ calculations, as used by a few studies, are not comparable with the ‘annual balance’ calculation method used by other studies. [ABSTRACT FROM AUTHOR]