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Scholars have often applied the concept of boundary work and its conceptual progeny to explain how science, policy, and practice collaborate to introduce change into agrifood systems. However, previous studies focused primarily on specific boundary elements (i.e., boundary spanners, boundary organizations, and boundary objects) or particular innovation processes (in terms of scope or timescale) within broad transformative change. This study aims to deepen the understanding of long-term transformative processes in agri-food systems by looking at how boundary infrastructures influenced the evolution of the Brazilian pig production system from a setting in which it mainly produced pork lard for a domestic market to a setting of being integrated in global supply chains and following international standards. Mainly, we add to the extant literature by highlighting that boundary infrastructures influenced the longterm transformative process experienced by BPPS by establishing a space where science-policy-practice interactions legitimized particular visions and values and instilled responsibility and accountability to spur various joint actions in support of innovation. We also contribute to the extant literature by showing that boundary infrastructures evolution in BPPS was incremental, long-term, multi-site, and with intertwined leverage. Boundary infrastructures provide structuration to system transformation and are also (re)structured while transitions unfold. Since boundary infrastructures have a certain directionality and may become hegemonic and exclusionary, this requires sensitiveness to the need to reorient a hegemonic boundary infrastructure or create a parallel one. Our study deepens the understanding of how coordination unfolds in long-term transformative processes, a topic deemed of interest given current debates on promoting agri-food systems transformation. We argue that better awareness of boundary infrastructures in which science-policy-practice interactions occur can help guide the direction of innovation to support sustainability transitions in agri-food systems. • An expanded boundary work view is applied to analyze changes in an agri-food system. • Boundary elements in an infrastructure are highly intertwined and complementary. • Interactions between boundary infrastructure elements play a role in long-term changes. • Boundary infrastructure evolves through a 'mutual structuration process'. • Boundary infrastructure sheds light on political dynamics and inclusion and exclusion. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic (SARS-CoV-2 virus) is the global crisis of our time. The absence of mass testing and the relevant presence of asymptomatic individuals causes the available data of the COVID-19 pandemic in Brazil to be largely under-reported regarding the number of infected individuals and deaths. We develop an adapted Susceptible-Infected-Recovered (SIR) model, which explicitly incorporates the under-reporting and the response of the population to public health policies (confinement measures, widespread use of masks, etc). Large amounts of uncertainty could provide misleading predictions of the COVID-19 spread. In this paper, we discuss the role of uncertainty in these model-based predictions, which is illustrated regarding three key aspects: (i) Assuming that the number of infected individuals is under-reported, we demonstrate anticipation regarding the infection peak. Furthermore, while a model with a single class of infected individuals yields forecasts with increased peaks, a model that considers both symptomatic and asymptomatic infected individuals suggests a decrease of the peak of symptomatic cases. (ii) Considering that the actual amount of deaths is larger than what is being registered, we demonstrate an increase of the mortality rates. (iii) When we consider generally under-reported data, we demonstrate how the transmission and recovery rate model parameters change qualitatively and quantitatively. We also investigate the "the uncertainty tripod": under-reporting level in terms of cases, deaths, and the true mortality rate of the disease. We demonstrate that if two of these factors are known, the remainder can be inferred, as long as proportions are kept constant. The proposed approach allows one to determine the margins of uncertainty by assessments on the observed and true mortality rates. [ABSTRACT FROM AUTHOR]

Abstract: This article aims to investigate the introduction, sustenance and consolidation of bioethanol in Brazil. It presents an analysis of its introductory stage, from the first decades of the 20th century until the early 1970s, when, in a second stage, additional measures allowed for its consolidation and maturity, under the widely known Proalcool. The paper presents a historical reinterpretation of the policies, mechanisms and instruments adopted in both stages, aiming to highlight the economical and political links. It is concluded that the interests of the agrarian elites, operating at the political level, and the fuel supply crisis during Second World War were basic during the first stage, to sustain a productive and logistic capacity and maintain ethanol alive as an automotive fuel. It is also concluded that the launching of Proalcool represented a transition combining the interests of the sugarcane agribusiness, burdened by the drop in sugar prices, and the need to equilibrate the balance of payments due to the oil shocks of the 1970s. Ethanol supply shocks harmed its credibility and its commercial consolidation was only possible through the introduction of flex-fuel vehicles with expectations strongly relying on climate change mitigation actions. [Copyright &y& Elsevier]

• Five precipitation datasets were evaluated on 714 basins across Brazil. • CHIRPS, MERRA-2 and IMERG excelled in hydrological simulations. • Hydrologic modelling presented KGE > 0.5 for 78 % of the catchments. • The worst hydrological performances were in the most arid hydrographic regions. • Parameter sensitivity varies with catchment climate and aridity. Satellite-based and reanalysis precipitation products are widely adopted as complementary information to in situ measurements for estimating river discharge using hydrological modelling. However, there is still a notable research gap in the literature associated with assessing the accuracy of satellite-based or reanalysis products in different tropical and sub-tropical catchments at large-sampling hydrological modelling with sensitivity analysis. We investigated the accuracy of precipitation, hydrological model performance and parameter sensitivity related to seven precipitation data sets based on satellite and reanalysis products, i.e., CHIRPS, TRMM, GLDAS, IMERG, MERRA-2, PERSIANN-CDR, and ERA5 over 714 contrasting tropical and subtropical catchments located in Brazil. We used the Génie Rural Journalier 4 (GR4J) hydrological model to simulate the hydrological processes of the different catchments with two approaches for the calibration: using measured ground-based precipitation data (approach I) or using each individual satellite/reanalysis precipitation products (approach II) to calibrate the models. The results showed that the precipitation products tend to overestimate precipitation, with the exception of ERA5 and MERRA-2. CHIRPS is the only product that produces unbiased precipitation estimates for most catchments. The model calibration using each precipitation product individually improved the hydrological model performance. CHIRPS, IMERG, and MERRA-2 showed good accuracy in terms of both, precipitation estimation and hydrological simulation performance in the calibration period. In the validation period, the best products in terms of KGE were CHIRPS, IMERG and TRMM (KGE > 0.64). The errors in precipitation products are better compensated via hydrological modelling in wet regions. The model parameter sensitivity varies according to precipitation input, climate, and catchment aridity. Overall, all seven products exhibited their worst hydrological performance in arid regions. This study helps to improve our understanding of the catchment response in tropical and subtropical regions while also providing key insights into the reliability of satellite/reanalysis rainfall products for streamflow simulation. This study is valuable in hydrometeorological applications, climate change assessment, water resources and disaster management, especially in regions with a relatively sparse density of precipitation stations. [ABSTRACT FROM AUTHOR]

This paper formulates a Model Predictive Control (MPC) policy to mitigate the COVID-19 contagion in Brazil, designed as optimal On-Off social isolation strategy. The proposed optimization algorithm is able to determine the time and duration of social distancing policies in the country. The achieved results are based on data from the period between March and May of 2020, regarding the cumulative number of infections and deaths due to the SARS-CoV-2 virus. This dataset is assumably largely sub-notified due to the absence of mass testing in Brazil. Thus, the MPC is based on a SIR model which is identified using an uncertainty-weighted Least-Squares criterion. Furthermore, this model includes an additional dynamic variable that mimics the response of the population to the social distancing policies determined by the government, which affect the COVID-19 transmission rate. The proposed control method is set within a mixed-logical formalism, since the decision variable is forcefully binary (existence or the absence of social distance policy). A dwell-time constraint is included to avoid too frequent shifts between these two inputs. The achieved simulation results illustrate how such optimal control method would operate in practice, pointing out that no social distancing should be relaxed before mid August 2020. If relaxations are necessary, they should not be performed before this date and should be in small periods, no longer than 25 days. This paradigm would proceed roughly until January/2021. The results also indicate a possible second peak of infections, which has a forecast to the beginning of October. This peak can be reduced if the periods of days with relaxed social isolation measures are shortened. [ABSTRACT FROM AUTHOR]

The Amazon is the largest river by discharge volume and one of the most biodiverse biomes in the world. Lately, there has been a rapid increase of the urban population in the region, which has been translated into a growing emission of organic contaminants such as polycyclic aromatic hydrocarbons (PAHs) into surface water bodies. This study provides the most comprehensive evaluation of the PAH contamination levels in surface waters of the Amazon basin. We investigated the occurrence and potential sources of 16 priority PAHs and characterised their risks for freshwater ecosystems. For this, we took 40 water samples from different sites along the Brazilian part of the Amazon River, including three major tributaries, and smaller rivers crossing the main urban areas. The results of this study show that PAHs are widespread contaminants in rivers of the Brazilian Amazon. The sum of the total concentration of the 16 priority PAHs reached values of 134 ng L−1 in the Amazon River, and 163 ng L−1 near densely populated areas. On the other hand, the total PAH concentration was generally lower in the monitored tributaries. In most samples, the contamination pattern was dominated by high molecular weight PAHs, suggesting a major contribution of pyrogenic sources, although petrogenic contamination was also present in some locations near urban areas. We assessed ecological risks posed by PAH mixtures using a hazard index. The results indicated that PAH contamination is not likely to pose direct toxic effects for Amazonian freshwater organisms, however continued monitoring is recommended near densely populated areas. [Display omitted] • The presence of 16 priority PAHs was investigated in Amazonian surface waters. • PAHs were found in all samples, with total concentrations up to 163 ng L−1. • Higher concentrations were found next to large urban areas. • In most samples, PAH contamination was of pyrogenic origin. • PAHs may not directly harm Amazonian freshwater ecosystems. [ABSTRACT FROM AUTHOR]