Estudo da poluição pontual e difusa na bacia de contribuição do reservatório da usina hidrelétrica de Funil utilizando modelagem espacialmente distribuída em Sistema de Informação Geográfica

RESUMO Este estudo avaliou o potencial poluidor da bacia de contribuição do reservatório de Funil (BCRF), localizado na bacia hidrográfica do rio Paraíba do Sul, considerando a geração da carga de nutrientes, nitrogênio (N) e fósforo (P), por fontes pontuais e difusas, a partir de uma modelagem distribuída utilizando Sistema de Informação Geográfica (SIG). As cargas e concentrações médias anuais desses nutrientes foram geradas a partir do acoplamento de equações empíricas, em SIG, considerando informações espaciais de uso e cobertura do solo, população residente na bacia e vazão média anual de longo período, obtida por equações do tipo chuva vazão. Os resultados indicaram que 80% da carga total de nitrogênio foram provenientes de fontes pontuais e 20% de fontes difusas, enquanto que, da carga total de fósforo, 89,1% foram originadas de fontes pontuais e 10,9% de fontes difusas. As concentrações de nutrientes estimadas pelo modelo empírico apresentaram bons ajustes em relação aos valores observados de fósforo e de nitrogênio no rio Paraíba do Sul, com R²=0,96 (p<0,01) e R²=0,70 (p<0,01), respectivamente. Dessa forma, o modelo foi capaz de detectar, de forma significativa, a tendência das variações nas concentrações de nutrientes ao longo de diferentes trechos da BCRF

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Estimating future scenarios for farm–watershed nutrient fluxes using dynamic simulation modelling

A dynamic model of phosphorus (P) movement through the Peel-Harvey watershed in South Western Australia was developed using STELLA dynamic modelling software. The model was developed to provide a means to illustrate watershed P flux and of predicting future P loss scenarios. Model input parameters were sourced from extensive surveys of local agricultural practices and regional soil testing data. Model P-routing routines were developed from the known interactions between the various watershed P compartments and fluxes between various P stores. The model simulated a 200. year time-frame to reflect 100. years to the present day since initial land development, and forecast 100. years into the future. Although the watershed has an annual P loss target of 70. tonnes per annum (tpa), the measured present day loss is double this amount (140. tpa) and is projected to rise to 1600. tpa if current land management practices continue. This has significant implications for both future land use and subsequent water quality in the watershed

Estimating farm to catchment nutrient fluxes using dynamic simulation modelling – Can agri-environmental BMPs really do the job?

A dynamic model of Phosphorus (P) movement through the Peel-Harvey catchment in South Western Australia was developed using system dynamics modelling software. The model was developed to illustrate watershed P flux and to predict future P loss rates under a range of management scenarios. Model input parameters were sourced from extensive surveys of local agricultural practices and regional soil testing data. Model P-routing routines were developed from the known interactions between the various watershed P compartments and fluxes between the various P stores. Phosphorus-retention characteristics of a variety of management practices were determined from local field trials where available and published values where not. The model simulated a 200 year time frame to reflect 100 years to the present day since initial land development, and forecast 100 years into the future. Although the catchment has an annual P-loss target of 70 tonnes per annum (tpa), the measured (and modelled) present-day loss is double this amount (140tpa) and this is projected to rise to 1300tpa if current land management practices continue. Broad implementation of neither "biological" BMPs such as perennial pastures and managed riparian zones, or of "chemical" BMPs such as reduced water solubility fertilisers and P-retentive soil amendments, produces reductions in P-loss from present-day levels. Even if broad-scale implementation of the large suite of BMPs tested in this research occurs, catchment P-losses are likely to increase from the present level of 140tpa to approximately 200tpa over the next 100 years. This has significant implications for both future land use and subsequent water quality in the catchment as well as questioning the wisdom and perceptions of efficacy of past and future BMP implementation strategies

Estimating future scenarios for farm-watershed nutrient fluxes using dynamic simulation modelling – Cac on-farm BMPs really do the job at the watershed scale?

A dynamic model of Phosphorus (P) movement through the Peel-Harvey Watershed in South Western Australia was developed using STELLA dynamic modelling software. The model was developed to illustrate watershed P flux and to predict future P loss rates under a range of management scenarios. Input parameters were sourced from surveys of local agricultural practices and regional soil testing data. Model P-routing routines were developed from the known interactions between the various watershed P compartments and fluxes between various P stores. P-retention characteristics of a variety of management practices were determined from field trials where available and published values where not. The model simulated a 200 year time frame to reflect 100 years to the present day since initial land development, and forecast 100 years into the future. Although the watershed has an annual P loss target of 70 tonnes per annum (tpa), the measured present day loss is double this amount (140 tpa) and this is projected to rise to 1300 tpa if current land management practices continue. Even if broad-scale BMP implementation occurs, P losses are likely to increase to approximately 200 tpa. This has significant implications for both future land use and subsequent water quality in the watershed