Amazon forest biomass density maps: tackling the uncertainty in carbon emission estimates

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Season changes in water quality and Sargassum biomass in Southwest Australia

Sargassum C. Agardh is one of the most diverse genera of marine macro-algae and commonly inhabits shallow tropical and sub-tropical waters. This study aimed to investigate the effect of seasonality and the associated water quality changes on the distribution, canopy cover, mean thallus length and the biomass of Sargassum beds around Point Peron, Shoalwater Islands Marine Park, Southwest Australia. Samples of Sargassum and seawater were collected every three months from summer 2012 to summer 2014 from four different reef zones. A combination of in situ observations and WorldView-2 satellite remote-sensing images were used to map the spatial distribution of Sargassum beds and other associated benthic habitats. The results demonstrated a strong seasonal variation in the environmental parameters, canopy cover, mean thallus length, and biomass of Sargassum, which were significantly (P < 0.05) influenced by the nutrient concentration (PO43-, NO3-, NH4+) and rainfall. However, no variation in any studied parameter was observed among the four reef zones. The highest Sargassum biomass peaks occurred between late spring and early summer (from September to January). The results provide essential information to guide effective conservation and management, as well as sustainable utilisation of this coastal marine renewable resource.

Occurrence, abundance and biomass of photo- and heterotrophic plankton in Norwegian coastal waters

The purpose of the present study was to explore the composition and variation of the pico-, nano- and micro-plankton communities in Norwegian coastal waters and Skagerrak, and the co-occurrence of bacteria and viruses. Samples were collected along three cruise transects from Jaeren, Lista and Oksoy on the south coast of Norway and into the North Sea and Skagerrak. We also followed a drifting buoy for 55 h in Skagerrak in order to observe diel variations. Satellite ocean color images (SeaWiFS) of the chlorophyll a (chl a) distribution compared favorably to in situ measurements in open waters, while closer to the shore remote sensing chl a data was overestimated compared to the in situ data. Using light microscopy, we identified 49 micro- and 15 nanoplankton sized phototrophic forms as well as 40 micro- and 12 nanoplankton sized heterotrophic forms. The only picoeukaryote (0.2-2.0 µm) we identified was Resultor micron (Pedinophyceae). Along the transects a significant variation in the distribution and abundance of different plankton forms were observed, with Synechococcus spp and autotrophic picoeukaryotes as the most notable examples. There was no correlation between viruses and chl a, but between viruses and bacteria, and between viruses and some of the phytoplankton groups, especially the picoeukaryotes. Moreover, there was a negative correlation between nutrients and small viruses (Low Fluorescent Viruses) but a positive correlation between nutrients and large viruses (High Fluorescent Viruses). The abundance of autotrophic picoplankton, bacteria and viruses showed a diel variation in surface waters with higher values around noon and late at night and lower values in the evening. Synechococcus spp were found at 20 m depth 25-45 nautical miles from shore apparently forming a bloom that stretched out for more than 100 nautical miles from Skagerrak and up the south west coast of Norway. The different methods used for assessing abundance, distribution and diversity of microorganisms yielded complementary information about the plankton community. Flow cytometry enabled us to map the distribution of the smaller phytoplankton forms, bacteria and viruses in more detail than has been possible before but detection and quantification of specific forms (genus or species) still requires taxonomic skills, molecular analysis or both.

Mapping Height and Biomass of Mangrove Forests in Everglades National Park with SRTM Elevation Data

We produced a landscape scale map of mean tree height in mangrove forests in Everglades National Park (ENP) using the elevation data from the Shuttle Radar Topography Mission (SRTM). The SRTM data was calibrated using airborne lidar data and a high resolution USGS digital elevation model (DEM). The resulting mangrove height map has a mean tree height error of 2.0 m (RMSE) over a pixel of 30 m. In addition, we used field data to derive a relationship between mean forest stand height and biomass in order to map the spatial distribution of standing biomass of mangroves for the entire National Park. The estimation showed that most of the mangrove standing biomass in the ENP resides in intermediate- height mangrove stands around 8 m. We estimated the total mangrove standing biomass in ENP to be 5.6 X 109 kg.

Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present collection presents the original data sets used to compile Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates

Global distributions of diazotrophs abundance and biomass - Depth integrated values computed from a collection of source datasets - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. The present data set presents depth integrated values of diazotrophs abundance and biomass, computed from a collection of source data sets.

Global distributions of diazotrophs abundance, biomass and nitrogen fixation rates - Gridded data product (NetCDF) - Contribution to the MAREDAT World Ocean Atlas of Plankton Functional Types

The MAREDAT atlas covers 11 types of plankton, ranging in size from bacteria to jellyfish. Together, these plankton groups determine the health and productivity of the global ocean and play a vital role in the global carbon cycle. Working within a uniform and consistent spatial and depth grid (map) of the global ocean, the researchers compiled thousands and tens of thousands of data points to identify regions of plankton abundance and scarcity as well as areas of data abundance and scarcity. At many of the grid points, the MAREDAT team accomplished the difficult conversion from abundance (numbers of organisms) to biomass (carbon mass of organisms). The MAREDAT atlas provides an unprecedented global data set for ecological and biochemical analysis and modeling as well as a clear mandate for compiling additional existing data and for focusing future data gathering efforts on key groups in key areas of the ocean. This is a gridded data product about diazotrophic organisms . There are 6 variables. Each variable is gridded on a dimension of 360 (longitude) * 180 (latitude) * 33 (depth) * 12 (month). The first group of 3 variables are: (1) number of biomass observations, (2) biomass, and (3) special nifH-gene-based biomass. The second group of 3 variables is same as the first group except that it only grids non-zero data. We have constructed a database on diazotrophic organisms in the global pelagic upper ocean by compiling more than 11,000 direct field measurements including 3 sub-databases: (1) nitrogen fixation rates, (2) cyanobacterial diazotroph abundances from cell counts and (3) cyanobacterial diazotroph abundances from qPCR assays targeting nifH genes. Biomass conversion factors are estimated based on cell sizes to convert abundance data to diazotrophic biomass. Data are assigned to 3 groups including Trichodesmium, unicellular diazotrophic cyanobacteria (group A, B and C when applicable) and heterocystous cyanobacteria (Richelia and Calothrix). Total nitrogen fixation rates and diazotrophic biomass are calculated by summing the values from all the groups. Some of nitrogen fixation rates are whole seawater measurements and are used as total nitrogen fixation rates. Both volumetric and depth-integrated values were reported. Depth-integrated values are also calculated for those vertical profiles with values at 3 or more depths.

Towards A Deeper Understanding Of Structural Biomass Recalcitrance Using Phase-contrast Tomography.

The development of technological routes to convert lignocellulosic biomass to liquid fuels requires an in-depth understanding of the cell wall architecture of substrates. Essential pretreatment processes are conducted to reduce biomass recalcitrance and usually increase the reactive surface area. Quantitative three-dimensional information about both bulk and surface structural features of substrates needs to be obtained to expand our knowledge of substrates. In this work, phase-contrast tomography (PCT) was used to gather information about the structure of a model lignocellulosic biomass (piassava fibers). The three-dimensional cellular organization of piassava fibers was characterized by PCT using synchrotron radiation. This technique enabled important physical features that describe the substrate piassava fibers to be visualized and quantified. The external surface area of a fiber and internal surface area of the pores in a fiber could be determined separately. More than 96% of the overall surface area available to enzymes was in the bulk substrate. The pore surface area and length exhibited a positive linear relationship, where the slope of this relationship depended on the plant tissue. We demonstrated that PCT is a powerful tool for the three-dimensional characterization of the cell wall features related to biomass recalcitrance. Original and relevant quantitative information about the structural features of the analyzed material were obtained. The data obtained by PCT can be used to improve processing routes to efficiently convert biomass feedstock into sugars.

Biomass Refinery as a Renewable Complement to the Petroleum Refinery

Biomass Refinery is a sequential of eleven thermochemical processes and one biological process with two initial basic treatments: prehydrolysis for lignocellulosics and low temperature conversion for biomass with medium-to-high content of lipids and proteins. The other ten processes are: effluent treatment plant, furfural plant, biodiesel plant, cellulignin dryer, calcination, fluidized bed boiler, authotermal reforming of cellulignin for syngas production, combined cycle of two-stroke low-speed engine or syngas turbine with fluidized bed boiler heat recovery, GTL technologies and ethanol from cellulose, prehydrolysate and syngas. Any kind of biomass such as wood, agricultural residues, municipal solid waste, seeds, cakes, sludges, excrements and used tires can be processed at the Biomass Refinery. Twelve basic products are generated such as cellulignin, animal feed, electric energy, fuels (ethanol, crude oil, biodiesel, char), petrochemical substitutes, some materials (ash, gypsum, fertilizers, silica, carbon black) and hydrogen. The technology is clean with recovery of energy and reuse of water, acid and effluents. Based on a holistic integration of various disciplines Biomass Refinery maximizes the simultaneous production of food, electric energy, liquid fuels and chemical products and some materials, achieving a competitive position with conventional and fossil fuel technologies, as well as payment capacity for biomass production. Biomass Refinery has a technical economical capability to complement the depletion of the conventional petroleum sources and to capture its GHGs resulting a biomass + petroleum ""green"" combination.

Genotoxic potential generated by biomass burning in the Brazilian Legal Amazon by Tradescantia micronucleus bioassay: a toxicity assessment study

Background: The Brazilian Amazon has suffered impacts from non-sustainable economic development, especially owing to the expansion of agricultural commodities into forest areas. The Tangara da Serra region, located in the southern of the Legal Amazon, is characterized by non-mechanized sugar cane production. In addition, it lies on the dispersion path of the pollution plume generated by biomass burning. The aim of this study was to assess the genotoxic potential of the atmosphere in the Tangara da Serra region, using Tradescantia pallida as in situ bioindicator. Methods: The study was conducted during the dry and rainy seasons, where the plants were exposed to two types of exposure, active and passive. Results: The results showed that in all the sampling seasons, irrespective of exposure type, there was an increase in micronucleus frequency, compared to control and that it was statistically significant in the dry season. A strong and significant relationship was also observed between the increase in micronucleus incidence and the rise in fine particulate matter, and hospital morbidity from respiratory diseases in children. Conclusions: Based on the results, we demonstrated that pollutants generated by biomass burning in the Brazilian Amazon can induce genetic damage in test plants that was more prominent during dry season, and correlated with the level of particulates and elevated respiratory morbidity.

Impact of outdoor biomass air pollution on hypertension hospital admissions

Background This study aimed to evaluate the association between the total suspended particles (TSP) generated from burning sugar cane plantations and the incidence of hospital admissions from hypertension in the city of Araraquara. Methods The study was an ecological time-series study. Total daily records of hypertension (ICD 10th I10-15) were obtained from admitted patients of all ages in a hospital in Araraquara, Sao Paulo State, Brazil, from 23 March 2003 to 27 July 2004. The daily concentration of TSP (mu g/m(3)) was obtained using a Handi-Vol sampler placed in downtown Araraquara. The local airport provided daily measures of temperature and humidity. In generalised linear Poisson regression models, the daily number of hospital admissions for hypertension was considered to be the dependent variable and the daily TSP concentration the independent variable. Results TSP presented a lagged effect on hypertension admissions, which was first observed 1 day after a TSP increase and remained almost unchanged for the following 2 days. A 10 mu g/m(3) increase in the TSP 3 day moving average lagged in 1 day led to an increase in hypertension-related hospital admissions during the harvest period (12.5%, 95% CI 5.6% to 19.9%) that was almost 30% higher than during non-harvest periods (9.0%, 95% CI 4.0% to 14.3%). Conclusions Increases in TSP concentrations were associated with hypertension-related hospital admissions. Despite the benefits of reduced air pollution in urban cities achieved by using ethanol produced from sugar cane to power automobiles, areas where the sugar cane is produced and harvested were found to have increased public health risk.

The Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) - Part 2: Model sensitivity to the biomass burning

We describe an estimation technique for biomass burning emissions in South America based on a combination of remote-sensing fire products and field observations, the Brazilian Biomass Burning Emission Model (3BEM). For each fire pixel detected by remote sensing, the mass of the emitted tracer is calculated based on field observations of fire properties related to the type of vegetation burning. The burnt area is estimated from the instantaneous fire size retrieved by remote sensing, when available, or from statistical properties of the burn scars. The sources are then spatially and temporally distributed and assimilated daily by the Coupled Aerosol and Tracer Transport model to the Brazilian developments on the Regional Atmospheric Modeling System (CATT-BRAMS) in order to perform the prognosis of related tracer concentrations. Three other biomass burning inventories, including GFEDv2 and EDGAR, are simultaneously used to compare the emission strength in terms of the resultant tracer distribution. We also assess the effect of using the daily time resolution of fire emissions by including runs with monthly-averaged emissions. We evaluate the performance of the model using the different emission estimation techniques by comparing the model results with direct measurements of carbon monoxide both near-surface and airborne, as well as remote sensing derived products. The model results obtained using the 3BEM methodology of estimation introduced in this paper show relatively good agreement with the direct measurements and MOPITT data product, suggesting the reliability of the model at local to regional scales.