Agricultural land use dynamics in the Brazilian Amazon based on remote sensing and census data

The potential impact of deforestation in the Brazilian Amazon on greenhouse gas emissions to the atmosphere calls for policies that take account of changes in forest cover. Although much research has focused on the location and effects of deforestation, little is known about the distribution and reasons for the agricultural uses that replace forest cover. We used Landsat TM-based deforestation and agricultural census data to generate maps of the distribution and proportion of four major agricultural land uses throughout the Brazilian Amazon in 1997 and 2007. We built linear and spatial regression models to assess the determinant factors of deforestation and those major agricultural land uses - pasture, temporary agriculture and permanent agriculture - for the states of Pará, Rondônia, and Mato Grosso. The data include 30 determinant factors that were grouped into two years (1996 and 2006) and in four categories: accessibility to markets, public policies, agrarian structure, and environment. We found an overall expansion of the total agricultural area between 1997 and 2007, and notable differences between the states of Pará, Rondônia, and Mato Grosso in land use changes during this period. Regression models for deforestation and pasture indicated that determinant factors such as distance to roads were more influential in 1997 than in 2007. The number of settled families played an important role in the deforestation and pasture, the effect was stronger in 2007 than 1997. Indigenous lands were significant in preventing deforestation in high-pressure areas in 2007. For temporary and permanent agricultures, our results show that in 1997 the effect of small farms was stronger than in 2007. The mapped land use time series and the models explain empirically the effects of land use changes across the region over one decade.     

Topodata: Brazilian full coverage refinement of SRTM data

This work presents the selection of a set of geostatistical coefficients suitable for a unified SRTM data refinement from 3″ to 1″ through kriging over the entire Brazilian territory. This selection aimed at data potential for geomorphometric derivations, given by the preservation of detailed geometric characteristics of the resulting digital elevation models (DEM), which are sensitive to refining procedures. The development contained a long-term experimentation stage, when data refinement through kriging was locally developed to support distinct regional projects, followed by a unified selection stage, where the acquired experience was applied to select a single and unified interpolation scheme. In this stage, the selected geostatistical models with promising performances were tested for unified refinement on 40 Brazilian areas with distinct geological settings. Tested areas encompass reliefs varying from mountainous to plain. The effects of data preparation were observed on the perception of patterns (texture and roughness), as well as of singularities (edges, peaks, thalwegs etc.). Results were evaluated mainly through the examination of shaded reliefs, transects and perspectives observed in different scales. Terrains with low slopes and small amplitudes had their DEM promptly affected by the refining methods, as opposed to mountainous terrains. The evaluation, unambiguously confirmed by all consulted interpreters, converged into a refining model with outstanding performance in all tested conditions.     

Nitrous oxide emissions from gasohol, ethanol and CNG light duty vehicles

A sample of 21 light duty vehicles powered by Otto cycle engines were tested on a chassis dynamometer to measure the exhaust emissions of nitrous oxide (N₂O). The tests were performed at the Vehicle Emission Laboratory of CETESB (Environmental Company of the State of Sao Paulo) using the US-FTP-75 (Federal Test Procedure) driving cycle. The sample tested included passenger cars running on three types of fuels used in Brazil: gasohol, ethanol and CNG. The measurement of N₂O was made using two methods: Non Dispersive InfraRed (NDIR) analyzer and Fourier Transform InfraRed spectroscopy (FTIR). Measurements of regulated pollutants were also made in order to establish correlations between N₂O and NO_x. The average N₂O emission factors obtained by the NDIR method was 78?±?41?mg.km^?1 for vehicles running with gasohol, 73?±?45?mg.km^?1 for ethanol vehicles and 171?±?69?mg.km^?1 for CNG vehicles. Seventeen results using the FTIR method were also obtained. For gasohol vehicles the results showed a good agreement between the two methods, with an average emission factor of 68?±?41?mg.km^?1. The FTIR measurement results of N₂O for ethanol and CNG vehicles were much lower than those obtained by the NDIR method. The emission factors were 17?±?10?mg.km^?1 and 33?±?17?mg.km^?1, respectively, possibly because of the interference of water vapor (present at a higher concentration in the exhaust gases of these vehicles) on measurements by the NDIR method.     

Detection and quantification of local anthropogenic and regional climatic transient signals in temperature logs from Czechia and Slovenia

The paper reports on detection and quantification of the impact of local anthropogenic structures and regional climatic changes on subsurface temperature field. The analyzed temperature records were obtained by temperature monitoring in a borehole in Prague-Spo?ilov (Czechia) and by repeated logging of a borehole in ?empeter (Slovenia). The observed data were compared with temperatures yielded by mathematical 3D time-variable geothermal models of the boreholes’ sites with the aim to decompose the observed transient component of the subsurface temperature into the part affected by construction of new buildings and other anthropogenic structures in surroundings of the boreholes and into the part affected by the ground surface temperature warming due to the surface air temperature rise. A direct human impact on the subsurface temperature warming was proved and contributions of individual anthropogenic structures to this change were evaluated. In the case of Spo?ilov, where the mean annual warming rate reached 0.034°C per year at the depth of 38.3?m during the period 1993–2008, it turned out that about half of the observed warming can be attributed to the air (ground) surface temperature change and half to the human activity on the surface in the immediate vicinity of the borehole. The situation is similar in ?empeter, where the effect of the recently built surface anthropogenic structures is detectable down to the depth of 80?m and the share of the anthropogenic signal on the non-stationary component of the observed subsurface temperature amounts to 30% at the depth of 50?m.     

Numerical simulation of the diurnal cycle of rainfall in SW Amazon basin during the 1999 rainy season: the role of convective trigger function

In continental areas, the maximum rainfall simulated with the Brazilian developments on the Regional Atmospheric Modeling System (BRAMS) occurs around 4?h earlier than the one observed with rain gauges. This work presents the successful implementation of a new convective trigger function (CTF) in the convective parameterization scheme used in BRAMS that corrects this misfit between model and observations. The importance of the CTF formulation on the diurnal cycle of rainfall over the Amazon Basin is reflected by the following numbers: Over Rondonia (SW Amazonia), the original version of BRAMS simulates the maximum rainfall at 1400 UTC (1000 LST), with the new CTF maximum shifting to 1800?UTC (1400?LST), while the S-band radar rainfall maximum is at 1900?UTC (1500?LST). This is attributed to two factors: (1) the new CTF is now coupled to the sensible and latent heat fluxes at surface; (2) during the early morning, the convective available potential energy is reduced.     

Methodology for the combination of sub-daily Earth rotation from GPS and VLBI observations

A combination procedure of Earth orientation parameters from Global Positioning System (GPS) and Very Long Baseline Interferometry (VLBI) observations was developed on the basis of homogeneous normal equation systems. The emphasis and purpose of the combination was the determination of sub-daily polar motion (PM) and universal time (UT1) for a long time-span of 13 years. Time series with an hourly resolution and a model for tidal variations of PM and UT1-TAI (dUT1) were estimated. In both cases, 14-day nutation corrections were estimated simultaneously with the ERPs. Due to the combination procedure, it was warranted that the strengths of both techniques were preserved. At the same time, only a minimum of de-correlating or stabilizing constraints were necessary. Hereby, a PM time series was determined, whose precision is mainly dominated by GPS observations. However, this setup benefits from the fact that VLBI delivered nutation and dUT1 estimates at the same time. An even bigger enhancement can be seen for the dUT1 estimation, where the high-frequency variations are provided by GPS, while the long term trend is defined by VLBI. The estimated combined tidal PM and dUT1 model was predominantly determined from the GPS observations. Overall, the combined tidal model for the first time completely comprises the geometrical benefits of VLBI and GPS observations. In terms of root mean squared (RMS) differences, the tidal amplitudes agree with other empirical single-technique tidal models below 4 μas in PM and 0.25 μs in dUT1. The noise floor of the tidal ERP model was investigated in three ways resulting in about 1 μas for diurnal PM and 0.07 μs for diurnal dUT1 while the semi-diurnal components have a slightly better accuracy.     

Rainfall trends in the Brazilian Amazon Basin in the past eight decades

Rainfall series at 18 stations along the major rivers of the Brazilian Amazon Basin, having data since 1920s or 1930s, are analyzed to verify if there are appreciable long-term trends. Annual, rainy-season, and dry-season rainfalls are individually analyzed for each station and for the region as a whole. Some stations showed positive trends and some negative trends. The trends in the annual rainfall are significant at only six stations, five of which reporting increasing trends (Barcelos, Belem, Manaus, Rio Branco, and Soure stations) and just one (Itaituba station) reporting decreasing trend. The climatological values of rainfall before and after 1970 show significant differences at six stations (Barcelos, Belem, Benjamin Constant, Iaurete, Itaituba, and Soure). The region as a whole shows an insignificant and weak downward trend; therefore, we cannot affirm that the rainfall in the Brazilian Amazon basin is experiencing a significant change, except at a few individual stations. Subregions with upward and downward trends are interspersed in space from the far eastern Amazon to western Amazon. Most of the seasonal trends follow the annual trends, thus, indicating a certain consistency in the datasets and analysis.     

Evaporation estimates from Nasser Lake, Egypt, based on three floating station data and Bowen ratio energy budget

Nasser Lake is located in a hyper-arid region in the south of Egypt. Evaporation is by far the most important factor in explaining the water losses from the lake. To obtain better management scenarios for Nasser Lake, an accurate estimation of the lake evaporation losses thus is essential. This paper presents an update of previous evaporation estimates, making use of local meteorological and hydrological data collected from instrumented platforms (floating weather stations) at three locations on the lake: at Raft, Allaqi, and Abusembel (respectively at 2, 75, and 280 km upstream of the Aswan High Dam). Results from six conventional evaporation quantification methods were compared with the values obtained by the Bowen ratio energy budget method (BREB). The results of the BREB method showed that there is no significant difference between the evaporation rates at Allaqi and Abusembel. At Raft, higher evaporation rates were obtained, which were assumed to be overestimated due to the high uncertainty of the Bowen ratio (BR) parameter. The average BR value at Allaqi and Abusembel was used to eliminate this overestimates evaporation. Variance-based sensitivity and uncertainty analyses on the BREB results were conducted based on quasi-Monte Carlo sequences (Latin Hypercube sampling). The standard deviation of the total uncertainty on the BREB evaporation rate was found to be 0.62 mm day^?1. The parameter controlling the change in stored energy, followed by the BR parameter, was found to be the most sensitive parameters. Several of the six conventional methods showed substantial bias when compared with the BREB method. These were modified to eliminate the bias. When compared to the BREB-based values, the Penman method showed most favorably for the daily time scale, while for the monthly scale, the Priestley–Taylor and the deBruin–Keijman methods showed best agreement. Differences in mean evaporation estimates of these methods (against the BREB method) were found to be in the range 0.14 and 0.36 mm day^?1. All estimates were based calculations at the daily time scale covering a 10-year period (1995–2004).     

Multivariate geostatistical application for climate characterization of Minas Gerais State, Brazil

The objective of the present study was to assess for Minas Gerais the cokriging methodology, in order to characterize the spatial variability of Thornthwaite annual moisture index, annual rainfall, and average annual air temperature, based on geographical coordinates, altitude, latitude, and longitude. The climatic element data referred to 39 INMET climatic stations located in the state of Minas Gerais and in nearby areas and the covariables altitude, latitude, and longitude to the SRTM digital elevation model. Spatial dependence of data was observed through spherical cross semivariograms and cross covariance models. Box–Cox and log transformation were applied to the positive variables. In these situations, kriged predictions were back-transformed and returned to the same scale as the original data. Trend was removed using global polynomial interpolation. Universal simple cokriging best characterized the climate variables without tendentiousness and with high accuracy and precision when compared to simple cokriging. Considering the satisfactory implementation of universal simple cokriging for the monitoring of climatic elements, this methodology presents enormous potential for the characterization of climate change impact in Minas Gerais state.     

Chemical characterization of fine particulate matter during peak PM10 episodes in Apulia (South Italy)

Some peak PM10 episodes, occurred during PM monitoring campaigns performed on October 2005 and February and June 2006 in Bari town, have been characterized. Moreover back trajectories of air masses and Principal Component Analyses were applied. Three of the peak PM10 episodes investigated were related to local emissions of primary pollutants during poor atmospheric dispersion conditions. The other two peak PM10 episodes considered are related with long range transport air masses toward Apulia region: in one case the chemical characterization and the back trajectories analysis indicate that high PM10 value detected is due to the Saharan dust advection in the Apulia region; in the other case air masses with different origin give rise to high PM10 value.Moreover PM10 daily mean concentrations, presented in this paper collected from January 2005 to August 2007 and obtained by automatic device in six stations of air quality monitoring networks in Bari territory, do not show a seasonal trend for PM10 concentrations, contrary to the PM10 trend shown in the towns of North Italy. This can be explained mostly considering that our region presents generally meteo-climatic conditions that favour pollutants dispersion.