883 resultados para Traffic emissions
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The Iowa Highway Research Board has identified the development of a simplified handbook of transportation studies as a high priority for the state of Iowa. The Center for Transportation Research and Education (CTRE) at Iowa State University was chosen to develop such a handbook. A well-executed, well-documented study is critical in the decision-making process for many transportation-related projects and in reporting to elected officials and members of the community. As more research is conducted in the area of transportation, study procedures in many cases have become more complex. It is often difficult for local jurisdictions with limited staff, training, experience, and time availability to perform these studies. The most commonly used publication for traffic studies is geared toward transportation professionals and professional engineers. That defining document, Manual of Transportation Studies (Institute of Transportation Engineers, 2000), is over 500 pages and includes several dozen types of transportation studies. Many of the transportation studies described in the manual are rarely (if ever) used by local jurisdictions. Further, those studies that are frequently used are at times very complex and possibly very costly to perform exactly as described. Local jurisdictions without the staff expertise to understand and apply the manual’s various studies have a need for a simplified handbook of procedures to perform common traffic studies themselves or properly define a scope of work to hire a consultant to perform the studies. This handbook describes simplified procedures that are easy to apply and are written for all potential users (civil engineers and traffic engineers, public works mangers, city managers and attorneys, and the general public).
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Vehicle Traffic Map produced by the Iowa Department of Transportation.
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Vehicle Traffic Map produced by the Iowa Department of Transportation.
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Vehicle Traffic Map produced by the Iowa Department of Transportation.
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The soil CO2 emission has high spatial variability because it depends strongly on soil properties. The purpose of this study was to (i) characterize the spatial variability of soil respiration and related properties, (ii) evaluate the accuracy of results of the ordinary kriging method and sequential Gaussian simulation, and (iii) evaluate the uncertainty in predicting the spatial variability of soil CO2 emission and other properties using sequential Gaussian simulations. The study was conducted in a sugarcane area, using a regular sampling grid with 141 points, where soil CO2 emission, soil temperature, air-filled pore space, soil organic matter and soil bulk density were evaluated. All variables showed spatial dependence structure. The soil CO2 emission was positively correlated with organic matter (r = 0.25, p < 0.05) and air-filled pore space (r = 0.27, p < 0.01) and negatively with soil bulk density (r = -0.41, p < 0.01). However, when the estimated spatial values were considered, the air-filled pore space was the variable mainly responsible for the spatial characteristics of soil respiration, with a correlation of 0.26 (p < 0.01). For all variables, individual simulations represented the cumulative distribution functions and variograms better than ordinary kriging and E-type estimates. The greatest uncertainties in predicting soil CO2 emission were associated with areas with the highest estimated values, which produced estimates from 0.18 to 1.85 t CO2 ha-1, according to the different scenarios considered. The knowledge of the uncertainties generated by the different scenarios can be used in inventories of greenhouse gases, to provide conservative estimates of the potential emission of these gases.
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The correct use of closed field chambers to determine N2O emissions requires defining the time of day that best represents the daily mean N2O flux. A short-term field experiment was carried out on a Mollisol soil, on which annual crops were grown under no-till management in the Pampa Ondulada of Argentina. The N2O emission rates were measured every 3 h for three consecutive days. Fluxes ranged from 62.58 to 145.99 ∝g N-N2O m-2 h-1 (average of five field chambers) and were negatively related (R² = 0.34, p < 0.01) to topsoil temperature (14 - 20 ºC). N2O emission rates measured between 9:00 and 12:00 am presented a high relationship to daily mean N2O flux (R² = 0.87, p < 0.01), showing that, in the study region, sampling in the mornings is preferable for GHG.
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Plants constantly adjust their repertoire of plasma membrane proteins that mediates transduction of environmental and developmental signals as well as transport of ions, nutrients, and hormones. The importance of regulated secretory and endocytic trafficking is becoming increasingly clear; however, our knowledge of the compartments and molecular machinery involved is still fragmentary. We used immunogold electron microscopy and confocal laser scanning microscopy to trace the route of cargo molecules, including the BRASSINOSTEROID INSENSITIVE1 receptor and the REQUIRES HIGH BORON1 boron exporter, throughout the plant endomembrane system. Our results provide evidence that both endocytic and secretory cargo pass through the trans-Golgi network/early endosome (TGN/EE) and demonstrate that cargo in late endosomes/multivesicular bodies is destined for vacuolar degradation. Moreover, using spinning disc microscopy, we show that TGN/EEs move independently and are only transiently associated with an individual Golgi stack.
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The cultivation of sugarcane with intensive use of machinery, especially for harvest, induces soil compaction, affecting the crop development. The control of agricultural traffic is an alternative of management in the sector, with a view to preserve the soil physical quality, resulting in increased sugarcane root growth, productivity and technological quality. The objective of this study was to evaluate the physical quality of an Oxisol with and without control traffic and the resulting effects on sugarcane root development, productivity and technological quality. The following managements were tested: no traffic control (NTC), traffic control consisting of an adjustment of the track width of the tractor and sugarcane trailer (TC1) and traffic control consisting of an adjustment of the track width of the tractor and trailer and use of an autopilot (TC2). Soil samples were collected (layers 0.00-0.10; 0.10-0.20 and 0.20-0.30 m) in the plant rows, inter-row center and seedbed region, 0.30 m away from the plant row. The productivity was measured with a specific weighing scale. The technological variables of sugarcane were measured in each plot. Soil cores were collected to analyze the root system. In TC2, the soil bulk density and compaction degree were lowest and total porosity and macroporosity highest in the plant row. Soil penetration resistance in the plant row, was less than 2 MPa in TC1 and TC2. Soil aggregation and total organic carbon did not differ between the management systems. The root surface and volume were increased in TC1 and TC2, with higher productivity and sugar yield than under NTC. The sugarcane variables did not differ between the managements. The soil physical quality in the plant row was preserved under management TC1 and TC2, with an improved root development and increases of 18.72 and 20.29 % in productivity and sugar yield, respectively.
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Traffic volumes represented on this map are annual average daily traffic volumes between major traffic generators: highway junctions and cities.
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Traffic volumes represented on this map are annual average daily traffic volumes between major traffic generators: highway junctions and cities.
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Traffic volumes represented on this map are annual average daily traffic volumes between major traffic generators: highway junctions and cities.
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Traffic volumes represented on this map are annual average daily traffic volumes between major traffic generators: highway junctions and cities.
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Traffic volumes represented on this map are annual average daily traffic volumes between major traffic generators: highway junctions and cities.
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Traffic volumes represented on this map are annual average daily traffic volumes between major traffic generators: highway junctions and cities.