Harris county used car sales tax,minister for water resources works and housing ghana,battery operated car online india - Videos Download

Things orleans - french quarter & , New orleans shopping explore great shopping just steps away from hotel monteleone french market.
In order to answer the first two study questions listed previously, ERG began the process of re-creating, using MOVES, the emissions inventory for the 8-county Houston-Galveston-Brazoria (HGB) ozone nonattainment area 1 prepared by the Texas Transportation Institute (TTI) using MOBILE6 and other associated tools.
TTI's inventory uses link-level travel demand model outputs obtained from the Houston-Galveston Area Council (H-GAC), which have been processed and combined with MOBILE6 factors for each of the model's 28 vehicle classes by TTI. The TDM-based VMT data was processed using SAS 3 programs developed by ERG to obtain VMT estimates usable in MOVES. The general data flow for the inputs required to the MOVES model is presented in Figure 2-1.
A description of the processes used in analysis of the data provided by TTI, along with documentation of the methodology employed in creating MOVES input and output files, is provided below.
The first step in preparing data for input to MOVES is to ensure that the activity data that will be used is representative and complete. In the case of TDM-based VMT, TTI provided tab-delimited summary files that included VMT, VMT mix, hours of operation, vehicle speed, and other parameters on an hourly basis for each county of interest. It became apparent to us that for the purposes of this study, using a combination of the tab-delimited summary files and MOBILE6 inputs provided by TTI would be the most efficient way to create representative MOVES input files. Each of these inputs are required for EPA's VMT processor, which is further described in Step 2.
For this study, ERG used a SAS program to process the VMT summary files provided by TTI, aggregated by MOBILE6 vehicle type and H-GAC roadway type.
In the case of HPMS-based VMT, a different set of procedures must be used to arrive at activity data that can be used as format to the EPA converter tools, and subsequently, to the MOVES model itself. Since MOVES requires VMT data formatted by source type, and the HPMS data provided was aggregated only by road type, it is necessary to convert the VMT basis for use in the model.
ERG then applied the VMT fraction by HPMSVtypeID to the HPMS total VMT provided for each county by TTI, as shown in this equation, and in Table 2-6. Finally, ERG formatted the local VMT data by HPMS vehicle type for import into MOVES according to the MOVES template for VMT by vehicle type. When using HPMS-based VMT as a source of activity data for MOVES, users must not only assign appropriate source types to the VMT described above, but also derive road type distributions for the data. ERG then multiplied the default VMT fraction (by vehicle type) with the total VMT (by MOVES road type) to obtain the VMT aggregated by HPMS Vehicle type and MOVES road type, according to the following equation. Because EPA understands that many users of MOVES will already be familiar with MOBILE6 and NMIM, and likely have on hand previously performed analyses for their areas of interest that use those models, the agency has developed a number of converter tools that allow for transition of older data to MOVES. Having processed the TDM-based VMT using SAS, ERG used the first of several EPA spreadsheet tools employed for this effort, the VMT Converter Tool, to prepare inputs for MOVES. A separate converter spreadsheet was created for each of the eight counties of interest for this effort.
The input ramp fraction calculated using SAS was input for each of the three road types (11, 23, and 25) specified in the Import Ramp Fractions sheet. VMT by hour were copied directly from TTI's MOBILE6 inputs for each county into the Import HourlyVMTFractions sheet.
VMT aggregated by class and road type obtained from SAS processing were copied directly into the Import vClass28 VMT sheet. Note that information was NOT supplied for the Import CountyVMTMonthAllocation sheet, because in re-creating the TTI inventory for the HGB area, modeling was only necessary for a single month (July) and single day. The output from the converter tool includes VMT by HPMS source type, monthly VMT fractions by source type, hourly VMT fractions by source type and vehicle type, road type distribution by source type, and a converted ramp fraction.
To use the AADVMT tool, the HMPS VMT obtained from the HPMSvTypeYear output sheet in the VMT converter tool shown above was copied (per guidance in the Instructions sheet) to the Import HPMS AADVMT and Factors sheet in the AADVMT calculator. Yet another converter tool 14 provided by EPA facilitates the transformation of MOBILE6-formatted registration distribution data into MOVES-compatible vehicle age distribution data files.
EPA also provides a tool 15 that converts MOBILE6-formatted speed distribution files to the format required by MOVES.
In addition to the various outputs from the converter tools described in the previous section, other inputs are also necessary for calculating emissions inventories at the county level in MOVES. EPA's Technical Guidance 16 prescribes the use of state motor vehicle registration data for developing vehicle populations in MOVES, which are used to calculate both start and evaporative emissions.
Although usage of registration data to develop vehicle populations is suggested by EPA in the Technical Guidance, users should understand that the vehicles registered in a county for a given point in time do not necessarily correspond to the VMT driven over that same period in the county.
Because we originally had difficulty obtaining registration data ourselves, ERG went through the process of developing populations surrogates based on VMT.
Once the model runs were complete, ERG exported the ActivityType table and the MOVESActivityOutput table from the output database generated by the model.
Next, ERG obtained the local VMT data, by source type, for the area of interest (which was obtained by summing the VMT by county as calculated in EPA's VMT Converter Tool spreadsheet). In order to most accurately represent the inventory modeled by TTI, ERG changed the test standards from default values to match those specified in MOBILE6 inputs.
MOBILE6 oxygenates are listed in terms of weight percent, and must be converted to volume percent for use in MOVES. This initial attempt to create a representative fuel supply and formulation uncovered a couple of notable bugs in MOVES2010. Because of the issues surrounding emissions calculations related to fuel formulations in MOVES, EPA 20 recommended that ERG use the default Fuel Formulation and Fuel Supply provided in MOVES for the HGB area instead of importing or adjusting custom formulations, until the existing bugs are fixed.
The first step in setting up these runs was to make appropriate selections for each model option on the submenus listed in the main MOVES interface (see Figure 2-5).
Scale - A County scale, along with an Inventory calculation type, was used for all MOVES performed for this analysis.
Pollutants and Processes - Carbon Monoxide, Oxides of Nitrogen, Volatile Organic Compounds (VOCs), Non-Methane Hydrocarbons, Total Gaseous Hydrocarbons, and Methane were all selected. Output - General Output: In this submenu, it is important to create an output database with appropriate descriptive nomenclature, particularly when many different such databases will be residing on a single server. Output -Output Emissions Detail: A time period of 24-hours was selected, along with a location of County, for ease of comparison with the daily emissions calculated on a by-county basis in TTI's inventory. Geographic Bounds: Having fully populated all of the model options in each of the above submenus, ERG then returned to the Geographic Bounds submenu. The next step in the process is to create an input database, using appropriate descriptive nomenclature, that will store county-specific data for the model. The above procedures describe the methodology for creating a single MOVES run - in this case, for a particular county and VMT basis. The XML generator was used to create an XML file, which was in turn used to import data into the input database for a given county outside of the MOVES interface, at the command line. In addition to creating multiple input databases using the XML generator, it was also necessary for ERG to create the 32 MOVES runspecs described earlier.
Having created model runspecs and input databases for the 32 model runs, ERG prepared to execute each of the runs in MOVES. Are you receiving any warnings from the MOVES interface during import of information to the County Data Manager? Using the XML Importer File Tool to generate scripts for multiple counties can be a big time saver if you need to set up multiple MOVES runs.
Double check your model options to ensure you are modeling exactly what you intend to model with respect to time span, source type, road type, pollutants.
3 SAS, or the Statistical Analysis System, is an integrated system of software products, developed by SAS Institute Inc., that ERG used in its data analysis during the course of this study. 4 These tools are provided electronically in Appendix A, and described in more detail in Section 2.1. 5 Because many users of MOVES are likely to already have MOBILE6 input files and (other information based on MOBILE6 vehicle types) available to them, and because EPA is encouraging usage of their conversion tools, we feel this process reflects the application of what will likely be a common way of creating MOVES runspecs.
8 ERG's SAS program also independently calculated MOBILE6-format facility VMT, speed VMT, and VMT by hour files. 9 For TTI-based VMT, the calculation of road type distribution was handled by the EPA converter tool, as discussed in the following section. 12 It is important to note that MOBILE6 vehicle types are developed primarily on a vehicle weight basis, while MOVES source types focus more on usage classification of a particular vehicle.

We selected this inventory as the subject for the analysis based on the level of detail utilized in the current modeling, as well as our long standing relationship with the Texas Commission on Environmental Quality (TCEQ) and the Texas Transportation Institute (TTI), the parties responsible for developing the inventory for the Houston region. TTI processing activities include application of vehicle miles traveled (VMT), volume, speed, time of day, and seasonal adjustment factors to the link-level H-GAC activity data to obtain hourly allocations, as well as preparation and execution of episode-specific MOBILE6 runs in order to develop final mass emissions estimates. ERG developed other spreadsheet tools and methodology for conversion of HPMS-based VMT into MOVES format 4. Correct application of VMT, whether obtained from a travel demand model, HPMS, or other sources, is crucial to ensure model outputs correctly estimate emissions for a given area. We arrived at this conclusion after perusing the MOVES conversion tools made available by EPA, which rely primarily on existing MOBILE6 inputs for use in creating MOVES input files. Table 2-2 presents the mapping ERG used for converting H-GAC roadway types to HPMS roadway types; a similar mapping will likely need to be developed for roadway types in other areas.
The HPMS VMT, also provided by TTI, is simplified and streamlined relative to the TDM-based VMT discussed above. This can be accomplished by extracting default VMT ratios from within MOVES itself , which can then be used to define the relationship between VMT by source type and VMT by road type, and thereby calculate representative VMT by HPMS source type.
9 In order to perform this calculation for the HPMS data, ERG mapped the Houston-Galveston Area Council (H-GAC) road types listed in the TTI tab files to the standard HPMS road types. The VMT for the urban HPMS road types (codes 23, 25, 27, 29, 31, and 33) was obtained by summing the HPMS VMT for small urban areas, large urban areas, and urbanized areas. The next step in the process was to obtain the MOVES default VMT fraction by vehicle type, using the same methodology described above in the HPMS-based VMT Conversion section.
These spreadsheet tools were most recently updated in February 2010, and are freely available at EPA's website 10. This was done primarily because the ramp VMT provided by TTI was not associated with a particular road type. If a user wished to populate this tab for use in MOVES, he could using derive it from an NMIM county database, if available, per the SQL script provided on the Instructions sheet in the converter tool.
The ramp fraction and road type distribution produced here were directly imported into MOVES, as described later. This tool is necessary to convert Average Annual Daily VMT, such as that provided to us by TTI, into annual VMT, which is required as input to MOVES whether a user is performing an annual analysis or not. In addition, all of the monthly and weekend-day adjustment factors on that sheet were changed from their default values to 1.0 to reflect that, for this inventory, we are ultimately only attempting to model emissions for a single day in a single month (thus, our daily VMT did not need to be re-weighted on an monthly or weekend-day basis for conversion to annual VMT). ERG input TTI's MOBILE6 registration data to the tool, which expands registration data across thirty-one years, applies the registration distribution to the vehicle count for the calendar year of interest, and maps the total vehicle counts, by age, to one of the thirteen appropriate MOVES source types. ERG obtained 2006 registration data for each county of interest in this study from the Texas Department of Motor Vehicles. For example, commuters living in Fort Bend county may drive a significant portion of their vehicle miles in Harris county. However, it has been our experience that this data can sometimes be difficult to obtain at the level of disaggregation required for import into MOVES.
As described in the EPA Technical Guidance, the first step in deriving local population estimates based on local VMT data is to perform a MOVES modeling run using MOVES default population and VMT data.
Using this data, ERG calculated the MOVES default population to VMT ratio for each source type by dividing the MOVES default population by the MOVES default VMT in the outputs. Finally, the local vehicle population, by source type, was calculated by applying the default MOVES population to default MOVES VMT ratio to the local VMT, by source type, by county. In particular, MOVES source types 31 and 32 can encompass MOBILE6 source types LDGT1 all the way up to HDGV5. The first, Fuel Supply, lists fuel formulations, along with their respective market shares, on a monthly and yearly basis. The most straightforward way to do this is to export MOVES default fuelformulation and fuelsupply tables via the interface, and then reimport them, as suggested in the MOVES User's Guide. ERG simply formatted the hourly temperature and relative humidity data from the MOBILE6 input files according to the template in an Excel spreadsheet.
A separate MOVES input runspec and associated database was created for each county of interest, using default MOVES drive cycles, for both TDM-based VMT, as well as HPMS-based VMT. It is very important to note that model option selections for all of the submenus pictured below must be made before entering data via the County Data Manager, or the user may experience difficulties.
The latter three pollutants are required, as indicated by the interface during selection, for calculation of VOCs.
For this study, we selected units of tons for mass, million BTU for energy, and miles for distance. For future detailed analysis, we selected calculation of emissions by emissions process, both by road type and source use type. These spreadsheets are listed in Table 2-10, and have been provided electronically in Appendix A for further reference. First of all, MOVES sometimes will return errors during an import of data directly from certain sheets in the EPA VMT tool. However, as previously discussed, 32 different MOVES runs were set up and executed for this analysis, and it would have been fairly tedious to set up all 32 of those runs manually within the MOVES interface. When generating MOVES runs for multiple counties, ERG found that it is a fairly straightforward process to run the County Data Manager for a single county, use the XML generator tool to prepare an XML importer template, and then alter that template in a text editor to produce importers for multiple counties. We found the most efficient way to do this was to start by creating a runspec for a given county using the MOVES graphical interface, and save that file, which is stored by MOVES in XML format. Figure 2-7 presents a summary of inputs necessary for preparing county-level MOVES runs, and issues to keep in mind while doing so. Defaults may be used, but users are encouraged to calculate these based on available VHT when possible.
These are needed for calculation of emission from vehicle starts and evaporative processes.
This will not apply to all areas, but if it is required, program test information, along with applicability to particular source types and model years, will be necessary. This includes not only physical characteristics of fuels to be modeled, but also information on fuel market share for a given area. If so, check your inputs carefully, as MOVES may still allow you to perform calculations even when there is an error in an input file. When using XML files to import information into multiple County Data Manager databases, closely check the syntax of input files before execution to avoid errors. These files were used for QC purposes, and were checked against similar files already provided by TTI, The result was that ERG's facility VMT and VMT by hour files for Harris County very closely resembled those provided by TTI. This distinction arises often while converting information from a MOBILE6 basis to a format useable in MOVES. The emissions inventory files, as well as all of the supporting data and documentation, used to support the 2006 Houston-Galveston-Brazoria ozone nonattainment SIP is posted on TCEQ's public ftp server 2. Data provided by TTI included tab delimited summary files containing travel demand model (TDM) based VMT, VMT mix, hours of operation, vehicle speed, and other parameters on an hourly basis for each county, which were used for development of the first set of MOVES model runs prepared for this analysis. 5 It is important to note that EPA's conversion tools are designed to accept activity data in NMIM 6 format, and data available in that format may require little to no additional processing on the part of the user. The SAS program was written solely for use with the TDM output provided by TTI, and was intended as both a QC measure (to verify MOBILE6 inputs provided by TTI were consistent with the TDM outputs) and as a tool to generate ramp fractions and VMT for use in the EPA conversion tools.
The TDM based-VMT was provided for a number of specific vehicle types and road types, across all 24 hours of a given ozone season weekday. In cases where the mapping was not transparent, ERG used its best engineering judgment to assign the H-GAC road types to the most appropriate HPMS road type category. After projecting 2006 VMT from 1999 base VMT using factors supplied in the HPMSVtypeYear table in MOVES, ERG calculated a VMT fraction by HPMS type using default VMT ratios, an example of which is shown in Table 2-9.
ERG made extensive use of these tools in adapting TTI's previously developed MOBILE6 files into a form usable in MOVES, and we expect that others users will want to do the same. This tool is necessary to convert both VMT and road type fractions from a MOBILE6 vehicle type basis to a MOVES source type basis 12. The monthly fractions produced, meanwhile, were ignored in favor of those produced by EPA's Average Annual Daily (AAD) VMT converter tool, because using the default monthly weighting provided in this tool for VMT in July (1.0871 in a non-leap year) would have over-estimated VMT for the scenario we were modeling.
The AADVMT tool calculates annual VMT based on provided AAD VMT, and weights the VMT appropriately across months and days (weekend or weekday) of interest.

The outputs of the speed distribution converter tool, formatted appropriately for import directly into MOVES to populate the AvgSpeedDistribution table, include source type, road type, hour and day, average speed bin, and speed distribution fraction. These model inputs were developed by ERG, are provided electronically as part of the MOVES County Data Manager input databases included in Appendix A, and are described in the section that follows. In this example, using registration data as a population surrogate may lead to overestimation of start and evaporative emissions in Fort Bend county, while underestimating those same emissions in Harris County. If adequate resources for development of vehicle populations are lacking, users can follow section 3.3 of EPA's Technical Guidance to calculate local vehicle population based on their VMT data.
This calculated population is what can ultimately be used for input to MOVES if other sources of population data are unavailable. The second table, Fuel Formulation, lists a number of descriptive parameters for the various fuel formulations. Sulfur content and RVP provided in MOBILE6 were directly input to the fuel formulation sheet. The ethanol volume percentage associated with this fuel, as calculated from the MOBILE6 inputs, was 9.28%. In most cases, modeling with the default Fuel Formulation and Fuel Supply for a given area should provide representative outputs.
Although this is a fairly straightforward conversion that ERG performed manually, EPA also provides two meteorological data converter tools on their website (one for MOBILE6-formatted data, and one for NMIM-formatted data) for modelers to use. The same runs were re-created using ERG's drive cycles developed from the Kansas City Emissions Study (discussed in detail in Section 3 below). All process types were selected by checking the box on the far left side of the interface for each pollutant.
In the Activity section, we checked boxes for distance traveled and population, as both are important when performing QC on outputs. We did so using the processed data described in the previous section, for each county and VMT basis modeled. The naming convention used here is not particularly meaningful with respect to MOVES; any filename can be used during the import process. This can be resolved by copying data from the VMT tool into a blank spreadsheet, and then importing that sheet instead.
Fortunately, MOVES provides a tool to assist with import of numerous sets of county-specific data. These XML files can then be called from the command line, or in a batch file, to create multiple input databases at once.
Remember that activity data may require a significant amount of pre-processing, even prior to use of EPA's converter tools.
Speed VMT differed in that ERG's speeds were not as widely distributed across the speed range as TTI's - this was later determined to be caused by ERG's use of the VMT summary, whereas TTI was using link-level VMT as a basis for its speed distribution, which is more accurate.
HPMS-based VMT was also provided, and was used to develop the second set of MOVES modeling runs.
In this section, we discuss procedures we undertook in preparing our activity data, prior to subsequent processing in EPA's VMT spreadsheet tools, which will be discussed later. However, since activity data for a given region may be available in a variety of formats, users interested in preparing TDM-based VMT for input to MOVES for their own region may need to develop their own methods for processing VMT. If VHT are not available, defaults ramp fractions can be used, although this is not preferred. ERG's SAS program produced appropriately formatted VMT, ramp fractions, and other QC outputs 8 for each county, which were subsequently used as input to the EPA converter tools discussed later. The HPMS VMT used in this analysis, however, is organized only by road types and area types, as seen in Table 2-3, which are less specific that what is available in the TDM-based VMT, a sample of which is presented previously in Figure 2-2. Table 2-8 illustrates the HPMS road type to MOVES road type mapping, which was derived from calculation sheets contained in the EPA converter tools discussed below in Section 2.2. Each of the converter tools used during this study have been included electronically in Appendix A, and are discussed in additional detail below. Note that although we used only one of the VMT converter tools EPA provides on the Tools for MOVES website, there are seven other such VMT converters available. Users with a more specific association between road type and ramp VMT could use more detailed fractions.
The calculated VMT itself, as shown in Figure 2-3, was in turn used as input to the AADVMT tool. As before, a separate AADVMT spreadsheet was created for of the eight counties to be modeled. In order to prepare the data for modeling in MOVES, ERG converted the vehicle populations provided to MOVES source types by using the mapping ratios available in Table A.1 of the Appendix in the Technical Guidance. While a better alternative for determining representative source populations does not currently exist, it is an important issue for users to be aware of. To avoid this problem, EPA suggests that users should currently adjust data associated only with existing fuel formulation IDs, and not create new IDs. Before a MOVES run can be performed, data must be imported into each of the tabs shown in the County Data Manager, pictured in Figure 2-6. Because the County Data Manager requires a number of different inputs to be properly populated, users may find it helpful to use a table such as the one shown here for QC purposes in creating their own MOVES input databases. Secondly, Fuel Formulation data should be imported before Fuel Supply data; if not imported in that order, MOVES will return an error regarding unknown formulations.
This is a simple process which involved changing a few references to the county modeled, as well as input and output database paths, within the XML runspec file.
Subsequently, VMT by hour and speed VMT from TTI were used as input to EPA's converter tools for all subsequent MOVES runs.
For the cases being evaluated in this exercise, the selections for time span were a 24-hour period for a weekday in the month of July.
Reid vapor pressures, oxygenate weight percentages, and sulfur content for both gasoline and diesel fuels were specified in the MOBILE6 runs. The fuel supply sheet was populated with two new fuel formulation IDs for July 2006, one representing gasoline and one diesel, each with 100% market share.
Therefore, MOVES did not handle calculation of VOC emissions correctly, and underestimated them by approximately an order of magnitude 19. Finally, note that after importing all four of the VMT sheets required for the Vehicle Type VMT tab, the red X in the interface may not change to a green check, even when you've imported valid data. ERG has provided example XML importers generated for this analysis, as well as the batch file created to perform multiple imports at once, in Appendix A of this document. Users of MOVES are encouraged to closely examine EPA's available converter tools to determine which is best suited for their own application. All vehicle and fuel types (except the placeholder fuel type) were selected, as well as all road types for this modeling scenario.
Similarly, the testStandardsID was changed from 43 to 45 for an evaporative program affecting light-duty vehicles, which represented an OBD Evap and Gas Cap program, as opposed to only an Evap program.
In this particular case, the workaround suggested by EPA was to use a different fuel type ID of 13, which corresponds to E8 fuel and has an expected ethanol range that includes the 9.28% specified. Since the only interest here is obtaining the default population to VMT ratio, selection of a particular pollutant is not relevant. Note that per the Technical Guidance, creating some sort of single average fuel to be representative of a given area is discouraged - rather, multiple fuels in use for a given area should be input, and market share adjusted appropriately for each of those fuels. However, the model required the selection of at least one pollutant, so Oxides of Nitrogen was selected for these runs. In this case, however, ERG created a single fuel, since that most closely mirrored the inputs used in TTI's MOBILE6 input files. Finally, output data selections were made, which are important to ensure the required information for calculating the default MOVES population to VMT ratios is present.

Survival kit contents dr strangelove uottawa
Emergency survival food diy

Comments to «Harris county used car sales tax»

  1. 10 writes:
    Atmosphere to produce clean mannequin generator will carry a higher granulated Activated Charcoal.
  2. salam writes:
    The distinction between life and get a guaranty in your survival backpack, go ahead this rolling.