MOVES3 Sensitivity Analysis: Regional Level
Sector: Advanced Electronics • Location: Washington, United States of America (USA)
Source: Federal Highway Administration (FHWA)
In November 2020, the US Environmental Protection Agency released the latest version of the Motor Vehicle Emission Simulator, MOVES3.0, the regulatory model for developing emission inventories from highway vehicles. Building off previous sensitivity analyses of earlier model releases, MOVES2010 and MOVES2014, this projects involves testing the influence of certain local inputs on emission results
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | active |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | In November 2020, the US Environmental Protection Agency released the latest version of the Motor Vehicle Emission Simulator, MOVES3.0, the regulatory model for developing emission inventories from highway vehicles. Building off previous sensitivity analyses of earlier model releases, MOVES2010 and MOVES2014, this projects involves testing the influence of certain local inputs on emission results that have been shown to be highly sensitive. The MOVES3 sensitivity analysis will assess the relative impact of four county-scale inputs: Truck hoteling. Off-network idle. Average speed distributions. Age distributions. Truck hoteling, average speed, and age default data have been updated for MOVES3 while off-network idle was added for this release. This task aims to identify which of these regional inputs will be the most impactful for state transportation agencies and metropolitan planning organizations (MPOs) to invest budget into collecting or procuring data for improved emission inventories. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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