Literature DB >> 23858998

Accounting for acceleration and deceleration emissions in intersection dispersion modeling using MOVES and CAL3QHC.

Mark Ritner1, Kurt K Westerlund, C David Cooper, Michael Claggett.   

Abstract

Near-road dispersion modeling with CAL3QHC has traditionally been accomplished by assuming vehicles are either idling in queue links or flowing freely in cruise links. With the introduction of the new mobile-source emissions model MOVES, second-by-second activity patterns can be used to produce emission factors (EFs) that vary by vehicular modal activity, that is, acceleration, deceleration, idle, and cruise. By using these EFs in unique modal links in CAL3QHC input files, the predicted concentration of pollutants near roadways can be modeled with greater precision in regard to real-world intersection vehicle behavior. It is noted that this work does not include any comparisons with real-world monitored data, and thus only the precision and not the accuracy of the proposed method is addressed. This work poses the question of how best to include modal links into near-road dispersion modeling. Specifically, it examines dividing acceleration and deceleration segments into multiple sublinks for greater resolution. It is shown that such an approach can produce much higher CO predictions at an intersection (up to 400% higher) compared with the current cruise-and-idle-links modeling approach. A method of dividing links by increments of speed change is suggested. The method relies upon obtaining EFs from standstill to various cruise speeds (or from cruise speed to stopped) and using those results to obtain position-specific acceleration (or deceleration) EFs needed for dispersion modeling inputs. Acceleration EFs (in g/mile) are an order of magnitude larger than cruise EFs; deceleration EFs are smaller than cruise EFs. The number of sublinks used to model one acceleration link makes a difference in the predicted concentrations. MOVES can produce erratic EFs when longer links are broken into smaller sublinks.

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Year:  2013        PMID: 23858998     DOI: 10.1080/10962247.2013.778220

Source DB:  PubMed          Journal:  J Air Waste Manag Assoc        ISSN: 1096-2247            Impact factor:   2.235


  1 in total

1.  Short-Term Trend Forecast of Different Traffic Pollutants in Minnesota Based on Spot Velocity Conversion.

Authors:  Xiaojian Hu; Dan Xu; Qian Wan
Journal:  Int J Environ Res Public Health       Date:  2018-09-04       Impact factor: 3.390

  1 in total

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