Description

This paper develops a conceptual model of optimal vehicle trips in a region plagued by weather-dependent, mobile-source air pollution, and numerically estimates optimal trips for one of the nation's perennially worst air quality regions in terms of short-term particulate matter. Based upon data-driven parameters and damage estimates, our numerical model generates steady-state values for region-wide vehicle trips and associated PM2.5 concentrations along with their corresponding optimal time paths. Our dataset includes a host of pertinent weather variables that determine PM2.5 concentrations both independently as well as interacted with vehicle trips. As a result, our empirical model enables us to isolate the conditions under which vehicle travel most affects air pollution levels. Our results suggest that maximizing net social welfare in the presence of mobile-source pollution requires substantial reductions in traditional, emissions-generating vehicle usage on days experiencing critical weather conditions - in the case of our study area, temperature inversions. Because they are socially optimal and targeted solely for days with temperature inversions, the estimated reductions in vehicle usage are substantially larger than those proposed by Moscardini and Caplan (2017) to attain the USEPA's daily standard for particulate matter on an average basis.

OCLC

1078404529

Document Type

Dataset

DCMI Type

Dataset

File Format

.csv, .txt

Viewing Instructions

Any software that can read or convert CSV format

Publication Date

9-17-2018

Publisher

Utah State University

Award Number

Utah Agricultural Experiment Station UTA0-1334

Methodology

Details appear in forthcoming paper

Start Date

1-1-2002

End Date

12-31-2013

Language

eng

Code Lists

Details appear in forthcoming paper

License

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.

Checksum

e7b3149ab52cf9f5031c448c0b7f4aa3

Additional Files

USU README File for Optimal Vehicle Trips Study.txt (3 kB)
MD50faae70df8ca4fce57772a42e90fc533

Optimal_Vehicle_Trips_Regressions.csv (278 kB)
MD5712531d22d2c671967a8ad504a958c26

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