Evaluation of WRF-Chem Simulated Carbon Dioxide Atmospheric Transport and Emissions in the Baltimore / Washington Metropolitan Area

Published: November 10, 2018

Author(s)

Cory R. Martin, Ning Zeng, Anna Karion, Kimberly L. Mueller, Subhomoy Ghosh, Israel Lopez Coto, Kevin Gurney, Tomohiro Oda, Kuldeep R. Prasad, Yun Liu, Russell R. Dickerson, James R. Whetstone

Abstract

Urban areas are major sources of carbon dioxide (CO2) emissions, contributing to the increase in global concentrations and leading to concerns about Earth's future climate. In recent years, several urban testbeds have been implemented to improve and demonstrate measurement capabilities to quantify greenhouse gas concentrations, and fluxes, in, as well as the fossil fuel emissions from, metropolitan areas. The NIST Northeast Corridor greenhouse gas observation network, starting operation in late 2015, is one such urban testbed, centered around the Baltimore, MD - Washington, D.C. metropolitan area. We present a high-resolution (1km) WRF-Chem simulation of modeled CO2 mole fractions for the month of February 2016 over the Baltimore-Washington area, and compare them to observations from three urban/suburban sites as well as one rural site at Shenandoah National Park. Four different global and regional fossil fuel emissions inventories are used to provide an ensemble of model simulated atmospheric CO2, and a vegetation model is coupled to provide biospheric fluxes. The amplitude of the diurnal cycle in atmospheric CO2 varied on the order of 50+ µmol mol-1 of dry air (parts per million, or ppm) as observed at the three urban/suburban sites over the course of one month, whereas only 5-10 ppm fluctuations in the amplitude of the diurnal cycle were observed at the rural site. Simulated and observed average CO2 time series are in good agreement overall, with three of the four inventories having a 1-3 ppm low bias, and the other, a slight high bias, when averaged at all sites over the entire month. Differences can vary much more widely however at a given hour, depending on the prevailing synoptic weather condition, time of day, and other meteorological factors. Three typical scenarios are presented to illustrate the range of model prediction relative to observations. Despite the large variation in emissions from the four different inventories, which also are noticeable in the
Citation: Atmospheric Environment
Pub Type: Journals

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Created November 10, 2018, Updated June 13, 2019