English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

This paper describes the methodology for making comparisons between IASI (Infrared Atmospheric Sounding Interferometer) CO satellite observations and the data calculated by the WRF-Chem model for the period of February 2011. Satellite average kernels were used to smooth the model column (Rodgers and Connor, 2003) with the purpose of making the analysis with information that has the same characteristics of vertical sensitivity.  The analysis is made at the satellite crossing local hour (10:00 a.m. approximately) over the center of Mexico (Stremme et al., 2013; Clerbaux et al., 2009). Contribution from local emissions and neighboring cities were estimated using model data and satellite observations. The model was run with the chemistry turned off and scaling factors were calculated for each region by comparing the satellite and model data, then the emissions were adjusted and modeled was run again with the chemistry turn on to finally make comparisons against surface measurements.  For the Mexico Valley metropolitan area an adjustment factor equal to 0.43 was obtained, for Toluca, Morelos and Puebla a factor less than one was also estimated whereas for Hidalgo its value was close to two. The concentration from model boundaries was also considered for which was obtained an adjustment factor close to two. When the model results using original and adjusted emissions are compared against surface measurem ents, it is observed that the performance of the model improves using the adjusted carbon monoxide emissions.

Carbon monoxide emissions assessment by using satellite and modeling data: Central Mexico case study