7 research outputs found
Effect of different emission inventories on modeled ozone and carbon monoxide in Southeast Asia
In order to improve our understanding of air quality in Southeast Asia, the
anthropogenic emissions inventory must be well represented. In this work, we
apply different anthropogenic emission inventories in the Weather Research
and Forecasting Model with Chemistry (WRF-Chem) version 3.3 using Model for Ozone and
Related Chemical Tracers (MOZART)
gas-phase chemistry and Global Ozone Chemistry Aerosol Radiation and Transport (GOCART) aerosols to examine the differences in
predicted carbon monoxide (CO) and ozone (O<sub>3</sub>) surface mixing ratios for
Southeast Asia in March and December 2008. The anthropogenic emission
inventories include the Reanalysis of the TROpospheric chemical composition
(RETRO), the Intercontinental Chemical Transport Experiment-Phase B
(INTEX-B), the MACCity emissions (adapted from the Monitoring Atmospheric
Composition and Climate and megacity Zoom for the Environment projects), the
Southeast Asia Composition, Cloud, Climate Coupling Regional Study (SEAC4RS)
emissions, and a combination of MACCity and SEAC4RS emissions. Biomass-burning emissions are from the Fire Inventory from the National Center for
Atmospheric Research (NCAR) (FINNv1) model.
WRF-Chem reasonably predicts the 2 m temperature, 10 m wind, and
precipitation. In general, surface CO is underpredicted by WRF-Chem while
surface O<sub>3</sub> is overpredicted. The NO<sub>2</sub> tropospheric column predicted
by WRF-Chem has the same magnitude as observations, but tends to
underpredict the NO<sub>2</sub> column over the equatorial ocean and near Indonesia.
Simulations using different anthropogenic emissions produce only a slight
variability of O<sub>3</sub> and CO mixing ratios, while biomass-burning emissions
add more variability. The different anthropogenic emissions differ by up to
30% in CO emissions, but O<sub>3</sub> and CO mixing ratios averaged over the
land areas of the model domain differ by ~4.5% and
~8%, respectively, among the simulations. Biomass-burning
emissions create a substantial increase for both O<sub>3</sub> and CO by
~29% and ~16%, respectively, when
comparing the March biomass-burning period to the December period with low biomass-burning emissions. The simulations show that none of the anthropogenic
emission inventories are better than the others for predicting O<sub>3</sub>
surface mixing ratios. However, the simulations with different anthropogenic
emission inventories do differ in their predictions of CO surface mixing
ratios producing variations of ~30% for March and
10â20% for December at Thai surface monitoring sites
Sex and stature estimation from adult lumbar vertebrae in a thai population based on image analysis
Although molecular techniques evolved considerably in last years, anthropological methods of assessing skeletal remains, continues to be an important tool in the identification process in medico legal investigations. The objective of this study was to develop a discriminant function equation for estimating sex and stature using several measurements of lumbar vertebrae in a Thai population. We studied 150 lumbar columns (75 male and 75 female) age range of 22 to 89 years from the Forensic Osteology Research Center, Chiang Mai University, Thailand. The quantitative variables with sex were analyzed by the discriminant function analysis and that with stature were calculated using linear regression. The pixel density of the major axis of the trabecular surface of superior endplate of the first lumbar vertebra had the most accuracy in sex determination. The regression equation with quantitative variables in stature estimation described 32.3 % of the total variance with standard error of estimate of 7.736 cm. Lumbar vertebrae can be used as part of the stature and sex quantitatively and qualitatively estimating in Thais incomplete skeletal remains