It has been more than 20 years that the Measurement of Pollution in The Troposphere (MOPITT) mission onboard the NASA Terra satellite keeps providing us CO atmospheric concentration measurements around the globe. The current paper observes CO mixing ratio from the MOPITT Version 8 (MOP03J_V008) instrument in order to study the spatiotemporal analysis of CO (spanning from April 2000 to February 2020) in the Troposphere of Iran. Results indicate that the average CO in Iran’s troposphere has been 133.5 ppbv (i.e., 5.5 ppbv lower than the global mean CO). The highest distribution of CO (with an average of 150 ppbv) belongs to the city of Tehran (the capital of Iran) as well as the Caspian Sea coastal area, while the lowest value (with an average of less than 110 ppbv) has been estimated on the Zagros Mountains (southwestern Iran). The highest and lowest CO values have been observed in cold and hot months, respectively. Seasonally speaking, it is also clear that the highest and lowest carbon monoxide values occur in winter and summer, respectively. The vertical profile of MOPITT CO shows the maximum CO concentration at lower levels of the troposphere. It has been expanded up to 150 hPa. The trend is investigated by means of Pearson correlation coefficient statistical method. Overall, long-term monitoring of MOPITT CO in Iran indicates a decreasing trend of tropospheric CO over the 20 years (Y=-0.008X+449.31). Possible reasons for such a decrease can be related to improved transportation fleet, increased fuel quality, plans for traffic control, promotion of heating systems, and promotion of industrial fuels and factories.

A comprehensive, high resolution, ground truthed benthic habitat map has been completed for Qatar's coastal zone and Halul Island. The objectives of this research were to; 1. Systematically compare and contrast pixel- and object-based classifiers for benthic mapping in a limited focus area and then to, 2. Apply these learnings to develop an accurate high resolution benthic habitat map for the entirety of the Qatari coastal zone. Results indicate object-based methods proved more efficient and accurate when compared to pixel based classifiers. The developed country-wide map covers 4500 km² and underscores the complex interplay of seagrass, macroalgal, and reefal habitats, as well as areas of expansive mangrove forests and microbial mats. The map developed here is a first of its kind in the region. Many potential applications exist for the datasets collected to provide fundamental information that can be used for ecosystem-based management decision making.