The distribution of gaseous atmospheric hydrocarbon compounds, halocarbons, and nitrous oxide were studied. Whole air samples were collected aboard the NCAR Electra aircraft platform during the Monsoon Experiment (MONEX) flights in Kuala Lumpur, Malaysia, and on ferry flights to and from the United States. Foliage emission rates were also measured on some tropical plants. The average free tropospheric TNMHC (total non‐methane hydrocarbon) levels from both the transit flight and mission flights were low (2.5 μg/m3). TNMHC just above the forest canopy over Borneo but within the mixing layer was higher and the concentrations over land were higher than those obtained over the ocean. The fluorocarbons showed a small latitude gradient or a difference between continental and oceanic air masses or (possibily) both. Methyl chloroform also showed a significant latitude profile. Nitrous oxide was uniformly distributed in the atmosphere. The C2 hydrocarbons, ethane and acetylene, also showed latitudinal gradients. The emission rates of foliage in the tropics were higher than those reported by other investigators for the mid‐latitudes. The species sampled indicated that most tropical vegetation emits predominantly isoprene, rather than terpenes.

A new gas chromatographic technique with a modified photoionization detector connected in series with a conventional flame ionization detector was used to determine low concentrations of atmospheric hydrocarbons in remote atmospheres. Average mixing ratios of five aromatic hydrocarbons measured between 42°N and 30°S latitude in the Pacific Ocean in October/November 1983 were highest in the Northern Hemisphere. The average mixing ratios in the northern and southern marine atmospheres were 49-+ 25 ppt (n = 35) and 10-+ 2 ppt (n = 21) for benzene, 20 + -12ppt (n = 32) and 5.6 -+ 1.6 ppt (n = 12) for toluene, 7.6 -+ 3.7 ppt (n = 35) and 3.7 -+ 1.6 ppt (n = 21) for ethylbenzene, 25 -+ 12 ppt (n --35) and 13 +-5 ppt (n = 20) for the sum of m-and p-xylenes, and 14 ± 6 ppt (n = 35) and 6.6 +-3.0 ppt (n = 21) for o-xylene, respectively. The first latitudinal gradients for these five aromatic compounds are reported. Benzene and toluene mixing ratios measured between July 1982 and October 1983 at a rural, mid-latitude continental site in eastern Washington state gave average values of 226 +-108 ppt and 133 +-84 ppt, respectively, with higher wintertime than summertime benzene levels. These continental samples gave calculated air mass ages averaging six days based on benzene-to-toluene ratios.

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Over 50 whole‐air gas samples were collected in Mt. St. Helens volcanic plumes beginning with the original steam and ash plumes in March 1980 and continuing through June 1980. Four research aircraft were used to collect the samples, which were analyzed by five different analytical techniques for 14 separate trace gases. COS, CS2, CH3Cl, CO2, CO, N2O, C2H6 and C2H2 were found in elevated amounts in the volcanic plume gases. Order‐of‐magnitude estimates of COS, CS2, CH3Cl, CO2 and CO fluxes have been made for several types of eruptive phases. COS was a substantial fraction of the sulfur‐carrying gases during the May 18 eruptions, although SO2 and H2S still predominated.

Numerous studies have been undertaken to determine the optimal land use/cover classification algorithm. However, there have not been many studies that have compared and evaluated the performance of maximum likelihood (ML), random forest (RF), support vector machine (SVM), and classification and regression trees (CART) using ASTER imagery, especially in a mining district. Therefore, this study aims to investigate land use/cover (LULC) change over three decades (1990–2020), comparing the performance of the ML, RF, SVM, and CART machine learning algorithms. The Landsat and ASTER data were retrieved using Google Earth Engine (GEE). Traditional ML classification was performed on ArcGIS 10.2 software while RF, SVM, and CART classification were undertaken on GEE. Then, thematic accuracy assessments were conducted for the four algorithms and their performances were compared. The results showed that the largest changes in area occurred in forest cover that decreased from 37.8 to 27.3 km2 during the three decades. The remarkable expansion of gold mining occurred during 2005–2010 with the increases of 1.6%. The mining land rose by 2.9% during the study period whereas agricultural land increased significantly by 10.7% between 1990 and 2020. When comparing the four algorithms, the RF algorithm gives the highest accuracy with an overall accuracy of 95.85% while SVM follows RF with 91.69%. This study proved that RF is the best choice for optimal land use/cover classification, particularly in the mining district.