Methyl halide gases are important sources of atmospheric inorganic halogen compounds, which in turn are central reactants in many stratospheric and tropospheric chemical processes. By observing emissions of methyl chloride, methyl bromide, and methyl iodide from flooded California rice fields, we estimate the impact of rice agriculture on the atmospheric budgets of these gases. Factors influencing methyl halide emissions are stage of rice growth, soil organic content, halide concentrations, and field-water management. Extrapolating our data implies that about 1 percent of atmospheric methyl bromide and 5 percent of methyl iodide arise from rice fields worldwide. Unplanted flooded fields emit as much methyl chloride as planted, flooded rice fields.

[1] Stable carbon isotope ratios for 37 hydrocarbon, CFC and halocarbon compounds were determined over the course of 1 year (86 samples) from the urban Belfast environment, Northern Ireland (NI). A smaller number of samples were collected from rural locations at Crossgar and Hillsborough, NI, and one marine location at Mace Head, Republic of Ireland. Source d 13 C ''signatures'' suggest that C5 alkanes and !C4 alkenes are most likely derived from vehicle emissions. C3-C5 hydrocarbons show significant enrichment of d 13 C with iso-alkanes < n-alkanes < alkenes < alkynes. There is also significant enrichment of d 13 C from propane to n-butane to n-pentane. There is no significant separation between n-pentane, n-hexane, n-heptane or methyl-butane, methyl pentane and methyl hexanes. Calculated hydroxyl reaction kinetic isotope effects and subsequent d 13 C enrichment are insufficient to explain shifts in isotopic ratio relative to concentration for all compounds as is differences in origin of air mass. Very few compounds show significant diurnal shifts; however, alkanes and !C4 alkenes demonstrate consistent enrichment of isotopic ratios when summer samples are compared to winter samples. Benzene is the sole compound measured that appears to become more depleted in d 13 C when summer samples are compared against winter samples. Urban air, sampled at Belfast, which has originated in Europe shows enriched values for hydrocarbons while air which has originated in the Arctic Ocean is most similar to marine air off the Atlantic, sampled at Mace Head, Ireland.Citation: Redeker, K. R., S. Davis, and R. M. Kalin (2007), Isotope values of atmospheric halocarbons and hydrocarbons from Irish urban, rural, and marine locations,

[1] This paper examines primary controlling factors that affect methyl halide emissions from rice paddy ecosystems. Observations of four cultivars under multiple growth conditions during studies in commercial fields and the University of California, Irvine, greenhouse lead to the conclusion that daily emissions of methyl halides are primarily determined by the growth stage of the rice plant, with the exception that methyl chloride emissions show no clear seasonal pattern. Methyl chloride emissions appear to be more from the paddy water and/or soil as opposed to the plants; however, in soils with high chloride content, these emissions appear to peak during the reproductive phase. Strong secondary influences include air temperature, soil halide concentration, and soil pore water saturation. The cultivars studied had statistically separate seasonally integrated emissions. Irradiant light and aboveground biomass appear to have little effect on emissions. Emissions of methyl chloride, methyl bromide, and methyl iodide are estimated to be 3.5, 2.3, and 48 mg/m 2 /yr, or 5.3, 3.5, and 72 Gg/yr, from rice paddies globally.

Volatile compounds contained in human breath reflect the inner workings of the body. A large number of studies have been published that link individual components of breath to disease, but diagnostic applications remain limited, in part due to inconsistent and conflicting identification of breath biomarkers. New approaches are therefore required to identify effective biomarker targets. Here, volatile organic compounds have been identified in the literature from four metabolically and physiologically distinct diseases and grouped into chemical functional groups (e.g. – methylated hydrocarbons or aldehydes; based on known metabolic and enzymatic pathways) to support biomarker discovery and provide new insight on existing data. Using this functional grouping approach, principal component analysis doubled explanatory capacity from 19.1% to 38% relative to single individual compound approaches. Random forest and linear discriminant analysis reveal 93% classification accuracy for cancer. This review and meta-analysis provides insight for future research design by identifying volatile functional groups associated with disease. By incorporating our understanding of the complexities of the human body, along with accounting for variability in methodological and analytical approaches, this work demonstrates that a suite of targeted, functional volatile biomarkers, rather than individual biomarker compounds, will improve accuracy and success in diagnostic research and application.