Wetlands are important habitats and spawning grounds to a diverse wildlife population and are particularly vulnerable to adverse effects of endocrine disruptors. Many pesticides possess hormonal activity and have thus been classified as endocrine disruptors. A new analytical method based on ultrasonic-assisted extraction, solid-phase extraction, and gas chromatography technologies was developed for analysis of selected potential endocrine-disrupting pesticide residues in wetland sediment samples from northern Beijing, China. The newly developed method was a less time-consuming and less solvent-consuming way of analyzing residues without an air-drying process prior to extraction. The selected pesticides included the compounds hexachlorocyclohexane, cyclodiene, DDTs, chlordane, hexachlorobenzene, heptachlor, endrin aldehyde, heptachlor epoxide, dicofol, acetochlor, alachlor, metolachlor, chlorpyrifos, nitrofen, trifluralin, cypermethrin, fenvalerate, and deltamethrin. Characterization and identification of the selected endocrine-disrupting pesticide residues in sediments may help to assess current pollution status of endocrine-disrupting pesticides in the area. Total concentrations of pesticides ranged from 15.4 to 38.1 ng/g (dry weight) with a mean concentration of 23.7 ng/g (dry weight) for sediment samples. Although levels of all detected pesticides were below the New York State Department of Environmental Conservation, USA, sediment quality criteria, considering the potential health effects of endocrine disruptors even in a trace level, the use of the pesticides in the agricultural system should be minimized and regular monitoring is needed in the area.

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A photonic quasi-crystal fiber (PQF) methane sensor based on surface plasmon resonance (SPR) is designed and described. The double-side polished six-fold photonic quasi-crystal fiber coated with a silver film produces enhanced SPR effects and sensitivity. A nanostructured thin film with cryptophane-E-doped polysiloxane is deposited on silver as the methane-sensitive surface layer and to mitigate oxidation of silver. The sensor is analyzed and optimized numerically by the full-vector finite element method. For methane concentrations in the range of  0% to 3.5%, the maximum sensitivity of the sensor is 8 nm/%, and the average sensitivity is 6.643 nm/%. Compared to traditional gas sensors, this sensor provides accurate sensing of methane besides offering advantages such as the low cost, miniaturized size, online monitoring, and immunity to electromagnetic field interference.

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