An interval-parameter two-stage optimization model for CO_(2) collection,distribution,transportation,utilization,and storage planning

Geological carbon dioxide (CO_(2)) utilization and storage have been widely recognized as one of the important options to deliver greenhouse gas emissions reduction. Reasonable planning is critical to promote CO_(2) utilization and storage. However, CO_(2) emissions gas collection exhibits a stochastic probability distribution, and CO_(2) utilization and storage features fluctuation demands, which have gone beyond current determine planning techniques. To fulfill the current research gap, this study develops an interval-parameter two-stage programming-based CO_(2) collection, distribution, transportation, utilization, and storage optimization model, integrating interval parameter planning and two-stage planning into a general framework. Therefore, the model can address uncertainties expressed as random probabilistic distributions and discrete intervals, tackle dynamic facilities capacity expansion issues, develop optimal predefined CO_(2) distribution policy, and generate recourse schemes to address gas shortage or gas surplus issues. The model is examined by a typical hypnotical case study in China. The results revealed that the model could generate a set of first-stage reasonable CO_(2) distribution and facilities capacity expansion schemes to maximum system benefits and the highest feasibility. Besides, a set of two-stage CO_(2) outsourcing purchases and facilities capacity expansion in reserve storage regions solutions were also generated to address the gas oversupplies and shortage issues. The modeling approach enriches the current CO_(2) utilization and storage distribution research content under multiple uncertainties.

Applying a new method for direct collection, volume quantification and determination of N_2 emission from water

The emission of N2 is important to remove excess N from lakes, ponds, and wetlands. To investigate the gas emission from water, Gao et al.（2013） developed a new method using a bubble trap device to collect gas samples from waters. However, the determination accuracy of sampling volume and gas component concentration was still debatable. In this study, the method was optimized for in situ sampling, accurate volume measurement and direct injection to a gas chromatograph for the analysis of N2 and other gases. By the optimized new method, the recovery rate for N2 was 100.28% on average; the mean coefficient of determination（R2） was 0.9997; the limit of detection was 0.02%. We further assessed the effects of the new method, bottle full of water, vs. vacuum bag and vacuum vial methods, on variations of N2 concentration as influenced by sample storage times of 1,2, 3, 5, and 7 days at constant temperature of 15°C, using indices of averaged relative peak area（%） in comparison with the averaged relative peak area of each method at 0 day.The indices of the bottle full of water method were the lowest（99.5%–108.5%） compared to the indices of vacuum bag and vacuum vial methods（119%–217%）. Meanwhile, the gas chromatograph determination of other gas components（O2, CH4, and N2O） was also accurate. The new method was an alternative way to investigate N2 released from various kinds of aquatic ecosystems.