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We have studied dispersion of surface plasmon polaritons (SPPs) in the Kretschmann geometry (prism/Ag/dye-doped polymer) in weak, intermediate, and ultra-strong exciton–plasmon coupling regimes. The dispersion curves obtained in the reflection experiment were in good agreement with the simple model predictions at small concentrations of dye (Rhodamine 590, Rh590) in the polymer (Poly(methyl methacrylate), PMMA). At the same time, highly unusual multi-segment “staircase-like” dispersion curves were observed at extra-large dye concentrations, also in agreement with the simple theoretical model predicting large, small, and negative group velocities featured by different polariton branches. In a separate experiment, we measured angular dependent emission of Rh590 dye and obtained the dispersion curves consisting of two branches, one nearly resembling the SPP dispersion found in reflection and the second one almost horizontal. The results of our study pave the road to unparalleled fundamental science and future applications of weak and strong light—matter interactions.

Wastewater treatment plants (WWTPs) in the City of New York, United States, are particularly vulnerable to frequent extreme weather events, including storm surges, high-intensity rainfall, and sea level rise, and are also affected by the cascade of these events. The complex structural configuration of WWTPs requires very fine-scale flood risk assessment, which current research has not pursued. We propose a robust technique to quantify the risk of inundations for the fourteen WWPTs through an automated sub-basin creation tool; 889 sub-basins were generated and merged with high-resolution building footprint data to create a comprehensive database for flood inundation analysis. The inundation depths and extents for the WWTPs and flood-prone regions were identified from hydrodynamic modeling of storm surge and sea level rise. The economic damage due to flooding for the WWTPs was also quantified using the HAZUS-MH model. Results indicated that the storm surges from various categories of hurricanes have the dominant impacts on flood depths around WWTPs, followed by high-intensity rainfall. Sea level rise was shown to have a relatively minor impact on flood depths. Results from economic damage analysis showed that the WWTPs are subjected to damage ranging from USD 60,000 to 720,000, depending on the size of the WWTP and the extremity of storm surge. The method of analyzing the inundation status of the research object through the sub-basin enables more accurate data to be obtained when calculating the runoff. It allows for a clearer view of the inundation status of the WWTPs when combined with the actual buildings. Using this database, predicting flood conditions of any extreme event or a cascade of extreme events can be conducted quickly and accurately.

Subsurface temperature is a critical indicator for the identification of the risk associated with subsurface fire hazards in landfills. Most operational landfills in the United States (US) have experienced exothermic reactions in their subsurface. The subsurface landfill area is composed of various gases generated from chemical reactions inside the landfills. Federal laws in the US mandate the monitoring of gases in landfills to prevent hazardous events such as landfill fire breakouts. There are insufficient investigations conducted to identify the causes of landfill fire hazards. The objective of this research is to develop a methodological approach to this issue. In this study, the relationship was investigated between the subsurface elevated temperature (SET) and soil gases (i.e., methane, carbon dioxide, carbon monoxide, nitrogen, and oxygen) with the greatest influence in landfills. The significance level of the effect of soil gases on the SET was assessed using a decision tree approach. A naïve Bayes technique for conditional probability was implemented to investigate how different gas combinations can affect different temperature ranges with respect to the safe and unsafe states of these gases. The results indicate that methane and carbon dioxide gases are strongly associated with SETs. Among sixteen possible gas combinations, three were identified as the most probable predictors of SETs. A three-step risk assessment framework is proposed to identify the risk of landfill fire incidents. The key findings of this research could be beneficial to landfill authorities and better ensure the safety of the community health and environment.

Subsurface fires and smoldering events at landfills can present serious health hazards and threats to the environment. These fires are much more costly and difficult to extinguish than open fires at the landfill surface. The initiation of a subsurface fire may go unnoticed for a long period of time and undetected fires may spread over a large area. Unfortunately, not all landfill operators keep or publish heat elevation data and many landfills are not equipped with a landfill gas extraction system to control subsurface temperatures generated from the chemical reactions within. The timely and cost-effective identification of subsurface fires is an important and pressing issue. In this work, we describe a method for using satellite thermal infrared imagery at a moderate spatial resolution to identify the locations of subsurface fires and monitor their migration within landfills. The focus of this study was the Bridgeton Sanitary Landfill in Bridgeton, MO, USA where a subsurface fire was first identified in 2010 and continues to burn today. Observations from Landsat satellites over the last seventeen years were examined for surface temperature anomalies (or hot spots) that may be associated with subsurface fires. The results showed that the locations of hot spots identified in satellite imagery match the known locations of the subsurface fires. Changes in the hot-spot locations with time, as determined by in situ measurements, correspond to the spreading routes of the subsurface fires. These results indicate that the proposed approach based on satellite observations can be used as a tool for the identification of landfill subsurface fires by landfill owners/operators to monitor landfills and minimize the expenses associated with extinguishing landfill fires.