Modeling the relationships between land use and land cover on private lands in the Upper Midwest, USA

This paper presents an approach to modeling land-cover change as a function of land-use change. We argue that, in order to model the link between socio-economic change and changes in forest cover in a region that is experiencing residential and recreational development and agricultural abandonment, land-use and land-cover change need to be represented as separate processes. Forest-cover change is represented here using two transition probabilities that were calculated from Landsat imagery and that, taken together, describe a Markov transition matrix between forest and non-forest over a 10-year period. Using a three-date land-use data set, compiled and interpreted from digitized parcel boundaries, and scanned aerial photography for 136 sites (c. 2500 ha) sampled from the Upper Midwest, USA, we test functional relationships between forest-cover transition probabilities, standardized to represent changes over a decade, and land-use conditions and changes within sample sites. Regression models indicated that about 60% of the variation in the average forest-cover transition probabilities (i.e. from forest to non-forest and vice versa) can be predicted using three variables: amount of agricultural land use in a site; amount of developed land use; and the amount of area increasing in development. In further analysis, time lags were evaluated, showing that agricultural abandonment had a relatively strong time-lag effect but development did not. We demonstrate an approach to using forest-cover transition probabilities to develop spatially-constrained simulations of forest-cover change. Because the simulations are based on transition probabilities that are indexed to a particular time and place, the simulations are improved over previous applications of Markov transition models. This modeling approach can be used to predict forest-cover changes as a result of socio-economic change, by linking to models that predict land-use change on the basis of exogenous human-induced drivers.     

Wet bench reactive hazards of cleaning stages in semiconductor manufacturing processes

According to the research from FM Global (Factory Mutual Insurance Company), most of the incidents that have occurred in semiconductor plants in the past two decades were reported as “Fire Cases”. They claim that the fires in wet chemical cleaning processes were mainly caused by heater failure. However, depending on the process conditions, electrical heaters are designed to turn off automatically when the temperature reaches a set point. Therefore, a thorough study of the situations related to possible fires in wet chemical cleaning processes is necessary.

This study focused on the incompatible behaviors of cleaning materials used in the wet bench stage. These results can be applied to determine the causes of fires in the wet bench stage from using reactive chemicals for cleaning purposes.

Another purpose of this study was to investigate the potential hazards of widely used chemicals (hydrogen peroxide, concentrated sulfuric acid, hydrochloric acid and isopropyl alcohol) within similar processes in semiconductor plants. Experimental data were also verified in order to establish a concentration triangular diagram, which could be used to identify a combustion, deflagration or even detonation zone. Finally, this study can provide basic design data for an inherently safer process to avoid potential hazards caused by dangerous mixtures, which may result in large property loss in semiconductor plants.     

Promoting catalytic ozonation of phenol over graphene through nitrogenation and Co3O4 compositing

Catalytic ozonation is progressively becoming an attractive technique for quick water purification but efficient and stable catalysts remains elusive. Here we solvothermally synthesized highly-dispersed Co₃O₄ nanocrystals over microscale nitrogen-doping graphene (NG) nanosheets and tested it as a synthetic catalyst in the ozonation of phenol in aqueous solutions. Transmission electron microscopy, powder X-ray diffraction, Fourier transform infrared spectra and X-ray photoelectron spectroscopy were used to determine its morphology, crystallinity, elemental composition and molecular bonds, respectively. The comparative experiments confirmed the highest catalytic activity and oxidation degree (AOSC) of Co₃O₄/NG among four nanocomposites (G, NG, Co₃O₄/G, and Co₃O₄/NG). Co₃O₄/NG also has exhibited the highest degradation rate: complete conversion of a near-saturated concentration of phenol (941.1 mg/L) was achieved within 30 min under ambient conditions with only a small dosage of Co₃O₄/NG (50 mg/L) and ozone (4 mg/L, flow rate: 0.5 L/min). It also resulted in 34.6% chemical oxygen demand (COD_Cr) and 24.2% total organic carbon (TOC) reduction. In this work, graphene nanosheets not only functioned as a support for Co₃O₄ nanocrystals but also functioned as a co-catalyst for the enhancement in phenol removal efficiency. The surface nitridation and Co₃O₄ modification treatment further improved the removal rate of the phenol pollutants and brought in the higher oxidation degree. Our finding may open new perspectives for pursuing exceptional activity for catalytic ozonation reaction.