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It will be important for land managers, ecological researchers and policymakers to understand how predicted climate changes may affect the flora of Illinois. A climate change vulnerability assessment was completed in 2011 for the162 Animal Species in Greatest Need of Conservation using NatureServe’s Climate Change Vulnerability Index (CCVI) tool. Here we selected 73plant species found in Illinois and calculated their relative vulnerabilities to predicted climate changes, also using the NatureServe CCVI tool. We selected species from several groups that we felt would be broadly representative of the Illinois flora. These groups included: rare plants, invasive plants, important prairie species, important woodland/savanna species, important forest species, and plants important to society. We compiled and entered data regarding both the species’ exposures to predicted climate changes and their sensitivities to those changes. Exposures were determined by overlapping species range maps for Illinois with maps of temperature and moisture (AET:PET) predictions for the middle of this century. Species sensitivities were determined by interviewing between 4 and 12 experts for each plant species. Experts answered questions found in the CCVI tool regarding the species’ biologies, ecologies and behaviors. Results for each individual survey were averaged for each species. Results fell into one of five vulnerability categories: Extremely Vulnerable, Highly Vulnerable, Moderately Vulnerable, Not Vulnerable/Presumed Stable, and Not Vulnerable/Increase Likely. Results for these 73species in Illinois fell into all 5 vulnerability categories, with the majority (67%) falling into the Presumed Stable category. The species most vulnerable to predicted climate changes were all of conservation concern; most were federal or state listed species. Native species tended to be more vulnerable than non-natives, and plants important to prairies, savannas and forests were equally vulnerable to predicted changes. The four species were ranked as ...

Growing interest in improving the energy consumption efficiency in residential and commercial buildings has led to the emergence of intelligent energy management systems. This growing technology allows the transformation of the outdated electric distribution network within buildings to a smart and intelligent system. A major challenge in the development of such infrastructure is the need for low cost, integrated, self-contained, and non-invasive wireless sensor nodes. While an electric meter provides the utility company with information regarding the total energy consumption, no information is provided to the consumers regarding the energy consumed by individual appliances. Such visibility can provide consumers with the ability to better control and manage their energy usage leading to a reduced overall energy consumption. This work explores the design and development of a self-contained and non-invasive integrated system intended for real-time electricity monitoring within residential and commercial buildings. The proposed system includes an Energy Harvester, an electric current sensor, a Micro-controller Unit, and a wireless communication device. The proposed system is self-powered and non-invasive, which offers a promising solution in providing real time information regarding the energy distribution within buildings. The design featured in this work provides an innovative approach in the development of a customized interface circuitry that is designed to collect and regulate the energy from the Energy Harvester. The entire sensor node will operate under a power budget in the range of microwatts collected by the Energy Harvester. A Wireless MCU is programmed to acquire, process, and transmit the data from the sensor to the central hub via Bluetooth Low Energy connectivity. The real-time data transmitted to the central hub provides detailed information regarding the energy consumed by individual appliances within the building.

Photosynthetic light-harvesting proceeds by the collection and highly efficient transfer of energy through a network of pigment-protein complexes. Inter-chromophore electronic couplings and interactions between pigments and the surrounding protein determine energy levels of excitonic states and dictate the mechanism of energy flow. The excitonic structure (orientation of excitonic transition dipoles) of pigment-protein complexes is generally deduced indirectly from x-ray crystallography in combination with predictions of transition energies and couplings in the chromophore site basis. Here, we demonstrate that coarse-grained excitonic structural information in the form of projection angles between transition dipole moments can be obtained from polarization-dependent two-dimensional electronic spectroscopy of an isotropic sample, particularly when the nonrephasing or free polarization decay signal rather than the photon echo signal is considered. The method provides an experimental link between atomic and electronic structure and accesses dynamical information with femtosecond time resolution. In an investigation of the Fenna-Matthews-Olson complex from green sulfur bacteria, energy transfer connecting two particular exciton states in the protein is isolated as being the primary contributor to a cross peak in the nonrephasing 2D spectrum at 400 fs under a specific sequence of polarized excitation pulses. The results suggest the possibility of designing experiments using combinations of tailored polarization sequencesto separate and monitor individual relaxation pathways.

"February 6, 1981." ; "Distribution category UC-63b." ; "This work was performed for the Jet Propulsion Laboratory, California Institute of Technology, under NASA Contract NAS7100 for the U.S. Department of Energy, Division of Solar Energy. The JPL Low-Cost Solar Array Project is funded by DOE and forms part of the DOE Photovoltaic Conversion Program to initiate a major effort toward the development of low-cost solar arrays." ; Includes bibliographical references. ; Mode of access: Internet.

2015 Fall. ; Includes illustrations (some color). ; Includes bibliographical references. ; Thin film heterojunction solar cells based on CuSb(S,Se)2 absorbers are investigated for two primary reasons. First, antimony is more abundant and less expensive than elements used in current thin film photovoltaics, In, Ga, and Te, and so, successful integration of Sb based materials offers greater diversification and scalability of solar energy. Second, the CuSb(S,Se)2 ternary is chemically, electronically, and optically similar to the well-known, high efficiency, CuIn(S,Se)2 based materials. It is therefore postulated that the copper antimony ternaries will have similar defect tolerant electronic transport that may allow for similar highly efficient photoconversion. However, CuSb(S,Se)2 forms a layered crystal structure, different from the tetrahedral coordination found in conventional solar absorbers, due to the non-bonding lone pair of electrons on the antimony site. Thus examination of 2D antimony ternaries will lend insight into the role of structure in photoconversion processes. To address these questions, the semiconductors of interest (CuSbS2 & CuSbSe2) were first synthesized on glass by combinatorial methods, to more quickly optimize process condi- tions. Radio-frequency (RF) magnetron co-sputtering from Sb2(S,Se)3 and Cu2(S,Se) targets were used, without rotation, to produce chemical and flux graded libraries which were then subjected to high throughput characterization of structure (XRD), composition (XRF), con- ductivity (4pp), and optical absorption (UV/Vis/NIR). This approach rapidly identified processes that generated phase pure material with tunable carrier concentration by apply- ing excess Sb2(S,Se)3 within a temperature window bound by the volatility of Sb2(S,Se)3 and stability of the ternary phase. The resulting phase pure thin films were then incor- porated into the traditional CuInGaSe2 (CIGS) substrate photovoltaic (PV) architecture, and the resulting device performance was correlated to ...

Approximately 370 million tons of plastic are being produced annually (Plastics Europe, 2020). Only a small portion is recycled due to poor waste management practices. An estimated eight million tons of plastic moves from the land to ocean every year (IUCN, 2018) while rivers transport between 1.15 and 2.41 million tons of debris into the oceans annually (Lebreton et al., 2017). The pervasiveness of microplastics (MP), plastic polymer debris less than 5mm in diameter, in aquatic environments, their ingestion by freshwater fish, and the accumulation of MP through trophic transfer in food webs raise concern for the sustainability of fisheries, food security, and public health (Campbell et al., 2017; Wagner et al., 2019). Fish are excellent indicators of aquatic ecosystem health since they integrate changes in their physical environment (Pinheiro et al., 2017). Assessing MP contamination in fish therefore provides valuable information about MP concentrations in freshwater systems and raises attention to potential risks. My research investigated how fish feeding habitats, trophic position, body size (weight and length), and species variation influence MP ingestion and accumulation in St Lawrence River freshwater fish by collecting samples of pelagic, bentho-pelagic, and benthic fish species. I hypothesized that MP particles would be present in the GI tracts of most fish samples regardless of feeding habitat since MP can be found throughout the water column in most aquatic environments, and that the GI tracts of benthic fish would contain higher concentrations of MP beads and fragments while the GI tracts of pelagic fish would contain higher concentrations of MP fibers. I expected a greater concentration of plastic particles would be found in benthic than pelagic fish because of the prevalence of MPs found in the St Lawrence River sediments (Crew et al., 2020; Castaneda et al., 2014), and the data modeling performed by Lebreton et al. (2018). To address these questions, I collected 73 fish (seven species) from the ...

Temperature and salinity are two of the key properties of ocean water masses. The distribution of these two independent but related characteristics reflects the interplay of incoming solar radiation (insolation) and the uneven distribution of heat loss and gain by the ocean, with that of precipitation, evaporation, and the freezing and melting of ice. Temperature and salinity to a large extent, determine the density of a parcel of water. Small differences in temperature and salinity can increase or decrease the density of a water parcel, which can lead to convection. Once removed from the surface of the ocean where 'local' changes in temperature and salinity can occur, the water parcel retains its distinct relationship between (potential) temperature and salinity. We can take advantage of this 'conservative' behavior where changes only occur as a result of mixing processes, to track the movement of water in the deep ocean (Figure 1). The distribution of density in the ocean is directly related to horizontal pressure gradients and thus (geostrophic) ocean currents. During the Quaternary when we have had systematic growth and decay of large land based ice sheets, salinity has had to change. A quick scaling argument following that of Broecker and Peng [1982] is: the modern ocean has a mean salinity of 34.7 psu and is on average 3500m deep. During glacial maxima sea level was on the order of {approx}120m lower than present. Simply scaling the loss of freshwater (3-4%) requires an average increase in salinity a similar percentage or to {approx}35.9psu. Because much of the deep ocean is of similar temperature, small changes in salinity have a large impact on density, yielding a potentially different distribution of water masses and control of the density driven (thermohaline) ocean circulation. It is partly for this reason that reconstructions of past salinity are of interest to paleoceanographers.

Climate change is undeniably one of humanity’s utmost concerns. Human actions, such as deforestation, exhaustive use of fossil fuels, and intensive farming, are changing weather patterns, threatening polar bears, and causing other detrimental environmental changes. Most people are aware of these effects, yet many are not engaging in behaviour to alleviate the impacts of climate change. This project examined through a literature review and data analysis to determine the extent to which instructional strategies could change these types of behaviours. This quantitative study analyzed 2006 PISA (Program for International Student Assessment) data to determine if the pedagogy utilized by climate change teachers in Kyrgyzstan, Turkey, and Qatar impacted students’ willingness to engage in climate-change mitigating behaviour. These countries were selected because they are Muslim cultures of varied histories with different political and social situations. Thus, this study was additionally interested in discovering how the pedagogical approaches of teachers differed in their impact on students’ willingness to engage in climate-change mitigating behaviour among these three Muslim countries. Factor and reliability analyses were conducted in addition to a regression analysis, which indicated a small but significant relationship between instructional approaches and behaviour to lessen climate change. Instructional approach accounted for 4.0 percent of the climate change mitigating variable for Kyrgyzstan, 2.1 percent for Turkey, and 2.3 percent for Qatar. Future research could focus on the development of a questionnaire to better establish the range of factors that could lead to students more often engaging in behaviour to alleviate the effects of climate change.

The applications of WSN can be quiet numerous. In applications like battlefield monitoring, grid power generation, health systems, sensors are deployed on large scale. During such deployment, energy efficiency must be proficient, which requires clustering, in the WSN architecture. Clustering architecture requires maintenance of sensor nodes due to alfunctioning of sensor which becomes depleted of energy. As some nodes leaves and some are being replaced, congestion is introduced in the network due the limited processing capability of memory, computations, and bandwidth condition. This paper proposes one of the energy efficient clustering techniques (HAEEW), using asynchronous data transfer (ADT), which has been modeled from data transfer technique (EEHCR), and using hierarchical clustering. Our model uses synchronization in clock time queries in one and each iterations round time, to determine cluster head, and head-set member formation, using Ad hoc on-demand energy aware routing protocols (AOERP) to make decision. In each iteration, the head-set members receives message request from neighboring nodes to confirm their average distance estimation, in which to transmit aggregated data to the base station. In a sensor deployment, which is aimed for data collection, control and management of sensor nodes, play a vital role, where nodes can be adjusted to boost energy in the network life time. We used matlab for simulations analysis of our result.

Describes the importance of shade trees within city limits, including: how to plan the layout of street trees; the various types of trees best suited for city growth; and how to properly maintain city-grown trees.