PAH Analysis of Sediments from Pleasant Run Creek adjacent to a Former Manufactured Gas Plant

Polycyclic aromatic hydrocarbons (PAHs) are known to be toxic and some are even carcinogenic. A prime source of PAHs is coal tar. Coal tar can be found in soils and sediments near former manufactured gas plants (MGPs) or coking facilities. This study involves characterizing the chemical composition and concentrations of PAHs within stream sediments at a former MGP site by Pleasant Run Creek in Indianapolis, Indiana. To characterize the stream sediments, sediment cores were removed from various locations along the stream and sampled with depth. Sample collection was conducted in partnership with the environmental engineering firm, August Mack Environmental. Samples were taken at 2 feet intervals from the surface (0.5 ft.) to a depth of 8 to 12 feet. Since the study is ongoing, samples continue to be processed in the lab to analyze concentrations of 17 PAHs by gas chromatography-mass spectrometry (GC/MS). A comparison between measured concentrations and published risk-based criteria will be performed to determine if observed concentrations pose an environmental risk. The results are expected to indicate significant PAH weathering (i.e., variable composition) in the sediment, due to the water volume and velocity of Pleasant Run Creek being affected by storm events. The results of this project will be used by August Mack Environmental to evaluate remediation strategies

Modernizing Life Cycle Assessment Via Informatic Techniques

Life Cycle Assessment (LCA) is a widely recognized tool used to evaluate environmental impacts of a product or process, based on environmental inventory database, and supply chain information. Although significant progress has been made on the development of LCA methodology and growth of LCA applications, there are issues to be addressed. As the number of LCA related publication increases rapidly it becomes challenging to gain a comprehensive understanding on the state-of-the-art: only a small number of review papers have been published and they tend to narrowly focus on a particular field or application while literature search is largely done manually. In addition, almost all LCA software tools are still using the legacy desktop application which have steep learning curve, unfriendly user interface, and complicated installation and maintenance requirements. Moreover, life cycle inventory databases, which serve as the data foundation of LCA, are designed and managed as a centralized structure with slow updates and low spatial and temporal resolution i.e., not supply chain specific. The development of informatics techniques opens up numerous opportunities to address these issues. This dissertation reports one of the first effort on applying informatics techniques i.e., automatic content analysis (ACA), webbased application, and blockchain to modernize LCA. For the first time, ACA is applied on LCA related research to comprehend the big picture and get a better overview regarding the focus and evolution of LCA related research. The results show that while the field changed overtime, the most interested environmental category remained to be carbon emissions. However, the result also shows that while computer science has evolved considerably, modern informatic techniques have only had a scattered impact on LCA. To overcome the limitation of current LCA software, an idea of developing a web-based application to benefit LCA implementation is proposed, especially for a certain type of industry with complex and hierarchical bills of materials. In cooperation with International Electronics Manufacturing Initiative (iNEMI), a web-based application is developed named Eco-impact Estimator (EiE). EiE is capable of performing quick and straightforward eco-impact estimation, especially for information and communication technology (ICT) products, with more than 50 users currently. To further optimize LCA, decentralized structure might be necessary. A new method is needed that can automatically back track supply chain along with material flow, with robust data availability and privacy. A blockchain-based LCA (BC-LCA) is proposed to solve this problem, with a framework built up, a detailed mechanism discussed, and a case study provided based on a practical industrial supply chain. Result shows that BC-LCA could improve data availability by providing increased data privacy and timeliness with the application of blockchain. Furthermore, the more nodes from a supply chain that join in BC-LCA, the better it could get. With the help of informatic techniques, LCA can be improved significantly, including generating a more quantitative research overview, developing a more user-friendly LCA webbased application for ICT product manufacturing, and providing a LCA framework with more data availability, data privacy and data timeliness. Though it is still necessary to estimate the budget for such implication, which e is left as future work, trialing on interdisciplinary solutions may bring a new possibility to classic LCA

The Application of Blockchain-Based Life Cycle Assessment on an Industrial Supply Chain

Life cycle assessment (LCA) is a widely recognized tool used to evaluate the environmental impacts of a product or process, based on the environmental inventory database and bills of material. Data quality is one of the most significant factors affecting the analysis results. However, currently, most datasets in inventory databases are generic, i.e., they may represent the material and energy flow of a process at a market average, instead of a specific process used by a manufacturer. As a result, stockholders are unable to track their supply chain to find out the actual environmental impact from each supplier and to compare the environmental performance of alternative options. In this paper, we developed a new framework, i.e., blockchain-based LCA (BC-LCA), where blockchain technology is adapted to secure and transmit inventory data from upstream suppliers to downstream manufacturers. With BC-LCA, more specific data can be acquired along the supply chain in a real-time manner. Moreover, the availability, accuracy, privacy, and automatic update of inventory data can be improved. A case study is provided based on an industrial supply chain to demonstrate the utilization of BC-LCA

Pollution Contribution Response in Governance and Potential Pollution Factors in Licun River

The development of the city results in deterioration of the water quality of the Licun River. As a result, years of governance have been conducted to improve its water quality. In order to clarify the response changes of water quality in the water governance, the governance process is divided into three stages (2000–2007, 2008–2016, 2017–2020) according to different priorities. Spearman’s rank correlation coefficient and the comprehensive pollution index are applied to analyze the variation of water quality response at various stages. In addition, the main pollution contributions with the governance changes were obtained. It is concluded that flood control and incomplete river pollution interception have a limited effect on water quality improvement, with NH3-N (ammonia nitrogen) and COD (chemical oxygen demand) being the main pollution contributions at the first stage. At the second stage, the point source control and sewage treatment facilities significantly improve water quality, and the main pollution contributions are NH3-N and TP (total phosphorus). At the third stage, sewage treatment facilities and supporting pipelines are improved, water sources are replenished, and the main pollution contribution is TN (total nitrogen). For further treatment, the factors affecting pollution are analyzed, including the contradiction of sewage system, point source pollution caused by pipe network problems, shortage of water resources, sludge pollution, and non-point source pollution

Load quantification and effect evaluation of urban non-point source pollution in the Licun River based on SWAT model

With the gradual control of point source pollution, the impact of urban nonpoint source pollution on river water quality is becoming more prominent. Regarding the current problem that nonpoint source pollution loads in urban basins are difficult to quantify and the impact on water quality is difficult to analyze, the Licun River basin in Qingdao was selected as the research object. Through the field survey and surface accumulation sampling analysis of the basin, the evaluation model of urban nonpoint source pollution was constructed by revising the land type data of the basin and the urban database of the SWAT model. The results showed that concentration of nitrate in precipitation was most sensitive to the simulation of nitrogen loading; organic P in baseflow was most sensitive to the simulation of phosphorus loading. The Nash–Sutcliffe efficiency coefficient (ENS) and the coefficients of determination (R2) of the SWAT model for runoff, total phosphorus (TP), and total nitrogen (TN) in the simulation validation period meet the model requirements,indicating a good model fit. In addition, the spatial and temporal distribution characteristics of urban nonpoint source pollution of TN and TP in 2021 were analyzed. In July, rainfall-runoff from the Licun River basin was the most polluted. HIGHLIGHTS High-accuracy simulation of urban nonpoint source pollution in small-scale basins.; Revising the land type data of the basin and modifying the model's town database.; Realize quantification and impact analysis of urban nonpoint source pollution load.

Periodic Arrays of Metal Nanoclusters on Ultrathin Fe-Oxide Films Modulated by Metal-Oxide Interactions

Rational design of highly stable and active metal catalysts requires a deep understanding of metal–support interactions at the atomic scale. Here, ultrathin films of FeO and FeO2–x grown on Pt(111) are used as templates for the construction of well-defined metal nanoclusters. Periodic arrays of Cu clusters in the form of monomers and trimers are preferentially located at FCC domains of FeO/Pt(111) surface, while the selective location of Cu clusters at FeO2 domains is observed on FeO2–x/Pt(111) surface. The preferential nucleation and formation of well-ordered Cu clusters are driven by different interactions of Cu with the Fe oxide domains in the sequence of FeO2-FCC > FeO-FCC > FeO-HCP > FeO-TOP, which is further validated by density functional theory calculations. It has been revealed that the p-band center as a reactivity descriptor of surface O atoms determines the interaction between metal adatoms and Fe oxides. The modulated metal-oxide interaction provides guidance for the rational design of supported single-atom and nanocluster catalysts