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Academic literature on the topic 'Footprint'

Author: Grafiati

Published: 4 June 2021

Last updated: 20 February 2023

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Journal articles on the topic "Footprint"

1

Chen, Bilin, Weiran Qian, Yiduo Yang, Hong Liu, and Laili Wang. "Carbon Footprint and Water Footprint of Cashmere Fabrics." Fibres and Textiles in Eastern Europe 29, no. 4(148) (August 31, 2021): 94–99. http://dx.doi.org/10.5604/01.3001.0014.8235.

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Given the serious problems of climate change, water shortage and water pollution, researchers have paid increasing attention to the concepts of the carbon footprint and water footprint as useful indices to quantify and evaluate the environmental impacts of the textile industry. In this study, assessment of the carbon footprints and water footprints of ten kinds of cashmere fabrics was conducted based on the PAS 2050 specification, the Water Footprint Network approach and the ISO 14046 standard. The results showed that knitted cashmere fabrics had a greater carbon footprint than woven cashmere fabrics. Contrarily, woven cashmere fabrics had a greater water footprint than knitted cashmere fabrics. The blue water footprint, grey water footprint and water scarcity footprint of combed sliver dyed woven cashmere fabric were the largest among the ten kinds of cashmere fabrics. The main pollutants that caused the grey water footprints of cashmere fabrics were total phosphorus (TP), chlorine dioxide, hexavalent chromium (Cr (VI)) and sulfide. The leading contributors to the water eutrophication footprint were total nitrogen, ammonia nitrogen, chemical oxygen demand and TP. These typical pollutants contributed 39% ~ 48%, 23% ~ 28%, 12% ~ 24% and 12% ~ 14% to each cashmere product’s water eutrophication footprint, respectively. The leading contributors to the water ecotoxicity footprint were aniline, Cr (VI) and absorbable organic halogens discharged in the dyeing and finishing process.

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Samkurashvili, Irakli, and Donal S. Luse. "Structural Changes in the RNA Polymerase II Transcription Complex during Transition from Initiation to Elongation." Molecular and Cellular Biology 18, no. 9 (September 1, 1998): 5343–54. http://dx.doi.org/10.1128/mcb.18.9.5343.

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ABSTRACT We obtained exonuclease III (exoIII) footprints for a series of RNA polymerase II transcription complexes stalled between positions +20 to +51. Downstream advance of the exoIII footprint is normally tightly coordinated with RNA synthesis. However, arrested RNA polymerases slide back along the template, as indicated by exoIII footprints in which the last transcribed base is abnormally close to the downstream edge of the footprint. None of the polymerase II complexes stalled between +20 and +51 were arrested. Nevertheless, the exoIII footprints of complexes with 20-, 23-, or 25-nucleotide RNAs resembled those of arrested complexes, with the last transcribed base very close to the footprint’s front edge. The exoIII footprint of the +27 complex was displaced downstream by 17 bp compared to the footprint of the +25 complex. Many complexes between +27 and +42 also showed evidence of sliding back along the template. We compared the effects of template sequence and transcript length by constructing a new template in which the initial transcribed sequence was duplicated beginning at +98. The exoIII footprints of transcription complexes stalled between +122 to +130 on this DNA did not resemble those of arrested complexes, in contrast to the footprints of analogous complexes stalled over the same DNA sequences early in transcription. Our results indicate that the RNA polymerase II transcription complex passes through a major, sequence-independent structural transition about 25 bases downstream of the starting point of transcription. The fully mature form of the elongation complex may not appear until more than 40 bonds have been made.

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Marsa, Mardhatillah, Yudha Nurhantari, and Santosa Budiharjo. "PENENTUAN RUMUS TINGGI BADAN BERDASARKAN PANJANG JEJAK KAKI PADA ETNIS JAWA." Indonesian Journal of Legal and Forensic Sciences (IJLFS) 8, no. 1 (November 15, 2018): 1. http://dx.doi.org/10.24843/ijlfs.2018.v08.i01.p01.

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Background: Proof of footprints in forensic identification can be used in the determination of personal identification, for example the height. Estimated the height is done by measuring the length of footprints. Based on the literature, height was correlates directly with long bones. Footprints are made by the soles of the feet that are part of the long bones. The calculation of the height is more accurate using the formula derived from the population concerned so that testing needs to be done on each population. Objective: To find out whether there is a correlation between the length of the footprint of a person's height, especially the Javanese ethnic population and determine the estimation formula of height based on the length of the footprint. Methods: The study subjects consisted of 100 men and 100 Javanese ethnic women aged 21-30 years who were taken by consecutive sampling technique. Measurements were made by measuring subject height and footprint imprint then calculated each of the length of right and left footprints. Result: The average height of male Javanese ethnic is 172,36 cm and woman 158,45 cm. The average length of right and left footprints in males is 23,02 cm and female 22 cm. Pearson correlation test on all subjects had r value of 0.968 for right footprint and r 0.967 for left footprint. On the male subject has r value 0.908 for right foot print and r 0.902 for left footprint. In the female subject has r value 0.927 for the right foot print and r 0.931 for the left footprint. Conclusion: There is a strong relationship between the length of a person's footprint with height and this study has earned a formula of height estimation based on the length of the footprint on the Javanese. Keywords: height, footprint, identification, Javanese ethnics

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Kan, Daxue, and Weichiao Huang. "An Empirical Study of the Impact of Urbanization on Industry Water Footprint in China." Sustainability 12, no. 6 (March 13, 2020): 2263. http://dx.doi.org/10.3390/su12062263.

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How to advance new urbanization initiatives and reduce the water footprint of industries is one urgent issue about urbanization that needs to be resolved. Based on spatial dynamic panel data, we used the system GMM (Generalized Method of Moments) to study the impact of urbanization on the industrial water footprint. The results show that, overall, urbanization increases the industrial water footprint, industrial virtual water footprint, and industrial gray water footprint in China. There are sectoral and regional differences in the impact of urbanization. Specifically, urbanization reduces the agricultural water footprint and agricultural virtual water footprint but raises the agricultural gray water footprint. Urbanization increases the manufacturing water footprint, manufacturing virtual water footprint, and gray water footprint. Urbanization reduces the virtual water footprint of the service industry but increases the water footprint and gray water footprint in the service industry. At the regional level, urbanization increases the industrial water footprint and gray water footprint across the three major regions. In the eastern region, urbanization has little effect on increasing the industrial water footprint, and reduces the industrial virtual water footprint, whereas in the central and western regions urbanization increases the industrial virtual water footprint. In all three regions, urbanization reduces the agricultural water footprint, increases the manufacturing and service water footprints, reduces the virtual water footprints of agriculture and services, and increases the gray water footprint of agriculture, manufacturing, and services. In the eastern region, the reducing effect of urbanization is the greatest and the increasing effect of urbanization is the smallest. Additionally, in the eastern region, urbanization has reduced the virtual water footprint of manufacturing, whereas in the central and western regions urbanization has increased the virtual water footprint of manufacturing.

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Buchanan, Rachel, Erica Southgate, Shamus P. Smith, Tiana Murray, and Brittany Noble. "Post no photos, leave no trace: Children’s digital footprint management strategies." E-Learning and Digital Media 14, no. 5 (September 2017): 275–90. http://dx.doi.org/10.1177/2042753017751711.

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Given that today’s children are prolific users of the internet, concern has been raised about the future impact of the digital footprints they are currently generating. Here, we report on the Best Footprint Forward project which utilised focus groups to investigate the digital footprint awareness of 33 children (ranging in age from 10 to 12 years old) from three primary schools in regional Australia. The children were very aware of their digital footprints and cyber safety but had little awareness of the positive potential of digital footprints. Instead, they exercised their agency through the use of strategies to minimise their digital footprint. We offer an alternative perspective to the dominant discourse that insists that a digital footprint is primarily a liability and seek to counter the positioning of children as naïve, passive consumers of digital culture. We conclude that 10–12 years old is an appropriate age to begin to educate for positive digital footprint curation as this would build on children’s demonstrated knowledge of cyber safety and supplement their existing digital footprint management strategies with beneficial alternatives.

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Stolen, Eric D., Donna M. Oddy, Mike L. Legare, David R. Breininger, Shanon L. Gann, Stephanie A. Legare, Stephanie K. Weiss, Karen G. Holloway-Adkins, and Ron Schaub. "Preventing Tracking-Tube False Detections in Occupancy Modeling of Southeastern Beach Mouse." Journal of Fish and Wildlife Management 5, no. 2 (August 1, 2014): 270–81. http://dx.doi.org/10.3996/032014-jfwm-025.

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Abstract Quantifying habitat occupancy of the southeastern beach mouse Peromyscus polionotus niveiventris is important for managing this threatened species throughout its limited range. Tracking tubes were used to detect the southeastern beach mouse in coastal areas on the federal lands of the Kennedy Space Center, Cape Canaveral Air Force Station, and Canaveral National Seashore. Because this method relied on observations of footprints, detections of beach mice were confounded by the co-occurrence of cotton mice Peromyscus gossypinus, which have wider but slightly overlapping footprint widths. Mice of both species were captured and footprinted using tracking tubes to collect a database of footprints of known identity. These data were used to develop a Bayesian hierarchical model of the cutoff width at which a print could be assigned as a beach mouse with a known probability of error. Specifically, within the model, observed footprint widths were used to estimate a mean and variance of footprint width for each species, while accounting for variation between individual mice. Then, a distribution of new footprint widths was generated for each species by drawing from their modeled distributions. Finally, the new footprints were compared with a range of potential cutoff widths to evaluate the proportion of times the correct decision to exclude or accept the footprint was made. We graphically evaluated the performance of the cutoff widths and chose one that traded off between reducing false positives and retaining more correct detections for use in occupancy models. We explored the use of the cutoff width using occupancy models that allow for false-positive detections, and found that the use of the cutoff performed as expected. Over 40% of primary dune habitat on the Kennedy Space Center was occupied by beach mice during the period sampled. The proportion of vegetated habitat at a site had a negative influence on detection probability. No ecological covariates had a measurable influence on beach mouse occupancy, probably due to the limited range of environmental variation in the sampled region. The use of a cutoff for footprint width resulted in a reliable method to deal with false-positive detections in tracking tubes with small mammals and allowed the use of occupancy models that rely on certain detection.

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Scott, LuAnn, Daniel LaFoe, and Clifford F. Weil. "Adjacent Sequences Influence DNA Repair Accompanying Transposon Excision in Maize." Genetics 142, no. 1 (January 1, 1996): 237–46. http://dx.doi.org/10.1093/genetics/142.1.237.

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Mobile elements transposing via DNA intermediates often leave small rearrangements, or “transposon footprints,” at sites where they excise. Each excision event leaves its own footprint and, at any given site, these vary in size and sequence. Footprint formation involves DNA repair of sequences flanking the element. We have analyzed the footprints formed by a 2-kb Ds element excising from six different sites in exons of the maize waxy (Wx) gene. We find that groups of footprints left at individual sites are surprisingly nonrandom; different excision products predominate consistently at each site. Less frequent footprints left by each insertion appear related to the predominant type. The data suggest that flanking sequences affect the DNA repair processes associated with element excision. Two models have been proposed to explain footprint formation, one featuring a 5′ exonuclease and the other featuring hairpin loop formation and an endonuclease. Our data have interesting implications for both these models. Evidence is also presented to support the presence of a separate excision mechanism that can remove Ac/Ds elements without leaving any footprint and that operates in parallel with the footprint-forming mechanism.

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Reid, James E., Andreas Pfaffling, and Julian Vrbancich. "Airborne electromagnetic footprints in 1D earths." GEOPHYSICS 71, no. 2 (March 2006): G63—G72. http://dx.doi.org/10.1190/1.2187756.

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Existing estimates of footprint size for airborne electromagnetic (AEM) systems have been based largely on the inductive limit of the response. We present calculations of frequency-domain, AEM-footprint sizes in infinite-horizontal, thin-sheet, and half-space models for the case of finite frequency and conductivity. In a half-space the original definition of the footprint is extended to be the side length of the cube with its top centered below the transmitter that contains the induced currents responsible for 90% of the secondary field measured at the receiver. For a horizontal, coplanar helicopter frequency-domain system, the in-phase footprint for induction numbers less than 0.4 (thin sheet) or less than 0.6 (half-space) increases from around 3.7 times the flight height at the inductive limit to more than 10 times the flight height. For a vertical-coaxial system the half-space footprint exceeds nine times the flight height for induction numbers less than 0.09. For all models, geometries, and frequencies, the quadrature footprint is approximately half to two-thirds that of the in-phase footprint. These footprint estimates are supported by 3D model calculations that suggest resistive targets must be separated by the footprint dimension for their individual anomalies to be resolved completely. Analysis of frequency-domain AEM field data acquired for antarctic sea-ice thickness measurements supports the existence of a smaller footprint for the quadrature component in comparison with the in-phase, but the effect is relatively weak. In-phase and quadrature footprints estimated by comparing AEM to drillhole data are considerably smaller than footprints from 1D and 3D calculations. However, we consider the footprints estimated directly from field data unreliable since they are based on a drillhole data set that did not adequately define the true, 3D, sea-ice thickness distribution around the AEM flight line.

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Gustavsson, D. J. I., and S. Tumlin. "Carbon footprints of Scandinavian wastewater treatment plants." Water Science and Technology 68, no. 4 (August 1, 2013): 887–93. http://dx.doi.org/10.2166/wst.2013.318.

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This study estimates the carbon footprints of 16 municipal wastewater treatment plants (WWTPs), all situated in Scandinavian countries, by using a simple model. The carbon footprint calculations were based on operational data, literature emission factors (efs) and measurements of greenhouse gas emissions at some of the studied WWTPs. No carbon neutral WWTPs were found. The carbon footprints ranged between 7 and 108 kg CO2e P.E.−1 year−1. Generally, the major positive contributors to the carbon footprint were direct emissions of nitrous oxide from wastewater treatment. Whether heat pumps for effluents have high coefficient of performance or not is extremely important for the carbon footprint. The choice of efs largely influenced the carbon footprint. Increased biogas production, efficient biogas usage, and decreased addition of external fossil carbon source for denitrification are important activities to decrease the carbon footprint of a WWTP.

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Zhuo, L., M. M. Mekonnen, and A. Y. Hoekstra. "Sensitivity and uncertainty in crop water footprint accounting: a case study for the Yellow River Basin." Hydrology and Earth System Sciences Discussions 11, no. 1 (January 7, 2014): 135–67. http://dx.doi.org/10.5194/hessd-11-135-2014.

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Abstract. Water Footprint Assessment is a quickly growing field of research, but as yet little attention has been paid to the uncertainties involved. This study investigates the sensitivity of water footprint estimates to changes in important input variables and quantifies the size of uncertainty in water footprint estimates. The study focuses on the green (from rainfall) and blue (from irrigation) water footprint of producing maize, soybean, rice, and wheat in the Yellow River Basin in the period 1996–2005. A grid-based daily water balance model at a 5 by 5 arcmin resolution was applied to compute green and blue water footprints of the four crops in the Yellow River Basin in the period considered. The sensitivity and uncertainty analysis focused on the effects on water footprint estimates at basin level (in m3 t−1) of four key input variables: precipitation (PR), reference evapotranspiration (ET0), crop coefficient (Kc), and crop calendar. The one-at-a-time method was carried out to analyse the sensitivity of the water footprint of crops to fractional changes of individual input variables. Uncertainties in crop water footprint estimates were quantified through Monte Carlo simulations. The results show that the water footprint of crops is most sensitive to ET0 and Kc, followed by crop calendar and PR. Blue water footprints were more sensitive to input variability than green water footprints. The smaller the annual blue water footprint, the higher its sensitivity to changes in PR, ET0, and Kc. The uncertainties in the total water footprint of a crop due to combined uncertainties in climatic inputs (PR and ET0) were about ±20% (at 95% confidence interval). The effect of uncertainties in ET0 was dominant compared to that of precipitation. The uncertainties in the total water footprint of a crop as a result of combined key input uncertainties were on average ±26% (at 95% confidence level). The sensitivities and uncertainties differ across crop types, with highest sensitivities and uncertainties for soybean.

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Dissertations / Theses on the topic "Footprint"

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Tharp, Sean Patrick. "Architecture's ecological footprint." Thesis, Montana State University, 2007. http://etd.lib.montana.edu/etd/2007/tharp/TharpS0507.pdf.

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Chikoti, I. "The ecological footprint." Thesis, Видавництво СумДУ, 2012. http://essuir.sumdu.edu.ua/handle/123456789/26505.

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Dore, Kevin M. "Establishing the neoconservative footprint." Thesis, Monterey, California. Naval Postgraduate School, 2011. http://hdl.handle.net/10945/5726.

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Approved for public release; distribution is unlimited.
This thesis evaluates efforts by neoconservatives during the George W. Bush administration to re-orient and perpetuate their foreign policy principles away from the status quo realist stance dominant during the Cold War. It will examine the main principles of neoconservatives, namely the promotion of democracy through the exertion of American power, and demonstrate how these principles have changed America's foreign policy. This thesis argues that neoconservatives have advocated a forward leaning foreign policy stance by drawing on themes linked to American exceptionalism and democracy promotion. Neoconservatives further perpetuate their arguments by connecting their message to American nationalism and through access to media outlets to voice their positions on issues. Overall, many of the neoconservative policies enacted in the first term of the Bush Administration continue, albeit through different means in the Obama Administration.

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Netz, Johannes, and Jessica Sundin. "Water Footprint of Concrete." Thesis, KTH, Miljöstrategisk analys (fms), 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-173895.

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Vanham, Davy, Adrian Leip, Alessandro Galli, Thomas Kastner, Martin Bruckner, Aimable Uwizeye, Dijk Kimo van, et al. "Environmental footprint family to address local to planetary sustainability and deliver on the SDGs." Elsevier, 2019. http://dx.doi.org/10.1016/j.scitotenv.2019.133642.

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The number of publications on environmental footprint indicators has been growing rapidly, but with limited efforts to integrate different footprints into a coherent framework. Such integration is important for comprehensive understanding of environmental issues, policy formulation and assessment of trade-offs between different environmental concerns. Here, we systematize published footprint studies and define a family of footprints that can be used for the assessment of environmental sustainability. We identify overlaps between different footprints and analyse how they relate to the nine planetary boundaries and visualize the crucial information they provide for local and planetary sustainability. In addition, we assess how the footprint family delivers on measuring progress towards Sustainable Development Goals (SDGs), considering its ability to quantify environmental pressures along the supply chain and relating them to the water-energy-food-ecosystem (WEFE) nexus and ecosystem services. We argue that the footprint family is a flexible framework where particular members can be included or excluded according to the context or area of concern. Our paper is based upon a recent workshop bringing together global leading experts on existing environmental footprint indicators.

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Torkos, Nick. "Footprint-based quadruped motion synthesis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq29244.pdf.

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Danielsson, Lina. "Water footprint calculationfor truck production." Thesis, Uppsala universitet, Institutionen för geovetenskaper, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-220449.

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Water is an irreplaceable resource, covering around two thirds of Earth´s surface, although only one percent is available for use. Except from households, other human activities such as agriculture and industries use water. Water use and pollution can make water unavailable to some users and places already exposed for water scarcity are especially vulnerable for such changes. Increased water use and factors such as climate change make water scarcity to a global concern and to protect the environment and humans it will be necessary to manage this problem. The concept of water footprint was introduced in 2002 as a tool to assess impact from freshwater use. Since then, many methods concerning water use and degradation have been developed and today there are several studies made on water footprint. Still, the majority of these studies only include water use. The aim of this study was to evaluate three different methods due to their ability to calculate water footprint for the production of trucks, with the qualification that the methods should consider both water use and emissions. Three methods were applied on two Volvo factories in Sweden, located in Umeå and Gothenburg. Investigations of water flows in background processes were made as a life cycle assessment in Gabi software. The water flows were thereafter assessed with the H2Oe, the Water Footprint Network and the Ecological scarcity method. The results showed that for the factory in Umeå the water footprint values were 2.62 Mm3 H2Oe, 43.08 Mm3 and 354.7 MEP per 30,000 cabins. The variation in units and values indicates that it is complicated to compare water footprints for products calculated with different methods. The study also showed that the H2Oe and the Ecological scarcity method account for the water scarcity situation. A review of the concordance with the new ISO standard for water footprint was made but none of the methods satisfies all criteria for elementary flows. Comparison between processes at the factories showed that a flocculation chemical gives a larger water footprint for the H2Oe and the Ecological scarcity method, while the water footprint for the WFN method and carbon footprint is larger for electricity. This indicates that environmental impact is considered different depending on method and that a process favorable regarding to climate change not necessarily is beneficial for environmental impact in the perspective of water use.
Vatten är en ovärderlig resurs som täcker cirka två tredjedelar av jordens yta men där endast en procent är tillgänglig för användning. Människan använder vatten till olika ändamål, förutom i hushåll används vatten bland annat inom jordbruk och industrier. Vattenanvändning och utsläpp av föroreningar kan göra vatten otillgängligt, vilket kan vara extra känsligt i de områden där människor redan lider av vattenbrist. Den ökade vattenanvändningen tillsammans med exempelvis klimatförändringar bidrar till att göra vattenbrist till en global angelägenhet och det kommer att krävas åtgärder för att skydda människor och miljö. År 2002 introducerades begreppet vattenfotavtryck som ett verktyg för att bedöma miljöpåverkan från vattenanvändning. Sedan dess har begreppet utvecklats till att inkludera många olika beräkningsmetoder men många av de befintliga studierna har uteslutit föroreningar och bara fokuserat på vattenkonsumtion. Syftet med denna rapport var att utvärdera tre olika metoder med avseende på deras förmåga att beräkna vattenfotavtryck vid produktion av lastbilar, med villkoret att metoderna ska inkludera både vattenkonsumtion och föroreningar. I studien användes tre metoder för att beräkna vattenfotavtrycket för två Volvo fabriker placerade i Umeå och Göteborg. En livscykelanalys utfördes i livscykelanalysverktyget Gabi, för att kartlägga vattenflöden från bakgrundsprocesser. Därefter värderades vattenflödena med metoderna; H2Oe, WFN och Ecological scarcity. Resultatet för fabriken i Umeå gav för respektive metod ett vattenfotavtryck motsvarande 2,62 Mm3 H2Oe, 43,08 Mm3 respektive 354,7 MEP per 30 000 lastbilshytter. Variationen i enheter och storlek tyder på att det kan vara svårt att jämföra vattenfotavtryck för produkter som beräknats med olika metoder. Studien visade att H2Oe och Ecological scarcity tar hänsyn till vattentillgängligheten i området. En granskning av metodernas överensstämmelse med den nya ISO standarden för vattenfotavtryck gjordes men ingen av metoderna i studien uppfyllde alla kriterier. Av de processer som ingår i fabrikerna visade det sig att vattenfotavtrycket för H2Oe och Ecological scarcity metoden var störst för en fällningskemikalie. För den tredje metoden och koldioxid var avtrycket störst för elektriciteten. Detta tyder på att olika metoder värderar miljöpåverkan olika samt att de processer som anses bättre ur miljösynpunkt för klimatförändringar inte nödvändigtvis behöver vara bäst vid vattenanvändning.

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Mummidisetti, Karthik. "Development of My Footprint Calculator." VCU Scholars Compass, 2017. http://scholarscompass.vcu.edu/etd/4887.

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The Environmental footprint is a very powerful tool that helps an individual to understand how their everyday activities are impacting environmental surroundings. Data shows that global climate change, which is a growing concern for nations all over the world, is already affecting humankind, plants and animals through raising ocean levels, droughts & desertification and changing weather patterns. In addition to a wide range of policy measures implemented by national and state governments, it is necessary for individuals to understand the impact that their lifestyle may have on their personal environmental footprint, and thus over the global climate change. “My Footprint Calculator” (myfootprintcalculator.com) has been designed to be one the simplest, yet comprehensive, web tools to help individuals calculate and understand their personal environmental impact. “My Footprint Calculator” is a website that queries users about their everyday habits and activities and calculates their personal impact on the environment. This website was re-designed to help users determine their environmental impact in various aspects of their lives ranging from transportation and recycling habits to water and energy usage with the addition of new features that will allow users to share their experiences and their best practices with other users interested in reducing their personal Environmental footprint. The collected data is stored in the database and a future goal of this work plans to analyze the collected data from all users (anonymously) for developing relevant trends and statistics.

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Awuondo, Benjamin Martin Onyango. "Long range planning of manufacturing footprint." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117977.

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Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, 2018.
Cataloged from PDF version of thesis.
Includes bibliographical references (pages 57-58).
Firms developing an Operations Strategy need to make decisions across a wide spectrum. Within the field of operations strategy, common practice defines the stratification of these decisions into structural and infrastructural elements. Structural decisions relating to the amount of capacity and facilities a firm deploys can impact a firm's cost competitiveness if implemented incorrectly because of the large capital expenditures and time horizons involved. Boston Scientific, a medical device manufacturer, recognizes the importance of operations strategy in achieving competitive success and continually seeks tools that assist in the creation of strategy as it pursues growth. This thesis discusses the development of a scenario planning tool that is focused on estimation of manufacturing footprint requirements for the company's internal manufacturing network. The tool we develop takes a demand forecast as an input and converts it to a physical space requirement in square feet. Additionally, the tool exhibits significant flexibility in being able to develop multiple scenarios, especially given the ability to modify parameters ranging from growth rates to improvement factors within facilities. The tool also offers a deeper level of detail than previously available, with the critical decision unit being the value stream, rather than an aggregation of data to only present factory or network level results. Whilst this work is applied to the context of a medical device manufacturer, the methodology is easily transferable to a range of industries. The work can be applied to any manufacturing setting where investment decisions for new facilities take significant time and capital. Our research of the literature on this topic identified a gap, and the development of the tool is a positive addition to the field of estimation of manufacturing footprint.
by Benjamin Martin Onyango Awuondo.
M.B.A.
S.M.

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Золотова, Світлана Григорівна, Светлана Григорьевна Золотова, Svitlana Hryhorivna Zolotova, and D. S. Volovik. "Solar Power in Reducing Carbon Footprint." Thesis, Видавництво СумДУ, 2011. http://essuir.sumdu.edu.ua/handle/123456789/13461.

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Books on the topic "Footprint"

1

Colet, John. Footprint Vietnam. 4th ed. Bath: Footprint, 2004.

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Newman, Marjorie. Footprint detective. Aylesbury: Ginn, 1995.

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Arghiris, Richard. Footprint Nicaragua. 3rd ed. Bath: Footprint, 2008.

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Footprint Laos. 5th ed. Bath: Footprint, 2008.

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Spooner, Andrew. Footprint Cambodia. 5th ed. Bath: Footprint, 2008.

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Muthu, Subramanian Senthilkannan, ed. Water Footprint. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-4377-1.

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Footprint Croatia. 4th ed. Bath: Footprint, 2008.

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Richard, Leonardi, ed. Footprint Nicaragua. 2nd ed. Bath: Footprint, 2005.

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O'Reilly, Victor. The devil's footprint. [s.l: s.n.], 1998.

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Daisy, Kunstaetter, ed. Footprint Ecuador & Galápagos. 6th ed. Bath: Footprint, 2007.

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Book chapters on the topic "Footprint"

1

Weik, Martin H. "footprint." In Computer Science and Communications Dictionary, 628. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_7409.

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Shekhar, Shashi, and Hui Xiong. "Footprint." In Encyclopedia of GIS, 321. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-35973-1_426.

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Rannik, Üllar, Andrey Sogachev, Thomas Foken, Mathias Göckede, Natascha Kljun, Monique Y. Leclerc, and Timo Vesala. "Footprint Analysis." In Eddy Covariance, 211–61. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-94-007-2351-1_8.

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Jachmann, Hugo. "Footprint Measurements." In Estimating Abundance of African Wildlife, 191–94. Boston, MA: Springer US, 2001. http://dx.doi.org/10.1007/978-1-4615-1381-0_10.

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Leclerc, Monique Y., and Thomas Foken. "Footprint Studies." In Footprints in Micrometeorology and Ecology, 103–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-54545-0_4.

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Harkiolakis, Nicholas. "Carbon Footprint." In Encyclopedia of Corporate Social Responsibility, 309–13. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-28036-8_38.

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Harkiolakis, Nicholas. "Ecological Footprint." In Encyclopedia of Corporate Social Responsibility, 880–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-28036-8_380.

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Wilson, Jeffrey. "Ecological Footprint." In Encyclopedia of Quality of Life and Well-Being Research, 1776–79. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-007-0753-5_3333.

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Gray, N. F. "Ecological Footprint." In Facing Up to Global Warming, 159–76. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-20146-7_7.

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Amrhein, Sebastian, and Dirk Reiser. "Ecological Footprint." In Encyclopedia of Sustainable Management, 1–6. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-02006-4_181-1.

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Conference papers on the topic "Footprint"

1

Fu, Binzhang, and John Kim. "Footprint." In ISCA '17: The 44th Annual International Symposium on Computer Architecture. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3079856.3080249.

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Wu, Haitao, Kun Tan, Jiangfeng Liu, and Yongguang Zhang. "Footprint." In the 4th ACM international workshop. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1614293.1614305.

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Pisleaga, Mihaela. "WATER FOOTPRINT, CARBON FOOTPRINT, ENERGY FOOTPRINT GENERAL ASPECTS AND THEIR INFLUENCE ON SOCIETY." In 15th International Multidisciplinary Scientific GeoConference SGEM2015. Stef92 Technology, 2011. http://dx.doi.org/10.5593/sgem2015/b51/s20.138.

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Gouveia, Rúben, and Evangelos Karapanos. "Footprint tracker." In CHI '13: CHI Conference on Human Factors in Computing Systems. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2470654.2481405.

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Sundarrajan, Aditya, Mingdong Feng, Mangesh Kasbekar, and Ramesh K. Sitaraman. "Footprint Descriptors." In CoNEXT '17: The 13th International Conference on emerging Networking EXperiments and Technologies. New York, NY, USA: ACM, 2017. http://dx.doi.org/10.1145/3143361.3143368.

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Liu, Qiong, Youquan Tian, Chao Wang, Freddy O. Chekem, and John W. Sutherland. "Flexible Job-Shop Scheduling for Reduced Manufacturing Carbon Footprint." In ASME 2017 12th International Manufacturing Science and Engineering Conference collocated with the JSME/ASME 2017 6th International Conference on Materials and Processing. American Society of Mechanical Engineers, 2017. http://dx.doi.org/10.1115/msec2017-2630.

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Abstract:

In order to help manufacturing companies quantify and reduce product carbon footprints in a mixed model manufacturing system, a product carbon footprint oriented multi-objective flexible job-shop scheduling optimization model is proposed. The production portion of the product carbon footprint, based on the mapping relations between products and the carbon emissions within the manufacturing system, is proposed to calculate the product carbon footprint in the mixed model manufacturing system. Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) is adopted to solve the proposed model. In order to help decision makers to choose the most suitable solution from the Pareto set as its execution solution, a method based on grades of product carbon footprints is proposed. Finally, the efficacy of the proposed model and algorithm are examined via a case study.

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McDonald, Tom, and Javier Sanchez. "Characterizing the Geometry and Footprint of the DELVE Survey." In Characterizing the Geometry and Footprint of the DELVE Survey. US DOE, 2021. http://dx.doi.org/10.2172/1826128.

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Williams, Alison. "The creative footprint." In Proceeding of the seventh ACM conference. New York, New York, USA: ACM Press, 2009. http://dx.doi.org/10.1145/1640233.1640327.

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Kacmar, Donna. "Carbon Footprint Analysis." In 5th Annual International Conference on Architecture and Civil Engineering (ACE 2017). Global Science & Technology Forum (GSTF), 2017. http://dx.doi.org/10.5176/2301-394x_ace17.7.

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Liu, Eryun. "Infant Footprint Recognition." In 2017 IEEE International Conference on Computer Vision (ICCV). IEEE, 2017. http://dx.doi.org/10.1109/iccv.2017.183.

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Reports on the topic "Footprint"

1

Bolton, Laura. Fair Water Footprint Stakeholder Mapping. Institute of Development Studies, March 2022. http://dx.doi.org/10.19088/k4d.2022.080.

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This rapid review provides a stakeholder mapping of key players, initiatives, and networks with an operational or strategic interest in the Fair Water Footprint Declaration, based on a list provided by the commissioning adviser. The Declaration commits signatories to take action in terms of sustainable water use whilst minimising pollution. Fair Water Footprint (FWP) is concerned with the water embedded in consumer goods (The Glasgow Declaration for Fair Water Footprints COP 2026, 2021). Considering the water used in the production of a goods or service and whether it is being managed sustainably. FWPs aim to ensure that everything produced ‘does no harm’ and ‘does good’ for water security and climate resilience.

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WATSON, T. B., R. N. DIETZ, R. WILKE, G. HENDREY, K. LEWIN, J. NAGY, and M. LECLERC. FLORIDA TOWER FOOTPRINT EXPERIMENTS. Office of Scientific and Technical Information (OSTI), January 2007. http://dx.doi.org/10.2172/909972.

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Preston, John R., Steven Troutman, Ernie Keen, Mark Silva, Natalie Whitman, Mark Calvert, Mike Cardamone, Marvin Moulton, and Samuel W. Ferguson. Rotorwash Operational Footprint Modeling. Fort Belvoir, VA: Defense Technical Information Center, July 2014. http://dx.doi.org/10.21236/ada607614.

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Winnestaffer, Jessica E. D. Uk’e koley (no footprint) Project. Office of Scientific and Technical Information (OSTI), March 2014. http://dx.doi.org/10.2172/1126406.

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none,. Cement Footprint, December 2010 (MECS 2006). Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1218596.

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none,. Foundries Footprint, December 2010 (MECS 2006). Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1218600.

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none,. Machinery Footprint, December 2010 (MECS 2006). Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1218601.

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none,. Textiles Footprint, December 2010 (MECS 2006). Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1218603.

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none,. Aluminum Footprint, December 2010 (MECS 2006). Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1218609.

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none,. Chemical Footprint, December 2010 (MECS 2006). Office of Scientific and Technical Information (OSTI), June 2010. http://dx.doi.org/10.2172/1218623.

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