Level 3 language summary, Pupil's Book sample and YLE mapping. structures and grammar covered in each unit of this level. View PDF Footprints Levels mapped against Cambridge Young Learners Exam (YLE) grammar. View PDF. Footprints 3 pupil's book. Файл формата pdf; размером 46,95 МБ. Добавлен пользователем svetlana_nhd ; Отредактирован language as an instrument of communication. Pleasure in learning more English. Interest in meeting the. Footprints 3 characters. C2 Mathematical competence.
|Language:||English, Spanish, Indonesian|
|Distribution:||Free* [*Registration needed]|
Footprints 3 McMillan - Download as PDF File .pdf) or read online. Footprints 3 McMillan. Read Carol Footprints 3 Pupil s Book - Download as PDF File .pdf) or read online. footptint pupil 's book. Carol Read. Footprints 3. Language Summary. Introduction. 1 My day. 2 People and food. 3 My community. 4 People and possessions. 5 A world of sport.
Major sectors that emit greenhouse gases GHG include fossil fuel combustion, land conversion, livestock production, and crop production. Following established best practices for carbon accounting, the C footprint is reported in three categories of scopes, which reflect how institutional decisions are capable of directly influencing carbon emissions. This article presents a newly developed integrated tool that allows institutions to track and manage their carbon and nitrogen footprints together. Combining these two tools expands the ability of institutions to account for a wider range of environmental impacts.
This article presents the integrated nitrogen and carbon footprint tool for institutions; compares the nitrogen and carbon footprints of five institutions by several metrics; and identifies reduction strategies that will reduce both the nitrogen and carbon footprints. Combining the distinct institution-level nitrogen and carbon footprint tools requires four phases: The first three will be complete when the first version of the integrated tool is launched in , and projections and scenarios will be incorporated in a future version of the tool.
The sectors included in the carbon and nitrogen footprint calculations were compared, and any differences in the sectors were identified. For example, the sector refrigerants is part of the C footprint but not the N footprint.
All sectors in each stand-alone footprint tool are included in the integrated tool. For any sector that was in one tool but not the other, a review was conducted to determine if that sector should be added to the other footprint tool. For example, refrigerants have a negligible nitrogen footprint so were not added to the Nitrogen Footprint Tool. The methods and equations for the two footprints were aligned for consistency and comparability in the integrated tool.
The calculations were aligned by first ensuring that the data input describing resource consumption e. Any conversions necessary to calculate the total resource consumption e. For most sectors, the only difference in the two footprint calculations is the emissions factors used e. However, the calculations for the carbon and nitrogen footprint do diverge for food consumption and food production because of the different pathways through which greenhouse gases and nitrogen pollution are released from these sectors.
Complete documentation for the carbon and nitrogen footprints can be found in the user's guide for each tool. The food sector will be added to the C footprint using the N footprint methods for estimating the weight of food downloads. Food weights can be scaled based on the percent of downloads or percent of weight represented in the subset of data.
Each food product is placed in a food category based on up to three ingredients, and the weight is distributed evenly across those ingredients. Guidance for assigning food categories is provided in the Nitrogen Footprint User's Manual. For food production, the C footprint is calculated by multiplying a weight of food by a greenhouse gas emissions factor, 18 whereas the N footprint has several components that are summed: See the Supplementary Material, Table S1 and Equations for more information about the food calculations, which may be found online at www.
Because the two footprints mostly represent different environmental impacts, the footprints will be reported separately as the C footprint units of metric tons CO 2 e and the N footprint units of metric tons of N. It should be noted that there is one area of overlap: Nitrous oxide N 2 O is both a greenhouse gas and a part of the N footprint. However, nitrous oxide is included in both footprints because of its contribution to the nitrogen cascade e. The geographic scale for the two footprints also differs.
Greenhouse gas emissions are well mixed and contribute to global climate effects regardless of where they are emitted. Nitrogen losses can have a range of effects, from local to global, depending on the type of nitrogen released. The carbon and nitrogen footprints are each reported on a total basis, on a per capita basis, by sector, and by scope. The results are reported as the total C footprint and total N footprint.
The per capita C footprint and per capita N footprint are reported to normalize the data to each institution's population. The per capita footprints are calculated using full-time equivalents FTE , which consider how often different populations e.
For more information, see Table S2 in Supplementary Material, which may be found online at www.
Scope 1 includes on-site stationary combustion, fleet vehicles, and research animals; scope 2 is downloadd electricity; and scope 3 includes commuting, air travel, food production, wastewater, and feed for research animals.
Results for the carbon and nitrogen footprints are presented as a case study here for the following five institutions: Nitrogen footprint results were obtained from Castner et al. Additional offsets e.
The calculation year is fiscal year The total footprints were compared by sector and by scope. The footprints were also compared on a per capita basis for the total footprint, on a per capita basis by sector utilities , and the footprint per kilogram of food downloadd food. Additional comparison metrics for the N footprint are explored in Castner et al. The effect of management strategies on the carbon and nitrogen footprints were explored for the five institutions and are presented as case studies in this article.
These scenarios do not include projections of changes in population because they aim to show the direct effect of specific changes in practices. However, when institutions are setting carbon and nitrogen footprint reduction goals, projections must be included. A review of the data inputs required for the existing carbon and nitrogen footprints identified substantial overlap in the utilities and transport sectors Table 1.
Also see Table S3 for a complete list of data inputs, which may be found in the Supplementary Material online at www. In these sectors, the C footprint incorporates more options e. The C footprint does not currently include a major sector of the nitrogen footprint: As part of this integration, the C footprint of food will be incorporated into the combined carbon and nitrogen footprint tool.
When footprints are compared on a per capita basis, the effects of different practices begin to emerge Figure 1B, 1D. Across the carbon and nitrogen footprints, the two largest sectors are food and utilities. Institution nitrogen N and carbon C footprints by sector, shown as: Footprints are shown for: The food production carbon and nitrogen footprints are driven by the types and amounts of food downloadd by an institution.
For example, Dickinson College has larger food footprints because nearly all students eat most meals on campus and the campus hosts summer programs that include meals in its dining services, which is not the case for the other universities in the comparison. The utilities footprints differ across institutions based on the total energy consumption and the types of fuel used. For example, the University of New Hampshire has small utilities carbon and nitrogen footprints because its energy is derived from an on-campus cogeneration facility that uses processed methane generated at the local landfill.
The University of Virginia has a larger utilities footprint because its campus includes a hospital and because most of its electricity is downloadd and the electricity fuel mix has a high percentage of coal.
Carbon and nitrogen footprint results can also be presented by scopes, which describe how directly emissions are related to institution activities scope 1 is the most direct; scope 3 is the least; see Figure 2. This means that most carbon emissions that are currently tracked occur closer to the institution, while most nitrogen losses occur elsewhere.
Greenhouse gas emissions contribute to the global greenhouse effect regardless of where they are emitted. Conversely, nitrogen losses have more local pollution effects for most forms of nitrogen, such as local water quality and air quality effects. Given this, institutions may consider implementing two N footprint reduction goals: Many of the benefits from an overall nitrogen reduction goal could occur in ecosystems far removed from the institution itself, but those environmental impacts are still the responsibility of the institution.
Institution nitrogen N and carbon C footprints by scope, shown as: The carbon and nitrogen footprint results of the five institutions were compared Figure 3. For example, Dickinson has a large food N footprint because 94 percent of students have meal plans, and a moderate per capita C footprint.
We infer that this find represents the rediscovery of the site where the footprints were originally found in The track-bearing surfaces are fully lithified tufa deposits and include a trampled area with human footmarks.
One of them clearly represents a footprint CPC, 26 em with toe impressions. A nearby surface presents an incomplete track way of 13 footprints, of which 7 are also well-preserved, mostly with well-defined toe impressions. The best preserved footprint at the first-found trampled site is designated as "the rediscovery track". It is about 27 em long by 53 IV Simposio Intemacional EI hombre temprano en America 10 em wide, but owing to the imperfect preservation these measurements are less accurate than those obtained for the main track way described below.
Footprints in the main track way found nearby are 27 ern wide and 10 m long with steps varying from em in length. The first footprint identified in the sequence number 1 shows four clear toe impressions, and is followed by a gap of 3 meters before footprint number 5. This average measurement is consistent with step lengths of 81, 75 and 74 ern respectively between tracks, 5 and 6, 6 and 7, and 7 and 8 mean of Track number 5 shows only poorly impressed toe impressions but the morphology of the heel and ball is clear.
Tracks are well preserved and it is possible to identify 4 or 5 clear toe impressions in each footprint. There is a gap of 2. Thus, the average length of the ten steps between track 10 and track II is In order to protect the site, precise location of the deposits is not given.
The tracks occur on a surface that is moderately extensive, but still partially covered with overburden and alluvium. The surface has the potential to preserve additional tracks for future study. Does the discovery also represent the location of the finds? We suggest that the site where the two MUDE specimens were originally excavated IS identical with the location of the footprints for the following reasons: 1 At least a dozen footprints are found at separate locations on a single surface; 2 this is the only confirmed site with in situ footprints; 3 the footprints quite closely match the two MUDE specimens in size and style and mode of preservation; 4 in the two quarried areas, but especially at the footprint site described herein, the tufa is quite well-bedded showing an irregular alternation of more- and less- porous layers.
Cross sections of the track-bearing layer also appear very similar.
The pools near the track site contain deposits of homogenous mud containing abundant small gastropod shells. Lithified, but mound-like, unstratified deposits of this type can be found on the banks of several "pozas", and attest to the fact that the pools were previously more extensive with higher water levels. By contrast, the bedded tufa deposits are associated with seeps that produce saturated substrates, not pools. Depending on local geochemical and hydrological conditions, these wet areas may be overgrown by vegetation or may develop as barren zones in which it is easy to observe modern animal footprints.
Our observations of some of these barren areas show that they are in the process of being "encrusted" or mineralized to varying degrees. Thus, it is possible to observe or extract 54 Gonzalez et al.
Age of the Cuatro Cienegas footprints A total of nine sub-samples were taken from the 2 ern thick travertine section containing the footprints, and analysed for U- Th isotopic composition using the method outlined in Hoffmann et al. This value was used to correct for detrital contamination. Corrected U-series dates from the uppermost layer Discussion The chronology of the arrival of humans in the Americas remains controversial since directly dated human fossils are rare, and chronologies often rely on the dating of associated non-anthropogenic material.
Recently, hominid presumably H. With the exception of one track from Chile dated at about 12, years Dillehay, , the oldest well-documented and well-preserved hominid tracks are from Nicaragua, California and Argentina, and date to about , years BP Williams, ; Rector, ; Bay6n and Politis, , respectively. Footprints are thus uncommon and the record from the Americas more than scarce. The new Coahuila tracks from Cuatro Cienegas provide direct evidence of human presence.
These footprints impressed in fast-forming travertine can be dated using U-Th disequilibrium and add evidence for an antiquity of human occupation of These data are comparable with the earliest known direct dates on human fossils in Central Mexico and the Yucatan Peninsula Gonzalez Gonzalez et al. Age of the Cuatro Cienegas footprints A total of nine sub-samples were taken from the 2 em thick travertine section containing the footprints, and analysed for U-Th isotopic composition using the method outlined in Hoffmann et al.
Isochron analyses using five coeval samples from the base of the travertine give a detrital. It Table 1. Lab code In U! OOS 0. OOS OOS g OOI 1. Decay constants A are 9. Literature cited Bay6n, C. Retnsta de la SeccionArqueologia 6: 8S Crane, H. R University of Michigan radiocarbon dates. Science Dillehay, T.
While it is possible to deal with such a level of spatial detail in LCIA, this is traditionally not the case for MRIOs, since trade flows are usually available on a country-basis only. Accurate linking of spatial detail is crucial, as argued by Godar et al. Irrigation areas, as another example, may lie in areas with little impact on ecosystems and could therefore be unproblematic. It would therefore also here be beneficial to conduct analyses at small spatial scales, if the spatial resolution of Eora would allow for this.
However, we checked the alignment between water use data and impact factors data for the examples of maize, wheat and cotton in the US see SI and found that water is indeed to a large extent consumed in areas with higher ecosystem impact, thus being to a certain degree aligned. Data on production and environmental pressures are nowadays generally available at the grid-cell level.
Therefore, the basic MRIO framework is amenable to this enhancement. Subnational areas, or grid cells, may potentially be treated as additional regions. While this improved detail would increase the accuracy of the results, we have no reason to expect a priori that this shortcoming introduces any systematic bias into the results. The issue of error in MRIO models has been discussed extensively in the literature 46 , 47 , 48 especially in regards to aggregation and allocation error. Limitations A major advance of LC-Impact is the inclusion of spatial detail and the consideration of per-species vulnerability see Methods.
Having impact factors available at a fine spatial detail is a significant step forwards as this allows for calculating differentiated impacts for different regions. Moreover, differences in species richness and the vulnerability of species can be taken into account. There is, however, a potential information bias regarding the presence of threatened species, even for well-studied taxonomic groups including mammals 49 , meaning that it may appear there are more species threats in one region simply because there is more threat reporting in that region.
The IUCN Red List data used in this study may be biased because data availability varies between regions and taxonomic groups towards 1 better-studied taxonomic groups and 2 countries which study taxonomic groups more intensively, i. Nevertheless, LC-Impact is based on the latest available data of multiples species of several taxonomic groups mammals, birds, amphibians, reptiles.
This ensures an adequate representation of the overall species present. In addition to biased over-reporting, under-reporting may also occur.
Several taxa, in particular plants, insects and fungi, are still underrepresented in the IUCN dataset.
The issue of sample bias is discussed by Larsen et al. We therefore most likely underestimate the level of biodiversity threat. We combine the impacts of several pressures into one final result see Table 3. This allows us to see a more complete picture of the set of impacts that occur alongside each other instead of just focusing on single pressures. However, despite the common unit used, we have to stress that we do not assess the potentially synergistic effects of cumulative impacts such as changes in the local water availability due to a change in land use and thus a change in water storage capacity in the ground.
These complex interactions are so far missing in LCIA and will need to be addressed in the future. Eutrophication impacts are comparatively very small, for example, which is most likely an underestimation.
Eora provides data for agricultural sources of available nitrogen and phosphorus see Table 3 , but not for other sources, such as sewage. This means that we neglect part of the nutrient sources responsible for eutrophication. On the other hand, characterization factors for freshwater eutrophication only cover phosphorus and the one for marine eutrophication only nitrogen since each is the major limiting nutrient in the respective ecosystem.
However, impacts from an over-availability of the other nutrient e. Full size table The need for covering the consequences of anthropogenic activities Current biodiversity loss and ecosystem degradation puts our planet beyond its boundaries This has been acknowledged by the global community and several international initiatives have been set in place.
The Aichi Biodiversity Targets of the Convention on Biological Diversity aims to significantly reduce habitat loss and degradation by 53 and the European Commission announced the goal to halt biodiversity loss within the EU by , while also increasing their contribution to prevent and reduce global biodiversity loss Most recently, two of the newly released sustainable development goals of the United Nations directly address the issue of biodiversity loss SDG 15 and ecosystem degradation SDG These initiatives must be accompanied with the appropriate tools to assess the drivers behind biodiversity loss and to design responses to counter it.
Until now, resource usage was used as a proxy for the impact. However, our study highlights the need for going further along the DPSIR framework in order to cover the consequences of anthropogenic trade and consumption and not just the pressure of those activities. This allows one to highlight the trade flows, resource use and emissions with the most impact and helps consumers to identify trade-offs between different trade options and their consequences.
The proposed framework provides a possibility to track the impact of biodiversity loss through all stages of the DPSIR framework and identify the underlying drivers. This enables the design of targeted policy responses to halt further ecosystem degradation.
Materials and Methods Overview In this study a standard Leontief demand-pull model 48 was applied to an environmentally extended multi-region input output EE-MRIO table in order to calculate a consumption-based account, the footprints of resource demand. The resource demands are the non-monetary inputs to production land, fertilizer, phosphorus P and nitrogen N emissions, etc. These pressures were translated into measures of environmental impact using the characterization factors from the LC-Impact model Those factors report the impact per unit of resource demand, e.