full transcript

## Unscramble the Blue Letters

Let’s emxanie the glass for bottles. The way they calculate glass emissions is the following. They take the total amount of glass bought last year — let’s say 1,000 tons. They multiply it by a conversion factor, which represents the average kilos of CO2 equivalent for one ton of glass — let’s say 950. 950 x 1000 makes 950,000. Of course this is hugely inaccurate because it does not take into account all the numerous factors that impact actual emissions, so it’s hard to set tagerts and action plans. This is where the sustainability team calls data scientists to come in and process detailed data about the type of glass, the coolr of the gasls, the rienycclg sahre, the supplier country of origin, the transportation mode, by brand, by product. They can simulate the design and the supply chain and integrate in the calculation the importance of the glass color — 1.5 tiems more emissions for a clear bottle versus a green bottle; the importance of the country of origin — twice the amount of emissions for one country versus another one, depending on the energy mix; the importance of the design itself — for the same tatol weight, 1.5 times more emissions for one design versus another one. Instead of having one big, average number, you now have a model which correlates and calculates esniismos at a granular level.

## Open Cloze

Let’s _______ the glass for bottles. The way they calculate glass emissions is the following. They take the total amount of glass bought last year — let’s say 1,000 tons. They multiply it by a conversion factor, which represents the average kilos of CO2 equivalent for one ton of glass — let’s say 950. 950 x 1000 makes 950,000. Of course this is hugely inaccurate because it does not take into account all the numerous factors that impact actual emissions, so it’s hard to set _______ and action plans. This is where the sustainability team calls data scientists to come in and process detailed data about the type of glass, the _____ of the _____, the _________ _____, the supplier country of origin, the transportation mode, by brand, by product. They can simulate the design and the supply chain and integrate in the calculation the importance of the glass color — 1.5 _____ more emissions for a clear bottle versus a green bottle; the importance of the country of origin — twice the amount of emissions for one country versus another one, depending on the energy mix; the importance of the design itself — for the same _____ weight, 1.5 times more emissions for one design versus another one. Instead of having one big, average number, you now have a model which correlates and calculates _________ at a granular level.

1. total
2. targets
3. emissions
4. examine
5. glass
6. times
7. color
8. recycling
9. share

## Original Text

Let’s examine the glass for bottles. The way they calculate glass emissions is the following. They take the total amount of glass bought last year — let’s say 1,000 tons. They multiply it by a conversion factor, which represents the average kilos of CO2 equivalent for one ton of glass — let’s say 950. 950 x 1000 makes 950,000. Of course this is hugely inaccurate because it does not take into account all the numerous factors that impact actual emissions, so it’s hard to set targets and action plans. This is where the sustainability team calls data scientists to come in and process detailed data about the type of glass, the color of the glass, the recycling share, the supplier country of origin, the transportation mode, by brand, by product. They can simulate the design and the supply chain and integrate in the calculation the importance of the glass color — 1.5 times more emissions for a clear bottle versus a green bottle; the importance of the country of origin — twice the amount of emissions for one country versus another one, depending on the energy mix; the importance of the design itself — for the same total weight, 1.5 times more emissions for one design versus another one. Instead of having one big, average number, you now have a model which correlates and calculates emissions at a granular level.

## Frequently Occurring Word Combinations

### ngrams of length 2

collocation frequency
artificial intelligence 5
climate impact 3
action plans 3
financial accounting 2
set meaningful 2
sustainability team 2
emissions reduction 2

## Important Words

1. account
2. action
3. actual
4. amount
5. average
6. big
7. bottle
8. bottles
9. bought
10. brand
11. calculate
12. calculates
13. calculation
14. calls
15. chain
16. clear
17. color
18. conversion
19. correlates
20. country
21. data
22. depending
23. design
24. detailed
25. emissions
26. energy
27. equivalent
28. examine
29. factor
30. factors
31. glass
32. granular
33. green
34. hard
35. hugely
36. impact
37. importance
38. inaccurate
39. integrate
40. kilos
41. level
42. mode
43. model
44. multiply
45. number
46. numerous
47. origin
48. plans
49. process
50. product
51. recycling
52. represents
53. scientists
54. set
55. share
56. simulate
57. supplier
58. supply
59. sustainability
60. targets
61. team
62. times
63. ton
64. tons
65. total
66. transportation
67. type
68. weight
69. year