full transcript

From the Ted Talk by Charlotte Degot: A more accurate way to calculate emissions

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.

Solution

  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