📁 Topic 6 · 6.1 Impacts of Technology
6.1b Environmental impacts of digital technology
Edexcel 4CP0 · iGCSE Computer Science · ~11 min read
Notes

Energy Consumption

Digital technology consumes vast amounts of electricity:

  • Data centres that power cloud services, websites, and streaming use enormous amounts of energy — estimated to account for 1–2% of global electricity consumption
  • Device use — billions of computers, smartphones, and IoT devices draw power constantly
  • Cryptocurrency mining is particularly energy-intensive, using specialised hardware running 24/7
  • Much electricity still comes from fossil fuels, contributing to greenhouse gas emissions and climate change

Electronic Waste (E-Waste)

E-waste refers to discarded electronic devices — old phones, computers, TVs, printers, and cables. It is one of the fastest-growing waste streams globally.

  • E-waste contains toxic materials including lead, mercury, cadmium, and flame retardants — hazardous to human health and the environment if improperly disposed of
  • Many devices are sent to developing countries where informal recycling exposes workers to toxic chemicals
  • Rapid technology cycles (planned obsolescence) mean devices are replaced before the end of their usable life
  • Only around 20% of global e-waste is formally recycled

Manufacturing Impacts

  • Producing devices requires rare earth metals (e.g. cobalt, lithium) — mined in environmentally damaging processes, often in politically unstable regions
  • Manufacturing semiconductors (chips) requires large quantities of ultra-pure water and chemicals
  • The carbon footprint of producing a device can be greater than that of using it over its lifetime

Positive Environmental Impacts of Technology

Technology also enables environmental improvements:

  • Remote working reduces commuting and office energy consumption
  • Smart energy systems optimise electricity grid use and reduce waste
  • AI in agriculture reduces pesticide and water usage
  • Paperless systems reduce paper consumption and deforestation
  • Renewable energy monitoring — sensors and AI improve efficiency of wind and solar farms
  • Videoconferencing replaces international flights

Green Computing

Green computing refers to practices aimed at reducing the environmental impact of digital technology:

PracticeBenefit
Energy-efficient hardware (low-power CPUs, SSDs)Reduces electricity consumption
Data centre efficiency (cooling, virtualisation)Less energy per unit of computing
Using renewable energy to power data centresReduces carbon footprint
Device repair and refurbishment schemesExtends device life, reduces e-waste
Responsible e-waste recyclingRecovers valuable materials, prevents toxic pollution
Cloud computing (shared infrastructure)More efficient than individual on-premise servers

Emerging Technologies

New computing technologies are being developed that could transform how we process information in the future.

Quantum Computing

Traditional computers use bits (0 or 1). Quantum computers use qubits, which can exist in multiple states simultaneously (superposition) and can be linked (entanglement), allowing certain types of problems to be solved exponentially faster than classical computers.

  • Potential applications: breaking current encryption, drug discovery, weather modelling, optimisation problems
  • Still largely experimental; requires extreme cooling conditions; prone to errors (decoherence)
  • Could render current RSA encryption obsolete — driving research into quantum-safe cryptography

DNA Computing

DNA computing uses DNA molecules to store and process information, exploiting the massive parallelism of biochemical reactions.

  • DNA can store data at extraordinary density — far exceeding silicon-based storage
  • Potential for solving complex combinatorial problems in parallel
  • Currently very slow to read/write and highly experimental; not a replacement for conventional computers yet

Artificial Intelligence and Machine Learning

Artificial intelligence (AI) enables computers to perform tasks that typically require human intelligence — recognising images, understanding speech, making decisions. Machine learning is a subset of AI where systems learn from data rather than being explicitly programmed.

  • Applications: medical diagnosis, self-driving vehicles, recommendation systems, fraud detection, natural language processing
  • Raises ethical concerns: bias in decision-making, job displacement, surveillance, accountability for AI decisions

Nanotechnology

Nanotechnology involves working with materials and devices at the scale of nanometres (billionths of a metre). In computing, it drives miniaturisation of transistors, enabling more powerful and energy-efficient chips.

  • Current transistors are just a few nanometres in size — approaching atomic scale limits
  • Nanotech could enable new computing paradigms, ultra-precise medical devices, and novel materials
  • Challenges include manufacturing precision, heat dissipation, and quantum effects at nanoscale
📝 Exam Tip: Exam questions on this topic often ask you to "discuss" or "evaluate" the environmental impacts — always give both negative impacts (energy consumption, e-waste, manufacturing) and positive impacts (paperless working, smart systems, remote work). Balance your answer and conclude.
⚠️ Common Mistakes
  • Saying technology is always bad for the environment — it has significant negative impacts, but also enables many positive environmental solutions
  • Forgetting manufacturing impacts — the environmental cost doesn't start when you switch a device on; it begins when the raw materials are mined
  • Ignoring e-waste in answers about environmental impact — this is a major and growing concern that the exam expects you to know
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