This question asks how far science and technology can actually solve the world's waste problem, and where technical fixes fall short and other answers, like changing behaviour, policy or how much we consume, are needed.
Question type: To what extent
An ETG General Paper original study guide to the 2024 A-Level GP Paper 1 essay on science & technology. Not affiliated with, or endorsed by, UCLES, Cambridge Assessment or SEAB. A study aid, not an official answer.
The question assumes waste disposal is mainly a technical problem awaiting a technical fix, rather than a behavioural and economic one about how much we consume.
conditions: technology solves the disposal problem where the bottleneck is capacity or recovery, but not where the bottleneck is consumption volume or political will.
How to approach it. Calibrate how far technology can solve waste disposal, naming what 'solve' and 'the problem' actually mean before answering.
Science and technology can solve waste disposal where the binding constraint is treatment capacity or material recovery, but they cannot solve it where the constraint is the rising volume we generate, because no recovery rate keeps pace with limitless growth in waste.
Sanitary landfill, waste-to-energy, water reclamation and material recovery are all engineering victories, and a society that bet against them would be buried. Yet accepting this conflates managing waste with solving the problem: every one of these advances handles waste better without reducing how much we make, which is why a country can lead the world on treatment and still face a landfill running out.
Science and technology solve the disposal problem where it is a problem of capacity and recovery, and Singapore is the proof; but where the problem is the volume itself, the fix is behavioural and economic, and no machine can want less on our behalf.
Whether technology solves waste disposal depends less on the technology and more on the domain of the bottleneck: in the engineering domain the answer is largely yes, but in the domain of governance, incentives and global inequality the same technology fails, because the obstacle is who pays and who enforces, not what is possible.
AI-sorted recovery lines, blockchain waste-tracking and sensor-based bins do automate parts of the governance problem, and dismissing them would be unserious. But each still needs a policy to mandate it, a budget to fund it and citizens to use it, so the technology removes a step without removing the dependence on human institutions that decide whether to deploy it at all.
Science and technology have very nearly solved the engineering of waste disposal; what they cannot solve is the domain that actually decides outcomes, the governance, the pricing and the global inequality that determine whether the proven solution is ever built or merely exported.
Option A runs on conditions (capacity and recovery, where technology wins, versus consumption volume, where it loses), keeping the lens on the waste itself. Option B runs on domain (engineering versus governance versus the global), arguing the real bottleneck is institutional, not technical. Both are defensible: A concedes the consumption limit a marker expects; B reframes the question, which scores higher if controlled.

These outlines are free to read. Book a trial lesson to have your own GP essays marked against the band descriptors, the way ETG teaches General Paper from the exam backwards.