ESEGH common mistakes
ESEGH · Understand the traps and how to avoid them.
Treating grid emissions factor as a single constant (e.g., using annual average) when the question specifies marginal versus average, or time-of-day and location-specific factors, then reporting a CO2e result with the wrong factor basis.
Candidates learn one national factor early and reuse it everywhere, missing that the exam tests whether you know which factor is methodologically correct for the decision (consequential vs. attributional accounting).
What to do instead
Before computing, state the accounting question (attributional or consequential), then pick the matching factor: average for inventory reporting, marginal for intervention/abatement analysis. Practice tagging each practice item as 'inventory' or 'intervention' before touching numbers.
Confusing installed capacity (MW) with energy generated (MWh) when computing capacity factor, annual yield, or share of demand, and then dividing or multiplying by 8,760 hours incorrectly.
Units are visually similar and questions often give capacity and a capacity factor in the same stem; candidates shortcut to capacity comparisons and forget the hours conversion or the difference between AC and DC ratings.
What to do instead
Write the dimensional chain explicitly: MW x hours x capacity factor = MWh. Convert DC to AC using the stated ratio before any capacity-factor math. Sanity-check results against typical capacity factors (solar 15-25%, onshore wind 25-45%).
Answering demand-response and energy-efficiency items by citing technology benefits without quantifying the load-shape effect (peak kW reduction versus annual kWh savings) that the question actually asks about.
Study material emphasizes technology descriptions; candidates memorize 'LEDs save energy' or 'DR shifts load' but not the distinction between peak demand reduction, energy savings, and load shifting, which drive different program economics.
What to do instead
For every efficiency/DR item, classify the metric as kW (peak), kWh (energy), or time (shift), then answer in that metric. Build a one-page table of measures with typical peak vs. annual impacts and cost-effectiveness test (TRC, utility cost test) implications.
Mixing up scope 1, 2, and 3 boundaries, especially assigning purchased electricity to scope 1 or treating upstream fuel extraction as scope 1 for the reporting company.
Organizational boundary (equity share vs. operational control) and scope definitions interact; candidates conflate physical location of emissions with ownership/control.
What to do instead
Apply a two-step test: (1) does the company own or control the source? then scope 1; (2) is it purchased energy? then scope 2; (3) is it value-chain? then scope 3. Practice with a consolidation approach stated up front, and always state the boundary assumption in your answer.
Treating levelized cost of energy (LCOE) as a complete investment decision metric and ignoring system costs, integration costs, or the discount rate sensitivity the question probes.
LCOE is the most memorized metric; candidates default to it even when the question asks about system value, curtailment, or firm capacity, and they overlook that discount-rate assumptions can flip rankings.
What to do instead
When an item mentions variability, storage, or grid services, evaluate levelized cost of storage (LCOS) or system LCOE alongside LCOE. Always identify the discount rate and lifetime assumptions before comparing options, and note that LCOE excludes integration and transmission costs.
Describing climate risk only in terms of chronic physical hazards (temperature, sea level) while omitting transition risk, liability risk, and the adaptation-versus-mitigation distinction the question is testing.
Media coverage emphasizes physical climate impacts; candidates under-study transition (policy, technology, market) and liability channels, and conflate adaptation with mitigation responses.
What to do instead
For every climate-risk item, run a checklist: physical (acute/chronic), transition (policy, technology, market, reputational), liability. Then classify the response as mitigation (reduce emissions) or adaptation (reduce vulnerability). State which channel and which response the question targets.
Applying a policy instrument (carbon tax, cap-and-trade, feed-in tariff, renewable portfolio standard) to the wrong failure mode, e.g., recommending a carbon tax to solve a network externality or an RPS to internalize a global externality.
Instruments are taught by description rather than by the market failure they correct; candidates match keywords rather than diagnosing the externality, information problem, or public-good characteristic.
What to do instead
Diagnose the market failure first (global externality, local pollution, learning-by-doing, network, information asymmetry), then select the instrument that targets it. Memorize a mapping table: global externality to carbon price; learning spillovers to subsidies/auctions; local pollution to standards or local pricing.
Ignoring grid integration constraints-curtailment, ramp rates, inertia, hosting capacity-when assessing a high-renewable scenario, and concluding that nameplate capacity equals delivered clean energy.
Candidates reason from generation totals and overlook that system operators must balance instantaneous supply and demand; flexibility, transmission, and storage are treated as afterthoughts.
What to do instead
For any high-VRE scenario, explicitly account for curtailment, required flexible capacity, and transmission/storage needs. Compare nameplate versus firm capacity and state the flexibility resources assumed. Practice computing a simple residual-load curve and identifying the ramping requirement.
Failing to apply additionality, baseline, and leakage tests when evaluating an offset or emissions-reduction project, and crediting reductions that would have happened anyway.
Candidates focus on the tonnage claimed and skip the integrity tests; baseline setting and leakage are abstract until practiced, so they are easy to omit under time pressure.
What to do instead
For every offset/reduction item, run four tests in order: additionality, baseline accuracy, leakage, permanence. Write one sentence per test before selecting an answer. Reject projects whose baseline cannot be shown to be counterfactual or whose leakage is unaddressed.
Solving resilience and adaptation items with a single deterministic climate scenario instead of using scenario ranges and stress-testing thresholds, then presenting one number as the answer.
Candidates seek a single 'right' projection and ignore that decision-relevant resilience work uses multiple scenarios, return periods, and threshold analysis; they also forget uncertainty communication.
What to do instead
Use at least a low/high scenario pair plus a stress-test threshold (e.g., the hazard level at which the asset fails). Report the range and the decision criterion, not one point estimate. Practice framing answers as 'under scenario X the threshold is exceeded at Y, triggering adaptation Z'.