IB Environmental systems and societies (ESS) - Old SL Internal Assessment Example

The research question clearly identifies both the independent and dependent variables and specifies the precise scope in Al Zahiyah, Abu Dhabi, ensuring a focused and measurable inquiry.

The introduction provides substantial AQI data and local ‘urban canyon’ context, but delves into extended health effects that distract from the core environmental issue. Consider tightening focus.

Survey statistics are well integrated as secondary data, reinforcing site selection rationale and demonstrating coherence between methods and context.

The risk assessment table lists only two hazards and omits ethical considerations (e.g., surveying minors, public filming). Expand to include comprehensive ethical review.

The systematic grab sampling rationale is well justified, clearly linking interval selection to data stability and replicability.

The variables table provides clear methods but the justification for using secondary experimenters and smartphones is based on a non‐specific citation (“Muodon”). Clarify the source or replace it.

The choice of the uHoo monitor is well justified, citing its reliability and ease of data retrieval, which increases confidence in pollutant measurements.

The materials list is comprehensive, detailing all necessary equipment for air and traffic measurement, which enhances replicability and safety.

The procedural steps are clear and replicable, specifying site setup, interval timing, and repetition. This design supports reliable data collection.

Ethical considerations around informed consent and anonymity for survey participants are not addressed. Include an ethics section to discuss confidentiality and voluntary participation.

Incorporate quantitative historical traffic growth data to strengthen context and justify focusing on current density trends. This will enhance connections between past and present conditions.

Raw data tables are detailed but column headings lack units and error bar notation. Include explicit units (e.g. ppm, µg/m³) and uncertainty notation.

Several raw data entries include symbols like $\tau$ and overlined numerals without explanation. Clarify these annotations or remove them to uphold data integrity.

The processed data methodology is clearly explained, detailing Excel functions and conversion to density. This transparency supports reproducibility.

Mean values are calculated, but uncertainty propagation (e.g. combining $\pm 1$ errors) is not addressed. Incorporate error analysis in processed data.

Line graphs effectively illustrate pollutant trends against traffic density, aiding visual interpretation of correlations.

The graphs lack error bars and clear legends for different pollutants. Add these elements to convey data variability and support robust analysis.

Pearson’s $r$ is introduced but no discussion of statistical significance or $p$-values is provided. Include significance testing to validate correlations.

The correlation summary table concisely presents $r$-values and qualitative strength, enhancing reader comprehension of comparative pollutant relationships.

Including the IB Maths correlation strength chart clarifies interpretation of $r$-values and aligns analysis with IB standards.

The discussion situates conclusions within local urban canyon and coastal wind contexts, effectively linking results to the environmental setting.

The evaluation acknowledges broader socio‐economic and policy implications only in passing. Expand on feasibility and potential trade‐offs of proposed applications.

The multi‐factor source table effectively highlights that traffic is one of several significant contributors to PM and NO₂, enriching environmental evaluation.

The evaluation section effectively identifies strengths (sensor reliability, replication) and weaknesses (external wind effects, single device use).

Suggested improvements (longer intervals) are meaningful but limited. Propose additional extensions such as meteorological controls or a paired sensor network.

The application section proposes fuel price increases but lacks economic or social impact analysis to justify feasibility.

Citing public transport uptake data strengthens the application argument by demonstrating community receptiveness to alternatives.

The title concisely conveys the environmental focus and location, providing immediate context. This aids reader orientation and reinforces clarity throughout the report.

The hypothesis uses “vehicles/10 min”, which is inconsistent with “vehicles/min” in the research question. Ensure variable definitions remain uniform to avoid confusion.

The survey table is overloaded with demographic and behavioral questions, raising potential participant fatigue. Consider reducing optional fields to improve completion rates.

The manual Pearson $r$ calculation is overly detailed and interrupts flow. Summarize in a concise table and reference the calculation tool.

The narrative interpretation is verbose and occasionally unclear, with grammatical slips. Edit for concision, consistency, and correct notation of units.