ESS

1. What makes ESS distinct?

An ESS EE must:

• examine interactions between natural systems and human activities

• focus on measurable environmental variables or clearly defined social impacts

• use ecological and environmental science concepts alongside socio environmental perspectives

• collect or analyse valid primary or secondary environmental data

• integrate scientific, cultural, political or economic factors where appropriate

• apply systems thinking to explain causes, feedback loops or consequences

• evaluate environmental, social and ethical implications of findings

Your essay should feel interdisciplinary, not purely scientific or purely social.

2. What counts as a suitable ESS topic?

A strong topic is:

• centred on a clear environmental issue with a measurable component

• focused on interactions between people and natural systems

• supported by data that reflect environmental change or impact

• narrow enough to investigate in depth

• aligned with ESS theory rather than Biology, Chemistry or Geography alone

Examples of suitable topic types

• impact of land use change on local biodiversity

• effectiveness of waste reduction or recycling initiatives

• factors influencing water quality in a defined area

• evaluation of renewable energy adoption in a community

• relationship between air quality and traffic patterns

Examples of unsuitable topic types

• pure ecology (belongs in Biology)

• pure environmental chemistry (belongs in Chemistry)

• pure human geography or politics without environmental data

• broad global questions without a local focus

• projects requiring specialised environmental testing equipment

ESS requires an integrated environmental and societal perspective supported by data.

3. Using data in ESS

Your essay must draw upon environmental or socio environmental data, such as:

• water, soil or air quality measurements

• biodiversity counts or ecological indicators

• survey data connected to environmental behaviour

• GIS based environmental datasets

• official environmental reports or policy documents

Avoid

• anecdotal claims about environmental issues

• unverified online environmental data

• purely opinion based surveys with no environmental measurement

• datasets too coarse for meaningful analysis

Data must be interpreted using both environmental science and societal context.

4. Research methods appropriate for ESS

Your methods may include:

• water, soil or air sampling using safe, accessible equipment

• biodiversity surveys using quadrats or transects

• observation based fieldwork supported by quantitative measurement

• questionnaires linked to measurable environmental indicators

• analysis of published environmental datasets

• evaluation of local environmental policy outcomes

Methods must demonstrate both scientific and socio environmental thinking.

5. Expectations for analysis

ESS analysis should:

• identify patterns or trends in environmental data

• link results to ecosystems, cycles, flows or systems models

• explain how human activities influence environmental outcomes

• discuss cultural, economic or political factors where relevant

• use graphs, tables and diagrams meaningfully

• remain centred on the environmental system defined in the research question

Analysis must integrate both scientific understanding and social context.

6. Evaluation in ESS

Evaluation may include:

• precision and reliability of environmental measurements

• limitations of sampling design or fieldwork methods

• bias or representativeness of survey responses

• influence of external variables on environmental outcomes

• effectiveness of environmental policies or mitigation measures

• extent to which findings can be generalised

• ethical or cultural considerations in human environment interactions

A strong ESS EE explains both the environmental significance and societal implications of findings.

7. Common pitfalls in ESS EEs

Avoid these issues, as they frequently lead to weak outcomes:

• topics that belong entirely to Biology, Chemistry or Geography

• broad investigations with no measurable variables

• surveys without supporting environmental data

• unsafe or unethical environmental sampling

• insufficient field data for meaningful analysis

• essays that become advocacy pieces rather than investigations

• lack of integration between environmental and social components

8. Model research questions

Here are high quality examples of ESS research questions:

1. How has organic waste composting influenced soil quality in community gardens in Hong Kong?

2. To what extent does roadside vegetation reduce particulate matter concentrations along urban footpaths?

3. How effectively has a plastic bag charge reduced consumer waste generation in a local district?

4. To what extent does land use type influence macroinvertebrate diversity in small urban streams?

5. How has household energy behaviour changed following the introduction of a local sustainability campaign?

Each question is interdisciplinary, measurable and suitable for ESS.