A class of students in the UK wanted to investigate how the quality of the urban environment varied between different areas of their town. They decided to do an environmental quality survey. The students decided to focus their investigation on four types of land use: • industry • open space • residential (housing) • shops. They concentrated their investigation on the following hypotheses: Hypothesis 1: The quality of the urban environment varies between different types of land use. Hypothesis 2: The quality of the urban environment improves as distance from the town centre increases.
- (a)The students selected 20 sites (including 5 of each land use) to do their environmental quality survey. At each chosen site there was one main land use. The sites varied in distance from the town centre. The location of the survey sites are shown on Fig. 8.1 below. [Figure 8.1] Complete Fig. 8.1 by marking on the location of two sites, O5 and R3, using the information below. Reference number Main land use Distance from town centre (km) Direction from town centre O5 Open space 4.5 south west R3 Residential 3.8 east north east[2]
- (b)(i)Complete the Traffic category by writing the following descriptions in the correct order on Fig. 8.2. Traffic not moving with many parked vehicles Traffic moving slowly with many parked vehicles Traffic moving freely with few parked vehicles[1]
- (b)(ii)Suggest advantages of using the reference sheet during the environmental quality survey.[2]
- (b)(iii)The students agreed to work in four groups with each group doing the environmental quality surveys in one type of land use. Each group did their surveys at different times of the day. Why might this make the results less reliable?[1]
- (b)(iv)Give two pieces of advice about safety which the students would be given by their teacher.[2]
- (c)(i)The students needed to record the results of their environmental quality survey. In Fig. 8.3 below, draw a results sheet which they could use to record results at each site they visited. Environmental Quality Survey Results Sheet Site reference number ..................................... [Figure 8.3][3]
- (c)(ii)The results of the environmental quality survey are shown in Table 8.1 (Insert). Use these results to complete the dispersion graph in Fig. 8.4 below. Plot the environmental quality score of: the residential site R1 the average (mean) value for industry. [Figure 8.4][2]
- (c)(iii)The students' conclusion was that Hypothesis 1: The quality of the urban environment varies between different types of land use is true. Do you agree with this conclusion? Support your decision with evidence from Fig. 8.4 and Table 8.1.[4]
- (c)(iv)Suggest reasons why there is variation in the quality of the environment between industrial sites in an urban area.[3]
- (d)(i)Use the results in Table 8.1 to plot the environmental quality score of the shops site S5 on the scatter graph, Fig. 8.5, below. [Figure 8.5][1]
- (d)(ii)The students made a conclusion that Hypothesis 2: The quality of the urban environment improves as distance from the town centre increases was false. Support this conclusion with evidence from Fig. 8.5 and Table 8.1.[3]
- (e)Having completed their environmental quality survey the students learned that the scores varied between areas of the town. Suggest two ways that the local government could improve the environment of low-scoring areas. 1 2..[2]
- (f)One group of students wanted to do some extension work to find out the opinions of local people about the environment at the sites they had visited. Describe a fieldwork method the students could use to find out people's opinions.[4]
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Mark scheme
Marking points from the official mark scheme (Oct/Nov 2018). The mark or mark type is shown in brackets.
- [2] Plotting O5 at 4.5 km SW from town centre
- Plotting R3 at 3.8 km ENE from town centre
- [1] Traffic moving freely (with few parked vehicles)
- Traffic moving slowly with many parked vehicles
- Traffic not moving (with many parked vehicles)
- [2] Tells students what they are looking for at each site / gives a description to choose from / categories / specific description
- Gives standardised / range of scores for different situations / scores are specific
- Decision is less subjective / scoring is more objective / unbiased
- [1] Example of conditions which might vary during the day, i.e. noise / litter / traffic
- Creates time as a variable
- [2] Watch out for traffic / keep away from road / be careful crossing road / stay on pavement
- Stay in your group / do not go off by yourself
- Take a mobile phone
- Wear appropriate clothing / high visibility jacket / sunblock, etc.
- Do not talk to strangers / take valuables with you / go into dangerous areas / pick up sharp objects, etc.
- [3] Results sheet to include:
- At least 3 categories
- Scoring system (3 2 1 0) / score out of 3 / score
- Total score / EQ score
- [2] Plotting site R1 = 8 (x)
- Plotting average industry score = 10.6 (---)
- [4] Agree with conclusion / Yes / conclusion is correct – 1 mark reserve (✓ HA)
- There is variation in (mean) scores / values / figures
- Compare any 2 types of land use – shops, residential, open space, industry
- e.g. Highest score is for shops and lowest score is for industry OR
- e.g. Shops score is higher than industry score
- Credit 1 mark(s) for supporting paired data e.g.
- (Average) score for shops = 16.2 and for industry = 10.6
- Disagree with conclusion / conclusion is incorrect= 0 (XHA)
- If no hypothesis conclusion ^HA and credit evidence
- [3] Depends on type / age of industry / different industries / examples of two different industries
- Some industrial areas are more built-up / more concentrated number of buildings / less open space
- Some industries are noisier
- Some industries cause more atmospheric pollution / smell
- Some industries have no waste treatment / recycling
- Variation in type / amount of transport / traffic to industry
- Amount of landscaping in industrial sites vary
- Need reference to variation or comparison between industries
- [1] Plotting score for site S5: 1.7 km distance and 15 EQ score
- [3] No pattern / random / no relationship / no correlation / no trend / scattered / all over
- Same score at different distances from town centre
- Credit 1 mark for paired data which shows that hypothesis is false – need environmental scores and distances from centre
- e.g. EQ score = 20 at 0.2 km (S1) and EQ score = 6 at 4.0 km (03)
- e.g. EQ score is 10 at 2.6 km and 5.3 km
- [2] Repair roads / pavements
- Landscaping / plants trees / cut grass
- Example of ways to reduce number of vehicles or vehicles parking on road – yellow lines / parking meters / more public transport / pedestrianisation / congestion charge, etc.
- Laws / regulations on noise / atmospheric pollution / fines for companies polluting the air
- Litter bins // recycling facility / fines for dropping litter / fines for graffiti
- Teams of people to tidy area / remove graffiti
- Repair broken street furniture or e.g.
- [4] Produce a questionnaire / ask questions
- Example of appropriate question e.g. Do you think this area / site is noisy? / introduction or explanation about questionnaire
- Name of sampling method (to use questionnaire)
- Description of sampling method
- Number of people to sample (20–100)
- Do fieldwork at different times of day / decide which time to do fieldwork
- Decide on who does which task within the group
- OR interview methodology
- No credit for environmental quality scores
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