Urban Environments: Curitiba Option G Urban Environments: Investigating Urban Sustainability

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1 Urban Environments: Curitiba Option G Urban Environments: Investigating Urban Sustainability Comentario [M1]: TOTAL MARKS 28/30 Amalia Bastos Candidate number: Geography IB High Level N o v e m b e r Word Count: 2,420 1 Image Attribution 3.0 Non-commercial license to Amalia Bastos 2012

2 Table of Contents Introduction 3 Statement of Hypotheses 6 Methods of Data Collection 7 Data Collection 14 Presentation and Analysis of Data 17 Conclusion 28 Evaluations 28 Appendix A 30 2

Introduction Curitiba is the capital of the state of Paraná, located in the South region of Brazil. Its population is of approximately 1.76 million in the main area alone, with an additional 3.

3 Introduction Curitiba is the capital of the state of Paraná, located in the South region of Brazil. Its population is of approximately 1.76 million in the main area alone, with an additional 3.2 million living in the metropolitan area. It is the tallest city in its region, built on a plateau at 930 metres Comentario [M2]: Highest? above sea level. 1 Figure 1. There are several parks and green spaces throughout the city. 1 Curitiba is considered to be amongst the most sustainable cities in the world due to its planned construction and public transport system, having won the Global Sustainable City Award Students taking the Geography IB Course at the British School Rio de Janeiro went on a fieldtrip to Curitiba in order to investigate aspects of urban environments, including but not limited to urban stress, urban development and land use, and sustainability in cities. 1 Image Amalia Bastos < Access date:

In this investigation, different neighbourhoods of Curitiba will be evaluated in terms of

consideration: environmental and socio-economic aspects.

through the creation of the Sustainability Index.

Curitiba is located in the South of Brazil. 1 Figure 3. Curitiba, divided by neighbourhoods.

4 In this investigation, different neighbourhoods of Curitiba will be evaluated in terms of its sustainability, taking two of the main features comprising sustainability 3 into consideration: environmental and socio-economic aspects. Adding up these factors gives a more general idea of sustainability in an urban area, through the creation of the Sustainability Index. Comentario [M3]: Good idea Map of South America Map of Curitiba Figure 2. Curitiba is located in the South of Brazil. 1 Figure 3. Curitiba, divided by neighbourhoods. 1 Comentario [M4]: Good quality candidate-generated maps. Figure 4. Government reduces property taxes when trees are present in backyards. 1 3 < >; Access date

5 Figure 5. View of the city from above. 1 Figure 6. Students after interview with Jamie Lerner, former mayor and governer. 1 5

Statement of Hypotheses In this investigation, the sustainability of Curitiba will be tested in association to other variables such as location and accessibility. The hypothesis investigated is: 1.

Relationship to de syllabus on the cover. Explanation is basic though. Locational map is good.

6 Statement of Hypotheses In this investigation, the sustainability of Curitiba will be tested in association to other variables such as location and accessibility. The hypothesis investigated is: 1. Sustainability Index values will be higher in the North of the city and closer to the city centre. Comentario [M5]: A2.Focused question (hypothesis) Good locational context and geographic context. Relationship to de syllabus on the cover. Explanation is basic though. Locational map is good. The North of the city contains most of its high-class residential buildings and hence also its highest land values, and is close to the city centre. As usually occurs in urban environments, the CBD also has some of the highest land values in the city. Higher class houses are usually located in regions with the best infrastructural amenities and access to transport, but also are better managed. Therefore, it would be expected that their sustainability index, comprised of environmental and socio-economic factors, would be higher, since these neighbourhoods would show less vandalism and graffiti, poverty or air pollution, and more natural features and infrastructural amenities. Figure 7. Museums are an important factor in terms of infrastructural amenities. 1 Figure 8. Parks are green spaces considered in the natural features indicator. 1 6

7 Methods of Data Collection Curitiba is a very large city and hence it would be impossible to collect data for every single neighbourhood. Therefore, it was decided that the furthest suburbs would not be included (due to time constraints), and random sample points would be selected on a map to avoid bias, through random number assorted to pre-established individual squares on a grid over the map of the city. This was tested previously in a pilot study which took place in Rio de Janeiro, and proved to be a successful strategy. All other methods involving interviews and sample data collection were also tested during that study. Comentario [M6]: Well explained and justified. Comentario [M7]: Validity of methods. Students were separated into groups, which would have to get to these previously established locations in order collect their data at these points. There, analyses of the locations were made, by filling in a form with descriptors for several aspects being evaluated. Descriptors were previously agreed on in class. The index for this investigation was comprised of five different factors, which were used to evaluate sustainability of the sample points where data was collected: for the environmental aspect, natural features and sulphur dioxide levels were taken into consideration, whilst for the socio-economic aspect infrastructural amenities, poverty and vandalism and graffiti were looked into. Another aspect which was looked into is transportation. Curitiba is well-known for its public transport system, and this was evaluated through the use of maps and graphs to find with what frequency and how commonly it is used by the city s inhabitants based on interview responses. 7

8 Figure 9. A fine grip was overlaid on the map. 1 Figure 10. Potential sample squares were numbered. 1 Figure 11. A random number numerator was used to select sample points. 4 Comentario [M8]: Good sampling method. 4 < Access date:

Questionnaires were devised, using the questions shown in Figure 2, with annotations showing the data to be used in the transport section of this study.

Comentario [M9]: A locational map of the sample points would have been useful in this section, and another one with the neighbourhoods in the introduction.

9 Questionnaires were devised, using the questions shown in Figure 2, with annotations showing the data to be used in the transport section of this study. They were asked on two different occasions on the main street of the city s CBD. Comentario [M9]: A locational map of the sample points would have been useful in this section, and another one with the neighbourhoods in the introduction. Used to calculate the distance travelled from home to work. Form of transport used to work. Figure 12. The questionnaire used to interview people on the street. Students worked in groups for safety precautions and greater efficiency. Comentario [M10]: Good use of annotated photographs. Group work also greatly facilitated data collation for the students. Figure 13. Students evaluate their location using descriptors. 9

Figure 14. Tally table for traffic and pedestrian counts.

Descriptors used for data collection at sample points.

Negative features gain the lowest numbers.

10 Figure 14. Tally table for traffic and pedestrian counts. Each column is filled in with information for one location. Figure 15. Descriptors used for data collection at sample points. Positive features gain the highest numbers. Negative features gain the lowest numbers. Lichens were used to evaluate sulphur dioxide levels in the air. Figure 16. Table showing selected lichens for each level of air pollution. 1 10

11 Figure 17. Overall primary data collected in personal interviews. Boxes showing an affirmative response contain a 1. Figure 16. Overall primary data collected in personal interviews. Averages for sample point values are calculated for each neighbourhood. 11 Figure 18. Raw data collected for sample points, using descriptors.

12 Figure 19. Averages were calculated for samples in each neighbourhood. 12 Comentario [M11]: Good explanation of how the index calculated on the next page.

Sustainability Index calculated was comprised of five indicators. Sustainability Index values are expressed as a percentage. Lichens at each sample point indicated air sulphur dioxide levels.

Natural features: the presence of local green spaces and parks. Infrastructural amenities include bus stops, museums and public telephones.

13 Sustainability Index calculated was comprised of five indicators. Sustainability Index values are expressed as a percentage. Lichens at each sample point indicated air sulphur dioxide levels. Distance calculated by measuring distance between neighbourhoods on a map. Vandalism and graffiti levels were assessed for each sample point. Natural features: the presence of local green spaces and parks. Infrastructural amenities include bus stops, museums and public telephones. Poverty was evaluated at each sample point judging by appearance. Distances between two given neighbourhoods are an average. All values used to calculate the Index are between 0 and 4. Figure 21. Processing of sample point data for sustainability index. Data in red represents invalid data for specific investigation. Data for all neighbourhoods was processed in this way. Figure 20. Processing of the distance data from interviews. 13

The method carried out at each sample point was as follows: Figure 22.

14 Data Collection Groups of two or three students went to pre-established random locations throughout the city. The method carried out at each sample point was as follows: Figure 22. Students write down the latitude and longitude of sample point. Figure 23. Student sets a stopwatch for one minute. 14

15 Figure 24. Students count 360º traffic and pedestrian flows for one minute. Descriptors include air pollution, poverty and infrastructural amenities, amongst others. 15

The apparatus used in this investigation are shown and labelled below: 56 Comentario [M12]: C 3Clear description, with sound justification of very

16 Figure 25. Usage of descriptors to evaluate aspects from 0 to 4. Figure 26. All data collected is recorded into tables to be collated. Data collated between students was used for the creation of tables and graphs relevant to the subsequent studies. The apparatus used in this investigation are shown and labelled below: 56 Comentario [M12]: C 3Clear description, with sound justification of very well suited methods. Well done Amalia! GPS or equivalent Stopwatch Figure 27. Apparatus used in the study. 5 GPS app image: < 6 Stopwatch image: < 16

17 Presentation and Analysis of Data A sustainability index was developed as explained in the Introduction and Methods of Data Collection, in order to access the quality of each of the neighbourhoods studied in that respect. Throughout the next parts, this index will be broken down so its composition and individual results may be better understood. It is recommended that Appendix A is used for better understanding of the data. Below are the sheltergrams showing the SI (sustainability index) calculated for each neighbourhood, grouped by overall SI score. As explained, individual indicators, or ratings, were evaluated for each neighbourhood. Comentario [M13]: Good would help being able to see map for them to be more me Figure 28. Neighbourhoods with SI scores below 50% show low overall ratings. Figure 29. Neighbourhoods with 50-60% scores show more dispersed average ratings. 17

Candidate Name: Amalia Bastos Candidate Number: 000461-008 Geography HL IA: Option G Figure 30. Neighbourhoods with slightly higher SI values show higher overall ratings. Figure 31.

18 Candidate Name: Amalia Bastos Candidate Number: Geography HL IA: Option G Figure 30. Neighbourhoods with slightly higher SI values show higher overall ratings. Figure 31. Neighbourhoods with 65-70% SI values show high infrastructural amenities values. 18 Figure 32. Neighbourhoods with high SI values show high average poverty ratings. Figure 33. Neighbourhoods with very high SI values generally show excellent ratings. 18

19 The choropleth map to the left shows the ratings for Infrastructural Amenities one of the indicators evaluated for every sample point evaluated for all neighbourhoods analysed in Curitiba. Higher numbers indicate better infrastructural amenities. The highest-rated neighbourhoods seem to be those relatively far from the centre, but not quite in the periphery, which may be high-middle class suburbs. The lowest-rated neighbourhoods are in the western and northeast peripheries and near the centre, which may be low-class residential zones. The hypothesis claims that the centre and the north of the city will have the highest sustainability index values, but so far this does not appear to be the case for Infrastructural Amenities, since only four neighbourhoods in the north show rates of over 3.6, but five neighbourhoods to the south show this rate. Comentario [M14]: Accu description of a very good qu candidate generated map. 19 Figure 34. Choropleth map for Infrastructural Amenities in Curitiba.

20 The choropleth map to the left shows the ratings for Sulphur Dioxide Levels another individual indicator evaluated for every sample point, by the use of lichens as an indicator for air pollution in the studied neighbourhoods of Curitiba. Higher numbers indicate lower sulphur dioxide levels. The peripheries and the centre of the city seem to show the lowest levels, between 1 and 1.5, whilst only three neighbourhoods to the north of the city and one to the south show levels between 3 and 3.5. Overall, there seems to be less sulphur dioxide pollution to the north of the city, which partially confirms the hypothesis. On the other hand, the centre has high levels of pollution, at the same range as the Cidade Industrial, the biggest neighbourhood to the west, where factories and industries are located. It is unlikely that pollution from this neighbourhood would be responsible for greatly affecting the two neighbourhoods to the east with the same levels, however, since the prevailing wind blows to the northwest. Comentario [M15]: Accu explanation. 20 Figure 35. Choropleth map for Sulphur Dioxide Levels in Curitiba.

The choropleth map for Natural Features an indicator evaluated for all sample points in the studied neighbourhoods in Curitiba shows the greatest ratings for four neighbourhoods to the south.

21 The choropleth map for Natural Features an indicator evaluated for all sample points in the studied neighbourhoods in Curitiba shows the greatest ratings for four neighbourhoods to the south. The following ranking range of 3.1 to 3.5 is clearly observed in the northern neighbourhoods north of the CBD, Centro, where the majority of high-middle class people live. Natural features such as parks and other open green spaces are essential to enhance life quality of the local population, so it is expected that it would be present in such neighbourhoods. This seems to partially support the hypothesis that areas to the north of the city but in this case, not the city centre would show more sustainability. The CBD is usually the oldest part of the city and also the one with the highest land values. Hence, it is expected and understandable that natural features are not widely present in the CBD. In this case, both environmental and social sustainability are shown to be present in these areas. Comentario [M16]: Anom accounted for. 21 Figure 36. Choropleth map for Natural Features in Curitiba.

22 This choropleth map shows Poverty ratings in the studied neighbourhoods of Curitiba. This indicator was evaluated for each of the sample points visited individually. Clearly, the highest ranges indicating less signs of poverty are located to the north and the city centre, with the exception of four neighbourhoods. Five neighbourhoods to the south show Poverty levels between 1.5 and 2.5, against four in the north and central areas, where high-middle classes are expected to inhabit. Therefore, the information on this map seems to support the hypothesis regarding sustainability and location, though not entirely. Comentario [M17]: Cons references to fieldwork quest 22 Figure 37. Choropleth map for Poverty Levels in Curitiba.

23 The presence of Vandalism and Graffiti was rated throughout all the studied neighbourhoods of Curitiba. In this choropleth map, two neighbourhoods in the northern and central regions show levels of 0, which indicates a very high level of vandalism and graffiti, whilst six neighbourhoods are rated in the same way. Most neighbourhoods in the north and central areas show ratings of above 2.1. This supports the hypothesis that these areas would be more sustainable in this case, in a social manner than those to the south and in the peripheries. 23 Figure 38. Choropleth map for Vandalism and Graffiti in Curitiba.

24 The final map shows the overall sustainability index values, comprised of all five indicators shown in the previous choropleth maps, calculated for each of the neighbourhoods studied in Curitiba. Only three neighbourhoods showed values above 80%: two in the north and one in the south. Two neighbourhoods showed values below 40%, with both being located to the south of the city centre. Overall, if can be said that the central and northern areas of the city obtained higher sustainability index values, on average, then those further down and especially more than peripheries. It could be said, therefore, that the hypothesis seems to be supported by these results. Comentario [M18]: Well visually effective map, good id processing. 24 Figure 39. Choropleth map for total Sustainability Index in Curitiba.

25 Sustainability Index (%) Candidate Name: Amalia Bastos Candidate Number: Geography HL IA: Option G 90,00 80,00 70,00 Correlation: Sustainability Index vs. Distance from CBD R² = 0, ,00 50,00 40,00 30,00 20,00 10,00 0,00 Distance from the CBD (km) Figure 40. Scatter graph showing distance from CBD versus sustainability index. The scatter graph above shows distance from the CBD values plotted against the sustainability index, showing data for all the neighbourhoods assessed. The negative correlation, however, is not certain, since the R 2 value is below 0.4. It cannot be claimed that, mathematically, the hypothesis is entirely correct, since the statistical correlation is irrelevant. The sheltergrams and maps, however, seem to contradict this, and show that the SI does not change simply with distance from the CBD, but also with direction. As expected, high-class residential zones such as the north of the city usually show higher SI values. 25

26 Figure 41. Table showing sustainability index for studied neighbourhoods, in increasing order. The bar graph shows all neighbourhoods Sustainability Index calculated values, in ascending order. Comentario [M19]: Again desirable to have this linked t 26

27 In the questionnaire applied, people answered where and how they went to work, besides several other forms of information required. The flow map to the left shows the home to work daily migration patterns by public transportation, coloured by destination. Neighbourhoods with only one commuter were ignored since they are not relevant to the study. Unfortunately, there was insufficient information to make a similar flow map for private transport exclusively. The CBD, or Centro, is where most of the arrows point to. A significant number of workers go to Cajurú and Jardim das Américas, which are probably also highly commercial areas of the city, and potentially secondary CBDs. Most commuters using public transport seem to come from the neighbourhoods below the city centre considered to be in the south of the city, rather than from the north. This seems to oppose the Figure 42. Flow map for use of public transport to work. hypothesis, since people appear to take public transport due to necessity and not preference, and so lower-class residential areas show more public transport commuters. This may show that being sustainable has social implications, as those who have the option between taking private and public transport seem opt against the latter. 27 Comentario [M20]: Very well spotted. Comentario [M21]: C 5. relevant information collecte effective and different techn been used. Outstanding visua display of information. D. 9 Analysis is good and dem understanding. Sometimes th component is missed because know exactly where the neigh are. Good attempt to explain Reference to FQ is clear all th pity that the sheltergrams we mentioned in the analysis.

28 Conclusion In conclusion, it can be said that the hypothesis could not be fully supported. The hypothesis, which claims that the sustainability index would be greater in areas closest to the city centre and the northern neighbourhoods of the city, seems at least partially valid judging only by the maps, but the correlation between distance from the city centre and sustainability index values is too weak to confirm it. Similarly, the flow map for public transport commuting shows a greater number of people leaving from the southern neighbourhoods. This indicates that fewer Comentario [M22]: clear reference to findings. people in high-class residential areas use public transport, and hence are less sustainable. Besides these, the study showed several other interesting forms of information regarding the city of Curitiba, however. Firstly, it gave in-depth information on the five factors being used for the sustainability index throughout the different neighbourhoods, and showed how different forms of sustainability economic, social, environmental and cultural are spread differently throughout the city. Comentario [M23]: E 2. Clear and directly linked to findings. Evaluation As with any other study, changes could be made to further improve the results. Firstly, one of the main sources of error in any study is human error and personal bias. In this case, this would have especially significant in the collection of data at sample points of different neighbourhoods, in assessing aspects according to the descriptors. In order to reduce that error, it would be necessary to have several different groups analyse the same sample point, and take an average of all the results obtained. Another source for error is the weather. This may bring litter to the streets, for example, reducing the ratings for pollution or litter disposal at a given time. However, these external weather circumstances are unpredictable and cannot be changed. Instead, they should be 28

29 avoided, and data at sample points should only be collected under similar and favourable weather conditions. The selection of interviewees may also be a potential source of bias: usually people who were not busy or walking quickly down the streets were selected. The choices consisted mostly of people sitting at bus stops, in benches along the streets, or working at small shops. There is little way to reduce this source of bias, however. People who are busy or have an appointment are less likely to accept taking an interview and therefore a certain portion of the population will be assessed less often or not at all such as delivery people or business workers. Last but not least, the time of the day when either interviews or sample point data are being collected greatly affects and causes variability amongst different sets of information. During rush hours, for example, pedestrian and traffic counts will be much higher than at times like noon or the early evening. In order to reduce this form of bias, students should only carry out this type of study at the same approximate time range each day, preferably not at rush hours. There are few improvements to be made to the study, however, as overall most of the errors and bias which could be addressed were minimized during the elaboration of the method. As far more data was collected and not used, this also allows for potential further investigation on several different aspects, which can lead to the creation of different hypotheses. Furthermore, correlating Sustainability Index percentages with secondary data such as land values could prove very interesting in future investigations. Comentario [M24]: F3 Outstanding evaluation with realistic recommendations. Bibliography: Comentario [M25]: G4. Fully meets requirements. outstanding presentation! Nagle, Garrett; Cooke, Briony. Geography Course Companion. New York: Oxford University Press, < Accessed on: 08/08/12. < Accessed on: 05/07/12. < Accessed on: 05/08/12 29

30 Appendix A: Curitiba Map with Labelled Neighbourhoods Comentario [M26]: It is a pity it is not in the introduction. 30

0471 Travel and Tourism November 2007

0471 Travel and Tourism November 2007 www.xtremepapers.com TRAVEL AND TOURISM Paper 0471/01 Written Paper General comments There was quite a large entry for this examination session and it is pleasing to note that candidate performance is