Initial assessment of some related socio-Economic parameters under the impacts of climate change at district 8 in Ho Chi Minh city

Journal of Science and Technology 54 (2A) (2016) 214-221 INITIAL ASSESSMENT OF SOME RELATED SOCIO-ECONOMIC PARAMETERS UNDER THE IMPACTS OF CLIMATE CHANGE AT DISTRICT 8 IN HO CHI MINH CITY Nguyen Phu Bao 1 , Tran Tuan Viet 1, * , Nguyen Thi Minh Hoa 2 , Nguyen Dinh Huan 3 , VoThi Yen 4 , Pham Hong Nhat 1 1 Institute for Tropicalization and Environment (ITE), 57A Truong Quoc Dung, Phu Nhuan District, Ho Chi Minh City, Vietnam 2 University of Labour and Social Affairs, 1018 To Ky, District 12, Ho Chi Minh City, Vietnam 3 Industrial university of Ho Chi Minh City, 12 Nguyen Van Bao Street, Go Vap District, Ho Chi Minh City, Vietnam 4 Ho Chi Minh University of Technology, 268 Ly Thuong Kiet, District 10, Ho Chi Minh City * Email: viet.vittep@gmail.com Received: 1 April 2016; Accepted for publication: 15 June 2016 ABSTRACT About 7.9 % of population is living in poverty at District 8, which is one of the most vulnerable areas to climate change in Ho Chi Minh City (HCMC). The impacts of climate change (CC) on some related socio-economic parameters at District 8 were assessed using analytic hierarchy process (AHP) and livelihood vulnerability index (LVI). For this, four Asian Development Bank’s criteria including public health, transport, energy, and water supply and drainage (WSD) were used. In addition, however, six World Bank’s criteria including land use, population, gross domestic product (GDP), urban expansion, agriculture and wetland were also used just for initially trying whether or to what extent they can be useful for such downscaled application. Results of this study show that the level of CC impacts on the residential areas is rather high, with an average LVI of 0.056. In addition, the results of AHP shown that the impact levels on the study fields are determined to follow a decreasing order as: first level group including energy, water supply and drainage, transport, and public health (with total score 0.22); the second level group including land use and wetland (with total score 0.14); the third level group including population and urban expansion (with total score 0.1); and at last the fourth level group including GDP and agriculture (with total score 0.09). Keywords: climate change, analytic hierarchy process, district 8. 1. INTRODUCTION The impacts of CC on the periurban areas of HCMC, including District 8, are increasingly serious. There are 21 canals with total 106 km in length are winding through the District 8 (see Initial Assessment of some related socio-economic parameters under the impacts of 215 Fig. 1), occupying 13 % of its total area [1]. Moreover, there are some other unfavourable characteristics making the district become the most vulnerable area in HCMC, such as for instance high elevation (from 0.5 to 2 m), high precipitation (average 1.743 mm), and high tide peak (ranging between 1.36 and 1.46 m) etc [2]. Besides, about 7.9 % of population is living in poverty at this district [1] and they are the most vulnerable people by CC impacts [3]. In this study, analytic hierarchy process (AHP) [4 - 6] was selected to assess CC impacts on some related socio-economic parameters in the study area. The process is based mainly on four ADB’s criteria including public health, transport, energy, and water supply and drainage [7]. In addition, six WB’s criteria including land use, population, GDP, urban expansion, agriculture and wetland [3] were also used just for initially trying whether or to what extent they can be useful for such downscaled application. 2. MATERIALS AND METHODS 2.1. Study area Six out of total sixteen wards, all administratively belong to District 8, were surveyed, including wards No. 2, 3, 5, 13, 14 and 15 (Fig. 1). Figure 1. Study area. 2.2. Survey methods Ten households at each studied ward were requested to fill a 50-question-list sheet about CC impacts on them. An environment staff in each ward people’s committee was asked to fill another survey questionnaire about policy and other issues related to CC. Population and socio- economic data were extracted from published sources [2]. In addition, three experts were asked for consultation about CC impacts in HCMC and District 8. 2.3. Analytic hierarchy process AHP is based on three rules including (1) making decision analyzing (priority set up), (2) assessing the pairwise comparison, and (3) summarizing priority levels. The AHP is shown below: Step 1: Define the problem and determine the kind of knowledge sought. Step 2: Define the elements and criteria. Nguyen Phu Bao, et al. 216 Step 3: Determine the priority based on professional advices. The 1-to-9 scale of relative importance was used (see table 1). Step 4: Construct a set of pairwise comparison matrices. Step 5: Compute the vector of criteria weights (w) for each level and each group as follow: Once the matrix A is built, it is possible to derive from A the normalized pairwise comparison matrix Anorm by making equal to 1 the sum of the entries on each column, i.e. each entry aij of the matrix Anorm is computed as: (1) where, m is the number of elements. Thus, the w (an m-dimensional column vector) is built by averaging the entries on each row of Anorm, i.e. . (2) Table 1. Scale of relative importance [4 – 6]. Inten sity of importance Definition Explanation 1 Equal importance Two activities contribute equally to the objective 3 Weak importance of one over another Experience and judgment slightly favour one activity over another 5 Essential or strong importance Experience and judgment strongly favour one activity over another 7 Demonstrated importance An activity is strongly favoured and its dominance demonstrated in practice 9 Absolute importance The evidence favouring one activity over another is of the highest possible order of affirmation 2, 4, 6, 8 Intermediate values between the two adjacent judgments When compromise is needed Step 6: Calculate the consistency ratio (CR). The CR value should be under 10 %, if not, re-do step 3, 4 and 5: (3) where CI is Consistency Index and RI is Random Index (see Table 2). Table2. Random index RI (with m ≤ 10) [4 - 6]. m 3 4 5 6 7 8 9 10 RI 0.58 0.9 1.12 1.24 1.32 1.41 1.45 1.49 Initial Assessment of some related socio-economic parameters under the impacts of 217 The CI is obtained by first computing the scalar λmax as the average of the consistency vector ). Then (4) If ; and If re-assessment. Step 7: Do step 3, 4, 5, 6 for all levels and groups. Step 8: Compute the total weight and give comments. 2.4. Livelihood Vulnerability Index LVI is calculated based on the following function [8]: (5) where LVId is LVI in each area d (or ward d); Md is main element/criterion in area d; and WMi is weight of each main criterion, which is determined using the number of sub-criteria. 3. RESULTS AND DISCUSSION 3.1. AHP and LVI results 1. Energy, and water supply and drainage (WSD) 2. Transport 3. Public health 4. Land use and wetland 5. Population and urban expansion 6. GDP and agriculture 1.1. Increase of demand 1.2. Damage of infrastructure 1.3. Changes in supply 1.4. Salinization of ground water 2.1. High flood level 2.2. Effects on human activities 2.3. Duration of flood 2.4. Damage of vehicles 3.1. Arise and spread of diseases 3.2. Effects on human health 3.3. Increase of medical treatment costs 4.1. Loss of land 4.2. Changes in landuse 4.3. Salt intrusion of soil 5.1. Migration 5.2. Changes in population 6.1. Decrease of per capita income 6.2. Changes in production structure Figure 2. Prioritization of CC impacts at District 8. Level 2 Climate change impacts at District 8 Level 1 ADB’s criteria WB’s criteria Nguyen Phu Bao, et al. 218 The priority elements based on the ADB’s but also WB’s criteria were defined and determined as shown in Fig. 2. Totally 7 weighting factor groups have been used in this step including (1) one group for level 1 criteria (main criteria), and (2) six groups for level 2 criteria (sub-criteria). Pairwise comparison matrix was built up based on the survey results as shown in Table 3. Calculations for pairwise comparison matrix and CR are shown in Step 5 and 6 above. Results of vector of criterion weights is shown in Table 4 and CR in Table 5. Table 6 presents vector of all criterion weights and LVI of each main criterion. Table 3. Pairwise comparison matrix of main criteria (Level 1) Criteria 1 2 3 4 5 6 1 1 1 1 2 3 2 2 1 1 1 2 3 2 3 1 1 1 2 3 2 4 0.500 0.500 0.500 1 3 2 5 0.333 0.333 0.333 0.3333 1 3 6 0.5 0.5 0.5 0.5 0.333 1 Total 4.333 4.333 4.333 7.833 13.333 12.000 Table 4. Vectors of criterion weights for level 1 group Criterion 1 2 3 4 5 6 Average 1 0.23 0.23 0.23 0.26 0.23 0.17 0.22 2 0.23 0.23 0.23 0.26 0.23 0.17 0.22 3 0.23 0.23 0.23 0.26 0.23 0.17 0.22 4 0.12 0.12 0.12 0.13 0.23 0.17 0.14 5 0.08 0.08 0.08 0.04 0.08 0.25 0.10 6 0.12 0.12 0.12 0.06 0.03 0.08 0.09 Table 5. CR of main group and each criterion Criterion 1 2 3 4 5 6 CR 0.026 7.4*10 -4 0 0.02 0 0 CR of main criteria 9.6*10 -3 Table 6. Vector of all criterion weights and LVI of each main criterion for assessing CC impacts at District 8 Criteria The vector of criteria weights (w) Priority LVI 1. Energy and WSD 0.22 1 0.055 1.1. Increase of demand 0.114 1 1.2. Damage of infrastructure 0.067 6 1.3. Changesin supply 0.025 11 1.4. Salinization of ground water 0.014 13 2. Transportation 0.22 1 0.055 Initial Assessment of some related socio-economic parameters under the impacts of 219 Criteria The vector of criteria weights (w) Priority LVI 2.1. High flood level 0.073 4 2.2. Effects on human activities 0.073 4 2.3. Duration of flood 0.037 9 2.4. Damage of vehicles 0.037 8 3. Public health 0.22 1 0.073 3.1. Arise and spread of diseases 0.11 2 3.2. Effects on human health 0.055 7 3.3. Increase of medical treatment costs 0.055 7 4. Land use and wet land 0.14 2 0.046 4.1. Loss of land 0.08 3 4.2. Changes in land use 0.047 8 4.3. Salt intrusion of soil 0.014 13 5. Population and urban expansion 0.1 3 0.05 5.1. Migration 0.067 6 5.2. Changes in population 0.033 10 6. GDP and agriculture 0.09 4 0.045 6.1. Decrease of per capita income 0.068 5 6.2. Changes in production structure 0.022 12 Average LVI 0.056 3.2. Discussion According the survey and AHP results, energy, WSD, transportation and public health are the aspects that are most seriously impacted by CC in the study area. The vector of all those criterion weights is 0.22 and they are the first priority. More specifically, the increase of energy demand and WSD is impacted as the most, followed by arise and spread of diseases. Following the first priority group are land use and wetland (total score 0.14); population and urban expansion (total score 0.1); and GDP and agriculture (total score 0.09). Figure 3. Spider chart of LVI of criterion groups caused by CC impacts in the study area. Nguyen Phu Bao, et al. 220 The LVI of public health was highest (0.073), meaning that human health is seriously impacted by CC in the study area. A similar result has been shown by Pham Hong Nhat et al. in their study at HCMC in 2012 [9], which concluded, among other issues, that CC could cause various hygienic and environmental problems. Results of LVI also show that the vulnerability level of the remaining criterion groups follows a decreasing order as: (1) energy and WSD and transportation (LVI = 0.055); (2) population and urban expansion (LVI = 0.050); (3) land use and wet land (LVI = 0.046); and GDP and agriculture (LVI = 0.045) (see Fig. 3). 4. CONCLUSIONS Results of AHP and LVI evaluation show that CC impacts on the studied parameters at District 8 in HCMC can be divided into two groups of level from four criteria guided by the ADB but also six criteria by the WB as tried in this study. The first impact level group includes six main criteria whereas the second impact level group includes eighteen sub-criteria. Calculated figures from both AHP (score 0.022, level 1) and LVI (0.073, which is the highest) shows the strongest impacts of CC on public health, which well agrees with previous studies by Pham [9] and Nguyen & Le [2]. Furthermore, this study points out a rather high level of CC impacts on the study area, with an average LVI of 0.056. In addition, the results of AHP show that the impact levels follow a decreasing order as: the first level group including energy, water supply and drainage, transport, and public health; the second level group including land use and wetland; the third level group including population and urban expansion; and at last the fourth level group including GDP and agriculture. Acknowledgements. This paper presents part of a research project funded by the Ho Chi Minh City’s Department of Science and Technology that is much acknowledged. The authors also thank all colleagues from ITE, who have contributed to this study. REFERENCES 1. Perucca. 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