Impact of a Collective Action in a Disaster-affected Community to Site a Temporary Debris Management Site, Makarand HASTAK
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6th International Disaster and Risk Conference IDRC 2016 Integrative Risk Management - Towards Resilient Cities. 28 August - 01 September 2016 in Davos, Switzerland
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Impact of a Collective Action in a Disaster-affected Community to Site a Temporary Debris Management Site, Makarand HASTAK
- 1. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Impacts of a collective action in a disaster-affected community to site a temporary debris management site Makarand (Mark) Hastak, PhD, PE, CCP Professor and Head of Construction Engineering and Management Professor of Civil Engineering Purdue University, USA Authors: Jooho Kim, David Yu, and Makarand Hastak
- 2. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Disaster Trends
- 3. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Types of disasters
- 4. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org DISASTER DEBRIS Earthquake (Nepal, 2015) Tornado (Alabama, USA, 2011) Hurricane (New Orleans, USA, 2005) Tsunami (Japan, 2011) Flood (China, 2011)
- 5. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Background • Debris – Materials – both natural and man-made disasters – Any material including trees, branches, personal property and building material on public or private property that is directly deposited by a disaster (FEMA 2007) Debris removal in Kansas(2009)Debris removal in Texas(2008)Debris removal in Louisiana (2005)
- 6. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Debris Generation After a disaster • Amount of debris generated by a disaster Football stadium volume = about 1M CY (Berger et al. 2011)
- 7. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Needs for debris management 1. Debris generated by a disaster >> Amount of daily or monthly solid waste generated under normal conditions – Instantly overwhelms current solid waste management system <Fetter G. and Rakes T (2011)> 0.1 2.975 5.2 Daily waste Monthly waste Debris after Hurricane Sandy e.x.) Hurricane Sandy debris in NYC VS. Monthly solid waste in NYC
- 8. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Needs for debris management 2. The cost of debris removal can be 27 ~ 40% of total disaster recovery costs Hurricane Isabel 900,000 CY($8 million) Hurricane Katrina 113 M CY (more than $ 4.4 billion)) Left : Tsunami in Japan(2011) , Center : Hurricane Katrina (2005) Right : Tornado in Mississippi, USA(2011) <Fetter G. and Rakes T (2011)> <CAL EMA (2013)> Debris 40% Others 60% Disaster recovery cost Debris Others
- 9. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Temporary Debris Management Site (TDMS) • Past strategy for debris removal Debris in a community Final destination (EPA 2008, FEMA 2007, UNEP 2011)
- 10. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org • Recommended strategy Debris in a community Final destinationTDMS (EPA 2008, FEMA 2007)• Roles of TDMS 1. Provide buffer and space to haul debris from a community to TDMS / TDMS to a final destination 2. Chipping, burning and sorting of debris (Shrink the volume of debris) An acre of TDMS contains about 1 million CY of debris Temporary Debris Management Site (TDMS)
- 11. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org (EPA 2008, FEMA 2007, UNEP 2011) Advantages Disadvantages Speed-up cleaning of debris from a community Expense of double handling of debris / acquiring lands for installation of TDMS Speed up concurrent / following disaster recovery (i.e., Emergency service, Reconstruction) Unsuitable locations of TDMS have negative effects (Environmental effects – noise / odor / groundwater contamination)) Provide a buffer to properly sort, burn, and recycle debris in a TDMS Heavy traffic near TDMS area Temporary Debris Management Site (TDMS)
- 12. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Disaster affects Debris Management Plan Resource Debris generated Infrastructure Disaster Timeline Debris Management Plan Randomness of impacts and problems Uniqueness of incidents Dynamic, real-time, effective and cost efficient solutions Additional resource From NPO & NGO demand How to implement debris management plan?
- 13. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Previous Research from DRR group in SPARC lab <Kim J. (2014) A framework of effective debris management for a resilient community> Disaster Debris estimation Infrastructure Resources Estimating current situation after a disaster for debris management Debris Collect Process Final destination Effective debris management strategy Report solutions Data analysis Data analysis Yes No Transportation Electricity Debris handling facility Governmental management Labor Equipment Simulation results : total duration, Productivity, Amount of debris in transferring sites Input current data Bottle-neck Resource shortage issues Infrastructure capacity issues Environmental conditions Historical conditions Shortest path algorithm Geographical analysis Optimization analysis Feasible TDMS Debris removal time Debris removal cost Required equipment 102 62 47 57 42 32 156 148 146 146 143 143 0 200 T2R250 T2R300 T2R350 T3R250 T3R300 T3R350 Workingdays Comparison of the simulation results Debris in NYC to TDMS TDMS to final destinations 1. Framework for effective debris management 13 2. Identify Temporary Debris Management Site 3. Cost-benefit analysis
- 14. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Previous Research from DRR group in SPARC lab TDMS(A) TDMS(B) TDMS(C) • Comparison of average distance from the debris generated to a TDMS Unit() = 5 tons of debris TDMS(A) TDMS(B) 12.46 8.37 6.847.26 4.85 4.01 0 2 4 6 8 10 12 14 1 2 3 Average distance (Mile) Average distance S.D.
- 15. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org $0 $10,000,000 $20,000,000 $30,000,000 $40,000,000 $50,000,000 $60,000,000 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 T1R180 T1R210 T1R240 T2R180 T2R210 T2R240 T3R180 T3R210 T3R240 Workingdays Total Cost Debris hauled from collection points to TDMS Debris hauled from TDMS to final destination 34M 56M Total costD-147 D-70 Total working days Previous Research from DRR group in SPARC lab
- 16. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Prior Research Work and Needs Debris MGMT Technical Environm ental Socio- political Vehicle routing and allocation (queuing theory and scenario-based simulation) Siting a TDMS through cost-benefit analysis and process automation using GIS Regulations for debris removal in federal, state and local level Which TDMS should be opened to accept debris transported from collection sites ? Opinions for TDMS from the people nearby?
- 17. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org OBJECTIVES 0 5 10 15 20 25 30 35 40 45 50 0 50 100 150 200 250 % of Opposition for waste transfer facilities Lober, D. J., and Green, D. P. (1994). “NIMBY or NIABY: a Logit Model of Opposition to Solid-waste-disposal Facility Siting.” Journal of Environmental Management. Distance (Miles) %ofpublicopposition “Perception of needs” & “Distributional equality” This study investigates social behaviors to provide insights into factors which give rise to public oppositions, and to identify the actions taken to reduce/overcome that opposition.
- 18. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org METHODOLOGY Spatial opinion dynamics: The proposed ABM represents a category of spatial decision-making problems where multiple actors having multiple desires and goals regarding to the TDMS The dynamics of opinions are characterized by the following aspects; - Initial condition (Needs) - % of the agents affected by the disaster (agent’s property) - Spatial influence - Distance from TDMS - Geographical characteristics - Social influence - Neighbors’ opinions Spatial influence Social influence Initial Condition supporter opponent
- 19. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org METHODOLOGY Spatial influence Social influence Initial Condition supporter opponent 𝐷 𝑘, 𝑡+1 = 𝑓 ( 𝐷𝑖𝑛 𝑘,𝑡 , 𝐷 𝑠𝑝 𝑘,𝑡 , 𝐷 𝑠𝑜 𝑘,𝑡 ) Within the three aspects above, the dynamics of opinion 𝐷 𝑘, 𝑡+1 of agent k at time t + 1 in a social-spatial system can be defined as 𝐷𝑖𝑛 𝑘,𝑡 ; 𝑖𝑛𝑖𝑡𝑖𝑎𝑙 𝑜𝑝𝑖𝑛𝑖𝑜𝑛 𝑓𝑜𝑟 𝑇𝐷𝑀𝑆 𝑜𝑓 𝑎𝑔𝑒𝑛𝑡 𝑘 𝐷 𝑠𝑝 𝑘,𝑡 ∶ 𝑠𝑝𝑎𝑡𝑖𝑎𝑙 𝑖𝑛𝑓𝑙𝑢𝑒𝑛𝑐𝑒 𝑓𝑟𝑜𝑚 𝑇𝐷𝑀𝑆 𝐸𝑛𝑣𝑖𝑟𝑜𝑛𝑚𝑒𝑛𝑡𝑎𝑙 𝑖𝑠𝑠𝑢𝑒𝑠 𝑎𝑛𝑑 𝑐𝑜𝑛𝑐𝑒𝑟𝑛𝑠 𝐷 𝑠𝑜 𝑘,𝑡 ∶ the effect of the social influence
- 20. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Expected results • Identify the importance of socio-political approach to site a TDMS including technical and environmental aspects • Simulate possible social behaviours (public attitude) and spatial characteristics which give rise to public oppositions • Identify actions required to reduce / overcome that opposition by enhancing technical and environmental aspects, or rewards program Transition of dominant attitude (opposition -> support) when a parameter, disaster-affected area, is increasing (disaster affected area parameter 0.4, 0.5. 0.6 from left) (TDMS location is not informed to agents in this scenario)
- 21. 6th International Disaster and Risk Conference IDRC 2016 ‘Integrative Risk Management – Towards Resilient Cities‘ • 28 Aug – 1 Sept 2016 • Davos • Switzerland www.grforum.org Questions ? hastak@purdue.edu
Editor's Notes
- # of disasters up
- Needs might be different by the type of disaster
- However, it left a same residue, disaster debris
- Definition of debris
- Historical amount of debris generated by disasters Football stadium = 1 M CY debris can be stored
- Debris generated overwhelms current capacity of debris removal. NYC – 0.1 M CY/day of waste generated Hurricane Sandy -> 5.2 M CY debris generated
- The cost of debris removal is around 30% of the total disaster recovery cost.
- Past debris removal strategies : hauling debris to final destinations ASAP not consider other factors such as sustainable debris management by recycling and reuse of the debris
- The roles of TDMS
- Pros and Cons of TDMS when it is operated without technical and environmental validations
- We, DRR group, developed a framework and the system dynamic modeling for effective debris management including required TDMS (by GIS) and resources.
- ***ADD NOTE Show the changes of average distances from collection points to TDMS by increasing a number of TDMS. The star in the box is a location of TDMS ----- Slide-14: What are the numbers 12.46, 8.37, 6.84 etc. What is SD...system dynamics? Why are the numbers different Red dots are average hauling distances from the collection points to TDMS. e.g., The left one (install one TDMS) shows that the average distance is 12.46 and SD(standard deviation) is 7.26. The figure in the middle describe that the average hauling distance will be 8.37 and the standard deviation is 4.85 miles when we install two TDMS. These diagrams show that how the average distance and stadard deviation will be changed by increasing a number of TDMS (from 1 to 3)
- *** ADD NOTE The figure compared the debris removal performance by # of TDMS and resources. T1R180 = Install 1 TDMS with 180 resources. For example, comparing T1R240 to T2R180, we identified balancing between infrastructure and resource is critical to enhance debris removal capacity. T3R240 (fastest removal speed by 3 TDMS and 240 resources) was not selected as a plan since overwhelmed input from collection point to TDMS are exceed the capacity of TDMS. ---- Slide-15: what do we mean by 180 resources. What area was covered by each TDMS and what capacity for each. Resource is a hauling truck. 180 resources means 180 trucks are operated to transfer debris. By operating 3 TDMSs with 240 resources (T3R240), the amount of debris (hauled to TDMS) exceed the TDMS capacity (1M CY can be stored in the TDMS in this scenario). That is, the amount of debris hauled to TDMS is higher than the amount transported from the TDMS to a final destination. The maximum number of resources are 240 in the scenario above. Thus, T3R240 is inappropriate solution in this case.
- Several researchers have used queuing theory and scenario-based simulation for Vehicle routing and allocation based on static data or assumptions Siting a TDMS through cost-benefit analysis and process automation using GIS Environmental : regulations from federal, state and local level Few research for socio-political are, particularly for siting TDMS (Decision process)
- Left side, the TDMS, marked with star and red circle, is selected by technical aspect to expedite debris removal speed among 30 candidates. What are the public opinions about it? How about the people living near TDMS? People do not want to live near facilities related to waste. On the right side, Lober and Green developed the logit model after survey. They identified people’s need and distributional equality are most important factors to reduce general public opposition. --- what is NIABY...Not in any backyard? What factors are being considered and how were they evaluated. What were the results? - NIABY is Not In Anyone’s Backyard. Opposition to certain developments as inappropriate anywhere in the world. For example the building of nuclear power plants is often subject to NIABY concerns. A logit model of public opposition to solid waste facility siting is constructed. Data are collected from in-person surveys regarding attitudes toward transfer station. The authors hypothesis is “ people will object less if they perceive a need for the facility” . To test this, a model of opposition was developed that controls for perception of need. Perception of need is a significant determinant of siting attitudes for transfer stations. To test the hypothesis that individuals include equity concerns in their siting attitudes, a question on distributional fairness was posed. Responders were asked whether they would prefer that a waste facility be located either 50 miles away in A area or 50 miles away in B area.
- Methodology: Spatial opinion dynamics used for this model. Neighbors’ opinion ? - Local opinion, Moore 3x3 neighborhood : Moore neighborhood is defined on a two0dimensional square lattice and is composed of a central cell and the eight cells which surround it
- what are the three figures. Please send me a larger image. What is 0.4, 0.5, 0.6 and what does it mean location is uninformed 0.4 -> 40 % of the agents are affected by a disaster (Initial condition) 0.5 -> 50 % of the agents are affected by a disaster (Initial condition) 0.6 -> 60 % of the agents are affected by a disaster (Initial condition) As shown above, the initial condition ( % of disaster-affected) affect people’s opinion toward a TDMS (TDMS location is not informed to agents in this scenario) -> So agents decided their opinion based on initial condition (disaster-affected or not ) and social influence. That is, the spatial influence was not activated since they don’t have information yet. What socio-political factors were considered? The spatial influence has additional indicator, equality, which compare a distance from TDMS to the average distance of the agents from TDMS, The modeling will identify social behavior (opposition map) via ABM model and the opposition percentage by a location of and a number of TDMS. The results can be used to develop a policy to site a TDMS