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Assessing Climate Change Risk and
Adaptation Policy Improvements through
Text-mining
Research Director, Site planning
Youngeun Kang
Contents
1. Introduction
2. Literature Review
3. Results
4. Discussion for Climate Change Adaptation Policy
5. Conclusion
1.1. Background and Goal
1.2. Scope and Methodologies
2.1. Climate Change Risk and Climate Adaptation
2.2. Related Research Review
3.1. Climate Change Risk Assessment Using Newspaper Articles
3.2. Comparison between Risk Assessment and Adaptation Measures
1.1. Background and Goal
1. Introduction
Recently, climate change issues are perceived as a major threat
since a number of studies have been published to prove
abnormal climate change. However, skeptics criticized it for
reasons such as development logic, political tendency, and
insufficient scientific evidence.
From this point of view, using Big data for securing relevant
data has great potential in terms of reflecting policy through
coordination of opinions on climate change, systematic data
analysis and forecasting(Kim et al., 2015; Hamed et al., 2015;
Jang & Hart, 2015; Boussalis & Coan, 2016)
3
1. Introduction
International trend in response to climate change is being
reorganized into a risk management system that predicts and
manages urcertain future losses
• Climate change risk is universally recognized as a function of probabilities and
consequences of clmate change and serves as a basis for setting priorties for
climate change adaptation policy implementation
4
Past climate change risk assessments have been based on
qualitative assessment studes by expert surveys because of the
difficulty of measuring and predicting the extent of climate
change risks
In this paper, we aim to evaluate the risk of climate change by
using big data analysis (text-mining) based on newspaper
articles in terms of securing objectivity of climate change risk
assessment and suggest implications for adaptation measures
1.1. Background and Goal
1. Introduction
1.2. Scope and Methodologies
This study aims to present the climate change adaptation policy
implication by analyzing the consequence and the possibilities
(frequency) of each climate risk item
Division Contents
Climate change risk
item
181 climate change risk items in seven categories of health
(HE), water (WA), forest ecosystem (ES), land and coastal
land (LC), industrial energy (IE), agriculture and
livestock(AG), marine fisheries (MF) (ex: ‘Increased hazard
due to harmful substances’, ‘Increased marine garbage
caused by coastal flooding’ etc) from expert survey and
elicitation
Climate observation
impact data
4,150 newspaper articles related with climate change
impact over 24 years, since 1990(1990.1.1~2013.12.31)
5
1. Introduction
Using climate change impact newspaper articles (4,150 cases) as
analytical data, the contents of newspaper articles are recorded
as property damage (billion units) or the number of causaulties
(including missing individuals)
In the selected newspaper articles, matching with 181 risk items
from the previous study was processed (Park et al., 2014)
The frequency with which the risk item was matched was set as
‘probability’, and the damage amount was set as
‘consequences’(mean value of matched items)
The calculation of matching tasks and finding out risk
consequences (damage amount) by each newspaper article was
performed by using Python program
The comprehensive risk assessment is derived by multiplying
the consequences (damage amount) and frequency of each risk
item
6
1.2. Scope and Methodologies (Refining Newspaper Articles)
Climate Change Driver
Newspa
per
Climate Change Damage Division Risk
Reg
ion
• Newspaper article data (Duration: 1990. 1. 1 ~ 2013. 12. 31/ 24 years)
• based on 22 different national and regional newspapers (ex. the Kyunghyang
newspaper, Dong-A ilbo, Seoul newspaper, etc)
1. Introduction
Example of Newspaper Article Analysis
1.2. Scope and Methodologies (Refining Newspaper Articles)
7
1. Introduction
Climate Change Risk Assessment
Literature
Review
- Climate Change Risk
Consept
- Risk Assessment
Framework
Newspap
er
Analysis
- Climate Change Risk
Status (Frequency
andamount of
damage)
- Main Risk items
- Main Climate
Change driver/Type
of damage
Comparison with existing
related study
Climate
change
risk
comparis
on
- Comparison
of major
risk items
- Confirming
overlapped
climate
change risks
with
previous
study
Implicatio
n for
Climate
Change
Adaptatio
n Policy
(Korea)
8
1.2. Scope and Methodologies (Research Process)
2. Literature Review
2.1. Climate Change Risk and Climate Adaptation
Risk refers to the potential to lose something of value, where
value includes physical health, social status, emotional
happiniess or economic security: damage, loss, negativity, or
threats caused by vulnerability
Climate change risk is understood as the potential to lose
something of value due to climate change
• Risk = Vulnerability * Exposure * Hazard
• Risk = Probability * Consequence (damage amount, causalties, etc)
Climate change risks are directly linked to adaptation, which is
one of the direction of climate change response
• Climate change risk analysis can be as an intermediate step for
improving climate change adaptation policy effectiveness and
minimizing uncertainty
9
1. Introduction
10
Researchers Climate change risk concept Characteristics
Kaplan (1981) Consists of three components: “outco
tcome,” “likelihood,” and“severity”
Adds “seriousness” to
existingrisk concepts
Brauner (2002) Increases the likelihoodof climate
-
-
related damage andloss
rela Applies opportunity terms
to risks (positive effects of cli
climate change)
Brooks (2003) Expressedas a function of climate haza
hazard andvulnerability -
Taylor et al. (2014
4)
An unprecedentedchallenge to human
man adaptability -
Eakin (2005)
Expressedin terms of vulnerability and
andexposure to extreme climate chan
hange
-
Kim (2013)
Apotential negative impact or outcom
come that may occur in the present or
nt or future
Appliedtime concept (presen
sent andfuture)
Kim and Park
(2013)
The realization of scientific techniques
ues andempirical means, amongmany
many ways to face an uncertain future;
ture; a way of expressingpredictions of
ns of the future
-
2.1. Climate Change Risk and Climate Adaptation
Climate Change Risk Concept and Characteristics
2. Literature Review
2.2. Related research review
Climate change risk studies have increased significantly as
climate change ‘adapatation’ becomes more important
• Studies on the value calculation based on climate change risk index
or modeling (Bowering et al., 2010; Morsch, 2010; Lung et al., 2013;
Veronesi et al., 2014)
• Socioeconomic risk assessment studies (Carlton and Jacobson, 2013;
Van der Linden, 2015)
• Risk assessment by expert survey or elicitation (Defra, 2012; Park et
al., 2014; Kim, 2015)
The main purpose of this risk assessment is to quantify the risk
by probability, standardized score, loss amount, etc., and to
suggest effective policy direction for awareness of the problem
consciousness and risk reduction
However, due to the difficulty in obtaining data on climate
change risks and the uncertainty of future forecasts, there are
many limitations in quantifying risks
11
3. Results
3.1. Climate Change Risk Assessment Using Newspaper Articles
As a result of investigating the number of risk cases (shown
damage amount or causalties by each newspaper article), 3,098
out of 4,150 of the total analysis articles were about 74.7%
It was found that up to five climate change risk items were
matched by the impact of climate change observation (each
newspaper article) with 181 climate change risk items
The risk assessment values were compiled in descending order
by the risk consequence (damage amount: billion units) and
frequency (the number of matching newspaper articles per risk)
• The maximum amount of damages per one case was 5,388.7 billion,
and the maximum amount of damage by the average value of risk
was 2,693.6 billion
• Other major risk items include ‘erosion of agricultural land due to
increased precipitation’, ‘increase in mortality rate from disaster’, etc.
12
3. Results
• Based on the result of the final value of the risk, it is arranged in descending order
• Number of cases: number of matches with newspaper articles (observation effect)
Risk Assessment by
newspaper articles
Frequency /percent of
matching of major climate
chanre risk items by sector
13
3.1. Climate Change Risk Assessment Using Newspaper Articles
Code Risk item Frequency Damage
amount
LC42 deterioratingresidential environment due to coastal flooding 554 26,936
AG04 Croplanderosiondue to increasedprecipitation 482 26,824
HE18 Increasedmortality due to disasters 573 20,086
HE24 Increasedmortality rate due to short-term suddenweather changes 467 20,048
AG09 Collapse of agricultural andlivestockfacilities due to weather disasters 252 26,934
LC06 Decompositionandfunctiondegradationof river facilities suchas embankments andbridges
bridges
211 22,001
LC34 Increasedmortality anddamage causedby coastal flooding 212 5,600
LC01 Degradationandsuspensionof traffic facilities due to flooding 617 5,000
AG03 Increaseddamage to cropsandlivestockcausedbyfloodsandtyphoons 405 22,043
IE25 Increase in demandfor constructionfollowingthe destructionof facilities andinfrastructures 78 5,600
:
Division HE WA ES LC IE AG MF Total
Matching 5 5 3 26 11 7 2 59
Percent 8.5% 8.5% 5.1% 44.1% 18.6% 11.9% 3.4% 100%
*health (HE), water (WA), forest ecosystem(ES), landandcoastal land(LC), industrial energy(IE), agriculture andlivestock(AG), marine fisheries(MF)
3. Results
Setting the x-axis and y-axis values as the average of the
frequency of occurrence and consequence (112.2 cases, 4,397.4
billion) for the 59 major climate change risk
14
3.1. Climate Change Risk Assessment Using Newspaper Articles
Damage
Amount
Frequency
3. Results
3.2. Comparison between Risk Assessment and Adaptation Measures
Main climate change risk by climate change adaptation
measures (2014) include preparing a preliminary list of risks for
climate change -> establishing climate change risk items ->
evaluating climate change risk by expert survey -> ordering
main climate change risk items
High overlapped percent between climate change adaptation
measures (2014) and our results (59 main risk items); LC (12,
48.0%), AG (16.0%), and HE (12.0%)
In previous study, primary risk and secondary risk have been
emphasized, but this results was focused mainly on primary
climate change risk
15
3. Results
Risk items that match the main risks from previous study
16
3.2. Comparison between Risk Assessment and Adaptation Measures
code Risk item code Risk item
HE13 Incresedimpacts onvulnerable populationdueto intenseurbanheat
urbanheat islandphenomenon
LC09 Degradationandsuspensionof traffic facilities dueto heavysnow
snow
HE18 Increasedmortality dueto disasters LC32 Increaseddamageto harbors andfishingport facilitiescausedbycoastal
bycoastal flooding
HE19 Increasedinjury due to disasters LC10 Damageandcollapseof temporary buildingscausedbysnowfall
snowfall
WA12 Water quality deteriorationdueto increasingalgae in rising
temperature levels
LC27 Coastal buildingdamage causedby coastal flooding
WA18 Destructionof river bankdueto flooding LC11 Residents at increasedriskof isolationandvulnerability dueto snowfall
snowfall
ES03 Changesin the growthandsurvival ratesof eachspecies through
throughclimate change
LC33 Incresedriskregardingcoastal structurescausedby coastal erosion
erosion
ES13 Increasedsoil erosionwith increasingprecipitation LC24 Damageto distributionfacilitiesdue to strongwinds
LC02 Damageandlossof traffic facilities dueto landslidesonsteepslopes
slopes
LC26 Damageto facilitiessuchas signboardsdueto strongwinds
LC22 Flooddamageto traffic facilitiescausedbytyphoonandtsunami
tsunami
IE21 Increasedstorage andmanagement costs for raw materials and
products
LC01 Degradationandsuspensionof traffic facilities dueto flooding AG09 Collapseof agricultural andlivestockfacilitiesdue to weather disasters
disasters
LC06 Decompositionandfunctiondegradationof river facilities suchas
suchas embankments andbridges
AG13 Increasedstress, disease, anddeath of livestockcausedbyextreme
extremeweather
AG06 Changesin the timingandlocationof suitable cultivation AG04 Croplanderosiondueto increasedprecipitation
MF02 Influxof harmful marine organismsdueto risingseawater
*health (HE), water (WA), forest ecosystem(ES), landandcoastal land(LC), industrial energy(IE), agriculture andlivestock(AG), marine fisheries(MF)
4. Discussion for Climate Change Adaptation Policy
4. Discussion for Climate Change Adaptation Policy
Korea implemented the second adaption measures covering 20 specific plan
in 5 fields, and compared its relevance with our results
17
Division Code Climate Change RiskItems Relevance
Quadrant 1
AG03 Increaseddamage to cropsandlivestockcausedbyfloodsandtyphoons ○
AG04 Croplanderosiondue to increasedprecipitation ○
AG09 Collapse of agricultural andlivestockfacilities due to weather disasters ○
HE18 Increasedmortality due to disasters ○
HE24 Increasedmortality rate due to short-term suddenweather changes ○
LC01 Degradationandsuspensionof traffic facilities due to flooding ○
LC02 Damage andlossof traffic facilities due to landslides onsteepslopes ○
LC06 Decompositionandfunctiondegradationof river facilities suchas embankments andbridges ○
LC25 Buildingdamage due to strongwinds △
LC34 Increasedmortality anddamage causedby coastal flooding ○
LC42 Increasein floodedareas anda deterioratingresidential environment due to coastal flooding ○
Quadrant 2
HE15 Increasedrespiratory disease due to abnormal low temperature phenomenon ○
IE25 Increase in demandfor constructionfollowingthe destructionof facilities andinfrastructures ○
LC26 Damage to facilities suchas signboardsdue to strongwinds ○
WA18 Destructionof river bankdue to flooding ○
Quadrant 3
AG02 Increaseddamage to cropsandlivestockdue to the spreadof pests anddiseases ○
ES13 Increasedsoil erosionwith increasingprecipitation ○
HE19 Increasedinjury due to disasters ○
IE26 Increasedriskof insurance industry lossesdue to abnormal weather ○
LC09 Degradationandsuspensionof traffic facilities due to heavy snow ○
LC10 Damage andcollapse of temporary buildingscausedbysnowfall ○
WA03 Shortage of water for daily needsdue to drought ○
5. Conclusion
5. Conclusion
This study derived the climate change risk value based on the
observed influence data (newspaper articles) and suggested
adaptation policy implications
The comparison of the climate change risk items derived from
previous study and the newspaper articles on climate change
impacts shows a high impact on observation, but some cases
are not selected as climate change risk items
The frequency of risk matching for events or damage centered
on the human system was much higher than the impact on the
natural system
Comparison of risk results by observed impacts and previous
related study (Primary and secondary risk differentiation)
This study can be used to provide objectivity in presenting
climate change risk items and it will be reflected in the
adaptation measures in parall with the existing survey method
18
Thank you

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1.3c Methodology for Climate Change Risk Assessment Using Text Mining

  • 1. Assessing Climate Change Risk and Adaptation Policy Improvements through Text-mining Research Director, Site planning Youngeun Kang
  • 2. Contents 1. Introduction 2. Literature Review 3. Results 4. Discussion for Climate Change Adaptation Policy 5. Conclusion 1.1. Background and Goal 1.2. Scope and Methodologies 2.1. Climate Change Risk and Climate Adaptation 2.2. Related Research Review 3.1. Climate Change Risk Assessment Using Newspaper Articles 3.2. Comparison between Risk Assessment and Adaptation Measures
  • 3. 1.1. Background and Goal 1. Introduction Recently, climate change issues are perceived as a major threat since a number of studies have been published to prove abnormal climate change. However, skeptics criticized it for reasons such as development logic, political tendency, and insufficient scientific evidence. From this point of view, using Big data for securing relevant data has great potential in terms of reflecting policy through coordination of opinions on climate change, systematic data analysis and forecasting(Kim et al., 2015; Hamed et al., 2015; Jang & Hart, 2015; Boussalis & Coan, 2016) 3
  • 4. 1. Introduction International trend in response to climate change is being reorganized into a risk management system that predicts and manages urcertain future losses • Climate change risk is universally recognized as a function of probabilities and consequences of clmate change and serves as a basis for setting priorties for climate change adaptation policy implementation 4 Past climate change risk assessments have been based on qualitative assessment studes by expert surveys because of the difficulty of measuring and predicting the extent of climate change risks In this paper, we aim to evaluate the risk of climate change by using big data analysis (text-mining) based on newspaper articles in terms of securing objectivity of climate change risk assessment and suggest implications for adaptation measures 1.1. Background and Goal
  • 5. 1. Introduction 1.2. Scope and Methodologies This study aims to present the climate change adaptation policy implication by analyzing the consequence and the possibilities (frequency) of each climate risk item Division Contents Climate change risk item 181 climate change risk items in seven categories of health (HE), water (WA), forest ecosystem (ES), land and coastal land (LC), industrial energy (IE), agriculture and livestock(AG), marine fisheries (MF) (ex: ‘Increased hazard due to harmful substances’, ‘Increased marine garbage caused by coastal flooding’ etc) from expert survey and elicitation Climate observation impact data 4,150 newspaper articles related with climate change impact over 24 years, since 1990(1990.1.1~2013.12.31) 5
  • 6. 1. Introduction Using climate change impact newspaper articles (4,150 cases) as analytical data, the contents of newspaper articles are recorded as property damage (billion units) or the number of causaulties (including missing individuals) In the selected newspaper articles, matching with 181 risk items from the previous study was processed (Park et al., 2014) The frequency with which the risk item was matched was set as ‘probability’, and the damage amount was set as ‘consequences’(mean value of matched items) The calculation of matching tasks and finding out risk consequences (damage amount) by each newspaper article was performed by using Python program The comprehensive risk assessment is derived by multiplying the consequences (damage amount) and frequency of each risk item 6 1.2. Scope and Methodologies (Refining Newspaper Articles)
  • 7. Climate Change Driver Newspa per Climate Change Damage Division Risk Reg ion • Newspaper article data (Duration: 1990. 1. 1 ~ 2013. 12. 31/ 24 years) • based on 22 different national and regional newspapers (ex. the Kyunghyang newspaper, Dong-A ilbo, Seoul newspaper, etc) 1. Introduction Example of Newspaper Article Analysis 1.2. Scope and Methodologies (Refining Newspaper Articles) 7
  • 8. 1. Introduction Climate Change Risk Assessment Literature Review - Climate Change Risk Consept - Risk Assessment Framework Newspap er Analysis - Climate Change Risk Status (Frequency andamount of damage) - Main Risk items - Main Climate Change driver/Type of damage Comparison with existing related study Climate change risk comparis on - Comparison of major risk items - Confirming overlapped climate change risks with previous study Implicatio n for Climate Change Adaptatio n Policy (Korea) 8 1.2. Scope and Methodologies (Research Process)
  • 9. 2. Literature Review 2.1. Climate Change Risk and Climate Adaptation Risk refers to the potential to lose something of value, where value includes physical health, social status, emotional happiniess or economic security: damage, loss, negativity, or threats caused by vulnerability Climate change risk is understood as the potential to lose something of value due to climate change • Risk = Vulnerability * Exposure * Hazard • Risk = Probability * Consequence (damage amount, causalties, etc) Climate change risks are directly linked to adaptation, which is one of the direction of climate change response • Climate change risk analysis can be as an intermediate step for improving climate change adaptation policy effectiveness and minimizing uncertainty 9
  • 10. 1. Introduction 10 Researchers Climate change risk concept Characteristics Kaplan (1981) Consists of three components: “outco tcome,” “likelihood,” and“severity” Adds “seriousness” to existingrisk concepts Brauner (2002) Increases the likelihoodof climate - - related damage andloss rela Applies opportunity terms to risks (positive effects of cli climate change) Brooks (2003) Expressedas a function of climate haza hazard andvulnerability - Taylor et al. (2014 4) An unprecedentedchallenge to human man adaptability - Eakin (2005) Expressedin terms of vulnerability and andexposure to extreme climate chan hange - Kim (2013) Apotential negative impact or outcom come that may occur in the present or nt or future Appliedtime concept (presen sent andfuture) Kim and Park (2013) The realization of scientific techniques ues andempirical means, amongmany many ways to face an uncertain future; ture; a way of expressingpredictions of ns of the future - 2.1. Climate Change Risk and Climate Adaptation Climate Change Risk Concept and Characteristics
  • 11. 2. Literature Review 2.2. Related research review Climate change risk studies have increased significantly as climate change ‘adapatation’ becomes more important • Studies on the value calculation based on climate change risk index or modeling (Bowering et al., 2010; Morsch, 2010; Lung et al., 2013; Veronesi et al., 2014) • Socioeconomic risk assessment studies (Carlton and Jacobson, 2013; Van der Linden, 2015) • Risk assessment by expert survey or elicitation (Defra, 2012; Park et al., 2014; Kim, 2015) The main purpose of this risk assessment is to quantify the risk by probability, standardized score, loss amount, etc., and to suggest effective policy direction for awareness of the problem consciousness and risk reduction However, due to the difficulty in obtaining data on climate change risks and the uncertainty of future forecasts, there are many limitations in quantifying risks 11
  • 12. 3. Results 3.1. Climate Change Risk Assessment Using Newspaper Articles As a result of investigating the number of risk cases (shown damage amount or causalties by each newspaper article), 3,098 out of 4,150 of the total analysis articles were about 74.7% It was found that up to five climate change risk items were matched by the impact of climate change observation (each newspaper article) with 181 climate change risk items The risk assessment values were compiled in descending order by the risk consequence (damage amount: billion units) and frequency (the number of matching newspaper articles per risk) • The maximum amount of damages per one case was 5,388.7 billion, and the maximum amount of damage by the average value of risk was 2,693.6 billion • Other major risk items include ‘erosion of agricultural land due to increased precipitation’, ‘increase in mortality rate from disaster’, etc. 12
  • 13. 3. Results • Based on the result of the final value of the risk, it is arranged in descending order • Number of cases: number of matches with newspaper articles (observation effect) Risk Assessment by newspaper articles Frequency /percent of matching of major climate chanre risk items by sector 13 3.1. Climate Change Risk Assessment Using Newspaper Articles Code Risk item Frequency Damage amount LC42 deterioratingresidential environment due to coastal flooding 554 26,936 AG04 Croplanderosiondue to increasedprecipitation 482 26,824 HE18 Increasedmortality due to disasters 573 20,086 HE24 Increasedmortality rate due to short-term suddenweather changes 467 20,048 AG09 Collapse of agricultural andlivestockfacilities due to weather disasters 252 26,934 LC06 Decompositionandfunctiondegradationof river facilities suchas embankments andbridges bridges 211 22,001 LC34 Increasedmortality anddamage causedby coastal flooding 212 5,600 LC01 Degradationandsuspensionof traffic facilities due to flooding 617 5,000 AG03 Increaseddamage to cropsandlivestockcausedbyfloodsandtyphoons 405 22,043 IE25 Increase in demandfor constructionfollowingthe destructionof facilities andinfrastructures 78 5,600 : Division HE WA ES LC IE AG MF Total Matching 5 5 3 26 11 7 2 59 Percent 8.5% 8.5% 5.1% 44.1% 18.6% 11.9% 3.4% 100% *health (HE), water (WA), forest ecosystem(ES), landandcoastal land(LC), industrial energy(IE), agriculture andlivestock(AG), marine fisheries(MF)
  • 14. 3. Results Setting the x-axis and y-axis values as the average of the frequency of occurrence and consequence (112.2 cases, 4,397.4 billion) for the 59 major climate change risk 14 3.1. Climate Change Risk Assessment Using Newspaper Articles Damage Amount Frequency
  • 15. 3. Results 3.2. Comparison between Risk Assessment and Adaptation Measures Main climate change risk by climate change adaptation measures (2014) include preparing a preliminary list of risks for climate change -> establishing climate change risk items -> evaluating climate change risk by expert survey -> ordering main climate change risk items High overlapped percent between climate change adaptation measures (2014) and our results (59 main risk items); LC (12, 48.0%), AG (16.0%), and HE (12.0%) In previous study, primary risk and secondary risk have been emphasized, but this results was focused mainly on primary climate change risk 15
  • 16. 3. Results Risk items that match the main risks from previous study 16 3.2. Comparison between Risk Assessment and Adaptation Measures code Risk item code Risk item HE13 Incresedimpacts onvulnerable populationdueto intenseurbanheat urbanheat islandphenomenon LC09 Degradationandsuspensionof traffic facilities dueto heavysnow snow HE18 Increasedmortality dueto disasters LC32 Increaseddamageto harbors andfishingport facilitiescausedbycoastal bycoastal flooding HE19 Increasedinjury due to disasters LC10 Damageandcollapseof temporary buildingscausedbysnowfall snowfall WA12 Water quality deteriorationdueto increasingalgae in rising temperature levels LC27 Coastal buildingdamage causedby coastal flooding WA18 Destructionof river bankdueto flooding LC11 Residents at increasedriskof isolationandvulnerability dueto snowfall snowfall ES03 Changesin the growthandsurvival ratesof eachspecies through throughclimate change LC33 Incresedriskregardingcoastal structurescausedby coastal erosion erosion ES13 Increasedsoil erosionwith increasingprecipitation LC24 Damageto distributionfacilitiesdue to strongwinds LC02 Damageandlossof traffic facilities dueto landslidesonsteepslopes slopes LC26 Damageto facilitiessuchas signboardsdueto strongwinds LC22 Flooddamageto traffic facilitiescausedbytyphoonandtsunami tsunami IE21 Increasedstorage andmanagement costs for raw materials and products LC01 Degradationandsuspensionof traffic facilities dueto flooding AG09 Collapseof agricultural andlivestockfacilitiesdue to weather disasters disasters LC06 Decompositionandfunctiondegradationof river facilities suchas suchas embankments andbridges AG13 Increasedstress, disease, anddeath of livestockcausedbyextreme extremeweather AG06 Changesin the timingandlocationof suitable cultivation AG04 Croplanderosiondueto increasedprecipitation MF02 Influxof harmful marine organismsdueto risingseawater *health (HE), water (WA), forest ecosystem(ES), landandcoastal land(LC), industrial energy(IE), agriculture andlivestock(AG), marine fisheries(MF)
  • 17. 4. Discussion for Climate Change Adaptation Policy 4. Discussion for Climate Change Adaptation Policy Korea implemented the second adaption measures covering 20 specific plan in 5 fields, and compared its relevance with our results 17 Division Code Climate Change RiskItems Relevance Quadrant 1 AG03 Increaseddamage to cropsandlivestockcausedbyfloodsandtyphoons ○ AG04 Croplanderosiondue to increasedprecipitation ○ AG09 Collapse of agricultural andlivestockfacilities due to weather disasters ○ HE18 Increasedmortality due to disasters ○ HE24 Increasedmortality rate due to short-term suddenweather changes ○ LC01 Degradationandsuspensionof traffic facilities due to flooding ○ LC02 Damage andlossof traffic facilities due to landslides onsteepslopes ○ LC06 Decompositionandfunctiondegradationof river facilities suchas embankments andbridges ○ LC25 Buildingdamage due to strongwinds △ LC34 Increasedmortality anddamage causedby coastal flooding ○ LC42 Increasein floodedareas anda deterioratingresidential environment due to coastal flooding ○ Quadrant 2 HE15 Increasedrespiratory disease due to abnormal low temperature phenomenon ○ IE25 Increase in demandfor constructionfollowingthe destructionof facilities andinfrastructures ○ LC26 Damage to facilities suchas signboardsdue to strongwinds ○ WA18 Destructionof river bankdue to flooding ○ Quadrant 3 AG02 Increaseddamage to cropsandlivestockdue to the spreadof pests anddiseases ○ ES13 Increasedsoil erosionwith increasingprecipitation ○ HE19 Increasedinjury due to disasters ○ IE26 Increasedriskof insurance industry lossesdue to abnormal weather ○ LC09 Degradationandsuspensionof traffic facilities due to heavy snow ○ LC10 Damage andcollapse of temporary buildingscausedbysnowfall ○ WA03 Shortage of water for daily needsdue to drought ○
  • 18. 5. Conclusion 5. Conclusion This study derived the climate change risk value based on the observed influence data (newspaper articles) and suggested adaptation policy implications The comparison of the climate change risk items derived from previous study and the newspaper articles on climate change impacts shows a high impact on observation, but some cases are not selected as climate change risk items The frequency of risk matching for events or damage centered on the human system was much higher than the impact on the natural system Comparison of risk results by observed impacts and previous related study (Primary and secondary risk differentiation) This study can be used to provide objectivity in presenting climate change risk items and it will be reflected in the adaptation measures in parall with the existing survey method 18