Cold Spot Risk Assessment
Ukraine - Winterization 2022/23
This story map is based on the analysis and content of the Winterization 2022/2023: Cold Spot Risk Assessment factsheet :
Introduction
In their flash update from 17th October 2022, the United Nations Office for the Coordination of Humanitarian Affairs (UNOCHA) highlighted the ongoing winterization efforts to help at least 2.4 million Ukrainians prepare for the upcoming cold conditions. Overall capacity to cope with cold temperatures is being further impaired by ongoing destruction and failure of infrastructures (e.g., electricity, water, heating) (UNOCHA 2022) .
Conflict escalation and ongoing hostilities have caused significant damage to public utilities, gas and energy infrastructure in most oblasts putting the population at risk of losing access to heating due to potential hostilities-related damage to centralized heating systems or energy infrastructure. In addition, hostilities lead to the inability to repair damage, thus further impacting functionality of these systems (REACH 2022a) .
Video: Damaged residential building in Kharkiv City. © Ines Dadda/ACTED November 2022
The combination of more severe climatic conditions and considerable damage to infrastructure and private houses caused by hostilities can potentially further aggravate vulnerabilities of the affected population exposed to low winter temperatures.
Image: Damaged residential building. © Maria Kratik/ACTED 2022
Those impacts have been putting a growing number of people at risk of having insufficient heating or insulation to cope with cold temperatures. The approaching winter conditions are particularly concerning for IDPs living in collective centers and people living in damaged homes or homes needing renovation, especially in rural areas (ACAPS 2022) .
Video: Damaged residential building in Dnipro City. © Ines Dadda/ACTED November 2022
Winterization needs therefore include but are not limited to repairing damaged buildings (e.g., broken windows) and bomb shelters, restoring infrastructures, providing cash assistance and supporting preparations for an influx of new IDPs. 6.2 million Ukrainian are already internally displaced and some oblasts expect that many more could arrive before winter. This expected wave of displacement before the start of the winter could increase the impacts of winter-related hazards.
Image: Window reparations in Chernivtsi Oblast. © ACTED Ukraine 2022
Methodology
This Cold Spot Risk Assessment aims to identify geographic locations of ‘Cold Spots’, meaning geographic areas where winter-related hazards (e.g., cold waves) compound with susceptibilities (e.g., internal displacement; older persons; etc.) and the Lack of Coping Capacity (LOCC) (e.g., infrastructure damages), impacting vulnerable people most severely. The concept of the analysis is derived from the disaster risk model by the United Nations Office for Disaster Risk Reduction (UNDRR 2017) which defines risk as a combination of hazard, exposure, and vulnerability (consisting of susceptibility and the LOCC).
Risk is defined as the consequence of the interaction between hazards and the characteristics of exposure and vulnerabilities. Within this study, the following risk formula is used:
Risk = Hazard x Exposure x Vulnerability (Susceptibility + Lack of Coping Capacity)
Hazard ‘A hazard is a process, phenomenon or human activity that may cause loss of life, injury or other health impacts, property damage, social and economic disruption or environmental degradation. Hazards may be natural, anthropogenic or socionatural in origin’. This study focuses on winter-related hydrometeorological hazards, including cold waves and cold temperatures.
Exposure ‘The situation of people, infrastructure, housing, production capacities and other tangible human assets located in hazard-prone areas’. This study focuses on people exposed to winter-related hazards.
Vulnerability ‘The characteristics determined by physical, social, economic and environmental factors or processes which increase the susceptibility of an individual, a community, assets or systems to the impacts of hazards.’ In this study vulnerability is defined as a combination of susceptibility and the Lack of Coping Capacity (LOCC):
- Susceptibility: People’s susceptibility to the impacts of hazards, which can be enhanced due to certain conditions (e.g., internal displacement, age, economic instability).
- Lack of Coping Capacity: Conditions which reduce people’s capacity to cope with impacts of hazards (e.g., damages to heating infrastructures, structural damages to buildings like broken windows or pipes).
The ‘Cold Spot Index (CSI)’ was then calculated, using following formula:
CSI = Hazard Class * 0.35 + Exposure Class * 0.25 + Vulnerability ((Susceptibilities Class + LOCC Class) / 2) * 0.4
This formula defines Cold Spot risk as a combination of hazard (weighted 35%), exposure (weighted 25%), and vulnerability (weighted 40% and understood as a combination of susceptibility and the LOCC).
Image: Damaged residential building. © Ines Dadda/ACTED November 2022
Winter Conditions
The climate in Ukraine is temperate continental, with cold winters and warm summers.
Winter conditions can be characterized by the number of days when the temperature drops below 0˚C for at least a short time within a day (frost days) or when it persists below 0˚C across an entire day (ice days).
During the past cold seasons (from September until May) in 2010-2020 the number of frost days in Ukraine on average was estimated to 105 days per season (REACH 2022b) . The map on the left shows the mean number of frost days per cold season (2010-2020) when daily minimum temperature fell below 0°C.
Interact with the map: Click on a raion to open pop-ups with detailed information. Use the '+/-' buttons to the right to zoom in on an area.
Data source: ECMWF / Copernicus Climate Change Service
The raions marked in red are the 20% of all raions in Ukraine with the highest number of mean frost days per season.
This includes raions along the north-eastern border of Ukraine...
... as well as the areas of the Carpathian mountain range in the west of Ukraine.
Cold waves are defined by either a rapid drop in air temperature or a sustained period of excessive cold (IFRC 2022) . Severe cold is a threat to human health as prolonged exposure can lead to conditions such as hypothermia, frostbite or cardiac arrest (Wang et al. 2016) .
Satellite derived land surface temperature suggests that north-east oblasts are the most exposed to cold waves. The map to the left shows the mean percentage of days experiencing cold waves (days with temperatures below -15°C) per raion (Dec-Feb: 2000-2021).
Interact with the map: Click on a raion to open pop-ups with detailed information. Use the '+/-' buttons to the right to zoom in on an area.
Data source: ECMWF / Copernicus Climate Change Service
The raions marked in red are the 20% of all raions in Ukraine with the highest percentage of days experiencing cold waves (days with temperatures below -15°C) per raion (Dec-Feb: 2000-2021).
This is the case for the raions along the north-eastern border of Ukraine until Kyiv in the north and until the borders of Dnipropetrovsk oblast in the east.
Hazard Exposure Vulnerability
Data sets of indicators for the groups of hazard (frost days; cold waves), exposure (population density), susceptibilities (number of IDPs per raion; percentage of elderly population; average income), and the LOCC (conflict incidences; heating infrastructure damages; central heating outputs) were identified and analysed. The following maps show the classes for each group which were defined through assessing the indicator values per raion.
Interact with the maps: Click on a raion to open pop-ups with detailed information or use the '+/-' buttons on the right to zoom in on an area.
Hazard Class
The hazard component in the analysis assesses exposure to winter-related hazards across Ukraine.
Hazard Indicators
Cold Waves Cold waves have been selected as the indicator due to the strong impact of extreme cold temperature on lives and livelihoods. Unit: The mean percentage of days experiencing cold waves (days with temperatures below -15°C) in Ukraine (Dec-Feb: 2000-2021). Source: MODIS Land Surface Temperature and Emissivity Data (MOD11) . Limitations: (REACH 2022c) .
Imagery: Dniprovskyi raion after snowfall (December 2011). © Maxar Technologies 2022, viewed in Google Earth 2022
Frost Days The mean number of frost days was included as the indicator to assess areas with long durations of cold temperatures. Unit: The mean number of frost days (daily minimum temperature < 0°C) during the cold season (Sep-May) in Ukraine (2010-2020). Source: Own calculation (REACH 2022) based on ERA5 Daily Aggregates (ECMWF / Copernicus Climate Change Service) . Limitations: (REACH 2022c) .
Imagery: Dniprovskyi raion after snowfall (December 2011) © Maxar Technologies 2022, viewed in Google Earth 2022
Hazard Class
The hazard component in the analysis assesses exposure to winter-related hazards across Ukraine. Select the buttons below to view the different hazard classes:
Exposure Class
The exposure component focuses on identifying the areas where most people are potentially exposed to winter-related hazards.
Exposure Indicator
Population Density Population density has been included as the indicator in order to consider people’s presence and therefore exposure per area. Unit: The number of people present per km2 based on population statistics per oblast (2020). Source: Common Operational Dataset on Population Statistics (COD-PS) (UNFPA 2020) . Limitations: (REACH 2022c) .
Image: Ukrainian residents at the frozen Sea of Azov water front. © Roxana Kuranova 2022
Susceptibility Class
The Susceptibility component assesses susceptibilities to winter conditions across Ukraine.
Susceptibility Indicators
Internal Displacement Internally displaced people have been identified as a group particularly vulnerable to winter-related hazards like extreme cold. Unit: The number of IDPs per raion as of 03 October 2022. Source: The International Organization for Migration (IOM) 2022 . Limitations: (REACH 2022c) .
Image: Damaged residential building. © Maria Kratik/ACTED 2022
Older Persons Older persons (>65 years) have been identified as a group particularly vulnerable to winter-related hazards like extreme cold. Unit: The percentage of older persons (>65 years) population per oblast. Source: Common Operational Dataset on Population Statistics (COD-PS) (UNFPA 2020) . Limitations: (REACH 2022c) .
Image: Ukrainian resident in Lviska Oblast © Ines Dadda/ACTED 2022
Household Income Average monthly income has been included as a vulnerability indicator to winter-related hazards since the capacity to purchase e.g., heating fuels or pay for infrastructure repairs can have a strong impact on the vulnerability to cold conditions. Unit: The average monthly income per household per oblast in 2020 divided by actual subsistence level (MEB: UAH 4334 (Aug 2021)). Source: Income: State Statistics Service of Ukraine 2020 ; MEB: Ukraine Cash Working group 2022 . Limitations: (REACH 2022c) .
Image: Building resident in front of a damaged residential building. © Brendan Hoffman for ACTED Ukraine 2022
Susceptibility Class
The Susceptibility component assesses susceptibilities to winter conditions across Ukraine. Select the buttons below to view the different susceptibility classes:
Lack of Coping Capacity
The LOCC component assesses infrastructure damages and capacities relevant for coping with cold conditions across Ukraine.
LOCC Indicators
Conflict Incidences Conflict incidences were included as a indicator to assess potential structural damages (e.g., broken windows, damaged pipelines) per raion which reduce capacities to cope with cold-conditions. Most recent incidences are weighted more than incidences from earlier this year to consider potential repairs over time. Unit: The number of conflict incidences (type: ‘battles’ or ‘explosions/remote violence’) per raion (February - October 2022) weighted by time period. Source: The Armed Conflict Location & Event Data Project 2022. Limitations: (REACH 2022c) .
Image: Damaged infrastructure after missile strike. © Maria Kratik/ACTED 2022
Damages to Heating Infrastructure Heating infrastructure damages were included as a indicator to assess potential structural damages to heating infrastructure (e.g., nuclear power plant (NPP), combined heat and power plant (CHP), Thermal Power Plant (TTP), gas pipelines, etc.) per raion. Heat pipeline networks, particularly above ground, are exposed to damage from artillery shelling and air strikes. Electricity is critical for both domestic and industrial activities. Because of the linkages between electricity, heating and water supply systems, electricity shortages can have cascading negative consequences for households, inhibiting their ability to heat their homes and access water. Unit: The number of heating infrastructure damages (e.g., NPP, CHP, TTP, gas pipelines, etc.) per raion (February - October 2022) weighted by time period (Most recent incidences are weighted more to consider potential repairs over time). Source: REACH 2022 – infrastructure damages database (data on request). Limitations: (REACH 2022c) .
Image: Damaged infrastructure after missile strike. © Maria Kratik/ACTED 2022
Heat Output High heat outputs indicate high needs for heating as well as reliance on central heating. Citizens of eastern and central Ukraine as well as the capital city of Kyiv are dependent on heat energy supplied from centralized facilities usually managed by public utility companies. The highest share of residential buildings which are equipped with central heating facilities are in Zaporizka, Donetska, Dnipropetrovska and Kharkivska oblasts and Kyiv city ranging from 55,8 % to 98,7 % (State Statistics Service of Ukraine 2020) . Unit: The heat output per oblast, indicating the amount of heat energy generated and supplied to consumers by centralized heat generating facilities. Source: State Statistics Service of Ukraine 2020 . Limitations: (REACH 2022c) .
Image: Radiator at residential building near Chernihiv. © ACTED Ukraine 2022
LOCC Class
The LOCC component assesses infrastructure damages and capacities relevant for coping with cold conditions across Ukraine. Select the buttons below to view the different LOCC classes:
Cold Spot Risk Assessment
Definition of ‘Cold Spots’: Geographic areas where winter-related hazards (e.g., cold waves) compound with susceptibilities (e.g., internal displacement; elderly population etc.) and the Lack of Coping Capacity (LOCC), impacting vulnerable people most severely.
Cold Spot Index
The ‘Cold Spot Index‘ provides an indication of the raions where people will likely face the highest, compounding impacts of exposure to winter-related hazards, and vulnerabilities (as a combination of susceptibilities and the LOCC) in winter 2022/23 in Ukraine.
Interact with the map: Click on a raion to open pop-ups with detailed information. Use the '+/-' buttons to the right to zoom in on an area and change to satellite imagery on a local level.
Highest Cold Spot Index:
- Bohodukhivskyi
- Kharkivskyi
- Chuhuivskyi
Cold Spot Index
Select the buttons below to view the different Cold Spot Index classes:
Key Takeaways
The Cold Spot Risk Assessment provides insights into the impacts of winter conditions on vulnerable people, including the following key findings:
I) The raions with the highest Cold Spot Index (CSI) are: (CSI = 4.8) (CSI = 4.8) (CSI = 4.8)
Those raions are also , likely facing severe impacts and needing specific winterization assistance.
Interact with the map: Click on the red text parts above to to change the map view.
II) Overall, the assessment showed that cold spot impacts will likely be most severe (CSI = Very High) in the eastern region of the country, including raions in the oblasts:
Interact with the map: Click on the red text parts above to to change the map view.
III) The analysis of indicators per group showed that are most severe in the north-eastern areas. Considering vulnerability, to winter conditions are most severe in the central and eastern regions and the in the eastern and southern regions, following the areas along the present or historic line of conflict.
IV) In the upcoming winter months, it will be essential to improve data availability and data quality of groups vulnerable to winter conditions which are under- or not represented in currently available data sets (e.g., older persons who did not move, IDPs in collective sites, IDPs demographics, accurate and up-to-date population statistics, status of infrastructure damages and repairs, etc.).
Imagery: Dnipro City after snowfall (December 2011). © Maxar Technologies 2022, viewed in Google Earth 2022
Case Stories
Following chapter shows case examples from Kharkiv City (Highest Cold Spot Index) and Dnipro City (Very High Cold Spot Index). These examples aim to give insights into conditions impacting cold spot risks on a local level.
The imagery below shows Kharkiv City Centre on 22 February 2022 (left) and 22 May 2022 (right). In the imagery on the right, building damages due to missile strikes are visible. Interact with the imagery: Move the slider in the middle to change between viewing the before and after imagery.
Kharkiv City Centre - Building Damages: 22 February (left) & 22 May (right) 2022. © Maxar 2022
Kharkiv City
Kharkiv is the second largest city in Ukraine and the administrative center of Kharkiv Oblast (Britannica 2022) .
The line of conflict reached up until the eastern borders of Kharkiv City before Russian forces were repelled by Ukrainian forces in early September 2022 (liveuamap 2022) .
Image: Damaged residential building Kharkiv City. © Ines Dadda/ACTED November 2022
Interact with the map: Use the '+/-' buttons to the right to zoom in or out and view areas of control.
Capacities to cope with cold temperatures is being further impaired by the ongoing destruction and failure of infrastructure (e.g., electricity, water, heating) (UNOCHA 2022) . The compounding impacts of severe climatic winter conditions and considerable damage to residential buildings and infrastructure caused by hostilities can potentially further aggravate vulnerabilities of the affected population.
Image: Damaged residential building Kharkiv City. © Ines Dadda/ACTED November 2022
Testimonies: Kharkiv Oblast
Kateryina, 52 years old, she lives in Kharkiv Oblast, 55km away from the front line:
“March 13th, part of our house was destroyed due to shelling, the roof the windows were damaged while my father and I were in it, luckily no one got hurt. Our friends and neighbors helped us do some repairs but there are still holes and winter is starting. It’s going to be very cold because we could not fix everything. We could not leave the house my father is too old we couldn’t go anywhere but we have a basement, so we stayed there during attacks. I used to work in a factory but after the war escalated in February the factory had to let a lot of people go. I was left without a job. Now we live on my father’s pension and it’s not much. Electricity and gas are very expensive right now. My father’s pension is 400 hryvnias per month. Our house works on gas, and at the end of the months the bills amount to 6000 hryvnias. We have food here, you can buy anything, if you have enough money. I really hope I can find a new job, this would really help our situation.” (21/11/2022)
Testimonies: Kharkiv Oblast
Alyona, 35 years old, she lives in Kharkiv Oblast, 55km away from the front line:
“I loved my job, I used to organize the security at a hotel. A few months ago the building where I work was destroyed, and I lost my job. I have a son who is 22 and he works in security as well, he works at a supermarket. Paying bills at the end of the month is getting hard we need help to pay for wood to heat the house, for gas to cook. My house is not destroyed so it’s ok. It’s not easy but we try to survive. ACTED supports us with money so we will be able to pay for gas and electricity during winter to get more food and to pay for medicine.” (21/11/2022)
Testimonies: Kharkiv Oblast
N., 35 years old, used to live around 50 km from the front line in Kharkiv Oblast:
“I work in repairs, technical equipment like phones and other machines. I really like my job, everyone breaks something from time to time and I like to fix things. I have two daughters, they are 3 and 8 years old. Our house was destroyed, now we live in Kharkiv. We have gas and wood so everything is ok for now. We have many friends, they help me and my family, we support each other.” (21/11/2022)
Dnipro City
Dnipro is located near the Dnipro River and with about 1 million residents, Ukraine's fourth largest city (Britannica 2022) .
Dnipro is well known for its industrial productions. A huge iron and steel industry has developed, with...
...manganese from Nikopol, ...
...iron ore from Kryvyy Rih, ...
...coal from the Donets Basin, ...
... and electric power from hydroelectric plants of the Dnipro River.
Since 24 February 2022, the conflict escalation and the ongoing hostilities have caused significant damage to residential buildings, public utilities, and energy infrastructure.
Image: Damaged residential building Dnipro City. © Ines Dadda/ACTED November 2022
This is putting the population at risk of losing access to energy and heating due to potential hostilities-related damages (REACH 2022a) .
Image: Damaged residential building Dnipro City. © Ines Dadda/ACTED November 2022
Further Resources
Limitations
This ‘Cold Spot Risk Assessment’ highlights areas with likely most severe impacts on people, based on the analysed indicators. Areas which are classified as ‘Very Low’ have a very low CSI based on those specific indicators. However, this does not mean that those areas have overall no vulnerability or needs. It is likely that vulnerabilities are present which were not captured with the analysed indicators. For example, using number of IDPs per raion as indicator draws the focus to raions with high numbers of IDPs, meanwhile conflict-affected population which did not leave might face severe impacts by winter conditions as well. It is therefore essential to capture data on those currently ‘invisible’ groups. The strongest technical limitations in this assessment are the availability and quality of data sets. The most accurate data is on climate conditions and hazards. However, it is historic data and therefore provides insights into historic trends but does not provide an outlook to winter conditions in 2022/23. The least accurate and most outdated data is on population statistics, income, and capacities of central heating systems. Data is available per oblast, which is very general and dated back to 2020.
Especially for analysis of population exposure to hazards it is essential to have accurate and up-to date population statistics. Therefore, population statistics are estimates and not fully accurate in terms of current population distribution across Ukraine. Inaccuracies in population statistics are enhanced by the massive movements of population between oblasts, raions as well as people leaving Ukraine throughout the past months. Therefore, population numbers and densities calculated based on currently available sources are estimates and likely over represent population in non-government controlled areas and conflict-affected zones. Due to these strong limitations it was decided to assign exposure the least weight in the CSI formula.
A further limitation of the assessment is the classification of analysed data and the final CSI values. It was decided to use quantiles as method in setting group classes of indicators in order to provide insight on the most impacted areas relative within Ukraine. However, using quantiles can group quite differing values into one class. For the final CSI map, natural breaks were used as method to group raions with similar situations in terms of winter-related impacts. There is no standardized classification or fixed thresholds for this type of analysis which is why it was aimed to find the best balance between providing detailed information while keeping clarity in the results. Lastly, this assessment highlights areas of likely most severe impacts on people in winter 2022/23, ultimately putting a spotlight on those raions. It will be essential to ensure coordination of humanitarian assistance to avoid an over-representation of actors and humanitarian assistance in ‘spotlight area’, leaving out other areas which might face relatively less but still severe impacts.
