The Aral Sea was one of the largest lakes in the world, but almost 60,000 km 2 of the waterbody has dried up due to water withdrawal for irrigation. Afforestation on the desiccated seafloor could be important in preventing soil flation, dust storms, and negative impact on human health. In this study, we aimed to delineate potential vegetation establishment areas on the dried Aral Sea bed using remote-sensed data in support of the decision-making related to afforestation. Various indices such as normalized difference vegetation index (NDVI), topsoil grain size index (TGSI), soil salinity index (SSI), and normalized multiband drought index (NMDI) were calculated from the LANDSAT-8 OLI satellite imagery. As an indicator of vegetation existence, NDVI was classified into three groups and set as a base for classifying other indices by performing statistical analyses. Based on the decision tree method, indices were combined and the potential vegetation establishment area was detected. Higher NDVI was identified in the southeast than the west of the study area. The results of statistical analyses showed that TGSI had a positive correlation with NDVI, while SSI and NMDI had a negative correlation. Overall, the potential vegetation area comprised 7,295.21 km 2 (61.34%) of the 'unsuitable' area, 2,818.64 km 2 (23.7%) of the 'intermediate' area, 1,612.15 km 2 (13.56%) of the 'suitable' area, and 166.42 km 2 (1.4%) of the 'very suitable' area. The developed map enables to identify dried seafloor area suitable for vegetation establishment thus contributing to planning the land rehabilitation efforts and preventing further land degradation.

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Faced with the prospect that the impact of the COVID-19 pandemic and climate change will be far-reaching and long-term, the international community is showing interest in urban green space (UGS) and urban green infrastructure utilization as a solution. In this study, we investigated how citizens’ perceptions and use of UGS have changed during COVID-19. We also collected their ideas on how UGS can raise its usability. As a result, more people became to realize the importance of UGS. In particular, the urban environmental purification function from UGS was recognized as giving great benefits to respondents. On the other hand, the patterns of UGS use were mixed with decreasing UGS use to maintain social distancing or increasing UGS use to maintain health or substitute other restricted facilities. More than half of respondents had their UGS visit patterns impacted by COVID-19. In particular, the increase rate of UGS use was rather high in the group that seldom used UGS before COVID-19. In addition, they increased the use of UGS to replace other limited facilities, and thus tended to demand an increase in rest facilities. Based on these results, this paper suggested securing social support and sustainability for the policy by reflecting users’ demand in landscape planning related to the increase of UGS in the city. This study can contribute to improving the resilience of UGS and the sustainability of urban space planning.

<p>Climate change is becoming a serious global problem every year as it intensifies, and increasing uncertainty and frequency of extreme weather is part of the problem that is getting worse. The Earth is getting warmer overall, but the frequency of extreme cold waves is not decreasing, which can be a risk in many sectors. On February 2021, the worst cold outbreak in the United States has stopped the electricity supply to 5.5 million households in 18 states including factories as Samsung Austin Semiconductor. Factories, especially semiconductor-chip-factories, are sensitive to stabilized power supply, and unstable power supply might cause huge financial losses. Those unexpected extreme climate events hinder the estimation of future electricity demand, which can lower the accuracy of expected demand and interfere with secure power supply. Also, sudden snowfall and cold temperature can cause roads to freeze, disturbing the smooth transportation of materials and products. In this study, the unpredictability of cold waves was assumed as a hazard, and evaluating the adequacy of data to assess vulnerability to abnormal cold wave in industrial sector was done. The study was conducted in South Korea.</p> <p>This study was done by first defining the abnormal cold wave using the difference between normal and observed temperatures during winter season in Korea (November to April). Then, the relations between the power supply reserve ratio and the degree of abnormal cold wave was identified using regression models. The degree was decided as distance of observed from normal temperature data. Also, chronically frozen section of roads provided by Ministry of the Interior and Safety(ROK), was also included as data for assessing vulnerability. Categorizing an assessment was approached by following the IPCC risk assessment methodology, which classified chronically frozen sections of roads as ‘exposure’, the degree of abnormal cold wave as ‘vulnerability’ from stable power supply, and cold weather itself as ‘climate.’ As a result, compared to SSP1-2.6 scenario, frequency and degree of abnormal cold wave has slightly increased overall in the scenario SSP5-8.5. Also, chip factories in Cheongju, Yongin and Icheon for example, has at least three chronically frozen sections within 5 kilometers from the factories, average 7 sections within 10 kilometers. This study has a point in focusing on the non-decreasing, unusual cold waves despite the increasing temperature and reviewing data before assessing vulnerability of cold wave in industry. The result may be useful by offering additional methods and categories in evaluating vulnerabilities and risks to the party concerned, which can be used by working groups in making climate change adaptation plans in industrial sectors.</p> <p> </p> <p><strong><em>Keywords:</em></strong><em> climate change, cold wave, IPCC risk assessment, vulnerability, industrial sector, stable power supply, SSP scenario</em></p> <p><strong>Acknowledgements:</strong> This work was supported by Korea Environment Industry & Technology Institute (KEITI) through “Climate Change R&D Project for New Climate Regime (RE202201934)”, Funded by Korea Ministry of Environment (MOE).</p>

The IPCC emphasizes the role of forests in the sequestration of greenhouse gases, a significant cause of climate change. Accordingly, it shows the importance of predicting changes in forests due to climate change, evaluating them to reduce vulnerability under adaptive capacity, and finding ways to find climate resilient development pathways. In this study, the KO-G-Dynamic model, a Korean growth model, was linked with the frameworks of AR5 and 6 to assess risk dynamics in the forest growth sector. At this time, the sensitivity is a variability due to the reduction in forest growth, the exposure is the forest as an object, the hazard is climate change, the adaptive capacity is forest management, and the vulnerability is a mechanism that sensitivity could not be adjusted according to adaptive capacity. The risk was assessed by ranking overall risks derived from the process of vulnerability generated by the interaction of the above factors. As a result, the current forests in Korea are age class imbalanced, and the effects of distribution are centered on fast-growing tree species. If climate change and overprotection continue, the vulnerable area expands as sensitivity increases, since the total growth reduces due to increasing over-matured forests. From the regional-based analysis, Gangwon-do and Gyeongsangnam-do mostly consist of the higher V age class, the ratio of ‘very high’ risk grade was high and the area of ‘high’ risk grade changed rapidly. However, after applying forest management scenarios of adaptive capacity such as harvesting, reforestation, and thinning based on Republic of Korea’s forest management policy, the ratio of ‘Low’ risk grades increased according to the reduction of vulnerability areas. Therefore, forest management can act as an important factor to reduce the risk of forest growth in response to climate change.