In Chang Hwang

Cities warm faster than the global mean, and how much of that excess is the city’s own heat island decides how much of it city-level measures can reach. Estimates range from negligible to a third of a country’s warming, because no station study separates the regional background from the urban term, and because global assessments rest on homogenized records that remove the gradual urban trend. Using raw, non-homogenized GHCN-Daily records for 553 cities in 37 countries, this paper decomposes observed warming from a 1951–80 baseline to 2001–20 into global warming, regional amplification measured at rural stations, and the urban excess. The share is reported for six reference windows, and covariates are tested over the same years on two settlement records. The urban heat island supplies about a tenth of observed city warming: two-fifths in North America and a few percent in Europe and Japan. The difference lies not in the cities but in how far the countryside kept pace with them. Population growth explains the share, whereas size, density or built surface at one moment does not, and separating the regional term reconciles global and single-country studies. For city planning and for economic assessments of urban heat, the result separates two quantities. Cooling measures act on the heat island’s level, which is nocturnal and close to a degree in North American cities. Growth management and urban form act on its change, the tenth measured here. The remaining nine-tenths is regional and global climate beyond the reach of city-level measures alone.

The results of five Integrated Assessment Models are discussed in this concluding paper. All the scenarios measure the National Social Cost of Carbon (NSCC) across approximately 200 countries in a scenario with no mitigation. Despite assuming similar population and economic growth rates (RFF-SPs), the five models imply a wide range of forecasted climate impacts. Summing the mean NSCC estimates of all countries leads to a mean global Social Cost of Carbon (SCC) that varies from $33/tCO ₂ to $1373/tCO ₂ across the models. Most of the literature on climate IAMs has focused on these SCC values. This special issue, in contrast, is focused on the NSCC. However, the assumptions in each IAM model that led to different SCC values also determine the cumulative magnitude of the NSCCs from each model. The discount rate, the climate damage function, and the modeling of uncertainty strongly influence the magnitude of the NSCCs across models. What is unique to the analysis of the NSCCs is how they are distributed across countries. The NSCC values explain how climate damages and, therefore, the benefits of mitigation are distributed across nations. The IAMs predict that China and especially the United States are particularly exposed to climate change due to their large asset bases. About half of the global damage is assumed to happen in the 10 largest countries in the world, measured using GDP PPP. Most of the models predict every country has some damage, but one model predicts 29 countries — mostly in high latitudes — will benefit from near-term climate change. Regression analysis confirms that the distribution of climate damages across countries is primarily determined by the total size of the national economy. Because IAMs scale physical risks by economic exposure, they predict that two-thirds of the global climate burden is concentrated in the mid-to-high latitudes, where the majority of global economic activity is located. Finally, the IAMs predict a very wide range of NSCC values in 2100, ranging from a 40% increase to an eight-fold increase over current NSCC values, depending on structural assumptions regarding adaptation and catastrophic risk.

This paper presents a refined country-level integrated assessment model, Framework for Uncertainty, Negotiation, and Distribution (FUND) 3.9n, that extends the regional FUND 3.9 framework by incorporating sector-specific climate impact functions and parametric uncertainty analysis for 198 individual countries. The model enables estimation of the national social cost of carbon (NSCC), capturing heterogeneity across nations from economic structure, climate sensitivity, and population exposure. Our results demonstrate that both the NSCC and the global sum estimates are highly sensitive to damage specifications and preference parameters, including the pure rate of time preference and relative risk aversion. Compared to aggregated single-sector approaches, the disaggregated model with uncertainty yields higher values of the NSCC for low- and middle-income countries. The paper contributes to the literature by quantifying how sector-specific vulnerabilities and stochastic variability amplify climate damages and reshape global equity in the distribution of the NSCC. The NSCCs derived from our model offer policy-relevant metrics for adaptation planning, mitigation target setting, and equitable burden-sharing in international climate negotiations. This approach bridges the gap between globally harmonized carbon pricing and nationally differentiated climate impacts, providing a theoretically grounded and empirically rich framework for future climate policy design.

This paper presents a refined country-level integrated assessment model, FUND 3.9n, that extends the regional FUND 3.9 framework by incorporating sector-specific climate impact functions and parametric uncertainty analysis for 198 individual countries. The model enables estimation of the national social cost of carbon (NSCC), capturing heterogeneity across nations from economic structure, climate sensitivity, and population exposure. Our results demonstrate that both the NSCC and the global sum estimates are highly sensitive to damage specifications and preference parameters, including the pure rate of time preference and relative risk aversion. Compared to aggregated single-sector approaches, the disaggregated model with uncertainty yields higher values of the NSCC for low- and middle-income countries. The paper contributes to the literature by quantifying how sector-specific vulnerabilities and stochastic variability amplify climate damages and reshape global equity in the distribution of the NSCC. The NSCCs derived from our model offer policy-relevant metrics for adaptation planning, mitigation target setting, and equitable burden-sharing in international climate negotiations. This approach bridges the gap between globally harmonized carbon pricing and nationally differentiated climate impacts, providing a theoretically grounded and empirically rich framework for future climate policy design.

This study compared the annual per-unit area greenhouse gas (GHG) emissions from buildings in Seoul from 2017 to 2019, with those from 2020 to 2023. The objective was to empirically analyze how changes in building occupant behavior due to COVID-19 impacted GHG emissions from buildings. The analysis utilized the ‘Seoul Building GHG Emission Database,’ which integrates building information and monthly energy supply data (electricity, LNG, district heating) for all buildings in Seoul. The analysis revealed that behavioral changes induced by the COVID-19 pandemic temporarily reduced overall GHG emissions from buildings in Seoul by approximately 3% on an annual basis. GHG emissions from commercial buildings (49.4%) and residential buildings (50.6%) in Seoul were nearly identical. While emissions from commercial buildings decreased by 4.6%, those from residential buildings increased by 1.1%. However, these GHG reductions were observed only immediately after the introduction of social distancing measures and subsequently reverted to the pre-2019 levels. Additionally, the reductions primarily were driven by non-residential buildings, while emissions from residential buildings increased. Even after the easing of social distancing measures, the increased emissions from residential buildings did not return to previous levels. In 2022, there was an observed increase in GHG emissions compared to pre-COVID-19 level. The findings of this study can serve as a foundation for emission reduction scenarios through behavioral improvements and for policies aimed at encouraging such improvements.