@article{WarszawskiKrieglerLentonetal.2021, author = {Warszawski, Lila and Kriegler, Elmar and Lenton, Timothy M. and Gaffney, Owen and Jacob, Daniela and Klingenfeld, Daniel and Koide, Ryu and Costa, Mar{\´i}a M{\´a}{\~n}ez and Messner, Dirk and Nakicenovic, Nebojsa and Schellnhuber, Hans Joachim and Schlosser, Peter and Takeuchi, Kazuhiko and van der Leeuw, Sander and Whiteman, Gail and Rockstr{\"o}m, Johan}, title = {All options, not silver bullets, needed to limit global warming to 1.5 °C}, series = {Environmental research letters}, volume = {16}, journal = {Environmental research letters}, number = {6}, publisher = {IOP Publishing}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/abfeec}, pages = {15}, year = {2021}, abstract = {Climate science provides strong evidence of the necessity of limiting global warming to 1.5 °C, in line with the Paris Climate Agreement. The IPCC 1.5 °C special report (SR1.5) presents 414 emissions scenarios modelled for the report, of which around 50 are classified as '1.5 °C scenarios', with no or low temperature overshoot. These emission scenarios differ in their reliance on individual mitigation levers, including reduction of global energy demand, decarbonisation of energy production, development of land-management systems, and the pace and scale of deploying carbon dioxide removal (CDR) technologies. The reliance of 1.5 °C scenarios on these levers needs to be critically assessed in light of the potentials of the relevant technologies and roll-out plans. We use a set of five parameters to bundle and characterise the mitigation levers employed in the SR1.5 1.5 °C scenarios. For each of these levers, we draw on the literature to define 'medium' and 'high' upper bounds that delineate between their 'reasonable', 'challenging' and 'speculative' use by mid century. We do not find any 1.5 °C scenarios that stay within all medium upper bounds on the five mitigation levers. Scenarios most frequently 'over use' CDR with geological storage as a mitigation lever, whilst reductions of energy demand and carbon intensity of energy production are 'over used' less frequently. If we allow mitigation levers to be employed up to our high upper bounds, we are left with 22 of the SR1.5 1.5 °C scenarios with no or low overshoot. The scenarios that fulfil these criteria are characterised by greater coverage of the available mitigation levers than those scenarios that exceed at least one of the high upper bounds. When excluding the two scenarios that exceed the SR1.5 carbon budget for limiting global warming to 1.5 °C, this subset of 1.5 °C scenarios shows a range of 15-22 Gt CO2 (16-22 Gt CO2 interquartile range) for emissions in 2030. For the year of reaching net zero CO2 emissions the range is 2039-2061 (2049-2057 interquartile range).}, language = {en} } @article{SedovaKalkuhlMendelsohn2020, author = {Sedova, Barbora and Kalkuhl, Matthias and Mendelsohn, Robert}, title = {Distributional impacts of weather and climate in rural India}, series = {Economics of disasters and climate change}, volume = {4}, journal = {Economics of disasters and climate change}, number = {1}, publisher = {Springer}, address = {Cham}, issn = {2511-1280}, doi = {10.1007/s41885-019-00051-1}, pages = {5 -- 44}, year = {2020}, abstract = {Climate-related costs and benefits may not be evenly distributed across the population. We study distributional implications of seasonal weather and climate on within-country inequality in rural India. Utilizing a first difference approach, we find that the poor are more sensitive to weather variations than the non-poor. The poor respond more strongly to (seasonal) temperature changes: negatively in the (warm) spring season, more positively in the (cold) rabi season. Less precipitation is harmful to the poor in the monsoon kharif season and beneficial in the winter and spring seasons. We show that adverse weather aggravates inequality by reducing consumption of the poor farming households. Future global warming predicted under RCP8.5 is likely to exacerbate these effects, reducing consumption of poor farming households by one third until the year 2100. We also find inequality in consumption across seasons with higher consumption during the harvest and lower consumption during the sowing seasons.}, language = {en} } @article{SchultesPiontekSoergeletal.2021, author = {Schultes, Anselm and Piontek, Franziska and Soergel, Bjoern and Rogelj, Joeri and Baumstark, Lavinia and Kriegler, Elmar and Edenhofer, Ottmar and Luderer, Gunnar}, title = {Economic damages from on-going climate change imply deeper near-term emission cuts}, series = {Environmental research letters}, volume = {16}, journal = {Environmental research letters}, number = {10}, publisher = {IOP Publishing}, address = {Bristol}, issn = {1748-9326}, doi = {10.1088/1748-9326/ac27ce}, pages = {11}, year = {2021}, abstract = {Pathways toward limiting global warming to well below 2 ∘C, as used by the IPCC in the Fifth Assessment Report, do not consider the climate impacts already occurring below 2 ∘C. Here we show that accounting for such damages significantly increases the near-term ambition of transformation pathways. We use econometric estimates of climate damages on GDP growth and explicitly model the uncertainty in the persistence time of damages. The Integrated Assessment Model we use includes the climate system and mitigation technology detail required to derive near-term policies. We find an optimal carbon price of \$115 per tonne of CO2 in 2030. The long-term persistence of damages, while highly uncertain, is a main driver of the near-term carbon price. Accounting for damages on economic growth increases the gap between the currently pledged nationally determined contributions and the welfare-optimal 2030 emissions by two thirds, compared to pathways considering the 2 ∘C limit only.}, language = {en} } @phdthesis{Šedova2022, author = {Šedov{\´a}, Barbora}, title = {Heterogeneous effects of weather and climate change on human migration}, doi = {10.25932/publishup-53673}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-536733}, school = {Universit{\"a}t Potsdam}, pages = {xix, 284}, year = {2022}, abstract = {While estimated numbers of past and future climate migrants are alarming, the growing empirical evidence suggests that the association between adverse climate-related events and migration is not universally positive. This dissertation seeks to advance our understanding of when and how climate migration emerges by analyzing heterogeneous climatic influences on migration in low- and middle-income countries. To this end, it draws on established economic theories of migration, datasets from physical and social sciences, causal inference techniques and approaches from systematic literature review. In three of its five chapters, I estimate causal effects of processes of climate change on inequality and migration in India and Sub-Saharan Africa. By employing interaction terms and by analyzing sub-samples of data, I explore how these relationships differ for various segments of the population. In the remaining two chapters, I present two systematic literature reviews. First, I undertake a comprehensive meta-regression analysis of the econometric climate migration literature to summarize general climate migration patterns and explain the conflicting findings. Second, motivated by the broad range of approaches in the field, I examine the literature from a methodological perspective to provide best practice guidelines for studying climate migration empirically. Overall, the evidence from this dissertation shows that climatic influences on human migration are highly heterogeneous. Whether adverse climate-related impacts materialize in migration depends on the socio-economic characteristics of the individual households, such as wealth, level of education, agricultural dependence or access to adaptation technologies and insurance. For instance, I show that while adverse climatic shocks are generally associated with an increase in migration in rural India, they reduce migration in the agricultural context of Sub-Saharan Africa, where the average wealth levels are much lower so that households largely cannot afford the upfront costs of moving. I find that unlike local climatic shocks which primarily enhance internal migration to cities and hence accelerate urbanization, shocks transmitted via agricultural producer prices increase migration to neighboring countries, likely due to the simultaneous decrease in real income in nearby urban areas. These findings advance our current understanding by showing when and how economic agents respond to climatic events, thus providing explicit contexts and mechanisms of climate change effects on migration in the future. The resulting collection of findings can guide policy interventions to avoid or mitigate any present and future welfare losses from climate change-related migration choices.}, language = {en} } @article{KalkuhlWenz2020, author = {Kalkuhl, Matthias and Wenz, Leonie}, title = {The impact of climate conditions on economic production}, series = {Journal of Environmental Economics and Management}, volume = {103}, journal = {Journal of Environmental Economics and Management}, publisher = {Elsevier}, address = {San Diego}, issn = {0095-0696}, doi = {10.1016/j.jeem.2020.102360}, pages = {20}, year = {2020}, abstract = {We present a novel data set of subnational economic output, Gross Regional Product (GRP), for more than 1500 regions in 77 countries that allows us to empirically estimate historic climate impacts at different time scales. Employing annual panel models, long-difference regressions and cross-sectional regressions, we identify effects on productivity levels and productivity growth. We do not find evidence for permanent growth rate impacts but we find robust evidence that temperature affects productivity levels considerably. An increase in global mean surface temperature by about 3.5°C until the end of the century would reduce global output by 7-14\% in 2100, with even higher damages in tropical and poor regions. Updating the DICE damage function with our estimates suggests that the social cost of carbon from temperature-induced productivity losses is on the order of 73-142\$/tCO2 in 2020, rising to 92-181\$/tCO2 in 2030. These numbers exclude non-market damages and damages from extreme weather events or sea-level rise.}, language = {en} }