@article{AtharePradhanKropp2020,
  author    = {Athare, Tushar Ramchandra and Pradhan, Prajal and Kropp, J{\"u}rgen},
  title     = {Environmental implications and socioeconomic characterisation of Indian diets},
  series = {The science of the total environment},
  volume    = {737},
  journal   = {The science of the total environment},
  publisher = {Elsevier Science},
  address   = {Amsterdam [u.a.]},
  issn      = {0048-9697},
  doi       = {10.1016/j.scitotenv.2020.139881},
  pages     = {9},
  year      = {2020},
  abstract  = {India is facing a double burden of malnourishment with co-existences of under- and over-nourishment. Various socioeconomic factors play an essential role in determining dietary choices. Agriculture is one of the major emitters of greenhouse gases (GHGs) in India, contributing 18\% of total emissions. It also consumes freshwater and uses land significantly. We identify eleven Indian diets by applying k-means cluster analysis on latest data from the Indian household consumer expenditure survey. The diets vary in calorie intake [2289-3218 kcal/Consumer Unit (CU)/day] and dietary composition. Estimated embodied GHG emissions in the diets range from 1.36 to 3.62 kg CO2eq./CU/day, land footprint from 4 to 5.45 m(2)/CU/day, whereas water footprint varies from 2.13 to 2.97m(3)/CU/day. Indian diets deviate from a healthy reference diet either with too much or too little consumption of certain food groups. Overall, cereals, sugar, and dairy products intake are higher. In contrast, the consumption of fruits and vegetables, pulses, and nuts is lower than recommended. Our study contributes to deriving required polices for the sustainable transformation of food systems in India to eliminate malnourishment and to reduce the environmental implications of the food systems. (c) 2020 Elsevier B.V. All rights reserved.},
  language  = {en}
}
@article{AtharePradhanSinghetal.2022,
  author    = {Athare, Tushar Ramchandra and Pradhan, Prajal and Singh, S. R. K. and Kropp, J{\"u}rgen},
  title     = {India consists of multiple food systems with scoioeconomic and environmental variations},
  series = {PLOS ONE / Public Library of Science},
  volume    = {17},
  journal   = {PLOS ONE / Public Library of Science},
  number    = {8},
  publisher = {PLoS},
  address   = {San Fransisco},
  issn      = {1932-6203},
  doi       = {10.1371/journal.pone.0270342},
  pages     = {18},
  year      = {2022},
  abstract  = {Agriculture in India accounts for 18\% of greenhouse gas (GHG) emissions and uses significant land and water. Various socioeconomic factors and food subsidies influence diets in India. Indian food systems face the challenge of sustainably nourishing the 1.3 billion population. However, existing studies focus on a few food system components, and holistic analysis is still missing. We identify Indian food systems covering six food system components: food consumption, production, processing, policy, environmental footprints, and socioeconomic factors from the latest Indian household consumer expenditure survey. We identify 10 Indian food systems using k-means cluster analysis on 15 food system indicators belonging to the six components. Based on the major source of calorie intake, we classify the ten food systems into production-based (3), subsidy-based (3), and market-based (4) food systems. Home-produced and subsidized food contribute up to 2000 kcal/consumer unit (CU)/day and 1651 kcal/CU/day, respectively, in these food systems. The calorie intake of 2158 to 3530 kcal/CU/day in the food systems reveals issues of malnutrition in India. Environmental footprints are commensurate with calorie intake in the food systems. Embodied GHG, land footprint, and water footprint estimates range from 1.30 to 2.19 kg CO(2)eq/CU/day, 3.89 to 6.04 m(2)/CU/day, and 2.02 to 3.16 m(3)/CU/day, respectively. Our study provides a holistic understanding of Indian food systems for targeted nutritional interventions on household malnutrition in India while also protecting planetary health.},
  language  = {en}
}
@article{BoettleRybskiKropp2016,
  author    = {Boettle, Markus and Rybski, Diego and Kropp, J{\"u}rgen},
  title     = {Quantifying the effect of sea level rise and flood defence-a point process perspective on coastal flood damage},
  series = {Natural hazards and earth system sciences},
  volume    = {16},
  journal   = {Natural hazards and earth system sciences},
  publisher = {Copernicus},
  address   = {G{\"o}ttingen},
  issn      = {1561-8633},
  doi       = {10.5194/nhess-16-559-2016},
  pages     = {559 -- 576},
  year      = {2016},
  abstract  = {In contrast to recent advances in projecting sea levels, estimations about the economic impact of sea level rise are vague. Nonetheless, they are of great importance for policy making with regard to adaptation and greenhouse-gas mitigation. Since the damage is mainly caused by extreme events, we propose a stochastic framework to estimate the monetary losses from coastal floods in a confined region. For this purpose, we follow a Peak-over-Threshold approach employing a Poisson point process and the Generalised Pareto Distribution. By considering the effect of sea level rise as well as potential adaptation scenarios on the involved parameters, we are able to study the development of the annual damage. An application to the city of Copenhagen shows that a doubling of losses can be expected from a mean sea level increase of only 11 cm. In general, we find that for varying parameters the expected losses can be well approximated by one of three analytical expressions depending on the extreme value parameters. These findings reveal the complex interplay of the involved parameters and allow conclusions of fundamental relevance. For instance, we show that the damage typically increases faster than the sea level rise itself. This in turn can be of great importance for the assessment of sea level rise impacts on the global scale. Our results are accompanied by an assessment of uncertainty, which reflects the stochastic nature of extreme events. While the absolute value of uncertainty about the flood damage increases with rising mean sea levels, we find that it decreases in relation to the expected damage.},
  language  = {en}
}
@misc{BoettleRybskiKropp2016,
  author    = {Boettle, Markus and Rybski, Diego and Kropp, J{\"u}rgen},
  title     = {Quantifying the effect of sea level rise and flood defence},
  series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  journal   = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe},
  number    = {559},
  issn      = {1866-8372},
  doi       = {10.25932/publishup-41240},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-412405},
  pages     = {18},
  year      = {2016},
  abstract  = {In contrast to recent advances in projecting sea levels, estimations about the economic impact of sea level rise are vague. Nonetheless, they are of great importance for policy making with regard to adaptation and greenhouse-gas mitigation. Since the damage is mainly caused by extreme events, we propose a stochastic framework to estimate the monetary losses from coastal floods in a confined region. For this purpose, we follow a Peak-over-Threshold approach employing a Poisson point process and the Generalised Pareto Distribution. By considering the effect of sea level rise as well as potential adaptation scenarios on the involved parameters, we are able to study the development of the annual damage. An application to the city of Copenhagen shows that a doubling of losses can be expected from a mean sea level increase of only 11 cm. In general, we find that for varying parameters the expected losses can be well approximated by one of three analytical expressions depending on the extreme value parameters. These findings reveal the complex interplay of the involved parameters and allow conclusions of fundamental relevance. For instance, we show that the damage typically increases faster than the sea level rise itself. This in turn can be of great importance for the assessment of sea level rise impacts on the global scale. Our results are accompanied by an assessment of uncertainty, which reflects the stochastic nature of extreme events. While the absolute value of uncertainty about the flood damage increases with rising mean sea levels, we find that it decreases in relation to the expected damage.},
  language  = {en}
}
@article{BoettleRybskiKropp2013,
  author    = {B{\"o}ttle, Markus and Rybski, Diego and Kropp, J{\"u}rgen},
  title     = {How changing sea level extremes and protection measures alter coastal flood damages},
  series = {Water resources research},
  volume    = {49},
  journal   = {Water resources research},
  number    = {3},
  publisher = {American Geophysical Union},
  address   = {Washington},
  issn      = {0043-1397},
  doi       = {10.1002/wrcr.20108},
  pages     = {1199 -- 1210},
  year      = {2013},
  abstract  = {While sea level rise is one of the most likely consequences of climate change, the provoked costs remain highly uncertain. Based on a block-maxima approach, we provide a stochastic framework to estimate the increase of expected damages with sea level rise as well as with meteorological changes and demonstrate the application to two case studies. In addition, the uncertainty of the damage estimations due to the stochastic nature of extreme events is studied. Starting with the probability distribution of extreme flood levels, we calculate the distribution of implied damages in a specific region employing stage-damage functions. Universal relations of the expected damages and their standard deviation, which demonstrate the importance of the shape of the damage function, are provided. We also calculate how flood protection reduces the damages leading to a more complex picture, where the extreme value behavior plays a fundamental role. Citation: Boettle, M., D. Rybski, and J. P. Kropp (2013), How changing sea level extremes and protection measures alter coastal flood damages, Water Resour. Res., 49, 1199-1210, doi: 10.1002/wrcr.20108.},
  language  = {en}
}
@article{CostaKropp2019,
  author    = {Costa, Lu{\´i}s F{\´i}l{\´i}pe Carvalho da and Kropp, J{\"u}rgen},
  title     = {Estimating investments in knowledge and planning activities for adaptation in developing countries: an empirical approach},
  series = {Climate \& development},
  volume    = {11},
  journal   = {Climate \& development},
  number    = {9},
  publisher = {Routledge, Taylor \& Francis Group},
  address   = {Abingdon},
  issn      = {1756-5529},
  doi       = {10.1080/17565529.2018.1562865},
  pages     = {755 -- 764},
  year      = {2019},
  abstract  = {Costs of adaptation in the developing world have been mostly equated to those of climate proofing infrastructure under the assumption of unconstrained knowledge and planning capacities. To correct this, we introduce a cost-scaling methodology estimating sectoral investments to enhance the knowledge and planning capacities of countries based on an empirical collection of 385 climate-related projects. We estimate that circa 9.2 billion USD are required for financing knowledge and planning activities in developing countries in 2015. The agricultural and water sectors demand the higher investments ? 3.8 and 3.5 billion USD, respectively. Average investments between 2015 and 2050 are projected at 7 billion USD per year ? the largest fraction of which (4 billion) in Africa. Investments in this study were found to constitute approximately 40\%, 20?60\% and 5?15\% of previous cost estimates to climate-proof infrastructure in the agricultural, water, and coastal sectors, respectively. The effort to finance the knowledge and planning capacities in developing countries is therefore not marginal relative to the costs of adapting infrastructure. The findings underline the potential of using empirical collections of climate-related projects for adaptation cost assessments as complementary to process and economic models.},
  language  = {en}
}
@article{FluschnikKriewaldRosetal.2016,
  author    = {Fluschnik, Till and Kriewald, Steffen and Ros, Anselmo Garcia Cantu and Zhou, Bin and Reusser, Dominik Edwin and Kropp, J{\"u}rgen and Rybski, Diego},
  title     = {The Size Distribution, Scaling Properties and Spatial Organization of Urban Clusters: A Global and Regional Percolation Perspective},
  series = {ISPRS International Journal of Geo-Information},
  volume    = {5},
  journal   = {ISPRS International Journal of Geo-Information},
  publisher = {MDPI},
  address   = {Basel},
  issn      = {2220-9964},
  doi       = {10.3390/ijgi5070110},
  pages     = {1543 -- 1559},
  year      = {2016},
  abstract  = {Human development has far-reaching impacts on the surface of the globe. The transformation of natural land cover occurs in different forms, and urban growth is one of the most eminent transformative processes. We analyze global land cover data and extract cities as defined by maximally connected urban clusters. The analysis of the city size distribution for all cities on the globe confirms Zipf's law. Moreover, by investigating the percolation properties of the clustering of urban areas we assess the closeness to criticality for various countries. At the critical thresholds, the urban land cover of the countries undergoes a transition from separated clusters to a gigantic component on the country scale. We study the Zipf-exponents as a function of the closeness to percolation and find a systematic dependence, which could be the reason for deviating exponents reported in the literature. Moreover, we investigate the average size of the clusters as a function of the proximity to percolation and find country specific behavior. By relating the standard deviation and the average of cluster sizes—analogous to Taylor's law—we suggest an alternative way to identify the percolation transition. We calculate spatial correlations of the urban land cover and find long-range correlations. Finally, by relating the areas of cities with population figures we address the global aspect of the allometry of cities, finding an exponent \&\#948; \&\#8776; 0.85, i.e., large cities have lower densities.},
  language  = {en}
}
@misc{FluschnikKriewaldRosetal.2017,
  author    = {Fluschnik, Till and Kriewald, Steffen and Ros, Anselmo Garc{\´i}a Cant{\´u} and Zhou, Bin and Reusser, Dominik Edwin and Kropp, J{\"u}rgen and Rybski, Diego},
  title     = {The size distribution, scaling properties and spatial organization of urban clusters},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-400486},
  pages     = {14},
  year      = {2017},
  abstract  = {Human development has far-reaching impacts on the surface of the globe. The transformation of natural land cover occurs in different forms, and urban growth is one of the most eminent transformative processes. We analyze global land cover data and extract cities as defined by maximally connected urban clusters. The analysis of the city size distribution for all cities on the globe confirms Zipf's law. Moreover, by investigating the percolation properties of the clustering of urban areas we assess the closeness to criticality for various countries. At the critical thresholds, the urban land cover of the countries undergoes a transition from separated clusters to a gigantic component on the country scale. We study the Zipf-exponents as a function of the closeness to percolation and find a systematic dependence, which could be the reason for deviating exponents reported in the literature. Moreover, we investigate the average size of the clusters as a function of the proximity to percolation and find country specific behavior. By relating the standard deviation and the average of cluster sizes—analogous to Taylor's law—we suggest an alternative way to identify the percolation transition. We calculate spatial correlations of the urban land cover and find long-range correlations. Finally, by relating the areas of cities with population figures we address the global aspect of the allometry of cities, finding an exponent δ ≈ 0.85, i.e., large cities have lower densities.},
  language  = {en}
}
@article{GanzenmuellerPradhanKropp2018,
  author    = {Ganzenm{\"u}ller, Raphael and Pradhan, Prajal and Kropp, J{\"u}rgen},
  title     = {Sectoral performance analysis of national greenhouse gas emission inventories by means of neural networks},
  series = {Science of The Total Environment},
  journal   = {Science of The Total Environment},
  number    = {656},
  publisher = {Elsevier},
  doi       = {10.1016/j.scitotenv.2018.11.311},
  pages     = {80 -- 89},
  year      = {2018},
  abstract  = {Annual greenhouse gas emissions have increased more than threefold between 1950 and 2014, posing a major threat to the integrity of the entire earth system and subsequently to humankind. Consequently, roadmaps towards low-carbon pathways are urgently needed. Our study contributes to a more detailed understanding of the dynamics of country based emission patterns and uses them to discuss prospective low-carbon pathways for countries. As availability of databases on sectoral emissions substantially increased, we employ machine learning techniques to classify emission features and pathways. By doing so, 18 representative emission patterns are derived. Overall emissions from seven sectors and for 167 countries covering the time span from 1950 to 2014 have been used in the analyses. The following significant trends can be observed: a) increasing per capita emissions due to growing fossil fuel use in many parts of the world, b) a decline in per capita emissions in some countries, and c) a shift in the emission shares, i.e., a reduction of agricultural and land use contributions in certain regions. Using the emission patterns, their dynamics, and best performing countries as role models, we show the possibility for gaining a decent human development without significantly increasing per capita emissions.},
  language  = {en}
}
@article{GudipudiLuedekeRybskietal.2018,
  author    = {Gudipudi, Ramana Venkata and L{\"u}deke, Matthias K. B. and Rybski, Diego and Kropp, J{\"u}rgen},
  title     = {Benchmarking urban eco-efficiency and urbanites' perception},
  series = {Cities},
  volume    = {74},
  journal   = {Cities},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0264-2751},
  doi       = {10.1016/j.cities.2017.11.009},
  pages     = {109 -- 118},
  year      = {2018},
  abstract  = {Urbanization as an inexorable global trend stresses the need to identify cities which are eco-efficient. These cities enable socioeconomic development with lower environmental burden, both being multidimensional concepts. Based on this approach, we benchmark 88 European cities using (i) an advanced version of regression residual ranking and (ii) Data Envelopment Analysis (DEA). Our results show that Stockholm, Munich and Oslo perform well irrespective of the benchmarking method. Furthermore, our results indicate that larger European cities are eco-efficient given the socioeconomic benefits they offer compared to smaller cities. In addition, we analyze correlations between a subjective public perception ranking and our objective eco-efficiency rankings for a subset of 45 cities. This exercise revealed three insights: (1) public perception about quality of life in a city is not merely confined to the socioeconomic well-being but rather to its combination with a lower environmental burden; (2) public perception correlates well with both formal ranking outcomes, corroborating the choice of variables; and (3) the advanced regression residual method appears to be more adequate to fit the urbanites' perception ranking (correlation coefficient about 0.6). This can be interpreted as an indication that urbanites' perception reflects the typical eco-efficiency performance and is less influenced by exceptionally performing cities (in the latter case, DEA should have better correlation coefficient). This study highlights that the socioeconomic growth in cities should not be environmentally detrimental as this might lead to significant discontent regarding perceived quality of urban life.},
  language  = {en}
}