@article{GudipudiFluschnikRosetal.2016, author = {Gudipudi, Venkata Ramana and Fluschnik, Till and Ros, Anselmo Garcia Cantu and Walther, Carsten and Kropp, J{\"u}rgen}, title = {City density and CO2 efficiency}, series = {Energy policy : the international journal of the political, economic, planning, environmental and social aspects of energy}, volume = {91}, journal = {Energy policy : the international journal of the political, economic, planning, environmental and social aspects of energy}, publisher = {Elsevier}, address = {Oxford}, issn = {0301-4215}, doi = {10.1016/j.enpol.2016.01.015}, pages = {352 -- 361}, year = {2016}, abstract = {Cities play a vital role in the global climate change mitigation agenda. City population density is one of the key factors that influence urban energy consumption and the subsequent GHG emissions. However, previous research on the relationship between population density and GHG emissions led to contradictory results due to urban/rural definition conundrum and the varying methodologies for estimating GHG emissions. This work addresses these ambiguities by employing the City Clustering Algorithm (CCA) and utilizing the gridded CO2 emissions data. Our results, derived from the analysis of all inhabited areas in the US, show a sub-linear relationship between population density and the total emissions (i.e. the sum of on-road and building emissions) on a per capita basis. Accordingly, we find that doubling the population density would entail a reduction in the total CO2 emissions in buildings and on-road sectors typically by at least 42\%. Moreover, we find that population density exerts a higher influence on on-road emissions than buildings emissions. From an energy consumption point of view, our results suggest that on-going urban sprawl will lead to an increase in on-road energy consumption in cities and therefore stresses the importance of developing adequate local policy measures to limit urban sprawl. (C) 2016 Elsevier Ltd. All rights reserved.}, language = {en} } @misc{GudipudiRybskiLuedekeetal.2019, author = {Gudipudi, Venkata Ramana and Rybski, Diego and L{\"u}deke, Matthias K. B. and Kropp, J{\"u}rgen}, title = {Urban emission scaling - Research insights and a way forward}, series = {Environment and Planning B: Urban Analytics and City Science}, volume = {46}, journal = {Environment and Planning B: Urban Analytics and City Science}, number = {9}, publisher = {Sage Publ.}, address = {London}, issn = {2399-8083}, doi = {10.1177/2399808319825867}, pages = {1678 -- 1683}, year = {2019}, language = {en} } @article{GudipudiRybskiLuedekeetal.2018, author = {Gudipudi, Venkata Ramana and Rybski, Diego and L{\"u}deke, Matthias K. B. and Zhou, Bin and Liu, Zhu and Kropp, J{\"u}rgen}, title = {The efficient, the intensive, and the productive}, series = {Applied Energy}, volume = {236}, journal = {Applied Energy}, publisher = {Elsevier}, address = {Oxford}, issn = {0306-2619}, doi = {10.1016/j.apenergy.2018.11.054}, pages = {155 -- 162}, year = {2018}, abstract = {Urban areas play an unprecedented role in potentially mitigating climate change and supporting sustainable development. In light of the rapid urbanisation in many parts on the globe, it is crucial to understand the relationship between settlement size and CO2 emission efficiency of cities. Recent literature on urban scaling properties of emissions as a function of population size has led to contradictory results and more importantly, lacked an in-depth investigation of the essential factors and causes explaining such scaling properties. Therefore, in analogy to the well-established Kaya Identity, we develop a relation combining the involved exponents. We demonstrate that application of this Urban Kaya Relation will enable a comprehensive understanding about the intrinsic factors determining emission efficiencies in large cities by applying it to a global dataset of 61 cities. Contrary to traditional urban scaling studies which use Ordinary Least Squares (OLS) regression, we show that the Reduced Major Axis (RMA) is necessary when complex relations among scaling exponents are to be investigated. RMA is given by the geometric mean of the two OLS slopes obtained by interchanging the dependent and independent variable. We discuss the potential of the Urban Kaya Relation in mainstreaming local actions for climate change mitigation.}, 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} } @phdthesis{Gudipudi2017, author = {Gudipudi, Venkata Ramana}, title = {Cities and global sustainability}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407113}, school = {Universit{\"a}t Potsdam}, pages = {xxii, 101}, year = {2017}, abstract = {In the wake of 21st century, humanity witnessed a phenomenal raise of urban agglomerations as powerhouses for innovation and socioeconomic growth. Driving much of national (and in few instances even global) economy, such a gargantuan raise of cities is also accompanied by subsequent increase in energy, resource consumption and waste generation. Much of anthropogenic transformation of Earth's environment in terms of environmental pollution at local level to planetary scale in the form of climate change is currently taking place in cities. Projected to be crucibles for entire humanity by the end of this century, the ultimate fate of humanity predominantly lies in the hands of technological innovation, urbanites' attitudes towards energy/resource consumption and development pathways undertaken by current and future cities. Considering the unparalleled energy, resource consumption and emissions currently attributed to global cities, this thesis addresses these issues from an efficiency point of view. More specifically, this thesis addresses the influence of population size, density, economic geography and technology in improving urban greenhouse gas (GHG) emission efficiency and identifies the factors leading to improved eco-efficiency in cities. In order to investigate the in uence of these factors in improving emission and resource efficiency in cities, a multitude of freely available datasets were coupled with some novel methodologies and analytical approaches in this thesis. Merging the well-established Kaya Identity to the recently developed urban scaling laws, an Urban Kaya Relation is developed to identify whether large cities are more emission efficient and the intrinsic factors leading to such (in)efficiency. Applying Urban Kaya Relation to a global dataset of 61 cities in 12 countries, this thesis identifed that large cities in developed regions of the world will bring emission efficiency gains because of the better technologies implemented in these cities to produce and utilize energy consumption while the opposite is the case for cities in developing regions. Large cities in developing countries are less efficient mainly because of their affluence and lack of efficient technologies. Apart from the in uence of population size on emission efficiency, this thesis identified the crucial role played by population density in improving building and on-road transport sector related emission efficiency in cities. This is achieved by applying the City Clustering Algorithm (CCA) on two different gridded land use datasets and a standard emission inventory to attribute these sectoral emissions to all inhabited settlements in the USA. Results show that doubling the population density would entail a reduction in the total CO2 emissions in buildings and on-road sectors typically by at least 42 \%. Irrespective of their population size and density, cities are often blamed for their intensive resource consumption that threatens not only local but also global sustainability. This thesis merged the concept of urban metabolism with benchmarking and identified cities which are eco-efficient. These cities enable better socioeconomic conditions while being less burden to the environment. Three environmental burden indicators (annual average NO2 concentration, per capita waste generation and water consumption) and two socioeconomic indicators (GDP per capita and employment ratio) for 88 most populous European cities are considered in this study. Using two different non-parametric ranking methods namely regression residual ranking and Data Envelopment Analysis (DEA), eco-efficient cities and their determining factors are identified. This in-depth analysis revealed that mature cities with well-established economic structures such as Munich, Stockholm and Oslo are eco-efficient. Further, correlations between objective eco-efficiency ranking with each of the indicator rankings and the ranking of urbanites' subjective perception about quality of life are analyzed. This analysis revealed that urbanites' perception about quality of life is not merely confined to the socioeconomic well-being but rather to their combination with lower environmental burden. In summary, the findings of this dissertation has three general conclusions for improving emission and ecological efficiency in cities. Firstly, large cities in emerging nations face a huge challenge with respect to improving their emission efficiency. The task in front of these cities is threefold: (1) deploying efficient technologies for the generation of electricity and improvement of public transportation to unlock their leap frogging potential, (2) addressing the issue of energy poverty and (3) ensuring that these cities do not develop similar energy consumption patterns with infrastructure lock-in behavior similar to those of cities in developed regions. Secondly, the on-going urban sprawl as a global phenomenon will decrease the emission efficiency within the building and transportation sector. Therefore, local policy makers should identify adequate fiscal and land use policies to curb urban sprawl. Lastly, since mature cities with well-established economic structures are more eco-efficient and urbanites' perception re ects its combination with decreasing environmental burden; there is a need to adopt and implement strategies which enable socioeconomic growth in cities whilst decreasing their environment burden.}, language = {en} }