x small (less than 100 k) small (100 k -2 mil) med ( 2 mil - 4 mil) large ( 4 mi
ID: 118920 • Letter: X
Question
x small (less than 100 k) small (100 k -2 mil) med ( 2 mil - 4 mil) large ( 4 mil - 6 mil) x large ( over 6 mil)
Does the size of a city impact levels of CO? what is the probability the cities of each size are of unusual levels?
please show step by step and explain. thank you!!!!
8-hr (ppm) 03 8-hr ( Percptaton ue, NM Springs-Roswell GA altimore-Columbia-Townson, MD nt-Port Arthur, TX Dam, Wi 10 Birmingham-Hoover, AL Stamford-Norwa k, CT 15 uffalo-Cheektowaga-Niagara Falls, NY ington-South Burlington, VT arlotte-Concord-Gastonia, NG-SC 23 Chicago-Naperville-Elign, IL-IN-w 24 Cincinnati, OH-KY-IN d-Elyria, OH 370 llas-Fort Worth-Arlington, TX 31 Davenport-Moline-Rock Island, IA-IL 33 Denver-Aurora-lakewood, CO 4 Des Molnes-West Des Moines, IAExplanation / Answer
Scaling is simply an emergent relationship between systemic size and emissions. Our results show that emissions in urban areas belong to a broader paradigm since every system needs to consume energy to maintain structure and order. The existence of approximate scaling phenomena for urban areas documented using a variety of socio-economic metrics is an indication that there are generic social mechanisms and properties of social systems at play across the entire urban system. Mechanisms such as networks and flows, nonlinearities and feedback loops integrate complex interactions among the individuals, households, firms, and institutions living, residing and operating in these spaces, leading to emergent phenomena such as scaling laws.
The near-linear relationship between population size and carbon emissions suggests that large urban areas in the U.S. are only slightly more emissions efficient than small ones. For each year in our sample, variation in population size across cities in the U.S. urban system explains approximately 70% of the variation of CO emissions with density and wealth not adding explanatory power to the models. This figure does not change when considering only MSAs – that is excluding settlements with populations between 10,000 and 50,000 people. This leaves a substantial proportion of the variation to be explained in the cross-sectional data by factors other than total population, density and wealth. Overall, stated in terms of CO emissions savings, cities in the US do not exhibit economies of scale on average (as defined by the elasticity concept we estimate in this paper) since they scale almost linearly. We suggest that this can only be claimed “on average” because we are not testing for scaling across different population types (e.g. we do not examine a potentially deviating scaling relationship arising from population specializing in distinct industrial sectors). That is, while more substantial economies of scale may be present when a city grows in terms of service sector or “creative” professionals, no economies may be present when the same cities adds manufacturing jobs. Our finding represents the average effect in the specific ten year evolution of the U.S. urban system. Controlling for variation in population density and wealth in cities does not alter our findings.
The intuitive interpretation of the linear scaling finding can be explored first through the analogy urban metabolism. Our finding creates a paradox when one considers that in nature, as organisms grow in size they become more efficient (see discussion on Kleiber’s Law above). A near-linear scaling in CO emissions, and thus only marginal gains in efficiency, casts some doubt on the hypothesis that urban systems function similarly to biological ones. While the analogy between urban metabolism and biological metabolism has been questioned before, our analysis provides further evidence that the analogy may have empirical limits. We now know that cities exhibit characteristics that make the natural organism analogy difficult, such as the urban phenomena that produce super-linear scaling. Still, a theoretical possibility that energy use scales sub-linearly but CO emissions scale linearly; this would be the case if efficiencies in energy use where overshadowed by increased carbon intensiveness of the energy source mix that serves larger cities, the fossil fuel intensiveness of energy used in larger cities or the energy required to produce a unit of GDP in larger cities. Energy and emissions could scale differently because emissions are dependent on the type of energy used to generate final energy, the technology employed to use the energy, and the energy intensity of the economy.
We thus argue that an intuitive interpretation of the linear scaling finding requires an interpretation from economics, combined with an understanding of the nature of greenhouse gas emissions in the US. CO emissions depend significantly on the carbon intensity of the energy source and the drivers of demand for fossil fuels. Several hypotheses can be made on the basis of a decomposition of factors that drive demand for fossil fuels in localized markets. Expecting a pattern of increased savings in CO in larger urban agglomerations, a linear scaling of CO emissions may signify that larger urban areas are lagging in their capacity to curb demand for fossil fuels proportionally to smaller urban areas. Or, it may be the case that residents in larger urban areas are not incentivized structurally (through urban form) or economically (through energy prices) to demand lower proportions of fossil fuels in their energy mix. Furthermore, although large urban areas are more innovative than smaller ones, they may lack capacity in steering eco-innovations towards their local markets for fossil fuels. These important hypotheses remain untested and need to be addressed in future research.
Notwithstanding, our results have important energy policy implications for a rapidly urbanizing planet since they reveal the importance of urban scale/size relative to factors such as population density and wealth. The research shows that policymakers need to renew their attention on issues of distributions of city sizes within national urban systems; we show that size trumps the effects of all other variables (such as population density and wealth) in explaining variation in CO emissions. A focus on urban densities and wealth is still required, as these factors are critical for addressing various facets of global environmental change related to urban development. But as (new) world cities continue to grow, it is important that policymakers consider the CO emission effects of urban size and contrast it to the effects of urban form, building materials and transportation network structure. While we expect that scaling laws characterize the structure and order of urban systems globally, whether our specific U.S. results hold for all typologies of cities is beyond the scope of this study.
The issues associated with emissions and energy accounting methods highlight the limitations of assuming cities as “closed systems”. The “closed system” perspective is in large part driven by the dominant conceptualization of a city through its narrow administrative boundaries – a definition of urban areas that drives data collection globally and dominates research practice surrounding urban phenomena. As we build our capacity to associate the increase of a city’s size to effects that occur far away from a city’s boundaries, we can overcome the data-specific challenge and adopt an “open system” perspective that could drastically alter our perspective on urban scaling. Through this new perspective, wealth, for example, may be found to be a more significant driver of total urban emissions; this is especially the case when considering emissions that occur in distal locations (or carbon sequestration capacity that is lost in distal places) but can be attributed to demand of goods and services that arises in specific urban areas.
Our “closed system” approach findings question the efficacy of using urban size as a climate change mitigation strategy. Our results show that, at least in the case of U.S. cities, there are no significant economies of scale with city size and CO emissions. Therefore, cities and policies must consider other mitigation strategies that have been shown to have greater impacts on emissions than population size. Furthermore, considering the policy relevance of these findings, we claim that limited economies of scale with respect to carbon emissions should be viewed in conjunction to the build-up of additional evidence on urban scaling. Any strategic decision on city growth considering sustainability will have to carefully weigh the implications of urban scale on a variety of urban metrics (including innovation, crime, environmental indicators, etc.). Our results contribute to the larger picture of scaling relationships present in urban systems: given that larger cities “speed up” the process of wealth creation and innovation and do not offer significant economies of scale in CO emissions, a policy favoring larger city sizes may bring about carbon reductions primarily through technological advancements and eco-innovations.
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