Allometric Scaling Laws Research Articles

Settlement scaling law reveals population-land tensions in 7000+ African urban agglomerations

Allometric urban scaling law quantifies disproportional relationships between urban indicators and city size, which has been reported across developed countries and parts of the global south, but its applicability in Africa is neglected. Here, taking built-up areas derived from remote sensing in more than 7000 African agglomerations in 2015 as examples, we systematically investigate this settlement scaling law from continental, regional, and country levels. Results show that the built-up area linearly scales with population across the African continent and within northern and western Africa, while it sub-linearly scales with population in southern (β = 0.85, 95% CI: 0.808–0.891) and central (β = 0.93, 95% CI: 0.906–0.957) Africa, but super-linearly (β = 1.10, 95% CI:1.068–1.121) in eastern Africa. National settlement scaling exponents (β) vary from 0.65 to 1.25 with an average of 0.96, whose 63.6% variance can be explained by their share of built-up area, share of metropolitan population, GDP per capita, and proportion of slum dwellers. Residuals of scaling fitting reflect local population-land tensions. Western and eastern Africa are relatively rich in buildable land resources, while northern Africa is relatively poor. This study expanded the settlement scaling theory in Africa and multiple indicators are needed to further understand the rapidly evolving African urban systems.

Phase shift between joint rotation and actuation reflects dominant forces and predicts muscle activation patterns.

During behavior, the work done by actuators on the body can be resisted by the body's inertia, elastic forces, gravity, or viscosity. The dominant forces that resist actuation have major consequences on the control of that behavior. In the literature, features and actuation of locomotion, for example, have been successfully predicted by nondimensional numbers (e.g. Froude number and Reynolds number) that generally express the ratio between two of these forces (gravitational, inertial, elastic, and viscous). However, animals of different sizes or motions at different speeds may not share the same dominant forces within a behavior, making ratios of just two of these forces less useful. Thus, for a broad comparison of behavior across many orders of magnitude of limb length and cycle period, a dimensionless number that includes gravitational, inertial, elastic, and viscous forces is needed. This study proposes a nondimensional number that relates these four forces: the phase shift (ϕ) between the displacement of the limb and the actuator force that moves it. Using allometric scaling laws, ϕ for terrestrial walking is expressed as a function of the limb length and the cycle period at which the limb steps. Scale-dependent values of ϕ are used to explain and predict the electromyographic (EMG) patterns employed by different animals as they walk.

Coupling Random Forest, Allometric Scaling, and Cellular Automata to Predict the Evolution of LULC under Various Shared Socioeconomic Pathways

Accurately estimating land-use demand is essential for urban models to predict the evolution of urban spatial morphology. Due to the uncertainties inherent in socioeconomic development, the accurate forecasting of urban land-use demand remains a daunting challenge. The present study proposes a modeling framework to determine the scaling relationship between the population and urban area and simulates the spatiotemporal dynamics of land use and land cover (LULC). An allometric scaling (AS) law and a Markov (MK) chain are used to predict variations in LULC. Random forest (RF) and cellular automata (CA) serve to calibrate the transition rules of change in LULC and realize its micro-spatial allocation (MKCARF-AS). Furthermore, this research uses several shared socioeconomic pathways (SSPs) as scenario storylines. The MKCARF-AS model is used to predict changes in LULC under various SSP scenarios in Jinjiang City, China, from 2020 to 2065. The results show that the figure of merit (FoM) and the urban FoM of the MKCARF-AS model improve by 3.72% and 4.06%, respectively, compared with the MKCAANN model during the 2005–2010 simulation period. For a 6.28% discrepancy between the predicted urban land-use demand and the actual urban land-use demand over the period 2005–2010, the urban FoM degrades by 21.42%. The growth of the permanent urban population and urban area in Jinjiang City follows an allometric scaling law with an exponent of 0.933 for the period 2005–2020, and the relative residual and R2 are 0.0076 and 0.9994, respectively. From 2020 to 2065, the urban land demand estimated by the Markov model is 19.4% greater than the urban area predicted under scenario SSP5. At the township scale, the different SSP scenarios produce significantly different spatial distributions of urban expansion rates. By coupling random forest and allometric scaling, the MKCARF-AS model substantially improves the simulation of urban land use.

Demonstration of duality of fractal gravity models by scaling symmetry

A pair of fractal gravity models can be derived from spatial interaction models based on the entropy maximizing principle and the allometric scaling law. The models can be expressed in dual form in mathematics and are important for analyzing and predicting spatial flows in networks of cities. However, the dual relationship of urban gravity parameters has remained an empirical relationship for a long time and lacks theoretical proof. This paper is devoted to proving the duality of fractal gravity models by means of ideas from scaling invariance. The results show that a fractal gravity model can be derived from its dual form. The observational data of interurban spatial flows of the Beijing-Tianjin-Hebei region of China are employed to make a case study, lending further support for the theoretical derivation. It appears that the duality of gravity models rests with the scaling symmetry of fractal structure. This work may be helpful for understanding the theoretical essence and application direction of spatial interaction modeling.

One-stop patient-specific myocardial blood flow quantification technique based on allometric scaling law

Establishing a patient-specific and non-invasive technique to derive blood flow as well as coronary structural information from one single cardiac CT imaging modality. 336 patients with chest pain or ST segment depression on electrocardiogram were retrospectively enrolled. All patients underwent adenosine-stressed dynamic CT myocardial perfusion imaging (CT-MPI) and coronary computed tomography angiography (CCTA) in sequence. Relationship between myocardial mass (M) and blood flow (Q), defined as log(Q) = b · log(M) + log(Q0), was explored based on the general allometric scaling law. We used 267 patients to obtain the regression results and found strong linear relationship between M (gram) and Q (mL/min) (b = 0.786, log(Q0) = 0.546, r = 0.704; p < 0.001). We Also found this correlation was applicable for patients with either normal or abnormal myocardial perfusion (p < 0.001). Datasets from the other 69 patients were used to validate this M−Q correlation and found the patient-specific blood flow could be accurately estimated from CCTA compared to that measured from CT-MPI (146.480 ± 39.607 vs 137.967 ± 36.227, r = 0.816, and 146.480 ± 39.607 vs 137.967 ± 36.227, r = 0.817, for the left ventricle region and LAD-subtended region, respectively, all unit in mL/min). In conclusion, we established a technique to provide general and patient-specific myocardial mass-blood flow correlation obeyed to allometric scaling law. Blood flow information could be directly derived from structural information acquired from CCTA.

Fractal Organization of Chilean Cities: Observations from a Developing Country

Urban forms are human-made systems that display a close connection with fractal objects, following organisation patterns that are not as random as believed. In this context, fractal theory can be seriously considered as a powerful tool for characterizing land-use planning. By applying the box-counting method and image-processing methods, the morphology and fractal metrics of urban networks of Chilean cities were measured. This dimension shows a close correlation with area, population and gross domestic product of each entity, revealing significant asymmetries regarding their distribution throughout the country. Such asymmetries have influenced the current shape of cities, issues concerning economic and social inequalities of urban development that still remain in the territory and explained by social segregation process and the historical evolution of cities. Additionally, some interesting allometric scaling laws obtained from these urban forms are also reported. Our results suggest that the use of fractal metrics can be a meaningful and cheap tool for characterizing the complexity of urban networks, providing useful and quick information about the organisation and efficiency of urban planning in developing countries.

Biomass allometric models for Larix rupprechtii based on Kosak's taper curve equations and nonlinear seemingly unrelated regression.

The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass model. Therefore, it is still an urgent scientific problem to build a high-precision biomass model system. A dataset of 114 trees was destructively sampled to obtain dry biomass components, including stems, branches, and foliage, and taper measurements to explore the applicability of biomass components to allometric scaling laws and develop a new system of additive models with the diameter in relative height (DRH) for each component of a Larch (Larix principis-rupprechtii Mayr) plantation in northern China. The variable exponential taper equations were modelled using nonlinear regression. In addition, applying nonlinear regression and nonlinear seemingly unrelated regression (NSUR) enabled the development of biomass allometric models and the system of additive models with DRH for each component. The results showed that the Kozak's (II) 2004 variable exponential taper equation could accurately describe the stem shape and diameter in any height of stem. When the diameters in relative height were D0.2, D0.5, and D0.5 for branches, stems, and foliage, respectively, the allometric exponent of the stems and branches was the closest to the scaling relations predicted by the MST, and the allometric exponent of foliage was the most closely related to the scaling relations predicted by geometry theory. Compared with the nonlinear regression, the parameters of biomass components estimated by NSUR were lower, and it was close to the theoretical value and the most precise at forecasting. In the study of biomass process modelling, utilizing the DRH by a variable exponential taper equation can confirm the general biological significance more than the DBH of a fixed position.

Using Material Flow and Stock Indicators to Evaluate Urban Allometry: Evidence from the Beijing–Tianjin–Hebei Region

The growing urban population is intensifying global resource shortages. It is essential for scholars and policymakers to better understand the material-based metabolism of cities for sustainable urban resource management. Taking the Beijing–Tianjin–Hebei region of China as a representative case, this study quantifies domestic material consumption (DMC) and material stock (MS) and reveals the dynamics of the material-based urban metabolism of cities during 2000 to 2017 based on the allometric scaling law. The results show that the DMC and MS of each city exhibited an overall increasing trend during 2000 to 2017, with Beijing, Tianjin, Shijiazhuang, Baoding, Handan, and Tangshan having larger material bases than the other cities. Cities at different stages of development usually follow different material-based allometric scaling law relationships. Most cities in this region (9 out of 13) follow a superlinear relationship, indicating excessive consumption of resources in these cities. The scaling coefficient of Beijing is most similar to the value (0.75) that has been observed in many types of biological research, which suggests that Beijing has reached a relative stabilization stage of development. This study provides key points for future resource allocation and industrial optimization related to urban material metabolism in the Beijing–Tianjin–Hebei region. The findings of this study can enrich the theoretical and empirical bases for urban allometry research and provide urban managers with additional insights for consideration to achieve sustainable urban resource management.

Aberrant allometric scaling of cortical folding in preterm-born adults.

A universal allometric scaling law has been proposed to describe cortical folding of the mammalian brain as a function of the product of cortical surface area and the square root of cortical thickness across different mammalian species, including humans. Since these cortical properties are vulnerable to developmental disturbances caused by preterm birth in humans and since these alterations are related to cognitive impairments, we tested (i) whether cortical folding in preterm-born adults follows this cortical scaling law and (ii) the functional relevance of potential scaling aberrances. We analysed the cortical scaling relationship in a large and prospectively collected cohort of 91 very premature-born adults (<32 weeks of gestation and/or birthweight <1500 g, very preterm and/or very low birth weight) and 105 full-term controls at 26 years of age based on the total surface area, exposed surface area and average cortical thickness measured with structural magnetic resonance imaging and surface-based morphometry. We found that the slope of the log-transformed cortical scaling relationship was significantly altered in adults (very preterm and/or very low birth weight: 1.24, full-term: 1.14, P = 0.018). More specifically, the slope was significantly altered in male adults (very preterm and/or very low birth weight: 1.24, full-term: 1.00, P = 0.031), while there was no significant difference in the slope of female adults (very preterm and/or very low birth weight: 1.27, full-term: 1.12, P = 0.225). Furthermore, offset was significantly lower compared with full-term controls in both male (very preterm and/or very low birth weight: -0.546, full-term: -0.538, P = 0.001) and female adults (very preterm and/or very low birth weight: -0.545, full-term: -0.538, P = 0.023), indicating a systematic shift of the regression line after preterm birth. Gestational age had a significant effect on the slope in very preterm and/or very low birth weight adults and more specifically in male very preterm and/or very low birth weight adults, indicating that the difference in slope is specifically related to preterm birth. The shape or tension term of the scaling law had no significant effect on cognitive performance, while the size of the cortex did. Results demonstrate altered scaling of cortical surface and cortical thickness in very premature-born adults. Data suggest altered mechanical forces acting on the cortex after preterm birth.

Data-driven stochastic simulation leading to the allometric scaling laws in complex systems.

We propose a data-driven stochastic method that allows the simulation of a complex system's long-term evolution. Given a large amount of historical data on trajectories in a multi-dimensional phase space, our method simulates the time evolution of a system based on a random selection of partial trajectories in the data without detailed knowledge of the system dynamics. We apply this method to a large data set of time evolution of approximately one million business firms for a quarter century. Accordingly, from simulations starting from arbitrary initial conditions, we obtain a stationary distribution in three-dimensional log-size phase space, which satisfies the allometric scaling laws of three variables. Furthermore, universal distributions of fluctuation around the scaling relations are consistent with the empirical data.

Potential Zoning of Construction Land Consolidation in the Loess Plateau Based on the Evolution of Human-Land Relationship.

Towns serve as the basic unit of implementation for comprehensive land consolidation and rehabilitation. The utilization of scaling law can provide a new perspective for construction land consolidation. From two perspectives of the town hierarchic system and the growth of a single town, this research applies the Rank-Size Rule and Allometric Scaling Law to analyze the scale structure, hierarchy and allometric scaling evolution relationship of population and construction land in the Loess Plateau at the town scale in 2000, 2010, and 2017. Furthermore, the consolidation potential of construction land is divided into five zones and puts forward recommendations for the comprehensive consolidation of the construction land. The results indicate: (1) The majority of towns have small or medium populations and 62% of the towns in the study show negative population growth. Geographically, the northern part has a smaller population size compared with the southern part. 96% of the towns show an increasing trend in the quantity of construction land, and the south and north parts of the study area have more construction land compared with the center part. The zone of the Valley Plain has the largest population size, and the zone of the Sandy and Desert Area has the largest quantity of construction land. (2) The rank-size distributions of both population and construction land comply with the power-law relation. The population hierarchy has changed from equilibrium to concentration, while the hierarchy of construction land shows an opposite pattern. So, the whole town hierarchic system of the Loess Plateau is gradually tending to the optimal distribution, which is the town hierarchic system gradually forming an ideal sequence structure. (3) The population-construction land relationship obeys the allometric scaling law, and the major allometric type is positive allometry. The human-land relationship tends to be coordinated, and the town system tends to be reasonable. The allometric scaling coefficient is not robust in different geographical areas, especially in Irrigated Agricultural Areas. Furthermore, 90% of the towns have weak coordination of human-land relationships, and 60% of the towns have a relatively faster growth rate of construction land than the relative growth (decline) rate of population. (4) The consolidation potential of construction land is divided into five types. High Consolidation Potential Area concentrates in the Eastern Loess Plateau, while Medium and Low Consolidation Potential Area concentrically distribute in the Western Loess Plateau. The Human-land Coordination Area has a small number and scattered spatial distribution. The land use of towns that are concentrated around prefecture-level cities or with unique resources is not intensive enough. The zoning of construction land consolidation potential based on the results of the allometric scale is in line with reality, and local governments should make use of the characteristics and trends of the town system to formulate planning schemes to promote the integrated development of urban and rural areas.

Allometric scaling laws for temporal proximity in perceptual organization.

In both space and time, proximity plays an important role in the formation of perceived groups, objects, and scenes. Proximity is especially critical in the temporal domain where there are constraints-pauses or delays between neighboring events, that when of sufficient size, defeat the grouping processes that underlay temporal integration. A framework is developed where temporal proximity constraints are theorized to reflect lifetimes of exponential decay processes, and this identification leads to an inquiry into their scaling properties. In a study focusing on rhythmic pulse, the slowest tempo permitting stable rhythmic performance is shown to satisfy an allometry with a power-law exponent close to that of heart rate. The coefficient of variation, a measure of drumming stability and precision, is also shown to obey an allometry. A theory is developed that predicts that allometry in the coefficient of variation exists only at adagio and largo tempi. In a second experiment, this theory is tested by replicating the finding of precision allometry at 60 bpm, and by finding that precision is independent of body size at the marching tempo of 120 bpm. A third experiment examined proximity constraints in apparent motion, historically a defining example of temporal organization. Using a behavioral method for measuring path vividness, it is demonstrated that proximity constraints for the percept of illusory motion paths also satisfy an allometry. These two examples of proximity constraint scaling suggest that allometry may be a generic feature of temporal integration. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The origin of the allometric scaling of lung ventilation in mammals

A model of optimal control of ventilation has recently been developed for humans. This model highlights the importance of the localization of the transition between a convective and a diffusive transport of respiratory gas. This localization determines how ventilation should be controlled in order to minimize its energetic cost at any metabolic regime. We generalized this model to any mammal, based on the core morphometric characteristics shared by all mammalian lungs and on their allometric scaling from the literature. Since the main energetic costs of ventilation are related to convective transport, we prove that, for all mammals, the localization of the shift from a convective transport to a diffusive transport plays a critical role on keeping this cost low while fulfilling the lung function. Our model predicts for the first time the localization of this transition in order to minimize the energetic cost of ventilation, depending on mammal mass and metabolic regime. From this optimal localization, we are able to predict allometric scaling laws for both tidal volumes and breathing rates, at any metabolic rate. We ran our model for the three common metabolic rates -- basal, field and maximal -- and showed that our predictions reproduce accurately experimental data available in the literature. Our analysis supports the hypothesis that mammals allometric scaling laws of tidal volumes and breathing rates at a given metabolic rate are driven by a few core geometrical characteristics shared by mammalian lungs and by the physical processes of respiratory gas transport.

Energy consumption and economic growth: Does it accord with the allometric scaling law in biology?

Energy consumption plays an important role in economic growth. It has been reported that the pattern of energy use in human economies possesses the same form as the biological relationship governing the amount of energy required by animals for their base metabolism, namely the relationship is characterized by a power function having a scaling factor (exponent) of 0.75. Using two different sets of data, we consider whether these data for China support this hypothesis. Energy use per head in relation to its GDP per capita for the whole of China for the period 1980–2011 is examined. A similar exercise is completed for the three main regions of China (its Eastern, Middle and Western Regions) for the period 1980–2008. Substantial differences in regional energy intensities are found and reasons for these are suggested. Furthermore, it is discovered that the overall results do not support the hypothesis that China’s energy use accords with the above mentioned biological relationship. Alternative relationships are found to provide a better fit to the available data.

How mammals adapt their breath to body activity – and how this depends on body size

A model of optimal control of ventilation has recently been developed for humans. This model highlights the importance of the localization of the transition between a convective and a diffusive transport of respiratory gas. This localization determines how ventilation should be controlled in order to minimize its energetic cost at any metabolic regime. We generalized this model to any mammal, based on the core morphometric characteristics shared by all mammalian lungs and on their allometric scaling from the literature. Since the main energetic costs of ventilation are related to convective transport, we prove that, for all mammals, the localization of the shift from a convective transport to a diffusive transport plays a critical role on keeping this cost low while fulfilling the lung function. Our model predicts for the first time the localization of this transition in order to minimize the energetic cost of ventilation, depending on mammal mass and metabolic regime. From this optimal localization, we are able to predict allometric scaling laws for both tidal volumes and breathing rates, at any metabolic rate. We ran our model for the three common metabolic rates -- basal, field and maximal -- and showed that our predictions reproduce accurately experimental data available in the literature. Our analysis supports the hypothesis that mammals allometric scaling laws of tidal volumes and breathing rates at a given metabolic rate are driven by a few core geometrical characteristics shared by mammalian lungs and by the physical processes of respiratory gas transport.

Abstract P344: Validation of Computational Fluid Dynamics Against PC-MRI Measurements of Blood Flow in Healthy Intracranial Arteries: On the Threshold to Clinical Utility for Stroke Prediction

Aim: Computational Fluid Dynamics (CFD) modeling of blood flow is a promising technique to obtain hemodynamic biomarkers and predict recurrent strokes. Few studies, however, have validated CFD against other methods for measuring hemodynamics, e.g. phase contrast MRI (PC-MRI). To resolve the uncertainties about the accuracy of CFD, this study validates the results of an automated software that combines deep learning and CFD for simulating blood flow given an MR angiogram against PC-MRI. Methods: Intracranial arteries in 10 healthy volunteers (60% male, mean age 38 ± 16 years) were automatically segmented from TOF MRA obtained at 3T using deep learning. Subject-specific CFD modelling was undertaken. PC-MRI flow rate for each subject was used at the inlet boundary condition, but not at the outlets. Outlet boundary condition was set to lumped parameter Windkessel model, with the resistance programmatically determined using allometric scaling laws based on the dimension and branching of vasculature. For comparison, two commonly used outlet conditions (exponent 2 &amp; 3 in Murray’s Law) were also considered. CFD results for flow rate and wall shear stress were compared against PC-MRI using Pearson’s correlation coefficient. Results: The flow rate across major intracranial arteries from CFD was in excellent agreement with the PC-MRI (MCA: r = 0.83, ACA: r = 0.81 &amp; PCA: r = 0.82). In addition, there was good correlation for both wall shear stress (WSS) and WSS Ratio (WSSR, i.e. the ratio of WSS between a branch and its parent vessel) (MCA (WSS/WSSR): r = 0.6/0.77, ACA (WSS/WSSR): r = 0.86/0.93 &amp; PCA (WSS/WSSR): r = 0.72/0.85). The inter-subject variability of the flow rate (i.e. standard deviation) obtained from CFD matched closely the variation range observed from PC-MRI and the literature. The two alternative outlet models behaved similarly but suffered from vessel truncation and high errors in some cases. Conclusion: CFD modelling of blood flow in intracranial arteries from static images has good agreement with PC-MRI measurements when allometric scaling laws are applied for setting Windkessel outflow conditions. This lays the foundation for using CFD to predict recurrent strokes as the technique uses standard MRA images already commonly acquired for stroke evaluation.

Intra- and inter-specific scaling laws of plants and animals

The allometric scaling laws of metabolism in 447 animal and 1200 plant species showed convex and concave curvatures between mass and metabolic rate, respectively. The objective of the study is to explain the difference of curvatures between animals and plants based on fractal models. Several intraspecific scaling laws were derived from an asymmetric vascular tree with the fractal dimension (i.e., a in $${k}_{1}^{a}+{k}_{2}^{a}+\dots =1$$ , where $${k}_{i}$$ refers to the ratio of daughter to mother diameters). Based on the intraspecific scaling laws, the allometric scaling exponent of metabolism (i.e., an interspecific scaling law) was shown to be equal to one-third of fractal dimension. Moreover, a novel piecewise-defined function in conjunction with the intraspecific scaling laws was proposed to explain the diverse metabolic scaling in animals and plants. The intraspecific and interspecific scaling laws showed good agreement with morphometric measurements. The experimentally-validated scaling models predict the diversity of intraspecific and interspecific scaling seen in nature. To our knowledge, this is the first study to use fractal models to explain the convex and concave forms of metabolic scaling in animals and plants. The study resolves the long-term controversies to use the resource-transport network models for explanation of the allometric scaling law of metabolism. This study validated intraspecific scaling laws of asymmetric vascular trees instead of idealized symmetric trees. The fractal dimension was found to greatly affect the scaling exponents. Based on the intraspecific scaling laws, the allometric scaling exponent of metabolism was shown to be equal to one-third of fractal dimension. The piecewise-defined asymmetric vascular tree was further proposed to accurately explain convex and concave curvatures in metabolic scaling of animals and plants, respectively.

Dynamic allometric scaling of tree biomass and size.

Allometric scaling laws critically examine structure-function relationships. In estimating the forest biomass carbon and its response under climate change, the issue of scaling has resulted in difficulties when modelling the biomass for different-sized trees, especially large ones, and has not yet been solved in either theory or practice. Here, we propose the concept of a dynamic allometric scaling relationship between stem biomass and above-ground biomass The allometric curve approaches an asymptote with an increase in tree size. An asymptotic allometric equation is presented that has a better fit to the data than the simple power-law allometric equation. The non-constant exponent is determined by the change in the biomass ratio for different organs and is governed by the dynamic allometric coefficient. This study presents a methodological framework to theoretically characterize allometric relationships and provides new insights in understanding the general scaling pattern and carbon sequestration capacity of large trees across global forests.

Urban Scaling as Validation for Predictions of Imperviousness From Population

AbstractStrategies for creating quantitative projections for human systems, especially impervious surfaces, are necessary to consider the human drivers of climate and ecosystem change. There are models that generate predictions of how impervious surfaces may change in response to different potential futures, but few tools exist for validating those predictions. We seek to fill that gap. We demonstrate a statistically robust sublinear scaling relationship between population and urban imperviousness across a 15 year history. We show that Integrated Climate and Land‐Use Scenarios (ICLUS) urbanization projections are also consistent with theory. These results demonstrate a theory that can be used to validate other models' predictions of urban growth and land cover change, analogous to the ways in which allometric scaling laws in biology have been used to validate process‐based models of ecosystem composition under different climate scenarios.

Driving Factors of Transportation CO2 Emissions in Beijing: An Analysis from the Perspective of Urban Development

There is a coupling relationship between the development of urban transportation and cities: Urban growth leads to increase in the demand for urban transportation and consequently, a lot of transportation emissions. Therefore, an in-depth understanding of the mechanism behind the driving effect of urban development on transportation emissions is a crucial prerequisite for coordinated development of low-carbon urban transportation and cities. Based on the oil product allocation method, this paper estimates the transportation emission in Beijing from 1995 to 2016. Then based on the understanding of the driving mechanism, this paper applies the urban allometric scaling law to analyze the relationship between city size and transportation emission. Finally, the driving mechanism is analyzed using the STRIPAT model. The results reveal a superlinear relationship between transportation emission in Beijing and the expansion of the city, as the former outgrew the latter. Population size, urbanization, economic size, industrial structure, spatial scale and infrastructure construction are positive driving factors of transportation emission, whereas progress of energy technologies as a negative driving factor can restrain the growth of transportation emission. Urbanization has the most significant impact on urban transportation emission, and economic size contributes the most to the growth of transportation emission. Based on the results, we make a few policy recommendations for low-carbon urban transportation of Beijing, which include: improving transportation efficiency in the process of urbanization; promoting energy conservation and emission reduction while pursuing economic development so as to decouple transportation emission from urban development; restricting unordered urban expansion and updating the concept of transportation infrastructure supply; and developing energy technologies to improve energy efficiency.