Cities have been envisioned as biological organisms as the integral part of nature's energy and material flows. Recent advances in urban scaling research have uncovered systematic changes in socioeconomic rates and infrastructural networks as urban population increases, providing predictive contents for the comparison between cities and organisms. However, it is still unclear how and why larger and smaller cities may differ in their per capita environmental impacts. Here, we study scaling patterns of urban energy, water, and waste flows as well as other relevant measures in Chinese cities. We divide cities into different groups using an algorithm that automatically assigns cities to clusters with distinct scaling patterns. Despite superlinear scaling of urban GDP, as predicted by urban scaling theories, resource consumption, such as the supply of electricity and water, and waste generation, such as wastewater and domestic waste, do not show significant deviations from linear scaling. The lengths of resource pipelines scale linearly in most cases, as opposed to sub-linearity predicted by theory. Furthermore, we show two competing forces underlying the overall observed effects of scale: a higher population density tends to decrease per capita resource consumption and infrastructure provisions, while intensified socioeconomic activities have the opposite effect.
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