Linking city‐level input–output table to urban energy footprint: Construction framework and application

Abstract

Multiregion input-output (MRIO) models have become increasingly important in economic and environmental analysis. However, the current resolution of most MRIO models fails to capture the heterogeneity between subregions, especially in cities. The lack of city-level MRIO tables has impeded the accomplishment of city-level studies and hampered the understanding of the relationship between urban growth and consumption, and teleconnections to other regions. In this paper, we propose a partial survey-based multiple-layer framework for MRIO table compilation of a Chinese province that distinguishes city-based regions. This framework can effectively address a large number of data processes and retain consistency between layers. Using the framework, we first compile a nested Hebei-China city-level MRIO table and then apply city-level energy footprint accounting of the North China urban agglomeration. Our results present the critical role of Hebei cities in energy supply in 2012 and quantify energy use embodied in goods for the domestic trade. Tangshan, Shijiazhuang, and Handan are distinctive cities in the energy supply chain of other regions, for both less developed and developed regions. This multiple-layer framework represents a feasible approach for developing subregional-level MRIO models and offers the possibility to analyze global trade at the subregional level with limited data.

Mapping Carbon and Water Networks in the North China Urban Agglomeration

“…Using population-weighted distance could be more accurate than the average distance, but still cannot address the problem. 16 Some uncertainties are from the process of MRIO table construction. For example, we applied the RAS technique to optimize the matrix because conflicting data in the construction often led to an imbalanced MRIO table.…”

“…More details can be found in the references. 16 These calculations yielded an origin-destination matrix by sector that we used as the initial matrix for RAS (biproportional techniques; see Lahr and Mesnard 68 ), which used the set of the outflow and inflow constraints in the city IO tables for the 11 cities in Hebei and the Hebei IO table for the 12th city. To ensure that the modeled trade flow matches the constraints, it should be subject to the following equations:…”

“…With increasing urban populations and urban expansion, global cities are facing great challenges of decarbonization and water scarcity. How a city controls carbon and the water supply network largely determines how sustainable the city could be [14][15][16] and also provides the knowledge base for coordinated intercity policy. With an intercity supply chain, urban sustainability not only controls the sustainability of an individual city, but more importantly, it controls a sustainable network for trade between cities.…”

Structural patterns of city-level CO2 emissions in Northwest China

“…However, in Yinchuan and Yulin, the shares of coal-related emissions from EP in total emissions increased apparently. Thus, regarding this phenomenon, one possible explanation is that interregional CO 2 flows may occur more evidently, but to explore the exact CO 2 flows, establishing a multi-region input-output table across regions is necessary (Meng et al, 2018;Zheng et al, 2019).…”

Nesting a city input–output table in a multiregional framework: a case example with the city of Bogota

“…Malik et al (2018) also highlight the need for a better understanding of within-countries effects of inter-regional interactions. These Spatially Explicit Input-Output models (SIO), as (Sun et al 2019) called them, are relevant in the case of environmental assessments since they connect global production and trade to local environmental impacts and local consumption (Sun et al 2019) or urban development (Zheng et al 2019). These initiatives could be of the most interest in those cases where the region or city are a substantive part of the national economy, and its production systems are strongly intertwined in the global economy; as it happens in the case of Bogota which accounts for more than a quarter of the Colombian economy.…”