A factorial environment-oriented input-output model for diagnosing urban air pollution. (10th November 2019) - Xu, Xinli; Huang, Guohe; Liu, Lirong; He, Chengyu
Abstract: The excessive emissions of various air pollutants seriously hinder the sustainability of cities. It is imperative to conduct a thorough diagnose of urban emission systems. The objective of this study is to develop a factorial environment-oriented input-output (FEIO) model to reveal the urban emission system's structural characteristics and possible internal interactions. Through constructing urban emissions networks regarding multiple air pollutants, the crucial transfer sectors and their relevant transactions are identified. Based on the results of identification, factorial analysis (FA) is further introduced to explore the effects of designed factors and their combinations. The results of the case study for Guangdong Province, China demonstrate that the urban emission system differs from the natural ecosystem because of its complex structure. The impact of various air pollutants on the urban ecosystem is different from what they are expected, both the emitting sectors and their energy consumption structures are decisive. In Guangdong province, Manufacture of Metal and Non-metallic Mineral Products (MMN), Electric Power (EP), Electronic and Telecommunications Equipment (ETE) and Chemical Products (CP) are identified as transfer centers in the emission network. The contribution of air pollution derived from coal consumption is more than 48.30%. Both in 2012 and 2015, the contribution of interactions exceeded 17.46%. The VOCs emissions emitted by MMN and SO2 emissions emitted by EP have the greatest impact on the regional ecosystem. These findings can provide reliable information for ensuring regional air environmental protection targets. Highlights: A factorial environment-oriented input-output (FEIO) model is developed. An emissions network regarding multiple air pollutants is established. The network centrality of various sectors and transactions are measured. The possible interactions in the system are quantified by factorial design.