Is benzo[a]pyrene a reliable chemical indicator of social-economic development in China?

The current approaches to study the coupling mechanism between economy and environment seem to fall into self-circulation, failed to reveal economyeenvironment interdependence. In this context, an exogenous variable is introduced into these models for better understanding the relationship. Benzo[a] pyrene (Bap) environment inventories in different cities in China were estimated by fugacity model based on Bap concentration data collected from previous studies. An extended model, stochastic impacts by regression on population, affluence and technology (STIRPAT), generated from original IPAT (a model that expresses the idea that environmental impact (I) is the product of three factors: population (P), affluence (A) and technology (T)) was used to study the relationship between Bap environment inventory and anthropogenic factors including population, vehicle amount, affluence and energy consumption. A ridge regression has been applied to optimize the model parameters. Overall, there exist good relationships between Bap inventories and economic factors. Specifically, population and affluence are the most significant factors that influence Bap inventory. Rise of the scale of population and vehicle amount increases the Bap inventory, as growth of GDP per capita and the efficiency of energy utilization have inhibitory effect on Bap inventory. Apparently, the influences of anthropogenic factors on Bap inventory are different between north and south China. Bap inventory in north China is more sensitive to the change of population and energy consumption, while is highly correlated to GDP per capita in south China. Further, according to social-economic development prediction, with assist of the result from STIRPAT model, we find out that Bap inventory drop 31% from 2001 to 2020 in China. Our estimates are comparable with the published data and confirmed that Bap can be regarded as a chemical indicator of social-economic development in China. (C) 2020 Elsevier Ltd. All rights reserved.