Quantitative relationships among social, economic, and climate parameters, and energy consumption for Chinese provinces, provide data for regression models' estimated rates of energy consumption and emission of polycyclic aromatic hydrocarbons (PAHs) by county. A nonlinear model was used for domestic coal combustion with total population and annual mean temperature as independent variables. Linear regression models were utilized for all other types of fuel consumption. Monte Carlo simulation demonstrated that emission factors, rather than the regression modeling, constitute the main source of uncertainty in prediction. Models were validated using available energy data of several northern and southern counties of China from the literature. The total PAHs produced by each county is approximately equivalent to the sum of the total emission from energy, coke, and aluminum production.

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