Zhang Yanxu, Tao Shu, Cao Jun, Coveney Raymond M
Laboratory for Earth Surface Processes, College of Environmental Sciences, Peking University, Beijing 100871, China.
Environ Sci Technol. 2007 Feb 1;41(3):683-7. doi: 10.1021/es061545h.
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.
中国各省社会、经济、气候参数与能源消耗之间的定量关系,为回归模型估算各县能源消耗率及多环芳烃(PAHs)排放量提供了数据。以总人口和年平均温度为自变量,采用非线性模型模拟家庭煤炭燃烧情况。对所有其他类型的燃料消耗则使用线性回归模型。蒙特卡洛模拟表明,预测中的不确定性主要源于排放因子,而非回归建模。利用文献中中国南北几个县的现有能源数据对模型进行了验证。各县产生的多环芳烃总量大致相当于能源、焦炭和铝生产排放总量之和。