انرژی کاربردی گرایش های موقتی و فضایی مصرف انرژی مسکونی و میزان انتشار آلاینده ها در چین

Residential energy consumptions of both electricity and fuels are associated with emissions of many air pollutants. Temporally and spatially resolved energy consumption data are scarce in China, which are critical for a better understanding of their environmental impacts. In this study, a space-for-time substitution method was proposed and two models for predicting fuel and electricity consumptions in residential sector of China were developed using provincial data. It was found that fuel consumption was not directly proportional to heating degree day and was also affected by heating day, defined as the number of days when heating is required in a year. The models were validated against a set of historical annual data and two sets of survey data on seasonal variations. The models were applied to predict spatial and temporal variations of residential energy consumptions and emissions of various pollutants and to predict net effects of climate warming on energy consumptions and pollutant emissions. The emissions of black carbon (BC), carbon monoxide (CO), and polycyclic aromatic carbons (PAHs) in winter were significantly higher than those in other seasons. For the emissions of carbon dioxide (CO2), sulfur dioxide (SO2), and nitrogen oxides (NOx), there were two peaks in winter and summer, with the latter increasing gradually over years. It was predicted that per-capita residential energy consumptions would reach 0.43, 0.33, and 0.26 toe/cap in 2050 for IPCC scenarios of A1B, B1, and A2, respectively. Climate warming in the future would lead to less residential fuel but more electricity consumptions. Consequently, emissions of BC, CO, and PAHs would decrease mainly in cold climate zones, while emissions of CO2, SO2, and NOx would increase largely in southeast China.

Energy is of fundamental importance to our society. However, the acquisition, production, and utilization of energy have great adverse impacts on environment by emitting pollutants, greenhouse gases, and heat [1]. A portion of energy, mainly electricity and fuels, is used in residential sector for heating, cooling, cooking, lighting, and appliances. According to the National Bureau of Statistics of China, electricity and various fuels account for 11% and 89% of the total residential energy consumption in China, respectively [2]. Although the quantities of fuels, mainly coal and biomass fuel, used in residential sector contribute to a relatively small fraction of total energy consumption, the environmental impacts of residential fuel consumption cannot be ignored due to relatively low combustion efficiencies and high emission factors [3], [4], [5] and [6]. For example, it was estimated that over 50% of black carbon and approximately 70% of polycyclic aromatic hydrocarbons (PAHs) emitted in China were from residential fuel combustions [7] and [8]. Residential energy consumption is affected by temperature and socioeconomic conditions [9] and [10], both of which vary in space (hot or cold, rich or poor) and over time (month–month, year–year), resulting in spatial and temporal variations in residential energy consumptions. The concept of degree-day, defined as the accumulated degree deviations from predefined base temperatures, is widely applied to characterize the relationship between energy use and temperature [11], [12], [13] and [14]. Both heating degree day (hdd) and cooling degree day (cdd) are used by assuming that the heating (or cooling) energy requirement is proportional to hdd (or cdd) [10], [15] and [16]. However, this assumption is questionable for hdd because an ‘initial fuel (a minimum quantity of fuel to be used to start a fire for heating no matter how far the temperature below the base temperature)’ has to be consumed once the ambient temperature drops below a given base temperature. Moreover, heating demand may not increase linearly as the difference between the base and daily temperature increases.

Based on annual residential fuel and electricity consumption data at provincial level, the effects of a number of climate and socioeconomic parameters on the residential energy consumptions were studied and quantified. A hypothesis that spatial and temporal variations in residential energy consumptions are driven by the same factors was successfully tested. Based on the regression models developed for residential fuel and electricity consumptions in China, relatively highly spatial (1° × 1°) and temporal (monthly) resolved inventories of fuel consumption, electricity consumption, and emissions of a number of greenhouse gases and air pollutants were projected. Difference in seasonality between emissions of regular pollutants (CO2, SO2, and NOx) and incomplete combustion by-products (BC, CO, and PAHs) were found. Winter peaks occur for all pollutants studied while summer peaks were found only for the former. Based on the three IPCC scenarios of A1B, B1, and A2, the per-capita residential energy consumptions would reach 0.43, 0.33, and 0.26 toe/cap in 2050, respectively. In case of climate warming in the future, less residential fuel but more electricity would be consumed. As a result, emissions of BC, CO, and PAHs would decrease mainly in cold climate zones of north China, while emissions of CO2, SO2, and NOx would increase largely in southeast China.