基于卫星和统计资料的东北地区生物质燃烧源近实时排放清单研究

Biomass burning is a major source of particulate matter that affect air quality, human health and climate change. Emission inventories of biomass burning are the fundemental information required to assess the environment effects of this ubiquitous phenomenon. However, there are large uncertainties assocaited with biomass burning emisison inventories, due to lack of detailed information of biomass combused and emission factors. Especially in the Northeastern China, where biomass burning and regional haze often contributed extreme hazy weather conditions, only few studies have attempted to estimate fuel loading and burned area using statistic materials or single satellite data, but much is unknown regarding the emission density and chemical profiles of this important source. We propose to develop and test a near-real-time emission modeling approach based on statistics data and retrievals from multiple geostationary and polar-orbiting satellites. The emission factors of particulate matter from biomass burning will be determined from in-situ measurements during designed biomass burning experiments. Indoor biomass combustion and open field biomass combustion was calculated by statistics data and satellite data, respectively. The temporal and spatial characteristic of biomass burning will be detected by geostationary satellites and polar orbiting satellites, respectively. The satellites also provide fire radiative power data. Fire radiative power is theoretically a function of fire size and fire temperature which is closely relately to brightness temperature observed from satellite thermal bands. Therefore, biomass combustion will be determind by fire radiavive power. Finally, near-real-time emission inventory will be calculated by local emission factors and biomass combustion. Therefore, this study could provide timely update of emissions for air quality forecasting. The results of this research will improve quality of emission inventory of particulate matter from biomass burning, and provide key inputs data to support real-time haze forecasting operations and air quality regulatory research.

生物质燃烧的颗粒物排放是影响当今区域雾霾和气候变化的重要因素。但由于目前本地化排放因子的缺乏和生物质燃烧监测手段的落后，导致生物质燃烧源颗粒物排放清单存在极大的不确定性。特别是在生物质燃烧和雾霾污染严重的东北地区，仅有的少量研究局限在基于统计资料或单一卫星的燃烧量和燃烧面积估算方面，缺乏准确的排放清单。而极轨和静地卫星的综合运用，可准确定位火点位置，明确燃烧时间和燃烧量，实现对生物质燃烧的实时监测。本项目将在前期研究的基础上，实时监测不同燃烧过程，获取本地化的排放因子；综合运用卫星的火产品数据及统计资料，确定各生物质的露天燃烧量和室内燃烧量；编制空气质量预报所急需的每天甚至每小时更新的近实时排放清单。该项目的执行，将大大提高生物质燃烧的污染物排放在时间和空间上的准确性。项目的研究成果，将广泛应用到区域雾霾和空气质量预报系统中，为区域近实时空气质量预报及污染防治提供科学支撑。

生物质燃烧的颗粒物排放是影响当今区域雾霾和气候变化的重要因素。但由于本地化排放因子的缺乏和生物质燃烧监测手段的落后，导致生物质燃烧源颗粒物排放清单存在极大的不确定性。特别是在生物质燃烧和雾霾污染严重的东北地区，仅有的少量研究局限在基于统计资料或单一卫星的燃烧量和燃烧面积估算方面，缺乏准确的排放清单。而极轨和静地卫星的综合运用，可准确定位火点位置，明确燃烧时间和燃烧量，实现对生物质燃烧的实时监测。本项目通过生物质露天燃烧过程实时监测和室内燃烧模拟实验相结合的方法，获取了生物质燃烧源主要大气污染物的本地化排放因子和颗粒物源谱数据，阐明了生物质燃烧的大气污染物排放特征；针对东北地区供暖期长，室内燃烧严重的问题，基于户均燃烧量的算法，编制了东北农村室内燃烧的主要大气污染物排放清单，弥补了当前研究中室内燃烧排放缺乏的问题；针对露天燃烧问题，综合运用极轨卫星和静止卫星的火产品，结合本地化参数，开发了一套生物质燃烧源的近实时排放清单构建算法，编制了空气质量预报所急需的高精度、动态化、近实时的排放清单，实现了生物质燃烧源清单与空气质量模式的无缝对接，解决了空气质量模式中的清单处理问题。项目成果，显著提高了生物质燃烧的污染物排放在时间和空间上的准确性。同时，也可广泛应用到区域雾霾和空气质量预报系统中，为区域近实时空气质量预报及污染防治提供科学支撑。