Particle Nucleation Events in the Ohio River Valley

将采集和分析俄亥俄河谷森林中超细颗粒的时间序列，以量化成核事件和高超细颗粒浓度的频率和特征，包括化学成分、成核的主要机制以及成核和生长的限制。将对当前的数值模型进行评估，以确定它们预测成核和随后颗粒生长的能力。有待检验的具体研究假设包括：1)尽管平均凝结汇相对较高，但成核事件将至少在10%的天数内观察到，最高数量发生在春季；2)以高超细颗粒浓度为特征的事件的空间范围约为数十至数百公里；3)成核发生在林冠上方，所产生的颗粒随后被输送到树冠内和穿过树冠；4)在该位置成核的主要机制是硫酸-水-氨(硫酸、水、氨)的三元成核；5)随后的颗粒增长主要是通过添加生物和人为有机化合物氧化形成的半挥发性有机物；6)对成核的主要物理控制是现有的颗粒表面积(通过冷凝汇表现出来)和紫外线辐射通量；以及7)对成核的主要化学控制是NH3的有效性。该研究的广泛科学影响包括与其他长期数据集的比较分析以量化共性和差异，以及验证和开发用于全球大气化学和气候模式的大气边界层成核预测模型所需的信息。更广泛的影响还包括对研究生和本科生的教育和培训。

A time series of ultra-fine particles in a forest in the Ohio River Valley will be acquired and analyzed to quantify the frequency and characteristics of nucleation events and high ultra-fine particle concentrations, including chemical composition, principal mechanisms of nucleation, and limitations on nucleation and growth. Current numerical models will be assessed for their ability to predict the occurrence of nucleation and subsequent particle growth. Specific research hypotheses to be tested include: 1) Despite a relatively high average condensational sink, nucleation events will be observed on at least 10% of days, with the highest number occurring in spring; 2) The spatial extent of events characterized by high ultra-fine particle concentrations is of the order of tens to hundreds of kilometers; 3) Nucleation occurs above the forest canopy and the resulting particles are subsequently transported into and through the canopy; 4) The principal mechanism of nucleation at this location is ternary nucleation of H2SO4-H2O-NH3 (sulfuric acid, water, ammonia); 5) Subsequent particle growth is principally by addition of semi-volatile organics formed from oxidation of biogenic and anthropogenic organic compounds; 6) The major physical controls on nucleation are existing particle surface area (as manifest through the condensational sink) and UV radiative flux; and 7) The major chemical control on nucleation is NH3 availability.Broader scientific impacts of the research include comparative analyses with other long-term data sets to quantify commonalities and differences, and information necessary to validate and develop predictive models of nucleation in the atmospheric boundary layer for use in global atmospheric chemistry and climate models. The broader impacts also include education and training of graduate and undergraduate students.