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Development of a fast, urban chemistry metamodel for inclusion in global models

机译:开发快速,城市化学元模型,包括在全球模型中

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A reduced form metamodel has been produced to simulate the effects of physical, chemical, and meteorological processing of highly reactive trace species in urban areas, which is capable of efficiently simulating the urban concentration, surface deposition, and net export flux of these species. A polynomial chaos expansion and the probabilistic collocation method have been used to develop the metamodel, and its coefficients, so that it is applicable under a broad range of present-day and future conditions. The inputs upon which this metamodel have been formed are based on a combination of physical properties (average temperature, diurnal temperature range, date, and latitude), anthropogenic properties (patterns and amounts of emissions), and the nature of the surrounding environment (background concentrations of species). The metamodel development involved using probability distribution functions (PDFs) of the inputs to run a detailed parent chemical and physical model, the Comprehensive Air Quality Model with Extensions (CAMx), thousands of times. Outputs from these runs were used in turn to both determine the coefficients of and test the precision of the metamodel, as compared with the detailed parent model. It was determined that the deviations between the metamodel and the parent mode for many important species (O3, CO, NOx, and black carbon (BC)) were found to have a weighted RMS error less than 10 % in all cases, with many of the specific cases having a weighted RMS error less than 1 %. Some of the other important species (VOCs, PAN, OC, and sulfate aerosol) usually have their weighted RMS error less than 10 % as well, except for a small number of cases. In these cases, the complexity and non-linearity of the physical, chemical, and meteorological processing is too large for the third order metamodel to give an accurate fit. Finally, sensitivity tests have been performed, to observe the response of the 16 metamodels (4 different meteorologies and 4 different urban types) to a broad set of potential inputs. These results were compared with observations of ozone, CO, formaldehyde, BC, and PM10 from a few well observed urban areas, and in most of the cases, the output distributions were found to be within ranges of the observations. Overall, a set of efficient and robust metamodels have been generated which are capable of simulating the effects of various physical, chemical, and meteorological processing, and capable of determining the urban concentrations, mole fractions, and fluxes of species, important to human health and the global climate.
机译:已经制作了一种缩减的形式元模型,以模拟物理,化学和气象加工在城市地区的高度反应性痕量物种的影响,这能够有效地模拟这些物种的城市浓度,表面沉积和净出口通量。多项式混沌扩展和概率搭配方法已被用于开发元模型及其系数,以便在广泛的当前和未来条件下适用。已经形成该元素的输入基于物理性质(平均温度,昼夜温度范围,日期和纬度),人为性质(排放量和量)的组合,以及周围环境的性质(背景物种浓度)。使用输入的概率分布函数(PDF)涉及使用输入的概率分布函数(PDF)来运行详细的母体化学和物理模型,具有延伸(CAMX),千万次的综合空气质量模型。与详细的父模型相比,这些运行的输出反向依次确定元模型的精度和测试元素的精度。据发现,在所有情况下,发现在许多重要物种(O 3,Co,NOx和黑碳(BC)之间的偏差和母体模式的偏差在所有情况下具有小于10%的加权RMS误差具有重量rms误差小于1%的具体情况。除了少量病例外,还有一些其他重要的物种(VOCS,PAN,OC和硫酸盐气溶胶)通常也具有小于10%的加权RMS误差。在这些情况下,物理,化学和气象处理的复杂性和非线性对于第三阶Metamodel来说太大了,以准确拟合。最后,已经进行了灵敏度测试,以观察16个元晶型(4种不同的象室和4种不同城市类型)的响应到广泛的潜在输入。将这些结果与臭氧,CO,甲醛,BC和PM10的观察结果进行了比较,来自几个良好的城市地区,在大多数情况下,发现产出分布在观察结果范围内。总的来说,已经产生了一组高效且稳健的元晶片,其能够模拟各种物理,化学和气象处理的影响,并能够确定城市浓度,摩尔分数和物种的势态,对人类健康很重要全球气候。

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