Collaborative Research: Evaluation of a Coupled Meteorology-Chemistry Model Against Long-term Measurements of Elemental Carbon and Sulfate for Regional Climate Applications
Collaborative Research: Evaluation of a Coupled Meteorology-Chemistry Model Against Long-term Measurements of Elemental Carbon and Sulfate for Regional Climate Applications
批准号:
0612640
负责人:
Liaquat Husain
金额:
$18.44万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-10-01 至 2010-03-31
中文摘要
本研究项目的主要目标是:(1)确定在两个不同年份的夏季和冬季,在纽约州Mayville和纽约州Whiteface Mt下风向约530 km处收集的存档过滤器中的元素碳浓度{EC};以及(2)使用这些数据来评估PI Shankar开发的用于颗粒物化学和传输的耦合气象学-化学模型,臭氧及其前体,以及它们对大气动力学的辐射反馈。该项目的动机是这样一个事实,即颗粒黑碳(BC),在测量中被视为等同于EC,是太阳辐射的强吸收剂,并被认为占全球变暖估计的15-30%,仅次于温室气体;然而,这种对气候的强迫程度是高度不确定的。气溶胶BC的停留时间约为一周,因此它可以在去除之前旅行数千公里;因此其浓度取决于与排放源的距离。可靠的估计辐射的影响在美国从附近和远程来源的BC关键取决于获得区域代表性的测量。PI将测定1998年和2002年在Whiteface Mt夏季每6 h采集一次、冬季每48 h采集一次以及同年在Mayville每24 h采集一次的过滤器中的{EC}。此外,已经确定了{SO 4},并在这段时间内对这两个地点的臭氧进行了实时测量。先前的研究表明,EC和SO 4测量从这两个网站是区域代表性和高度相关的已知进口的逆风气团。测量结果将用于评估METCHEM(METERMS ology-CHEMICAL),该模型将第五代宾夕法尼亚州立大学/国家大气科学中心(NCAR)中尺度模型(MM 5)的中尺度气象学与多尺度空气质量模拟平台(MAQSIP)模拟的颗粒物和气相物种化学和运输算法动态耦合。最终目的是模拟它们对大气动力学的辐射反馈。在观测点进行嵌套的大陆到区域到地方尺度的模拟将使PI能够检查远距离传输和网格细化对模型预测的影响。模型对排放量增长和控制的敏感性,以及对野火和风沙等来源代表性的连续改进的敏感性,将使用输入数据中的三种不同排放清单进行检查。该项目将建立在现有的NSF资助的测量和建模项目的基础上,并增强这两个PI正在执行的项目。它将有助于评估一个模型,用于预测下风向的负担和气候影响的EC和其他排放的化石燃料消费。经过评估的模型及其生成的数据集将为科学界提供有价值的工具,以阐明这些排放对气候的影响。该项目的成果将成为博士学位的基础。纽约州立大学奥尔巴尼分校的一名学生的论文以及北卡罗来纳大学环境项目的入门级建模人员的参与也将促进新研究人员的培训。最后,方案执行机构和协调机构的积极作用将扩大在性别和地域方面代表性不足的群体在这一领域的参与。
英文摘要
The primary objectives of this research project are to: (1) determine the elemental carbon concentrations, {EC}, in archived filters collected at Mayville, NY, and ~530 km downwind at Whiteface Mt, NY, for a summer and a winter month in two different years; and (2) to use these data to evaluate a coupled meteorology-chemistry model developed by PI Shankar for the chemistry and transport of particulates, ozone and their precursors, and their radiative feedbacks to the atmospheric dynamics. The project is motivated by the fact that particulate black carbon (BC), which is treated equivalent to EC in the measurements, is a strong absorber of solar radiation, and thought to account for ~15-30% of global warming estimates, next only to greenhouse gases; however, the magnitude of this forcing on climate is highly uncertain. Aerosol BC has a residence time of about a week so it can travel thousands of kilometers before removal; thus its concentrations are dependent on the distance from emission sources. Reliable estimation of the radiative impacts in the U.S. from nearby and remote sources of BC depends critically on obtaining regionally representative measurements. The PIs will determine the {EC} in filters collected every 6 h during summer and every 48 h during the winter of 1998 and 2002 at Whiteface Mt, and every 24 h at Mayville for the same years. In addition, {SO4} have already been determined, and real-time measurements of ozone are available for both the sites for the duration. Prior studies have shown EC and SO4 measurements from these two sites to be regionally representative and highly correlated with known import of upwind airmasses. The measurements will be used to evaluate METCHEM (METeteorology-CHEMistry), a model that dynamically couples the mesoscale meteorology of the Fifth Generation Penn State/National center for Atmospheric Sciences (NCAR) Mesoscale Model (MM5) with algorithms for particulates and gas-phase species chemistry and transport simulated by the Multiscale Air Quality Simulation Platform (MAQSIP). The ultimate purpose is to simulate their radiative feedbacks to the atmospheric dynamics. Nested continental- to-regional- to-local-scale simulations over the observational sites will allow the PIs to examine the effects of long-range transport and grid refinement on the model predictions. The model sensitivity to emissions growth and control, and to successive improvements in the representation of sources such as wild fires and wind-blown dust will be examined using three different emission inventories in the input data. The project will build upon, and augment current NSF-funded measurement and modeling projects being performed by both PIs. It will help evaluate a model used to predict the downwind burden and climate impacts of EC and other emissions from fossil fuel consumption. The evaluated model and the datasets it generates will provide tools of value to the scientific community in illuminating the impacts of these emissions on climate. The results from this project will be the basis for the Ph.D. dissertation of a student at SUNY, Albany, and participation by entry-level modelers at the University of North Carolina-Carolina Environmental Program will also foster training of new researchers. Finally, the active roles of the PIs and Co-Is will broaden participation by groups underrepresented in gender and geography in this field.
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Lake Sediments as Records of Atmospheric Elemental Carbon, ~1900 to 2014
-
批准号:1523405
-
项目类别:Continuing Grant
-
资助金额:$15.13万
-
财政年份:2015
-
负责人:Liaquat Husain
-
依托单位:
Collaborative Research: Sources of Black Carbon, Methane Sulfonic Acid, and Other Particulate Constituents over 45 Years in the Arctic
-
批准号:1523406
-
项目类别:Continuing Grant
-
资助金额:$4.33万
-
财政年份:2015
-
负责人:Liaquat Husain
-
依托单位:
Lake Sediments as Records of Atmospheric Elemental Carbon, ~1900 to 2014
-
批准号:1063323
-
项目类别:Continuing Grant
-
资助金额:$25.63万
-
财政年份:2011
-
负责人:Liaquat Husain
-
依托单位:
Collaborative Research: Sources of Black Carbon, Methane Sulfonic Acid, and Other Particulate Constituents over 45 Years in the Arctic
-
批准号:1007261
-
项目类别:Continuing Grant
-
资助金额:$27.39万
-
财政年份:2010
-
负责人:Liaquat Husain
-
依托单位:
Long-Term Trends (~1850 - 2007) of Atmospheric Elemental Carbon Concentrations: Measurements and Comparison with Model Estimates
-
批准号:0503850
-
项目类别:Standard Grant
-
资助金额:$14.37万
-
财政年份:2005
-
负责人:Liaquat Husain
-
依托单位:
Application of a Tracer Technique to Study Sulfur Dioxide Oxidation in Cloud Drops as a Function of Drop Size
-
批准号:9712436
-
项目类别:Standard Grant
-
资助金额:$17.87万
-
财政年份:1997
-
负责人:Liaquat Husain
-
依托单位:
国内基金
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