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Measurements and Analyses of Urban Metabolism and Trace Gas Respiration

Research and Teaching Output of the MIT Community

Show simple item record McManus, J.B. Shorter, J.H. Zahniser, M.S. Kolb, C.E. O’Neill, S.M. Stock, D. Napelenok, S. Allwine, E.J. Lamb, B.K. Scheuer, E. Talbot, R.W. San Martini, F. Adamkiewicz, G. LiPun, B.K. Wang, C. McRae, G.J. Cao, L. Ismail, A.A. Kawabata, M. Yeang, C-H. Narasimhan, G. Humbad, S. Zhang, M. Ferreira, J. Jr 2006-07-20T20:34:52Z 2006-07-20T20:34:52Z 2002-05-30
dc.identifier.govdoc NASA ARI No. RR-1330
dc.description Final Report on NASA ARI Contract No. 10066. en
dc.description.abstract Human society has well defined metabolic processes that can be characterized and quantified in the same way that an ecosystem’s metabolism can be defined and understood [Fischer-Kowalski, 1998.] The study of “industrial metabolism” is now a well-established topic, forming a key component of the emerging field of industrial ecology [Ayres and Simmonis, 1994; Fischer-Kowalski and Hüttler, 1998]. The fact that the metabolism of cities can be analyzed in a manner similar to that used for ecosystems or industries has long been recognized [Wolman, 1965.] However, the increasingly rapid pace of urbanization and the emergence of megacities, particularly in the developing world, lends increased urgency to the study of “urban metabolism.” A recent review by Decker et al. [2000] surveys energy and materials flow though the world’s twenty-five largest metropolitan areas. In 1995 these cities had populations estimated to range between 6.6 and 26.8 million people; all are expected to exceed 10 million by 2010. Urban metabolism, driven by the consumption of energy and materials, cannot take place without respiration. Both combustion based energy sources and the human and animal populations of cities consume atmospheric oxygen and expire carbon dioxide as well as a range of other trace gases and small particles. While the detail content of these urban emissions are generally not well known, there is no doubt that they are large and varied [Decker et al., 2000.] There is growing recognition that airborne emissions from major urban and industrial areas influence both air quality and climate change on scales ranging from regional up to continental and global. Urban/industrial emissions from the developed world, and increasingly from the megacities of the developing world change the chemical content of the downwind troposphere in a number of fundamental ways. Emissions of nitrogen oxides (NOx), CO and volatile organic compounds (VOCs) drive the formation of photochemical smog and its associated oxidants, degrading air quality and threatening both human and ecosystem health. On a larger scale, these same emissions drive the production of ozone (a powerful greenhouse gas) in the free troposphere, contributing significantly to global warming. Urban and industrial areas are also large sources of the major directly forcing greenhouse gases, including CO2, CH4, N2O and halocarbons. Nitrogen oxide and sulfur oxide emissions are also processed to strong acids by atmospheric photochemistry on regional to continental scales, driving acid deposition to sensitive ecosystems. Direct urban/industrial emission of carbonaceous aerosols is compounded by the emission of copious amounts of secondary aerosol precursors, including: NOx, VOCs, SO2, and NH3. The resulting mix of primary (directly emitted) and secondary aerosols is now recognized to play an important role in the climate of the Northern Hemisphere. What is less widely recognized is the poor state of our knowledge of the magnitudes, and spatial and temporal distributions, of gaseous and aerosol pollutants from urban/industrial areas. While most cities in the developed world do have a few continuous fixed site monitoring stations measuring point concentrations of regulated air pollutants; these measurements very poorly constrain the patterns of pollutant measurements from the urban area as a whole. Most cities in the developing world lack even these relatively sparse routine measurements. Air quality agencies in the developed world have assembled urban/industrial emissions inventories for some key pollutants, most notably NOx, CO, some VOCs, SO2, and some primary aerosols such as soot and particulate lead. However, far too often these emission inventories are based on engineering estimates rather than measured emissions. In addition, they often miss or poorly quantify smaller fixed sources, mobile sources (motor vehicles, trains, boats, aircraft) and area sources like landfills. Emissions inventories in developing countries, where they exist, are often based on dubious extrapolations of those used for cities in the developed world. This sad state of affairs is a serious problem. First, it is difficult to predict the impact of poorly defined emissions and pollutant distributions on urban air quality and its impact on citizen’s health and local ecosystem viability. Second, since the atmospheric chemistry which drives processes like ozone or secondary aerosol production is highly nonlinear, the impact of urban/industrial emissions on larger scales cannot be predicted without a relatively accurate and detailed knowledge of the temporal and spatial distributions of their precursors. Since “business as usual” is doing a poor job of specifying the real distributions of urban/ industrial atmospheric pollutants, new tools and techniques need to be developed to more easily and accurately quantify these emissions and allow accurate prediction of their subsequent chemical transformations and transport to larger scales. Our NASA Earth Science Enterprise funded Urban Metabolism and Trace Gas Respiration Project is an effort to better understand the distribution and emission patterns of pollutants in urban areas. The project took place between February, 1997 and October, 2001 as an Interdisciplinary Science (IDS) investigation associated with the Earth Observing System (EOS) project. It involved a highly interdisciplinary collaboration between five research teams from the Center for Atmospheric and Environmental Chemistry at Aerodyne Research, Inc. (ARI), the Departments of Chemical Engineering and Urban Studies and Planning at the Massachusetts Institute of Technology (MIT), the Institute of Earth, Oceans, and Space at the University of New Hampshire (UNH), and the Laboratory for Atmospheric Research at Washington State University (WSU). The team included physicists, physical chemists, and environmental engineers expert in atmospheric measurement techniques, chemical and environmental engineers skilled in developing and utilizing models of atmospheric chemistry and dynamics, and urban planners with a research focus on the development of geographical information systems (GIS) and their innovative use in mapping and intercomparing urban characteristics, including pollutant distributions. Graduate students from MIT, UNH, and WSU were involved in both the measurement and modeling/analyses portions of the project. Airborne platforms featuring fast response sensors have previously been deployed, with dramatic effect, to measure stratospheric and free tropospheric processes (e.g. Anderson et al., 1989) and even to follow urban emission plumes to quantify downwind pollution evolution [Trainor et al., 1995; Nunnermacker et al., 1998]. Components of our team have also used ground vehicles equipped with fast response trace gas sensors to quantify methane emissions from urban (and rural) components of natural and town gas systems, urban landfills, and sections of towns and cities [Lamb et al., 1995; Mosher et al, 1999; Shorter et al., 1996; 1997]. However, mobile fast response sensors had not been used previously to characterize multi-pollutant distributions and source emissions within urban areas. For this project we proposed to develop, deploy and demonstrate better urban atmospheric measurement techniques based on sensitive, accurate, real-time trace gas and particulate sensors onboard a ground mobile platform (a mobile laboratory.) We anticipated that the deployment of real-time (~1s response) sensitive and specific trace pollutant instruments in a mobile laboratory would generate a wealth of data on the distribution of both urban ambient pollutant levels and the distribution and nature of both mobile and stationary (including point and area) emission sources. As proposed, we first tested our instrumented mobile laboratory in two field missions in Manchester, NH a compact urban area with a population of ~100,000 well isolated from other urban centers. We then deployed our mobile laboratory in a intensive campaign in Boston, MA at the center of a metropolitan area with ~3 million people. These field programs allowed us to learn how to effectively deploy real-time mobile instruments in a major urban area and gain valuable data on pollutant distributions and emission sources. Our field measurement tools and strategies are presented in Section 2 of this report and an overview of the urban field measurement data we obtained is presented in Section 3. Since our real-time mobile measurements would generate copious amounts of data, a key programmatic goal was to develop the data reduction and analysis methods that would allow us to learn the most about pollutant distributions and emission sources. Further, since we proposed to develop novel methods of investigating urban gaseous polluant and fine particle emissions and distributions, we planned that analyses and evaluations of our initial field measurements would be used to design better measurement strategies to collect and analyze trace gas and fine particle concentration and flux data. In order to analyze experimental strategies and field measurement data the MIT and WSU groups have used state-of-the-art air quality models and developed new model analysis techniques. The WSU team developed a two component approach to model the turbulent atmospheric dynamics over urban landscapes. First, they used the Environmental Protection Agency’s (EPA’s) state-of-the-art MM5 model to provide a mesoscale model of the regional wind field and then applied TEMPEST, a 3-d turbulence model developed at the Pacific Northwest National Laboratory (PNNL) that simulates the actual urban landscape. WSU also developed a capability for predicting the downwind urban pollution footprint by combining MM5 computed windfields, MCIP, the meteorological processor from EPA’s Models-3/CMAQ model to invert the windfields, and the CALPUFF plume dispersion model. MIT used the MM5 windfields generated by WSU to test urban scale diffusion models by analyzing SF6 tracer release experiments performed as part of our Boston field campaign. In addition, the MM5 output was used to input the California Institute of Technology (CIT) air quality model to assist in analyses of the ozone and NOx trace gas distributions measured in Boston. Finally, MIT investigated the use of air quality model inversion techniques to determine how well spatial emissions distributions can be deduced from measured urban pollutant distributions. The project also involved the novel use of geographic information systems (GIS) and urban databases to correlate observed trace gas emission fluxes (urban respiration) with urban and industrial activity and consumption factors (urban metabolism). Finally, correlations between measured trace gas emissions and urban/industrial activity/ consumption factors are used to identify parameters accessible to air- and satellite-borne remote sensing systems in order to enable automated estimates of urban and industrial trace gas emissions relevant to global change and regional pollution issues. en
dc.description.sponsorship National Aeronautic and Space Administration, en
dc.format.extent 18423808 bytes
dc.format.mimetype application/msword
dc.language.iso en_US en
dc.publisher NASA en
dc.relation.ispartofseries RR-1330 en
dc.subject urban metabolism en
dc.subject GIS en
dc.subject trace gas respiration en
dc.subject land use impacts en
dc.subject atmospheric models en
dc.subject air quality measurement en
dc.subject mobile laboratory en
dc.subject urban emissions en
dc.title Measurements and Analyses of Urban Metabolism and Trace Gas Respiration en
dc.type Technical Report en
dc.identifier.citation NASA ARI Report No. RR-1330, ARI Contract no 10066 en

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