Greenhouse gas observations from the Northeast Corridor tower network

Karion, A.; Callahan, William J.; Stock, Michael; Prinzivalli, Steve; Verhulst, K. R.; Kim, Jooil; Salameh, Peter K.; López-Coto, I.; Whetstone, J. R.

doi:10.5194/essd-12-699-2020

Cited by 33 publications

(30 citation statements)

References 44 publications

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“…Locations were determined by network design studies (Lopez-Coto et al, 2017;Mueller et al, 2018). Details on the atmospheric CO2 and CH4 mole fraction measurements from this network are found in Karion et al (2020). In this study we use observations from the six urban sites in Figure 1, as we focus on November 2016 through October 2017, when only these six had been established.…”

Section: Definition Of Domain and Backgroundmentioning

confidence: 99%

“…CO2 was chosen rather than CH4 because we believe we have a relatively realistic flux field to use for CO2, whereas for CH4, we find large differences between model estimates and observations. In particular, BUC is in an area with a large influence of local wetlands (Karion et al, 2020), so that the synthetic experiment would not yield necessarily realistic results without an accurate wetland model. The same-day afternoon sampling of CO2 is also more likely to be a problem due to strong biospheric fluxes in summer influencing observed concentrations at the background station; whether the column method alleviates this issue was a key question to answer with the synthetic experiment.…”

Section: Synthetic Experiments Evaluation Of Upwind Observation-based Co2 Backgroundsmentioning

confidence: 99%

“…The goal of this study is to construct and evaluate a background for the Northeast Corridor Washington DC/Baltimore towerbased urban network described in Karion et al (2020). We investigate many of the methods mentioned above, with some exceptions: we do not investigate the baseline/remote station, the low-percentile, or the optimized background methods.…”

Section: Introductionmentioning

confidence: 99%

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Comment on acp-2020-1256

Barkley¹

2021

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As city governments take steps towards establishing emissions reduction targets, the atmospheric research community is increasingly able to assist in tracking emissions reductions. Researchers have established systems for observing atmospheric greenhouse gases in urban areas with the aim of attributing greenhouse gas concentration enhancements (and thus, emissions) to the region in question. However, to attribute enhancements to a particular region, one must isolate the component of the observed concentration attributable to fluxes inside the region by removing the background, which is the component due to fluxes outside. In this study, we demonstrate methods to construct several versions of a background for our carbon dioxide and methane observing network in the Washington, DC and Baltimore, MD metropolitan region. Some of these versions rely on transport and flux models, while others are based on observations upwind of the domain. First, we evaluate the backgrounds in a synthetic data framework, then we evaluate against real observations from our urban network. We find that backgrounds based on upwind observations capture the variability better than model-based backgrounds, although care must be taken to avoid bias from biospheric carbon dioxide fluxes near background stations in summer. Model-based backgrounds also perform well when upwind fluxes can be modeled accurately. Our study evaluates different background methods and provides guidance determining background methodology that can impact the design of urban monitoring networks.

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Section: Definition Of Domain and Backgroundmentioning

confidence: 99%

Section: Synthetic Experiments Evaluation Of Upwind Observation-based Co2 Backgroundsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comment on acp-2020-1256

Barkley¹

2021

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“…Further details about the stations, calibration and quality control can be found in Karion et al (2020). CO 2 enhancements were computed subtracting from each hourly observation, the measurements at the background tower (BUC) similarly to other work in urban areas (Lauvaux et al (2016) Both ceilometers use an InGaAs laser diode with a 910 nm wavelength.…”

Section: ) Co 2 Measurementsmentioning

confidence: 99%

Assessment of Planetary Boundary Layer Parameterizations and Urban Heat Island Comparison: Impacts and Implications for Tracer Transport

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et al. 2020

Journal of Applied Meteorology and Climatology

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Accurate simulation of planetary boundary layer height (PBLH) is key to greenhouse gas emission estimation, air quality prediction and weather forecasting. This manuscript describes an extensive performance assessment of several Weather Research and Forecasting (WRF) model configurations where novel observations from ceilometers, surface stations and a flux tower were used to study their ability to reproduce planetary boundary layer heights (PBLH) and the impact that the urban heat island (UHI) has on the modeled PBLHs in the greater Washington, D.C. area. In addition, CO2 measurements at two urban towers were compared to tracer transport simulations. The ensemble of models used 4 PBL parameterizations, 2 sources of initial and boundary conditions and 1 configuration including the building energy parameterization (BEP) urban canopy model. Results have shown low biases over the whole domain and period for wind speed, wind direction and temperature with no drastic differences between meteorological drivers. We find that PBLH errors are mostly positively correlated with sensible heat flux errors, and that modeled positive UHI intensities are associated with deeper modeled PBLs over the urban areas. In addition, we find that modeled PBLHs are typically biased low during nighttime for most of the configurations with the exception of those using the MYNN parametrization and that these biases directly translate to tracer biases. Overall, the configurations using MYNN scheme performed the best, reproducing the PBLH and CO2 molar fractions reasonably well during all hours, thus opening the door to future nighttime inverse modeling.

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“…A lowest percentile method has also been used as background, e.g., the lowest 5 % of measurements during a certain time period, or a network-wide minimum value (Shusterman et al, 2016;Ammoura et al, 2016). In many studies, observations from a station that is upwind given daily meteorological conditions are used for background (Xueref-Remy et al, 2018;Lauvaux et al, 2016;Breon et al, 2015;Balashov et al, 2020), most often using observations from the same time of day as the urban station. A recent study of carbon dioxide (CO 2 ) in Boston used a more complex back-trajectory-based method to sample the upwind station (Sargent et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Background conditions for an urban greenhouse gas network in the Washington, DC, and Baltimore metropolitan region

et al. 2021

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Abstract. As city governments take steps towards establishing emissions reduction targets, the atmospheric research community is increasingly able to assist in tracking emissions reductions. Researchers have established systems for observing atmospheric greenhouse gases in urban areas with the aim of attributing greenhouse gas concentration enhancements (and thus emissions) to the region in question. However, to attribute enhancements to a particular region, one must isolate the component of the observed concentration attributable to fluxes inside the region by removing the background, which is the component due to fluxes outside. In this study, we demonstrate methods to construct several versions of a background for our carbon dioxide and methane observing network in the Washington, DC, and Baltimore, MD, metropolitan region. Some of these versions rely on transport and flux models, while others are based on observations upwind of the domain. First, we evaluate the backgrounds in a synthetic data framework, and then we evaluate against real observations from our urban network. We find that backgrounds based on upwind observations capture the variability better than model-based backgrounds, although care must be taken to avoid bias from biospheric carbon dioxide fluxes near background stations in summer. Model-based backgrounds also perform well when upwind fluxes can be modeled accurately. Our study evaluates different background methods and provides guidance in determining background methodology that can impact the design of urban monitoring networks.

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Greenhouse gas observations from the Northeast Corridor tower network

Cited by 33 publications

References 44 publications

Comment on acp-2020-1256

Comment on acp-2020-1256

Assessment of Planetary Boundary Layer Parameterizations and Urban Heat Island Comparison: Impacts and Implications for Tracer Transport

Background conditions for an urban greenhouse gas network in the Washington, DC, and Baltimore metropolitan region

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