Long-term imaging of calcium dynamics using genetically encoded calcium indicators and automatic tracking of cultured cells

© 2018 Future Science. All rights reserved. Calcium dynamics is crucial for many signaling pathways and cell functions. Understanding how calcium regulates cell function often requires long-term imaging of calcium dynamics. Here we report a methodological approach of long-term (5–10 h) imaging of calcium dynamics in cultured cells. The approach links calcium imaging using genetically encoded calcium indicators and semi-automatic tracking of individual cells. It can be used in a large variety of situations, ranging from the role of calcium in biological processes to cell heterogeneity and screening of drugs modifying signaling pathways

Quantification of urban atmospheric boundary layer greenhouse gas dry mole fraction enhancements in the dormant season: Results from the Indianapolis Flux Experiment (INFLUX)

We assess the detectability of city emissions via a tower-based greenhouse gas (GHG) network, as part of the Indianapolis Flux (INFLUX) experiment. By examining afternoon-averaged results from a network of carbon dioxide (CO2), methane (CH4), and carbon monoxide (CO) mole fraction measurements in Indianapolis, Indiana for 2011–2013, we quantify spatial and temporal patterns in urban atmospheric GHG dry mole fractions. The platform for these measurements is twelve communications towers spread across the metropolitan region, ranging in height from 39 to 136 m above ground level, and instrumented with cavity ring-down spectrometers. Nine of the sites were deployed as of January 2013 and data from these sites are the focus of this paper. A background site, chosen such that it is on the predominantly upwind side of the city, is utilized to quantify enhancements caused by urban emissions. Afternoon averaged mole fractions are studied because this is the time of day during which the height of the boundary layer is most steady in time and the area that influences the tower measurements is likely to be largest. Additionally, atmospheric transport models have better performance in simulating the daytime convective boundary layer compared to the nighttime boundary layer. Averaged from January through April of 2013, the mean urban dormant-season enhancements range from 0.3 ppm CO2 at the site 24 km typically downwind of the edge of the city (Site 09) to 1.4 ppm at the site at the downwind edge of the city (Site 02) to 2.9 ppm at the downtown site (Site 03). When the wind is aligned such that the sites are downwind of the urban area, the enhancements are increased, to 1.6 ppm at Site 09, and 3.3 ppm at Site 02. Differences in sampling height affect the reported urban enhancement by up to 50%, but the overall spatial pattern remains similar. The time interval over which the afternoon data are averaged alters the calculated urban enhancement by an average of 0.4 ppm. The CO2 observations are compared to CO2 mole fractions simulated using a mesoscale atmospheric model and an emissions inventory for Indianapolis. The observed and modeled CO2 enhancements are highly correlated (r2 = 0.94), but the modeled enhancements prior to inversion average 53% of those measured at the towers. Following the inversion, the enhancements follow the observations closely, as expected. The CH4 urban enhancement ranges from 5 ppb at the site 10 km predominantly downwind of the city (Site 13) to 21 ppb at the site near the landfill (Site 10), and for CO ranges from 6 ppb at the site 24 km downwind of the edge of the city (Site 09) to 29 ppb at the downtown site (Site 03). Overall, these observations show that a dense network of urban GHG measurements yield a detectable urban signal, well-suited as input to an urban inversion system given appropriate attention to sampling time, sampling altitude and quantification of background conditions

Hestia: Urban scale high resolution fossil fuel CO2 emissions: from Science to Policy

Lunch Session: Innovative Tools for Climate Action Plannin

Quantification of Fossil Fuel CO₂ Emissions on the Building/Street Scale for a Large U.S. City

In order to advance the scientific understanding of carbon exchange with the land surface, build an effective carbon monitoring system, and contribute to quantitatively based U.S. climate change policy interests, fine spatial and temporal quantification of fossil fuel CO₂ emissions, the primary greenhouse gas, is essential. Called the “Hestia Project”, this research effort is the first to use bottom-up methods to quantify all fossil fuel CO₂ emissions down to the scale of individual buildings, road segments, and industrial/electricity production facilities on an hourly basis for an entire urban landscape. Here, we describe the methods used to quantify the on-site fossil fuel CO₂ emissions across the city of Indianapolis, IN. This effort combines a series of data sets and simulation tools such as a building energy simulation model, traffic data, power production reporting, and local air pollution reporting. The system is general enough to be applied to any large U.S. city and holds tremendous potential as a key component of a carbon-monitoring system in addition to enabling efficient greenhouse gas mitigation and planning. We compare the natural gas component of our fossil fuel CO₂ emissions estimate to consumption data provided by the local gas utility. At the zip code level, we achieve a bias-adjusted Pearson <i>r</i> correlation value of 0.92 (<i>p</i> < 0.001)

High‐resolution atmospheric inversion of urban CO2 emissions during the dormant season of the Indianapolis Flux Experiment (INFLUX)

Based on a uniquely dense network of surface towers measuring continuously the atmospheric concentrations of greenhouse gases (GHGs), we developed the first comprehensive monitoring systems of CO2 emissions at high resolution over the city of Indianapolis. The urban inversion evaluated over the 2012–2013 dormant season showed a statistically significant increase of about 20% (from 4.5 to 5.7 MtC ± 0.23 MtC) compared to the Hestia CO2 emission estimate, a state‐of‐the‐art building‐level emission product. Spatial structures in prior emission errors, mostly undetermined, appeared to affect the spatial pattern in the inverse solution and the total carbon budget over the entire area by up to 15%, while the inverse solution remains fairly insensitive to the CO2 boundary inflow and to the different prior emissions (i.e., ODIAC). Preceding the surface emission optimization, we improved the atmospheric simulations using a meteorological data assimilation system also informing our Bayesian inversion system through updated observations error variances. Finally, we estimated the uncertainties associated with undetermined parameters using an ensemble of inversions. The total CO2 emissions based on the ensemble mean and quartiles (5.26–5.91 MtC) were statistically different compared to the prior total emissions (4.1 to 4.5 MtC). Considering the relatively small sensitivity to the different parameters, we conclude that atmospheric inversions are potentially able to constrain the carbon budget of the city, assuming sufficient data to measure the inflow of GHG over the city, but additional information on prior emission error structures are required to determine the spatial structures of urban emissions at high resolution