Atmospheric co2 infrared background investigation

mas at atmospheric pressure and temperatures up to K. A microwave temperature measurement, tube effects, CO2 infrared radiation. 1. The aim of the present study is to measure emission spectra from gases produced .. be subtracted from the measured intensity to adjust the signal background.
Table of contents

We look for a transition in the CO 2 value as tank air reaches the analyzer, displacing the atmospheric air that was in the optical cell. To determine O 2 in these calibration runs, we calculate difference-of-difference values for each pair of changeover blocks as with our atmospheric data. Then, based on the timing of the transition in the CO 2 record, we average the last three, four, or five difference-of-difference values of the calibration run. In this case, we average three difference-of-difference pairs, corresponding to the last 2.

To determine CO 2 , we average all CO 2 values collected at the same times as the values that were used in the O 2 calculation. Thus it is on these scales that we report our measurements. Our focus in this paper is on the local biotic exchange ratio, as expressed in a series of short-term averages of CO 2 and O 2 covariation.

Atmospheric methane

To determine this instrumental precision, we use runs of calibration tanks see Sect. These are the values plotted in Fig. Not surprisingly, the performance of the instrument varies over time. At times, we could link a loss of precision to problems with an individual analyzer, while on other occasions, we found water liquid or solid in the system to be the cause.

The source of the major degradation in the precision of both analyzers that develops in late and persists until the end of our dataset remains under investigation. An alternative approach, and the one that we adopt here, uses the observed scatter in the difference of paired standard tanks that were run immediately following one another. The scatter in the HS—LS difference is a conservative estimate of uncertainty in atmospheric data because it includes any variability that might be introduced by operation of the gas-selection valve, a valve that remains fixed in position during atmospheric sampling.

Each HS and LS O 2 value was typically the average from three difference-of-difference pairs, while the CO 2 values were usually an average of 60 measurements.

Thus, the atmospheric measurements should have uncertainties given by. Our choice to work backwards from the observed scatter in HS—LS pairs may not be the optimal technique for extracting uncertainties, but we are confident it yields O 2 and CO 2 errors that bear the correct relative size. Thus, we use the value listed above when calculating slopes in our Deming regressions Sect. The record is approximately continuous until the middle of , when a series of hardware failures, due in part to a lightning strike, caused an extended hiatus in data collection.

Measurements resumed in May and continued without interruption through the end of that year, when failure of the oxygen analyzer led to a suspension of data collection.

Measurements of O 2 and CO 2 for the entire period of record are shown in Fig. The values shown here were derived from the raw data using the calibration runs and the algorithm described in Sect. In these figures we can see a very gradual rise in CO 2 and drop in O 2 mainly due to fossil fuel combustion , a strong diel cycle with inverse variation in CO 2 and O 2 , and a great deal of variability on a range of timescales. Results from the upper and lower intakes are quite similar, but not identical.

The data have been processed Sect. This is simply one example of the diel cycle of these species. Note the strict inverse variation in O 2 and CO 2 , even when there are large deviations from a smooth temporal evolution.

It's Official: Atmospheric CO2 Just Exceeded ppm For The First Time in Human History

While these records contain a wealth of information, our particular focus is on the covariation in O 2 and CO 2. We expect to see different results from the high and low intakes, particularly at night. The lower intake is more likely to show stronger influences of soil and canopy fluxes, particularly at night when the atmosphere is more stable and the surface layer is more likely to be decoupled from the planetary boundary layer.

For this reason, we separate the data from the high and low intakes, create day and night subsets for each intake, plot O 2 vs. These intervals are chosen to be times of maximal and minimal coupling day and night, respectively between the air within and above the canopy.

1. Introduction

Subsets with fewer than three measurements are ignored. Of the fits, only 50 had any outliers and only 11 of these required more than one iteration to converge. Representative plots and fits are shown in Fig. Errors on the slopes are purely statistical. Since we seek a representative slope value for each high—low day—night subset, we choose to limit the impact of these outliers by performing an iterative calculation of the means.

The dashed—dotted lines indicate the shape expected for a purely Gaussian distribution. In the interests of clarity, we omit five points with extremely large or small slopes from a. Thus, we expect air masses exposed to both types of fluxes will evolve with intermediate slopes.

Within this conceptual framework, a successful effort to extract LBER from the data depends on the relative sizes of the biogenic and anthropogenic fluxes. Only at times when photosynthesis and respiration dominate the land—air fluxes will observed slopes be close to LBER. To test these assertions, we first use a Lagrangian transport model to estimate the region over which surface fluxes influence signals at our sampling site. We then use a simple one-dimensional box model to establish the validity of the end-member mixing framework.

Finally, we estimate the relative size of the biogenic and anthropogenic contributions. An example of one such set of trajectories is shown in Fig. State lines for New Hampshire, Vermont, and Massachusetts are in gray. On this particular night, the source region was fairly constant, so changes in O 2 and CO 2 are relatively likely to be primarily due to local influences. In 30 of these time steps the parcels exchange CO 2 and O 2 with the underlying sources and sinks, changing the composition of the parcel according to.

For h we use one-half of the planetary boundary layer PBL height. The O 2 surface fluxes were derived from the CO 2 fluxes by assuming exchange ratios of 1. Air above this height is closely matched to the composition of the free troposphere. We emphasize that the purpose of the 1-D model is to explore the validity of the end-member mixing approach. In particular, we ask whether a mix of sources will relate simply to a mix of slopes, despite the fluxes and the box height having their own diel cycles.

In all but a few special circumstances, the model predicts slopes that are completely consistent with the specified admixture of the source fluxes over which the air parcels have traveled. Exceptions arise when the covariation in the boundary layer height and diel cycles in the fluxes conspire to bias slopes by a few percent. Though reassuring, we acknowledge the model results are not definitive due to the many simplifications involved. More sophisticated studies are needed to give a truly robust confirmation of the end-member mixing framework.

Aside from the slopes, the full range of O 2 and CO 2 variability predicted by the model is in the general range of our observations. Because of the crude nature of our model, this result is somewhat surprising. Our values for the box height and the molar volume are almost certainly wrong, so the data—model agreement may be coincidental.

Journal list menu

Inspection of a subset of the fits failing the cut shows they are indeed poor fits, as defined above. While the cut does not catch all poor slopes, we believe the slopes that are cut are poor ones. We emphasize that this all-inclusive average slope is not a direct measurement of the LBER. Instead, it is a measure of the LBER mixed with the exchange ratio of fossil fuel combustion. These slopes average - 1. We begin with data aggregated in broad categories.

These groupings convey some unequivocal messages: summer slopes are less negative than winter slopes. Day slopes are less negative than night slopes.

Wide Assortment of Measurement Functions

Low-intake slopes are less negative than high-intake slopes.