Archives for posts with tag: greenhouse gases

A while back, I was discussing the many ways that we can monitor greenhouse gases. One of these methods, the inventory method, involves estimating the greenhouse gases from human activity as an associated factor of how much emissions that activity generates. We can check that these estimates make sense in the context of the atmosphere by also taking measurements of greenhouse gases. If we want to do a really good job of checking the inventory estimates, we can apply both the inventories and some greenhouse gas measurements into a specialised transport model. This method is relatively new, and still under development.

In urban areas there are a number of obstacles to taking greenhouse gas measurements and to applying transport models. Firstly, cities are very rough, rather warm and have a lot of very concentrated emissions sources.  The first two issues cause problems for accurately modelling how greenhouse gases are transported up into the atmosphere and also on how easy it is to place an instrument that can be representative of the whole city. We need both of these things to be done well if we are ever to produce results that are accurate enough to help us check our inventories. The third issue is of interest to the discussion here and I am going to focus particularly on CO2 for this. Cities have a lot of fossil fuel CO2 emissions sources such as traffic and local power generation, but they also have a lot of biological sources; such as plants and humans breathing. So the question is, how do we separate out the part of the measured greenhouse gas that comes from the fossil fuels from the background and from the biological sources?

The solution to this issue comes in the form of isotope analysis. In this case we can think of isotopes as a ‘tag’ for different types of CO2.  You might not know this, but actually there are three slightly different types of carbon. Back to basic chemistry for a few moments now.  All atoms are made up of protons, electrons and neutrons. Protons have a positive charge and make up the atom nucleus along with the neutrons which don’t have a charge.  Electrons (negative charge) then buzz around the outside of the nucleus. The protons and the neutrons are what gives the atom most of its mass. Carbon always has 6 protons and 6 electrons to balance the charge. It usually has 6 neutrons too, and this form of Carbon with 6 of each is very stable. It is common and you’d expect to see it everywhere you see Carbon.  But this is not the only type of Carbon there is. Sometimes an atom has more neutrons than it has protons and the more that it has (heavier it gets), the more it tries to decay back down to its stable form. Carbon can have 6, 7 or 8 neutrons. Add that to the 6 protons and you have carbon with a mass of 12, 13 or 14.

 

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Now, because 12 is the stable form and 14 is the unstable form, you might expect that as time goes on, any Carbon 14 that exists will gradually decay away until it becomes Carbon 12.  The time that this takes is called its radioactive half-life.  The half life of Carbon 14 is about 5,730 years. This is important because the reason fossil fuels are called fossil fuels is because they are old, certainly older than 5,730 years. That means that the carbon that is contained in the fossil fuel will have already decayed to its stable form before it is combusted and releases CO2 to the atmosphere. So when we measure the isotopic composition of the carbon in the atmosphere, we can get a quite good indication of the fossil fuel contribution.

To take this a step further, we might want to attribute the fossil fuel we detect to one type of fossil fuel or another. We can do this using a tracer species, commonly carbon monoxide (CO) is used for this. CO is a tracer of ‘incomplete’ combustion, and usually the more incomplete the combustion, the more ‘dirty’ it is in terms of CO2 and air pollutants. We can use the ratio between the CO tracer and the isotopically derived ‘fossil fuel CO2’ to tell us something about how clean the combustion process is likely to have been. For example, a tar pit has a high CO/fossil fuel CO2 ratio of about 20 ppb/ppm, a car has a medium value of about 14 and a clean modern car has a CO/ fossil fuel CO2 ratio or 8 or 9 ppb/ppm. A clean power station has a CO/ fossil fuel CO2 ratio of about 3 ppb/ppm.

If we have an idea of what the CO/ fossil fuel CO2 ratio is in a sample of air, we can use measurements of CO to tell us how much of the total measured CO2 from the same place can be attributed to fossil fuels. This is important for modelling (which tries to estimate the fossil fuel CO2 from inventories) and for improving estimates from the inventories themselves.

I would like to talk about this topic again another time in more detail, as it is a very interesting area of science. Next time at Ground to Sky, I will discuss the balance of science between studying greenhouse gas emissions from natural and urban environments as a point of interest from my recent trip to the European Geosciences Union (EGU) General Assembly in Vienna.

 

After a long hiatus, I have returned to Ground to Sky! I have been very busy, dealing with finalising two research publications and spending every lunchtime in the university music practice rooms but now I am pleased to return to this blog. In this article I will provide a brief discussion of my latest research paper to be published. The (open access) paper is available online here.

The work that I will describe took place during my PhD and was located at West Sedgemoor in the (currently terribly flooded) Somerset Levels and Moors. This land is very low lying, and floods every winter as it is part of the floodplain of the River Parrett. This seasonal cycle creates a unique habitat for wetland birds, and the site is managed by the RSPB for their conservation. West Sedgemoor is a system of small fields that are separated by a series of interconnected drainage ditches. These are managed by the RSPB to ensure that the conditions are always good for wetland birds. Part of the management of West Sedgemoor involves short term grazing during the autumn months by young beef cattle. As part of my study into the greenhouse gas emissions from these seasonally waterlogged peatlands, I was interested to see how the cattle’s urine stimulated production of greenhouse gases inside the soil and their emission as the field went from dry to flooded.

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West Sedgemoor

To measure the greenhouse gas emissions (I was looking at carbon dioxide, CO2, methane, CH4 and nitrous oxide, N2O), I used ‘flux chambers’. These are boxes that are dug into the soil. A lid is put on the box and you wait a while for the gas to accumulate inside the box and take samples during this time. You can then calculate the emission of the gas from the rate of change of the gas inside the box. To measure greenhouse gases in the soil, I used ‘soil atmosphere collectors’. These are silicone tubes that are porous. Air from in the soil moves into these collectors as if they were a large soil pore and you can then take samples from the air inside through a cap accessible from the surface. Dipwells were used to measure the depth of the water-table from the surface.

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Equipment in the field.

Before we could start sampling, we needed some cattle urine. Although cattle were to be loose in the field at the time of sampling, we did not want them getting close to the equipment and actually we didn’t want them to pee near it either! For a controlled experiment, we needed to be sure that every plot (with box, soil atmosphere collector and dipwell) received the same amount of urine. This would be impossible letting the cows loose in the area, so we used urine from cows at the University of Reading farms and fenced the equipment away from the cows in the field. There were ten plots, five to be treated with the urine and five to act as controls and be treated only with water. This allowed us to be sure that it was the urine that caused any changes in the soil and not just the act of the soil getting wet. The experiment ran between September and November in 2010.

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This graph shows the effect of cattle urine and water application on CO2 emissions. There was a large emission of CO2 from the urine treated plots on the day that the cattle urine was applied. This is due to ‘hydrolysis’ of the urea in the urine when it impacts the soil. Bacteria make an enzyme called ‘urease’ which is found very commonly in soils and is catalyses the hydrolysis process. Despite this initial CO2 release, there was not much increase in CO2 due to the urine addition over the full period and there was no significant difference at all in CO2 in the soil atmosphere between urine treated and water treated plots.

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Here we look at the methane in the cattle urine plots and can see there was a substantial reduction in the methane a few days after applying urine. We are not sure what caused this; it is a very unusual finding. It happened in 3 of the 5 urine treated plots and none of the control plots. Overall, however, adding cattle urine increased the amount of methane that came out of the soil during the experiment. As you can see, the control plots remained sinks of methane – that is, soil bacteria were taking methane from the atmosphere and using it to metabolise. This is called methane oxidation. In the plots treated with urine, this activity was prevented as a result of the urine contents. This supports other studies for this is a known effect of adding urea to soils. Under the soil surface there was also evidence of increased methane in the urine treated soil relative to the controls.

n2oThe most profound effect of adding cattle urine to the peat soil was shown for nitrous oxide, N2O. Here we see that throughout the experiment, the urine caused large increase in N2O compared to the control. This peaked 12 days after application, following rainfall. This shows how important soil moisture and water-table can be in determining what happens to added nutrients in soil. Under the soil surface, the differences between control and urine treated plots were even more interesting.

n2oWhen you look at the above figure, notice the numbers on the y axis. On day 2 after the urine was applied, you could already see the difference in production of N2O in the urine treated soils. By the twelth day, the production in the control soils was dwarfed entirely, with production at 20cm depth dominating. By Day 56, the field was entirely flooded and N2O concentrations were very high. We believe that the reason why this happened so strongly at 20cm was due to the fact that the peat soil was covered by a layer of clay. Clay soils, when saturated, are not very good at letting air pass through them and therefore N2O that was produced at levels lower than 20cm, will also get trapped here.

For more information on this experiment, please see the full paper. This is only a short summary of all of the results that were presented there. But what does this mean for managing greenhouse gases in peat soils? Well, N2O and CH4 emissions will get worse after cattle have been on the field and they will get especially worse if the field then floods. This implies that if you are concerned about the greenhouse gas balance of the field, grazing cattle earlier rather than later is likely to reduce the emissions after the field floods. However, there are far more things to balance than just the greenhouse gas emissions; for example, managing the feed supply for the cattle, managing the field grass level and, in the case of RSPB West Sedgemoor, managing the land for wetland birds. Balancing all of these demands and best practice is never an easy task and will require a carefully considered compromise.

I will write again at Ground to Sky shortly, and will attempt to reduce the long time span between blog entries. Next time, I will write about using trace gases to help us to understand where greenhouse gas emissions come from, in particular the use of carbon monoxide as a tracer for fossil-fuel carbon dioxide in cities.

Greenhouse gases are top of the worldwide green agenda and all around the world industrious groups of people are seeking to reduce emissions. Whether by legislating against irresponsible fossil fuel use, encouraging energy efficiency or creating traffic-free zones (and many, many other methods besides), the only way we’ll know whether such schemes are having an effect is by knowing the rate of emission of gases into the atmosphere.  We need to be able to do this to a fine enough level of detail to be able to tell if our reduction strategies are successful or not.

This is no mean feat. The atmosphere is notoriously complicated, as is the land surface with sinks (take up gases) and sources (emitters of gases) springing up all over the place, often as quick as you can count and varying wildly according to environmental conditions.  In spite of these difficulties, scientists, industry and policy have created methodologies and taken steps towards putting some figures on greenhouse gas emission.  There are three main methods, which I will introduce in turn.

1. Emissions inventories.

I like to call this the “let’s just tot up what we know” method.  It relies on accurate figures for the extent of a certain activity (i.e. how many cars there are, how many power stations are running and for how long) and an accurate figure for how much greenhouse gas is emitted by each of these activities. These are called activity data and the emissions factor.

Flux = sum of all (activity data x emissions factor).

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I call this the “tot up what we know” method because all that goes into an inventory is the emissions sources we know about.  They also usually only include human activities or have a subjective or modelled term for natural sources and sinks.  We have several uncertainties in the inventory method and they require extensive checking:

  • is the activity data right? i.e.  is our traffic count up to date?, are the power companies telling the truth about what’s coming out of that chimney?, are we up to date with all of the new houses?
  • are the emissions factors right? i.e. are we simply estimating over a large range of possible values?
  • are we summing up all of the sources we know about? what about the sources that we don’t know about? could we be overestimating the total emissions by ignoring the effect of vegetation uptake?

Because of questions like these, inventories work best in a coarse resolution (over a large area, like a country).  They aren’t checked using measurements and are best for making broad decisions (i.e. cutting back on fossil fuel energy in a certain country) than narrow ones (i.e. implementing a neighbourhood road closure and cycling scheme).

2. Direct measurement.

Measurement of greenhouse gas fluxes can happen at all sorts of scales. From a chamber placed over a square metre of soil right up to an instrument mounted on a tall tower above a city.  For the purpose of this discussion I will focus on these tall tower instruments.  The instrument on the new tower in the drawing below is designed to capture fluxes from a wide area.  So all of those terms that we put in our emissions inventory (plus or minus the influence of the sources/sinks that we ‘forgot’) are contributing to the flux measurement.

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This particular system measures the difference in concentration of greenhouse gas between two vertical air packets (I will come back to how this works some other time).  This tells us the overall flux.

To be able to interpret this, we need to know where the fluxes measured by the instrument are coming from.  That is, we need to know the area of the ground that is sending gas up to be captured by the instrument.  We don’t want to consider sources that aren’t being included in the measurement and likewise we don’t want to miss any.  To do this, we need a ‘source area’ or ‘footprint’ model.  This can calculate the area of ground we can expect the fluxes to be coming from and then we can investigate how they might be influencing this measurement.

Hm, you might think this is a little vague.  You’re right, when it comes to making decisions about changing the number of cars in your city or increasing the amount of green space, it makes sense to be able to tell more exactly where the sources really are and whether or not the action has made a difference to their extent.  But if you want to monitor what the overall flux is over the city, what it really is, through observations rather than approximations, a direct measurement scheme is what you need.

How about a middle ground between the two?  A method that includes all the knowledge we have about what is out there generating greenhouse gases (inventories) plus real greenhouse gas measurements to tell us if we’re going wrong?  This brings me to the final method, which is newest to science and very much still in development.  This is one of the things that is keeping me busy during the working day right now.

3. Measurements + Model (the “inversion” method)

Inversion methodology is where we start to get really clever.  I will explain this step by step.

a. Take the inventories and make it as accurate as you possibly can for your chosen area.

b. Place an instrument on a tower that measures concentrations of greenhouse gases.  (Note: this is concentration not flux.  The instrument tells us what the concentration of gas is, not the change in that concentration).

c. Use a meteorological forecast model to tell you what the winds are doing throughout the surface km of atmosphere.

d. Place the inventories and the wind data (plus some other information such as the height of the boundary layer and the surface roughness) into a chemistry-transport model.  This model can give you an idea of what the concentration of the greenhouse gas in question is EXPECTED to be.

e. (And here’s the clever bit) Use the real data from the atmosphere, plus the expected concentrations and then run the model BACKWARDS.  This “inversion” of the method uses everything we know to ‘go back to source’ and tell us where we should be checking our inventories a little more closely.

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This last method has a lot of potential. But right now it is in its pilot stages.  New science is consistently being published in developing this method and industry is becoming aware of the economic opportunity in providing governments with such a service.

The method that an international group/national govenment/local authority will choose depends on what they wish to get out of the investigation. Benchmark figures? Real measurements? In-depth analysis? Participating in new development of new scientific technology? The future is bright for estimation methodology, so don’t let “how will we even know if it works?” put you off taking your bike to work instead of your car.

In the next article at Ground to Sky, I will be discussing the ups and downs of wading through huge piles of scientific literature and providing some tips from my experience.  Following this I will return to the technical science and will be discussing some of the methods that we can use to cool down our hot cities during the summer months, without compromising winter warmth.