Narrator: The following presentation is part
of the agronomy and horticulture seminar series
at the University of Nebraska Lincoln.
Patricio: It is my great pleasure today
to introduce my colleague, Eri Saikawa.
Eri is an associate professor
in the Department of Environmental Sciences
and also the Department of Environmental Health
at Emory University.
Eri has an impressive academic background.
She completed her Bachelor of Engineering
at the University of Tokyo in Japan.
Afterwards, she moved to the US
and got her Master of Public Affairs at Indiana University,
and then moved to Princeton University to get her PhD.
She completed her post doctorate research studies
at Princeton University,
and afterwards she moved to the University of Emory,
first as an assistant professor,
and now as an associate professor.
Eri conducts interdisciplinary research
about the environment,
mostly focused on the atmospheric chemistry,
environmental health, biogeochemistry, climate science,
and environmental policy.
Eri has a very impressive scientific output,
including 55 scientific publications,
including articles published in top-notch journals,
including nature, environmental science and technology,
and nature climate change.
Eri, it's a pleasure to have you with us today.
Eri: Thank you so much, Patricio.
And you have such great record,
and so I am just so flattered to be able to be here with you
and share my work.
If I were in the room with everybody,
I would have wanted to know
how many of you have seen this figure before?
But I am from Japan, as Patricio introduced.
And I just became very fascinated with air pollution
when I was a kid,
and I wanted to understand why we get air pollution.
So these are the pictures from Beijing.
I think that this is an amazing illustration
of how communication matters, in my opinion.
Because what happened was,
a photographer in China came up with this idea
of taking a picture
from the same place at the same time,
every single day, to compile them together for 365 days.
This is for 2014.
And so when I first went to China,
I asked people about air pollution
and they looked at me and they said,
"What do you mean, air pollution? This is all fog."
In 10 years, when I asked them about air pollution,
they all know what that means.
And they all know that gray sky is not because of fog.
So what I'm trying to explain here
is that data is so powerful,
and I think communication
and how we communicate about data
is also extremely important.
But so what do I mean by air pollution?
We looked at the blue sky and the gray skies
in the previous slide.
But I've been interested in air pollution, sorry,
is because of this,
not just because of the aesthetic unpleasantness
of air pollution,
but because low air quality
can cause adverse health impacts.
And also, importantly,
they can reduce agricultural yields as well.
So what I'm showing you on the right hand side
is the lung tissue.
On the top is a normal lung tissue.
And on the bottom is when you are exposed
to very bad air pollution.
So what causes this gray sky that we just saw
and this difference between the blue sky and the gray sky?
When I'm saying air pollution,
I mainly mean tropospheric ozone and aerosols,
aerosols or particulate matter.
So tropospheric ozone is a secondary pollutant.
And so they are not directly emitted,
but they form in the atmosphere,
and you need precursor species,
including methane, CH4, nitrogen oxides,
NOx coming from NO and NO2,
and volatile organic compounds, VOCs,
to react in the sunlight.
And tropospheric ozone is an oxidant and an air pollutant.
And they are very different from the good ozone
in the stratosphere, preventing us from the UV exposure.
Aerosols or particulate matter,
usually called PM2.5 or PM10
depending on the size of the particles,
are one of the air pollutants that also causes the gray sky.
And so I'm putting the figure so you can compare
the size of PM 2.5 to your piece of hair
and the sand.
You can see how small they are.
And because of the size,
they can really go deep into your lungs
and cause the problems in your health.
Tropospheric ozone is the main pollutant that can cause
agricultural yield loss.
Importantly, the particulate matter,
they can be directly emitted or they can be formed
through physical and chemical processes.
So you must be thinking,
"Okay, wasn't she supposed to talk about greenhouse gases?
And why is she suddenly talking about air pollution?"
The thing is,
I started learning about air pollution in my PhD,
and then I got very much into emissions.
And I didn't realize that there is so much link
between agriculture and emissions.
And so I hope this slide makes that clearer.
When we think about air pollution,
and that's how I was when I started,
I didn't necessarily think about agricultural emissions
as important source for air pollution.
But agricultural emissions include air pollutants
like methane and ammonia, and they lead to health impacts.
So methane, as I mentioned,
is important for tropospheric ozone formation,
and ammonia leads to particulate matter formation.
And so, as you can see here,
both of these are emitted from agricultural fields
and they have impacts on your health
and also on the agricultural yields as well.
So I think in this study by Bauer et al.,
they show us very well how much agriculture contributes to
fine PM or PM2.5 concentrations.
At the top left and the middle,
you can see for both Western and Eastern US,
the magnitude of agricultural sector contribution to PM2.5.
What you are seeing as "AGR" is the agricultural sector,
and this is the anthropogenic sector.
So the magnitude of agricultural sector
contributing to PM2.5 concentrations
is equal to the other anthropogenic sector
for both Western US and the Eastern US.
This green is the ammonium in the PM2.5,
and they are mainly coming from ammonia
that I just talked about.
And so you can see how important that part is
for PM2.5 concentrations in both Western US,
Eastern US and also in other parts of the world.
And to me, what's really fascinating about agriculture
and agricultural soils is that
it's not just about air pollutants,
that they also result in greenhouse gas emissions,
including carbon dioxide, methane and nitrous oxide.
So this is the figure from IPCC,
or the Intergovernmental Panel on Climate Change,
fifth assessment report, AR5.
And it shows the difference in energy coming in from the sun
and what's emitted from the earth.
So when we have more energy
that's trapped in the atmosphere,
it becomes positive.
And so you are seeing the largest greenhouse gas
in terms of global warming potential, CO2 at the top
and methane is the second and then N2O,
nitrous oxide is the third.
And so these are all being emitted
from the agricultural sector.
And the aerosols, the PM2.5 that I mentioned,
is also listed here
because they impact climate change as well.
They can scatter and absorb radiation.
But the important difference between the aerosols
and the greenhouse gases
is that aerosols are so much shorter lived.
They live only up to a week or so
compared to the greenhouse gases that live
up to 100 years for CO2 and N2O.
Methane is a medium year long,
so it's about 10, 13 years.
So I guess most of us here have seen the Keeling Curve
showing the CO2 mixing ratio increased over time.
When I was at MIT for a post-doc, I was involved in this,
what was called
Advanced Global Atmospheric Gases Experiment.
And so there were six, no, sorry,
five stations in the world
that were getting the measurements
for non-CO2 greenhouse gases.
And so this is the one that's showing
the methane mixing ratio over time.
And you can see that in the beginning it was increasing,
and around 2000, it was quite stable.
And in the recent years
we are seeing the increase of methane.
And this is the figure for N2O.
The increase has been very stable, about 2%, per decade.
And you can notice that the accuracy of the equipment
has increased dramatically.
And that's why we are seeing much better graph,
showing much finer data in the more recent years.
So working on air pollution
really made me interested in agriculture.
And looking at how important nitrous oxide was
made me really get interested in understanding better
the sources and the magnitude of these emissions.
So nitrous oxide, in my mind is very fascinating
because it's an inner gas in the troposphere.
And so it does not react at all.
But because it's very long lived,
it can get to the stratosphere.
And when it does it reacts
and it actually destroys stratospheric ozone,
the good ozone.
And so it's not only a major greenhouse gas,
but it also becomes a major stratospheric ozone substance.
And I'm sure many of us here know of Montreal Protocol
that was created to prevent the ozone hole.
And the main thing it did was to ban CFCs,
the chlorofluorocarbons,
but it also banned
major stratospheric ozone depleting substance.
Nitrous oxide,
even though it is a stratospheric ozone depleting substance,
it did not get included in the Montreal Protocol.
And the main reason is because
the natural soil that's shown here in the ocean,
the natural component, the natural source of N2O,
is pretty substantial.
And that is why it's not included in the protocol.
And we are seeing a big increase in that as well
in terms of emissions.
And what I'm trying to convey here,
I don't know if it's clear or not,
but this is the total emissions estimate
from different regions.
And I'm going to explain a little bit more in detail,
but what I'm just trying to show here
is that we really don't know very well
about the magnitude of emissions.
It's easy to put the mean based on the total
from each of the regions.
But you can see that there is so much uncertainty
when you try to,
even when we try to optimize the emissions.
And so knowing that natural soil is so important,
I got very interested in trying to understand
the process behind it.
And what I tried to do was to create the model
for natural N2O emissions in a model called
Community Land Model version 3.5.
And so what I was doing
was just using a very simple technique
to include the decomposition and denitrification
into the model to estimate nitrous oxide emissions.
And so the CLM-CN framework is shown here.
If anybody is interested,
I'm happy to show the framework
that includes my module as well.
But what I did was to analyze the emissions
from 1975 to 2008.
And I was extremely interested in
how the meteorological data would impact the N2O emissions
in the model,
and so that's why I used four different forcing datasets.
And these are the results.
So you can see that even when I use the same model,
the forcing data or the meteorological data
has really large impact on soil N2O emissions.
So the trend you see over time is very similar,
but the range in emissions is extremely big.
It's very substantial.
We are seeing from seven teragrams of N2O nitrogen per year,
up to 11 or so.
So I tried to compare my model results
with some of the existing datasets.
And this one is coming from Fazenda Vitoria in Brazil.
The red is the observational data
and the solid lines are my model results.
And as I used four different forcing datasets,
I'm showing you in different color,
my results from using different forcing data sets.
And you might realize that NCC data, for example,
only go up to 2000,
in gold, they only had the data up to 2001.
And so those were also one of the reasons
why I used four different data sets.
But I think I was quite happy
with how the model results compared with the data,
the observational data.
On the other hand, this is the comparison
for the White Mountain National Park in New Hampshire.
So you can see that the model doesn't do too well.
And the range in the model is much smaller
in terms of the N2O flux magnitude.
And even though in the observational data
there are times when it goes negative,
meaning the soil is acting as a sink,
that will not happen in the model because of how I code.
If the temperature goes below zero, for example,
there is nothing that happens.
And these are the times
when temperature is going below zero.
So there are obviously a lot of defects
in the current model.
But when we looked at the seasonality,
we were seeing what we would expect.
So in the summer, for example, June, July,
and August in the northern hemisphere,
you are seeing higher emissions
because of the higher soil temperature
and more soil moisture.
And in December, January and February,
the same thing was happening for the southern hemisphere,
their summer.
And the total that we would get from the global total
matched with the existing global total estimates.
And so we were quite satisfied.
And now that we had a pretty good estimate
for natural soil emissions,
we wanted to optimize other sectors
that we weren't quite sure about.
And so what we did was we used the atmospheric observations
that exist for N2O.
This is the figure that shows all the sites
that I got the data from.
And then I was able to run the model that's called
global 3-dimensional chemical transport model.
The model name is the abbreviation, is MOZART.
That comes from Model for Ozone
and Related Chemical Tracers.
And I run the model for from 1995 to 2000.
And what I was trying to do was to optimize
for five different soil sectors,
including agricultural soil, natural soil,
anthropogenic, ocean, and biomass burning.
So listed here are the model setup,
but I optimized emissions by minimizing this equation
at the below, just further information.
H is the sensitivity matrix, x is the prior emissions,
the best guess,
and y is the observed mixing ratio,
S is the uncertainty in prior emissions,
and W is the uncertainty in the model.
So I'll be happy to explain more in detail
if anybody is interested.
But just to be very brief, so what I'm doing here is
I'm using a 3-D chemical transport model
that I talked about.
First, I will create the best guess
from each of the soil sectors for each of the regions.
And I will run that as is
knowing that there is model uncertainty,
so I can calculate,
or rather predict the atmospheric mixing ratio.
What I can do is I can perturb emissions
from a specific soil sector in a specific region
one at a time,
and then run multiple simulations
and predict atmospheric mixing ratio when I turn on the,
when I change the emissions from a specific soil sector
in the specific region.
So I will have many different combinations
in the simulation results from that.
And so by comparing these different results
to the predicted mixing ratio from the baseline,
I can calculate the sensitivity
of how that specific soil sector
and the specific region emission
actually affect the mixing ratio in a certain region
for a certain source, and also in other parts of the world.
And then using the equation that I listed
and weighing the prior emissions and the observational data,
knowing that there are uncertainties in both,
I can come up with the improved emissions estimate,
what we call the posterior or optimized emissions
for each of the soil sector and for each of the region.
And then this is what we got.
And we found that the only region and the only soil sector
where we see increase in N2O
was the Southern Asia agricultural soil emissions.
And agricultural, sorry,
the Southern Asia includes both India and China,
and this was the best guess, the prior emissions.
And as I mentioned earlier,
there were four different emissions estimates
for natural soil emissions.
And so I run the model using four different
natural soil emissions estimates and optimize them.
And so either, whatever data set I used,
I was seeing the increasing optimized emissions,
but only for agricultural soil in the Southern Asia.
So this made me very curious why this might be happening,
and you might have known that already,
but this is because of the nitrogen fertilizer we use,
we think.
And so China is the number one nitrogen fertilizer user
in the world.
It has taken over the United States in about 1980s.
This is China and this is United States.
And India has taken over the US as well
in the early 2000s.
And so we are having
the two largest nitrogen fertilizer users
in this Southern Asia region.
And so we were curious,
how can we reduce these nitrous oxide emissions
from this region?
And so we looked into the crop
that uses the nitrogen fertilizer the most.
And you might know this as a common sense. I didn't.
And so we found out that maize is a very big crop
that uses nitrogen fertilizer.
And that was very convenient for us
because they grow in Georgia as well,
and that's where I am right now.
And so finally it comes to the climate smart agriculture.
So what I was mainly interested in was how can we reduce
nitrous oxide emissions?
And then we decided that we wanted to try out
in Georgia as well,
because it's too much to be going to China
and conduct the work.
But, got very interested in this definition
of climate smart agriculture.
And then we wanted to add another aspect of reducing,
not just greenhouse gas emissions,
oops sorry, but also to reduce ammonia emissions,
so the air pollutant emissions as well.
Can we do climate smart agriculture
that's going to mitigate both greenhouse gas emissions
and air pollutant emissions?
And then that was when I was able to meet with my colleague
at the university of Georgia
that was looking into this living mulch system.
What this is, is he plants white clover
that is a perennial nitrogen fixer over the winter time.
And then it's able to live because our winter is very mild.
And in the spring, he creates a strip and grows corn.
As corn grows, it doesn't compete too much with the corn,
and so it can provide nitrogen
and we can reduce the amount of
synthetic nitrogen fertilizer.
And because it's perennial and it doesn't die completely
at the end, and so it can come back
and then we can start the cycle all over.
And so we wanted to figure out if this living mulch system,
could we reduce both the greenhouse gas emissions
and ammonia emissions at the same time
compared to a traditional method
where we use a lot of fertilizer?
So this is the site where we have been doing the field work.
So I'm based in Atlanta at Emory,
and this is close to Athens in Georgia.
And this is the University of Georgia experimental farm
that's called J Phil Campbell experimental farm.
And that's what JPC stands for.
And this is in the west unit.
And we have been having a plot since 2016.
And we had four different techniques,
agricultural techniques for corn.
One was crimson clover as a cover crop.
And the other was cereal rye as a cover crop.
We wanted to introduce them because crimson clover
is an annual nitrogen fixer,
and cereal rye is the most used cover crop in Georgia.
Obviously, these cannot provide nitrogen.
And living mulch is what I was just talking about.
And we compared that to the no cover crop, the bare soil,
the traditional methods with a lot of synthetic fertilizer.
And so this was our study design.
We had three chambers per plot,
and we had three replicates of four agricultural practices.
So the CR was the cereal rye,
LM was the living much, CC was crimson clover,
and TR is the traditional that I mentioned earlier.
And so at first from 2016 to 2017,
we were taking measurements every 3.5 minutes
from the chambers manually.
This is my PhD student at the time,
Sam Peters, taking the measurements with the syringe.
And we would collect them and bring them to the lab
and analyze them
with the GC gas chromatography mass spectrometry.
We also created what's called the acid trap
to measure ammonia coming from the soil.
And so what we would do is we would bubble the,
we would have sulfuric acid inside
and bubble the air so that we can capture ammonia.
And this is a way to control the airflow to be stable.
And we had a battery to operate the system.
So this is a very low-cost method
to see if we could capture ammonia.
So this is the result from four different techniques.
As you might expect,
we were seeing a very big difference
between the four techniques.
This is after four years of doing the experiment.
So "none" is the traditional, no cover crop,
no living mulch system.
This is cereal rye, this is crimson clover,
and this is living mulch.
Even qualitatively, even to somebody like me that has,
that doesn't know anything about agriculture,
it was very clear that the soil was very different.
And the data shows that bulk density
is statistically different from the others,
and it's much smaller for the living mulch.
The porosity was much higher compared to the others.
Ksat was extremely larger, and so was labile carbon.
So in terms of soil health,
we thought that there was a pretty significant improvement
using living mulch system.
But when we looked at the soil CO2 fluxes,
we were also seeing the highest CO2 flux
coming out of the living mulch system.
Sorry, this is not as consistent,
but WC is white clover,
so this is the living mulch system.
And that is the highest in 2016.
And also, you can see the dark green
is the highest in 2017 as well.
And so we found out that compared to the traditional,
when we controlled for different variables
that I'm showing here.
These are the agricultural techniques that I mentioned
and all of them using cover crop or intercrop,
crimson clover, cereal rye, and the living mulch system,
they had higher CO2 emissions
compared to the traditional methods
using just the bare soil.
So moving on to soil N2O fluxes,
we were very sad to find that there were very big spikes
coming from the living mulch system as well.
So this one, again, the dark green
is the living mulch system.
And you are also seeing a very high peak in yellow
right after the fertilizer application,
just for the traditional in 2016.
In 2017, we applied the fertilizer on May 18th.
And we actually saw a quite high peak
from the living mulch as well,
even though the amount of fertilizer applied was 1/5
of what was applied to the traditional.
And overall, you can see that there is, again,
a very big peak in middle of June
that's making the N2O flux very large
compared to the other agricultural techniques.
And so again, we are having a statistical analysis,
and what we found was that the living mulch
was statistically significantly higher
compared to the traditional
when we controlled for other variables
that would affect the N2O emissions.
And also, when we looked at ammonia,
unfortunately, ammonia fluxes were also higher.
We were only able to compare between the living mulch system
and the traditional,
but the living mulch system had higher ammonia
compared to the traditional
for every single day almost, that we measured,
other than this one day.
But what was very interesting to us was for ammonia,
we were actually able to measure from China, Rwanda as well.
And we compared how the magnitude differs
in different areas of the world.
So the dates don't really matter.
I'm sorry, if you cannot see very well,
but what's most important is that China is in red,
and the y-axis for ammonia for China is on this side.
And you can see that it goes up
to almost over 500 nanograms
per square meter per second.
Whereas for Rwanda that's in green and for US in blue,
it's kept at two nanograms per square meter per second.
So there were two orders of magnitude difference
of ammonia fluxes coming from China,
and Rwanda and the US that we found very interesting.
So cumulatively and also the mean,
that's what I'm showing you here in the table.
The mean N2O and CO2 and ammonia,
as well as the cumulative fluxes,
unfortunately, we were finding much higher emissions
from the living mulch system, and not just for a year,
but also for both 2016 and 2017.
And so then we decided that it would be nicer
if we could make the in situ measurements.
So instead of doing the syringe measurements,
we were able to purchase the Picarro G2508.
And so now with the multiplexer,
we are able to measure different plots at the same time
in sequence, not at the same time.
And we are able to also measure ammonia as well
at the same time as CO2, nitrous oxide and methane.
And I'm not showing you the automated chambers,
but we were able to use the automated chambers as well,
in addition to the manual chamber this summer.
So we were very excited about the experiment
that we are starting.
What I'm showing you here
is the results from 2018 using Picarro.
And the black arrows here are the dates when we fertilized,
and the blue arrows here are when we irrigated.
But just like I showed you for 2016,
in 2017 we were seeing very high CO2 fluxes
from the living mulch system,
especially in the earlier season.
And the same thing for N2O,
we are seeing higher emissions.
But what was interesting was for this 2018,
we were seeing high emissions
from other cover crop practices as well.
So for example, especially on this day
after the fertilization,
the living mulch was not extremely high.
What was most interesting for 2018
was that we were actually able to measure methane
for that first time.
It was not possible
when we were doing the manual measurements.
But using Picarro,
we found out that soils are serving as a sink for methane,
and it was more significant
for the intercrop
or the cover crop practices.
And so then we had the soil carbon data,
and then we had the total greenhouse gas data.
And so we wanted to put them together
and understand the impact as a whole.
So we took into the three greenhouse gas fluxes,
the CO2, methane, and nitrous oxide, the soil carbon,
and also how much CO2 is used,
how much CO2 is emitted by using fertilizer
or herbicide production.
Took that into account and tried to calculate
the carbon equivalents
for each of the agricultural practices.
And that's what I'm showing you here for 2018.
So, unfortunately,
even though we were finding that soil served
as a greater methane sink for intercrops and cover crops,
you can see that the number for carbon equivalents
it's much bigger for living mulch.
And also, if you compare that
to the traditional, crimson clover and cereal rye practices
are also higher than the traditional method.
So right now, there has been a lot of talk
about how important
the soil carbon sequestration potential is.
I believe it's also important that we think about
other greenhouse gas emissions that come out of it.
And so in conclusion,
we found that living mulch system increases
the labile carbon content in the soil.
And we were finding the two orders of magnitude difference
in the ammonia emissions,
comparing China to Rwanda and the US from the corn fields.
Mitigating soil greenhouse gas emissions,
and also ammonia emissions together is a very big challenge.
So I say that mitigating soil greenhouse gas emissions
in agriculture is a big challenge,
but mitigating soil greenhouse gas
and air pollutant emissions together
is even a bigger challenge.
I would like to thank my lab members.
We are still living in the Zoom world right now
for the office hours
and also for the lab meetings, unfortunately.
And I wanted to especially acknowledge
my lab members that worked, especially on these projects
and the collaborators from Emory,
from the University of Georgia,
from Nanjing University and in Rwanda as well,
as well as the funding.
And I am happy to take questions if there is any.
Thank you so much.
-: Thank you very much, Eri,
for the very exciting presentation.
And we can now open up for questions again.
The first one, Eri, is about, well, I have two questions.
One is about the productivity
of the systems that you compare,
and in particular, the productivity of the corn crop,
because after all,
that's where the money for the farmer comes from.
Do you find differences in productivity
between your treatments?
And then my second question is,
is a little bit of a provocation.
But you know, here in the corn belt
we are spending a lot of time researching,
and money and subsidies
to incentivize the use of cover crops as a way to,
for example, reduce nitrogen leaching.
However, in some of your research shows that actually,
in some cases, the cover crops have higher N2O emission
compared with a traditional management.
So are we missing something here in the Midwest
by only looking at leaching
and not looking at other gases
with potentially warming potential?
Thank you.
-: Yeah. Thank you for that great question.
And I should have thought about including the harvest data.
So that's a very important point.
So obviously for the living mulch system,
it needs so much more water.
And so that becomes a very important point
for the harvest.
So when we have the drought year,
the grain yield decreases quite substantially.
And so that is a very big problem
for the living mulch system.
I think
what my colleague is trying to say
is that if you try to take into account
the amount of fertilizer that you don't need
into economic calculation,
even though you get less grain yield,
you would still be able to be better off.
I'm not sure how that would work every year,
but I thinking the normal, non-drought year
that could potentially work.
And then other question about the nitrogen leaching,
I think the indirect N2O emissions coming from leaching
is a very important one.
And so when I was working on it,
I wasn't necessarily including that.
There is so much uncertainty
in how much the emissions might come from
based on the leached N2O.
And I think that could be a very important topic,
and I think there needs more research into it.
I do think it is very, it is very concerning to me
that we are only looking at carbon
when we think about greenhouse gases
or mitigating climate change
in agricultural field right now.
And I think we need to think a bit more about
how it's connected to carbon nitrogen together,
and how does that work as a whole,
for the whole greenhouse gas emissions together,
if that makes sense.
-: Thank you, Eri.
There is here another question from Bijesh.
He's asking if you can please tell us
a bit more about the Picarro equipment.
How easy is, sorry,
how easy is to use it and how reliable the data are?
-: Yeah, so I'm not an instrumentalist per se,
but the Picarro to me, is fairly easy to use.
And it is, I think,
the only thing that you need to make sure is that
you would equilibrate enough time
before you actually start measuring.
It does take quite some time to stabilize,
especially to measure N2O.
And so you do need to have,
you do need to think about that.
But other than that,
it is quite easy to maintain and also to use.
And I believe the data are pretty reliable,
and it is especially useful for the field work.
I'm happy to talk more about how it might use.
There's so many different Picarro instrument as well,
what we are using is called G2508.
It is especially for soil.
And that is the only equipment that I know of
that can measure all of the three greenhouse gases together
and ammonia and water.
So in that aspect, that is great for our purposes.
And I know that some other companies like LI-COR,
they are able to do CO2.
So we have compared the LI-COR CO2
to GC-MS methods, for example.
We would be interested in doing the data comparison
with other equipment, if we are able to do that.
We haven't got there yet.
-: Thank you, Eri.
There is here another question from Othler.
He is asking about the China, US, Rwanda comparison,
and he's asking which were the crops
that were being compared
And if there is any,
well, if I may reformulate his question, I guess,
that we want to know a little bit about the why
behind those differences that you were showing.
-: Yeah. So, sorry.
I forgot to mention,
but all of them were growing corn, the maize.
And so we were interested in measuring
the ammonia fluxes coming from the maize field.
And I think the biggest difference is the application of,
application amount of nitrogen fertilizer.
And so there has been a significant application
of the nitrogen fertilizer in China,
as I mentioned in the slides.
And so I believe that that might be
the reason why we are seeing that.
We haven't been able to do multiple measurements.
And so it is also possible
that it was just a very specific year.
And so we would like to go back and measure again.
And also, this result is coming from the acid trap,
not from the Picarro.
And so there is also a significant uncertainty
that we need to think about.
-: If I may jump in there with a comment,
is that your comparison also show
not too much difference in emissions
between the Rwanda and the US systems.
Despite, my guess is that the level of nitrogen input
is probably very different.
So we've seen that also it's a question of balance there,
not only applying fertilizer,
but also have a healthy crop there
that will uptake most of that nitrogen that is being applied
and therefore, reduce losses.
-: Yeah, so that's why I'm trying to understand
why we didn't see much lower ammonia emissions from Rwanda.
I was quite surprised that the magnitude is about the same.
And we would like to go back again and do more experiments.
We haven't been able to do that so far.
-: All right. There are more questions here.
The next one is about
what will be your suggestions to lower ammonia emissions?
-: Yeah, so that's a very difficult one.
And I think right now we are also trying to understand
how the microbes impact these emissions as well,
and what will be the best way to lower emissions.
And so one of the things that we've been thinking about
was the types of fertilizer, how much that would affect.
And if we were to put them also inside the soil,
not just apply on top of the soil, if that would reduce.
Those are the things that we would like to try,
but we haven't done the experiment enough
to say what would be the best way.
-: Yeah. There is a question from Martha.
Martha, I think that I you're allowed to talk.
So go ahead and ask the question directly to Eri.
Martha: Thank you, Patricio.
Thank you, Eri, for a great presentation.
I have two question.
Fertilizer types influence
the degree of ammonia emission
from the soil.
So could you share with us the source of fertilizer.
But also,
sometimes the ammonia is deposited back
downwind in the same field.
Were you able to measure within the field,
how far the ammonia, you know,
traveled or dissipated across the field?
So that's one question.
And the second question is,
your living mulch resulted in high CO2 emissions,
but you also benefited from an increase
in soil organic matter in other parameters.
So holistically,
have you looked at that to see the trade-off
between the emission and the other benefits
that the mulch provides?
Thank you.
-: Yeah. Thank you so much.
These are all great questions.
And so for the fertilizer we were using urea
for all of the years that we did the measurements,
from 2016 to 2019.
And so you read my mind obviously,
about the deposition and how far it travels.
So as somebody that's interested in the atmosphere,
we've been really trying to figure out
if we can put the flux tower of some sort
to really figure out the ammonia moving away
and also coming in.
We have not been able to do that,
but I think that would be really interesting
and that would be necessary if we wanted to understand
the impact on air quality as well.
So that's definitely something that I would love to do,
but not have been able to do.
Your second question, so what we tried to do
was just to simply calculate a carbon equivalence.
And I understand that that's a very simple method.
And so I would love to know
what you would suggest that we would do
to take into account the soil carbon.
What we were just doing was to use the Laos method
of this carbon equivalence that he suggested,
that we would put all the greenhouse gas emissions
into carbon equivalents
and then consider how much carbon we were able to gain,
and then see if that resulted in
lower or higher impact.
And what we are seeing is that even if we take into account
the greenhouse gas emissions are so much higher
from the living mulch system,
that it seemed like we might not be able to mitigate
as much as we had hoped.
But I would love to hear your thoughts on that.
Martha: Thank you.
So you have considered then,
the increase in soil organic carbon?
-: Right. Martha: Okay. Okay.
-: Great, and I think that there was also, Eri,
a question from Martha about the source of fertilizer.
-: The source of it.
What do you mean by the source of fertilizer?
-: If it was urea? Eri: Yeah, it was urea.
-: Okay. All right.
And in connection to that point, I have a question.
From the perspective of farmers,
how much is there to gain
by selecting the proper source of fertilizer
compared with what they can gain
by managing naturally in the field?
-: Okay, so your question is,
if we change the fertilizer source?
-: Yep.
-: Yeah. So that's what we would like to do.
We haven't been able to try it yet.
Some people actually suggested
what about we tried different, like,
even the human dung, for example,
human manure, and then put it in the soil?
They were saying they saw very little N2O emissions.
I think that is going to be potentially a problem
for the agricultural soil,
but there are some people that would like to test like,
just the manure putting it into deeper soil,
and does that reduce emissions?
I have not done any experiments on that.
And so, yeah, that would be very interesting to see.
-: Great. Any other question for Eri?
-: Oh, difference of pH, I guess.
-: Can you please read the question,
since there is some terms there I did not understand?
-: Yeah, so there's a question.
Do I plan to look into the difference in pH
for the ammonia emissions?
So, yeah, that is a very interesting point.
We actually, for the modeling,
we really wanted to take into account the pH.
We haven't been able to do that.
I think, the soil pH we haven't looked at.
And so that might be an important issue.
I had a feeling that maybe in the same field
the pH wouldn't be so different, but I don't know.
Maybe I'm completely wrong
and I should be taking the soil pH measurements
more frequently.
This year, we did try to take the soil carbon
and soil nitrogen and quantify
the nitrate and ammonium each week
and see how that changes
and so that we can better understand the process.
But we haven't looked into the pH.
-: Thank you.
And I can see that Martha still has her hand raised there.
I'm not sure if you forgot. Martha: Yeah.
-: Okay, great. Go ahead.
Martha: I have another question.
You, in your model simulation,
you showed natural soils, right, and CO2.
Have you done different biomes?
I'm asking this question
because we have both agricultural land
and grassland in Nebraska, for example,
looking at maybe climate regimes and biomes.
-: Yeah, so when I was doing
the natural soil N2O emissions modeling,
I intentionally only looked at
the soil that doesn't get the fertilizer applied.
So I did not look into the agricultural soil
because it's just so difficult.
And so the main areas that I was looking at
was the forest land and then grassland
that doesn't get the fertilizer applied.
Martha: Thank you.
I'll be curious to know more about the grassland.
-: Yeah.
So I think, I've been really wanting to do more modeling
in the agricultural field,
and I think that would be really interesting.
-: Well, maybe we need to open up a position
for you here, Eri.
-: Yes. Please do.
-: Yep. All right, any other question?
Eri: Yeah. There is another question.
-: All right. Let me see.
Sorry. I'm a horrible host here.
-: No, no, no. -: I'm losing the question.
So, have you considered looking into
ammonia deposition?
-: Yeah, so I really need to be doing that,
and I haven't.
So if you know of a good way to do that,
I would love to know.
The only data I have is based on the model results
and I know that's not good enough.
And then from the model results,
it doesn't change over different plots.
So if there is a good way
to take that into account or measure, I would love to know.
-: Right. Any other question from Eri?
If not, I have one more question.
And this is from the perspective of graduate students.
And if I were a young, I wish, grad student now,
and I'm looking, you know, for what's the next challenge
in the area of greenhouse gas emissions,
what do you think, Eri, are the major gaps of research
that exist within that field?
-: Yeah, I think what's really important is
how can we feed the people
and also trying to be mitigating greenhouse gas emissions?
So I feel we need to be taking that into account more
and there is going to be potentially
the climate change can impact nutrition as well.
So how are we going to make sure
that people are going to fed with enough nutrition
and also reduce greenhouse gases,
and then be able to adapt to the climate?
Those are so complicated issues
that the young, current scientists needed to be finding out.
-: Great.
Anything else, Eri, that you may want to add
about your ongoing research?
And maybe you want to elaborate a little bit
about these Emory Climate Talks.
What's your role and what they're about?
-: Oh, that's great.
Thank you so much for allowing me to promote
the climate talks.
But actually, I would love to have,
if you are all interested in
food to energy conversion,
we've been interested in understanding
the anaerobic digester process.
And this is not just about climate talks,
but Emory Climate Talks,
this is the program that I run
because I take students to
the UN climate change negotiations.
So this year it's going to take place in November.
Unfortunately, because of COVID,
we will not be taking students.
But we have been doing webinars series
and inviting people, like you are doing Patricio, here.
And next week we are actually going to have
an international workshop on anaerobic digestion.
And so if anybody is interested,
I would love to have
the agricultural scientists' perspectives on that,
because we don't have agriculture at Emory.
So all we talk about is food insecurity,
environmental justice, et cetera.
But we are going to hopefully have a prototype
for anaerobic digestion.
And that's why we are trying to have this workshop.
So I will-
-: I want to thank you again, Eri, very much.