Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming

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Global and Local Effect of Increasing Land
Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of
Mediterranean Greenhouse Farming
Pablo Campra
University of Almeria
Spain
1. Introduction
Current warming trends have been generated by a recent imbalance in the Earth’s energy
budget, characterized by the reduction in 2.6 Wm-2 of the global mean annual outgoing
terrestrial longwave (LW) radiation from pre-industrial times (Forster et al., 2007). As a
result, there is an excess of incoming solar shortwave (SW) radiation that is driving surface
and atmospheric temperatures to higher values of equilibrium. This alteration is called
radiative forcing (RF) of the climate, and is very probably originated on the unprecedented
growth of greenhouse gases (GHGs) in the atmosphere due to human activities.
The reduction to zero emissions might be the only long term effective action to stabilize
temperatures at reasonable levels (Mathews & Caldeira, 2008), before impacts are too
catastrophic to manage. But on the other hand, in recent years there is a growing interest in
the design of geo-engineering strategies to offset this warming exerted by GHGs through
radiative rebalancing of the Earth´s energy budget. These proposals can be divided in two
groups, according to which parte of the energy budget is addressed for rebalancing. The
first group, named as Solar Radiation Management tecniques (SRM), joins up all strategies
that attempt to reduce the net amount of SW radiation absorbed by the Earth, by limiting the
solar energy reaching the planet. SRM can be achieved by increasing the reflectivity or
“albedo” of the Earth to SW radiation at different levels of the atmosphere, at the surface, or
even from the outer space. The second group, called Carbon Dioxide Removal (CDR),
groups all strategies that aim to increase the amount of LW radiation emitted by the Earth,
directly counteracting the greenhouse effect by actively removing the excess CO2 from the
atmosphere, and storing it in long term reservoirs.
One practical way to make comparisons among the potential impacts on climate of different
agents is using estimated RF values, thought it must be borne in mind that this metric does
not fully represent their overall impact on climate (Pielke et al., 2002), and that further
modelling studies are required. Lenton & Vaughan (2009) have recently quantified in terms
of RF the climate cooling potential of a wide range of geo-engineering proposals discussed
in the recent literature (Boyd, 2008), taking into account their current feasibility of
implementation. In the case of proposals aimed to increase the Earth’s albedo at low levels,
their estimation of RF potentials (SWRF) is summarized in the Table 1:

Climate Change – Research and Technology for Adaptation and Mitigation
454
Option
Fraction of
Earth for
implementation
Albedo change
within area
Planetary
albedo change
Global
Radiative
Forcing (Wm−2)
Increase marine cloud albedo
Mechanical 0.175 0.074 0.011 −3.71
Biological 0.1 0.008 0.000056 −0.019
Increase land surface albedo
Desert 0.02 0.44 0.0064 −2.12
Grassland 0.075 0.0425 0.0015 −0.51
Cropland 0.028 0.08 0.0011 −0.35
Settlements 0.0064 0.15 0.00046 −0.15
Urban 0.0029 0.1 0.00014 -0.047
Table 1. Estimated radiative forcing potential of different SRM geo-engineering proposals
(Adapted from Lenton & Vaughan, 2009).
As it can be concluded from these values, most SRM geo-engineering proposals seem to
have a limited effectiveness in offsetting present and projected forcing due to GHGs
increase. Only “whitening” marine clouds through aerosol seeding, or enhancing albedo on
a huge fraction of the Earth’s surface through land cover changes, i.e. on big desserts, could
achieve levels of forcing high enough as to counteract present unbalance, as well as the
estimated forcing due to a doubling of atmospheric CO2 (+3.71 Wm-2) (Forster et al., 2007).
However, these two approaches are still in an early stage of development, and their global
scale implementation seems not to be feasible nowadays due to technical and financial
barriers related to its big required scale of application.
Nonetheless, though this can be true at a global scale, a different perspective of geo-
engineering is usually missed: its value as an effective and cost feasible strategy for local
and regional adaptation to projected warming. The increase of land cover albedo at small
scales appears nowadays as one of the few available geo-engineering options, particularly to
offset or minimize global warming impact over human settlements. The physical basis of
this strategy is an SRM approach, reflecting back to the outer space a higher amount of
reflected shortwave solar energy than pre-existing land cover over a given area. This way,
less energy is available to heat the surface air above when emitted back as sensible heat flux
from the surface, thus resulting in a net cooling effect that can totally or partially
compensate warming due to GHGs in the area of implementation. At the moment, the most
promising strategy of SRM geo-engineering, increasingly being considered by policymakers,
is increasing urban albedo through cool roofs and pavements promotion.
2. Cool roofs strategy
In May 2009, the US Secretary of State Steve Chu launched a global call to promote albedo
increase in major urban areas in the world. This is one of the first calls from a high level
policymaker to promote ge-enginering strategies to counteract global warming. His call was
supported by a simulation study carried out by scientists at the Lawrence Berkeley National
Laboratory (USA) (Akbari et al., 2008). In this work it was estimated that global
implementation of cool roofs in the big metropolitan areas could offset as much as 44 Gt of

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 455
emitted CO2, an amount that would counteract the radiative effect of the growth in CO2-
equivalent emission rates for 11 years.
However, an essential parameter to project micro-climate impacts of this geo-engineering
strategy not addressed in this study was to determine the local climatic sensitivity
associated to a given density and total surface of albedo enhancement. This question needs
further radiative transfer modelling validated with empirical study cases. This means that
projections of changes in mean temperature and other variables must be linked to
independent variables such as extension and distribution of modified surface, time for local
climate to adjust to new reflectivity, and changes in RF due to projected increases GHGs
emissions. Some global simulations have been published with estimations of temperature
changes associated to surface albedo changes (Betts, 2000; Myhre & Myhre, 2003). A further
progress in this field is a recent work (Menon et al., 2010) that includes an estimation of the
climatic sensitivity of the development of this strategy on global urban areas through a
GEOS-5 GCM simulation. In this work they showed the potential effectiveness in reducing
high summer temperatures in urban areas, thus mitigating the effects of urban heat islands
on energy consumption, pollution, and human health. The potential of cool roofs and
pavements for regional adaptation was also reported, with an increase in the total outgoing
radiation by 2.3 Wm−2 for an average 0.01 increase in surface albedo in the continental US,
and land surface temperature decreased by 0.03 K.
Menon et al. (2010) increase substantially the potential forcing that can be achieved by urban
albedo enhancement, in comparison to Lenton & Vaughan (2009) estimations. The difference
is due to divergences in the estimations of global urban area (1% of global land surface in
the first work). Nevertheless, and though the global average increase in the total outgoing
radiation was 0.5 W m-2 for a simulated 0.1 increase in urban albedo in all global land areas,
the global summer temperature reduction obtained by these authors still seems to be
negligible (0.008 K), if we take into account that the projections for future warming at the
end of this century range from 2-6 ºC, depending on emission trends. However, the
reductions obtained in regional and seasonal temperatures are big enough as to consider
albedo enhancement as a key adaptation strategy for the next decades, and these global
simulations studies highlight the need to study the potential of albedo forcing at smaller
scales, i.e. in regional or local domains. A growing number of simulation research with
meso-scale models such as Weather Research and Forecasting (WRF, National Center for
Atmospheric Research, Boulder, CO, USA) is getting added to literature, but there are still a
very few observational studies that show the impact of recent land albedo changes in long
term air surface temperature trends. One of these studies (Campra et al., 2008) is
summarized in the next section.
3. Albedo enhancement experience by greenhouse farming development in
South-eastern Spain
In order to increase the total area of modification of land cover reflectivity, other categories
of land use have been proposed to develop this geo-engineering approach, such as pasture
and agricultural land, oceans and big desert areas. In the case of farmland, there are several
low cost effective strategies that have been proposed to increase reflectivity. The increase in
cropland albedo by replacing currently grown crops with high reflective varieties has been
recently suggested as a new “bio-geo-engineering” approach (Ridgwell et al., 2009).
According to climate simulations made by these authors, the potential for mitigation of

Climate Change – Research and Technology for Adaptation and Mitigation
456
regional warming could reach a summertime cooling of >1ºC in mid-latitude arable regions
of the northern hemisphere through an albedo increase of 0.04. Same as with urban albedo
enhancement, limited impact on global warming was obtained in these simulations.
On the other hand, a particular type of agricultural land cover, greenhouse farming, has
shown its efficacy offsetting local warming, showing a net cooling effect in the long term
climatic data, as it has been shown in our empiric study in SE Spain (Campra et al., 2008).
This recent experience of greenhouses development has resulted in a unique pilot-scale trial,
based on field observations of air surface temperatures trends in three decades of a non
deliberate geo-engineering experiment based on of the impact of changes in albedo at the
biggest concentration of greenhouses in the world (27,000 ha), located at the province of
Almeria (Fernandez et al., 2007).
AEMET Control stations in SE Spain
MALAGA (MA)
GRANADA (GR)
MURCIA (MU)
ALMERIA (AL)
Agroclimatic stations in Campo de Dalias
Almeria
LAS PALMERILLAS (PAL)
MOJONERA (MOJ)
PAL
MOJ
200 Km
20 Km
Analysis of air surface temperature series
8
Fig. 1. Location of control (MA, GR, MU, AL) and experimental (PAL, MOJ) stations where
air surface temperature series where analyzed in SE Spain (Campra et al., 2008).
Air surface temperature series of agro-climatic stations inside the greenhouses area (MOJ
and PAL, Fig 1) showed an anomalous long term cooling trend of -0.3 ºC/decade from 1983
to 2005, during the years of greenhouses expansion, while the control stations located
around the area, where no influence from greenhouses land cover is assumed to occur,
showed a regional warming trend of +0.4 ºC/decade, that matches with generalized
warming in the western Mediterranean area in the same period (Fig. 2).

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 457
Fig. 2. Anomalies in air surface temperature series in SE Spain (Campra et al., 2008).
The working hypothesis of this study was that this differential climatic trend was caused by
the gradual expansion of a highly reflective land cover of plastic greenhouses over a broad
area. The increase of surface albedo reduces the net solar SW energy absorbed in the area,
and this change in the energy budget might have been the most probable cause of the
cooling trend detected in the agro-climatic stations in the area. In order to test this
hypothesis, remote sensing albedo data from MODIS were analyzed to compare outgoing
SW fluxes (OSW) from greenhouses area, and previous land cover type of semi-arid
pastures. The difference series between the two outgoing fluxes is a measure of the SWRF
due to land cover change (Fig. 3).
Our ongoing research using meso-scale simulations with WRF (unpublished results) shows
changes in the energy budget according with the working hypothesis. The reduction in the
sensible heat flux (HFX), and the net SW radiation (netSWrad) are solid evidences of the
existence of a causal relationship between albedo change and the decrease in surface air
temperatures (Fig 4).
The greenhouses development experience is a solid empiric proof that through designed
SRM geo-engineering strategies such as the albedo effect, “cool islands” can be generated to
protect human settlements by a low-cost and low-impact effective approach, helping to
protect human health, lives and food production from global warming and increased
frequency of heat waves projected for the next decades.
Our study shows that the main direct benefit of high albedo surfaces is the potential for
adaptation to climate change at local scales, offsetting global warming through the
generation of local microclimates in high vulnerability human settlements. This local effect
is the key finding of our study in the province of Almeria, but is generally forgotten or just
assumed to be a “secondary indirect benefit” of a global CO2 offsetting. Geo-engineering
aimed at increasing albedo at local or meso-scale is not even considered as a mitigation or
adaptation measure in international protocols, or IPCC-UN reports. In fact, this strategy can
help closing the loop between adaptation and mitigation, an unresolved issue in climate
mitigation policies (Parry, 2009).

Climate Change – Research and Technology for Adaptation and Mitigation
458
Fig. 3. Annual time series of outgoing solar radiation (OSW) from greenhouses and pasture
surface and radiative forcing (-RF) as difference series (Campra et al., 2008).
Fig. 4. Change in the surface energy budget components from pasture land use (PS) towards
greenhouses land use (GH) (in Wm-2). WRF simulation output: monthly averages for
August 2005 (data not published). Radiation components: HFX=sensible heat, LH=latent
heat, GRDFLX=ground flux, SWDOWN=incoming solar rad., OSW=outgoing solar rad.,
netWSrad=net incoming solar rad., GLW=incoming long wave rad., OLWsup=outgoing long
wave rad., netLW=net long wave rad., net (SW+LW)=total net rad.
0
20
40
60
80
100
120
0 100 200 300 400
OSW (Wm-2)
Time (DOI)
Greenhouses
Pasture
Difference (-RF)
-100.0
0.0
100.0
200.0
300.0
400.0
500.0
PS
GH

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 459
Nonetheless, modelling of the greenhouses land cover change case has not yet been
completed as to try to extrapolate the particular outcomes to other areas in the world with a
scientifically sound basis. The case of Mediterranean greenhouses development is a very
singular experience of climatic geo-engineering whose conclusions by now only apply to a
particular set of modified variables affecting a particular local climate. In this sense our
ongoing research aims at developing an operative methodology through building a meso-
scale WRF model of this particular case, constrained by field climatic observations and
remote sensing data of land cover changes that might be adaptable to make projections in
different locations in the world.
4. Integration of albedo forcing and carbon footprint of greenhouses
production
In our previous research (Campra et al., 2008), we only addressed the impact on the local
climate of a change in land cover. However, the net impact on global climate of any geo-
engineering option must also be assessed, and three steps are required in the case of surface
albedo enhancement strategies:
1. Estimate carbon footprint of the development and maintenance of high albedo surfaces,
and compare it to the footprint associated to the economic activities over pre-existing
land cover
2. Integrate the global forcing of SW budget change and the forcing exerted by the change
in the net GHGs emissions associated to the land use change.
3. Develop meso-scale climate models of the area of implementation of albedo change, in
order to simulate the projected change in temperatures in the area of study and in
boundary domains around it, up to global scale.
Process GWP-20 GWP-100 GWP-500
Chan
g
e in biomass carbon stock 2 2 2
Carbon fixation b
y
crop -190 -190 -190
Greenhouse infrastructure 283 226 204
Soil
p
re
p
aratio
n
666
Greenhouse maintenance <1 <1 <1
Fertilizers 94 93 65
N2O emissions 55 57 29
Greenhouse dis
p
osal 6 3 2
Water
p
um
p
in
g
24 22 21
Green waste treatment 83 84 83
Overall emissions
(
a
)
365 303 223
Chan
g
e in surface albedo
(
b
)
-93 -134 -202
Net with albedo chan
g
e
(
c=a+b
)
272 168 21
Ratio (c) to (a) (%) 75 56 9
Table 2. Global warming potentials (GWP, in kilograms of CO2-eq.) at 20, 100 and 500 years
associated to the production of 1,000 kg of tomatoes under Mediterranean greenhouses in SE
Spain (From Muñoz et al., 2010).
For the case of greenhouse farming, we have estimated the carbon footprint of a
representative production by the rigorous methodology of Life Cycle Assessment (LCA)
(Muñoz et al., 2010). A cradle-to-gate LCA of an intensive production in the province of

Climate Change – Research and Technology for Adaptation and Mitigation
460
Almeria was first time carried out in this study. First, an inventory of all inputs to the farm
was collected. As background emissions data, the Ecoinvent 2.0 database was used (Swiss
Centre for Life Cycle Inventories, 2008). This analysis concluded that a gross Global
Warming Potential (GWP-100) of 303 kg CO2-eq. per ton tomato was generated this
greenhouse product system (Table 2).
The second step was to develop a novel methodology to integrate SW local radiative forcing
and LW global forcing exerted by the indirect GHGs emissions associated to the farming
activities, measured as GWPs. Our approach was to consider albedo increase equivalent to
“negative emissions” or “emission offset”, as this physical change exerts a negative radiative
forcing on the climate system opposed to the positive forcing generated by the increase in
GHGs. The calculation of CO2-eq. emissions related to surface albedo change was done with
the next three main equations:
1. SW radiative forcing (RFTOA) of a surface albedo change at the top-of-atmosphere
(TOA)
RFTOA = -RTOA Δαp, (1)
where RFTOA = -RS Ta Δαs
(RS= solar radiation at surface ; RTOA = solar radiation at the top of atmosphere; αp =
planetary albedo; αs = surface albedo; Ta = atmospheric transmittance)
2. CO2-eq emissions of SW radiative forcing
22TOA ,ref
2
2
RF ln2 2pCo
.CO air
Earth X air
AMm
CO eq AFMAF

 (2)
where A is the area affected by the change in surface albedo (m2), RFTOA is the SW radiative
forcing of a surface albedo change (W m2) , pCO2,ref is a reference partial CO2 pressure in the
atmosphere (383 ppmv), MCO2 is the molecular weight of CO2 (44.01 g mol−1), mair is
5.148×1015 Mg, AEarth is the area of the Earth (5.1×1014 m2), ΔF2X is the radiative forcing
resulting from a doubling of current CO2 concentration in the atmosphere (+3.7 W m−2), Mair
is the molecular weight of dry air (28.95 g mol−1), and AF is the average CO2 airborne
fraction.
3. CO2-eq emissions avoided through land use change, per functional unit (one kg of fresh
product)
2
FU
2LT
.RF AF
sa s
CO
RT
CO eq


 (3)
Where (LTFU) = land transformation per functional unit (m2)
As it will be explained in detail in the next section, one of the main sources of uncertainty in
these calculations is the calculated value of AF, i.e. the fraction of CO2 that remains in the
atmosphere after carbon cycle has partially removed it in a given time frame. In this study
we used a value of 0.48, calculated from the integration of Bern carbon cycle model in a time
horizon of 100 years, considering a GWP-100.
Including in the LCA the CO2-eq emissions equivalence of land cover changes is not a
simple task, as many methodological and conceptual problems arise. For instance, the choice
of time horizon in the GWP affects the impact of the albedo effect, increasing with time
horizon selected. Another source of variability in this methodology is the choice of service

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 461
lifetime for the activity (here we assumed and expected 50 years lifetime for greenhouse
production) (Muñoz et al., 2010). The emission offset increases for shorter lifetimes, for
example in this case it increased from 134 to 269 kg CO2-eq. per ton product when a 25-year
lifetime was considered but decreased to 67 kg CO2-eq. per ton tomato when it was
expanded to 100 years.
Through the application of this methodology, the gross GWP-100 estimated (303 kg CO2-eq.
per ton) was reduced to a net 168 kg CO2-eq. per ton tomato if the change in surface albedo
was taken into account. We concluded that the local radiative forcing caused by albedo
increase has a remarkable offset effect on the overall GHGs emissions balance of this
particular product system, equivalent to 44% of its gross indirect emissions when GWP-100
was considered. However it must be taken into account that albedo effect is always
reversible: if in the same system albedo is changed but returned to its previous state at the
end of the service lifetime, the net albedo change, and thus, the CO2-eq. emissions offset,
will be zero.
Another particular case where albedo could have an important influence in the CO2-eq.
emission balance is in the context of forestry or any other system involving sharp changes in
land cover reflectivity. In this sense, it must be taken into account that forestry plans aimed
to mitigate global warming by carbon fixation in biomass should have a complementary
assessment of the equivalent forcing exerted by the change in land cover reflectivity. In
some regions, particularly in high latitudes where snow cover remains in winter months,
this forcing could offset the climatic benefits of carbon fixation (Betts, 2000). This might also
happen in semi-arid environments, where the previous disperse shrubland albedo is
generally much higher than the forested land albedo.
In any case, other climatic effects apart from temperature changes might be worth to
consider, as well as other “conventional” environmental benefits of forestry plans should be
regarded as a whole. For example, deforestation in the tropics decreases evapotranspiration
rates and increases sensible heat fluxes, resulting in regionally decreased precipitation and
increased surface temperature (Bala et al. 2007). In conclusion, new metrics different from
radiative forcing and carbon offset might be advisable to take into account these kind of
effects of land use change on climate (Pielke et al., 2002). In the words of Dr. R.A. Pielke, “a
more complete indication of human contributions to climate change will require the climatic
influences of land-surface conditions and other processes to be factored into climate-change-
mitigation strategies. Many of these processes will have strong regional effects that are not
represented in a globally averaged metric.” In conclusion, our study is just a first operative
approach to highlight the methodological problems that arise when an integration of land
albedo changes with associated GHGs emissions is required prior to the development of
climate policy regulations related to land use changes.
5. Estimation of carbon offset equivalences of global albedo enhancement
A key conflicting issue introduced by Akbari et al, 2008 is the conversion of SW radiative
forcing (SWRF) generated by land cover changes to equivalent CO2 emissions offset. In this
paper, it was estimated that a carbon emissions offset of 44 Gt CO2 could be achieved by
albedo enhancement of main global urban areas. Menon et al. (2010) used the same
conversion factors and raised this figure to 57 Gt CO2 using a summer General Circulation
Model (GCM) simulation. These two works are a landmark approach for the estimation of
global GHGs offset by albedo increase at urban areas, and offer a remarkable scientific basis

Climate Change – Research and Technology for Adaptation and Mitigation
462
for the development of more inclusive climate protocols in the post-Kyoto agreements that
do not just rely on GHGs emissions reductions as the only mitigation currency. However,
these global estimates should be carefully revised when local or regional effects are to be
considered. Furthermore, as we have shown before, there are still complex methodological
issues when we pretend to express SWRF due to albedo changes in terms of equivalent
reduction in carbon emissions. There are at least 3 main sources of uncertainty that must
carefully be taken into account:
1. The calculation of SWRF exerted per unit albedo change, and the use of global
or regional averages of this parameter in the estimation of carbon offsets at particular
cases
2. The equivalence parameter between SWRF per unit albedo change and the amount of
atmospheric carbon that would exert the same but opposite forcing
3. The conversion from that atmospheric carbon to equivalent carbon emissions reduction
5.1 SWRF per unit albedo change
There are still significant uncertainties in the SWRF generated per unit of albedo increase,
both at global and local scales. Radiative forcing associated with land use changes has been
derived largely from GCM simulations (Hansen et al. 1997; Betts, 2001), using climate
simulations, and there are very few observational estimates of this “missing” radiative
forcing (Myhre et al. 2005). Some of these studies have shown that the GCM computations
significantly underestimate the local SWRF due to land use changes, with observational
estimates even more than twice the model-derived values over some regions (Nair et al.,
2007). Finally, an additional factor not to be forgotten is that Earth radiation budget changes
with time, making more confusing to determine the best value from literature.
In the case of observational studies, such as our work in Almeria greenhouses (Campra et al.
2008), we used and empirical approach and calculated this forcing in our area of study from
the outgoing SW radiation (OSR), by the formula from Betts (2001):
SWRF = OSR final land cover - OSR fprior land cover (4)
OSR values were calculated from averaged satellite MODIS data, and SW incoming
radiation using an insolation model that accounted for local geographic factors and
transmissivity in clear sky conditions (Van Dam, 2000). By this method we calculated an
annual averaged SWRF of -19.8 W m-2 associated to an average increase albedo of 0.09 in the
study area. From these data we can obtain an observational estimate of -2.2 W m-2 of SWRF
for every 0.01 albedo increase. This forcing is almost double than the forcing of -1.27 W m-2
estimated by Akbari et al. (2008) at global scale. Hansen et al. (1997) did not provide any
direct estimate of SWRF associated to a global albedo increase. Instead they used a global
climate model with an idealized global geography, and determined the effectiveness of
surface albedo forcing applied on fictitious land masses. As they state, this approach was
intended to analyze climatic mechanisms, rather than to simulate impacts on specific real
world regions. On the contrary, Hatzianastassiou et al (2004), used a radiative transfer
model coupled with climatological data to estimate Earth SW radiation budget at top of
atmosphere (TOA), and performed sensitivity tests of their model to changes in relevant
parameters such as albedo, reporting a 3.3 W m-2 change in OSR at TOA with a simulated
10% increase in surface planetary albedo. If we combine this sensitivity of SW radiation
budget at TOA with the estimation of surface albedo of 0.129 given by these authors with

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 463
the same model (Hatzianastassiou et al, 2005), a 0.01 increase of surface albedo equals to a
global SWRF of -2.57 W m-2 at TOA, again far from Akbari et al. (2008) lower estimate.
It is important to notice that surface albedo changes do not produce equivalent changes in
planetary albedo, and must be adjusted by atmospheric absorption and reflection. Thus,
when comparing forcings of GHGs TOA, and SWRF due to land use change, both estimates
must refer to the net radiative flux change at the same level in the atmosphere, and for the
same state of adjustment of the stratospheric temperature profile (Hansen et al., 1997). In
this sense, as radiative forcing estimates of GHGs generally refer to values at TOA (Hansen
et al., 1997, Myhre et al., 1998), so radiative forcing due to albedo increase must be estimated
at TOA as well for comparison. However, adjustment of stratospheric temperatures is not so
relevant when dealing with SWRF.
Therefore, the value of estimated global SWRF per 0.01 albedo increase of -1.27 W m-2 used
in Akbari et al. (2008) needs further discussion, as all CO2 offset potential calculations are
drastically affected by this estimation. For the calculation of this key parameter, they use an
averaged value (1984-2000) of total incoming SW Radiation (SWDOWN) at surface of 172
Wm-2, obtained from Hatzianastassiou et al. (2005). This value is at the lower end of
previous estimates reviewed by these authors (169-219 Wm-2). Similarly, the value of net
SWDOWN at surface (total minus reflected) given by these authors (149 Wm-2), is at the
lower range of earth energy budget estimates reviewed (142-191 Wm-2). These values are
significantly smaller than most previous estimates, by up to 30 Wm-2, and disagreement is
associated with differences in atmospheric absorption. However, Earth radiation budgets at
surface and TOA from Hatzianastassiou et al. (2005, 2004) seems very reliable, as they have
been validated against surface measurements with good agreement with the model.
Another source of uncertainty of Akbari et al. (2008) estimate is that it is based on the
combination of simulated data from two different modelling studies, (Kiehl and Trenberth,
1997, and Hatzianastassiou et al. 2005), thus resulting in a lack of methodological coherence.
There is a remarkable difference in net SWDOWN radiation between both estimates, that
arises from an overestimation of absorbed SW radiation by atmosphere in the last study
(26.7%), compared to earlier studies (20%). However, when calculating f (fraction of
radiation absorbed by the atmosphere), Akbari et al. (2008) use a SWDOWN value of 172
Wm-2 from Hatzianastassiou et al. 2005, and then simply scale down data from (Kiehl and
Trenberth, 1997), considering the value of 30 Wm-2 as the OSW radiation AT SURFACE.
However, this value is referred in the modelling as the OSW radiation AT THE TOA
(although the “30” label in Figure 7 can mislead). It makes no sense to reduce its magnitude
by atmospheric correction (f) as Kiehl and Trenberth have already accounted for any further
absorption in their 67 Wm-2 value of total SW absorbed radiation in atmosphere.
In order to make this key issue clearer, we can better use a simple analytical approach
recently employed to evaluate the radiative forcing potential of different geo-engineering
options (Lenton & Vaughan, 2009). Forcing at TOA caused by planetary albedo change Δαp
can be estimated from average incoming solar radiation at TOA (DSR), by the formula:
SWRFTOA = DSRTOA Δαp (5)
But planetary albedo has two components, atmospheric albedo (αa), and surface albedo (αs),
and the latter must be corrected at TOA with atmospheric absorption (Aa) and atmospheric
albedo (αa). This way, forcing due to land albedo increase (SWRF) can be calculated as:

Climate Change – Research and Technology for Adaptation and Mitigation
464
SWRF = DSRTOA [Δαs (1- αa) (1- Aa)] (6)
Lenton & Vaughan (2009) make a global estimation of forcing using global energy budget
values (αa, Aa, and net DSRTOA) taken from Kiehl and Trenberth (1997) to obtain an
SWRFTOA = DSRTOA 0.579 Δαs. Through this formula we can obtain a parameter of SWRF for
every 0.01 increase in surface albedo equal to -1.98 W m-2. This is the constant parameter
value these authors use to assess the potential for all geo-engineering options based on
surface albedo increase.
However, if alternatively we use global energy budget values from Hatzianastassiou et al.
(2005), then
SWRFTOA = DSRTOA 0.50 Δαs (7)
and SWRF for every 0.01 increase in surface albedo results in -1.71 W m-2, still well above
Akbari et al. (2008) estimate (+34%).
These conflicting issues have been exposed above to highlight that forcing per unit to albedo
increase is a key parameter that needs a more detailed analysis and validation against local
surface measurements, as the final associated carbon offset is directly biased by the value of
choice.
As an example, in Table 3 is summarized the big changes in final annual CO2 offset potential
of urban albedo increase at urban areas in the state of California, implemented in a 15 year
period, depending on the value used in different works for this parameter.
Akbari
et al.,
2008
Hatzianastassiou
et al., 2005
Lenton &
Vaughan,
2009
Lenton &
Vaughan,
2009
Campra et
al., 2008
Data source1 Ref. RAD ERB1 ERB2 AL
SWRF per
+0.01 albedo
(W m-2)
-1.27 -2.57 -1.98 -1.71 -2.2
California
Urban offset
(MTCO2-
eq/year)
31 63 48 42 54
1 Data used for estimations: Ref.= from Kiehl and Trenberth, 1997, and Hatzianastassiou et al. 2005;
RAD= From radiative transfer model; ERB1= based on radiation budget from Kiehl and Trenberth,
1997; ERB2= based on radiation budget from Hatzianastassiou et al., 2005; AL= empiric value for
Almeria study case, from MODIS OSW data (lat N 36º 45’)
Table 3. Forcing per unit albedo change and estimation of associated carbon emissions offset
in California urban areas, according to the values of this parameter in different works
Finally, it must be taken into account that energy radiation budget of the Earth changes with
time, and this is affecting the value of this key parameter. For instance, Hatzianastassiou et
al. (2005) detected a decadal increase in solar absorption of 2.2 Wm-2, over the period 1984-
2000, probably due to reduction of low level clouds.
On the other hand, a linear relation between global albedo increase and SWRF cannot be
directly applied to local or regional cases, whatever the value of the equivalence parameter
used. The uncertainties and the geographic variation of the equivalence between albedo

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 465
increase and SWRF are too big as to simply assume an averaged value of -1.27 W m-2 , for
any location in the world. Due to variability of latitude and average cloud cover, there will
be significantly different values of this parameter than any global average estimate,
resulting in an underestimation or over estimations of CO2 offset potentials of albedo
increase.
Ultimately, given the uncertainties in global estimates, in practice the issue of applicating
global studies to particular urban areas could be overcome by the use of updated local
surface based observational estimates of radiative fluxes, averaging long term climatic data.
The effectiveness of the changes in surface albedo is a function of the geographic location of
the changes. Estimation of this key parameter must include the time-space variability in net
incoming solar radiation fields. Local observational estimates of average SWDOWN and
OSR at surface are needed. This estimates must integrate different factors, mainly latitude
and average cloud cover, but also key variables in urban areas such as aerosol pollution.
Updated surface radiation data sets can be used to determine the annual average of net
radiation. Alternatively, SWRF can be calculated from OSR data at TOA obtained from
remote sensing products, but resolution of these products might do more practical the use of
surface observations when dealing with urban albedo changes.
5.2 The equivalence parameter between SWRF per unit albedo change and the
amount of atmospheric carbon offset that would exert the same forcing
This issue ultimately deals with the choice of a correct parameter that accounts for the
longwave radiative forcing (LWRF) exerted by a unit CO2-eq or the estimate of adjusted
(TOA) radiative forcing per ton CO2. Akbari et al. (2008) use a RF value of 0.91 kW/tonne of
CO2 for a 385 ppmv concentration, based on estimates by Hansen et al. (2005) and Myhre et
al. (1998), who use a RF [Wm−2] = 5.35 ln(1 + ΔC/C), where ΔC is the difference from pre-
industrial times to current CO2 concentration. The problem is that this parameter can have
different values according to the methodological approach, and must also be actualized with
present concentration.
5.3 The conversion from atmospheric carbon equivalence to carbon emissions
reduction
Given the ultimate goal of computing albedo changes in climate policy, a key issue has
arisen when the forcing on climate of a static alteration of the energy budget has to be
compared to time-varying forcing exerted by emissions of GHGs. The standard emission
metric used in United Nations Framework Convention on Climate Change (UNFCCC) and
carbon markets is the GWP (Forster et al., 2007), that was formulated to compare the
contribution of different GHGs to climate change over an arbitrary period of time, set in 100
years in the Kyoto Protocol. The calculation of GWPs of different agents involves the
integration of their forcing per unit mass increase in a given time horizon, and includes a
time-dependent abundance of both the gas considered and the reference gas (CO2). One of
the problems of GWP metrics is that it does not account for the different residence times of
different forcing agents. This problem of time varying impacts becomes even more complex
when trying to express albedo forcing in terms of GWP. There are two basic conflicting
issues here:
1. Whether the use of a correction factor based on CO2 decay concentration is appropriate
or not when comparing to equivalent instantaneous forcing of albedo changes.

Climate Change – Research and Technology for Adaptation and Mitigation
466
As we showed in our approach to the integration of albedo forcing and carbon footprint
(Muñoz et al., 2010), this mixing of a static invariant forcing (SWRF) and a time
dependent forcing (LWRF
CO2
) that changes with gas concentration is still controversial
and methodologically complex, and might be an inappropriate approach.
2. The choice of a given value for the CO
2
airborne fraction (AF). If this correction is applied,
the methodological approach chosen to integrate the carbon decay in a given time frame
can yield different values of the AF, and marked differences in final carbon offsets.
In one of the pioneering works dealing with the integration of albedo and carbon forcing,
Betts (2000) accounts for an AF of emissions of 0.5, assumed to remain constant over forest
growth timescales. This figure is used as well by Akabari et al. (2008), and Menon et al.
(2010). This value of AF is obtained by a simple arithmetic average of the fraction of fossil
fuel emissions remaining in the atmosphere each year for the period 1958-2005 (Denmann,
2007). However, the range of AF in those years is almost (0.3-0.8), and the inter-annual
variability is two broad for this fixed value of 0.5 to be considered as an intrinsic property of
the climatic system. Furthermore, simulation studies constrained by observations give a
similar range of uncertainty in the value of AF, and future projections yield lower AF as CO
2
concentration increases in the atmosphere (Fig. 5).
Fig. 5. Predicted increase in the fraction of total emissions that add to atmospheric CO
2
.
Changes in the mean partitioning of emissions as simulated by the C4MIP models up to
2000 (black symbols) and for the entire simulation period to 2100 (red symbols). The box
shown by the dotted line is a constraint on the historical carbon balance based on records of
atmospheric CO
2
increase. The black and red diamonds show the model-mean carbon
partitioning for the historical period and the entire simulation period, respectively. (From
Denmann et al., 2007).
As it can be seen, the choice of an AF of 0.5 seems too simplistic, and other proposals
address this issue by introducing correction operations based on atmospheric carbon decay
models. For instance, in our work on greenhouses footprint (Muñoz et al, 2010) we used an

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 467
simple integration of the Bern carbon cycle model (Joos et al, 1996) in a time horizon of 100
years, generally used in the calculation of GWP, to obtain an AF value of 0.48. According to
this model, after 10 years 66% of the initial emission remains in the atmosphere, while only
36% remains after 100 years. As a consequence, the choice of a time horizon affects the
magnitude of the CO2-eq.emissions. In a more complex formulation, Schwaiger & Bird
(2010) use a convolution operation to integrate the instantaneous forcing by albedo change
and the inverse of a carbon decay function.
In conclusion, the conversion of albedo forcing into emissions equivalent is still an open and
challenging issue that needs further considerations and consensus prior to the development
of accounting standards that provide a tool to implement albedo enhancement policies. It
must be bear in mind that, if AF no correction is applied, the value of carbon offset
estimations will be at least two fold lower than values corrected with AF.
6. Intensive use of land and high yield conservation
By now, in our estimation of the climatic impact of greenhouse farming development we
have accounted for on-site impact of changes in the solar energy budget, and for the global
impact related to indirect GHGs emissions required for all inputs and processes in the farm.
But there is another remarkable indirect trade-off of this land use transformation that must
be accounted for, if we wish to have an overall picture of the climatic and environmental
effects on the whole territory of the influence of this productive system. When dealing with
changes in the use of land and natural resources by a given human population, not only
land use changes, but also associated local population migrations, and changes in the
intensity of land use in a broader area of their historical settlement should also be included
in the analysis. This way, in the southern Mediterranean coast of Spain, the shift from
extensive dry crops towards irrigated intensive greenhouse farming has generated the
concentration of highly profitable farming activities in a limited portion of the settling
territory of the population, while low income extensive farming and grazing activities have
been abandoned in an area around ten times larger. This has boosted a spontaneous
recovery of natural vegetation, and allowed the development of forestry plans in the
abandoned farmland, with the natural or aided generation of huge carbon sinks in soils and
biomass. This sinks should be accounted for when estimating the net environmental and
climatic impact of greenhouse farming, urbanization processes or any intensification of land
use along with similar changes in the human use of the surrounding territory.
As an example, I will summarize the basic figures of this non intentional trade-off, restricted
to the province of Almeria for practical statistical reasons. However, it is difficult to
determine the geographical limits of the surrounding area of influence affected by
greenhouse farming development. The sudden generation of this new source of income has
mostly attracted populations from inland mountains of the province of Almeria, but also
from neighbouring province of Granada, and furthermore, an intense migration flow of
labourers from 200 different countries around the globe seeking for alternatives to the use of
their own homeland.
The province of Almeria has a total extension of 877,400 ha. The population has grown from
357,000 in 1957 to 667,600 in 2008. The Gross Value Added (GVA) of the agricultural sector
in this province has multiplied 10 times the value in 1957, and 3 times since the beginning of
the greenhouses boom in the early 80s, turning from the poorest provinces in Spain to one of
the biggest agricultural exports area in the Mediterranean. At the same time, it has turned
from a source of emigrants to an attracting pole of migrants from all over the world.

Climate Change – Research and Technology for Adaptation and Mitigation
468
Despite this economic boom and population growth, the extension of natural areas has not
decreased in the province in the last decades (Fig. 6). Greenhouse farming has been
concentrated in coastal flat lands accounting for 27,000 ha, just a 3% of the total land in the
province. On the contrary, hundreds of thousands of hectares of dry crops and semi-arid
pastures (40-50% of total surface of the province) have been abandoned inland, and natural
Mediterranean plant communities have since then developed a dynamic process of
succession that has transformed thousands of hectares to new shrublands with a potential
forestry use. Most abandoned crops do not show in the statistic summary in Fig 5, as they
are still accounted in official statistics as farmland, and a big portion of pastures that have
also been abandoned are included in the natural areas category. In addition, to this
spontaneous recovery, Spanish government plans from the 50s, and more recent EU
assistance to farm tree planting have increased the forested surface in 90% from 66,000 ha in
1957 to present 130,000. Along with this, historical erosion in this semi-arid territory has
been reduced by the abandonment of extensive areas of mountain dry crops that suffered
vegetation clearance and tillage in high steep slopes.
This pattern of land use change in the province (Fig. 6) has been boosted in great part by the
new source of income generated by off-season greenhouse production, an activity that has
grown thanks to the conjunction of a very specific climatic and export marketing condition.
Nonetheless, the growth in population, per capita income, along with the reduction in total
extension of human use of land, and the increase and recovery of natural areas characterize
a pattern of economic development based on the intensification and concentration of land
use that can be adapted to different latitudes on the world in order to achieve both local
populations needs and natural habitats and cycles maintenance and regeneration.
Fig. 6. Rates of change in population and different land use categories in the province of
Almeria during the period 1956-2003.
-100
0
100
200
300
400
500
600

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 469
In terms of climate change mitigation, it is important to account for this new carbon sinks
generated in this abandoned farmlands. Due to the intense dynamics of this land use
changes, the province of Almeria holds one of the most intense carbon sinks in the south of
Spain (Agudo, 2007). According to the last regional carbon sink inventory, elaborated
according to the IPCC methodology for Land Use and Land Use Change and Forestry
(Penmann et al., 2003), the forest areas in the province would be nowadays fixing around 3.8
million tons of CO2 (Table 4). This figure, only accounting for biomass fixation, should be
increased by fixation in soils in regeneration in abandoned farmlands, but this huge sink has
not been estimated yet in the area.
Net carbon fixation in biomass Province of
Almeria
TCO2 ha-1 stock surface (ha-1 ) TCO2 ha-1 a-1 TC ha-1 a-1
Forest Land
(only trees) 81 154,000 2.5 385,000
Forest Land
(shrublands) 120 335,000 10.4 3,490,000
Total
3.87 M TCO2
Table 4. CO2 fixation in natural areas in the province of Almeria (from Agudo et al., 2007).
This phenomenon of land use change, associated farmland abandonment, and forests
recovery is not unique of greenhouse farming, but is a common trend in many developing
areas in the world, such as the northern Mediterranean basin and China (Fig. 8), through
natural expansion and afforestation programs.
Global deforestation is mainly due to conversion of forests to agricultural land. However,
and though each year about 13 million hectares of the world's forests are lost due to
deforestation, the rate of net forest loss is slowing down, thanks to new planting and natural
expansion of existing forests due to abandonment of pastures and farmlands. This way, net
forest loss dropped from 8.9 million hectares per year in the 90s to 7.3 million hectares per
year in the period 2000-2005 (FAO, 2005).
For instance, EU assistance to forestry under the regulation 2080/92, forestry measures on
farms, aimed to reduce agricultural surpluses and enhance forest resources, and “combat
the greenhouse effect by absorbing carbon dioxide”. In the first period of this plan, one
million farmland in EU changed to forestry between 1994 and 1999, a biggest portion in
Spain (Evaluation, 2000). Evaluations have shown that this measure has led to the
conservation and regeneration of valuable habitats and increases in the use of land for
environmental purposes.
It is very important to highlight that this trend goes in the direction of the reversal of
historical land use change from pre-industrial reference data of 1750, characterized by a
global replacement of forests and natural vegetation by farmland and pastures (Fig. 7). In
the last 40 years, 500 million ha have been added to global farmland, 300 out of them are
pasture land for extensive livestock grazing. Nowadays, around 40-50% of land surface has
an agricultural use, and 80% of deforested land changes towards agricultural or pasture use.
Furthermore, present population growth and demands make unsustainable to maintain this

Climate Change – Research and Technology for Adaptation and Mitigation
470
trend towards extensive use of land in the present century. Human population is projected
to grow from 6,700 million to 9,000 milling around 2050, with skyrocketing demands for
meat consumption in developing countries like China and India, due to higher income
levels. Is has been estimated that food demands will in crease in 50% in the XXI century.
This means increased human use of land, with higher pressure on natural habitats that will
additionally suffer intense stress from climatic change. Less adaptation options through
migration will be available to natural populations of plants and animals. However, best
soils and potential farmland have already been occupied, and further tillage will have to be
done in marginal land, with lower quality soils, higher slopes or worst climatic conditions,
with lower productivity yields, with growing environmental and sustainability problems.
The only feasible alternative then to make with higher food production compatible with
natural habitats conservation and adaptation requirements in a changing climate is the
reduction and concentration of human land use through the development of high yield
production systems, such as greenhouse horticulture. Additionally, local populations must
be offered alternative sources of rent in order to abandon the extensive low income use of
land, or they might need to migrate to growing urban areas.
In developed regions such as US and Europe, farmland extension is maintained or
decreasing, and forests extension is stabilized or promoted by forestry plans, feasible due to
the generation in the last decades of alternative sources of income for rural population, and
urbanization processes.
Fig. 7. Potential natural vegetation and land use changes from preindustrial time to present
due to agriculture and livestock development (From Forster et al., 2007).

Global and Local Effect of Increasing Land Surface Albedo as a Geo-Engineering
Adaptation/Mitigation Option: A Study Case of Mediterranean Greenhouse Farming 471
The environmental benefit of this pattern of land use change been named as “high yield
conservation”, and the essential message states that “growing more crops per acre leaves
more land for Nature”. On the other hand, intensifying food production systems requires
higher energy inputs. This issue of energetic supply must be addressed, but is out of the
scope of this chapter. This novel approach, that reconciles human land use of the Earth with
natural habitats conservation and regeneration and enhancement of natural cycles, is worth
to deserve much more consideration by climate and environmental policies, and might
become one key option of the human sustainable use of the available surface of the planet in
the present century.
Fig. 8. Recent rates of net forest area change (2000-2005). Red >0.5% decrease per year;
Green > 0.5% increase pr year; Grey = change rate below 0.5% per year (FAO, 2005).
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