1. Introduction
1.1. Global overview of fuelwood use and patterns
Approximately 2.6 billion people in the world currently use fuelwood (FW) and
charcoal, as their principal energy source. Globally, these two woodfuels
account for 10% of primary energy or 50.5 EJ. Of this figure, about 31 EJ are
used mostly in open fires and rustic traditional stoves to mainly cover needs
such as cooking and heating in the poorest households of developing countries.
People relying on fuelwood are mainly located in Asia, India, Sub-Saharan
Africa, Indonesia and Latin America where users account for 37%, 28%, 22%, 6%
and 2% of the total users, respectively (Chum et al., 2011).
Reliance on FW has positive and negative impacts. On the positive side, FW is a
potentially renewable energy source, it is locally available in most
circumstances and it represents zero monetary cost for those families
collecting the fuel. Fuelwood can come as a byproduct of other activities such
as agriculture or forestry. When conducted on a sustainable basis, harvesting
FW from natural forests reduces the incidence of fires and pests. Traditional
devices –such as three-stone fires– are well adapted to the local needs and often represent zero monetary cost. FW
use is also a fundamental social activity among women in rural areas because
while sometimes other family members could also gather FW, only women carried
out cooking tasks.
On the negative side, harmful particles and gases are released when FW is burned
in traditional open fires and they severely affect FW users` health as well as
the local and global environment. Particularly, FW smoke has been related to
several health problems that increase the mortality rates or disease causes
(Bruce et al., 2006; Naeher et al., 2007; Pérez Padilla, Schilmann & Riojas, 2010; Torres et al., 2008). FW smoke is also classified as a possible carcinogen agent by the
International Agency for Research on Cancer (IARC) (Straif et al., 2006). Health problems derived from FW smoke exposition range from difficulty
to breath and acute respiratory illness that could lead to premature deaths
mainly in women and children. Under a sustainable extraction pattern, emissions
of carbon dioxide or CO2 derived from FW combustion are considered zero (also
named neutral), that is the CO2 emitted when the wood is burned is re-captured by re-growing
trees through photosynthesis. Nevertheless, when FW is burned in traditional
devices an incomplete combustion occurs and other powerful greenhouse gases and
pollutants such as methane (CH4), nitrogen dioxide (NO2), and carbon monoxide
(CO) are released. Black carbon is also emitted during incomplete combustion of
fuelwood. Therefore, traditional fuelwood use could also contribute to climate
change (Arora, Jain & Sachdeva, 2013; Johnson et al., 2008; Johnson, Edwards & Masera, 2010; Preble et al., 2014; Roden et al., 2009; Schauer et al., 2001; Shen et al., 2013a, 2013b, 2014).
Understanding the evolution of FW use and its environmental impacts has proved a
challenging goal. Different models have been proposed to explain FW use
dynamics in developing countries. The fuelwood gap model was the first attempt
to describe FW demand and supply relationships. This model predicted a severe
FW energy crisis resulting from a combination of a growing population reliant
on firewood and a depletion of FW supply due to an increasing deforestation
(Openshaw, 1974, 1978; Eckholm, 1975). However, this crisis –to the extent predicted by the model– never occurred. Later, the energy ladder model (also known as the energy transition or fuel switching model) described how people relying on FW to cover their main energy needs could
rapidly switch from “traditional” fuels –at the bottom of the ladder– to “modern” fuels –at the top of the ladder– such as LPG as soon as the household income increased (Baldwin, 1987; Smith,
1987; Hosier & Dowd, 1988; Leach & Mearns, 1988; Leach, 1992). This model has failed to explain residential fuel
transitions in developing countries, very particularly within rural and
peri-urban areas.
Masera, Saatkamp and Kammen (2000) proposed an alternative model to the fuel
switching approach. This model explains that rather than switching linearly and
permanently from traditional to modern fuels, people stack different fuels to
cover their energy needs according to the tasks each fuel performs the best.
Stacking also provides households with more flexibility and reliability in case
of shortages of modern fuels. LPG and other modern stoves are also not well
adapted to local cooking practices (such as making tortillas in Central America or njeras in Ethiopia). Fuel stacking patterns have prevailed despite many governments
have launched active policies to boost the use of modern fuels (Masera et al., 2015). Furthermore, the probability that this stacking pattern continues in
the mid-term is high as projections highlight that near two billion people are
going to still relay on FW in the year 2040 (IEA, 2016).
Additionally, examining the spatial distribution of FW users –and their related impacts– is also very important because FW use patterns are very heterogeneous and
highly dependent on geographic variables (Ghilardi, Guerrero & Masera, 2007, 2009; Masera, Drigo & Trossero, 2003; Masera et al., 2006). Spatially explicit and multi-temporal FW models are needed to better
understand FW use dynamics at the household level. Recent developments in this
area include Woodfuel Integrated Supply/Demand Overview Mapping (WISDOM) and
Modeling Fuelwood Saving Scenarios (MoFuSS) models, which have been applied in
several regions of the world and at different geographic scales –from pan-tropical to landscape level analysis (e.g. Bailis et al., 2015; Ghilardi, Tarter & Bailis, 2018).
WISDOM is a spatial-explicit method for highlighting and determining priority
areas of intervention and supporting wood energy/bioenergy planning and policy
formulation. WISDOM supports strategic planning and policy formulation, through
the spatial integration and analysis of existing demand- and supply-related
information and indicators, and by modeling access patterns to supply sources.
It provides relative/qualitative values such as risk zoning or criticality
ranking, highlighting, at the highest possible spatial detail, the areas
deserving urgent attention and, if needed, additional data collection. In other
words, WISDOM serves as an assessing and strategic planning tool to identify
priority places for action. WISDOM is a spatial, non-temporal model, meaning
that applies geoprocessing operations such as proximity, overlay, or cumulative
cost, i.e., beyond maps of administrative units depicting data from a table, but lacking
any temporal dynamics (Masera et al., 2006).
MoFuSS is an open-source freeware developed to evaluate potential impacts of
firewood harvest and charcoal production over the landscape. It’s a GIS-based model that simulates the spatio-temporal effect of woodfuel
harvesting on the landscape vegetation and that accounts for savings in
non-renewable woody biomass from reduced consumption. MoFuSS is a
spatiotemporal model, meaning that incorporates both spatial dynamics and
geoprocessing operations (Ghilardi et al., 2016).
In Mexico, FW is the main energy source in the rural sector, and accounts for
almost 40% of total residential energy consumption in the country. Economic and
environmental accessibility, as well as social and cultural factors play an
important role in the persistence of FW use. Fuelwood users accounted 22.5
million and FW consumption reached 19.4 million tons of dry matter (MtDM) in
2010. Liquefied petroleum gas (LPG) is the other main fuel in the residential
sector in the country. Penetration of LPG has been steadily increasing in rural
areas, largely as a complement rather than a substitute to FW. Several
projections have estimated that FW use will remain the dominant rural cooking
fuel in the short and middle term in Mexico (Diaz, 2000; Serrano et al., 2014).
In this study, we examined the historical evolution and implications of FW
consumption in Mexico from 1960 to the present. We first review the different
theoretical approaches that have been used to explain FW use dynamics in
developing countries. We then use Mexico as a case study. We argue that in
Mexico, energy transitions at the household level have followed a multiple fuel
use pattern, where an increasing adoption of LPG has not displaced but mostly
complemented FW use. We also present future scenarios of FW use assuming
different socio-demographic and technological variables. We conclude the paper
examining the implications of the current patterns of fuelwood use in the
future in terms of fuelwood consumption, numbers of users and emissions of
greenhouse gases.
1.2. Theoretical approaches to energy transitions in the residential sector
1.2.1. Fuelwood Gap model
During the 1970’s a firewood energy crisis was predicted assuming that reliance on fuelwood by
an increasing population would rapidly deplete the available forests.
Plantations had to be established to avoid a major ecological disaster
(Openshaw, 1974, 1978; Eckholm, 1975). Even global institutions such as the
Food and Agricultural Organization (FAO) and the World Bank relied on these
assumptions (Eberhard, 1992). The fuelwood energy crisis was modeled as the gap
between sustainable fuelwood supply and demand. This gap was estimated to
increase along with population growth. For some regions in Africa, the fuelwood
gap model predicted a total devastation of the fuelwood stock within 5 to 30
years. These predictions motivated large- policy interventions to decrease this
gap. Considerable afforestation or demand driven measures by dissemination of
efficient cookstoves were the most common elections to reinstate the balance
(Eberhard, 1992). However, the studies supporting a general energy crisis fail
to account for fuelwood use resilience by means of regrowth or that people
managed tree growing to cope with fuelwood scarcity (Leach & Mearns, 1988; Bailis et al., 2015). As a result, recent studies suggested that woodfuel sustainability
depends on local factors that are generally dismissed when using aggregated
data and therefore they highlight the heterogeneous nature of fuelwood
surpluses or deficits across regions (Eberhard, 1992; Bailis et al., 2015).
1.2.2. Energy ladder model
Energy use in the residential sector was explained early by the energy ladder
model (Figure 1). This model sought to explain household decisions when
substituting or switching between fuels at a household level by means of
socioeconomic status (Baldwin, 1987; Smith, 1987; Hosier & Dowd, 1988; Leach & Mearns, 1988; Leach, 1992). The model assumes that as a household income
increases, people “naturally” abandon dirty, less costly fuel such as dung, charcoal or fuelwood –bottom of the energy ladder– and opt for “modern” fuels that are “cleaner”, more expensive and less pollutant such as LPG –top of the energy ladder– (Smith, 1987; Hosier & Dowd, 1988). The rationale behind this model was that the transition from the
bottom to the top of the energy ladder responded not only to pursue energy
efficiency or to decrease indoor air pollution but also to gain status. As
modern fuels are also used by means of “advanced” technologies, families desire to move up the ladder to demonstrate prosperity
(Masera, Saatkamp & Kammen, 2000). Nevertheless, this model fails to explain observed dominant
households’ decisions such as combining (i.e. stacking) different fuels options according to certain cooking tasks or to
ensure coverage of households’ energy needs and, therefore, only changing partially to modern fuels (Masera & Navia, 1997; Masera, Saatkamp & Kammen, 2000; Masera et al., 2015). The energy ladder model has proven insufficient to describe household
energy transitions in rural areas where economic, and even cultural aspects
need to be addressed to understand energy dynamics (Masera, 1993; Masera & Navia, 1997; Masera, Saatkamp & Kammen, 2000; Masera et al., 2015). This approach has even been limited while explaining energy transitions
in urban areas of developing countries (Hiemstra-van der Horst & Hovorka, 2008).
FIGURE 1
The classic energy ladder diagram
Source: Kowsari and Zerriffi (2011: 7505-17).
1.2.3. Fuel stacking model
As a response to the energy ladder failure to describe household energy
transitions, Masera, Saatkamp and Kammen (2000) proposed an alternative
approach, the multiple fuel model (Figure 2), to explain fuel use dynamics in the residential sector after
conducting a longitudinal study in one village and analyzing data from a large-
scale survey in four states in Mexico. This study showed that a fuel stacking
approach better described actual household fuel use dynamics. The proposed
model also encompassed previous observed patterns of multiple fuel use in other
countries (Evans, 1987; Leach & Mearns, 1988; Fitzgerald, Barnes & McGranahan, 1990). It has been increasingly documented that a multiple fuel use
strategy is more common than rare in developing countries, and not necessarily
a short-term transitional stage but a rather mid to long-term strategy1. A multiple fuel model is able to describe the stacking behavior within the
process of fuel use decision-making among households. It recognizes that the
adoption of modern fuels is a complex process where economic, social and
cultural aspects interact, rather than simply a change from one cooking fuel to
another. Furthermore, inter-fuel substitution not only depends on decisions at
the household level but also on the macroeconomic context and policies at the
national level, like investment in roads or establishment of subsidies to
purchase modern fuels like LPG. Once a household overcome the LPG stove
investment, other barriers to maintain a steady use of LPG are likely to arise.
With the LPG purchase, families very often build even a new kitchen and all the
furnishing and cookware that this involves. These barriers together with income
variability in rural households, position LPG adoption as a complex process
taking place mostly in mid- high or high-income families in the communities
(Masera, Saatkamp & Kammen, 2000). The multiple or stacking fuel model better adapts under the vast
variety of circumstances existing in most rural and suburban areas of
developing countries (Masera, Saatkamp & Kammen, 2000)2.
FIGURE 2
Energy stacking diagram
Note: ICT is information and communication technology.
Source: Kowsari and Zerriffi (2011: 7505-17), adopted from IEA (2002).
2. Fuelwood Use Patterns in Mexico
2.1. Characteristics and evolution of the Mexican rural sector, 1960-2010
The Mexican rural sector is highly diverse regarding its economic,
socio-cultural and ecological characteristics. Rural population lives in more
than 196,000 localities, which shows the high level of dispersion existing in
this sector. Most rural communities still lack infrastructure and services
since economic development policies have usually favored industrial and urban
sectors. Rural living conditions are in many cases insufficient to provide
rural population the opportunity to overcome poverty. Poverty has remained as
an enduring characteristic of rural population (OECD, 2009). As a result, many
people have migrated from villages to urban centers. Seasonal and permanent
migration to the United States has been very important too.
During the period of analysis rural demographics have changed considerably. In
1960, rural population was estimated at 17.2 million people living in 3.3
million households versus 23.3 million people (3.9 million households) in 1990
and 24.8 million people (6.3 million households) in 2010. Rural population has
increased in absolute figures during the 1960-2010 period, but the share of
people living in rural areas with respect to total population has decreased
from 49.3% in 1960 to 22.2% in 2010. Family size in this sector has shrunk from
5.2 to 3.9 members in 1960 and 2010, respectively, resulting in a faster
increase of the rural housing stock relative to that of absolute rural
population.
Lustig and Székely (1997) found that moderate and extreme poverty are systematically
concentrated in rural Mexican communities. Furthermore, these authors found
that the concentration of extreme poverty in rural areas is higher than in
urban centers, a trend that holds up to the present.
2.2. General characteristics of the Mexican rural sector, 1960-2010
2.2.1. Organization and land tenure
The Agrarian Reform that took place as a result of the Mexican Revolution (fist
quarter of the 20th Century) is a key feature to understand the agrarian
history of Mexico. Three main forms of land tenure were established: private,
public and social –the social property was subdivided in communal land and ejidos (Minutti Lavazzi, 2007). Ejidos were created to empower peasants, by eliminating huge private extensions of
land known as latifundios. Ejido members (or ejidatarios) were given the right to own and cultivate the land but not to sell it; also, ejidos were given representation at a federal level, and also were assisted in terms
of technology and credits (Gordillo, Janvry & Sadoulet, 1998). After the Cardenista period in 1940, near 50% of the
agricultural land had been converted to ejidos. The agricultural production of the ejidos increased from 11% in 1930 to 53% of the total in 1940 (Gómez Oliver, 1996). However, after the government of President Lázaro Cárdenas, incentives to ejidos decreased gradually as agricultural policies of subsequent governments were
oriented to empower the agrarian private sector. Since the 1990s, a decided “counter- agrarian reform” has taken place in Mexico as a result of neoliberal policies favoring the
privatization of land. The process initiated in 1991 when President Carlos
Salinas de Gortari announced a constitutional reform that legally allowed ejidos peasants to sell their land (Medina, 2006).
2.2.2. Subsistence versus commercial agriculture
The agriculture sector in Mexico is very heterogeneous across the territory.
There are sharp and increasing contrasts between a large number of subsistence
small-scale farmers and a commercial –mostly export oriented– sector. In the Central and Southern regions, the agriculture sector remains
mostly traditional (i.e. subsistence agriculture). Peasants generally depend on rainfed agriculture,
cultivate maize and other staple food, mechanization is low and, produce mostly
for self-consumption. On the contrary, the agriculture in the Northern region
of the country, and within irrigated areas, is generally commercial with
conspicuous mechanization and intensive use fertilizers and pesticides. This
pattern has remained since the 60’s and intensified after the signature of the Free Trade Agreement with the
United States in 1994 (Minutti Lavazzi, 2007). The main crops cultivated in the
Northern part of the country are cereals, tomatoes, vegetables for export, and
sugar cane while in the Southern region the corn –as the base of the Mexican diet– is the most important crop, although tropical crops are also important.
3. Methods
3.1. Estimation of fuelwood consumption
FW use evolution for the 1960-90 period was estimated from previous work by
Masera (1993) and Díaz (2000) at national and state levels, respectively. For the 1990-2010 period
and the projection 2010-30, a model was constructed at a county or municipality
level (Serrano et al., 2014).
Total FW consumption (FWTC) was estimated considering both exclusive and mixed
FW-LPG users to align with the fuel-stacking patterns observed in Mexican rural
households.
A bottom up model was used to determine exclusive and mixed FW consumption as
follows.
Where FWTC is total fuelwood consumption in tones of dry matter per year
(tDM/year), FWCEk is exclusive fuelwood consumption per county k, and FWCMk is
the fuelwood when used in combination with LPG consumption per county k.
Annual FW consumption by county for both types of FW users was estimated as the
product of FW per capita consumption (Cpc), saturation of FW users (S) and
population. A total of 2,500 counties were analyzed. Saturation of FW users per
county was obtained based on the National Bureau of Statistics (INEGI) census
data. Data regarding which fuel was used to cook in dwellings, population, and
average inhabitants per dwelling were used to estimate the number of FW users.
By saturation of FW users per county we mean the proportion of FW users against
total population within each municipality. The estimated saturation of FW users
per county and per year (with values ranging from 0% to 100%) is multiplied by
the total population at that given year and county in order to obtain the total
number of FW users. The model assumed that people using FW to cook was a good
proxy variable to estimated household FW use since Díaz (2000) found that more than 90% of residential FW use in Mexico is for
cooking. Saturation of FW mixed users per county was estimated a function of FW
exclusive saturation.
Average per capita fuelwood consumption for each of the five main ecological
regions was estimated by means of an exhaustive literature review (Díaz, 2000; Masera & Navia, 1997; Puentes, 2002; Sánchez González, 1993; Tovar, 2004). Average per capita consumption ranges between 1.X and
3.0 kg/day, which are consistent with values reported for other Central
American countries (Wang et al., 2013). These five average values were assigned to the counties depending on
their location within each ecological region using geographic information
systems (GIS). Minimum average temperatures were also used to adjust these
values. In other words, an additional factor was applied to FW consumption to
increase its value within counties located in cold regions. These counties were
identified using a GIS. Per capita FW consumption of mixed users was assumed
optimistically to be half of FW exclusive per capita consumption (Ghilardi,
Guerrero & Masera, 2009). There is not a large data base on actual FW savings of mixed FW
users with regards to exclusive users. Existing estimates have a large
variability, ranging from negligible to 50% or more (see Masera & Navia, 1997; Masera, Saatkamp & Kammen, 2000). In this study we chose a 50% value in order to have an estimate
of the potential savings to be achieved by the adoption of clean devices such
as LPG stoves.
In order to project FW consumption values to the year 2030 using the per capita
values and saturation of both, exclusive and mixed, users previously explained,
a business as usual scenario (BAU) was constructed3. The main assumptions were: a) per capita consumption values remain fixed
because without additional measures, no significant technological change in the
traditional devices used for cooking is expected –this is, three stone fires (TSF) are assumed to continue to be used during the
entire period of analysis–; and b) FW saturation change following annual growth rates derived from 1990
and 2000 Census Data. The model also assumed population values from census data
and from the National Population Bureau projections figures (CONAPO, 2012).
4. Results
4.1. Historic and expected future residential fuelwood use patterns in Mexico,
1960-2030
4.1.1. Fuelwood users 1960-2030
The number of estimated total FW users for the 1960-2010 period is shown in
Table 1. In 1960, the number of exclusive users reached about 22.62 million and
about 1.1 million for mixed users. Mixed users were located principally in the
urban sector. From then on, there has been a slight decrease in the number of
total FW users, composed by a decrease in exclusive users and a six-fold
increase of mixed FW-LPG users. This trend is expected to continue up to 2030,
where we estimate that FW exclusive and mixed users will reach near 15.3 and
6.7 million in the year 2030, respectively4.
4.1.2. Fuelwood consumption 1960-20305
In 1960, total FW consumption reached about 19.5 million tons of dry matter
(MtDM). In this year, exclusive and mixed consumption accounted for 18.9 and
0.7 MtDM, respectively. By 2010 total FW use had reached 19.74 MtDM. FW
exclusive and mixed consumption were projected to reach near 15.1 and 3.32 MtDM
in the year 2030, respectively. FW total consumption is expected to decrease
slightly from 19.53 MtDM in 1990 to 18.42 MtDM in 2030.
It is interesting to note that official figures have routinely underestimated
the amount of FW consumed in Mexico. Estimates from the Environmental Ministry
(SEMARNAT) only account for the wood that is reported in the “formal system”, that is, the wood that is harvested with management plans, and is recorded and
taxed. However, this is less than 20% of total FW used, or a 5-fold
underestimate of actual use.
Table 1
Fuelwood users and consumption, 1960-2030
| Year | Exclusive users (Million) | Mixed users | Total users | Exclusive use | Mixed use (MtDM/year) | Total use |
| 1960 | 22.62 | 1.09 | 23.71 | 18.85 | 0.70 | 19.55 |
| 1970 | 21.52 | 2.11 | 23.63 | 18.57 | 1.13 | 19.70 |
| 1980 | 19.86 | 3.10 | 22.96 | 18.20 | 1.57 | 19.77 |
| 1990 | 18.01 | 3.73 | 21.73 | 17.70 | 1.83 | 19.53 |
| 2000 | 17.56 | 4.94 | 22.49 | 17.30 | 2.44 | 19.74 |
| 2010 | 16.78 | 5.73 | 22.51 | 16.55 | 2.84 | 19.39 |
| 2020 | 15.99 | 6.28 | 22.28 | 15.80 | 3.12 | 18.92 |
| 2030 | 15.27 | 6.67 | 21.94 | 15.10 | 3.32 | 18.42 |
Sources: 1960-80, adapted and adjusted from Díaz (2000); 1990-2030, adapted from Serrano et al. (2014). Projected values.
4.1.3. Spatial distribution of FW consumption
The spatial distribution of FW consumption is very heterogeneous. FW consumption
is very important in the Central, Southern and Northwestern regions of the
country (Figure 4, left). This spatial pattern of FW consumption is projected
to prevail to the year 2030 (Figure 4, right). Change in FW consumption is also
heterogeneous, while in many counties FW demand is expected to decrease, FW
demand is expected to increase in several counties located in the Northwestern
and Southeastern regions of the country (Figure 5).
FIGURE 4
Spatial distribution of FW consumption, 2010 and 2030
Source: Serrano et al. (2014).
FIGURE 5
FW consumption trends, 2010-2030
Source: elaborated with data using the model described in Serrano et al. (2014).
4.1.4. Environmental impacts of FW use
The harvesting patterns of FW and their associated impacts are also very
heterogeneous in Mexico. Conventional wisdom states that all the “traditional FW harvested” contributes to forest degradation and deforestation. To test this assumption,
we used a spatial-explicit model (WISDOM; Ghilardi, Guerrero & Masera, 2007) to determine the fraction of non-renewable FW (fNRB) for each of
the 2,500 Mexican counties (municipality) scale (i.e., the fraction of FW used that exceeds the county woody biomass growth rates).
We first obtained maps of land-use provided by the National Bureau of
Statistics (INEGI) and use them to estimate the productivity (supply) of the
sustainable standing woody biomass that could be obtained in each county. In
other words, we only accounted for the standing woody biomass that could
potentially be used for FW consumption depending on the different land cover
types. Estimates of sustainable FW supply were then compared to the estimated
data on FW consumption per county. The fNRB in each county was obtained from
the respectively balance between the sustainable supply and demand of FW. We
obtained a national fNRB figure of 34%, meaning that 64% of total FW use is in
fact renewable6. fNRB values vary a lot by county; we identified 10% of total counties that
could be considered critical or “hot-spots” because they show high fNRB values. Actions to improve the sustainability of FW
could be concentrated in these areas, making policy interventions more
cost-effective.
Other impacts from traditional FW use include GHG emissions. From them, net CO2
emissions from FW combustion are considered to be zero when FW is extracted on
a sustainable manner. Yet, other greenhouse gases (GHG’s) such as CH4 and N2O and short-lived pollutants such as black carbon are
released as a result of incomplete combustion of FW in open fires contributing
directly to climate change. When FW is not harvested in a sustainable way, net
emissions of CO2 are obtained, and they are added to other GHG’s emissions like CH4 and N2O within the county. Recent studies have estimated
that the cumulative emissions between 2014 and the year 2030 from FW combustion
–for exclusive and mixed users– could reach about 360 MtCO2e under the business as usual scenario (BAU)7. This figure represents about 50% of current total Mexican GHG annual
emissions. This estimate accounts for methane (CH4), carbon monoxide (CO),
black carbon (BC) and net emissions of CO2 resulting from a non-sustainable
extraction of FW (Serrano et al., 2018). The accelerated penetration of LPG in the countryside does not
contribute to reduce substantially the expected future GHG emissions mainly
because LPG is used in combination with TSF. On the other side, an intensive
dissemination of clean woodburning cookstoves (CCS) targeting initially
counties with the highest fNRB values, and including mixed LPG-FW users, helps
achieve a 35% reduction in cumulative emissions by 2030. The health benefits of
this last intervention are also the largest as TSF are more effectively
displaced from the local kitchens when CCS are incorporated than when LPG alone
is adopted.
5. Discussion
Since 1960, major changes in Mexico’s social, demographic and macro-economic conditions have occurred: Mexico
shifted from a semi-rural to an urban country; there has been a large reduction
in average rural household size; and there have also been accelerated
industrialization and modernization of specific sectors of the Mexican economy
including commercial agriculture. Also, during this period, Mexico switched
from an oil-importing to an oil-exporting country and sustained for decades
large subsidies to LPG and other fossil fuels8.
Regarding FW use, we have seen that during the period analyzed rural Mexican
households have not followed the “expected” energy transition or fuel switching from woodfuels to modern fuels proposed by
the conventional energy ladder model, but a multiple fuel or fuel stacking strategy. In fact, while declining as total country population share, since 1960 the
absolute number of FW users in Mexico has remained virtually constant and is
expected to continue above 20 million people in the mid-term. At the same time,
there has been an increasing growth of mixed LPG-FW users i.e., LPG use in combination with FW, which is also expected to cover an increasing
share of total rural households. Very rarely, when adopting LPG, rural users
have completely abandoned FW. As a consequence of stacking LPG stoves with
traditional woodburning open fires, the so called modernization of rural residential cooking has not resulted in substantial savings in FW use nor in the associated GHG
emissions or in tangible health benefits, i.e., there have not been reductions of indoor air pollution levels.
A number of macro- and micro-economic factors may help explain these trends. At
the macro-economic level, the resilience of exclusive FW users may be explained
by the large number and high-dispersion of Mexican rural villages, the
existence of a large number of indigenous groups with strong attachments to
culinary traditions and practices. Also, Mexico’s economic development has been very unequal, favoring the urban-industrial
sectors and large-commercial agriculture against rural settlements and
small-farmers; as a result, over 58% rural people currently live in poverty and
17% in extreme-poverty (CONEVAL, 2017). Most of these people simply don’t have the economic means to access modern fuels such as LPG.
At the household level, Masera et al. (2015) have described the rationale behind LPG and FW stacking as having to do
with the interplay between culture, the nature and extent of residential energy
needs satisfied by traditional open fires and livelihood strategies.
Traditional open fires satisfy more needs that only cooking. Heating, lighting,
sealing roofs, smoking of meat and crops, and providing hot water for bathing,
are examples of the diverse energy services open fires usually provide. Many
tasks are also involved while cooking a meal. Heating, boiling, baking or
frying require each very specific energy demand in terms of fuel, device,
cookware and time. Under these circumstances, LPG stoves represent partial
substitutes –or suboptimal alternatives– of open fires and traditional rustic stoves. Moreover, FW use remains a back-up
strategy when family cash incomes are uncertain and/or acquiring clean fuels
could be difficult (such as within the rainy season). Under these conditions,
fuel/stove stacking is a flexible strategy that allows families to cope with
their cooking and other energy needs (Masera et al., 2015).
An alternative strategy has been the inclusion of clean woodburning cookstoves
(CCS) into the menu of cooking options for rural households. This strategy has
been tested regionally with chimney CCS adapted to the regional conditions and
cooking needs (Berrueta et al., 2015). As shown by a series of case studies (see for example, García Frapolli et al., 2010) and by country-wide analysis and future scenarios (Serrano et al., 2018), when properly implemented to assure a sustained use over the long-term,
these CCS have the potential to: a) more effectively reach the poorest
FW-exclusive households, currently out of the reach of modern fuels; b) more
effectively displace traditional fires, either alone or particularly in
combination with LPG; and c) provide significant FW savings and mitigation of
GHG emissions.
We should note finally, that there are also important regional variations in the
amounts, impacts and future trends of FW use. For example, there are counties
where FW users will continue to grow (particularly within Central-Western and
Southern Mexico), and other where exclusive users are rapidly shifting to
FW-LPG users (like in many areas of Central-Northern Mexico) (Serrano et al., 2018). There is also a heterogeneous pattern of FW renewability across the
territory. While most FW consumed is renewable, specific counties in Central
and Southern Mexico presented large values of non-renewable FW consumption
(Serrano, 2016).
6. Conclusions
We have shown that during the past 60 years FW has represented a major
residential fuel for Mexican rural households. Mid-term scenarios show that
this trend will continue in the foreseeable future. FW use has been resilient
even with an increasing penetration of LPG in the rural areas. Complete switch
to modern fuels such as LPG has proven very rare due to economic, technical and
cultural reasons. The so called energy transition to modern fuels among rural Mexican households has actually been, for an
increasing percentage of the population a fuel stacking strategy, where the combination of LPG with FW is providing more flexible, reliable and
convenient strategy. However, for another large share of the rural population,
impoverished and “left behind” under recent and current rural development and agrarian strategies, even the
stacking of fuels is a dream and, if no other actions are taken, will continue
relying entirely on traditional open fires with negative health and
environmental consequences. Even mixed FW-LPG users, as they continue relying
on traditional fires for cooking, do not get the potential large health
benefits brought about by access to modern fuels.
Under these conditions, clean woodburning chimney cookstoves (CCS) have risen as
a relevant cost-effective option to both more effectively displace open fires
and reach a larger share of rural households. Adequately designed, implemented,
and disseminated, these stoves have shown that either alone or together with
other clean fuels such as LPG, could reduce FW use, provide substantive
mitigation and large health benefits to local people, in particular to women.
In fact, CCS dissemination has been estimated to reach up to 34% of total
cumulative GHG emissions when households targeted include both exclusive and
mixed users and are located within regions where FW is extracted unsustainably
(Serrano et al., 2018). These results confirm the importance of promoting integrated strategies
that include the clean and efficient use of FW while also benefiting from
increasing access to clean modern fuels.
Finally, the paper also makes clear that large disparities among rural regions
exist in Mexico, in terms of the total number and future expected evolution of
exclusive FW users, sustainability of fuelwood use, cultural cooking and other
practices associated to traditional fires, and physical and economic
accessibility to LPG. Therefore, any alternative, to be successful, will need
to be regionally-specific and tailored to the local socio-environmental
conditions and priorities.
Acknowledgments
The authors would like to acknowledge the valuable comments of two anonymous
reviewers of Historia Agraria. The first author acknowledges financial support from the DGAPA-UNAM
postdoctoral fellowship at CIGA-UNAM under the supervision of the second
author. This study was also supported through a grant from the Research and
Technology Innovation Support Program (PAPIIT) (No. IT101512), of the
Universidad Nacional Autónoma de México.
References
Alberts, J. H., Moreira, C. & Pérez, R. M. (1997). Firewood Substitution by Kerosene Stoves in Rural and Urban Areas of
Nicaragua, Social Acceptance, Energy Policies, Greenhouse Effect and Financial
Implications. Energy for Sustainable Development, 3 (5), 26-39.
Arora, P., Jain, S. & Sachdeva, K. (2013). Physical Characterization of Particulate Matter Emitted from Wood
Combustion in Improved and Traditional Cookstoves. Energy for Sustainable Development, 17 (5), 497-503.
Bailis, R., Drigo, R., Ghilardi, A. & Masera, O. R. (2015). The Carbon Footprint of Traditional Woodfuels. Nature Climate Change, 5 (3), 266-72.
Baldwin, S. (1987). Biomass Stoves: Engineering Design, Development, and Dissemination. Arlington: Volunteers in Technical Assistance.
Berrueta, V., Serrano, M., García Bustamante, C., Astier, M. & Masera, O. R. (2017). Promoting Sustainable Local Development of Rural Communities and
Mitigating Climate Change: The Case of Mexico’s Patsari Improved Cookstove Project. Climatic Change, 140 (1), 63-77.
Bruce, N., Rehfuess, E., Mehta, S., Hutton, G. & Smith, K. (2006). Indoor Air Pollution. In D. T. Jamison, J. G. Breman, A. R. Measham, G. Alleyne, M. Claeson, D. D. Evans et al. (Eds.), Disease Control Priorities in Developing Countries (pp. 793-815). 2nd ed. New York/Washington, DC: Oxford University Press/World
Bank.
Chum, H., Faaij, A., Moreira, J., Berndes, G., Dhamija, P., Dong, H., Gabrielle,
B., Eng, A. G., Lucht, W., Mapako, M., Cerutti, O. M., McIntyre, T., Minowa, T.
& Pingoud, K. (2011). Bioenergy. In O. Edenhofer, R. Pichs-Madruga, Y. Sokona, K. Seyboth, P. Matschoss, S. Kadner,
T. Zwickel, P. Eickemeier, G. Hansen, S. Schlömer & C. von Stechow (Eds.), Renewable Energy Sources and Climate Change Mitigation: Special Report of the
Intergovernmental Panel on Climate Change. Cambridge: Cambridge University Press.
CONAPO (2012). Proyecciones de la Población 2005-2050. Consejo Nacional de Población. [Retrieved October, 2012].
Consejo Nacional de Evaluación de la Política de Desarrollo Social (CONEVAL) (2017). Medición de la pobreza en México y en las Entidades Federativas 2016.
Davis, M. (1995). Fuel Choice in Rural Communities. Energy for Sustainable Development, 2 (3), 45-8.
Díaz, R. (2000). Consumo de leña en el sector residencial de México: Evolución histórica y emisiones de CO2. Master’s thesis. México, DF: Universidad Nacional Autónoma de México.
Eberhard A. A. (1992). Shifting Paradigms in Understanding the Fuelwood Crisis: Policy
Implications for South Africa. Journal of Energy Research and Development in Southern Africa, 3 (2), 19-25.
Eckholm, E. P. (1975). The Other Energy Crisis: Firewood. Washington, DC: Worldwatch Institute.
Evans, M. (1987). Stoves Programmes in the Framework of Improved Cooking Practices: A Change in
Focus with Special Reference to Latin America. Genève: International Labour Office.
Fitzgerald, K. B., Barnes, D. & McGranahan. G. (1990). Interfuel Substitution and Changes in the Way Households use Energy:
The Case of Cooking and Lighting Behavior in Urban Java. The World Bank. Industry and Energy Department Working Paper, (29).
García Frapolli, E., Schilmann, A., Berrueta, V. M., Riojas, H., Edwards, R. D.,
Johnson, M., Guevara, A., Armendariz, C. & Masera, O. R. (2010). Beyond Fuelwood Savings: Valuing the Economic Benefits of Introducing
Improved Biomass Cookstoves in the Purépecha Region of Mexico. Ecological Economics, 69 (12), 2598-2605.
Ghilardi, A., Guerrero, G. & Masera, O. R. (2007). Spatial Analysis of Residential Fuelwood Supply and Demand Patterns in
Mexico using the WISDOM Approach. Biomass and Bioenergy, 31 (7), 475-91.
Ghilardi, A., Guerrero, G. & Masera, O. R. (2009). A GIS-Based Methodology for Highlighting Fuelwood Supply/Demand
Imbalances at the Local Level: A Case Study for Central Mexico. Biomass and Bioenergy, 33 (6-7), 957-72.
Ghilardi, A., Bailis, R., Mas, J. F., Skutsch, M., Elvir, J. A., Quevedo, A.,
Masera, O. R., Dwivedi, P., Drigo, R. & Vega, E. (2016). Spatiotemporal Modeling of Fuelwood Environmental Impacts: Towards
Improved Accounting for Non-Renewable Biomass. Environmental Modelling & Software, (82), 241-54.
Ghilardi, A.,Tarter, A. & Bailis, R. (2018). Potential Environmental Benefits from Woodfuel Transitions in Haiti:
Geospatial Scenarios to 2027. Environmental Research Letters, 13 (3).
Gómez Oliver, L. (1996). El papel de la agricultura en el desarrollo de México. Estudios Agrarios, (3), 1-52.
Gordillo, G., Janvry, A. de & Sadoulet, E. (1998). Entre el control político y la eficiencia: Evolución de los derechos de propiedad agraria en México. Revista de la CEPAL, (66), 149-66.
Hiemstra-van der Horst, G. & Hovorka, A. J. (2008). Reassessing the “Energy Ladder”: Household Energy Use in Maun, Botswana. Energy Policy, 36 (9), 3333-34.
Hosier, R. H. & Dowd, J. (1988). Household Fuel Choice in Zimbabwe: An Empirical Test of the Energy
Ladder Hypothesis. Resources and Energy, 9 (4), 337-61.
International Energy Agency (IEA) (2002). World Energy Outlook 2002. Paris: International Energy Agency.
International Energy Agency (IEA) (2016). World Energy Outlook 2016. Paris: International Energy Agency.
Johnson, M., Edwards, R., Alatorre, C. & Masera, O. R. (2008). In-Field Greenhouse Gas Emissions from Cookstoves in Rural Mexican
Households. Atmospheric Environment, 42 (6), 1206-22.
Johnson, M., Edwards, R. & Masera, O. R. (2010). Improved Stove Programs need Robust Methods to estimate Carbon Offsets.
Climatic Change, 102 (3-4), 641-49.
Kowsari, R. & Zerriffi, H. (2011). Three Dimensional Energy Profile: A Conceptual Framework for Assessing
Household Energy Use. Energy Policy, 39 (12), 7505-17.
Leach, G. (1992). The Energy Transition. Energy Policy, 20 (2), 116-23.
Leach, G. & Mearns, R. (1988). Beyond the Woodfuel Crisis: People, Land, and Trees in Africa. London: Earthscan.
Lustig, N. & Székely, M. (1997). México: Evolución económica, pobreza y desigualdad. Washington, DC: Inter-American Development Bank.
handle/11319/5293
Masera, O. R. (1993). Sustainable Fuelwood Use in Rural Mexico. Vol. I: Current Patterns of Resource
Use. Berkeley: Lawrence Berkeley Laboratory, US Dept. of Energy.
Masera, O. R. & Navia, J. (1997). Fuel Switching or Multiple Cooking Fuels? Understanding Inter-Fuel
Substitution Patterns in Rural Mexican Households. Biomass and Bioenergy, 12 (5), 347-61.
Masera, O. R., Saatkamp, B. D. & Kammen, D. M. (2000). From Linear Fuel Switching to Multiple Cooking Strategies: A Critique
and Alternative to the Energy Ladder Model. World Development, 28 (12), 2083-2103.
Masera, O. R., Drigo, R., Trossero, M. A. (2003). Woodfuels Integrated Supply/Demand Overview Mapping (WISDOM): A Methodological
Approach for Assessing Woodfuel Sustainability and Support Wood Energy Planning. Rome: Food and Agriculture Organization of the United Nations.
Masera, O. R., Ghilardi, A., Drigo, R. & Trossero, M. A. (2006). WISDOM: A GIS-Based Supply Demand Mapping Tool for Woodfuel Management. Biomass Bioenergy, 30 (7), 618-37.
Masera, O. R., Drigo, R., Bailis, R., Ghilardi, A. & Ruiz Mercado, I. (2015). Environmental Burden of Traditional Bioenergy Use. Annual Review of Environment and Resources, 40 (1), 121-50.
Medina, S. (2006). La reforma al artículo 27 constitucional y el fin de la propiedad social de la tierra en México. México, DF: El Colegio Mexiquense. (Documentos de Investigación, 121).
Minutti Lavazzi, M. (2007). Análisis de los sectores agrícolas de México y Estados Unidos desde la perspectiva de la sincronización económica: Una evaluación general de los efectos para México. Master’s thesis. Puebla: Universidad de las Américas Puebla.
Naeher, L. P., Brauer, M., Lipsett, M., Zelikoff, J. T., Simpson, C. D., Koenig,
J. Q. & Smith, K. R. (2007). Woodsmoke Health Effects: A Review. Inhalation Toxicology, 19 (1), 67-106.
Organization of Economic Cooperation and Development (OECD) (2009). The Role of Agriculture and Farm Household Diversification in the
Rural Economy of Mexico.
Openshaw, K. (1974). Wood Fuels the Developing World. New Scientist, (61), 271-72.
Openshaw, K. (1978). Woodfuel: A Time for Re-Assessment. Natural Resources Forum, (3), 35-51.
Pérez Padilla, R., Schilmann, A. & Riojas, H. (2010). Respiratory Health Effects of Indoor Air Pollution. The International Journal of Tuberculosis and Lung Disease, 14 (9), 1079-86.
Preble, C. V., Hadley, O. L., Gadgil, A. J. & Kirchstetter, T. (2014). Emissions and Climate-Relevant Optical Properties of Pollutants Emitted
from a Three-Stone Fire and the Berkeley-Darfur Stove Tested under Laboratory
Conditions. Environmental Science & Technology, 48 (11), 6484-91.
Puentes, V. (2002). Impacto del consumo de leña en el bosque de Santa Fe de la Laguna, Michoacán. Bachelor thesis. México, DF: Universidad Nacional Autónoma de México.
Roden, C. A., Bond, T. C., Conway, S., Osorto Pinel, A. B., MacCarty, N. & Still, D. (2009). Laboratory and Field Investigations of Particulate and Carbon Monoxide
Emissions from Traditional and Improved Cookstoves. Atmospheric Environment, 43 (6), 1170-81.
Sánchez González, M. C. (1993). Uso y manejo de la leña en X-uilub, Yucatán. Bachelor thesis. México, DF: Universidad Nacional Autónoma de México.
Schauer, J. J., Kleeman, M. J., Cass, G. R. & Simoneit, B. (2001). Measurement of Emissions from Air Pollution Sources. 3. C1-C29 Organic
Compounds from Fireplace Combustion of Wood. Environmental Science & Technology, 35 (9), 1716-28.
Serrano, M., Arias, T., Ghilardi, A. & Masera, O. R. (2014). Spatial and Temporal Projection of Fuelwood and Charcoal Consumption in
Mexico. Energy for Sustainable Development, (19), 39-46.
Serrano, M. (2016). Escenarios espaciales explícitos de uso múltiple de combustibles para cocción en el sector energético residencial mexicano y su potencial de mitigación de gases de efecto invernadero. PhD thesis. México, DF: Universidad Nacional Autónoma de México.
Serrano, M, Ruiz García, V. M., García Bustamante, C., Berrueta, V. M., Martínez Bravo, R., Ghilardi, A. & Masera, O. R. (2018). Promoting LPG, Clean Woodburning Cookstoves or Both?: Climate Change
Mitigation Implications of Household Energy Transition Scenarios in Rural
Mexico. Environmental Research Letters.
Shen, G., Wei, S., Zhang, Y., Wang, B., Wang, R. et al. (2013a). Emission and Size Distribution of Particle-bound Polycyclic Aromatic
Hydrocarbons from Residential Wood Combustion in Rural China. Biomass Bioenergy, (55), 141-47.
Shen, G., Tao, S., Wei, S., Chen, Y., Zhang, Y. et al. (2013b). Field Measurement of Emission Factors of PM, EC, OC, Parent, Nitro-,
and Oxy- Polycyclic Aromatic Hydrocarbons for Residential Briquette, Coal Cake,
and Wood in Rural Shanxi, China. Environmental Science & Technology, 47 (6), 2998-3005.
Shen, G., Xue, M., Chen, Y., Yang, C., Li, W., Shen, H. et al. (2014). Comparison of Carbonaceous Particulate Matter Emission Factors among
Different Solid Fuels Burned in Residential Stoves. Atmospheric Environment, (89), 337-45.
Smith, K. (1987). The Biofuel Transition. Pacific and Asian Journal of Energy, 1 (1), 13-32.
Soussan, J., O’Keefe, P. & Munslow, B. (1990). Urban Fuelwood: Challenges and Dilemmas. Energy Policy, 18 (6), 572-82.
Straif, K., Baan, R., Grosse,Y., Secretan, B., El Ghissassi, F., Cogliano,V. et al (2006). Carcinogenicity of Household Solid Fuel Combustion and of
High-Temperature Frying. Lancet-Oncology, (7), 977-78. Pdf?
pii=S1470-2045%2806%2970969-X
Tauro, R., Serrano, M. & Masera, O. R. (2018). Solid Biofuels in Mexico: A Sustainable Alternative to satisfy the
Increasing Demand for Heat and Power. Clean Technologies and Environmental Policy, 20 (7), 1527-39.
NOTAS A PIE DE PÁGINA / FOOTNOTES
