Reducing energy poverty in small rural communities through in situ electricity generation

Abstract

Energy is key in achieving sustainable societies. There have been great efforts towards improving energy access worldwide. Despite the advances in energy access, energy poverty remains a major problem in many parts of the world, particularly in rural communities. Modern energy, in particular electricity, can help rural communities develop through improving education and health. During the last two decades, there have been improvements on bioenergy technological innovations, e.g. electricity generation from bioenergy from residual biomass from several agricultural crops in biorefineries. Most research has focussed on large biorefineries, with limited research on small-scale gasifiers’ location and contribution to energy poverty. This paper is aimed at assessing technological options to generate electricity in situ from biomass to reduce energy poverty of rural communities. This is done using four analysis methods: (1) crops availability data; (2) poverty and marginalisation data; (3) electricity provision/distribution; and, (4) GIS/Geographical latitude and longitude to locate municipalities in Mexico. The results shows that the generating potential for electricity using residual biomass with gasifiers could improve the welfare of almost 10 million people communities using residual biomass from crops harvested in such communities. This research provides location solutions on the best places to locate small-scale biorefineries. The research also provides systemic analysis to reduce energy poverty through in situ electricity generation using cheap accessible small plant technologies and biomass as raw material, as well as their location. Generating electricity in a decentralised way through agricultural residual biomass can help lift rural communities from poverty and improve their well-being, and, thus, make societies more sustainable.

Introduction

Sustainable development (SD) and sustainability have appeared as concepts to help address the economic, environmental, and social impacts from previous generations, on this generation, and future ones through a holistic perspective [1–3]. One of the most recent initiatives for SD are the 17 United Nations (UN) Sustainable Development Goals (SDG) and their 169 targets were agreed by 195 states and cover the most important points that modern societies need to address to become less unsustainable [4, 5]. The SDGs are indivisible, i.e. they need to be addressed as a whole, and not through a silo mentality [6].

Energy is key in making modern societies sustainable [7–9]. According to the latest report on SDG7 (Ensure access to affordable, reliable, sustainable, and modern energy for all), 2.6 billion people use dangerous and inefficient cooking systems and 759 million people lack access to electricity [10]. Energy improves welfare and supports economic well-being (e.g. through the use of modern sources reliant on electricity) [11], and can thus contribute to SDG 1 (End poverty in its forms everywhere) [4, 5]. Energy and social evolution are closely connected, as explained by White [12] through “culture evolves as the amount of energy harnessed per capita per year is increased, or as the efficiency of the instrumental means of putting the energy to work is increased”.

There have been great improvements in energy access worldwide [13]; however, energy poverty remains a major problem in many parts of the world [7, 8], particularly in rural communities. Energy poverty, i.e. the minimum quantity of energy needed to perform such basic tasks as cooking, heating homes, and lighting [9, 11], accentuates the existence of social asymmetry in conditions of living [11, 13]. Around 2 billion people worldwide, mostly in rural areas, continue to suffer from energy poverty [14]. It is estimated that the minimum energy monthly per capita requirement is over 4 kg_OE [11].

Energy poverty directly affects rural communities, which are dependent on biomass (from agriculture, forest residues, and energy crops) to satisfy their energy needs for cooking and heating, with around 2.7 billion using biomass for cooking [13]. Low quality fuels, particularly from biomass, are usually the only choice available, although not always the cheapest [9]; however, using biomass generates indoor air pollution and become a health hazard [9, 14, 15].

Modern energy, in particular electricity, can help rural communities develop [11, 13] through improving education and health [13]; however, around 1.4 billion people lack access to electricity [7, 15], and many of those who have access are constrained by connections to the grid or high costs of electricity [11, 13].

Electricity can be produced through bioenergy from residual biomass from several agricultural crops [16]. During the last two decades, there have been improvements on bioenergy technological innovations as alternatives to grid expansion, such as microgeneration and renewable energy technologies, which can benefit rural electrification through complementary in situ energy production [13, 15]; however, the share of such innovations is less than 1% in most developing countries, due to factors such as: cost barriers for new technologies; lack of awareness of benefits relative to costs; technical problems; lack of market acceptance; and lack of incentives for individuals and industry [7].

Electricity production through bioenergy can be done through: (1) large biorefineries that have the advantage of economies of scale, but they require large quantities of residual biomass availability, high transportation costs, and coordination between rural communities [17]; or, (2) small-scale biorefineries can provide in situ electrical energy for small rural communities are more suitable due to their advantages in investment and operation costs [18]. Research on small-scale biorefineries’ location and contribution to energy poverty has been quite limited (see [17]).

This paper’s aim is to assess technological options to generate electricity in situ from biomass to reduce energy poverty of rural communities based on small-scale biorefineries.

The remainder of paper is structured in the following way: Sect. 2 provides an overview of bioenergy generation; Sect. 3 explains the methods used; Sect. 4 presents the results; Sect. 5 discusses the results; and presents the conclusions.

Bioenergy generation overview

Bioenergy is an alternative to produce sustainable energy [19]. Research on this topic has included he use of biofuels scenarios based on technical and economic feasibility of using renewable energy sources for using biofuels in electricity generation and transportation sectors [20], and energy production using residual biomass, minimising production costs under several restrictions, production sites location, connection to markets, and the potential to produce energy [19].

Residual biomass from several agricultural crops can be used to produce energy [16], and to avoid clearing land for increasing agriculture or forestry [21]. Worldwide, there is a large amount of residual biomass that is potentially available, in the order of 1000 million barrels of diesel equivalent from cereals, legumes, and food crops [22]. An analysis in Italy showed the availability of 22.2 Tg/year residual biomass, which could provide 192 PJ of energy, and help meet the European Union (EU) energy targets [23]. A study of the potential use of residual biomass in Croatia analysed the its use as feedstock for power plants, whilst considering biomass price level, transport cost and plant location [24]. Research on residual biomass in China, taking into account environmental and conservation issues, as well as transportation costs and technology issues, highlighted that there were 506 Tg/year available [25].

Agricultural residual biomass can be transformed to energy through gasification [see 16]. Gasification technologies allow to generate a gas mixture that can be used to produce electricity [18]. There are different equipment sizes [as presented in Table 1 [26–28], from 150 to 10 kW. When residual biomass availability is low (below 30,000 Mg/year), small-scale gasifiers with an internal combustion engine, coupled to an electricity generator, provides in situ electrical energy for small rural communities are more suitable due to their advantages in investment and operation costs. A study that evaluated small-scale gasification units to produce electricity in the Czech Republic [29], considering electrical power gasifiers from 10 to 200 kWh_el, showed that there is profit only for the largest size assessed (200 kW_el), and highlighted that these units are under development in Central and Southern Europe. An assessment for biomass gasification combined heat and power (CHP) systems in different sizes concluded that for larger sizes the Net Present Value is higher, the smallest system considered [100 kW_thermal (13.6 kW_el)] generating a profit yearly [30].

Table 1. Gasifier type and size

Equipment	Power (kW)	Electricity generated [MWh/(year-equipment)]
GEK 150	150	384
GEK 100	100	256
GEK 20	20	51.2
GEK 10	10	25.6

A literature review for the small-scale and micro-scale combined heat and power systems (15–100 kW_el) showed that they have high market potential [31]; however, more research and development is needed for these technologies, particularly on their commercialisation.

In addition to costs and biomass availability, it is necessary to consider the location of storage depots and the processing facilities, as well as transportation cost from harvesting sites to warehouses, which can help to minimise production and capital [32, 33]

A number of approaches have been used in decision-making for processing plant location selection, including: the incorporation of economic, environmental, and social indicators for site selection; the use of Geographical Information Systems (GIS) to model residual biomass availability and sustainability indicators in the USA that estimate availability of 1.6 Tg/year of cotton stalks is available, enough to support 7 pellet plants [34]; and, the use of GIS based heuristics resulting in biomass availability to process 184 Tg/year of biomass in 77 biorefineries and 171 storage depots [35]; and [36].

Methods

This paper uses four analysis methods to assess the potential to generate electricity in situ to reduce poverty: (1) crops availability data; (2) poverty and marginalisation data; (3) electricity provision/distribution; and (4) GIS/Geographical latitude and longitude to locate municipalities. These methods are used to expand and provide more insights on previous research on transformation of agricultural residual biomass to energy, where the economic feasibility and close-by availability of the biomass determined the location for the processing facilities [see 16]. The focus of the current paper is on small-scale gasifiers (10–150 kW) processing agricultural residual biomass as feedstock in sites with biomass less than 30,000 Mg/year.

The analyses were carried out using data from Mexico due to previous works from the authors [18, 37–40] and availability of biomass and poverty data in the country [41–43].

Residual biomass from agricultural crops availability data and GIS location

Crops that generate large residual biomass and can be processed through a gasification process (to be discussed further down). These crops are corn, wheat, barley, rice, sorghum, sugarcane, agave, and pecan nut. The ratio of residue to crop is shown in Table 2.

Table 2. Residue to Crop Ratios

Main crop	Agricultural residue	Residue amount per crop
		kgresidue/kg crop	References
Agave	Agave residue	0.111	[52]
Rice	Rice straw	1.625	[53]
Sugar cane	Sugar cane bagasse	0.135	[54]
Barley	Barley straw	1.660	[22]
Maize	Corn stover	0.825	[53]
Pecan Nut	Pecan nut shell	0.550	[53]
Sorghum	Sorghum straw	1.425	[53]
Wheat	Wheat straw	1.835	[53]

The use of GIS for residual biomass has been used to assess the processing sites location for large scale residual biomass in Mexico for the crops presented in Table 1 considering uncertainty in crop yield, restrictor layers related to protected areas, terrain slope, community type, water bodies, power plants and grids, roads and highways; frequency of hurricanes, frosts, and droughts [37]. The location method was fine-tuned by using a sequential method linking GIS and mathematical programming for optimal energy production, where a set of products were considered, such as: ammonia, formaldehyde, Fischer–Tropsch liquids, urea, electricity and refrigeration through gasification, and methanol [38]. The chosen municipalities for this study are based on the results from the potential corn stover processing site location, as shown in Fig. 1, where the regions in yellow and orange colours represent residual biomass from 0.1 to 2000 Mg/year [40].

Fig. 1 [Images not available. See PDF.]

Average estimated production of Corn stover (Mg/year) assigned to agricultural areas within each municipality for the years 2009–2014

The crops in Table 2 represent in Mexico a total amount of 98,710 Gg for 2014, with an estimate of 48,974 Gg of residual biomass available. A summary map for the residual biomass types per state is shown in Fig. 2. Corn stover is widely distributed in the country, as it would be expected for corn, which originates from Mexico. Wheat is grown mainly in North-western Sonora state, while sugarcane bagasse is clustered in coastal Veracruz state and western Jalisco state. Sorghum straw is concentrated in North-eastern Tamaulipas state, as well as Central Guanajuato state and Western Sinaloa state.

Fig. 2 [Images not available. See PDF.]

Residual biomass per type in Mexico's states

Figures 3, 4, 5, 6 show choropleths graphs for corn stover, sorghum and wheat straw, and sugar cane bagasse availability throughout Mexico the residual biomass range is shown in each figure.

Fig. 3 [Images not available. See PDF.]

Corn stover availability (Mg/year) [Choropleth]

Fig. 4 [Images not available. See PDF.]

Sorghum straw availability (Mg/year) [Choropleth]

Fig. 5 [Images not available. See PDF.]

Wheat straw availability (Mg/year) [Choropleth]

Fig. 6 [Images not available. See PDF.]

Sugarcane bagasse availability (Mg/year) [Choropleth]

Corn stover is available through most of Mexico’s region. This residue is, thus, taken as the basis for estimating electricity generation in situ in this paper.

Poverty, marginalisation index, and human development index data

Evaluating the Human Development Index (HDI) can help to assess poverty worldwide, and the Marginalisation Index (IM) in Mexico can be used to evaluate poverty at a municipality level.

The IM is a database generated by the Mexican Government [44, 45]. It is based on socio-economic indicators for each municipality for all Mexican states. It calculates the index using total population; deficiencies associated with inhabited dwellings, dwellings having either electricity, toilets, and sewage; and population older than 15 years illiterate or having finished primary education. Positive index values indicate high poverty levels in municipalities.

Mexican states and some of their municipalities have a low Human Development Index (HDI) and a large poverty index (PI), that is correlated to the Marginalisation Index (IM for its acronym in Spanish) as established by CONAPO [Consejo Nacional de Población (National Population Council)]. Figure 7 presents the HDI for Mexico in 2014, where it can be seen that the Southern states of Chiapas, Guerrero and Oaxaca have the lowest value for HDI from 0.648 to 0.671. Figure 8 shows the population percentage in poverty for each Mexican state, where the aforementioned states have the largest percentage of population in poverty. The Marginalisation Index (IM) is shown in Fig. 9, which highlights that the above-mentioned states have the largest value for IM.

Fig. 7 [Images not available. See PDF.]

Mexico’s Human Development Index for 2014 [Choropleth]

Fig. 8 [Images not available. See PDF.]

Poverty percentage in Mexico [Choropleth]

Fig. 9 [Images not available. See PDF.]

Marginalisation Index per State (2015) [Choropleth]

The following states were selected for more detailed analysis because of their high poverty incidence: Guerrero, Chiapas, Oaxaca, Puebla, Veracruz, and México. The data from municipalities in those states were used to generate Fig. 10, where it can be seen that on average the IM data is higher than 0. Table 3 shows the total municipalities, population, municipalities with a IM higher than 0 and their percentage against the total municipalities, and the population with a IM higher than 0 and their percentage against the total population in each state.

Fig. 10 [Images not available. See PDF.]

Frequency of Marginalisation Index (IM) for municipalities in several Mexican States with high poverty

Table 3. Demographics and IM of the municipalities of the states analysed

State	Municipalities IM > 0	Population IM > 0	Municipalities	Population	Municip. with IM > 0/Municip. (%)	Pop. with IM > 0/Popul. (%)
Guerrero	70	1,909,909	81	3,533,251	86.4	54.1
Chiapas	105	3,653,205	115	5,256,144	91.3	69.5
Oaxaca	249	896,878	327	1,911,584	76.1	46.9
Veracruz	24	384,168	39	1,229,109	61.5	31.3
Puebla	123	1,491,430	172	5,474,874	71.5	27.2
Hidalgo	24	404,913	77	2,702,445	31.2	15.0
México	21	856,852	124	15,147,741	16.9	5.7

Electricity provided by the Federal Electricity Commission (CFE) to México’s municipalities

Electricity in Mexico is distributed by Federal Electricity Commission (Comisión Federal de Electricidad) (CFE) where data for electricity user and consumers in municipalities is given in [42], the decentralised government entity that by law manages distribution. The municipalities in the chosen states receive electricity, but consumption per user is related to the marginalisation index. Electricity tariff categories are shown in Table 4.

Table 4. Electricity rate categories for domestic use

Price rate	Comment	kWh/month
1	Domestic	250
1A	Domestic	300
1B	Domestic	400
1C	Domestic	850
1D	Domestic	1000
1E	Domestic	2000
1F	Domestic	2500

Municipalities’ location

The location of municipalities in maps need information on latitude and longitude. These data are obtained from National Institute of Statistics and Geography (INEGI is its acronym in Spanish). For the selected states the data was obtained for Geographical areas at the state and municipality level for Guerrero [46], Chiapas [47], Oaxaca [48], Veracruz [49], Puebla [50], and Mexico [51].

Methods limitations

The residual biomass availability was obtained from governmental databases across time for different years, and some municipalities and months there might be some gaps in the available data. The marginalisation index, linked to poverty is a similar situation where data must be available and validated regarding the index and population for municipalities, also it is obtained from governmental databases where there might be gaps in the data. Data from the public facility providing electricity (CFE), there are several tariff rates from low consumption to higher, and consumption from industry and agriculture uses, herein data availability and reliability might be with gaps for the various rate categories and municipalities. Regarding GIS data the resolution is 1:250,000, where the state and municipalities limits are given.

Results

Relating residual biomass availability and gasifiers’ electricity generation

Table 5 shows an extract for some municipalities in the state of Oaxaca, showing the number of gasifiers and potential electricity produced, the residual biomass available, residual biomass used for gasification, and the capital investment needed.

Table 5. Extract of Small-scale sites in Oaxaca state for electricity generation using Gasifiers

Location (Municipality)	State	Available residual biomass (Mg/year)	Equipment type (kW)	Biomass used (Mg/year)	Cap. Invest. 103 USD	Number of equipment	Electricity produced (MWh/year)
Asunción Cuyotepeji	Oaxaca	16,126	150	7257	5251	21	8063
Calihualá	Oaxaca	17,774	150	7998	5751	23	8887
Coicoyán de Las Flores	Oaxaca	3242	150	1459	1000	4	1621
Constancia del Rosario	Oaxaca	643	150	289	250	1	321
Cosoltepec	Oaxaca	94	20	42	31	1	42
Chalcatongo de Hidalgo	Oaxaca	1929	150	868	750	3	964
Fresnillo de Trujano	Oaxaca	176	20	79	61	2	79
Guadalupe de Ramírez	Oaxaca	331	100	149	158	1	149
Mesones Hidalgo	Oaxaca	1465	150	659	500	2	732
Heroica Ciudad de Huajuapan de León	Oaxaca	2238	150	1007	750	3	1119
Magdalena Jaltepec	Oaxaca	1332	150	599	500	2	666

For residual biomass availability lower than 30,000 Mg/year the map in Fig. 11 presents a magnification of the states of Oaxaca, Chiapas, and Guerrero with municipalities where gasifiers from 10 to 150 kW, which generate electricity in situ, are shown. The gasifiers’ location is clustered in mountain areas of Chiapas, Guerrero, Oaxaca, Puebla, and Veracruz, presenting a high to very high marginalisation grade. The Gulf of Mexico coastal plane and Tehuantepec isthmus do not have such gasifiers since the available residual biomass is larger than 30,000 Mg/year, and they better highways and roads to transport residual biomass to possible processing sites.

Fig. 11 [Images not available. See PDF.]

Equipment with Power type for biomass availability less than 30,000 Mg/year (Close up view for various states)

Relating residual biomass availability with marginalisation index

This section presents the link between potential electricity produced for municipalities and the marginalisation index (IM). The Mexican states chosen for the analysis were Guerrero, Chiapas, Oaxaca, Puebla, and Veracruz.

Table 6 presents the marginalisation index and marginalisation grade for those municipalities in Table 5 except for 2 sites the range goes from High to Very high marginalisation.

Table 6. Marginalisation index and grade for Oaxaca state sites extract [41]

Location (Municipality)	Marginalisation index	Marginalisation grade
Asunción Cuyotepeji	− 0.165	Middle
Calihualá	1.061	High
Coicoyán de Las Flores	3.052	Very high
Constancia del Rosario	1.447	Very high
Cosoltepec	0.141	High
Chalcatongo de Hidalgo	0.433	High
Fresnillo de Trujano	1.103	High
Guadalupe de Ramírez	0.364	High
Mesones Hidalgo	1.376	Very high
Heroica Ciudad de Huajuapan de León	− 0.698	Low
Magdalena Jaltepec	0.799	High

A summary for the states of Chiapas, Guerrero, Oaxaca, and Puebla is presented in Table 7, showing the gasifier type, the marginalisation grade, and the average for the marginalisation index; besides the communities’ population and the electricity generated (MWh/year). The population that could benefit from electricity generation for the chosen municipalities is in the order of 9.8 million, with a high marginalisation grade, while electrical energy is in the order of 1360 GWh/year. Table 7 also presents the potential to produce electricity with various gasifiers and its relation to population with high and very high marginalisation grade providing a potential benefit to 3,459,688 (Chiapas); 1,885,019 (Guerrero); 790,498 (Oaxaca); and 1,508,254 (Puebla) persons.

Table 7. Marginalisation grade and Gasifier power for four states. Including electricity produced and population

Marginalisation grade and Gasifier power (kW)	Sum of electricity produced (MWh/year)	Average of Marg_ind	Sum of Population
Chiapas	408,948	0.874	3,993,382
150	408,752	0.876	3,977,226
High	256,728	0.602	2,040,884
Middle	40,798	− 0.075	533,694
Very high	111,226	1.769	1,402,648
20	196	0.721	16,156
High	196	0.721	16,156
Guerrero	496,607	1.223	2,159,706
150	496,607	1.223	2,159,706
High	231,345	0.575	979,467
Middle	38,968	− 0.184	274,687
Very high	226,294	2.091	905,552
Oaxaca	124,197	0.780	1,054,504
10	93	1.160	6557
High	19	0.761	356
Middle	14	− 0.092	483
Very high	59	1.711	5718
100	5357	0.885	71,561
High	3027	0.666	38,780
Middle	553	− 0.178	8964
Very high	1776	1.602	23,817
150	113,713	0.787	891,293
High	66,058	0.666	451,137
Middle	23,799	− 0.143	240,958
Very high	23,855	1.669	199,198
20	5035	0.678	85,093
High	2996	0.569	49,808
Middle	706	− 0.098	13,601
Very high	1333	1.621	21,684
Puebla	331723	0.574	2,608,403
10	62	1.093	13,228
High	42	0.594	8042
Very high	20	2.090	5186
100	744	0.364	20,704
High	610	0.468	12,761
Middle	134	− 0.049	7943
150	329496	0.571	2,513,602
High	183,966	0.586	1,101,645
Middle	128,053	− 0.210	1,080,622
Very high	17,477	1.668	331,335
20	1421	0.578	60,869
High	913	0.614	42,714
Middle	373	0.026	11,584
Very high	136	1.485	6571
Total general	1,361,475	0.789	9,815,995

Criteria selection and analysis regarding marginalisation index and potential electricity produced

The analysis was carried out on the municipalities that have the Marginalisation Index (IM) greater than zero, since this represents the population with higher poverty situation. As shown in the frequency graph versus IM for the chosen states (see Fig. 12a–f).

Fig. 12 [Images not available. See PDF.]

Histogram for Marginalisation Index (IM) for municipalities with IM > 0 in several states. Weighted IM: a Guerrero [1.05], b Chiapas [1.06], c Oaxaca [1.05], d Veracruz [1.03], e Puebla [0.88], f México [0.43]

The histogram for Marginalisation Index in municipalities with IM > 0 for several states is shown in Fig. 12, for Guerrero, Chiapas, Oaxaca, Veracruz, Puebla, and Mexico states, with bins corresponding to the marginalisation index (IM), the IM weighted value is around 1.05 for Guerrero, Chiapas, Oaxaca, and Veracruz; while for Puebla is slightly lower 0.88, and México state the lowest 0.43.

The average marginalisation index for all municipalities, and for all values of IM is shown in Fig. 13, where Guerrero, Chiapas and Oaxaca have the highest values for IM, these states have 68%, 79%, and 67% of their population in poverty (see Fig. 8).

Fig. 13 [Images not available. See PDF.]

Average Marginalisation Index (IM) for all municipalities in several states

The data for electricity consumed per capita in municipalities with IM > 0 is presented as histograms in Fig. 14, where for Guerrero and Chiapas the consumption values are the lowest, which emphasises the high poverty for those states, while the data for Mexico state has the highest values, and the lowest IM. The values for the weighted average electricity consumed in kWh/capita are: 25 (Guerrero), 90 (Chiapas), 281 (Oaxaca), 292 (Veracruz), and 457 (México). The increase in electricity consumed per capita indicating a lower poverty level.

Fig. 14 [Images not available. See PDF.]

Histogram for Electricity consumed per capita (kWh/capita) for IM > 0 in several states. Weighted value: a Guerrero [25], b Chiapas [90], c Oaxaca [281], d Veracruz [292], e Puebla [383], f México [457]

The data for marginalisation index (IM) and electricity consumed per capita from CFE for each municipality, for IM > 0, can be used to generate plots for the states of Oaxaca and Puebla (Fig. 15 and Fig. 16), where it can be seen that for higher IM values there are lower values per capita of electricity consumed. The summary for the average values of marginalisation index and per capita electricity consumption is shown in Fig. 17, which highlights that at higher IM values there is lower per capita consumption. The data trend as IM increases goes to a lower consumption per capita; see Fig. 15 and Fig. 16, decreasing from around 300 to 100 kWh/capita for both states. Figure 17 shows the per capita consumption versus IM for all states, with the highest value of 548 kWh/capita and IM = 0.383 is for México state, and the lowest value of 19 kWh/capita and IM = 1.348 is for the state of Guerrero. The trend to lower consumption is related to a higher marginalisation index, Guerrero having a 68% of its population in poverty (see Fig. 8) and IM = 1.11 (see Fig. 9).

Fig. 15 [Images not available. See PDF.]

Relation between Marginalisation Index (IM) and Electricity consumed per capita in Oaxaca state

Fig. 16 [Images not available. See PDF.]

Relation between Marginalisation Index (IM) and Electricity consumed per capita in Puebla state

Fig. 17 [Images not available. See PDF.]

Relation between Annual Electricity consumption per capita and Marginalisation Index (IM). Using primary data to calculate y-axis. Examples in Tables 7, 8, 9, 10

Comparison of electricity consumed from the public company (CFE), potential electricity produced through gasifiers, equipment number and marginalisation index (IM)

Summary tables were prepared with an extract of municipalities in several states based on data from the previous sections and the results of potential electricity produced using the gasifiers.

The state extracts for Oaxaca, Veracruz, Puebla, and México are presented in Tables 8, 910, and 11 respectively. Data are ordered from the highest IM value in the state to the lowest, and overall municipalities selection has the constraint that IM > 0. The last column in each table presents the ratio between the potential electricity produced and electricity consumed in each municipality, representing the possible energy surplus for the municipalities. The marginalisation index for the municipalities in Oaxaca state is in the range of 1.81 to 3.05; for Veracruz state the range is 0.51 to 3.33; for Puebla state the range is 1.4 to 2.43; and Mexico state the range is 0.20 to 0.79. This highlights the high poverty level of Oaxaca and Veracruz.

Table 8. Extract for Oaxaca state, municipalities sample

Municipality	Population	kWh annual consumed	Equipment	Electricity produced (MWh/year)	kWh consumed/ Population	IM	Electricity potential/ consumed
Coicoyán de Las Flores	9936	1,049,939	4	1621	105.67	3.052	1.544
San Martín Peras	12,246	1,945,797	2	580	158.89	2.711	0.298
Magdalena Teitipac	4563	783,418	1	328	171.69	2.390	0.419
San Martín Itunyoso	2298	333,807	1	214	145.26	2.348	0.641
Santa Lucía Miahuatlán	3361	259,922	1	158	77.33	2.334	0.610
Santiago Apoala	875	155,958	2	123	178.24	2.243	0.786
San José Lachiguiri	3251	475,675	1	30	146.32	2.216	0.063
San Miguel Tilquiápam	3149	461,887	2	123	146.68	2.189	0.267
San Simón Zahuatlán	3526	528,143	1	16	149.79	2.155	0.030
Santiago Amoltepec	12,683	155,958	2	837	12.30	2.154	5.365
San Pedro Mártir	1694	442,943	1	233	261.48	2.067	0.525
Santa Cruz Zenzontepec	18,512	2,142,319	5	1874	115.73	2.059	0.875
Santa Lucía Monteverde	6398	1,026,407	3	1147	160.43	2.020	1.117
San Marcial Ozolotepec	1557	109,397	1	149	70.26	2.009	1.361
San Lorenzo Texmelúcan	8323	633,237	2	744	76.08	1.988	1.174
San Juan Tamazola	2877	377,039	1	361	131.05	1.949	0.957
Magdalena Peñasco	3381	501,614	1	141	148.36	1.806	0.282

Table 9. Extract for Veracruz state, municipalities sample

Municipality	Population	kWh annual consumed	Equipment	Electricity produced (MWh/year)	kWh consumed/ Population	IM	Electricity potential/ consumed
Mixtla de Altamirano	11,646	680,590	1	415.3	58.4	3.334	0.610
Atlahuilco	10,933	1,192,824	1	240.7	109.1	1.891	0.202
Los Reyes	5830	523,960	2	875.7	89.9	1.794	1.671
Aquila	1924	252,300	1	412.1	131.1	1.566	1.633
La Perla	26,880	2,766,649	1	466.1	102.9	1.475	0.168
Astacinga	6534	744,966	1	543.8	114.0	1.399	0.730
Calcahualco	12,929	1,715,757	3	986.7	132.7	1.220	0.575
Coetzala	2236	77,155	2	79.0	34.5	1.065	1.024
Comapa	19,859	2,388,707	13	5178.9	120.3	0.977	2.168
Alpatláhuac	10,189	1,415,442	3	1294.2	138.9	0.971	0.914
San Andrés Tenejapan	2921	309,772	1	560.4	106.0	0.958	1.809
Magdalena	3043	203,898	2	81.1	67.0	0.765	0.398
Carrillo Puerto	16,996	23,427	3	1054.0	1.4	0.748	44.990
Acultzingo	22,969	3,302,238	1	451.6	143.8	0.670	0.137
Naranjal	4559	573,680	1	49.4	125.8	0.653	0.086
Coscomatepec	58,479	11,170,556	7	2751.4	191.0	0.635	0.246
Omealca	24,020	266,995	1	199.7	11.1	0.512	0.748

Table 10. Extract for Puebla state, municipalities sample

Municipality	Population	kWh annual consumed	Equipment	Electricity produced (MWh/year)	kWh consumed/ Population	IM	Electricity potential/consumed
Huehuetla	18,803	1,891,172	1	499.1	100.58	2.434	0.264
Olintla	11,517	1,420,050	1	574.6	123.30	2.394	0.405
Hueytlalpan	5186	518,720	1	20.0	100.02	2.090	0.039
Eloxochitlán	12,520	218,214	2	835.7	17.43	2.085	3.830
Zoquitlán	18,278	3,108,576	1	393.7	170.07	2.065	0.127
San Sebastián Tlacotepec	14,092	283,933	2	707.9	20.15	1.919	2.493
Tepetzintla	11,622	953,705	1	325.4	82.06	1.695	0.341
Coyomeapan	13,942	1,846,194	2	697.7	132.42	1.679	0.378
Vicente Guerrero	24,660	3,772,474	3	1222.6	152.98	1.677	0.324
Chiconcuautla	16,569	479,780	2	719.7	28.96	1.581	1.500
San Felipe Tepatlán	3838	155,842	1	252.8	40.61	1.532	1.622
Tepango de Rodríguez	3947	417,460	1	34.5	105.77	1.520	0.083
Teopantlán	3707	1,686,159	2	946.3	454.86	1.475	0.561
Camocuautla	2624	209,469	2	101.3	79.83	1.450	0.484
Ahuacatlán	15,637	1,395,149	1	350.7	89.22	1.443	0.251
Huitzilan de Serdán	15,096	1,309,176	1	364.3	86.72	1.415	0.278
Tlaola	19,982	1,731,289	3	987.1	86.64	1.400	0.570

Table 11. Extract for Mexico state, municipalities sample

Municipality	Population	kWh annual consumed	Equipment	Electricity produced (MWh/year)	kWh consumed/ Population	IM	Electricity potential/ consumed
Donato Guerra	34,000	6,675,764	28	10,787.7	0.00	0.789	1.616
Ixtapan del Oro	6791	1,378,844	7	2804.1	220.44	0.758	2.034
Zacualpan	14,958	2,780,324	19	7435.7	366.60	0.749	2.674
Villa Victoria	104,612	20,301,412	67	25,889.3	3394.27	0.679	1.275
Zumpahuacán	16,927	3,777,292	6	2403.9	278.78	0.543	0.636
San José del Rincón	93,878	14,859,690	81	31,164.4	491.10	0.538	2.097
Sultepec	26,832	6,324,934	16	6267.0	185.80	0.509	0.991
Morelos	29,862	4,587,048	23	8997.9	638.69	0.424	1.962
Acambay de Ruíz Castañeda	66,034	13,998,074	66	25,181.0	169.41	0.380	1.799
Luvianos	27,860	8,008,339	29	11,321.0	700.55	0.379	1.414
Amatepec	26,610	7,840,187	30	11,413.9	332.22	0.332	1.456
Tlatlaya	34,937	6,580,236	33	12,575.0	284.76	0.315	1.911
Villa de Allende	52,641	8,265,593	66	25,277.1	0.00	0.308	3.058
Temascaltepec	31,631	8,693,316	13	4816.0	375.64	0.293	0.554
San Felipe del Progreso	134,143	23,882,442	81	31,215.9	1217.76	0.276	1.307
Otzoloapan	3872	1,259,933	7	2790.6	373.83	0.249	2.215
Aculco	49,026	13,512,458	31	11,724.7	645.10	0.197	0.868

The results show that the ratio of potential electricity produced to consumed (i.e. PEP/C) has a large dispersion (see last column in Tables 8, 9, 10, 11), with an average of the extract in the sampled states of 2.17 (see Table 12, 7th column) meaning that there is a 117% increase in electrical energy that can be produced. For each state the ratio is different with a large standard deviation of 144%.

Table 12. Results summary for chosen States, with Marginalisation Index (IM) greater than zero

State	Population	GWh annual consumed	Equipment	Electricity produced (GWh/year)	Average:kWh consumed/population	Ratio electricity produced/consumed	Average IM
Guerrero	1,909,909	51	1,214	465	19.4	9.11	1.348
Chiapas	3,653,205	189	1,060	405	60.9	2.14	0.933
Oaxaca	896,878	180	398	106	205.6	0.59	0.923
Veracruz	384,168	49	51	18	118.4	0.37	0.920
Puebla	1,491,430	266	556	202	180.6	0.76	0.760
Hidalgo	404,913	63	132	51	175.3	0.81	0.445
México	856,852	181	650	250	548.1	1.38	0.383
						Average ↓	Average ↓
Total	9,597,355	980	4061	1497		2.17	0.816

The PEP/C has wide variation for certain states and municipalities. The PEP/C range for all states analysed is between 9.11 and 0.37 as shown in Table 12, 7th column. For the state of Oaxaca, as shown in Table 8, the PEP/C ranges between 5.365 and 0.030, with 0.59 as the average value. For Veracruz state, the PEP/C is between 1.809 and 0.086 (leaving out the largest value of 44.99), as shown in Table 9, with 0.37 as the average value. For Puebla state (see Table 10) the PEP/C ranges between 2.493 and 0.127. For México state (see Table 11) the PEP/C ranges between 3.058 and 0.554.

Table 12 provides a summary, where the population benefitted with this electrical energy is around 9.6 million people. The potential electricity produced is 1497 GWh/year, the average ratio of potential electricity produced to consumed (PEP/C) is 2.17; for municipalities with an averaged of 0.82 for the marginalisation index.

Corn crop is widespread in all Mexican regions and, thus, there is adequate corn stover availability in the municipalities analysed in the results section. The latter can be used as raw material for the small-scale gasifiers, herein considered having the potential to produce electricity in situ for these municipalities, as shown in the results obtained in Table 12 supplementing the electricity consumed from the public facility.

The aforementioned results show that using the gasifiers coupled to electricity generators can potentially alleviate energy poverty.

The results show that electricity consumption from the public facility, CFE, is low when the IM values are high.

Discussion and conclusions

The results show that small-scale gasifiers have great potential to generate energy in small rural communities (as discussed by [13, 15, 18]), particularly through gasification [18]. Biomass can be an excellent option as input for such small-scale gasifiers due to its availability and low transportation and storage costs (see [16]).

The results provide a method to locate the gasifiers using GIS (complementing the proposals by [34–36]). This research shows the potential that in situ bioenergy production through small-scale gasifiers has to reduce energy poverty in small rural communities (addressing the gaps highlighted by [17]).

Energy is key in achieving sustainable societies. During the last two decades, there have been improvements on bioenergy technological innovations. Nonetheless, energy poverty remains a major problem in many parts of the world, particularly in rural communities, which are dependent on biomass (from agriculture, forest residues, and energy crops) to satisfy their energy needs. Modern energy, in particular electricity, can help rural communities develop; however, around 1.4 billion people lack access to electricity, and many of those who have access are constrained by connections to the grid or high costs of electricity.

Electricity can be produced through bioenergy from residual biomass from several agricultural crops in biorefineries. There has been limited research on small-scale gasifiers’ location and contribution to energy poverty. This work addresses the technical aspects of electricity generation through small scale gasifiers (complementing previous research [see 29–31]).

This paper uses four analysis methods to assess the potential to generate electricity in situ of small-scale gasifiers (10 to 150 kW) to reduce poverty: (1) crops availability data; (2) poverty and marginalisation data; (3) electricity provision/distribution; and (4) GIS/Geographical latitude and longitude to locate municipalities.

This research provides an in-depth analysis into technological approaches to generate energy. It shows the generating potential for electricity using residual biomass with gasifiers, the potential for electricity production using gasifiers that can impact 9.6 million people in communities where poverty is high, and the possible use of 60% of residual biomass from crops harvested in such communities. The research also analyses the best places to locate small-scale gasifiers.

This article provides systemic analysis to reduce energy poverty through in situ electricity generation using cheap accessible small plant technologies and biomass as raw material, as well as their location.

Assessing the potential for installing small-scale gasifiers is relevant from a societal stance, because normally those communities are not close to the power grid and proper communication through good quality roads.

In countries where rural communities cannot afford to pay electricity from the grid, having residual biomass available; with a decentralised approach aiming to reduce poverty, and improving well-being, fostering sustainability, and contributing to SDG 7 (Ensure access to affordable, reliable, sustainable, and modern energy for all) and SDG 1 (End poverty in its forms everywhere).

Further research needs to be carried out considering seasonal variations of the crops, and how to combine technologies, as well as the associated technical knowledge and training for maintenance, infrastructure needed if generation is in situ or needed for connection to the public facility grid, considering also educational, social and cultural aspects with economic and policy instruments.

Author contributions

FJL: conceptualization, writing—original draft, methodology, writing—review and editing, validation, project administration, and data curation. RL: writing—original draft, methodology, writing—review and editing, and validation. DFL-G: validation and visualization. AF-T: writing—review and editing. All authors read and approved the final manuscript.

Funding

Open access funding provided by University of Gävle.

Data availability

To estimate residual biomass, actual agricultural produce is needed and has been obtained from the following:

Data for agricultural produce on a monthly or yearly base for each municipality and irrigation district is available from:

http://infosiap.siap.gob.mx:8080/agricola_siap_gobmx/ResumenProducto.do.

https://www.gob.mx/siap/acciones-y-programas/produccion-agricola-33119.

Annual data in Excel format for agricultural produce in each municipality and irrigation district.

https://nube.siap.gob.mx/cierreagricola/.

Electricity

CFE [Comisión Federal de Electricidad (Federal Electricity Commision)].

Users and electricity consumption for municipalities.

https://datos.gob.mx/busca/dataset/usuarios-y-consumo-de-electricidad-por-municipio-a-partir-de-2018.

Poverty and Marginalisation Index obtained from CONAPO [Consejo Nacional de Población (Population National Council)].

https://www.gob.mx/conapo/articulos/indice-de-marginacion-por-entidad-federativa-y-municipio-2020-271404?idiom=es.

Declarations

Competing interests

The authors declare no competing interests.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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