Product system

The system under study corresponds to milk production in small and medium scale farms in Mexico, considered as a semi-intensive system whose production inventory amounts to 85 % of the national total^23,24. It is a very heterogeneous production system with respect to its technological, agroecological, and socioeconomic level²⁵. Small and medium-scale dairy farming is characterized by a small number of animals in the production units²⁶. Out of a total of 257 thousand small- and medium-scale producers, 47.30 % have 30 cows or less²⁷, the milk-producing breeds are mainly Holstein, and the milking is done manually²⁸.

In 2021, the semi-intensive production system had an inventory of 2’579,223 heads of dairy cattle and an output volume of 11’046,795.96 liters of fluid milk. The annual productivity per cow was 4,017 liters, i.e., 13.17 liters per day²⁹.

Definition of objectives and scope

The objective of this study was to evaluate the environmental performance of cow’s milk production in a semi-intensive family system in Mexico in the year 2030. The functional unit was 1 kg of milk adjusted for fat and protein (MAFP). According to the International Dairy Federation (IDF), the use of the MAFP unit ensures a fair comparison with different breeds or feeding regimes³⁰. The weight of raw milk was converted to MAFP using the following equation:

The fat and protein contents were established considering the average of the values established in the book Bovine milk production in the family system in Mexico ("Producción de leche de bovino en el sistema familiar en México"), being 4.5 % and 3.5 %, respectively⁵.

System limits

System boundaries were established considering a cradle-to-gate approach (Figure 1), i.e., from the extraction of raw materials used in cattle feed until the milk is ready to leave the farm. The system considered two main sub-systems: 1) Cow feed production: considers the activities and processes related to the cultivation of fodder crops and legumes. 2) Milk production: considers the activities of transporting feed to the farm and feeding the cows for 305 d corresponding to the milking period³¹.

Figure 1 Outline of the limits of the milk production system 

Inventory analysis

The study considered data from secondary sources of information. The volume of production and the inventory of heads at the national level were obtained from the database of the Agri-Food Information System for Consultation (Sistema de Información Agroalimentaria de Consulta)²⁹. Inputs used in livestock feed were obtained from scientific books of the National Institute for Research on Forestry, Agriculture, and Livestock (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias)^5,6.

In order to determine the milk production per cow per year, the values corresponding to the volume of national production and the national cattle head inventory were estimated²⁹. The volume of fluid milk output (thousands of liters) in Mexico was forecast for the period 2021-2030, using the univariate statistical method of series (ARIMA)³². Statistical tests, model estimation and forecasts were performed with the Simetar^® software.

The probability distribution was used as a risk factor to determine the minimum and maximum of the milk volume and price series. These confidence intervals were used to construct the pessimistic (lower interval), baseline (mean), and optimistic (upper interval) scenarios. Milk volumes were calculated by production system (barns with an average of 8 cows); the volume of production per cow per day and per year was calculated considering a 305-d lactation period (Table 1).

Table 2 shows the various proportions of the dietary ingredients used in the feeding of the cows.

The inventory for the production of 1 kg of milk - MAFP was integrated according to the above information. (Table 3).

The inventory for S1 was integrated considering the feed supplied to the cows: corn silage, hay alfalfa, corn stubble, green alfalfa, fodder corn, concentrate 01, agricultural residues and protein 10. The data were obtained from the Agricultural and Food Database (AGRIBALYSE), Environment and Energy Management Agency (Agribusiness)³³.

The inventory for S2 was integrated considering:

Occupation of barn floor: bovine milk production in a semi-intensive system is regularly carried out in individual cubicles with free access in a paved corral; according to the manual of good livestock practices in bovine milk production units³⁴, under these conditions, dairy cattle require a surface area of 9 m²/cow.

Fuel consumption: the number of liters of fuel per kg of MAFP produced was calculated based on the type of vehicle required to transport the ingredients, the fuel efficiency expressed in km/liter, and the load capacity, adjusted for the functional unit.

Electricity consumption: in small and medium-scale production systems, the milking is done manually; therefore, only artificial lighting of the barn was considered³⁴, and adjustment was made for the number of days (305) that the cows remain in lactation.

Water consumption: water consumption per cow was estimated for the lactation period (305 days); lactating cows consumed an average of 110 L of water per day³⁵.

Methane (CH₄) emissions from manure fermentation and manure management, and nitrogen (N) and nitrous oxide (N₂O) emissions from manure management were estimated using the emission factors established for Mexico by the National Institute of Ecology and Climate Change (Instituto Nacional de Ecología y Cambio Climático)³⁶.

Environmental impact assessment

The impact assessment was performed in OpenLCA V.1.11.0 software, using the ReCiPe 2008 method. Seven midpoint categories were considered for this study: agricultural land occupancy (ALO), climate change (CC), fossil depletion (FD), human toxicity (HT), marine ecotoxicity (ME), soil acidification (SA), and water depletion (WD)³⁷. These categories were selected for having the highest relative contribution of environmental impacts and for the frequency of their use in the literature on similar researches.

Environmental impact assessment

The results of the characterization for the baseline scenario identified seven categories (ALO, CC, FD, HT, ME, SA, and WD) as the main contributors to the environmental impacts in the production of 1 kg of MAFP. Table 4 shows that the food production subsystem (S1) is responsible for most of the total impact, with percentages of over 71 % in the following categories: CC, FD, HT, WD, ME, and ALO. While the milk production subsystem (S2) contributes to environmental loads in the categories SA (58.94 %), CC (28.16 %), and FD (25.58 %).

The processes involved in the production of 1 kg MAFP involved in the generation of environmental loads are presented in Figure 2. In subsystem 1, the main contributors are: concentrate 01 production in categories HT (60.83 %), ME (44.12 %), FD (37.78 %) and CC (17.35 %), corn silage production in categories SA (28.03 %), WD (26.74 %), ALO (26.74 %), CC (17. 94 %) and ME (16.73 %), protein 10 production in categories HT (37.63 %), ME (28.10 %) and FD (26.79 %), forage corn production in category WD (67.79 %) and green alfalfa production in categories ALO (62.68 %) and CC (18.42 %).

Figure 2 Contribution of the processes involved to the different impact categories 

In subsystem 2, the environmental load of the production of 1 kg MAFP, is derived from livestock rearing mainly for categories TA (58.94 %) and CC (26.61 %) and from the transport of inputs to the farm, specifically in category FD (25.58 %).

Comparative analysis of scenarios for the production of 1 kg MAFP

Figure 3 shows the comparison of the environmental results in the baseline, optimistic and pessimistic scenarios for the seven impact categories for the years 2021 and 2030.

Figure 3 Comparative analysis of environmental loads between 2021 and 2030, for the pessimistic, baseline, and optimistic scenarios. 

The comparative results between the pessimistic, baseline, and optimistic scenarios show that, in 2021 and 2030, the optimistic scenario allows a reduction of 6 % and 5 %, respectively, of emissions in all impact categories. This is due to the increase in production volume and the improvement in production efficiency, which allows for a reduction in the intensity of emissions¹⁹.

For the years 2021 and 2030, in the ALO category, the optimistic scenario exhibited a reduction of 0.36 and 0.33 m² per kilo of MAFP, respectively. A pessimistic scenario implied an increase of 0.44 and 0.37 m² per kilo of MAGP.

In the CC category, the optimistic scenario allowed a decrease of 0.53 kg for 2021 and 0.49 kg CO₂ eq per kg MAFP for 2030. On the other hand, the production of 1 kg of MAFP in a pessimistic scenario implied an increase of 0.066 and 0.045 kg of CO₂ eq per kg of milk, respectively.

In the optimistic 2021 and 2030 scenarios, a decrease of 0.0027 and 0.0026 kg oil eq per kilo of MAFP, respectively, was observed in the FD category. The pessimistic scenario showed an increase of 0.0034 and 0.0028 kg oil eq per kilogram of MAFP.

For the year 2030, the HT and ME categories in the optimistic scenario predicted a reduction of 0.059 and 0.095 kg 1,4-DB eq per kilo of MAFP, respectively, and in the pessimistic scenario, an increase of 0.12 and 0.10 kg 1,4-DB eq per kilo of MAFP, respectively.

In the SA category, the optimistic scenario for the years 2021 and 2030 allowed a reduction of 0.0027 and 0.0025 kg SO₂ eq while the pessimistic scenario implied an increase of 0.0033 and 0.0027 kg SO₂ eq per kg MAFP.

Finally, in the WD category for the years 2021 and 2030, there was a reduction of 0.0026 and 0.0024 m³ of water per kilo of MAFP, respectively, in the optimistic scenario, and an increase of 0.0032 and 0.0027 m³ of water per kilo of MAFP, respectively, in the pessimistic scenario.

Agricultural land occupancy

The environmental load of the production of 1 kg of MAFP in the ALO category was 6.14 m² in its baseline 2021 scenario. The main contributors to this category are related to the cultivation of green alfalfa (62.68 %), followed by corn silage (26.74 %). These results are higher than the 1.89 m²/yr per kg of MAFP cited by Berton et al¹⁶, where the land was destined for agriculture that produces the inputs required for livestock feeding in traditional small-scale systems in Italy, and also superior to the results presented by Xiaoquin et al³⁸, where the production per kilo of MAFP requires occupancy of 1.16 m² to 2.49 m², highlighting that 98 % corresponds to land occupation for feed production and 2 % corresponds to stables. Rivera et al³⁹ reported an occupancy of 1.33 m² per kilo of MAFP in a conventional milk production system in Colombia.

However, the results of this study showed an occupancy below 8.8 to 11.2 m² per kg of milk in Ethiopia⁴⁰ and agree that fodder production on soils with low biomass yields is a determinant for the contribution of impacts in the ALO category¹⁸; thus, it is possible to use 2.25 m² less soil in intensive systems than in less technified ones⁴¹.

In the year 2021, the optimistic scenario presented a production of 4,594 kg of milk per cow (15.06 kg/d), being the highest production of the compared scenarios, which meant the lowest contribution in the ALO category with 5.78 m², while in the pessimistic scenario milk production decreased to 4,010 kg cow/yr (13.16 kg/d); this represented an increase in land occupation of 6.62 m² (Figure 3). An increase in milk production per area of agricultural land is accompanied by an improvement in environmental efficiency⁴².

Climate change

In the CC impact category, 0.85 kg CO₂ eq was generated per 1 kg MAFP in the baseline scenario. The main contributors for this category are related to cattle breeding (26 %), followed by green alfalfa (18.32 %), corn silage (17.84 %), and concentrate 01 productions (17.26 %) (Figure 2). Environmental burdens from livestock breeding are mainly attributed to CH₄ emissions from enteric fermentation and manure management, while environmental burdens from forage and legume production are mainly related to N₂O emissions generated by the use of agrochemicals in agricultural practices.

The environmental impact of CC found in this study is below 1.42 kg CO₂ eq per kilo of MAFP in a semi-intensive system¹⁸. Kim et al⁴³, compared small-scale (150 cows) and intensive (1,500 cows) systems and reported values of 1.22 and 0.98 kg CO₂ eq, respectively, demonstrating that feeding practices such as a reduction in the proportion of fodder to 50 %, as well as the use of more digestible fodders, can help to improve the quality of the feed, and that an increase in fat supplementation can reduce CC contributions by up to 7 %. With respect to the production of concentrates⁴⁴, they point out that it is possible to relate this to an increase in GHG generation by modeling a reduction in feed consumption, attributing the increase to a diminution of the milk production volume per cow.

The values found in the different scenarios of the current study range from 0.853 kg CO₂ eq per kg MAFP for barns with a yield of 4,594 kg of milk per year (15.06 liters/d) in an optimistic scenario, to 0.977 kg CO₂ eq per kg MAFP for barns with a yield of 4,010 kg of milk per year (13.16 liters/d), 0.788 kg CO₂ eq per kg MAFP in a semi-stabled system in Brazil with a yield of 6,335 kg milk⁴⁵, where lower CO₂ eq. values may be associated with higher levels of milk production per cow¹⁸.

Fossil depletion

The environmental impact for the FD category was 0.48 kg oil eq. for 1 kg of MAFP; the main contributions for the production of concentrate 01 (34.59 %) and protein 10 (24.52 %) correspond to S1, while 25 % of the emissions are generated in the transportation of inputs to the farm (Figure 2). This value is below the 4.82 kg oil eq¹⁸, where the processes with the greatest impact were corn silage production (45.7 %), pasture production (34.3 %), and transportation of inputs to the farm (10 %). Ferreira et al⁴⁶⁾ point out the importance of knowing the origin of inputs in the supply chain in order to reduce transportation impacts.

The values found in the different scenarios considered in this study range from 0.044 kg oil eq, in an optimistic 2021 scenario, to 0.051 kg oil eq, in a pessimistic 2030 scenario (Figure 3); these variations correspond to the increase or decrease in milk productivity per cow.

Soil acidification

For the SA category, 1 kg of MAFP generated a total of 0.043 kg SO₂ eq in its 2021 baseline scenario. The main generator of emissions for this category is livestock farming (58.75 %), followed by corn silage production (28.83 %) and emissions generated by livestock farming from the volatization of nitrogen in the form of ammonia (NH₃) (Figure 2). Emissions from corn silage production are NH₃ and N₂O.

The total emissions generated in this category are higher than the 0.001 kg SO₂ eq.¹⁸ and the 0.020 kg SO₂ eq. attributable mostly to emissions from manure management and nitrogen fertilizer use reported⁴³. In both studies, corn silage was one of the main contributors to emissions generation for this impact category. The specialized literature has shown how reliance on commercial concentrates can result in the contamination of soils and water bodies by excess nutrients, in addition to competing directly with the production of other foods for human consumption.

The optimistic 2021 scenario presents the lowest value in the SA category with 0.043 kg SO₂ while the pessimistic 2021 and 2030 scenario presents the highest value with 0.049 kg SO₂; the increase in production volume allows the reduction of the environmental impact in the SA category.

Water depletion

Water depletion per 1 kg MAFP was 0.04225m³ in its 2021 baseline scenario; the main consumption was for the production of fodder corn (67.08 %) and corn silage (27.74 %). Water consumption in this study is slightly above 0.00587 m³⁽¹⁸; similarly, in this study, the highest water consumption was in corn crops. However, there is high variability in the WD category with consumptions from 0.02800 m³ to 0.09900 m³, so that, as farm size increases, water consumption decreases, because the largest water footprint of milk production corresponds to the cultivation of fodder crops to sustain smaller scale production systems⁴¹.

The values presented in the comparative scenarios (Figure 3) range from 0.042 m³ of water for the optimistic scenario to 0.048 m³ for the pessimistic scenario. Water is an essential input for the cleaning and consumption of animals⁴⁷, although there is no way to reduce the water intake, as an animal’s physiological requirements and milk production influence its consumption; proper water management is an adequate alternative to minimize losses of this vital liquid.

Human toxicity and marine ecotoxicity

Toxicity-related categories presented values of 1.5 kg 1,4-DB eq for HT and 1.64 kg 1,4-DB eq for ME. Although these values are not generally considered in the literature, since there are no comparative reference data, in this study they represent an important relative contribution to the environmental loads; the main contributors are the production of concentrate 01 and protein 10 (Figure 2), with percentages of 60.83 % and 37.63 % for HT, and 44.12 % and 28.10 for ME. The values presented in the comparative scenarios (Figure 3) are the lowest in the optimistic 2021 scenario (1.56 kg 1,4-DB eq for HT and 1.64 kg 1,4-DB eq for ME), while the highest value is presented for the pessimistic 2030 scenario (1.78 kg 1,4-DB eq for HT and 1.88 kg 1,4-DB eq for ME).

Environmental impact mitigation strategies

The results of the evaluated scenarios provide a great opportunity for action to position dairy farming in a positive scenario; the increase in production volumes was observed to be accompanied by a decrease in environmental loads. One strategy to improve the environmental performance of semi-technified milk production systems is to improve the productivity per lactating cow¹⁸; this would allow the mitigation of the environmental impacts without reducing the milk production. It is possible to increase the production volume by increasing efficiency with fewer cows. This implies not only an environmental benefit but also an economic and social benefit that allows progress towards the sustainability of milk production systems.

This study identified the main processes that contribute to the generation of environmental impacts, first of all, agricultural activities related to crop cultivation required for livestock feeding and manure management. This gives way to the implementation of comprehensive strategies such as the transition to a circular economy through regenerative processes to eliminate losses and waste throughout the biological cycle. As an opportunity to close the cycle, the feces and urine of livestock can be used as natural fertilizer; the use of good management practices and with the corresponding monitoring, can contribute to soil health and reduce CH₄ emissions to the atmosphere⁴⁸.