University of São Paulo: Reducing carbon dioxide emissions can reduce soybean transport costs by 28% by 2050

The transport sector, responsible for 47% of carbon dioxide (CO2) emissions in Brazil, is one of the largest producers of greenhouse gases in the country, due to the high use of road vehicles, with a significant participation of soybean logistics, which moves about 60 thousand trucks every year. For this reason, research by the Luiz de Queiroz Higher School of Agriculture (Esalq) at USP, in Piracicaba, created a mathematical model that, based on data on demand, soybean transport and economic costs of the different modes of transport, estimates the impact of measures to increase efficiency and reduce emissions. The study calculates that actions such as improving the energy efficiency of road transport and more use of railways, waterways and larger ships could reduce costs by 28% and CO2 emissions by 32% by 2050.


“Brazilian soy logistics are highly dependent on road transport, with low energy efficiency and, if used for long distances, incurs higher costs and higher greenhouse gas emissions. There is a matrix imbalance in soybean transport, which moves more than 63% by road and only 23% by rail and 14% by waterway”, reports the author of the study, Thiago Guilherme Péra, technical coordinator and researcher at the Research and Extension Group. in Agroindustrial Logistics (ESALQ-LOG) at Esalq. “We estimate that around 60,000 trucks are needed annually to carry out soybean logistics in the country. The amount transported is about 30% higher than the amount of soy produced, as a result of the various logistical activities in the soy supply chain,

The researcher explains that the mathematical model proposed in the study quantifies a series of sustainability metrics in transport. “Metrics are the parameters of logistics costs, carbon dioxide emissions, losses in logistics activities, truck demand, fuel demand and transport demand, which incorporate multiple objectives to be optimized: logistics costs, carbon dioxide emissions and losses”, he reports. “The model also incorporates Brazil’s infrastructure logistics network, involving economic costs of road, rail, waterway and maritime transport, from production regions in Brazil to consumer centers and importing countries, considering infrastructure capacity constraints, supply, demand, among others, for the time horizon of 2020, 2030, 2040 and 2050.”

According to Péra, the model is geared towards the adoption of green logistics, which seeks solutions that bring an environmental perspective to a discussion normally treated only as an economic concern, such as logistics costs, for example. “With the model, it is possible to evaluate different strategies and, as it is an approach with multiple objectives, it is possible to evaluate the efficient frontier that generates the best results involving the combinations of costs, emissions and losses”, he highlights. “The environmental approach used in this research was the search for an evaluation of strategies related to decarbonization, understood as a process of mitigating carbon dioxide emissions resulting from logistics activities, mainly transport.”

Demand
To exemplify the method, the researcher cites the data obtained on the influence of Asian demand on soybean logistics. “A 1% increase in the Asian demand parameter causes an increase of 1.305% in the total cost of transport variable, 1.197% in CO2 emissions, 0.264% in losses during transport”, he describes, “an increase of 1.346% in the demand for trucks in the country, of 1.733% in the demand for diesel oil, of 0.966% in the demand for fuel oil, used for maritime transport, and a growth of 0.621% in the railway demand, 3.476% in the waterway, 0.966% in the maritime and 1.895% at the bus station”.

The research identified conflicts that improve total transport costs and CO2 emissions, but worsen losses. “The improvement in costs is obtained by increasing the capacity of rail and waterway terminals, reducing the cost of rail and waterway transport, improving the energy efficiency of rail transport and increasing the average speed of rail transport”, points out Péra. “The worsening in losses is due to the fact that the greater use of multimodality promotes a greater level of physical loss during transport.”

At the same time, the study pointed to factors that improve transport costs and reduce losses, but increase emissions. “We identified a reduction in the cost of road transport to the port, an increase in the driver’s working hours and an increase in the average speed of road transport”, says the researcher. “Finally, the main solutions that provide cost, emissions and loss reductions are the reduction of demand from Asia, Europe and the domestic market, in addition to increasing the load capacity of trucks and the energy efficiency of road transport.”

The work also evaluated the impact of technological and infrastructure shocks on sustainability metrics. “The best scenario that promotes decarbonization and cost reduction compared to the baseline scenario, without technological progress by 2050, involves improvements in energy efficiency standards of road transport, greater use of rail and waterways, as well as the replacement of current ships (Panamax) for larger ships (Capesize)”, highlights Péra. “Such a scenario reduces logistics costs by 28%, promotes decarbonization by reducing carbon dioxide emissions by 32%, in addition to reducing the demand for trucks by 43%, diesel by 43% and oil demand. fuel by 28%.”

The study indicates a series of actions aimed at promoting green soy logistics by 2050, with a view to decarbonization and cost reduction. “There are a series of public and private policies recommended, at different levels, so that Brazil can enter the decarbonization route in transport, also generating cost reductions for the soy agribusiness production chain”, emphasizes the researcher. The research is described in a doctoral thesis supervised by Professor José Vicente Caixeta-Filho, from the Graduate Program in Applied Economics at Esalq and defended on February 23.

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