This study focused on verifying whether the emission of air pollutants in São Paulo increases the costs and number of hospitalizations for respiratory diseases in Brazil. Data on pollutant emissions, hospitalizations, and hospital costs were collected from 2008 to 2017 and correlated with air quality standards. The results showed that the concentration of particulate matter increased each year during the study period and was highly correlated with hospitalizations due to respiratory diseases. Ozone (O₃) was within the quality standard throughout the study period but registered an increase in the mean and a positive correlation with hospitalizations due to respiratory diseases. The carbon monoxide (CO), sulfur dioxide (SO₂), and nitrogen dioxide (NO₂) levels were within the quality standards throughout the study period with a decrease in the last years studied, but showed a positive correlation with hospitalizations due to respiratory diseases. The pollutant emissions and hospitalizations due to respiratory diseases had an inverse relationship with the monthly rainfall curve for São Paulo, which indicates that rainfall tended to reduce pollutant emissions and consequently hospitalizations due to inhalation of these pollutants. Because costs are directly associated with hospitalizations, both increased during the study period—302,000 hospitalizations at an average cost of 368 USD resulted in a total cost of 111 million USD. To reduce these costs, Brazil should implement stricter policies to improve the air quality of its major cities and develop a viable alternative to diesel vehicles.

Renewable energies are cleaner forms of energy, and their use, has intensified in recent decades. Thus, this work presents a proposal for reducing the emissions, fuel cost, and respiratory disease hospitalizations using environmental cost accounting principles to produce biodiesel production from waste frying oil. In our methodology, we conducted surveys, and collected waste cooking oil samples from local households and restaurants in São Paulo city, Brazil. Then, we produced biodiesel using these samples. Data on air pollutants were collected and correlated with the number of hospitalizations for respiratory diseases and their costs. Our results indicate that 330,000 respiratory disease hospitalizations were recorded in São Paulo city between 2009 and 2018, and the total cost for the Brazilian government reached US $117 million. Improving the city air quality by switching from fossil fuels to biodiesel could reduce the annual number of hospitalizations to 9880 and cost US $3.518 million, because the amount of pollutants emitted from burning fossil fuels was positively correlated with the number of respiratory disease hospitalizations and their costs. Moreover, the emission rates of particulate matter with particles less than 10 and 2.5 µm in diameter exceeded the World Health Organization limits throughout the study period. Using the survey data, we estimated that the average monthly quantity of waste cooking oil was 9794.6 m³, which could generate 9191.2 m³ of biodiesel and produce 239,713 t CO₂ of carbon credits. Environmental cost accounting revealed that it would be possible to achieve an annual profit of approximately US $300 million from the sale of excess biodiesel, carbon credits, and glycerine, and fuel acquisition savings which could improve the image of São Paulo city and quality of life of its residents. Thus, we present this as a way to reduce cost and hospitalizations, and increase the number of available hospital beds for other diseases, such as COVID-19.

Over the last few years, electric vehicles (EVs) have turned into viable urban transportation alternatives. Charging infrastructure is an issue, since high investment is needed and there is a lot of demand uncertainty. Seeking to fill gaps in past studies, this investigation proposes a set of procedures to identify the most adequate places for implementing the EV charging infrastructure. In order to identify the most favorable districts for the installation and operation of electric charging infrastructure in São Paulo city, the following public available information was considered: the density of points of interest (POIs), distribution of the average monthly per capita income, and number of daily trips made by transportation mode. The current electric vehicle charging network and most important business corridors were additionally taken into account. The investigation shows that districts with the largest demand for charging stations are located in the central area, where the population also exhibits the highest purchasing power. The charging station location process can be applied to other cities, and it is possible to use additional variables to measure social inequality.

This paper explores the transition to electric cars in Brazil. The country has been successful to reduce its carbon footprint using biofuels, but it is facing a dilemma in vehicle electrification. It cannot shift abruptly to battery electric vehicles, as current consumers are unable to afford them and investment in recharging infrastructure is uncertain. However, it has a significant manufacturing base, and it cannot isolate itself from global industrial trends. This study relies on the inductive case study method, identifying the core green technologies in vehicle electrification and extrapolating their trends, to explain how the transition process is feasible. The emergence of a dominant design (set of core technologies defining a product category and adopted by the majority of players in the market) in small and affordable segments is essential for the diffusion of electric cars in developing countries. Biofuel hybrid technologies may support the transition. The Brazilian industry can engage in electric vehicle development by designing small cars based on global architectures, targeting consumers in emerging markets. The article contributes by using a dominant design core technologies framework to explain and map the transition to electric vehicles in developing countries, supporting academic research, government, and industry planning.

Overview: Forecasting demand for new products is a challenging task, as it involves capturing relations of complex variables in markets where little or no historical data exist. Managers usually rely on surveys, intuition, and heuristics to forecast new products. Linear statistical tools used to predict demand for existing products are not suitable because there are not enough data to capture complex nonlinear relations in yet-to-be launched products. Other tools are appropriate for aggregate new categories but not for incremental company-specific products. Machine learning can capture complex nonlinear relations, but it usually requires significant amounts of data. Using an expert’s domain knowledge can circumvent the need for vast training datasets. To support product development activities, we propose a method that combines domain knowledge and machine learning to forecast market share of complex incremental new products. An experiment from the automobile industry shows the approach yields expressive results (82 percent forecast accuracy).

The access to open government data has been a relevant topic for societies around the world, especially over the last ten years. This paper aims to analyze the indicators of the São Paulo City Observatory (ObservaSampa), confronting them with the ISO 3712x series (sustainable, smart, and resilient cities) standards, to assess if the former meet both open data principles and the ISO prescriptions. Bibliometric analysis, comparative analysis, cluster analysis, and principal component analysis (PCA) were the methods used in this research. From the comparative analysis, 18 indicators were identified as conforming and 41 as partially conforming. Thus, 20% of the ObservaSampa indicators adhere to the ISO standards. The PCA applied to the conforming indicators shows component 1 is related to socioeconomic dimensions, while component 2 refers to social policy, with both appraisals confirmed by cluster analysis. Measuring and presenting city data in compliance with indicator standards is relevant because they open the possibility of comparing different cities. However, there is still a lack of consensus on a common set of indicators to be accommodated within the current ISO standards system.