Urban freight transport (UFT) is simultaneously responsible for maintaining the urban lifestyle and the negative externalities impacting urban areas, necessitating strategies that promote sustainable urban freight transport (SUFT). In addition, the stakeholders and geographic factors involved in UFT impose specific concerns in the planning and operation stages of SUFT. Therefore, this paper proposes a model addressing sustainable last-mile delivery considering the relationship between the activity system, transportation system, and stakeholders involved in UFT. Based on the literature review, we identified UFT planning procedures to achieve SUFT. In a cyclical process, these procedures were considered on the proposed model, integrating freight transport planning with urban planning to develop SUFT and, consequently, sustainable cities.

On-road measurement of vehicle tailpipe emissions, analyzing the data and developing a model, is very important to identify and recommend improved design and management approaches for the transport sector. A light-duty vehicle, the flex-fuel Nissan Versa equipped with a 1.6 liter engine and manual transmission was monitored in real operation. The on-board monitoring equipment consisted of a five-gas analyzer for CO, HC(CH4), NOx, CO2 and SO2 in addition to dry systems, with sample lines directly connected to the tailpipe, and an on-board diagnostics (OBD II) connector, GPS, including other additional parameters monitoring (i.e. data logger with embedded microcontrollers). The operating parameters registered in this vehicle were: vehicle speed, engine speed, fuel consumption, angle position of the throttle valve, cooling water, oil and exhaust gas temperatures. The measurements were performed using gasoline with 27%, and 100% ethanol blends (E27 and E100 respectively, where E27 is used in emission certification). The vehicle-experiment (driving pattern) was realized in an urban route in the Fortaleza City, Brazil, under typical traffic conditions. The analysis indicates that the average emission rates (kg/h) for CO are more than a factor of 10 higher to NO idling emissions. AVL CRUISE integrated with AVL BOOST software were used to model the vehicle and the flex-fuel engine engine in both certification driving cycles and real operation ones. Real operation data is used to validate the model

Este trabalho se propõe a verificar a influência dos modos de operação nas emissões de poluentes provenientes de veículos flex. Para isto, um ciclo de condução real foi desenvolvido para o veículo leve tipo flex em um trecho urbano da cidade de Fortaleza. Para a coleta de dados foi utilizado um método on-board de coleta instantânea de parâmetros cinemáticos, de motor, de emissões veicular e de via. Devido às características locais do tráfego, observou-se uma maior representatividade do modo de operação idle. Em geral, observou-se ainda uma maior influência do modo de operação aceleração nas emissões de poluentes e no consumo de combustíveis. A maior taxa de emissão média de CO2 foi observada durante o modo de operação aceleração (6,38 mg/s), seguido do modo idle (4,70 mg/s). Para o poluente CO, a maior taxa de emissão média foi observada também durante o modo de operação aceleração (55,60 µg/s), seguido do modo idle (35,01 µg/s). Já para o poluente NOx, maiores taxas de emissão foram observadas no modo de operação aceleração, com 5,08 µg/km e 1,98 µg/km para o modo idle. O consumo médio de combustível no modo de operação aceleração foi de 6,61 L/100 km durante os testes, seguido dos modos idle e desaceleração, com 4,84 e 3,39 L/100 km, respectivamente.

The increase in the fleet of motor vehicles circulating in urban centers is one of the main generators of gaseous pollutants harmful to human health and the environment. Pollutants can be economically and effectively monitored through passive sampling. This study aims to estimate NO2 levels on roads of Fortaleza city /CE using the passive sampling method. 12 campaigns covered the rainy (March-June) and the dry (July-November) seasons in 2019. The seasonal averages of NO2 in the rainy season were higher than the dry one, and Almirante Rubim Street showed the greatest difference in the averages: 26.6 µg m-3 in the rainy and 19.3 µg m-3 in the dry season. The principal component analysis applied to the averages of NO2 concentration in the rainy and dry seasons, vehicle traffic and Height of the road/width ratio indicated that components 1, 2 and 3 explain 94.4% of the studied cases. Passive sampling proved to be efficient, contributing to the production of unpublished data about NO2 levels in streets of Fortaleza/Ceará/Brazil from mobile sources.