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. 2025 Aug 7;25(15):4874.
doi: 10.3390/s25154874.

Integrating Environmental Sensing into Cargo Bikes for Pollution-Aware Logistics in Last-Mile Deliveries

Leonardo Cameli  1 , Margherita Pazzini  1 , Riccardo Ceriani  1 , Valeria Vignali  1 , Andrea Simone  1 , Claudio Lantieri  1
Affiliations

Integrating Environmental Sensing into Cargo Bikes for Pollution-Aware Logistics in Last-Mile Deliveries

Leonardo Cameli et al. Sensors (Basel). .

Abstract

Cycling represents a significant share of urban transportation, especially in terms of last-mile delivery. It has clear benefits for delivery times, as well as for environmental issues related to freight distribution. Furthermore, the increasing accessibility of low-cost environmental sensors (LCSs) provides an opportunity for urban monitoring in any situation. Moving in this direction, this research aims to investigate the use of LCSs to monitor particulate PM2.5 and PM10 levels and map them over delivery ride paths. The calibration process took 49 days of measurements into account, spanning different seasonal conditions (from May 2024 to November 2024). The employment of multiple linear regression and robust regression revealed a strong correlation between pollutant levels from two sources and other factors such as temperature and humidity. Subsequently, a one-month trial was carried out in the city of Faenza (Italy). In this study, a commercially available LCS was mounted on a cargo bike for measurement during delivery processes. This approach was adopted to reveal biker exposure to air pollutants. In this way, the operator's route would be designed to select the best route in terms of delivery timing and polluting factors in the future. Furthermore, the integration of environmental monitoring to map urban environments has the potential to enhance the accuracy of local pollution mapping, thereby supporting municipal efforts to inform citizens and develop targeted air quality strategies.

Keywords: LCS; air quality; cargo bike; cycling routes; environmental sensors.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Figure 1
Figure 1
Flowchart of research activities.
Figure 2
Figure 2
Smart Citizen Kit concept.
Figure 3
Figure 3
Cargo bike of the Faenza Pilot Project.
Figure 4
Figure 4
Correlation analysis for PM2.5 (a) and PM10 (b).
Figure 5
Figure 5
Bland–Altman plot for PM2.5 (a) and PM10 (b).
Figure 6
Figure 6
Histogram (a) and scatterplot (b) to standardize the residual PM2.5.
Figure 7
Figure 7
Histogram (a) and scatterplot (b) for standardizing the residual PM10.
Figure 8
Figure 8
Histograms for standardized residuals of PM2.5 (a) and PM10 (b).
Figure 9
Figure 9
Delivery heatmap (a) and speed (b) during delivery process.
Figure 10
Figure 10
Environmental map in Faenza urban center: PM2.5 (a) and PM10 (b).
See this image and copyright information in PMC

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