Development of Software Tool for Optimization and Evaluation of Cycling Routes by Characterizing Cyclist Exposure to Air Pollution Petar Zhivkov Inst. of I&C Tech., Bulgarian Academy of Sciences Sofia, Bulgaria Email: pzhivkov@iit.bas.bg Alexander Simidchiev Medical Institute of Ministry of Interior. Sofia, Bulgaria Email: alex@simidchiev.net Abstract—In modern cities, poor air quality has contributed to replacing motorized cars with active modes of transportation such as cycling. However, when designing and building bike infrastructure, officials neglect to consider air quality concerns connected to cyclists, and most cycling lanes are developed next to heavy-traffic roadways. This poses additional health risks to cyclists, due to their increased ventilation rate. To preserve a sustainable quality of life for a city’s residents, it’s critical to understand how to detect and quantify PM exposure, especially in potentially hazardous locations. This study offers a software tool based on experimental data to optimize and evaluate cycling routes by calculating the overall amount of particulate matter intake in terms of the physiological response of cyclists. I. I NTRODUCTION A IR POLLUTION is a significant public health problem that has long been a source of anxiety for citizens. An air pollutant is described as any substance that can affect humans, animals, plants, or materials. In the case of humans, an air pollutant may cause or lead to an increase in mortality or serious illness, as well as pose a current or potential health risk [1]. Measurements of air emissions are critical for epidemiology and air quality control, but the scope of ground-based air pollution observations has limitations [2]. Somatic symptoms of asthma in adults and children have been linked to moderate increases in vehicular exhaust such as fine particulate matter (PM2.5), nitrogen dioxide (NO2), ozone, carbon monoxide, and traffic-related air pollution (TRAP) [3]. The presence of PM (Particulate Matter) is one of the key causes of increased morbidity and mortality in modern cities. It is a suspended combination of solid and liquid particles that vary in quantity, size, shape, surface area, chemical composition, solubility, and origin. Total suspended particles (TSPs) have a trimodal size distribution in the ambient air, including coarse particles (PM10), fine particles (PM2.5), and ultrafine particles (PM1) [4]. PM size-selective sampling refers to the collection of particles that are below, above, or within a defined aerodynamic range of sizes, which is commonly chosen to be relevant to inhalation and deposition, causes, or toxicity [5]. Poor air quality in large cities has contributed to the substitution of motorized vehicles with an active means of transportation, such as cycling [6]. This method has been extensively adopted by multiple communities due to reduced congestion [7] and the numerous health benefits of physical exercise. Cycling infrastructure near roadways, on the other hand, has been identified as a harmful scenario for cyclists owing to air pollution exposure [8]. Although this has piqued the scientific community’s interest [9], there have been few studies conducted in European cities where many individuals are continually exposed to PM from anthropogenic sources, such as automobile traffic. Estimates of air pollution exposure for research projects are frequently based on measurements obtained by stationary reg- ulatory monitors, such as those operated by the European En- vironmental Agency (EEA). While these monitors are highly precise and well-suited to assuring compliance with federal air quality requirements, their utility for recording individual- level pollution exposure is limited for many reasons: 1) Firstly because monitor locations rarely coincide with exposure loca- tions (e.g., home, work, or school), an individual’s exposure to air pollution can only be measured indirectly through spatial interpolation techniques such as inverse distance weighted interpolation and kriging, or statistical methods such as land- use regression modeling. [10] 2) Secondly, regulatory monitors offer limited temporal resolution (e.g., hourly averages in the case of particulate matter monitors), which may lead them to miss transient spikes in pollution levels; 3) Thirdly, indirect methods of exposure assessment typically estimate exposure for a single location per individual, such as their location of residence, place of work [11], or school [12], which does not capture exposures that occur while people are at different locations or during regular activities like commuting and errands. The majority of dedicated bicycle lanes in cities are close to heavy-traffic roadways, this can lead to a substantial health risk to cyclists due to their high pollutant intake via higher ventilation rates [13], [14] and high levels of physical ac- tivity [8], [15]. Researchers have concentrated on assessing actual exposure levels of cyclists on pre-selected routes using personal samplers [16] or inferring personal exposure from measurements of street-level pollution using mobile labs or Communication Papers of the of the 17 th Conference on Computer Science and Intelligence Systems pp. 105–112 DOI: 10.15439/2022F230 ISSN 2300-5963 ACSIS, Vol. 32 ©2022, PTI 105