Air Pollution alongside Bike-Paths in Bogotá-Colombia - PDF

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ORIGINAL RESEARCH published: 25 November 2016 doi: /fenvs Air Pollution alongside Bike-Paths in Bogotá-Colombia JuanF.Franco 1 *,JuliánF.Segura 2 andivanmura 3 1 GroupofStudiesonUrbanandRegionalSustainability,SchoolofEngineering,UniversidaddelosAndes,Bogotá,Colombia,

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ORIGINAL RESEARCH published: 25 November 2016 doi: /fenvs Air Pollution alongside Bike-Paths in Bogotá-Colombia JuanF.Franco 1 *,JuliánF.Segura 2 andivanmura 3 1 GroupofStudiesonUrbanandRegionalSustainability,SchoolofEngineering,UniversidaddelosAndes,Bogotá,Colombia, 2 ResearchGrouponEnvironmentalManagement,SchoolofEngineering,UniversidadEAN,Bogotá,Colombia, 3 COPA Research Group, Department of Industrial Engineering, School of Engineering, Universidad de los Andes, Bogotá, Colombia Edited by: Maurice Millet, University of Strasbourg, France Reviewed by: Maria De Fatima Andrade, University of São Paulo, Brazil Delhomme Olivier, University of Lorraine, France *Correspondence: Juan F. Franco Specialty section: This article was submitted to Air Pollution, asectionofthejournal Frontiers in Environmental Science Received: 20 September 2016 Accepted: 09 November 2016 Published: 25 November 2016 Citation: FrancoJF,SeguraJFandMuraI (2016) Air Pollution alongside Bike-Paths in Bogotá-Colombia. Front. Environ. Sci. 4:77. doi: /fenvs The study we present in this paper aims at characterizing the range of fine particulate matter(pm 2.5 )andblackcarbon(bc)concentrationstowhichbike-pathusersinbogotá are exposed to. Using a bike equipped with a DustTrak and a micro-aethalometer we measured PM 2.5 and BC concentration levels along bike-paths corridors, during weekdays and weekends. Experiments were conducted in fours streets, representing four typical configurations of bike-paths in the city. Traffic data for workdays was also available from local mobility authority. Results indicate that bike-paths users in Bogotá are exposed to air pollution levels far exceeding the threshold values established as potentially dangerous for human health. Average concentrations for PM 2.5 ranged between 80 and 136ug/m 3 in workdays and between 30 and 72 ug/m 3 in weekends. BC mean concentrations were between 16 and 38 µg/m 3 during workdays and in the range 10 32µg/m 3 during weekends. A statistically significant difference exists in the levels of pollutants concentrations measured during workdays and weekends for all the considered bike paths. According to our results, both traffic volume and diffusions conditions, which are affected by many factors including street geometry, affect bike-path user s exposure levels. Taking into account the important role that bicycling is playing as an alternative transport mode in Latin American cities, we consider these results provide useful insights to increase the appreciation of the excessive bikers exposure to air pollution in Bogotá. Moreover, these findings contribute with technical elements that should lead to the inclusion of air quality variable when designing and planning sustainable urban mobility infrastructures. Keywords: particulate matter, black carbon, bike infrastructure, urban planning, sustainable transportation INTRODUCTION Over the last decade, Bogotá has been recognized for its large bike-dedicated infrastructure. The city is currently endowed with more than 450 km of bike-paths and near 600 thousand trips are made by bicycle, accounting for 6% of the total daily trips (Ríos et al., 2015). These figures make Bogotá the Latin-American city with the largest number of kilometers of bike-lines, almost as the double as Sao Paulo, Ciudad de México, and Santiago de Chile (Baumann et al., 2013). The initial motivation for cycling in Colombian cities was primary related to economic reasons. Many people simply could not afford paying the everyday cost of public transportation. Moreover, there has been a relatively recent initiative for encouraging bicycle usage as a sustainable transport mode to face to the critical urban mobility conditions, while fostering healthier life-styles, and increasing the level of physical activity. Frontiers in Environmental Science 1 November 2016 Volume 4 Article 77 However, most of the bike-paths in Bogotá are located alongside busy roads, where cyclists are experimenting air quality conditions that may not be adequate for performing such physical activity. A question arises as to whether biking under such conditions may overcome the benefits of cycling. This is even more of concern, since Bogotá has been listed among the most polluted cities in Latin America (WHO, 2016). Elevated concentrations of pollutants, especially respirable particulate matter (PM 10 ), represent a constant issue (Franco R, 2012). According to the data from the city s air quality monitoring network, in 2013 the annual PM 10 average concentration in the city ranged between 32 and 81 µg/m 3, in the northern and western regions of the city, respectively (SDA, 2014). In some areas of the city, both WHO reference threshold values (annual 20 µg/m 3 and 24-h 50 µg/m 3 ) and national standards (annual 50 µg/m 3 and24-h 100 µg/m 3 ),areregularlyexceeded. This is a matter of concern, since inhalation of particulate matter has been related to various diseases. Many epidemiological studies have provided evidence of association between the exposure to PM and asthma, bronchitis and chronic obstructive pulmonary disease, as well as cardiovascular diseases (van Berlo et al., 2012). Closeness to highly polluted locations, such as heavy traffic streets, reveals to be a risk factor for respiratory complications in vulnerable population, leading to reduction of pulmonary function(peters et al., 1999; Fritz and Herbarth, 2001; Kim et al., 2004; Calderón-Garcidueñas et al., 2006; Ni et al., 2015). Much like in other Latin-American cities, transportation is one of the most important sources of air pollution in Bogotá(WMO, 2012). According to the city emission inventory, 65% of PM 10 is generated by mobile sources (SDA, 2011), in particular from public transport and freight vehicles using diesel fuel. Although this vehicular category represents 5% of the actual fleet, it emits more than 60% of the PM associated to mobile sources in the city (SDA, 2011). In terms of exposure, mobile sources imply higher negative effects than other sources (i.e., industries), as a consequence of the closer distance between the exhaust pipes and the people in transport-related microenvironments. Inspiteofitsrelevanceforpublichealth,theexposureofbikepaths users to air pollution in Bogotá has so far received limited attention and few researches have been conducted. One previous study (Fajardo and Rojas, 2012), drew as a conclusion the need for a more detailed characterization of the environmental conditions of bikers in the city. The main objective of our work is to measure the levels of fine particulate matter (PM 2.5 ) and black carbon (BC) to which bike-paths users are exposed in Bogotá. In addition, we identified some of the factors that must be considered when designing bike-dedicated infrastructure to minimize users exposure. METHODS Study Area and Selection of the Bike-Paths This study was conducted in the urban area of Bogotá D.C., Colombia s capital and largest city (8 million inhabitants; DNP, 2015).ItislocatedontheAndesmountainrange,at2600m.a.s.l. with a temperate climate, no marked seasonal variation (Cfb, according to the Köppen-Geiger classification), and with an average temperature of 13.5 C and an average rainfall of 866 mm/year. The city urban area and its dwellers are classified in six socio-economical strata (with stratum 1 being the lowest and stratum 6 the highest), with people living in strata 2 and 3 accounting for about 80% of the total population (DAPD, 2007). The economy of Bogotá represents 25% of the GDP of the country, with prominent sectors being those of services, commerce, and manufacturing(luna and Behrentz, 2011). More than 10 million trips occur daily within the city in both motorized and bicycle modes. Public transportation, which includes massive transport (a bus rapid transit system known as Transmilenio), conventional buses and micro-busses, and taxis, accounts for 60% of the daily trips(ccb, 2015). The selected bike-paths are located alongside major streets. We chose bike-paths with distinct configurations (see Table 1 andfigure1).onetypeisabike-pathlocatedatthecenterofthe corridor, in the division between lanes in a two-way street. The othertypeisabike-pathattheright-sideofthestreet.cyclelanes are segregated in both cases. In addition, we considered the street geometry to represent different diffusion conditions. We chose two paths located along narrow streets (average street width less or equal than 30 m) with a consistent canyon configuration along the selected transects, and two paths located on wide streets (average street width 50 m) with variable configuration of flanking buildings. Moreover, we only consider bike-paths located in streets with mixed traffic where both public and private transport modes operate. These types of streets are representative for the bike-paths locations in Bogotá. Taking into account the average length of bike trips in the city (7km according to SDM, 2013), we selected a section of a similar distance on each bike-path to run our experiments. Safety conditions for the field team and logistic factors were also considered in the final selection of the bike-paths. Field Data Collection The field campaign was conducted in 2013 between April and May. For each bike-path we conducted two (or more) experiments during work days and two during weekends(always on Sundays). Each experiment consisted of a data collection along the bike-path, with a specially equipped bike for the simultaneous and real-time measurement of PM 2.5 and BC concentrations. Bike users were asked to bike at their average speed. To measure PM 2.5 concentrations we used a portable photometer DustTrak 8533 (TSI Inc., USA) with a flow rate of 1.5 l/min. The DustTrak uses 90-deg light scattering to quantify the mass concentration of particles in an air stream that passes through an impactor assembly (Yanosky et al., 2002). The instrument was factory calibrated, and zero point and flow rate were verified and/or reset according to the manufacturer s instructions prior to each experiment. Real-time BC concentrations were obtained using a microaethalometer model AE51 (AethLabs Inc., USA). Operating at a flow rate of 100 ml/min, the AE51 performs the analysis by measuring the rate of change in absorption of transmitted light Frontiers in Environmental Science 2 November 2016 Volume 4 Article 77 TABLE 1 Characterization of the selected bike-path sections. Number of Experiments Vehicular Flow (Vehicles/hour) Public Transit Type Average Bike-path Width (m)* Average Street Width (m)* Configuration Street/Path Selection Stretch Stretch Length (Km) Street Name Total Week days Week-ends** Cars Motorcycle Buses and Trucks Regular collective service 6.53 Open with lateral bike-path Between Calle 13 and Calle 80 Avenida Boyacá BRT*** system + collective service 6.19 Open with central bike-path Between Carrera 96 and Carrera 50 Avenida Calle Regular collective service 4.42 Closed with central bike-path Between Calle 146 and Calle 100 Avenida Carrera Regular collective service 4.3 Closed with lateral bike-path Carrera 11 Between Calle 100 and Calle 63 *Includes both ways, for streets to which applies. **In all cases, the weekend day was Sunday. ***Bus rapid transit. (880 nm) due to continuous collection of aerosol deposit on a filter media. On each experiment geographical position was register using a GARMIN 60CSX. All the instruments were set to 1-s time resolution. Dates and times of each experiment are reported in Table2, together with background concentrations of PM 2.5 and meteorological data obtained from the city s air quality monitoring network for the same dates and times of the experiments. We selected a time frame between 6:00 and 9:30 a.m. to do the experiments. According to the hourly distribution of the bike trips in the city (SDM, 2012), the peak of the bike trips corresponds to that period (about 60,000 trips/hour). Data regarding vehicular volume at the corridors was obtained from the transport local authorities. This information is reported in Table 1 and in all cases corresponds to workdays. Field Data Processing Field data was downloaded using the specific software of each measuring instrument. A total of 33,700 observations were obtained.eachofthemconsistedofatuplewithameasuredlevel ofpm 2.5,BC,andtheGPScoordinates. All the observations were submitted to a process of filtering and validation. The filtering consisted in the identification and removal of spurious values, generated by equipment errors. Null and negative values were removed, as well as extreme ones outside of the data trend (e.g., spikes), which were obviously spurious measurements determined by mechanical stresses affecting the data collection devices. The validation process implemented a cross-check of pollutant levels, identifying, and removing all observations for which the PM 2.5 was not greater than that of BC. This validation processes removed 11% of the observations. We computed descriptive statistics of the measured data to identify its variability range, average standard deviation, distribution, and to determine the percentage of observations above the threshold values(who and national regulations). We analyzed pollution levels with their geographical position, to identify differences in exposure levels along the bike-path and analyze possible impacts from crossings, traffic lights, and bus stops on the air quality. A different analysis considered an aggregation of data to compute the average values of PM 2.5 and BC during workdays and weekends. For the estimation of the average measures, we used confidence intervals to determine a measure of the error or uncertainty. As it was not possible to assume that the measurement data was normally distributed, we used empirical bootstrap confidence intervals (Efron and Tibshirani, 1993) at a 95% confidence level. We then used a boxplot visualization (with standard settings, Q1, Q2, and Q3, whiskers at 1.5 times the interquartile range, outliers not plotted) of the measured concentrations of air pollutants to determine possible differences in their distributions across bike-paths and with respect to the day of the measurement (i.e., workday or weekend). For each of the bike-paths, we ran a one-way ANOVA to ascertain the existence of a statistical difference between the Frontiers in Environmental Science 3 November 2016 Volume 4 Article 77 FIGURE 1 Configuration of the streets and bike-paths selected for this study. (A) Open street with lateral bike-path; (B) closed street with lateral bike-path; (C) closed street with central bike-path; (D) open street with central bike-path. TABLE 2 Summary of the field data, pollutant levels and meteorological conditions. Experiment details Air pollutants concentrations (µg/m 3 ) Meteorological data Street Day Date Start End PM 2.5 BC Background Pressure Precipitation Wind Speed Time Time Average (SD) Average (SD) PM 2.5 (mmhg) (mm) (m/s) Avenida Sun 21/04/2013 9:12:49 9:48: (61.1) 28.0 (35.0) Boyacá Wed 24/04/2013 8:20:01 9:04: (89.8) 22.5 (17.2) Thu 25/04/2013 8:23:18 8:52: (143.5) 48.8 (44.0) Sun 28/04/2013 8:32:00 9:06: (65.6) 37.6 (32.24) Calle 26 Sun 21/04/2013 7:50:00 8:25: (19.9) 12.2 (13.9) Wed 24/04/2013 7:11:28 7:45: (44.7) 26.5 (19.2) Thu 25/04/2013 7:27:09 7:54: (40.5) 48.8 (23.0) Sun 28/04/2013 7:24:00 7:54: (15.1) 22.7 (17.6) Carrera 19 Sun 5/05/2013 7:18:42 7:45: (39.8) 11.0 (14.1) Thu 9/05/2013 7:37:08 8:04: (228.9) 22.4 (32.1) Sun 12/05/2013 7:12:16 7:31: (33.2) 8.6 (6.3) Wed 15/05/2013 7:20:17 7:40: (158.1) 13.4 (15.7) Thu 23/05/2013 7:01:11 7:22: (67.8) 11.4 (9.8) Carrera 11 Sun 5/05/2013 7:54:51 8:18: (76.3) 24.1 (28.3) Thu 9/05/2013 8:15:29 8:40: (156.5) 44.3 (65.4) Sun 12/05/2013 7:37:59 7:56: (173.6) 12.6 (12.1) Wed 15/05/2013 7:46:32 8:07: (192.1) 19.6 (21.4) Thu 23/05/2013 7:32:25 7:55: (167.9) 16.3 (14.1) Frontiers in Environmental Science 4 November 2016 Volume 4 Article 77 averagesoftheconcentrationsofpm 2.5 andbcmeasuredduring workdays and weekends. This analysis led us to conduct a more detailed graphical characterization of the distributions of the air contaminants, of their correlation, and of the differences between the amounts measured during workdays and weekends. RESULTS AND DISCUSSION Table3 shows the descriptive statistics for the total number of valid observations of PM 2.5 and BC. For PM 2.5, more than 75% of the measurements are above the 24-h threshold value of 25 µg/m 3 setbywho,withextremevaluesbeyond1000µg/m 3. The measurements of BC concentrations raise similar worries (i.e.,33%ofthemeasurementsarehigherthan25 µg/m 3 ). Figure2 showsthehistogramsforpm 2.5 andbcconsidering all the samples (for both measurements the rightmost part of the distribution was cut for the sake of visualization). Both distributions of values are exhibiting a long tail, as also indicated by the coefficient of variation 1 (see Table 3). Moreover, the distribution of PM 2.5 shows multimodality, which can be attributed to the presence of multiple emitting sources along the bike-paths. Both pollutants show highly dynamical patterns in its concentrations, with many swift peaks. Figure 3 shows a georeferenced display of PM 2.5 concentrations along the four bike-paths (for one specific experiment). Different levels of each pollutant are represented by using a color scale, were the nuances of red are assigned to the highest concentration levels and those of blue to the lowest ones. Bikers are exposed to highly variable pollution levels during their bike ride. For those particular experiments we reported in Figure 3, the highest concentrations were recorded in the proximity to the main road crossing (e.g., along bike-path c), but also close to traffic lights and public transportation bus stops along the street (e.g., along bike-path a). The results of this analysis, as well as the proximity of the bike-paths to the street, indicate that the concentrations of air pollutants to which bikers are exposed are highly influenced by vehicular traffic emissions. Figure 4 presents the average and the 95% confidence interval for PM 2.5 and BC concentrations, classed by workdays and weekends. These charts confirm cyclists are consistently exposed to high concentrations of both pollutants, irrespective of the type ofday.forpm 2.5,theaverageconcentrationiswithin80and136 µg/m 3 for workdays. These levels are three to five times higher thanthosesuggestedbythewho(ifwetakethe24h 25 µg/m 3 as a reference value). During weekends, the concentrations of this pollutantrangedbetween30and72 µg/m 3. The average concentrations of BC were between 16 and 38 µg/m 3 during workdays and in the range of µg/m 3 during weekends. Such air pollution levels are relevant from a TABLE 3 Descriptive statistics. Min Median Mean Max Standard Coeff. % % % % Deviation Variation 25 µg/m 3 50 µg/m 3 100 µg/m 3 200 µg/m 3 PM 2.5 (µg/m 3 ) BC (µg/m 3 ) FIGURE 2 Histograms of PM 2.5 and BC concentrations measured along the bike-paths. Frontiers in Environmental Science 5 November 2016 Volume 4 Article 77 FIGURE 3 Concentrations of PM 2.5 measured during data collection experiments along the four selected bike-paths. FIGURE 4 Average concentrations and 95% confidence intervals for PM 2.5 (µg/m 3 ) and BC (µg/m 3 ) (all the bike-paths, classed by work days and weekends). public health point of view, considering the positive association of the exposure to particle related pollutants with respiratory and cardiovascular problems(calderón-garcidueñas et al., 2003; Kim, 2004; WHO, 2005; Holguin et al., 2007). We compared the results of this study with the measured concentrations to which bike users are exposed to in other cities of the world. The PM 2.5 levels found in Bogotá are up to one order of magnitude higher than those measured in the proximity of streets along bike-paths in cities such as Minneapolis and Berkeley in the United
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