Mobile measurements of black carbon: Comparison of normal traffic with reduced traffic conditions during COVID-19 lock-down.

A mobile monitoring campaign was conducted (by bicycle) to assess the black carbon (BC) concentrations in Cluj-Napoca city, Romania, in 2020, before, during and after COVID-19 lock-down. Over the entire study period, the BC concentrations ranged between 1.0 and 25.9 µg/m³ (averaged per street section and period characterized by different traffic conditions). Marked spatial and temporal differences were observed. Observed differences in BC concentrations between locations are attributed to traffic intensities, with average BC concentrations, under normal circumstances, of 6.6-14.3 µg/m³ at roads with high to intense traffic, compared to 2.8-3.1 µg/m³ at areas with reduced traffic, such as residential areas, parks and pedestrian streets. The COVID-19 measures impacted traffic volumes, and hence average BC concentrations decreased from 5.9 µg/m³ to 3.0 µg/m³ during lock-down and in a lower extent to 3.4 µg/m³ and 4.4 µg/m³ in post-lockdown periods with reduced and more normalized traffic. Two approaches to account for variations in background concentrations when comparing different situations in time are assessed. Subtracting background concentrations that are measured at background sites along the monitoring route is an appropriate method to assess spatio-temporal differences in concentrations. A reduction of about 1-2 µg/m³ was observed for the streets with low to medium traffic, and up to 6 µg/m³ at high traffic locations under lockdown. The approach presented in this study, using mobile measurements, is useful to understand the personal exposure to BC along the roads in different seasons and the influence of traffic reduction on BC pollution during prolonged restrictions. All these will support policymakers to reduce pollution and achieve EU directives targets and WHO recommendations.

Whether cycling around the city is in fact healthy in the light of air quality - Results of black carbon.

Studying the air quality and exposure of the inhabitants of urban agglomerations to pollution is the basis for the creation and development of more sustainable cities. Although research on black carbon (BC) has not yet reached the official acceptable levels and guidelines, the World Health Organization clearly indicates the need to measure and control the level of this pollutant. In Poland, monitoring of the level of BC concentration is not included in the air quality monitoring network. To estimate the extent of this pollutant to which pedestrians and cyclists are exposed, mobile measurements were carried out on over 26 km of bicycle paths in Wroclaw. The obtained results indicate the influence of urban greenery next to the bicycle path (especially if the cyclist is separated from the street lane by hedges or other tall plants) and the 'breathability' (i.e., associated with surrounding infrastructure) of the area on the obtained concentrations; the average concentration of BC in such places ranged from 1.3 to 2.2 µg/m3, whereas a cyclist riding directly on bike paths adjacent to the main roads in the city center is exposed to concentrations in the range of 2.3-14 µg/m3. The results of the measurements, also related to stationary measurements made at a selected point of one of the routes, clearly indicate the importance of the infrastructure surrounding the bicycle paths, their location, and the impact of urban traffic on the obtained BC concentrations. The results presented in our study are based only on short-term-field campaigns preliminary studies. To determine the quantitative impact of the characteristics of the bicycle route on the concentration of pollutants, and thus the exposure of users, the systematized research should cover a greater part of the city and be representative in terms of various hours of the day.

SensEURCity: A multi-city air quality dataset collected for 2020/2021 using open low-cost sensor systems.

Low-cost air quality sensor systems can be deployed at high density, making them a significant candidate of complementary tools for improved air quality assessment. However, they still suffer from poor or unknown data quality. In this paper, we report on a unique dataset including the raw sensor data of quality-controlled sensor networks along with co-located reference data sets. Sensor data are collected using the AirSensEUR sensor system, including sensors to monitor NO, NO2, O3, CO, PM2.5, PM10, PM1, CO2 and meteorological parameters. In total, 85 sensor systems were deployed throughout a year in three European cities (Antwerp, Oslo and Zagreb), resulting in a dataset comprising different meteorological and ambient conditions. The main data collection included two co-location campaigns in different seasons at an Air Quality Monitoring Station (AQMS) in each city and a deployment at various locations in each city (also including locations at other AQMSs). The dataset consists of data files with sensor and reference data, and metadata files with description of locations, deployment dates and description of sensors and reference instruments.

Changed gene expression in brains of mice exposed to traffic in a highway tunnel.

CONTEXT: Air pollution has been suggested to have an impact on the brain. OBJECTIVE: The objective was to assess the expression of inflammation-related genes in the brains of mice that had been exposed for 5 days to a well-characterized traffic-polluted environment, i.e. a highway tunnel. MATERIALS AND METHODS: Twenty C57BL6 mice were randomly allocated to four groups of five animals. Two groups were placed in the tunnel for 5 days (mean PM 2.5, 55.1 µg/m³, mean elemental carbon, EC 13.9 µg/m³) in cages with or without filter, two control groups were housed outside the tunnel. Animals were assessed within 24 hours after the last exposure day. Lung injury and inflammation were assessed by bronchoalveolar lavage (BAL) and histology. Blood leukocytosis and coagulation parameters were determined in peripheral blood. The olfactory bulb and hippocampus were analyzed for changes in expression of inflammatory genes and brain-derived neurotrophic factor (BDNF). RESULTS AND DISCUSSION: Although carbon particles were abundant in alveolar macrophages of exposed mice and absent in non-exposed mice, there was no evidence of pulmonary or systemic inflammation. There was an increased expression of genes involved in inflammatory response (COX2, NOS2, NOS3, and NFE2L2) in the hippocampus of the exposed mice. In the olfactory bulb, a downregulation was found for IL1α, COX2, NFE2L2, IL6, and BDNF. CONCLUSION: Although this short-term exposure to traffic-related pollution did not induce pulmonary or systemic inflammation, the expression of inflammatory genes was affected in different brain areas. The decreased BDNF expression in the olfactory bulb suggests lower brain neurotrophic support in response to traffic-related air pollution.

Personal exposure to equivalent black carbon in children in Milan, Italy: Time-activity patterns and predictors by season.

Air pollution is a global threat to public health, especially when considering susceptible populations, such as children. A better understanding of determinants of exposure could help epidemiologists in refining exposure assessment methods, and policy makers in identifying effective mitigation interventions. Through a participatory approach, 73 and 89 schoolchildren were involved in a two-season personal exposure monitoring campaign of equivalent black carbon (EBC) in Milan, Italy. GPS devices, time-activity diaries and a questionnaire were used to collect personal information. Exposure to EBC was 1.3 ± 1.5 µg/m3 and 3.9 ± 3.3 µg/m3 (mean ± sd) during the warm and the cold season, respectively. The highest peaks of exposure were detected during the home-to-school commute. Children received most of their daily dose at school and home (82%), but the highest dose/time intensity was related to transportation and outdoor environments. Linear mixed-effect models showed that meteorological variables were the most influencing predictors of personal exposure and inhaled dose, especially in the cold season. The total time spent in a car, duration of the home-to-school commute, and smoking habits of parents were important predictors as well. Our findings suggest that seasonality, time-activity and mobility patterns play an important role in explaining exposure patterns. Furthermore, by highlighting the contribution of traffic rush hours, transport-related microenvironments and traffic-related predictors, our study suggests that acting on a local scale could be an effective way of lowering personal exposure to EBC and inhaled dose of children in the city of Milan.

Black Carbon Reduces the Beneficial Effect of Physical Activity on Lung Function.

INTRODUCTION: When physical activity is promoted in urban outdoor settings (e.g., walking and cycling), individuals are also exposed to air pollution. It has been reported that short-term lung function increases as a response to physical activity, but this beneficial effect is hampered when elevated air pollution concentrations are observed. Our study assessed the long-term impact of air pollution on the pulmonary health benefit of physical activity. METHODS: Wearable sensors were used to monitor physical activity levels (SenseWear) and exposure to black carbon (microAeth) of 115 healthy adults during 1 wk in three European cities (Antwerp, Barcelona, London). The experiment was repeated in three different seasons to approximate long-term behavior. Spirometry tests were performed at the beginning and end of each measurement week. All results were averaged on a participant level as a proxy for long-term lung function. Mixed effect regression models were used to analyze the long-term impact of physical activity, black carbon and their interaction on lung function parameters, forced expiratory volume in the first second (FEV1), forced vital capacity (FVC), FEV1/FVC, forced expiratory flow (FEF)25-75, and peak expiratory flow. Interaction plots were used to interpret the significant interaction effects. RESULTS: Negative interaction effects of physical activity and black carbon exposure on FEV1 (P = 0.07), FEV1/FVC (P = 0.03), and FEF25-75 (P = 0.03) were observed. For black carbon concentrations up to approximately 1 µg·m, an additional MET·h·wk resulted in a trend toward lung function increases (FEV1, FEV1/FVC, and FEF25-75 increased 5.6 mL, 0.1% and 14.5 mL·s, respectively). CONCLUSIONS: We found that lung function improved with physical activity at low black carbon levels. This beneficial effect decreased in higher air pollution concentrations. Our results suggest a greater need to reduce air pollution exposures during physical activity.

Short-term effects of physical activity, air pollution and their interaction on the cardiovascular and respiratory system.

Physical activity (PA) in urban environments may lead to increased inhalation of air pollutants. As PA and air pollution (AP) have respectively beneficial and detrimental effects on the cardiorespiratory system, the responses to these exposures can interact. Therefore, we assessed the short-term effects of PA, AP and their interaction on a set of subclinical cardiovascular and respiratory outcomes in a panel of healthy adults: heart rate variability (HRV), retinal vessel diameters, lung function and fractional exhaled nitric oxide (FeNO). One hundred twenty two participants measured their PA level and exposure to black carbon (BC), a marker of AP exposure, with wearable sensors during an unscripted week in three different seasons. The study was part of the PASTA project in three European cities (Antwerp: 41 participants, Barcelona: 41 participants, London: 40 participants). At the end of each measurement week, the health outcomes were evaluated. Responses to PA, BC and their interaction were assessed with mixed effect regression models. Separate models were used to account for a 2-h and 24-h time window. During the 2-h time window, HRV and lung function changed statistically significantly in response to PA (METhours) and logarithmic BC (%change). Changes in HRV marked an increased sympathetic tone with both PA (logarithmic LF/HF: +7%; p < 0.01) and BC (logarithmic HF: -19%; p < 0.05). In addition, PA provoked bronchodilation which was illustrated by a significant increase in lung function (FEV1: +15.63 mL; p < 0.05). While a BC %increase was associated with a significant lung function decrease (PEF: -0.10 mL; p < 0.05), the interaction indicated a potential protective effect of PA (p < 0.05). We did not observe a response of the retinal vessel diameters. Most subclinical outcomes did not change in the 24-h time window (except for a few minor changes in LF/HF, FeNO and PEF). Our results on the separate and combined effects of short-term PA and AP exposure on subclinical markers of the cardiorespiratory system are relevant for public health. We provide insights on the physiological responses of multiple, complementary markers. This may move further research towards elucidating potential pathways to disease and the long-term clinical impact of the observed physiological changes.

A comparison of strategies for estimation of ultrafine particle number concentrations in urban air pollution monitoring networks.

We propose three estimation strategies (local, remote and mixed) for ultrafine particles (UFP) at three sites in an urban air pollution monitoring network. Estimates are obtained through Gaussian process regression based on concentrations of gaseous pollutants (NOx, O3, CO) and UFP. As local strategy, we use local measurements of gaseous pollutants (local covariates) to estimate UFP at the same site. As remote strategy, we use measurements of gaseous pollutants and UFP from two independent sites (remote covariates) to estimate UFP at a third site. As mixed strategy, we use local and remote covariates to estimate UFP. The results suggest: UFP can be estimated with good accuracy based on NOx measurements at the same location; it is possible to estimate UFP at one location based on measurements of NOx or UFP at two remote locations; the addition of remote UFP to local NOx, O3 or CO measurements improves models' performance.

Blood Pressure and Same-Day Exposure to Air Pollution at School: Associations with Nano-Sized to Coarse PM in Children.

BACKGROUND: Ultrafine particles (UFP) may contribute to the cardiovascular effects of particulate air pollution, partly because of their relatively efficient alveolar deposition. OBJECTIVE: In this study, we assessed associations between blood pressure and short-term exposure to air pollution in a population of schoolchildren. METHODS: In 130 children (6-12 years of age), blood pressure was determined during two periods (spring and fall 2011). We used mixed models to study the association between blood pressure and ambient concentrations of particulate matter and ultrafine particles measured in the schools' playground. RESULTS: Independent of sex, age, height, and weight of the child, parental education, neighborhood socioeconomic status, fish consumption, heart rate, school, day of the week, season, wind speed, relative humidity, and temperature on the morning of examination, an interquartile range (860 particles/cm3) increase in nano-sized UFP fraction (20-30 nm) was associated with a 6.35 mmHg (95% CI: 1.56, 11.14; p = 0.01) increase in systolic blood pressure. For the total UFP fraction, systolic blood pressure was 0.79 mmHg (95% CI: 0.07, 1.51; p = 0.03) higher, but no effects on systolic blood pressure were found for the nano-sized fractions with a diameter > 100 nm, nor PM2.5, PMcoarse, and PM10. Diastolic blood pressure was not associated with any of the studied particulate mass fractions. CONCLUSION: Children attending school on days with higher UFP concentrations (diameter < 100 nm) had higher systolic blood pressure. The association was dependent on UFP size, and there was no association with the PM2.5 mass concentration.

Implementation and validation of a modeling framework to assess personal exposure to black carbon.

Because people tend to move from one place to another during the day, their exposure to air pollution will be determined by the concentration at each location combined with the exposure encountered in transport. In order to estimate the exposure of individuals in a population more accurately, the activity-based modeling framework for Black Carbon exposure assessment, AB(2)C, was developed. An activity-based traffic model was applied to model the whereabouts of individual agents. Exposure to black carbon (BC) in different microenvironments is assessed with a land use regression model, combined with a fixed indoor/outdoor factor for exposure in indoor environments. To estimate exposure in transport, a separate model was used taking into account transport mode, timing of the trip and degree of urbanization. The modeling framework is validated using weeklong time-activity diaries and BC exposure as revealed from a personal monitoring campaign with 62 participants. For each participant in the monitoring campaign, a synthetic population of 100 model-agents per day was made up with all agents meeting similar preconditions as each real-life agent. When these model-agents pass through every stage of the modeling framework, it results in a distribution of potential exposures for each individual. The AB(2)C model estimates average personal exposure slightly more accurately compared to ambient concentrations as predicted for the home subzone; however the added value of a dynamic model lies in the potential for detecting short term peak exposures rather than modeling average exposures. The latter may bring new opportunities to epidemiologists: studying the effect of frequently repeated but short exposure peaks on long term exposure and health.

Land use regression models as a tool for short, medium and long term exposure to traffic related air pollution.

BACKGROUND AND AIMS: In the HEAPS (Health Effects of Air Pollution in Antwerp Schools) study the importance of traffic-related air pollution on the school and home location on children's health was assessed. 130 children (aged 6 to 12) from two schools participated in a biomonitoring study measuring oxidative stress, inflammation and cardiovascular markers. METHODS: Personal exposure of schoolchildren to black carbon (BC) and nitrogen dioxide (NO2) was assessed using both measured and modeled concentrations. Air quality measurements were done in two seasons at approximately 50 locations, including the schools. The land use regression technique was applied to model concentrations at the children's home address and at the schools. RESULTS: In this paper the results of the exposure analysis are given. Concentrations measured at school 2h before the medical examination were used for assessing health effects of short term exposure. Over two seasons, this short term BC exposure ranged from 514 ng/m(3) to 6285 ng/m(3), and for NO2 from 11 µg/m(3) to 36 µg/m(3). An integrated exposure was determined until 10 days before the child's examination, taking into account exposures at home and at school and the time spent in each of these microenvironments. Land use regression estimates were therefore recalculated into daily concentrations by using the temporal trend observed at a fixed monitor of the official air quality network. Concentrations at the children's homes were modeled to estimate long term exposure (from 1457 ng/m(3) to 3874 ng/m(3) for BC; and from 19 µg/m(3) to 51 µg/m(3) for NO2). CONCLUSIONS: The land use regression technique proved to be a fast and accurate means for estimating long term and daily BC and NO2 exposure for children living in the Antwerp area. The spatial and temporal resolution was tailored to the needs of the epidemiologists involved in this study.

Airway oxidative stress and inflammation markers in exhaled breath from children are linked with exposure to black carbon.

BACKGROUND: The current study aimed at assessing the associations between black carbon (BC) exposure and markers for airway inflammation and oxidative stress in primary school children in a Western European urban area. METHODS: In 130 children aged 6-12 years old, the fraction of exhaled nitric oxide (FeNO), exhaled breath condensate (EBC) pH, 8-isoprostane and interleukin (IL)-1ß were measured in two seasons. BC concentrations on the sampling day (2-h average, 8:00-10:00 AM) and on the day before (24-h average) were assessed using measurements at a central monitoring site. Land use regression (LUR) models were applied to estimate weekly average BC exposure integrated for the time spent at home and at school, and seasonal average BC exposure at the home address. Associations between exposure and biomarkers were tested using linear mixed effect regression models. Next to single exposure models, models combining different BC exposure metrics were used. RESULTS: In single exposure models, an interquartile range (IQR) increase in 2-h BC (3.10 µg/m(3)) was linked with a 5.9% (95% CI: 0.1 to 12.0%) increase in 8-isoprostane. FeNO increased by 16.7% (95% CI: 2.2 to 33.2%) per IQR increase in 24-h average BC (4.50 µg/m(3)) and by 12.1% (95% CI: 2.5 to 22.8%) per IQR increase in weekly BC (1.73 µg/m(3)). IL-1ß was associated with weekly and seasonal (IQR=1.70 µg/m(3)) BC with respective changes of 38.4% (95% CI: 9.0 to 75.4%) and 61.8% (95% CI: 3.5 to 153.9%) per IQR increase in BC. An IQR increase in weekly BC was linked with a lowering in EBC pH of 0.05 (95% CI: -0.10 to -0.01). All associations were observed independent of sex, age, allergy status, parental education level and meteorological conditions on the sampling day. Most of the associations remained when different BC exposure metrics were combined in multiple exposure models, after additional correction for sampling period or after exclusion of children with airway allergies. In additional analyses, FeNO was linked with 24-h PM10 levels, but the effect size was smaller than for BC. 8-Isoprostane was not linked with either 2-h or 24-h concentrations of PM2.5 or PM10. CONCLUSION: BC exposure on the morning of sampling was associated with airway oxidative stress while 24-h and weekly exposures were linked with airway inflammation.

Methodology for setup and data processing of mobile air quality measurements to assess the spatial variability of concentrations in urban environments.

A case study is presented to illustrate a methodology for mobile monitoring in urban environments. A dataset of UFP, PM2.5 and BC concentrations was collected. We showed that repeated mobile measurements could give insight in spatial variability of pollutants at different micro-environments in a city. Streets of contrasting traffic intensity showed increased concentrations by a factor 2-3 for UFP and BC and by <10% for PM2.5. The first quartile (P25) of the mobile measurements at an urban background zone seems to be good estimate of the urban background concentration. The local component of the pollutant concentrations was determined by background correction. The use of background correction reduced the number of runs needed to obtain representative results. The results presented, are a first attempt to establish a methodology for setup and data processing of mobile air quality measurements to assess the spatial variability of concentrations in urban environments.

Street characteristics and traffic factors determining road users' exposure to black carbon.

Many studies nowadays make the effort of determining personal exposure rather than estimating exposure at the residential address only. While intra-urban air pollution can be modeled quite easily using interpolation methods, estimating exposure in transport is more challenging. The aim of this study is to investigate which factors determine black carbon (BC) concentrations in transport microenvironments. Therefore personal exposure measurements are carried out using portable aethalometers, trip diaries and GPS devices. More than 1500 trips, both by active modes and by motorized transport, are evaluated in Flanders, Belgium. GPS coordinates are assigned to road segments to allow BC concentrations to be linked with trip and road characteristics (trip duration, degree of urbanization, road type, traffic intensity, travel speed and road speed). Average BC concentrations on highways (10.7µg/m(3)) are comparable to concentrations on urban roads (9.6µg/m(3)), but levels are significantly higher than concentrations on rural roads (6.1µg/m(3)). Highways yield higher BC exposures for motorists compared to exposure on major roads and local roads. Overall BC concentrations are elevated at lower speeds (<30km/h) and at speeds above 80km/h, in accordance to vehicle emission functions. Driving on roads with low traffic intensities resulted in lower exposures than driving on roads with higher traffic intensities (from 5.6µg/m(3) for roads with less than 500veh/h, up to 12µg/m(3) for roads with over 2500veh/h). Traffic intensity proved to be the major explanatory variable for in-vehicle BC exposure, together with timing of the trip and urbanization. For cyclists and pedestrians the range in BC exposure is smaller and models are less predictive; for active modes exposure seems to be influenced by timing and degree of urbanization only.

Wintertime spatio-temporal variation of ultrafine particles in a Belgian city.

Simultaneous measurements of ultrafine particles (UFPs) were carried out at four sampling locations situated within a 1 km(2) grid area in a Belgian city, Borgerhout (Antwerp). All sampling sites had different orientation and height of buildings and dissimilar levels of anthropogenic activities (mainly traffic volume). The aims were to investigate: (i) the spatio-temporal variation of UFP within the area, (ii) the effect of wind direction with respect to the volume of traffic on UFP levels, and (iii) the spatial representativeness of the official monitoring station situated in the study area. All sampling sites followed similar diurnal patterns of UFP variation, but effects of local traffic emissions were evident. Wind direction also had a profound influence on UFP concentrations at certain sites. The results indicated a clear influence of local weather conditions and the more dominant effect of traffic volumes. Our analysis indicated that the regional air quality monitoring station represented the other sampling sites in the study area reasonably well; temporal patterns were found to be comparable though the absolute average concentrations showed differences of up to 35%.