Telematics data for geospatial and temporal mapping of urban mobility: New insights into travel characteristics and vehicle specific power

This paper describes a new approach for understanding urban mobility called geospatial and temporal (GeoST) mapping, which translates telematics (location) data into travel characteristics. The approach provides the speed-acceleration profile of transport flow at high spatial and temporal resolution. The speed-acceleration profiles can be converted to vehicle-specific power (VSP), which can be used to estimate vehicle emissions. The underlying data used in the model is retrieved from a large telematics dataset, which was collected from GPS-connected vehicles during their journeys over the UK's West Midlands region road network for the years 2016 and 2018. Single journey telematics data were geospatially aggregated and then distributed over GeoST-segments. In total, approximately 354,000 GeoST-segments, covering over 17,700 km of roads over 35 timeslots are parameterized. GeoST mapping of the average vehicle speed (traffic flow), and VSP over different road types are analysed. The role of road slope upon VSP is estimated for every GeoST-segment through knowledge of the elevation of the start and end points of the segments. Previously, road slope and its effect upon VSP have been typically ignored in transport and urban planning studies. A series of case studies are presented that highlight the power of the new approach over differing spatial and temporal scales. For example, results show that the total vehicle fleet moved faster by an average of 3% in 2016 compared to 2018. The studied roads at weekends are shown to be less safe, compared to weekdays, because of lower adherence to speed limits. By including road slope in VSP calculations, the annually averaged VSP results differ by +12.6%, +14.3%, and + 12.7% for motorways, primary roads, and secondary roads, respectively, when compared to calculations that ignore road slope

Mapping urban mobility using vehicle telematics to understand driving behaviour

Telematics data, primarily collected from on-board vehicle devices (OBDs), has been utilised in this study to generate a thorough understanding of driving behaviour. The urban case study area is the large metropolitan region of the West Midlands, UK, but the approach is generalizable and translatable to other global urban regions. The new approach of GeoSpatial and Temporal Mapping of Urban Mobility (GeoSTMUM) is used to convert telematics data into driving metrics, including the relative time the vehicle fleet spends idling, cruising, accelerating, and decelerating. The telematics data is also used to parameterize driving volatility and aggressiveness, which are key factors within road safety, which is a global issue. Two approaches to defining aggressive driving are applied and assessed, they are vehicle jerk (the second derivative of vehicle speed), and the profile of speed versus acceleration/deceleration. The telematics-based approach has a very high spatial resolution (15–150 m) and temporal resolution (2 h), which can be used to develop more accurate driving cycles. The approach allows for the determination of road segments with the highest potential for aggressive driving and highlights where additional safety measures could beneficially be adopted. Results highlight the strong correlation between vehicle road occupancy and aggressive driving

Air pollution and economic growth in Dubai a fast-growing Middle Eastern city

This paper discusses the impact of rapid economic development on air quality in the Emirate of Dubai, United Arab Emirates (UAE). Dubai is one of the fastest-growing cities in the world, with a population increase of approximately 80× over the last 60 years. The concentrations of five criteria air pollutants (CAPs) including carbon monoxide (CO), nitrogen dioxide (NO2), particulate matter with diameter less than 10 μm (PM10), ozone (O3) and sulphur dioxide (SO2) were studied from 2013 to 2021 at 14 regulatory monitoring stations. Results show that the biggest improvements in air pollution are for the primary air pollutants NO2 and SO2, with reductions of 54% and 93% respectively over the period studied. Gross domestic product (GDP), population growth and energy consumption are significantly and negatively correlated with NO2 and SO2 and strongly and positively correlated with PM10. CO is positively correlated with the number of buildings completed, while the results for O3 are inconclusive. Trends in NO2 and SO2 indicate that these two pollutants are decoupled from economic development, supporting, with caution, the Environmental Kuznets Curve hypothesis on the relationship between economic growth and environmental degradation. The improvement in the city's air quality is due to the effective implementation of local environmental policies, unaffected by large-scale development and urbanization. The monthly assessments of Dubai's air pollution for 2019 and 2020 show a 3–16% COVID-related improvement in the levels of the studied air pollutants, except for ozone, which increased by an average of 8%

Emissions of ultrafine particles from civil aircraft:dependence upon aircraft type and passenger load

Very high concentrations of ultrafine particles (UFP) were measured at Heathrow Airport London. Exposure to UFP is strongly linked to adverse health effects and guidance for exposure limits has recently been provided by the World Health Organization (WHO). Using 1 s resolution UFP measurements and aircraft GPS data, measurements were assigned to individual aircraft and their operating mode, and this information was used to model UFP emission rates. In all cases, the highest emission rates were associated with departing aircraft, with rates for larger aircraft higher than smaller aircraft. Emission rates per passenger is influenced by the number of passengers carried, especially for arriving aircraft. Calculated emission rates are significantly higher than stated literature values, due to the inclusion of condensable particles in the measurements. These condensable particles are specifically not included in the regulated emission rates. Measured UFP concentrations within the airport boundary (and therefore not accessible to the general public) exceed the WHO guidance, indicating that UFP concentrations outside of the airport boundary could also be of concern. Assessing population exposure close to airports will be of increasing importance in future

Airborne particulate matter monitoring in Kenya using calibrated low-cost sensors [final revised article]

East African countries face an increasing threat from poor air quality stemming from rapid urbanization, population growth, and a steep rise in fuel use and motorization rates. With few air quality monitoring systems available, this study provides much needed high temporal resolution data to investigate the concentrations of particulate matter (PM) air pollution in Kenya. Calibrated low-cost optical particle counters (OPCs) were deployed in Kenya in three locations: two in the capital Nairobi and one in a rural location in the outskirts of Nanyuki, which is upwind of Nairobi. The two Nairobi sites consist of an urban background site and a roadside site. The instruments were composed of an AlphaSense OPC-N2 ran with a Raspberry Pi low-cost microcomputer, packaged in a weather-proof box. Measurements were conducted over a 2-month period (February–March 2017) with an intensive study period when all measurements were active at all sites lasting 2 weeks. When collocated, the three OPCN2 instruments demonstrated good inter-instrument precision with a coefficient of variance of 8.8 ± 2.0 % in the fine particle fraction (PM2.5). The low-cost sensors had an absolute PM mass concentration calibration using a collocated gravimetric measurement at the urban background site in Nairobi. The mean daily PM1 mass concentration measured at the urban roadside, urban background and rural background sites were 23.9, 16.1 and 8.8 µg m−3 , respectively. The mean daily PM2.5 mass concentration measured at the urban roadside, urban background and rural background sites were 36.6, 24.8 and 13.0 µg m−3, respectively. The mean daily PM10 mass concentration measured at the urban roadside, urban background and rural background sites were 93.7, 53.0 and 19.5 µg m−3, respectively. The urban measurements in Nairobi showed that PM concentrations regularly exceed WHO guidelines in both the PM10 and PM2.5 size ranges. Following a “Lenschow”-type approach we can estimate the urban and roadside increments that are applicable to Nairobi (Lenschow et al., 2001). The median urban increment is 33.1 µg m−3 and the median roadside increment is 43.3 µg m−3 for PM2.5. For PM1, the median urban increment is 4.7 µg m−3 and the median roadside increment is 12.6 µg m−3. These increments highlight the importance of both the urban and roadside increments to urban air pollution in Nairobi. A clear diurnal behaviour in PM mass concentration was observed at both urban sites, which peaks during the morning and evening Nairobi rush hours; this was consistent with the high roadside increment indicating that vehicular traffic is a dominant source of PM in the city, accounting for approximately 48.1 %, 47.5 % and 57.2 % of the total PM loading in the PM10, PM2.5 and PM1 size ranges, respectively. Collocated meteorological measurements at the urban sites were collected, allowing for an understanding of the location of major sources of particulate matter at the two sites. The potential problems of using low-cost sensors for PM measurement without gravimetric calibration available at all sites are discussed. This study shows that calibrated low-cost sensors can be successfully used to measure air pollution in cities like Nairobi. It demonstrates that low-cost sensors could be used to create an affordable and reliable network to monitor air quality in cities

Airborne particulate matter monitoring in Kenya using calibrated low cost sensors [discussion paper]

East African countries face an increasing threat from poor air quality, stemming from rapid urbanisation, population growth and a steep rise in fuel use and motorization rates. With few air quality monitoring systems available, this study provides the much needed high temporal resolution data to investigate the concentrations of particulate matter (PM) air pollution in Kenya. Calibrated low cost optical particle counters (OPCs) were deployed in Kenya in three locations: two in the capital of Nairobi and one in a rural location in the outskirts of Nanyuki, which is upwind of Nairobi. The two Nairobi sites consist of an urban background site and a roadside site. The instruments were composed of an Alphasense OPC-N2 optical particle counter (OPC) ran with a raspberry pi low cost microcomputer, packaged in a weather proof box. Measurements were conducted over a two-month period (February–March 2017) with an intensive study period when all measurements were active at all sites lasting two weeks. When collocated, the three OPC-N2 instruments demonstrated good inter-instrument precision with a coefficient of variance of 8.8±2.0% in the PM2.5 fraction. The low cost sensors had an absolute PM mass concentration calibration using a collocated gravimetric measurement at the urban background site in Nairobi. The mean daily PM1 mass concentration measured at the urban roadside, urban background and rural background sites were 23.9, 16.1, 8.8µgm−3. The mean daily PM2.5 mass concentration measured at the urban roadside, urban background and rural background sites were 36.6, 24.8, 13.0µgm−3. The mean daily PM10 mass concentration measured at the urban roadside, urban background and rural background sites were 93.7, 53.0, 19.5µgm−3. The urban measurements in Nairobi showed that particulate matter concentrations regularly exceed WHO guidelines in both the PM10 and PM2.5 size ranges. Following a Lenschow type approach we can estimate the urban and roadside increments that are applicable to Nairobi. Median urban and roadside increments are 33.1 and 43.3µgm−3 for PM10, respectively, the median urban and roadside increments are 7.1 and 18.3µgm−3 for PM2.5, respectively, and the median urban and roadside increments are 4.7 and 12.6µgm−3 for PM1, respectively. These increments highlight the importance of both the urban and roadside increments to urban air pollution in Nairobi. A clear diurnal behaviour in PM mass concentration was observed at both urban sites, which peaks during the morning and evening Nairobi rush hours; this was consistent with the high measured roadside increment indicating vehicular traffic being a dominant source of particulate matter in the city, accounting for approximately 48.1, 47.5, and 57.2% of the total particulate matter loading in the PM10, PM2.5 and PM1 size ranges, respectively. Collocated meteorological measurements at the urban sites were collected, allowing for an understanding of the location of major sources of particulate matter at the two sites. The potential problems of using low cost sensors for PM measurement without gravimetric calibration available at all sites are discussed. This study shows that calibrated low cost sensors can be used successfully to measure air pollution in cities like Nairobi. It demonstrates that low cost sensors could be used to create an affordable and reliable network to monitor air quality in cities

1064 nm Dispersive Raman Microspectroscopy and Optical Trapping of Pharmaceutical Aerosols.

Raman spectroscopy is a powerful tool for investigating chemical composition. Coupling Raman spectroscopy with optical microscopy (Raman microspectroscopy) and optical trapping (Raman tweezers) allows microscopic length scales and, hence, femtolitre volumes to be probed. Raman microspectroscopy typically uses UV/visible excitation lasers, but many samples, including organic molecules and complex tissue samples, fluoresce strongly at these wavelengths. Here we report the development and application of dispersive Raman microspectroscopy designed around a near-infrared continuous wave 1064 nm excitation light source. We analyze microparticles (1-5 μm diameter) composed of polystyrene latex and from three real-world pressurized metered dose inhalers (pMDIs) used in the treatment of asthma: salmeterol xinafoate (Serevent), salbutamol sulfate (Salamol), and ciclesonide (Alvesco). For the first time, single particles are captured, optically levitated, and analyzed using the same 1064 nm laser, which permits a convenient nondestructive chemical analysis of the true aerosol phase. We show that particles exhibiting overwhelming fluorescence using a visible laser (514.5 nm) can be successfully analyzed with 1064 nm excitation, irrespective of sample composition and irradiation time. Spectra are acquired rapidly (1-5 min) with a wavelength resolution of 2 nm over a wide wavenumber range (500-3100 cm-1). This is despite the microscopic sample size and low Raman scattering efficiency at 1064 nm. Spectra of individual pMDI particles compare well to bulk samples, and the Serevent pMDI delivers the thermodynamically preferred crystal form of salmeterol xinafoate. 1064 nm dispersive Raman microspectroscopy is a promising technique that could see diverse applications for samples where fluorescence-free characterization is required with high spatial resolution