A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> China implemented systematic air pollution con- trol measures during the 2008 Beijing Summer Olympics and Paralympics to improve air quality. This study used a versatile mobile laboratory to conduct in situ monitoring of on-road air pollutants along Beijing's Fourth Ring Road on 31 selected days before, during, and after the Olympics air pollution control period. A suite of instruments with re- sponse times of less than 30 s was used to measure tempo- ral and spatial variations in traffic-related air pollutants, in- cluding NOx, CO, PM1.0 surface area (S(PM1)), black car- bon (BC), and benzene, toluene, the sum of ethylbenzene, and m-, p-, and o-xylene (BTEX). During the Olympics (8- 23 August, 2008), on-road air pollutant concentrations de- creased significantly, by up to 54% for CO, 41% for NO x, 70% for SO2, 66% for BTEX, 12% for BC, and 18% for SPM1 , compared with the pre-control period (before 20 July). Concentrations increased again after the control period ended (after 20 September), with average increases of 33% for CO, 42% for NOx, 60% for SO2, 40% for BTEX, 26% for BC, and 37% for S(PM1), relative to the control period. Variations in pollutants concentrations were correlated with changes in traffic speed and the number and types of vehi- cles on the road. Throughout the measurement periods, the concentrations of NOx, CO, and BTEX varied markedly with the numbers of light- and medium-duty vehicles (LDVs and MDVs, respectively) on the road. Only after 8 August was a noticeable relationship found between BC and S(PM1) and the number of heavy-duty vehicles (HDVs). Additionally, BC and S(PM1) showed a strong correlation with SO2 before the Olympics, indicating possible industrial sources from lo- cal emissions as well as regional transport activities in the Beijing area. Such factors were identified in measurements conducted on 6 August in an area southwest of Beijing. The ratio of benzene to toluene, a good indicator of traffic emis- sions, shifted suddenly from about 0.26 before the Olympics to approximately 0.48 after the Olympics began. This find- ing suggests that regulations on traffic volume and restric- tions on the use of painting solvents were effective after the Olympics began. This study demonstrated the effectiveness of air pollution control measures and identified local and re- gional pollution sources within and surrounding the city of Beijing. The findings will be invaluable for emission inven- tory evaluations and model verifications. <s> BIB001 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> BackgroundThe relationship between traffic emissions and mobile-source air pollutant concentrations is highly variable over space and time and therefore difficult to model accurately, especially in... <s> BIB002 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> This research assessed the comparative risk associated with exposure to traffic pollution when travelling via different transport modes in Christchurch, New Zealand. Concentrations of PM1, UFPs and CO were monitored on pre-defined routes during the morning and evening commute on people travelling concurrently by car, bus and bicycle. It was found that car drivers were consistently exposed to the highest levels of CO; on-road cyclists were exposed to higher levels of all pollutants than off-road cyclists; car and bus occupants were exposed to higher average levels of UFP than cyclists, and travellers were occasionally exposed to very high levels of pollution for short periods of time. PM10 and PM2.5 were found to be poor indicators of exposure to traffic pollution. Studying Christchurch adds to our understanding as it was a lower density city with limited traffic congestion compared most other cities previously studied. <s> BIB003 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Cyclists are exposed to traffic-related air pollution (TRAP) during their commutes due to their proximity to vehicular traffic. Two of the main components of TRAP are black carbon (BC) and nitrogen dioxide (NO2), which have both been causally associated with increased mortality. To assess the impact of cyclists' exposure to TRAP, a battery-powered mobile monitoring station was designed to sample air pollutants along five bike routes in Boston, Massachusetts. The bike routes were categorized into three types: bike paths, which are separated from vehicle traffic; bike lanes, which are adjacent to traffic; and designated bike lanes, which are shared traffic lanes for buses and cyclists. Bike lanes were found to have significantly higher concentrations of BC and NO2 than bike paths in both adjusted and unadjusted generalized linear models. Higher concentrations were observed in designated bike lanes than bike paths; however, this association was only significant for NO2. After adjusting for traffic density, background concentration, and proximity to intersections, bike lanes were found to have concentrations of BC and NO2 that were approximately 33% higher than bike paths. Distance from the road, vegetation barriers, and reduced intersection density appear to influence these variations. These findings suggest that cyclists can reduce their exposure to TRAP during their commute by using bike paths preferentially over bike lanes regardless of the potential increase of traffic near these routes. <s> BIB004 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Cycling in British cities is increasing but at a slow rate nationally. The ultimate realizations of cycling benefits in urban areas, such as cities in North East England, are hampered by lack of appropriate data to aid in our understanding of cycling behaviors to inform policy strategies and improve cycling uptake as well as data processing methodologies. Several efforts are being made to enhance data availability to understand cycling behaviors to inform policy strategies for which this research aims to contribute by providing evidence on the use of the area’s cycling infrastructure by utility cyclists. A proposed corridor space analytical approach was used to analyze the newly collected 7-day GPS data from 79 utility cyclists to estimate the extent to which respondents used the area’s cycling infrastructure. The data was used together with the area cycling infrastructure data from Newcastle City Council. Findings from the corridor space analysis suggest that 57.4 % of cyclists from sample prefer cycling on the cycle network, while 33.8 % cycle outside the cycle network with 8.8 % near the cycle network. Also, for all cycle trips, men tend to dominate in cycling on and near the cycle network. Both the males and females tend to use the cycle network more than off the network for utility trips. With 42.6 % of cyclists still cycling outside the designated cycle network, it is imperative that policy initiatives are aimed towards investing in cycling research and infrastructure to further deepen our understanding to encourage cycling around the study area. It was also suggested that the captured detailed actual route choice preferences could serve as input to the development of agent-based models towards understanding cycling behaviors around the study area. <s> BIB005 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Up-to-date information on urban air pollution is of great importance for health protection agencies to assess air quality and provide advice to the general public in a timely manner. In particular, ultrafine particles (UFPs) are widely spread in urban environments and may have a severe impact on human health. However, the lack of knowledge about the spatio-temporal distribution of UFPs hampers profound evaluation of these effects. In this paper, we analyze one of the largest spatially resolved UFP data set publicly available today containing over 25 million measurements. We collected the measurements throughout more than a year using mobile sensor nodes installed on top of public transport vehicles in the city of Zurich, Switzerland. Based on these data, we develop land-use regression models to create pollution maps with a high spatial resolution of 100m × 100 m. We compare the accuracy of the derived models across various time scales and observe a rapid drop in accuracy for maps with subweekly temporal resolution. To address this problem, we propose a novel modeling approach that incorporates past measurements annotated with metadata into the modeling process. In this way, we achieve a 26% reduction in the root-mean-square error—a standard metric to evaluate the accuracy of air quality models—of pollution maps with semi-daily temporal resolution. We believe that our findings can help epidemiologists to better understand the adverse health effects related to UFPs and serve as a stepping stone towards detailed real-time pollution assessment. <s> BIB006 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Ever growing populations in cities are associated with a major increase in road vehicles and air pollution. The overall high levels of urban air pollution have been shown to be of a significant risk to city dwellers. However, the impacts of very high but temporally and spatially restricted pollution, and thus exposure, are still poorly understood. Conventional approaches to air quality monitoring are based on networks of static and sparse measurement stations. However, these are prohibitively expensive to capture tempo-spatial heterogeneity and identify pollution hotspots, which is required for the development of robust real-time strategies for exposure control. Current progress in developing low-cost micro-scale sensing technology is radically changing the conventional approach to allow real-time information in a capillary form. But the question remains whether there is value in the less accurate data they generate. This article illustrates the drivers behind current rises in the use of low-cost sensors for air pollution management in cities, whilst addressing the major challenges for their effective implementation. <s> BIB007 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Expanding urban cycling networks requires consideration of a number of important factors. Yet there exists no set of best practices and surprisingly little research detailing which sorts of cycling infrastructure may be better or worse in terms of exposure to harmful pollutants. A large air-quality data collection campaign was conducted in summer 2012 whereby cyclists equipped with ultrafine particle (UFP) and black carbon (BC) monitors covered over 550 kilometers of streets, including 325 kilometers of designated cycling facilities on the Island of Montreal. The clearest result from this exercise is that pollution levels on trails, often far from vehicular streets, are markedly lower than cycling facilities located on or alongside the street. For in-street and separated facilities, both UFP and BC were more closely associated with the hierarchy of the street than the type of cycling facility. Between in-street and separated facilities, the difference in UFP levels was not statistically significant. However, the difference between BC levels on in-street and separated facilities was significant, with separated facilities yielding lower concentrations. Ultimately, more research is needed to understand the potential efficacy of facility and network design as a pollution exposure abatement measure; however, these findings show moderate advantages of separated facilities over in-street facilities and more substantial advantages for off-road facilities over either. <s> BIB008 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Few studies have quantified relationships between bicyclist exposure to air pollution and roadway and traffic variables. As a result, transportation professionals are unable to easily estimate exposure differences among bicycle routes for network planning, design, and analysis. This paper estimates the effects of roadway and travel characteristics on bicyclist exposure concentrations, controlling for meteorology and background conditions. Concentrations of volatile organic compounds (VOC) and carbon monoxide (CO) are modeled using high-resolution data collected on-road. Results indicate that average daily traffic (ADT) provides a parsimonious way to characterize the impact of roadway characteristics on bicyclists’ exposure. VOC and CO exposure increase by approximately 2% per 1000 ADT, robust to different regression model specifications. Exposure on off-street facilities is higher than at a park, but lower than on-street riding – with the exception of a path through an industrial corridor with significantly higher exposure. VOC exposure is 20% higher near intersections. Traffic, roadway, and travel variables have more explanatory power in the VOC models than the CO model. The quantifications in this paper enable calculation of expected exposure differences among travel paths for planning and routing applications. The findings also have policy and design implications to reduce bicyclists’ exposure. Separation between bicyclists and motor vehicle traffic is a necessary but not sufficient condition to reduce exposure concentrations; off-street paths are not always low-exposure facilities. <s> BIB009 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> We introduce Mosaic, a mobile sensor network system for city scale sensing. Currently, we focus on accurate PM2.5 measurements. We design and implement low-cost smart sensors for this purpose. Those sensors are specifically designed for moving vehicles such as buses and taxies. The mobile sensing capability of our system enables a wide coverage of a city with a modest number of sensors. We incorporate a three-layer architecture in Mosaic. Mosaic faces many practical challenges which need to be properly addressed, e.g., reliable node hardware and software design, and accurate PM2.5 measurements. We have built three versions of Mosaic nodes. We present a novel data calibration approach combining traditional Artificial Neural Network (ANN) and Support Vector Machines (SVMs). We launch real-world deployments of Mosaic in two main cities in China -- Hangzhou and Ningbo. Our initial efforts show that Mosaic is a feasible approach for city scale sensing and our system can produce highly accurate PM2.5 measurements. <s> BIB010 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> For protecting the public health, many research groups have tried to capture dense air quality information using sensorized vehicles that travel within urban areas. However, it remains difficult to accumulate real-time and fine-grained air quality information to fulfill a wide variety of requests from citizens and authorities. In this paper, we propose on-demand urban air quality monitoring using public vehicles. By adapting the monitoring behavior of sensors to each city's individual's needs, smart cities can accumulate enough air quality information with just a few sensorized vehicles. This paper describes the mechanisms of remote update programs on sensor nodes mounted on public vehicles for on-demand monitoring. We adopted the mechanisms on sensorized public vehicles in Fujisawa City, Japan. The paper also reports our air quality monitoring field trial and describes a functional design for on-demand air quality monitoring. <s> BIB011 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> Air quality monitoring has attracted a lot of attention from governments, academia and industry, especially for PM2.5 due to its significant impact on our respiratory systems. In this paper, we present the design, implementation, and evaluation of Mosaic, a low cost urban PM2.5 monitoring system based on mobile sensing. In Mosaic, a small number of air quality monitoring nodes are deployed on city buses to measure air quality. Current low-cost particle sensors based on light-scattering, however, are vulnerable to airflow disturbance on moving vehicles. In order to address this problem, we build our air quality monitoring nodes, Mosaic-Nodes, with a novel constructive airflow-disturbance design based on a carefully tuned airflow structure and a GPS-assisted filtering method. Further, the buses used for system deployment are selected by a novel algorithm which achieves both high coverage and low computation overhead. The collected sensor data is also used to calculate the PM2.5 of locations without direct measurements by an existing inference model. We apply the Mosaic system in a testing urban area which includes more than 70 point-of-interests. Results show that the Mosaic system can accurately obtain the urban air quality with high coverage and low cost. <s> BIB012 </s> A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods <s> Monitoring Data Acquisition <s> This paper reports a readout circuit for a resistive CO2 sensor, which operates by measuring the CO2-dependent thermal conductivity of air. A suspended hot-wire transducer, which acts both as a resistive heater and temperature sensor, exhibits a CO2-dependent heat loss to the surrounding air, allowing CO2 concentration to be derived from its temperature rise and power dissipation. The circuit employs a dual-mode incremental delta-sigma ADC to digitize these parameters relative to those of an identical, but isolated, reference transducer. This ratiometric approach results in a measurement that does not require precision voltage or power references. The readout circuit uses dynamically-swapped transducer pairs to cancel their baseline-resistance, so as to relax the required dynamic range of the ADC. In addition, dynamic element matching (DEM) is used to bias the transducer pairs at an accurate current ratio, making the measurement insensitive to the precise value of the bias current. The readout circuit has been implemented in a standard 0.16 $\mu \text {m}$ CMOS technology. With commercial resistive micro-heaters, a CO2 sensing resolution of about 200 ppm ( $1\sigma $ ) was achieved in a measurement time of 30 s. Similar results were obtained with CMOS-compatible tungsten-wire transducers, paving the way for fully-integrated CO2 sensors for air-quality monitoring. <s> BIB013
Traditionally, air pollution concentrations are measured at fixed monitoring stations that are mainly built by environmental or governmental authorities. The main advantages of these stations lie in the measurement availability for a variety of pollutants, and the measurement reliability, which benefits long-term pollution estimation. However, air pollution monitoring using these fixed stations suffers from the low spatial resolution of the data, which may lead to inaccurate assessment over the whole study area. As the development of sensing technology, low-cost portable devices have been increasingly used to monitor the air pollution BIB007 BIB008 . A number of publications have reported the use of such mobile monitoring equipments. Wallace et al. conducted the mobile surveys on a variety of pollutants in the city of Hamilton, ON, Canada since 2005  . Pollution data with timestamps and GPS coordinates were collected using a monitoring unit consisting of an enclosed van equipped with pollution monitors, a GPS unit, a laptop and an integrated battery pack. Sampling routes were specially designed to cover the areas of "hot spots" such as heavy industries and major highways under various meteorological conditions. During the 2008 Beijing Olympic Games, Wang et al. equipped a van with a large suite of devices for measuring particle size distribution and black carbon concentration BIB001 . MacNaughton et al. designed a battery-powered mobile monitoring station to study the spatial variation in air pollution BIB004 . Shi et al. applied a Toyota HiAce vehicle with monitoring sensors to estimate the spatial variation of PM 2.5 and PM 10 in the downtown area of Hong Kong  . Although different pollutants were measured in the researches aforementioned, utilized mobile platforms share the same key components: a vehicle (e.g., a van and a car), pollution monitors, a GPS unit, and a battery to power the pollution monitors and the GPS unit. In addition, all of the data collection were conducted along the pre-designed routes (mostly on the major roads). To explore the personal exposure of other road users to air pollutants, researchers have improved the monitoring units to be more compact and flexible. Bigazzi and Figliozzi mounted the pollution measuring instruments to bicycles to monitor the bicyclists' exposure to volatile organic compounds and carbon monoxide BIB009 . Zwack et al. designed backpacks containing pollution monitoring instruments and a GPS device to be carried along scripted walking routes, so as to cover all roads in the study area. The recorded data was used to build an air pollution map over that area, and to evaluate the contributions of traffic to neighborhood-scale air pollution BIB002 . Kingham et al. also designed bags with pollutant equipments to collect mobile pollution data for exposure assessment in different modes of transport, including car, bike, and bus BIB003 . No matter which type of vehicles were utilized to carry the pollution monitors in the research aforementioned, the data collection was conducted only for a short-term period (limited to the power supply), to cover various meteorological conditions or all the roads in the study area. These collected data over a short period of sampling time was sufficient to analyze the impact of the environmental parameters (e.g., wind, weather) and generate pollution statistics. However, longer-period of data collection on a regular basis (such as "daily") is required for more accurate air pollution modeling and prediction. The "daily" mobile monitoring data can be collected by the current road users from their daily commutes, such as buses, taxis and frequent cyclists BIB005 . Shirai et al. proposed mechanisms for a real-time air quality monitoring system using public transports and had this system tested using garbage trucks in Fujisawa, Japan BIB011 . Dong et al. developed a mobile sensor network system called Mosaic and mounted them on the cleaning vehicles in Ningbo and buses in Hongzhou, China for city-scale pollution sensing BIB010 BIB012 . Hasenfratz et al. collected enormous amount of "daily" air pollution data using ten trams of the public transport network of Zurich, Switzerland as carriers for their OpenSense measurement (http://www.opensense.ethz.ch/trac/) BIB006 . Furthermore, imec developed low-power sensors BIB013 and employed postal trucks as carriers during "daily" data collection. Compared to traditional fixed monitoring stations, mobile devices measure pollution close to the people affected by it, or close to the vehicles producing it. They offer high spatial and temporal resolution, albeit concentrated on specific routes and specific time periods (e.g., rush hour). This data is therefore of a very different and complementary nature than fixed sensor data.