Spatiotemporal monitoring of the built thermal environment plays an important role in promoting building thermal and energy management for development of sustainable buildings. However, the limited number of sensors and the uncertain airflow dynamics increase the difficulty for monitoring the nonuniformly distributed temperature states in the built thermal environment. In this study, a deep learning based predictive monitoring framework is proposed for spatiotemporal reconstruction and uncertainty quantification of the high-dimensional airflow fields in built environment based on limited sensors. The monitoring framework (iCVAE-BiLSTM) is developed by combining improved Conditional Variational Auto-Encoder (iCVAE), Bi-directional Long Short-Term Memory Network (BiLSTM) and Monte Carlo Simulation (MCS). Specifically, iCVAE is used in combination with BiLSTM model to model the spatiotemporal variations of the distributed indoor temperature states, while MCS is applied to quantify the uncertainties in temperature variations. A case study is carried out in a confined space under mixing convection for validation of the iCVAE-BiLSTM based monitoring framework. Moreover, the effects of sensor numbers and sensor placement on monitoring accuracy are quantitatively investigated. Our study demonstrates that the proposed iCVAE-BiLSTM model has significant application potentials for monitoring built environment and for promoting the development of energy-efficient buildings.

Pollution data were collected at five schools in Hong Kong using low-cost, sensor-based monitors both indoors and outdoors during two consecutive high pollution episodes. The pollutants monitored included NO2, O3, PM2.5, and PM10, which were also used as input to a health risk communication protocol known as Air Quality Health Index (AQHI). CO2 was also measured simultaneously. The study aimed to assess the relationship between indoor pollutant concentrations and AQHI levels with those outdoors and to evaluate the efficacy of building operating practices in protecting students from pollution exposure. The results indicate that the regular air quality monitoring stations and outdoor pollutant levels at schools exhibit similar patterns. School AQHI levels indoors were generally lower than those outdoors, with PM10 levels showing a larger proportional contribution to the calculated values indoors. NO2 levels in one school were in excess of outdoor values. CO2 monitored in classrooms commonly exceeded indoor guidelines, suggesting poor ventilation. One school that employed air filtration had lower indoor PM concentrations compared to other schools; however, they were still similar to those outdoors. O3 levels indoors were consistently lower than those outdoors. This study underscores the utility of on-site, sensor-based monitoring for assessing the health impacts of indoor and community exposure to urban air pollutants. The findings suggest a need for improved ventilation and more strategic air intake placement to enhance indoor air quality.

A novel approach for measurement of stable carbon isotopic ratio of atmospheric aerosols was developed by tandem operation of two instruments: a Sunset Organic Carbon-Elemental Carbon (OC-EC) analyzer and an online Carbon Dioxide Stable Isotope Analyzer (LGR, CCIA-36d). Sensitivity, accuracy and measurement uncertainty of the CCIA was comprehensively investigated using the standard reference CO2 gas with known concentration and isotopic ratio. Drift in CCIA measurement due to varying CO2 and water vapor concentration was evaluated and a humidity stabilizer was designed and developed to control the water vapor concentration of exhaust gas flow from OC-EC prior to entering the CCIA. A Keeling approach was applied to separate the ratio in the samples from the mixture of PM sample-produced CO2 and reference gas and we developed a protocol to derive the isotopic composition of the particle samples. A lithium carbonate standard (in powder form) from National Institute of Standards and Technology (NIST) was used to validate measurement of δ13C ratios by CCIA. Offline measurement on ambient aerosol and diesel exhaust aerosols produced comparable results of isotopic ratio with literature values. This study demonstrates the utility of this tandem operation for carbon isotopic measurement of atmospheric particles with better than 1.0‰ precision as a cost-effective alternative of conventional Isotopic Ratio Mass Spectrometer (IR-MS).

Quantifying uncertainties in the prediction of building energy consumption is critical to building energy management systems. In this study, a deep-learning-based interval forecasting model is developed by combining fuzzy information granulation, attention mechanism, and long short-term memory (LSTM) network for predicting building energy consumption and to present future uncertainties in the form of intervals. In particular, fuzzy information granulation theory is used for interval estimation, and attention-based LSTM is deployed in combination with automatic hyperparameter optimizer to provide interval prediction. A case study based on real building dataset is carried out for validation of the proposed model. Our study demonstrates that granulation window size is one of the most significant parameters that determines the quality of prediction intervals (PIs). The decrease of granulation window size would result in decrease in PI coverage probability. Moreover, the proposed interval forecasting model using attention-based LSTM is compared with the model using conventional LSTM. It is shown that the attention-based LSTM provides better interval forecasting performance than the conventional LSTM in terms of PI coverage probability, indicating that the attention mechanism has significant advantages to improve interval forecasting performance by increasing the efficiency with which the model uses information.

With growing urbanization and industrialization, problems such as poor disposal practices of solid waste and ensuing uncontrolled air pollution adjacent to landfill pose threats to human and environmental wellbeing. Ahmedabad is highly polluted urban city in India and unregulated burning of solid waste further aggravates already appalling situation caused by a large number of industries and vehicle fleets. The present work was carried out to understand sources of metals in ambient air surrounding a municipal landfill known as Pirana. For the study, surrounding area of the landfill was divided into 100 rectangular cells covering almost 5 km distance from its outer boundary. A location representing major land-use feature of each cell was classified. Sampling was carried out at these locations. A total of 100 PM5.0 samples were collected. Sampling was conducted for 3 h at each sampling location with samples collected on quartz filter paper. Measurements were performed over approximately 6 months from August to February, 2018. The filters were analyzed for metals using an Atomic Absorption Spectrometer. These measurements were used to identify pollution sources using positive matrix factorization technique and locate the hotspots of emission sources of heavy metals pollution. Five major sources namely, ferrous industry, nonferrous industry, vehicular emissions, re-suspended dust and solid waste burning/industrial coal combustion were identified and quantified. The average contributions of these sources to heavy metals were 20.7 ± 16.2, 18.4 ± 14.3, 19.9 ± 13.6, 21.4 ± 17.6, and 19.6 ± 10.6%, respectively. The average contribution from solid waste and industrial coal combustion is only 19.6% against the total from the combined remaining sources (~ 80.4), which means contribution from former will be lesser. Thus, solid waste burning is minor contributor for degradation of air quality; presence of many other sources around the site is actually the dominant cause of pollution.

The ongoing outbreak of coronavirus disease 2019 (COVID-19) has spread rapidly on a global scale. Although it is clear that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is transmitted through human respiratory droplets and direct contact, the potential for aerosol transmission is poorly understood 1 – 3 . Here we investigated the aerodynamic nature of SARS-CoV-2 by measuring viral RNA in aerosols in different areas of two Wuhan hospitals during the outbreak of COVID-19 in February and March 2020. The concentration of SARS-CoV-2 RNA in aerosols that was detected in isolation wards and ventilated patient rooms was very low, but it was higher in the toilet areas used by the patients. Levels of airborne SARS-CoV-2 RNA in the most public areas was undetectable, except in two areas that were prone to crowding; this increase was possibly due to individuals infected with SARS-CoV-2 in the crowd. We found that some medical staff areas initially had high concentrations of viral RNA with aerosol size distributions that showed peaks in the submicrometre and/or supermicrometre regions; however, these levels were reduced to undetectable levels after implementation of rigorous sanitization procedures. Although we have not established the infectivity of the virus detected in these hospital areas, we propose that SARS-CoV-2 may have the potential to be transmitted through aerosols. Our results indicate that room ventilation, open space, sanitization of protective apparel, and proper use and disinfection of toilet areas can effectively limit the concentration of SARS-CoV-2 RNA in aerosols. Future work should explore the infectivity of aerosolized virus.

Brown carbon (BrC), an aerosol carbonaceous matter component, impacts atmospheric radiation and global climate because of its absorption in the near-ultraviolet-visible region. Simultaneous air sampling was conducted in two megacities of Xi'an (northern) and Hong Kong (southern) in China in winter of 2016-2017. The aim of this study is to determine and characterize the BrC compounds in collected filter samples. Characteristic absorption peaks corresponding to aromatic C-C stretching bands, organo-nitrates, and C═O functional groups were seen in spectra of Xi'an samples, suggesting that the BrC was derived from freshly smoldering biomass and coal combustion as well as aqueous formation of anthropogenic secondary organic carbon. In Hong Kong, the light absorption of secondary BrC accounted for 76% of the total absorbances of BrC. The high abundance of strong C═O groups, biogenic volatile organic compounds (BVOCs) and atmospheric oxidants suggest secondary BrC was likely formed from photochemical oxidation of BVOCs in Hong Kong. Several representative BrC molecular markers were detected using Fourier transform ion cyclotron resonance mass spectrometry and their absorption properties were simulated by quantum chemistry. The results demonstrate that light absorption capacities of secondary anthropogenic BrC with nitro-functional groups were stronger than those of biogenic secondary BrC and anthropogenic primary BrC.

The air quality in classrooms is a critical factor that affects students' daily exposure. Although air filtration units (AFUs) are often used to reduce exposure to air pollution in China, the effectiveness of installing AFUs in Chinese classrooms have not been quantitatively studied. Hence, we carried out concurrent air quality experiments in two identical classrooms where one room was equipped with commercial AFUs and the other one relied on the natural introduction of outside air. Measurements were taken during regular school days in the winter at a primary school in Hangzhou, China. Three AFU ventilation modes, i.e., fresh air, mixed air and recirculation mode were evaluated, respectively. We found that classrooms equipped with AFU showed significant PM2.5 reductions, but this was accompanied by CO2 build-ups. In classroom with AFUs on internal recirculation, nearly 70% of the PM2.5 concentration at the beginning of the class was reduced by the end of a 40-min class. However, the CO2 concentration was observed to reach levels that were six times greater than that of the ambient due to inadequate air change rate (<1 h(-1)). To mitigate the issue of excessive in-classroom CO2 accumulation when using AFUs, filtered outside air must be brought in during their operation. In comparison with the internal recirculation mode, we demonstrated that the fresh air mode that draws the supply air from outdoor can considerably lower CO2 build-ups in the classroom with a moderate increase in PM2.5 concentration of 15 +/- 10 mu g/m(3). The findings from this study helps policy makers especially in developing countries with serious air pollution issues to determine whether or not to install AFU in primary schools and what ventilation mode is effective in reducing negative health effects. (C) 2020 Elsevier Ltd. All rights reserved.

Public transport interchanges (PTI) are special transportation-impacted micro-environments in Hong Kong where public transport such as buses, taxis and mini-buses pass through or terminate, and where passengers queue for the transport. Hong Kong has 65 PTIs in total and most of these are located under residential or commercial buildings. Mechanical ventilation is included in all PTIs due to very limited natural ventilation and it is intended to limit the accumulation of air pollution from the various vehicles. However, numerous complaints were reported concerning PTIs’ air quality, and data are lacking to characterize pollution in these places. The purpose of this study was to determine the overall nature of pollutants in a sample of PTIs, to identify whether hot spots were present and how these might be related to both ventilation practices and bus activities in PTIs. 8 PTIs were selected for simultaneous measurement of NO, NO2 and PM2.5 in 4 days of sampling. A monitoring network was formed by a group of sensor-based air monitoring facilities which were deployed at multiple points in the passenger waiting areas of each selected PTI and also at the ventilation intakes. Specific data calibration and validation protocols were well designed for sensor data control and assurance in such near-source monitoring application. NO, NO2 and PM2.5­ measured inside the PTIs were compared with the ambient air quality data reported by nearby routine air quality monitoring stations. The average concentration levels of NOx were about 4-16 times higher than the ambient levels. NO, NO2 and NOx in the PTIs themselves showed similar daily repeatable variation patterns and NO concentration levels were always higher than NO2’s during the daytime, while the ambient showed opposite patterns. This indicates NOx pollutants inside the PTIs were mainly produced by the local bus activities. NO and NO2 measured at some ventilation intakes had even higher concentration levels than those of PTIs, which means the existing ventilation systems were generally not adequate to control the pollution concentration and sometimes could even make the problem worse. Exceedances of NO2’s 1-hour concentration limit (0.30 mg/m3) were observed at several monitoring sites and were found mainly located in the middle of the PTIs where ventilation is poorer or close to the bus stops occupied by older buses. PM2.5 measured inside the PTIs followed the patterns of ambient PM2.5 and showed comparable concentration levels, which implies traffic emission, especially the exhaust from buses in the PTIs may not be the main source for particle pollution. Concern was raised on the implementation of pollution mitigation plans inside PTIs to satisfy the urgent health protection need for the commuters and also for the staff of bus companies who work there. To effectively control the PTI pollution and limit exposures, it is necessary to consider the bus volume, bus emission type and ventilation design.

Background The ongoing outbreak of COVID-19 has spread rapidly and sparked global concern. While the transmission of SARS-CoV-2 through human respiratory droplets and contact with infected persons is clear, the aerosol transmission of SARS-CoV-2 has been little studied. Methods Thirty-five aerosol samples of three different types (total suspended particle, size segregated and deposition aerosol) were collected in Patient Areas (PAA) and Medical Staff Areas (MSA) of Renmin Hospital of Wuhan University (Renmin) and Wuchang Fangcang Field Hospital (Fangcang), and Public Areas (PUA) in Wuhan, China during COVID-19 outbreak. A robust droplet digital polymerase chain reaction (ddPCR) method was employed to quantitate the viral SARS-CoV-2 RNA genome and determine aerosol RNA concentration. Results The ICU, CCU and general patient rooms inside Renmin, patient hall inside Fangcang had undetectable or low airborne SARS-CoV-2 concentration but deposition samples inside ICU and air sample in Fangcang patient toilet tested positive. The airborne SARS-CoV-2 in Fangcang MSA had bimodal distribution with higher concentration than those in Renmin during the outbreak but turned negative after patients number reduced and rigorous sanitization implemented. PUA had undetectable airborne SARS-CoV-2 concentration but obviously increased with accumulating crowd flow. Conclusions Room ventilation, open space, proper use and disinfection of toilet can effectively limit aerosol transmission of SARS-CoV-2. Gathering of crowds with asymptomatic carriers is a potential source of airborne SARS-CoV-2. The virus aerosol deposition on protective apparel or floor surface and their subsequent resuspension is a potential transmission pathway and effective sanitization is critical in minimizing aerosol transmission of SARS-CoV-2.

Pollutants from navigation sector are key contributors to emission inventories of most coastal cities with heavy port activities. The use of high fuel sulfur content (FSC) bunker oil by ocean going vessels (OGVs) has been identified as a major source of sulfur dioxide (SO2). Government authorities all over the world, including Hong Kong government, have implemented air pollution control regulations to cap FSC of fuel used by OGVs to 0.5%, from the existing 3.5%, to reduce SO2 emissions. However, the lack of efficient screening tools to identify non-compliant OGVs has prevented effective enforcement. This study developed and evaluated an unmanned aerial vehicle (UAV)-borne lightweight (750 g) microsensor system (MSS), which is capable of measuring ship plume SO2, NO2, NO, CO2, CO, and particulate matter in real-time. Extensive experiments were conducted on the sensor system to evaluate its performance during laboratory and field operations. The effects of cross-sensitivity and meteorological conditions were studied and incorporated to account for the measurement conditions in dispersed ship plumes. The SO2 to CO2 concentration ratio-based FSC expression was formulated as per the 2016 European Union Directive and Regulations. Furthermore, the impact of plume dilution on the accuracy of FSC measurement was investigated at different stages using the MSS, with and without the UAV in both simulated conditions and real-world scenarios, maintaining a safe distance from the OGV exhaust stacks. The study demonstrates the robustness of using UAV-borne sensor system for ship emission sniffing and FSC determination. The results will assist in development of a technological framework for effective enforcement of ship emission control regulations.

In most major cities of China, commuters inevitably spend a considerable amount of time in vehicle cabins due to the escalation of traffic congestion and a rapidly increasing vehicle population. The in-vehicle microenvironment that is in close proximity to traffic emission sources is at particular risk of increased exposure to traffic-related air pollutants (TRAPs). In this study, a mobile measurement campaign was carried out to investigate in-vehicle exposure to TRAPs in China where the elevated level of TRAPs has drawn worldwide attention in recent years. Our analysis demonstrates that vehicle ventilation mode (i.e., mechanical ventilation, natural ventilation, hybrid ventilation, and infiltration) played a critical role in determining the level of in-vehicle exposure. Although the outside air (OA) mode of mechanical ventilation provided adequate air exchange to passengers, the average in-vehicle PM2.5 and UFP concentrations (119 mu g/m(3) and 97,227 cm(-3) on freeway, and 93 mu g/m(3) and 42,829 cm(-3) on local roadway) during a 20-min sampling period were observed at the level that are markedly greater than those from studies conducted in the U.S., posing a serious health threat to vehicle occupants. We elaborated how our results collected in China with a significantly more polluted on-road environment differ from existing studies in terms of ventilation and driving conditions. In addition, we made the first effort to examine in-vehicle exposure under hybrid ventilation that is a common ventilation practice in everyday commute to potentially reduce symptoms similar to sick building syndrome (SBS). Our data indicate that vehicle occupants under hybrid ventilation are at much greater risk of TRAPs exposure if operating in a polluted on-road environment, and we call for future research on automated ventilation system with advanced window control especially for vans and buses with a large cabin volume.

Air monitoring is desirable in many places to understand dynamic pollution trends and sources and improve knowledge of population exposure. While highly miniaturized low cost sensor technology is quickly evolving, there is also a need for the advancement of mid-tier systems that are closer to reference-grade technologies in their longevity and performance, but also feature compactness that requires less significant infrastructure. This project evaluated the performance of a prototype solar-powered air monitoring system known as a Village Green Project (VGP) system with wireless data transmission that was deployed on a school rooftop in Hong Kong and operated for over one year. The system provided highly time-resolved and long-term data utilizing mid-tier cost ozone, PM2.5 and meteorological instruments. It operated with very minimal maintenance but shading by a nearby building reduced solar radiation, thus battery run time, over the 16-months measurement period, approximately 330,000 1-min observations were recorded (data completeness of ~62%). The monitoring data were evaluated by comparison with a nearby Hong Kong Environment Protection Department (EPD) station and exhibited good performance for 1-h resolution (R2 = 0.74 for PM2.5 and R2 = 0.76 for ozone). Furthermore as a demonstration, a nonparametric regression (NPR) model was applied for identifying the location of pollution source, combining air pollution and meteorological measurements. In addition, based on the high time-resolution wind data, local-scale back-trajectories were calculated as an input for receptor-oriented Nonparametric Trajectory Analysis (NTA) model. The combination of the VGP air monitoring system and NTA model identified apparent local sources in urban area. The demonstration was largely successful and operational improvements are clearly suggested to insure better siting and configurations to insure adequate power and air flow.

Summer and winter fine particulate matter (PM2.5) samples were collected to provide insight into the seasonal variations of the optical properties and source profiles of PM2.5 black carbon (BC) and brown carbon (BrC) in Xi'an, China. The average PM2.5 mass concentration during the winter haze (WH) period was 292.5 μg m-3, which was 2.6, 5.0 and 9.2 times higher than that during winter non-haze (WNH), summer haze (SH), and summer non-haze (SNH) periods, respectively. Regarding optical properties, the PM2.5 chemical-derived light extinction coefficient was the highest during the WH period (1019.2 Mm-1) and decreased by approximately one-fourth in the SH period (237.6 Mm-1). During the WH period, the light absorption coefficient of BC (babs-BC) was considerably higher than that during the SH period; this is attributable to the thick coatings of inorganic ions on BC and intensive fossil fuel and biomass burning emissions in winter. Source apportionment also proved that fossil fuels were the major emission source of BC in SH and WH periods with high light absorption coefficient babs_FF (fossil fuel) fractions (>70%). Biomass burning contributed to 25.8% of BC in the winter haze period, but to only 5.4% of BC in the summer haze period. The mass absorption coefficient of BC (MAC-BC) was higher in summer, as it was considerably influenced by vehicle emissions, whereas it was lower in winter due to the strong influences of biomass burning. Moreover, the high light absorption coefficient of BrC (babs-BrC) in both WH and WNH indicated substantial light absorption during winter; however, this coefficient was considerably lower in summer. A remarkable difference in the diurnal pattern of haze between babs-BrC and babs-BC indicated that BC leads to a severe visibility reduction during traffic rush hours. In addition, the BrC abundance observed in Xi'an revealed different diurnal patterns in WH and SH periods, which can be attributed to different secondary formation processes. SH BrC was generally contributed by photochemical-derived secondary organic carbon (SOC) whereas the abundant WH BrC was mainly transformed from aqueous-SOC.

Metropolitan residents are concerned about their exposure to airborne pollutants. But establishing these exposures is challenging. A compact personal exposure kit (PEK) was developed to evaluate personal integrated exposure (PIE) from time-resolved data to particulate matter with aerodynamic diameter less than 2.5 mu m (PM2.5) in five microenvironments, including office, home, commuting, other indoor activities (other than home and office), and outdoor activities experienced both on weekdays and weekends. The study was conducted in Hong Kong. The PEK measured PM2.5, reported location and several other factors, stored collected data, as well as reported the data back to the investigators using global system for mobile communication (GSM) telemetry. Generally, PM2.5 concentrations in office microenvironment were found to be the smallest (13.0 mu g/m(3)), whereas the largest PM2.5 concentration microenvironments were experienced during outdoor activities (54.4 mu g/m(3)). Participants spent more than 85% of their time indoors, including in offices, homes, and other public indoor venues. On average, 42% and 81% of the time were spent in homes, which contributed 52% and 79% of PIE (during weekdays and weekends, respectively), suggesting that improvement of air quality in homes may reduce overall exposures and indicating the need for actions to mitigate possible public health burdens in Hong Kong. This study also found that various indoor/outdoor microenvironments experienced by urban office workers cannot be accurately represented by general urban air quality data reported from the regulatory monitoring. Such personalized air quality information, especially while in transit or in offices and homes, may provide improved information on population exposures to air pollution. Implications: A newly developed personal exposure kit (PEK) was used to monitor PM2.5 exposure of metropolitan citizens in their daily life. Different microenvironments and time durations caused various personal integrated exposure (PIE). The stationary monitoring method for PIE was also compared and evaluated with PEK. Positive protection actions can be taken after understanding the major contribution to PM2.5 exposure.

The increasing applications of low-cost air sensors promises more convenient and cost-effective systems for air monitoring in many places and under many conditions. However, the data quality from such systems has not been fully characterized and may not meet user expectations in research and regulatory uses, or for use in citizen science. In our study, electrochemical sensors (Alphasense B4 series) for carbon monoxide (CO), nitric oxide (NO), nitrogen dioxide (NO2), and oxidants (O-x) were evaluated under controlled laboratory conditions to identify the influencing factors and quantify their relation with sensor outputs. Based on the laboratory tests, we developed different correction methods to compensate for the impact of ambient conditions. Further, the sensors were assembled into a monitoring system and tested in ambient conditions in Hong Kong side-by-side with regulatory reference monitors, and data from these tests were used to evaluate the performance of the models, to refine them, and validate their applicability in variable ambient conditions in the field. The more comprehensive correction models demonstrated enhanced performance when compared with uncorrected data. One over-arching observation of this study is that the low-cost sensors may promise excellent sensitivity and performance, but it is essential for users to understand and account for several key factors that may strongly affect the nature of sensor data. In this paper, we also evaluated factors of multi-month stability, temperature, and humidity, and considered the interaction of oxidant gases NO2 and ozone on a newly introduced oxidant sensor.

Over the past decade, a range of sensor technologies became available on the market, enabling a revolutionary shift in air pollution monitoring and assessment. With their cost of up to three orders of magnitude lower than standard/reference instruments, many avenues for applications have opened up. In particular, broader participation in air quality discussion and utilisation of information on air pollution by communities has become possible. However, many questions have been also asked about the actual benefits of these technologies. To address this issue, we conducted a comprehensive literature search including both the scientific and grey literature. We focused upon two questions: (1) Are these technologies fit for the various purposes envisaged? and (2) How far have these technologies and their applications progressed to provide answers and solutions? Regarding the former, we concluded that there is no clear answer to the question, due to a lack of: sensor/monitor manufacturers' quantitative specifications of performance, consensus regarding recommended end-use and associated minimal performance targets of these technologies, and the ability of the prospective users to formulate the requirements for their applications, or conditions of the intended use. Numerous studies have assessed and reported sensor/monitor performance under a range of specific conditions, and in many cases the performance was concluded to be satisfactory. The specific use cases for sensors/monitors included outdoor in a stationary mode, outdoor in a mobile mode, indoor environments and personal monitoring. Under certain conditions of application, project goals, and monitoring environments, some sensors/monitors were fit for a specific purpose. Based on analysis of 17 large projects, which reached applied outcome stage, and typically conducted by consortia of organizations, we observed that a sizable fraction of them (~ 30%) were commercial and/or crowd-funded. This fact by itself signals a paradigm change in air quality monitoring, which previously had been primarily implemented by government organizations. An additional paradigm-shift indicator is the growing use of machine learning or other advanced data processing approaches to improve sensor/monitor agreement with reference monitors. There is still some way to go in enhancing application of the technologies for source apportionment, which is of particular necessity and urgency in developing countries. Also, there has been somewhat less progress in wide-scale monitoring of personal exposures. However, it can be argued that with a significant future expansion of monitoring networks, including indoor environments, there may be less need for wearable or portable sensors/monitors to assess personal exposure. Traditional personal monitoring would still be valuable where spatial variability of pollutants of interest is at a finer resolution than the monitoring network can resolve.

Black carbon (BC) aerosols were observed over Xi’an (XA) and Hong Kong (HK) to better compare its properties and sources in two geographically separate regions in China. High-BC (7.9 ± 3.3 μg·m−3) and -PM2.5 (182 ± 80.5 μg·m−3) concentrations were observed in XA, and these were much higher than those in HK (BC, 3.2 ± 0.9 μg·m−3; PM2.5, 34.5 ± 9.3 μg·m−3). The contribution of BC to PM2.5 in HK reached 10.7%, which was ~ 1.5 times than that in XA (7.6%). The results emphasized that BC played an important role in HK PM2.5. The diurnal distribution of HK BC was highly correlated with vehicle emissions during the daytime; it peaked during heavy traffic times. Whereas XA BC exhibited flat distribution owing to stable BC sources. It is not markedly driven by traffic patterns. Additionally, the potential source contribution function (PSCF) analysis showed that XA BC mainly originated from local emissions while nearly half of the HK BC originated from distant sources, such as industrial emissions from northeastern regions and ship emissions from marine regions. These anthropogenic BC sources were found to be regional in nature based on multilinear engine (ME-2) analysis. Specifically, the XA BC sources were dominated by three factors: 22.5% from coal burning, 19.6% from biomass burning, and 32.9% from vehicle emissions. In HK, the majority of BC contributions originated from vehicle and ship emissions (78.9%), while only 14.5% and 1.5% originated from coal and biomass burning from residential combustion, as well as industrial and power plants in inland China.

Air pollution, both indoor and outdoor, has acute and chronic effects on human health, and air quality is affected by pollutants such as nitrogen dioxide, carbon monoxide and particulate matters. [...]

Epidemiology studies have demonstrated an association between airborne pollutant and adverse effects [...]