PM2.5 exposure in highly polluted cities: A case study from New Delhi, India

A review of personal exposure studies in selected Asian countries' public transport microenvironments: lessons learned and future directions

This comprehensive paper conducts an in-depth review of personal exposure and air pollutant levels within the microenvironments of Asian city transportation. Our methodology involved a systematic analysis of an extensive body of literature from diverse sources, encompassing a substantial quantity of studies conducted across multiple Asian cities. The investigation scrutinizes exposure to various pollutants, including particulate matters (PM10, PM2.5, and PM1), carbon dioxide (CO2), formaldehyde (CH2O), and total volatile organic compounds (TVOC), during transportation modes such as car travel, bus commuting, walking, and train rides. Notably, our review reveals a predominant focus on PM2.5, followed by PM10, PM1, CO2, and TVOC, with limited attention given to CH2O exposure. Across the spectrum of Asian cities and transportation modes, exposure concentrations exhibited considerable variability, a phenomenon attributed to a multitude of factors. Primary sources of exposure encompass motor vehicle emissions, traffic dynamics, road dust, and open bus doors. Furthermore, our findings illuminate the influence of external environments, particularly in proximity to train stations, on pollutant levels inside trains. Crucial factors affecting exposure encompass ventilation conditions, travel-specific variables, seat locations, vehicle types, and meteorological influences. The culmination of this rigorous review underscores the need for standardized measurements, enhanced ventilation systems, air filtration mechanisms, the adoption of clean energy sources, and comprehensive public education initiatives aimed at reducing pollutant exposure within city transportation microenvironments. Importantly, our study contributes to the growing body of knowledge surrounding this subject, offering valuable insights for policymakers and researchers dedicated to advancing air quality standards and safeguarding public health.

Very high particulate pollution over northwest India captured by a high-density in situ sensor network

Exposure to particulate matter less than 2.5 µm in diameter (PM2.5) is a cause of concern in cities and major emission regions of northern India. An intensive field campaign involving the states of Punjab, Haryana and Delhi national capital region (NCR) was conducted in 2022 using 29 Compact and Useful PM2.5 Instrument with Gas sensors (CUPI-Gs). Continuous observations show that the PM2.5 in the region increased gradually from < 60 µg m-3 in 6-10 October to up to 500 µg m-3 on 5-9 November, which subsequently decreased to about 100 µg m-3 in 20-30 November. Two distinct plumes of PM2.5 over 500 µg m-3 are tracked from crop residue burning in Punjab to Delhi NCR on 2-3 November and 10-11 November with delays of 1 and 3 days, respectively. Experimental campaign demonstrates the advantages of source region observations to link agricultural waste burning and air pollution at local to regional scales.

Size fraction of hazardous particulate matter governing the respiratory deposition and inhalation risk in the highly polluted city Delhi

Delhi has been identified as one of the highly polluted cities in the world and recently associated with the highest population weighted PM_2.5 concentration. However, the unavailability of the health risk estimations using long-term data for Indian cities has been pointed out as a hurdle in performing the correct assessment. The present work estimated deposition of particles in different regions of respiratory systems (head airway = 67% deposition for 2.5 µm particles; tracheo-bronchiolar (TB) = 73% deposition for 1.0 µm particles; alveolar (AL) = 17% deposition for 0.5 µm, 0.25 µm, and < 0.25 µm particles) using PM samples collected at a breathing height of 1.5 m near the major ring road in New Delhi (India). The calculated risk index (RI) varied considerably between winter (1.21 ± 0.26 to 1.33 ± 0.50) and pre-monsoon-southwest monsoon months (0.34 ± 0.08 to 0.96 ± 0.27). Respiratory deposition dose of nanosized particles (≤ 500 nm) in the alveoli region of the lung was found to be considerable (35%) indicating the need for understanding the role of these particles in posing health risk. Although the calculated values of risk metric for exposures of PM-associated metals indicated no risk to IIT Delhi population (hazard quotient < 1 and excess risk of getting cancer < 10^-6-10^-9), continuous monitoring for particles of different sizes at inhalation height are required for protecting human health.

High contribution from outdoor air to personal exposure and potential inhaled dose of PM2.5 for indoor-active university students

People spend most of their time indoors, isolated from the outdoor environment where serious air pollution usually occurs. To what extent outdoor air pollution contributes to their daily personal exposure and inhaled dose? To fill this knowledge gap, an exposure assessment study was conducted for indoor-active university students during a wintertime period of hazy and non-hazy (clear) days in Beijing. Indoor and outdoor fine particulate matter (PM_2.5) samples were collected at six indoor microenvironments, and two outdoor environments representing traffic and ambient exposure in the university, respectively, to estimate the personal exposure of students. The average daily personal exposure and poteantial inhaled dose on hazy days (124.8 ± 72.3 μg m^-3 and 2.74 ± 1.53 mg) were much higher than that on clear days (57.5 ± 31.9 μg m^-3 and 1.26 ± 0.59 mg), indicating a significant influence from the ambient air quality. The indoor PM_2.5 concentrations were significantly and positively correlated with the outdoor ones (r = 0.67-0.96) with an F_INF (infiltration factor) range of 0.44-0.81 during sampling periods. The outdoor-origin air contributed 68%-95% to the total indoor PM_2.5, the average of which was higher during haze events (87%) than clear periods (73%). Correspondingly, outdoor-origin PM_2.5 contributed around 105.4 μg m^-3 and 2.41 mg (85% and 89%) to the daily exposure and inhaled dose of college students on hazy days, respectively, compared to just 39.2 μg m^-3 and 0.95 mg (68% and 75%) on clear days. Our results highlight the significant contribution of outdoor-origin PM_2.5 occurred indoor to both the daily personal exposure and inhaled dose due to air pollution filtration between outdoor and indoor environments. These also suggest a continuous effort not only on ambient air quality improvements, but also on environmental friendly building for public health protection with lower exposure.

Comparing human exposure to fine particulate matter in low and high-income countries: A systematic review of studies measuring personal PM2.5 exposure

BACKGROUND

Due to the adverse health effects of air pollution, researchers have advocated for personal exposure measurements whereby individuals carry portable monitors in order to better characterise and understand the sources of people's pollution exposure.

OBJECTIVES

The aim of this systematic review is to assess the differences in the magnitude and sources of personal PM2.5 exposures experienced between countries at contrasting levels of income.

METHODS

This review summarised studies that measured participants personal exposure by carrying a PM2.5 monitor throughout their typical day. Personal PM2.5 exposures were summarised to indicate the distribution of exposures measured within each country income category (based on low (LIC), lower-middle (LMIC), upper-middle (UMIC), and high (HIC) income countries) and between different groups (i.e. gender, age, urban or rural residents).

RESULTS

From the 2259 search results, there were 140 studies that met our criteria. Overall, personal PM2.5 exposures in HICs were lower compared to other countries, with UMICs exposures being slightly lower than exposures measured in LMICs or LICs. 34% of measured groups in HICs reported below the ambient World Health Organisation 24-h PM2.5 guideline of 15 μg/m3, compared to only 1% of UMICs and 0% of LMICs and LICs. There was no difference between rural and urban participant exposures in HICs, but there were noticeably higher exposures recorded in rural areas compared to urban areas in non-HICs, due to significant household sources of PM2.5 in rural locations. In HICs, studies reported that secondhand smoke, ambient pollution infiltrating indoors, and traffic emissions were the dominant contributors to personal exposures. While, in non-HICs, household cooking and heating with biomass and coal were reported as the most important sources.

CONCLUSION

This review revealed a growing literature of personal PM2.5 exposure studies, which highlighted a large variability in exposures recorded and severe inequalities in geographical and social population subgroups.

Socioeconomic and Demographic Associations with Wintertime Air Pollution Exposures at Household, Community, and District Scales in Rural Beijing, China

The Chinese government implemented a national household energy transition program that replaced residential coal heating stoves with electricity-powered heat pumps for space heating in northern China. As part of a baseline assessment of the program, this study investigated variability in personal air pollution exposures within villages and between villages and evaluated exposure patterns by sociodemographic factors. We randomly recruited 446 participants in 50 villages in four districts in rural Beijing and measured 24 h personal exposures to fine particulate matter (PM_2.5) and black carbon (BC). The geometric mean personal exposure to PM_2.5 and BC was 72 and 2.5 μg/m³, respectively. The variability in PM_2.5 and BC exposures was greater within villages than between villages. Study participants who used traditional stoves as their dominant source of space heating were exposed to the highest levels of PM_2.5 and BC. Wealthier households tended to burn more coal for space heating, whereas less wealthy households used more biomass. PM_2.5 and BC exposures were almost uniformly distributed by socioeconomic status. Future work that combines these results with PM_2.5 chemical composition analysis will shed light on whether air pollution source contributors (e.g., industrial, traffic, and household solid fuel burning) follow similar distributions.

Ambient Air Pollution and Socioeconomic Status in China

BACKGROUND

Air pollution disparities by socioeconomic status (SES) are well documented for the United States, with most literature indicating an inverse relationship (i.e., higher concentrations for lower-SES populations). Few studies exist for China, a country accounting for 26% of global premature deaths from ambient air pollution.

OBJECTIVE

Our objective was to test the relationship between ambient air pollution exposures and SES in China.

METHODS

We combined estimated year 2015 annual-average ambient levels of nitrogen dioxide (NO 2 ) and fine particulate matter [PM ≤ 2.5 μ m in aerodynamic diameter (PM 2.5 )] with national demographic information. Pollution estimates were derived from a national empirical model for China at 1 -km spatial resolution; demographic estimates were derived from national gridded gross national product (GDP) per capita at 1 -km resolution, and (separately) a national representative sample of 21,095 individuals from the China Health and Retirement Longitudinal Study (CHARLS) 2015 cohort. Our use of global data on population density and cohort data on where people live helped avoid the spatial imprecision found in publicly available census data for China. We quantified air pollution disparities among individual's rural-to-urban migration status; SES factors (education, occupation, and income); and minority status. We compared results using three approaches to SES measurement: individual SES score, community-averaged SES score, and gridded GDP per capita.

RESULTS

Ambient NO 2 and PM 2.5 levels were higher for higher-SES populations than for lower-SES population, higher for long-standing urban residents than for rural-to-urban migrant populations, and higher for the majority ethnic group (Han) than for the average across nine minority groups. For the three SES measurements (individual SES score, community-averaged SES score, gridded GDP per capita), a 1-interquartile range higher SES corresponded to higher concentrations of 6 - 9   μ g / m 3 NO 2 and 3 - 6   μ g / m 3 PM 2.5 ; average concentrations for the highest and lowest 20th percentile of SES differed by 41-89% for NO 2 and 12-25% for PM 2.5 . This pattern held in rural and urban locations, across geographic regions, across a wide range of spatial resolution, and for modeled vs. measured pollution concentrations.

CONCLUSIONS

Multiple analyses here reveal that in China, ambient NO 2 and PM 2.5 concentrations are higher for high-SES than for low-SES individuals; these results are robust to multiple sensitivity analyses. Our findings are consistent with the idea that in China's current industrialization and urbanization stage, economic development is correlated with both SES and air pollution. To our knowledge, our study provides the most comprehensive picture to date of ambient air pollution disparities in China; the results differ dramatically from results and from theories to explain conditions in the United States. https://doi.org/10.1289/EHP9872.

Exposure assessment of PM2.5 in temple premises and crematoriums in Kanpur, India

Regular use of incense and earthen lamps in temples leads to the release of particulate matter (PM), airborne flecks, and gaseous pollutants. Similarly, the cremation of dead bodies using timber and other accessories such as incense, organic chemicals containing carbon, and clothes generates air pollutants. It is currently unclear how much emissions and exposure these activities may lead. This work attempts to fill this gap in our understanding by assessing the associated emissions of PM_2.5 and the corresponding exposure. Ten temples and two cremation grounds were considered for the sampling of PM_2.5. The average PM_2.5 concentration at the ten temples and the two crematoriums was found to be 658.30 ± 112.63 µg/m³ and 1043.50 ± 191.63 µg/m³, respectively. The range of real-time PM_2.5 data obtained from the nearest twelve stations located in the vicinity was 113-191 µg/m³. The exposure assessment in terms of deposition dose was carried out using the ICRP model. The maximum and minimum total respiratory deposition dose rate for PM_2.5 for temples was 175.75 µg/min and 101.15 µg/min, respectively. For crematoriums, the maximum and minimum value of same was 252.3 µg/min and 194.31 µg/min, respectively, for an exposure period of 10 min.

Inequalities in occupational exposures among people using popular commute modes

Several recent studies have looked into the differences in air qualities inside popular commute modes. The impact of daily commuting patterns and work-related trips on inhalation doses, however, are not investigated. The purpose of this study is to quantify the variation in air pollutants within popular commute modes in Mumbai, India, and to estimate the variation in exposure as a result of occupational or work-related trips across different sub-groups. Real-time pollutants, both gaseous and particulate matters (PM), were measured on a pre-defined route during rush and non-rush hours on buses, cars, auto-rickshaws, sub-urban trains, and motorbikes through several trips (N = 98). Household surveys were conducted to estimate the exposures of different occupational subgroups (cab-driver, auto-rickshaw drivers, delivery persons) and people commuting to their offices daily. Participants (N = 800) from various socioeconomic backgrounds in the city were asked about their job categories, work-activity patterns, and work-related commute trips. Mass concentrations of particles in different size ranges (PM₁, PM_2.5, and PM₁₀) were substantially higher (p < 0.05) inside auto-rickshaws (44.6 μg/m³, 84.7 μg/m³, and 138.3 μg/m³) compared to other modes. Inside cars, gaseous pollutants such as carbon monoxide (CO) and total volatile organic compounds (TVOC) were significantly higher (p < 0.05). Although both gaseous and particulate concentrations were lower (p < 0.05) inside buses, bus-commuters were found to be highly exposed to the pollutants due to the extended trip time (∼1.2 times longer than other modes) and driving conditions. Office commuters inhale a large fraction of their daily doses (25-30%) during their work-related travel. Occupational sub-groups, on the other hand, inhale ∼90% of the pollutants during their work. In a day, an auto-rickshaw driver inhales 10-15% more (p < 0.05) pollutants than cab driver or delivery personnel. Therefore, this study highlights the inequalities in occupational exposure as a combined effect of in-cabin air qualities and commute patterns due to occupational obligations.

A review and analysis of personal and ambient PM2.5 measurements: Implications for epidemiology studies

BACKGROUND

In epidemiology studies, ambient measurements of PM_2.5 are often used as surrogates for personal exposures. However, it is unclear the degree to which ambient PM_2.5 reflects personal exposures.

OBJECTIVE

In order to examine potential sources of bias in epidemiology studies, we conducted a review and meta-analysis of studies to determine the extent to which short-term measurements of ambient PM_2.5 levels are related to short-term measurements of personal PM_2.5 levels.

METHODS

We conducted a literature search of studies reporting both personal and ambient measurements of PM_2.5 published in the last 10 years (2009-2019) and incorporated studies published prior to 2009 from reviews.

RESULTS

Seventy-one studies were identified. Based on 17 studies reporting slopes, a meta-analysis revealed an overall slope of 0.56 μg/m³ (95% CI: [0.39, 0.73]) personal PM_2.5 per μg/m³ increase in ambient PM_2.5. Slopes for summer months were higher (slope = 0.73, 95% CI: [0.64, 0.81]) than for winter (slope = 0.46, 95% CI: [0.36, 0.57]). Based on 44 studies reporting correlations, we calculated an overall personal-ambient PM_2.5 correlation of 0.63 (95% CI: [0.55, 0.71]). Correlations were stronger in studies conducted in Canada (r = 0.86, 95% CI: [0.67, 0.94]) compared to the USA (r = 0.60, 95% CI: [0.49, 0.70]) and China (r = 0.60, 95% CI: [0.46, 0.71]). Correlations also were stronger in urban areas (r = 0.53, 95% CI: [0.43, 0.62]) vs. suburban areas (r = 0.36, 95% CI: [0.21, 0.49]).

SIGNIFICANCE

Our results suggest a large degree of variability in the personal-ambient PM_2.5 association and the potential for exposure misclassification and measurement error in PM_2.5 epidemiology studies.

Personal Exposure to Black Carbon, Particulate Matter and Nitrogen Dioxide in the Paris Region Measured by Portable Sensors Worn by Volunteers

Portable sensors have emerged as a promising solution for personal exposure (PE) measurement. For the first time in Île-de-France, PE to black carbon (BC), particulate matter (PM), and nitrogen dioxide (NO₂) was quantified based on three field campaigns involving 37 volunteers from the general public wearing the sensors all day long for a week. This successful deployment demonstrated its ability to quantify PE on a large scale, in various environments (from dense urban to suburban, indoor and outdoor) and in all seasons. The impact of the visited environments was investigated. The proximity to road traffic (for BC and NO₂), as well as cooking activities and tobacco smoke (for PM), made significant contributions to total exposure (up to 34%, 26%, and 44%, respectively), even though the time spent in these environments was short. Finally, even if ambient outdoor levels played a role in PE, the prominent impact of the different environments suggests that traditional ambient monitoring stations is not a proper surrogate for PE quantification.

Assessing risk to human health for heavy metal contamination from public point utility through ground dust: a case study in Nantong, China

Heavy metal contamination in ground dust presents potential environmental and human health threats. However, the heavy metal contamination status of ground dust in the vicinity of public point utilities remains poorly explored. Therefore, this study has been designed to analyze the heavy metal contaminations in the ground dust collected monthly near a public bronze sculpture in an urban campus of Nantong, China, using geo-accumulation indexes (Igeo), enrichment factors (EF), potential ecological risk indexes (RI), and health risks (noncarcinogenic risks (HI) and carcinogenic risks (CR)). This study revealed that the maximum Cr, Cu, Mn, Ni, Pb, and Zn concentrations in ground dust samples were 156.2, 708.8, 869.8, 140.8, 180.5, and 1089.7 mg kg-1, respectively, in which the mean Cu and Zn concentrations were 9 and 7 times higher than the background level in the soil. Temporally speaking, for the majority of heavy metals (with the exception of Ni), the high-concentration seasons tend to be mainly summer and autumn. It was observed that Cu and Zn exhibited significant enrichment (EF = 11.7 and 8.4, respectively), moderate-to-strong pollution (Igeo = 2.4 and 2.0, respectively), and moderate- and low-potential ecological risks ([Formula: see text] = 45.6 and 6.6, respectively). The noncarcinogenic risks which adults exposed to the heavy metal concentrations suffered were found to be insignificant. However, the carcinogenic risks related to Ni (1.3E-04) had exceeded the acceptable level. Based on principal component analysis (PCA) and correlation analysis, the heavy metal concentrations in the ground dust of urban campuses could be related to public point utilities, traffic-related exhaust sources, and industrial activities. This study's findings demonstrated that urban public utilities require more attention due to their significant enrichment, ecological risk factors, and the significant carcinogenic risks to the population.

The Process and Platform for Predicting PM2.5 Inhalation and Retention during Exercise

In recent years, people have been increasingly concerned about air quality and pollution since a number of studies have proved that air pollution, especially PM2.5 (particulate matter), can affect human health drastically. Though the research on air quality prediction has become a mainstream research field, most of the studies focused only on the prediction of urban air quality and pollution. These studies did not predict the actual impact of these pollutants on people. According to the researchers’ best knowledge, the amount of polluted air inhaled by people and the amount of polluted air that remains inside their body are two important factors that affect their health. In order to predict the quantity of PM2.5 inhaled by people and what they have retained in their body, a process and a platform have been proposed in the current research work. In this research, the experimental process is as follows: (1) First, a personalized PM2.5 sensor is designed and developed to sense the quantity of PM2.5 around people. (2) Then, the Bruce protocol is applied to collect the information and calculate the relationship between heart rate and air intake under different activities. (3) The amount of PM2.5 retained in the body is calculated in this step using the International Commission on Radiological Protection (ICRP) air particle retention formula. (4) Then, a cloud platform is designed to collect people’s heart rate under different activities and PM2.5 values at respective times. (5) Finally, an APP is developed to show the daily intake of PM2.5. The result reveals that the developed app can show a person’s daily PM2.5 intake and retention in a specific population.

Fine particulate matter exposure in four transport modes of Greater Cairo

The number of daily commuters in Greater Cairo has exceeded 15 million nevertheless personal exposure studies in transport microenvironments are limited. The aim of this study is to quantify PM_2.5 exposure during peak hours in four transport modes of Greater Cairo - car (windows-open, windows-closed with recirculation and AC-on), microbus (windows-open), cycling and walking - and understand its underlying drivers. Data was collected using a pDR-1500 monitor and analysed to capture concentration variations, spatial variability, exposure doses, commuting costs versus inhaled doses, health burden and economic losses. Car with recirculation resulted in the least average PM_2.5 concentrations (32 ± 6 μg/m³), followed by walking (77 ± 35 μg/m³), car with windows-open (82 ± 32 μg/m³), microbus with windows-open (96 ± 29 μg/m³) and cycling (100 ± 28 μg/m³). Evening hours observed average PM_2.5 concentrations by 26-58% lesser than morning. Spatial variability analysis showed that 75th-90th percentile PM_2.5 concentrations coincided with congested spots. Cycling and walking lanes are rare hence commuters are exposed to surges in PM_2.5 concentrations when passing near construction and solid waste burning sites. Cycling and walking also resulted in inhaling 40-times and 32-times higher PM_2.5 dose per kilometre than for car with recirculation. Commuting by microbus cost (with windows-open) ~45% of car cost (with recirculation) but it resulted in 4-times higher inhaled PM_2.5 dose. As expected due to the lowest PM_2.5 exposure concentrations, health burden resulting from car travel (with recirculation) caused the least death rates of 0.07 (95% CI 0.07-0.08) prematures deaths per 100,000 commuters/year while microbus with windows-open resulted in the highest death rates; 0.52 (95% CI 0.49-0.56). Microbus deaths represent 57% of national economic losses due to PM_2.5 exposure amongst the four transport modes. This study provides real-time exposure data and analyses its implications on commuter health as a first step in informed decision-making and better urban planning.

Development and evaluation of air pollution-linked quality of life (AP-QOL) questionnaire: insight from two different cohorts

In this study, the air pollution-related quality of life (AP-QOL) questionnaire was carried out in two geographically and economically different groups including New Delhi (Megacity) and Hamirpur, Himachal Pradesh (town), and APE scores were linked with respiratory and cardiovascular illness. The APE-Score was developed by AP-QOL questionnaire responses using Delphi technique and further analyzed using principal component analysis (PCA). For reliability of APE-Score and AP-QOL questionnaire, α-Cronbach's test and basic statistics were performed. The linear mixed-effect model and odds ratios were used to evaluate air pollution exposure and health outcomes. Overall, 720 academicians and 276 security guards were invited to participate in the questionnaire. Cronbach's α coefficients ranged from 0.70 to 0.84 indicated significant reliability in the AP-QOL questionnaire conducted in this study. Substantial variation in respiratory symptoms and their medical history were found - 76.9% ([95% confidential interval (CI)]: (- 83.8, - 66.9) (p < 0.05)) and - 28.6% (95% CI: (- 37.8, - 18.0) (p < 0.05)), respectively, with interquartile range (IQR) increase of APE score. The odds ratios (ORs) of respiratory medical history (MH Res.) showed a significant increase from 1.01 to 1.35 for low to high air pollution exposure in the academic group of IIT Delhi. Interestingly, for an academic group of NITH, the ORs for medical history of cardiovascular (MH Card.) showed an increase from 1.08 to 1.13 for low to high APE which was not the case for IIT Delhi academicians.

Risk analysis of different transport vehicles in India during COVID-19 pandemic

Due to the airborne nature of viral particles, adequate ventilation has been identified as one suitable mitigation strategy for reducing their transmission. While 'dilution of air by opening the window' has been prescribed by national and international health agencies, unintended detrimental consequences might result in many developing countries with high ambient air pollution. In the present study, PM2.5 exposure concentration and probability of mortality due to PM2.5 in different scenarios were assessed. A COVID airborne infection risk estimator was used to estimate the probability of infection by aerosol transmission in various commuter micro-environments: (a) air conditioned (AC) taxi (b) non-AC taxi (c) bus and (d) autorickshaw. The following were the estimated exposure concentrations in the four types of vehicles during pre-lockdown, during lockdown, and lost-lockdown: AC taxi cars (17.16 μg/m3, 4.52 μg/m3, and 25.09 μg/m3); non-AC taxis: (28.74 μg/m3, 7.56 μg/m3, 42.01 μg/m3); buses (21.79 μg/m3, 5.73 μg/m3, 31.86 μg/m3) autorickshaws (51.30 μg/m3, 3.50 μg/m3, 75 μg/m3). Post-lockdown, the probability of mortality due to PM2.5 was highest for autorickshaws (5.67 × 10-3), followed by non-AC taxis (2.07 × 10-3), buses (1.39 × 10-3), and AC taxis (1.02 × 10-3). This order of risk is inverted for the probability of infection by SARS-COV-2, with the highest for AC taxis (6.10 × 10-2), followed by non-AC taxis (1.71 × 10-2), buses (1.42 × 10-2), and the lowest risk in autorickshaws (1.99 × 10-4). The findings of the present study suggest that vehicles with higher ventilation or air changes per hour (ACH) should be preferred over other modes of transport during COVID-19 pandemic.

Characterising professional drivers' exposure to traffic-related air pollution: Evidence for reduction strategies from in-vehicle personal exposure monitoring

Professional drivers working in congested urban areas are required to work near harmful traffic related pollutants for extended periods, representing a significant, but understudied occupational risk. This study collected personal black carbon (BC) exposures for 141 drivers across seven sectors in London. The aim of the study was to assess the magnitude and the primary determinants of their exposure, leading to the formulation of targeted exposure reduction strategies for the occupation. Each participant's personal BC exposures were continuously measured using real-time monitors for 96 h, incorporating four shifts per participant. 'At work' BC exposures (3.1 ± 3.5 µg/m³) were 2.6 times higher compared to when 'not at work' (1.2 ± 0.7 µg/m³). Workers spent 19% of their time 'at work driving', however this activity contributed 36% of total BC exposure, highlighting the disproportionate effect driving had on their daily exposure. Taxi drivers experienced the highest BC exposures due to the time they spent working in congested central London, while emergency services had the lowest. Spikes in exposure were observed while driving and were at times greater than 100 µg/m³. The most significant determinants of drivers' exposures were driving in tunnels, congestion, location, day of week and time of shift. Driving with closed windows significantly reduced exposures and is a simple behaviour change drivers could implement. Our results highlight strategies by which employers and local policy makers can reduce professional drivers' exposure to traffic-related air pollution.

Experimental study of a string-based counterflow wet electrostatic precipitator for collection of fine and ultrafine particles

Wet electrostatic precipitators (WESP) have been widely studied for collecting fine and ultrafine particles, such as diesel particulate matter (DPM), which have deleterious effects on human health. Here, we report an experimental and numerical simulation study on a novel string-based two-stage WESP. Our new design incorporates grounded vertically aligned polymer strings, along which thin films of water flow down. The water beads, generated by intrinsic flow instability, travel down the strings and collect charged particles in the counterflowing gas stream. We performed experiments using two different geometric configurations of WESP: rectangular and cylindrical. We examined the effects of the WESP electrode bias voltage, air stream velocity, and water flow rate on the number-based fractional collection efficiency for particles of diameters ranging from 10 nm to 2.5 μm. The collection efficiency improves with increasing bias voltages or decreasing airflow rates. At liquid-to-gas (L/G) as low as approximately 0.0066, our design delivers a collection efficiency over 70% even for fine and ultrafine particles. The rectangular and cylindrical configurations exhibit similar collection efficiencies under nominally identical experimental conditions. We also compare the water-to-air mass flow rate ratio, air flow rate per unit collector volume, and collection efficiency of our string-based design with those of previously reported WESPs. The present work demonstrates a promising design for a highly efficient, compact, and scalable two-stage WESPs with minimal water consumption.Implications: Wet Electrostatic Precipitators (WESPs) are highly effective for collecting fine particles in exhaust air streams from various sources such as diesel engines, power plants, and oil refineries. However, their large-scale adoption has been limited by high water usage and reduced collection efficiencies for ultrafine particles. We perform experimental and numerical investigation to characterize the collection efficiency and water flow rate-dependence of a new design of WESP. The string-based counterflow WESP reported in this study offers number-based collection efficiencies >70% at air flow rates per collector volume as high as 4.36 (m³/s)/m³ for particles of diameters ranging from 10 nm - 2.5 μm, while significantly reducing water usage. Our work provides a basis for the design of more compact and water-efficient WESPs.

Using the health beliefs model to explore children's attitudes and beliefs on air pollution

OBJECTIVES

Traffic-related air pollution (TRAP) negatively impacts children's health. Self-protective measures are available, but population uptake is variable. It is essential to understand human beliefs and behaviours related to air pollution in order to understand the lack of self-protection in communities. As a prelude to undertaking a comprehensive assessment of children's attitudes and beliefs on the health effects of TRAP exposure, we sought to develop and validate an appropriate instrument.

STUDY DESIGN

This study used exploratory sequential mixed methods.

METHODS

This instrument, based on the constructs of the health belief model (HBM), aimed to determine factors predicting wearing a mask to protect against TRAP exposure. An initial literature-based questionnaire was modified using in-depth interviews, focus group discussions, and a quantitative survey pilot. This study included 121 school students and nine professional experts in Vietnam. The questionnaire was tested for content validity, agreement, test-retest reliability, and internal consistency.

RESULTS

The concordance of questionnaire items between two repeated assessments ranged from 47.2% to 78.3%, intraclass correlation coefficients ranged from 0.16 to 0.87 and Cronbach's internal reliability coefficient for the instrument was 0.60.

CONCLUSION

The self-administered instrument, based on the HBM, is suitable to understand health attitudes and beliefs related to self-protective behaviours to reduce TRAP exposure.

The construction and examination of social vulnerability and its effects on PM2.5 globally: combining spatial econometric modeling and geographically weighted regression

Fine particulate matter (PM2.5) is of widespread concern, as it poses a serious impact on economic development and human health. Although the influence of socioeconomic factors on PM2.5 has been studied, the constitution and the effect analysis of social vulnerability to PM2.5 remain unclear. In this study, a comprehensive theoretical framework with appropriate indicators for social vulnerability to PM2.5 was constructed. Using spatial autocorrelation analysis, a positive global spatial autocorrelation and notable local spatial cluster relationships were identified. Spatial econometric modeling and geographically weighted regression modeling were performed to explore the cause-effect relationship of social vulnerability to PM2.5. The spatial error model indicated that population and education inequality in the sensitivity dimension caused a significant positive impact on PM2.5, and biocapacity and social governance in the capacity dimension strongly contributed to the decrease of PM2.5 globally. The geographically weighted regression model revealed spatial heterogeneity in the effects of the social vulnerability variables on PM2.5 among countries. These empirical results can provide policymakers with a new perspective on social vulnerability as it relates to PM2.5 governance and targeted environmental pollution management.

Assessment of Home-Based and Mobility-Based Exposure to Black Carbon in an Urban Environment: A Pilot Study

The combustion of fossil fuels is a significant source of particulate-bound black carbon (BC) in urban environments. The personal exposure (PE) of urban dwellers to BC and subsequent health impacts remain poorly understood due to a lack of observational data. In this study, we assessed and quantified the levels of PE to BC under two exposure scenarios (home-based and mobility-based exposure) in the city of Trivandrum in India. In the home-based scenario, the PE to BC was assessed in a naturally ventilated building over 24 h each day during the study period while in the mobility-based scenario, the PE to BC was monitored across diverse microenvironments (MEs) during the day using the same study protocol for consistency. Elevated BC concentrations were observed during the transport by motorcycle (26.23 ± 2.33 µg/m³) and car (17.49 ± 2.37 µg/m³). The BC concentrations observed in the MEs decreased in the following order: 16.58 ± 1.38 µg/m³ (temple), 13.78 ± 2.07 µg/m³ (restaurant), 11.44 ± 1.37 µg/m³ (bus stop), and 8.27 ± 1.88 µg/m³ (home); the standard deviations represent the temporal and spatial variations of BC concentrations. Overall, a relatively larger inhaled dose of BC in the range of 148.98–163.87 µg/day was observed for the mobility-based scenario compared to the home-based one (118.10–137.03 µg/day). This work highlights the importance of reducing PE to fossil fuel-related particulate emissions in cities for which BC is a good indicator. The study outcome could be used to formulate effective strategies to improve the urban air quality as well as public health.

Prenatal air pollution exposure and neurodevelopment: A review and blueprint for a harmonized approach within ECHO

BACKGROUND

Air pollution exposure is ubiquitous with demonstrated effects on morbidity and mortality. A growing literature suggests that prenatal air pollution exposure impacts neurodevelopment. We posit that the Environmental influences on Child Health Outcomes (ECHO) program will provide unique opportunities to fill critical knowledge gaps given the wide spatial and temporal variability of ECHO participants.

OBJECTIVES

We briefly describe current methods for air pollution exposure assessment, summarize existing studies of air pollution and neurodevelopment, and synthesize this information as a basis for recommendations, or a blueprint, for evaluating air pollution effects on neurodevelopmental outcomes in ECHO.

METHODS

We review peer-reviewed literature on prenatal air pollution exposure and neurodevelopmental outcomes, including autism spectrum disorder, attention deficit hyperactivity disorder, intelligence, general cognition, mood, and imaging measures. ECHO meta-data were compiled and evaluated to assess frequency of neurodevelopmental assessments and prenatal and infancy residential address locations. Cohort recruitment locations and enrollment years were summarized to examine potential spatial and temporal variation present in ECHO.

DISCUSSION

While the literature provides compelling evidence that prenatal air pollution affects neurodevelopment, limitations in spatial and temporal exposure variation exist for current published studies. As >90% of the ECHO cohorts have collected a prenatal or infancy address, application of advanced geographic information systems-based models for common air pollutant exposures may be ideal to address limitations of published research.

CONCLUSIONS

In ECHO we have the opportunity to pioneer unifying exposure assessment and evaluate effects across multiple periods of development and neurodevelopmental outcomes, setting the standard for evaluation of prenatal air pollution exposures with the goal of improving children's health.

Estimation of radiative forcing and heating rate based on vertical observation of black carbon in Nanjing, China

Owing to a lack of vertical observations, the impacts of black carbon (BC) on radiative forcing (RF) have typically been analyzed using ground observations and assumed profiles. In this study, a UAV platform was used to measure high-resolution in-situ vertical profiles of BC, fine particles (PM_2.5), and relevant meteorological parameters in the boundary layer (BL). Further, a series of calculations using actual vertical profiles of BC were conducted to determine its impact on RF and heating rate (HR). The results show that the vertical distributions of BC were strongly affected by atmospheric thermodynamics and transport. Moreover. Three main types of profiles were revealed: Type I, Type II, Type III, which correspond to homogenous profiles (HO), negative gradient profiles (NG), and positive gradient profiles (PG), respectively. Types I and II were related to the diurnal evolution of the BL, and Type III was caused by surrounding emissions from high stacks and regional transport. There were no obvious differences in RF calculated for HO profiles and corresponding surface BC concentrations, unlike for NG and PG profiles. RF values calculated using surface BC concentrations led to an overestimate of 13.2 W m^-2 (27.5%, surface) and 18.2 W m^-2 (33.4%, atmosphere) compared to those calculated using actual NG profiles, and an underestimate of approximately 15.4 W m^-2 (35.0%, surface) and 16.1 W m^-2 (29.9%, atmosphere) compared to those calculated using actual PG profiles. In addition, the vertical distributions of BC HR exhibited clear sensitivity to BC profile types. Daytime PG profiles resulted in a positive vertical gradient of HR, which may strengthen temperature inversion at high altitudes. These findings indicate that calculations that use BC surface concentrations and ignore the vertical distribution of BC will lead to substantial uncertainties in the effects of BC on RF and HR.

The changing PM2.5 dynamics of global megacities based on long-term remotely sensed observations

Satellite observations show that the rapid urbanization and emergence of megacities with 10 million or more residents have raised PM2.5 concentrations across the globe during the past few decades. This study examines PM2.5 dynamics for the 33 cities included on the UN list of megacities published in 2018. These megacities were classified into densely (>1500 residents per km²), moderately (300-1500 residents per km²) and sparsely (<300 residents per km²) populated areas to examine the effect of human population density on PM2.5 concentrations in these areas during the period 1998-2016. We found that: (1) the higher population density areas experienced higher PM2.5 concentrations; and (2) the megacities with high PM2.5 concentrations in these areas had higher concentrations than those in the moderately and sparsely populated areas of other megacities as well. The numbers of residents experiencing poor air quality is substantial: approximately 452 and 163 million experienced average annual PM2.5 levels exceeding 10 and 35 μg/m³, respectively in 2016. We also examined PM2.5 trends during the past 18 years and predict that high PM2.5 levels will likely continue in many of these megacities in the future without substantial changes in their economies and/or pollution abatement practices. There will be more megacities in the highest PM2.5 pollution class and the number of megacities in the lowest PM2.5 pollution class will likely not change. Finally, we analyzed how the PM2.5 pollution burden varies geographically and ranked the 33 megacities in terms of PM2.5 pollution in 2016. The most polluted regions are China, India, and South Asia and the least polluted regions are Europe and Japan. None of the 33 megacities currently fall in the WHO's PM2.5 attainment class (<10 μg/m³) while 9 megacities fall into the PM2.5 non-attainment class (>35 μg/m³). In 2016, the least polluted megacity was New York and most polluted megacity was Delhi whose average annual PM2.5 concentration of 110 μg/m³ is nearly three times the WHO's non-attainment threshold.

A framework for PM2.5 constituents-based (including PAHs) emission inventory and source toxicity for priority controls: A case study of Delhi, India

A simple mass-based emission inventory (EI) of PM_2.5 alone does not provide the information on the toxicity of the sources, as not all PM_2.5 particles are equally toxic. The PM_2.5 EI should have three inter-linked versions (i) mass-based, (ii) constituent-based and (iii) source toxicity-based. A framework (applied to the city of Delhi) to prepare constituent and source toxicity-based EI was developed. Mass emission of twelve sources was estimated for 89 constituents. The USEPA's CompTox database was used to estimate threshold concentration for the constituents of PM_2.5 for carcinogenic, chronic and acute health effects. A product of mass emission of the constituent and inverse of its threshold concentration provides an assessment of toxicity of the source. Toxicity was not linearly associated with the mass emission. Road dust, vehicles, coal, dung, wood and coal power plant showed the highest toxicity as presence of metals Cr, Co, Cd, and As make these sources disproportionately more toxic. Among PAHs, Dibenzo (ah)anthracene, showed the highest cancer risk with its 98% emission from vehicles. The soft options replacing wood, crop, coal and dung with LPG, elimination of diesel power generation, burning of waste were simple and effective measures to reduce chronic toxicity by about 40%.

Post-transcriptional air pollution oxidation to the cholesterol biosynthesis pathway promotes pulmonary stress phenotypes

The impact of environmentally-induced chemical changes in RNA has been fairly unexplored. Air pollution induces oxidative modifications such as 8-oxo-7,8-dihydroguanine (8-oxoG) in RNAs of lung cells, which could be associated with premature lung dysfunction. We develop a method for 8-oxoG profiling using immunocapturing and RNA sequencing. We find 42 oxidized transcripts in bronchial epithelial BEAS-2B cells exposed to two air pollution mixtures that recreate urban atmospheres. We show that the FDFT1 transcript in the cholesterol biosynthesis pathway is susceptible to air pollution-induced oxidation. This process leads to decreased transcript and protein expression of FDFT1, and reduced cholesterol synthesis in cells exposed to air pollution. Knockdown of FDFT1 replicates alterations seen in air pollution exposure such as transformed cell size and suppressed cytoskeleton organization. Our results argue of a possible novel biomarker and of an unseen mechanism by which air pollution selectively modifies key metabolic-related transcripts facilitating cell phenotypes in bronchial dysfunction.

Gonzales-Rivera et al. develop a method for 8-oxoG profiling using immunocapturing and RNA sequencing. They show that the FDFT1 transcript is susceptible to air pollution-induced oxidation, after identifying 42 transcripts that are differentially oxidized in bronchial epithelial BEAS-2B cells under air pollution conditions relative to clean air. FDFT1 oxidation affects cholesterol synthesis pathway, leading to phenotypes associated with several lung diseases.

Personal exposure to particulate matter in peri-urban India: predictors and association with ambient concentration at residence

Scalable exposure assessment approaches that capture personal exposure to particles for purposes of epidemiology are currently limited, but valuable, particularly in low-/middle-income countries where sources of personal exposure are often distinct from those of ambient concentrations. We measured 2 × 24-h integrated personal exposure to PM_2.5 and black carbon in two seasons in 402 participants living in peri-urban South India. Means (sd) of PM_2.5 personal exposure were 55.1(82.8) µg/m³ for men and 58.5(58.8) µg/m³ for women; corresponding figures for black carbon were 4.6(7.0) µg/m³ and 6.1(9.6) µg/m³. Most variability in personal exposure was within participant (intra-class correlation ~20%). Personal exposure measurements were not correlated (R_spearman < 0.2) with annual ambient concentration at residence modeled by land-use regression; no subgroup with moderate or good agreement could be identified (weighted kappa ≤ 0.3 in all subgroups). We developed models to predict personal exposure in men and women separately, based on time-invariant characteristics collected at baseline (individual, household, and general time-activity) using forward stepwise model building with mixed models. Models for women included cooking activities and household socio-economic position, while models for men included smoking and occupation. Models performed moderately in terms of between-participant variance explained (38-53%) and correlations between predictions and measurements (R_spearman: 0.30-0.50). More detailed, time-varying time-activity data did not substantially improve the performance of the models. Our results demonstrate the feasibility of predicting personal exposure in support of epidemiological studies investigating long-term particulate matter exposure in settings characterized by solid fuel use and high occupational exposure to particles.

Spatial-Temporal Pattern of Black Carbon (BC) Emission from Biomass Burning and Anthropogenic Sources in New South Wales and the Greater Metropolitan Region of Sydney, Australia

Biomass burnings either due to Hazards Reduction Burnings (HRBs) in late autumn and early winter or bushfires during summer periods in various part of the world (e.g., CA, USA or New South Wales, Australia) emit large amount of gaseous pollutants and aerosols. The emissions, under favourable meteorological conditions, can cause elevated atmospheric particulate concentrations in metropolitan areas and beyond. One of the pollutants of concern is black carbon (BC), which is a component of aerosol particles. BC is harmful to health and acts as a radiative forcing agent in increasing the global warming due to its light absorption properties. Remote sensing data from satellites have becoming increasingly available for research, and these provide rich datasets available on global and local scale as well as in situ aethalometer measurements allow researchers to study the emission and dispersion pattern of BC from anthropogenic and natural sources. The Department of Planning, Industry and Environment (DPIE) in New South Wales (NSW) has installed recently from 2014 to 2019 a total of nine aethalometers to measure BC in its state-wide air quality network to determine the source contribution of BC and PM2.5 (particulate Matter less than 2.5 μm in diameter) in ambient air from biomass burning and anthropogenic combustion sources. This study analysed the characteristics of spatial and temporal patterns of black carbon (BC) in New South Wales and in the Greater Metropolitan Region (GMR) of Sydney, Australia, by using these data sources as well as the trajectory HYSPLIT (Hybrid Single Particle Lagrangian Integrated Trajectory) modelling tool to determine the source of high BC concentration detected at these sites. The emission characteristics of BC in relation to PM2.5 is dependent on the emission source and is analysed using regression analysis of BC with PM2.5 time series at the receptor site for winter and summer periods. The results show that, during the winter, correlation between BC and PM2.5 is found at nearly all sites while little or no correlation is detected during the summer period. Traffic vehicle emission is the main BC emission source identified in the urban areas but was less so in the regional sites where biomass burnings/wood heating is the dominant source in winter. The BC diurnal patterns at all sites were strongly influenced by meteorology.

A methodology for the characterization of portable sensors for air quality measure with the goal of deployment in citizen science

The field of small air quality sensors is of growing interest within the scientific community, especially because this new technology is liable to improve air pollutant monitoring as well as be used for personal exposure quantification. Amongst the myriad existing devices, the performances are highly variable; this is why the sensors must be rigorously assessed before deployment, according to the intended use. This study is included in the Polluscope project; its purpose is to quantify personal exposure to air pollutants by using portable sensors. This paper designs and applies a methodology for the evaluation of portable air quality sensors to eight devices measuring PM, BC, NO₂ and O₃. The dedicated testing protocol includes static ambient air measurements compared with reference instruments, controlled chamber and mobility tests, as well as reproducibility evaluation. Three sensors (AE51, Cairclip and Canarin) were retained to be used for the field campaigns. The reliability of their performances were robustly quantified by using several metrics. These three devices (for a total of 36 units) were deployed to be worn by volunteers for a week. The results show the ability of sensors to discriminate between different environments (i.e., cooking, commuting or in an office). This work demonstrates, first, the ability of the three selected sensors to deliver data reliable enough to enable personal exposure estimations, and second, the robustness of this testing methodology.

Assessment of Daily Personal PM2.5 Exposure Level According to Four Major Activities among Children

Particulate matters less than 2.5 micrometers in diameter (PM2.5), whose concentration has increased in Korea, has a considerable impact on health. From a risk management point of view, there has been interest in understanding the variations in real-time PM2.5 concentrations per activity in different microenvironments. We analyzed personal monitoring data collected from 15 children aged 6 to 11 years engaged in different activities such as commuting in a car, visiting a commercial building, attending an education institute, and resting inside home from October 2018 to March 2019. The fraction of daily mean exposure duration per activity was 72.7 ± 18.7% for resting inside home, 27.2 ± 14.4% for attending an education institute, and 11.5 ± 9.6% and 5.3 ± 5.9% for visiting a commercial building, commuting in a car, respectively. Daily median (interquartile range) PM2.5 exposure amount was 88.9 (55.9–159.7) μg in houses and that in education buildings was 43.3 (22.9–55.6) μg. Real-time PM2.5 exposure levels varied by person and time of day (p-value < 0.05). This study demonstrated that our real-time personal monitoring and data analysis methodologies were effective in detecting polluted microenvironments and provided a potential person-specific management strategy to reduce a person’s exposure level to PM2.5.

Spatio-Temporal Variation Characteristics of PM2.5 in the Beijing-Tianjin-Hebei Region, China, from 2013 to 2018

Air pollution, including particulate matter (PM_2.5) pollution, is extremely harmful to the environment as well as human health. The Beijing–Tianjin–Hebei (BTH) Region has experienced heavy PM_2.5 pollution within China. In this study, a six-year time series (January 2013–December 2018) of PM_2.5 mass concentration data from 102 air quality monitoring stations were studied to understand the spatio-temporal variation characteristics of the BTH region. The average annual PM_2.5 mass concentration in the BTH region decreased from 98.9 μg/m³ in 2013 to 64.9 μg/m³ in 2017. Therefore, China has achieved its Air Pollution Prevention and Control Plan goal of reducing the concentration of fine particulate matter in the BTH region by 25% by 2017. The PM_2.5 pollution in BTH plain areas showed a more significant change than mountains areas, with the highest PM_2.5 mass concentration in winter and the lowest in summer. The results of spatial autocorrelation and cluster analyses showed that the PM_2.5 mass concentration in the BTH region from 2013–2018 showed a significant spatial agglomeration, and that spatial distribution characteristics were high in the south and low in the north. Changes in PM_2.5 mass concentration in the BTH region were affected by both socio-economic factors and meteorological factors. Our results can provide a point of reference for making PM_2.5 pollution control decisions.

Ecological and human health risk assessment of heavy metal contamination in road dust in the National Capital Territory (NCT) of Delhi, India

The present study was carried out to determine the contamination levels of heavy metals in road dust of the National Capital Territory of Delhi (NCT), India and its consequent effect on human and environment. The levels of heavy metals (Pb, Zn, Cu, Cr, Ni, Mn, and Fe) in 9 districts (Z1-Z9) of NCT were monitored and the corresponding human health risk was estimated. District-wise evaluation of heavy metal pollution in the road dust was performed. The mean concentrations of Pb, Zn, Cu, Ni, Cr, Mn, and Fe in the road dust samples over the study area were 164.2 ± 53.2, 200.7 ± 45.3, 99.9 ± 64.8, 24.7 ± 5.7, 57.7 ± 25.9, 241.4 ± 39.8, and 11113.9 ± 1669.7 mg kg^-1, respectively. PLI showed a high pollution load in the monitored nine locations, indicating an alarming condition and the urgent need for immediate remedial actions. Ecological risk assessment depicted that a 74% risk was attributed to Pb. Hazard quotient (HQ) values indicated that ingestion was the major pathway of road dust heavy metal exposure to human beings. Hazard index values showed that there was no probable non-carcinogenic risk of the heavy metals present in the road dust of the area. Children were found vulnerable to the risks of road dust metals. The findings of this study showed the alarming status of heavy metal contamination to road dust in NCT and the associated risk to human health.

Estimation of Emissions at Signalized Intersections Using an Improved MOVES Model with GPS Data

Emissions from the transport sector are responsible for a large proportion of urban air pollution. Scientific and efficient measurements on traffic pollution emissions have already been a vital concern of decision makers in environmental protection. In China or other counties, many high-technology companies, such as Baidu, DiDi, have a large number of real-time GPS traffic data, but such data have not been fully exploited, especially in purpose of estimation of vehicle fuel consumption and emissions. In this paper, the traditional MOVES (Motor Vehicle Emission Simulator) model has been improved by adding the real-time GPS data and tested in representative signalized intersection in Changchun, China. The results showed that adding the GPS data sets in the MOVES model can effectively improve the estimation accuracy of traffic emissions and provide a strong scientific basis for environmental decision-making, planning and management.

In-vehicle PM2.5 personal concentrations in winter during long distance road travel in India

During travel, passengers are exposed to high concentrations of PM which constitute a significant fraction of daily personal exposures. We carried out comprehensive mobile monitoring for a distance of 400km on an Indian National Highway during the winter season to evaluate the PM_2.5 Personal Concentrations (PC) and mass exposure in three traffic microenvironments (public bus, car with AC (Car CW) and car without AC (Car OW)) and to quantify the key factors that influence it. The mean concentrations were highest inside Car OW (175.3±142.7μgm^-3) followed by bus (134.0±113.9μgm^-3) and lowest in Car CW (78.8±37.1μgm^-3). PC during in-city highway sections were greater than out-city highway sections during Bus and Car OW journeys. PC were higher during morning than evening journeys in Bus and Car OW. Mean PC in different seating positions in Bus followed the trend: middle>rear>front. Results of the Linear Mixed-Effects Models (LMM) indicated that journey timings were the significant predictors of PC for Bus and Car OW. The exposures per unit time followed trend: Car OW>Bus>Car CW. Total mass of inhaled exposures however followed a different trend: Bus>Car OW>Car CW, because Bus needed longer duration to cover the entire distance. Car CW users experienced both the least PC and mass exposures. We estimated that the road repairing works contributed ~22% in Bus and Car OW, and ~12% in Car CW increment in mass exposures. These findings indicate that management of exposures needs to consider mass exposures in addition to PC, for curtailing the adverse health effects relating to long distance journeys. Highway authorities should focus on early completion of construction and repairing activities to reduce exposures to passengers.

Dependence of urban air pollutants on morning/evening peak hours and seasons

Traffic emission is a major source of air pollution in urban cities of developing world. This paper shows dependence of traffic-related air pollutants in urban cities on morning/evening peak hours and winter/summer seasons. This research also shows the meteorological impact, such as temperature (T), relative humidity (RH), and wind speed (WS), on traffic-related air pollutants in urban cites. Based on the research output, the elevated level of PM concentration was observed between 1.8 and 6.7 times at all nearby roadway locations compared with background (IIT [ISM] campus). We have found 2.3, 2.4, 2.6 (morning) and 2.0, 2.1, and 2.1 (evening) times higher average PM₁₀, PM_2.5, and PM₁ concentrations, respectively, in the winter than summer monitoring periods across all locations, due to the stable boundary layer, lower mixing height, and lower friction velocity. It is indicated that urban meteorology plays a crucial role in increasing or decreasing exposed pollutant concentrations in various microenvironments. The analysis of PM_2.5/PM₁₀ ratios was lower during whole campaign due to higher contribution of coarser particles generated by vehicles. During winter and summer seasons, 0.57 and 0.33 was observed, respectively. It is indicated that 57% and 33% of PM₁₀ makes up PM_2.5 particle, respectively. PM concentrations have showed a negative linear relationship with T and WS and positive relationship with RH in winter/summer seasons. Therefore, traffic and meteorology play a big role to increase or decrease in traffic-related air pollutants in urban air quality.

Personal exposure to PM2.5 in Chinese rural households in the Yangtze River Delta

High levels of PM_2.5 exposure and associated health risks are of great concern in rural China. For this study, we used portable PM_2.5 monitors for monitoring concentrations online, recorded personal time-activity patterns, and analyzed the contribution from different microenvironments in rural areas of the Yangtze River Delta, China. The daily exposure levels of rural participants were 66 μg/m³ (SD 40) in winter and 65 μg/m³ (SD 16) in summer. Indoor exposure levels were usually higher than outdoor levels. The exposure levels during cooking in rural kitchens were 140 μg/m³ (SD 116) in winter and 121 μg/m³ (SD 70) in summer, the highest in all microenvironments. Winter and summer values were 252 μg/m³ (SD 103) and 204 μg/m³ (SD 105), respectively, for rural people using biomass for fuel, much higher than those for rural people using LPG and electricity. By combining PM_2.5 concentrations and time spent in different microenvironments, we found that 92% (winter) and 85% (summer) of personal exposure to PM_2.5 in rural areas was attributable to indoor microenvironments, of which kitchens accounted for 24% and 27%, respectively. Consequently, more effective policies and measures are needed to replace biomass fuel with LPG or electricity, which would benefit the health of the rural population in China.

Modeling the Impact of an Indoor Air Filter on Air Pollution Exposure Reduction and Associated Mortality in Urban Delhi Household

Indoor exposure to fine particulate matter (PM_2.5) is a prominent health concern. However, few studies have examined the effectiveness of long-term use of indoor air filters for reduction of PM_2.5 exposure and associated decrease in adverse health impacts in urban India. We conducted 20 simulations of yearlong personal exposure to PM_2.5 in urban Delhi using the National Institute of Standards and Technology's CONTAM program (NIST, Gaithersburg, MD, USA). Simulation scenarios were developed to examine different air filter efficiencies, use schedules, and the influence of a smoker at home. We quantified associated mortality reductions with Household Air Pollution Intervention Tool (HAPIT, University of California, Berkeley, CA, USA). Without an air filter, we estimated an annual mean PM_2.5 personal exposure of 103 µg/m³ (95% Confidence Interval (CI): 93, 112) and 137 µg/m³ (95% CI: 125, 149) for households without and with a smoker, respectively. All day use of a high-efficiency particle air (HEPA) filter would reduce personal PM_2.5 exposure to 29 µg/m³ and 30 µg/m³, respectively. The reduced personal PM_2.5 exposure from air filter use is associated with 8-37% reduction in mortality attributable to PM_2.5 pollution in Delhi. The findings of this study indicate that air filter may provide significant improvements in indoor air quality and result in health benefits.

Estimation of personal exposure to fine particles (PM2.5) of ambient origin for healthy adults in Hong Kong

Personal exposure and ambient fine particles (PM_2.5) measurements for 13 adult subjects (ages 19-57) were conducted in Hong Kong between April 2014 and June 2015. Six to 21 personal samples (mean = 19) per subject were obtained throughout the study period. Samples were analyzed for mass by gravimetric analysis, and 19 elements (from Na to Pb) were analyzed using X-Ray Fluorescence. Higher subject-specific correlations between personal and ambient sulfur (r_s = 0.92; p < 0.001) were found as compared to PM_2.5 mass (r_s = 0.79; p < 0.001) and other elements (0.06 < r_s < 0.86). Personal vs. ambient sulfur regression yielded an average exposure factor (F_pex) of 0.73 ± 0.02, supporting the use of sulfur as a surrogate to estimate personal exposure to PM_2.5 of ambient origin (E_a). E_a accounted for 41-82% and 57-73% of total personal PM_2.5 exposures (P) by season and by subject, respectively. The importance of both E_a and non-ambient exposures (E_na, 11.2 ± 5.6 μg/m³; 32.5 ± 10.9%) are noted. Mixed-effects models were applied to estimate the relationships between ambient PM_2.5 concentrations and their corresponding exposure variables (E_a, P). Higher correlations for E_a (0.90; p < 0.001) than for P (0.58; p < 0.01) were found. A calibration coefficient < 1 suggests an attenuation of 22% (ranging 16-28%) of the true effect estimates when using average ambient concentrations at central monitoring stations as surrogates for E_a. Stationary ambient data can be used to assess population exposure only if PM exposure is dominated by E_a.

When, Where, and What? Characterizing Personal PM2.5 Exposure in Periurban India by Integrating GPS, Wearable Camera, and Ambient and Personal Monitoring Data

Evidence identifying factors that influence personal exposure to air pollutants in low- and middle-income countries is scarce. Our objective was to identify the relative contribution of the time of the day ( when?), location ( where?), and individuals' activities ( what?) to PM_2.5 personal exposure in periurban South India. We conducted a panel study in which 50 participants were monitored in up to six 24-h sessions ( n = 227). We integrated data from multiple sources: continuous personal and ambient PM_2.5 concentrations; questionnaire, GPS, and wearable camera data; and modeled long-term exposure at residence. Mean 24-h personal exposure was 43.8 μg/m³ (SD 24.6) for men and 39.7 μg/m³ (SD 12.0) for women. Temporal patterns in exposure varied between women (peak exposure in the morning) and men (more exposed throughout the rest of the day). Most exposure occurred at home, 67% for men and 89% for women, which was proportional to the time spent in this location. Ambient daily PM_2.5 was an important predictor of 24-h personal exposure for both genders. Among men, activities predictive of higher hourly average exposure included presence near food preparation, in the kitchen, in the vicinity of smoking, or in industry. For women, predictors of exposure were largely related to cooking.

Exposure to air pollutants in Vietnam: Assessing potential risk for tourists

Tourism can form an important component of a nation's GDP, and Vietnam is among the most visited countries in Southeast Asia. Most studies on personal exposure focus on the general population, or occupational cohorts with exposure to specific pollutants. However, short-term exposure to air pollutants while visiting regions with high levels of air pollution can lead to acute health effects. A personal exposure study was conducted across three cities in Vietnam to estimate exposure to particulate matter (PM_2.5) and black carbon for tourists. Measurements were conducted during the wet season in 2014 in Ho Chi Minh City, Da Lat and Nha Trang using portable instrumentation. Average 24-hr PM_2.5 and BC exposures were estimated as 18.9±9.24 and 3.41±1.33μg/m³ and among the three cities, Ho Chi Minh was found to have the highest PM_2.5 concentrations. Environmental tobacco smoke, commuting and street food stands were found to contribute to highest levels of exposure to PM_2.5 and BC across all cities.

Wearable camera-derived microenvironments in relation to personal exposure to PM2.5

Data regarding which microenvironments drive exposure to air pollution in low and middle income countries are scarce. Our objective was to identify sources of time-resolved personal PM_2.5 exposure in peri-urban India using wearable camera-derived microenvironmental information. We conducted a panel study with up to 6 repeated non-consecutive 24 h measurements on 45 participants (186 participant-days). Camera images were manually annotated to derive visual concepts indicative of microenvironments and activities. Men had slightly higher daily mean PM_2.5 exposure (43 μg/m³) compared to women (39 μg/m³). Cameras helped identify that men also had higher exposures when near a biomass cooking unit (mean (sd) μg/m³: 119 (383) for men vs 83 (196) for women) and presence in the kitchen (133 (311) for men vs 48 (94) for women). Visual concepts associated in regression analysis with higher 5-minute PM_2.5 for both sexes included: smoking (+93% (95% confidence interval: 63%, 129%) in men, +29% (95% CI: 2%, 63%) in women), biomass cooking unit (+57% (95% CI: 28%, 93%) in men, +69% (95% CI: 48%, 93%) in women), visible flame or smoke (+90% (95% CI: 48%, 144%) in men, +39% (95% CI: 6%, 83%) in women), and presence in the kitchen (+49% (95% CI: 27%, 75%) in men, +14% (95% CI: 7%, 20%) in women). Our results indicate wearable cameras can provide objective, high time-resolution microenvironmental data useful for identifying peak exposures and providing insights not evident using standard self-reported time-activity.

A comparison of personal exposure to air pollutants in different travel modes on national highways in India

People often travel a long distance on highways to the nearest city for professional/business activities. However, relatively few publications on passenger exposure to pollutants on highways in India or elsewhere are available. The aim of this study was to examine the contribution of different travel modes to passengers' pollutant exposure for a long distance travel on a national highway in India. We measured PM_2.5 and CO exposure levels of the passengers over 200km on a national highway using two portable air monitors, EVM-7 and EPAM-5000. Personal concentration exposures and per min-, per hour-, per trip- and round trip mass exposures for three travel modes were calculated for 9 trips. Association between pollutants and weather variables were evaluated using levels Spearman correlation. ANOVA was carried out to evaluate the influence of travel mode, the timing of trips, temperature and RH on personal exposures. On an average, PM_2.5 personal concentration exposure levels were highest in the car (85.41±61.85μgm^-3), followed by the bus (75.08±55.39μgm^-3) and lowest in the car (ac) (54.43±34.09μgm^-3). In contrast, CO personal exposure was highest in the car (ac) (1.81±1.3ppm). Travel mode explained the highest variability for CO (18.1%), CO₂ (9.9%), PM_2.5 (1.2%) exposures. In-city mass exposures were higher than trip averages; PM_2.5:1.21-1.22, 1.13-1.19 and 1.03-1.28 times; CO: 1.20-1.57, 1.37-2.10 and 1.76-2.22 times for bus, car and car (ac) respectively. Traveling by car (ac) results in the lowest PM_2.5 exposures, although it exposes the passenger to high CO level. Avoiding national highways passing through cities can reduce up to 25% PM_2.5 and 50% CO mass exposures. This information can be useful for increasing environmental awareness among the passengers and for framing better pollution control strategies on highways.

Spatiotemporal Variations and Driving Factors of Air Pollution in China

In recent years, severe and persistent air pollution episodes in China have drawn wide public concern. Based on ground monitoring air quality data collected in 2015 in Chinese cities above the prefectural level, this study identifies the spatiotemporal variations of air pollution and its associated driving factors in China using descriptive statistics and geographical detector methods. The results show that the average air pollution ratio and continuous air pollution ratio across Chinese cities in 2015 were 23.1 ± 16.9% and 16.2 ± 14.8%. The highest levels of air pollution ratio and continuous air pollution ratio were observed in northern China, especially in the Bohai Rim region and Xinjiang province, and the lowest levels were found in southern China. The average and maximum levels of continuous air pollution show distinct spatial variations when compared with those of the continuous air pollution ratio. Monthly changes in both air pollution ratio and continuous air pollution ratio have a U-shaped variation, indicating that the highest levels of air pollution occurred in winter and the lowest levels happened in summer. The results of the geographical detector model further reveal that the effect intensity of natural factors on the spatial disparity of the air pollution ratio is greater than that of human-related factors. Specifically, among natural factors, the annual average temperature, land relief, and relative humidity have the greatest and most significant negative effects on the air pollution ratio, whereas human factors such as population density, the number of vehicles, and Gross Domestic Product (GDP) witness the strongest and most significant positive effects on air pollution ratio.

PM2.5, Population Exposure and Economic Effects in Urban Agglomerations of China Using Ground-Based Monitoring Data

This paper adopts the PM_2.5 concentration data obtained from 1497 station-based monitoring sites, population and gross domestic product (GDP) census data, revealing population exposure and economic effects of PM_2.5 in four typical urban agglomerations of China, i.e., Beijing-Tianjin-Hebei (BTH), the Yangtze River delta (YRD), the Pearl River delta (PRD), and Chengdu-Chongqing (CC). The Cokriging interpolation method was used to estimate the PM_2.5 concentration from station-level to grid-level. Next, an evaluation was conducted mainly at the grid-level with a cell size of 1 × 1 km, assisted by the urban agglomeration scale. Criteria including the population-weighted mean, the cumulative percent distribution and the correlation coefficient were applied in our evaluation. The results showed that the spatial pattern of population exposure in BTH was consistent with that of PM_2.5 concentration, as well as changes in elevation. The topography was also an important factor in the accumulation of PM_2.5 in CC. Moreover, the most polluted urban agglomeration based on the population-weighted mean was BTH, while the least was PRD. In terms of the cumulative percent distribution, only 0.51% of the population who lived in the four urban agglomerations, and 2.33% of the GDP that was produced in the four urban agglomerations, were associated with an annual PM_2.5 concentration smaller than the Chinese National Ambient Air Quality Standard of 35 µg/m³. This indicates that the majority of people live in the high air polluted areas, and economic development contributes to air pollution. Our results are supported by the high correlation between population exposure and the corresponding GDP in each urban agglomeration.