Individual and population intake fractions of diesel particulate matter (DPM) in bus stop microenvironments

Examining the relationship between land use and childhood leukemia and lymphoma in Tehran

We conducted a hospital-based case-control study to explore the association between proximity to various land use types and childhood leukemia and lymphoma. This research involved 428 cases of childhood leukemia and lymphoma (2016-2021), along with a control group of 428 children aged 1-15 in Tehran. We analyzed the risk of childhood cancer associated with land use by employing logistic regression adjusted for confounding factors such as parental smoking and family history. The odds ratio (OR) for children with leukemia and lymphoma residing within 100 m of the nearest highway was 1.87 (95% CI = 1.00-3.49) and 1.71 (95% CI = 1.00-2.93), respectively, in comparison to those living at a distance of 1000 m or more from a highway. The OR for leukemia with exposure to petrol stations within 100 m was 2.15 (95% CI = 1.00-4.63), and for lymphoma it was 1.09 (95% CI = 0.47-2.50). A significant association was observed near power lines (OR = 3.05; 95% CI = 0.97-9.55) within < 100 m for leukemia. However, no significant association was observed between power lines and the incidence of childhood lymphoma. There was no association between bus stations, major road class 2, and the incidence of childhood leukemia and lymphoma. In conclusion, our results suggest a possible association between the incidence of childhood leukemia and proximity to different urban land uses (i.e., highways and petrol stations). This study is the first step in understanding how urban land use affects childhood leukemia and lymphoma in Tehran. However, comprehensive studies considering individual-level data and specific pollutants are essential for a more nuanced understanding of these associations.

Relative contributions of ambient air and internal sources to multiple air pollutants in public transportation modes

Commuters are often exposed to relatively high air pollutant concentrations in public transport microenvironments (TMEs) because of their proximity to emission sources. Previous studies have mainly focused on assessing the concentrations of air pollutants in TMEs, but few studies have distinguished between the contributions of ambient air and internal sources to the exposure of commuters to air pollutants. The main objective of this study was to quantify the contributions of ambient air and internal sources to the measured particulate matter and gaseous pollutant concentrations in selected TMEs in Hong Kong, a high-rise, high-density city in Asia. A sampling campaign was conducted to measure air pollutant concentrations in TMEs in Hong Kong in July and November 2018 using portable air quality monitors. We measured the concentrations of each pollutant in different TMEs and quantified the infiltration of particulate matter into these TMEs. The double-decker bus had the lowest particulate matter concentrations (mean PM1, PM2.5, and PM10 concentrations of 5.1, 9.5, and 13 μg/m3, respectively), but higher concentrations of CO (0.9 ppm), NO (422 ppb), and NO2 (100 ppb). For all the TMEs, about half of the PM2.5 were PM1 particles. The Mass Transit Railway (MTR) subway system had a PM2.5/PM10 ratio of about 0.90, whereas the PM2.5/PM10 ratio was about 0.60-0.70 for the other TMEs. The MTR had infiltration factor estimates <0.4 for particulate matter, lower than those of the double-decker bus and minibus. The MTR had the highest contribution from internal sources (mean PM1, PM2.5, and PM10 concentrations of 4.6, 13.4, and 15.8 μg/m3, respectively). This study will help citizens to plan commuting routes to reduce their exposure to air pollution and help policy-makers to prioritize effective exposure reduction strategies.

Study on PM diffusion and distribution of trackless rubber-tyred vehicle under different driving conditions in underground coal mining environment

Particulate matter (PM) is one of the most harmful exhaust pollutants to human health. In this study, the PM diffusion and distribution emitted by trackless rubber-tyred vehicle under different driving conditions in coal mine were analyzed with numerical simulations and field measurements. The results show that when the vehicle velocity was constant, the PM concentration of the trackless rubber-tyred vehicle decreased with increasing distance from the exhaust pipe orifice. In addition, the proportion of PM with a concentration below 10 mg/m3 was the highest owing to the influences of diffusion and airflow dilution. However, when the diffusion distance is less than 3 m, the PM concentration far exceeds the occupational exposure limit (10 mg/m3). In this case, underground personnel should stay away from the area near and along the exhaust pipe as far as possible. With increasing vehicle velocity, the PM concentration gradient at a diffusion distance of 0-6 m showed the most significant slope. Besides, the concentration fluctuation of PM was the largest and relatively high when the diffusion distance was 5-15 m. Therefore, the area 15 m from the exhaust gas pipe opening of the trackless rubber-tyred vehicle should be controlled. In addition, the relative errors between the measured and numerical simulation results were mostly less than 10%, which proved that the numerical simulation results were reliable.

Emissions of air pollutants from non-road construction machinery in Beijing from 2015 to 2019

Construction machinery (CM) is considered to be a significant source of air pollution. The estimation of emissions from CM is essential for policy-makers to control air pollution and reduce carbon emissions. In this study, air pollutant emissions from CM with four emissions standards (Beijing I-IV) in Beijing from 2015 to 2019 were estimated by combining data from the Non-road Mobile Source Emissions Inventory Compiled Technical Guidelines, Motor Vehicle Emission Simulator (MOVES) and actual measurements. Taking an example for 2019, emissions of hydrocarbons (HCs), carbon monoxide (CO), nitrogen oxides (NO_x), particulate matter (PM) and carbon dioxide (CO₂) were estimated to be 4.80 Gg, 16.51 Gg, 27.77 Gg, 1.35 Gg and 5.09 Tg, respectively, representing annual mean decreases of 13.2%, 13.1%, 10.8%, 15.2% and 3.5%, respectively, over the five-year period. Tongzhou, Shunyi and Changping Districts contributed 53-67% of total CM emissions in 2019. Among the ten types of CM considered, loaders were the largest contributors to total emissions, accounting for 41-54% of total CM emissions in Beijing from 2015 to 2019. Machinery with a mean power above 75 kW accounted for the largest share (67-78%) of total CM emissions in Beijing from 2015 to 2019. Our results contribute to the limited data of estimated CM emissions and can help develop control strategies to improve air quality and alleviate climate change.

Quantifying the Impact of Alternative Bus Stop Platforms on Vehicle Emissions and Individual Pollution Exposure at Bus Stops

Due to stop-and-go events, bus stops are often treated as "hot spots" for air pollution. The design of bus stops should be optimized to reduce emissions and exposure for transit commuters. The objective of this study was to analyze the impact of bus stop platform types on vehicle emissions and individual pollution exposure. Second-by-second emissions data were first collected from one bus using a portable emission measurement system (PEMS). Microscopic traffic simulation was then used to estimate overall traffic emissions under six scenarios with different bus stop settings. Numerical simulation of pollutant dispersion was also conducted to calculate individual pollution exposure at bus stops. The results of PEMS tests showed no significant differences between bus emissions generated near two different types of stops. However, the effect of platform types on overall traffic emissions was revealed using traffic simulation. The results demonstrated that bus bays reduced the emissions of other heavy-duty vehicles. However, bus bays were not always effective during rush hours. The study also highlighted the importance of the location of bus stops, the number of bus lines, and the length of the platform, in addition to dynamic characteristics of traffic flows in the design of bus stop platforms. Bus stop platforms also affected individuals' exposure due to the changes in the pollutant flow field. The passenger's exposure at one bus stop was influenced by both the platform type and standing location. Results suggested that in a condition with a wind direction perpendicular to the bus stop shelter, the total exposure level to CO was lower at the bus bay stop if a passenger stood at the upstream of the station platform. However, the exposure was less at the downstream of the curbside bus stop.

Traffic-related organic and inorganic air pollution and risk of development of childhood asthma: A meta-analysis

The effect of early childhood exposure to traffic-related air pollution (TRAP) on the development of asthma remains unclear. The aim of this study was to clarify potential associations between TRAP (fine particulate matter, PM_2.5; nitrogen dioxide, NO₂; Benzene and total volatile organic pollutants, TVOCs) and childhood asthma by integrating the results from previous studies. Elsevier, LISTA (EBSCO) and Web of Science databases were searched for relevant studies. Adjusted odds ratio (OR) with corresponding 95% confidence interval (CI) for the association between traffic-related air pollutants and health effects were recovered from individual studies and summary effect estimates (meta-OR) were generated in Review Manager 5.3. Twenty-seven studies were included in the meta-analysis and the results showed that TRAP increased the risk of asthma among children: PM_2.5 (meta-OR = 1.07, 95% CI:1.00-1.13), NO₂ (meta-OR = 1.11, 95% CI:1.06-1.17), Benzene (meta-OR: 1.21, 95% CI:1.13-1.29) and TVOC (meta-OR:1.06, 95% CI: 1.03-1.10). Sensitivity analyses supported these findings. In addition, regional analysis showed that ORs of inorganic TRAP (PM_2.5 and NO₂) on the risk of childhood asthma were significantly higher in Asia than those in Europe and North America. Subsequent research should focus on the association between organic pollutants in TRAP and childhood asthma. Furthermore, the disentanglement between TRAP and other pollutant sources may be investigated in future studies.

Changes in extrapulmonary organs and serum enzyme biomarkers after chronic exposure to Buenos Aires air pollution

Urban air pollution is a serious environmental problem in developing countries worldwide, and health is a pressing issue in the megacities in Latin America. Buenos Aires is a megacity with an estimated moderate Air Quality Index ranging from 42 to 74 μg/m³. Exposure to Urban Air Particles from Buenos Aires (UAP-BA) induces morphological and physiological respiratory alterations; nevertheless, no studies on extrapulmonary organs have been performed. The aim of the present study was to explore the health effects of chronic exposure to UAP-BA (1, 6, 9, and 12 months) on the liver, heart, and serum risk biomarkers. BALB/c mice were exposed to UAP-BA or filtered air (FA) in inhalation chambers, and liver and heart histopathology, oxidative metabolism (superoxide dismutase, SOD; catalase, CAT; lipoperoxidation, TBARS), amino transaminases (AST, ALT) as serum risk biomarkers, alkaline phosphatase (ALP), paraxonase-1 (PON-1), and lipoprotein-associated phospholipase A2 (Lp-PLA2) were evaluated. Chronic exposure to real levels of UAP in Buenos Aires led to alterations in extrapulmonary organs associated with inflammation and oxidative imbalance and to changes in liver and heart risk biomarkers. Our results may reflect the impact of the persistent air pollution in Buenos Aires on individuals living in this Latin American megacity.

Integrated impacts of turbulent mixing and NOX-O3 photochemistry on reactive pollutant dispersion and intake fraction in shallow and deep street canyons

We employ computational fluid dynamics (CFD) simulations with NO-NO₂-O₃ chemistry to investigate the impacts of aspect ratios (H/W = 1,3,5), elevated-building design, wind catchers and two background ozone concentrations ([O₃]_b = 100/20 ppb) on reactive pollutant dispersion in two-dimensional (2D) street canyons. Personal intake fraction of NO₂ (P_IF_NO2) and its spatial mean value in entire street (i.e. street intake fraction <P_IF_NO2>) are calculated to quantify pollutant exposure in near-road buildings. Chemical reaction contribution of NO₂ exposure (CRC_{<P_IF>}), O₃ depletion rate (d_ozone) and photostationary state defect (δ_ps) are used to analyze the interplay of turbulent and chemical processes. As H/W increases from 1, 3 to 5 with [O₃]_b = 100 ppb, the flow pattern turns from single-main-vortex structure to two-counter-rotating-vortex structure, and pedestrian-level velocity becomes 1-2 orders smaller. The high-d_ozone regions and low-|δ_ps| regions get larger with more complete chemical reactions. Consequently, passive <P_IF_NO2> rises 1 order (4.09-5.71 ppm to 41.76 ppm), but reactive <P_IF_NO2> only increases several times (17.80-21.28 ppm to 58.50 ppm) and the contribution of chemistry (CRC_{<P_IF>}) decreases with higher H/W. Thus, chemistry raises <P_IF_NO2 > more effectively in shallow street canyons (H/W = 1-3). In deep street canyons (H/W = 5), elevated-building design and wind catchers destroy two-counter-rotating-vortex structure, improve street ventilation and reduce passive <P_IF_NO2> by 2 and 1 orders (41.76 ppm to 0.38-5.16 ppm), however they only reduce reactive <P_IF_NO2> by about 97.5% and 75% (58.50 ppm to 1.61-14.48 ppm). Such building techniques induce lower O₃ depletion rate but greater chemical contribution. Finally, raising [O₃]_b from 20 to 100 ppb causes greater O₃ depletion rate and chemical contribution and produces larger <P_IF_NO2>. For deep street canyons, the impact of higher [O₃]_b on <P_IF_NO2> is weaker than that in shallow street canyons, while it becomes stronger when fixing elevated-building design and wind catchers. This study provides some innovative findings on reactive pollutant exposure in 2D street canyons and offers effective CFD methodologies to evaluate pollutant exposure with more complicated chemistry and urban configurations.

Pollutant gas and particulate material emissions in ethanol production in Brazil: social and environmental impacts

The replacement of fossil-based fuels by renewable fuels (biofuels) was proposed in the IPCC report, as an alternative to reduce greenhouse gas emission and reach out to a low-carbon economy. On this perspective, the Brazilian government had implemented a renewable energy program based on the use of ethanol in the transport sector. This work evaluates the scenario of pollutant gas emissions and particulate material that comes from the biomass burning process involved in ethanol production cycle, in the city of Campos dos Goytacazes, Brazil. The gases and particulate material emitted by sugarcane and bagasse burning processes-the last one in energy co-generation mills-were analyzed. A laboratory-controlled burning of both samples was realized in an oven with temperature ramp from 250 to 400 °C, at a regular rate of 50 °C. The gas samples were collected directly from the oven's exhaust pipe. The particulates obtained were the residual material taken out of the burned samples: a powder with the aspect of soot. A photoacoustic spectroscopy system coupled with quantum cascade laser and electrochemical analyzers was used to measure the emission of polluting gases such as N₂O, CO₂, CO, NO_x (NO, NO₂), and SO₂ in ppmv range. Fluorescent X-ray spectrometry was applied to evaluate the chemical composition of particulate material, enabling the identification of elements such as Si, Al, Ca, K, Fe, S, P, Ti, Mn, Cu, Zn, Sc, V, Cu, and Sr.

Particulate Matter Exposure of Passengers at Bus Stations: A Review

This review clarifies particulate matter (PM) pollution, including its levels, the factors affecting its distribution, and its health effects on passengers waiting at bus stations. The usual factors affecting the characteristics and composition of PM include industrial emissions and meteorological factors (temperature, humidity, wind speed, rain volume) as well as bus-station-related factors such as fuel combustion in vehicles, wear of vehicle components, cigarette smoking, and vehicle flow. Several studies have proven that bus stops can accumulate high PM levels, thereby elevating passengers' exposure to PM while waiting at bus stations, and leading to dire health outcomes such as cardiovascular disease (CVD), respiratory effects, and diabetes. In order to accurately predict PM pollution, an artificial neural network (ANN) and adaptive neuro-fuzzy inference systems (ANFIS) have been developed. ANN is a data modeling method of proven effectiveness in solving complex problems in the fields of alignment, prediction, and classification, while the ANFIS model has several advantages including non-requirement of a mathematical model, simulation of human thinking, and simple interpretation of results compared with other predictive methods.

The health impacts of weekday traffic: A health risk assessment of PM2.5 emissions during congested periods

Little work has accounted for congestion, using data that reflects driving patterns, traffic volume, and speed, to examine the association between traffic emissions and human health. In this study, we performed a health risk assessment of PM_2.5 emissions during congestion periods in the Greater Toronto and Hamilton Area (GTHA), Canada. Specifically, we used a micro-level approach that combines the Stochastic User Equilibrium Traffic Assignment Algorithm with a MOVES emission model to estimate emissions considering congestion conditions. Subsequently, we applied a concentration-response function to estimate PM_2.5-related mortality, and the associated health costs. Our results suggest that traffic congestion has a substantial impact on human health and the economy in the GTHA, especially at the most congested period (7:00am). Considering daily mortality, our results showed an impact of 206 (boundary test 95%: 116; 297) and 119 (boundary test 95%: 67; 171) deaths per year (all-cause and cardiovascular mortality, respectively). The economic impact from daily mortality is approximately $1.3 billion (boundary test 95%: 0.8; 1.9), and $778 million (boundary test 95%: 478; 981), for all-cause and cardiovascular mortality, respectively. Our study can guide reliable projections of transportation and air pollution levels, improving the capability of the medical community to prepare for future trends.