Modeling the dispersion of traffic-derived black carbon emissions into hilly terrain.

This study examines hilly terrain's effect on black carbon (BC) dispersion. The apportionment of distinct sources obtained by a two-component mixing model (Aethalometer: AE-33) using improved radiative transfer equations showed the dominance of traffic-derived black carbon (BCFF) emissions in the study region. The AERMOD was used to model BC emissions from moving traffic as a line source and parking lot as area source using observational and WRF-processed meteorology for the winter (January to March 2020). The model results showed that the BC levels substantially vary with local meteorological conditions, traffic volume, and composition. The hilly terrain obstructs the winds and develops a negative pressure loading to a vacuum on the other side of the hills, which promotes the accumulation of emissions, causing high BC concentrations. The pockets of higher concentration were seen at the locations where steep slopes were associated with low winds (<1 m s-1) and hill fogs. The AERMOD model, after statistical evaluation against the observational datasets, has been applied to study the reduction in BCFF concentrations due to the implementation of Indian emission norms as mitigation measures, i.e., BS-IV (equivalent to Euro 4) and BS-VI (equivalent to Euro 6). It was found that the BCFF concentrations for BS-IV and BS-VI reduced by 35% and 75%, respectively. The model was also used to study the contribution of the different vehicular categories to BC concentration.

Urban workers' cardiovascular health due to exposure to traffic-originated PM2.5 and noise pollution in different microenvironments.

The cardiovascular health of the people in urbanised cities is linked to traffic air, and noise pollution. This study investigated the cardiovascular health of people working in two microenvironments such as street (vendors) and workplace (office workers) whose blood pressure (BP) and heart rate (HR) might be affected due to regular exposure to PM2.5 and traffic noise. The PM2.5 and noise levels measurements, face-to-face questionnaire survey and health check-ups were carried out on working days from 10 A.M. to 8 P.M. in Jan-Dec 2019. The data was analysed by various statistical approaches in which the link between the traffic-borne PM2.5 and noise level at 1/3rd octave frequencies has been established with the participants' BP and HR considering the demographic, socio-contextual, habitual and annoyance perception factors. The median measure of PM2.5 and noise levels violated the WHO and NAAQS limits, i.e. 106.67 µg/m3 at street level and 33.33 µg/m3 at office indoor; and 71.35 dB (A) at the street and 65.78 dB (A) at office indoor. The results further showed that the workers working in traffic corridors had abnormally high BP and HR. The systolic BP, diastolic BP and HR values were higher than normal in male workers than female workers. The influence of low noise spectrum (50-630 Hz) was mostly observed. Therefore, the combined effect of PM2.5 > 50 µg/m3 and noise spectrum (63 and 100 Hz) > 30 dB (A) significantly affect office workers' health in traffic corridors. The hearing aids, breathing troubles in the traffic corridor and annoyance perception also influenced the BP and HR of the respondents. The results are indicative and might be helpful in urban environmental planning to improve the well-being of urban traffic corridor users.

Piperine Attenuates Cigarette Smoke-Induced Oxidative Stress, Lung Inflammation, and Epithelial-Mesenchymal Transition by Modulating the SIRT1/Nrf2 Axis.

Piperine (PIP) is a major phytoconstituent in black pepper which is responsible for various pharmacological actions such as anti-inflammatory, antioxidant, and antitumor activity. To investigate the effects and mechanisms of PIP on cigarette smoke (CS)-induced lung pathology using both in-vitro and in-vivo models. BEAS-2B and A549 cells were exposed to CS extract (CSE) for 48 h; BALB/c mice were exposed to CS (9 cigarettes/day, 4 days) to induce features of airway disease. PIP at doses of (0.25, 1.25, and 6.25 µM, in vitro; 1 and 10 mg/kg, in vivo, i.n) and DEX (1 µM, in vitro; 1 mg/kg, in vivo, i.n) were used to assess cytotoxicity, oxidative stress, epithelial−mesenchymal transition (EMT), Sirtuin1 (SIRT1), inflammation-related cellular signaling, and lung function. PIP treatment protects cells from CSE-induced lung epithelial cell death. PIP treatment restores the epithelial marker (p < 0.05) and decreases the mesenchymal, inflammatory markers (p < 0.05) in both in vitro and in vivo models. The PIP treatment improves the altered lung function (p < 0.05) in mice induced by CS exposure. Mechanistically, PIP treatment modulates SIRT1 thereby reducing the inflammatory markers such as IL-1ß, IL-6 and TNF-α (p < 0.05) and enhancing the epigenetic marker HDAC2 (p < 0.05) and antioxidant marker Nrf2 (p < 0.05) expressions. Thus, PIP alleviates pulmonary inflammation by modulating the SIRT1-mediated inflammatory cascade, inhibits EMT, and activates Nrf2 signaling.

Effects of intranasal azithromycin on features of cigarette smoke-induced lung inflammation.

Airflow limitation in chronic obstructive pulmonary disease (COPD) is the result of exaggerated airway fibrosis and obliteration of the small airways due to persistent inflammation, and an impaired anti-oxidant response. EMT has been implicated as an active signalling process in cigarette smoke (CS)-induced lung pathology, and macrolide Azithromycin (AZT) use has gained interest in treating COPD. Here, we tested effectiveness of intra-nasal AZT alone and in combination with dexamethasone (DEX) on CS-induced acute lung inflammation. Human alveolar epithelial cells (A549) were treated with CS extract (CSE) for 48 h, and male Balb/c mice were exposed to CS (3 cigarettes-3 times/day) for 4 days. The effects of AZT alone (0.25 and 1.25 µM, in vitro; 0.5 and 5 mg/kg, in vivo) or in combination with DEX (1 µM, in vitro; 1 mg/kg, in vivo) on CS-induced cellular cytotoxicity, oxidative stress, inflammation, and lung function were assessed. AZT alone and in combination with DEX significantly inhibited the CS (E)-induced expression of mesenchymal protein markers and the regulatory protein ß-catenin. Furthermore, AZT by itself or in combination with DEX significantly suppressed CS-induced expression of the proinflammtory cytokines TNFα, IL1ß and IL6 and prevented pNFkB. Mechanistically, AZT restored the CS-induced reduction in anti-oxidant transcription factor NRF2 and upregulated HDAC2 levels, thereby repressing inflammatory gene expression. Beneficial effects of AZT functionally translated in improved lung mechanics in vivo. Further preclinical and clinical studies are warranted to fully establish and validate the therapeutic efficacy of AZT as a mono- or combination therapy for the treatment of COPD.

Source apportionment of size-segregated atmospheric particles and the influence of particles deposition in the human respiratory tract in rural and urban locations of north-east India.

Aerosol samples were collected using eight stage non-viable Andersen cascade impactor at three urban and two rural sites in north-east India during 2018 covering three seasons i.e., winter, summer and monsoon. The size-segregated samples collected in the selected locations were carefully analysed in terms of deposition in human respiratory tract using inhalation and deposition curves. Seasonal variation of fractional deposition of particulate matter (PM) in human respiratory tract was observed. For example, during winter, in one of the urban sites i.e., S3 (0.61) the maximum deposition was in Pulmonary (P) region, while in the case of other sites, the maximum deposition was in Nasopharyngeal (NOPL) region. Regional deposition in P was high in S1 and S3 when compared with other sites. Vehicular emissions was dominant in both S1 and S3 in P, while biomass burning being dominant in S3 which could be the reason for maximum deposition in P. Positive matrix factorization (PMF) revealed five to eight factors at each individual site in NOPL, tracheobronchial (TB) and P regions: biomass burning (accounting for 7-32% of PM), coal combustion (14-27%), construction dust (9-25%), dust emissions (17-28%), industrial emissions (12-26%), oil refinery (18%), secondary aerosols (17-33%) and vehicular emissions (12-39%). Dominant sources in urban and rural areas were vehicular emissions and dust emissions, respectively. Therefore, the present study highlights the importance of analyzing source apportionment of PM at ultrafine scale and forms a basis upon which the future air quality studies and mitigation strategies can be formulated in this region.

Urban black carbon - source apportionment, emissions and long-range transport over the Brahmaputra River Valley.

This research investigates whether the vehicular black carbon emissions originated in the North-Eastern city of Guwahati are transported over and in the Brahmaputra River Valley and the Himalayas. The total black carbon was apportioned between the fossil fuel and biomass burning by real-time measurements of black carbon concentrations at two distinct locations having different traffic volumes in 2016-17. The average observed BC concentrations were 20.58, 6.42, 3.50 and 5.29 µg/m3 at the low traffic location and 22.44, 17.14, 9.2 and 16.87 µg/m3 at the high traffic location in winter, pre-monsoon, monsoon and post-monsoon seasons, respectively. Temperature, wind speed, and solar radiation were found to have significant negative correlations with BC concentrations, while relative humidity had positive correlations. It was found that vehicles contributed over 85% of the ambient black carbon at both locations. Black carbon emission from this dominant source was estimated for 2018, which showed that from vehicles it increased to 0.44-0.55 Gg in 2018 from 0.29 to 0.33 Gg in 2011, which may result in the adverse impacts on the eco-sensitive Brahmaputra River Valley and the Himalayas. The transport and deposition of black carbon under different climatic seasons was modelled using HYSPLIT. The results showed that black carbon particulates are being transported and deposited all-round the year in the Himalayas and the surrounding region. Pre-monsoon and monsoon seasons contributed to the largest amounts of deposition, and a clear relation was found between deposition and rainfall. The total BC deposited in the Brahmaputra River Valley and the Himalayas during one year was 22,142.69 kg and 1566.53 kg with average deposition rates of 0.6452 µgm-2 day-1 and 0.0182 µgm-2 day-1, respectively.

Treatment of gaseous volatile organic compounds using a rotating biological filter.

Rotating biological filter (RBF), which provides higher oxygen mass transfer has been developed for treating gaseous volatile organic compounds (VOCs) such as BTEX (Benzene, toluene, ethylbenzene and xylene) at higher concentrations. The screening of enriched cultures has been done initially to enhance the performance of RBF for treating xylene, toluene and xylene, and BTEX at various loading rates. The removal efficiency of BTEX was maximum (82%), higher than toluene and xylene (79%), and xylene (72%). The presence of xylene enhanced the removal of toluene in the mixture. In the BTEX, toluene was found to be highly biodegradable followed by ethylbenzene, benzene and xylene. The RBF also removed nutrients from wastewater along with VOCs. The stability study of RBF showed that supply of nutrient media influenced the RBF performance more. Further, the predominant strain identified in the mixed culture was Enterobacter cloacae SP4001, responsible for biodegradation of BTEX.

Effects of moving-vehicle wakes on pollutant dispersion inside a highway road tunnel.

This study investigates the pollutant dispersion in a highway road tunnel in the presence of moving-vehicle wakes by a relative-velocity approach using 3-D CFD (3-Dimensional Computational Fluid Dynamics). The turbulent behavior of airflow around different-shaped vehicles and its impact on the pollutant dispersion have been studied. The different-shaped vehicle geometries were extracted, and simplified and dimensioned basing the typical vehicles on Indian roads. The model has been verified with the literature data of static pressure around a moving vehicle body before applying to simulate concentrations, and validated with on-site data at two locations. The results showed that wakes varied with the size, shape and speed of vehicles. The mixed-traffic flow produced higher near-field wakes and accelerated the piston effect, pushing pollutants toward the tunnel roof and out of exit portal in short-time. The findings have particular significance in the studies related to dispersion inside the tunnels having a mixed traffic of different dimensions and shape.

The impact of traffic-flow patterns on air quality in urban street canyons.

We investigated the effect of different urban traffic-flow patterns on pollutant dispersion in different winds in a real asymmetric street canyon. Free-flow traffic causes more turbulence in the canyon facilitating more dispersion and a reduction in pedestrian level concentration. The comparison of with and without a vehicle-induced-turbulence revealed that when winds were perpendicular, the free-flow traffic reduced the concentration by 73% on the windward side with a minor increase of 17% on the leeward side, whereas for parallel winds, it reduced the concentration by 51% and 29%. The congested-flow traffic increased the concentrations on the leeward side by 47% when winds were perpendicular posing a higher risk to health, whereas reduced it by 17-42% for parallel winds. The urban air quality and public health can, therefore, be improved by improving the traffic-flow patterns in street canyons as vehicle-induced turbulence has been shown to contribute significantly to dispersion.

A method to estimate spatiotemporal air quality in an urban traffic corridor.

Air quality exposure assessment using personal exposure sampling or direct measurement of spatiotemporal air pollutant concentrations has difficulty and limitations. Most statistical methods used for estimating spatiotemporal air quality do not account for the source characteristics (e.g. emissions). In this study, a prediction method, based on the lognormal probability distribution of hourly-average-spatial concentrations of carbon monoxide (CO) obtained by a CALINE4 model, has been developed and validated in an urban traffic corridor. The data on CO concentrations were collected at three locations and traffic and meteorology within the urban traffic corridor.(1) The method has been developed with the data of one location and validated at other two locations. The method estimated the CO concentrations reasonably well (correlation coefficient, r≥0.96). Later, the method has been applied to estimate the probability of occurrence [P(C≥Cstd] of the spatial CO concentrations in the corridor. The results have been promising and, therefore, may be useful to quantifying spatiotemporal air quality within an urban area.

Passive control potentials of trees and on-street parked cars in reduction of air pollution exposure in urban street canyons.

This study investigates the passive-control-potentials of trees and on-street parked cars on pedestrian exposure to air pollutants in a street canyon using three-dimensional CFD. Since, according to some studies trees deteriorate air quality and cars parked roadside improve it, the combine as well as separate effects of trees and on-street parked cars have been examined. For this, different tree canopy layouts and parking configurations have been developed and pedestrian exposure for each has been analysed. The results showed, for example, tree crown with high porosity and low-stand density in combination with parallel or perpendicular car parking reduced the pedestrian exposure considerably.

An open-terrain line source model coupled with street-canyon effects to forecast carbon monoxide at traffic roundabout.

A double-lane four-arm roundabout, where traffic movement is continuous in opposite directions and at different speeds, produces a zone responsible for recirculation of emissions within a road section creating canyon-type effect. In this zone, an effect of thermally induced turbulence together with vehicle wake dominates over wind driven turbulence causing pollutant emission to flow within, resulting into more or less equal amount of pollutants upwind and downwind particularly during low winds. Beyond this region, however, the effect of winds becomes stronger, causing downwind movement of pollutants. Pollutant dispersion caused by such phenomenon cannot be described accurately by open-terrain line source model alone. This is demonstrated by estimating one-minute average carbon monoxide concentration by coupling an open-terrain line source model with a street canyon model which captures the combine effect to describe the dispersion at non-signalized roundabout. The results of the modeling matched well with the measurements compared with the line source model alone and the prediction error reduced by about 50%. The study further demonstrated this with traffic emissions calculated by field and semi-empirical methods.

Source apportionment of human personal exposure to volatile organic compounds in homes, offices and outdoors by chemical mass balance and genetic algorithm receptor models.

A number of past studies have shown the prevalence of a considerable amount of volatile organic compounds (VOCs) in workplace, home and outdoor microenvironments. The quantification of an individual's personal exposure to VOCs in each of these microenvironments is an essential task to recognize the health risks. In this paper, such a study of source apportionment of the human exposure to VOCs in homes, offices, and outdoors has been presented. Air samples, analysed for 25 organic compounds and sampled during one week in homes, offices, outdoors and close to persons, at seven locations in the city of Leipzig, have been utilized to recognize the concentration pattern of VOCs using the chemical mass balance (CMB) receptor model. In result, the largest contribution of VOCs to the personal exposure is from homes in the range of 42 to 73%, followed by outdoors, 18 to 34%, and the offices, 2 to 38% with the corresponding concentration ranges of 35 to 80 microg m(- 3), 10 to 45 microg m(- 3) and 1 to 30 microg m(- 3) respectively. The species such as benzene, dodecane, decane, methyl-cyclopentane, triethyltoluene and trichloroethylene dominate outdoors; methyl-cyclohexane, triethyltoluene, nonane, octane, tetraethyltoluene, undecane are highest in the offices; while, from the terpenoid group like 3-carane, limonene, a-pinene, b-pinene and the aromatics toluene and styrene most influence the homes. A genetic algorithm (GA) model has also been applied to carry out the source apportionment. Its results are comparable with that of CMB.

Performance evaluation of air quality models for predicting PM10 and PM2.5 concentrations at urban traffic intersection during winter period.

There are several models that can be used to evaluate roadside air quality. The comparison of the operational performance of different models pertinent to local conditions is desirable so that the model that performs best can be identified. Three air quality models, namely the 'modified General Finite Line Source Model' (M-GFLSM) of particulates, the 'California Line Source' (CALINE3) model, and the 'California Line Source for Queuing & Hot Spot Calculations' (CAL3QHC) model have been identified for evaluating the air quality at one of the busiest traffic intersections in the city of Guwahati. These models have been evaluated statistically with the vehicle-derived airborne particulate mass emissions in two sizes, i.e. PM10 and PM2.5, the prevailing meteorology and the temporal distribution of the measured daily average PM10 and PM2.5 concentrations in wintertime. The study has shown that the CAL3QHC model would make better predictions compared to other models for varied meteorology and traffic conditions. The detailed study reveals that the agreements between the measured and the modeled PM10 and PM2.5 concentrations have been reasonably good for CALINE3 and CAL3QHC models. Further detailed analysis shows that the CAL3QHC model performed well compared to the CALINE3. The monthly performance measures have also led to the similar results. These two models have also outperformed for a class of wind speed velocities except for low winds (<1 m s(-1)), for which, the M-GFLSM model has shown the tendency of better performance for PM10. Nevertheless, the CAL3QHC model has outperformed for both the particulate sizes and for all the wind classes, which therefore can be optional for air quality assessment at urban traffic intersections.

The performance evaluation of WinOSPM model for urban street canyons of Nantes in France.

Air quality modelling is primarily the quantative approach. It is more difficult as it demands input data accuracy, uncertainties and the efficient methodologies to judge the extent of models accuracy. As a result, model validation has to be regarded as an integral part of the modelling process. Furthermore, models are often validated on a limited number of testcases therefore, appropriate evaluation procedure must be implemented to ensure these models will be applicable for various conditions. The study presented here was carried out to evaluate the WinOSPM (Preliminary version of windows based Operational Street Pollution Model) for air pollutants viz. CO, NO, NO2, NOx and C6H6 for three street canyons of Nantes (France) and for the three base years 1999, 2000, and 2001. Each street canyon selected for this study has typical and unidentical features. The rue de Strasbourg and Boulevard Victor Hugo have many building exceptions whereas rue Crébillon has not any. Application of the model above to the three street canyons revealed that WinOSPM could be used in the case when measurements are not available. This was justified from the results at rue Crébillon. The special interest was in the benzene modelled values as its content in fuel has been targeted to reduce to 1% for the years 2000 and onwards (from its 5% until the year 1999). The 50 to 70% reduction in the benzene concentrations is found for both the years i.e. in 2000 and 2001. This has further justified that air quality models are useful and interesting tools in optimising emission reduction strategies. Moreover, it is also the new pollutant added to the measurement campaign of Air Pays de la Loire (APL) for the city of Nantes. For benzene weekly averages are estimated from the hourly-modelled values for all the streets and compared with that of measurements. They are found in excellent agreement with each other's. For other pollutants annual means and percentiles were compared. The statistical analysis was done to evaluate the models performance using index of agreement and correlation coefficient. The index of agreement (d) and correlation coefficient (r) for all the streets show that estimated concentration levels are in good agreement with that of measurements. From the index of agreements, it can be inferred that model has very less potential for errors. The model's sensitivity to building-exceptions was also tested for the rue de Strasbourg. Results did not reflect this feature very well. It is perceived that the influence of this feature might have been suppressed in averaging the annual hourly values. This influence is apparently seen in hourly average time series variations. Finally, WinOSPM model was found a simple but very useful model. It could very well represent the detailed flow and dispersion conditions in urban streets.