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1.
Sci Total Environ ; 806(Pt 3): 151347, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34728203

RESUMO

During the cold start and warm-up phase, modern vehicles emit considerable amounts of pollutants due to the incomplete combustion and deteriorated performance of aftertreatment devices. In terms of emission modeling, there have been many attempts to estimate cold start emission such as cold-hot conversion factor, regression model, and physis-based model. However, as the emission characteristic become complicated due to the adoption of aftertreatment devices and various emission control strategies for the strengthened emission regulations, the conventional cold start emission models do not always show satisfactory performances. In this study, artificial neural networks were used to predict the cold start emissions of carbon dioxide, nitrogen oxides, carbon monoxide, and total hydrocarbon of diesel passenger vehicles. We used real-world driving data to train neural networks as an emission prediction tool. Through machine leaning, numerous trainable variables of neural networks were properly adjusted to predict cold start emissions. For input variables of the ANN model, the velocity, vehicle specific power, engine speed, engine torque, and engine coolant temperature were used. The proposed ANN models accurately predicted sharp increases in carbon monoxide, hydrocarbon, and nitrogen oxides during the cold start phase. In addition to the quantitative estimations, the correlations between the operating variables and exhaust gas emissions were visually described in the form of emission maps. The emission map graphically showed the emission levels according to the vehicle and engine operating parameters.


Assuntos
Poluentes Atmosféricos , Gasolina , Poluentes Atmosféricos/análise , Gasolina/análise , Veículos Automotores , Redes Neurais de Computação , Óxidos de Nitrogênio/análise , Emissões de Veículos/análise
2.
J Environ Sci (China) ; 112: 218-230, 2022 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-34955206

RESUMO

Aiming to investigate the impacts of n-octanol addition on the oxidation reactivity, morphology and graphitization of diesel exhaust particles, soot samples were collected from a four-cylinder turbocharged diesel engine fueled with D100 (neat diesel fuel), DO15 (85% diesel and 15% n-octanol, V/V) and DO30 (70% diesel and 30% n-octanol, V/V). All tests were conducted at two engine speeds of 1370 and 2150 r/min under a fixed torque of 125 N·m. The soot properties were characterized by thermogravimetric analyzer (TGA), transmission electron microscopy (TEM) and Raman spectroscopy (RS). The higher volatile organic fraction content, lower soot oxidation temperatures and lower activation energy from TGA results indicated that both the increasing n-octanol concentration and engine speed enhanced the soot oxidation reactivity. Additionally, quantitative analysis of TEM images showed that the soot derived from DO30 had the smallest primary particle diameters and fractal dimension, followed by those of soot produced by DO15 and D100. The RS results demonstrated that the n-octanol addition and higher engine speed led to a larger D1-FWHM (D1-full width at half maximum), AD1/AT (area ratio of D1 band and the total spectral) and AD3/AT (area ratio of D3 band and the total spectral) as well as a smaller La (crystallite width), revealing a lower degree of graphitization. Furthermore, the correlations between characterization parameters of soot properties and reactivity were nonlinear.


Assuntos
Gasolina , Fuligem , 1-Octanol , Gasolina/análise , Microscopia Eletrônica de Transmissão , Fuligem/análise , Emissões de Veículos/análise
3.
Sci Total Environ ; 805: 150407, 2022 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-34818772

RESUMO

In this study, driving trajectory data from private vehicles were collected in Toronto, Canada to construct representative local drive cycles. In addition, real-driving emission testing for four conventional gasoline vehicles (ICEV) and one hybrid electric vehicle (HEV) was conducted in the same region using a Portable Emissions Measurement System. Instantaneous fuel consumption and emissions of Carbon Monoxide (CO), Nitrogen Oxides (NOx), and Particle Number (PN) were measured. The results for all vehicles indicate that the acceleration state tends to generate the highest emissions and fuel consumption with the largest variation due to higher power demand. When accelerating, the HEV was observed to generate four times more CO emissions than some ICEVs. Instantaneous fuel consumption and emissions were analyzed as a function of operating modes to estimate the fuel efficiency (FE) and emission factors (EF) associated with six representative local drive cycles and four regulatory drive cycles. With most regulatory drive cycles, vehicles can reach the labeled FE and EPA emission limits, except under the New York City Cycle with frequent stop-and-go conditions. In contrast, except for highway cycles, the FE of Toronto-specific drive cycles can hardly meet the labeled values. CO EFs of the HEV can be higher than ICEVs, while it is lower than the emission limit by 42% on average. ICEVs may exceed the CO limit by 131% under local highway cycles, while they can violate NOx and PN limits under local arterial cycles. The result of this study emphasizes the importance of local drive cycles and real driving emission tests.


Assuntos
Poluentes Atmosféricos , Gasolina , Poluentes Atmosféricos/análise , Monóxido de Carbono/análise , Gasolina/análise , Veículos Automotores , Óxidos de Nitrogênio/análise , Emissões de Veículos/análise
4.
Sci Total Environ ; 806(Pt 2): 150593, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34592297

RESUMO

In the last decades radon (Rn) has been widely proposed as a naturally occurring tracer for non-aqueous phase liquids (NAPL) in the soil. This work examines the feasibility of using soil gas data collected at some distance from the source zone for the application of the Rn deficit technique for the identification and quantification of NAPL contamination. To this end, we used a steady-state 1-D analytical solution that is based on a 3-layer model that allows to simulate the transport and distribution of Rn in the source zone, capillary fringe and overlying unsaturated soil. The analytical solution was first validated against a more detailed numerical model available in the literature. Then, a series of simulations were carried out to evaluate the vertical concentration profiles of Rn in soil gas above the source zone and in background location not impacted by NAPL. Simulation results showed that the parameters that most influence the migration and distribution of Rn in the subsurface are the distance of the soil gas probe from the source zone and, to a lower extent, the type of contamination (e.g. diesel or gasoline) and the soil type. On the basis of these results, we developed some easy-to-use nomographs to estimate the residual NAPL phase based on the observed radon deficit in soil gas and on the probe to source distance and soil and NAPL characteristics. According to the obtained results, the radon deficit technique results a feasible method for a qualitative identification of residual NAPL when radon in soil gas is measured at distances lower than 2 m from the contaminated zone. However, for an accurate quantitative estimation of the NAPL phase content, soil gas probes should be preferably located at distances lower than 1 m from the source zone.


Assuntos
Radônio , Poluentes do Solo , Poluentes Químicos da Água , Gasolina , Radônio/análise , Solo , Poluentes do Solo/análise , Poluentes Químicos da Água/análise
5.
Talanta ; 238(Pt 1): 122998, 2022 Feb 01.
Artigo em Inglês | MEDLINE | ID: mdl-34857331

RESUMO

In this work, a method for total sulphur determination in automotive gasoline using dried matrix spot sampling is proposed. The method is based on the deposition of the sample on a cellulose-based filter paper and subsequent sulphur quantification via CS diatomic molecule using high-resolution continuum source graphite furnace molecular absorption spectrometry (HR-CS GF MAS). The sample deposition was carried out, along with the chemical modifier, on a 20-mm filter paper disc previously adapted into a polytetrafluoroethylene (PTFE) mould. The liquid phase was removed by heating the PTFE mould, and then the gasoline sample-embedded filter paper was punched in smaller discs (procedure A) or pulverised (procedure B) before the analyses. The mixture of Pd and Mg was used as chemical modifier to stabilise the sulphur compounds on the filter paper and on the graphite furnace. All the calibration curves constructed using seven different sulphur-containing compounds had a coefficient of determination higher than 0.995 and a linear range from 2 to 150 mg kg-1 S. By using the optimised conditions, the best characteristic mass, limits of detection and quantitation were 6 ng, 0.6 and 1.8 mg kg-1, respectively. The two sampling procedures (A and B) were evaluated for real samples, and procedure B was chosen since it markedly improved the precision. Using this procedure, satisfactory recovery values from 95 to 106% were obtained in the spike-recovery tests. In addition, the S concentrations for the certified reference materials were not statistically different from the certified values at 95% confidence level. Sulphur concentrations from 20 to 46 mg kg-1 were found in the six analysed gasoline samples, and these values were statistically assessed using a reference method (ASTM 5453). Spectral interference caused by MgF and MgCl diatomic molecules was observed and investigated.


Assuntos
Gasolina , Grafite , Calibragem , Espectrofotometria Atômica , Enxofre
6.
J Environ Manage ; 304: 114284, 2022 Feb 15.
Artigo em Inglês | MEDLINE | ID: mdl-34915387

RESUMO

The present study examines the preheated (95 °C) and unheated (35 °C) Vateria indica methyl ester (VIME) blends by studying the engine performance, combustion, and emission characteristics at various loads. A single-cylinder, TV1 Kirloskar direct injection diesel engine is used to carry out the tests. Biodiesel produced from Dhupa fat through the transesterification process is used as a renewable fuel in a diesel engine. In this work, diesel (B0), VIME (B100), and two binary blends (B30 and B50) are used. VIME has a higher viscosity, higher density, and lower calorific value than diesel, resulting in lesser brake thermal efficiency (BTE) and higher brake specific energy consumption (BSEC). Due to high viscosity of the biodiesel, preheating of fuel is done before injecting into cylinder. Preheating reduces the viscosity, and enhances the atomization and vaporization of fuel, resulting in improved engine performance. For a given blend of VIME biodiesel and diesel, the preheated blend has better BTE, decreased BSEC and lesser CO and HC emissions, with a slight increment in NOX emission compared to the unheated blend. The preheated B30 blend has a BTE value of 30.3% which is close to the BTE value of 30.1% of unheated diesel at 100% load condition. CO, HC, and soot emissions are decreased by 16.2%, 34.4%, and 16.5%, respectively, for preheated B100 fuel compared to unheated B100, at full load.


Assuntos
Dipterocarpaceae , Gasolina , Biocombustíveis , Monóxido de Carbono/análise , Ésteres , Emissões de Veículos
7.
J Environ Sci (China) ; 115: 319-329, 2022 May.
Artigo em Inglês | MEDLINE | ID: mdl-34969459

RESUMO

As compared to conventional diesel heavy-duty vehicles, natural gas vehicles have been proved to be more eco-friendly due to their lower production of greenhouse gas and pollutant emissions, which are causing enormous adverse effects on global warming and air pollution. However, natural gas vehicles were rarely studied before, especially through on-road measurements. In this study, a portable emission measurement system (PEMS) was employed to investigate the real-world emissions of nitrogen oxides (NOx) (nitrogen monoxide (NO), nitrogen dioxide (NO2)), total hydrocarbons (THC), carbon monoxide (CO), and carbon dioxide (CO2) from two liquified natural gas (LNG) China V heavy-duty cleaning sanitation trucks with different weight. Associated with the more aggressive driving behaviors, the vehicle with lower weight exhibited higher CO2 (3%) but lower NOx (48.3%) (NO2 (78.2%) and NO (29.4%)), CO (44.8%), and THC (3.7%) emission factors. Aggressive driving behaviors were also favorable to the production of THC, especially those in the medium-speed range but significantly negative to the production of CO and NO2, especially those in the low-speed range with high engine load. In particular, the emission rate ratio of NO2/NO decreased with the increase of speed/scaled tractive power in different speed ranges.


Assuntos
Poluentes Atmosféricos , Gás Natural , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Gases , Gasolina/análise , Veículos Automotores , Saneamento , Emissões de Veículos/análise
8.
Spectrochim Acta A Mol Biomol Spectrosc ; 268: 120652, 2022 Mar 05.
Artigo em Inglês | MEDLINE | ID: mdl-34896682

RESUMO

Feature selection plays a vital role in the quantitative analysis of high-dimensional data to reduce dimensionality. Recently, the variable selection method based on mutual information (MI) has attracted more and more attention in the field of feature selection, where the relevance between the candidate variable and the response is maximized and the redundancy of the selected variables is minimized. However, multicollinearity often is a serious problem in linear models. Collinearity can cause unstable parameter estimation, unreliable models, and weak predictive ability. In order to address this problem, the variance inflation factor (VIF) was introduced for feature selection. Therefore, a variable selection method based on MI combined with VIF was proposed in this paper, called Mutual Information-Variance Inflation Factor (MI-VIF). By calculating the MI between the independent variable and the response variable, the variable with greater MI was selected to maximize the correlation between the independent variable and the response variable. By calculating the VIF between the independent variables, the multicollinearity test was performed. The variables that cause the multicollinearity of the model were eliminated to minimize the collinearity between the independent variables. The proposed method was tested based on two high-dimensional spectral datasets. The regression models (PLSR, MLR) were established based on feature selection through MI-VIF and MI-based methods (MIFS, MMIFS) to compare the prediction accuracy of the models. The results showed that under two datasets, the MI-VIF showed a good prediction performance. Based on the tea dataset, the established MI-VIF-MLR model achieved accuracy with Rp2 of 0.8612 and RMSEP of 0.4096, the MI-VIF-PLSR model achieved accuracy with Rp2 of 0.8614 and RMSEP of 0.4092. Based on the diesel fuels dataset, the established MI-VIF-MLR model achieved accuracy with Rp2 of 0.9707 and RMSEP of 0.6568, the MI-VIF-PLSR model achieved accuracy with Rp2 of 0.9431 and RMSEP of 0.9675. In addition, the MI-VIF was compared with the Successive projections algorithm (SPA), which is a method to reduce the collinearity between variables in the wavelength selection of the near-infrared spectrum. It was found that MI-VIF also had a good predictive effect compared to SPA. It proves that the MI-VIF is an effective variable selection method.


Assuntos
Algoritmos , Espectroscopia de Luz Próxima ao Infravermelho , Gasolina , Análise dos Mínimos Quadrados , Modelos Lineares
9.
Environ Pollut ; 292(Pt A): 118303, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34626703

RESUMO

Fine particulate matter cause profound adverse health effects in Iran. Road traffic is one of the main sources of particulate matter (PM) in urban areas, and has a large contribution in PM2.5 and organic carbon concentration, in Tehran, Iran. The composition of fine PM vehicle emission is poorly known, so this paper aims to determine the mixed fleet source profile by using the analysed data from the two internal stations and the emission factor for PM light-duty vehicles emission. Tunnels are ideal media for extraction vehicle source profile and emission factor, due to vehicles are the only source of pollutant in the urban tunnels. In this study, PM samples were collected simultaneously in two road tunnel stations and at a background site in Niyayesh tunnel in Tehran, Iran. The tunnel samples show a large contribution for some elements and ions, such as Fe (0.23 µg µg-1 OC), Al (0.02 µg µg-1 OC), Ca (0.055 µg µg-1 OC), SO4 (0.047 µg µg-1 OC), Docosane (0.0017 µg µg-1 OC), Triacontane (0.016 µg µg-1 OC), Anthracenedione (0.0003 µg µg-1 OC) and Benzo-perylene (0.0002 µg µg-1 OC). In overall, on-road gasoline vehicle fleets source profile extracted in this study is similar to composite profiles derived from roadside tunnel measurment performed in other countries during the last decades. The PM2.5 emission factor for Tehran's light-duty vehicle fleet has been extracted 16.23 mg km-1. vehicle-1and 0.09 g kg-1. The profile would be used for Chemical Mass Balance Model studies for Iran and other countries with a similar road traffic fleet mix. Also, it would be very suitable for use in emission inventories improvement. The results of this study can be used for choosing the best management strategies and provide comperhensive insight to fine PM traffic emission in Tehran.


Assuntos
Poluentes Atmosféricos , Gasolina , Poluentes Atmosféricos/análise , Monitoramento Ambiental , Gasolina/análise , Irã (Geográfico) , Veículos Automotores , Material Particulado/análise , Emissões de Veículos/análise
10.
Environ Pollut ; 292(Pt A): 118278, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34634405

RESUMO

SOx Emissions Control Areas (SECAs) have been established to reduce harmful effects of atmospheric sulfur. Typical technological changes for ships to conform with these regulations have included the combustion of low-sulfur fuels or installment of SOx scrubbers. This paper presents experimental findings from high-end real-time measurements of gaseous and particulate pollutants onboard a Roll-on/Roll-off Passenger ship sailing inside a SECA equipped with a diesel oxidation catalyst (DOC) and a scrubber as the exhaust aftertreatment. The ship operates between two ports and switched off the SOx scrubbing when approaching one of the ports and used low-sulfur fuel instead. Measurement results showed that the scrubber effectively reduced SO2 concentrations with over 99% rate. In terms of fuel, the engine-out PM was higher for heavy fuel oil than for marine gas oil. During open sea cruising (65% load) the major chemical components in PM having emission factor of 1.7 g kgfuel-1 were sulfate (66%) and organics (30%) whereas the contribution of black carbon (BC) in PM was low (∼4%). Decreased engine load on the other hand increased exhaust concentrations of BC by a factor exceeding four. As a novel finding, the secondary aerosol formation potential of the emitted exhaust measured with an oxidation flow reactor and an aerosol mass spectrometer was found negligible. Thus, it seems that either DOC, scrubber, or their combination is efficient in eliminating SOA precursors. Overall, results indicate that in addition to targeting sulfur and NOx emissions from shipping, future work should focus on mitigating harmful particle emissions.


Assuntos
Poluentes Atmosféricos , Material Particulado , Aerossóis , Poluentes Atmosféricos/análise , Gasolina/análise , Material Particulado/análise , Navios , Emissões de Veículos/análise
11.
Talanta ; 236: 122838, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34635228

RESUMO

Medium-resolution (MR-NMR) and time-domain NMR relaxometry (TD-NMR) using benchtop and low-field NMR instruments are powerful tools to tackle fuel adulteration issues. In this work, for the first time, we investigate the possibility of enhancing the low-field NMR capability on fuel analysis using data fusion of MR and TD-NMR. We used the ComDim (Common Dimensions Analysis) multi-block analysis to join the data, which allowed exploration, classification, and quantification of common adulterations of diesel fuel by vegetable oils, biodiesel, and diesel of different sources as well as the sulfur content. After data exploration using ComDim, classification (applying linear discriminant analysis, LDA), and regression (applying multiple linear regression, MLR), models were built using ComDim scores as input variables on the LDA and MLR analyses. This approach enabled 100% of accuracy in classifying diesel fuel source (refinery), sulfur content (S10 or S500), vegetable oil, and biodiesel source. Moreover, in the quantification step, all MLR models showed a root mean square error of prediction (RMSEP) and the residual prediction deviation (RPD) values comparable to the literature for determining diesel, vegetable oil, and biodiesel contents.


Assuntos
Biocombustíveis , Gasolina , Biocombustíveis/análise , Gasolina/análise , Espectroscopia de Ressonância Magnética , Monitorização Fisiológica , Óleos Vegetais
12.
J Hazard Mater ; 423(Pt A): 127046, 2022 02 05.
Artigo em Inglês | MEDLINE | ID: mdl-34481398

RESUMO

Mangroves (Avicennia marina) growing in intertidal areas are often exposed to diesel spills, adversely damaging the ecosystem. Herein, we showed for the first time that mangrove seedlings' associations with bacteria could reprogram host-growth, physiology, and ability to degrade diesel. We found four bacterial strains [Sphingomonas sp.-LK11, Rhodococcus corynebacterioides-NZ1, Bacillus subtilis-EP1 Bacillus safensis-SH10] exhibiting significant growth during diesel degradation (2% and 5%, v/v) and higher expression of alkane monooxygenase compared to control. This is in synergy with reduced long-chain n-alkanes (C24-C30) during microbe-diesel interactions in the bioreactor. Among individual strains, SH10 exhibited significantly higher potential to improve mangrove seedling's morphology, anatomy and growth during diesel treatment in rhizosphere compared to control. This was also evidenced by reduced activities and gene expression of antioxidant enzymes (catalases, peroxidases, ascorbic peroxidases, superoxide dismutases and polyphenol peroxidases) and lipid peroxidation during microbe-diesel interactions. Interestingly, we noticed significantly higher soil-enzyme activities (phosphatases and glucosidases) and essential metabolites in seedling's rhizosphere after bacteria and diesel treatments. Degradation of longer n-alkane chains in the rhizosphere also revealed a potential pathway that benefits mangroves by bacterial strains during diesel contaminations. Current results support microbes' application to rhizoengineer plant growth, responses, and phytoextraction abilities in environments contaminated with diesel spills. AVAILABILITY OF DATA AND MATERIALS: The datasets generated during the current study are available in the NCBI GenBank ((https://www.ncbi.nlm.nih.gov).


Assuntos
Microbiologia do Solo , Poluentes do Solo , Biodegradação Ambiental , Ecossistema , Gasolina , Poluentes do Solo/análise
13.
Sci Total Environ ; 802: 149750, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34454158

RESUMO

The continuous growing demand for fossil fuel puts an enormous pressure on finding a better replacement. This research paper explores the detailed information on the improved production, emission and performance characteristics of the distinct bio-oil derived from the micro algae of Schizochytrium. The algae were grown in the artificial seawater with enough nitrogen supply at the required standard conditions. The lipid growth and production of the bio-oil were monitored closely and measured. Different fuel blends were used at different concentrations as B0 (100% Diesel), B10 (10% schizochytrium biofuel +90% diesel), B20 (20% schizochytrium biofuel +80% diesel) and B30 (30% schizochytrium biofuel +70% diesel). A small single cylinder, four stroke diesel engine was used to conduct the tests. All tests were conducted at different speed conditions of 1200 rpm to 2100 rpm in six intervals. The performance qualities of bio-oil such as CO, NOX, and smoke and CO2 emission along with the performance qualities of brake thermal efficiency and brake specific fuel consumption. Form the results, the Schizochytrium microalgae bio-oil as the bio fuel for diesel engines in the moderate level showed the improved performance by increasing the BTE and reducing the harmful gas emissions except NOX. However, the emission level of NOX was slightly higher than the diesel emitted value. The difference between them was negligible.


Assuntos
Biocombustíveis , Gasolina , Monóxido de Carbono/análise , Transferência de Energia , Óxidos de Nitrogênio/análise , Emissões de Veículos
14.
Sci Total Environ ; 802: 149863, 2022 Jan 01.
Artigo em Inglês | MEDLINE | ID: mdl-34525749

RESUMO

The depletion of fuel production and raising ecological issues have paid the progress of biofuels in the entire world. Among different biofuels is introducing renewable fuel additives as prospective beneficial blendstocks towards fulfilling systematic, low-carbon technologies internal combustion engines. This research article proposes a new approach to formulate a Fuzzy modeling for examining various promising alternative renewable oxygenated compounds, including ethanol, isopropanol, MTBE, and 2-methyl furan into heavy hydrocracked gasoline a base fuel. No previous study has utilized Fuzzy modeling in formulation of producing high octane fuel based on renewable additives compounds. The effect of selected additives was investigated on the antiknock characteristics. The results reported that the quality and quantity of heavy hydrocracked naphtha have been reinforced, using low carbon oxygenates. Besides, the acquired results provided the possibility to determine the optimum range of selected renewable oxygenates percentages of 30-50% wt. The calculated data of Fuzzy modeling were verified with experimental results. It illustrated that predicted environmental gasoline yields agreed well with experimental results. Finally, low carbon liquid fuel could contribute to produce high quality environmental gasoline, improve environmental characteristics, in terms of decreasing greenhouses emissions, and maximize the vehicles technologies.


Assuntos
Gasolina , Petróleo , Biocombustíveis , Octanos , Estudos Prospectivos , Emissões de Veículos
15.
Sci Total Environ ; 805: 150171, 2022 Jan 20.
Artigo em Inglês | MEDLINE | ID: mdl-34537714

RESUMO

Different powertrains passenger cars, homologate in compliance with Euro 6 standard, were compared in a life cycle perspective for assessing both environmental and human health impacts. For this latter aspect, some correlation between the emission of heavy metals, elemental carbon, organic carbon, the oxidative potential of particulate matter and the adverse effect on human health were also analyzed and discussed. Battery electric vehicle (BEV) showed the lower greenhouse gases emissions, from 0.1 kgCO2eq/km to 0.2 kgCO2eq/km but were charged by the higher emissions of freshwater eutrophication and freshwater ecotoxicity, about 6 × 10-6 kgPeq/km and 4 CTUe/km, respectively. Lower resource depletion was detected for cars powered by internal combustion and hybrid powertrains. Amount of particulate matter (PM) emitted resulted lower for petrol-hybrid electric vehicles (Petrol-HEV), of about 5 × 10-5 kgPM2.5eq/km. BEV were charged by the higher values of human toxicity cancer, from about 2 × 10-5 CTUh/km to about 5 × 10-5 CTUh/km whereas Petrol-HEV were credited by the lower impact on human health (DALY/km). The large contribution to PM emission from all the analyzed cars was from tyre and brake wear. Main PM components were elemental (ElC) and organic carbon (OC) compounds. ElC is also a specific marker of PM emitted from traffic. Both ElC and OC were characterized by a strong correlation with the oxidative potential of PM, indicating a threat for human respiratory tract only marginally decreased by the transition from conventional to electric poweretrains vehicles.


Assuntos
Poluentes Atmosféricos , Material Particulado , Poluentes Atmosféricos/análise , Animais , Automóveis , Gasolina , Humanos , Estágios do Ciclo de Vida , Veículos Automotores , Estresse Oxidativo , Material Particulado/análise , Emissões de Veículos/análise
16.
Artigo em Inglês | MEDLINE | ID: mdl-34948649

RESUMO

In order to have an accurate and fast prediction of the artificial intelligence (AI) model, the choice of input features is at least as important as the choice of model. The effect of input features selection on the emission models of light diesel vehicles driven on real roads was investigated in this paper. The gradient boosting regression (GBR) model was used to train and to predict the emissions of nitrogen oxide (NOx), carbon dioxide (CO2), and the fuel consumption of real driving diesel vehicles in urban scenarios, the suburbs, and on highways. A portable emissions measurement system (PEMS) system was used to collect data of vehicles as well as environmental conditions. The vehicle was run on two routes. The model was trained with the first route data and was used to predict the emissions of the second route. There were ten features related to the NOx model and nine features associated with the CO2 model. The importance of each feature was sorted, and a different number of features were used as input to train the models. The best NOx model had the coefficient of determination (R2) values of 0.99, 0.99, and 0.99 in each driving pattern (urban, suburbs, and highways). Predictions of the second route had the R2 values of 0.88, 0.89, and 0.96 respectively. The best CO2 model had the R2 values of 0.98, 0.99, and 0.99 in each driving pattern, respectively. Predictions of the second route had the R2 values are 0.79, 0.82, and 0.83, respectively. The most important features for the NOx model are mass air flow rate (g/s), exhaust flow rate (m3/min), and CO2 (ppm), while the important features for the CO2 model are exhaust flow rate (m3/min) and mass air flow rate (g/s). It is noted that the regression models based on the top three features may give predictions very close to the measured data.


Assuntos
Poluentes Atmosféricos , Poluentes Atmosféricos/análise , Inteligência Artificial , Dióxido de Carbono/análise , Monitoramento Ambiental , Gasolina , Veículos Automotores , Emissões de Veículos/análise
17.
PLoS One ; 16(12): e0260528, 2021.
Artigo em Inglês | MEDLINE | ID: mdl-34937056

RESUMO

Electrogenic bacteria produce power in soil based terrestrial microbial fuel cells (tMFCs) by growing on electrodes and transferring electrons released from the breakdown of substrates. The direction and magnitude of voltage production is hypothesized to be dependent on the available substrates. A sensor technology was developed for compounds indicative of anthropological activity by exposing tMFCs to gasoline, petroleum, 2,4-dinitrotoluene, fertilizer, and urea. A machine learning classifier was trained to identify compounds based on the voltage patterns. After 5 to 10 days, the mean voltage stabilized (+/- 0.5 mV). After the entire incubation, voltage ranged from -59.1 mV to 631.8 mV, with the tMFCs containing urea and gasoline producing the highest (624 mV) and lowest (-9 mV) average voltage, respectively. The machine learning algorithm effectively discerned between gasoline, urea, and fertilizer with greater than 94% accuracy, demonstrating that this technology could be successfully operated as an environmental sensor for change detection.


Assuntos
Fontes de Energia Bioelétrica/microbiologia , Técnicas Biossensoriais/métodos , Fertilizantes/análise , Gasolina/análise , Aprendizado de Máquina , Microbiologia do Solo , Ureia/análise
18.
J Occup Health ; 63(1): e12307, 2021 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-34957641

RESUMO

OBJECTIVE: This study assessed the health risk of benzene exposure among Thai gasoline station workers through biomarker detection and experience of adverse symptoms. METHODS: Trans, trans-muconic acid (tt-MA) metabolites of benzene were analyzed from spot urine sampled among gasoline station workers after shift work using HPLC-UV. Air benzene monitoring was done with an active sampler connected to a charcoal sorbent tube, and analyzed by GC-FID. The health risk was calculated by using the biomatrix of the likelihood of benzene exposure and the severity of adverse symptoms. RESULTS: The tt-MA concentration, among 235 workers, ranged from less than 10-2159 µg/g Cr, which corresponded to the air benzene concentration range of <0.1 to 65.8 ppb. In total, 32.3% of workers had a higher than acceptable risk level and there was a significant association between gasoline station work zones and the likelihood of benzene exposure as well as the health risk of workers. The health risk levels estimated from the biomarker monitoring were consistent with the risk matrix of air benzene monitoring. CONCLUSION: This tt-MA biomarker monitoring and biomatrix of health risk assessment is suggested as useful for health surveillance of gasoline station workers exposed to benzene.


Assuntos
Poluentes Ocupacionais do Ar/análise , Benzeno/toxicidade , Gasolina/toxicidade , Exposição Ocupacional/efeitos adversos , Medição de Risco/métodos , Adolescente , Adulto , Benzeno/análise , Biomarcadores/urina , Monitoramento Ambiental , Feminino , Humanos , Masculino , Pessoa de Meia-Idade , Ácido Sórbico/análogos & derivados , Ácido Sórbico/toxicidade , Tailândia , Adulto Jovem
19.
Sensors (Basel) ; 21(24)2021 Dec 13.
Artigo em Inglês | MEDLINE | ID: mdl-34960418

RESUMO

Following the increase in stringency of the European regulation limits for laboratory and real world automotive emissions, one of the main transport related aspects to improve the air quality is the mass scale in-use vehicle testing. Solid particle number (SPN) emissions have been drastically reduced with the use of diesel and gasoline particulate filters which, however, may get damaged or even been tampered. The feasibility of on-board monitoring and remote sensing as well as of the current periodical technical inspection (PTI) for detecting malfunctioning or tampered particulate filters is under discussion. A promising methodology for detecting high emitters is SPN testing at low idling during PTI. Several European countries plan to introduce this method for diesel vehicles and the European Commission (EC) will provide some guidelines. For this scope an experimental campaign was organized by the Joint Research Centre (JRC) of the EC with the participation of different instrument manufacturers. Idle SPN concentrations of vehicles without or with a malfunctioning particulate filter were measured. The presence of particles under the current cut-off size of 23 nm as well as of volatile particles during idling are presented. Moreover, the extreme case of a well performing vehicle tested after a filter regeneration is studied. In most of the cases the different sensors used were in good agreement, the high sub-23 nm particles existence being the most challenging case due to the differences in the sensors' efficiency below the cut-off size.


Assuntos
Poluentes Atmosféricos , Poluição do Ar , Poluentes Atmosféricos/análise , Poluição do Ar/análise , Automóveis , Monitoramento Ambiental , Gasolina/análise , Veículos Automotores , Tamanho da Partícula , Material Particulado/análise , Emissões de Veículos/análise
20.
Environ Monit Assess ; 193(12): 809, 2021 Nov 16.
Artigo em Inglês | MEDLINE | ID: mdl-34783906

RESUMO

The use of biodiesel blends with petroleum diesel in vehicular engines demands the evaluation of the possible impacts and effects of the gases emitted from their combustion on the environment. Among studies on these questions, biomonitoring using lichens is a viable alternative, given their interactions with the elements dispersed in the atmosphere, as well as its sensitivity and capacity to retain contaminants. In this study, we analyzed the effects of gas emissions from the combustion of biodiesel mixture with petroleum diesel on Cladonia verticillaris thalli. Samples of the lichen (10 g) were exposed to the gases emitted by the exhaust of the generator engine during the combustion process of biodiesel mixtures to petroleum diesel (7% (B7), 10% (B10), 40% (B40), 50% (B50), and 70% (B70)). At 90 days after exposure, samples were analyzed for n-alkane profiles, thallus morphology, photosynthetic pigment contents, and secondary lichen metabolites (protocetraric and fumarprotocetraric acids). Sets B7 and B10 showed better resistance of the lichen to pollutants. Set B40 showed a high stress evidenced by the chain elongation of n-alkanes structure and high chlorophyll production, presenting high morphological damages when compared to the control sets, B7 and B10. The results showed significant reductions of n-alkanes profiles for mixtures with high concentrations of biodiesel (B50 and B70), as well as decreases in the chlorophyll content. These groups showed an increase in the synthesis of secondary metabolites, corroborating the hypothesis that high concentrations of biodiesel in the mixture with petroleum diesel have greater impacts on the lichen. Schematic model for demonstration of using the lichen Cladonia verticillaris as biomonitor of effects from gas emissions from the combustion of biodiesel blends with petroleum diesel by a stationary engine.


Assuntos
Biocombustíveis , Líquens , Ascomicetos , Biocombustíveis/análise , Conservação dos Recursos Naturais , Monitoramento Ambiental , Gasolina/análise , Emissões de Veículos/análise
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