Exhaust Pollutants Research Articles

Optimal Water Addition in Emulsion Diesel Fuel Using Machine Learning and Sea-Horse Optimizer to Minimize Exhaust Pollutants from Diesel Engine

Water-in-diesel (W/D) emulsion fuel is a potentially viable diesel fuel that can simultaneously enhance engine performance and reduce exhaust emissions in a current diesel engine without requiring engine modifications or incurring additional costs. In a consistent manner, the current study examines the impact of adding water, in the range of 5–30% wt. (5% increment) and 2% surfactant of polysorbate 20, on the performance in terms of brake torque (BT) and exhaust emissions of a four-cylinder four-stroke diesel engine. The relationship between independent factors, including water addition and engine speed, and dependent factors, including different exhaust released emissions and BT, was initially generated using machine learning support vector regression (SVR). Subsequently, a robust and modern optimization of the sea-horse optimizer (SHO) was run through the SVR model to find the optimal water addition and engine speed for improving the BT and lowering exhaust emissions. Furthermore, the SVR model was compared to the artificial neural network (ANN) model in terms of R-squared and mean square error (MSE). According to the experimental results, the BT was boosted by 3.34% compared to pure diesel at 5% water addition. The highest reduction in carbon monoxide (CO) and unburned hydrocarbon (UHC) was 9.57% and 15.63%, respectively, at 15% of water addition compared to diesel fuel. The nitrogen oxides (NOx) emissions from emulsified fuel were significantly lower than those from pure diesel, with a maximum decrease of 67.14% at 30% water addition. The suggested SVR-SHO model demonstrated superior prediction reliability, with a significant R-Squared of more than 0.98 and a low MSE of less than 0.003. The SHO revealed that adding 15% water to the W/D emulsion fuel at an engine speed of 1848 rpm yielded the optimum BT, CO, UHC, and NOx values of 49.5 N.m, 0.5%, 57 ppm, and 369 ppm, respectively. Finally, these outcomes have important implications for the potential of the SVR-SHO approach to minimize engine exhaust emissions while maximizing engine performance.

Analysis of Exhaust Pollutants from Four-Stroke Marine Diesel Engines Based on Bench Tests

Implementation of new emissions regulations calls for a reassessment of the emissions levels of newly built ships sailing in Chinese regions. In this paper, marine diesel engines are subjected to emissions bench tests using high-precision testing equipment. A total of 135 marine diesel engines meeting the Limits and Measurement Methods for Exhaust Pollutants from Marine Engines (CHINA I/II) were first systematically analyzed. The emission factors of marine main engines (ME) and auxiliary engines (AE) were obtained under different displacements. The results show that the fuel-based emission factors for NOX + HC and CO meeting CHINA I/II are 25.80~44.87/16.47~46.35 and 2.47~13.22/1.64~5.62 kg/t-fuel, respectively. The energy-based emission factors for NOX + HC, CO, CO2, and PM satisfying CHINA I/II are 5.70~9.24/3.70~9.07, 0.49~2.30/0.36~0.99, 620~683/612~718, and 0.05~0.36/0.05~0.27 g/kWh, respectively. Additionally, the specific emission of NOx rises with the increase in single-cylinder displacement, so the CO emission limit of pure diesel fuel is recommended to be lower than 5 g/kWh. The results in this paper provide valuable basic data for research on and estimation of ship emissions in waterway transportation and for understanding the emission characteristics of marine diesel engines.

Effect of various nanoparticle biodiesel blends on thermal efficiency and exhaust pollutants

Effect of various nanoparticle biodiesel blends on thermal efficiency and exhaust pollutants

An integrated Method for Evaluating the Energy-Saving and Emission Reduction of Thermal Power Plants with Interval-Valued Intuitionistic Fuzzy Numbers

With the continuous development of the domestic economy, the demand for electricity is also increasing, and the number of power plants is also increasing. Thermal power plants have become the main source of power generation in my country. According to statistics, thermal power generation accounts for more than half of the country's power generation. In the process of thermal power generation, it is also accompanied by a large amount of exhaust gas and pollutant emissions. The emission of sulfur dioxide (sulfur dioxide) from thermal power plants accounts for about half of the total national emissions, and the emissions of greenhouse gases such as carbon dioxide and nitrogen oxides also account for more than 30% of the total national emissions. and clean emissions have become an important task. Before energy conservation and emission reduction of thermal power plants, it is necessary to find out the current situation of thermal power plants and to find out the current energy conservation and emission reduction effects of thermal power plants. row for evaluation. The problems of evaluating the energy-saving and emission reduction of thermal power plants are classical multiple attribute decision making (MADM) problems. In this paper, firstly the definition of interval-valued intuitionistic fuzzy sets (IVIFSs), Heronian mean (HM) operator, Dombi operations are introduced and the interval-valued intuitionistic fuzzy Dombi power Heronian mean (IVIFDPHM) operator is proposed. Some desirable properties of this operator are established, such as commutativity, idempotency and monotonicity. Then, the IVIFDPHM operator is used to deal with the interval-valued intuitionistic fuzzy (IVIF) multiple attribute decision making (IVIF-MADM) problems. Finally, an illustrative example for evaluating the energy-saving and emission reduction of thermal power plants is given to verify the built approach.

Review on the research status of marine natural gas engine

with the ship emission becoming more and more strictand the shortage of oil resources, looking for clean alternative energy sources is imminent, natural gas with its high calorific value per unit, low exhaust pollution, reliable supply, economical advantages hasbecome the preferred alternative fuel, and as the second trial production of combustible ice was successful, the development prospect of natural gas can be expected. This paper mainly introduces the research status of natural gas engine at home and abroad, the advantages of natural gas, focuses on the analysis of the emission of natural gas engine,so as to provide reference for its subsequent development.

Sustainable Production of Emerging Diesel Additive from Butene by Palladium-Catalyzed Alkoxycarbonylation

Pentanoic esters are a new class of biofuels (additives) and are typically produced from biomass-derived levulinic acid/esters via hydrogenation-cyclization/ring-opening/hydrogenation three-step transformations. Here, a one-step and atom-economic alkoxycarbonylation route is developed to produce pentanoic esters from widely available 1-butene. Based on the screening of 21 monophosphine and 26 diphosphine ligands, a Pd/diphosphine ligand (bis(2-diphenylphosphinophenyl) ether, DPEphos) system gives 91% yield of linear and branched ethyl pentanoate (78/22 ratio) with a turnover number (TON) up to 26100 and demonstrates outstanding recycle potential. The apparent activation energy (Ea) of 1-butene alkoxycarbonylation in the presence of this catalytic system was estimated to be 89.4 kJ/mol via kinetic measurements. More importantly, homogeneously blending 10 vol % of the resultant esters in pure diesel can improve the low-temperature fluidity and pumpability of diesel and decrease the emission of exhaust pollutants of diesel without affecting the power performance of diesel engines. Compared with pure diesel, the CO, NOx, HC, and soot emission of blend diesel at 2500 rpm are reduced by 28%, 9%, 6%, and 42%, respectively. This work provides a promising route to produce high-performance fuel additive and simultaneously broadens the comprehensive utilization of C4 olefin.

A compensation mechanism for air pollutants generated by tourism-related land-based transportation: An exergy-based case study from Macao

This paper discusses the compensation standard for exhaust pollution and devises a compensation mechanism for Macao's tourism-related transport sector based on an integration of chemical exergy and universal exergy, using data on gasoline consumption by automobile sector retrieved from the transportation industry. The results reveal that: (1) the exergy values of air pollutant emissions increased from 1.53 × 1012 kJ in 2010 to 2.03 × 1012 kJ in 2019 (an increase of 1.33 times), and the exergy of CO, NOx, and SO2 emissions accounted for 77.5%, 20.4% and 2.1% of total exhaust emissions in Macao respectively. (2) In 2019, the monetary value of emission exergy, and the environmental costs of air pollution, were 1.7 times greater than in 2010. (3) If Light Rail Transit is compensated for, then the mean interval's values of the upper and lower limits of the compensation standard are 0.55 USD and 0.05 USD, respectively. When gasoline tax is used as a means of compensation it is necessary to raise its rate by about 8% based on the tax rate. A three-stage bargaining game model is used to provide evidence that this compensation standard is practical and acceptable.

Estimating mortality cost and social cost of CO2 emitted by items, applied to passenger vehicles

Over 60% of carbon emissions are from residential consumption. People in developed nations need to reduce their carbon footprints six-fold to stabilize CO2 levels in the atmosphere. This research develops a method of estimating and monetizing mortality costs of items. Mortality Cost of Carbon Rate (MCCR) is the fraction of a climate change related death that would probably occur over 80 yr with a specified temperature trajectory, from the emission of 1 tCO2e. MCCRs are allocated to items on an exponential curve generated from two researched MCCRs corresponding to temperature trajectories. MCC of an item (MCCI) is its MCCR multiplied by its life cycle CO2e emissions. The method was applied to the 2020 Australian passenger vehicle fleet and 6 vehicle types. MCCI was compared to mortalities from crashes and exhaust pollution. Total fleet mortality was estimated at around 62,000/ year. Mortality from 2020 CO2 emissions will probably be around 56,000 - 75 times higher than crash deaths - with uncertainty range 28,000 to 106,000, compared to toxic exhaust emissions 5,600 and crashes 750. A Sustainable Personal CO2 Footprint' of 1.5 t CO2/ person/ year was set as a benchmark for sustainable consumption. Electric buses, E-bicycles/ scooters and micro-EVs are sustainable and if universally adopted, would reduce mortality by 96%. Social Cost of Carbon Mortality Rate (SCCMR) monetizes MCCR using a global Value of a Statistical Life Year. SCCM of items (SCCMI) is calculated as for MCCI. Research estimates of MCCR and SCCMR vary according to assumed causes of mortality, temperature trajectories and discount rates; many are underestimated as they exclude some mortality damage sectors. Toxic exhaust emission and crash mortalities were monetized using the Australian Value of a Statistical Life. Total social mortality cost of a large 4 wd ICE diesel SUV was approximately $6300, current fleet average $4800, and micro-EV $400.

DESIGN OF A NOVEL DEVICE TO REDUCE ENGINE EMISSIONS

Air pollution is a threat in which air has adverse effects on humans and the ecosystem. It is caused by substances which may be solid particles, liquid droplets or gases. Pollutants are classified as primary and secondary. Primary pollutants include carbon monoxide and nitrogen oxides from automobile vehicle exhaust and secondary pollutants includes the Sulphur-dioxide released from factories. The aim of the present work is to fabricate a novel device to reduce the emission of harmful gases such as carbon monoxide, CO2, unburnt hydrocarbons, nitrogen oxides (NOX) which are released from the stationary Engines. Nowadays Diesel particulate filters are used in high-end vehicles to reduce the emission and we are using chemical solutions in our project to reduce the harmful gases released from stationary Engines. The chemical solution used in our project is ammonical cuprous chloride and potassium hydroxide and activated charcoal. Activated charcoal is coated on the baffle plates to absorb the carbon content and the heat generated in the combustion chamber and also filter the harmful nitrous and sulfur content produced by the engine.

An experimental investigation on the effects of magnesia and alumina nano additives on the exhaust emissions and performance of CI engine using spirulina microalgae biodiesel.

The need for non-renewable fuels is steadily decreasing with their ever-increasing cost and air pollution. As a result, renewable fuel such as biofuel is used as a fuel substitute for diesel engines. The effects of magnesia and alumina nanoparticles on the exhaust pollutants and performance of a naturally aspirated, 17.5 compression ratio, 4-stroke CI engine operating on spirulina microalgae biodiesel, and its amalgams were explored. Oxides of nitrogen, thermal efficiency, carbon dioxide, fuel consumption, and hydrocarbons were among the attributes studied. Test outcomes revealed that the doping of magnesia and alumina nano additives in spirulina biodiesel resulted in increased thermal efficiency and oxides of nitrogen, succeeded by a decrease in fuel consumption and hydrocarbons, at all loads, compared to amalgams without nano additives. At maximum load, the increase in thermal efficiency and oxides of nitrogen was found to be 1.15 and 1.46% with nano magnesia-doped blends when compared to corresponding spirulina blends. On the other, hand when nano alumina is doped in spirulina amalgams, the increase in thermal efficiency and oxides of nitrogen was observed to be 0.82 and 0.97%, respectively. Similarly, fuel consumption and hydrocarbons were reduced by 1.02 and 9.52%, 1.014, and 7.66%%, respectively, for magnesia and alumina-enriched biodiesel, contrasted to that of biodiesel blends.

Extraction and Performance Analysis of Hydrocarbons from Waste Plastic Using the Pyrolysis Process

Ecosystem destruction is one of today’s significant challenges due to fast industrialisation and an increasing population. It takes several years for solid trash, such as plastic bottles and super-market bags, to decompose in nature. In addition, plastic disposal techniques such as landfilling, reuse, and incineration pose significant threats to human health and the environment. In this paper, we investigated whether the impact of mixing biodiesel with waste oil from recycled plastic on the resulting fuel mixture’s yields better physical and chemical properties. Consequently, pyrolysis is one of the most advantageous and practical waste disposal methods as it is both environmentally benign and efficient. Pyrolysis is the high-temperature thermal breakdown of solid waste to produce pyrolytic oil. The pyrolytic (plastic) oil produced is converted to a hydrocarbon-rich pyrolytic fuel. Similar to diesel and gasoline, pyrolytic fuel has the same calorific value. Internal combustion engines may operate on pyrolytic fuel without suffering a performance reduction. Researchers examined engine performance and exhaust pollutants. The research discovered that the engine could operate on plastic pyrolysis fuel at full load, enhance brake thermal efficiency by 6–8%, and lower UBHC and CO emissions; however, nitrous oxide (NOx) emissions were noticeably higher. The findings demonstrated the possibility of using plastic pyrolysis fuel as a diesel substitute.

Numerical study on temporal and spatial distribution of particulate matter under multi-vehicle working conditions

The high growth in the use of underground diesel vehicles has led to a large number of exhaust pollutants, especially particulate matter (PM), which is a serious threat to the lives and health of underground personnel. In this paper, based on numerical simulations and field measurements, the temporal and spatial distribution of PM in the exhaust of two vehicles and the impact on the health of underground personnel was analyzed. The results showed that in both conditions, the airflow velocity between two vehicles showed a zonal distribution, and there was an airflow vortex in the chamber under the interaction of the wind. When the vehicles were running in the same direction into the wind, PM with a concentration range of 15.79–26.32 mg/m3 could reach the height of the human respiratory belt and was mainly distributed on the east side of the roadway. Therefore, underground personnel should avoid approaching the right area of the vehicle body. In addition, PM concentration around the driver position of the vehicle was still higher than the human contact limit, so the drivers of the vehicle would need personal protection. When the vehicles were running in the same direction with the wind, compared with the airflow inlet side, the amount of PM on the airflow outlet side increased more obviously with time, especially for PM with a concentration range of 21.05–31.58 mg/m3. Also, partial PM flowed into the chamber with the airflow, such that personnel should avoid being located on the downwind side of the vehicle, and personnel in the chamber should also have personal protection.

Effect of auto-exhaust pollution on leaf anatomy and micromorphology of Pistacia vera L.

One of the important causes of air pollution is automobile emissions Automobile exhausts can be toxic and harmful to plants. In light of this, this study aimed to examine the anatomical and micromorphological effects of auto exhaust pollution on Pistacia vera L. (Pistachio), an important agricultural plant. Pistachio leaflet samples taken from heavy traffic areas and rural areas were compared anatomically and micromorphologically. Also, the data were statistically evaluated. As a result of the study, it was seen that there are anatomical and micromorphological differences between the plant in the rural area and the plant in the heavy traffic area in the city center where air pollution and the number of cars are high. In particular, significant differences were detected in the epidermis surface and cuticle structure, trichome cover, stomatal characteristics, as well as mesophyll width, and epidermis anticlinal outer wall width. As a result, the study revealed that the agriculturally important P. vera is affected by pollution anatomically and micromorphologically.

Real world evaluation and control of vehicle engine exhaust air pollution using adaptive neural fuzzy inference system

Internal combustion engines are considered primarily responsible for air pollution. Accordingly, a concentrated effort has been made to reduce these pollutants which are emitted from the exhaust system of these engines while preserving energy and fuel consumption. There are also other sources besides internal combustion engines, such as power stations and those released from industry and home consumption. Industrial and household fuel consumers are also adding pollution. The industrial development requires the establishment of effective control systems to deal with its equipment to increase its operational life and increase its productivity with lower maintenance costs. Therefore, the aim of the study in this research is exposed to be used of adaptive neural fuzzy inference system to control the components of the emission of exhaust pollutants for gasoline vehicle. Exhaust pollutants consist of unburned carbon monoxide, hydrocarbons, carbon dioxide, water vapor nitrogen oxides, and energy produced from the combustion process which emit into atmosphere through the exhaust tailpipe. Also, there are hydrocarbons produced from gasoline vaporization and from the crankcase of the vehicle. The results indicate that the adaptive neural fuzzy inference system proves to be a useful tool for simulating and controlling vehicle engine exhaust emissions.

Design and Optimization of Electronic Nose Sensor Array for Real-Time and Rapid Detection of Vehicle Exhaust Pollutants

Traditional vehicle exhaust pollutant detection methods, such as bench test and remote sensing detection, have problems such as large volume, high cost, complex process, long waiting time, etc. In this paper, according to the main components of vehicle exhaust pollutants, an electronic nose with 12 gas sensors was designed independently for real-time and rapid detection of vehicle exhaust pollutants. In order to verify that the designed electronic nose based on machine learning classification method can accurately identify the exhaust pollutants from different engines or different concentration levels from the same engine. After feature extraction of the collected data, Random Forest (RF) was used as the classifier, and the average classification accuracy reached 99.92%. This result proved that the designed electronic nose combined with RF method can accurately and sensitively judge the concentration level of vehicle exhaust pollutants.. Then, in order to enable the electronic nose to be vehicle-mounted and to achieve real-time and rapid detection of vehicle exhaust pollutants. We used Recursive Feature Elimination with Cross Validation (RFECV), Random Forest Feature Selector (RFFS) and Principal Component Analysis (PCA) to optimize the sensor array. The results showed that these methods can effectively simplify the sensor array while ensuring the RF classifier’s classification recognition rate. After using RFECV and RFFS to optimize the sensor array, the RF classifier’s classification recognition rate of the optimized sensor arrays for vehicle exhaust pollutants reached 99.77% and 99.44%, respectively. The numbers of sensors in the optimized sensor arrays were six and eight respectively, which achieved the miniaturization and low-cost of the electronic nose. With the limitation of six sensors, RFECV is the best sensor array optimization method among the three methods.

Effect of butanol additive with mango seed biodiesel and diesel ternary blends on performance and emission characteristics of diesel engine

ABSTRACT Current research investigates performance and emission characteristics of single cylinder 4-S diesel engine powered by different ternary fuel blends of diesel, mango seed (potential renewable feedstock of energy generation) biodiesel (MSB) and butanol (promising, sustainable, renewable and eco-friendly) oxygenated additive at different loading conditions experimentally. For the purpose, oil is extracted from discarded mango seeds through Soxhlet apparatus and biodiesel is prepared through transesterification process. Different blending mixture of MSB (fixed in 20%), diesel (80%, 75%, 70%, and 65%) and butanol (0%, 5%, 10%, and 15%) additive on their volume basis are prepared through magnetic stirring. These blends are named as MSB20B0, MSB20B5, MSB20B10, and MSB20B15, respectively. Experiment reveals that MSB20B5 lowers the BSFC by 25.79% and increases the BTE by 8.46% in comparison to MSB20B0 at maximum loading and approaching diesel fuel. In addition, MSB20B5 blend reduces the exhaust pollutants such as HC, NOx, CO2, and CO by 9.16%, 17.74%, 9.92%, and 13.33%, respectively, compared to MSB20B0 biodiesel blend at maximum loading. Overall, MSB20B5 ternary blend improves engine performance and reduce emissions hence recommended for diesels.

Application of Remote Sensing Methodology for Vehicle Emission Inspection

Remote sensing detection of vehicle emissions is an effective supplement to the statutory periodic inspection of in-use vehicle emissions and it is a convenient technical method for real-time screening of high-emission vehicles. The principle of remote sensing detection is to inversely calculate the absolute concentrations of gaseous pollutants in vehicle exhaust according to the relative volume concentration ratio of each exhaust component to carbon dioxide (CO2) in the vehicle exhaust plume. Because the combustion mechanisms of gasoline engines and diesel engines are different, different inversion calculation methods of remote sensing data must be applied. The absolute concentrations of gasoline vehicle gaseous emissions measured by remote sensing can be calculated by the inversion calculation method based on the theoretical air–fuel ratio combustion mechanism. However, the absolute concentrations of diesel vehicle nitrogen oxide (NOx) measured by remote sensing must be calculated by the inversion calculation method based on the correction of the excess air coefficient. For the integrated remote sensing test system of gasoline and diesel vehicles, it is necessary to determine the vehicle category according to the vehicle type and license plate and adopt different inversion calculation methods to obtain the correct remote sensing results of vehicle emissions. The big data statistical analysis method for vehicle emission remote sensing results can quickly screen high-emission vehicles and dynamically determine the remote sensing emission screening threshold of high-emission vehicles as the composition of in-use vehicles changes and the overall emission of vehicles declines, so as to achieve dynamic and accurate screening of high-emission vehicles.

Assessment of diesel exhaust pollutants effects in Tillandsia capillaris and Ramalina celastri by laboratory trials

Traffic-related air pollution is one of the most relevant environmental problems in urban areas. Several cryptogams (i.e., lichens and mosses) and vascular species have been employed to monitor urban air pollution since they allow the assessment of air quality in a large number of sampling sites simultaneously at low cost. In large urban cities, vehicle emissions are frequently the major source of air pollution along with residential energy (for cooking and heating), industry, power generation, and waste incineration. Biomonitors in these urban environments are exposed to a mixture of pollutants making it difficult to identify which pollutant causes the greatest damage to organisms. However, studies that analyze the effect of pollutants emitted by vehicle exhaust are scarce and in the particular case of the most used biomonitor species in Argentina, no analysis of how they are affected by vehicle emissions has been carried out so far. So, the aim of this work was to analyze changes in physiochemical parameters (pigment content, pro-oxidant products, and sulfur accumulation) in Ramalina celastri, and heavy metal accumulation in Tillandsia capillaris, exposed to diesel exhausts under laboratory conditions. A strong damage in the photosynthetic apparatus of R. celastri was observed as well as metal concentration in T. capillaris after 20 min of exposure and 48 h of permanence in the exposure chambers. The results indicate that not only the particles and metals cause damage to these two well-known biomonitors, but the interaction of these pollutants with other components of the atmosphere that form different secondary pollutants, together with a longer exposure time, could cause the highest level of damage in them.

Performance and pollutant characteristics of an old generation diesel engine fuelled with dual-fuel diesel-dimethyl ether

An old generation diesel engine running on dual-fuel dimethyl ether (DME) and diesel was tested for pollution reduction and performance enhancement. DME was pre-mixed with intake air using a single-port gaseous fuel injection system to replace 5% (DME5) and 10% (DME10) diesel. Study results show that the fuel economy improves when the engine operates with dual fuel. The brake-specific energy consumption reduces by 2.5% and 3.0% at full load condition and 4.5% and 5.1% at a medium speed of 1600 rpm on average for DME5 and DME10 compared to pure diesel case. The in-cylinder pressure, temperature, and vibration rate were evaluated to determine DME's effect on engine combustion. The impact of DME was noticeable as exhaust pollutants enhanced remarkably for NOx and smoke components. When the engine was fueled with DME5 and DME10, the specific particulate matter fell dramatically by 32.90% and 50.23%, NOx declined moderately by 8.66% and 20.39%.

Influence of exposure history on the particle retention capacity and physiological responses of Euonymus japonicus Thunb. var. aurea-marginatus Hort.

Green plants in urban environments experience cyclical particulate matter stress. And this history of exhaust exposure may generate stress memory in plants, which may alter their subsequent response. Studies combining urban pollution characteristics and stress memory are limited. Therefore, we selected E. japonicus var. aurea-marginatus, a common urban greening tree species in the Yangtze River Delta, and conducted an experiment in three periods: the initial pollution period (S1: 28 days), the recovery period (R: 14 days) and the secondary pollution period (S2: 28 days). The experimental design consisted of an elevated pollution treatment (173 μg•cm−3) and an ambient control (34 μg•cm−3) with three replicates. In S2, the net total particle retention and saturated particle retention decreased by 11.5% and 19.3%, respectively, while PM10 and PM2.5 did not change significantly. E. japonicus var. aurea-marginatus exhibited recovery of chlorophyll levels, slower degradation of carotenoid, faster accumulation of ASA, lower accumulation of MDA, reduced activity of SOD under the second pollution period, and the period had a significant effect on the physiological indicators. Collectively, the effect of autoexhaust exposure history on the particle retention capacity of selected plant varied across particle sizes, and stress memory may confer plant resistance to recurrent exhaust pollution via combined regulations of physiological responses. Fine particles which pose a great risk to human health arise predominantly from vehicular traffic and energy production. So, E. japonicus tends to play a stabilising role in particle retention in industrial, traffic and residential areas.