PM Emissions Research Articles

2050 UK shipping emissions of NOx, SOx, PM10, and PM2.5: What are the determining factors, is the zero pollution by 2050 feasible, and will the reduction rate for these pollutants be at the same pace?

2050 UK shipping emissions of NOx, SOx, PM10, and PM2.5: What are the determining factors, is the zero pollution by 2050 feasible, and will the reduction rate for these pollutants be at the same pace?

Assessment of Dust Retention Capacity and Metal(Loid) Accumulation in Plants of Singrauli Region, India

ABSTRACTParticulate matter (PM) emissions from activities associated with the coal industry in regions like Singrauli, India, where thermal power plants and heavy traffic are prevalent, pose significant risks to human health and the ecosystem due to dust and heavy metal pollution. The mean concentrations of pollutants ranged from 151 to 436 and 48 to 166 μg/m3 for PM10 and PM2.5, respectively. The study examined the dust retention capacity (DRC) of 30 plants, considering three particle sizes (PM10, PM2.5, and PM0.2). Among them, the leaves of Ficus benghalensis (4.35 mg/cm2), Anogesissus latifolia (3.77 mg/cm2), Butea monosperma (3.74 mg/cm2), Neolamarckia cadamba (3.34 mg/cm2), Lantana camara (3.22 mg/cm2), and Calotropis gigantea (3.14 mg/cm2) showed high DRC. Estimation of the geo‐accumulation index of soil revealed that elements such as As, Cr, Cu, Fe, Mn, Ni, Pb, V, Zn, Li, and Al were found to be higher, indicating that the study area could be classified under the extremely polluted category. High accumulation of metal(loid)s (in mg/kg) was observed in plants of Alstonia scholaris (Cd = 8.5 ± 1), B. monosperma (Cr = 384.25 ± 26.78 and Pb = 13.5 ± 1.5), and Saraca asoca (Zn = 198.63 ± 13.89). Finally, the leaf surface analysis confirmed that plants with elongated glandular trichomes, furrows/ridges, rough texture, ruptured surfaces, and deep grooves could retain a greater amount of dust. To establish green belts near the coal mine areas, the study recommends using the aforementioned plants to concurrently retain the emitted PM and associated metal(loid)s.

Experimental investigation on metal, PM and unregulated emissions along with their toxicity from conventional diesel and RCCI engines employing gasoline and methanol as low reactivity fuels

Experimental investigation on metal, PM and unregulated emissions along with their toxicity from conventional diesel and RCCI engines employing gasoline and methanol as low reactivity fuels

Characteristics of inland ship and the effect of combined diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) aftertreatment system on their pollutant emissions.

Characteristics of inland ship and the effect of combined diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) aftertreatment system on their pollutant emissions.

Furniture Design with an Ecological Approach to Improve Air Quality

As the significance of environmental sustainability continues to grow, furniture designs are now focusing not only on aesthetics, functionality, and ergonomics but also on ecological compatibility. The primary objective of this study is to evaluate the impact of plant-integrated furniture designs on CO₂, CO, PM2.5, and PM10 emissions while also assessing the particulate matter (PM) retention capacity of the materials used. Additionally, the effects of furniture shape and material selection on environmental sustainability will be scientifically analyzed. Within the scope of this study, emission measurements will be conducted, and the materials used in furniture designs will be compared and discussed based on these results. By comparing the findings from different furniture samples, the most environmentally sustainable design combinations for outdoor furniture will be proposed. This study aims to provide a scientific foundation for sustainable furniture design and the reduction of environmental impacts, offering valuable insights for designs that achieve both aesthetic and environmental benefits. The findings reveal the potential of plants in absorbing PM10, PM2.5, CO, and CO₂ while improving air quality. Plant-integrated furniture designs have demonstrated significantly greater absorption of harmful emissions compared to non-plant designs, thereby contributing positively to air quality. Furthermore, the use of natural stone and wood materials in furniture has shown notable differences in particulate matter retention capacity.

Emission Control in Sulphuric Acid Treatment Plant, HIL - Birla Copper, Dahej, Gujarat

Being the world`s 2nd Largest producer of Copper Rods and leading copper producer in India, serving over held of the Indian demand for refined Copper. The process involves electrolytic ally refined, 99.99% pure, continuous cast Copper rods, O2 free rods, from LME grade copper Cathodes. Sulphur Acid treatment of copper cathodes is primarily used in the electro winning process, where copper is extracted from a solution containing Copper Ions and purified – in this process sulphuric acid acts as an electrolyte. Since, Sulphuric acid being used is very highly concentrated hence, the associated environmental damages and risks are high too. This paper will describe various technology options including: Flue Gas Desulfurization System, Spray Dryer Absorber (SDA), Circulating Dry Scrubber (CDS), Limestone-based Wet FGD, Low NOX burners, Selective Non-Catalytic Reduction, Electrostatic Precipitator, Bag House Dust Collector, all of which have been evaluated and installed extensively to reduce SO2, NOx, PM and other emissions. As each technology having advantage and disadvantage, for each of the technologies considered, major features, potential operating and maintenance cost impacts, as well as key factors that contribute to the selection of one technology over another are discussed here.

Evaluation of Turkey’s Road-Based Greenhouse Gas Inventory and Future Projections

As road traffic in Turkey is a significant source of emissions due to the increasing number of vehicles on the road, the goal of this study is to calculate greenhouse gas emissions from Turkey’s roads between 2010 and 2020, create an inventory, and estimate possible emissions until 2050. In the study, both greenhouse gases (carbon dioxide (CO2) and nitrous oxide (N2O) and co-emitting air pollutants that indirectly contribute to climate change (ammonia—NH3, nitrogen oxide—NOX, sulfur dioxide—SO2, carbon monoxide—CO, non-methane volatile organic compounds—NMVOC, and particulate matter—PM) were investigated. The study revealed that the total number of vehicles using state roads in Turkey increased by 60% between 2010 and 2020. As a result, emissions of CO2, N2O, NH3, NOX, SO2, CO, NMVOC, and PM increased by 29.6%, 24.2%, 0.5%, 19.9%, 9.9%, 18.2%, 21.5%, and 39.7%, respectively. When emissions were analyzed on a provincial basis, particular attention was drawn to provinces with high levels of urbanization. Based on forecast studies, the total number of vehicles registered for traffic will increase by 105% by 2050. Due to this increase, CO2, N2O, NH3, NOX, SO2, CO, NMVOC, and PM emissions are estimated to increase by 149.17%, 151.78%, 154.39%, 138.95%, 150.97%, 153.09%, 152.09%, and 151.47%, respectively.

Theoretical Analysis of Suspended Road Dust in Relation to Concrete Pavement Texture Characteristics

Particulate matter (PM) originating from road dust is an increasing concern in urban air quality, particularly as non-exhaust emissions from tire–pavement interactions gain prominence. Existing models often focus on meteorological and traffic-related variables while oversimplifying pavement surface characteristics, limiting their applicability across diverse spatial and traffic conditions. This study investigates the influence of concrete pavement macrotexture—specifically the Mean Texture Depth (MTD) and surface wavelength—on PM10 resuspension. Field data were collected using a vehicle-mounted DustTrak 8530 sensor following the TRAKER protocol, enabling real-time monitoring near the tire–pavement interface. A multivariable linear regression model was used to evaluate the effects of MTD, wavelength, and the interaction between silt loading (sL) and PM10 content, achieving a high adjusted R2 of 0.765. The surface wavelength and sL–PM10 interaction were statistically significant (p < 0.01). The PM10 concentrations increased with the MTD up to a threshold of approximately 1.4 mm, after which the trend plateaued. A short wavelength (<4 mm) resulted in 30–50% higher PM10 emissions compared to a longer wavelength (>30 mm), likely due to enhanced air-pumping effects caused by more frequent aggregate contact. Among pavement types, Transverse Tining (T.Tining) exhibited the highest emissions due to its high MTD and short wavelength, whereas Exposed Aggregate Concrete Pavement (EACP) and the Next-Generation Concrete Surface (NGCS) showed lower emissions with a moderate MTD (1.0–1.4 mm) and longer wavelength. Mechanistically, a low MTD means there is a lack of sufficient voids for dust retention but generates less turbulence, producing moderate emissions. In contrast, a high MTD combined with a very short wavelength intensifies tire contact and localized air pumping, increasing emissions. Therefore, an intermediate MTD and moderate wavelength configuration appears optimal, balancing dust retention with minimized turbulence. These findings offer a texture-informed framework for integrating pavement surface characteristics into PM emission models, supporting sustainable and emission-conscious pavement design.

Microstructural Characterization of the Mn Lepidolite Distribution in Dark Red Clay Soils

Lepidolite is one of a small number of minerals that contains a significant amount of lithium. Some areas, like the Apuseni and Metalifer Mountains in Romania, present dark red layers intercalated with reddish-yellow clay soils with interesting aspects. X-ray diffraction (XRD) analysis coupled with polarized light optical microscopy (POM) revealed that this dark red soil contains a large amount of fine microstructured lepidolite (24–35%) mixed with quartz sand and fine traces of kaolinite and muscovite. Scanning electron microscopy (SEM) elemental analysis revealed a typical clay composition with Mn traces (specific to red lepidolite), confirming POM observation. SEM also revealed fine tabular platelets of lepidolite with a maximum size of 1.5 µm surrounding quartz particles (5–50 µm), indicating the presence of numerous nano fractions. Their presence was confirmed by atomic force microscopy (AFM), which showed particle sizes ranging from 40 to 60 nm, closely matching the crystallite size estimated using the Scherrer formula. The finest fraction allows easy separation from the quartz sand through bi-distilled water washing. Quartz particles settle at the bottom of the container, while the finest lepidolite particles are easily separated. Water evaporation ensures their recovery. Thus, the enriched lepidolite powder could be utilized for specific applications in the lithium industry. On the other hand, the large number of the finest particles found in the samples investigated presents the risk of PM1, PM2.5m, and PM10 emission, with impacts on atmospheric environmental safety.

Understanding particulate matter emissions from cooking meals, health impacts and policy path in Ecuador.

Cooking is a major source of indoor air pollution, but little is known about its emissions or health impacts in Ecuadorian households. This study quantified PM₂.₅ and PM₁₀ emissions from six common menus (three fried, three stewed) cooked in a real-life kitchen in Guayaquil lacking natural or mechanical ventilation. Each menu was replicated 30 times, yielding 180PM concentration profiles. After quality control, 120 profiles were retained for analysis. Median PM₂.₅ and PM₁₀ 24h concentrations were 16μg/m3 and 21μg/m3, respectively-exceeding WHO 24-hour guidelines 16% for PM₂.₅. Using Disability-Adjusted Life Years (DALYs), the harm from exposure was estimated at 990 DALYs per 100,000 person-years for the analyzed cooking scenarios. These levels indicate quantifiable chronic health risks despite emissions being lower than in other Low Middle Income Countries studies. Findings support the need for indoor air quality guidelines, ventilation strategies, and public health policies tailored to urban Latin American households.

Assessment of reductions in CO, PAHs and PM emissions in a forced-draft biomass gasification cookstove

Assessment of reductions in CO, PAHs and PM emissions in a forced-draft biomass gasification cookstove

Evaluating public exposure to airborne particulates from major incident fires: A back trajectory plume modelling approach.

Evaluating public exposure to airborne particulates from major incident fires: A back trajectory plume modelling approach.

The Co-Firing of Pine Biomass and Waste Coal in 100 and 600 MW Power Plants: A Sustainable Approach to Reduce GHG Emissions

Climate change is a global issue that has gained much attention recently. Co-firing biomass with coal/waste coal reduces the electricity sector’s GHG emissions sustainably. This study uses commercial software to model waste coal and biomass co-firing in 100 MW and 600 MW power plants. The objective is to assess the effects of fluid types (subcritical and supercritical), plant capacities (100 MW and 600 MW), boiler types (pulverized coal and circulating fluidized bed boilers), biomass and waste coal co-firing ratios (0:100, 20:80, 40:60, 60:40, 80:20, and 100:0), and carbon capture and storage efficiencies (0%, 90%, 95%, and 97%) on performance parameters such as net plant efficiency, heat rate, net plant CO2 and SO2, and particulate matter emissions. The feedstocks selected for this investigation include anthracite waste coal and loblolly pine biomass. As the biomass fraction increases from 0% to 100%, co-fired power plants net efficiency increases by 3–8%. Supercritical plants had a 6% higher net plant efficiency than the subcritical plants. The study found that the biomass’s high heating value decreased the fuel flow rate and reduced plant CO2 emissions by 10–16%. With 100% biomass power plant feed and 90% carbon capture and storage efficiency, CO2 emissions drop by 83% and SO2 and PM emissions drop to zero.

Review: Implications of Air Pollution on Trees Located in Urban Areas

Air pollution in cities is intensifying, inevitably affecting all living organisms, gincluding trees. Urban trees are vital for cities because they improve air quality and regulate the climate; however, like all living organisms, they are affected by the environment to which they are exposed. In cities, the primary atmospheric pollutants of inorganic origin include NO, SOX, COX, O3, and suspended particulate matter (PM2.5 and PM10). Each of these pollutants impacts population health, with urban trees undergoing a series of consequent alterations. In this study, we review the inorganic pollutants identified by the World Health Organization (WHO) as impacting air quality in cities in different regions of the world; discuss the regulations that govern NO2, SO2, CO, O3, and PM2.5 and PM10 emissions and their impact they have on urban trees; analyze the processes involved in pollutant–tree interactions and the related tolerance and/or resistance mechanisms; and determine the tree species with the best tolerance, classified using an air pollution tolerance index (APTI).

In-situ measurements of emissions and fuel loading of non-catalytic cordwood stoves in rural Oregon

ABSTRACT Residential wood combustion is an important source of heat for millions of households, yet it represents the third largest source of PM2.5 pollution in the United States. Development of cleaner-burning cordwood heating stove designs is necessary to reduce health and climate impacts from this important renewable energy source. Effective design requires an understanding of operation and performance of existing stoves in real-world settings. In this study, one uncertified stove, three EPA Phase I or II stoves, and three New Source Performance Standards (NSPS) stoves were sampled for 48 consecutive hours each in households in rural Oregon. The methodology included stack sampling of undiluted CO and CO2 with a diluted sample train for cooling and condensation of PM and an optical sensor to apportion integrated gravimetric measurements of particle mass over time. A data-logging scale directly measured fuel loading mass and timing, enabling emissions mass calculations via both stack flow and carbon balance methods. Results across all stoves showed that together cold starts and reloads contribute 70% of total PM emissions. The measured period emission rate of PM over all stoves was 5.6 ± 2.2 g/hr, while the average emission factor of PM was 8.5 ± 3.0 g/kg. There was a statistically significant reduction of between 29.6–48.5% in the PM emission rate during all periods except burnout and a 40.6 increase in thermal efficiency of the NSPS stoves relative to the single uncertified stove during the fire period. Implications of this study include both a database of in-field emissions and efficiency performance measures and comparison of stove certification levels that are useful to wood stove designers and policymakers for optimizing air quality impacts of stove-user systems. In addition, the methods demonstrated here can be used by researchers to promote needed field monitoring capabilities at a lower cost and complexity. Implications: Detailed time-apportioned PM emissions data identified conditions leading to high emission rates including startup, large loads, and operation of an uncertified stove. Provides wood stove designers insights toward optimizing performance of future stove designs, and policy makers information about the impact of user and technology on air quality objectives. Demonstrated new equipment for real-time emissions and fuel consumption monitoring that enables time-resolved PM and direct fuel mass measurements to yield better design insights for heating stoves. This method can be used by other researchers to gather much needed field measurements at a lower cost and complexity than existing methods.

Toxicological assessment of particulate and unregulated emissions from methanol and gasoline fueled reactivity controlled compression ignition engines

Reactivity-controlled compression ignition (RCCI) engines have emerged as a promising technology for achieving higher thermal efficiency while minimizing particulate (PM) and NOx emissions. However, concerns arise from the unregulated emissions of RCCI engines due to low temperature and premixed combustion. These unregulated species may condense on formed PM, potentially elevating the toxicity potential. This study investigates the toxicity potential of PM and unregulated emissions from RCCI engines employing gasoline and methanol as low-reactivity fuel and diesel as a high-reactivity fuel. In-vitro cytotoxicity tests with the BEAS-2B (human epithelial cell line) are conducted to characterize PM toxicity. A lung compartment model is used to estimate the particle risk, focusing on lung retention of PM particles emitted. Cancer risk potential is calculated for formaldehyde and acetaldehyde, constituents of unregulated emissions, to evaluate their impact on human health. Environmental risk assessment includes estimation of global warming potential, acidification potential, eutrophication potential, and ozone-forming potentials equivalents. Results indicate that with premixing ratio increases, unregulated emissions, cancer risk, cytotoxicity, and adverse environmental impacts increase. Methanol Diesel-RCCI engine particles exhibit lower lung retention than Gasoline Diesel-RCCI under all tested conditions. Methanol reduces cytotoxicity and particle inhalation toxicity at medium engine load. This study offers insights into the complex relationship between fuel, operating parameters, and the toxicity potential of emissions from RCCI engines.

Joint Optimization of Route and Speed for Methanol Dual-Fuel Powered Ships Based on Improved Genetic Algorithm

Effective route and speed decision-making can significantly reduce vessel operating costs and emissions. However, existing optimization methods developed for conventional fuel-powered vessels are inadequate for application to methanol dual-fuel ships, which represent a new energy vessel type. To address this gap, this study investigates the operational characteristics of methanol dual-fuel liners and develops a mixed-integer nonlinear programming (MINLP) model aimed at minimizing operating costs. Furthermore, an improved genetic algorithm (GA) integrated with the Nonlinear Programming Branch-and-Bound (NLP-BB) method is proposed to solve the model. The case study results demonstrate that the proposed approach can reduce operating costs by more than 15% compared to conventional route and speed strategies while also effectively decreasing emissions of CO2, NOx, SOx, PM, and CO. Additionally, comparative experiments reveal that the designed algorithm outperforms both the GA and the Linear Interactive and General Optimizer (LINGO) solver for identifying optimal route and speed solutions. This research provides critical insights into the operational dynamics of methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies for conventional fuel vessels are not directly applicable. This study provides critical insights into the optimization of voyage decision-making for methanol dual-fuel vessels, demonstrating that traditional route and speed optimization strategies designed for conventional fuel vessels are not directly applicable. It further elucidates the impact of methanol fuel tank capacity on voyage planning, revealing that larger tank capacities offer greater operational flexibility and improved economic performance. These findings provide valuable guidance for shipping companies in strategically planning methanol dual-fuel operations, enhancing economic efficiency while reducing vessel emissions.

An Estimation Model of Emissions from Burning Areas Based on the Tier Method

The emissions of particulates from burning agricultural fields threaten the environment and human health, contributing to air pollution and increasing the risk of respiratory and cardiovascular diseases. An analysis of total suspended particulate (TSP), PM2.5, and PM10 emissions from crop residue burning is presented in this study. A primary goal is to improve emission estimation accuracy by integrating satellite imagery from modes of Moderate Resolution Imaging Spectroradiometers (MODIS) and Visible Infrared Imaging Radiometers (VIIRS) with traditional data. Particulate emissions were estimated using Tier 1 and Tier 2 methodologies outlined in the EEA/EMEP Emission Inventory Guidebook based on thermal anomaly data from satellite observations. According to the findings, burning wheat, maize, barley, and rice residue accounts for most emissions, with significant variations identified in India, China, and the United States. The variations highlight the need for a location-specific approach to emission management. Particulate emissions cause adverse environmental and health impacts, which can be minimized by targeting mitigation strategies at key emission hotspots. The research provides important insights to inform policymakers and support developing strategies to reduce fine particulate agricultural emissions.

Investigation of Dust Emission in Limestone Mines and its Statistical Prediction using Supervised Machine Learning (Regression) Modelling

In India, the fugitive dust emissions in the processing plant and mining area of limestone mines are very high. The dust emission of (particulate matter) PM10 and PM2.5 forms an unsafe working environment for workers in processing plant areas and mining areas. The excessive emission of PM10 and PM2.5 will cause lung-related diseases to the workers and the people existing in the adjacent areas of the mine. The dust emission majorly causes air pollution to occur due to the distribution of particulate matter in the work area. This study majorly investigates the dust emission levels of PM10 and PM2.5 in the limestone mine of Kadapa, Andra Prasad, India. The investigation on the dust emission of PM10 and PM2.5 was carried out as per the guidelines of DGMS and MoEF and CC guidelines, with a specific focus on PM10 and PM2.5 particulate matter. From the study, it was clear that the dust emission levels of PM10 and PM2.5 in the mine area and some parts of the processing area were below the permissible limit of 1200 μg/m³ as per the National Ambient Air Quality Standards (NAAQS, 2009). It was also found that the dust emission levels of PM10 and PM2.5 in the crushing and screening area of the processing plant were above the permissible limit of 1200 μg/m³. Further the statistical prediction model was developed using linear, quadratic and cubic supervised machine learning (regression) modelling. The results indicated that the cubic regression model will provide the accurate prediction of fugitive dust emission with lower error and standard deviation.

Impact of Electric Vehicle Transition Scenarios on Road Transport Emission in Semarang City

The transition from fossil-fueled vehicles into electric vehicles is considered to be a strategy that can significantly reduce emissions and improve urban air quality. This study aims to examine the impact of the battery electric vehicles growth in Semarang City on carbon emissions within the road transport sector. Projections were made to assess the long-term impact and contribution of this trend towards meeting government targets in 2030 and 2060. Low Emission Analysis Platform (LEAP) software was used to estimate carbon emissions based on amount of vehicle and vehicle kilometer traveled (VKT) data. Three scenarios were set: the BEV scenario, which focuses on the widespread use of electric vehicles, demonstrates a significant reduction, especially in PM10 emissions, highlighting the advantages of transitioning away from internal combustion engine vehicles. The EMX scenario, which emphasizes an energy mix plan to support electricity, does not demonstrate a significant reduction in emissions. The COM scenario, which combine the BEV and EMX scenarios achieves the lowest emissions overall, indicating that a comprehensive strategy is most effective for achieving long-term emission reductions. All scenarios indicate the need for more aggressive policies, technological innovations, and carbon capture strategies to achieve reduction targets, particularly in the road transport sector.