Source Of Urban Air Pollution Research Articles

Simulation of the cooking organic aerosol concentration variability in an urban area

Cooking activities are a source of urban air pollution that has been often ignored. The corresponding particulate matter (PM) emissions are not included or are seriously underestimated in urban emission inventories. However, several field studies suggest that cooking organic aerosol (COA) can be an important component of the organic PM in urban areas. In this study we propose and evaluate a methodology for the simulation of the COA concentration and its variability in space and time in an urban area. The city of Patras, the third biggest in Greece, is used for this first application during a typical late summer period.The spatial distribution of COA emissions was based on the exact location of restaurants and grills, while the emission rates on the per person meat consumption in Greece. We estimated COA emissions of 0.6 g d−1 per person that corresponds to 150 kg d−1 for Patras. The temporal distribution of COA emissions was based on the known cooking times and the results of past field studies in the area. We estimated that half of the daily COA is emitted during dinner time (21:00–0:00 LT), while approximately 25% during lunch time (13:00–16:00 LT). The COA is simulated using the Volatility Basis Set approach and is treated as semivolatile and reactive. Its volatility distribution is based on laboratory measurements of COA from meat grilling.The chemical transport model PMCAMx predicts that the COA concentration reaches values up to 15 μg m−3 during the nights of the simulated summertime period in an area with high restaurant density. The average predicted COA concentration is around 1.2 μg m−3 in the center and 0.1–0.2 μg m−3 in the suburbs of the city. COA has a distinct daily profile that peaks during lunch (13:00–15:00 LT) and dinner (21:00–23:00 LT) periods. The local production of secondary COA is predicted to be slow and it represents just a few percent of the total COA. The model reproduces well the average PM2.5 concentrations at the outskirts of Patras and its overall performance for hourly PM2.5 values is rated as good. A 50% uncertainty of the reported COA emissions is estimated based on the results of the sensitivity tests and the observations in the city core. The emissions can be further constrained and the corresponding uncertainty can be further reduced with measurements focusing on COA and not on total PM2.5 as was the case in this study. These should take place in different areas of the city, selected based on the model predictions, to also improve our estimates of the spatial distribution of the emissions.

Give full play to the role of M station and promote the new normal of vehicle emission pollution control

With the rapid growth of car ownership in use, vehicle emissions have become one of the main sources of urban air pollution. In view of the problems existing in the maintenance and treatment of vehicle emission pollution, this paper puts forward the enthusiasm and necessity of speeding up the establishment of compulsory maintenance station (M station), adheres to the road of realizing practice, and combines with the practical experience of vehicle emission control in Jiaozuo City, puts forward the practical path of the new normalization management of vehicle emission compulsory maintenance, creatively promotes the treatment of vehicle emission Career development. It is of great significance to solve the more and more outstanding vehicle exhaust pollution.

A Mayor's Perspective on Tackling Air Pollution

Abstract We review recent empirical economic studies on urban ambient air pollution from a mayor’s perspective. We discuss the sources of urban air pollution, the economic costs that it imposes, and the policy tools available to a mayor to alleviate it. For economic costs, we briefly summarize traditional estimates of health and mortality costs and focus on more recent evidence on mental and psychological health, labor productivity and supply, avoidance behavior, willingness to pay for clean air and long-term (multi-decade) impacts. The policy tools we evaluate include pollution information disclosure, auto license and driving restrictions, congestion tolls, public transit investments, emission standards and controls, and gasoline taxes. We also discuss challenges posed by transboundary pollution across cities and the extent to which mayors’ incentives encourage tackling air pollution under different political systems. We briefly discuss possible future research agendas.

The Impacts of Urban Air Pollution Emission Density on Air Pollutant Concentration Based on a Panel Model

In terms of urban planning, the impact of urbanization and high density on the environment is a major issue. This study intended to analyze the effect of spatial density characteristics of urban air pollution sources on urban air pollution concentration using a panel model. As the total population density, the number of cars registered per capita, and the total emission facility density increased, together with a closer distance to a thermal power plant, the nitrogen dioxide(NO2) concentration increased. Net population density was also found to have the greatest impact on the structure and density of emission sources of ozone(O3) followed by the number of cars registered per person and the total emission facility density. It was confirmed that particular matter(PM10) concentrations are strongly influenced in positive directions by the spatial density characteristics of emission sources that show significant differences between regions.

Internal and External Costs of Motor Vehicle Pollution

On-road emissions, a dominant source of urban air pollution, damage human health. Emissions increase air pollution intake (and damage health) of travelers (internal costs), and of non-travelers (external costs). This research constructs a framework modeling the microscopic production of emission cost from the vehicle and link level and applies it to a metropolitan road network. It uses project-level Motor Vehicle Emission Simulator (MOVES) simulations to model link-specific on-road emissions, and then employs the RLINE dispersion model to estimate on- and off-road concentrations of pollutants from vehicles. The internal and external emission costs are measured accordingly by counting the health damage costs of travelers and general population because of exposure. The framework is applied to the Minneapolis-St. Paul (Twin Cities) Metropolitan Area as a proof-of-concept. The estimates show that highways have higher emission concentrations because of higher traffic flow, but that the internal and external emission costs per vehicle kilometer traveled are lower. The emission costs that commuters impose on others greatly exceeds that which they bear. This modeling process is replicable for planners and practitioners assessing emission costs in other regions.

Nanodomains in cardiopulmonary disorders and the impact of air pollution.

Air pollution is a major environmental threat and each year about 7 million people reported to die as a result of air pollution. Consequently, exposure to air pollution is linked to increased morbidity and mortality world-wide. Diesel automotive engines are a major source of urban air pollution in the western societies encompassing particulate matter and diesel exhaust particles (DEP). Air pollution is envisioned as primary cause for cardiovascular dysfunction, such as ischemic heart disease, cardiac dysrhythmias, heart failure, cerebrovascular disease and stroke. Air pollution also causes lung dysfunction, such as chronic obstructive pulmonary disease (COPD), asthma, idiopathic pulmonary fibrosis (IPF), and specifically exacerbations of these diseases. DEP induces inflammation and reactive oxygen species production ultimately leading to mitochondrial dysfunction. DEP impair structural cell function and initiate the epithelial-to-mesenchymal transition, a process leading to dysfunction in endothelial as well as epithelial barrier, hamper tissue repair and eventually leading to fibrosis. Targeting cyclic adenosine monophosphate (cAMP) has been implicated to alleviate cardiopulmonary dysfunction, even more intriguingly cAMP seems to emerge as a potent regulator of mitochondrial metabolism. We propose that targeting of the mitochondrial cAMP nanodomain bear the therapeutic potential to diminish air pollutant — particularly DEP — induced decline in cardiopulmonary function.

Technology and the Effectiveness of Regulatory Programs over Time: Vehicle Emissions and Smog Checks with a Changing Fleet

Personal automobile emissions are a major source of urban air pollution. Many U.S. states control emissions through mandated vehicle inspections and repairs. But there is little empirical evidence directly linking mandated inspections, maintenance, and local air pollution levels. To test for a link, we estimate the contemporaneous effect of inspections on local air quality. We use day-to-day, within-county variation in the number of vehicles repaired and recertified after failing an initial emissions inspection, with individual-level data from 1998–2012 from California’s inspection program. Additional re-inspections of pre-1985 model year vehicles reduce local carbon monoxide, nitrogen oxide, and particulate matter levels, while re-inspections of newer vehicles with more modern engine technology have no economically significant effect on air pollution. This suggests emissions inspections have become less effective at reducing local air pollution as more high-polluting vehicles from the 1970s and 1980s leave the road, and provides an example of how the social efficiency of programs can change under improving technologies. We also estimate the importance of station quality, using a metric devised for California’s new STAR certification program. We show re-inspections of older vehicles conducted by low quality inspection stations do not change air pollution, while inspections at high quality stations have a moderate effect on pollution concentrations, which suggests the potential for ineffective monitoring at low quality inspection stations. We find little effect on ambient ozone levels, regardless of station quality or vehicle age.

Urban forests near municipal solid waste incinerators do not show elevated trace metal or rare earth element concentrations across three cities in the northeast USA.

With the World Bank estimating global municipal solid waste MSW to increase to 3.4 billion tonnes by 2050, municipal solid waste incineration (MSWI) needs to be considered as part of sustainable waste management. In spite of major advancements in air pollution control systems and emission regulations, emissions of trace metals (TMs) (As, Cd, Cu, Ga, Mn, Ni, Pb, V, W, Zn) and rare earth elements (REEs) (La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Yb) may occur. Here, leaves, wood, forest floor, and A horizons in urban forests were assessed to determine if TM and REE concentrations show enrichment near MSWI relative to other urban areas for three cities in the northeastern USA. Vegetation and soil concentrations measured were generally comparable to concentrations observed in previous studies in non-urban sites. Overall, higher TM and REE in forest floor, A horizons, leaves, and wood were not observed consistently for MSWI sites when compared to city sites. Although pooled forest floor Ni and V and A horizon La and Nd concentrations were significantly different, they were not consistent but driven by a large difference at one of the three cities. This indirect study suggests air pollution control systems have prevented or have reduced TM and REE emissions to local urban forests to negligible amounts. Further studies are needed to evaluate potential interferences from other urban air pollution sources, and conduct direct emission measurements to validate MSWIs are not emitting TMs and REEs.

Application of a combined standard deviation and mean based approach to MOPITT CO column data, and resulting improved representation of biomass burning and urban air pollution sources

This work presents a new methodology to simultaneously account for both the mean and variance of 17 years of Carbon Monoxide [CO] measurements from the MOPITT satellite (from 2000 to 2016) over Southeast and East Asia. We demonstrate that the new technique is stable and produces a set of results which are both consistent with the understood geographical and temporal distribution of CO sources, as well as those of some other co-emitted species. These regions were chosen because they have high levels of CO loadings and complex factors driving their underlying emissions profiles. We first successfully categorize the region, based on the total CO column measurements, into those locations impacted by intense urbanization (high climatological mean, low climatological variance, high loading throughout most of the year, and variation mostly due to global-scale chemistry and climatology), large-scale biomass burning (low climatological mean, high climatological variance, mostly clean but with short and intense peak events occurring around a similar time year-to-year), those regions undergoing a significant change from one type to another, and those regions which are clean. We further reproduce the temporal and spatial distributions of other co-emitted species measured by other measurement platforms, including aerosols (AOD) and gasses (NO2), and demonstrate consistency across all three platforms. Third of all, we produce an important scientific finding using these new results, in terms of a significant geographic expansion of the known biomass burning regions from Myanmar through Northern Vietnam, as compared with previous research. Fourth, we also find that urbanization dominates emissions of CO over both known urban agglomerations in East and Southeast Asia, including around Beijing, Shanghai, the Pearl River Delta, Seoul, Shandong, Chengdu, Chongqing, Hanoi and Bangkok, but also extend into otherwise unclassified or recently emerging mega-cities including Shanxi Province, Henan Province, and Liaoning Province. Additionally, we have found that there is a 37% overlap with emissions from FINN, providing both validation of the technique over known biomass burning regions, and an ability to quantify regions that are burning but not presently identified. Finally, we have a consistent and value-adding comparison and contrast with an EOF/PCA analysis in terms of both our regions classified as biomass burning and mixed/urban, with each approach offering its unique advantages and drawbacks. Although our approach has made some very simple assumptions in terms of cutoff that can and should be improved by the community, its robust results provide new insights into the rapid changes impacting CO throughout Asia, and will allow models to have an improved chance at representing peak events or areas undergoing rapid change.

Characterizing Elevated Urban Air Pollutant Spatial Patterns with Mobile Monitoring in Houston, Texas.

Diverse urban air pollution sources contribute to spatially variable atmospheric concentrations, with important public health implications. Mobile monitoring shows promise for understanding spatial pollutant patterns, yet it is unclear whether uncertainties associated with temporally sparse sampling and instrument performance limit our ability to identify locations of elevated pollution. To address this question, we analyze 9 months of repeated weekday daytime on-road mobile measurements of black carbon (BC), particle number (PN), and nitrogen oxide (NO, NO2) concentrations within 24 census tracts across Houston, Texas. We quantify persistently elevated, intermittent, and extreme concentration behaviors at 50 m road segments on surface streets and 90 m segments on highways relative to median statistics across the entire sampling domain. We find elevated concentrations above uncertainty levels (±40%) within portions of every census tract, with median concentration increases ranging from 2 to 3× for NO2, and >9× for NO. In contrast, PN exhibits elevated concentrations of 1.5-2× the domain-wide median and distinct spatial patterns relative to other pollutants. Co-located elevated concentrations of primary combustion tracers (BC and NOx) near 30% of metal recycling and concrete batch plant facilities within our sampled census tracts are comparable to those measured within 200 m of highways. Our results demonstrate how extensive mobile monitoring across multiple census tracts can quantitatively characterize urban air pollution source patterns and are applicable to developing effective source mitigation policies.

Vehicle atmospheric pollution evaluation using AERMOD model at avenue in a Brazilian capital city

One of the most complex environmental problems is the air pollution, and automotive vehicles are one of the main sources of urban air pollution. Aracaju-SE, Sergipe’s capital in the northeast of Brazil, faces frequent congestion in traffic and does not have a monitoring network of air quality, so mathematical models are useful for impact assessment. This work consisted of an unusual application of AERMOD View software for vehicular pollution evaluation at Tancredo Neves Avenue in Aracaju’s city. The modeling was performed for the two avenue tracks, considered as urban linear sources. The rate of emission source was calculated from emission factors, average speed, and the number of vehicles accounted for footage circulating on the promenade at peak times. Concentrations distributions of total suspended particles (TSP), carbon monoxide (CO), and nitrogen oxide (NOx) on the mesh receptors were determinated from weather, topographic, and sources of emission data. The dispersion maps showed that the pollutants were concentrated around the sources; the estimated TSP concentrations were within the standards of CONAMA 491/2018 law. The CO concentration values exceeded the standard due to the high rate of emission sources. NO2 concentrations also exceeded the standard for hourly average, attributed to the contribution of heavy vehicles and the emission rates of light vehicles and motorcycles. The simulations showed that the meteorological and topographical conditions of Aracaju favor the atmospheric pollutants dispersion, that vehicles significantly affect air quality in the region and that the mathematical modeling is a useful tool for the study of atmospheric dispersion.

Estimating Exposure to Traffic-Related Air Pollution and Its Consequences on Respiratory Health in Population Working or Living along the Trunk Road: A Systematic Review

Introduction: Urban Air pollution is increasingly becoming a major health and sustainable development issue. Several studies showed that Traffic-related air pollution (TRAP) is one of the main sources of urban air pollution and has serious consequences on respiratory health. As no systematic review focused on the traffic-related air pollution and respiratory health in the target population of individuals working in a shop or in an office or individuals living along the trunk road, the authors conducted the current study to try to fill this gap. Methods: A systematic review search was conducted using MEDLINE (PubMed), Scientific Research Publishing: SCIRP, Web of Science, Google scholar. Studies were included if they meet the following selection criteria: 1) focus on population working or living along a major/trunk road; 2) studies had reported clearly at least on the exposure variables related to TRAP; 3) the association between TRAP and development of respiratory symptoms or respiratory diseases was established. Results: 13 articles were selected on the 192 articles that were retrieved in the initial research. Exposure to traffic-related air pollution was determined by using distance to road, traffic intensity and pollutants measured. The main respiratory health problems found were cough, wheeze, asthma and bronchitis. No article discussed about roundabouts in characterizing exposure to traffic-related air pollution. Conclusion: Distance to road, traffic density and pollutants measured are the usual methods to characterize the exposure to traffic-related air pollution and its consequences on respiratory health. Regarding the context of area occupations in African cities, it is necessary to focus on population around roundabouts and see if they are not more exposed to TRAP.

Urban air pollution monitoring using scanning Lidar

We have developed a scanning Lidar system in this work to detect urban air pollution changes in real time and locate the sources of urban air pollution. We first proposed an algorithm to retrieve atmospheric extinction coefficients, which we used to create Lidar maps. Using Lidar map of the average extinction coefficients, we identified the locations of the local maximum values, and hence, the positions of the urban air pollution sources. Experimental results indicate that this method is effective for urban air pollution monitoring.

What explains cross-city variation in mortality during the 1918 influenza pandemic? Evidence from 438 U.S. cities

Disparities in cross-city pandemic severity during the 1918 Influenza Pandemic remain poorly understood. This paper uses newly assembled historical data on annual mortality across 438 U.S. cities to explore the determinants of pandemic mortality. We assess the role of three broad factors: i) pre-pandemic population health and poverty, ii) air pollution, and iii) the timing of onset and proximity to military bases. Using regression analysis, we find that cities in the top tercile of the distribution of pre-pandemic infant mortality had 21 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. Similarly, cities in the top tercile of the distribution of proportion of illiterate residents had 21.3 excess deaths per 10,000 residents during the pandemic relative to cities in the bottom tercile. Cities in the top tercile of the distribution of coal-fired electricity generating capacity, an important source of urban air pollution, had 9.1 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. There was no statistically significant relationship between excess mortality and city proximity to World War I bases or the timing of onset. In a counterfactual analysis, the three statistically significant factors accounted for 50 percent of cross-city variation in excess mortality in 1918.

What Explains Cross-City Variation in Mortality During the 1918 Influenza Pandemic? Evidence from 438 U.S. Cities

Disparities in cross-city pandemic severity during the 1918 Influenza Pandemic remain poorly understood. This paper uses newly assembled historical data on annual mortality across 438 U.S. cities to explore the determinants of pandemic mortality. We assess the role of three broad factors: i) pre-pandemic population health and poverty, ii) air pollution, and iii) the timing of onset and proximity to military bases. Using regression analysis, we find that cities in the top tercile of the distribution of pre-pandemic infant mortality had 21 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. Similarly, cities in the top tercile of the distribution of the proportion of illiterate residents had 21.3 excess deaths per 10,000 residents during the pandemic relative to cities in the bottom tercile. Cities in the top tercile of the distribution of coal-fired electricity generating capacity, an important source of urban air pollution, had 9.1 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. There was no statistically significant relationship between excess mortality and city proximity to World War I bases or the timing of onset. Together the three statistically significant factors accounted for 50 percent of cross-city variation in excess mortality in 1918.

What Explains Cross-City Variation in Mortality During the 1918 Influenza Pandemic? Evidence from 438 U.S. Cities

Disparities in cross-city pandemic severity during the 1918 Influenza Pandemic remain poorly understood. This paper uses newly assembled historical data on annual mortality across 438 U.S. cities to explore the determinants of pandemic mortality. We assess the role of three broad factors: i) pre-pandemic population health and poverty, ii) air pollution, and iii) the timing of onset and proximity to military bases. Using regression analysis, we find that cities in the top tercile of the distribution of pre-pandemic infant mortality had 21 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. Similarly, cities in the top tercile of the distribution of proportion of illiterate residents had 21.3 excess deaths per 10,000 residents during the pandemic relative to cities in the bottom tercile. Cities in the top tercile of the distribution of coal-fired electricity generating capacity, an important source of urban air pollution, had 9.1 excess deaths per 10,000 residents in 1918 relative to cities in the bottom tercile. There was no statistically significant relationship between excess mortality and city proximity to World War I bases or the timing of onset. Together the three statistically significant factors accounted for 50 percent of cross-city variation in excess mortality in 1918.

Assessing the Impact of Vehicle Speed Limits and Fleet Composition on Air Quality Near a School

Traffic is a major source of urban air pollution that affects health, especially among children. As lower speed limits are commonly applied near schools in many cities, and different governments have different policies on vehicle fleet composition, this research estimated how different speed limits and fleet emissions affect air quality near a primary school. Based on data of traffic, weather, and background air quality records in Dublin from 2013, traffic, emission, and dispersion models were developed to assess the impact of different speed limits and fleet composition changes against current conditions. Outside the school, hypothetical speed limit changes from 30 km/h to 50 km/h could reduce the concentration of NO2 and PM10 by 3% and 2%; shifts in the fleet from diesel to petrol vehicles could reduce these pollutants by 4% and 3% but would increase the traffic-induced concentrations of CO and Benzene by 63% and 35%. These changes had significantly larger impacts on air quality on streets with higher pollutant concentrations. Findings suggest that both road safety and air quality should be considered when determining speed limits. Furthermore, fleet composition has different impacts on different pollutants and there are no clear benefits associated with incentivising either diesel or petrol engine vehicles.

DETERMINATION OF ADDITIONAL HEALTH RISK DUE TO POLLUTANTS IN AMBIENT AIR DURING OPERATION OF ROAD-VEHICLES COMPLEX

Introduction. According to the materials of the World Health Organization, air pollutants are one of the most significant factors affecting the health of the population. The main urban air pollution source is road transport. The determination of air pollutants amount during the operation of the road-vehicles complex (RVC) with suspended substances is an important procedure for monitoring the risk to human health, planning, and evaluation of measures for the protection of residential areas ambient air. The existing methodical documents and regulations do not fully regulate important aspects of air pollution monitoring and assessment by-products caused by exhaust gases of the vehicle and emissions associated with the operation of the RVC. Thus, the purpose of this study is to determine the additional population health risks due to pollutants reaching the air of residential areas during the RVC operation. Material and methods. The method of emissions measurement reaching the air during the operation of the RVC is based on existing methodical documents and regulations. To assess the pollution, the data of observations of the intensity of traffic flow in different time periods in the experimental territories are used. The calculation of pollutants amount released into the air during the operational wear of the RVC is determined separately for the tire treads, brake system, and road pavement. Results. Guided by the constructed nomogram, taking into account distribution zone of the air pollution, it is possible to determine population health risk during the RVC operation in the city based on the calculation of the hazard coefficient. Discussion. On the basis of the calculations, data on the number of pollutants reaching the air during the RVC operation (wear of tire treads, brake system, road pavement) and from vehicles of various types for 1 year are presented. The data on the pollutants quantities generating on the road on a per 1 km car run basis, reaching the ambient air for various periods of time (hours, days) with the aim of the derivation of the spatial-temporal characteristics of the pollutants. On the basis of the obtained data, approximate calculations of the number of pollutants reaching the air during the operation of the RVC from all vehicles registered by St. Petersburg traffic police at the moment and the forecast for the period 2020 were carried out. Сonclusions. The given data on the hazard coefficient calculation of suspended solids emissions of RVC allow summarizing the risk from all the compartmental RVC sources. On the basis of the distance from the road to residential buildings presented in the nomogram, it is possible to determine an additional population health risk due to pollutants reaching the air during the RVC operation using a mathematical model of dispersion.

An optimization model of signal timing plan and traffic emission at intersection based on Synchro

With the rapid development of urbanization in China, the pressure of urban traffic keeps increasing. The problem of traffic pollution is increasingly serious as the automobile exhaust has been one of the main sources of urban air pollution. The major causes of traffic emission are the traffic jam and delay in the urban road intersections. Many advanced traffic signal control methods have been widely applied in the traffic management to reduce traffic jam. This paper proposes an optimization model of signal timing plan that comprehensively considers operating efficiency and traffic emission, which is based on signal timing plan for building a model of network topology and simulation for optimizing the signal timing. Meanwhile, this plan is to improve the efficiency of intersections, reduce queuing time and harmful emission. Taking some intersections in Harbin as an example, the measured pollutant emissions data at the intersections before and after signal optimization were collected and compared, then the levels of vehicle exhaust pollution and emissions of various emissions under different control strategies were analyzed, thus the emissions under different traffic management and control were evaluated. All these data has a great importance both in theoretical and practical value.

A rapid method for the determination of levoglucosan in NIST standard reference material 1649a by HPLC-MS/MS

The biomass burning marker levoglucosan is produced via combustion of woody cellulose at temperature over 300 °C, and is hence widely used to trace fires or discriminate urban air pollution sources. In this context, it is very useful the availability of a standard reference material (SRM) with a certified value of levoglucosan, to check the quality, reliability and accuracy of the measurements.To this aim, in this work a simple and rapid method was developed for the detection and quantification of levoglucosan in an urban dust Standard Reference Material 1649a, available from the National Institute of Standards and Technology and the results were compared to those obtained in our previous investigations. 5 mg of SRM particulate material were analyzed, after an ultrasonic extraction with deionized water, using a column, with stationary phase based on hydrophilic interaction, assembled on a liquid chromatography system combined with triple tandem quadrupole mass spectrometry (HPLC-MS/MS) with electrospray ionization. Unlike existing methods, it does not require neither derivatization or extensive clean-up of the sample. For the method validation, the matrix effect, limit of detection (LOD), limit of quantification (LOQ), linearity, accuracy, recovery and precision were evaluated. The concentration determined in the SRM was in good agreement with that determined by gas chromatography-mass spectrometry in our previous study. The precision, tested on SRM, over five replicates and five aliquots were within 15%, whereas accuracy ranged between 85 and 115%. To demonstrate the method is fit for the purpose, particulate matter samples collected in an urban area of the city of Rome Italy were analyzed. The amount of levoglucosan was consistent with the urban emissions typical of the considered season.