Nonlinear analysis and prediction of coarse particulate matter concentration in ambient air

This study attempts to characterize and predict coarse particulate matter (PM10) concentration in ambient air using the concepts of nonlinear dynamical theory. PM10 data observed daily from 1999 to 2002 at a site in Mumbai, India, was used to study the applicability of the chaos theory. First, the autocorrelation function and Fourier power spectrum were used to analyze the behavior of the time-series. The dynamics of the time-series was additionally studied through correlation integral analysis and phase space reconstruction. The nonlinear predictions were then obtained using local polynomial approximation based on the reconstructed phase space. The results were then compared with the autoregressive model. The results of nonlinear analysis indicated the presence of chaotic character in the PM10 time-series. It was also observed that the nonlinear local approximation outperforms the autoregressive model, because the observed relative error of prediction for the autoregressive model was greater than the local approximation model. The invariant measures of nonlinear dynamics computed for the predicted time-series using the two models also supported the same findings.     

A novel methodology for determining low-cost fine particulate matter street sweeping routes

This paper addresses the problem of low-cost PM10 (particulate matter with aerodynamic diameter < 10 microm) street sweeping route. In order to do so, only a subset of the streets of the urban area to be swept is selected for sweeping, based on their PM10 emission factor values. Subsequently, a low-cost route that visits each street in the set is computed. Unlike related problems of waste collection where streets must be visited once (Chinese or Rural Postman Problem, respectively), in this case, the sweeping vehicle route must visit each selected street exactly as many times as its number of street sides, since the vehicle can sweep only one street side at a time. Additionally, the route must comply with traffic flow and turn constraints. A novel transformation of the original arc routing problem into a node routing problem is proposed in this paper. This is accomplished by building a graph that represents the area to sweep in such a way that the problem can be solved by applying any known solution to the Traveling Salesman Problem (TSP). As a way of illustration, the proposed method was applied to the northeast area of the Municipality of Santiago (Chile). Results show that the proposed methodology achieved up to 37% savings in kilometers traveled by the sweeping vehicle when compared to the solution obtained by solving the TSP problem with Geographic Information Systems (GIS)--aware tools.     

New tabletop SEM-EDS-based approach for cost-efficient monitoring of airborne particulate matter

Recent developments in scanning electron microscopy (SEM) have produced tabletop instruments capable of reasonable imaging resolution at less cost compared to conventional equipment. Combining the SEM with energy dispersive spectroscopy (EDS) allows the possibility of elemental analysis through detection of X-rays emitted from interaction between individual particles and the SEM electron beam, revealing their atomic composition. It’s well known that exposure to inhalable particulate matter (PM) poses health risks and routine monitoring of the chemical content of these has been realized. Exposure information is of a general character but by combining the chemical build-up of monitored particles and knowledge of their inherent health effects will allow better risk assessment. An analysis technique using a tabletop SEM with EDS is demonstrated on particles collected onto nucleopore filters from urban, industrial and rural areas. Detailed characterization of the instruments analysis capabilities as applied to PM are described.     

Behavior of particulate matter during high concentration episodes in Seoul

The behavior of particulate matter (PM) during high-concentration episodes was investigated using monitoring data from Guui station, a comprehensive air monitoring station in Seoul, Korea, from January 2008 to March 2010. Five non-Asian dust (ND) episodes and two Asian dust (AD) episodes of high PM concentrations were selected for the study. During the ND episode, primary air pollutants accumulated due to low wind speeds, and PM_2.5 increased along with most other air pollutants. Particles larger than PM_2.5 were also high since these particles were generated by vehicular traffic rather than wind erosion. During strong AD episodes, PM_10–2.5 primarily increased and gaseous primary air pollutants decreased under high wind speeds. However, even during the AD episode, PM_2.5 and gaseous primary air pollutants increased when the effects of AD were weak and wind speeds were low. This study corroborates that accumulation of air pollutants due to a drop in surface wind speed plays an important role in short-term high-concentration occurrences. However, low wind speeds could not be directly linked to local emissions because a significant portion of accumulated air pollutants resulted from long-range transport.     

A comprehensive particulate matter monitoring system and dosimetry-based ambient particulate matter standards

A numerical particulate matter (PM) measurement model is developed to characterize and evaluate PM sampling methods. Simulations are conducted using the model to evaluate currently widely used PM samplers, including Federal Reference Method (FRM) samplers. The simulations show that current PM samplers are very vulnerable to both changes in measurement target (i.e., natural variability of particle size distribution) and the sampler's design, manufacturing, and operating conditions, potentially resulting in significant errors in the monitoring data. The numerical model is used in conjunction with two types of commercially available PM monitoring devices to form a Comprehensive Particulate Matter Monitoring System (CPMMS). The first type of device can be any mass-based PM monitor with a well-defined sampling efficiency curve. The second type of device is one capable of measuring particle size distribution with a reasonably good relative accuracy between size categories but not necessarily accurate in measuring absolute mass concentrations. This study shows that CPMMS can produce much higher quality PM monitoring data than the current PM samplers under the same conditions. In addition, unlike past and current PM monitoring data such as total suspended particulates, coarse PM (PM10), fine PM (PM2.5), etc., the CPMMS monitoring data will survive changes in PM regulatory definition. A new concept, dosimetry-based PM metrics and standards, is proposed to define ambient PM level based on the deposition fraction of particles in the human respiratory tract. The dosimetry-based PM metrics is more meaningful because it correlates the ambient PM level with the portion that can be deposited in the respiratory tract without an arbitrary cutoff particle diameter. CPMMS makes dosimetry-based PM metrics and standards feasible.     

Influence of natural events on the concentration and composition of atmospheric particulate matter

A ten-month field study aimed to determine the contribution of natural events (i.e. sea-salt and mineral dust events) to urban PM concentration was carried out at six sampling sites in Central Italy (Lazio region). Four indicators have been used to identify natural events during the period of the study. The first one is constituted by the ratio between number of particles in the coarse to the accumulation mode. It is simple, cheap, and the information are given in quasi-real time, but the nature of the event (sea-salt or mineral dust) is not detectable. The second indicator relies on the chemical analysis of the collected PM by X-ray fluorescence (XRF) and allows a robust identification of sea-salt and crustal components. The third one is based on diagnostic ratios of elemental fractions: Mg_extractable/Ti_residue for sea-salt and Ti_residue/Sb_residue for mineral dust. It requires skilled staff but it is most accurate and sensible. The last indicator, constructed on the basis of natural radioactivity data, is not diagnostic for the nature of the event but it is able to estimate the increase in PM concentration with respect to the expected concentration in the absence of natural events.The relevance of natural events and the variations in PM concentration and composition during the study are discussed. The joined use of the four indicators allowed the identification of about 20 natural PM episodes. In general, sea-salt aerosol events did not cause exceedance of the daily EU limit value for PM₁₀. Saharan dust events, instead, were in most cases responsible for the exceedance of the limit value at all stations.     

Enhancing the performance of data-driven models for monthly reservoir evaporation prediction

Environmental Science and Pollution Research - The accuracy level for reservoir evaporation prediction is an important issue for decision making in the water resources field. The traditional...     

Theoretical study of the impact of particulate matter gravitational settling on ambient coarse particulate matter monitoring for agricultural emissions

The particle size distributions (PSDs) of particulate matter (PM) in the downwind plume from simulated sources of a cotton gin were analyzed to determine the impact of PM settling on PM monitoring. The PSD of PM in a plume varies as a function of gravitational settling. Gravitational settling has a greater impact on the downwind PSD from sources with PSDs having larger mass median diameters (MMDs). The change in PSD is a function of the source PSD of emitted PM, wind speed, and downwind distance. Both MMD and geometric standard deviation (GSD) in the downwind plume decrease with an increase in downwind distance and source MMD. The larger the source MMD, the greater the change in the downwind MMD and GSD. Also, the greater the distance from the source to the sampler, the greater the change in the downwind MMD and GSD. Variations of the PSD in the downwind plume significantly impact PM10 sampling errors associated with the U.S. Environmental Protection Agency (EPA) PM10 samplers. For the emission sources with MMD > 10 microm, the PM10 oversampling rate increases with an increase in downwind distance caused by the decrease of GSD of the PSD in the downwind plume. Gravitational settling of particles does not help reduce the oversampling problems associated with the EPA PM10 sampler. Furthermore, oversampling rates decrease with an increase of the wind speed.     

Characteristics of inhalable particulate matter concentration and size distribution from power plants in China

In this investigation, the collection efficiency of particulate emission control devices (PECDs), particulate matter (PM) emissions, and PM size distribution were determined experimentally at the inlet and outlet of PECDs at five coal-fired power plants. Different boilers, coals, and PECDs are used in these power plants. Measurement in situ was performed by an electrical low-pressure impactor with a sampling system, which consisted of an isokinetic sampler probe, precut cyclone, and two-stage dilution system with a sample line to the instruments. The size distribution was measured over a range from 0.03 to 10 microm. Before and after all of the PECDs, the particle number size distributions display a bimodal distribution. The PM2.5 fraction emitted to atmosphere includes a significant amount of the mass from the coarse particle mode. The controlled and uncontrolled emission factors of total PM, inhalable PM (PM10), and fine PM P(M2.5) were obtained. Electrostatic precipitator (ESP) and baghouse total collection efficiencies are 96.38-99.89% and 99.94%, respectively. The minimum collection efficiency of the ESP and the baghouse both appear in the particle size range of 0.1-1 microm. In this size range, ESP and baghouse collection efficiencies are 85.79-98.6% and 99.54%. Real-time measurement shows that the mass and number concentration of PM10 will be greatly affected by the operating conditions of the PECDs. The number of emitted particles increases with increasing boiler load level because of higher combustion temperature. During test run periods, the data reproducibility is satisfactory.     

Source apportion of atmospheric particulate matter: a joint Eulerian/Lagrangian approach

PM_2.5 samples were collected during an annual monitoring campaign (January 2012–January 2013) in the urban area of Naples, one of the major cities in Southern Italy. Samples were collected by means of a standard gravimetric sampler (Tecora Echo model) and characterized from a chemical point of view by ion chromatography. As a result, 143 samples together with their ionic composition have been collected. We extend traditional source apportionment techniques, usually based on multivariate factor analysis, interpreting the chemical analysis results within a Lagrangian framework. The Hybrid Single-Particle Lagrangian Integrated Trajectory Model (HYSPLIT) model was used, providing linkages to the source regions in the upwind areas. Results were analyzed in order to quantify the relative weight of different source types/areas. Model results suggested that PM concentrations are strongly affected not only by local emissions but also by transboundary emissions, especially from the Eastern and Northern European countries and African Saharan dust episodes.     

Total element concentration and chemical fractionation in airborne particulate matter from Santiago,Chile

Total element determination and chemical fractionation were carried out in airborne particulate matter (PM₁₀) from the Cerrillos monitoring station in Santiago, Chile, sampled in July (winter), 1997–2003.Element concentration in the period under study (1997–2003) was statistically analyzed through cluster analysis in order to identify groups of elements having similar behavior along time. Elements such as Cd, Cu, Pb, Ni, As and Mg show a clear decrease in concentration with time. On the contrary, chromium increases its concentration almost linearly during the period.In order to estimate whether the presence of a certain element in PM₁₀ matrix is mainly due to anthropogenic or natural processes, the enrichment factor of each element was determined.According to their behavior in the sequential extraction procedure, the elements were grouped by multivariate analysis in three clusters: (a) those mobile elements (Pb, Cd, Zn, Mn, Cu and As) which are weakly bound to the matrix (fractions 1 and 2) (b) those elements (V, Ti, and Cr) mainly bound to carbonates and oxides (fraction 3) and (c) the most immobile elements (Ni, Mo, Ca, Mg, Ba and Al), mainly bound to silicates and organic matter (fraction 4). A source of great concern is the fact that elements of such high toxicity as Pb, Cd and As are highly concentrated in both mobile fractions, indicating that these elements have a direct impact on the environment and on the health of the exposed population.     

A new methodological approach: The combined use of two-stage streaker samplers and optical particle counters for the characterization of airborne particulate matter

We describe a new experimental methodology based on the contemporary use of two-stage continuous streaker samplers and optical particle counters. This is a complementary approach to size-segregated particulate matter (PM) sampling, and it is able to give information on the elemental size distribution and to assess the contribution of major PM source to size bins. PM samples in the fine and coarse fraction of PM10 have been collected by a two-stage streaker sampler and analyzed by particle-induced X-ray emission (PIXE) to obtain elemental concentration time series with hourly resolution. PM sources and profiles were singled out by positive matrix factorization (PMF). A multi-linear regression of size-segregated number of particles versus the sources, resolved by PMF, made possible the apportionment of size-segregated particles number in a fast and direct way. Results obtained in three sampling sites, located in different urban districts are discussed.     

Characterization of particulate matter for three sites in Kuwait

Many studies have shown strong associations between particulate matter (PM) levels and a variety of health outcomes, leading to changes in air quality standards in many regions, especially the United States and Europe. Kuwait, a desert country located on the Persian Gulf, has a large petroleum industry with associated industrial and urban land uses. It was marked by environmental destruction from the 1990 Iraqi invasion and subsequent oil fires. A detailed particle characterization study was conducted over 12 months in 2004-2005 at three sites simultaneously with an additional 6 months at one of the sites. Two sites were in urban areas (central and southern) and one in a remote desert location (northern). This paper reports the concentrations of particles less than 10 microm in diameter (PM10) and fine PM (PM2.5), as well as fine particle nitrate, sulfate, elemental carbon (EC), organic carbon (OC), and elements measured at the three sites. Mean annual concentrations for PM10 ranged from 66 to 93 microg/m3 across the three sites, exceeding the World Health Organization (WHO) air quality guidelines for PM10 of 20 microg/m3. The arithmetic mean PM2.5 concentrations varied from 38 and 37 microg/m3 at the central and southern sites, respectively, to 31 microg/m3 at the northern site. All sites had mean PM2.5 concentrations more than double the U.S. National Ambient Air Quality Standard (NAAQS) for PM2.5. Coarse particles comprised 50-60% of PM10. The high levels of PM10 and large fraction of coarse particles comprising PM10 are partially explained by the resuspension of dust and soil from the desert crust. However, EC, OC, and most of the elements were significantly higher at the urbanized sites, compared with the more remote northern site, indicating significant pollutant contributions from local mobile and stationary sources. The particulate levels in this study are high enough to generate substantial health impacts and present opportunities for improving public health by reducing airborne PM.     

Evaluation of particulate matter abatement strategies for almond harvest

Almond harvest accounts for substantial PM10 (particulate matter [PM] < or =10 microm in nominal aerodynamic diameter) emissions in California each harvest season. This paper evaluates the effects of using reduced-pass sweepers and lower harvester separation fan speeds (930 rpm) on lowering PM emissions from almond harvesting operations. In-canopy measurements of PM concentrations were collected along with PM concentration measurements at the orchard boundary; these were used in conjunction with on-site meteorological data and inverse dispersion modeling to back-calculate emission rates from the measured concentrations. The harvester discharge plume was measured as a function of visible plume opacity during conditioning operations. Reduced-pass sweeping showed the potential for reducing PM emissions, but results were confounded because of differences in orchard maturity and irrigation methods. Fuel consumption and sweeping time per unit area were reduced when comparing a reduced-pass sweeper to a conventional sweeper. Reducing the separation fan speed from 1080 to 930 rpm led to reductions in PM emissions. In general, foreign matter levels within harvested product were nominally affected by separation fan speed in the south (less mature) orchard; however, in samples conditioned using the lower fan speed from the north (more mature) orchard, these levels were unacceptable.     

Heavy-metal ion complexation by particulate matter in the leachate of solid waste: a multi-method approach

The metal ion binding characteristics of particulate matter obtained from column experiments on the anaerobic digestion of solid waste were studied using a titrimetric approach. The experimental set-up allowed us to study the dynamics of particle bound ligand concentrations during digestion processes typically found in landfills.We developed a continuous titration method by simultaneously using a Cd-sensitive and pH electrode and combining metal and acid/base titrations. This technique allows for a more precise determination of pK_a-log K_M pairs for each ligand than metal titrations alone. The results were compared with titration methods using differential pulse anodic stripping voltammetry (DPASV) and atomic absorption spectroscopy (AAS) with longer equilibration times in order to further characterize ligand properties such as reaction kinetics, the electrochemical lability of the respective complex during DPASV, the distinction between metal adsorption to particulate matter and metal complexation by soluble ligands adhered to particles, reversibility of the binding process by competition studies, and resistance against purging with nitrogen gas.The properties of seven major metal binding ligands were identified and assignments to the most likely functional groups were made. The most important ligand properties are for ligand A: pK_a ≈ 9.2, log K_cd ≈ 7.0 fast reaction kinetics (mercapto groups); ligand B: pK_a = 4.8, log K_Cd ≈ 6.0, slow reaction kinetics (chelates with 3 or 4 carboxylic groups); ligand C: pK_a ≈ 6.0, log K_Cd ≈ 13.0, irreversible metal binding at basic pH-values (uptake inside bacterial cells); ligand D: pK_a = 7.7, log K_Cd = 4.0, runs parallel to N content of particulate matter with digestion time (primary amines neighboring oxo groups); ligand E: pK_a ≈ 12.0, log K_Cd = 9.0, runs parallel to P content of particulate matter (phosphate); ligand F:pK_a > 9.0, log K_{Cdf = pKa + 0.4}, runs parallel to N content of particulate matter (primary amines neighboring SH groups); and ligand G: pK_a ≤ 4.8, log K_Pb ≈ 4.3, strong Pb²⁺ ligand, even at low pH-values.Metal ions were found to be irreversibly bound by ligand C at low heavy-metal concentratins, whereas at higher concentrations the binding is reversible and can be predicted using the mass of the digestion process (methanogenic phase). All other ligands have their concentration maximum in the transition phase between acetogenic and methanogenic phase.     

Model for forecasting expressway fine particulate matter and carbon monoxide concentration: application of regression and neural network models

The Borman Expressway is a heavily traveled 16-mi segment of the Interstate 80/94 freeway through Northwestern Indiana. The Lake and Porter counties through which this expressway passes are designated as particulate matter < 2.5 microm (PM2.5) and ozone 8-hr standard nonattainment areas. The Purdue University air quality group has been collecting PM2.5, carbon monoxide (CO), wind speed, wind direction, pressure, and temperature data since September 1999. In this work, regression and neural network models were developed for forecasting hourly PM2.5 and CO concentrations. Time series of PM2.5 and CO concentrations, traffic data, and meteorological parameters were used for developing the neural network and regression models. The models were compared using a number of statistical quality indicators. Both models had reasonable accuracy in predicting hourly PM2.5 concentration with coefficient of determination -0.80, root mean square error (RMSE) <4 microg/m3, and index of agreement (IA) > 0.90. For CO prediction, both models showed moderate forecasting performance with a coefficient of determination -0.55, RMSE < 0.50 ppm, and IA -0.85. These models are computationally less cumbersome and require less number of predictors as compared with the deterministic models. The availability of real time PM2.5 and CO forecasts will help highway managers to identify air pollution episodic events beforehand and to determine mitigation strategies.     

某高密度街区大气颗粒物质量浓度分布特征实测研究

为研究城市高密度街区大气颗粒物浓度分布特征,2019年秋季对上海市某高密度街区道路大气颗粒物浓度、空气温度、相对湿度、地理位置、车辆与道路图像视频信息进行了同步移动在线监测,并结合街区内固定站数据和后向轨迹模拟结果,总结了影响街区大气颗粒物浓度变化的主要因素。结果表明:城市大气颗粒物背景拟合值处于较低水平时,街区内的大气颗粒物浓度变化和影响因素易被识别;机动车污染源对大气颗粒物浓度贡献大,其中大型机动车的影响明显;户外施工和道路清扫会引起大气颗粒物浓度上升,其中PM₁₀上升更明显;交通密度大的十字路口大气颗粒物浓度通常较高;城市高架的盖状结构会阻碍大气颗粒物在垂直方向上的扩散,引起局部大气颗粒物浓度上升;街区内高大浓密的乔木对近地面的大气颗粒物屏蔽效果不理想,甚至有助于颗粒物累积;早晚高峰时段大气颗粒物浓度较非高峰时段高。     

A predictive model for copper partitioning to suspended particulate matter in river waters

A chemical equilibrium-based predictive model expressing Cu partitioning as a function of aqueous and solid phase characteristics was developed. The model takes into account only the most important factors that govern Cu partitioning, and therefore results in a relatively simple formulation. It assumes particulate organic carbon (POC) and dissolved organic carbon (DOC) binding sites play the most important role in solid and aqueous phases. The model formulation assumed one-surface site and two dissolved organic matter (DOM) sites, and included the "solids effect". Proton effects were considered for both the particle surface sites and the DOM. The model was calibrated with data for samples collected from the Susquehanna River, and validated with White Clay Creek and Delaware River samples. Copper partitioning in natural water systems with different pH, and concentrations of alkalinity, DOC, POC, total suspended solids (TSS), and total copper was predicted reasonably well.     

某高密度街区大气颗粒物质量浓度分布特征实测研究

为研究城市高密度街区大气颗粒物浓度分布特征,2019年秋季对上海市某高密度街区道路大气颗粒物浓度、空气温度、相对湿度、地理位置、车辆与道路图像视频信息进行了同步移动在线监测,并结合街区内固定站数据和后向轨迹模拟结果,总结了影响街区大气颗粒物浓度变化的主要因素。结果表明:城市大气颗粒物背景拟合值处于较低水平时,街区内的大气颗粒物浓度变化和影响因素易被识别;机动车污染源对大气颗粒物浓度贡献大,其中大型机动车的影响明显;户外施工和道路清扫会引起大气颗粒物浓度上升,其中PM₁₀上升更明显;交通密度大的十字路口大气颗粒物浓度通常较高;城市高架的盖状结构会阻碍大气颗粒物在垂直方向上的扩散,引起局部大气颗粒物浓度上升;街区内高大浓密的乔木对近地面的大气颗粒物屏蔽效果不理想,甚至有助于颗粒物累积;早晚高峰时段大气颗粒物浓度较非高峰时段高。