In this study, the performance of two types of source apportionment models was evaluated by assessing the results provided by 40 different groups in the framework of an intercomparison organised by ...FAIRMODE WG3 (Forum for air quality modelling in Europe, Working Group 3). The evaluation was based on two performance indicators: z-scores and the root mean square error weighted by the reference uncertainty (RMSEu), with pre-established acceptability criteria. By involving models based on completely different and independent input data, such as receptor models (RMs) and chemical transport models (CTMs), the intercomparison provided a unique opportunity for their cross-validation. In addition, comparing the CTM chemical profiles with those measured directly at the source contributed to corroborate the consistency of the tested model results. The most commonly used RM was the US EPA- PMF version 5. RMs showed very good performance for the overall dataset (91% of z-scores accepted) while more difficulties were observed with the source contribution time series (72% of RMSEu accepted). Industrial activities proved to be the most difficult sources to be quantified by RMs, with high variability in the estimated contributions. In the CTMs, the sum of computed source contributions was lower than the measured gravimetric PM10 mass concentrations. The performance tests pointed out the differences between the two CTM approaches used for source apportionment in this study: brute force (or emission reduction impact) and tagged species methods. The sources meeting the z-score and RMSEu acceptability criteria tests were 50% and 86%, respectively. The CTM source contributions to PM10 were in the majority of cases lower than the RM averages for the corresponding source. The CTMs and RMs source contributions for the overall dataset were more comparable (83% of the z-scores accepted) than their time series (successful RMSEu in the range 25% - 34%). The comparability between CTMs and RMs varied depending on the source: traffic/exhaust and industry were the source categories with the best results in the RMSEu tests while the most critical ones were soil dust and road dust. The differences between RMs and CTMs source reconstructions confirmed the importance of cross validating the results of these two families of models.
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•Receptor models (RMs) and chemical transport models (CTMs) were tested jointly.•Unprecedented database with 49 independent source apportionment results.•Differences between brute force and tagged species CTM approaches were observed.•CTMs tend to have lower source contributions or impacts than RMs.•The study provides the basis for the joint application of RMs and CTMs.
River dust has severe impact on air quality in western Taiwan under prevailing strong northeasterly winds during passage of cold fronts. Data showed that river dust in western Taiwan from November to ...April came mainly from Choshui River (CS). The difference in mean seasonal concentration of river dust upstream of CS at station Erlin (EL) and downstream at station Lunbei (LB) could be as high as 14.2 μg/m3 during northeasterly monsoon from 1994 to 2015. A major river-dust event with unprecedented PM10 concentration occurring in western Taiwan on 2 November, 2009 was examined to understand further the mechanism behind its occurrence and impact on air quality. Weather conditions of 1–2 November, 2009 showed a clear pressure gradient in a strong baroclinic environment associated with a prevailing strong continental outflow (northeasterly, ≥ 12 m/s) that lasted more than 30 h over the coastal area of China. On 2 November, 2009, the peak concentration of PM10 concentration was 600 μg/m3at EL but exceeded 2500 μg/m3 at LB. While wind speeds of these two stations were comparable, the PM10 concentration at LB was more than four times that at EL due to dust blown up from CS riverbed. These findings could be reasonably captured by the WRF-Chem model. Simulation results also indicated that the depth of this strong northerly wind (>10 m/s) was below 1000 m and its intensity increased significantly after 0 LST on 2 November, 2009. Strong wind did not favor vertical diffusion of river dust, thus trapping it below 200 m in height and causing severe dust concentration at near-surface level. Besides high wind speed, dry atmospheric and surface drought conditions also contributed to increase river dust suspension in the air. The results and methods obtained in this study can be applied to other regions of similar environment and with comparable relief.
Temporal variation of observed and simulated PM10 concentration at Erlin (EL) and Lunbei (LB) from 12 LST, 1 Nov., to 8 LST, 3 Nov., 2009 (Left panel). Observed PM10 concentration and wind recorded in Taiwan (right panel) at 08 UTC (16 LST) 02 Nov., 2009. Display omitted
•We analyzed potential river dust events from 1994 to 2015 over western Taiwan.•A significant river dust event with unprecedented PM10 concentration was examined.•Impact of atmospheric conditions on river dust suspension were discussed.•Findings of this study will fill the estimation gap of PM10 due to river dust.
Urban particulate pollution in the UK remains at levels which have the potential to cause negative impacts on human health. There is a need, therefore, for mitigation strategies within cities, ...especially with regards to vehicular sources. The use of vegetation as a passive filter of urban air has been previously investigated, however green roof vegetation has not been specifically considered. The present study aims to quantify the effectiveness of four green roof species – creeping bentgrass (Agrostis stolonifera), red fescue (Festuca rubra), ribwort plantain (Plantago lanceolata) and sedum (Sedum album) – at capturing particulate matter smaller than 10 μm (PM10). Plants were grown in a location away from major road sources of PM10 and transplanted onto two roofs in Manchester city centre. One roof is adjacent to a major traffic source and one roof is characterised more by urban background inputs. Significant differences in metal containing PM10 capture were found between sites and between species. Site differences were explained by proximity to major sources. Species differences arise from differences in macro and micro morphology of the above surface biomass. The study finds that the grasses, A. stolonifera and F. rubra, are more effective than P. lanceolata and S. album at PM10 capture. Quantification of the annual PM10 removal potential was calculated under a maximum sedum green roof installation scenario for an area of the city centre, which totals 325 ha. Remediation of 2.3% (±0.1%) of 9.18 tonnes PM10 inputs for this area could be achieved under this scenario.
► Green roofs act as passive filters of airbourne particulate matter. ► Species differences in particle capture efficiency were observed. ► Morphological reasons for differences in particle capture efficiency were posited. ► Spatial differences in leaf SIRM were observed in relation to PM10 sources. ► 0.24 tonnes of PM10 a year could be removed from Manchester city centre.
Economic development and urban expansion have accelerated particulate matter pollution in urban areas in China. Particulate matter-driven haze poses a serious threat to human beings from a public ...health point of view. Substantial evidences had linked adverse health effects with exposures to PM2.5, but recent research indicated that PM10–2.5 also had great risk. However, the relative contributions of driving forces to PM10–2.5 pollution are not well understood in the urban areas in China, and no targeted policies have been regulated to control the pollution. In this study, we quantified the contributions of potential driving factor across China with the structural equation model (SEM). Our results showed that in 2015 and 2016, the annual average concentrations of PM10–2.5 in the 290 prefecture-level cities with a mean value of 36 and 35 μg/m3, respectively. Industrial scale contributed more to PM10–2.5 pollution than city size and residents' activities in urban areas based on SEM results. Driving forces included in our model could explain 42% of variations in PM10–2.5 pollution, which indicated that there existed influences from other anthropogenic sources and natural sources. Eleven targeted recommendations were then proposed to control PM10–2.5 pollution based on our mechanism analysis. Findings from our study are beneficial to control PM10–2.5 pollution on a national scale, and also can provide a theoretical basis for the formulation of PM10–2.5 pollution control policy in China.
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•PM10–2.5 poses a serious threat to human beings from a public health point of view.•Structural equation model is used to determine the driving mechanisms.•Urban PM10–2.5 pollution was concentrated in central regions of China.•Industrial scale contributed most to PM10–2.5 pollution in urban areas.•Eleven recommendations to control PM10–2.5 pollution are proposed.
More than 400 PM1 and 400 PM10 daily samples were collected in the urban center of Elche (close to the Spanish Mediterranean coast) from February 2015 to February 2018. Samples were analyzed to ...determine the concentrations of major and trace components with the aim of evaluating the influence of specific pollution events on the chemical composition of both PM fractions. The concentrations of crustal elements in PM10 significantly increased during Saharan dust outbreaks, particularly titanium, which has been identified as a good tracer of these events in the study area. Sulfate and nitrate levels were also enhanced due to secondary aerosol formation on mineral dust particles. Local pollution episodes had a great impact on submicron nitrate, whose mean concentration was more than four times higher than on non-event days. The chemical mass closure method was used to reconstruct PM1 and PM10 concentrations. Reasonably good correlations between measured and reconstructed concentrations were obtained, except for PM10 samples collected during Saharan dust events. This was due to the underestimation of the dust contribution during these episodes. Moderate differences in the average chemical composition of PM10 were observed between event and non-event days. Regarding PM1, only local pollution episodes had a certain impact on its chemical composition.
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•Ti in PM10 is a good indicator of Saharan dust events (SDE).•Submicron nitrate is the best tracer of local pollution episodes.•The calcium-to-dust ratio for SDE is lower than for non-event days.•Moderate differences in the composition of PM10 between event and non-event days.•SDE have little impact on the average composition of PM1.
Worldwide photovoltaic power generation is affected by deposited dust on photovoltaic (PV) systems, which creates soiling losses. In this work, factors that have a detrimental influence on dust ...deposition and an impact on PV systems performance were reviewed. The different ways that dust deposition can be a barrier for India’s energy security plan involving PV were also discussed. Different available cleaning techniques were also introduced. The nature, size, and morphology of dust particles vary with geographical location. Any increase of the PV tilt angle, or high wind speed and heavy rain showers reduce dust deposition. Deposited dust reduces the incident transmitted light on the PV, which has an adverse impact on the reduction of short circuit current. However, the open-circuit voltage has a reduced effect due to dust deposition. The enhancement of temperature caused by dust-covered PVs is still a debatable area. A universal cleaning technique is required to eliminate the soiling losses from PV. India has a solar mission to generate 100 GW of PV power by 2022. However, India’s poor air quality can undermine efforts to achieve this target.
The Lesser Antilles is an intermediate zone located between the Caribbean Sea and the Atlantic Ocean. This area is frequently affected by the major long range Saharan dust transportation from West ...African desert sources. The aerosols optical properties are provided by the AEronet Robotic NETwork (AERONET) measurement sites in Puerto Rico, Guadeloupe, and Barbados. Thus, Aerosols Optical Depth (AOD), Angstrom Exponent (AE), Volume Particle Size Distribution (VPSD), complex refractive indexes, and Single Scattering Albedo (SSA) were used to define the predominant type of atmospheric particles namely sea salt aerosols, mineral dust or aerosols mixture. Obtained results show that aerosols in the atmospheric column (AOD) and surface dust measurements (PM10) are well correlated with correlation coefficients of 0.72 and 0.81 respectively for Puerto Rico, and Guadeloupe. Detailed analysis of optical data associated to daily PM10 concentrations highlighted that dust phenomenon can be observable below PM10 threshold of 50 μg∕m3 given by the European directives to detect dust episodes. Indeed, for Caribbean islands, episodes of desert dust phenomenon have been detected from 35 μg∕m3. The climatological assessment of monthly dust events observed in Puerto Rico, Guadeloupe, and Martinique between 2006 and 2016 highlighted a low dust season from November to February and a high dust season from May to August. Both seasons are separated by two transition dust periods: March to April and September to October. Lastly, the day-to-day back trajectories (NOAA-HYSPLIT) illustrated the general atmospheric circulation and show three main dust transportation routes: the North West African Path (62.7%); the South West African Path (20.8%) ; and the North East Atlantic Path (15.1%). By computing the average PM10 concentrations bring from each path, we notice that South West African Path is the most loaded in mineral dust because he comes from one of the most persistently active and intense dust sources in the world, i.e. Bodélé Depression in northern Chad.
•Microphysical characterization of aerosol particles in Caribbean islands is studied.•Surface dust concentrations are linked to aerosol optical properties.•A new PM10 threshold linked to African dust in the Lesser Antilles is proposed.•General circulation of dusty air mass paths in the North Atlantic area is identified.•Impact of desert dust phenomenon on vertical temperature profile is highlighted.
Low concentrations of pollutants may already be associated with significant health effects. An accurate assessment of individual exposure to pollutants therefore requires measuring pollutant ...concentrations at the finest possible spatial and temporal scales. Low-cost sensors (LCS) of particulate matter (PM) meet this need so well that their use is constantly growing worldwide. However, everyone agrees that LCS must be calibrated before use. Several calibration studies have already been published, but there is not yet a standardized and well-established methodology for PM sensors. In this work, we develop a method combining an adaptation of an approach developed for gas-phase pollutants with a dust event preprocessing to calibrate PM LCS (PMS7003) commonly used in urban environments. From the selection of outliers to model tuning and error estimation, the developed protocol allows to analyze, process and calibrate LCS data using multilinear (MLR) and random forest (RFR) regressions for comparison with a reference instrument. We demonstrate that the calibration performance was very good for PM1 and PM2.5 but turns out less good for PM10 (R2 = 0.94, RMSE = 0.55 μg/m3, NRMSE = 12 % for PM1 with MLR, R2 = 0.92, RMSE = 0.70 μg/m3, NRMSE = 12 % for PM2.5 with RFR and R2 = 0.54, RMSE = 2.98 μg/m3, NRMSE = 27 % for PM10 with RFR). Dust events removal significantly improved LCS accuracy for PM2.5 (11 % increase of R2 and 49 % decrease of RMSE) but no significant changes for PM1. Best calibration models included internal relative humidity and temperature for PM2.5 and only internal relative humidity for PM1. It turns out that PM10 cannot be properly measured and calibrated because of technical limitations of the PMS7003 sensor. This work therefore provides guidelines for PM LCS calibration. This represents a first step toward standardizing calibration protocols and facilitating collaborative research.
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•Low-cost calibrated sensors can be an effective tool in PM exposure assessment.•A 7-step protocol and guidelines are designed to calibrate low-cost sensors.•RFR & MLR methods performed better than traditional ones for all PM sizes.•For PM1: R2 = 0.94, NRMSE = 12 % and for PM2.5: R2 = 0.92, NRMSE = 12 %•Calibration of PM10 turned out to be less good (R2 = 0.54, NRMSE = 27 %).
According to the WHO, 3 million deaths are attributable to air pollution due to particulate matter (PM) world-wide. However, there are no specific updated studies which calculate short-term ...PM-related cause specific mortality in Spain. The objective is to quantify the relative risks (RRs) and attributable risks (ARs) of daily mortality associated with PM10 concentrations, registered in Spanish provinces and to calculate the number of PM-related deaths. We calculated daily mortality due to natural (ICD-10: A00 R99), circulatory (ICD-10: I00 I99) and respiratory causes (ICD-10: J00 J99) for each province across the period 2000–2009. Mean daily concentrations of PM10, NO2 and O3 was used. For the estimate of RRs and ARs, we used generalised linear models with a Poisson link. A meta-analysis was used to estimate RRs and ARs in the provinces with statically significant results. The overall RRs obtained for these provinces, corresponding to increases of 10 μ g/m3 in PM10 concentrations were 1.009 (95% CI: 1.006 1011) for natural, 1.026 (95% CI: 1.019 1033) for respiratory, and 1.009 (95% CI: 1.006 1012) for circulatory-cause mortality. This amounted to an annual overall total of 2683 deaths (95% CI: 852 4354) due to natural, 651 (95% CI: 359 1026) due to respiratory, and 556 (95% CI: 116 1012) due to circulatory causes, with 90% of this mortality lying below the WHO guideline values. This study provides an updated estimate of the effect had by this type of pollutant on causes of mortality, and constitutes an important basis for reinforcing public health measures.
Relative risks (RRs) of natural-cause mortality calculated for increases of 10 μg/m3 in PM10 levels. Display omitted
•According to the WHO, 3 million deaths are attributable to PM world-wide.•The RRs obtained for Spain were 1.009 (95% CI: 1.006 1011) for natural causes.•This amounted to an annual overall total for Spain of 2683 deaths (852 4354).•90% of this mortality lying below the WHO guideline values.•This study provides an updated estimate of the effect of PM on mortality.
Capsule: This is an updated specific study to calculate PM-specific mortality in the short term in Spain.
Short-term measurements of PM10, trace gases (SO2, NO2, and O3) and heavy metals during Diwali festival were studied in a moderately polluted site in the city of Jamshedpur (India). In this study, ...Diwali day event recorded extremely high 12-h PM10 levels (500.5 μgm−3, which is >5 times to the WHO standard) and massive loadings of ozone (53.33 μgm−3), SO2(8.6 μgm−3) and NO2 (73.32 μgm−3), On Diwali day, all the measured values for PM10, SO2, NO2 and O3 were found to be higher than prescribed limit of National Ambient Air Quality Standard (NAAQS) (PM10 = 60 μg/m3). The first time study about any firework episode was carried in this region. The concentrations of Fe, Zn, Pb, Mn, Cu, Cd, Be and Ni were higher by the 2.2,1.5,2.8,1.6,2.2,1.2,5.9 and 3.3, times respectively, on Diwali as compared to normal days values. The metal concentrations on Diwali day were found to be significantly different from a normal day (except Zn & Cd). In Diwali day the Diurnal variation of PM10, SO2, and NO2 was found to be significantly higher than daytime concentrations for a normal day (control). It was estimated that firework aerosol contributed 21–27% to ambient PM10 on Diwali. Inter correlation among the trace gases, PM10 and metals are clearly indicates the fireworks emissions extremely fluctuates in air quality. These results indicate that fireworks episode during Diwali festival affected the ambient air quality adversely due to emission and accumulation of PM10, SO2, NO2, O3, and trace metals.
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