ALBERT

Description: Although laboratory experiments have shown that organic compounds in both gasoline fuel and diesel engine exhaust can form secondary organic aerosol (SOA), the fractional contribution from gasoline and diesel exhaust emissions to ambient SOA in urban environments is poorly known. Here we use airborne and ground-based measurements of organic aerosol (OA) in the Los Angeles (LA) Basin, California made during May and June 2010 to assess the amount of SOA formed from diesel emissions. Diesel emissions in the LA Basin vary between weekdays and weekends, with 54% lower diesel emissions on weekends. Despite this difference in source contributions, in air masses with similar degrees of photochemical processing, formation of OA is the same on weekends and weekdays, within the measurement uncertainties. This result indicates that the contribution from diesel emissions to SOA formation is zero within our uncertainties. Therefore, substantial reductions of SOA mass on local to global scales will be achieved by reducing gasoline vehicle emissions.

Description: Rapid industrialization and urbanization in developing countries has led to an increase in air pollution, along a similar trajectory to that previously experienced by the developed nations. In China, particulate pollution is a serious environmental problem that is influencing air quality, regional and global climates, and human health. In response to the extremely severe and persistent haze pollution experienced by about 800 million people during the first quarter of 2013 (refs 4, 5), the Chinese State Council announced its aim to reduce concentrations of PM2.5 (particulate matter with an aerodynamic diameter less than 2.5 micrometres) by up to 25 per cent relative to 2012 levels by 2017 (ref. 6). Such efforts however require elucidation of the factors governing the abundance and composition of PM2.5, which remain poorly constrained in China. Here we combine a comprehensive set of novel and state-of-the-art offline analytical approaches and statistical techniques to investigate the chemical nature and sources of particulate matter at urban locations in Beijing, Shanghai, Guangzhou and Xi'an during January 2013. We find that the severe haze pollution event was driven to a large extent by secondary aerosol formation, which contributed 30-77 per cent and 44-71 per cent (average for all four cities) of PM2.5 and of organic aerosol, respectively. On average, the contribution of secondary organic aerosol (SOA) and secondary inorganic aerosol (SIA) are found to be of similar importance (SOA/SIA ratios range from 0.6 to 1.4). Our results suggest that, in addition to mitigating primary particulate emissions, reducing the emissions of secondary aerosol precursors from, for example, fossil fuel combustion and biomass burning is likely to be important for controlling China's PM2.5 levels and for reducing the environmental, economic and health impacts resulting from particulate pollution.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Huang, Ru-Jin -- Zhang, Yanlin -- Bozzetti, Carlo -- Ho, Kin-Fai -- Cao, Jun-Ji -- Han, Yongming -- Daellenbach, Kaspar R -- Slowik, Jay G -- Platt, Stephen M -- Canonaco, Francesco -- Zotter, Peter -- Wolf, Robert -- Pieber, Simone M -- Bruns, Emily A -- Crippa, Monica -- Ciarelli, Giancarlo -- Piazzalunga, Andrea -- Schwikowski, Margit -- Abbaszade, Gulcin -- Schnelle-Kreis, Jurgen -- Zimmermann, Ralf -- An, Zhisheng -- Szidat, Sonke -- Baltensperger, Urs -- El Haddad, Imad -- Prevot, Andre S H -- England -- Nature. 2014 Oct 9;514(7521):218-22. doi: 10.1038/nature13774. Epub 2014 Sep 17.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland [2] State Key Laboratory of Loess and Quaternary Geology (SKLLQG), and Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710075, China [3]. ; 1] Department of Chemistry and Biochemistry, and Oeschger Centre for Climate Change Research, University of Bern, 3012 Bern, Switzerland [2] Laboratory of Radiochemistry and Environmental Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland. ; Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland. ; The Jockey Club School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong, China. ; State Key Laboratory of Loess and Quaternary Geology (SKLLQG), and Key Laboratory of Aerosol Chemistry and Physics, Institute of Earth Environment, Chinese Academy of Sciences, Xi'an 710075, China. ; 1] Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland [2] European Commission, Joint Research Centre, Institute for Environment and Sustainability, Air and Climate Unit, Via Fermi, 2749, 21027 Ispra, Italy. ; Department of Earth and Environmental Sciences, University of Milano Bicocca, Piazza della Scienza 1, Milan 20126, Italy. ; Helmholtz Zentrum Munchen, German Research Center for Environmental Health (GmbH), Joint Mass Spectrometry Centre, Cooperation Group Comprehensive Molecular Analytics and Helmholtz Virtual Institute of Complex Molecular Systems in Environmental Health - Aerosol and Health (HICE), 85764 Neuherberg, Germany. ; 1] Helmholtz Zentrum Munchen, German Research Center for Environmental Health (GmbH), Joint Mass Spectrometry Centre, Cooperation Group Comprehensive Molecular Analytics and Helmholtz Virtual Institute of Complex Molecular Systems in Environmental Health - Aerosol and Health (HICE), 85764 Neuherberg, Germany [2] University of Rostock, Joint Mass Spectrometry Centre, Institute of Chemistry, Analytical Chemistry, 18015 Rostock, Germany. ; Department of Chemistry and Biochemistry, and Oeschger Centre for Climate Change Research, University of Bern, 3012 Bern, Switzerland. ; 1] Laboratory of Atmospheric Chemistry, Paul Scherrer Institute (PSI), 5232 Villigen, Switzerland [2].〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25231863" target="_blank"〉PubMed〈/a〉

Description: Black carbon aerosols (BC) at a London urban site were characterised in both winter- and summertime 2012 during the Clean Air for London (ClearfLo) project. Positive matrix factorisation (PMF) factors of organic aerosol mass spectra measured by a high-resolution aerosol mass spectrometer (HR-AMS) showed traffic-dominant sources in summer but in winter the influence of additional non-traffic sources became more important, mainly from solid fuel sources (SF). Measurements using a single particle soot photometer (SP2, DMT), showed the traffic-dominant BC exhibited an almost uniform BC core size (Dc) distribution with very thin coating thickness throughout the detectable range of Dc. However, the size distribution of Dc (project average mass median Dc = 149 ± 22 nm in winter, and 120 ± 6 nm in summer) and BC coating thickness varied significantly in winter. A novel methodology was developed to attribute the BC number concentrations and mass abundances from traffic (BCtr) and from SF (BCsf), by using a 2-D histogram of the particle optical properties as a function of BC core size, as measured by the SP2. The BCtr and BCsf showed distinctly different Dc distributions and coating thicknesses, with BCsf displaying larger Dc and larger coating thickness compared to BCtr. BC particles from different sources were also apportioned by applying a multiple linear regression between the total BC mass and each AMS-PMF factor (BC–AMS–PMF method), and also attributed by applying the absorption spectral dependence of carbonaceous aerosols to 7-wavelength Aethalometer measurements (Aethalometer method). Air masses that originated from westerly (W), southeasterly (SE), and easterly (E) sectors showed BCsf fractions that ranged from low to high, and whose mass median Dc values were 137 ± 10 nm, 143 ± 11 nm and 169 ± 29 nm, respectively. The corresponding bulk relative coating thickness of BC (coated particle size/BC core – Dp/Dc) for these same sectors was 1.28 ± 0.07, 1.45 ± 0.16 and 1.65 ± 0.19. For W, SE and E air masses, the number fraction of BCsf ranged from 6 ± 2% to 11 ± 5% to 18 ± 10%, respectively, but importantly the larger BC core sizes lead to an increased fraction of BCsf in terms of mass than number (for W, SE and E air masses, the BCsf mass fractions ranged from 16 ± 6%, 24 ± 10% and 39 ± 14%, respectively). An increased fraction of non-BC particles (particles that did not contain a BC core) was also observed when SF sources were more significant. The BC mass attribution by the SP2 method agreed well with the BC–AMS–PMF multiple linear regression method (BC–AMS–PMF : SP2 ratio = 1.05, r2 = 0.80) over the entire experimental period. Good agreement was found between BCsf attributed with the Aethalometer model and the SP2. However, the assumed absorption Ångström exponent (αwb) had to be changed according to the different air mass sectors to yield the best comparison with the SP2. This could be due to influences of fuel type or burn phase.

Description: Radiocarbon (14C) measurements of elemental carbon (EC) and organic carbon (OC) separately (as opposed to only total carbon, TC) allow an unambiguous quantification of their non-fossil and fossil sources and represent an improvement in carbonaceous aerosol source apportionment. Isolation of OC and EC for accurate 14C determination requires complete removal of interfering fractions with maximum recovery. The optimal strategy for 14C-based source apportionment of carbonaceous aerosols should follow an approach to subdivide TC into different carbonaceous aerosol fractions for individual 14C analyses, as these fractions may differ in their origins. To evaluate the extent of positive and negative artefacts during OC and EC separation, we performed sample preparation with a commercial Thermo-Optical OC/EC Analyser (TOA) by monitoring the optical properties of the sample during the thermal treatments. Extensive attention has been devoted to the set-up of TOA conditions, in particular, heating program and choice of carrier gas. Based on different types of carbonaceous aerosols samples, an optimised TOA protocol (Swiss_4S) with four steps is developed to minimise the charring of OC, the premature combustion of EC and thus artefacts of 14C-based source apportionment of EC. For the isolation of EC for 14C analysis, the water-extraction treatment on the filter prior to any thermal treatment is an essential prerequisite for subsequent radiocarbon measurements; otherwise the non-fossil contribution may be overestimated due to the positive bias from charring. The Swiss_4S protocol involves the following consecutive four steps (S1, S2, S3 and S4): (1) S1 in pure oxygen (O2) at 375 °C for separation of OC for untreated filters and water-insoluble organic carbon (WINSOC) for water-extracted filters; (2) S2 in O2 at 475 °C followed by (3) S3 in helium (He) at 650 °C, aiming at complete OC removal before EC isolation and leading to better consistency with thermal-optical protocols like EUSAAR_2, compared to pure oxygen methods; and (4) S4 in O2 at 760 °C for recovery of the remaining EC. WINSOC was found to have a significantly higher fossil contribution than the water-soluble OC (WSOC). Moreover, the experimental results demonstrate the lower refractivity of wood-burning EC compared to fossil EC and the difficulty of clearly isolating EC without premature evolution. Hence, simplified techniques of EC isolation for 14C analysis are prone to a substantial bias and generally tend towards an overestimation of fossil sources. To obtain the comprehensive picture of the sources of carbonaceous aerosols, the Swiss_4S protocol is not only implemented to measure OC and EC fractions, but also WINSOC as well as a continuum of refractory OC and non-refractory EC for 14C source apportionment. In addition, WSOC can be determined by subtraction of the water-soluble fraction of TC from untreated TC. Last, we recommend that 14C results of EC should in general be reported together with the EC recovery.

Description: Air quality and heat are strong health drivers, and their accurate assessment and forecast are important in densely populated urban areas. However, the sources and processes leading to high concentrations of main pollutants, such as ozone, nitrogen dioxide, and fine and coarse particulate matter, in complex urban areas are not fully understood, limiting our ability to forecast air quality accurately. This paper introduces the Clean Air for London (ClearfLo; www.clearflo.ac.uk) project’s interdisciplinary approach to investigate the processes leading to poor air quality and elevated temperatures. Within ClearfLo, a large multi-institutional project funded by the U.K. Natural Environment Research Council (NERC), integrated measurements of meteorology and gaseous, and particulate composition/loading within the atmosphere of London, United Kingdom, were undertaken to understand the processes underlying poor air quality. Long-term measurement infrastructure installed at multiple levels (street and elevated), and at urban background, curbside, and rural locations were complemented with high-resolution numerical atmospheric simulations. Combining these (measurement–modeling) enhances understanding of seasonal variations in meteorology and composition together with the controlling processes. Two intensive observation periods (winter 2012 and the Summer Olympics of 2012) focus upon the vertical structure and evolution of the urban boundary layer; chemical controls on nitrogen dioxide and ozone production—in particular, the role of volatile organic compounds; and processes controlling the evolution, size, distribution, and composition of particulate matter. The paper shows that mixing heights are deeper over London than in the rural surroundings and that the seasonality of the urban boundary layer evolution controls when concentrations peak. The composition also reflects the seasonality of sources such as domestic burning and biogenic emissions.

Description: Radiocarbon offers a unique possibility for unambiguous source apportionment of carbonaceous particles due to a direct distinction of non-fossil and fossil carbon. In this work, particulate matter of different size fractions was collected at 4 sites in Switzerland to examine whether fine and coarse carbonaceous particles exhibit different fossil and contemporary sources. Elemental carbon (EC) and organic carbon (OC) as well as water-soluble OC (WSOC) and water-insoluble OC (WINSOC) were separated and determined for subsequent 14C measurement. In general, both fossil and non-fossil fractions in OC and EC were found more abundant in the fine than in the coarse mode. However, a substantial fraction (∼20 ± 5%) of fossil EC was found in coarse particles, which could be attributed to traffic-induced non-exhaust emissions. The contribution of biomass burning to coarse-mode EC in winter was relatively high, which is likely associated to the coating of EC with organic and/or inorganic substances emitted from intensive wood burning. Further, fossil OC (i.e. from vehicle emissions) was found to be smaller than non-fossil OC due to the presence of primary biogenic OC and/or growing in size of wood-burning OC particles during aging processes. 14C content in WSOC indicated that the second organic carbon rather stems from non-fossil precursors for all samples. Interestingly, both fossil and non-fossil WINSOC concentrations were found to be higher in fine particles than in coarse particles in winter, which is likely due to primary wood burning emissions and/or secondary formation of WINSOC.

Description: Four different parameterizations for the formation and evolution of secondary organic aerosol (SOA) are evaluated using a 0-D box model representing the Los Angeles Metropolitan Region during the CalNex 2010 field campaign. We constrain the model predictions with measurements from several platforms and compare predictions with particle and gas-phase observations from the CalNex Pasadena ground site. That site provides a unique opportunity to study aerosol formation close to anthropogenic emission sources with limited recirculation. The model SOA formed only from the oxidation of VOCs (V-SOA) is insufficient to explain the observed SOA concentrations, even when using SOA parameterizations with multi-generation oxidation that produce much higher yields than have been observed in chamber experiments, or when increasing yields to their upper limit estimates accounting for recently reported losses of vapors to chamber walls. The Community Multiscale Air Quality (WRF-CMAQ) model (version 5.0.1) provides excellent predictions of secondary inorganic particle species but underestimates the observed SOA mass by a factor of 25 when an older VOC-only parameterization is used, which is consistent with many previous model-measurement comparisons for pre-2007 anthropogenic SOA modules in urban areas. Including SOA from primary semi-volatile and intermediate volatility organic compounds (P-S/IVOCs) following the parameterizations of Robinson et al. (2007), Grieshop et al. (2009), or Pye and Seinfeld (2010) improves model/measurement agreement for mass concentration. When comparing the three parameterizations, the Grieshop et al. (2009) parameterization more accurately reproduces both the SOA mass concentration and oxygen-to-carbon ratio inside the urban area. Our results strongly suggest that other precursors besides VOCs, such as P-S/IVOCs, are needed to explain the observed SOA concentrations in Pasadena. All the parameterizations over-predict urban SOA formation at long photochemical ages (≈ 3 days) compared to observations from multiple sites, which can lead to problems in regional and global modeling. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Polycyclic aromatic hydrocarbons (PAHs) are less important precursors and contribute less than 4% of the SOA mass. The amounts of SOA mass from diesel vehicles, gasoline vehicles, and cooking emissions are estimated to be 16–27, 35–61, and 19–35%, respectively, depending on the parameterization used, which is consistent with the observed fossil fraction of urban SOA, 71 (±3) %. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μg m−3 is also present due to the long distance transport of highly aged OA. The percentage of SOA from diesel vehicle emissions is the same, within the estimated uncertainty, as reported in previous work that analyzed the weekly cycles in OA concentrations (Bahreini et al., 2012; Hayes et al., 2013). However, the modeling work presented here suggests a strong anthropogenic source of modern carbon in SOA, due to cooking emissions, which was not accounted for in those previous studies. Lastly, this work adapts a simple two-parameter model to predict SOA concentration and O/C from urban emissions. This model successfully predicts SOA concentration, and the optimal parameter combination is very similar to that found for Mexico City. This approach provides a computationally inexpensive method for predicting urban SOA in global and climate models. We estimate pollution SOA to account for 26 Tg yr−1 of SOA globally, or 17% of global SOA, 1/3 of which is likely to be non-fossil.

Description: Black carbon aerosols (BC) at a London urban site were characterized in both winter and summer time 2012 during the Clean Air for London (ClearfLo) project. Positive matrix factorization (PMF) factors of organic aerosol mass spectra measured by a high resolution aerosol mass spectrometer (HR-AMS) showed traffic-dominant sources in summer but in winter the influence of additional non-traffic sources became more important, mainly from solid fuel sources (SF). Measurements using a single particle soot photometer (SP2, DMT), showed the traffic-dominant BC exhibited an almost uniform BC core size (Dc) distribution with very thin coating thickness throughout the detectable range of Dc. However the size distribution of Dc (project average mass median Dc = 149 ± 22 nm in winter, and 120 ± 6 nm in summer) and BC coating thickness varied significantly in winter. A novel methodology was developed to attribute the BC number concentrations and mass abundances from traffic (BCtr) and from SF (BCsf), by using a 2-D histogram of the particle optical properties as a function of BC core size, as measured by the SP2. The BCtr and BCsf showed distinctly different Dc distributions and coating thicknesses, with BCsf displaying larger Dc and larger coating thickness compared to BCtr. BC particles from different sources were also apportioned by applying a multiple linear regression between the total BC mass and each AMS-PMF factor (BC-AMS-PMF method), and also attributed by applying the absorption spectral dependence of carbonaceous aerosols to 7-wavelength Aethalometer measurements (Aethalometer method). Air masses that originated from westerly (W), southeasterly (SE), or easterly (E) sectors showed BCsf fractions that ranged from low to high, and whose mass median Dc values were 137 ± 10 nm, 143 ± 11 nm, and 169 ± 29 nm respectively. The corresponding bulk relative coating thickness of BC (coated particle size / BC core – Dp / Dc) for these same sectors was 1.28 ± 0.07, 1.45 ± 0.16, and 1.65 ± 0.19. For W, SE and E air masses, the number fraction of BCsf ranged from 6 ± 2% to 11 ± 5% to 18 ± 10% respectively, but importantly the larger BC core sizes lead to an increased fraction of BCsf in terms of mass than number (for W–SE–E air masses, the BCsf mass fractions ranged from 16 ± 6 %–24 ± 10%–39 ± 14% respectively). An increased fraction of non-BC particles (particles that did not contain a BC core) was also observed when SF sources were more significant. The BC mass attribution by the SP2 method agreed well with the BC-AMS-PMF multiple linear regression method (BC-AMS-PMF : SP2 ratio = 1.05, r2 = 0.80) over the entire experimental period. Good agreement was found between BCsf attributed with the Aethalometer model and the SP2. However, the assumed Absorption Ångström Exponent (αwb) had to be changed according to the different air mass sectors to yield the best comparison with the SP2. This could be due to influences of fuel type or burn phase.

Description: Determining the contribution of wood smoke to air pollution in large cities such as London is becoming increasingly important due to the changing nature of domestic heating in urban areas. During winter, biomass burning emissions can exceed the contributions from traffic emissions, and have been identified as a major cause of exceedences of European air quality limits. The aim of this work was to quantify the contribution of biomass burning in London to concentrations of PM2.5 and determine whether local emissions or regional contributions were the main source of biomass smoke. To achieve this, a number of biomass burning chemical tracers were analysed at a site within central London and two sites in surrounding rural areas. Concentrations of levoglucosan, elemental carbon (EC), organic carbon (OC) and K+ were generally well correlated across the three sites. At all the sites, biomass burning was found to be a source of OC and EC, with the largest contribution of EC from traffic emissions, while for OC the dominant fraction likely included contributions from secondary organic aerosols, primary biogenic and cooking sources. Source apportionment of the EC and OC using average source ratios from published data was found to give reasonable estimation of the total carbon from non-fossil and fossil fuel sources based upon comparison with estimates derived from 14C analysis. Black carbon (BC) data from 2 and 7 wavelength Aethalometers were also apportioned into the contributions from biomass burning and traffic, based upon the enhanced absorption of wood smoke at UV wavelengths compared to BC. While the source apportionment of BC using this approach found similar trends to that observed for EC, higher percentage contributions of wood burning to BC were estimated. Based on a wood smoke mass conversion factor for levoglucosan, mean wood smoke mass at the sites was found to range from 0.78–1.0 μg m−3 during the campaign in January–February 2012. Measurements on a 160 m tower in London suggested a similar ratio of brown to black carbon (reflecting wood burning and traffic respectively) in regional and London air. Peaks in the levoglucosan and K+ concentrations were observed to coincide with low ambient temperature, consistent with domestic heating as a major contributing local source in London. Overall, the source of biomass smoke in London was concluded to be a background regional source overlaid by contributions from local domestic burning emissions. This could have implications when considering future emission control strategies during winter and may be the focus of future work in order to better determine the contributing local sources.

Description: While several studies have investigated winter-time air pollution with a wide range of concentration levels, hardly any results are available for longer time periods covering several winter-smog episodes at various locations; e.g. often only a few weeks from a single winter are investigated. Here, we present source apportionment results of winter-smog episodes from 16 air pollution monitoring stations across Switzerland from five consecutive winters. Radiocarbon (14C) analyses of the elemental (EC) and organic (OC) carbon fractions, as well as levoglucosan, major water-soluble ionic species and gas-phase pollutant measurements were used to characterize the different sources of PM10. The most important contributions to PM10 during winter-smog episodes in Switzerland were on average the secondary inorganic constituents (sum of nitrate, sulfate and ammonium = 41 ± 15%) followed by organic matter OM (30 ± 12%) and EC (5 ± 2%). The non-fossil fractions of OC (fNF,OC) ranged on average from 69–85% and 80–95 % for stations north and south of the Alps, respectively, showing that traffic contributes on average only up to ~30% to OC. The non-fossil fraction of EC (fNF,EC), entirely attributable to primary biomass burning, was on average 42 ± 13% and 49 ± 15% for north and south of the Alps, respectively. While a high correlation was observed between fossil EC and nitrogen oxides, both primarily emitted by traffic, these species did not significantly correlate with fossil OC (OCF), which seems to suggest that a considerable amount of OCF is secondary, formed from fossil precursors. Elevated fNF,EC and fNF,OC values and the high correlation of the latter with other wood burning markers, including levoglucosan and water soluble potassium (K+) indicate that biomass burning is the major source of carbonaceous aerosols during winter-smog episodes in Switzerland. The inspection of the non-fossil OC and EC levels and the relation with levoglucosan and water-soluble K+ shows different ratios for stations north and south of the Alps, most likely because of differences in burning technologies, for these two regions in Switzerland.