High secondary aerosol contribution to particulate pollution during haze events in China

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 2.5micrometres) 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.

Does Age Matter? Semantic Memory in Healthy Young and Elderly Adults

Background: Semantic memory processes have been well described in literature. However, the available findings are mostly based on relatively young subjects and concrete word material (e.g. tree). Comparatively little information exists about semantic memory for abstract words (e.g. mind) and possible age related changes in semantic retrieval. In this respect, we developed a paradigm that is useful to investigate the implicit (i.e. attentionindependent) access to concrete and abstract semantic memory. These processes were then compared between young and elderly healthy subjects. Methods: A well established tool for investigating semantic memory processes is the semantic priming paradigm, which consists both of semantically unrelated and related word pairs. In our behavioral task these noun-noun word pairs were further divided into concrete, abstract and matched pronounceable non-word conditions. With this premise, the young and elderly participants performed a lexical decision task: they were asked to press a choice of two buttons as an indication for whether the word pair contained a non-word or not. In order to minimize controlled (i.e. attention-dependent) retrieval strategies, a short stimulus onset asynchrony (SOA) of 150ms was set. Reaction time (RT) changes and accuracy to related and unrelated words (priming effect) in the abstract vs. concrete condition (concreteness effect) were the dependent variables of interest. Results and Discussion: Statistical analysis confirmed both a significant priming effect (i.e. shorter RTs in semantically related compared to unrelated words) and a concreteness effect (i.e. RT decrease for concrete compared to abstract words) in the young and elderly subjects. There was no age difference in accuracy. The only age effect was a commonly known general slowing in RT over all conditions. In conclusion, age is not a critical factor in the implicit access to abstract and concrete semantic memory.

Modeling the formation and aging of secondary organic aerosols during CalNex 2010

Four different literature parameterizations for the formation and evolution of urban secondary organic aerosol (SOA) frequently used in 3-D models are evaluated using a 0-D box model representing the Los Angeles metropolitan region during the California Research at the Nexus of Air Quality and Climate Change (CalNex) 2010 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 that 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. The results from the three parameterizations show large differences (e.g., a factor of 3 in SOA mass) and are not well constrained, underscoring the current uncertainties in this 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 recent parameterizations overpredict urban SOA formation at long photochemical ages (3 days) compared to observations from multiple sites, which can lead to problems in regional and especially global modeling. However, reducing IVOC emissions by one-half in the model to better match recent IVOC measurements improves SOA predictions at these long photochemical ages. Among the explicitly modeled VOCs, the precursor compounds that contribute the greatest SOA mass are methylbenzenes. Measured polycyclic aromatic hydrocarbons (naphthalenes) contribute 0.7% of the modeled 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) %. The relative contribution of each source is uncertain by almost a factor of 2 depending on the parameterization used. In-basin biogenic VOCs are predicted to contribute only a few percent to SOA. A regional SOA background of approximately 2.1 μgm-3 is also present due to the long-distance transport of highly aged OA, likely with a substantial contribution from regional biogenic SOA. 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 and which is higher on weekends. 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, one third of which is likely to be non-fossil.