Fungal spores overwhelm biogenic organic aerosols in a midlatitudinal forest

Both primary biological aerosol particles (PBAPs) and oxidation products of biogenic volatile organic compounds (BVOCs) contribute significantly to organic aerosols (OAs) in forested regions. However, little is known about their relative importance in diurnal timescales. Here, we report biomarkers of PBAP and secondary organic aerosols (SOAs) for their diurnal variability in a temperate coniferous forest in Wakayama, Japan. Tracers of fungal spores, trehalose, arabitol and mannitol, showed significantly higher levels in nighttime than daytime (p＜0.05), resulting from the nocturnal sporulation under near-saturated relative humidity. On the contrary, BVOC oxidation products showed higher levels in daytime than nighttime, indicating substantial photochemical SOA formation. Using tracer-based methods, we estimated that fungal spores account for 45％ of organic carbon (OC) in nighttime and 22％ in daytime, whereas BVOC oxidation products account for 15 and 19％, respectively. To our knowledge, we present for the first time highly time-resolved results that fungal spores overwhelmed BVOC oxidation products in contributing to OA especially in nighttime. This study emphasizes the importance of both PBAPs and SOAs in forming forest organic aerosols

Rapid reduction in black carbon emissions from China: evidence from 2009–2019 observations on Fukue Island, Japan

A long-term, robust observational record of atmospheric black carbon (BC) concentrations at Fukue Island for 2009–2019 was produced by unifying the data from a continuous soot monitoring system (COSMOS) and a Multi-Angle Absorption Photometer (MAAP). This record was then used to analyze emission trends from China. We identified a rapid reduction in BC concentrations of (−5.8±1.5) % yr−1 or −48 % from 2010 to 2018. We concluded that an emission change of (−5.3±0.7) % yr−1, related to changes in China of as much as −4.6 % yr−1, was the main underlying driver. This evaluation was made after correcting for the interannual meteorological variability (IAV) by using the regional atmospheric chemistry model simulations from the Weather Research and Forecasting (WRF) and Community Multiscale Air Quality (CMAQ) models (collectively WRF/CMAQ) with the constant emissions. This resolves the current fundamental disagreements about the sign of the BC emissions trend from China over the past decade as assessed from bottom-up emission inventories. Our analysis supports inventories reflecting the governmental clean air actions after 2010 (e.g., MEIC1.3, ECLIPSE versions 5a and 6b, and the Regional Emission inventory in ASia (REAS) version 3.1) and recommends revisions to those that do not (e.g., Community Emissions Data System – CEDS). Our estimated emission trends were fairly uniform across seasons but diverse among air mass origins. Stronger BC reductions, accompanied by a reduction in carbon monoxide (CO) emissions, occurred in regions of south-central East China, while weaker BC reductions occurred in north-central East China and northeastern China. Prior to 2017, the BC and CO emissions trends were both unexpectedly positive in northeastern China during winter months, which possibly influenced the climate at higher latitudes. The pace of the estimated emissions reduction over China surpasses the Shared Socioeconomic Pathways (SSPs with reference to SSP1, specifically) scenarios for 2015–2030, which suggests highly successful emission control policies. At Fukue Island, the BC fraction of fine particulate matter (PM2.5) also steadily decreased over the last decade. This suggests that reductions in BC emissions started without significant delay when compared to other pollutants such as NOx and SO2, which are among the key precursors of scattering PM2.5

Stable carbon and nitrogen isotopic compositions of ambient aerosols collected from Okinawa Island in the western North Pacific Rim, an outflow region of Asian dusts and pollutants

Stable carbon (delta C-13) and nitrogen (delta N-15) isotope ratios were measured for total carbon (TC) and nitrogen (TN), respectively, in aerosol (TSP) samples collected at Cape Hedo, Okinawa, an outflow region of Asian pollutants, during 2009-2010. The averaged delta C-13 and delta N-15 ratios are -22.2 parts per thousand and +12.5 parts per thousand, respectively. The delta C-13 values are similar in both spring (-22.5 parts per thousand) and winter (-22.5 parts per thousand), suggesting the similar sources and/or source regions. We found that delta C-13 from Okinawa aerosols are ca. 2 parts per thousand higher than those reported from Chinese megacities probably due to photochemical aging of organic aerosols. A strong correlation (r = 0.81) was found between nss-Ca and TSP, suggesting that springtime aerosols are influenced from Asian dusts. However, carbonates in the Asian dusts were titrated with acidic species such as sulfuric acid and oxalic acid during atmospheric transport although two samples suggested the presence of remaining carbonate. No correlations were found between delta C-13 and tracer compounds (levoglucosan, elemental carbon, oxalic acid, and Na+). During winter and spring, coal burning is significant source in China. Based on isotopic mass balance, contribution of coal burning origin particles to total aerosol carbon was estimated as ca. 97% in winter, which is probably associated with the high emissions in China. Contribution of NO3- to TN was on average 45% whereas that of NH4+ was 18%. These results suggest that vehicular exhaust is an important source of TN in Okinawa aerosols. Concentration of water-soluble organic nitrogen (WSON) is higher in summer, suggesting that WSON is more emitted from the ocean in warmer season whereas inorganic nitrogen is more emitted in winter and spring from pollution sources in the Asian continent

Organic tracers of primary biological aerosol particles at subtropical Okinawa Island in the western North Pacific Rim

Primary biological aerosol particles (PBAPs) play an important role in affecting atmospheric physical and chemical properties. Aerosol samples were collected at Cape Hedo, Okinawa Island, Japan, from October 2009 to February 2012 and analyzed for five primary saccharides and four sugar alcohols as PBAP tracers. We detected high levels of sucrose in spring when blossoming of plants happens and prolifically emits pollen to the air. Concentrations of glucose, fructose, and trehalose showed levels higher than the other saccharides in spring in 2010. In comparison, primary saccharide levels were mutually comparable in spring, summer, and autumn in 2011, indicating the interannual variability of their local production in subtropical forests, which is driven by local temperature and radiation. High trehalose events were found to be associated with Asian dust outflows, indicating that Asian dust also contributes to PBAPs at Okinawa. Sugar alcohols peaked in summer and correlated with local precipitation and temperature, indicating high microbial activities. Positive matrix factorization analysis confirmed that the PBAPs are mainly derived from local vegetation, pollen, and fungal spores. A higher contribution of PBAP tracers to water-soluble organic carbon (WSOC) was found in summer (14.9%). The annual mean ambient loadings of fungal spores and PBAPs were estimated as 0.49 mu gm(-3) and 4.12 mu gm(-3), respectively, using the tracer method. We report, for the first time, year-round biomarkers of PBAP and soil dust and their contributions to WSOC in the subtropical outflow region of the Asian continent

Springtime variations of organic and inorganic constituents in submicron aerosols (PM1.0) from Cape Hedo, Okinawa

During the spring season with enhanced Asian outflow, we collected submicron aerosol (PM1.0) samples at Cape Hedo, Okinawa Island in the western North Pacific Rim. We analyzed the filter samples for diacids, oxoacids, pyruvic acid, alpha-dicarbonyls and fatty acids to better understand the sources and atmospheric processes in the outflow regions of Asian pollutants. Molecular distributions of diacids show a predominance of oxalic acid (C-2) followed by malonic (C-3) and succinic (C-4) acids. Total diacids strongly correlated with secondary source tracers such as SO42- (r = 0.87), NH4+ (0.90) and methanesulfonate (MSA(-)) (0.84), suggesting that diacids are secondarily formed from their precursor compounds. We also found good correlations among C-2, organic carbon (OC) and elemental carbon (EC) in the Okinawa aerosols, suggesting that diacids are mainly derived from anthropogenic sources. However, a weak correlation of diacids with levoglucosan, a biomass burning tracer, suggests that biomass buring is not the main source of diacids, rather diacids are secondarily formed by photochemical oxidation of organic precursors derived from fossil fuel combustion. We found a strong correlation (r = 0.98) between inorganic nitrogen (NO3-N + NH4-N) and total nitrogen (TN), to which organic nitrogen (ON) contributed 23%. Fatty acids were characterized by even carbon number predominance, suggesting that they are derived from biogenic sources. The higher abundances of short chain fatty acids (C-20) further suggest that fatty acids are largely derived from marine phytoplankton during spring bloom. (C) 2015 Elsevier Ltd. All rights reserved

Thirteen years of observations on biomass burning organic tracers over Chichijima Island in the western North Pacific : An outflow region of Asian aerosols

East Asia is the world's greatest source region for the emission of anthropogenic aerosols and their precursors due to the rapid industrialization and intensive biomass burning (BB) activities. BB emits specific organic tracers such as levoglucosan, mannosan, and galactosan, which are produced by pyrolysis of cellulose and hemicellulose and then transported downwind to the western North Pacific by westerly winds. Here we present long-term observations of BB tracers over the remote Chichijima Island in the western North Pacific (WNP) from 2001 to 2013. Elevated concentrations of BB tracers by an order of magnitude were found in midautumn to midspring with winter maxima, which are strongly involved with the atmospheric transport by westerly winds from the Asian continent to the WNP, as supported by backward trajectory analyses. Throughout the observations, we found an increase in the averaged concentrations of BB tracers from 2006 to 2013, which is mainly caused by enhanced BB events in Asian urban and rural areas, as supported by enhanced fire/hot spots in East Asia via satellite images. We also found that the period of the high concentrations was prolonged from 2006 to 2013. Comparison between monthly averaged concentrations of BB tracers and backward air mass trajectories clearly demonstrates that the winter/spring maxima over Chichijima are involved with the seasonal shifting of atmospheric circulation followed by downwind transport of BB aerosols to the WNP. High abundances of BB tracers over the WNP indicate that BB-laden air masses can be transported to remote marine environments

DII-GCN: Dropedge Based Deep Graph Convolutional Networks

Graph neural networks (GNNs) have gradually become an important research branch in graph learning since 2005, and the most active one is unquestionably graph convolutional neural networks (GCNs). Although convolutional neural networks have successfully learned for images, voices, and texts, over-smoothing remains a significant obstacle for non-grid graphs. In particular, because of the over-smoothing problem, most existing GCNs are only effective below four layers. This work proposes a novel GCN named DII-GCN that originally integrates Dropedge, Initial residual, and Identity mapping methods into traditional GCNs for mitigating over-smoothing. In the first step of the DII-GCN, the Dropedge increases the diversity of learning sample data and slows down the network’s learning speed to improve learning accuracy and reduce over-fitting. The initial residual is embedded into the convolutional learning units under the identity mapping in the second step, which extends the learning path and thus weakens the over-smoothing issue in the learning process. The experimental results show that the proposed DII-GCN achieves the purpose of constructing deep GCNs and obtains better accuracy than existing shallow networks. DII-GCN model has the highest 84.6% accuracy at 128 layers of the Cora dataset, highest 72.5% accuracy at 32 layers of the Citeseer dataset, highest 79.7% accuracy at 32 layers of the Pubmed dataset