Finer Particle Size Distribution and Potential Higher Toxicity of Elemental Carbon and Polycyclic Aromatic Hydrocarbons Emitted by Ships after Fuel Oil Quality Improvement.

Ship emissions are a significant source of air pollution, and the primary policy to control is fuel oil quality improvement. However, the impact of this policy on particle size distribution and composition characteristics remains unclear. Measurements were conducted on nine different vessels (ocean-going vessels, coastal cargo ships, and inland cargo ships) to determine the impact of fuel upgrading (S < 0.1% m/m marine gas oil (MGO) vs S < 0.5% m/m heavy fuel oil (HFO)) on elemental carbon (EC) and polycyclic aromatic hydrocarbons (PAHs) emitted by ships. (1) Fuel improvement significantly reduced EC and PAH emission, by 31 ± 25 and 45 ± 38%, respectively. However, particle size distributions showed a trend toward finer particles, with the peak size decreasing from DP = 0.38-0.60 µm (HFO) to DP = 0.15-0.25 µm (MGO), and the emission factor of DP < 100 nm increased. (2) Changes in emission characteristics led to an increase in the toxicity of ultrafine particulate matter. (3) Ship types and engine conditions affected the EC and PAH particle size distributions. Inland ships have a more concentrated particle size distribution. Higher loads result in higher emissions. (4) The composition and engine conditions of fuel oils jointly affected pollutant formation mechanisms. MGO and HFO exhibited opposite EC emissions when emitting the same level of PAHs.

Characteristics of PM2.5 bounded carbonaceous aerosols, carbon dioxide and its stable carbon isotopes (δ13C) in rural households in northwest China: Effect of different fuel combustion.

In order to fully understand the carbon emission from different fuels in rural villages of China, especially in the typical atmospheric pollution areas. The characteristics of carbonaceous aerosols and carbon dioxide (CO2) with its stable carbon isotope (δ13C) were investigated in six households, which two households used coal, two households used wood as well as two households used biogas and liquefied petroleum gas (LPG), from two rural villages in Fenwei Plain from March to April 2021. It showed that the fine particulate matter (PM2.5) emitted from biogas and LPG couldn't be as lower as expected in this area. However, the clean fuels could relatively reduce the emissions of organic carbon (OC) and element carbon (EC) in PM2.5 compare to the solid fuels. The pyrolyzed carbon (OP) accounted more total carbon (TC) in coal than the other fuels use households, indicating that more water-soluble OC existed, and it still had the highest secondary organic carbon (SOC) than the other fuels. Meantime, the coal combustions in the two villages had the highest CO2 concentration of 527.6 ppm and 1120.6 ppm, respectively, while the clean fuels could effectively reduce it. The average δ13C values (-26.9‰) was much lighter than almost all the outdoor monitoring and similar to the δ13C values for coal combustion and vehicle emission, showing that they might be the main contributors of the regional atmospheric aerosol in this area. During the sandstorm, the indoor PM2.5 mass and CO2 were increasing obviously. The indoor cancer risk of PAHs for adults and children were greater than 1 × 10-6, exert a potential carcinogenic risk to human of solid fuels combustion in rural northern China. It is important to continue concern the solid fuel combustion and its health impact in rural areas.

Historical trajectories of antibiotics resistance genes assessed through sedimentary DNA analysis of a subtropical eutrophic lake.

Investigating the occurrence of antibiotic-resistance genes (ARGs) in sedimentary archives provides opportunities for reconstructing the distribution and dissemination of historical (i.e., non-anthropogenic origin) ARGs. Although ARGs in freshwater environments have attracted great attention, historical variations in the diversity and abundance of ARGs over centuries to millennia remain largely unknown. In this study, we investigated the vertical change patterns of bacterial communities, ARGs and mobile genetic elements (MGEs) found in sediments of Lake Chenghai spanning the past 600 years. Within resistome preserved in sediments, 177 ARGs subtypes were found with aminoglycosides and multidrug resistance being the most abundant. The ARG abundance in the upper sediment layers (equivalent to the post-antibiotic era since the 1940s) was lower than those during the pre-antibiotic era, whereas the ARG diversity was higher during the post-antibiotic era, possibly because human-induced lake eutrophication over the recent decades facilitated the spread and proliferation of drug-resistant bacteria. Statistical analysis suggested that MGEs abundance and the bacterial community structure were significantly correlated with the abundance and diversity of ARGs, suggesting that the occurrence and distribution of ARGs may be transferred between different bacteria by MGEs. Our results provide new perspectives on the natural history of ARGs in freshwater environments and are essential for understanding the temporal dynamics and dissemination of ARGs.

Biogas production prediction model of food waste anaerobic digestion for energy optimization using mixup data augmentation-based global attention mechanism.

Achieving rapid, efficient, and cost-effective anaerobic digestion (AD) of food waste is a key means to improve the efficiency of food waste treatment. However, in view of the shortage of historical anaerobic digestion data, the limitation of general neural networks in predicting biogas production, and its sensitivity to abnormal variation points, achieving accurate prediction of biogas production is not easy. This paper proposes a novel biogas production prediction model of food waste AD for energy optimization based on the mixup data augmentation integrating an improved global attention mechanism long short-term memory (LSTM). Taking the AD data of the actual factory as samples, the mixup data augmentation is introduced to generate virtual samples with the similar distribution as original samples. Then original samples and generated virtual samples are used as the input of the global attention mechanism LSTM to establish the food waste AD biogas production prediction model. Finally, the proposed method is applied in the biogas production prediction of actual food waste treatment plants. Compared with other industrial modeling models, the experimental results show that the proposed method has the highest prediction accuracy of 0.988, which performs well in predicting biogas production and can effectively guide and timely adjust feed configuration of AD plants.

Exposure to polycyclic aromatic hydrocarbons (PAHs) from domestic heating and cooking combustion of different fuel types for elders in rural China.

Solid fuel combustion emitted abundant pollutants, especially polycyclic aromatic hydrocarbons (PAHs) which had significant minus impact on human health in rural China. PAHs in PM2.5 emitted from different fuels combustion and hydroxylated metabolites of PAHs (OH-PAHs) in urine samples of different fuel users were detected in this study. The indoor PAHs were higher than that in outdoors for solid fuel use households, and the concentration of PAHs in the indoor of liquefied petroleum gas (LPG) use household was not much lower than solid fuel use households. Biogas-use household produced the lowest PAHs, which significantly reduced 64-82% compared with those emitted by solid fuel combustion. The different combustion conditions influenced the gaseous PAHs in indoors between two sampling sites. The gas/particle partition indicated that PAHs tended to occur in the particle phase with increased molecular weight, and the absorption was the main mechanism. The relative higher contribution of high molecular weight PAHs (HMW-PAHs) in solid fuel use households than in clean fuel use households, induced more health risks of PAHs. The concentration of Σ10OH-PAHs in the urine samples for elders of different fuel-use households displayed the trend of coal (83.27 ng/mL) > wood (79.32 ng/mL) > LPG (51.61 ng/mL) > biogas (28.96 ng/mL), and OH-NaPs was the predominant metabolites, which accounted for more than 90% of the total concentration. The carcinogenic risk of PAHs based on internal exposure was greater than or close to 10-4, with serious carcinogenic risks. This was different with the incremental lifetime cancer risk based on the atmospheric concentrations. The exposure of PAHs from solid fuel combustion for human being especially for the elders in this region should be concerned, and more data should be done for the internal exposure of PAHs.

Correction: Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

[This corrects the article DOI: 10.1371/journal.pone.0287187.].

Combined use of principal component analysis/multiple linear regression analysis and artificial neural network to assess the impact of meteorological parameters on fluctuation of selected PM2.5-bound elements.

Based on the data of the State of Global Air (2020), air quality deterioration in Thailand has caused ~32,000 premature deaths, while the World Health Organization evaluated that air pollutants can decrease the life expectancy in the country by two years. PM2.5 was collected at three air quality observatory sites in Chiang-Mai, Bangkok, and Phuket, Thailand, from July 2020 to June 2021. The concentrations of 25 elements (Na, Mg, Al, Si, S, Cl, K, Ca, Sc, Ti, V, Cr, Mn, Fe, Co, Ni, Cu, Zn, Ga, As, Se, Br, Sr, Ba, and Pb) were quantitatively characterised using energy-dispersive X-ray fluorescence spectrometry. Potential adverse health impacts of some element exposures from inhaling PM2.5 were estimated by employing the hazard quotient and excess lifetime cancer risk. Higher cancer risks were detected in PM2.5 samples collected at the sampling site in Bangkok, indicating that vehicle exhaust adversely impacts human health. Principal component analysis suggests that traffic emissions, crustal inputs coupled with maritime aerosols, and construction dust were the three main potential sources of PM2.5. Artificial neural networks underlined agricultural waste burning and relative humidity as two major factors controlling the air quality of Thailand.

Reconstructing atmospheric 129I deposition over 170 years with the varved sediment in the Sihailongwan Maar Lake, northeast China.

Long-term deposition of atmospheric radioactive iodine-129 (129I) is important for assessing the impact of human nuclear activities (HNAs), but still not well understood in East Asia. In this study, we quantitatively reconstructed the deposition history of airborne 129I using varved sediment from Sihailongwan Maar Lake (SHLW) in northeast China. Our results revealed significant increases in 129I concentrations and 129I/127I atomic ratios since the 1950s, indicating the influence of HNAs on the environment and marking the onset of the Anthropocene. The variation of 129I in the investigated site can be primarily attributed to the global fallout of ANWT as well as nuclear fuel reprocessing in Europe, Russia and the USA. Notably, neither the Chernobyl nor the Fukushima nuclear accidents have had any discernable impact on the SHLW Lake. Over the past 170 years (1846-2021), the reconstructed fluxes indicate a rapid increase in 129I deposition from the early 1950s until the 1970s followed by dramatic changes thereafter. The measured 129I fluxes range between (1.26-349) × 109 atoms m-2 yr-1 in the SHLW Lake, which are consistent with similar latitude zones across East Asia, but differ significantly from those observed in high-elevation glaciers within the Northern Hemisphere due to prevailing atmospheric circulation patterns. The total 129I inventory was calculated to be 11.9 × 1012 atoms m-2, with natural and anthropogenic 129I accounting for 2.86 % and 97.1 %, respectively, suggesting an overwhelming artificial contribution. The reconstructed fluxes and inventory of atmospheric 129I deposition quantitatively distinguish the natural and artificial contributions, and provide a novel insight into the historical environmental impact of HNAs in East Asia and the characteristics of the Anthropocene.

The impacts of regional transport on anthropogenic source contributions of PM2.5 in a basin city, China.

PM2.5 pollution events are often happened in urban agglomeration locates in mountain-basin regions due to the complex terra and intensive emissions. Source apportionment is essential for identifying the pollution sources and important for developing local mitigation strategies, however, it is influenced by regional transport. To understand how the regional transport influences the atmospheric environment of a basin, we connected the PM2.5 source contributions estimated by observation-based receptor source apportionment and the regional contributions estimated by a tagging technology in the comprehensive air quality model with extensions (CAMx) via an artificial neural network (ANNs). The result shows that the PM2.5 in Xi'an was from biomass burning, coal combustion, traffic related emissions, mineral dust, industrial emissions, secondary nitrate and sulfate. 48.8 % of the PM2.5 in study period was from Xi'an, then followed by the outside area of Guanzhong basin (28.2 %), Xianyang (14.6 %) and Weinan (5.8 %). Baoji and Tongchuan contributed trivial amount. The sensitivity analysis showed that the transported PM2.5 would lead to divergent results of source contributions at Xi'an. The transported PM2.5 from the outside has great a potential to alter the source contributions implying a large uncertainty of the source apportionment introduced when long-range transported pollutants arrived. It suggests that a full comprehension on the impacts of regional transport can lower the uncertainty of the local PM2.5 source apportionment and reginal collaborative actions can be of great use for pollution mitigation.

Near-gapless and haplotype-resolved apple genomes provide insights into the genetic basis of rootstock-induced dwarfing.

Dwarfing rootstocks have transformed the production of cultivated apples; however, the genetic basis of rootstock-induced dwarfing remains largely unclear. We have assembled chromosome-level, near-gapless and haplotype-resolved genomes for the popular dwarfing rootstock 'M9', the semi-vigorous rootstock 'MM106' and 'Fuji', one of the most commonly grown apple cultivars. The apple orthologue of auxin response factor 3 (MdARF3) is in the Dw1 region of 'M9', the major locus for rootstock-induced dwarfing. Comparing 'M9' and 'MM106' genomes revealed a 9,723-bp allele-specific long terminal repeat retrotransposon/gypsy insertion, DwTE, located upstream of MdARF3. DwTE is cosegregated with the dwarfing trait in two segregating populations, suggesting its prospective utility in future dwarfing rootstock breeding. In addition, our pipeline discovered mobile mRNAs that may contribute to the development of dwarfed scion architecture. Our research provides valuable genomic resources and applicable methodology, which have the potential to accelerate breeding dwarfing rootstocks for apple and other perennial woody fruit trees.