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Traffic is a major source of ultrafine aerosol particles in urban environments. Recent studies show that a significant fraction of traffic-related particles are only few nanometers in diameter. Here, we study the dispersion of this nanocluster aerosol (NCA) in the size range 1.3-4 nm. We measured particle concentrations near a major highway in the Helsinki region of Finland, varying the distance from the highway. Additionally, modelling studies were performed to gain further information on how different transformation processes affect NCA dispersion. The roadside measurements showed that NCA concentrations fell more rapidly than the total particle concentrations, especially during the morning. However, a significant amount of NCA particles remained as the aerosol population evolved. Modelling studies showed that, while dilution is the main process acting on the total particle concentration, deposition also had a significant impact. Condensation and possibly enhanced deposition of NCA were the main plausible processes explaining why dispersion is faster for NCA than for total particle concentration, while the effect of coagulation on all size ranges was small. Based on our results, we conclude that NCA may play a significant role in urban environments, since, rather than being scavenged by larger particles, NCA particles remain in the particle population and grow by condensation.
Natural gas usage in the traffic and energy production sectors is a growing trend worldwide; thus, an assessment of its effects on air quality, human health and climate is required. Engine exhaust is a source of primary particulate emissions and secondary aerosol precursors, which both contribute to air quality and can cause adverse health effects. Technologies, such as cleaner engines or fuels, that produce less primary and secondary aerosols could potentially significantly decrease atmospheric particle concentrations and their adverse effects. In this study, we used a potential aerosol mass (PAM) chamber to investigate the secondary aerosol formation potential of natural gas engine exhaust. The PAM chamber was used with a constant UV-light voltage, which resulted in relatively long equivalent atmospheric ages of 11 days at most. The studied retro-fitted natural gas engine exhaust was observed to form secondary aerosol. The mass of the total aged particles, i.e., particle mass measured downstream of the PAM chamber, was 6-268 times as high as the mass of the emitted primary exhaust particles. The secondary organic aerosol (SOA) formation potential was measured to be 9-20ĝ€mgĝ€kgfuelĝ'1. The total aged particles mainly consisted of organic matter, nitrate, sulfate and ammonium, with the fractions depending on exhaust after-Treatment and the engine parameters used. Also, the volatility, composition and concentration of the total aged particles were found to depend on the engine operating mode, catalyst temperature and catalyst type. For example, a high catalyst temperature promoted the formation of sulfate particles, whereas a low catalyst temperature promoted nitrate formation. However, in particular, the concentration of nitrate needed a long time to stabilize-more than half an hour-which complicated the conclusions but also indicates the sensitivity of nitrate measurements on experimental parameters such as emission source and system temperatures. Sulfate was measured to have the highest evaporation temperature, and nitrate had the lowest. The evaporation temperature of ammonium depended on the fractions of nitrate and sulfate in the particles. The average volatility of the total aged particles was measured to be lower than that of primary particles, indicating better stability of the aged natural gas engine-emitted aerosol in the atmosphere. According to the results of this study, the exhaust of a natural gas engine equipped with a catalyst forms secondary aerosol when the atmospheric ages in a PAM chamber are several days long. The secondary aerosol matter has different physical characteristics from those of primary particulate emissions.
Shipping emissions are a major source of particulate matter in the atmosphere. The volatility of gaseous and particulate phase ship emissions are poorly known despite their potentially significant effect on the evolution of the emissions and their secondary organic aerosol (SOA) formation potential. An approach combining a genetic optimisation algorithm with volatility modelling was used on volatility measurement data to study the volatility distribution of a ship engine’s emissions in real-world conditions. The fuels used were marine gas oil (MGO) and methanol. The engine was operated with 50% and 70% loads with and without active NOx after-treatment with selective catalytic reduction (SCR). The volatility distributions were extended to higher volatilities by combining the speciation information of the gas phase volatile organic compounds with particle phase volatility distributions and organic carbon measurements. These measurements also provided the emission factors of the gas and particle phase emissions. The results for the particle phase volatility matched well with the existing results placing most of the volatile organic mass in the intermediate volatile organic compounds (IVOC). The IVOCs also dominated the speciated gas phase. Partitioning of the emissions in the gas and particle phases was affected significantly by the total organic mass concentration, underlining the importance of the effect of the dilution on the phase of the emissions.
Shipping emissions are a major source of particulate matter in the atmosphere. The volatility of gaseous and particulate phase ship emissions are poorly known despite their potentially significant effect on the evolution of the emissions and their secondary organic aerosol (SOA) formation potential. An approach combining a genetic optimisation algorithm with volatility modelling was used on volatility measurement data to study the volatility distribution of a ship engine’s emissions in real-world conditions. The fuels used were marine gas oil (MGO) and methanol. The engine was operated with 50% and 70% loads with and without active NOx after-treatment with selective catalytic reduction (SCR). The volatility distributions were extended to higher volatilities by combining the speciation information of the gas phase volatile organic compounds with particle phase volatility distributions and organic carbon measurements. These measurements also provided the emission factors of the gas and particle phase emissions. The results for the particle phase volatility matched well with the existing results placing most of the volatile organic mass in the intermediate volatile organic compounds (IVOC). The IVOCs also dominated the speciated gas phase. Partitioning of the emissions in the gas and particle phases was affected significantly by the total organic mass concentration, underlining the importance of the effect of the dilution on the phase of the emissions.
Abstract Understanding genetic architecture of plasma lipidome could provide better insights into lipid metabolism and its link to cardiovascular diseases (CVDs). Here, we perform genome-wide association analyses of 141 lipid species (n = 2,181 individuals), followed by phenome-wide scans with 25 CVD related phenotypes (n = 511,700 individuals). We identify 35 lipid-species-associated loci (P <5 ×10−8), 10 of which associate with CVD risk including five new loci-COL5A1, GLTPD2, SPTLC3, MBOAT7 and GALNT16 (false discovery rate<0.05). We identify loci for lipid species that are shown to predict CVD e.g., SPTLC3 for CER(d18:1/24:1). We show that lipoprotein lipase (LPL) may more efficiently hydrolyze medium length triacylglycerides (TAGs) than others. Polyunsaturated lipids have highest heritability and genetic correlations, suggesting considerable genetic regulation at fatty acids levels. We find low genetic correlations between traditional lipids and lipid species. Our results show that lipidomic profiles capture information beyond traditional lipids and identify genetic variants modifying lipid levels and risk of CVD.