Overestimation of self-reported driving exposure: Results from the SHRP2 Naturalistic Driving Study

Objectives: The accuracy of self-reported driving exposure has questioned the validity of using self-reported mileage to inform research questions. Studies examining the accuracy of self-reported driving exposure compared to objective measures find low validity, with drivers overestimating and underestimating driving distance. The aims of the current study were to (1) examine the discrepancy between self-reported annual mileage and driving exposure the following year and (2) investigate whether these differences depended on age and annual mileage.

Methods: Two estimates of drivers’ self-reported annual mileage collected during vehicle installation (obtained via prestudy questionnaires) and approximated annual mileage driven (based upon Global Positioning System data) were acquired from 3,323 participants who participated in the Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study.

Results: A Wilcoxon signed rank test showed that there was a significant difference between self-reported and annual driving exposure during participation in SHRP 2, with the majority of self-reported responses overestimating annual mileage the following year, irrespective of whether an ordinal or ratio variable was examined. Over 15% of participants provided self-reported responses with over 100% deviation, which were exclusive to participants underestimating annual mileage. Further, deviations in reporting differed between participants who had low, medium, and high exposure, as well as between participants in different age groups.

Conclusions: These findings indicate that although self-reported annual mileage is heavily relied on for research, such estimates of driving distance may be an overestimate of current or future mileage and can influence the validity of prior research that has utilized estimates of driving exposure.     

Ionic imbalance due to hydrogen carbonate from Asian dust

In an attempt to identify the ionic imbalance, hydrogen carbonate, HCO₃⁻ (bicarbonate), was determined together with the commonly determined nine major ions because the imbalance was frequently encountered in the chemical analysis of samples with high pHs. Titration method was applied for the determination of the samples with pH higher than 5.6. These samples amounted to 102 of the 1536 samples collected in Hokkaido, Northern Japan, from April 1998 to December 2002. Of the 102 samples, 74 (Group A) showed an acceptable ion balance without including HCO₃⁻. In the other 28 (Group B), however, inclusion of HCO₃⁻ successfully improved the ion balance. These results suggested that hydrogen carbonate was a potential candidate for explaining the imbalance. The hydrogen carbonate concentrations showed a strong correlation with the corresponding non-sea salt calcium (nss-Ca²⁺) concentrations, which implied that hydrogen carbonate was derived from calcium carbonate particles incorporated into falling raindrops or cloud droplets. For Group A, the relationship between hydrogen carbonate and the nss-calcium ion concentration was very similar to that for commonly suspended particles in Hokkaido. On the other hand, Group B exhibited a stronger but significantly different correlation. To the samples of Group B, a back-trajectory analysis was applied to demonstrate that the samples were associated with aerosol travelling from Northern China or Mongolia, which indicated that alkaline aerosol affected the chemistry. In consideration of these findings, the current standard of the ion balance should be critically reviewed for modification in regard to the contribution of hydrogen carbonate not only in source areas but also in receptor areas of alkaline aerosol.     

Analysis of the Trend and Seasonal Cycle of Carbon Monoxide Concentrations in an Urban Area (4 pp)

Background, Aim and Scope Air quality is an field of major concern in large cities. This problem has led administrations to introduce plans and regulations to reduce pollutant emissions. The analysis of variations in the concentration of pollutants is useful when evaluating the effectiveness of these plans. However, such an analysis cannot be undertaken using standard statistical techniques, due to the fact that concentrations of atmospheric pollutants often exhibit a lack of normality and are autocorrelated. On the other hand, if long-term trends of any pollutant’s emissions are to be detected, meteorological effects must be removed from the time series analysed, due to their strong masking effects. Materials and Methods The application of statistical methods to analyse temporal variations is illustrated using monthly carbon monoxide (CO) concentrations observed at an urban site. The sampling site is located at a street intersection in central Valencia (Spain) with a high traffic density. Valencia is the third largest city in Spain. It is a typical Mediterranean city in terms of its urban structure and climatology. The sampling site started operation in January 1994 and monitored CO ground level concentrations until February 2002. Its geographic coordinates are W0°22′52″ N39°28′05″ and its altitude is 11 m. Two nonparametric trend tests are applied. One of these is robust against serial correlation with regards to the false rejection rate, when observations have a strong persistence or when the sample size per month is small. A nonparametric analysis of the homogeneity of trends between seasons is also discussed. A multiple linear regression model is used with the transformed data, including the effect of meteorological variables. The method of generalized least squares is applied to estimate the model parameters to take into account the serial dependence of the residuals of this model. This study also assesses temporal changes using the Kolmogorov-Zurbenko (KZ) filter. The KZ filter has been shown to be an effective way to remove the influence of meteorological conditions on O₃ and PM to examine underlying trends. Results The nonparametric tests indicate a decreasing, significant trend in the sampled site. The application of the linear model yields a significant decrease every twelve months of 15.8% for the average monthly CO concentration. The 95% confidence interval for the trend ranges from 13.9% to 17.7%. The seasonal cycle also provides significant results. There are no differences in trends throughout the months. The percentage of CO variance explained by the linear model is 90.3%. The KZ filter separates out long, short-term and seasonal variations in the CO series. The estimated, significant, long-term trend every year results in 10.3% with this method. The 95% confidence interval ranges from 8.8% to 11.9%. This approach explains 89.9% of the CO temporal variations. Discussion The differences between the linear model and KZ filter trend estimations are due to the fact that the KZ filter performs the analysis on the smoothed data rather than the original data. In the KZ filter trend estimation, the effect of meteorological conditions has been removed. The CO short-term componentis attributable to weather and short-term fluctuations in emissions. There is a significant seasonal cycle. This component is a result of changes in the traffic, the yearly meteorological cycle and the interactions between these two factors. There are peaks during the autumn and winter months, which have more traffic density in the sampled site. There is a minimum during the month of August, reflecting the very low level of vehicle emissions which is a direct consequence of the holiday period. Conclusions The significant, decreasing trend implies to a certain extent that the urban environment in the area is improving. This trend results from changes in overall emissions, pollutant transport, climate, policy and economics. It is also due to the effect of introducing reformulated gasoline. The additives enable vehicles to burn fuel with a higher air/fuel ratio, thereby lowering the emission of CO. The KZ filter has been the most effective method to separate the CO series components and to obtain an estimate of the long-term trend due to changes in emissions, removing the effect of meteorological conditions. Recommendations and Perspectives Air quality managers and policy-makers must understand the link between climate and pollutants to select optimal pollutant reduction strategies and avoid exceeding emission directives. This paper analyses eight years of ambient CO data at a site with a high traffic density, and provides results that are useful for decision-making. The assessment of long-term changes in air pollutants to evaluate reduction strategies has to be done while taking into account meteorological variability     

北京市农业机械排放因子与排放清单

利用车载排放测试技术对典型的联合收割机、拖拉机、农用运输车和农田建设机械实际工况下的尾气进行测试,建立了实际工况下农业机械的排放因子和2017年北京市农用机械排放清单.结果表明,不同的工作状态对农业机械尾气排放有较大的影响,怠速和行走时CO、NO_x、HC和PM排放趋于平稳;而切地和翻地模式下的波动较为明显.根据各类机械的分类和排放标准对排放因子进行细化,建立了较为完整的实际工况下的排放因子.根据农业机械排放因子和燃油消耗量计算出2017年北京市CO、NO_x、HC和PM的排放量分别是2 566.60、 1 239.29、 563.08和538.32 t.拖拉机、运输机械和联合收割机的污染物总量占CO、NO_x、HC和PM这4种污染物总量的98%、 95%、 95%和98%.因此,农用拖拉机、运输机械和联合收割机在农业机械污染减排中应作为重点控制对象.     

深圳大气PM2.5中水溶性有机物的来源特征

对2017年9月~2018年8月深圳市北部大气PM_2.5中水溶性有机物（WSOM）的质量浓度、质谱及来源结构进行测量和分析.结果表明：PM_2.5的质量浓度为（32.3±18.4）μg/m³,WSOM的质量浓度为（9.4±5.7）μg/m³,占颗粒物总有机物的（77.6%±14.0%）.质谱分析显示,WSOM的氧碳比（O/C）平均值达到（0.57±0.09）,属于二次有机物的O/C值范围,且生物质燃烧排放的离子碎片C₂H₄O₂⁺的丰度显著,说明WSOM的来源中有显著的生物质燃烧排放的有机气溶胶.为了明确WSOM的来源结构,利用正矩阵因子分解法（PMF）模型进行来源解析,发现3个合理因子：高氧化态有机气溶胶（MO-OOA）,低氧化态有机气溶胶（LO-OOA）和生物质燃烧（BBOA）,贡献比例分别为51.7%,31.8%和16.5%.MO-OOA和BBOA贡献浓度均呈现秋冬高、春夏低的季节变化特征,反向轨迹分析显示其与内陆污染传输关系密切.LO-OOA的变化相对稳定,本地源的贡献较大.结合¹⁴C同位素示踪法对秋冬季WSOM样品分析,发现机动车等化石源二次有机物是WSOM的主要来源,贡献比例达到53.9%,需继续加强对化石燃料控制来降低WSOM污染.     

Tuning the fill percentage in the hydrothermal synthesis process to increase catalyst performance for ozone decomposition

The performance of Ce-OMS-2 catalysts was improved by tuning the fill percentage in the hydrothermal synthesis process to increase the oxygen vacancy density. The Ce-OMS-2 samples were prepared with different fill percentages by means of a hydrothermal approach (i.e. 80%, 70%, 50% and 30%). Ce-OMS-2 with 80% fill percentage (Ce-OMS-2-80%) showed ozone conversion of 97%, and a lifetime experiment carried out for more than 20?days showed that the activity of the catalyst still remained satisfactorily high (91%). For Ce-OMS-2-80%, Mn ions in the framework as well as K ions in the tunnel sites were replaced by Ce⁴⁺, while for the others only Mn ions were replaced. O₂-TPD and H₂-TPR measurements proved that the Ce-OMS-2-80% catalyst possessed the greatest number of mobile surface oxygen species. XPS and XAFS showed that increasing the fill percentage can reduce the AOS of Mn and augment the amount of oxygen vacancies. The active sites, which accelerate the elimination of O₃, can be enriched by increasing the oxygen vacancies. These findings indicate that increasing ozone removal can be achieved by tuning the fill percentage in the hydrothermal synthesis process.     

Role of glycine on sulfuric acid-ammonia clusters formation: Transporter or participator

Glycine(Gly) is ubiquitous in the atmosphere and plays a vital role in new particle formation(NPF).However,the potential mechanism of its on sulfuric acid(SA)-ammonia(A)clusters formation under various atmospheric conditions is still ambiguous.Herein,a(Gly)_x·(SA)_y·(A)_z(z≤x+y≤3) multicomponent system was investigated by using density functional theory(DFT) combined with Atmospheric Cluster Dynamics Code(ACDC) at different temperatures and precursor concentrations.The results show that Gly,with one carboxyl(-COOH) and one amine(-NH_2) group,can interact strongly with SA and A in two directions through hydrogen bonds or proton transfer.Within the relevant range of atmospheric concentrations,Gly can enhance the formation rate of SA-A-based clusters,especially at low temperature,low [SA],and median [A].The enhancement(R) of Gly on NPF can be up to 340 at T=218.15 K,[SA]=10~4,[A]=10~9,and [Gly]=10~7 molecules/cm~3.In addition,the main growth paths of clusters show that Gly molecules participate into cluster formation in the initial stage and eventually leave the cluster by evaporation in subsequent cluster growth at low [Gly],it acts as an important "transporter" to connect the smaller and larger cluster.With the increase of [Gly],it acts as a "participator" directly participating in NPF.     

Influence of environmental factors on arsenic accumulation and biotransformation using the aquatic plant species Hydrilla verticillata

Hydrilla verticillata(waterthyme) has been successfully used for phytoremediation in arsenic(As) contaminated water.To evaluate the effects of environmental factors on phytoremediation,this study conducted a series of orthogonal design experiments to determine optimal conditions,including phosphorus(P),nitrogen(N),and arsenate(As(Ⅴ))concentrations and initial pH levels,for As accumulation and biotransformation using this aquatic plant species,while also analyzing As species transformation in culture media after 96-hr exposure.Analysis of variance and the signal-to-noise ratio were used to identify both the effects of these environmental factors and their optimal conditions for this purpose.Results indicated that both N and P significantly impacted accumulation,and N was essential in As species transformation.High N and intermediate P levels were critical to As accumulation and biotransformation by H.verticillata,while high N and low P levels were beneficial to As species transformation in culture media.The highest total arsenic accumulation was(197.2±17.4) μg/g dry weight when As(V) was at level 3(375μg/L),N at level 2(4 mg/L),P at level 1(0.02 mg/L),and pH at level 2(7).Although H.verticillata is highly efficient in removing As(Ⅴ) from aquatic environments,its use could be potentially harmful to both humans and the natural environment due to its release of highly toxic arsenite.For cost-effective and ecofriendly phytoremediation of As-contaminated water,both N and P are helpful in regulating As accumulation and transformation in plants.     

Recent advances in catalytic decomposition of ozone

Ozone (O₃), as a harmful air pollutant, has been of wide concern. Safe, efficient, and economical O₃ removal methods urgently need to be developed. Catalytic decomposition is the most promising method for O₃ removal, especially at room temperature or even subzero temperatures. Great efforts have been made to develop high-efficiency catalysts for O₃ decomposition that can operate at low temperatures, high space velocity and high humidity. First, this review describes the general reaction mechanism of O₃ decomposition on noble metal and transition metal oxide catalysts. Then, progress on the O₃ decomposition performance of various catalysts in the past 30 years is summarized in detail. The main focus is the O₃ decomposition performance of manganese oxides, which are divided into supported manganese oxides and non-supported manganese oxides. Methods to improve the activity, stability, and humidity resistance of manganese oxide catalysts for O₃ decomposition are also summarized. The deactivation mechanisms of manganese oxides under dry and humid conditions are discussed. The O₃ decomposition performance of monolithic catalysts is also summarized from the perspective of industrial applications. Finally, the future development directions and prospects of O₃ catalytic decomposition technology are put forward.     

Ozone pollution characteristics and sensitivity analysis using an observation-based model in Nanjing, Yangtze River Delta Region of China

Ground-level ozone (O₃) has become a critical pollutant impeding air quality improvement in Yangtze River Delta region of China. In this study, we present O₃ pollution characteristics based on one-year online measurements during 2016 at an urban site in Nanjing, Jiangsu Province. Then, the sensitivity of O₃ to its precursors during 2 O₃ pollution episodes in August was analyzed using a box model based on observation (OBM). The relative incremental reactivity (RIR) of hydrocarbons was larger than other precursors, suggesting that hydrocarbons played the dominant role in O₃ formation. The RIR values for NO_X ranged from –0.41%/% to 0.19%/%. The O₃ sensitivity was also analyzed based on relationship of simulated O₃ production rates with reductions of VOC and NO_X derived from scenario analyses. Simulation results illustrate that O₃ formation was between VOCs-limited and transition regime. Xylenes and light alkenes were found to be key species in O₃ formation according to RIR values, and their sources were determined using the Positive Matrix Factorization (PMF) model. Paints and solvent use was the largest contributor to xylenes (54%), while petrochemical industry was the most important source to propene (82%). Discussions on VOCs and NO_X reduction schemes suggest that the 5% O₃ control goal can be achieved by reducing VOCs by 20%. To obtain 10% O₃ control goal, VOCs need to be reduced by 30% with VOCs/NO_X larger than 3:1.