基于多时相遥感数据的典型区生态格局变化分析

利用1985、2000、2013年遥感影像提取的土地覆盖数据,通过景观格局指数、动态度计算、转移矩阵等,分析1985—2013年我国典型地区各类型生态系统景观格局及其动态变化特征、生态系统相互转化时空变化特征等,揭示1985—2013年生态环境格局变化的特点和规律:一级分类生态系统综合变化率,赣江、闽江、白龙江和岷江上游流域分别为4.7%、3.9%、3.3%和1.7%,生态系统变化强度1985—2000年较缓,2000—2013年更剧烈。1985—2013年典型区生态系统的主要转化方向具有持续性和双向性特征,岷江、白龙江和赣江上游流域退耕还林还草政策效果明显,出现较高比例的耕地转为森林和草地;面积占67.4%生态系统类型变化与耕地生态系统和人工表面生态系统变化有关;生态系统变化具有明显的区域差异,生态变化主要表现为沿主要河流谷地的线状延伸,主要城镇居民点附近生态系统类型变化较为突出,人类活动是典型地区生态系统类型格局变化的主要驱动力;典型区尤其是敏感区应加大退耕还林还草政策,减少人类经济活动,降低洪水泥石流灾害发生的概率和程度。     

基于地理探测器的土壤重金属影响因子分析及其污染风险评价

地理探测器能快速定量化揭示驱动重金属含量影响因素的强度,这对于重金属空间预测模型构建变量的确定和土壤污染修复措施的精准实施具有重要意义。利用地理探测器模型,对5种土壤重金属元素Cu、Zn、Pb、Cr、Ni的空间分布和11种环境因子的交互作用进行定量评估,通过单因子指数法进行重庆市土壤重金属污染风险评价。结果表明:研究区内土壤Cu、Zn、Cr和Pb的平均含量是重庆市土壤背景值的1.3—1.4倍,Ni含量低于背景值;其中Cu、Pb达到重度污染水平,其余3种重金属为中度或轻度污染水平。5种重金属元素中Cu和Pb为高度变异(变异系数为0.57、0.4),Zn、Cr和Ni为中等变异(变异系数为0.22—0.29),且各重金属元素之间呈显著正相关性,表明研究区重金属富集受人为干扰影响较大,且污染具有复合性或同源性。地理探测器的因子探测发现高程、坡度和土壤类型对5种土壤重金属含量的解释力最显著,说明地势和土壤类型是土壤重金属含量分布差异的最主要影响因素。交互作用探测发现,高程与其他因子交互作用是重金属空间分异的主导因素,气候条件和土壤类型也是重要影响因子。土壤重金属空间分布是多种因素共同作用的结果,而高程、坡度和土壤类型具有较强的解释力,这些因子可作为土壤重金属含量空间预测模型的辅助变量,也可促进重金属污染治理措施的靶向实施。     

北京市典型废弃物焚烧源2010—2017年二NFDA1英排放特征和减排效果分析

分析2010—2017年北京市三类典型废弃物焚烧源的废气二NFDA1英排放监测数据,计算排放因子和排放量,评估减排政策成效,并分析不同排放源达标排放时同类物分布特征异同和变化规律,探讨影响排放的重要因素。结果表明: 5家焚烧源平均排放浓度为 0.008～0.069 ng/m³(以TEQ计,下同),废气二NFDA1英排放因子为 0.027～1.7 μg/t,2016年向空气中排放的二NFDA1英量为 0.002 5～0.058 g；生活垃圾、危险废物和医疗废物焚烧源的低、高氯代同类物质量分数比的平均值分别为接近于 0.5、大于0.5和小于0.5,危险废物焚烧源的 ∑PCDFs、∑PCDDs质量分数比的平均值大于2； 123478-HxCDF和123678-HxCDF质量浓度接近且线性相关,具有相近的生成机理和去除效率； I-TEQ变化趋势与∑PCDFs质量分数的变化趋势基本一致,活性炭喷射和布袋除尘的去除效率是影响二NFDA1英排放的重要因素之一；危险废物焚烧源HWI1随运行时间增加排放浓度增加,而及时更换烟道管壁有助于消除“记忆效应”的不良影响。     

夏季渭河西安段溶解性有机质(DOM)的特征、分布及来源分析

通过紫外吸收光谱,三维荧光光谱结合平行因子分析(EEMs-PARAFAC)方法及主成分分析(PCA),研究了夏季渭河西安段水体中的溶解性有机质(DOM)的组成、来源,及其与水质指标的相关性.在研究区域共检出2种类别5个不同的DOM组分,分别为类腐殖质荧光组分C1、C2、C3、C5和1个类蛋白类荧光组分C4,5个组分具有同源性.对比分析光谱斜率S、SUVA₂₅₄、α355和DOC浓度,上游(S1—S5)和下游(S13—S17)各组分分子量和腐殖化程度接近但来源有所差异,中游(S6—S12、S18—S19)分子量和腐殖化程度最低;研究区域DOM和CDOM浓度值变化基本保持一致.通过三维光谱参数和主成分分析进行DOM源解析,内源贡献率为72.36%,外源贡献率为12.45%,累计方差贡献率为84.81%;污废水排放是组分C1、C4的主要来源,C2、C3、C5则来源于城市景观水体和湿地公园中微生物和浮游动植物的活动产生,TN与外源具有较好的相关性而TP与内源相关性较高.水质指标DO、DOC、COD、TN、TP与DOM组分有较强的相关性.在此基础上建立了多元线性回归方程,一定程度上能够利用荧光组分组成和特征反映渭河夏季的水质状况.     

磺胺氯哒嗪在海水中的间接光降解

以有色溶解有机物(CDOM)作为主要光敏剂研究磺胺氯哒嗪(SCP)间接光降解行为和机理,分析CDOM组成、盐度和pH值对SCP间接光降解的影响.SCP间接光降解速率随CDOM浓度升高而逐渐加快.CDOM产生的光化学反应活性中间体对SCP间接光降解的贡献率不同,其中³CDOM^*起主要作用,对SCP间接光降解的贡献率高达77.94%.所用CDOM由4种荧光组分组成,包含3种外源腐殖质(C1,C2,C3)和1种内源腐殖质(C4), SCP间接光降解去除率和³CDOM^*浓度分别与荧光组分的相关性大小顺序均为C3>C2>C4>C1.其中C3和C2与[³CDOM^*]具有较高线性相关性(R²>0.97),是³CDOM^*的主要贡献者.盐度和pH值对SCP间接光降解的影响作用显著.在盐度为15‰时,SCP的间接光降解速率最大.在低盐度范围(0~15‰)内,离子强度效应对间接光降解的促进作用大于无机阴离子带来的抑制作用,使得间接光降解速率随着盐度的升高而加快.溶液pH=(5.00±0.10)时,SCP的间接光降解速率最大.SCP的间接光降解速率随着溶液pH值的升高而减慢,中性和碱性环境不利于SCP的间接光降解.     

Aerosol transmission,an indispensable route of COVID-19 spread: case study of a department-store cluster

• Aerosol transmission is an indispensable route of COVID-19 spread. • Different outbreak sites have different epidemiologic feature. • SRAS-CoV-2 can exist for a long time in aerosol. • SRAS-CoV-2 RNA can be detected in aerosol in diverse places. • Some environmental factors can impact SARS-CoV-2 transportation in aerosol. Patients with COVID-19 have revealed a massive outbreak around the world, leading to widespread concerns in global scope. Figuring out the transmission route of COVID-19 is necessary to control further spread. We analyzed the data of 43 patients in Baodi Department Store (China) to supplement the transmission route and epidemiological characteristics of COVID-19 in a cluster outbreak. Incubation median was estimated to endure 5.95 days (2–13 days). Almost 76.3% of patients sought medical attention immediately upon illness onset. The median period of illness onset to hospitalization and confirmation were 3.96 days (0–14) and 5.58 days (1–21), respectively. Patients with different cluster case could demonstrate unique epidemiological characteristics due to the particularity of outbreak sites. SRAS-CoV-2 can be released into the surrounding air through patient’s respiratory tract activities, and can exist for a long time for long-distance transportation. SRAS-CoV-2 RNA can be detected in aerosol in different sites, including isolation ward, general ward, outdoor, toilet, hallway, and crowded public area. Environmental factors influencing were analyzed and indicated that the SARS-CoV-2 transportation in aerosol was dependent on temperature, air humidity, ventilation rate and inactivating chemicals (ozone) content. As for the infection route of case numbers 2 to 6, 10, 13, 16, 17, 18, 20 and 23, we believe that aerosol transmission played a significant role in analyzing their exposure history and environmental conditions in Baodi Department Store. Aerosol transmission could occur in some cluster cases when the environmental factors are suitable, and it is an indispensable route of COVID-19 spread.     

Are older drivers’ driving patterns during an on-road driving task representative of their real-world driving patterns?

Abstract

Objective: The current study investigated whether older drivers’ driving patterns during a customized on-road driving task were representative of their real-world driving patterns.

Methods: Two hundred and eight participants (male: 68.80%; mean age?=?81.52 years, SD?=?3.37 years, range?=?76.00–96.00 years) completed a customized on-road driving task that commenced from their home and was conducted in their own vehicle. Participants’ real-world driving patterns for the preceding 4-month period were also collected via an in-car recording device (ICRD) that was installed in each participant’s vehicle.

Results: During the 4-month period prior to completing the on-road driving task, participants’ median real-world driving trip distance was 2.66?km (interquartile range [IQR]?=?1.14–5.79?km) and their median on-road driving task trip distance was 4.41?km (IQR?=?2.83–6.35?km). Most participants’ on-road driving task trip distances were classified as representative of their real-world driving trip distances (95.2%, n?=?198).

Conclusions: These findings suggest that most older drivers were able to devise a driving route that was representative of their real-world driving trip distance. Future research will examine whether additional aspects of the on-road driving task (e.g., average speed, proportion of trips in different speed zones) are representative of participants’ real-world driving patterns.     

Structural equation model analysis for the evaluation of overall driving performance: A driving simulator study focusing on driver distraction

Objective: The present research relies on 2 main objectives. The first is to investigate whether latent model analysis through a structural equation model can be implemented on driving simulator data in order to define an unobserved driving performance variable. Subsequently, the second objective is to investigate and quantify the effect of several risk factors including distraction sources, driver characteristics, and road and traffic environment on the overall driving performance and not in independent driving performance measures.

Methods: For the scope of the present research, 95 participants from all age groups were asked to drive under different types of distraction (conversation with passenger, cell phone use) in urban and rural road environments with low and high traffic volume in a driving simulator experiment. Then, in the framework of the statistical analysis, a correlation table is presented investigating any of a broad class of statistical relationships between driving simulator measures and a structural equation model is developed in which overall driving performance is estimated as a latent variable based on several individual driving simulator measures.

Results: Results confirm the suitability of the structural equation model and indicate that the selection of the specific performance measures that define overall performance should be guided by a rule of representativeness between the selected variables. Moreover, results indicate that conversation with the passenger was not found to have a statistically significant effect, indicating that drivers do not change their performance while conversing with a passenger compared to undistracted driving. On the other hand, results support the hypothesis that cell phone use has a negative effect on driving performance. Furthermore, regarding driver characteristics, age, gender, and experience all have a significant effect on driving performance, indicating that driver-related characteristics play the most crucial role in overall driving performance.

Conclusions: The findings of this study allow a new approach to the investigation of driving behavior in driving simulator experiments and in general. By the successful implementation of the structural equation model, driving behavior can be assessed in terms of overall performance and not through individual performance measures, which allows an important scientific step forward from piecemeal analyses to a sound combined analysis of the interrelationship between several risk factors and overall driving performance.     

矿工心理因素、工作压力反应和不安全行为关系研究

为研究在巨大工作压力下，矿工的心理因素与工作压力反应和不安全行为的关系，以问卷的形式调查陕西省2家具代表性煤矿的工人，分别以矿工的心理因素、工作压力反应和作业过程中的不安全行为作为外生变量、中介变量和内生变量，构建心理因素、压力反应和不安全行为的结构方程模型。通过对调研数据处理与分析，得出如下结论:本研究中的4项心理因素，性格因素、心理素质、注意力和工作态度显著影响不安全行为的发生；性格因素、心理素质和注意力对压力反应有显著影响；工作态度与煤矿工人的压力反应的关系不显著；性格因素、心理素质、注意力和工作态度通过影响矿工的压力反应，间接影响矿工的不安全行为。     

The accounting method and application of CO2 emissions responsibility by the electricity sector at the provincial level in China

When accounting the CO₂ emissions responsibility of the electricity sector at the provincial level in China,it is of great significance to consider the scope of both producers’ and the consumers’ responsibility,since this will promote fairness in defining emission responsibility and enhance cooperation in emission reduction among provinces.This paper proposes a new method for calculating carbon emissions from the power sector at the provincial level based on the shared responsibility principle and taking into account interregional power exchange.This method can not only be used to account the emission responsibility shared by both the electricity production side and the consumption side,but it is also applicable for calculating the corresponding emission responsibility undertaken by those provinces with net electricity outflow and inflow.This method has been used to account for the carbon emissions responsibilities of the power sector at the provincial level in China since 2011.The empirical results indicate that compared with the production-based accounting method,the carbon emissions of major power-generation provinces in China calculated by the shared responsibility accounting method are reduced by at least 10%,but those of other power-consumption provinces are increased by 20% or more.Secondly,based on the principle of shared responsibility accounting,Inner Mongolia has the highest carbon emissions from the power sector while Hainan has the lowest.Thirdly,four provinces,including Inner Mongolia,Shanxi,Hubei and Anhui,have the highest carbon emissions from net electricity outflow- 14 million t in 2011,accounting for 74.42% of total carbon emissions from net electricity outflow in China.Six provinces,including Hebei,Beijing,Guangdong,Liaoning,Shandong,and Jiangsu,have the highest carbon emissions from net electricity inflow- 11 million t in 2011,accounting for 71.44% of total carbon emissions from net electricity inflow in China.Lastly,this paper has estimated the emission factors of electricity consumption at the provincial level,which can avoid repeated calculations when accounting the emission responsibility of power consumption terminals（e.g.construction,automobile manufacturing and other industries）.In addition,these emission factors can also be used to account the emission responsibilities of provincial power grids.