The secret life of pets: The intersection of animals and organizational life

Although often overlooked, pets and other animals intersect with organizations in interesting, important ways. We seek to define how various animals intersect with organizations, highlight opportunities for theory development, and illustrate important areas for future research. We also explore how pandemics such as COVID-19 might affect the animals we highlight.     

Methodology for risk assessment of COVID-19 pandemic propagation

This paper proposes a methodology to perform risk analysis of the virus spread. It is based on the coupling between CFD modelling of bioaerosol dispersion to the calculation of probability of contact events. CFD model of near-field sneeze droplets dispersion is developed to build the SARS-CoV-2 effect zones and to adequately capture the safe distance. The most shared classification of droplets size distribution of sneezes was used.Droplets were modeled through additive heating/evaporation/boiling laws and their impact on the continuous phase was examined. Larger droplets move behind the droplet nuclei front and exhibit greater vertical drop due to the effect of gravity. CFD simulations provided the iso-risk curves extension (i.e., the maximum distance as well as the angle) enclosed by the incident outcome effect zone. To calculate the risk indexes, a fault tree was developed and the probability of transmission assuming as of the top event “COVID-19 infection” was calculated starting from the virus spread curve, as main base case. Four phases of virus spread evolution were identified: initiation, propagation, generalised propagation and termination. For each phase, the maximum allowable close contact was computed, being fixed the values of the acceptable risk index. In particular, it was found that during the propagation case, the maximum allowable close contacts is two, suggesting that at this point lockdown should be activated. The here developed methodology could drive policy containment design to curb spread COVID-19 infection.     

面向重大疫情防控的应急管理规划

为进一步推进疫情防控应急管理规划理论和相关制度的改进完善，采用国外先进作战任务规划方法探讨面向重大疫情的应急管理规划问题，从理论和实践相结合的角度论述面向疫情的应急防控管理规划基本任务、主要类型、规划业务要求、任务规划成果；提出疫情防控应急管理规划流程，并设计预先规划、应急规划和临机调控规划3种典型规划，构建覆盖国家、省、市县和乡镇/街道4个层级的疫情防控应急管理规划体系。结果表明:基于作战任务规划的应急管理规划流程和体系科学性更强、适用性更高，对应急管理规划、应急预案与防疫预案的制定有参考价值。     

Predicting support for non‐pharmaceutical interventions during infectious outbreaks: a four region analysis

Non‐pharmaceutical interventions (NPIs) are an important public health tool for responding to infectious disease outbreaks, including pandemics. However, little is known about the individual characteristics associated with support for NPIs, or whether they are consistent across regions. This study draws on survey data from four regions—Hong Kong, Singapore, Taiwan, and the United States—collected following the Severe Acute Respiratory Syndrome (SARS) outbreak of 2002–03, and employs regression techniques to estimate predictors of NPI support. It finds that characteristics associated with NPI support vary widely by region, possibly because of cultural variation and prior experience, and that minority groups tend to be less supportive of NPIs when arrest is the consequence of noncompliance. Prior experience of face‐mask usage also results in increased support for future usage, as well as other NPIs. Policymakers should be attentive to local preferences and to the application of compulsory interventions. It is speculated here that some public health interventions may serve as ‘gateway’ exposures to future public health interventions.     

上海市PM2.5中重金属元素对COVID-19控制的高频响应

为研究城市大气重金属元素在新冠控制前、中（与春节重叠）、后的演化和来源,利用多金属在线分析仪于2020年1月1日至2月26日测定了上海市PM_2.5中重金属元素的小时浓度.利用PMF模型确定了8个来源.结果表明,大部分元素的浓度呈现"V"字型的变化趋势,主要受烟花爆竹（特征性元素有K、Cu、Ba）、Se工业、道路扬尘（Ca、Fe、Ba）和机动车（Mn、Zn、Fe、Cu）等排放源影响.但在新冠控制期间,K、Ba和Cu浓度仍较高.以Cu元素为例的特殊事件分析表明,其浓度高值在控制期前显著受到外来传输的影响,在控制期内主要来自于本地烟花爆竹排放的影响.     

2018~2020年北京市交通监测站点大气污染特征分析

基于北京市34个空气质量监测站点收集的5种主要污染物浓度（NO₂、CO、O₃、PM_2.5、PM₁₀）数据,对2018~2020年北京市5个交通站点污染物浓度进行分析,并与11个城市评价站点及2个背景点（密云水库、定陵）进行对比.结果表明：（1）3a间各污染物浓度年际变化总体呈下降趋势,除PM₁₀外,交通站点各污染物浓度降幅均大于城市评价站点.2020年交通站点NO₂降幅最大,比2018年下降了31.37%.除个别时期外,5种污染物浓度在交通站点比城市评价站点普遍高出3%~50%.且以NO₂最为突出.（2）2018~2020年各监测站点不同污染物浓度的季节变化特征表现不同.O₃夏季高、冬季低,最高值出现在2018年6月;其余4种污染物浓度基本表现为冬季高、夏季低;2018年3月受沙尘及不利气象条件影响,污染物浓度出现了极高值.（3）为研究新冠肺炎疫情对交通污染排放的影响,比较了5种污染物的浓度变化.与2019年同期相比,疫情后三个阶段的NO₂下降最为显著.交通站点NO₂、CO、PM_2.5平均降幅比城市评价站点高出了4.81%、10.21%、4.38%.     

Significant concurrent decrease in PM2.5 and NO2 concentrations in China during COVID-19 epidemic

The strict control measures and social lockdowns initiated to combat COVID-19 epidemic have had a notable impact on air pollutant concentrations. According to observation data obtained from the China National Environmental Monitoring Center, compared to levels in 2019, the average concentration of NO₂ in early 2020 during COVID-19 epidemic has decreased by 53%, 50%, and 30% in Wuhan city, Hubei Province (Wuhan excluded), and China (Hubei excluded), respectively. Simultaneously, PM_2.5 concentration has decreased by 35%, 29%, and 19% in Wuhan, Hubei (Wuhan excluded), and China (Hubei excluded), respectively. Less significant declines have also been found for SO₂ and CO concentrations. We also analyzed the temporal variation and spatial distribution of air pollutant concentrations in China during COVID-19 epidemic. The decreases in PM_2.5 and NO₂ concentrations showed relatively consistent temporal variation and spatial distribution. These results support control of NO_x to further reduce PM_2.5 pollution in China. The concurrent decrease in NO_x and PM_2.5 concentrations resulted in an increase of O₃ concentrations across China during COVID-19 epidemic, indicating that coordinated control of other pollutants is needed.     

疫情期间“2+26”城市污染减排成效评估

为评估“2+26”城市在疫情期间的减排效果,基于NAQPMS模式和情景模拟的方法,分析了2020年1~3月及疫情前后空气质量特征,对气象、重污染应急减排措施及社会经济活动对空气质量的影响和研究的不确定性进行了分析讨论.结果表明,2020年1~3月,“2+26”城市空气质量级别优良率为59.6%,同比上升10.9%;PM₁₀、PM_2.5、SO₂、NO₂、O₃-8h-90per和CO-95per平均浓度分别为108,76,14,36,109μg/m³和2.3mg/m³.疫情期间（1月24日~3月31日） PM₁₀、NO₂、PM_2.5和CO浓度比疫情前期（1月1~23日）同比降幅明显.气象条件造成沿燕山和太行山城市PM_2.5浓度约上升1%~8%.重污染减排促使区域性污染过程减少了2次,“2+26”城市PM_2.5季度均值降低约6~26 μg/m³.受春节和疫情综合影响,机动车排放量大幅下降,但焦化、火电等重点行业实际污染排放量变化不大,散煤燃烧对空气质量的负面影响增加.     

北京冬季疫情期间空气质量及气象影响分析

针对北京地区2020年冬季疫情防控期（1月24至2月29）的空气质量及两次持续性重污染过程进行分析,探究了该时段的大气污染特征及其气象影响.与过去5a同期相比,2020年疫情防控期间北京冷空气强度偏弱,活动频次偏少50%,气温偏高0.73℃,风速和混合层高度偏低17.8%和32.5%,相对湿度和露点温度增加60.9%和48.1%,偏北风频率减少7.5%,而偏南风和偏东风频率均增大6.0%;气象条件较历史同期明显转差;虽然降水量偏多,但整体降水强度弱、时次集中,因而颗粒物的整体清除作用有限.两次重污染过程（1月24~29日和2月8~13日）分别维持59和75h,两个过程累积阶段（1月24~25日和2月9~11日）均受区域输送影响较大,输送占比为70%和58%,分偏东和偏南两个通道.针对污染过程的源解析显示,本地污染贡献占比为67%和48%,可见在维持和加重阶段颗粒物的吸湿增长和二次生成占比增加.经分析,“高湿静稳”的不利气象背景下,大气垂直动力和水平辐合的叠加使PM_2.5和水汽在北京平原累积,将其压制在边界层内快速增长;升高的污染物也与静稳的边界层气象因子双向反馈,导致污染进一步加重.根据EMI指数计算,2020年冬季疫情防控期的气象条件约引起70.1%的PM_2.5浓度增加;而与过去5a同期相比,疫情防控期间排放的减少抵消了约53%的不利气象条件影响;两次污染过程与过去5a同期的9次过程相比,EMI分别偏大26.9%和19.7%,但PM_2.5浓度基本持平或略有降低.可见,在目前的排放基数上,即使出现特殊情况下的城市封锁,排放量的减少将削减污染浓度峰值,但仍不足以完全抵消不利气象条件的影响.     

混合菌群FF降解染料效果及生物毒性变化

利用混合菌群FF降解偶氮染料活性黑5和蒽醌染料活性蓝19,通过检测一些常规指标,如脱色率、DOC(溶解性有机碳)去除率、UV254、比紫外吸收值SUVA(UV254/DOC)等来表征降解效果,进一步通过固相萃取方法进行前处理,采用SOS/umu(又称umu试验)和双杂交酵母法分别检测染料降解过程中遗传毒性和抗雌激素活性。结果表明,采用混合菌群FF,活性黑5和活性蓝19(150 mg/L)在35℃和p H=8.0条件下静置培养48 h后脱色率分别为82.5%和89.2%;DOC去除率低,分别为19.5%和13.0%;降解后UV254和SUVA均增加。遗传毒性检测表明,活性黑5本身无遗传毒性,降解过程中也无遗传毒性;活性蓝19本身无遗传毒性,降解24 h、48 h后在高浓缩倍数下出现遗传毒性。随着降解的进行,活性黑5和活性蓝19的抗雌激素活性均显著增加。