Assessing washing methods for reduction of pesticide residues in Capia pepper with LC-MS/MS

Abstract

The effects of washing treatments on removal rates of some pesticides residues (acetamiprid, chlorpyrifos and formetanate hydrochloride) on pepper were investigated. Method verification was conducted through spiking pepper samples at 0.1, 1.0 and 10.0 × MRL. QuEChERS method produced average recovery of 104.91% with relative standard deviation (RSD) of 13.41%. LOQ values of acetamiprid, chlorpyrifos and formetanate hydrochloride were estimated as 2, 10 and 5?µg/kg, respectively. Capia peppers grown in open fields were sprayed three times with pesticides. Peppers were harvested after 1st, 2nd and 3rd day of the treatments. Then the peppers were subjected to tap water, acetic acid and citric acid washing and ultrasonic cleaning treatments (for 2 and 5?min). Based on three different harvest times and two different washing durations, processing factors (PFs) and reduction rates were calculated for each washing treatment. The residues gradually decreased during washing treatments with increasing process duration. Similarly, a gradual reduction was noted with the progress of harvest times. This in turn corresponded to an increase in PF. Ultrasonic cleaning and citric acid (9%) washing were more effective than the others. Non-systemic pesticides (chlorpyrifos) were more readily removed than the systemic ones (acetamiprid). Similarly, highly soluble pesticides exhibited higher reduction.     

生态环境监测中高锰酸盐指数测定影响因素分析研究

文中从水浴时间、计时开始方式和溶液酸度3个方面,对环保部标准样品研究所低、中、高3个已知浓度标准样品进行实验分析。结果表明,在加入5 mL 1+3硫酸,从每锅第一个样品放入水浴锅开始计时和最佳水浴时间为29 min条件下,所测定的高锰酸盐指数值具有较高的准确度和精密度。     

Identifying factors that influence soil heavy metals by using categorical regression analysis: A case study in Beijing,China

A method was proposed to identify the main influence factors of soil heavy metals. The influence degree of different environmental factors was ranked. Parent material, soil type, land use and industrial activity were main factors. Interactions between some factors obviously affected soil heavy metal distribution. Identifying the factors that influence the heavy metal contents of soil could reveal the sources of soil heavy metal pollution. In this study, a categorical regression was used to identify the factors that influence soil heavy metals. First, environmental factors were associated with soil heavy metal data, and then, the degree of influence of different factors on the soil heavy metal contents in Beijing was analyzed using a categorical regression. The results showed that the soil parent material, soil type, land use type, and industrial activity were the main influencing factors, which suggested that these four factors were important sources of soil heavy metals in Beijing. In addition, population density had a certain influence on the soil Pb and Zn contents. The distribution of soil As, Cd, Pb, and Zn was markedly influenced by interactions, such as traffic activity and land use type, industrial activity and population density. The spatial distribution of soil heavy metal hotspots corresponded well with the influencing factors, such as industrial activity, population density, and soil parent material. In this study, the main factors affecting soil heavy metals were identified, and the degree of their influence was ranked. A categorical regression represents a suitable method for identifying the factors that influence soil heavy metal contents and could be used to study the genetic process of regional soil heavy metal pollution.     

黄淮海地区干热风灾害致灾因子时空特征分析

黄淮海地区是我国冬小麦主产区,也是干热风灾害危害最重、影响最广的地区,本研究利用黄淮海冬麦主产区81个站点1961-2017年的逐日气象数据和冬小麦生育期资料,分析了该地区小麦成熟期和干热风致灾因子的时空变化特征。在81个测站中,有23个成熟期提前趋势显著或极显著,但大部地区成熟期变化趋势不显著,有63%的站点未通过显著性检验。对干热风致灾因子达标日数和相似系数的分析表明,达到干热风灾害阈值的概率依次为14:00风速>14:00相对湿度>日最高气温,最高气温是形成干热风的主要限制因素,轻干热风的发生最高气温和相对湿度起主要作用,重干热风则是高温胁迫起决定作用,低湿条件使胁迫加重,风速只起辅助作用。揭示了该地区干热风危害总体减轻的气象条件基础,即干热风3要素表现为最高气温略降、14:00相对湿度略增、14:00风速明显减小的特征,3要素均向有利于减轻干热风发生的方向变化,对于冬小麦籽粒灌浆和产量形成是有利的。但灌浆成熟期内最低气温的显著升高,意味着气温日较差减小、小麦夜间呼吸消耗增大,对其干物质积累和产量形成带来潜在不利影响。     

基于验证性因素分析的台风风暴潮灾害经济损失影响因子优化分析

建立客观有效的指标体系是精准估算台风风暴潮灾害经济损失的途径之一。本文以广东省为案例研究区,用验证性因素分析方法对影响灾害经济损失的危险性、脆弱性、抗灾能力3类风险要素进行指标甄别遴选,并将研究区按照经济发展条件分为3个时段,分别分析不同时段内各个风险要素指标的变化。研究表明,对于不同时段,各风险要素的影响指标变化不大,但与风险要素的关联程度会有差异。与传统的指标体系构建相比,本文结合历史案例构建备选指标更具有事实依据,并且利用验证性因素分析方法进行指标遴选,排除了人为主观因素的干扰,增强了指标与研究对象的关联度,减少了指标冗余,使得结果更具有合理性、科学性,为指标体系的研究提供了一个新的思路。     

煤制油基地安全激励因素识别及安全动机模型的实证研究

为探求安全是否需要激励以及如果采用激励、从何激励的问题,对848名煤制油基地的员工进行问卷调查,将员工需求分为低层次需求、尊重需求、成就实现需求和超越自我需求4个方面,对每个具体需求构建需求场景。对控制变量进行差异性检验分析和相关性分析,得出文化程度和年龄对不同层次需求的影响,在此基础上进行结构方程模型验证分析。结果表明:安全需要激励,低层需求和成就需求大于尊重需求,超我需求最小,负向激励不受欢迎;受欢迎的因素在不同年龄和文化下略有差异,考核制度、人际关系、物质激励等均排在前列,且安全动机由经济性满足和自我价值实现共同确定,精神激励制度不是安全动机的核心要素。     

应急状态下矿井瓦斯爆炸致灾因子传播快速分类器研究*

为了在矿井瓦斯爆炸灾变发生后,快速确定瓦斯爆炸冲击波的压力、温度、有毒有害气体等致灾因子在井巷网络中的传播情况。利用CFD数值模拟或爆炸实验获得瓦斯爆炸冲击波的压力、温度、有毒有害气体等致灾因子传播大数据,将影响瓦斯爆炸传播的因素以及观测点等参数作为人工神经网络的输入节点,压力、温度等致灾因子作为输出节点,建立瓦斯爆炸致灾因子传播快速预测机器学习模型,解决CFD数值模拟的建模、计算及数据分析处理等过程耗时大、不适应灾变应急的快速响应等问题。研究结果表明:在给定爆炸位置和爆炸当量的均直巷道,获得任一点的爆炸冲击波压力、温度以及有毒有害气体所需时间是瞬时的,人工神经网络平均训练误差为6.92 %,有训练样本的验证误差为5.24 %,无训练样本的验证误差为6.88 %。     

气象因素对泉州臭氧的影响

利用泉州城区2017年全年连续观测的O_3和气象要素资料,统计了臭氧浓度的分布特征,分析了气象要素对O_3质量浓度的影响,对比了O_3超标日和非超标日的气象要素特征。结果表明:(1)泉州市O_3质量浓度月变化呈双峰形,春季最高,夏季最低;日变化呈单峰形,最大值出现在13:00—14:00,最小值出现在06:00—07:00,上下游站O_3浓度存在明显传输效应。(2)泉州O_3质量浓度与相对湿度呈负相关,其相关性最高;与风速呈正相关,其相关系数最低,且存在明显区位性差异;与气温的相关性比较复杂,既有正相关,也有负相关。(3)各站点O_3小时质量浓度超标时,均对应2个气象要素区间值。(4)对比污染日非污染日发现,污染日相对湿度较低(50%～60%),非污染日较高(70%～80%);污染日温度略低于非污染日;污染日风向总体为西南偏南,非污染日风向为西南-东南。     

冰封期呼伦湖浮游藻类群落结构及其与水环境因子的关系

为探讨冰封状态下呼伦湖的水生态系统演变过程,2015年12月—2016年3月环湖设置6个采样点进行浮游藻类及湖水水质的监测。浮游藻类以绿藻门Chlorophyta种类最多(52.5%),其次为硅藻门Bacillariophyta(29.8%),蓝藻门Cyanophyta(10.5%)。物种丰富度和3种生物多样性指数(Shannon-Wiener多样性指数、Margalef丰富度指数、Pielou均匀度指数)从12月至次年3月呈下降趋势。浮游藻类丰度自12月至次年3月呈现上升趋势。典范对应分析(CCA)排序结果表明:NH₃-N、TN、TP、电导率、DO、BOD₅、CODMn和pH是影响呼伦湖浮游藻类群落结构特征的主要环境因子,其中,NH₃-N、TN和TP分别对硅藻门、绿藻门和蓝藻门的影响较大。     

不同因素对黄山贡菊叶中过氧化氢酶活性的影响

以黄山贡菊离体叶片中过氧化氢酶为研究对象,采用室内模拟方法,研究不同因素处理对黄山贡菊离体叶片中过氧化氢酶活力的影响。结果表明,在30℃时酶活力较高,高温或低温时酶活力均减小;低浓度的K^＋和Ca^2＋对过氧化氢酶有激活作用,高浓度的K^＋和Ca^2＋对过氧化氢酶有抑制作用;Mg^2＋、Pb^2＋、Cu^2＋对过氧化氢酶均具有抑制作用,生长素和赤霉素对过氧化氢酶活性的影响不明显。