Dissipation kinetics and residues of triazolopyrimidine herbicides flumetsulam and florasulam in corn ecosystem

The dynamic and residues of florasulam and flumetsulam in corn field ecosystem were investigated using quick, easy, cheap, effective, rugged, and safe (QuEChERS) procedure with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The limits of quantification (LOQs) of the proposed method ranged from 0.005 to 0.01 mg/kg. Mean recoveries and relative standard deviations (RSDs) of the two compounds in all samples at three spiking levels ranged 94–110 % and 2.0–9.2 %, respectively. Florasulam and flumetsulam degradation followed first-order kinetics with half-lives 1.7–2.9 and 3.3–8.7 days in soil and 1.3–1.8 and 0.9–1.7 days in plant, respectively. The residues in all the samples were found to be less than the LOQs at preharvest intervals of 53 and 78 days. The results suggest that the combined use of florasulam and flumetsulam on corn is considered to be safe under the recommended conditions and can be utilized for establishing the maximum residue limit (MRL) of florasulam in corn in China.     

SPE-HPLC法测定水中硝基苯酚类化合物

建立了以固相萃取为前处理条件,用液相色谱法测定水中10种硝基苯酚类化合物的分析方法。实验使用HLB(6 L/150 g)固相萃取柱富集水样中的目标化合物,二氯甲烷与乙酸乙酯体积比1:2的混合溶剂洗脱,采用Phenyl柱(4.6 mm×250 mm,5 μm)分离目标化合物,以乙腈(1%甲酸)/水(1%甲酸)为流动相进行梯度洗脱,二极管阵列检测器检测。10种硝基苯酚类物质在0.02~10 mg/L范围内呈现良好的线性。方法检出限为0.1~0.3 μg/L,水样加标相对标准偏差为5.19%~18.2%,平均加标回收率为49.8%~124%。该方法适用于水中10种硝基苯酚类化合物的测定。     

Evaluating the difference between the normalized difference vegetation index and net primary productivity as the indicators of vegetation vigor assessment at landscape scale

Both the net primary productivity (NPP) and the normalized difference vegetation index (NDVI) are commonly used as indicators to characterize vegetation vigor, and NDVI has been used as a surrogate estimator of NPP in some cases. To evaluate the reliability of such surrogation, here we examined the quantitative difference between NPP and NDVI in their outcomes of vegetation vigor assessment at a landscape scale. Using Landsat ETM+ data and a process model, the Boreal Ecosystem Productivity Simulator, NPP distribution was mapped at a resolution of 90 m, and total NDVI during the growing season was calculated in Heihe River Basin, Northwest China in 2002. The results from a comparison between the NPP and NDVI classification maps show that there existed a substantial difference in terms of both area and spatial distribution between the assessment outcomes of these two indicators, despite that they are strongly correlated. The degree of difference can be influenced by assessment schemes, as well as the type of vegetation and ecozone. Overall, NDVI is not a good surrogate of NPP as the indicators of vegetation vigor assessment in the study area. Nonetheless, NDVI could serve as a fairish surrogate indicator under the condition that the target region has low vegetation cover and the assessment has relatively coarse classification schemes (i.e., the class number is small). It is suggested that the use of NPP and NDVI should be carefully selected in landscape assessment. Their differences need to be further evaluated across geographic areas and biomes.     

Biodegradation of Poly(Aspartic Acid-Itaconic Acid) Copolymers by Miscellaneous Microbes from Natural Water

Poly(aspartic acid-itaconic acid) copolymers (PAI) is a new scale inhibitor for water treatment. Thus, it is necessary to investigate its biodegradability. The biodegradability of PAI was investigated through CO₂ evolution tests under different conditions based on determination of carbon dioxide production. The investigation results showed that the degradation rate of PAI on day 10 and day 28 were respectively 38.7 and 79.5%, indicating that PAI was one kind of easily biodegradable scale inhibitors. With the increase in the content of itaconic acid in copolymerization process, the biodegradability of PAI was significantly reduced. In addition, the high biodegradability might be attributed to the existence of C–N bone-structure and more –COO–. Finally, Cu²⁺ could decrease the degradation percentage and the enzyme inhibition effect of Cu²⁺ was not the linear effect, but the “low-dosage effect”.     

An automated (novel) algorithm for estimating green vegetation cover fraction from digital image: UIP-MGMEP

Green vegetation cover fraction (VCF) is an important indicator of vegetation status in ecology and agronomy. Digital image analysis (DIA) has been widely accepted as a new VCF measurement technique. In this study, we present a novel fully automatic threshold segmentation algorithm for VCF measurements, which is named as upper inflection point plus mean gradient magnitude of edge pixels (UIP-MGMEP). The algorithm performs VCF estimation upon the vegetation index Excess Green (EXG). UIP-MGMEP optimizes the EXG threshold by searching the upper inflection point (UIP) of the M-Et curve (mean gradient magnitude of edge pixels (MGMEP) vs. EXG threshold), based on the assumption that EXG variance of the boundary pixels between vegetation and background is larger than the variance of the background. Five typical sample images are used to illustrate how ground complexity reduces the distinctness of the UIP. Three controlled experiments are illustrated to test the robustness of UIP-MGMEP to resolution, exposure, and ground complexity. The results show that UIP-MGMEP is a promising algorithm for automatic VCF estimation upon digital images. Compared to broad-leaved grass, narrow-leaved grass is more sensitive to resolution and exposure. To reduce ground complexity, smaller footprint size while more images to cover the same area may be better than one image with large footprint size. UIP-MGMEP is fully automatic, making it promising for batch processing of VCF measurements that is very difficult in any wide-range field survey in the past. UIP-MGMEP algorithm can only extract green vegetation and is not suitable for non-green (even grayish-green) vegetation, due to the limits of vegetation index EXG. In addition, UIP-MGMEP is not recommended for images with VCF less than 0.5% or greater than 99.5%.     

江苏省水质全要素代表性监测体系的设计

为了评价并进行城市水环境质量考核排名,介绍了江苏省组织开展涵盖地表水、饮用水、地下水、近岸海域和城市内河5种类型"全要素、代表性"水质监测断面(点位)体系建设工作的情况以及全要素断面设置的基本原则和做法。分苏南、苏北、苏中3个区域,对全省地表水监测代表性进行了量化计算,结果表明,调整后全省水质综合指数极差从41.07降至7.17,标准差从3.16降为0.49;采用德尔斐层次分析法分析,设计了水质代表性指数,含1项一级指标、5项二级指标、12项三级指标,计算表明,调整前全省水质代表性指数得分为69.1分,调整后为88.7分。将调整结果进行论证后再与各市环保主管部门交换意见,取得最终一致后正式实施。     

Robust Regression with Data-Dependent Regularization Parameters and Autoregressive Temporal Correlations

We introduce robust procedures for analyzing water quality data collected over time. One challenging task in analyzing such data is how to achieve robustness in presence of outliers while maintaining high estimation efficiency so that we can draw valid conclusions and provide useful advices in water management. The robust approach requires specification of a loss function such as the Huber, Tukey’s bisquare and the exponential loss function, and an associated tuning parameter determining the extent of robustness needed. High robustness is at the cost of efficiency loss in parameter loss. To this end, we propose a data-driven method which leads to more efficient parameter estimation. This data-dependent approach allows us to choose a regularization (tuning) parameter that depends on the proportion of “outliers” in the data so that estimation efficiency is maximized. We illustrate the proposed methods using a study on ammonium nitrogen concentrations from two sites in the Huaihe River in China, where the interest is in quantifying the trend in the most recent years while accounting for possible temporal correlations and “irregular” observations in earlier years.     

彩色玉米粉粉尘云最低引燃温度试验研究

利用HY16429粉尘云引燃温度试验装置,分别对5种彩色玉米粉在不同喷尘压力和不同质量浓度下进行粉尘云最低引燃温度的测定。结果表明:在不同的喷尘压力下,粉尘云最低引燃温度随粉尘云质量浓度增加先下降后上升,在2 250~3 500 g/m~3达到最危险浓度;在不同的质量浓度下,粉尘云最低引燃温度随喷尘压力增加先下降后上升,在60~80 k Pa达到最低值,表明当粉尘云形成的悬浮状态最佳时,最低引燃温度为360℃;无色玉米粉的引燃温度普遍低于含色素的玉米粉,表明色素的添加可使玉米粉的燃爆危险性降低,这与玉米粉粒度分布情况和所含元素中碳氮比有关,C元素含量和碳氮比越高所需引燃温度越低;无色玉米粉粒度分布相对分散且粉尘粒度相对较大,加入色素后粒度分布较集中且粉尘粒度相对较小;不同颜色的玉米粉最低引燃温度呈现不同的变化规律,可解释为色素的发色基团对应于不饱和双键的共轭体系,在受热时它的结构易发生变化所导致。     

Road traffic injuries among riders of electric bike/electric moped in southern China

Objective: Electric bike/moped-related road traffic injuries have become a burgeoning public health problem in China. The objective of this study was to identify the prevalence and potential risk factors of electric bike/moped-related road traffic injuries among electric bike/moped riders in southern China.

Methods: A cross-sectional study was used to interview 3,151 electric bike/moped riders in southern China. Electric bike/moped-related road traffic injuries that occurred from July 2014 to June 2015 were investigated. Data were collected by face-to-face interviews and analyzed between July 2015 and June 2017.

Results: The prevalence of electric bike/moped-related road traffic injuries among the investigated riders was 15.99%. Electric bike/moped-related road traffic injuries were significantly associated with category of electric bike (adjusted odds ratio [AOR] = 1.36, 95% confidence interval [CI], 1.01–1.82), self-reported confusion (AOR = 1.77, 95% CI, 1.13–2.78), history of crashes (AOR = 6.14, 95% CI, 4.68–8.07), running red lights (AOR = 3.57, 95% CI, 2.42–5.25), carrying children while riding (AOR = 1.96, 95% CI, 1.37–2.85), carrying adults while riding (AOR = 1.68, 95% CI, 1.23–2.28), riding in the motor lane (AOR = 2.42, 95% CI, 1.05–3.93), and riding in the wrong traffic direction (AOR = 1.63, 95% CI, 1.13–2.35). In over 77.58% of electric bike/moped-related road traffic crashes, riders were determined by the police to be responsible for the crash. Major crash-causing factors included violating traffic signals or signs, careless riding, speeding, and riding in the wrong lane.

Conclusion: Traffic safety related to electric bikes/moped is becoming more problematic with growing popularity compared with other 2-wheeled vehicles. Programs need to be developed to prevent electric bike/moped-related road traffic injuries in this emerging country.     

Zr掺杂TiO_2介孔材料光催化降解头孢氨苄

采用固相合成法制备了Zr掺杂TiO_2(Zr-TiO_2),运用XRD技术对其进行了表征,并将其用于水中头孢氨苄的光催化降解,通过单因素实验及正交实验优化了光催化反应条件。结果表明:制备的Zr-TiO_2为锐钛矿型介孔材料,孔径约为8.12 nm;各因素对头孢氨苄去除率的影响由大到小依次为光照时间、Zr-TiO_2投加量、初始头孢氨苄质量浓度;在Zr-TiO_2投加量为1.5 g/L、初始头孢氨苄质量浓度为10 mg/L、溶液pH为7.0、光照(300 W UV)时间为1.5 h的优化条件下,头孢氨苄去除率高达99.46%;Zr-TiO_2光催化剂的重复使用性能良好。