生态发酵床运行参数变化规律研究

为了探究发酵床运行过程中参数的变化规律,试验在某生态养殖场开展研究,获取发酵床运行过程中温湿度、碳氮比(C/N)等数据,并分析其变化趋势。结果表明,控制好养殖密度及粪污负荷,发酵床能够保持合适的温度、湿度和pH,并具有一定的自我调节功能;垫料中固相C/N下降趋势缓慢,可以为发酵反应提供长期的碳源,水溶性C/N经过短期波动后趋于稳定,能够给微生物提供足够的养分;在不同粪污负荷条件下,氨态氮转化趋势不同,高负荷条件下更容易造成氮素的损失。研究结果在一定程度上可以为今后发酵床运营维护提供指导和技术支撑。     

石油化工催化剂生产过程中的职业病防治及应急处理

石化企业使用了大量的催化剂,催化剂开发、生产过程复杂,有许多原料和生产工艺,存在许多潜在的安全隐患和职业病危害因素。为预防催化剂生产过程中的事故,通过分析催化剂生产过程中的职业病危害分析,提出了相应的职业病防范及应急处置措施,加强催化剂生产过程中的职业病防治和应急处置能力,创造良好的经济、生态和社会效益,有效防止催化剂生产过程中发生安全事故和职业病。     

石油化工企业含苯胺消防污水处理技术研究

针对石油化工企业含苯胺的消防污水,利用基于过氧化氢和氯化铁为氧化剂的深度氧化技术,通过氧化、絮凝、过滤和吸附对消防污水进行处理。实验确定氧化剂的投加量为理论投加量,氧化时间1.0h,消防污水pH值为6.86时,絮凝剂最佳使用浓度约为2%,消防污水中苯胺和COD去除率达到99.5%以上,达到了消防污水处理效果。     

Impact of green credit on industrial structure in China: theoretical mechanism and empirical analysis

Environmental Science and Pollution Research - Chinese industrial structure is characterized by a large proportion of industries with high energy consumption and high pollution, such as coal,...     

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.     

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.     

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。     

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%.     

生物沸石滤池处理富营养化水体的挂膜实验

采用上向流生物沸石滤池处理富营养化水体,考察了挂膜阶段(前30 d)滤池对浊度、COD和TP等的去除效果,重点研究了系统中各形态氮素(NH4+-N、NO2--N、NO3--N和TN)的变化情况。结果表明,对于富营养化水体,生物沸石滤池对浊度、COD和TP的去除率分别约为80%、30%和24%;出水NH4+-N始终保持在0.5 mg/L以下,去除率在90%以上;NO2--N出现峰值(4.98 mg/L,第9 d),第13 d后即一直低于进水值;实验后期出水NO3--N与进水NH4+-N变化趋势基本一致,表明硝化生物膜已成熟,原位再生可行;生物沸石床内可能存在同步硝化反硝化现象。出水NO2-N浓度低于进水可作为生物沸石挂膜成功的一个标志。