Low-carbon transition of iron and steel industry in China: Carbon intensity, economic growth and policy intervention

As the biggest iron and steel producer in the world and one of the highest CO₂ emission sectors, China's iron and steel industry is undergoing a low-carbon transition accompanied by remarkable technological progress and investment adjustment, in response to the macroeconomic climate and policy intervention. Many drivers of the CO₂ emissions of the iron and steel industry have been explored, but the relationships between CO₂ abatement, investment and technological expenditure, and their connections with the economic growth and governmental policies in China, have not been conjointly and empirically examined. We proposed a concise conceptual model and an econometric model to investigate this crucial question. The results of regression, Granger causality test and impulse response analysis indicated that technological expenditure can significantly reduce CO₂ emissions, and that investment expansion showed a negative impact on CO₂ emission reduction. It was also argued with empirical evidence that a good economic situation favored CO₂ abatement in China's iron and steel industry, while achieving CO₂ emission reduction in this industrial sector did not necessarily threaten economic growth. This shed light on the dispute over balancing emission cutting and economic growth. Regarding the policy aspects, the year 2000 was found to be an important turning point for policy evolution and the development of the iron and steel industry in China. The subsequent command and control policies had a significant, positive effect on CO₂ abatement.     

Do vehicular emissions dominate the source of C6–C8 aromatics in the megacity Shanghai of eastern China?

The characteristic ratios of volatile organic compounds(VOCs) to i-pentane, the indicator of vehicular emissions, were employed to apportion the vehicular and non-vehicular contributions to reactive species in urban Shanghai. Two kinds of tunnel experiments, one tunnel with more than 90% light duty gasoline vehicles and the other with more than 60% light duty diesel vehicles, were carried out to study the characteristic ratios of vehicle-related emissions from December 2009 to January 2010. Based on the experiments, the characteristic ratios of C6–C8aromatics to i-pentane of vehicular emissions were 0.53 ± 0.08(benzene), 0.70 ± 0.12(toluene),0.41 ± 0.09(m,p-xylenes), 0.16 ± 0.04(o-xylene), 0.023 ± 0.011(styrene), and 0.15 ± 0.02(ethylbenzene), respectively. The source apportionment results showed that around 23.3% of C6–C8 aromatics in urban Shanghai were from vehicular emissions, which meant that the non-vehicular emissions had more importance. These findings suggested that emission control of non-vehicular sources, i.e. industrial emissions, should also receive attention in addition to the control of vehicle-related emissions in Shanghai. The chemical removal of VOCs during the transport from emissions to the receptor site had a large impact on the apportionment results. Generally, the overestimation of vehicular contributions would occur when the VOC reaction rate constant with OH radicals(k OH) was larger than that of the vehicular indicator, while for species with smaller k OH than the vehicular indicator, the vehicular contribution would be underestimated by the method of characteristic ratios.     

3种酚酸对中肋骨条藻生长的抑制作用

采用外源添加方式,通过监测藻细胞数量变化,分析了香草酸、对羟基苯甲酸和焦性没食子酸对中肋骨条藻生长的抑制作用。结果表明,在32~256mg/L浓度范围内,随着浓度的增大,3种酚酸对中肋骨条藻的抑制作用明显增强。当浓度为192mg/L时,3种酚酸对中肋骨条藻的生长抑制率超过50%。香草酸、对羟基苯甲酸和焦性没食子酸对中肋骨条藻的半抑制浓度分别为153mg/L、145mg/L和108.0mg/L。进一步,研究发现3种酚酸的半抑制浓度作用下,藻细胞内叶绿素、蛋白质和多糖含量明显低于对照组,胞外蛋白质和胞外多糖含量没有明显差异,但二者比值与对照组相比,有明显的增大趋势。3种酚酸显著降低了藻细胞SOD和POD比活力,尤其是显著降低了POD比活力,使其比活力降低为对照组的18%~39%。香草酸、对羟基苯甲酸和焦性没食子酸均致使藻细胞MDA含量明显升高,其数值增大为对照组的1.6、2.2和2.4倍。上述研究表明,3种酚酸通过影响某些主要生化成分的合成及其活性的影响,从而实现对中肋骨条藻生长的抑制作用。     

PM2.5与O3协同控制视角下深圳市工业VOCs源谱特征

选取深圳8类典型工业行业开展VOCs样品采集,检测分析了100种VOCs组分,从PM_2.5和O₃协同控制的角度分析了不同污染源的成分谱特征和对环境的影响.结果表明：加油站源谱组成以烷烃（48.4%）占主导,OVOCs （27.6%）占比突出,乙酸乙酯（14.1%）、异戊烷（13.0%）、正戊烷（12.0%）为其优势排放物种;涂料制造、胶黏剂生产、油墨制造、化工制品、纺织印染、医药制造行业排放组成均以OVOCs （42.3%~97.1%）占主导,丙酮为大多数行业的优势物种,且乙腈在部分行业中占比突出.垃圾发电行业以OVOCs （33.9%）和卤代烃（28.3%）占主导,乙醛（13.4%）、丙酮（11.0%）、一氯甲烷（6.1%）为该行业排放的优势物种.以PM_2.5和O₃协同控制为导向,芳香烃和烯烃是储存运输源需要控制的重点;OVOCs和芳香烃都应成为工艺过程源和废弃物处理源控制的关键.涂料制造行业的源反应活性SR_O3和SR_SOA值分别为6.0g/g和1.2g/g,削减单位质量排放的VOCs所减少的PM_2.5和O₃生成潜势最多,应成为深圳市PM_2.5和O₃协同控制下的优先控制行业.     

Potassium ferrate pretreatment promotes short chain fatty acids yield and antibiotics reduction in acidogenic fermentation of sewage sludge

During the acidogenic fermentation converting waste activated sludge (WAS) into short-chain fatty acids (SCFA), hydrolysis of complex organic polymers is a limiting step and the transformation of harmful substances (such as antibiotics) during acidogenic fermentation is unknown. In this study, potassium ferrate (K₂FeO₄) oxidation was used as a pretreatment strategy for WAS acidogenic fermentation to increase the hydrolysis of sludge and destruct the harmful antibiotics. Pretreatment with K₂FeO₄ can effectively increase the SCFA production during acidogenic fermentation and change the distribution of SCFA components. With the dosage of 0.2 g/g TS, the maximum SCFA yield was 4823 mg COD/L, which is 28.3 times that of the control group; acetic acid accounts for more than 90% of the total SCFA. The higher dosage (0.5 g/g TS) can further increase the proportion of acetic acid, but inhibit the overall performance of SCFA production. Apart from the promotion of hydrolysis and acidogenesis, K₂FeO₄ pretreatment can also simultaneously oxidizes and degrades part of the antibiotics in the sludge. When the dosage is 0.5 g/g TS, the degradation efficacy of antibiotics is the most significant, and the contents of ofloxacin, azithromycin, and tetracycline in the sludge are reduced by 69%, 42%, and 50%, respectively. In addition, K₂FeO₄ pretreatment can also promote the release of antibiotics from sludge flocs, which is conducive to the simultaneous degradation of antibiotics in the subsequent biological treatment process.     

基于MGWR的黄河流域土壤有机碳密度和影响因素分析

土壤有机碳作为最大陆地碳库,其空间分布特征和影响因素对于全球碳循环过程具有重要影响.基于土壤有机碳密度数据,结合环境因子,使用多尺度地理加权回归（MGWR）模型预测了黄河流域土壤有机碳密度（SOCD）和影响因素.结果表明：①黄河流域0~20 cm和0~100 cm的SOCD范围分别为0~14.82 kg ·m^-2和0~32.39kg ·m^-2,均值分别为3.48 kg ·m^-2和8.07kg ·m^-2,储量则分别为2.76 Pg和6.48 Pg;②各生态系统类型中,0~20 cm的SOCD从大到小依次为：森林>水体与湿地>其他>草地>农田>聚落>荒漠,0~100 cm的SOCD从大到小依次为：水体与湿地>森林>其他>草地>农田>聚落>荒漠,SOCR从大到小皆为：草地>农田>森林>荒漠>水体与湿地>聚落>其他;③黄河流域SOCD的分布主要受常数项、剖面曲率、NDVI和降水的影响,曲率和粉砂对深层的SOCD的分布也具有重要影响;此外,降水、NDVI和常数项（除森林外）是影响各生态系统的主要因素,曲率和粉砂则仅对荒漠和其他生态系统具有重要影响.研究结果得出了黄河流域SOCD的空间分布和影响因素,可为黄河流域碳平衡、土壤质量评价和生态治理恢复与巩固提升提供科学依据.     

萘降解菌MQ合成靛蓝的研究

利用萘降解菌(丛毛单胞菌)MQ完整细胞对吲哚进行转化合成靛蓝,结果表明菌株MQ具有较好的靛蓝合成能力,靛蓝产量在4h左右即达到稳定.薄层色谱和高效液相色谱分析结果表明,合成的蓝色产物为靛蓝.考察了反应温度及摇床转速对靛蓝合成的影响,结果表明最适温度和转速分别为25℃和150r·min-1.随后,采用表面响应法确定了菌株MQ合成靛蓝的最优条件:菌株接种量OD6602.16,吲哚浓度200.55mg·L-1,pH=6.91.在最优条件下,菌株MQ合成靛蓝的产量为53.05mg·L-1,比初始条件下的产量提高了179%.     

Development of a model to simulate soil heavy metals lateral migration quantity based on SWAT in Huanjiang watershed, China

Lateral transportation of soil heavy metals in rainfall events could significantly increase the scope of pollution. Therefore, it is necessary to develop a model with high accuracy to simulate the migration quantity of heavy metals. A model for heavy metal migration simulation was developed based on the SWAT(Soil and Water Assessment Tool) model. This model took into consideration the influence of soil p H value, soil particle size, runoff volume, sediment amount,concentration of water-soluble heavy metals dissolved in runoff and insoluble absorbed to the soil particles. This model was reasonable in Huanjiang watershed, Guangxi Zhuang Autonomous Region, south China, covering an area of 273 km~2. The optimal drainage area threshold was determined by analyzing the effects of watershed subdivision on the simulation results to ensure the simulation accuracy. The main conclusions of this paper were:(1) watershed subdivision could affect simulation migration quantity of heavy metals;(2) the quantity of heavy metals transported by sediment accounted for 97%–99% of the total migration quantity in the study watershed. Therefore, sediment played the most important role in heavy metal migration;(3) the optimal drainage area threshold percentage to ensure high simulation accuracy was determined to be 2.01% of the total watershed;(4) with the optimal threshold percentage, this model could simulate the migration quantity of As, Pb and Cd accurately at the total watershed and subwatershed level. The results of this paper were useful for identifying the key regions with heavy metal migration.     

涪江上游滑坡相关因素研究

采用灰色系统理论的关联度分析方法，研究了涪江上游骨滑坡的主要形成条件及触发因素。结果显示，相对主同差是滑坡的主要形成条件，地震是滑坡的主要触发因素，此外，还对滑坡相关因素进行了相关显著性比较，评价了每项相关因素的其中所起的作用，最后讨论了灰色系统理论的关联度分析方法在滑坡研究中的利弊。