The performance of nitrate-reducing Fe(II) oxidation processes under variable initial Fe/N ratios: The fate of nitrogen and iron species

•Bacterially-mediated coupled N and Fe processes examined in incubation experiments. •NO₃⁻ reduction was considerably inhibited as initial Fe/N ratio increased. •The maximum production of N₂ occurred at an initial Fe/N molar ratio of 6. •Fe minerals produced at Fe/N ratios of 1–2 were mainly easily reducible oxides. The Fe/N ratio is an important control on nitrate-reducing Fe(II) oxidation processes that occur both in the aquatic environment and in wastewater treatment systems. The response of nitrate reduction, Fe oxidation, and mineral production to different initial Fe/N molar ratios in the presence of Paracoccus denitrificans was investigated in 132 h incubation experiments. A decrease in the nitrate reduction rate at 12 h occurred as the Fe/N ratio increased. Accumulated nitrite concentration at Fe/N ratios of 2–10 peaked at 12–84 h, and then decreased continuously to less than 0.1 mmol/L at the end of incubation. N₂O emission was promoted by high Fe/N ratios. Maximum production of N₂ occurred at a Fe/N ratio of 6, in parallel with the highest mole proportion of N₂ resulting from the reduction of nitrate (81.2%). XRD analysis and sequential extraction demonstrated that the main Fe minerals obtained from Fe(II) oxidation were easily reducible oxides such as ferrihydrite (at Fe/N ratios of 1–2), and easily reducible oxides and reducible oxides (at Fe/N ratios of 3–10). The results suggest that Fe/N ratio potentially plays a critical role in regulating N₂, N₂O emissions and Fe mineral formation in nitrate-reducing Fe(II) oxidation processes.     

Prevention of an atmospheric storage tank bund failure

Secondary containment (bunds, drip trays, interceptors/sumps) is an integral part of many chemical, petrochemical, as well as agricultural, food and pharmaceutical facilities. Bunds are the built-in cases for accidental liquid substance spillage where there is a hazard that a substance could leak into the surroundings and the potential of health or environmental damage. The authors focus on the cases installed in large-volume atmospheric tanks storing hazardous chemicals in liquid form, where the bund failure occurred. In the first part of the study, a database of these accidents was created, numbering a total of 15 items. Attention was paid to the course of the accident, its causes and consequences. Several basic representative scenarios of bund failure have also been developed. The second part of the study is devoted mainly to the measures against the bund failure, such as risk assessment, technical and organizational measures. The aim of this study is to provide readers (including experts in the field of safety engineering, maintenance experts and building designers) with the information that can subsequently be used in the risk assessment of bund failure, possibly also for planning the construction of new bunds, or revitalization and maintenance of the existing ones.     

北京市典型废弃物焚烧源2010—2017年二NFDA1英排放特征和减排效果分析

分析2010—2017年北京市三类典型废弃物焚烧源的废气二NFDA1英排放监测数据,计算排放因子和排放量,评估减排政策成效,并分析不同排放源达标排放时同类物分布特征异同和变化规律,探讨影响排放的重要因素。结果表明: 5家焚烧源平均排放浓度为 0.008～0.069 ng/m³(以TEQ计,下同),废气二NFDA1英排放因子为 0.027～1.7 μg/t,2016年向空气中排放的二NFDA1英量为 0.002 5～0.058 g；生活垃圾、危险废物和医疗废物焚烧源的低、高氯代同类物质量分数比的平均值分别为接近于 0.5、大于0.5和小于0.5,危险废物焚烧源的 ∑PCDFs、∑PCDDs质量分数比的平均值大于2； 123478-HxCDF和123678-HxCDF质量浓度接近且线性相关,具有相近的生成机理和去除效率； I-TEQ变化趋势与∑PCDFs质量分数的变化趋势基本一致,活性炭喷射和布袋除尘的去除效率是影响二NFDA1英排放的重要因素之一；危险废物焚烧源HWI1随运行时间增加排放浓度增加,而及时更换烟道管壁有助于消除“记忆效应”的不良影响。     

美缝剂TVOC释放量与释放规律的测试与分析

提出了环境舱法测试美缝剂总挥发性有机化合物(TVOC)释放量的方法,对市场常见的美缝剂产品的TVOC进行了测试,并研究了美缝剂的TVOC释放规律和主要污染物.同时对美缝剂的甲醛释放量进行了测试.通过对16种环氧树脂美缝剂产品的数据分析显示,美缝剂产品的甲醛释放量风险较低;75%的产品在第7天的TVOC释放量可达到500μg·m^-3以下.但个别产品在28 d时仍有明显的VOC释放,显示其具有长期缓慢释放的特点.美缝剂释放的主要污染物为苯甲醛与苯甲醇,个别产品检出有甲苯和邻苯二甲酸酯类物质.     

资阳市大气污染源排放清单研究

采用实地调研、资料收集等方式获得了2017年资阳市典型污染源的活动水平数据,参照城市大气污染物排放清单编制技术手册建立了基于排放因子法和物料衡算法的资阳市大气污染源排放清单,分析了主要污染物的行业排放特征和空间分布特征。结果表明,2017年资阳市SO₂、NO_X、CO、PM₁₀、PM_2.5、VOCs、NH₃总排放量分别为3.58kt、13.91kt、94.91kt、25.51kt、8.67kt、23.84kt和46.44kt。SO₂排放主要来自工业源;NOX排放主要来自移动源;CO排放主要来自工业过程及移动源;PM₁₀和PM_2.5、排放来自扬尘源和露天秸秆焚烧;VOCs主要来自溶剂使用源;NH₃主要来自农业活动。资阳市主要污染物排放分布在工业点源较为集中的雁江区和安岳县,乐至县污染物排放量相对较小。     

北京首都机场绿色滑行时间估算

采用北京首都机场2014年实际CDM地面放行数据确定航空器的污染物排放量与离场排队飞机数量和落地滑入飞机数量的强关联性,构建包含这两个解释变量为影响因素的多元线性回归模型,用以估算几种常见机型在首都机场地面运行时的最小污染物排放量和绿色滑行时间。对比实际污染物排放量与最小污染物排放量,得出首都机场离场地面污染物排放量远远超过最小污染物排放量。     

北京地区PM10与秸秆燃烧排放单颗粒对比分析

采用场发射带能谱扫描电镜(FESEM/EDS)法分析北京怀柔地区PM₁₀与秸秆燃烧排放颗粒的形貌特征和成分差异。结果显示:秸秆燃烧后排放颗粒物多为大粒径颗粒,成分上都含S、Cl和K元素。含有生物质燃烧标志元素K的PM₁₀颗粒物多为含Si、Al和Na元素的燃煤飞灰和矿物颗粒,与秸秆燃烧排放颗粒组成化学元素差异明显。据此推断,北京区域PM₁₀受秸秆燃烧排放影响相对较弱,化石燃料燃烧来源影响仍然显著。     

A new prediction method of industrial atmospheric pollutant emission intensity based on pollutant emission standard quantification

● Established a quantification method of pollutant emission standard. ● Predicted the SO₂ emission intensity of single coking enterprises in China. ● Evaluated the influence of pollutant discharge standard on prediction accuracy. ● Analyzed the SO₂ emissions of Chinese provincial and municipal coking enterprises. Industrial emissions are the main source of atmospheric pollutants in China. Accurate and reasonable prediction of the emission of atmospheric pollutants from single enterprise can determine the exact source of atmospheric pollutants and control atmospheric pollution precisely. Based on China’s coking enterprises in 2020, we proposed a quantitative method for pollutant emission standards and introduced the quantification results of pollutant emission standards (QRPES) into the construction of support vector regression (SVR) and random forest regression (RFR) prediction methods for SO₂ emission of coking enterprises in China. The results show that, affected by the types of coke ovens and regions, China’s current coking enterprises have implemented a total of 21 emission standards, with marked differences. After adding QRPES, it was found that the root mean squared error (RMSE) of SVR and RFR decreased from 0.055 kt/a and 0.059 kt/a to 0.045 kt/a and 0.039 kt/a, and theR² increased from 0.890 and 0.881 to 0.926 and 0.945, respectively. This shows that the QRPES can greatly improve the prediction accuracy, and the SO₂ emissions of each enterprise are highly correlated with the strictness of standards. The predicted result shows that 45% of SO₂ emissions from Chinese coking enterprises are concentrated in Shanxi, Shaanxi and Hebei provinces in central China. The method created in this paper fills in the blank of forecasting method of air pollutant emission intensity of single enterprise and is of great help to the accurate control of air pollutants.     

The accounting method and application of CO2 emissions responsibility by the electricity sector at the provincial level in China

When accounting the CO₂ emissions responsibility of the electricity sector at the provincial level in China,it is of great significance to consider the scope of both producers’ and the consumers’ responsibility,since this will promote fairness in defining emission responsibility and enhance cooperation in emission reduction among provinces.This paper proposes a new method for calculating carbon emissions from the power sector at the provincial level based on the shared responsibility principle and taking into account interregional power exchange.This method can not only be used to account the emission responsibility shared by both the electricity production side and the consumption side,but it is also applicable for calculating the corresponding emission responsibility undertaken by those provinces with net electricity outflow and inflow.This method has been used to account for the carbon emissions responsibilities of the power sector at the provincial level in China since 2011.The empirical results indicate that compared with the production-based accounting method,the carbon emissions of major power-generation provinces in China calculated by the shared responsibility accounting method are reduced by at least 10%,but those of other power-consumption provinces are increased by 20% or more.Secondly,based on the principle of shared responsibility accounting,Inner Mongolia has the highest carbon emissions from the power sector while Hainan has the lowest.Thirdly,four provinces,including Inner Mongolia,Shanxi,Hubei and Anhui,have the highest carbon emissions from net electricity outflow- 14 million t in 2011,accounting for 74.42% of total carbon emissions from net electricity outflow in China.Six provinces,including Hebei,Beijing,Guangdong,Liaoning,Shandong,and Jiangsu,have the highest carbon emissions from net electricity inflow- 11 million t in 2011,accounting for 71.44% of total carbon emissions from net electricity inflow in China.Lastly,this paper has estimated the emission factors of electricity consumption at the provincial level,which can avoid repeated calculations when accounting the emission responsibility of power consumption terminals（e.g.construction,automobile manufacturing and other industries）.In addition,these emission factors can also be used to account the emission responsibilities of provincial power grids.     

乌鲁木齐市近年来大气降尘变化规律及空间分布特征

基于乌鲁木齐市多年监测的降尘数据,对乌鲁木齐市城区的降尘量进行了统计分析,得出了乌鲁木齐市近10年来降尘的总体变化规律;利用方差分析方法检验了不同季节降尘的显著性差异,发现采暖期的降尘量明显大于非采暖期;按行政区分析降尘量的分布变化,结果为不同行政区存在差别;利用秩相关系数法对其进行了趋势分析。结果表明,乌鲁木齐市的降尘呈下降趋势。利用Arc GIS9.3中的普通克里格插值方法绘制了乌鲁木齐市城市自然降尘的空间分布图。