典型地区农用地污染调查及风险管控标准探讨

针对《土壤污染风险管控标准——农用地土壤污染风险管控标准》(GB 15618—2018),提出以土壤中全量浓度筛选值和管控值作为衡量农用地土壤污染风险管控的标准,对湖南省部分稻田农用地土壤及点对点稻米样品中镉、铅、砷、汞的总量和有效态浓度及稻米中含量进行监测,根据重金属总量浓度分为低风险、中风险、高风险3组。结果显示:(1)土壤及稻米中镉含量基本为随着风险级别的升高而增加,铅、砷在土壤和稻米中含量无规律性结果,汞监测结果均为未检出。(2)低风险组稻米镉超标率为12. 0%,高风险组稻米镉达标率为33. 3%,表明利用总量浓度对农用地土壤潜在风险进行分组存在一定的局限性。(3)依据4种重金属在土壤中总量及稻米(早稻)中含量情况,对风险级别进行调整并综合判断:有58个样品为低风险组,占样品总数的68. 2%,超标率为零;有15个样品为中风险组,占样品总数的17. 7%,超标率为80. 0%;有12个样品为高风险组,占样品总数的14. 1%,超标率为100. 0%。调整后评价结果与上述标准的划分目标更接近,能够提高上述标准的准确性和实用性。     

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。     

基于SHERPA的环境空气质量减排情景模拟评估

分析了SHERPA综合评价模型的基本原理和主要建模理念,重点介绍了其在环境空气质量减排情景模拟评估方面的作用,以及在排放源与受体关系(SRR)方面的处理方法,比较了其与欧盟常用的其他情景模拟模型的优缺点。SHERPA模型的特点是空间灵活性较好,对于任何给定地点,可以快速评估不同地区对该研究地点空气质量的影响。SHERPA模型的3个主要功能为污染物来源分析、决策支持和情景模拟。基于SHERPA模型对法国环境空气中PM_(2.5)、PM_(10)和NO_2年均浓度进行污染来源分析、决策支持分析和减排情景模拟评估,展示了模型在环境治理措施优先级筛选和政府间联合治理措施协调建议方面的功能和作用,以期为中国环境空气质量预测预报、环境质量管理措施的制定和成效评估等环境服务与管理工作提供借鉴。     

郑州市土壤与绿色植物中汞的分布特征

汞污染具有生物积累性,因而得到社会广泛关注。研究监测和评估了郑州市城区土壤和绿色植物叶片中汞浓度、分布、污染水平等。研究发现郑州市主城区土壤总汞浓度为0. 150～0. 958 mg/kg,平均浓度为0. 448 mg/kg;郑州市主城区绿色植物叶片总汞浓度为0. 017～0. 249 mg/kg,平均浓度为0. 107 mg/kg;土壤和叶片中汞浓度按功能区排序为交通枢纽区工业区商业区行政区高教区住宅区。采用地累积指数法对郑州市80个土壤样品的汞污染水平进行评估,结果显示60%受到轻度污染,35%受到偏中度污染,5%受到中度污染。研究较为全面地分析了土壤汞污染的现状及浓度,为郑州市土壤汞污染防治提供参考。     

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。     

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.     

Variation in posture quality across musical instruments and its impact during performances

Objective. Bad posture increases the risk that a musician may suffer from musculoskeletal disorders. This study compared posture quality required by different instruments or families of instruments. Methods. Using an ad-hoc postural observation instrument embracing 11 postural variables, four experts evaluated the postures of 100 students attending a Spanish higher conservatory of music. Results. The agreement of the experts’ evaluations was statistically confirmed by a Cohen's κ value between 0.855 and 1.000 and a Kendall value between 0.709 and 1.000 (p?χ² tests revealed significant association between instrument families and seated posture with respect to pelvic attitude, dorsal curvature and head alignment in both sagittal and frontal planes. This analysis also showed an association between instrument families and standing posture with respect to the frontal plane of the axis of gravity, pelvic attitude, head alignment in the frontal plane, the sagittal plane of the shoulders and overall posture. Conclusions. While certain postural defects appear to be common to all families of instruments, others are more characteristic of some families than others. The instrument associated with the best posture quality was the bagpipe, followed by percussion and strings.     

Effects of EGR on performance and emissions of a diesel engine fuelled with balanites aegyptiaca/diesel blends

In this study, balanites Aegyptiaca (L.) Del biodiesel was blended in proportions of 10% and 20% on the volume basis with diesel fuel and tested in a single cylinder, VCR diesel engine under measured load conditions with varied EGR rates (0, 10 and 20%). The results showed that B10 and B20 blends shown a significant reduction rate in terms of NO_x emissions that were familiar with biodiesel blends. At peak load conditions, BTE increased slightly for test fuel blends compared with pure diesel fuel while the BSFC rate and EGT suffered from increasing and decreasing nature with respect to blending percentage. From the emissions point of view, with the increase in blends percentage, a significant reduction rate is observed in terms of CO and HC concentrations (up to 12.34 and 17.5%, respectively) while NOx emissions decreased at peak load conditions (up to 24.34%). HC and CO emissions decreased with increase in blends percentage. However, lower levels of NO_x and EGT (up to 21.37 and 8.47%, respectively) and the average increase in terms of BTE and BSFC (up to 2.83 and 2.9%, respectively) can be realised with B20 test fuel blend under 20% EGR rate.     

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.     

水环境指示生物筛选及水质评价方法研究

以齐齐哈尔市近30年地表水生物监测数据、理化监测数据为研究依据,提出一套基于指示生物的地表水体评价方法。该方法将地表水体划分为5个级别,并从中筛选出每个级别对应的指示生物,最终建立一套基于指示生物描述水体污染程度的评价体系。该方法以理化指标为基础,筛选多种优势种作为指示生物,对水体进行综合评价。相比单一生物监测评价指标,该评价方法更能反映整个生态系统状况,从而更客观地反映水体真实情况,有望为地表水体污染评价新方法的建立提供参考。