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。     

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.     

钻孔间距对水力压裂促抽煤层瓦斯的影响

针对定量确定合理钻孔间距困难问题，基于损伤力学和多场耦合理论，建立了水力压裂和瓦斯抽采的煤层流固耦合模型，包括和水运移场、应力场以及孔隙度、渗透率演化方程，并采用Comsol联合Matlab求解，研究了不同钻孔间距时压裂和抽采过程中煤层弹模、损伤值、渗透率、瓦斯压力、抽采量和压裂贯通时间的变化规律。结果表明:耦合模型可较准确地模拟煤层水力压裂和瓦斯抽采过程；压裂贯通时间与钻孔间距呈指数增长关系；在马堡煤矿，当钻孔间距为4~8 m时，压裂损伤区在抽采孔贯通，渗透率呈“n”型曲线，瓦斯抽采后，瓦斯压力迅速下降，抽采有效区随间距的增加而增大；当钻孔间距为9~12 m时，压裂损伤区未贯通，煤层渗透率呈“m”型曲线，抽采有效区随间距的增加而减小，与间距4~8 m相比，瓦斯抽采量较小。     

近15a江苏省水源涵养功能时空变化与影响因素探析

定量评估生态系统服务功能是合理利用自然资源、促进人地关系与可持续发展的基础。以江苏省为研究区，基于InVEST模型产水模块，定量分析了江苏省2000~2015年产水功能和水源涵养功能的时空变化特征，并采用回归分析和主成分分析法评估了水源涵养功能与社会经济要素之间的关系。结果表明：（1）江苏省多年平均产水量为571×108 m³/a，水源涵养总量78.39×108 m³/a；（2）2000~2010年江苏省水源涵养功能呈下降趋势，2010~2015年有所回升，考虑到降水因素，江苏省实际水源涵养功能持续降低；（3）土地利用变化使15a来水源涵养功能下降15.2×108 m³，降低幅度为16.9%；（4）流域尺度上水源涵养功能与江苏社会经济因素相关关系不显著。研究结果可以为土地利用优化、流域水资源管理提供科学参考和支持。     

矿工心理因素、工作压力反应和不安全行为关系研究

为研究在巨大工作压力下，矿工的心理因素与工作压力反应和不安全行为的关系，以问卷的形式调查陕西省2家具代表性煤矿的工人，分别以矿工的心理因素、工作压力反应和作业过程中的不安全行为作为外生变量、中介变量和内生变量，构建心理因素、压力反应和不安全行为的结构方程模型。通过对调研数据处理与分析，得出如下结论:本研究中的4项心理因素，性格因素、心理素质、注意力和工作态度显著影响不安全行为的发生；性格因素、心理素质和注意力对压力反应有显著影响；工作态度与煤矿工人的压力反应的关系不显著；性格因素、心理素质、注意力和工作态度通过影响矿工的压力反应，间接影响矿工的不安全行为。     

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.     

基于支持向量回归机的南黄海浒苔分布面积预测模型

绿潮作为一种新型的海洋灾害,已经引起了各个国家的重视.依据2012年南黄海海域浒苔遥感监测分布面积数据,选取了温度、天气状况、风向、风力、浪高5种影响浒苔扩散的气候因子,建立了基于SVR的浒苔分布面积预测模型,并与经典的最近邻点插值模型、线性插值模型、3次样条函数插值模型和分段3次Hermite插值模型进行了回归效果的对比.分析结果表明,基于SVR的浒苔分布面积预测模型能够为浒苔遥感数据的插补提供一种方法,且回归效果优于传统的回归方法,为浒苔的防治提供辅助决策信息.     

高效率颗粒物微物理模型简介与重污染过程应用分析

中国细颗粒物(PM2.5)导致的空气污染和雾霾天气问题越来越突出,在低层对流层中很多地方都有显著的二次颗粒物生成过程,因此对颗粒物物理化学转化过程的研究具有重要意义,其转化过程对空气质量模式模拟和预报的准确性有重要影响。高效率颗粒物微物理(APM)模型经过近20多年的研究和发展,在全球化学传输模型(GEOS-Chem)、区域性气象和化学预报模型(WRF-Chem)通用地球系统模型(CESM-CAM5)等气象及环境空气质量预报模型中取得了很好的应用验证,能够在全球/区域等不同尺度对粒子生成、长大、凝聚、消除等微物理过程以及气溶胶光学厚度(AOD)、直接/间接辐射强迫等进行模拟。应用GEOS-Chem-APM模式模拟了2014年2月京津冀区域的重污染过程。结果显示,湿度模拟的准确性对其他物理和污染物浓度等模拟结果有重要作用;2月20—26日的重污染过程模拟结果与实际观测较为吻合,主要污染特点是较高的湿度(90%以上),同时,二次颗粒物和包裹了二次物种的一次颗粒物(黑碳/有机碳)是低能见度的最大贡献者。     

济南市空气污染现状及控制对策

利用2013年1—12月济南市大气监测数据,分析该市空气质量现状及时空分布特征,结果表明:2013年济南市空气主要污染物质量浓度均超过《环境空气质量标准》(GB 3095—2012)二级标准限值,空气污染严重时段为冬季采暖期,颗粒物污染严重区域为该市西部和西北部地区,SO2、NO2污染严重区为中心城区,并从点源、面源和移动源3个方面提出相应的污染防治对策。在SO2、NOx和工业烟粉尘分别减排22.5%、18.2%和31.4%的条件下,运用Models-3/CMAQ模型模拟计算得出:2015年1月和7月,济南市空气中SO2、NO2、PM10和PM2.5的质量浓度与2010年同期相比将分别降低23.9%和29.7%、11.4%和15.9%、21.9%和32.6%、13.5%和26.9%,空气质量得到明显改善。