农田NO排放的时间变异性

在采用基于箱法的自动观测技术对苏州地区一个完整的科小麦生育期的麦田的ＮＯ排放进行全天候连续观测的基础上,讨论了ＮＯ排放的季节变化和日变化特征及其温度和植物生长的影响,观测实验发现,苏州地区上麦田的ＮＯ排放具有极其显著的季节变化规律怀,冬季以前２的小麦苗期物返青至淹水种稻之前的春季,ＮＯ排放量分别为０．１５６－０．７５８ｍｇ·ｍ＾－２·ｈ＾－１和１．２２９－１０．８０２·ｍ＾－２·ｈ＾－１,前者是全     

水稻土中胱氨酸分解产生含硫气体的研究

测定在室内培养情况下南京水稻土中挥发性含硫气体的释放．结果表明,该土壤中产生Ｈ２Ｓ、羰基硫（ＣＯＳ）和二甲基硫（ＭＤＳ）气体．当土壤中加入胱氨酸后,检测到甲硫醇（ＣＨ３ＳＨ）、二硫化碳（ＣＳ２）、ＣＯＳ、Ｈ２Ｓ和ＤＭＳ气体．除ＤＭＳ之外,这些气体的释放量随胱氨酸添加量增加而增加．据此推测,水稻土中胱氨酸的分解可能是ＣＨ３ＳＨ、ＣＳ２、ＣＯＳ、Ｈ２Ｓ等４种气体产生释放的来源之一．在厌氧条件（充氮淹水）下检测到的含硫气体低于好氧条件（普通大气淹水）．光照、ｐＨ值、土壤含水量等对含硫气体的释放量均有影响     

基于多项污染物综合相对重要性的主成分子集合环境测点优选法

根据对多项污染物环境测点的优选,提出了单项污染物测值的相对重要性和多项污染物测值的综合相对重要性新概念,并给出了综合相对重要性的计算公式．根据测点的综合相对重要性,再用主成分子集合选择法优选测点该方法与基于交叉相关性的主成分子集合优选法相比,不仅减少了计算量,而且避免了当各单项污染物选出的测点不一致时,难以确定公共优化点的困难．该方法用于成都市大气污染物的12个测点优选结果符合实际情况．     

吉林省城市大气降水pH值时空分异及成因

通过对吉林省８个代表城市１９９２－１９９７年大气降水观测数据的统计分析,对大气降水ＰＨ值的时空分异进行了探讨。结果表明：吉林省中西部城市大气降水基本呈中性;东部的图们,珲春两市大气降水酸化亚得,多年平均降水ＰＨ分别为５．１２和５．３８;全省碱性降水多集中在吉林市。     

Trends of air pollution in the Fichtelgebirge Mountains, Bavaria

We analyzed 13 years of hourly measurements of SO₂, NO_x, and O₃, at forest ecosystem research sites in SE Germany. A quasi-continuous data record was obtained by combining data sets from two locations. Before interpreting trends in the combined data set, we analyzed if the change of location introduced a systematic bias. We employed autocorrelation functions, Hurst statistics, complexity analysis, and recurrence quantification and found that the partial data sets exhibited no indication of the presence of any bias. For SO₂, we also compared the data from the forest sites with data obtained in nearby cities and also found no indications for any systematic effects. Applying nonparametric trend statistics we found a significant decrease of the SO₂. Most of the observed decrease is due to the reductions of SO₂ emissions in eastern Germany, but reductions in western Germany and the Czech Republic also played important roles. For O₃, we observed a significant increase, the causes of which are unclear from our data alone. No trend was identified for NO_x.     

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.     

城市区域土壤铅含量空间变异的多尺度研究进展

我国城市土壤仍存在Pb的严重富集,准确地评价土壤Pb污染水平和范围是进行科学的土壤Pb污染风险评估和管理的基础.城市土壤Pb含量的空间变异性强且结构复杂,现有的大多数研究在单一空间尺度上开展,不足以全面揭示空间结构特征,不利于促进更加科学的风险评估和管理.因此,探寻一种能够全面揭示城市土壤Pb含量的空间结构信息的方法尤为重要.为了实现这一目的,本文首先分析了造成城市土壤Pb含量高空间变异性的主要因素:污染源的多样性、污染过程的层次性,以及城市景观的异质性.在此基础上归纳出城市土壤Pb含量的空间变异特征——由3个空间层次嵌套而成的等级结构.在此概念性的空间结构之上提出一个基于地统计学理论、以线性混合效应模型为核心的方法框架,可以将城市土壤Pb含量的空间结构划分为3个层次:全局趋势、具有空间自相关的随机变异以及异常高值点.最后,提出完善城市土壤Pb含量空间变异多尺度研究的重点是:探讨更加高效的空间抽样策略;确定特征尺度.     

哈大绥城市“十三五”期间大气环境容量分析

根据2016—2020年哈尔滨市、大庆市、绥化市(以下称哈大绥)国控环境空气自动监测站的SO₂、NO₂、PM_2.5监测资料,统计年鉴中行政区划、污染物排放及气象等监测数据,分析哈大绥区域环境空气质量的变化趋势和测算因子,采用A值法核定了哈大绥区域SO₂、NO₂、PM_2.5的大气环境容量。结果表明:哈大绥SO₂、NO₂、PM_2.5 3项污染物采暖季的大气环境容量均呈逐年递增趋势。通过计算环境承载能力发现,哈大绥SO₂、NO₂、PM_2.5 3项污染物在非采暖季均具有高承载能力,哈大绥非采暖季环境容量高于采暖季。哈尔滨的个别污染物仍然处于临界超载状态,为减少重污染天气,应进一步削减采暖季污染物排放量。     

基于区域环境空气质量和碳排放数据的减污降碳协同效果评估

化石燃料燃烧产生的温室气体与大气污染物具有同根同源性,但具体治理中减污降碳的协同效果尚不明确。以浙江省11个设区市为研究样本,对环境空气质量和二氧化碳(CO₂)排放数据进行分析研究,结果显示：2016—2020年浙江省环境空气质量持续改善,但CO₂排放总量仍处于增长阶段。11个设区城市PM_2.5年均浓度降幅在26%～41%之间,二氧化氮(NO₂)年均浓度下降趋势不明显,大部分城市呈现碳排放增加、NO₂浓度下降的特征,只有杭州和温州两市呈现碳排放总量和NO₂、PM_2.5浓度协同下降的趋势。因子相关性分析结果表明,各设区市呈现NO₂浓度与碳排放相关性较大、协同性强,PM_2.5浓度与碳排放相关性较小的特点。进一步通过减污降碳协同定量评价分析表明,浙江地区在环境空气质量改善和温室气体减排已表现出一定成效,但各设区市因产业结构、环境基础条件、协同程度等不同导致减污降碳综合绩效有明显差异。从源头减排实现...     

城市空气质量达标规划编制中的关键技术及其案例应用

本文结合重庆市空气质量限期达标规划编制案例,介绍了城市空气质量达标规划编制中的几个关键技术及其具体应用,包括本地化污染源排放清单编制、污染物来源解析、污染物排放形势预测与减排潜力分析以及大气环境容量核算等。本地化污染源排放清单是城市空气质量达标规划编制的基础,针对现有污染源制定科学合理的减排方案是达标规划的核心内容。分析不同区域的污染物组分浓度特征、污染源贡献以及未来污染排放形势预测,有助于识别出制约未来空气质量达标的关键因素及污染源。基于污染源减排潜力和污染传输矩阵制定的污染源减排方案更具合理性和可行性,应用空气质量模型估算大气环境容量可为规划目标可达性提供依据。