山东省PM2.5污染现状及预报效果对比分析

对2019—2022年山东省16个市的细颗粒物（PM_2.5 ）污染特征进行了分析,并对2021和2022年的4个数值模式［社区多尺度空气质量模拟系统（CMAQ）、扩展综合空气质量模型（CAMx）、区域气象-大气化学在线耦合模式（WRF-Chem）、嵌套网格空气质量预报系统（NAQPMS）］及集合预报模式预测的效果进行评估。结果表明：2019—2022年山东省PM_2.5 年均质量浓度逐年降低,污染程度逐步减轻,但在1—3,11—12月,PM_2.5 质量浓度超标现象较为普遍。2021年底更换污染源清单后,2022年5个模式的24 h级别准确率和相关系数（r）同比升高,均方根误差（RMSE）同比降低,模式预报准确率有所提升,但由于参数调整略大,CMAQ、CAMx、WRF Chem、集合预报模式易漏报或偏轻预报PM_2.5 的中度污染和重度污染天气。由于NAQPMS模式在更换污染源排放清单时,同时改进了非均相化学反应机制,因此对PM_2.5 不同污染类别尤其是中度污染、重度污染的预报准确率明显提升。     

基于LSTM-GCN的PM2.5浓度预测模型

应用机器学习算法开展空气质量预测已成为当前研究热点之一,空气质量监测数据具有显著的时空特征,即具有时间维度时序特征和空间维度传输演化特征。面向空气质量监测数据,联合LSTM提取的时间特征和GCN提取的空间特征,提出预测PM_2.5浓度的LSTM-GCN组合模型。以北京市35个空气质量监测站2018—2020年监测数据进行仿真实验,并将LSTM-GCN模型与LSTM模型、GCN模型以及时空地理加权回归模型(GTWR)进行对比,结果显示:LSTM-GCN模型相较于LSTM模型均方根误差(RMSE)、平均绝对误差(MAE)分别降低了11.68%、7.34%;相较于GCN模型RMSE、MAE分别降低了40.22%、36.37%;相较于GTWR模型RMSE、MAE分别降低了17.52%、23.69%,表明所提出LSTM-GCN模型在准确率上有所提升。用LSTM-GCN模型预测2021年1—7月PM_2.5浓度,结果显示预测效果较好。     

山东省O3污染概况及预报效果评估

对山东省各市2018—2021年的O₃污染特征进行了分析,并对2021年5—9月O₃污染较重月份空气质量模型的O₃预报结果进行了分析评估。结果表明:山东省2018—2021年O₃-8 h第90百分位数(O₃-8 h-90per)先升高后降低,O₃污染呈现波动变化,污染月主要集中在5—9月,并呈现内陆高、沿海低,中北部高、南部低的空间分布特征。集合预报模式对O₃模拟效果最好,预测结果与O₃监测值的相关性最大、偏差最小,但较难预测出O₃的峰值浓度,易漏报O₃重度污染。WRF-Chem、CMAQ、CAMx、NAQPMS对O₃的模拟效果比集合预报稍差,CMAQ、CAMx存在系统性偏低的情况,但对优级别的模拟效果明显好于其他模式;WRF-Chem、NAQPMS存在系统性偏高的情况,WRF-Chem能较好地模拟出O₃超标日,对中度、重度日的24h级别准确率分别达94.08%、100%,对O₃超标预报尤其是中至重度污染的预测预报有重要指导意义。     

基于OPAQ的城市空气质量预报系统研究

空气质量预测在国内的关注度日益提高,传统的空气质量预测系统通常运用数值化学传输模型,利用物理方程来计算污染物的扩散、沉降和化学反应。而化学传输模型的预测准确性很大程度上需要依赖详细的污染源排放信息和气象模型的输出结果。基于统计模型的OPAQ空气质量预报业务系统,采用人工神经网络算法,可预测各污染物的日均值或日最大值。并对北京空气质量预报的结果进行了评价,OPAQ空气质量预报业务系统对空气质量预测的准确性较高,能够利用较低的计算资源得到较为准确的预测结果。与数值预报相比,OPAQ空气质量预报业务系统不需要大量的基础数据作为输入,可弥补数值预报的不足,并成为数值预报的有力补充。     

OPAQ系统两种模式对O 3预报准确率的探讨

以江苏省宿迁环境监测中心OPAQ系统为例,基于人工神经网络算法的OPAQ空气质量预报系统的2种模式对O 3预报准确率的进行了分析,结果表明,趋势最优模式(RMSE模式)对预报当天及未来3 d的预报值与监测值的相关性系数均>0.78,相对误差在25%以下,在预测当天及未来24、48及72 h优-良天的预测准确率较高,分别为88.8%、87.2%、86.3%及84.7%,在预测轻度污染-重度污染的准确率较低;极值最优模式(SI模式)对预报当天及未来3 d的预报值与监测值的相关性系数(R)均>0.76,相对误差<32%,预测未来24和48 h的轻度污染-中度污染的级别准确率>60%。OPAQ系统的极值最优模式(SI模式)更适合作为夏季ρ(O 3)较高时的预测工具。     

2019年江苏省PM2.5和O3多模式集合预报算法效果评估

基于江苏省重污染天气监测预报预警系统多模式预报结果,分析了不同数值模式对江苏省13个城市细颗粒物(PM_2.5)和臭氧(O₃)的预报偏差特征,发展了多模式集合预报算法,并对其进行了评估。结果表明,相较于单一数值模式,集合预报算法显著改善了PM_2.5和O₃预报的准确率,其对江苏省PM_2.5和O₃空气质量分指数等级的预报准确率超过了80%。就江苏省整体而言,PM_2.5集合预报的准确率相比最优单一数值模式提升了6%。O₃浓度较低时,集合预报能有效改善各模式存在的高估现象。但受限于目前的校正策略,出现高浓度O₃污染时,集合预报对预报效果的提升相对有限。     

基于深度学习的空气质量预报方法新进展

空气质量预报与人们的日常生活密切相关,其基本思想是分析历史空气质量数据,发现其内在的时空相关性,结合未来气象信息以及污染源排放量,对未来的空气质量进行预测。目前,环境管理和社会公众服务对空气质量预报提出了长时间、多维度、高精度的预测要求,一些新型的空气质量预测方法仍处于起步探索阶段。近年来,随着人工智能的普及与推广(特别是云计算与大数据的发展),深度学习这项基于传统人工神经网络的技术被国内外研究者所重视。笔者对现有典型的空气质量预报方法进行了阐述,包括数值预测模型方法、统计预报模型方法、基于机器学习模型的预测方法等,并重点介绍了该领域最新进展:基于深度学习模型的预测方法,并在此基础上进行了总结与展望。     

广东省清远市PM2.5污染天气分型及污染潜在源区分析

利用2016—2021年清远市逐时空气质量监测数据和相关气象资料,基于统计分析、主观天气分型方法和后向轨迹模式（HYSPLIT）,归纳总结粤北代表城市清远市在不同细颗粒物（PM_2.5 ）污染天气分型下的气象要素特征及污染潜在源区特征,为大气污染精细化防控提供有效参考。结果表明：在日均风速＜2m/s、日均相对湿度为75%～90%、日均气温为18～22℃时的无降水或微量降水天气下,清远市易出现PM_2.5 污染。变性高压脊型、脊后槽前型、冷锋前型、弱冷高压脊型、高压底后部型、台风外围型是造成清远市PM_2.5 污染的典型天气型,其中PM_2.5 重度污染均出现在秋、冬季弱冷高压脊型控制下;变性高压脊型下出现PM_2.5 轻度和中度污染的频率最高;脊后槽前型是清远市春季PM_2.5 污染的主要天气型;冷锋前型、高压底后部型和台风外围型下的PM_2.5 污染程度较轻。加剧清远市PM_2.5 污染的主要气流轨迹为弱偏南气流和南北气流辐合,当弱偏南气流控制时,污染潜在源区主要位于清远市辖区及广州、佛山、东莞、江门等珠三角城市;当南北气流辐合时,潜在源区主要位于清远市南部、韶关及珠三角,南岭山脉阻挡作用削弱了偏北方向长距离输送的PM_2.5 污染。     

基于特征指标的气象因子对PM2.5浓度的影响分析

以西安为研究区域,为探究气象因子对PM_2.5浓度的影响,采集2017-2019年空气质量与气象因子数据,改进k-Means聚类算法,形成严重污染、重度污染、中度污染、轻度污染共4个PM_2.5浓度与气象因子样本簇集。分析簇集数据分布,选择Spearman相关性分析方法,确定影响PM_2.5浓度的气象因子;定义PM_2.5凸显性条件,给出幅度特征FOA、浮动特征FOF和凸显特征FOH,构建三维空间,确定气象因子对PM_2.5影响的大小,进而建立气象因子对PM_2.5浓度的影响分析方法。比较多元线性回归和随机森林回归方法,结果表明:该方法提高了分析效率,且无需考虑因子选取和表达,能有效确定影响PM_2.5浓度的气象因子种类及影响程度。在低温、高湿、高压和相对静风的气象条件下,空气中颗粒物难以扩散和输送,使西安市PM_2.5浓度升高。严重污染、重度污染和中度污染中,PM_2.5浓度与相对湿度呈显著正相关,与风速、气温呈显著负相关,且影响大小依次为相对湿度>风速>气温;轻度污染中,PM_2.5浓度与相对湿度、气压呈显著正相关,与风速、气温呈显著负相关,且影响大小依次为气温>相对湿度>气压>风速。     

广州市污染季节空气质量预报效果评估及误差分析

基于广州市2016年第四季度空气质量实测及预报数据,对广州市污染季节空气质量预报效果进行了评估,结果表明,2016年第四季度广州市空气质量级别预报准确率83.7%、AQI范围预报准确率67.4%、首要污染物预报准确率67.2%、综合考核评分87.4分、相关系数0.78,预报效果总体良好,预报准确率在优良级别时相对较高,而在轻度污染以上级别时相对较低。预报误差分析表明,气象预报精细化程度不足、模式预报不确定性等客观因素,预报员缺乏对污染过程物理化学机制的深入理解等主观因素共同导致了预报的误差。     

A New Mathematical Approach in Environmental and Life Sciences: Gene–Environment Networks and Their Dynamics

An important research area in life sciences is devoted to modeling, prediction, and dynamics of gene-expression patterns. As clearly understood in these days, this enterprise cannot become satisfactory without acknowledging the role of the environment. To a representation of past, present, and most likely future states, we also encounter measurement errors and uncertainties. This paper surveys and improves recent advances in understanding the foundations and interdisciplinary implications of the newly introduced gene–environment networks, and it integrates the important theme of carbon dioxide emission reduction into the networks and dynamics. We also introduce some operational and managerial issues of practical working and decision making, expressed in terms of sliding windows, quadrants (modules) of parametric effects, and navigating (controlling) between such effects and directing them. Given data from DNA microarray experiments and environmental records, we extract nonlinear ordinary differential equations that contain parameters that have to be determined. For this, we employ modern (Chebychevian) approximation and (generalized semi-infinite) optimization. After this is provided, time- discretized dynamical systems are studied. A combinatorial algorithm with polyhedra sequences allows to detect the region of parametric stability. Finally, we analyze the topological landscape of gene–environment networks with its structural (in)stability. By embedding as a module and investigating CO₂ emission control and figuring out game theoretical aspects, we conclude. This pioneering work is theoretically elaborated, practically devoted to health care, medicine, education, living conditions, and environmental protection, and it invites the readers to future research.      

微波消解-原子吸收光度法测定土壤中铜锌铅镉镍铬

用微波消解－原子吸收光度法测定土壤中铜，锌，铅，镉，镍和铬。通过硝酸－氢氟酸－过氧化氢体系消解液对土壤样品消解，选择出微波最佳消解条件。对硝酸－盐酸－过氧化氢体系消解液和硝酸－氢氟酸－过氧化氢体系消解液进行消解对比试验，发现前者不能将土壤样品完全消解，后者能将样品消解完全，但需将消解液中剩余的酸赶尽，否则测定结果将明显偏低。微波消解土壤与传统电热消解相比，操作简便快速，可提高工作效率。     

Topsoil and Housedust Metal Concentrations in the Vicinity of a Lead Battery Manufacturing Plant

The aim of the study was to determine the extent of heavy metal pollution in the vicinity of a lead battery manufacturing plant in the Czech Republic, both in the general environment and within homes. Topsoils (0–5 cm) were sampled from 100 sites along 4 transects which crossed the battery factory, the town centre and outlying rural areas. Housedust samples were collected from 15 plant-workers' homes and 15 non plant-workers' homes located at various distances from the factory. Samples were analysed for levels of Pb, Zn, Cd, Cu, As and Sb, using ICP-AES. Soil concentrations of Pb, Cd, As and Sb peaked at the perimeter fence of the battery factory with Pb levels of up to 12 650 g g> ^-1. Concentrations of these metals decreased exponentially within 500 m of the plant. Whilst the battery factory does appear to be a source of all the metals with the exception of Zn, emissions do not appear to be transported to any great extent over distances of more than 0.5 km. Topsoil and housedust concentrations of Pb, Zn, Cd, Cu, As and Sb in the general Mlada Boleslav area do not appear to be significantly different from those recorded in a large scale survey of urban soils in the United Kingdom. A comparison of housedust Pb concentrations in homes of plant workers and non-plant workers suggests that there may be a small input of Pb into the home environment by battery plant employees.     

An Overview of Contaminant-Related Issues Identified by Monitoring in San Francisco Bay

The San Francisco Estuary Regional Monitoring Program for Trace Substances (RMP) began in 1993 and is sponsored by 74 local, state, and federal agencies and companies through their discharge or Bay use permits. The RMP monitors water, sediment, toxicity, and bivalve bioaccumulation at 25 sites in the Bay that are considered to represent "background" conditions. Several major environmental issues have been identified by the RMP. Polychlorinated biphenyls and mercury were often above water quality guidelines, and often occurred in fish tissues above U.S. Environmental Protection Agency (U.S. EPA) screening values. Concentrations do not appear to be decreasing, suggesting continuing inputs. Episodes of aquatic toxicity often occurred following runoff events that transport contaminants into the Bay from urbanized and agricultural portions of the watershed. Sediment toxicity occurred throughout the Bay, and has been correlated with concentrations of specific contaminants (chlordanes, polynuclear aromatic hydrocarbons) at some locations; mixtures of contaminants were probably also important. Since the RMP does not monitor all ecosystem components, assessments of the overall condition of the Bay cannot be made. However, in terms of contamination, the RMP samples suggest that the South Bay, and North Bay sites are moderately contaminated.     

Biomagnification factors (fish to Osprey eggs from Willamette River,Oregon, U.S.A.) for PCDDs,PCDFs, PCBs and OC pesticides

A migratory population of 78 pairs of Osprey (Pandion haliaetus) nesting along the Willamette River in westernOregon was studied in 1993. The study was designed to determinecontaminant concentrations in eggs, contaminant concentrationsin fish species predominant in the Ospreys diet, andBiomagnification Factors (BMFs) of contaminants from fish specieseaten to Osprey eggs. Ten Osprey eggs and 25 composite samplesof fish (3 species) were used to evaluate organochlorine (OC)pesticides, polychlorinated biphenyls (PCBs), polychlorinateddibenzo-p-dioxins (PCDDs), and polychlorinated dibenzofurans(PCDFs). Mercury was also analyzed in fish. Geometric meanresidues in Osprey eggs were judged low, e.g., DDE 2.3 g g^-1 wet weight (ww), PCBs 0.69 g g^-1, 2,3,7,8-TCDD 2.3 ng kg^-1, and generally well below known threshold values for adverse effects on productivity, and the population was increasing. Osprey egg residue data presentedby River Mile (RM) are discussed, e.g., higher PCDDs were generally found immediately downstream of paper mills and eggsfrom the Willamette River had significantly elevated PCBs and PCDDs compared to reference eggs collected nearby in the CascadeMountains. Prey remains at nest sites indicated that the Largescale Sucker (Catostomus macrocheilus) and NorthernPikeminnow (Ptychocheilus oregonensis) accounted for an estimated 90.1% of the biomass in the Osprey diet, and composite samples of these two species were collected from different sampling sites throughout the study area for contaminant analyses. With the large percentage of the fishbiomass in the Osprey diet sampled for contaminants (and fisheaten by Ospreys similar in size to those chemically analyzed),and fish contaminant concentrations weighted by biomass intake, a mean BMF was estimated from fish to Osprey eggs for the largeseries of contaminants. BMFs ranged from no biomagnification(0.42) for 2,3,7,8-TCDF to 174 for OCDD. Our findings for themigratory Osprey were compared to BMFs for the resident HerringGull (Larus argentatus), and differences are discussed. Webelieve a BMF approach provides some basic understanding ofrelationships between contaminant burdens in prey species offish-eating birds and contaminants incorporated into their eggs,and may prove useful in understanding sources of contaminants inmigratory species although additional studies are needed.     

Cyanobacterial Flora from Polluted Marine Shores

Citation of cyanobacterial cultures from the shores of south west coast of Gujarat, India and their relationship with sea water quality, influenced by extensive pollutant runoff is reported in this study. Intensity of pollution was evaluated by physico-chemical analysis of water. Higher load of suspended solids (60–1000 mg l⁻¹) and nutrients (PO₄ ⁻P: 1.3–4 μmole l⁻¹ and NO₃ ⁻N: 12.5–17.8 μmole l⁻¹) were persistent throughout the analysis. Community structure is seen to be influenced by such persistent pollution. Twenty nine cyanobacterial species were isolated belonging to 9 genera of 4 families, with an elevated occurrence of Oscillatoria and Lyngbya species. No heterocystous cyanobacteria were isolated throughout the study.     

An investigation on biological stability of product water generated by lab-scale and pilot-scale distillation systems

Material Disposal Area G is the primary low-levelradioactive waste disposal site at Los Alamos NationalLaboratory, New Mexico, and is adjacent to Pueblo of SanIldefonso lands. Pueblo residents and Los Alamos scientists areconcerned about radiological doses resulting from uptake of AreaG radionuclides by mule deer (Odocoileus hemionus) andRocky Mountain elk (Cervus elaphus), then consumption ofdeer and elk meat by humans. Tissue samples were collected fromdeer and elk accidentally killed near Area G and were analyzedfor ³H, ⁹⁰Sr, total U, ²³⁸Pu, ^{239, 240}Pu,²⁴¹Am, and ¹³⁷Cs. These data were used to estimatehuman doses based on meat consumption of 23 kg y^-1. Humandoses were also modeled using RESRAD, and dose rates to deer andelk were estimated with a screening model. Dose estimates tohumans from tissue consumption were 2.9 × 10^-3 mSv y^-1and 1.6 × 10^-3 mSv y^-1 from deer and elk, respectively,and RESRAD dose estimates were of the same order of magnitude. Estimated dose rates to deer and elk were 2.1 × 10^-4 mGyd^-1 and 4.7 × 10^-4 mGy d^-1, respectively. Allestimated doses were significantly less than established exposurelimits or guidelines.     

The Draft of the New German Guideline VDI 3782/8 to Model Automobile Exhaust Dispersion

The draft of the German guideline to calculate automobile exhaust dispersion is explained. It contains a two-stage-system: For first quick estimates the guideline contains the simple models MLuS and STREET. In case these models are not applicable or their results shows concentration levels close to the air quality standards, the more complex models PROKAS_V and MISKAM are recommended. PROKAS_V is a Gaussian plume model, MISKAM is a 3-dimensional microscale non hydrostatic flow model for built-up areas with an Eulerian dispersion model. The guideline comprises cases in rural areas without or with few adjacent buildings as well as urban areas with buildings near the roads. The contribution gives information about the models, typical results and some of the problems showing up presently.     

Hydrocarbon Utilization in Yeast Isolates Found to Grow in Association with Petroleum in a Polluted Ultisol of Midwestern Nigeria

The population counts of hydrocarbon-utilising yeasts weremonitored at six sampling stations in the Benin City municipalarea over a four-week period. Although the population countswere relatively constant in each locality, the highest countsoccurred in areas heavily polluted by domestic and industrialeffluents. A total of thirty-five hydrocarbon-degrading yeastswere isolated from soil at the sampling stations usingn-hexadecane as sole carbon source. The isolates were identifiedas belonging to the genera Candida (27 strains), Endomycopsis (4 strains). All the organisms grew on long-chainn-alkane, kerosene, diesel oil and crude oil but failed to growon short-chain n-alkane, aromatic and alicyclic hydrocarbons.Measurement of growth attributes of the isolates usingn-hexadecane, diesel oil and crude oil as substrates showed thatthe Candida species were better utilizers of hydrocarbonsubstrates relative to Endomycopsis and Schizosaccharomyces species.     

Hydrologic–Economic Model for Managing Irrigation Intensity in Irrigation Areas under Watertable and Soil Salinity Targets

This paper gives mathematical details and sample applications of SWAGMAN Farm (SWAGMAN, Salt Water and Groundwater Management), a farm-scale hydrologic economic model that integrates agronomic, climatic, irrigation, hydrogeological and economic aspects of irrigated agriculture. The model is capable of determining optimum mix of land use to keep watertable and soil salinity within acceptable limits while maximising the economic returns. Alternatively, the model can simulate water and salt balance and economics of a given cropping preference. Web-based and Geographic Information Systems versions of the model are available for integration with the environmental reporting systems of the irrigation areas.