城市钢厂大气颗粒物环境风险预警方法探索

有效的环境预警体系对城市钢厂的可持续发展至关重要。大气颗粒物是钢铁生产中排放的主要污染物之一,具有排放源数量大、点源面源共存、无组织排放量占比高等特点。以南方某钢铁集团的烧结厂区域为例,使用BP人工神经网络模型,研究城市钢厂的大气颗粒物风险预警方法。模型使用背景值、气象参数、生产参数作为输入层,颗粒物浓度为输出层进行训练。结果显示,训练集和测试集的相关系数R分别为0.996 4和0.995 8,大部分样本的颗粒物浓度预测值误差在±5μg/m~3范围内,BP网络模型的预测精度较高。     

石化企业无组织排放源强核算方法综述

石化企业的无组织排放源众多,排放量计算方法各异,源强的确定一直是石化企业环境影响评价和项目设计中的重点与难点。本文从认识石化企业的无组织排放出发,着重讨论了各类无组织排放的产生节点,并进一步分析了石化企业的无组织排放源强的核算方法的特点与适用性,可为石化企业设计者和环评工作者提供一定的参考。     

国内外工业源颗粒物无组织排放控制标准研究

工业企业颗粒物无组织排放是环境空气中颗粒物的主要来源之一。长期以来,由于我国工业生产粗放型发展,环境管理不够精细,企业重视程度不够,从而导致颗粒物无组织排放问题越发突出,严重影响了我国大气环境质量的根本改善。工业源颗粒物无组织排放控制标准是我国大气污染物排放标准体系的重要组成部分,亦是颗粒物无组织排放管理和执法监管的重要技术依据。了解国内外当前工业源颗粒物无组织排放控制标准的发展现状、体系特点及存在的问题,有助于科学指导我国工业源颗粒物无组织排放控制标准的制定。本文系统研究了中国、美国、德国和日本的工业源颗粒物无组织排放控制法规及标准,通过对比分析,指出了我国工业源颗粒物无组织排放控制标准存在的问题,并提出完善标准的建议,为优化我国现行大气污染物排放标准体系、深化颗粒物污染防治和管理提供参考依据。     

储罐VOCs源强核算参数合理性分析

源强核算是环保部门实施污染控制、企业申请排污许可的重要依据,如何准确识别核算公式中的关键参数,提高核算结果的准确性一直备受关注。基于生态环境部推荐使用的《石化行业VOCs污染源排查工 作指南》方法,在对公式参数进行分类的基础上,重点对反映罐体结构和特点、反映外界条件和油品特性、变化范围较大的参数进行敏感性分析,在参数变化范围为20％时,确定VOCs源强核算敏感性参数和该参数对排放 量的影响程度分别为年周转量（7.35％）、油罐壁油垢因子（7.35％）、有风边缘密封损耗因子（4.47％）和零风边 缘密封损耗因子（3.18％）。结合某油库的实际调查和分析结果,对上述参数取值进行合理性分析,确定最佳参数组合,计算求得油库全年VOCs排放量为45.77 t/a,相较参数优化前的242.13 t/a低81.1％。该参数合理性分析方法为油库无组织排放源的调查与核算提供依据,也为企业合规性及排污许可的获取,及后期VOCs排放污染控制对策的制定和实施提供技术支持。     

秦皇岛市农业面源污染特征分析

对2011年秦皇岛市农业污染源进行分析并测算各污染物排放量,结果表明,农业面源COD排放量为38768．27t,NH3-N为7593．71t,TN为15684．63t,TP为7821．18t;昌黎县是秦皇岛市农业面源污染最重的污染区域;农村生活源对COD排放量的贡献率最大,种植业对NH3-N、TN和TP排放量的贡献率最大。     

洁净型煤源强核算方法探究

为准确核算洁净型煤大气污染物的排放浓度及排放量,文章分析了使用实测法、物料衡算法和产/排污系数法三种方法进行洁净型煤源强核算的准确性.选取内蒙古呼和浩特市某城区推广使用的6组方形型煤进行大气污染物排放水平测试,结合煤质数据对比源强核算的方法.研究测定的方形洁净型煤主要大气污染物(PM、SO2、NOx)的排放浓度分别为1...     

成都市污染源VOCs排放与O3污染相关性分析

挥发性有机物(VOCs)是形成细颗粒物(PM_2.5)、臭氧(O₃)等二次污染物的重要前体物,随着工业化和城市化的快速发展,以臭氧为特征的区域性复合型大气污染日益突出,为研究成都市污染源VOCs排放情况,根据成都市最新污染源普查数据,我们针对成都市工业源、农业源、移动源和生活源,采用监测数据法和系数法核算了成都市VOCs排放量,行业分布、地区分布,并结合各地区大气臭氧污染情况进行了相关性分析。经过统计分析,工业源和移动源为成都市主要VOCs排放源,工业源VOCs排放量位居前3位的行业分别为家具制造业、石油、煤炭及其他燃料加工业及印刷和记录媒介复制业,VOCs原辅材料使用量及VOCs排放量最多的是胶黏剂,移动源VOCs排放主要为机动车排放。成都市各地区VOCs排放量及臭氧年均值空间分布整体表现为西北高东南低,22个区(市)县VOCs排放量与大气臭氧日均值超标率正相关,15个区(市)县呈现出明显相关性,指数曲线较线性拟合程度较好,存在非线性关系。7个区(市)县VOCs排放与大气臭氧日均值超标率拟合程度较差,呈现出较弱的相关性。     

防治新的污染源——农村面源污染

【案情】 2002年湖北省被列为全国8个农业面源污染高风险地区之一,农村面源污染成为威胁农村地区环境的主要因素。2007年,湖北农村主要污染物的排放量已超过全省工业污染排放总量,仅占全省国民生产总值16％的农村地区排放了超过全省50％以上污染物。全省化肥施用量是全国平均水平的2．13倍,     

社河流域污染物来源解析及对策分析

对社河流域水质进行现状评价,确定其主要污染物;利用经验系数法及环境统计数据,从生活源、畜禽养殖源、农田源、工业源等方面,分析社河流域污染物来源及排放强度.结果表明,面源污染是社河流域污染负荷的主要来源,2015年面源污染中畜禽养殖占比最大,但占比在不断减少;其次是农村生活源与农田排放源,占比逐渐增加.     

大气颗粒物源解析技术

由南开大学环境科学与工程学院开发、天津市环境保护局推荐的大气颗粒物源解析技术适用于国内各级政府、环保管理、科研、监测部门。主要技术内容一、基本原理通过测定和研究颗粒物排放源和环境空气受体中颗粒物的物理和化学特性,从而确定对受体有贡献的源类,以及各源类对受体颗粒物化学组成成分谱的贡献值和分担率。二、技术关键颗粒物源样品的采集技术;共线性排放源类识别方法和解决共线性源类不能同时纳入模型计算的问题;CMB数据模型结果的不确定性问题。效益分析通过源解析研究工作,定量给出各颗粒物排放源类对环境受体的贡献,并据此…     

Seasonal variation of atmospheric polycyclic aromatic hydrocarbons along the Kaohsiung coast

Thirty-three air samples were collected by high-volume samplers from May 2007 to June 2008 in the coastal area of southwest Taiwan and analyzed for total suspended particulates (TSP) and polycyclic aromatic hydrocarbons (PAHs). Concentrations of TSP and total PAHs ranged from 40.4 to 251 μg m(-3) and 1.86-56.4 ng m(-3), respectively. Except for joss paper burning during the religious celebration of Ghost Month, which resulted in the highest concentration of PAHs in the summer of 2007, a seasonal variation in total PAH concentration was observed over this study period, with the highest concentrations in winter and the lowest in summer. Because of the geographical and climatic characteristics of the sampling site, monsoon activities modulate the seasonal variations of PAHs. Diagnostic ratios showed that PAHs in the atmosphere of the Kaohsiung coastal area arose predominantly from vehicle emissions (mainly from diesel exhaust), joss paper burning, and coal/wood combustion. The results of hierarchical cluster analysis (HCA) and principal component analysis (PCA) indicated that the sampling days could be divided into three groups and that the major source identification of PAHs was the same as the identification by diagnostic ratios. In addition, the results of HCA and PCA suggest that the samples collected with a prevailing northerly or northeasterly wind direction contain both local emissions and those from neighboring sources. On the other hand, the cases related to westerly or northwesterly winds indicated that local emission was the major source for the sampling site.     

Quantifying ammonia emissions from a cattle feedlot using a dispersion model

Livestock manure is a significant source of ammonia (NH3) emissions. In the atmosphere, NH3 is a precursor to the formation of fine aerosols that contribute to poor air quality associated with human health. Other environmental issues result when NH3 is deposited to land and water. Our study documented the quantity of NH3 emitted from a feedlot housing growing beef cattle. The study was conducted between June and October 2006 at a feedlot with a one-time capacity of 22,500 cattle located in southern Alberta, Canada. A backward Lagrangian stochastic (bLS) inverse-dispersion technique was used to calculate NH3 emissions, based on measurements of NH3 concentration (open-path laser) and wind (sonic anemometer) taken above the interior of the feedlot. There was an average of 3146 kg NH3 d(-1) lost from the entire feedlot, equivalent to 84 microg NH3 m(-2) s(-1) or 140 g NH3 head(-1) d(-1). The NH3 emissions correlated with sensible heat flux (r2 = 0.84) and to a lesser extent the wind speed (r2 = 0.56). There was also evidence that rain suppressed the NH3 emission. Quantifying NH3 emission and dispersion from farms is essential to show the impact of farm management on reducing NH3-related environmental issues.     

Effects of Meteorological Parameters on Air Pollutant Concentrations in Elazig,Turkey

In the present study, air pollutant concentrations have been analyzed statistically with meteorological factors in the city of Elazig, which is located in the east Anatolia region of Turkey, for the months of September, October, November, December, January, February, March, and April during the years 2003 and 2004. SPSS code was used for statistical analyses. The relationship between monitored air pollutant concentrations, such as SO₂ and the total suspended particles (TSP) data, and meteorological factors such as wind speed, temperature, relative humidity and pressure was investigated. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elazig. The correlation between the previous day's SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and the coefficient of determination R was found to be 0.80 and 0.76, respectively. The statistical models of SO₂ and TSP, including all of the meteorological parameters, gave an R of 0.50 and 0.40, respectively. Further, in order to develop this model, the previous day's SO₂ and TSP concentrations were added to the equations. The new model for SO₂ and TSP was improved considerably with R = 0.85 and 0.80, respectively.     

西宁市环境空气中TSP和PM10来源解析研究

在西宁市7个采样点分别采集了环境空气中的总悬浮颗粒物(TSP)和可吸入颗粒物(PM10),用化学质量平衡(CMB)受体模型和二重源解析技术解析了TSP和PM10的来源。结果表明:扬尘、煤烟尘和土壤风沙尘是造成该市TSP和PM10污染的主要源类。扬尘是造成该市颗粒物污染的首要因素,控制城市扬尘污染是城市环境空气颗粒物达标的关键。     

深圳大气污染特征模拟及环境容量估算

本文根据深圳市8 个监测站点2013 年的逐日PM₁₀ 和PM_2.5 浓度监测数据、气象数据,统计风向、风速、稳定度联合频率等,利用污染物在大气中输送扩散模式,由实测的浓度值反推出污染物的产生量或排放量的方法,重点分析龙华新区PM₁₀ 和PM_2.5 的污染特征,并依据环境目标值,估算该区域剩余环境容量。研究结果表明,龙华新区全年盛行东风、南风,其风频分别为16.7%、13.2%,风速约为1.6m/s,PM₁₀、PM_2.5 浓度均呈现出季节性变化,秋、冬季浓度值较高,尤其在10 月到次年1 月份,其排放强度主要受本地污染源的影响。除此以外,其西、北部的污染源对其污染物浓度有一定的影响。新区PM₁₀ 和PM_2.5 的剩余环境容量均呈现负值,尤其以PM_2.5 最为突出,须大力加强减排控制,以达到环境目标值     

A novel wind speed forecasting model for wind farms of Northwest China

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon’s Signed-Rank test, and Morgan--Granger--Newbold test tell us that the proposed model is different from the compared models.     

The relationship between greenhouse gas emissions and the intensity of milk production in Ireland

European Union agri-environmental schemes aim to reduce the environmental impact of agricultural production, but were developed before consideration of greenhouse gas emissions from agriculture. Life cycle assessment methodology provided a framework for comparing emissions as kg CO2 equivalent per kg of energy corrected milk (ECM) (kg CO2 kg(-1) ECM yr(-1)) and per hectare (kg CO2 ha(-1) yr(-1)) for farms both within and outside the Irish agri-environmental scheme. The agri-environmental scheme farms operate extensive systems from 40 to 120 cows producing between 3032 and 5946 kg ECM cow(-1) lactation(-1). The cows are fed on grass, conserved silage, and concentrates. Supplementation ranged between 250 and 620 kg cow(-1) yr(-1). The conventional farms had between 30 and 77 milking cows producing 4736 to 6944 kg ECM cow(-1) lactation(-1). Supplementation ranged from 400 to 1000 kg cow(-1) yr(-1). The emissions from each unit were estimated using published emissions factors and possible error was evaluated by using ranges for each factor. Calculated emissions ranged from 0.92 to 1.51 kg CO2 kg(-1) ECM yr(-1) and 5924 to 8323 kg CO2 ha(-1). On average, total emissions from conventional farms were around 18% (p = 0.01) greater than the agri-environmental scheme farms and emissions per hectare (total area required) were 17% greater (p = 0.02) but there was no significant difference (p = 0.335) in terms of emission per unit milk produced. To evaluate greenhouse gas emissions for each farm in terms of the system intensity it was necessary to define a measure of intensification and area per liter of milk produced that was best.     

Design and analysis of artificial bee-colony-based MPPT algorithm for DFIG-based wind energy conversion systems

In this article, the proposed maximum power point tracking (MPPT) method is designed by taking rotor speed as an optimization problem, which is solved by artificial bee colony (ABC) algorithm to generate the maximum power output. The main advantage of this algorithm is that its optimal solution is independent of the initial positions and requirement of lesser number of control parameters, which leads to simple and robust MPPT algorithm than other algorithm. Furthermore, the hill climb search and particle swarm optimization-based MPPT algorithm are also discussed and the results obtained by these are compared to verify the effectiveness of proposed algorithm. Simulations for MPPT control along with doubly fed induction-generator-based wind energy conversion system is carried out in MATLAB/Simulink environment. Three statistical methods are used to evaluate the accuracy of each MPPT algorithm. All results are analyzed and compared under randomly selected wind as well as real wind speed configuration. Comparison of both numerical and simulation results under two different varying wind speed conditions strongly suggest that the proposed ABC-based MPPT algorithm is superior than other two MPPT algorithms.     

Near-field dust exposure from cotton field tilling and harvesting

The frequency and intensities of dust exposures in and near farm fields, which potentially contribute to high intensity human exposure events, are undocumented due to the transient nature of local dust plumes and the difficulties of making accurate concentration measurements. The objective of this study is to measure near-field spatial concentrations of the dust plumes emitted during tilling and harvesting of an irrigated cotton field outside of Las Cruces, NM (soil class: fine-loamy, mixed, superactive, thermic Typic Calciargid). A comparison of remote lidar measurements of plumes emitted from cotton field operations with in situ samplers shows a strong agreement between the two techniques: r2 = 0.79 for total suspended particulates (TSP) and r2 = 0.61 for particulate matter with diameter less than or equal to 10 microm (PM10). Plume movement was dependent on the short-term wind field and atmospheric stability. Horizontal spread rate of the plumes, determined from lidar measured Gaussian dispersion parameters, was less than expected by a factor of 7. Thus, in-plume downwind concentrations were higher than expected. Vertical dispersion was dependent on the rise of "cells" of warm air convecting off the soil surface. On a windy day, discing the field showed TSP and PM10 concentrations at the source itself of up to 176 microg m(-3) and 120 microg m(-3), respectively. These resulted in in-plume peak TSP concentrations of about 1.22 microg m(-3) at 10 m downwind and 0.33 microg m(-3) at 100 m downwind. The measured concentrations highlight a potential exposure risk to people in and around farming operations.     

Location wise comparison of mixture distributions for assessment of wind power potential: A parametric study

Scientific literature discussed various types of mixture models and models derived from maximum entropy principle using short-term wind speed data for their relative assessment. The literature on suitability of these mixture models for long-term data is rarely available. However, for correct assessment of wind power potential both wind speed and wind direction are equally important. Therefore, in this paper, both wind speed and wind direction are simultaneously analyzed using several types of mixture distribution and compared the same with conventional Weibull distribution. For wind speed and wind power density assessment, the mixture distributions such as Weibull--Weibull distribution, Gamma--Weibull distribution, Truncated Normal--Weibull distribution, Truncated Normal--Normal distribution, proposed Truncated Normal--Gamma distribution and Gamma--Gamma distribution along with MEP-distribution are compared with conventional 2-parameter Weibull distribution. Similarly, for wind direction analysis, the finite mixtures of von-Mises distribution are compared with conventional von-Mises distribution. Judgment criteria include R², RMSE, Kolmogorov--Smirnov test and relative percentage error in wind power density. The sites selected are the three onshore locations of India, viz., Calcutta, Trivandrum, and Ahmedabad. The results show that for wind speed assessment, mixture distribution performs better than the conventional Weibull distribution for analyzing wind power density. However, location wise comparison of all mixture distribution is of prime importance. For wind direction analysis, finite mixture of two von-Mises distributions proved to be a suitable candidate for Indian climatology.