全国火电厂二氧化硫污染现状及其控制对策

火电行业飞速发展的同时引发了二氧化硫的大量排放。文章在总结全国火电厂二氧化硫排放现状的基础上提出,火电厂二氧化硫是全国二氧化硫排放大户,其排放量占全国工业二氧化硫排放量的42%,且有逐年递增的趋势,而其去除率却一直保持一个较低的水平;大型火电厂又是电厂中二氧化硫的排放大户,且主要集中在广东、江苏、河北、山东、河南等几个省,这几个省应成为火电厂二氧化硫排放的重点监控对象。文章最后提出了电厂减排二氧化硫的几点对策和建议。     

二氧化硫实测结果与计算结果的比较

20 0 0年底 ,江苏省所有工业企业必须实现二氧化硫达标排放。我国现行的锅炉、窑炉以及火电厂、水泥厂等行业的大气污染物排放标准中均对二氧化硫排放浓度有所要求 ;总量控制管理模式提出以后 ,环境管理又对二氧化硫排放总量提出了要求。要想了解一个单位全年的二氧化硫排放总量 ,仅用瞬时测试结果还远远不够 ,必须依靠在线自动监测系统 ,然而我国目前还不具备这种能力。但管理部门和监测部门可根据某单位的燃煤情况 ,粗略判断其排放是否达标 ,也可据此核定排放总量。1　二氧化硫排放量和排放浓度的计算二氧化硫排放浓度与锅炉运行负荷 (α…     

浅析火电厂脱硫脱硝技术与应用

火电厂运行的过程中,容易造成空气污染,增加了环境保护的压力。近几年,我国在火电厂内采用烟气脱硫、脱硝技术,用于降低排放烟气中二氧化硫、氮氧化物的含量,改善排放烟气的污染状况。烟气脱硫、脱硝技术在火电厂烟气治理中发挥重要的作用,有利于减轻排放烟气造成的污染。因此,文章以火电厂为研究背景,分析烟气脱硫、脱硝技术的应用。     

火电厂执行大气污染物排放新标准的达标研究

新标准《火电厂大气污染物排放标准》(GB 13223—2011)中现役机组排放限值于2014年7月1日正式执行,与旧标准《火电厂大气污染物排放标准》(GB 13223—2003)相比排放限值大幅趋严,且增加了燃煤电厂汞排放限值。选取具有代表性的电厂锅炉进行手工和在线监测,结果表明,燃煤机组需有高效除尘器和脱硝设施才可稳定达标;燃油机组无法达到标准限值要求,未来应逐步淘汰或改用清洁能源;天然气机组二氧化硫和氮氧化物可以达到该标准要求。建议对燃煤电厂锅炉低负荷下脱硝设施的运行、低浓度下烟尘测定的准确性以及汞排放监测进一步研究。     

大气污染源低浓度二氧化硫监测方法比较

燃煤电厂烟气脱硫大多采用湿法脱硫原理,导致脱硫尾部烟气排放温度低、湿度高、二氧化硫浓度低,现有的二氧化硫监测采样系统和仪器无法准确测定其排放浓度。通过对不同方法和仪器的对比实验,确定了适合在低温、高湿、低二氧化硫排气情况下的采样分析方法。     

美欲控制火电厂碳排放 将鼓励企业使用清洁技术

人民网消息奥巴马政府近日表示,他们要与新国会在气候变化问题上进行斗争,对火电厂排放的温室气体进行监管。美国环保局表示,他们会为火电厂和炼油厂设定相关标准。火电厂和炼油厂的温室气体排放占美国总排放量的40%左右。美国环保局是在＂总量控制和排污交易＂计划在参议院中夭折后做出这一决定的。美国环保局还表示,     

火电厂烟气自动化监测系统的比对监测

介绍了火电厂烟气自动化在线监控系统按照《固定污染源烟气连续监测系统技术要求及检测方法》(HJ/T 76-2001),以及《固定污染源排气中颗粒物测定与气态污染物采样方法》(GB/T 16157-1996)和《固定污染源排气中二氧化硫的测定定电位电解法》(HJ/T 57-2000)对大气污染物中颗粒物、二氧化硫和流速进行了比对监测,结果表明,颗粒物、二氧化硫和流速的测定结果均符合规定要求.     

“十一五”新疆火电行业二氧化硫减排潜力分析

污染减排是落实科学发展观、促进经济又好又快发展的重要举措，但随着今后新疆经济的强力复苏以及新一轮战略的转型，大型煤电、煤化工、石油化工等工业基地的建成，新疆二氧化硫新增排放量势必会显著增加，尤其是火力发电行业二氧化硫排放增长更为迅猛，对新疆总量控制来讲，面临的形势也就更为严峻。本文就新疆火力发电行业二氧化硫排放的现状，结合今后火力发电的增长趋势，对火力发电行业二氧化硫的减排潜力进行分析。     

仪化热电厂周围地区二氧化硫浓度分布规律的研究

通过对仪征化纤厂热电厂现有污染源二氧化硫排放情况、周围地区二氧化硫分布规律、变化规律的调查及浓度的监测分析，并在此基础上做了该厂二氧化硫对环境影响的预测评价。结果表明，周围地区的二氧化硫浓度分布符合国家大气环境质量二级标准。     

大型火电机组二氧化硫排放规律研究

选取35台装机容量30万千瓦以上大型火电机组,进行了为期2年的监测。总结出大型火电机组二氧化硫排放规律,对大型火电机组燃煤含硫量、脱硫设施脱硫效率和二氧化硫排放浓度三者间的关系进行了统计分析,建立了线性回归方程,进而对燃用不同含硫量燃煤的火电机组执行不同排放标准时,配套脱硫设施需要达到的脱硫效率进行了预测。     

Decadal emission estimates of carbon dioxide,sulfur dioxide,and nitric oxide emissions from coal burning in electric power generation plants in India

This study aims to estimate the emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitric oxide (NO) for coal combustion in thermal power plants in India using plant-specific emission factors during the period of 2001/02 to 2009/10. The mass emission factors have been theoretically calculated using the basic principles of combustion under representative prevailing operating conditions in the plants and fuel composition. The results show that from 2001/02 to 2009/10 period, total CO₂ emissions have increased from 324 to 499 Mt/year; SO₂ emissions have increased from 2,519 to 3,840 kt/year; and NO emissions have increased from 948 to 1,539 kt/year from the Indian coal-fired power plants. National average emissions per unit of electricity from the power plants do not show a noticeable improvement during this period. Emission efficiencies for new plants that use improved technology are found to be better than those of old plants. As per these estimates, the national average of CO₂ emissions per unit of electricity varies between 0.91 and 0.95 kg/kWh while SO₂ and NO emissions vary in the range of 6.9 to 7.3 and 2.8 to 2.9 g/kWh, respectively. Yamunagar plant in Haryana state showed the highest emission efficiencies with CO₂ emissions as 0.58 kg/kWh, SO₂ emissions as 3.87 g/kWh, and NO emissions as 1.78 g/kWh, while the Faridabad plant has the lowest emission efficiencies with CO₂ emissions as 1.5 kg/kWh, SO₂ emissions as 10.56 g/kWh, and NO emissions as 4.85 g/kWh. Emission values at other plants vary between the values of these two plants.     

Gaseous and particulate emissions from thermal power plants operating on different technologies

This paper presents the assessment of gaseous and particulate emissions from thermal power plants operating on different combustion technologies. Four thermal power plants operating on heavy furnace oil were selected for the study, among which three were based on diesel engine technology, while the fourth plant was based on oil-fired steam turbine technology. The stack emissions were monitored for critical air pollutants carbon monoxide, carbon dioxide, oxides of nitrogen, sulfur dioxide, particulate matter, lead, and mercury. The pollutant emissions were measured at optimum load conditions for a period of 6 months with an interval of 1 month. The results of stack emissions were compared with National Environmental Quality Standards of Pakistan and World Bank guidelines for thermal power plants, and few parameters were found higher than the permissible limits of emissions. It was observed that the emissions carbon monoxide, oxides of nitrogen, and particulate matters from diesel engine-based power plants were comparatively higher than the turbine-based power plants. The emissions of sulfur dioxide were high in all the plants, even the plants with different technologies, which was mainly due to high sulfur contents in fuel.     

南京某燃煤电厂汞的排放特点及分布特征

选择南京某燃煤电厂330 MW机组，对煤、炉渣、粉煤灰、烟尘、石灰石、石膏和烟气中的汞取样测量，探讨煤中汞在燃烧过程中的变化情况，并进一步分析汞的排放特点及分布特征。指出，煤经燃煤锅炉炉内高温燃烧后，炉渣中的汞对环境影响不明显；粉煤灰、烟尘中的汞存在富集现象，且随着粒径变细，富集程度加剧；燃煤锅炉燃烧后，随石膏排放的汞占比较大，应采取相应的防治措施。     

Environmental impact of electricity relocation: A quasi-natural experiment from interregional electricity transmission

Pollutants such as sulfur would concentrate in the source regions and thus the localized impacts are more obvious. Local balance of electricity by transporting coal has resulted in dense concentration of coal-fired power plants in load centers and caused severe environmental problems. Electricity relocation through interregional transmission is another choice for energy transportation to achieve electricity balance across regions and pollution mitigation. Using interregional electricity transmission (IRET) lines in China as a quasi-natural experiment, this paper assesses the environmental impact of electricity relocation. In the assessment, the grid organization of “province as executor” in China is considered because it affects the sphere of IRET's influence on pollution mitigation. Here we show the environmental benefits of electricity relocation. We find that, electricity relocation through interregional transmission leads to the growth rate of sulfur dioxide (SO₂) emission decreasing 7% in landing areas and Sichuan province benefits most from electricity relocation. It is interesting that there is no significant increase of SO₂ emission growth rate in sending areas compared to counterfactuals if there had no IRET due to more integration of clean energy and improved emission efficiency in sending areas. Placebo study and robustness check show that the results are quite convincing. Therefore, IRET provides an appealing choice for China's environmental control in eastern region, and it is not necessarily at the cost of pollution in western region. The methodology can be applied to assess the environmental impacts of other program or policy elsewhere.     

Atmospheric haze: Its sources and effects on visibility in rural areas of the continental United States

Spatial and temporal trends in visibility are examined at a national level. It is shown that visibility is impaired in all antional parks approximately 90% of the time, and that eastern visibilities are about 10 times lower than western visibilities. Measurement of atmospheric particulates that affect visibility shows that sulfates associated with man-made emissions of sulfur dioxide are the single largest contributor to visibility reduction, except in the northwestern United States, where organic aerosols contribute significantly. In the East, coal fired power plants along the Ohio River Vallery contribute the most SO₂, while oil refining activities and other industrial sources in southern California, copper smelters in southern Arizona, and industrial activity along the Gulf Coast of Mexico contribute most of the SO₂, and thus sulfates, in the West.Contribution from Fourth World Wilderness Congress-Acid Rain Symposium, Denver (Estes Park), Colorado, September 11–18, 1987.The assumptions, findings, conclusions, judgments and views presented herein are those of the authors and should not be interpreted as necessarily representing official National Park Service policies.     

燃用蔗髓锅炉的硫平衡及二氧化硫排放分析

通过现场监测和调研数据,分析燃用蔗髓锅炉的硫平衡及SO 2排放情况。结果显示,烟气排放的SO 2主要来源于鲜蔗和回用洗布水中含有的硫。8个锅炉硫排放在线监测均值与手工监测均值相对偏差为3.76%~14.9%,表明结果一致性较好。蔗髓硫质量分数为0.01%~0.04%,蔗髓含硫折算后的SO 2值和在线监测SO 2值分别为22.1 mg/m 3~49.9 mg/m 3和43.9 mg/m 3~114.5 mg/m 3,说明鲜蔗和制糖工艺流程的共同影响使得燃用蔗髓锅炉排放烟气SO 2值偏高。     

阿图什市不同类型的炉灶及能源消耗现状调查评价

对不同类型的炉灶煤耗及污染物的排放量进行了定量计算,在大量的统计资料及监测数据的基础上,分析阿图什市各类型炉灶燃煤及污染物排放的情况,并通过定量计算进行了探讨,提出相关的对策和建议.     

An Integrated Assessment by Models for Energy Systems Analysis and Life-Cycle Assessment with a Case Study of Advanced Fossil-Fired Power Plants in China

We developed an integrated assessment (IA) using models for energy systems analysis and life-cycle assessment (LCA). Based on this assessment framework, we developed cost-benefit analysis (CBA) case studies for a hypothetical project designed to introduce advanced fossil-fired power generation technologies in China. Our MARKAL model for Japan confirmed that radical reductions (i.e., 80 % by 2050) of carbon dioxide (CO₂) could be attained from energy systems alone and that credit for emission allowances was required. We evaluated life-cycle costs and emissions of carbon dioxide, sulfur oxide, and nitrogen oxide gases for the energy technologies using an LCA model. Further, we applied a power generation planning model for six Chinese grids to provide a power mix structure, potentially producing credit by installing fossil-fired power generation technology and by using baseline grid emission factors with an average cost of electricity. Finally, by using dynamic emission reductions and additional costs from the two models, we conducted case studies of CBA for a hypothetical project to install the technologies in China. This was accomplished by evaluating emission reductions in monetary terms and by applying a life-cycle impact assessment model. A unique feature of our IA is its dynamic (time-varying) assessment of costs and benefits.