Suspended Particulate Matter Distribution in Rural-Industrial Satna and in Urban-Industrial South Delhi

An air quality sampling program was designed and implemented to collect the baseline concentrations of respirable suspended particulates (RSP = PM₁₀), non-respirable suspended particulates (NRSP) and fine suspended particulates (FSP = PM_2.5). Over a three-week period, a 24-h average concentrations were calculated from the samples collected at an industrial site in Southern Delhi and compared to datasets collected in Satna by Envirotech Limited, Okhla, Delhi in order to establish the characteristic difference in emission patterns. PM_2.5, PM₁₀, and total suspended particulates (TSP) concentrations at Satna were 20.5 ± 6.0, 102.1 ± 41.1, and 387.6 ± 222.4 μg m⁻³ and at Delhi were 126.7 ± 28.6, 268.6 ± 39.1, and 687.7 ± 117.4 μg m⁻³. Values at Delhi were well above the standard limit for 24-h PM_2.5 United States National Ambient Air Quality Standards (USNAAQS; 65 μg m⁻³), while values at Satna were under the standard limit. Results were compared with various worldwide studies. These comparisons suggest an immediate need for the promulgation of new PM_2.5 standards. The position of PM₁₀ in Delhi is drastic and needs an immediate attention. PM₁₀ levels at Delhi were also well above the standard limit for 24-h PM₁₀ National Ambient Air Quality Standards (NAAQS; 150 μg m⁻³), while levels at Satna remained under the standard limit. PM_2.5/PM₁₀ values were also calculated to determine PM_2.5 contribution. At Satna, PM_2.5 contribution to PM₁₀ was only 20% compared to 47% in Delhi. TSP values at Delhi were well above, while TSP values at Satna were under, the standard limit for 24-h TSP NAAQS (500 μg m⁻³). At Satna, the PM₁₀ contribution to TSP was only 26% compared to 39% in Delhi. The correlation between PM₁₀, PM_2.5, and TSP were also calculated in order to gain an insight to their sources. Both in Satna and in Delhi, none of the sources was dominant a varied pattern of emissions was obtained, showing the presence of heterogeneous emission density and that nonrespirable suspended particulate (NRSP) formed the greatest part of the particulate load.     

Spatial & temporal variations of PM10 and particle number concentrations in urban air

The size of particles in urban air varies over four orders of magnitude (from 0.001 μm to 10 μm in diameter). In many cities only particle mass concentrations (PM10, i.e. particles <10 μm diameter) is measured. In this paper we analyze how differences in emissions, background concentrations and meteorology affect the temporal and spatial distribution of PM10 and total particle number concentrations (PNC) based on measurements and dispersion modeling in Stockholm, Sweden. PNC at densely trafficked kerbside locations are dominated by ultrafine particles (<0.1 μm diameter) due to vehicle exhaust emissions as verified by high correlation with NOx. But PNC contribute only marginally to PM10, due to the small size of exhaust particles. Instead wear of the road surface is an important factor for the highest PM10 concentrations observed. In Stockholm, road wear increases drastically due to the use of studded tires and traction sand on streets during winter; up to 90% of the locally emitted PM10 may be due to road abrasion. PM10 emissions and concentrations, but not PNC, at kerbside are controlled by road moisture. Annual mean urban background PM10 levels are relatively uniformly distributed over the city, due to the importance of long range transport. For PNC local sources often dominate the concentrations resulting in large temporal and spatial gradients in the concentrations. Despite these differences in the origin of PM10 and PNC, the spatial gradients of annual mean concentrations due to local sources are of equal magnitude due to the common source, namely traffic. Thus, people in different areas experiencing a factor of 2 different annual PM10 exposure due to local sources will also experience a factor of 2 different exposure in terms of PNC. This implies that health impact studies based solely on spatial differences in annual exposure to PM10 may not separate differences in health effects due to ultrafine and coarse particles. On the other hand, health effect assessments based on time series exposure analysis of PM10 and PNC, should be able to observe differences in health effects of ultrafine particles versus coarse particles.     

中国煤电和核电的环境影响与健康风险比较

将煤电与核电的环境影响和健康风险从全燃料链角度进行比较 ,结果表明 ,煤电燃料链的环境影响和健康风险比核电燃料链大。     

生态环境监理——天津市大港区的探索

环境保护包括污染防治和生态保护两大方面 ,目前 ,在污染源治理取得明显效果 ,生态环境遭受不同程度破坏的情况下 ,实施生态环境监理势在必行。大港区环保局就生态环境监理开展了探索性的工作。     

成都市城市环境与经济协调发展分析

从城市环境与经济发展的协调度方面分析了成都市１９９０－１９９７年间协调度的变化趋势,评估了成都市城市环境与经济协调发展的类型,得出了成都市属于总体协调发展类环境滞后型的结论。     

松嫩盆地资源环境信息系统空间数据库的设计与开发

文章介绍了松嫩盆地资源环境信息系统空间数据库的设计思路,总体目标、构成及功能以及系统建立的关键技术。该系统的建立,使得对松嫩盆地资源开发管理和相关信息的查询、检索更方便,同时对松嫩盆地资源合理开发利用和管理决策提供了科学依据。     

电磁环境对采后芒果的生理影响

系统研究了采后芒果在静电场,磁场,放电生成气环境下的生理变化。测试了呼吸速率,果体与果皮电解质渗出率,商品果率与病情指数等生理指标。研究结果表明,采后芒果在呼吸速率达到高峰之前电磁环境对其均有明显的作用,而在呼吸高峰之后,无明显影响。在我们设置的电磁环境参数中有几项显示保鲜作用。表１参６     

肥料投入水平与养分资源高效利用的关系

提高资源利用效率是实现农业可持续发展目标的核心,本文以山东省和全国作物施肥现状研究为基础,探讨了肥料投入与养分资源效率及环境风险的关系。从区域、农户和 吨粮田不同层次上的分析表明,高投入下可以实现高效率,关键是提高综合管理的科学水平;经济作物生产中存在经济效益和资源效率分离的现象,生产者受经济利益驱动,大量投入肥料,由此会带来极低的资源效率和巨大的环境风险;在注意经济发达地区高化肥投入带来的环境问题的同时,还需要关注发展高经济价值作物带来的低资源效率和高环境风险。     

资源和环境的存在价值的经济学基础

资源与环境的存在价值为独立与人们对资源的现期使用的价值。在资源,环境的代际问题中,存在价值会成为重要的决策参数。本文对存在价值的同予以分陈、归纳,并以反映其特点的结构进行表述;其次对存在价值与其它类别的价值尤其是期权价值,准期作出区分。     

日本水环境质量监测管理概述

伴随着日本经济的高速发展,其水环境污染问题十分严峻,防治水污染成为日本政府在20—21世纪的重要工作之一。经过几十年的努力,日本水污染治理取得长足进展。目前日本水环境监测已经形成由水和土壤等方面组成的水循环监测体系,包括地表水、近海、湖泊、地下水和土壤等。在日本的重要环保法律法规中均有涉及水环境监测工作内容的明确法律条文,国家行政机关、地方政府和公立的科研单位在具体实施水环境质量监测过程中的职责和义务不同,水环境质量监测管理的国家行政机关以环境省为主,地方政府根据环境省制定的水环境质量标准、监测技术方法及规范,制定所辖地域的监测方案并实施监测,公立的环境科研机构在环境质量监测工作中起到重要的支撑作用。笔者概述了日本开展水环境质量监测的法律依据和监测管理情况等。