ISTT推出了一個(gè)新的網(wǎng)絡(luò)研討會(huì)系列（僅面向會(huì)員），首次演講由美國(guó)路易斯安那標(biāo)準(zhǔn)大學(xué)非開(kāi)挖技術(shù)中心主任John C. Matthews博士于2020年11月18日美國(guó)東部標(biāo)準(zhǔn)時(shí)間上午
9:00進(jìn)行（
北京時(shí)間：11月18日晚上10:00）。該網(wǎng)絡(luò)研討會(huì)將介紹蒸汽固化對(duì)環(huán)境的潛在影響的最新研究結(jié)果。此網(wǎng)絡(luò)研討會(huì)僅對(duì)
CSTT會(huì)員開(kāi)放，會(huì)議視頻軟件為ZOOM。需要參加的此研討會(huì)的請(qǐng)聯(lián)系CSTT外事專(zhuān)員：Leon Xu (E-mail: leonxu@fastmail.com; ittc@cstt.org; 微信號(hào): leon_tsui)
ISTT Educational Webinar Series
First of a series to begin 18 November 2020; 09:00 - 10:00 am US Eastern Standard Time (14:00 GMT)
ISTT has launched a new webinar series (
dedicated to only members), with the first presentation given by Dr. John C. Matthews, Director, Trenchless Technology Center, Louisiana Tech University on 18 November 2020 at 09:00 am US Eastern Standard Time (14:00 GMT).
Please note that the time has now changed to 09:00 EST (14:00 GMT) due to the daylight saving time effective on Sunday, 01 November .
This webinar was organized by the ISTT Technology and Education Committee. ISTT plans more webinars in the coming months as our usual face-to-face meetings are on hold.
Environmental Impact Assessment of Steam-Cured CIPP
This webinar will present findings from a recent study of the potential environmental impacts of steam-cured cured-in-place pipe (CIPP) installations. This comprehensive study collected real data from multiple projects using various sampling methods to determine the extent of any impacts. The objectives of the study were to both evaluate air emissions from steam-cured CIPP and determine potential impacts on workers. This was accomplished by directly measuring worker exposure to emissions for locations onsite or offsite. The installation sites represented a range of scenarios typical of CIPP installations. Dispersion of the emissions was modeled to estimate compound concentrations for a large set of scenarios and weather conditions. The potential health risks were evaluated based on appropriate health-based action levels using the measured and modeled data.
