日韩麻豆国产精品欧美_久久精品视频免费_亚洲欧美另类精品久久久_日本国产成人久久精品

近日，一項(xiàng)利用移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)估算城市碳排放和空氣污染水平的研究新近出爐，據(jù)說(shuō)此法可以大大降低實(shí)施《巴黎協(xié)議》的成本。

　　•該研究針對(duì)來(lái)自移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)的移動(dòng)模式進(jìn)行分析，用以對(duì)城市應(yīng)用的不同交通運(yùn)輸模式進(jìn)行評(píng)估，以此對(duì)相應(yīng)的污染情況和污染成因進(jìn)行總結(jié)。

　　•這種創(chuàng)新的方法可使科學(xué)家在估算城市地區(qū)空氣污染物濃度時(shí)的準(zhǔn)確率達(dá)到77%。

　　•此法可以擴(kuò)展延伸，效率高且成本低，有助于世界各地的城市進(jìn)一步了解并治理溫室氣體（GHG）排放。

　　大數(shù)據(jù)分析公司和蘇黎世聯(lián)邦理工大學(xué)帶領(lǐng)Teralytics公司、Next電信公司以及可持續(xù)發(fā)展解決方案提供商南極集團(tuán)在德國(guó)的紐倫堡進(jìn)行了一項(xiàng)研究，研究發(fā)現(xiàn)，移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)分析可以作為一種有效又省錢(qián)的二氧化碳和氮氧化合物估算方法。為此，Teralytics對(duì)用戶(hù)通過(guò)手機(jī)接打電話(huà)、收發(fā)短信息和瀏覽網(wǎng)頁(yè)生成的電信數(shù)據(jù)進(jìn)行了匿名收集與研究，借以完善原始數(shù)據(jù)，通過(guò)人的移動(dòng)模式去分析其經(jīng)常乘坐的不同交通工具，如火車(chē)或汽車(chē)等。將這些信息與不同運(yùn)輸模式的排放量數(shù)據(jù)結(jié)合在一起，他們就能估計(jì)出城市空氣污染和溫室氣體的排放量

圖一：Teralytics公司和Next電信公司在德國(guó)有多個(gè)涉及到消費(fèi)者數(shù)據(jù)的項(xiàng)目。出于社會(huì)和經(jīng)濟(jì)利益將數(shù)據(jù)加以應(yīng)用，可以利用科學(xué)加快氣候保護(hù)的步伐。

　　因?yàn)槊糠N形式的運(yùn)輸方式所產(chǎn)生的二氧化碳和氮氧化物排放量是唯一的，所以對(duì)城市運(yùn)輸模式的了解是弄清排放源的重要方式。在紐倫堡進(jìn)行的研究表明，利用這些信息對(duì)城市空氣污染物濃度進(jìn)行估算，其精確率可高達(dá)77%。這些發(fā)現(xiàn)，為進(jìn)一步研究大數(shù)據(jù)用于理解和最終解決環(huán)境問(wèn)題（如世界各地城市中空氣污染情況）帶來(lái)了希望。尤其重要的是，較之制作精良、需要精心維護(hù)的測(cè)量站，分析和解讀數(shù)據(jù)的成本是非常低廉的。因此，這種新方法可以推廣為全國(guó)范圍內(nèi)的數(shù)據(jù)分析。

　　“雖然我們現(xiàn)在的城市生活方式導(dǎo)致了有害溫室氣體的產(chǎn)生，但同時(shí)也產(chǎn)生了大量的行為數(shù)據(jù)。我們?cè)赥eralytics的使命就是利用這些數(shù)據(jù)造福社會(huì)，” Teralytics的首席執(zhí)行官喬治.博爾茨指出，“我們從紐倫堡的調(diào)查結(jié)果顯示，這些數(shù)據(jù)可以讓城市規(guī)劃者看到人類(lèi)流動(dòng)是如何產(chǎn)生污染的。這是有效設(shè)計(jì)和實(shí)施清潔空氣及低碳戰(zhàn)略的重要組成部分。我們期待著對(duì)此能有進(jìn)一步的研究發(fā)現(xiàn)。”

　　采用三重流程，匿名匯總來(lái)的數(shù)據(jù)首先會(huì)被Teralytics的數(shù)據(jù)科學(xué)家轉(zhuǎn)化為運(yùn)動(dòng)流，并在所需分析的時(shí)間段內(nèi)，被識(shí)別成120萬(wàn)條交通路線(xiàn)，如圖2所示。然后，可持續(xù)發(fā)展解決方案專(zhuān)家南極集團(tuán)將根據(jù)德國(guó)聯(lián)邦環(huán)境部提供的關(guān)于不同交通工具排放量水平的數(shù)據(jù)，利用大氣模型來(lái)估計(jì)不同運(yùn)輸方式所造成的空氣污染水平。在第三個(gè)步驟中，還將對(duì)從空氣污染測(cè)量站得到的現(xiàn)有數(shù)據(jù)與該方法得到的數(shù)據(jù)進(jìn)行對(duì)比分析，以此確認(rèn)新方法的精準(zhǔn)度情況。經(jīng)此發(fā)現(xiàn)，測(cè)量值精準(zhǔn)率的關(guān)聯(lián)度高達(dá)77%左右。

圖二：紐倫堡郵編區(qū)域內(nèi)的交通流歷史數(shù)據(jù)。

　　紐倫堡試點(diǎn)研究的結(jié)果為進(jìn)一步研究構(gòu)成了良好的基礎(chǔ)。繼此成功之后，該項(xiàng)目還從氣候KIC的低碳城市實(shí)驗(yàn)室得到金融支持，將各大城市、企業(yè)、學(xué)術(shù)界和非政府組織召集在一起，共同提高環(huán)境和社會(huì)影響。有了這些支撐，研究伙伴們可以進(jìn)一步將方法進(jìn)行完善，聚焦于短途旅行路線(xiàn)，并將局部地區(qū)的排放因素，如機(jī)場(chǎng)、大型活動(dòng)場(chǎng)所和各類(lèi)道路車(chē)輛（電動(dòng)汽車(chē)和越野車(chē)）等考慮在內(nèi)。

　　此外，交通堵塞和紅燈等因素的影響將被將考慮在內(nèi)，以便更準(zhǔn)確地估算出一個(gè)城市的空氣污染水平。

“這項(xiàng)試驗(yàn)的研究結(jié)果超過(guò)了我們的預(yù)期，” Teralytics的業(yè)務(wù)發(fā)展與合作伙伴關(guān)系維護(hù)專(zhuān)員馬克西米連.格羅斯說(shuō)到 “我們有信心將此產(chǎn)品快速擴(kuò)展到世界各地，支持城市規(guī)劃者們凈化空氣，并且以最低的成本實(shí)現(xiàn)巴黎協(xié)議的目標(biāo)。”

　　除此研究之外，Teralytics公司、德國(guó)電信和弗朗霍夫研究學(xué)會(huì)針對(duì)移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)的應(yīng)用研究也取得了相關(guān)成果，其中包括斯圖加特交通方面的智能數(shù)據(jù)分析。

　　關(guān)于研究的其他評(píng)論：

　　“全球約70%的溫室氣體排放都來(lái)自城市，這意味著它們?cè)跉夂虮Ｗo(hù)中起著關(guān)鍵作用。在利用不斷產(chǎn)生的數(shù)據(jù)方面，如移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)在測(cè)量和減少城市污染水平領(lǐng)域方面，我們看到了巨大的潛力，”南極集團(tuán)首席執(zhí)行官雷納.休博格如是說(shuō)。

　　NEXT電信負(fù)責(zé)高級(jí)數(shù)據(jù)分析業(yè)務(wù)的總經(jīng)理弗洛瑞安.馬卡特指出：“在紐倫堡的試點(diǎn)項(xiàng)目已經(jīng)清楚地顯示出了匿名的移動(dòng)網(wǎng)絡(luò)數(shù)據(jù)為環(huán)境帶來(lái)的附加價(jià)值。這是來(lái)自人與人之間的數(shù)據(jù)，我們從試點(diǎn)結(jié)果看到了巨大的潛力，即將開(kāi)始進(jìn)行下一階段的研究。我們的目標(biāo)是開(kāi)發(fā)一款產(chǎn)品，供德國(guó)城市、德國(guó)各州及德國(guó)聯(lián)邦政府使用，以便更好地應(yīng)對(duì)對(duì)排放污染“。（本文系中國(guó)環(huán)保網(wǎng)www.chinaenvironment.com 高晶獨(dú)家編譯，如需轉(zhuǎn)載，請(qǐng)注明出處）

原文：Interesting study on how to use big data to reduce Green House gas Emissions

　　New study leverages mobile network data to estimate levels of carbon emissions and air pollution in cities, an approach that could substantially reduce the cost of implementing the Paris Agreement.

　　• The study analyses mobility patterns derived from mobile network data to estimate the usage of different transport modes within a city and derive conclusions about the respective pollution they cause.

　　• This innovative methodology allowed scientists to estimate the concentration of air pollutants in urban areas with up to 77% accuracy.

　　• The method could provide a scalable and cost effective way to help understand and combat greenhouse gas (GHG) emissions in cities worldwide.

　　Big data analytics company and ETH Zurich spin-off  Teralytics,  Telefónica NEXT and sustainability solution provider  South Pole Group conducted a study in Nuremberg, Germany that reveals the analysis of mobile network data as an effective way to estimate CO2 and NOX emissions in urban areas at very low cost. To achieve this, Teralytics examined aggregated and anonymised data, which is generated when mobile devices communicate with Telefónica’s mobile communication cells while users make calls, send texts or browse the internet. Teralytics was able to refine this raw data into human mobility patterns to understand how the different modes of transport, for instance trains or cars, are frequented. Combining this information with data on the emissions of the different transport modes, the three entities were able to estimate air pollution and GHG emissions in the city.

As each form of transportation produces a unique amount of CO2 and NOX emissions, understanding urban mobility patterns is vital to understand the source of emissions. The study in Nuremberg used this information to estimate with up to 77 per cent accuracy the concentration of air pollutants in the city. These findings encourage further exploration of how big data can be used to understand and ultimately solve environmental issues such as air pollution in cities across the world. This is particularly interesting with regards to the lower cost of analysing and interpreting data compared to the higher cost of production and maintenance of elaborate measuring stations. The novel approach could thus allow an ongoing analysis on a nationwide scale.

　　“While our contemporary urban lifestyles result in the generation of harmful greenhouse gasses, it also generates large amounts of behavioural data. Our mission at Teralytics is to use this data for the benefit of society,” says Georg Polzer, CEO of Teralytics. “Our findings from Nuremberg showed that this data can be used to give city planners insights into how human mobility contributes to pollution. This is a vital part to efficiently design and implement clean air and low carbon strategies. We are looking forward to further exploring this opportunity.”

　　Using a three-level process, the fully anonymised and aggregated data was first transformed into movement flows by the data scientists at Teralytics, identifying over 1.2 million transportation routes during the analysed time period, as depicted in Figure 2. The sustainability solution expert South Pole Group then used an atmospheric model to estimate air pollution levels caused by the usage of the different modes of transportation, taking into account meteorological data and information on the respective traffic carriers’ emission levels from the German Federal Ministry for the Environment (BMUB). In the third step, the accuracy of the method was examined by comparing the findings with existing data from air pollution measuring stations. The values measured at these stations were found to correlate up to 77 per cent with those from the Teralytics’ calculations.

The results of this pilot study in Nuremberg constitute a sound basis to further develop the methodology.  Following its success, the consortium was able to secure financial support from Climate KIC’s Low Carbon City Lab (LoCaL), an initiative that brings together cities, business, academia and NGO’s to deliver high environmental and societal impact. With this backing, the research partnership will expand and improve the methodology, focusing on short travel routes and taking into account local emission factors like airports, large-scale events, and types of vehicles on the road (i.e. electric cars and SUVs). Moreover, the influence of factors such as traffic jams and red lights will be taken into account in order to make even more accurate estimations of the air pollution levels in a city.

　　“The results from this pilot study exceed our expectations,” says Maximilian Groth, responsible for Business Development & Partnerships at Teralytics. “We are confident that we will soon be able to scale this product to cities worldwide to support urban planners in making our air cleaner and achieving the goals of the Paris Agreement at the lowest possible cost.”

　　This research follows other successful studies on usage of mobile network data, including a  smart data analysis for transport in Stuttgart by Teralytics, Telefónica Germany, and Fraunhofer IAO.

　　Additional comments on the topic:

　　“Approximately 70 per cent of global greenhouse gas emissions are generated in cities, meaning that they play a key role in climate protection. We see great potential in the use of continuously generated data, such as mobile network data, to measure and reduce pollution levels in cities." States Renat Heuberger, CEO of South Pole Group.

　　Florian Marquart, Managing Director of Telefónica NEXT for Advanced Data Analytics: “The pilot project in Nuremberg has clearly shown the specific added value of anonymised mobile network data for the environment. This is data from people for people. We see great potential in the results and will start the next phase of our research. The goal is to develop a product that German cities, German states and the German federal government can use to better face the challenges of emissions pollution”.