Assessing the effects of noise abatement measures on health risks: A case study in Istanbul

Ongel, Aybike; Sezgin, Fatih

doi:10.1016/j.eiar.2015.10.008

Cited by 25 publications

(14 citation statements)

References 12 publications

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“…Particularly, the economic costs of health risk to cities are being expressed with convertible units such as DALYS (disability adjusted life years), WTP (willing to pay), and YLLs (years of life lost) due to diseases. For instance, in Istanbul Turkey, a study calculated the DALYS related to noise pollution, air pollution, and impact of the emission of greenhouse gases and found that in 2010, 87,471 years of life lost (YLL) occurred due to cardiovascular disease in nine urban municipalities [56]. In Bangkok (Thailand), Li and Crawford-Brown [57] estimated that in year 2000 the total health damage cost due to exposure to traffic-related fine particulate matter was 2678 million U.S. dollars in the Bangkok Metropolitan area and that premature deaths accounted for 1369.2 million dollars or 51.1% of the total health damage costs.…”

Section: An Agenda For Redefining Urban Healthmentioning

confidence: 99%

Redefining the Use of Big Data in Urban Health for Increased Liveability in Smart Cities

2019

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Policy decisions and urban governance are being influenced by an emergence of data from internet of things (IoT), which forms the backbone of Smart Cities, giving rise to Big Data which is processed and analyzed by Artificial Intelligence models at speeds unknown to mankind decades ago. This is providing new ways of understanding how well cities perform, both in terms of economics as well as in health. However, even though cities have been increasingly digitalized, accelerated by the concept of Smart Cities, the exploration of urban health has been limited by the interpretation of sensor data from IoT devices, omitting the inclusion of data from human anatomy and the emergence of biological data in various forms. This paper advances the need for expanding the concept of Big Data beyond infrastructure to include that of urban health through human anatomy; thus, providing a more cohesive set of data, which can lead to a better knowledge as to the relationship of people with the city and how this pertains to the thematic of urban health. Coupling both data forms will be key in supplementing the contemporary notion of Big Data for the pursuit of more contextualized, resilient, and sustainable Smart Cities, rendering more liveable fabrics, as outlined in the Sustainable Development Goal (SDG) 11 and the New Urban Agenda.

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Section: An Agenda For Redefining Urban Healthmentioning

confidence: 99%

Redefining the Use of Big Data in Urban Health for Increased Liveability in Smart Cities

2019

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“…Bunun olası nedeni de gözenekli asfaltın gürültüyü absorbe ederek kaynağında azaltmasıdır. Gürültü azaltma yöntemlerinin sağlık etkilerini inceleyen teorik bir çalışmada da gözenekli asfaltın hız sınırı uygulamasına göre daha etkin bir yöntem olduğu gösterilmiştir [20]. Bu bağlamda, sonuçlar belirtilen önceki çalışmayı da destekleyici niteliktedir.…”

Section: Sonuç Ve öNeri̇lerunclassified

Trafik Gürültüsünü Etkileyen Faktörlerin SoundPlan 6.5 Programı ile İncelenmesi

Öngel¹,

Sezgin²

2017

Teknik Dergi

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ÖZUlaştırma kaynaklı gürültü kirliliği son yıllarda tüm dünyadaki en büyük çevresel sorunlardan biri haline gelmiştir. Gürültünün duyma kaybı, performans kaybı, rahatsızlık, uyku bozuklukları, kardiyovasküler problemler ve çocuklarda zihinsel bozukluklar gibi sağlık üzerine olumsuz etkileri vardır. Bu araştırmada, SoundPlan 6.5 gürültü haritalama programı kullanılarak D-100 Karayolu Okmeydanı mevkisi için gürültü haritaları oluşturulmuştur. Gürültüyü etkileyen faktörler olan trafik hacmi, kompozisyonu, hızı ve yol üstyapı tipinin gürültü maruziyeti,rahatsızlık, uyku bozuklukları ve kardiyovasküler hastalık riskine olan etkileri gürültü haritaları kullanılarak incelenmiştir. Bu çalışmalar sonucunda, hız limiti, toplu taşıma, ağır taşıt ve yol üstyapı türü bağlamında alınabilecek tedbirler önerilmiştir.Anahtar Kelimeler: Karayolu gürültüsü, SoundPlan, gürültü haritası, gürültü ve sağlık. ABSTRACT Evaluation of Effects of Traffic Variables on the Noise Levels Using SoundPlan V6.5In recent decades, noise pollution has been a worldwide concern. The health effects of noise pollution include noise-induced hearing loss, sleep disturbance, performance loss, annoyance, cardiovascular problems, and cognitive impairment in children. In this study, noise maps were prepared using SoundPlan 6.5 for D-100 Highway around Okmeydani. The effects of traffic volume, composition, and speed and pavement surface type on the number of people exposed to noise levels above threshold for annoyance, sleep disturbance, and cardiovascular diseases were investigated. Noise reduction strategies in terms of speed limit, public transportation, heavy vehicle traffic, and pavement type were proposed.

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“…Ongel () and Ongel and Sezgin () also proposed a noise evaluation model that borrows the typical characterization structure of LCA in a non‐LCA context. The method focuses on road transportation and was applied to the case of the city of Istanbul in Turkey.…”

Section: Introductionmentioning

confidence: 99%

Noise footprint from personal land‐based mobility

Cucurachi

Schiess

Froemelt

et al. 2019

J of Industrial Ecology

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A large part of the world population is exposed to noise levels that are unhealthy. Yet noise is often neglected when impact assessment studies are conducted and when policy interventions are designed. In this study, we provide a way to calculate the noise footprint of citizens directly determined by their use of private and public transport on land. The study combines the results of the large transport simulation model MATSim applied to Switzerland, with a noise characterization model, N‐LCA, developed in the context of life cycle assessment. MATSim results allow tracking the use of private and public transportation by agents in the model. The results after characterization provide a consumption‐based noise footprint, thus the total noise and impacts that are caused by the private mobility demand of the citizens of Switzerland. Our results confirm that road transportation is the largest contributor to the total noise footprint of land‐based mobility. We also included a scenario with a full transition to an electrified car fleet, which showed the potential for the reduction of impacts, particularly in urban areas, by about 55% as compared to the modeled regime with combustion engines.

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Assessing the effects of noise abatement measures on health risks: A case study in Istanbul

Cited by 25 publications

References 12 publications

Redefining the Use of Big Data in Urban Health for Increased Liveability in Smart Cities

Redefining the Use of Big Data in Urban Health for Increased Liveability in Smart Cities

Trafik Gürültüsünü Etkileyen Faktörlerin SoundPlan 6.5 Programı ile İncelenmesi

Noise footprint from personal land‐based mobility

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