scholarly journals Hygrothermal performance of log walls in a building of 18th century and prediction of climate change impact on biological deterioration

2020 ◽  
Vol 172 ◽  
pp. 15006 ◽  
Author(s):  
Petros Choidis ◽  
Katerina Tsikaloudaki ◽  
Dimitrios Kraniotis
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Future Climate ◽  
Future Climate Change ◽  
Main Body ◽  
Biological Degradation ◽  
Historical Structures ◽  
Hygrothermal Performance ◽  
Change Impact ◽  
The Impact

Several studies underline the dramatic changes that are expected to take place in nature and environment due to climate change. The latter is also expected to affect the built environment. Particular emphasis is currently given to the impact of climate change on historical structures. Within this context, it is important to use simple methods and novel tools in order to investigate specific case studies. In this study, the climate change impact on the hygrothermal performance of the log walls in a historic timber building is presented. The building under investigation is the Fadum storehouse, also known as ‘the coated house’, located in Tønsberg, Norway. The storehouse dates to the late 18th century. It has a particular design with the main features of stumps or piles up to which it stands and the ‘coating’ that covers its outer walls. The main damage of the construction is related to the biological degradation of the wood. The hygrothermal performance of the log walls, as well as the exterior and interior climate, have been monitored and the results have been used to validate a Heat, Air and Moisture transport (HAM) model. The validated HAM model is then used to examine the performance of the log walls for both current and potential future climate conditions. The transient hygrothermal boundary conditions serve as the input parameters to a biohygrothermal model that is used to investigate the biological deterioration of the building components. The findings reveal that currently there is no mould risk for the main body of the construction, which is in accordance with the visual inspection. The passive systems of the building are highly conducive to these results, since they protect it from driving rain and other sources of moisture and eliminate the potential impact of future climate change risk scenarios.

scholarly journals Assessment of Future Climate Change Impact on Groundwater recharge, Baseflow and Sediment in Steep Sloping Watershed

2014 ◽  
Vol 16 (2) ◽  
pp. 173-185 ◽  
Author(s):  
Ji Min Lee ◽  
Younghun Jung ◽  
Younshik Park ◽  
Hyunwoo Kang ◽  
Kyoung Jae Lim ◽  
...  
Keyword(s):  
Climate Change ◽  
Groundwater Recharge ◽  
Climate Change Impact ◽  
Future Climate ◽  
Future Climate Change ◽  
Change Impact

scholarly journals Assessing climate change impact on the hydropower potential of the Bamboi catchment (Black Volta, West Africa)

2021 ◽  
Vol 384 ◽  
pp. 349-354
Author(s):  
Yacouba Yira ◽  
Tariro Cynthia Mutsindikwa ◽  
Aymar Yaovi Bossa ◽  
Jean Hounkpè ◽  
Seyni Salack
Keyword(s):  
Climate Change ◽  
West Africa ◽  
Climate Change Impact ◽  
Climate Models ◽  
Future Climate Change ◽  
Mean Annual Precipitation ◽  
Hydropower Generation ◽  
Hydropower Potential ◽  
Change Impact ◽  
The Impact

Abstract. This study evaluates the impact of future climate change (CC) on the hydropower generation potential of the Bamboi catchment (Black Volta) in West Africa using a conceptual rainfall-runoff model (HBV light) and regional climate models (RCMs)–global climate models (GCMs). Two climate simulation datasets MPI-ESM-REMO (CORDEX) and GFDL-ESM2M-WRF (WASCAL) under RCP4.5 were applied to the validated hydrological model to simulate the catchment runoff. Based on reference and future simulated discharges, a theoretical 1.3 MW run of river hydro power plant was designed to evaluate the hydropower generation. Hydrological and hydropower generation changes were expressed as the relative difference between two future periods (2020–2049 and 2070–2099) and a reference period (1983–2005). The climate models' ensemble projected a mean annual precipitation increase by 8.8 % and 7.3 % and discharge increase by 11.4 % and 9.735 % for the 2020–2049 and 2070–2099 periods respectively (for bias corrected data). On the contrary an overall decrease of hydropower generation by −9.1 % and −8.4% for the 2020–2049 and 2070–2099 periods was projected respectively. The results indicate that projected increases in discharge should not solely be considered as leading to an increase in hydropower potential when prospecting climate change impact on hydropower.

scholarly journals Pollution control can help mitigate future climate change impact on European grayling in the UK

2020 ◽  
Vol 26 (4) ◽  
pp. 517-532
Author(s):  
J. Vanessa Huml ◽  
W. Edwin Harris ◽  
Martin I. Taylor ◽  
Robin Sen ◽  
Christel Prudhomme ◽  
...  
Keyword(s):  
Climate Change ◽  
Pollution Control ◽  
Climate Change Impact ◽  
Future Climate ◽  
Future Climate Change ◽  
European Grayling ◽  
Change Impact ◽  
The Uk

scholarly journals An Economy-Climate Model for Quantitatively Projecting the Impact of Future Climate Change and Its Application

2021 ◽  
Vol 9 ◽  
Author(s):  
Jieming Chou ◽  
Yuan Xu ◽  
Wenjie Dong ◽  
Weixing Zhao ◽  
Jiangnan Li ◽  
...  
Keyword(s):  
Climate Change ◽  
Economic System ◽  
Climate Change Impact ◽  
Future Climate Change ◽  
Future Scenarios ◽  
Climate Condition ◽  
Impact Of Climate Change ◽  
Economic Output ◽  
Change Impact ◽  
The Impact

Quantitatively projecting the impact of future climate change on the socio-economy and exploring its internal mechanism are of great practical significance to adapt to climate change and prevent climate risks. Based on the economy-climate (C-D-C) model, this paper introduces a yield impact of climate change (YICC) model that can quantitatively project the climate change impact. The model is based on the YICC as its core concept and uses the impact ratio of climate change (IRCC) indicator to assess the response of the economic system to climate change over a long period of time. The YICC is defined as the difference between the economic output under changing climate condition and that under assumed invariant climate condition. The IRCC not only reflects the sensitivity of economic output to climate change but also reveals the mechanism of the nonlinear interaction between climate change and non-climatic factors on the socio-economic system. Using the main grain-producing areas in China as a case study, we use the data of the ensemble average of 5 GCMs in CMIP6 to project the possible impact of climate change on grain production in the next 15–30 years under three future scenarios (SSP1-2.6, SSP2-4.5, SSP5-8.5). The results indicate that the long-term climate change in the future will have a restraining effect on production in North region and enhance production in South region. From 2021 to 2035, climate change will reduce production by 0.60–2.09% in North region, and increase production by 1.80–9.01% in South region under three future scenarios. From 2021 to 2050, compared with the climate change impact in 2021–2035, the negative impact of climate change on production in North region will weaken, and the positive impact on production in South region will enhance with the increase in emission concentration. Among them, climate change will reduce grain output in North region by 0.52–1.99%, and increase output in South region by 1.35–9.56% under the three future scenarios. The combination of economic results and climate change research is expected to provide scientific support for further revealing the economic mechanism of climate change impacts.

scholarly journals Future Climate Change Impact on Urban Heat Island in Two Mediterranean Cities Based on High-Resolution Regional Climate Simulations

Atmosphere ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 884
Author(s):  
Stavros Ch. Keppas ◽  
Sofia Papadogiannaki ◽  
Daphne Parliari ◽  
Serafim Kontos ◽  
Anastasia Poupkou ◽  
...  
Keyword(s):  
Climate Change ◽  
Urban Heat Island ◽  
Climate Change Impact ◽  
Urban Areas ◽  
Weather Prediction ◽  
Future Climate ◽  
Future Climate Change ◽  
Heat Island ◽  
Urban Heat ◽  
Change Impact

The Mediterranean is recognized among the most responsive regions to climate change, with annual temperatures projected to increase by 1–5 °C until 2100. Large cities may experience an additional stress discomfort due to the Urban Heat Island (UHI) effect. In the present study, the WRF-ARW numerical weather prediction model was used to investigate the climate change impact on UHI for two Mediterranean cities, Rome and Thessaloniki. For this purpose, three 5-year time-slice simulations were conducted (2006–2010, 2046–2050, 2096–2100) under the Representative Concentration Pathway (RCP) 8.5 emission scenario, with a spatial resolution of 2 km. In order to comprehensively investigate the urban microclimate, we analyze future simulation data across sections crossing urban/non-urban areas, and after grouping them into three classes depending on the location of the grid cells. The urban areas of both cities present increased average minimum temperature (Tmin) in winter/summer compared to other rural areas, with an UHI of ~+1.5–3 °C on average at night/early morning. Considering UHI under future climate change, we found no significant variations (~±0.2 °C). Finally, we found that the numbers of days with Tmin ≥ 20 °C will mostly increase in urban coastal areas until 2100, while the largest increase of minimum Discomfort Index (DImin) is expected in urban low-ground areas.

The impact of climate change on urban transport resilience in a changing world

2014 ◽  
Vol 38 (4) ◽  
pp. 448-463 ◽  
Author(s):  
David Jaroszweski ◽  
Elizabeth Hooper ◽  
Lee Chapman
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Smart Cities ◽  
Urban Transport ◽  
Transport Systems ◽  
Future Climate Change ◽  
Climate Projections ◽  
Impact Of Climate Change ◽  
Change Impact ◽  
The Impact

The assessment of the potential impact of climate change on transport is an area of research very much in its infancy, and one that requires input from a multitude of disciplines including geography, engineering and technology, meteorology, climatology and futures studies. This paper investigates the current state of the art for assessments on urban surface transport, where rising populations and increasing dependence on efficient and reliable mobility have increased the importance placed on resilience to weather. The standard structure of climate change impact assessment (CIA) requires understanding in three important areas: how weather currently affects infrastructure and operations; how climate change may alter the frequency and magnitude of these impacts; and how concurrent technological and socio-economic development may shape the transport network of the future, either ameliorating or exacerbating the effects of climate change. The extent to which the requisite knowledge exists for a successful CIA is observed to decrease from the former to the latter. This paper traces a number of developments in the extrapolation of physical and behavioural relationships on to future climates, including a broad move away from previous deterministic methods and towards probabilistic projections which make use of a much broader range of climate change model output, giving a better representation of the uncertainty involved. Studies increasingly demand spatially and temporally downscaled climate projections that can represent realistic sub-daily fluctuations in weather that transport systems are sensitive to. It is recommended that future climate change impact assessments should focus on several key areas, including better representation of sub-daily extremes in climate tools, and recreation of realistic spatially coherent weather. Greater use of the increasing amounts of data created and captured by ‘intelligent infrastructure’ and ‘smart cities’ is also needed to develop behavioural and physical models of the response of transport to weather and to develop a better understanding of how stakeholders respond to probabilistic climate change impact projections.

Sign in / Sign up

Export Citation Format

Share Document