| 1. |
- Baresel, Christian, et al.
(författare)
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Direct GHG emissions from a pilot scale MBR-process treating municipal wastewater
- 2022
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278 .- 2524-1761. ; 13:1, s. 138-145
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Tidskriftsartikel (refereegranskat)abstract
- To evaluate direct greenhouse gas emissions from Membrane Biological Reactor (MBR), measurements of nitrous oxide (N2O) and methane (CH4) were made at a pilot-scale MBR treating municipal wastewater Measurements were conducted during two campaigns with some changes in processes, i.e. introducing a pre-aeration tank in the second measurement, different distributions of aeration in the treatment line, not the same wastewater inflow rate, two types of ultrafiltration membrane. It was found that about 0.004% and 0.07% of the total ammonium loads were emitted as N2O, CH4 emissions were 0.026% and 0.12% of incoming TOC (0.008% and 0.04% of incoming COD) in 2014 and 2018. The obtained N2O emission values were relatively low.The study suggested that a high aeration at the beginning of the treatment line may result in significantly high emissions of both N2O and CH4. A significant change in aeration in the membrane ultrafiltration tank did not have the same impact. The MBR process is known for high quality effluent but have been questioned due to its higher carbon footprint due to energy consumption. This study gave a reference case about direct GHG emissions from MBR process and provide information for the further evaluation of MBR processes.
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| 2. |
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| 3. |
- Chen, Z., et al.
(författare)
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Deep learning projects future warming-induced vegetation growth changes under SSP scenarios
- 2022
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 13:2, s. 251-257
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Tidskriftsartikel (refereegranskat)abstract
- Climate warming has been projected to enhance vegetation growth more strongly in higher latitudes than in lower latitudes, but different projections show distinct regional differences. By employing big data analysis (deep learning), we established gridded, global-scale, climate-driven vegetation growth models to project future changes in vegetation growth under SSP scenarios. We projected no substantial trends of vegetation growth change under the sustainable development scenario (SSP1-1.9) by the end of the 21st century. However, the increase of vegetation growth driven by climate warming shows distinct regional variability under the scenario representing high carbon emissions and severe warming (SSP5-8.5), especially in Northeast Asia where growth could increase by (6.00% ± 4.21%). This may be attributed to the high temperature sensitivities of the deciduous needleleaf forests and permanent wetlands in these regions. When the temperature sensitivity that is defined as permutation importance in deep learning is greater than 0.05, the increase in vegetation growth will be more prominent. In addition, an extreme temperature increase across grasslands, as well as changing land-use management in northern China may also influence the vegetation growth in the future. The results suggest that the sustainable development scenario can maintain stable vegetation growth, and it may be a reliable way to mitigate global warming due to potential climate feedbacks driven by vegetation changes in boreal regions. Deciduous needleleaf forests will be a centre of greening in the future, and it should become the focus of future vegetation dynamics modelling studies and projections. © 2022 The Authors
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| 4. |
- Fan, Li Jun, et al.
(författare)
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Assessment of Central Asian heat extremes by statistical downscaling: Validation and future projection for 2015‒2100
- 2021
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 13:1, s. 14-27
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Tidskriftsartikel (refereegranskat)abstract
- Increasing heatwaves and extreme temperatures have recently been observed across Central Asia (CA). Accurately assessing and projecting the changing climate extremes at the local (station) scale required for climate risk management are therefore highly important. However, global and regional climate models often fail to represent the statistical distributions of observed daily extreme variables and hence extremes in complex terrain. In this work, we developed a statistical downscaling (SD) model to project summer daily maximum temperature (Tmax) and heatwave indices for 65 meteorological stations in CA toward 2100. The SD model involves first-order autoregression and multiple linear regression using large-scale Tmax and circulation indices (CIs) as predictors, and the model is cross-validated against historical observations. The local Tmax and heatwave indices are then projected for 2015–2100 driven by the output of a global climate model (CNRM-CM6-1) under four Shared Socioeconomic Pathways (SSP126, SSP245, SSP370, and SSP585). The application of the SD model significantly improves forecasting of the probability distribution (10th/90th percentiles) of Tmax at stations, particularly across mountainous regions. The model also captures interannual variability and the long-term trend in Tmax, consistent with synoptic-scale inputs. SD projections demonstrate strong warming trends of summer Tmax in CA toward 2100 with rates between 0.35–0.64 °C per decade based on the SSP245 and SSP370 scenarios. Consequently, heatwave occurrence is projected to rise by 1.0–5.0 and 2.0–7.0 d per decade under the SSP245 and SSP370 scenarios, respectively, by 2100. Duration, intensity, and amplitude of heatwaves rise at greater rates under higher-emission scenarios, particularly in southeastern CA. The proposed SD model serves as a useful tool for assessing local climate extremes, which are needed for regional risk management and policymaking for adaption to climate change.
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| 5. |
- Fan, L. J., et al.
(författare)
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Assessment of total and extreme precipitation over central Asia via statistical downscaling: Added value and multi-model ensemble projection
- 2023
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 14:1, s. 62-76
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Tidskriftsartikel (refereegranskat)abstract
- Central Asia (CA) is highly sensitive and vulnerable to changes in precipitation due to global warming, so the projection of precipitation extremes is essential for local climate risk assessment. However, global and regional climate models often fail to reproduce the observed daily precipitation distribution and hence extremes, especially in areas with complex terrain. In this study, we proposed a statistical downscaling (SD) model based on quantile delta mapping to assess and project eight precipitation indices at 73 meteorological stations across CA driven by ERA5 reanalysis data and simulations of 10 global climate models (GCMs) for present and future (2081-2100) periods under two shared socio-economic pathways (SSP245 and SSP585). The reanalysis data and raw GCM outputs clearly underestimate mean precipitation intensity (SDII) and maximum 1-day precipitation (RX1DAY) and overestimate the number of wet days (R1MM) and maximum consecutive wet days (CWD) at stations across CA. However, the SD model effectively reduces the biases and RMSEs of the modeled precipitation indices compared to the observations. Also it effectively adjusts the distributional biases in the downscaled daily precipitation and indices at the stations across CA. In addition, it is skilled in capturing the spatial patterns of the observed precipitation indices. Obviously, SDII and RX1DAY are improved by the SD model, especially in the southeastern mountainous area. Under the intermediate scenario (SSP245), our SD multi-model ensemble pro-jections project significant and robust increases in SDII and total extreme precipitation (R95PTOT) of 0.5 mm d-1 and 19.7 mm, respectively, over CA at the end of the 21st century (2081-2100) compared to the present values (1995-2014). More pronounced increases in indices R95PTOT, SDII, number of very wet days (R10MM), and RX1DAY are projected under the higher emission scenario (SSP585), particularly in the mountainous southeastern region. The SD model suggested that SDII and RX1DAY will likely rise more rapidly than those projected by previous model simulations over CA during the period 2081-2100. The SD projection of the possible future changes in precipitation and extremes improves the knowledge base for local risk management and climate change adaptation in CA.
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| 6. |
- Irannezhad, Masoud, et al.
(författare)
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Century-long variability and trends in daily precipitation characteristics at three Finnish stations
- 2016
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 7, s. 54-69
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Tidskriftsartikel (refereegranskat)abstract
- © 2016 National Climate Center (China Meteorological Administration) Long-term variations and trends in a wide range of statistics for daily precipitation characteristics in terms of intensity, frequency and duration in Finland were analysed using precipitation records during 1908–2008 from 3 meteorological stations in the south (Kaisaniemi), centre (Kajaani) and north (Sodankylä). Although precipitation days in northern part were more frequent than in central and southern parts, daily precipitation intensity in the south was generally higher than those in the centre and north of the country. Annual sum of very light precipitation (0 mm < daily precipitation ≤ long-term 50th percentile of daily precipitation more than 0 mm) significantly (p < 0.05) decreased over time, with the highest rate in northern Finland. These decreasing trends might be the result of significant increases in frequency of days with very light precipitation at all the stations, with the highest and lowest rates in northern and southern Finland, respectively. Ratio of annual total precipitation to number of precipitation days also declined in Finland over 1908–2008, with a decreasing north to south gradient. However, annual duration indices of daily precipitation revealed no statistically significant trends at any station. Daily precipitation characteristics showed significant relationships with various well-known atmospheric circulation patterns (ACPs). In particular, the East Atlantic/West Russia (EA/WR) pattern in summer was the most influential ACP negatively associated with different daily precipitation intensity, frequency and duration indices at all three stations studied.
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| 7. |
- Kaiqiang, Deng, et al.
(författare)
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Shifting of summertime weather extremes in Western Europe during the last decade
- 2022
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 13:2, s. 218-227
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Tidskriftsartikel (refereegranskat)abstract
- Over the past decades, droughts and heatwaves frequently appeared in Western Europe (45°–65°N, 10°W–20°E) during boreal summer, causing huge impacts on human society and ecosystems. Although these extremes are projected to increase in both frequency and intensity under a warming climate, our knowledge of their interdecadal variations and causes is relatively limited. Here we show that the droughts and heatwaves in Western Europe have shifted in their trends in the last decade: for 1979–2012, wind speed and precipitation have both strengthened in Western Europe; for 2012–2020, however, Western Europe have experienced declined wind speed, decreased precipitation, and higher air temperature, leading to more frequent droughts and heatwaves there. Recent changes in the WE climate and extremes are related to the variations of the North Atlantic westerly jet stream. In 1979–2012 (2012–2020), the westerly jet stream shifted equatorward (poleward), which enhanced (reduced) transportation of water vapor fluxes from the North Atlantic Ocean to the European land areas, resulting in wetter (drier) surface in Western Europe. Further analysis suggests that phase changes in the Pacific Decadal Oscillation could have played a key role in regulating the position of the jet stream, providing important implications for decadal predictions of the Western Europe summertime climate and weather extremes. © 2022 The Authors
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| 8. |
- Liu, Xuan, et al.
(författare)
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Increased southerly and easterly water vapor transport contributed to the dry-to-wet transition of summer precipitation over the Three-River Headwaters in the Tibetan Plateau
- 2023
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Ingår i: Advances in Climate Change Research. - 1674-9278 .- 2524-1761. ; 14:4, s. 502-510
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Tidskriftsartikel (refereegranskat)abstract
- The Three-River Headwaters (TRH) region in the Tibetan Plateau is vulnerable to climate change; changes in summer (June–August) precipitation have a significant impact on water security and sustainability in both local and downstream areas. However, the changes in summer precipitation of different intensities over the TRH region, along with their influencing factors, remain unclear. In this study, we used observational and ERA5 reanalysis data and employed a precipitation categorization and water vapor budget analysis to quantify the categorized precipitation variations and investigate their possible linkages with the water vapor budget. Our results showed an increasing trend in summer precipitation at a rate of 0.9 mm per year (p < 0.1) during 1979–2020, with a significant dry-to-wet transition in 2002. The category ‘very heavy precipitation’ (≥10 mm d−1) contributed 65.1% of the increased summer precipitation, which occurred frequently in the northern TRH region. The dry-to-wet transition was caused by the effects of varied atmospheric circulations in each subregion. Southwesterly water vapor transport through the southern boundary was responsible for the increased net water vapor flux in the western TRH region (158.2%), while southeasterly water vapor transport through the eastern boundary was responsible for the increased net water vapor flux in the central TRH (155.2%) and eastern TRH (229.2%) regions. Therefore, we inferred that the dry-to-wet transition of summer precipitation and the increased ‘very heavy precipitation’ over the TRH was caused by increased easterly and southerly water vapor transport.
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| 9. |
- Rayner, D.P. 1973, et al.
(författare)
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A multi-state weather generator for daily precipitation for the Torne River basin, northern Sweden/western Finland
- 2016
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Ingår i: Advances in Climate Change Research. - : Elsevier BV. - 1674-9278. ; 7:1-2, s. 70-81
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Tidskriftsartikel (refereegranskat)abstract
- This paper describes a new weather generator e the 10-state empirical model e that combines a 10-state, first-order Markov chain with a non-parametric precipitation amounts model. Using a doubly-stochastic transition-matrix results in a weather generator for which the overall precipitation distribution (including both wet and dry days) and the temporal-correlation can be modified independently for climate change studies. This paper assesses the ability of the 10-state empirical model to simulate daily area-average precipitation in the Torne River catchment in northern Sweden/western Finland in the context of 3 other models: a 10-state model with a parametric (Gamma) amounts model; a wet/dry chain with the empirical amounts model; and a wet/dry chain with the parametric amounts model. The ability to accurately simulate the dis- tribution of multi-day precipitation in the catchment is the primary consideration. Results showed that the 10-state empirical model represented accumulated 2- to 14-day precipitation most realistically. Further, the dis- tribution of precipitation on wet days in the catchment is related to the placement of a wet day within a wet-spell, and the 10-state models represented this realistically, while the wet/dry models did not. Although all four models accurately reproduced the annual and monthly averages in the training data, all models underestimated inter-annual and inter-seasonal variance. Even so, the 10-state empirical model performed best. We conclude that the multi-state model is a promising candidate for hydrological applications, as it simulates multi-day precipitation well, but that further development is required to improve the simulation of interannual variation.
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| 10. |
- Su, Bo, et al.
(författare)
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Changes in the supply and demand potentials of China's glacier water resources in the 21st century: Spatiotemporal mismatches and combined effects
- 2023
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Ingår i: Advances in Climate Change Research. - 1674-9278 .- 2524-1761. ; 14:5, s. 746-757
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Tidskriftsartikel (refereegranskat)abstract
- China's glacier water resources (GWRs) are not only indispensable suppliers of fresh water for humans living in large domestic areas but also affect the water supply to downstream neighbouring countries. Therefore, it is crucial to systematically evaluate the spatiotemporal (mis-) matches between the supply and demand potentials of China's GWRs and the combined supply and demand effects in the 21st century to enable regional sustainable development. To facilitate such research, in this study, we first regionalized the importance of China's GWRs in terms of the supply potential and downstream human dependence to reveal the spatial (mis-) matches between supply and demand potentials. Then, changes in the service potential of glacier meltwater and in population dynamics, as well as their temporal (mis-) matches and associated opportunities and risks, were further assessed at the river basin scale. The results showed that GWR plays an important role in 4 of 16 macroscale glacier-fed basins (i.e., Tarim, Junggar, Ili, and Zangxi) and 11 of 37 subbasins within the China region due to higher supply potential and demand potential in those basins. The importance of China's GWRs increases dramatically when taking the demand potential of downstream countries into account, especially in the Ganges and Indus river basins. The peaks in meltwater runoff from the most glacierized basins of the eastern Tianshan Mountains, eastern Qilian Mountains, and southeastern Tibetan Plateau of China occur slightly earlier than the projected peak population (around 2030) under the mid-range Shared Socioeconomic Pathway (SSP245), leading to a compound risk in terms of decreasing meltwater supply and increasing human dependence at the end of the 2020s. However, the peak meltwater is expected to occur later than the peak population in the Tarim, Qiangtang Plateau, and Qaidam basins. The opportunities offered by the increase in meltwater can relieve the water resource pressure for those populations under water-stressed conditions. Greater attention should also be paid to water shortage risks in the transboundary river basins, especially in the Indus and Ganges basins, because the peak meltwater within China is generally expected to occur sooner than the projected peak population of downstream countries. This study provides an effective planning and decision-making basis for the full utilization of China's GWRs and adaptation when glacier runoff declines.
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