Day 1 :
- Climate Change
Session Introduction
Bismark Ameyaw
University of Electronic Science and Technology of China
Title: Optimal CO2 emissions-mitigation pathways in the electric power sector based on high-accuracy forecasts
Biography:
Bismark Ameyaw is a third year doctoral student of the University of Electronic Science and Technology of China (UESTC). He researches into carbon emissions mitigation pathways by employing both Artificial Nueral Network (ANN) techniques as well as othe Recurrent Nueral Network (RNN) algorithm formulations and simulations. He currently has six (6) SSCI papers in the field of energy with his mst recent publication coming from Energy Policy Journal. He also serves as an editorial member and a reviewer to a number of pretigious journals in the field of energy.
Abstract:
Carbon dioxide emissions (CO2), a major greenhouse gas, has contributed massively towards the weight of each country’s share in global warming and climate change including the United States (US). The Energy Information Administration (EIA) uses the National Energy Modelling System (NEMS) to forecast and make projections on electric sector CO2 emissions in the US for short, medium and long-term timelines but the forecast inaccuracies of past projections are considerably high. The massive tradeoffs of factors, unrealized assumptions and scenarios on deterministic and peripheral variables, a uniform time effect used, and volatilities in patterns of electricity consumption are among the factors that cause such high forecast errors. Here we propose and apply a long short-term memory (LSTM) recurrent neural network (RNN) technique devoid of exogenous variables and their assumption and/or scenarios thereof; that allows for varying time effects and capable of withstanding volatilities; to forecast electric power sector CO2 emissions in the US for the 2005-2015 period. Based on the high-accuracy forecasts, we propose optimal emissions-mitigation pathways to achieve US’s set targets in the electric sector. The empirical results suggest the proposed LSTM model presents overwhelming improvement on accuracy of forecasts and projections of selected EIA's Annual Energy Outlooks (AEOs). We find that the forecasts accuracy on emissions from policy-targeted variables (PTVs), particularly petroleum products, is affected by the use of much outdated historic data as such cause outliers and that using recent reliable data in making short and medium-term forecasts of PTVs is recommended.
Zahra Noorisameleh
University of Toronto at Scarborough, Ontario, Canada
Title: Impact of climate change on drought variables in dry and semi-arid cities (Iran: Tehran Province (
Biography:
Shahriar Khaledi has completed his PhD (Physical Geography - Climatology in Environmental Planning) at Sorbonne University in 1985. Currently he is a full professor at Shahid Beheshti University, Faculty of Earth Sciences(Iran).
Abstract:
Drought is one of the greatest threats to lives and resources. climate change has made the drought more complicated. Iran is one of the most vulnerable countries to droughts. This paper discusses the impact of climate change on the characteristics of precipitation and drought in the Iran capital. In this regard, the data of nine precipitation daily synoptic stations in Tehran have been used since the establishment of the station until 2018. First, the most important variables of drought in Tehran province were extracted with CPEI index. Second, variable values and severity of drought were predicted under RCPS scenarios (2.6, 4.5 and 8.5) by 2070. Third, drought intensity trend was calculated for stations. The results showed that the variables MAR (Average annual precipitation depth) and TWD (The total number of wet days) and TDY (The total number of annual dry days) were the most important rainfall variables determine the severity of drought in Tehran Province. The results showed that the average of Hurst exponent in the province is 0.72 that means long-term persistence in the precipitation time series in Tehran Province. The simulation of climate change in the future showed that the west of the province would be more vulnerable and the severity of drought will increase at stations where drought persistence and precipitation variability coefficient are higher. The process of reducing the wet days and increasing the dry days indicates that the rainfall would be concentrated in limited days and the conditions for flood events could further be enhanced.
Joanne Muller
Florida Gulf Coast University, Australia
Title: A Millennial-Scale Record of Hurricane Landfalls along the Southwest Florida Coastline
Biography:
Dr. Muller is an Associate Professor of Paleoclimatology at Florida Gulf Coast University. Muller completeted her PhD at James Cook University, Australia in 2007 and postdoctoral studies at the Woods Hole Oceanographic Institution, USA in 2009. She is the Department Chair of Marine and Earth Sciences, within the Water School, at Florida Gulf Coast University. Muller’s current research interests center on past climate change in tropical and sub-tropical latitudes with a special focus on hurricane variability through time.
Abstract:
Forecasting future coastal storm impacts requires sophisticated modeling, predicated on accurate initialization data. The official NOAA database of historical hurricane tracks (HURDAT) along and near the Florida coast extends back in time to only 1851. However, this data is used for purposes along a spectrum from statistically estimating annual expected return frequencies to modeling the impacts of global climate change and sea level rise on shoreline change; hence, a longer and more complete dataset would result in greater accuracy at initialization. Current return period estimations used to generate insurance rates along the Florida coast appear to be an artifact of temporally-limited base data. In addition, research suggests a rise in sea surface temperatures caused by anthropogenic climate change has led to an increase in the intensity of hurricanes over the last 40 years. This interpretation has again, been challenged on the basis that the observational hurricane record is too short (161 years) and unreliable to reveal long-term trends in hurricane activity. Paleotempestology, a research area that uses geological proxy techniques to reconstruct hurricane frequency and strength over millennia, can address these limitations. We use the geologic record (Paleotempestology) to extend the HURDAT database even further back in time. This study presents continuous hurricane records for the Florida region that extend back well beyond the historic observational record (more than one thousand years). Hurricane overwash layers show clear active, versus inactive periods, of hurricane activity over the past few millennia. Correlations with sea surface temperature (SST) studies indicate a strong connection between SSTs and past Florida hurricane activity. In addition, the research demonstrates that the Gulf of Mexico and East Coast of Florida are sometimes in phase, but sometimes they are not. In addition to SSTs, climate drivers such as the Atlantic Meridional Mode (AMM), El Niño-Southern Oscillation (ENSO), and the position of the Intertropical Convergence Zone (ITCZ) may also exert significant influence over hurricane dynamics over longer time scales. These data sets will allow for increased accuracy in the determination of the spatial and temporal variation in hurricane impacts, thereby providing important information to reinsurance industries and emergeny planners.
Taheri Tizro
Bu-Ali Sina University, Hamedan, Iran
Title: The Relationship between Climate Change and Groundwater Recharge in Tuyserkan Plain, Hamadan Province, A case study western part of Iran
Biography:
Dr. Abdollah Taheri Tizro is an Associate Professor at the Department of Water Engineering; College of Agriculture, Bu-Ali Sina University, Hamedan, Iran. He obtained his PhD degree in Hydrology (Hydrogeology) from the Department of Hydrology, Indian Institute of Technology, Roorkee, India (1996). His research interests are mainly concerned in groundwater potential, Groundwater modeling, Field Hydrogeology, Aquifer Vulnerability to Pollution, Groundwater management and Quality. He is author of three books on groundwater (in Persian). He has supervised thesis of more than 23 Master students on water engineering. He has published a number of manuscripts in national and international journals. He has participated in many national projects for the past 20 years.
Abstract:
Changes in the future climate will alter the hydrological cycle and subsequently affect the quantity and quality of water resources. Understanding groundwater recharge is essential in managing groundwater resources. In this study, the effects of climate change on the future status of groundwater in Tuyserkan plain a sub basins of upper Karkhe River basin in Hamadan province, Iran are investigated. In recent years, Groundwater levels in the Tuyserkan plain have declined. Predictions of recharge in the Tuyserkan plain based on the Representative Concentration Pathways (RCP4.5) scenario from the Fifth Intergovernmental Panel on Climate Change, have been produced. The Regional Climate Model (RegCM) model was validated for 5 years (2000 to 2004) and predicted for the 10-year period 2015 to 2025. The Tuyserkan plain aquifer system was modeled using the MODFLOW code in the GMS software using a finite difference model; various hydrological, hydrogeological, topographic and geological maps and well logs in the area were used. The groundwater model was calibrated for one year period with monthly stress periods (October 87 to September 88) and validated for another one year period (October 88 to September 89). Model sensitivity analysis results showed that specific discharge changes had more effect on the aquifer model compared to hydraulic conductivity and recharge. Finally, two scenarios were defined for the 10-year forecast period; the first scenario assumes the continuation of the current withdrawal process, but the second scenario considers a 20% reduction in agricultural wells as a result of increased irrigation efficiency. The results indicate that the water level drop trend will continue in the aquifer and the increase in irrigation efficiency will not have a significant effect on the water level drop trend.