Water resources investigation in Pakistan with the help of ERTS imagery, snow surveys, 1975-1976
There are no author-identified significant results in this report.
Qureshy, A. A.↗
SEARCH · Engineering Papers
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Towards Developing a Customized Composite Drought Index for Pakistan: A Framework for Understanding Drought in an Agricultural Context
No abstract available
Mishra, Vikalp↗
Developing a Customized Composite Drought Index for Pakistan
This study aims to identify historical agricultural droughts between 2004-2019 using 10 geophysical variables (Table 1) and determine what variables have little importance in this identification. Satellite data products or model outputs are used for all input variables. Understanding the interactions between the data will provide information on temporal and spatial patterns of how drought is presented in irrigated and rainfed areas (Fig. 2). This knowledge will assist in creating a Customized Composite Drought Index in future work
Drought↗
Passive Microwave Brightness Temperature Assimilation to Improve Snow Mass Estimation across Complex Terrain in Pakistan, Afghanistan, and Tajikistan
An ensemble Kalman filter is used to assimilate Advanced Microwave Scanning Radiometer-2 (AMSR2) observations of passive microwave (PMW) brightness temperatures (spectral differences, ΔT b ) into land surface model estimates of snow mass over northwestern high mountain Asia (HMA). Trained support vector machines serve as the observation operator and map the geophysical modeled variables into ΔT b space within the assimilation framework. Evaluation of the assimilation routine is carried out through comparison of assimilated snow mass estimates with an in situ dataset. The assimilation framework helps improve the land surface model estimates through PMW ΔT b assimilation, particularly in terms of decreasing the domain-wide bias. The assimilation framework proved more effective during the (dry) snow accumulation season and decreased the bias and root-mean-square error (RMSE) in snow mass estimates at 76% and 58% of the comparative pixels, respectively. During the snow ablation season, the PMW brightness temperature signal contained less information related to snow mass due to the presence of other concurrent geophysical features that effectively serve as noise during the snow mass update. The utilization of PMW ΔT b for accurate snow mass estimation in complex terrain such as HMA is dependent on a multitude of factors for optimal results; however, it does add utility to the land surface model if the relevant pitfalls are taken into consideration prior to the state variable update.
Jawairia Ahmad↗
Hydrological projections over the Upper Indus Basin at 1.5 °C and 2.0 °C temperature increase
We analyse an ensemble of statistically downscaled Global Climate Models (GCMs) to investigate future water availability in the Upper Indus Basin (UIB) of Pakistan for the time horizons when the global and/or regional warming levels cross Paris Agreement (PA) targets. The GCMs data is obtained from the 5th Phase of Coupled Model Inter-Comparison Project under two Representative Concentration Pathways (RCP4.5 and RCP8.5). Based on the five best performing GCMs, we note that global 1.5 °C and 2.0 °C warming thresholds are projected in 2026 and 2047 under RCP4.5 and 2022 and 3036 under RCP8.5 respectively while these thresholds are reached much earlier over Pakistan i.e. 2016 and 2030 under RCP4.5 and 2012 and 2025 under RCP8.5 respectively. Interestingly, the GCMs with the earliest emergence at the global scale are not necessarily the ones with the earliest emergence over Pakistan, highlighting spatial non-linearity in GCMs response. The emergence of 2.0 °C warming at global scale across 5 GCMs ranges from 2031 (CCSM4) to 2049 (NorESM) under RCP8.5. Precipitation generally exhibits a progressive increasing trend with stronger changes at higher warming or radiative forcing levels. Hydrological simulations representing the historical, 1.5 °C and 2.0 °C global and region warming time horizons indicate a robust but seasonally varying increase in the inflows. The highest inflows in the baseline and future are witnessed in July. However, the highest future increase in inflows is projected in October under RCP4.5 (37.99% and 65.11% at 1.5 °C and 2.0 °C) and in April under RCP8.5 (37% and 62.05% at 1.5 °C and 2.0 °C). These hydrological changes are driven by increases in the snow and glacial melt contribution, which are more pronounced at 2.0 °C warming level. These findings should help for effective water management in Pakistan over the coming decades.
54 ENVIRONMENTAL SCIENCES↗
Performance Assessment of Pakistani Central Receiver Plant Case Study Using Aimpoint Strategy Optimization Tools
Pakistan has a high potential for both photovoltaic and Concentrated Solar Power (CSP) deployment to meet its energy requirements. Previous feasibility studies have shown that a variety of CSP technologies are both technically and economically viable in the Pakistani climate and can significantly mitigate the country's current lack of grid reliability. This work aims to enhance the performance of a previously designed Central Receiver System (CRS) plant for Pakistan using state-of-the-art aimpoint optimization methods. Results from our case study show that optimized aiming strategies have increased practicality due to their adherence to flux limitations on the receiver, and offer ~2.4% more thermal energy delivered to the receiver for the Pakistani case study compared to modern performance characterization software, translating to up to 149 additional hours of nameplate-capacity production to address the shortfall in an electricity-starved market.
central receiver system↗
Seasonal Assessment and Classification of Aerosols Transported to Lahore Using AERONET and MODIS Deep Blue Retrievals
Daily measurements of aerosol optical depth (𝜏) and Ångstrom wavelength exponent (𝛼) acquired from Aerosol Robotic Network (AERONET) and Moderate Resolution Imaging Spectrometer (MODIS) are analysed over Lahore - an urban city of Pakistan (period: 2010-2014) to investigate contribution of different types of aerosols originating from both local and regional source locations. The obtained annual averages (mean+/-standard deviation) for AERONET retrievals of 𝜏 (500 nm) and 𝛼 (440-870 nm) are 0.68+/-0.37 (0.08-2.91) and 0.99+/-0.33 (0-1.8), respectively. Of all the sources, 61% are found within Pakistan, 11% in India, 19% in Afghanistan, 6% in Iran and 2% in Saudi Arabia with seasonal contributions of 35, 25, 23 and 17% in pre-monsoon, monsoon, winter and post-monsoon, respectively. The bimodal distributions of 𝛼 show dominance of coarse-mode particles during pre-monsoon, fine-mode particles during post-monsoon and presence of both coarse-mode and fine-mode particles during winter and monsoon with winter showing more fine-mode particles. Two broad classes of aerosols namely desert dust (DD) and biomass burning/urban industrial (BU) are identified with criteria, e.g. 𝜏 ≥0.3 and 𝛼 ≤0.75 indicating presence of DD while 𝜏 ≥0.2 and 𝛼 ≥1.15 indicating BU. The frequency of occurrence (FOO) of DD and BU aerosols is further identified by applying classification criteria over Aqua-MODIS deep blue retrievals. The FOO identifies anthropogenic activity on-going throughout the year, disrupted with DD aerosols only during pre-monsoon and monsoon. The maximum dust activity is seen over Indo-Gangetic plains (IGP) (localized maxima: 35-45%) and the Arabian peninsula (>55%) during pre-monsoon, while maximum BU aerosols are found over IGP, central and south-eastern plains of India and the state of Gujarat (localized maxima: >70%) in winter and post-monsoon.
Zafar, Qudsia↗
A regional nuclear conflict would compromise global food security
A limited nuclear war between India and Pakistan could ignite fires large enough to emit more than 5 Tg of soot into the stratosphere. Climate model simulations have shown severe resulting climate perturbations with declines in global mean temperature by 1.8 °C and precipitation by 8%, for at least 5 y. Here we evaluate impacts for the global food system. Six harmonized state-of-the-art crop models show that global caloric production from maize, wheat, rice, and soybean falls by 13 (±1)%, 11 (±8)%, 3 (±5)%, and 17 (±2)% over 5 y. Total single-year losses of 12 (±4)% quadruple the largest observed historical anomaly and exceed impacts caused by historic droughts and volcanic eruptions. Colder temperatures drive losses more than changes in precipitation and solar radiation, leading to strongest impacts in temperate regions poleward of 30°N, including the United States, Europe, and China for 10 to 15 y. Integrated food trade network analyses show that domestic reserves and global trade can largely buffer the production anomaly in the first year. Persistent multiyear losses, however, would constrain domestic food availability and propagate to the Global South, especially to food-insecure countries. By year 5, maize and wheat availability would decrease by 13% globally and by more than 20% in 71 countries with a cumulative population of 1.3 billion people. In view of increasing instability in South Asia, this study shows that a regional conflict using <1% of the worldwide nuclear arsenal could have adverse consequences for global food security unmatched in modern history.
54 ENVIRONMENTAL SCIENCES↗
An Overview of Policies Influencing Air Pollution from the Electricity Sector in South Asia
The electricity sector is a substantial source of air pollution and associated health problems in South Asia and elsewhere. Fossil-fueled power plants emit a wide variety of harmful pollutants. Those with the greatest health impacts are particulate matter and ozone. Once released into the atmosphere, there is no practical way to remove air pollutants, which means that policies designed to improve air quality have to limit the pollutants before release. However, tackling such pollution is challenging because developing economies also need to provide electricity as a basic necessity for their citizens and as an engine of economic growth. This report provides examples of policies impacting air pollution from the fossil-fuel electricity sector in the South Asian countries of Afghanistan, Bangladesh, Bhutan, India, the Maldives, Nepal, Pakistan, and Sri Lanka. Some of this information was difficult to locate, so this is not a comprehensive study, but rather an overview or "scan" of the sector that includes examples of (1) policies that directly regulate air quality by limiting emissions from specific point sources (by restricting operating hours, for instance), and (2) indirect policies that incentivize or disincentivize polluting activities, such as policies to encourage fuel switching, for example. The report shows (1) the great variation among the policy instruments used in each country, (2) that many countries, especially those that have a mismatch between seasonal demand and resource availability, could improve energy security and reduce air pollution through increased cross-border electricity trade, and (3) some countries have contradictory policies (promoting both coal and renewables, for instance).
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Load Factor and Unserved Energy Webinar
This presentation consists of slides from a webinar given on October 25, 2019. The slides give an overview of load factor forecasting and how it can be incorporated into energy and power demand forecasts, with a special eye towards accounting for unserved energy. It includes case studies from other countries, highlighting how load factor is used in their individual load forecasts. The slides then review and compare various load forecasts for Pakistan's electricity grid.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Analysis of aerosol cloud interactions with a consistent signal of meteorology and other influencing parameters
Quantifying the impact of aerosols on cloud micro/macro physical properties and estimating the signature of Aerosol Cloud Interactions (ACI) is one of the challenging tasks in atmospheric sciences. The Moderate Resolution Imaging Spectroradiometer and the European Centre for Medium-Range Weather Forecasts ERA-5 reanalysis data are employed to systematically study the ACI over the monsoon region in Pakistan. Based on the monsoon occurrence and rainfall intensity, the whole region is divided into three sub-regions labeled as highly intensive (R1), moderately intensive (R2) and weak (R3) monsoon region. The results indicate that the monthly mean Aerosol Optical Depth (AOD) peaks in the summer monsoon months (Jun, Jul, Aug, Sep). Here, the well-known Twomey effect whereby the Cloud Droplet Radius (CDR) decreases with increasing AOD holds only over R3; the opposite effects (Anti-Twomey effect) are found over R1 and R2, all passing the test of statistical significance (p<0.05). The multi-year AOD is found to be positively correlated with Cloud Liquid Water Path (CLWP) and Cloud Optical Depth (COD) over R1 and R2, suggesting that thicker clouds containing more water droplets are formed in polluted atmosphere. Over R3, decreases in CLWP and COD are found with increasing AOD only when AOD is less than~0.325. The analysis of ACI over R1 and R2 during the winter months shows similar but stronger responses of CDR, CLWP and COD to the variation in AOD. The weaker responses during the summer monsoon season may attributed to the occurrence of high level cloud and unstable atmospheric condition. Further investigation of the influences of Relative Humidity and pressure vertical velocity on the CDR-AOD relationships shows that although the magnitude of the CDR-AOD correlations change with meteorological conditions, the sign of correlations remain unchanged with meteorological conditions.
54 ENVIRONMENTAL SCIENCES↗
Bioconversion and quantification of humic substances from low rank coals using indigenous fungal isolates
The major portion of coals around the world belongs to lignitic origin, and burning of these Low Rank Coals (LRCs) not only produces energy, but also release harmful gases into the environment. On the other hand, coal is a mega source of fossilized carbon compounds that can be utilized in diverse range of carbon/organic industries. Biosolubilization is one of the safest and economical way to consume these LRCs for the harvest of humic and fulvic acids for industrial applications. Present studies deal with solubilization of coal samples from five different mines of Punjab, Pakistan by indigenously isolated fungus. From a number of indigenously isolated fungal isolates, an isolate NF-2 was selected based on its solubilization potential on solid Sabouraud medium. The intensity of coal biosolubilization was found maximum for coal sample B-1 (59%) and lowest for sample B-26 (17.2%) with 5% (w/v) pulp density at 28 ± 2°C. Humification index value (A 4 /A 6 ) for biosolubilized products of coal sample B-1 was found 6.18 which was much higher than the A 4 /A 6 value (4.27) of commercially available standard humic acid. Biosolubilized products from coal sample B-1 was found maximum with 8681 mg/L humic acid concentration as determined by standard curve method. FTIR and FE-SEM analyses of sample B-1 treated with NF-2 confirmed the structural break down and solubilization of coal. Molecular identification of fungal isolate NF-2 showed 100% similarity to Aspergillus flavus. Here, this work paves the way to utilize lignitic coals for the environment friendly and low-cost production of humic acids by fungal biosolubilization as an alternate to chemical methods.
59 BASIC BIOLOGICAL SCIENCES↗
Source Contributions to Fine Particulate Matter and Attributable Mortality in India and the Surrounding Region
Fine particulate matter (PM 2.5 ) is a leading mortality risk factor in India and the surrounding region of South Asia. This study evaluates the contribution of emission sectors and fuels to PM 2.5 mass for 29 states in India and 6 surrounding countries (Pakistan, Bangladesh, Nepal, Bhutan, Sri Lanka, and Myanmar) by combining source-specific emission estimates, stretched grid simulations from a chemical transport model, high resolution hybrid PM 2.5 , and disease-specific mortality estimates. We find that 1.02 (95% Confidence Interval (CI): 0.78-1.26) million deaths in South Asia attributable to ambient PM 2.5 in 2019 were primarily from three leading sectors: residential combustion (28%), industry (15%), and power generation (12%). Solid biofuel is the leading combustible fuel contributing to the PM 2.5 -attributable mortality (31%), followed by coal (17%), and oil and gas (14%). State-level analyses reveal higher residential combustion contributions (35%-39%) in states (Delhi, Uttar-Pradesh, Haryana) with high ambient PM 2.5 (>95 µg/m 3 ). The combined mortality burden associated with residential combustion (ambient) and household air pollution (HAP) in India is 0.72 million (95% CI:0.54-0.89) (68% attributable to HAP, 32% attributable to residential combustion). Our results illustrate the potential to reduce PM 2.5 mass and improve population health by reducing emissions from traditional energy sources across multiple sources in South Asia.
63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
Examining the Climate Effects of a Regional Nuclear Weapons Exchange Using a Multiscale Atmospheric Modeling Approach.
Abstract not provided.
Wagman, Benjamin Moore↗
Historical and Future Global Irrigation Energy Consumption by Fuel and Region
Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.
Global Change Analysis Model (GCAM)↗
Global peak water limit of future groundwater withdrawals
Over the past 50 years, humans have extracted the Earth’s groundwater stocks at a steep rate, largely to fuel global agro-economic development. Given society’s growing reliance on groundwater, we explore ‘peak water limits’ to investigate whether, when and where humanity might reach peak groundwater extraction. Using an integrated global model of the coupled human–Earth system, we simulate groundwater withdrawals across 235 water basins under 900 future scenarios of global change over the twenty-first century. Here we find that global non-renewable groundwater withdrawals exhibit a distinct peak-and-decline signature, comparable to historical observations of other depletable resources (for example, minerals), in nearly all (98%) scenarios, peaking on average at 625 km 3 yr -1 around mid-century, followed by a decline through 2100. The peak and decline occur in about one-third (82) of basins, including 21 that may have already peaked, exposing about half (44%) of the global population to groundwater stress. Most of these basins are in countries with the highest current extraction rates, including the United States, Mexico, Pakistan, India, China, Saudi Arabia and Iran. Furthermore, these groundwater-dependent basins will probably face increasing costs of groundwater and food production, suggesting important implications for global agricultural trade and a diminished role for groundwater in meeting global water demands during the twenty-first century.
58 GEOSCIENCES↗
Identification of 2 Novel Subtypes of Hepatitis C Virus Genotype 8 and a Potential New Genotype Successfully Treated With Direct Acting Antivirals
Abstract Background Hepatitis C virus (HCV) has high genetic diversity and is classified into 8 genotypes and >90 subtypes, with some endemic to specific world regions. This could compromise direct-acting antiviral efficacy and global HCV elimination. Methods We characterized HCV subtypes “rare” in the United Kingdom (non-1a/1b/2b/3a/4d) by means of whole-genome sequencing via a national surveillance program. Genetic analyses to determine the genotype of samples with unresolved genotypes were undertaken by comparison with International Committee on Taxonomy of Viruses HCV reference sequences. Results Two HCV variants were characterized as being closely related to the recently identified genotype (GT) 8, with >85% pairwise genetic distance similarity to GT8 sequences and within the typical intersubtype genetic distance range. The individuals infected by the variants were UK residents originally from Pakistan and India. In contrast, a third variant was only confidently identified to be more similar to GT6 compared with other genotypes across 6% of the genome and was isolated from a UK resident originally from Guyana. All 3 were cured with pangenotypic direct-acting antivirals (sofosbuvir-velpatasvir or glecaprevir-pibrentasvir) despite the presence of resistance polymorphisms in NS3 (80K/168E), NS5A (28V/30S/62L/92S/93S) and NS5B (159F). Conclusions This study expands our knowledge of HCV diversity by identifying 2 new GT8 subtypes and potentially a new genotype.
59 BASIC BIOLOGICAL SCIENCES↗
Impact of Soil Salinity on the Cowpea Nodule-Microbiome and the Isolation of Halotolerant PGPR Strains to Promote Plant Growth under Salinity Stress
Cowpea is one of the major legumes cultivated in arid and semiarid regions of the world. Four soil-microbial samples (SS-1 through SS-4) collected from semiarid soils in Punjab, Pakistan were planted with cowpea (Vigna unguiculata) crops, which were grown under salinity stress to analyze bacterial composition in the rhizosphere and within nodules using cultivation-dependent and -independent methods. Two varieties, 603 and the salt-tolerant CB 46, were each inoculated with or without the four different native soil samples or grown in medium either N-deficient (-N) or supplemented with N (+N). Plants inoculated with soil samples SS-2 and SS-4 grew better than plants inoculated with SS-1- and SS-3 and grew comparably with the +N controls. Environmental DNA (eDNA) was isolated from SS-1 and SS-4, and, by 16S ribosomal RNA sequencing, the soil microbiomes consisted mainly of Actinobacteria, Firmicutes, Proteobacteria, and other nonproteobacterial genera. However, analysis of eDNA isolated from cowpea nodules established by the trap plants showed that the nodule microbiome consisted almost exclusively of proteobacterial sequences, particularly species of Bradyrhizobium. Bacteria were isolated from both soils and nodules, and 34 of the 51 isolates tested positive for plant-growth-promoting rhizobacteria traits in plate assays. Many could serve as future inocula for crops in arid soils. The discrepancy between the types of bacteria isolated by culturing bacteria isolated from surface-sterilized cowpea nodules (proteobacteria and nonproteobacteria) versus those detected by sequencing DNA isolated from the nodules (proteobacteria) from cowpea nodules (proteobacteria and nonproteobacteria) versus those detected in the nodule microbiome (proteobacteria) needs further study.
59 BASIC BIOLOGICAL SCIENCES↗