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27. Biogas Production Potential from Livestock Manure in Pakistan

Author

Khan, Muhammad U., Ahmad, Muhammad, Sultan, Muhammad, Ihsanullah, Sohoo, Ghimire, Prakash C., Zahid, Azlan, Sarwar, Abid, Farooq, Muhammad, Sajjad, Uzair, Abdeshahian, Peyman, and Yousaf, Maryam

Subjects
anaerobic digestion, Environmental effects of industries and plants, Landwirtschaft, Veterinärmedizin [630], TJ807-830, Ingenieurwissenschaften [620], TD194-195, renewable energy, Renewable energy sources, Environmental sciences, biogas production, livestock manure, ddc:630, GE1-350, ddc:620, ddc:600, Technik [600]
Abstract

Pakistan is facing a severe energy crisis due to its heavy dependency on the import of costly fossil fuels, which ultimately leads to expansive electricity generation, a low power supply, and interruptive load shedding. In this regard, the utilization of available renewable energy resources within the country for production of electricity can lessen this energy crisis. Livestock waste/manure is considered the most renewable and abundant material for biogas generation. Pakistan is primarily an agricultural country, and livestock is widely kept by the farming community, in order to meet their needs. According to the 2016–2018 data on the livestock population, poultry held the largest share at 45.8%, followed by buffaloes (20.6%), cattle (12.7%), goats (10.8%), sheep (8.4%), asses (1.3%), camels (0.25%), horses (0.1%), and mules (0.05%). Different animals produce different amounts of manure, based upon their size, weight, age, feed, and type. The most manure is produced by cattle (10–20 kg/day), while poultry produce the least (0.08–0.1 kg/day). Large quantities of livestock manure are produced from each province of Pakistan, Punjab province was the highest contributor (51%) of livestock manure in 2018. The potential livestock manure production in Pakistan was 417.3 million tons (Mt) in 2018, from which 26,871.35 million m3 of biogas could be generated—with a production potential of 492.6 petajoules (PJ) of heat energy and 5521.5 MW of electricity. Due to its favorable conditions for biodigester technologies, and through the appropriate development of anaerobic digestion, the currently prevailing energy crises in Pakistan could be eliminated.

Published
2021
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39. Simulating the Impact of Sowing Methods and Water Deficit Levels on Wheat Yield Under Semi-Arid Environment.

Author

Ansari, Rubina, Cheema, Muhammad Jehanzeb Masud, Liaqat, Muhammad Usman, Sarwat, Faiza, ul Haq Khan, Hafiz Ihsan, Zahid, Azlan, and Mushtaq, Sumra

Subjects
DEFICIT irrigation, WATER levels, WHEAT yields, WATER efficiency, WHEAT, GRAIN yields
Abstract

The present study was undertaken to investigate the effect of deficit irrigation (DI) on wheat grain yield under different sowing methods. The field experiment was layout using randomized complete block design (RCBD) with split plot arrangements by keeping four DI regimes (I1, I2, I3, I4 as 0%, 20%, 35% and 50% deficit respectively) and two sowing methods (bed sowing and drill sowing) in sub plots and main plots respectively with three repeats. Research also evaluated the ability of AquaCrop model to simulate wheat gain yield and biological yield under full and deficit water conditions in a semi-arid environment. The model was calibrated for the full irrigation treatments under both sowing method and remaining six treatments were used for validation purpose. The results showed that the maximum grain yield was recorded 5.724 tons/ha for 0% DI treatment under drill sowing method. The DI (I1, I2, I3, and I4) levels under drill sowing method gave 13.12%, 14.28%, 16.38%, and 19.59% more grain yield than the corresponding DI levels (I1, I2, I3, and I4) under bed sowing method respectively, whereas the average crop water use efficiency for I1, I2, I3, and I4 treatments under bed sowing was found higher than the corresponding treatments under drill sowing method by 17.94%, 14.34%, 9.96%, and 5.36% respectively. AquaCrop model simulated gain yields and biological yield showed a good agreement with measured values of both gain yield (RMSE=0.25ton ha-1, NRMSE= 5.41, d=0.96 and NSE=0.79) and biological yield (RMSE=0.59 ton ha-1, NRMSE= 5.36, d=0.94 and NSE=0.74). The high values of the statistical indicators confirmed that the AquaCrop model (v3.0) can simulate wheat yield under no to mild water stress conditions which makes it very useful for evaluating the deficit irrigation strategies under different cultural and management practices with minimal input data requirements and ease of use. [ABSTRACT FROM AUTHOR]

Published
2019

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