Inventory of main greenhouse gas emissions from energy sector in Palestine.

This paper analyzes the building process of the main greenhouse gas (GHG) emissions (CO2, CH4 and N2O) inventory from the energy sector in Palestine. The paper includes determination tools, i.e., emission factors, to estimate the amounts of national GHG emissions from sub-sectors of energy including energy industries, manufacturing industries and construction, transport and other sectors (households, agriculture and commerce and public services). The results show that the total amount of national GHG emissions from the energy sector in 2016 was 4131 thousand metric tons of CO2-equivalent (TtCO2e), which represented 0.011% of the total global GHG emissions. The average value of GHG emissions per capita from the energy sector was 0.86 tCO2e in Palestine, and its gross domestic product was estimated at 3212 $/ton of CO2e. The estimated amounts of CO2, CH4 and N2O emission from the energy sector were 4022, 49 and 60 TtCO2e, respectively. The transport and household sub-sectors dominated the national GHG emissions from the entire energy sector by 58 and 32%, respectively. In general, fuels including diesel, gasoline, wood and charcoal and liquefied petroleum gas made most of the total amount of the national GHG emissions from the energy sector at 50, 18, 18 and 12%, respectively. Finally, the mitigation actions included in the first nationally determined contribution of Palestine and recommendations to help lower the national GHG emissions from the Palestinian energy sector are provided.

In situ ATR-FTIR and surface complexation modeling studies on the adsorption of dimethylarsinic acid and p-arsanilic acid on iron-(oxyhydr)oxides.

Arsenic is an element that exists naturally in many rocks and minerals around the world. It also accumulates in petroleum, shale, oil sands, and coal deposits as a result of biogeochemical processes, and it has been found in fly ash from the combustion of solid biofuels. Arsenic compounds in their organic and inorganic forms pose both a health and an environmental risk, and continue to be a challenge to the energy industry. The environmental fate and removal technologies of arsenic compounds are controlled to a large extent by their surface interactions with inorganic and organic adsorbents. We report thermodynamic binding constants, K(binding), from applying the triple-layer surface complexation model to adsorption isotherm and pH envelope data for dimethylarsinic acid (DMA) and p-arsanilic acid (p-AsA) on hematite and goethite. Ligand exchange reactions were constructed based on the interpretation of ATR-FTIR spectra of DMA and p-AsA surface complexes. Surface coverage of adsorbates was quantified in situ from the spectral component at 840 cm(-1). The best fit to the DMA adsorption data was obtained using outer-sphere complex formation, whereas for p-AsA, the best fit was obtained using two monodentate inner-sphere surface complexes. The significance of the results is discussed in relation to improving modeling tools used by environmental regulators and the energy sector for optimum control of arsenic content in fuels.

Development of a flow system for the determination of cadmium in fuel alcohol using vermicompost as biosorbent and flame atomic absorption spectrometry.

In this study a method for the determination of cadmium in fuel alcohol using solid-phase extraction with a flow injection analysis system and detection by flame atomic absorption spectrometry was developed. The sorbent material used was a vermicompost commonly used as a garden fertilizer. The chemical and flow variables of the on-line preconcentration system were optimized by means of a full factorial design. The selected factors were: sorbent mass, sample pH, buffer concentration and sample flow rate. The optimum extraction conditions were obtained using sample pH in the range of 7.3-8.3 buffered with tris(hydroxymethyl)aminomethane at 50 mmol L(-1), a sample flow rate of 4.5 mL min(-1) and 160 mg of sorbent mass. With the optimized conditions, the preconcentration factor, limit of detection and sample throughput were estimated as 32 (for preconcentration of 10 mL sample), 1.7 microg L(-1) and 20 samples per hour, respectively. The analytical curve was linear from 5 up to at least 50 microg L(-1), with a correlation coefficient of 0.998 and a relative standard deviation of 2.4% (35 microg L(-1), n=7). The developed method was successfully applied to spiked fuel alcohol, and accuracy was assessed through recovery tests, with recovery ranging from 94% to 100%.