Portuguese agriculture and the evolution of greenhouse gas emissions—can vegetables control livestock emissions?

One of the most serious externalities of agricultural activity relates to greenhouse gas emissions. This work tests this relationship for the Portuguese case by examining data compiled since 1961. Employing cointegration techniques and vector error correction models (VECMs), we conclude that the evolution of the most representative vegetables and fruits in Portuguese production are associated with higher controls on the evolution of greenhouse gas emissions. Reversely, the evolution of the output levels of livestock and the most representative animal production have significantly increased the level of CO₂ (carbon dioxide) reported in Portugal. We also analyze the cycle length of the long-term relationship between agricultural activity and greenhouse gas emissions. In particular, we highlight the case of synthetic fertilizers, whose values of CO₂ have quickly risen due to changes in Portuguese vegetables, fruit, and animal production levels.

     

Emission factors of atmospheric and climatic pollutants from crop residues burning

Biomass burning is a common agricultural practice, because it allows elimination of postharvesting residues; nevertheless, it involves an inefficient combustion process that generates atmospheric pollutants emission, which has implications on health and climate change. This work focuses on the estimation of emission factors (EFs) of PM_2.5, PM₁₀, organic carbon (OC), elemental carbon (EC), carbon monoxide (CO), carbon dioxide (CO₂), and methane (CH₄) of residues from burning alfalfa, barley, beans, cotton, maize, rice, sorghum, and wheat in Mexico. Chemical characteristics of the residues were determined to establish their relationship with EFs, as well as with the modified combustion efficiency (MCE). Essays were carried out in an open combustion chamber with isokinetic sampling, following modified EPA 201-A method. EFs did not present statistical differences among different varieties of the same crop, but were statistically different among different crops, showing that generic values of EFs for all the agricultural residues can introduce significant uncertainties when used for climatic and atmospheric pollutant inventories. EFs of PM_2.5 ranged from 1.19 to 11.30 g kg^?1, and of PM₁₀ from 1.77 to 21.56 g kg^?1. EFs of EC correlated with lignin content, whereas EFs of OC correlated inversely with carbon content. EFs of EC and OC in PM_2.5 ranged from 0.15 to 0.41 g kg^?1 and from 0.33 to 5.29 g kg^?1, respectively, and in PM₁₀, from 0.17 to 0.43 g kg^?1 and from 0.54 to 11.06 g kg^?1. CO₂ represented the largest gaseous emissions volume with 1053.35–1850.82 g kg^?1, whereas the lowest was CH₄ with 1.61–5.59 g kg^?1. CO ranged from 28.85 to 155.71 g kg^?1, correlating inversely with carbon content and MCE. EFs were used to calculate emissions from eight agricultural residues burning in the country during 2016, to know the potential mitigation of climatic and atmospheric pollutants, provided this practice was banned.

Implications: The emission factors of particles, short-lived climatic pollutants, and atmospheric pollutants from the crop residues burning of eight agricultural wastes crops, determined in this study using a standardized method, provides better knowledge of the emissions of those species in Latin America and other developing countries, and can be used as inputs in air quality models and climatic studies. The EFs will allow the development of more accurate inventories of aerosols and gaseous pollutants, which will lead to the design of effective mitigation strategies and planning processes for sustainable agriculture.     

Influencing factors of carbon emissions and their trends in China and India: a machine learning method

China and India are the largest coal consumers and the most populated countries in the world. With industrial and population growth, the need for energy has increased, which has inevitably led to an increase in carbon dioxide (CO₂) emissions because both countries depend on fossil fuel consumption. This paper investigates the impact of energy consumption, financial development (FD), gross domestic product (GDP), population, and renewable energy on CO₂ emissions. The study applies the long short-term memory (LSTM) method, a novel machine learning (ML) approach, to examine which influencing driver has the greatest and smallest impact on CO₂ emissions; correspondingly, this study builds a model for CO₂ emission reduction. Data collected between 1990 and 2014 were analyzed, and the results indicated that energy consumption had the greatest effect and renewable energy had the smallest impact on CO₂ emissions in both countries. Subsequently, we increased the renewable energy coefficient by one and decreased the energy consumption coefficient by one while keeping all other factors constant, and the results predicted with the LSTM model confirmed the significant reduction in CO₂ emissions. Finally, this study forecasted a CO₂ emission trend, with a slowdown predicted in China by 2022; however, CO₂ emission’s reduction is not possible in India until 2023. These results suggest that shifting from nonrenewable to renewable sources and lowering coal consumption can reduce CO₂ emissions without harming economic development.

     

Scenarios of animal waste production and fertilizer use and associated ammonia emission for the developing countries

Livestock production and the use of synthetic fertilizer are responsible for about half of the global emission of NH₃. Depending on the animal category between 10 and 36% of the N in animal excreta is lost as NH₃. The current annual NH₃ emission in developing countries of 15 million ton N accounts for of the global emission from animal excreta. In addition, 7.2 million tons NH₃N of synthetic N fertilizers are lost as NH₃ in developing countries. This is 80% of the global NH₃ emission from synthetic fertilizer's use. Along with human population increase and economic growth, livestock production in developing countries may even increase by a factor of 3 between now and 2025. The net result of rapid increase of livestock production combined with higher efficiency is an increase in NH₃ emissions of only 60% from 15 to 24 million tons NH₃N between 1990 and 2025 in developing countries. Livestock production is an important consumer of feedstuffs, mainly cereals, thereby inducing additional demand for synthetic fertilizers. Despite the projected major increase of synthetic fertilizer use from 42 to 106 million ton N between 1990 and 2025, the NH₃ loss in developing countries may decrease if a shift towards other fertilizer types, that are less vulnerable to NH₃ volatilization, is realized. According to the scenario, the total emission of NH₃ associated with food production in developing countries will increase from 22 to 30 million ton N yr⁻¹ between 1990 and 2025. Although the NH₃ emission increases more slowly than food production, in particular, animal production may show geographic concentration in certain regions, which may lead to high local emission densities and associated environmental problems.     

Soil CO2 fluxes from direct seeding rice fields under two tillage practices in central China

Agricultural practices affect the production and emission of carbon dioxide (CO₂) from paddy soils. It is crucial to understand the effects of tillage and N fertilization on soil CO₂ flux and its influencing factors for a better comprehension of carbon dynamics in subtropical paddy ecosystems. A 2-yr field study was conducted to assess the effects of tillage (conventional tillage [CT] and no-tillage [NT]) and N fertilization (0 and 210 kg N ha^?1) on soil CO₂ fluxes during the 2008 and 2009 rice growing seasons in central China. Treatments were established following a split-plot design of a randomized complete block with tillage practices as the main plot and N fertilizer level as the split-plot treatment. The soil CO₂ fluxes were measured 24 times in 2008 and 17 times in 2009. N fertilization did not affect soil CO₂ emissions while tillage affected soil CO₂ emissions, where NT had similar soil CO₂ emissions to CT in 2008, but in 2009, NT significantly increased soil CO₂ emissions. Cumulative CO₂ emissions were 2079–2245 kg CO₂–C ha^?1 from NT treatments, and 2084–2141 kg CO₂–C ha^?1 from CT treatments in 2008, and were 1257–1401 kg CO₂–C ha^?1 from NT treatments, and 1003–1034 kg CO₂–C ha^?1 from CT treatments in 2009, respectively. Cumulative CO₂ emissions were significantly related to aboveground biomass and soil organic C. Before drainage of paddy fields, soil CO₂ fluxes were significantly related to soil temperature with correlation coefficients (R) of 0.67–0.87 in 2008 and 0.69–0.85 in 2009; moreover, the Q₁₀ values ranged from 1.28 to 1.55 and from 2.10 to 5.21 in 2009, respectively. Our results suggested that NT rice production system appeared to be ineffective in decreasing carbon emission, which suggested that CO₂ emissions from integrated rice-based system should be taken into account to assess effects of tillage.     

Changing pollutants to green biogases for the crop food cycle chain

Purpose

When fossil fuels on the Earth are used up, which kind of green energy can be used to replace them? Do every bioenergy generation or crop food chain results in environmental pollution? These questions are major concerns in a world facing restricted supplies of energy and food as well as environmental pollutions. To alleviate these issues, option biogases are explored in this paper.

Materials and methods

Two types of biogas generators were used for modifying the traditional crop food chain [viz. from atmospheric CO₂ photosynthesis to crops, crop stem/husk biowastes (burnt in cropland or as home fuels), to livestock droppings (dumping away), pork and people foods, then to CO₂], via turning the biowaste pollutants into green bioenergies. By analyzing the traditional food chain via observation method, the drawbacks of by-product biowastes were revealed. Also, the whole cycle chain was further analyzed to assess its ??greenness,?? using experimental data and other information, such as the material balance (e.g., the absorbed CO₂, investment versus generated food, energy, and wastes).

Results and discussion

The data show that by using the two types of biogas generators, clean renewable bioenergy, crop food, and livestock meat could be continuously produced without creating any waste to the world. The modification chain largely reduced CO₂ greenhouse gas and had a low-cost investment. The raw materials for the gas generators were only the wastes of crop stems and livestock droppings. Thus, the recommended CO₂ bioenergy cycle chain via the modification also greatly solved the environmental biowaste pollutions in the world.

Conclusions

The described two type biogases effectively addressed the issues on energy, food, and environmental pollution. The green renewable bioenergy from the food cycle chain may be one of suitable alternatives to fossil and tree fuels for agricultural countries.     

Does agriculture-induced environmental Kuznets curve exist in developing countries?

Even though the economic growth and the increased agricultural production bring welfare increment, they could also load significant environmental costs to society. This study aims to investigate the existence of agriculture-induced EKC hypothesis in 47 developing countries during 1976–2017 by using dynamic panel data estimators. According to the long-run findings of the DOLS and the FMOLS estimators, there is an inverted U-shaped relationship that exists between income and the CO₂ emissions, while agricultural production has a negative impact on environmental quality. In addition, the PMG estimator is also employed for robustness check. Likewise the DOLS and the FMOLS findings, the long-run results of the PMG estimator also support the existence of agriculture-induced EKC for developing countries. The empirical findings of this study provide stimulus results of policy makers to re-consider their current production infrastructure of agricultural sector to achieve sustainable development.

     

Trends in primary particulate matter emissions from Canadian agriculture

Particulate matter (PM) has long been recognized as an air pollutant due to its adverse health and environmental impacts. As emission of PM from agricultural operations is an emerging air quality issue, the Agricultural Particulate Matter Emissions Indicator (APMEI) has been developed to estimate the primary PM contribution to the atmosphere from agricultural operations on Census years and to assess the impact of practices adopted to mitigate these emissions at the soil landscape polygon scale as part of the agri-environmental indicator report series produced by Agriculture and Agri-Food Canada. In the APMEI, PM emissions from animal feeding operations, wind erosion, land preparation, crop harvest, fertilizer and chemical application, grain handling, and pollen were calculated and compared for the Census years of 1981–2006. In this study, we present the results for PM₁₀ and PM_2.5, which exclude chemical application and pollen sources as they only contribute to total suspended particles. In 2006, PM emissions from agricultural operations were estimated to be 652.6 kt for PM₁₀ and 158.1 kt for PM_2.5. PM emissions from wind erosion and land preparation account for most of PM emissions from agricultural operations in Canada, contributing 82% of PM₁₀ and 76% of PM_2.5 in 2006. Results from the APMEI show a strong reduction in PM emissions from agricultural operations between 1981 and 2006, with a decrease of 40% (442.8 kt) for PM₁₀ and 47% (137.7 kt) for PM_2.5. This emission reduction is mainly attributed to the adoption of conservation tillage and no-till practices and the reduction in the area of summerfallow land.

Implications: Increasing sustainability in agriculture often means adapting management practices to have a beneficial impact on the environment while maintaining or increasing production and economic benefits. We developed an inventory of primary PM emissions from agriculture in Canada to better quantify the apportionment, spatial distribution, and trends for Census years 1981–2006. We found major reductions of 40% in PM₁₀ and 47% in PM_2.5 emissions over the 25-yr period as a co-benefit of increasing carbon sequestration in agricultural soils. Indeed, farmers adopted conservation tillage/no-till practices, increased usage of cover crops, and reduced summerfallow, in order to increase soil organic matter and reduce carbon dioxide emissions, which also reduced primary PM emissions, although the agricultural production increased over the period.     

Economic complexity,ICT, biomass energy consumption,and environmental degradation: evidence from Iran

Economic complexity, biomass energy consumption, and information communication technology (ICT) have diverse impacts on energy consumption and carbon dioxide (CO₂) emissions. Nevertheless, analysis of these variable effects is not addressed in the previous literature; the antiqueness of this article is stuffing this gap. This study assessed the relationship between gross domestic product (GDP) per capita, biomass consumption, economic complexity index (ECI), ICT, and CO₂ emissions in Iran in 1994–2018. The autoregressive distributed lag (ARDL) model and the quantile regression (QR) econometric technique were used to investigate the factors affecting CO₂ emissions in the tails of the conditional distribution. The share of each influential factor was predicted through the variance decomposition analysis (VD) for the next 10 years. The empirical results showed a long-run relationship between the variables. So, the variables of biomass consumption, ECI, and ICT improve the quality of the environment in Iran by reducing CO₂ emissions, and the per capita GDP variable increases CO₂ emissions. Results suggest no evidence indicating the presence of environmental Kuznets curve (EKC); however, QR demonstrated the existence of EKCs in the lower quantiles of the conditional distribution. The ECI will have the most share to change the CO₂ emissions in the future. The income threshold should be determined at the turning point of the EKC to increase economic development. Moreover, investing in increasing biomass consumption is vital. Policymakers also need to consider strict added value for the export of products.

     

Greenhouse gas emissions from penguin guanos and ornithogenic soils in coastal Antarctica: Effects of freezing–thawing cycles

In coastal Antarctica, freezing and thawing influence many physical, chemical and biological processes for ice-free tundra ecosystems, including the production of greenhouse gases (GHGs). In this study, penguin guanos and ornithogenic soil cores were collected from four penguin colonies and one seal colony in coastal Antarctica, and experimentally subjected to three freezing–thawing cycles (FTCs) under ambient air and under N₂. We investigated the effects of FTCs on the emissions of three GHGs including nitrous oxide (N₂O), carbon dioxide (CO₂) and methane (CH₄). The GHG emission rates were extremely low in frozen penguin guanos or ornithogenic soils. However, there was a fast increase in the emission rates of three GHGs following thawing. During FTCs, cumulative N₂O emissions from ornithogenic soils were greatly higher than those from penguin guanos under ambient air or under N₂. The highest N₂O cumulative emission of 138.24 μg N₂O–N kg^?1 was observed from seal colony soils. Cumulative CO₂ and CH₄ emissions from penguin guanos were one to three orders of magnitude higher than those from ornithogenic soils. The highest cumulative CO₂ (433.0 mgCO₂–C kg^?1) and CH₄ (2.9 mgCH₄–C kg^?1) emissions occurred in emperor penguin guanos. Penguin guano was a stronger emitter for CH₄ and CO₂ while ornithogenic soil was a stronger emitter for N₂O during FTCs. CO₂ and CH₄ fluxes had a correlation with total organic carbon (TOC) and soil/guano moisture (M_c) in penguin guanos and ornithogenic soils. The specific CO₂–C production rate (CO₂–C/TOC) indicated that the bioavailability of TOC was markedly larger in penguin guanos than in ornithogenic soils during FTCs. This study showed that FTC-released organic C and N from sea animal excreta may play a significant role in FTC-related GHG emissions, which may account for a large proportion of annual fluxes from tundra ecosystems in coastal Antarctica.     

Bottom-up uncertainty estimates of global ammonia emissions from global agricultural production systems

Here we present an uncertainty analysis of NH₃ emissions from agricultural production systems based on a global NH₃ emission inventory with a 5×5 min resolution. Of all results the mean is given with a range (10% and 90% percentile). The uncertainty range for the global NH₃ emission from agricultural systems is 27–38 (with a mean of 32) Tg NH₃-N yr⁻¹, N fertilizer use contributing 10–12 (11) Tg yr⁻¹ and livestock production 16–27 (21) Tg yr⁻¹. Most of the emissions from livestock production come from animal houses and storage systems (31–55%); smaller contributions come from the spreading of animal manure (23–38%) and grazing animals (17–37%). This uncertainty analysis allows for identifying and improving those input parameters with a major influence on the results. The most important determinants of the uncertainty related to the global agricultural NH₃ emission comprise four parameters (N excretion rates, NH₃ emission rates for manure in animal houses and storage, the fraction of the time that ruminants graze and the fraction of non-agricultural use of manure) specific to mixed and landless systems, and total animal stocks. Nitrogen excretion rates and NH₃ emission rates from animal houses and storage systems are shown consistently to be the most important parameters in most parts of the world. Input parameters for pastoral systems are less relevant. However, there are clear differences between world regions and individual countries, reflecting the differences in livestock production systems.     

Emissions profile from new and in-use handheld, 2-stroke engines

The objective of this study was to characterize exhaust emissions from a series of handheld, 2-stroke small engines. A total of 23 new and used engines from model years 1981–2003 were studied; these engines spanned three phases of emission control (pre-control, phase-1, phase-2). Measured emissions included carbon monoxide (CO), carbon dioxide (CO₂), nitrogen oxides (NO_x), hydrocarbons (HC), fine particulate matter (PM_2.5), and sulfur dioxide (SO₂). Emissions reductions in CO (78%) and HC (52%) were significant between pre-control and phase-2 engines. These reductions can be attributed to improvements in engine design, reduced scavenging losses, and implementation of catalytic exhaust control. Total hydrocarbon emissions were strongly correlated with fuel consumption rates, indicating varying degrees of scavenging losses during the intake/exhaust stroke. The use of a reformulated gasoline containing 10% ethanol resulted in a 15% decrease in HC and a 29% decrease in CO emissions, on average. Increasing oil content of 2-stroke engine fuels results in a substantial increase of PM_2.5 emissions as well as smaller increases in HC and CO emissions. Results from this study enhance existing emission inventories and appear to validate predicted improvements to ambient air quality through implementation of new phase-2 handheld emission standards.     

Does energy consumption contribute to environmental pollutants? evidence from SAARC countries

The objective of the study is to examine the causal relationship between energy consumption and environmental pollutants in selected South Asian Association for Regional Cooperation (SAARC) countries, namely, Bangladesh, India, Nepal, Pakistan, and Srilanka, over the period of 1975–2011. The results indicate that energy consumption acts as an important driver to increase environmental pollutants in SAARC countries. Granger causality runs from energy consumption to environmental pollutants, but not vice versa, except carbon dioxide (CO₂) emissions in Nepal where there exists a bidirectional causality between CO₂ and energy consumption. Methane emissions in Bangladesh, Pakistan, and Srilanka and extreme temperature in India and Srilanka do not Granger cause energy consumption via both routes, which holds neutrality hypothesis. Variance decomposition analysis shows that among all the environmental indicators, CO₂ in Bangladesh and Nepal exerts the largest contribution to changes in electric power consumption. Average precipitation in India, methane emissions in Pakistan, and extreme temperature in Srilanka exert the largest contribution.     

Carbon dioxide emission in relation with irrigation and organic amendments from a sweet corn field

Soil moisture and organic matter level affects soil respiration and microbial activities, which in turn impact greenhouse gas (GHG) emissions. This study was conducted to evaluate the effect of irrigation levels (75% [deficit], 100% [full], and 125% [excess] of reference crop evapotranspiration requirements), and organic amendments (OA) type (chicken manure [CM] and bone meal [BM]) and OA application rates (0,168, 336 and 672 kg total N ha^?1) on (i) soil physical properties (bulk density, organic matter content and soil moisture content) and (ii) soil carbon dioxide (CO₂) emissions from a highly weathered tropical Hawai'ian soil. Carbon dioxide readings were consistently taken once or twice a week for the duration of the cropping season. A drip irrigation system was used to apply the appropriate amount of irrigation water to the treatment plots. Treatments were randomly selected and corresponding organic amendments were manually incorporated into the soil. Plots were cultivated with sweet corn (Zea mays ‘SS-16’). Soil moisture content within and below the rootzone was monitored using a TDR 300 soil moisture sensor (Spectrum Technologies, Inc., Plainfield, IL, USA) connected with 12 cm long prongs. Soil bulk density and organic matter content were determined at the end of the cropping season. Analysis of variance results revealed that OA type, rate, and their interaction had significant effect on soil CO₂ flux (P < 0.05). Among the OA rates, all CM mostly resulted in significantly higher soil CO₂ fluxes compared to BM and control treatment (p < 0.05). The two highest rates of BM treatment were not significantly different from the control with regard to soil CO₂ flux. In addition, organic amendments affected soil moisture dynamics during the crop growing season and organic matter content measured after the crop harvest. While additional studies are needed to further investigate the effect of irrigation levels on soil CO₂ flux, it is recommended that in order to minimize soil CO₂ emissions, BM soil amendments could be a potential option to reduce soil CO₂ fluxes from agricultural fields similar to the one used in this study.     

Carbon emission from global hydroelectric reservoirs revisited

Substantial greenhouse gas (GHG) emissions from hydropower reservoirs have been of great concerns recently, yet the significant carbon emitters of drawdown area and reservoir downstream (including spillways and turbines as well as river reaches below dams) have not been included in global carbon budget. Here, we revisit GHG emission from hydropower reservoirs by considering reservoir surface area, drawdown zone and reservoir downstream. Our estimates demonstrate around 301.3 Tg carbon dioxide (CO₂)/year and 18.7 Tg methane (CH₄)/year from global hydroelectric reservoirs, which are much higher than recent observations. The sum of drawdown and downstream emission, which is generally overlooked, represents 42 % CO₂ and 67 % CH₄ of the total emissions from hydropower reservoirs. Accordingly, the global average emissions from hydropower are estimated to be 92 g CO₂/kWh and 5.7 g CH₄/kWh. Nonetheless, global hydroelectricity could currently reduce approximate 2,351 Tg CO₂eq/year with respect to fuel fossil plant alternative. The new findings show a substantial revision of carbon emission from the global hydropower reservoirs.     

Estimates of carbon dioxide emissions based on incomplete condition information: a case study of liquefied natural gas in China

Recent calculations of carbon dioxide (CO₂) emissions have faced challenges because data consist of only partial information, which is called “incomplete information.” According to the emission factor method, energy consumption and CO₂ emission factors with incomplete information may lead to unmatched multiplication between themselves, which affects accuracy and increases uncertainties in emission results. To address a specific case of incomplete information that has not been fully explored, we studied the effects of incomplete condition information on the estimates of CO₂ emissions from liquefied natural gas (LNG) in China. Based on Chinese LNG sampling data, we obtained the specific-country CO₂ emission factor for LNG in China and calculated the corresponding CO₂ emissions. By applying hypothesis testing, regression analysis, variance analysis, or Monte Carlo (MC) simulations, the effects of incomplete information on the uncertainty of CO₂ emission calculations in three cases were analyzed. The results indicate that calorific values have more than a 9.8% impact on CO₂ emission factors and CO₂ emissions with incomplete sample information. Regarding incomplete statistical information, the impact of statistical temperature on CO₂ emissions exceeds 5.5%. Regarding incomplete sample and statistical information, sample and statistical temperatures can individually increase estimate biases by more than 5.2%. Significantly, the impacts of sample temperature and statistical temperature may offset each other. Therefore, the incomplete condition information is quite important and cannot be ignored in the estimation of CO₂ emissions from LNG and international fair comparison.

     

Utilization of waste bittern from saltern as a source for magnesium and an absorbent for carbon dioxide capture

During solar salt production, large quantities of bittern, a liquid by-product containing high inorganic substance concentrations, are produced. The purpose of this research was to examine the utilization of waste bittern generated from salterns as a source for Mg production and as an absorbent for carbon dioxide (CO₂) capture. The study was conducted in a sequential two-step process. At NaOH/Mg molar ratios of 2.70–2.75 and pH 9.5–10.0, > 99% Mg precipitation from the bittern was achieved. After washing with water, 100–120 g/L of precipitate containing 94% Mg(OH)₂ was recovered from the bittern. At the optimum NH₄OH concentration of 5%, 120 g of sodium bicarbonate precipitate per liter of bittern were recovered, which was equivalent to 63 g CO₂ captured per liter of bittern. These results can be used to support the use of bittern as a resource and reduce economic losses during solar salt production.     

The challenges of reducing greenhouse gas emissions and air pollution through energy sources: evidence from a panel of developed countries

The objective of the study is to investigate the long-run relationship between climatic factors (i.e., greenhouse gas emissions, agricultural methane emissions, and industrial nitrous oxide emission), air pollution (i.e., carbon dioxide emissions), and energy sources (i.e., nuclear energy; oil, gas, and coal energy; and fossil fuel energy) in the panel of 35 developed countries (including EU-15, new EU member states, G-7, and other countries) over a period of 1975–2012. In order to achieve this objective, the present study uses sophisticated panel econometric techniques including panel cointegration, panel fully modified OLS (FMOLS), and dynamic OLS (DOLS). The results show that there is a long-run relationship between the variables. Nuclear energy reduces greenhouse gases and carbon emissions; however, the other emissions, i.e., agricultural methane emissions and industrial nitrous oxide, are still to increase during the study period. Electricity production from oil, gas, and coal sources increases the greenhouse gases and carbon emissions; however, the intensity to increase emissions is far less than the intensity to increase emissions through fossil fuel. Policies that reduce emissions of greenhouse gases can simultaneously alter emissions of conventional pollutants that have deleterious effects on human health and the environment.     

Investigations of emissions and heterogeneous formation of HONO in a road traffic tunnel

Simultaneous measurements of nitrous acid (HONO) and nitrogen dioxide (NO₂) using a differential optical absorption spectroscopy system, nitrogen oxide (NO) by an in situ chemiluminescence analyser and carbon dioxide (CO₂) by a gas chromatographic technique were carried out in the Wuppertal Kiesbergtunnel. At high traffic density HONO concentrations of up to 45 ppbV were observed. However, at low traffic density unexpectedly high HONO concentrations of up to 10 ppbV were measured caused by heterogeneous HONO formation on the tunnel walls. In addition to the tunnel campaigns, emission measurements of HONO, NO₂, NO and CO₂ from different single vehicles (a truck, a diesel and a gasoline passenger car) were also performed. For the correction of the HONO emission data, the heterogeneous HONO formation on the tunnel walls was quantified by two different approaches (a) in different NO₂ emission experiments in the tunnel without traffic and (b) on tunnel wall residue in the laboratory. The HONO concentration corrected for heterogeneous formation on the tunnel walls, in relation to the CO₂ concentration can be used to estimate the amount of HONO, which is directly emitted from the vehicle fleet. From the measured data, emission ratios (e.g. HONO/NO_x) and emission indices (e.g. mg HONO kg⁻¹ fuel) were calculated. The calculated emission index of 88±18 mg HONO kg⁻¹ fuel allows an estimation of the HONO emission rates from traffic into the atmosphere. Furthermore, the heterogeneous formation of HONO from NO₂ on freshly emitted exhaust particles is discussed.     

UTILIZATION OF AGRICULTURAL WASTE CORN COB FOR THE PREPARATION OF CARBON ADSORBENT

In the present study, a series of activated carbons were prepared from agricultural waste corn cob by chemical and physical activations with potassium hydroxide (KOH)/potassium carbonate (K₂CO₃) and carbon dioxide (CO₂). The effect of process variables such as impregnation ratio, impregnation time, activation temperature and soaking time of CO₂ was studied in order to relate these preparation parameters with the physical properties of final carbon products. The resulting activated carbons were characterized by nitrogen adsorption[ch-[chdesorption isotherms at 77 K. The surface areas and pore volumes of carbons were estimated by the BET equation, the Langmuir equation and the t-plot method. Under the experimental conditions investigated, the main parameters in the activation of corn cob were found to be the impregnation ratio and activation temperature. The soaking time of CO₂ is another important variable, which had a strong effect on the pore volume development. The BET surface area and total pore volume were as large as about 2000 m²/g and about 1.0 cm³/g, respectively. This study showed that the activation of agricultural waste corn cob with KOH/K₂CO₃ and CO₂ was suitable for the preparation of large-surface-area activated carbons.