Greenhouse gas emissions from dairy open lot and manure stockpile in northern China: A case study

The open lots and manure stockpiles of dairy farm are major sources of greenhouse gas (GHG) emissions in typical dairy cow housing and manure management system in China. GHG (CO₂, CH₄ and N₂O) emissions from the ground level of brick-paved open lots and uncovered manure stockpiles were estimated according to the field measurements of a typical dairy farm in Beijing by closed chambers in four consecutive seasons. Location variation and manure removal strategy impacts were assessed on GHG emissions from the open lots. Estimated CO₂, CH₄ and N₂O emissions from the ground level of the open lots were 137.5±64.7 kg hd^-1 yr^-1, 0.45±0.21 kg hd^-1 yr^-1 and 0.13±0.08 kg hd^-1 yr^-1, respectively. There were remarkable location variations of GHG emissions from different zones (cubicle zone vs. aisle zone) of the open lot. However, the emissions from the whole open lot were less affected by the locations. After manure removal, lower CH₄ but higher N₂O emitted from the open lot. Estimated CO₂, CH₄ and N₂O emissions from stockpile with a stacking height of 55±12 cm were 858.9±375.8 kg hd^-1 yr^-1, 8.5±5.4 kg hd^-1 yr^-1 and 2.3±1.1 kg hd^-1 yr^-1, respectively. In situ storage duration, which estimated by manure volatile solid contents (VS), would affect GHG emissions from stockpiles. Much higher N₂O was emitted from stockpiles in summer due to longer manure storage.

Implications: This study deals with greenhouse gas (GHG) emissions from open lots and stockpiles. It’s an increasing area of concern in some livestock producing countries. The Intergovernmental Panel on Climate Change (IPCC) methodology is commonly used for estimation of national GHG emission inventories. There is a shortage of on-farm information to evaluate the accuracy of these equations and default emission factors. This work provides valuable information for improving accounting practices within China or for similar manure management practice in other countries.     

Diurnal Odor,Ammonia, Hydrogen Sulfide,and Carbon Dioxide Emission Profiles of Confined Swine Grower/Finisher Rooms

Abstract

The objective of this study was to obtain diurnal variation profiles of odor and gas (ammonia [NH₃], hydrogen sulfide [H₂S], carbon dioxide [CO₂]) concentrations and emission rate (OGCER) from confined swine grower/finisher rooms under three typical weather conditions (warm, mild, and cold weather) in a year. Two grower/finisher rooms, one with a fully slatted floor and the other with partially slatted floors, were measured for 2 consecutive days under each weather condition. The results revealed that the diurnal OGCER in the room with a fully slatted floor was 9.2–39.4% higher than that with a partially slatted floor; however, no significant differences in the diurnal OGCER were found between these two rooms, except for the NH₃ concentrations in August, the NH₃ and H₂S concentrations and emissions in October, and odor concentrations and emissions in February (p > 0.05). The OGCER variations presented different diurnal patterns as affected by time of day, season, type of floor, ventilation rate, animal growth cycles, in-house manure storage, and weather conditions. Significant diurnal fluctuations in the OGCER (except for the odor concentrations and H₂S emissions) were observed in August (p < 0.05); all of the gas emissions in October and the CO₂ concentrations and emissions in February also showed significant diurnal variations (p < 0.05). These significant diurnal variations indicated that the OGCER during different periods of a day should be monitored when quantifying OGCER concentrations and emissions; for example, source emission data used in air dispersion modeling to decrease the great incertitude of setback determination using randomly measured data.     

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.     

Autonomous mobile platform for monitoring air emissions from industrial and municipal wastewater ponds

Significant amounts of volatile organic compounds and greenhouse gases are generated from wastewater lagoons and tailings ponds in Alberta, Canada. Accurate measurements of these air pollutants and greenhouse gases are needed to support management and regulatory decisions. A mobile platform was developed to measure air emissions from tailings pond in the oil sands region of Alberta. The mobile platform was tested in 2015 in a municipal wastewater treatment lagoon. With a flux chamber and a CO₂/CH₄ sensor on board, the mobile platform was able to measure CO₂ and CH₄ emissions over two days at two different locations in the pond. Flux emission rates of CO₂ and CH₄ that were measured over the study period suggest the presence of aerobic and anaerobic zones in the wastewater treatment lagoon. The study demonstrated the capabilities of the mobile platform in measuring fugitive air emissions and identified the potential for the applications in air and water quality monitoring programs.

Implications: The Mobile Platform demonstrated in this study has the ability to measure greenhouse gas (GHG) emissions from fugitive sources such as municipal wastewater lagoons. This technology can be used to measure emission fluxes from tailings ponds with better detection of spatial and temporal variations of fugitive emissions. Additional air and water sampling equipment could be added to the mobile platform for a broad range of air and water quality studies in the oil sands region of Alberta.     

Impacts of feedlot floor condition,deposition frequency,and inhibitors on N2O and CH4 emissions from feedlot dung and urine patches

Patches of dung and urine are major contributors to the feedlot gas emissions. This study investigated the impacts of dung deposition frequency (partly reflecting animal stocking density of a feedlot), dairy feedlot floor conditions (old floor indicated with the presence of consolidated manure pad [CMP] vs. new floor with the absence of consolidated manure pad [CMPn]), and application of dicyandiamide (DCD) and hydroquinone (HQ) on nitrous oxide (N₂O) and methane (CH₄) emissions from patches in the laboratory, and the integrative impacts were expressed in terms of global warming potential (CO₂-equivalent). Dung deposition frequency, feedlot floor condition, and application of inhibitors showed inverse impacts on N₂O and CH₄ emissions from patches. Greenhouse gas (GHG) emissions from the dung, urine, and dung+urine patches on the CMP feedlot surface were approximately 7.48, 87.35, and 7.10 times those on the CMPn feedlot surface (P < 0.05). Meanwhile, GHG emissions from CMP and CMPn feedlot surfaces under high deposition frequency condition were approximately 10 and 1.7 times those under low-frequency condition. Moreover, application of HQ slightly reduced the GHG emission from urine patches, by 14.9% (P > 0.05), while applying DCD or DCD+HQ significantly reduced the GHG, by 60.3% and 65.0%, respectively (P < 0.05). Overall, it is necessary to include feedlot management such as animal stocking density and feedlot floor condition to the process of determining emission factors for feedlots. In the future, field measurements to quantitatively evaluate the relative contribution of nitrification and denitrification to the N₂O emissions of feedlot surfaces are highly required for effective N₂O control.

Implications: This study shows that feedlot CH₄ and N₂O emissions inversely respond to the dicyandiamide (DCD) application. Applying DCD significantly reduces GHG emissions of feedlot urine patches. Feedlot floor condition and stocking density strongly impact feedlot GHG emissions. Including feedlot floor condition and stocking density in the feedlot EF determining process is necessary.     

Spatiotemporal analysis of traffic emissions in over 5000 municipal districts in Brazil

Exposure to traffic emission is harmful to human health. Emission inventories are essential to public health policies aiming at protecting human health, especially in areas with incomplete or nonexistent air pollution monitoring networks. In Brazil, for example, only 1.7% of municipal districts have a monitoring network, and only a few studies have reported data on vehicle emission inventories. No studies have presented emission inventories by municipality. In this study, we predicted vehicular emissions for 5570 municipal districts in Brazil during the period 2001–2012. We used a top-down method to estimate emissions. Carbon dioxide (CO₂) is the pollutant with the highest emissions, with approximately 190 million tons per year during the period 2001–2012). For the other traffic-related pollutants, we predicted annual emissions of 1.5 million tons for carbon monoxide (CO), 1.2 million tons of nitrogen oxides (NO_x), 209,000 tons of nonmethane hydrocarbons (NMHC), 58,000 tons of particulate matter (PM), and 42,000 tons for methane (CH₄). From 2001 to 2012, CO, NMHC, and PM emissions decreased by 41, 33, and 47%, respectively, whereas those CH₄, NO_x, and CO₂ increased by 2, 4, and 84%, respectively. We estimated uncertainties in our study and found that NO_x was the pollutant with the lowest percentage difference, 8%, and NMHC with the highest one, 30%. For CO, CH₄, CO₂, and PM, the values were 22, 14, 21, and 20%, respectively. Finally, we found that during 2001 and 2012 emissions increased in the Northwest and Northeast. In contrast, pollutant emissions, except for CO₂, decreased in the Southeast, South, and part of Midwest. Our predictions can be critical to efforts developing cost-effective public policies tailored to individual municipal districts in Brazil.

Implications: Emission inventories may be an alternative approach to provide data for air quality forecasting in areas where air quality data are not available. This approach can be an effective tool in developing spatially resolved emission inventories.     

Temporal variability of soil-atmospheric CO2 and CH4 fluxes from different land uses in mid-subtropical China

Different land uses in subtropics play an important role in regulating the global environmental changes. To reduce uncertainties of greenhouse gas (GHG) emissions of agricultural soils in subtropical ecosystem, a four years campaign was started to determine the temporal GHG (CO₂ and CH₄) fluxes from seven sites of four land use types (1 vegetable field, 3 uplands, 2 orchards, 1 pine forest). The mean annual budgets of CO₂, and CH₄ were 6.5～10.5 Mg CO₂ ha^?1 yr^?1, and +0.47 ～ ?2.37 kg CH₄ ha^?1 yr^?1, respectively. Pine forest had significantly lower CO₂ emission and higher CH₄ uptake than agriculture land uses. Tilled orchard emitted more CO₂ and oxidized less CH₄ than non-tilled orchard. Upland crops had higher CO₂ emissions than orchards, while abrupt differences of CH₄ uptake were observed between upland crops and orchards. Every year, the climate was warm and wet from April to September (the hot–humid season) and became cool and dry from October to March (the cool–dry season). Driven by seasonality of temperature and WFPS, CO₂ fluxes were significantly higher in the hot–humid season than in cool–dry season. Soil temperature, WFPS, NO₃^?–N and NH₄⁺–N contents interactively explained CH₄ uptake which was significantly higher in cool–dry season than in hot–humid season. We conclude that soil C fluxes from different land uses are strongly under control of different climatic predictors along with soil nutrient status, which interact in conjunction with each other to supply the readily available substrates.     

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.     

Estimating and comparing greenhouse gas emissions with their uncertainties using different methods: A case study for an energy supply utility

Energy supply utilities release significant amounts of greenhouse gases (GHGs) into the atmosphere. It is essential to accurately estimate GHG emissions with their uncertainties, for reducing GHG emissions and mitigating climate change. GHG emissions can be calculated by an activity-based method (i.e., fuel consumption) and continuous emission measurement (CEM). In this study, GHG emissions such as CO₂, CH₄, and N₂O are estimated for a heat generation utility, which uses bituminous coal as fuel, by applying both the activity-based method and CEM. CO₂ emissions by the activity-based method are 12–19% less than that by the CEM, while N₂O and CH₄ emissions by the activity-based method are two orders of magnitude and 60% less than those by the CEM, respectively. Comparing GHG emissions (as CO₂ equivalent) from both methods, total GHG emissions by the activity-based methods are 12–27% lower than that by the CEM, as CO₂ and N₂O emissions are lower than those by the CEM. Results from uncertainty estimation show that uncertainties in the GHG emissions by the activity-based methods range from 3.4% to about 20%, from 67% to 900%, and from about 70% to about 200% for CO₂, N₂O, and CH₄, respectively, while uncertainties in the GHG emissions by the CEM range from 4% to 4.5%. For the activity-based methods, an uncertainty in the Intergovernmental Panel on Climate Change (IPCC) default net calorific value (NCV) is the major uncertainty contributor to CO₂ emissions, while an uncertainty in the IPCC default emission factor is the major uncertainty contributor to CH₄ and N₂O emissions. For the CEM, an uncertainty in volumetric flow measurement, especially for the distribution of the volumetric flow rate in a stack, is the major uncertainty contributor to all GHG emissions, while uncertainties in concentration measurements contribute a little to uncertainties in the GHG emissions.

Implications:Energy supply utilities contribute a significant portion of the global greenhouse gas (GHG) emissions. It is important to accurately estimate GHG emissions with their uncertainties for reducing GHG emissions and mitigating climate change. GHG emissions can be estimated by an activity-based method and by continuous emission measurement (CEM), yet little study has been done to calculate GHG emissions with uncertainty analysis. This study estimates GHG emissions and their uncertainties, and also identifies major uncertainty contributors for each method.     

Regional and sectoral assessment of greenhouse gas emissions in India

In this paper the authors have estimated for 1990 and 1995 the inventory of greenhouse gases CO₂, CH₄ and N₂O for India at a national and sub-regional district level. The district level estimates are important for improving the national inventories as well as for developing sound mitigation strategies at manageable smaller scales. Our estimates indicate that the total CO₂, CH₄ and N₂O emissions from India were 592.5, 17, 0.2 and 778, 18, 0.3 Tg in 1990 and 1995, respectively. The compounded annual growth rate (CAGR) of these gases over this period were 6.3, 1.2 and 3.3%, respectively. The districts have been ranked according to their order of emissions and the relatively large emitters are termed as hotspots. A direct correlation between coal consumption and districts with high CO₂ emission was observed. CO₂ emission from the largest 10% emitters increased by 8.1% in 1995 with respect to 1990 and emissions from rest of the districts decreased over the same period, thereby indicating a skewed primary energy consumption pattern for the country. Livestock followed by rice cultivation were the dominant CH₄ emitting sources. The waste sector though a large CH₄ emitter in the developed countries, only contributed about 10% the total CH₄ emission from all sources as most of the waste generated in India is allowed to decompose aerobically. N₂O emissions from the use of nitrogen fertilizer were maximum in both the years (more than 60% of the total N₂O). High emission intensities, in terms of CO₂ equivalent, are in districts of Gangetic plains, delta areas, and the southern part of the country. These overlap with districts with large coal mines, mega power plants, intensive paddy cultivation and high fertilizer use. The study indicates that the 25 highest emitting districts account for more than 37% of all India CO₂ equivalent GHG emissions. Electric power generation has emerged as the dominant source of GHG emissions, followed by emissions from steel and cement plants. It is therefore suggested, to target for GHG mitigation, the 40 largest coal-based thermal plants, five largest steel plants and 15 largest cement plants in India as the first step.     

A comparison of CH4, N2O and CO2 emissions from three different cover types in a municipal solid waste landfill

High-density polyethylene (HDPE) membranes are commonly used as a cover component in sanitary landfills, although only limited evaluations of its effect on greenhouse gas (GHG) emissions have been completed. In this study, field GHG emission were investigated at the Dongbu landfill, using three different cover systems: HDPE covering; no covering, on the working face; and a novel material-Oreezyme Waste Cover (OWC) material as a trial material. Results showed that the HDPE membrane achieved a high CH₄ retention, 99.8% (CH₄ mean flux of 12 mg C m^-2 h^-1) compared with the air-permeable OWC surface (CH4 mean flux of 5933 mg C m^-2 h^-1) of the same landfill age. Fresh waste at the working face emitted a large fraction of N₂O, with average fluxes of 10 mg N m^-2 h^-2, while N₂O emissions were small at both the HDPE and the OWC sections. At the OWC section, CH₄ emissions were elevated under high air temperatures but decreased as landfill age increased. N₂O emissions from the working face had a significant negative correlation with air temperature, with peak values in winter. A massive presence of CO₂ was observed at both the working face and the OWC sections. Most importantly, the annual GHG emissions were 4.9 Gg yr^-1 in CO₂ equivalents for the landfill site, of which the OWC-covered section contributed the most CH₄ (41.9%), while the working face contributed the most N₂O (97.2%). HDPE membrane is therefore, a recommended cover material for GHG control.

Implications: Monitoring of GHG emissions at three different cover types in a municipal solid waste landfill during a 1-year period showed that the working face was a hotspot of N₂O, which should draw attention. High CH₄ fluxes occurred on the permeable surface covering a 1- to 2-year-old landfill. In contrast, the high-density polyethylene (HDPE) membrane achieved high CH₄ retention, and therefore is a recommended cover material for GHG control.     

Measuring and modeling nitrous oxide and methane emissions from beef cattle feedlot manure management: First assessments under Brazilian condition

Intensive beef production has increased during recent decades in Brazil and may substantially increase both methane (CH₄) and nitrous oxide (N₂O) emissions from manure management. However, the quantification of these gases and methods for extrapolating them are scarce in Brazil. A case study examines CH₄ and N₂O emissions from one typical beef cattle feedlot manure management continuum in Brazil and the applicability of Manure-DNDC model in predicting these emissions for better understand fluxes and mitigation options. Measurements track CH₄ and N₂O emissions from manure excreted in one housing floor holding 21 animals for 78 days, stockpiled for 73 days and field spread (360 kg N ha^?1). We found total emissions (CH₄ + N₂O) of 0.19 ± 0.10 kg CO₂eq per kg of animal live weight gain; mostly coming from field application (73%), followed housing (25%) and storage (2%). The Manure-DNDC simulations were generally within the statistical deviation ranges of the field data, differing in ?28% in total emission. Large uncertainties in measurements showed the model was more accurate estimating the magnitude of gases emissions than replicate results at daily basis. Modeled results suggested increasing the frequency of manure removal from housing, splitting the field application and adopting no-tillage system is the most efficient management for reducing emissions from manure (up to about 75%). Since this work consists in the first assessment under Brazilian conditions, more and continuous field measurements are required for decreasing uncertainties and improving model validations. However, this paper reports promising results and scientific perceptions for the design of further integrated work on farm-scale measurements and Manure-DNDC model development for Brazilian conditions.     

Note on In-Traffic Measurement of Airborne Tire-Wear Participate Debris

Measuring greenhouse gas (GHG) source emissions provides data for validation of GHG inventories, which provide the foundation for climate change mitigation. Two Toyota RAV4 electric vehicles were outfitted with high-precision instrumentation to determine spatial and temporal resolution of GHGs (e.g., nitrous oxide, methane [CH₄], and carbon dioxide [CO₂]), and other gaseous species and particulate metrics found near emission sources. Mobile measurement platform (MMP) analytical performance was determined over relevant measurement time scales. Pollutant residence times through the sampling configuration were measured, ranging from 3 to 11 sec, enabling proper time alignment for spatial measurement of each respective analyte. Linear response range for GHG analytes was assessed across expected mixing ratio ranges, showing minimal regression and standard error differences between 5, 10, 30, and 60 sec sampling intervals and negligible differences between the two MMPs. GHG instrument drift shows deviation of less than 0.8% over a 24-hr measurement period. These MMPs were utilized in tracer-dilution experiments at a California landfill and natural gas compressor station (NGCS) to quantify CH₄ emissions. Replicate landfill measurements during October 2009 yielded annual CH₄ emissions estimates of 0.10 ± 0.01, 0.11 ± 0.01, and 0.12 ± 0.02 million tonnes of CO₂ equivalent (MTCO₂E). These values compare favorably to California GHG Emissions Inventory figures for 2007, 2008, and 2009 of 0.123, 0.125, and 0.126 MTCO₂E/yr, respectively, for this facility. Measurements to quantify NGCS boosting facility-wide emissions, during June 2010 yielded an equivalent of 5400 ± 100 TCO₂E/yr under steady-state operation. However, measurements during condensate transfer without operational vapor recovery yield an instantaneous emission rate of 2–4 times greater, but was estimated to only add 12 TCO₂E/yr overall. This work displays the utility for mobile GHG measurements to validate existing measurement and modeling approaches, so emission inventory values can be confirmed and associated uncertainties reduced.

Implications:?Measuring greenhouse gas (GHG) source emissions provides data and validation for GHG inventories, the foundation for climate change mitigation. Mobile measurement platforms with robust analytical instrumentation completed tracer-dilution experiments in California at a landfill and natural gas compressor station (NGCS) to quantify CH₄ emissions. Data collected for landfill CH₄ agree with the current California emissions inventory, while NGCS data show the possible variability from this type of facility. This work displays the utility of mobile GHG measurements to validate existing measurement and modeling approaches, such that emission inventory values can be confirmed, associated uncertainties reduced, and mitigation efforts quantified.     

Protection from wintertime rainfall reduces nutrient losses and greenhouse gas emissions during the decomposition of poultry and horse manure-based amendments

Manure-based soil amendments (herein “amendments”) are important fertility sources, but differences among amendment types and management can significantly affect their nutrient value and environmental impacts. A 6-month in situ decomposition experiment was conducted to determine how protection from wintertime rainfall affected nutrient losses and greenhouse gas (GHG) emissions in poultry (broiler chicken and turkey) and horse amendments. Changes in total nutrient concentration were measured every 3 months, changes in ammonium (NH₄⁺) and nitrate (NO₃^?) concentrations every month, and GHG emissions of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) every 7–14 days. Poultry amendments maintained higher nutrient concentrations (except for K), higher emissions of CO₂ and N₂O, and lower CH₄ emissions than horse amendments. Exposing amendments to rainfall increased total N and NH₄⁺ losses in poultry amendments, P losses in turkey and horse amendments, and K losses and cumulative N₂O emissions for all amendments. However, it did not affect CO₂ or CH₄ emissions. Overall, rainfall exposure would decrease total N inputs by 37% (horse), 59% (broiler chicken), or 74% (turkey) for a given application rate (wet weight basis) after 6 months of decomposition, with similar losses for NH₄⁺ (69–96%), P (41–73%), and K (91–97%). This study confirms the benefits of facilities protected from rainfall to reduce nutrient losses and GHG emissions during amendment decomposition.

Implications: The impact of rainfall protection on nutrient losses and GHG emissions was monitored during the decomposition of broiler chicken, turkey, and horse manure-based soil amendments. Amendments exposed to rainfall had large ammonium and potassium losses, resulting in a 37–74% decrease in N inputs when compared with amendments protected from rainfall. Nitrous oxide emissions were also higher with rainfall exposure, although it had no effect on carbon dioxide and methane emissions. Overall, this work highlights the benefits of rainfall protection during amendment decomposition to reduce nutrient losses and GHG emissions.     

Carbon dioxide and methane fluxes in the littoral zones of two lakes,east Antarctica

During the summertime of 2007/2008, carbon dioxide (CO₂) and methane (CH₄) fluxes across air–water interface were investigated in the littoral zones of Lake Mochou and Lake Tuanjie, east Antarctica, using a static chamber technique. The mean fluxes of CO₂ and CH₄ were ?70.8 mgCO₂ m^?2 h^?1 and 144.6 μgCH₄ m^?2 h^?1, respectively, in the littoral zone of Lake Mochou; The mean fluxes were ?36.9 mgCO₂ m^?2 h^?1 and 109.8 μgCH₄ m^?2 h^?1, respectively, in the littoral zone of Lake Tuanjie. Their fluxes showed large temporal and spatial dynamics. The CO₂ fluxes showed a significantly negative correlation with daily total radiation (DTR) and a weakly negative correlation with air temperature and water temperature, indicating that sunlight intensity controlled the magnitude of CO₂ fluxes from the open lakes. The CH₄ fluxes significantly correlated with local air temperature, water table and total dissolved solids (TDS), indicating that they were the predominant factors influencing CH₄ fluxes. Summertime CO₂ budgets in the littoral zones of Lake Mochou and Lake Tuanjie were estimated to be ?152.9 gCO₂ m^?2 and ?79.7 gCO₂ m^?2, respectively, and net CH₄ emissions were estimated to be 312.3 mgCH₄ m^?2 and 237.2 mgCH₄ m^?2, respectively. Our results show that shallow, open, alga-rich lakes might be strong summertime CO₂ absorbers and small CH₄ emitters during the open water in coastal Antarctica.     

Seasonal variations of CH(4) and N(2)O emissions in response to water management of paddy fields located in Southeast China

Water management is one of the most important practices that affect methane (CH₄) and nitrous oxide (N₂O) emissions from paddy fields. A field experiment was designed to study the effects of controlled irrigation (CI) on CH₄ and N₂O emissions from paddy fields, with traditional irrigation (TI) as the control. The effects of CI on CH₄ and N₂O emissions from paddy fields were very clear. The peaks of CH₄ emissions from the CI paddies were observed 1-2 d after the water layer disappeared. Afterward, the emissions reduced rapidly and remained low until the soil was re-flooded. A slight increase of CH₄ emission was observed in a short period after re-flooding. N₂O emissions peaks from CI paddies were all observed 8-10 d after the fertilization at the WFPS ranging from 78.1% to 85.3%. Soil drying caused substantial N₂O emissions, whereas no substantial N₂O emissions were observed when the soil was re-wetted after the dry phase. Compared with TI, the cumulative CH₄ emissions from the CI fields were reduced by 81.8% on the average, whereas the cumulative N₂O emissions were increased by 135.4% on the average. The integrative global warming potential of CH₄ and N₂O on a 100-year horizon decreased by 27.3% in the CI paddy fields, whereas no significant difference in the rice yield was observed between the CI and TI fields. These results suggest that CI can effectively mitigate the integrative greenhouse effect caused by CH₄ and N₂O emissions from paddy fields while ensuring the rice yield.     

Modeling of methane oxidation in landfill cover soil using an artificial neural network

Knowing the fraction of methane (CH₄) oxidized in landfill cover soils is an important step in estimating the total CH₄ emissions from any landfill. Predicting CH₄ oxidation in landfill cover soils is a difficult task because it is controlled by a number of biological and environmental factors. This study proposes an artificial neural network (ANN) approach using feedforward backpropagation to predict CH₄ oxidation in landfill cover soil in relation to air temperature, soil moisture content, oxygen (O₂) concentration at a depth of 10 cm in cover soil, and CH₄ concentration at the bottom of cover soil. The optimum ANN model giving the lowest mean square error (MSE) was configured from three layers, with 12 and 9 neurons at the first and the second hidden layers, respectively, log-sigmoid (logsig) transfer function at the hidden and output layers, and the Levenberg-Marquardt training algorithm. This study revealed that the ANN oxidation model can predict CH₄ oxidation with a MSE of 0.0082, a coefficient of determination (R ²) between the measured and predicted outputs of up to 0.937, and a model efficiency (E) of 0.8978. To conclude, further developments of the proposed ANN model are required to generalize and apply the model to other landfills with different cover soil properties.

Implications:

To date, no attempts have been made to predict the percent of CH₄ oxidation within landfill cover soils using an ANN. This paper presents modeling of CH₄ oxidation in landfill cover soil using ANN based on field measurements data under tropical climate conditions in Malaysia. The proposed ANN oxidation model can be used to predict the percentage of CH₄ oxidation from other landfills with similar climate conditions, cover soil texture, and other properties. The predicted value of CH₄ oxidation can be used in conjunction with the Intergovernmental Panel on Climate Change (IPCC) First Order Decay (FOD) model by landfill operators to accurately estimate total CH₄ emission and how much it contributes to global warming.     

Development of Instrumentation for Continuous On-line Monitoring of Non-Methane Organic Carbon in Air Emissions

ABSTRACT

Non-methane organic carbon (NMOC) is a measure of total organic carbon in an air emission, excluding that from methane. Thus, it measures the total amount of carbon, irrespective of the structure and functional groups in the molecule. The U.S. Environmental Protection Agency (EPA) Method 25 is used for quantification of NMOC in emission sources and in ambient air. This method involves laboratory analysis of collected air samples and cannot be used for real-time measurements. It is prone to interferences from CO₂, CH₄, and CO, as well as moisture. In this paper, a novel method for continuous, on-line monitoring of NMOC in air emissions and ambient air is presented. Detection limits are at ppb levels, and interference of permanent gases have been eliminated.     

Biomass fuel burning and its implications: Deforestation and greenhouse gases emissions in Pakistan

Pakistan is facing problem of deforestation. Pakistan lost 14.7% of its forest habitat between 1990 and 2005 interval. This paper assesses the present forest wood consumption rate by 6000 brick kilns established in the country and its implications in terms of deforestation and emission of greenhouse gases. Information regarding consumption of forest wood by the brick kilns was collected during a manual survey of 180 brick kiln units conducted in eighteen provincial divisions of country. Considering annual emission contributions of three primary GHGs i.e., CO₂, CH₄ and N₂O, due to burning of forest wood in brick kiln units in Pakistan and using IPCC recommended GWP indices, the combined CO₂-equivalent has been estimated to be 533019 t y⁻¹.     

Scenarios of global anthropogenic emissions of air pollutants and methane until 2030

We have used a global version of the Regional Air Pollution Information and Simulation (RAINS) model to estimate anthropogenic emissions of the air pollution precursors sulphur dioxide (SO₂), nitrogen oxides (NO_x), carbon monoxide (CO), primary carbonaceous particles of black carbon (BC), organic carbon (OC) and methane (CH₄). We developed two scenarios to constrain the possible range of future emissions. As a baseline, we investigated the future emission levels that would result from the implementation of the already adopted emission control legislation in each country, based on the current national expectations of economic development. Alternatively, we explored the lowest emission levels that could be achieved with the most advanced emission control technologies that are on the market today. This paper describes data sources and our assumptions on activity data, emission factors and the penetration of pollution control measures. We estimate that, with current expectations on future economic development and with the present air quality legislation, global anthropogenic emissions of SO₂ and NO_x would slightly decrease between 2000 and 2030. For carbonaceous particles and CO, reductions between 20% and 35% are computed, while for CH₄ an increase of about 50% is calculated. Full application of currently available emission control technologies, however, could achieve substantially lower emissions levels, with decreases up to 30% for CH₄, 40% for CO and BC, and nearly 80% for SO₂.