Empirical gas emission and oxidation measurement at cover soil of dumping site: example from Malaysia

Methane (CH₄) is one of the most relevant greenhouse gases and it has a global warming potential 25 times greater than that of carbon dioxide (CO₂), risking human health and the environment. Microbial CH₄ oxidation in landfill cover soils may constitute a means of controlling CH₄ emissions. The study was intended to quantify CH₄ and CO₂ emissions rates at the Sungai Sedu open dumping landfill during the dry season, characterize their spatial and temporal variations, and measure the CH₄ oxidation associated with the landfill cover soil using a homemade static flux chamber. Concentrations of the gases were analyzed by a Micro-GC CP-4900. Two methods, kriging values and inverse distance weighting (IDW), were found almost identical. The findings of the proposed method show that the ratio of CH₄ to CO₂ emissions was 25.4 %, indicating higher CO₂ emissions than CH₄ emissions. Also, the average CH₄ oxidation in the landfill cover soil was 52.5 %. The CH₄ and CO₂ emissions did not show fixed-pattern temporal variation based on daytime measurements. Statistically, a negative relationship was found between CH₄ emissions and oxidation (R ²?=?0.46). It can be concluded that the variation in the CH₄ oxidation was mainly attributed to the properties of the landfill cover soil.     

Greenhouse gas emissions from two hydroelectric reservoirs in Mediterranean region

Water reservoirs are used for many purposes, such as water supply, irrigation, flood mitigation, and hydroelectric energy generation. Although hydroelectric energy is considered “green,” many studies show that the construction of a reservoir enhances greenhouse gas (GHG) emissions at the transformed area. These emissions, mainly of CO₂, CH₄, and N₂O gases, depend on the age of the reservoir, landscape and soil composition, fauna and flora remnants of the impounded area, climatic conditions, and basin runoffs. Consequently, GHG emissions significantly vary between reservoirs and depending on local specificities. Several studies have investigated GHG emissions from reservoirs around the world, focusing mainly on reservoirs located in cold regions, temperate regions, and tropical regions. Research is lacking for reservoirs in Mediterranean countries, like Greece, and similar regions. This work initially assesses the net GHG emissions of a newly created reservoir (Ilarion est. 2012) in Western Macedonia, Greece. The methodology for net GHG emission calculation was based on the use of literature data concerning pre-impoundment emission factors and local specificities of the reservoir (terrain type, canopy cover), as well as on the 2-year measurement data that were collected using a “static floating chamber.” Furthermore, in this work, the gross GHG emissions of an older, in-line reservoir (Polyfytos est. 1974) were also calculated, based on 2-year measurement data. The results show that the global warming potential (GWP) of the reservoirs is dictated by methane emissions; it minimizes during winter and spring and maximizes during summer and autumn. Hydroelectric energy production at Ilarion Reservoir results in 32 to 97 times less total CO₂ equivalent emissions in comparison to fossil fuels, while at Polyfytos Reservoir only 8 to 24 times less (based on gross emissions). It appears that the impact of a reservoir’s morphology on GHG emissions is more significant than that of a reservoir’s age.     

Long-term spatiotemporal patterns of CH4 and N2O emissions from livestock and poultry production in Turkey

This study quantified spatiotemporal patterns of CH₄ and N₂O emissions from livestock and poultry production in Turkey between 1961 and 2007. CH_4(enteric) (from enteric fermentation), CH_4(manure) (from manure management), and N₂O_(AWM) (from animal waste management) emissions in Turkey were estimated at 1,164, 216, and 55 Gg in 1961 and decreased to 844, 187, and 39 Gg in 2007, contributing a share of roughly 2% to the global livestock-related CH₄ emissions and %1.5 to the global N₂O_(AWM) emissions, respectively. Total CO₂-eq emissions were estimated at 50.7 Tg in 1961 and declined from a maximum value of 60.7 Tg in 1982 to a minimum value of 34.5 Tg in 2003, with a mean emission rate of 48 Tg year^???1 due to a significant reduction in the number of ruminant livestock. The highest mean share of emissions belonged to West Black Sea (14% and 16%) for CH_4(enteric) and CH_4(manure) and to North East Anatolia (12% and %13) for N₂O_(AWM) and total CO₂-eq emissions, respectively. The highest emission density was 1.7 Mg km^???2 year^???1 for CH_4(enteric), 0.3 Mg km^???2 year^???1 for CH_4(manure), and 0.07 Mg km^???2 year^???1 for the total CO₂-eq emissions in the West and North East Anatolia regions and 0.09 Mg km^???2 year^???1 for N₂O_(AWM) in the East Marmara region. Temporal and spatial variations in CH_4(enteric), CH_4(manure), and N₂O_(AWM) emissions in Turkey were estimated using regression models and ordinary kriging at a 500-m resolution, respectively.     

A comparison of emission calculations using different modeled indicators with 1-year online measurements

The overall measurement of farm level greenhouse gas (GHG) emissions in dairy production is not feasible, from either an engineering or administrative point of view. Instead, computational model systems are used to generate emission inventories, demanding a validation by measurement data. This paper tests the GHG calculation of the dairy farm-level optimization model DAIRYDYN, including methane (CH₄) from enteric fermentation and managed manure. The model involves four emission calculation procedures (indicators), differing in the aggregation level of relevant input variables. The corresponding emission factors used by the indicators range from default per cow (activity level) emissions up to emission factors based on feed intake, manure amount, and milk production intensity. For validation of the CH₄ accounting of the model, 1-year CH₄ measurements of an experimental free-stall dairy farm in Germany are compared to model simulation results. An advantage of this interdisciplinary study is given by the correspondence of the model parameterization and simulation horizon with the experimental farm’s characteristics and measurement period. The results clarify that modeled emission inventories (2,898, 4,637, 4,247, and 3,600 kg CO₂-eq. cow^?1 year^?1) lead to more or less good approximations of online measurements (average 3,845 kg CO₂-eq. cow^?1 year^?1 (±275 owing to manure management)) depending on the indicator utilized. The more farm-specific characteristics are used by the GHG indicator; the lower is the bias of the modeled emissions. Results underline that an accurate emission calculation procedure should capture differences in energy intake, owing to milk production intensity as well as manure storage time. Despite the differences between indicator estimates, the deviation of modeled GHGs using detailed indicators in DAIRYDYN from on-farm measurements is relatively low (between ?6.4 % and 10.5 %), compared with findings from the literature.     

Availability of disaggregated greenhouse gas emissions from beef cattle production: A systematic review

Agriculture is a significant source of anthropogenic greenhouse gas (GHG) emissions, and beef cattle are particularly emissions intensive. GHG emissions are typically expressed as a carbon dioxide equivalent (CO₂e) ‘carbon footprint’ per unit output. The 100-year Global Warming Potential (GWP₁₀₀) is the most commonly used CO₂e metric, but others have also been proposed, and there is no universal reason to prefer GWP₁₀₀ over alternative metrics. The weightings assigned to non-CO₂ GHGs can differ significantly depending on the metric used, and relying upon a single metric can obscure important differences in the climate impacts of different GHGs. This loss of detail is especially relevant to beef production systems, as the majority of GHG emissions (as conventionally reported) are in the form of methane (CH₄) and nitrous oxide (N₂O), rather than CO₂. This paper presents a systematic literature review of harmonised cradle to farm-gate beef carbon footprints from bottom-up studies on individual or representative systems, collecting the emissions data for each separate GHG, rather than a single CO₂e value. Disaggregated GHG emissions could not be obtained for the majority of studies, highlighting the loss of information resulting from the standard reporting of total GWP₁₀₀ CO₂e alone. Where individual GHG compositions were available, significant variation was found for all gases. A comparison of grass fed and non-grass fed beef production systems was used to illustrate dynamics that are not sufficiently captured through a single CO₂e footprint. Few clear trends emerged between the two dietary groups, but there was a non-significant indication that under GWP₁₀₀ non-grass fed systems generally appear more emissions efficient, but under an alternative metric, the 100-year global temperature potential (GTP₁₀₀), grass-fed beef had lower footprints. Despite recent focus on agricultural emissions, this review concludes there are insufficient data available to fully address important questions regarding the climate impacts of agricultural production, and calls for researchers to include separate GHG emissions in addition to aggregated CO₂e footprints.     

Greenhouse gas emission inventory for Senegal, 1991

The first greenhouse gas (GHG) emission estimates for Senegal, for the year 1991, were produced according to the draft IPCC/OECD guidelines for national inventories of GHGs. Despite certain discrepancies, nonavailability of data, the quality of some of the data collected, and the methodology, the estimates provide a provisional basis for Senegal to fulfill its obligations under the UN Framework Convention on Climate Change. This inventory reveals that GHG emissions in Senegal, like those in many developing countries, can mainly be attributed to the use of biomass for energy, land-use change and forestry, and savanna burning. Taking into account the direct global warming potential of the main GHGs (CO₂, CH₄, and N₂O), Senegal's emissions are estimated at 17.6 Tg ECO₂. The major gases emitted are CO₂ (61% of GHG emissions), followed by CH₄ (35%) and N₂O (4%). Energy accounts for 45% of total emissions (12% from fossil energy and 33% from traditional biomass energy); land-use change and forests, 18%; agriculture, 24%; waste, 12%; and industry, 1%.     

Assessment of methane emission and oxidation at Air Hitam Landfill site cover soil in wet tropical climate

Methane (CH₄) emissions and oxidation were measured at the Air Hitam sanitary landfill in Malaysia and were modeled using the Intergovernmental Panel on Climate Change waste model to estimate the CH₄ generation rate constant, k. The emissions were measured at several locations using a fabricated static flux chamber. A combination of gas concentrations in soil profiles and surface CH₄ and carbon dioxide (CO₂) emissions at four monitoring locations were used to estimate the CH₄ oxidation capacity. The temporal variations in CH₄ and CO₂ emissions were also investigated in this study. Geospatial means using point kriging and inverse distance weight (IDW), as well as arithmetic and geometric means, were used to estimate total CH₄ emissions. The point kriging, IDW, and arithmetic means were almost identical and were two times higher than the geometric mean. The CH₄ emission geospatial means estimated using the kriging and IDW methods were 30.81 and 30.49 g m^?2 day^?1, respectively. The total CH₄ emissions from the studied area were 53.8 kg day^?1. The mean of the CH₄ oxidation capacity was 27.5 %. The estimated value of k is 0.138 year^?1. Special consideration must be given to the CH₄ oxidation in the wet tropical climate for enhancing CH₄ emission reduction.     

Monitoring variation in greenhouse gases concentration in Urban Environment of Delhi

Cities across the globe are considered as major anthropogenic sources of greenhouse gases (GHG), yet very few efforts has been made to monitor ambient concentration of GHG in cities, especially in a developing country like India. Here, variations in the ambient concentrations of carbon dioxide (CO₂) and methane (CH₄) in residential, commercial, and industrial areas of Delhi are determined from fortnightly daytime observations from July, 2008 to March, 2009. Results indicate that the average daytime ambient concentration of CO₂ varied from 495 to 554 ppm in authorized residential areas, 503 to 621 ppm in the slums or jhuggies in the unauthorized residential areas, 489 to 582 ppm in commercial areas, and 512 to 568 ppm in industrial areas with an average of 541?±?27 ppm. CH₄ concentration varied from 652 to 5,356 ppbv in authorized residential areas, 500 to15,220 ppbv in the unauthorized residential areas, 921 to 11,000 ppbv in the commercial areas, and 250 to 2,550 ppbv in the industrial areas with an average of 3,226?±?1,090 ppbv. A low mid-afternoon CO₂ concentration was observed at most of the sites, primarily due to strong biospheric photosynthesis coupled with strong vertical mixing.     

Soil respiration,labile carbon pools,and enzyme activities as affected by tillage practices in a tropical rice–maize–cowpea cropping system

In order to identify the viable option of tillage practices in rice–maize–cowpea cropping system that could cut down soil carbon dioxide (CO₂) emission, sustain grain yield, and maintain better soil quality in tropical low land rice ecology soil respiration in terms of CO₂ emission, labile carbon (C) pools, water-stable aggregate C fractions, and enzymatic activities were investigated in a sandy clay loam soil. Soil respiration is the major pathway of gaseous C efflux from terrestrial systems and acts as an important index of ecosystem functioning. The CO₂–C emissions were quantified in between plants and rows throughout the year in rice–maize–cowpea cropping sequence both under conventional tillage (CT) and minimum tillage (MT) practices along with soil moisture and temperature. The CO₂–C emissions, as a whole, were 24 % higher in between plants than in rows, and were in the range of 23.4–78.1, 37.1–128.1, and 28.6–101.2 mg m^?2 h^?1 under CT and 10.7–60.3, 17.3–99.1, and 17.2–79.1 mg m^?2 h^?1 under MT in rice, maize, and cowpea, respectively. The CO₂–C emission was found highest under maize (44 %) followed by rice (33 %) and cowpea (23 %) irrespective of CT and MT practices. In CT system, the CO₂–C emission increased significantly by 37.1 % with respect to MT on cumulative annual basis including fallow. The CO₂–C emission per unit yield was at par in rice and cowpea signifying the beneficial effect of MT in maintaining soil quality and reduction of CO₂ emission. The microbial biomass C (MBC), readily mineralizable C (RMC), water-soluble C (WSC), and permanganate-oxidizable C (PMOC) were 19.4, 20.4, 39.5, and 15.1 % higher under MT than CT. The C contents in soil aggregate fraction were significantly higher in MT than CT. Soil enzymatic activities like, dehydrogenase, fluorescein diacetate, and β-glucosidase were significantly higher by 13.8, 15.4, and 27.4 % under MT compared to CT. The soil labile C pools, enzymatic activities, and heterotrophic microbial populations were in the order of maize?>?cowpea?>?rice, irrespective of the tillage treatments. Environmental sustainability point of view, minimum tillage practices in rice–maize–cowpea cropping system in tropical low land soil could be adopted to minimize CO₂–C emission, sustain yield, and maintain soil health.     

Effect of elevated CO2 on degradation of azoxystrobin and soil microbial activity in rice soil

An experiment was conducted in open-top chambers (OTC) to study the effect of elevated CO₂ (580?±?20 μmol mol^?1) on azoxystrobin degradation and soil microbial activities. Results indicated that elevated CO₂ did not have any significant effect on the persistence of azoxystrobin in rice-planted soil. The half-life values for the azoxystrobin in rice soils were 20.3 days in control (rice grown at ambient CO₂ outdoors), 19.3 days in rice grown under ambient CO₂ atmosphere in OTC, and 17.5 days in rice grown under elevated CO₂ atmosphere in OTC. Azoxystrobin acid was recovered as the only metabolite of azoxystrobin, but it did not accumulate in the soil/water and was further metabolized. Elevated CO₂ enhanced soil microbial biomass (MBC) and alkaline phosphatase activity of soil. Compared with rice grown at ambient CO₂ (both outdoors and in OTC), the soil MBC at elevated CO₂ increased by twofold. Elevated CO₂ did not affect dehydrogenase, fluorescein diacetate, and acid phosphatase activity. Azoxystrobin application to soils, both ambient and elevated CO₂, inhibited alkaline phosphates activity, while no effect was observed on other enzymes. Slight increase (1.8–2 °C) in temperature inside OTC did not affect microbial parameters, as similar activities were recorded in rice grown outdoors and in OTC at ambient CO₂. Higher MBC in soil at elevated CO₂ could be attributed to increased carbon availability in the rhizosphere via plant metabolism and root secretion; however, it did not significantly increase azoxystrobin degradation, suggesting that pesticide degradation was not the result of soil MBC alone. Study suggested that increased CO₂ levels following global warming might not adversely affect azoxystrobin degradation. However, global warming is a continuous and cumulative process, therefore, long-term studies are necessary to get more realistic assessment of global warming on fate of pesticide.     

Nitrogen enrichment in runoff sediments as affected by soil texture in Beijing mountain area

Enrichment ratio (ER) is widely used in nonpoint source pollution models to estimate the nutrient loss associated with soil erosion. The objective of this study was to determine the ER of total nitrogen (ER_N) in the sediments eroded from the typical soils with varying soil textures in Beijing mountain area. Each of the four soils was packed into a 40 by 30 by 15 cm soil pan and received 40-min simulated rainfalls at the intensity of 90 mm h^?1 on five slopes. ER_N for most sediments were above unity, indicating the common occurrence of nitrogen enrichment accompanied with soil erosion in Beijing mountain area. Soil texture was not the only factor that influenced N enrichment in this experiment since the ER_N for the two fine-textured soils were not always lower. Soil properties such as soil structure might exert a more important influence in some circumstances. The selective erosion of clay particles was the main reason for N enrichment, as implied by the significant positive correlation between the ER of total nitrogen and clay fraction in eroded sediments. Significant regression equations between ER_N and sediment yield were obtained for two pairs of soils, which were artificially categorized by soil texture. The one for fine-textured soils had greater intercept and more negative slope. Thus, the initially higher ER_N would be lower than that for the other two soils with coarser texture once the sediment yield exceeded 629 kg ha^?1.     

Modeling seasonal variations of long-term soil CO<Subscript>2</Subscript> emissions in an orchard plantation in a semiarid area,SE Turkey

Emissions of soil CO₂ under different management systems have a significant effect on the carbon balance in the atmosphere. Soil CO₂ emissions were measured from an apricot orchard at two different locations: under the crown of trees (CO₂-UC) and between tree rows (CO₂-BR). For comparison, one other measurement was performed on bare soil (CO₂-BS) located next to the orchard field. Analytical data were obtained weekly during 8 years from April 2008 to December 2016. Various environmental parameters such as air temperature, soil temperature at different depths, soil moisture, rainfall, and relative humidity were used for modeling and estimating the long-term seasonal variations in soil CO₂ emissions using two different methods: generalized linear model (GLM) and artificial neural network (ANN). Before modeling, data were randomly split into two parts, one for calibration and the second for validation, with a varying number of samples in each part. Performances of the models were compared and evaluated using means absolute of estimations (MAE), square root of mean of prediction (RMSEP), and coefficient of determination (R²) values. CO₂-UC, CO₂-BR, and CO₂-BS values ranged from 11 to 3985, from 9 to 2365, and from 8 to 1722 kg ha^?1 week^?1, respectively. Soil CO₂ emissions were significantly correlated (p?<?0.05) with some environmental variables. The results showed that GLM and ANN models provided similar accuracies in modeling and estimating soil CO₂ emissions, as the number of samples in the validation data set increased. The ANN was more advantageous than GLM models by providing a better fit between actual observations and predictions and lower RMSEP and MAE values. The results suggested that the success of environmental variables for estimations of CO₂ emissions using the two methods was moderate.     

Adaptive nitrogen and integrated weed management in conservation agriculture: impacts on agronomic productivity,greenhouse gas emissions,and herbicide residues

Increasing nitrogen (N) immobilization and weed interference in the early phase of implementation of conservation agriculture (CA) affects crop yields. Yet, higher fertilizer and herbicide use to improve productivity influences greenhouse gase emissions and herbicide residues. These tradeoffs precipitated a need for adaptive N and integrated weed management in CA-based maize (Zea mays L.)—wheat [Triticum aestivum (L.) emend Fiori & Paol] cropping system in the Indo-Gangetic Plains (IGP) to optimize N availability and reduce weed proliferation. Adaptive N fertilization was based on soil test value and normalized difference vegetation index measurement (NDVM) by GreenSeeker? technology, while integrated weed management included brown manuring (Sesbania aculeata L. co-culture, killed at 25 days after sowing), herbicide mixture, and weedy check (control, i.e., without weed management). Results indicated that the ‘best-adaptive N rate’ (i.e., 50% basal + 25% broadcast at 25 days after sowing + supplementary N guided by NDVM) increased maize and wheat grain yields by 20 and 14% (averaged for 2 years), respectively, compared with whole recommended N applied at sowing. Weed management by brown manuring (during maize) and herbicide mixture (during wheat) resulted in 10 and 21% higher grain yields (averaged for 2 years), respectively, over the weedy check. The NDVM in-season N fertilization and brown manuring affected N₂O and CO₂ emissions, but resulted in improved carbon storage efficiency, while herbicide residuals in soil were significantly lower in the maize season than in wheat cropping. This study concludes that adaptive N and integrated weed management enhance synergy between agronomic productivity, fertilizer and herbicide efficiency, and greenhouse gas mitigation.     

Fuel characteristics and emissions from biomass burning and land-use change in Nigeria

Nigeria is one of the 13 low-latitude countries that have significant biomass burning activities. Biomass burning occurs in moist savanna, dry forests, and forest plantations. Fires in the forest zone are associated with slash-and-burn agriculture; the areal extent of burning is estimated to be 80% of the natural savanna. In forest plantations, close to 100% of litter is burned. Current estimates of emissions from land-use change are based on a 1976 national study and extrapolations from it. The following non-carbon dioxide (CO₂) trace gas emissions were calculated from savanna burning: methane (CH₄), 145 gigagrams (Gg); carbon monoxide (CO), 3831 Gg; nitrous oxide (N₂O), 2 Gg; and nitrogen oxides (NO_x), 49 Gg. Deforestation rates in forests and woodlands are 300 × 10³ ha (kilohectare, or kha) and 200 × kha per year, respectively. Trace gas emissions from deforestation were estimated to be 300 Gg CH₄, 2.4 Gg N₂O, and 24 Gg NO_x. CO₂ emissions from burning, decay of biomass, and long-term emissions from soil totaled 125 561 Gg. These estimates should be viewed as preliminary, because greenhouse gas emission inventories from burning, deforestation, and land-use change require two components: fuel load and emission factors. Fuel load is dependent on the areal extent of various land uses, and the biomass stocking and some of these data in Nigeria are highly uncertain.     

Decadal emission estimates of carbon dioxide,sulfur dioxide,and nitric oxide emissions from coal burning in electric power generation plants in India

This study aims to estimate the emissions of carbon dioxide (CO₂), sulfur dioxide (SO₂), and nitric oxide (NO) for coal combustion in thermal power plants in India using plant-specific emission factors during the period of 2001/02 to 2009/10. The mass emission factors have been theoretically calculated using the basic principles of combustion under representative prevailing operating conditions in the plants and fuel composition. The results show that from 2001/02 to 2009/10 period, total CO₂ emissions have increased from 324 to 499 Mt/year; SO₂ emissions have increased from 2,519 to 3,840 kt/year; and NO emissions have increased from 948 to 1,539 kt/year from the Indian coal-fired power plants. National average emissions per unit of electricity from the power plants do not show a noticeable improvement during this period. Emission efficiencies for new plants that use improved technology are found to be better than those of old plants. As per these estimates, the national average of CO₂ emissions per unit of electricity varies between 0.91 and 0.95 kg/kWh while SO₂ and NO emissions vary in the range of 6.9 to 7.3 and 2.8 to 2.9 g/kWh, respectively. Yamunagar plant in Haryana state showed the highest emission efficiencies with CO₂ emissions as 0.58 kg/kWh, SO₂ emissions as 3.87 g/kWh, and NO emissions as 1.78 g/kWh, while the Faridabad plant has the lowest emission efficiencies with CO₂ emissions as 1.5 kg/kWh, SO₂ emissions as 10.56 g/kWh, and NO emissions as 4.85 g/kWh. Emission values at other plants vary between the values of these two plants.     

Inter-seasonal and spatial distribution of ground-level greenhouse gases (CO<Subscript>2</Subscript>, CH<Subscript>4</Subscript>, N<Subscript>2</Subscript>O) over Nagpur in India and their management roadmap

Ground-level concentrations of carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O) were monitored over three seasons, i.e., post-monsoon (September–October), winter (January–February), and summer (May–June) for 1 year during 2013–2014 in Nagpur City in India. The selected gases had moderate to high variation both spatially (residential, commercial, traffic intersections, residential cum commercial sites) and temporally (at 7:00, 13:00, 18:00, and 23:00 hours in all three seasons). Concentrations of gases were randomly distributed diurnally over city in all seasons, and there was no specific increasing or decreasing trend with time in a day. Average CO₂ and N₂O concentrations in winter were higher over post-monsoon and summer while CH₄ had highest average concentration in summer. Observed concentrations of CO₂ were predominantly above global average of 400 ppmv while N₂O and CH₄ concentrations frequently dropped down below global average of 327 ppbv and 1.8 ppmv, respectively. Two-tailed Student’s t test indicated that post-monsoon CO₂ concentrations were statistically different from summer but not so from winter, while difference between summer and winter concentrations was statistically significant (P < 0.05). CH₄ concentrations in all seasons were statistically at par to each other. In case of N₂O, concentrations in post-monsoon were statistically different from summer but not so from winter, while difference between summer and winter concentrations was statistically significant (P < 0.05). Average ground-level concentrations of the gases calculated for three seasons together were higher in commercial areas. Environmental management priorities vis a vis greenhouse gas emissions in the city are also discussed.     

Spatio-temporal variations of carbon dioxide and its gross emission regulated by artificial operation in a typical hydropower reservoir in China

Supersaturation and excess emission of greenhouse gases in freshwater reservoirs have received a great deal of attention in recent years. Although impoundment of reservoirs has been shown to contribute to the net emission of greenhouse gases, reservoir age, geographical distribution, submerged soil type and artificial regulation also have a great impact on their emissions. To examine how large scale reservoir operation impact the water column CO₂ and its air–water interface flux, a field study was conducted in 2010 to evaluate potential ecological processes that regulate the partial pressure of CO₂ (pCO₂) in the water column in the Pengxi River backwater area (PBA), a typical tributary in the Three Gorges Reservoir, China. Measurements of total alkalinity (TA), pH and water temperature were applied to compute the pCO₂. And this approach was also validated by calculation of pCO₂ from the dissolved inorganic carbon data of samples. Partial least squares (PLS) regression was used to determine how the dynamics of the water pCO₂ were related to the available variables. The estimated pCO₂ in our sample ranged from 26 to 4,087 μatm in the surface water. During low water operation from July to early September, there was an obvious pCO₂ stratification, and pCO₂ in the surface was almost unsaturated. This phenomenon was also observed in the spring bloom during discharge period. Conversely, there was no significant pCO₂ stratification and the entire water column was supersaturated during high water operation from November to the following February. Significant correlation was observed between the magnitude of pCO₂, DO and chlorophyll a, suggesting that phytoplankton dynamics regulate pCO₂ in the PBA. The average areal rate of CO₂ emissions from the Pengxi River ranged from 18.06 to 48.09 mmol m^?2 day^?1, with an estimated gross CO₂ emission from the water surface of 14–37 t day^?1 in this area in 2010. Photosynthesis and respiration rates by phytoplankton might be the dominant processes that regulated pCO₂ in the water column. We conclude that pCO₂ values in the surface water of Pengxi River could be regarded as potential sources of CO₂ to the atmosphere were smaller or similar to those that have been reported for many other reservoirs to date.     

Characteristics of CO2 release from forest soil in the mountains near Beijing

CO₂ release from forest soil is a key driver of carbon cycling between the soil and atmosphere ecosystem. The rate of CO₂ released from soil was measured in three forest stands (in the mountainous region near Beijing, China) by the alkaline absorption method from 2004 to 2006. The rate of CO₂ released did not differ among the three stands. The CO₂ release rate ranged from ??341 to 1,193 mg m^???2 h^???1, and the mean value over all three forests and sampling times was 286 mg m^???2 h^???1. CO₂ release was positively correlated with soil water content and the soil temperature. Diurnally, CO₂ release was higher in the day than at night. Seasonally, CO₂ release was highest in early autumn and lowest in winter; in winter, negative values of CO₂ release suggested that CO₂ was absorbed by soil.     

北京市废弃物处理温室气体排放特征

基于《2006年IPCC国家温室气体清单指南》推荐的方法，结合《省级温室气体清单编制指南（试行）》和《城市温室气体核算工具指南》的部分数据与核算范围，针对固体废弃物填埋、焚烧和废水处理等过程，核算了北京市2005-2014年废弃物处理过程中温室气体总排放量。结果表明：2005-2014年北京市废弃物处理过程温室气体总排放量呈逐渐上升趋势，2014年温室气体总排放量比2005年增长98%。10年间，固体废弃物填埋过程一直是最主要的温室气体排放源，到2014年排放量达到最大，为416.3×10⁴t二氧化碳当量（CO₂e）。废弃物填埋、废水处理和废弃物焚烧过程占总排放量的比例分别为78.5%（CO₂e质量分数，下同）、13.5%和8%。结合已有研究，系统优化国内7个典型城市废弃物处理温室气体排放因子，核算7个城市排放情况，并对比分析了北京市排放情况。