Atmospheric methane concentrations were quantified along transects in Switzerland, using a mobile laser spectrometer combined with a GPS, to identify their spatio-temporal patterns and their controlling factors. Based on these measurements in complex terrain dominated by agriculture, three main factors were found to be responsible for the diurnal and regional patterns of atmospheric methane: (1) magnitude and distribution of methane sources within the region, (2) efficiency of vertical exchange, and (3) local wind patterns within the complex topography. An autocorrelation analysis of measured methane concentrations showed that nighttime measurements close to the ground provide information about regional sources (up to 8.3 km), while daytime measurements only carry information about sources located up to 240 m away in the upwind fetch. Compared to daytime concentrations, nighttime methane concentrations do also better reflect emissions obtained from a spatially explicit methane emission inventory and allowed the investigation of inconsistencies in this emission inventory.

The distributions of dissolved methane in the central Bohai Sea were investigated in November 2011, May 2012, July 2012, and August 2012. Methane concentration in surface seawater, determined using an underway measurement system combined with wavelength-scanned cavity ring-down spectroscopy, showed marked spatiotemporal variations with saturation ratio from 107% to 1193%. The central Bohai Sea was thus a source of atmospheric methane during the survey periods. Several episodic oil and gas spill events increased surface methane concentration by up to 4.7 times and raised the local methane outgassing rate by up to 14.6 times. This study demonstrated a method to detect seafloor CH4 leakages at the sea surface, which may have applicability in many shallow sea areas with oil and gas exploration activities around the world.

Development and urbanization over the past decade has led to rapid increase in the population of Delhi, the metropolitan city of India. Consequently, there has been a tremendous increase in the number of vehicles, which are causing very high levels of air pollution. Vehicular emissions are becoming most predominant source of air pollution in Delhi. An annual emission inventory of road transport emissions of pollutants including carbon monoxide (CO), methane (CH4), nitrogen oxides (NOX), sulfur dioxide (SO2), volatile organic compounds (VOCs), particulate matter (PM10), lead (Pb) and hydrocarbon (HC), organic carbon (OC) and black carbon (BC) has been developed (for the period 2000–2010), for the Delhi region. Emissions have been estimated using emission factor and activity–based approach recommended by IPCC. The emissions of CO and NOX have increased nearly 77% and 29% respectively over 2000 to 2010, whereas contribution of SO2 has greatly reduced (~21%) due to phasing out of diesel driven buses and implementation of Bharat Stage–III norms to commercial vehicles. An appreciable increase in NOX emissions has been observed after 2005, which might be due to the use of CNG fuel. Emissions of PM10, OC and BC have decreased in 2001 and 2002, however these are continuously increasing after 2002 due to rapid rise in the annual rate of growth of registered vehicles in Delhi. Two wheelers (2Ws), which constitute 60% of total registered vehicles, have been found to be major contributors towards emissions of the pollutants considered in the present study.

The carbon balance of secondary dry tropical forests of Mexico’s Yucatan Peninsula is sensitive to human and natural disturbances and climate change. The spatially explicit process model Forest-DeNitrification-DeComposition (DNDC) was used to estimate forest carbon dynamics in this region, including the effects of disturbance on carbon stocks. Model evaluation using observations from 276 sample plots in a tropical dry forest in the Yucatan Peninsula indicated that Forest-DNDC can be used to simulate carbon stocks for this forest with good model performance efficiency. The simulated spatial variability in carbon stocks was large, ranging from 5 to 115 Mg carbon (C) ha⁻¹, with a mean of 56.6 Mg C ha⁻¹. Carbon stocks in the forest were largely influenced by human disturbances between 1985 and 2010. Based on a comparison of the simulations with and without disturbances, carbon storage in the year 2012 with disturbance was 3.2 Mg C ha⁻¹, lower on average than without disturbance. The difference over the whole study area was 154.7 Gg C, or an 8.5 % decrease. There were substantial differences in carbon stocks simulated at individual sample plots, compared to spatially modeled outputs (200 m²plots vs. polygon simulation units) at some locations due to differences in vegetation class, stand age, and soil conditions at different resolutions. However, the difference in the regional mean of carbon stocks between plot-level simulation and spatial output was small. Soil CO₂and N₂O fluxes varied spatially; both fluxes increased with increasing precipitation, and soil CO₂also increased with an increase in biomass. The modeled spatial variability in CH₄uptake by soils was small, and the flux was not correlated with precipitation. The net ecosystem exchange (NEE) and net primary production (NPP) were nonlinearly correlated with stand age. Similar to the carbon stock simulations, different resolutions resulted in some differences in NEE and NPP, but the spatial means were similar.

Fugitive greenhouse gas emissions from unconventional gas extraction processes (e.g. shale gas, tight gas and coal bed methane/coal seam gas) are poorly understood due in part to the extensive area over which these emissions may occur. We apply a rapid qualitative approach for source assessment at the scale of a large gas field. A mobile cavity ring down spectrometer (Picarro G2201-i) was used to provide real-time, high-precision methane and carbon dioxide concentration and carbon isotope ratios (δ¹³C), allowing for “on the fly” decision making and therefore an efficient and dynamic surveying approach. The system was used to map the atmosphere of a production coal seam gas (CSG) field (Tara region, Australia), an area containing pre-production “exploration” CSG wells (Casino, Australia), and various other potential CO₂and CH₄sources (i.e. wetlands, sewage treatment plants, landfills, urban areas and bushfires). Results showed a widespread enrichment of both CH₄(up to 6.89 ppm) and CO₂(up to 541 ppm) within the production gas field, compared to outside. The CH₄and CO₂δ¹³C source values showed distinct differences within and outside the production field, indicating a CH₄source within the production field that has a δ¹³C signature comparable to the regional CSG. While this study demonstrates how the method can be used to qualitatively assess the location and source of emissions, integration with atmospheric models may allow for quantitative assessment of emissions. The distinct patterns observed within the CSG field demonstrates the need to fully quantify the atmospheric flux of natural and anthropogenic, point and diffuse sources of greenhouse gases from individual Australian gas fields before and after production commences.

In the present research work, different types of biodiesel were produced by a homogeneous alkali transesterification reaction using soybean oil, pork lard, and castor bean oil as raw materials, to evaluate how their different compositions may affect the biodegradability, namely, in the presence of benzene. Biodiesel was characterized according to the European standard EN 14214. The anaerobic biodegradation of the different types of biodiesel was examined as well as its influence on the biodegradation of benzene. Analyses were performed to determine the volume of methane (directly related to the anaerobic biodegradation of biodiesel), the concentration of benzene over time, and the production of organic acids. The results showed methane production resulting from the anaerobic degradation of all biodiesel types. The differences between the degradation behavior of each fuel were negligible, contrary to what was expected; however, the amount of methane produced was low due to nutrient limitations. This fact was confirmed by the organic acid analysis as well as by the addition of new media. Anaerobic benzene biodegradation was found to be negatively impacted by the presence of all biodiesel types on average; therefore, the results of this study may impact management of sites that contain biodiesel and fuel hydrocarbon contamination.

A pot experiment was conducted to investigate the effect of nitrogen fertilizer on CH₄ emission from a paddy soil under greenhouse conditions. The experiment was designed with two fertilizer types, i.e., controlled-release nitrogen fertilizer (CRNF) and urea (U), and two rice cultivars, i.e., herbicide-resistant transgenic rice (japonica line B2) and its parent conventional rice (japonica cv Xiushui 63). Compared with control (urea), one-time basal application of CRNF increased tiller number, plant height, biomass, and yield in rice and significantly decreased total CH₄ emission from the paddy soil. The total CH₄ emission was significantly lower from the transgenic cultivar than that from the conventional cultivar. It is suggested that CRNF and herbicide-resistant transgenic rice are helpful in mitigating CH₄ emission from the paddy soil.

This study focused on the pattern recognition of Malaysian air quality based on the data obtained from the Malaysian Department of Environment (DOE). Eight air quality parameters in ten monitoring stations in Malaysia for 7 years (2005–2011) were gathered. Principal component analysis (PCA) in the environmetric approach was used to identify the sources of pollution in the study locations. The combination of PCA and artificial neural networks (ANN) was developed to determine its predictive ability for the air pollutant index (API). The PCA has identified that CH₄, NmHC, THC, O₃, and PM₁₀are the most significant parameters. The PCA-ANN showed better predictive ability in the determination of API with fewer variables, with R²and root mean square error (RMSE) values of 0.618 and 10.017, respectively. The work has demonstrated the importance of historical data in sampling plan strategies to achieve desired research objectives, as well as to highlight the possibility of determining the optimum number of sampling parameters, which in turn will reduce costs and time of sampling.

In order to assess correctly the gases emissions from oil/gas field water and its contributions to the source of greenhouse gases (GHG) at the atmospheric temperature and pressure, a simulation experiment was first developed to study the natural emissions of GHG into the atmosphere in the southern gas field, Sichuan Basin, China. The result showed that methane (CH₄) and carbon dioxide (CO₂) were the two gases that released from the gas field water. Time and temperature played important roles in GHG emissions, and the higher temperature was found to enhance carbon emissions. Under the lower/intermediate temperature conditions (5 and 15 °C), majority of gases were released from the gas field water during the first 2 h, whereas under the higher temperature conditions (30 °C), the majority of gas released from the gas field water continued for 12 h. By dividing the whole emission duration into six time durations (one time duration was 12 h), we calculated the fluxes of CH₄and CO₂. The substantial variation in the gas fluxes reflected that the cumulation of time also played a crucial role in the process of GHG emissions. In the first emission duration (0–12 h) at 30 °C, the maximum fluxes of CH₄and CO₂were 1.47 and 1.87 g/m³·h, respectively. The values were obviously higher than those in other durations, so were the fluxes shift in different durations at 5 and 15 °C. Additionally, we found that the emissions released from the gas field water which came from overpressure formation formed higher carbon emissions.

Methane (CH₄) formation in wastewater treatment is linked to long residence times under anaerobic conditions such as those in sewers and primary treatment units. Emissions of this methane to the atmosphere can occur under turbulent flows and, potentially, during aeration in an activated sludge plant. An online, 8-week monitoring campaign of CH₄emissions and operational conditions was conducted to study emissions from a full-scale nitrifying activated sludge plant (ASP). Significant emissions were found throughout the aerated lane, with the highest values observed two thirds down the lane. Emissions had high diurnal and spatial variability, with values ranging from 0.3 to 24 g CH₄/h. No significant correlations were found between dissolved oxygen, aeration or influent loads. The results suggest that emissions are linked to upstream process conditions, with potential for methane generation in-lane due periods of limited oxygen availability. The dynamic oxygen profile observed suggests that aerobic and anoxic conditions coexist in the lane, leading to limited oxygen diffusion from the bulk liquid to the inner regions of the floc where anoxic/anaerobic layers may allow methanogenic microorganisms to survive. The average emission factor was 0.07 % of removed chemical oxygen demand, giving a total of 668 kg CH₄/year and 14,000 CO₂equivalents/year. The operational carbon associated with the energy requirements of the ASP increased by 5 %. With emerging legislation requiring the reporting of greenhouse gas emissions, the carbon impact may be significant, particularly as the industry moves towards a carbon-reducing future. Therefore, an adequate profiling of full-scale emissions is critical for future proofing existing treatment technologies.