Estimation of green house gas emissions from Koteshwar hydropower reservoir, India.

BackgroundSoil-derived prokaryotic gut communities of the Japanese beetle Popillia japonica Newman (JB) larval gut include heterotrophic, ammonia-oxidizing, and methanogenic microbes potentially capable of promoting greenhouse gas (GHG) emissions. However, no research has directly explored GHG emissions or the eukaryotic microbiota associated with the larval gut of this invasive species. In particular, fungi are frequently associated with the insect gut where they produce digestive enzymes and aid in nutrient acquisition. Using a series of laboratory and field experiments, this study aimed to (1) assess the impact of JB larvae on soil GHG emissions; (2) characterize gut mycobiota associated with these larvae; and (3) examine how soil biological and physicochemical characteristics influence variation in both GHG emissions and the composition of larval gut mycobiota.MethodsManipulative laboratory experiments consisted of microcosms containing increasing densities of JB larvae alone or in clean (uninfested) soil. Field experiments included 10 locations across Indiana and Wisconsin where gas samples from soils, as well as JB and their associated soil were collected to analyze soil GHG emissions, and mycobiota (ITS survey), respectively.ResultsIn laboratory trials, emission rates of CO2, CH4, and N2O from infested soil were ≥ 6.3× higher per larva than emissions from JB larvae alone whereas CO2 emission rates from soils previously infested by JB larvae were 1.3× higher than emissions from JB larvae alone. In the field, JB larval density was a significant predictor of CO2 emissions from infested soils, and both CO2 and CH4 emissions were higher in previously infested soils. We found that geographic location had the greatest influence on variation in larval gut mycobiota, although the effects of compartment (i.e., soil, midgut and hindgut) were also significant. There was substantial overlap in the composition and prevalence of the core fungal mycobiota across compartments with prominent fungal taxa being associated with cellulose degradation and prokaryotic methane production/consumption. Soil physicochemical characteristics such as organic matter, cation exchange capacity, sand, and water holding capacity, were also correlated with both soil GHG emission, and fungal a-diversity within the JB larval gut. Conclusions: Results indicate JB larvae promote GHG emissions from the soil directly through metabolic activities, and indirectly by creating soil conditions that favor GHG-associated microbial activity. Fungal communities associated with the JB larval gut are primarily influenced by adaptation to local soils, with many prominent members of that consortium potentially contributing to C and N transformations capable of influencing GHG emissions from infested soil.

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The capacity of soil to store carbon (C) and emit carbon dioxide (CO2) into the atmosphere primarily depends on soil management practices. It is essential to understand the impact of management strategies on the soil organic carbon (SOC) content and labile organic carbon (LOC) fraction. The impacts of 24‑year-long organic and inorganic nitrogen (N) treatments on SOC, KMnO4-oxidizable organic carbon and its fractions (highly labile organic carbon (HLOC), moderately labile organic carbon (MLOC), low labile organic carbon (LLOC) and nonlabile organic carbon (NLOC)), and a carbon management index (CMI) were investigated under a continuous maize cultivation system in a long-term experiment in Guizhou, Southwest China. Six fertilizer treatments were included: no fertilizer input (CK), chemical fertilizer alone (NPK), 25% N through farmyard manure (FYM) plus 75% N through chemical fertilizer (1/4N-M+3/4N-CF), 50% N through FYM plus 50% N through chemical fertilizer (1/2N-M+1/2N-CF), FYM plus chemical fertilizer (MNPK) and FYM alone (M). We used the LOC content and CMI value to assess the effects of long-term combinations of FYM and chemical fertilizers at different rates on the SOC pool in various soil layers (0–20, 20–40, 40–60, 60–80, 80–100 cm) and to identify the most suitable integrated treatment. The results showed that the application of organic fertilizer generally increased the SOC content, the LOC fraction, and the CMI values in different layers, especially the surface layer, compared to the CK and NPK fertilization treatments. The SOC content and LOC fraction decreased with increasing soil depth. The significant relationship between the LOC fraction, CMI value, LOC available ratio of carbon (LOC-AR), and soil parameters showed that these values can be used to sensitively assess soil quality and SOC changes in the system. Considering the comprehensive effects on the SOC content, LOC fraction, CMI value, AR value, etc., the 1/4N-M+3/4N-CF and 1/2N-M+1/2N-CF treatments showed the greatest influence on carbon sequestration and soil productivity; therefore, these could be the best options for maize cropping systems in this region.

Better information on greenhouse gas (GHG) emissions and mitigation potential in the agricultural sector is necessary to manage these emissions and identify responses that are consistent with the food security and economic development priorities of countries. Critical activity data (what crops or livestock are managed in what way) are poor or lacking for many agricultural systems, especially in developing countries. In addition, the currently available methods for quantifying emissions and mitigation are often too expensive or complex or not sufficiently user friendly for widespread use.The purpose of this focus issue is to capture the state of the art in quantifying greenhouse gases from agricultural systems, with the goal of better understanding our current capabilities and near-term potential for improvement, with particular attention to quantification issues relevant to smallholders in developing countries. This work is timely in light of international discussions and negotiations around how agriculture should be included in efforts to reduce and adapt to climate change impacts, and considering that significant climate financing to developing countries in post-2012 agreements may be linked to their increased ability to identify and report GHG emissions (Murphy et al 2010, CCAFS 2011, FAO 2011).

Life-cycle analysis (LCA) is an important tool used to assess the energy and environmental impacts of biofuels. Here, we review biofuel LCA methodology and its application in transportation fuel regulations in the United States, the European Union, and the United Kingdom. We examine the application of LCA to the production of ethanol from corn, sugarcane, corn stover, switchgrass, and miscanthus. A discussion of methodological choices such as co-product handling techniques in biofuel LCA is also provided. Further, we discuss the estimation of greenhouse gas (GHG) emissions of land use changes (LUC) potentially caused by biofuels, which can significantly influence LCA results. Finally, we provide results from LCAs of ethanol from various sources. Regardless of feedstock, bioethanol offers reduced GHG emissions over fossil-derived gasoline, even when LUC GHG emissions are included. This is mainly caused by displacement of fossil carbon in gasoline with biogenic carbon in ethanol. Of the ethanol pathways examined, corn ethanol has the greatest life-cycle GHG emissions and offers 30% reduction in life-cycle GHG emissions as compared to gasoline when LUC GHG emissions are included. Miscanthus ethanol demonstrates the highest life-cycle GHG emissions reductions compared to gasoline, 109%, when LUC GHG emissions are included.

Bridging the data gap: engaging developing country farmers in greenhouse gas accounting

At the UN climate change conference in Paris in November 2015, Norway committed itself to a 40% reduction in greenhouse gas (GHG) emissions by 2030 compared to 1990 levels. Agriculture accounts for 8% of Norway’s total GHG emissions. If GHGs from drained and cultivated wetland (categorized under land use, land use change and forestry) are included, the share is 13%; this for a sector that accounts for roughly 0.3% of GDP. As is the case in most countries, agriculture is currently exempt from emission reduction measures, including the European Union’s Emissions Trading System (ETS), in which Norway participates. But the country has recently signaled its intention to include agriculture in future emission reduction efforts. Consideration is being given to how best to achieve GHG reductions in the sector. A recent report by the Norwegian Green Tax Commission, established by the government to evaluate policy options for achieving emission reductions, (Government of Norway, 2015) emphasizes the importance of including agriculture. The Commission suggests that agricultural emissions should be taxed at the same rate as for other sectors. It also recommends that reductions in the production and consumption of red meat should be specifically targeted, through cuts in production grants to farmers and the imposition of consumption taxes. Unsurprisingly, this proposed policy shift is extremely controversial and faces resistance, particularly from the farmers’ unions. Farmers argue that the maintenance of domestic agricultural production is crucial for achieving national food security objectives, in addition to pursuing other aims such as the maintenance of economic activity in rural areas and landscape preservation. Food security, which has been a key policy objective since the end of the Second World War, has been interpreted in Norway as requiring high levels of selfsufficiency in basic agricultural commodities. To achieve this, substantial subsidies are provided to farmers and domestic prices of many commodities are kept at high levels by restricting imports. The Organization for Economic Cooperation and Development (OECD) estimates that the total financial support provided to Norwegian agriculture in 2015 was equivalent to 62% of the value of gross farm receipts, which made Norway (along with Switzerland) a leader in the amount of support provided to agriculture by the 50 OECD member and non-member countries monitored by the Organization (OECD, 2016). In this paper we analyze policy options for achieving a 40% reduction in agricultural GHG emissions, consistent with the economy-wide target, while imposing the restriction that national food production measured in calories should be maintained (the food security target). This is consistent with the way that the Norwegian government identifies the country’s food security objective. In section 2 we outline the current situation with respect to GHG emissions in Norwegian agriculture. In section 3 we illustrate the policy issues involved by considering two product aggregates that are intensive in the use of land for crop production (grainland) and grassland, respectively. The aggregates are based on data for the main commodities in Norwegian agriculture relating to GHG emissions, land use, caloric content, subsidies, and costs per unit of production. We show that even though the opportunity set (i.e., the production combinations that are possible within technical constraints) is narrow, a 40% cut in emissions is achievable by substituting from ruminant products that are intensive in the use of grassland to products based on grainland. We also show that the emissions reduction both reduces government budgetary costs and land use, i.e., ruminant products are characterized by relatively high subsidies and land use. Two-dimensional analysis ignores the fact that per unit emissions from dairy production are low compared to other ruminant products (i.e., beef and sheep production). Both in terms of production value and agricultural employment, dairy farming is the most important component of Norwegian agriculture. Consequently, milk production deserves to be separated from ruminant meat production. Finally in section 4, we present a detailed analysis 3 of policy options derived from a disaggregated model that includes all the major products in Norwegian agriculture. In the model-based analysis, we examine first the imposition of a carbon tax, while maintaining existing agricultural support policies and import protection, and achieving the food security (production of calories) target. Since the imposition of a carbon tax in agriculture presents both technical and political challenges, we then examine an alternative approach of changing the existing structure of agricultural support to approximate the same result. We show that it is possible to change current subsidy rates to mimic the carbon tax and calorie target solution. The explanation for this is that ruminant products not only generate high emissions per produced calorie, but they are also the most highly subsidized products. Meat from ruminants is relatively unimportant in achieving Norway’s food security objective of calorie availability.

Life cycle greenhouse gas emissions impacts of the adoption of the EU Directive on biofuels in Spain. Effect of the import of raw materials and land use changes

Globally, agriculture is directly responsible for 14% of annual greenhouse gas(GHG) emissions and induces an additional 17% through land use change, mostlyin developing countries (Vermeulen et al 2012). Agricultural intensification andexpansion in these regions is expected to catalyze the most significant relativeincreases in agricultural GHG emissions over the next decade (Smith et al 2008,Tilman et al 2011). Farms in the developing countries of sub-Saharan Africa andAsia are predominately managed by smallholders, with 80% of land holdingssmaller than ten hectares (FAO 2012). One can therefore posit that smallholderfarming significantly impacts the GHG balance of these regions today and willcontinue to do so in the near future.However, our understanding of the effect smallholder farming has on theEarth’s climate system is remarkably limited. Data quantifying existing andreduced GHG emissions and removals of smallholder production systems areavailable for only a handful of crops, livestock, and agroecosystems (Herrero et al2008, Verchot et al 2008, Palm et al 2010). For example, fewer than fifteenstudies of nitrous oxide emissions from soils have taken place in sub-SaharanAfrica, leaving the rate of emissions virtually undocumented. Due to a scarcity ofdata on GHG sources and sinks, most developing countries currently quantifyagricultural emissions and reductions using IPCC Tier 1 emissions factors.However, current Tier 1 emissions factors are either calibrated to data primarilyderived from developed countries, where agricultural production conditions aredissimilar to that in which the majority of smallholders operate, or from data thatare sparse or of mixed quality in developing countries (IPCC 2006). For the mostpart, there are insufficient emissions data characterizing smallholder agricultureto evaluate the level of accuracy or inaccuracy of current emissions estimates.Consequentially, there is no reliable information on the agricultural GHG budgetsfor developing economies. This dearth of information constrains the capacity totransition to low-carbon agricultural development, opportunities for smallholdersto capitalize on carbon markets, and the negotiating position of developingcountries in global climate policy discourse.Concerns over the poor state of information, in terms of data availability andrepresentation, have fueled appeals for new approaches to quantifying GHGemissions and removals from smallholder agriculture, for both existing conditionsand mitigation interventions (Berry and Ryan 2013, Olander et al 2013).Considering the dependence of quantification approaches on data and the currentdata deficit for smallholder systems, it is clear that in situ measurements must bea core part of initial and future strategies to improve GHG inventories and

Crop residues under different water regimes can cause significant alterations in soil organic carbon fractions, and in turn, soil-atmospheric carbon dioxide (CO2) emissions. To evaluate the effect of rice straw application on CO2 emissions and labile organic carbon fractions under different water regimes, an incubation experiment was conducted for 90 days. Ten treatments were developed from the interaction between five water levels (100, 85, 70, 55, and 40 % of water-holding capacity (WHC)) with and without incorporation of rice straw. Peaks of CO2 fluxes were observed after 13 days of rice straw incorporation, which decreased gradually till the end of the incubation period. The incorporation of rice straw caused significant increases in CO2 fluxes by 2.77-2.83 times from the paddy soil. In the presence of rice straw, the highest CO2 fluxes were generally observed at W3 (70 % of WHC), whereas the lowest fluxes were occurred at W1 (100 % of WHC). Addition of rice straw under a range of water regimes markedly improved the transformation of soil organic carbon and labile organic carbon pools such as dissolved organic carbon, microbial biomass carbon, light fraction organic carbon, particulate organic carbon, and permanganate oxidizable carbon. The significant correla- tions between all labile soil organic carbon fractions and CO2 concentrations confirmed their important roles in the emission of CO2 from the paddy soil. In summary, the results suggest that light fraction organic carbon, particu- late organic carbon, and permanganate oxidizable carbon were more sensitive indicators for CO2 emissions and organic matter alterations as compared to other carbon fractions.

Land use type is an important factor influencing greenhouse gas emissions from soils, but the mechanisms involved in affecting potential greenhouse gas (GHG) emissions in different land use systems are poorly understood. Since the northern regions of Canada and China are characterized by cool growing seasons, GHG emissions under low temperatures are important for our understanding of how soil temperature affects soil C and N turnover processes and associated greenhouse gas emissions in cool temperate regions. Therefore, we investigated the effects of temperature on the emission of N2O, CO2, and CH4 from typical forest and grassland soils from China and Canada. The soils were incubated in the laboratory at 10°C and 15°C under aerobic conditions for 15 days. The results showed that land use type had a large impact on greenhouse gas emissions. The N2O emissions were significantly higher in grassland than in forest soils, while CO2 emissions were higher in forest than in grassland soils. Grassland soils were weak sources of CH4 emission, while forest soils were weak sinks of atmospheric CH4. The global warming potential of forest soils was significantly greater than that of grassland soils. Soil pH, C/N ratio, and soluble organic carbon concentrations and clay content were dominant factors influencing the emissions of N2O and CO2, respectively. Increasing temperature from 10°C to 15°C had no effects on CH4 flux, but significantly increased N2O emissions for all studied soils. The same pronounced effect was also found for CO2 emission from forest soils. Indications from this study are that the effects of land use type on the source–sink relationship and rates of GHG emissions should be taken into consideration when planning management strategies for mitigation of greenhouse gas emissions in the studied region, and temperature changes must be taken into account when scaling up point- or plot-based N2O and CO2 flux data to the landscape level due to large spatial and temporal variations of temperature that exist in the field. The reader is cautioned about the limitation with incubation studies on a limited number of samples/locations, and care need to be exercised to extrapolate the result to field conditions.

This monograph is concerned with different aspects of green house gas (GHG) emissions in agriculture. The first part summarizes the total amount of GHG emissions and analyses them regarding their composition. A differentiation is made between the emissions which are already linked to agriculture (source group agriculture: digestion , manure-management and agricultural soils ) within the National Report on GHG Emissions and those which can be counted primarily in addition to agriculture ( energy and land use and land use change ). Depending on which database is used, agriculture is participating in emitting green house gases with 6.3% or 11.1% of total German GHG emissions in 2004. This means that agriculture is an important polluter. The development of GHG emissions in agriculture compared to the year 1990 is -18.5% for the source group agriculture. This means that the source group has reduced more emissions than the average (-17.5%) over all domains published within the National Report. Regarding the sources energy and land use and land use change in addition emission reduction is -16.4% in the same period and thus worse than the average. Moreover, realized emission reductions are predominantly based on structural changes, less on systematical measures. This fact raises the question how agriculture can make a contribution to the reduction of GHG emissions in future particularly with regard to higher aims in climate politics.For this reason the second part of the monograph identifies capacities for the reduction of GHG emissions by using available agricultural biomass for energetic purposes. Due to the heterogeneity of biomass and the variety of its possible products, a lot of technical processes concerning the conversion of biomass into energy exist in practice. Since all of them have different emission factors the derivation of realistic reduction capacities is a nontrivial problem. This work restricts the problem by combining existing biomass with those technologies which provide largest benefit concerning the reduction of GHG emissions. Thereby it is possible to evaluate the maximum contribution of GHG reductions from biomass usage in agriculture in Germany, which aggregates up to 50,341 Gg CO2-equivalent. This means that 78.3% of the emissions from the source group agriculture in 2004 could be compensated if biomass was used within those technologies which produce the largest benefit. In this regards the subsidy of energy crops in biogas plants based on the Erneuerbare Energien Gesetz (renewable energy law) in Germany should be reviewed because there they do not produce the largest benefit. Energy crops should be applied to replace solid fuels instead. Since in practice several biogas plants are already using energy crops as input material without having an option for alternatives, the question raises how this fact can be improved for the future regarding climate protection.Therefore the third part of this monograph analyses the possible emission reductions of different technologies for converting biogas into energy. Objects of investigation are existing technologies like block heat and power plants or direct gas feeding into public gas distribution system as well as future technologies like the application of biogas in different types of fuel cells. Although direct gas feeding has a better ratio concerning the conversion of primary to secondary energy the GHG reduction capacity is much less compared to technologies of cogeneration. The reason for this is that the production of electricity has much more effect on GHG emissions than the production of heat. This is to be seen when comparing the emission factors of certain reference systems used in this part like condensing boilers running with natural gas (253 gCO2/kWhheat), gas steam power plants (432 gCO2/kWhel) and the average emissions factor of German power production (653 gCO2/kWhel). The more electricity is produced by a conversion technology based on biogas, the higher is its GHG reduction capacity. Direct gas feeding is not the most efficient way of using biogas in matters of climate protection considering that only 13% of the natural gas in Germany is used for electric purposes and considering that replacing natural gas by biogas means that the part of fossil fuels with lowest emissions is replaced. Direct gas feeding is not even then the most efficient way of using biogas if there is a consumer at the other end of the public gas distribution system who theoretically uses the injected biogas for running cogeneration systems. The conditioning of biogas in order to feed public distribution combined with additional heat source for running the fermenter of the biogas plant is worse for efficiency. Considering ecological standpoints local heat and power production next to the fermenter is the most efficient way of using biogas in matters of climate protection. This can only be improved by using more efficient systems like fuel cells instead of existing block heat and power plants.

Greenhouse gas (GHG) emissions resulting from the Land Use, Land-Use Change, and Forestry sector (LULUCF) are estimated and reported in National Communications to the United Nations Framework Convention on Climate Change (UNFCCC). By definition, the LULUCF sector is a “greenhouse gas (GHG) inventory sector that covers emissions and removals of greenhouse gases resulting from direct human-induced land use, land-use change and forestry activities”. In principle, the annual GHG national inventory should be transparent, consistent, comparable, complete, and accurate. Also, it should be able to systematically account for all changes in land use and forest cover over many years. In this context, it is essential to investigate the development of an automated approach for mapping local GHG emissions/removals from the LULUCF sector for integration at the national level. In view of that, the aim of this work was to develop a semi-automated model for estimating GHG emissions and removals form the LULUCF sector at the local level. The specific objectives were to 1) map changes in land use and forest cover between two consecutive years, and 2) assess GHG emissions and removals from the LULUCF sector. The methodology of work comprised the use of Geographic Object-Based Image Analysis (GEOBIA) for modelling changes in the LULUCF sector and, subsequently, estimating GHG emissions/removals between two consecutive years. The combined use of Very High Resolution (VHR) SPOT imagery (2.5 m colour) and field data was involved in identifying and mapping land-use changes between 2014 and 2015. Subsequently, GHG emissions and removals were estimated using customized features in GEOBIA and following the 2003 Intergovernmental Panel on Climate Change “Good Practice Guidance for Land Use, Land-Use Change and Forestry”, which adopts a land use category-based approach to estimate emissions/removals from all land categories and all relevant GHGs. An accuracy assessment of the initial classification was conducted with the use of reference data. The overall classification accuracy of the LULUCF mapping in 2014 was found to be 83%, while the Kappa Index of Agreement (KIA) was 0.74. The developed GEOBIA model estimated for the year 2015 net annual GHG removals of -1.613 Gg of CO2 eq. (i.e., an approximate increase of 12.7% in removals between 2014 and 2015). Future work will involve further development of the model to account for all possible changes in the LULUCF sector and test the transferability of the model to other sites.

Land use change has a significant effect on soil organic carbon (SOC), especially on labile organic carbon (LOC) due to its rapid response to soil changes and carbon supply. The objective of the study was to assess the effects of different land uses on soil fraction size distribution, SOC and LOC concentrations and their stocks in karst region of Guizhou Province, Southwest China. Studies were based on soil sampling in paddy, dryland, abandoned cultivated land for 3-years (AC-3), and abandoned cultivated land for 15-years (AC-15) in the 0–10, 10–20, and 20–30 cm depths in karst mountain area of Guizhou Province. Three fraction-size classes [macro (250–2000 μm), micro (53–250 μm), silt + clay (<53 μm)] were fractioned, and SOC and LOC concentrations in whole soil (non-fractionated) and different fraction sizes were also determined. The results showed that paddy contained the highest SOC and LOC concentrations in whole soil and different size-fractions as compared with other land uses down to 30 cm depth. However, the proportions of LOC to SOC were higher in AC-3 than the other land uses, especially pronounced in whole soil, which ranged from 17.5 to 26.3 % in different soil depths. Paddy also contained 23.7 % (100.9 Mg ha−1) more SOC and 17.6 % (19.7 Mg ha−1) more LOC stocks than dryland, whereas the SOC and LOC stocks in AC-15 and dryland were very close to each other in each soil depth. In paddy field, we found that macro-sized fractions contributed the greatest quantities of SOC to whole soil. In addition, paddy had significantly higher SOC stock values in macro-sized fractions than the other land uses in the both 0–10 and 10–20 cm depths. In the present study, there were no obvious increases of SOC and LOC pools among whole soil and different soil size-fractions after 15 years of land abandonment. These results suggest that natural recovery of SOC may take a long time after land abandonment, and paddy could serve as an important land use type for long-term carbon sequestration in karst region of Southwest China.

Rivers play an important role in greenhouse gas emissions. Over the past decade, because of global urbanization trends, rapid land use changes have led to changes in river ecosystems that have had a stimulating effect on the greenhouse gas production and emissions. Presently, there is an urgent need for assessments of the greenhouse gas concentrations and emissions in watersheds. Therefore, this study was designed to evaluate river-based greenhouse gas emissions and their spatial-temporal features as well as possible impact factors in a rapidly urbanizing area. The specific objectives were to investigate how river greenhouse gas concentrations and emission fluxes are responding to urbanization in the Liangtan River, which is not only the largest sub-basin but also the most polluted one in Chongqing City. The thin layer diffusion model method was used to monitor year-round concentrations of pCO2, CH4, and N2O in September and December 2014, and March and June 2015. The pCO2 range was (23.38±34.89)-(1395.33±55.45) Pa, and the concentration ranges of CH4 and N2O were (65.09±28.09)-(6021.36±94.36) nmol·L-1 and (29.47±5.16)-(510.28±18.34) nmol·L-1, respectively. The emission fluxes of CO2, CH4, and N2O, which were calculated based on the method of wind speed model estimations, were -6.1-786.9, 0.31-27.62, and 0.06-1.08 mmol·(m2·d)-1, respectively. Moreover, the CO2 and CH4 emissions displayed significant spatial differences, and these were roughly consistent with the pollution load gradient. The greenhouse gas concentrations and fluxes of trunk streams increased and then decreased from upstream to downstream, and the highest value was detected at the middle reaches where the urbanization rate is higher than in other areas and the river is seriously polluted. As for branches, the greenhouse gas concentrations and fluxes increased significantly from the upstream agricultural areas to the downstream urban areas. The CO2 fluxes followed a seasonal pattern, with the highest CO2 emission values observed in autumn, then successively winter, summer, and spring. The CH4 fluxes were the highest in spring and the lowest in summer, while N2O flux seasonal patterns were not significant. Because of the high carbon and nitrogen loads in the basin, the CO2 products and emissions were not restricted by biogenic elements, but levels were found to be related to important biological metabolic factors such as the water temperature, pH, DO, and chlorophyll a. The carbon, nitrogen, and phosphorus content of the water combined with sewage input influenced the CH4 products and emissions. Meanwhile, N2O production and emissions were mainly found to be driven by urban sewage discharge with high N2O concentrations. Rapid urbanization accelerated greenhouse gas emissions from the urban rivers, so that in the urban reaches, CO2/CH4 fluxes were twice those of the non-urban reaches, and all over the basin N2O fluxes were at a high level. These findings illustrate how river basin urbanization can change aquatic environments and aggravate allochthonous pollution inputs such as carbon, nitrogen, and phosphorus, which in turn can dramatically stimulate river-based greenhouse gas production and emissions; meanwhile, spatial and temporal differences in greenhouse gas emissions in rivers can lead to the formation of emission hotspots.