Trends In Greenhouse Gas Emissions Research Articles

Trends in the contribution of greenhouse gas emissions from food and beverage purchases in Mexico: 1989–2020

BackgroundAssessing the trends in dietary GHGE considering the social patterning is critical for understanding the role that food systems have played and will play in global emissions in countries of the global south. Our aim is to describe dietary greenhouse gas emissions (GHGE) trends (overall and by food group) using data from household food purchase surveys from 1989 to 2020 in Mexico, overall and by education levels and urbanicity.MethodsWe used cross-sectional data from 16 rounds of Mexico’s National Income and Expenditure Survey, a nationally representative survey. The sample size ranged from 11,051 in 1989 to 88,398 in 2020. We estimated the mean total GHGE per adult-equivalent per day (kg CO2-eq/ad-eq/d) for every survey year. Then, we estimated the relative GHGE contribution by food group for each household. These same analyses were conducted stratifying by education and urbanicity.ResultsThe mean total GHGE increased from 3.70 (95%CI: 3.57, 3.82) to 4.90 (95% CI 4.62, 5.18) kg CO2-eq/ad-eq/d between 1989 and 2014 and stayed stable between 4.63 (95% CI: 4.53, 4.72) and 4.89 (95% CI: 4.81, 4.96) kg CO2-eq/ad-eq/d from 2016 onwards. In 1989, beef (19.89%, 95% CI: 19.18, 20.59), dairy (16.87%, 95% CI: 16.30, 17.42)), corn (9.61%, 95% CI: 9.00, 10.22), legumes (7.03%, 95% CI: 6.59, 7.46), and beverages (6.99%, 95% CI: 6.66, 7.32) had the highest relative contribution to food GHGE; by 2020, beef was the top contributor (17.68%, 95%CI: 17.46, 17.89) followed by fast food (14.17%, 95% CI: 13.90, 14.43), dairy (11.21%, 95%CI: 11.06, 11.36), beverages (10.09%, 95%CI: 9.94, 10.23), and chicken (10.04%, 95%CI: 9.90, 10.17). Households with higher education levels and those in more urbanized areas contributed more to dietary GHGE across the full period. However, households with lower education levels and those in rural areas had the highest increase in these emissions from 1989 to 2020.ConclusionsOur results provide insights into the food groups in which the 2023 Mexican Dietary Guidelines may require to focus on improving human and planetary health.

Climate Watch Country Greenhouse Gas Emissions Data and Methodology

The availability of open, high-quality, consistent, and comprehensive greenhouse gas (GHG) emissions data is essential to understanding the global trend in GHG emissions, and for countries to see their emission profiles, compare their impacts with those of other countries, identify mitigation opportunities, and reduce emissions.

The potential of agricultural and livestock wastes as a source of biogas in Vietnam: Energetic, economic and environmental evaluation

Many economies, including Vietnam, have substantial potential for producing energy from agricultural waste. However, the analysis of using agricultural waste as a renewable energy source and its associated economic and environmental benefits remain unclear. This study aims to a) estimate trends in greenhouse gas (GHG) emissions from livestock and crop residue burning; b) evaluate the environmental benefits of using biogas in substitution for coal, wood, and liquefied petroleum gas (LPG) under various scenarios; c) assess the economic viability of a household-scale biodigester, and d) propose recommendations for the effective exploitation and utilization of biogas. GHG emissions were calculated for livestock and crop residue burning (CRB) using activity data and emission factors. The environmental analysis was conducted to understand the role of biogas in reducing GHG by assuming 100 % exportation of biogas in substitution for fuels for electricity and heat generation. The economic benefits were assessed through internal rate of return (IRR), net present value (NPV), payback period, levelized cost of electricity (LCOE), and levelized cost of heat (LCOH). Results indicate that, between 2000 and 2050, CO2-eq emissions will rise from 38.5 to 95.2 Mt. Environmental analysis shows that replacing coal or wood with biogas can bring more benefits than LPG, in reducing GHG emissions by 68.2 and 67.9 Mt CO2-eq in 2020 and by 148.4 and 147.9 Mt CO2-eq by 2050. Economic analysis shows that investment in biodigesters is most viable when replacing LPG with biogas, with NPV = $4878, IRR = 57.2 %, PBP (simple) = 1.7 years, and LCOH = $0.029/kWh.

Quantitative impact analysis of cross-border tourism on global food greenhouse gas emissions

Globalization has fueled the rapid expansion of international tourism, significantly impacting global food systems. This study aims to quantitatively evaluate the influence of tourism on global food greenhouse gas (GHG) emissions. By integrating the Food and Agriculture Organization Statistical Database and the World Tourism Organization Tourism Statistics database, we analyze regional differences in dietary choices among cross-border tourists and connect them to detailed national-level food supply inventories, enabling us to estimate the GHG emissions associated with cross-border tourism. Additionally, we employ the modified Regional Integrated model of Climate and the Economy (RICE) model to project future trends in tourism-related GHG emissions across regions and countries. Our findings indicate that tourism has resulted in a reduction of 620 Mt CO2e in global food system emissions between 2001 and 2019. Taking into account tourism development trajectories and regional economic growth, our projection suggests that GHG emissions reduction from the global food system resulting from tourism could reach a substantial 96 Mt CO2e per year by 2100. The analysis shows that strengthening the national economy and increasing the labor force, and taking reasonable measures to change the social diet pattern in different regions can further reduce tourism embodied food GHG emissions. This study highlights the significant role of tourism in mitigating global food system emissions and underscores the potential for further emission reductions in the future.

Environmental sustainability of diets among children and adolescents in the German DONALD cohort study: age and time trends, and nutrient adequacy

BackgroundIdentifying diets beneficial for both human and planetary health has become increasingly important. However, to date, there is limited research on sustainable diets for children and adolescents, a vulnerable population group with specific nutritional needs. ObjectivesWe aimed to identify 1) the main determinants; 2) age and time trends of greenhouse gas emissions (GHGE), land use (LU), and water use (WU) of diets of children and adolescents; and 3) analyze the associations of dietary GHGE, LU, and WU with nutrient adequacy. MethodsA total of 5510 3-d-weighted dietary records (n = 856; 6–17 y; 48% ♀) of the DONALD (DOrtmund Nutritional and Anthropometric Longitudinally Designed) study between 2000 and 2021 were analyzed. Values of GHGE (kgCO2eq), LU (m2 × year), and WU (L) determined by life cycle assessment were assigned to all recorded foods. For nutrient adequacy, the mean adequacy ratio (MAR = ∑(nutrient intake / recommended intake) / number of nutrients) was used. Data were analyzed using polynomial mixed-effects regression models. ResultsThe main contributors to GHGE and LU were meat products (GHGE: 25.6%; LU: 32.8%), dairy products (22.2%; 17.7%), and sweets and pastries (14.0%; 14.3%); to WU, nonalcoholic beverages (24.3%), meat products (18.9%), and vegetables and fruits (17.7%). GHGE, LU, and WU per 1000 kcal increased with age (P < 0.01). GHGE and LU per 1000 kcal increased between 2000 and 2010 and decreased after that in females (P < 0.01) and males (GHGE only: P = 0.02). No significant time trend was found for WU (P > 0.05). A higher MAR was directly associated with GHGE/1000 kcal (MAR: β: 0.011, 95% CI: 0.008, 0.013, P < 0.0001), LU/1000 kcal (MAR: β: 0.009, 95%CI: 0.005, 0.013, P < 0.0001), and WU/1000 kcal (MAR: β: 0.429, 95% CI: 0.325, 0.533, P < 0.0001). ConclusionsOur findings underscore the further need and the capacity for change toward more environmentally sustainable diets. Yet, the tradeoff between environmental sustainability and nutrient adequacy in the diets of children and adolescents requires specific attention to dietary composition.

Balancing agricultural production and environmental sustainability: Based on Economic Analysis From North China Plain

The escalating trend of greenhouse gas emissions presents a dual threat to both food security and the exacerbation of global warming. Addressing this pressing issue demands concerted efforts on local and global scales to champion sustainable food production and foster environmental benefits. In 2015, a pivotal field experiment was conducted in the North China Plain, aiming to delineate the intricate balance between agricultural productivity and environmental stewardship. This study comprised eight meticulously designed treatments, incorporating two key components: the evaluation of economic and environmental parameters encompassing carbon footprint, energy consumption, and the carbon sustainability index. Notably, while the carbon sustainability index exhibited improvement, it also revealed a 9.4% increase in emissions compared to the baseline, underscoring the nuanced trade-offs involved. The findings underscored the efficacy of no-tillage (NT) practices coupled with soybean-based crop rotation, mitigating yield reduction compared to conventional tillage (RT). However, the optimal yield was observed in the RT-MW treatment, amalgamating conventional tillage with minimum tillage practices. Moreover, despite the higher cost associated with soybeans relative to milled wheat, their cultivation yielded a notable increase in net income. These compelling results advocate for the adoption of conservation agriculture as a means to optimize the delicate equilibrium between environmental preservation and economic prosperity. Furthermore, the study underscores the imperative for further research endeavors aimed at devising highly productive agricultural systems that seamlessly integrate environmental sustainability with economic viability, echoing the crucial insights gleaned from analogous contexts.

Spatiotemporal Trends of the Carbon Footprint of Sugar Production in China

Sugar is the main nutrient source of human beings and the basic raw material of the food industry. It is of great practical significance for China to find out the current situation and future trend of Greenhouse Gas (GHG) emissions from sugar production, and explore measures for reducing GHG emissions from sugar planting and processing. The IPCC GHG emissions accounting method is applied to analyze the carbon footprint of sugar production based on planting management and industrial development data, in which the GHG emissions per unit of sugar product are calculated and analyzed. According to Carbon Peak and Carbon Neutrality targets, the total GHG emissions of China's sugar industry in 2030 and 2060 are predicted and discussed. The results show that: (1) The average GHG emissions per unit yield of sugar show a downward trend from 2004 to 2021. The total GHG emissions of sugar production in China have reached 1319.9 × 104 t CO2eq in 2021, which has not yet reached its peak due to the growth of consumption demand. (2) The average GHG emissions per unit of Beet Sugar (1.477 tCO2eq/t) is higher than that of Cane Sugar (0.825 tCO2eq/t). It is more meaningful to enlarge the planting area of sugarcane than that of sugarbeet in the future. (3) Overall, in 2021 the GHG emissions of sugar production reached 0.91 tCO2eq/t in China, which would decline 15 %–87 % until 2030 and 2060. There is great potential for sugar production to reduce GHG emissions in the future.

Spatial and temporal evolution and drivers of GHG emissions from urban domestic wastewater treatment in China: a review at the provincial level.

To mitigate greenhouse gas (GHG) emissions from the wastewater treatment industry, it is crucial to explore GHG emission patterns and propose useful measures. In this study, we use the Kaya model and LMDI decomposition method to analyze the changes in GHG emissions from urban domestic wastewater treatment at the provincial level and further explore the distribution characteristics and driving factors of urban domestic wastewater treatment GHG emissions across various years and regions. The results indicate the following: (1) In the temporal dimension, urban domestic wastewater treatment GHG emissions are increasing, from 21.0 MtCO2 in 2011 to 27.1 MtCO2 in 2020, with an average annual growth rate of 2.88%. The spatial distribution is high in the southeast and low in the northwest. There is variability in the spatial evolution trend of GHG emissions by province, with the growth rate becoming slower or even negative in Jiangsu, Zhejiang, and North China, while the average annual growth rate exceeds 25% in Inner Mongolia and Xinjiang. (2) According to the decomposition results of driving factors, economic scale is the dominant positive driver, and the positive contributions of TI and the population effect are limited. The sludge disposal structure is the main negative driver, and the EEI and technology have restricted negative contributions. (3) Based on the decomposition results, for major coastal GHG emitters, such as Guangdong and Shandong, it is necessary to invest capital and technology to continuously upgrade the wastewater treatment process and reduce non-CO2 emissions. Along with adopting circular economy schemes, local governments in the northwestern region should transform the traditional sludge disposal structure and optimize the power supply structure to increase carbon offset and reduce CO2 emissions. The findings suggest a low-carbon transformation path to support the industry's dual carbon goals.

Greenhouse gas emissions and their trends over the last 3 decades across Africa

Abstract. A key goal of the Paris Agreement (PA) is to reach net-zero greenhouse gas (GHG) emissions by 2050 globally, which requires mitigation efforts from all countries. Africa's rapidly growing population and gross domestic product (GDP) make this continent important for GHG emission trends. In this paper, we study the emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in Africa over 3 decades (1990–2018). We compare bottom-up (BU) approaches, including United Nations Convention Framework on Climate Change (UNFCCC) national inventories, FAO, PRIMAP-hist, process-based ecosystem models for CO2 fluxes in the land use, land use change and forestry (LULUCF) sector and global atmospheric inversions. For inversions, we applied different methods to separate anthropogenic CH4 emissions. The BU inventories show that, over the decade 2010–2018, fewer than 10 countries represented more than 75 % of African fossil CO2 emissions. With a mean of 1373 Mt CO2 yr−1, total African fossil CO2 emissions over 2010–2018 represent only 4 % of global fossil emissions. However, these emissions grew by +34 % from 1990–1999 to 2000–2009 and by +31 % from 2000–2009 to 2010–2018, which represents more than a doubling in 30 years. This growth rate is more than 2 times faster than the global growth rate of fossil CO2 emissions. The anthropogenic emissions of CH4 grew by 5 % from 1990–1999 to 2000–2009 and by 14.8 % from 2000–2009 to 2010–2018. The N2O emissions grew by 19.5 % from 1990–1999 to 2000–2009 and by 20.8 % from 2000–2009 to 2010–2018. When using the mean of the estimates from UNFCCC reports (including the land use sector) with corrections from outliers, Africa was a mean source of greenhouse gases of 262221863239 Mt CO2 eq. yr−1 from all BU estimates (the subscript and superscript indicate min–max range uncertainties) and of +263717615873 Mt CO2 eq. yr−1 from top-down (TD) methods during their overlap period from 2001 to 2017. Although the mean values are consistent, the range of TD estimates is larger than the one of the BU estimates, indicating that sparse atmospheric observations and transport model errors do not allow us to use inversions to reduce the uncertainty in BU estimates. The main source of uncertainty comes from CO2 fluxes in the LULUCF sector, for which the spread across inversions is larger than 50 %, especially in central Africa. Moreover, estimates from national UNFCCC communications differ widely depending on whether the large sinks in a few countries are corrected to more plausible values using more recent national sources following the methodology of Grassi et al. (2022). The medians of CH4 emissions from inversions based on satellite retrievals and surface station networks are consistent with each other within 2 % at the continental scale. The inversion ensemble also provides consistent estimates of anthropogenic CH4 emissions with BU inventories such as PRIMAP-hist. For N2O, inversions systematically show higher emissions than inventories, on average about 4.5 times more than PRIMAP-hist, either because natural N2O sources cannot be separated accurately from anthropogenic ones in inversions or because BU estimates ignore indirect emissions and underestimate emission factors. Future improvements can be expected thanks to a denser network of monitoring atmospheric concentrations. This study helps to introduce methods to enhance the scope of use of various published datasets and allows us to compute budgets thanks to recombinations of those data products. Our results allow us to understand uncertainty and trends in emissions and removals in a region of the world where few observations exist and where most inventories are based on default IPCC guideline values. The results can therefore serve as a support tool for the Global Stocktake (GST) of the Paris Agreement. The referenced datasets related to the figures are available at https://doi.org/10.5281/zenodo.7347077 (Mostefaoui et al., 2022).

Predicting the Risks of Greenhouse Gases at Raising Temperatures in Syria Using Artificial Intelligence Models

The research aimed to study the general trend of the evolution of greenhouse gas emissions in Syria during the period (1993-2022) and to predict the risks of greenhouse gas emissions to rising temperatures during the period (2023-2030). The research adopted the descriptive analytical method in estimating the equations of the general time trend of greenhouse gas emissions and calculating the annual growth rate for each of them during the studied period based on the statistics of the World Bank. The amount of gas emissions during the studied period was multi-layered to suit the nature of the data. The neural network used in prediction consisted of three layers: the input layer, the processing layer, and the output layer. The results of the research showed that there is a general trend of increasing temperatures at a rate of 0.16% annually, which is within the internationally permitted limits according to the Paris Agreement in 2015. The amount emitted of nitrous oxide gas occupied the highest relative importance in terms of the effect on temperature rise 100%, followed by the amount emitted of methane gas 94.1%. In contrast, the percentage of carbon dioxide emissions did not exceed 4.3% in the proposed model. The results of the prediction using the neural network model showed that the average temperatures during the coming period (2023-2030) will reach their maximum value in the year (2024) with an average of (14.87) degrees Celsius, with a relatively increasing annual growth rate of 0.07%.

Greenhouse gas emissions trends and drivers insights from the domestic aviation in Thailand

Domestic aviation is a swiftly expanding contributor to global greenhouse gas (GHG) emissions. Presently, economic volatility and the Coronavirus disease (COVID-19) crisis have resulted in the decline of domestic aviation, but domestic aviation is rapidly recovering in many countries. However, from a GHG emissions viewpoint, the domestic aviation sector is largely unenforced even though the International Civil Aviation Organization's (ICAO) Carbon Offsetting and Reduction Scheme for International Aviation (CORSIA) provision for international aviation is currently in place. Accordingly, the knowledge base on emissions and their drivers from domestic aviation is weak, especially in developing countries, thus hindering an evidence-based policy debate. In this context, we have estimated and analyzed the pre-COVID-19 GHG emissions and their trends from commercial domestic aviation in Thailand; and provided insights on the role of key drivers that influence GHG emissions that are expected to be useful not only for Thailand but also for other developing countries. Emissions are estimated following Intergovernmental Panel on Climate Change (IPCC) Tier-II. Specifically, activity-based landing/take-off (LTO) cycle and cruise. This is compared to the Tier-I method, and key drivers were analyzed using an index decomposition method. The total annual average GHG emissions for all LTO cycles and cruises of commercial domestic aviation for 2015–2020 was 2254 Th. tonnes of CO2-eq. During the LTO cycle of the aircraft, GHG emissions were at an average of 983 Th. tonnes of CO2-eq. Additionally, during the cruise stage, emissions averaged 1270 Th. tonnes of CO2-eq. The choice of accounting methods (i.e., IPCC Tier II vs. Tier I) seems to have had only nominal implications. Our analysis showed that, in the 2008–2020 period, the aviation activity effect and economic growth were the key decisive factors in this sector's GHG emissions growth. It was followed by the fuel energy intensity levels and the population effect in descending order of impact. These findings have significant ramifications for present and future policies aimed at decreasing GHG emissions, aiding Thailand in achieving its climate targets by 2050, and enhancing energy efficiency as the domestic aviation market adapts.

Analyzing long-term dynamics of agricultural greenhouse gas emissions in Austria, 1830–2018

Agriculture is an important contributor to greenhouse gas (GHG) emissions. While the development of agricultural GHG emissions on national and global scales is well studied for the last three to six decades, little is known about their trajectory and drivers over longer periods. In this article, we address this research gap by calculating and analyzing GHG emissions related to agriculture in Austria from 1830 to 2018. We calculate territorial emissions on an annual basis and include all GHG emissions from the processes directly involved in agricultural production. Based on this time series, we quantify the relative importance of major drivers of changes in GHG emissions across time and agricultural product categories, applying a structural decomposition analysis. We find that agricultural GHG emissions in Austria increased by 69 % over the total study period, from 4.6 Mt. CO2e/yr in 1830 to 7.7 Mt. CO2e/yr in 2018. While emissions increased only moderately from 1830 to 1945 (+22 % overall), with strong fluctuations between 1914 and 1945, they doubled from 1945 to 1985. In the most recent period from 1985 to 2018, emissions fell by one third, with decreases leveling off over time. Our decomposition analysis reveals that increases in agricultural production per capita most importantly contributed to the high growth in GHG emissions from 1945 to 1985. Conversely, decreasing emission intensities of products and a more climate friendly product mix were key drivers in the emissions reduction observed after 1985. We also contribute to the discussion around the global warming potential star (GWP*), by calculating GHG emissions based on this alternative metric, and contextualize our data within total socio-economic GHG emission trends. By providing insights into the historical trends and drivers of agricultural GHG emissions, our findings enhance the understanding of their long-term historical dynamics and adds to the knowledge base for future mitigation efforts.

8 Impacts of Future Climate Scenarios on the Beef Industry of the Great Plains and Western Us

Abstract Global average temperatures have increased by 1.1 degrees Celsius compared with pre-Industrial times and future temperature increases will be driven by anthropogenic greenhouse gas emissions trends. Impacts of climate change vary by geographic regions, with the Great Plains and Western US likely to experience increased temperatures, increased frequency of drought, and more extreme precipitation events. These climate impacts can affect the beef industry in those regions in multiple ways from increasing heat stress, decreasing forage availability, impacting forage quality, and reducing water availability for drinking water and feed production. In the southwestern US, increasing temperatures are likely to increase evapotranspiration, reduce snow cover, and lead to earlier snow melts, all of which can contribute to the aridification of the region. For cow-calf production within the region, aridification will reduce the forage biomass available for grazing cattle operations and reduce carrying capacity, creating potential vulnerabilities to rangeland ecosystems and rural communities dependent upon the cattle industry. Increased incidence of heat waves in the Great Plains and Western US can negatively impact vulnerable cattle populations, such as finishing cattle, particularly those housed in environments with minimal heat stress mitigation measures. Decreased water availability can potentially shift cattle production and feed production away from arid regions dependent upon vulnerable water resources, such as the Colorado River and Ogallala aquifer. In general, the increased climate variability and aridification of some parts of the Great Plains and Western US will create risks for the beef industry that will likely necessitate changes, from shifting cattle population to increased use of heat stress mitigation strategies.

Livestock greenhouse gas emission and mitigation potential in China

Livestock is an important source of greenhouse gas emissions (GHGE) in China. Understanding the greenhouse gas (GHG) emission trends and reduction strategies in livestock is crucial for promoting low-carbon transformation of the livestock sector (LS) and achieving the goal of “carbon peak and carbon neutralization”. First, based on the life cycle assessment and IPCC coefficient methods, we calculated the GHGE of the LS in 31 provinces of China from 2000 to 2020 and identified the temporal and spatial evolution of GHG emission intensity. The LMDI method was then used to analyze the influence of efficiency, structure, economy, and population size on GHGE. Finally, the STIRPAT model was used to simulate the future evolution trend of the LS emissions under the SSPs scenario. The results revealed that the GHGE in the life cycle of livestock production decreased from 535.47 Mt carbon dioxide equivalent (CO2e) in 2000 to 532.18 Mt CO2e in 2020, and the main source was CH4 emissions from enteric fermentation of livestock. Economic and efficiency factors markedly influenced the changes in GHGE from the LS in China. Further, economic factors contributed >40% to the increase in GHGE in most provinces. Under the SSP1, SSP2, and SSP4 scenarios, livestock production can achieve the carbon peak target in 2030. Under the baseline scenario (SSP2), the GHGE of China's LS in 2030 and 2060 are expected to be 491.48 Mt CO2e and 352.11 Mt CO2e, respectively. The focus of mitigation measures for livestock production in the future is to optimize the production structure of the LS, promote the low-carbon transformation of the energy structure of livestock feeding, and establish an efficient and intensive management model. In addition, we focus on emission reduction in key areas, such as Northeast and Northwest China, while optimizing diet and reducing food waste from the consumer side.

Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle

Greenhouse gas emission is a key issue in the sustainable development of agriculture. To effectively predict the greenhouse gas emissions of beef cattle, a model is proposed based on system dynamics and greenhouse gas emission calculation methods, and a scenario is set as a ‘Straw to Beef’ project in Jilin Province. The model was built on a baseline emission scenario (feed precision: 60%, breeding environment: dry fattening farm, corn straw utilization: burning straw), with single- and comprehensive emission reduction scenarios considered, predicting trends and reduction potentials in greenhouse gas emissions from cattle breeding and straw burning in Jilin Province from 2013 to 2028, measured in CO2-eq (CO2 equivalent). The model also explored the impact of 11 controllable variables on greenhouse gas emissions. Results showed that (1) From 2013 to 2022, greenhouse gas emissions from straw burning and cattle breeding in Jilin Province increased significantly and had an annual growth rate of 6.51% in 2020. (2) Single emission reduction scenarios showed an increasing trend in greenhouse gas emissions, while comprehensive emission reduction scenarios showed a decreasing trend. Among them, the S2.2.1 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: burning straw) had the strongest emission reduction ability in the single reduction scenario, the S3.2.2 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: Feed-processing straw) had the strongest emission reduction ability in the comprehensive reduction scenario, reducing emissions by 5.10% and 69.24%, respectively, compared to the baseline scenario. This suggests that the comprehensive emission reduction scenarios which utilized straw resources reasonably can greatly reduce agricultural greenhouse gas emissions. (3) The optimal emission reduction scenario indicated that the higher the proportion of digestible energy in beef cattle’s total energy intake, the more perfect the fecal treatment process, and the higher the utilization rate of straw feed, the lower the greenhouse gas emissions. Therefore, to effectively reduce greenhouse gas emissions from cattle breeding and straw burning in Jilin Province, it is important to implement comprehensive emission reduction scenarios prioritizing the efficient utilization of straw resources and improving beef cattle management practices.

Climate Change and Water Scarcity at the Focus of Environmental Impacts Associated with the COVID-19 Crisis in Spain

The conditions of social distancing and home confinement imposed to contain the outbreak of the severe acute respiratory syndrome coronavirus 2 (COVID-19) pandemic have changed the dietary patterns and lifestyle of society. These changes have had significant consequences not only for our personal well-being but also for the health of the planet. In this context, the aim of this study was to describe the effect of household containment during the COVID-19 pandemic on greenhouse gas (GHG) emissions related to food and water consumption. In addition, the dietary pattern of the Spanish population during home confinement was compared with the usual dietary pattern of consumption for the immediately preceding reference year (2019) to elucidate in depth the environmental consequences derived from food consumption due to COVID-19 restrictions. Life Cycle Assessment (LCA) and Water Footprint Assessment (WFA) methodologies were used to assess carbon footprint and water footprint. The functional unit of reference was the average daily food intake per capita. The results showed that COVID-19 home confinement had a negative impact on the carbon footprint (CF) and water footprint (WF) of the Spanish dietary pattern mainly due to the increase in the amount of food consumed during 2020. The monthly analysis revealed two peaks in April and October for both environmental indicators in 2020 compared to the same period in 2019, which was mainly due to the increase in food consumption in Spanish households during the weeks of confinement as well as to the new COVID-19 wave in October. On the other hand, an upward trend in GHG emissions and water consumption could be observed in the last months of both years, which is attributed to increased consumption during the Christmas holidays. These findings indicate that people should be more aware than ever of the importance of maintaining a healthy lifestyle and dietary pattern, in line with health guidelines and the Sustainable Development Goals.

A methodology to formulate technology roadmap and policy package in biofuels

Today, with the rising trend of greenhouse gas emissions, biofuels appear to be a reliable solution to mitigate climate change impacts. There are different types of biofuels and their production requires various technologies. One of the basic questions of decision makers and industry managers is to know the details of technologies related to the production of biofuels. In other words, from the management and policy-making point of view, the technology roadmap is very important, which the policy makers use to formulate the appropriate strategy. This paper presents a methodology to develop biofuels’ technology roadmap and policy formulation. This paper presents technology mapping as well as actor mapping as decisive elements of technology roadmap procedure. It provides useful insights for policy makers and managers to understand which technologies are more suitable for investments in different contexts. Finally, the methodology is applied to the case of Iran, and the key local stakeholders and role-players are recognized. Based on the results of the analysis, practical suggestions for developing biofuels in Iran are offered, which can provide useful insights for other nations.

P02-050-23 Age and Time Trends in Greenhouse Gas Emissions and Land Use of Diets Among Children and Adolescents of the German DONALD Cohort Study

P02-050-23 Age and Time Trends in Greenhouse Gas Emissions and Land Use of Diets Among Children and Adolescents of the German DONALD Cohort Study

Optimizing fertilizer management mitigated net greenhouse gas emissions in a paddy rice-upland wheat rotation system: A ten-year in situ observation of the Yangtze River Delta, China

Optimizing the type and rate of nitrogen (N) fertilizer is an effective approach for achieving food security and minimizing environmental impacts. In this study, a ten-year in situ field experiment was conducted to evaluate the interannual responses of crop yields and greenhouse gas (GHG) emissions to the continuous application of chemical fertilizer (CF) and partial manure application (30 %, CFM) in a paddy rice-upland wheat rotation system. The results indicated that the trends of crop yields and GHG emissions were stable over ten years, and an appropriate N rate (200/150 kg N ha-1 for rice/wheat) in the rice-wheat system had greater potential for maintaining crop yields (9.25/3.32 t ha-1 for rice/wheat) and reducing their net GHG emissions by 20.8–38.7 % in contrast to the high rate (300/225 kg N ha-1 for rice/wheat). Among CF treatments, CH4 emissions had a negative correlation with the N rate, while N2O emissions were positively correlated. The CFM treatments significantly increased CH4 emissions (37.5–112.2 %) compared to the CF treatments during the rice season, but mitigated N2O emissions during both the rice (55.7–58.2 %) and wheat season (32.0–48.2 %). In a comprehensive assessment of the CH4 and N2O emissions in rice-wheat system, 81 % of the net GHG emissions was occurred in the rice season, and there was no significant difference between the CF and CFM at rate of 200/150 kg N ha-1. The study suggests that partial manure application at an optimum rate can effectively mitigate GHG emissions and be beneficial for the sustainability of rice and wheat production in a paddy rice-upland wheat rotation system.

Generalizable Thermal Performance of Ventilated Block Walls and Energy Implication of Substitution for Wood-Frame Walls in Cold-Climate Buildings

Space heating and cooling of buildings is a major contributor to the ascending trend of global energy consumption and greenhouse gas (GHG) emissions. A potential solution to reduce the space heating and cooling is to use buildings’ mass for active thermal energy storage (TES). Having air circulation between an active TES and its associated zones can significantly enhance their thermal coupling; however, reported research studies have not focused on this kind of active TES. To that end, this study aimed to evaluate the thermal performance of a ventilated block wall (VBW) in reducing space heating and cooling loads in cold-climate buildings. In this system, air is circulated between a zone and the voided cores of a VBW, where the air exchanges heat with the wall before returning to the zone. To have a generalizable assessment of the system’s performance, typical-day and annual energy analyses were conducted under various boundary conditions and air circulation speeds. The study found that for a typical day with significant temperature fluctuation, a VBW with a 2 m/s air circulation speed throughout the day can lead to 67% more net energy exchange (the sum of thermal energy storage and release) when compared to having no air circulation. The annual analysis compared the energy performance between a VBW and a traditional wood-frame wall in three different cold climates. The results showed that substituting a wood-frame wall with a VBW can reduce space heating and cooling loads by 35.1 kWh/m2 (wall surface area) for a mixed dry–cold climate throughout the year. Having cement plaster as interior finishing can lead to 9% more net energy exchange than having drywall, on average, for all zone air temperature profiles.