Evaluating policies to reduce greenhouse gas emissions from private transportation

This paper proposes a model system to forecast household-level greenhouse gas emissions (GHGEs) from private transportation and evaluate the effects of car-related taxation schemes on vehicle emissions. The system contains four submodels that specifically capture households' vehicle and vintage, quantity, usage, and GHGE rates (GHGERs) by vehicle type. The vehicle GHGERs are calculated with the Motor Vehicle Emission Simulator 2014, which is authorized by the Environmental Protection Agency. The whole model system was applied to the Washington, D.C., metropolitan area. The 2009 National Household Travel Survey was employed with supplementary data from Consumer Reports, American Fact Finder, and 2009 state motor vehicle registrations. The study proposed two tax schemes, vehicle purchase tax and fuel tax, and predicted their effects on reductions in vehicle GHGEs. The average annual GHGE per vehicle was 5.86 tons of carbon dioxide–equivalent gas without the proposed taxes. After two taxation policies were implemented, the results showed the following: (a) the impacts on reducing GHGEs from fuel taxes were higher than those from purchase taxes, (b) purchase taxes reduced GHGEs mainly by decreasing the number of cars of households with more vehicles, and (c) fuel taxes successfully reduced GHGEs by decreasing the use of cars by households with fewer vehicles. The model system can be extended to other zones, counties, states, and nations.

Spatiotemporal Trends of the Carbon Footprint of Sugar Production in China

Greenhouse gas (GHG) emissions are an important factor in the evaluation of green industrial growth, when low GHG emissions along with high industrial growth are expected. In this paper, the improvement of sustainable development of industry in China (2007–2015) was investigated via analysis of the relationships between the GHG emissions and energy consumption in comparison to European countries. A hierarchical cluster analysis (HCA) was conducted to distinguish industrial growth with GHG emission and energy consumption structures. The results of this research indicated that green industrial growth in Europe had a negative annual rate of GHG emissions. This contributed to the ratio of renewable energy consumption increasing to a maximum of 33% and an average of 16%. In comparison, the GHG emissions in China increased at a rate of 50% to 77% in the main industrial provinces since 2007 with their rapid industrial growth. The rate of GHG emissions decreased after 2012, which was 7% or less than the rate of emissions in the industrial provinces. Contrary to in Europe, the decreasing rate of GHG emissions in China was attributed to the improvement of fossil energy efficiency, as renewable energy consumption was less than 10% in most industrial provinces. Our data analysis identified that the two different energy consumption strategies improved green industrial growth in Europe and China, respectively. Our data analysis identified the two different energy consumption strategies employed by Europe and China, each of which promoted green industrial growth in the corresponding areas. We concluded that China achieved green industrial growth through an increase in energy efficiency through technology updates to decrease GHG emissions, which we call the “China Model.” The “Europe Model” proved to be quite different, having the core characteristic of increasing renewable energy use.

Mitigating Curtailment and Carbon Emissions through Load Migration between Data Centers

Abstract. To track progress towards keeping global warming well below 2 ∘C or even 1.5 ∘C, as agreed in the Paris Agreement, comprehensive up-to-date and reliable information on anthropogenic emissions and removals of greenhouse gas (GHG) emissions is required. Here we compile a new synthetic dataset on anthropogenic GHG emissions for 1970–2018 with a fast-track extension to 2019. Our dataset is global in coverage and includes CO2 emissions, CH4 emissions, N2O emissions, as well as those from fluorinated gases (F-gases: HFCs, PFCs, SF6, NF3) and provides country and sector details. We build this dataset from the version 6 release of the Emissions Database for Global Atmospheric Research (EDGAR v6) and three bookkeeping models for CO2 emissions from land use, land-use change, and forestry (LULUCF). We assess the uncertainties of global greenhouse gases at the 90 % confidence interval (5th–95th percentile range) by combining statistical analysis and comparisons of global emissions inventories and top-down atmospheric measurements with an expert judgement informed by the relevant scientific literature. We identify important data gaps for F-gas emissions. The agreement between our bottom-up inventory estimates and top-down atmospheric-based emissions estimates is relatively close for some F-gas species (∼ 10 % or less), but estimates can differ by an order of magnitude or more for others. Our aggregated F-gas estimate is about 10 % lower than top-down estimates in recent years. However, emissions from excluded F-gas species such as chlorofluorocarbons (CFCs) or hydrochlorofluorocarbons (HCFCs) are cumulatively larger than the sum of the reported species. Using global warming potential values with a 100-year time horizon from the Sixth Assessment Report by the Intergovernmental Panel on Climate Change (IPCC), global GHG emissions in 2018 amounted to 58 ± 6.1 GtCO2 eq. consisting of CO2 from fossil fuel combustion and industry (FFI) 38 ± 3.0 GtCO2, CO2-LULUCF 5.7 ± 4.0 GtCO2, CH4 10 ± 3.1 GtCO2 eq., N2O 2.6 ± 1.6 GtCO2 eq., and F-gases 1.3 ± 0.40 GtCO2 eq. Initial estimates suggest further growth of 1.3 GtCO2 eq. in GHG emissions to reach 59 ± 6.6 GtCO2 eq. by 2019. Our analysis of global trends in anthropogenic GHG emissions over the past 5 decades (1970–2018) highlights a pattern of varied but sustained emissions growth. There is high confidence that global anthropogenic GHG emissions have increased every decade, and emissions growth has been persistent across the different (groups of) gases. There is also high confidence that global anthropogenic GHG emissions levels were higher in 2009–2018 than in any previous decade and that GHG emissions levels grew throughout the most recent decade. While the average annual GHG emissions growth rate slowed between 2009 and 2018 (1.2 % yr−1) compared to 2000–2009 (2.4 % yr−1), the absolute increase in average annual GHG emissions by decade was never larger than between 2000–2009 and 2009–2018. Our analysis further reveals that there are no global sectors that show sustained reductions in GHG emissions. There are a number of countries that have reduced GHG emissions over the past decade, but these reductions are comparatively modest and outgrown by much larger emissions growth in some developing countries such as China, India, and Indonesia. There is a need to further develop independent, robust, and timely emissions estimates across all gases. As such, tracking progress in climate policy requires substantial investments in independent GHG emissions accounting and monitoring as well as in national and international statistical infrastructures. The data associated with this article (Minx et al., 2021) can be found at https://doi.org/10.5281/zenodo.5566761.

Increasing greenhouse gas (GHG) emissions is worsening the climate change and its impacts all over the world. Currently there are number of techniques to estimate the GHG emissions and their concentration in the atmosphere. This study estimates the GHG (carbon dioxide, methane and nitrous oxide) footprint based on the one-year average fossil fuel consumption in selected Private Sector Universities of Karachi. The annual average GHG emissions from all of the universities were calculated to be 2,183.84 Tons of carbon dioxide (CO2), 41.3544 kg of methane (CH4) and 7.2612 kg of nitrous oxide (N2O). The CO2 emission from individual universities were in the range of 800 to 5,000 tons per year. Similarly, the CH4 was emitted in the range of 15-90 kg per year. N2O emission from all the selected universities was found very low in the range 2-16 kg per annum. The study found that the overall rate of GHG emissions is rapidly increasing with an increase in fuel consumption resulted from high number of enrollments in selected universities. Study recommends the energy saving measures and the transition from fossil energy to renewable energy.

The contribution of artificial reservoirs to greenhouse gas (GHG) emissions has been emphasized in previous studies. In the present study, we collected and updated data on GHG emission rates from reservoirs at the global scale, and applied a new classification method based on the hydrobelt concept. Our results showed that CH4 and CO2 emissions were significantly different in the hydrobelt groups (p < 0.01), while no significant difference was found for N2O emissions, possibly due to their limited measurements. We found that annual GHG emissions (calculated as C or N) from global reservoirs amounted to 12.9 Tg CH4-C, 50.8 Tg CO2-C, and 0.04 Tg N2O-N. Furthermore, GHG emissions (calculated as CO2 equivalents) were also estimated for the 1950–2017 period based on the cumulative number and surface area of global reservoirs in the different hydrobelts. The highest increase rate in both the number of reservoirs and their surface area, which occurred from 1950 to the 1980s, led to an increase in GHG emissions from reservoirs. Since then, the increase rate of reservoir construction, and hence GHG emissions, has slowed down. Moreover, we also examined the potential impact of reservoir eutrophication on GHG emissions and found that GHG emissions from reservoirs could increase by 40% under conditions in which total phosphorus would double. In addition, we showed that the characteristics of reservoirs (e.g., geographical location) and their catchments (e.g., surrounding terrestrial net primary production, and precipitation) may influence GHG emissions. Overall, a major finding of our study was to provide an estimate of the impact of large reservoirs during the 1950–2017 period, in terms of GHG emissions. This should help anticipate future GHG emissions from reservoirs considering all reservoirs being planned worldwide. Besides using the classification per hydrobelt and thus reconnecting reservoirs to their watersheds, our study further emphasized the efforts to be made regarding the measurement of GHG emissions in some hydrobelts and in considering the growing number of reservoirs.

ObjectivesTo assess greenhouse gas (GHG) emissions from a regional hospital laundry unit, and model ways in which these can be reduced.DesignA cradle to grave process-based attributional life-cycle assessment.SettingA large hospital...

BackgroundPolicies to mitigate climate change by reducing greenhouse gas (GHG) emissions can yield public health benefits by also reducing emissions of hazardous co-pollutants, such as air toxics and particulate matter. Socioeconomically disadvantaged communities are typically disproportionately exposed to air pollutants, and therefore climate policy could also potentially reduce these environmental inequities. We sought to explore potential social disparities in GHG and co-pollutant emissions under an existing carbon trading program—the dominant approach to GHG regulation in the US and globally.Methods and findingsWe examined the relationship between multiple measures of neighborhood disadvantage and the location of GHG and co-pollutant emissions from facilities regulated under California’s cap-and-trade program—the world’s fourth largest operational carbon trading program. We examined temporal patterns in annual average emissions of GHGs, particulate matter (PM2.5), nitrogen oxides, sulfur oxides, volatile organic compounds, and air toxics before (January 1, 2011–December 31, 2012) and after (January 1, 2013–December 31, 2015) the initiation of carbon trading. We found that facilities regulated under California’s cap-and-trade program are disproportionately located in economically disadvantaged neighborhoods with higher proportions of residents of color, and that the quantities of co-pollutant emissions from these facilities were correlated with GHG emissions through time. Moreover, the majority (52%) of regulated facilities reported higher annual average local (in-state) GHG emissions since the initiation of trading. Neighborhoods that experienced increases in annual average GHG and co-pollutant emissions from regulated facilities nearby after trading began had higher proportions of people of color and poor, less educated, and linguistically isolated residents, compared to neighborhoods that experienced decreases in GHGs. These study results reflect preliminary emissions and social equity patterns of the first 3 years of California’s cap-and-trade program for which data are available. Due to data limitations, this analysis did not assess the emissions and equity implications of GHG reductions from transportation-related emission sources. Future emission patterns may shift, due to changes in industrial production decisions and policy initiatives that further incentivize local GHG and co-pollutant reductions in disadvantaged communities.ConclusionsTo our knowledge, this is the first study to examine social disparities in GHG and co-pollutant emissions under an existing carbon trading program. Our results indicate that, thus far, California’s cap-and-trade program has not yielded improvements in environmental equity with respect to health-damaging co-pollutant emissions. This could change, however, as the cap on GHG emissions is gradually lowered in the future. The incorporation of additional policy and regulatory elements that incentivize more local emission reductions in disadvantaged communities could enhance the local air quality and environmental equity benefits of California’s climate change mitigation efforts.

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.

Bioturbation frequency alters methane emissions from reservoir sediments

Emissions of greenhouse gases (GHGs) from animal feeding operations to the atmosphere are of environmental importance and concerns because of their impact on global warming. Gaseous concentrations and emission rates (ERs) of animal facilities can be affected by the animal production stages, animal species, dietary nutrition, housing types, manure handling schemes, and environmental conditions. This article reports ERs of methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2) for a typical, naturally ventilated 24-crate swine farrowing barn located in suburban Beijing, China, that was monitored over one-year period. The measurements were made at bi-monthly intervals (i.e., six measurement episodes total), with each measurement episode covering three consecutive days. Gaseous concentrations were monitored at bi-hourly intervals throughout each 3-day measurement episode. The ventilation rate of the barn was estimated using the CO2 mass balance method. The GHG concentrations and ERs of the farrowing barn showed diurnal and seasonal variations. Specifically, the concentrations (monthly mean ±SD, mg m-3) ranged from 2.3 (±0.3) to 9.3 (±2) for CH4, from 0.6 (±0.02) to 1.2 (±0.16) for N2O, and from 1,370 (±163) to 11,100 (±950) for CO2, with the higher levels occurring in January and the lower levels in July. The specific ER ranged from 95.2 to 261.8 mg h-1 pig-1 for CH4, from 6.4 to 12.9 mg h-1 pig-1 for N2O, and from 122.9 to 127.3 g h-1 pig-1 for CO2. On the basis of per animal unit (1 AU = 500 kg live body mass), the average daily ERs of the farrowing barn were 9.6 ±3.6 g AU-1 d-1 for CH4, 0.54 ±0.15 g AU-1 d-1 for N2O, and 7.5±0.1 kg AU-1 d-1 for CO2. Results of the GHG ERs from this study differ markedly from the limited literature data collected primarily under European production systems and conditions. Results of the current study provide some baseline data on GHG ERs for swine farrowing operations, thus contributing to development or improvement of GHG emission inventory under the Chinese livestock production conditions.

In this study, we sought to identify influent carbon-to-nitrogen (C/N) ratios that yield relatively high nutrient removal efficiency with relatively low greenhouse gas (GHG) emissions. The earthworm eco-filter (EE) system, which is composed of earthworms and plants (EP group), was found to be optimal for maximizing nutrient removal while reducing GHG emissions. In this EE system, the optimal influent C/N ratio for nutrient removal and GHG emission under C2N treatment conditions. Nutrient removal efficiency under this condition was 85.19 ± 6.40% chemical oxygen demand, 71.99 ± 11.28% total nitrogen, and 77.91 ± 8.51% total phosphorus, while the CO2 emission rate was 678.89 ± 201.87 mg m(-2) h(-1). Moreover, the highest nutrient removal and GHG emission rates were both achieved in late summer (August). Thus, carbon variation, season, system variation, as well as synergistic interaction between system variations and seasons, significantly affect nutrient removal efficiencies and GHG emissions.

The objective of this study was to determine the energy use and greenhouse gas emissions associated with sesame production. Energy use efficiency indicators and greenhouse gas emission rates were calculated for the 2022-2023 production season. The energy input and output for sesame production were found to be 12079.15 MJ ha-1 and 30052.44 MJ ha-1, respectively. The study found an energy use efficiency of 2.49, with a specific energy of 12.20 MJ kg-1, an energy productivity of 0.08 kg MJ-1, and a net energy value of 17973.29 MJ ha-1. The direct and indirect energy inputs were calculated to be 4584.41 MJ ha-1 (37.95%) and 7494.74 MJ ha-1 (62.05%), while the renewable and non-renewable energy inputs were calculated to be 469.12 MJ ha-1 (3.88%) and 11610.03 MJ ha-1 (98.65%), respectively. The calculation shows that the total greenhouse gas emissions are 380.52 kgCO2-eq ha-1 and the greenhouse gas emission rate is 0.38 kgCO2-eq ha-1. Sesame production is highly profitable for the 2022-2023 production season in terms of energy use efficiency.

The Best Graduate Medical Education Articles From 2021-in Our (Humble) Opinions.