Southeast Asian anthropogenic emission changes: An analysis from regional and global emission inventories

2020 ◽  
Author(s):  
Yun fat Lam ◽  
Shimul Roy ◽  
Ka Wing Chui
Keyword(s):  
Rural Areas ◽  
Industrial Sector ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Road Transportation ◽  
Global Emission ◽  
Transportation Sector ◽  
Emission Changes ◽  
Asean Countries ◽  
Average Contribution

<p>In ASEAN (Southeast Asia) countries, anthropogenic emissions have increased significantly over the last two decades from a variety of sources, including power and heating, industries, road-transportation, residential, and agricultural activities. In this study, we analyzed different emission inventories (i.e., MICS-Asia, REAS, EDGAR) to provide the integrated emissions for ASEAN during the period 2000-2010. The study found that anthropogenic emission contribution from ASEAN countries to the total Asian emission was notable during that period. For instance, from the MIX-Asian EI, our analysis shows that the average contribution was the highest from the transportation sector (34%), followed by residential (29%), power (24%), and industrial sector (14%), respectively in 2010. However, similar to the sector-specific emission contribution in 2000 in ASEAN countries, residential sector was the most significant contributor for CO (53%), PM10 (48%), PM2.5 (63%), BC (76%), OC (79%) in 2010, although it is in decreasing trend compared to other sectors. On the contrary, emission contribution of SO2 was the highest from the industrial sector (47%), followed by power (36%), while NOx and NMVOC were contributed mainly by transportation sector (55% and 45%, respectively). Spatially, the emission intensities of SO2, CO, NOx, NMVOC, PM10, PM2.5, BC, OC, and CO2 were high in the major urban cities of Thailand, Vietnam, Malaysia, Philippines, and Indonesia except CH4, N2O, and NH3, which were high in the rural areas of ASEAN countries.</p>

scholarly journals A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): An application of the Community Emissions Data System (CEDS)

2020 ◽  
Author(s):  
Erin E. McDuffie ◽  
Steven J. Smith ◽  
Patrick O'Rourke ◽  
Kushal Tibrewal ◽  
Chandra Venkataraman ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Data System ◽  
Atmospheric Pollutants ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Fuel Type ◽  
Road Transportation ◽  
Activity Data ◽  
Global Emission ◽  
Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the fate and transport of atmospheric pollution, as well as the resulting impacts on the environment, human health, and society. Rapid changes in today’s society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel-type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx, CO, SO2, NH3, NMVOCs, BC, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture, energy generation, industrial processes, transportation (on-road and non-road), residential, commercial, and other sectors (RCO), waste, solvent use, and international-shipping) and four fuel categories (total coal, solid biofuel, and the sum of liquid fuels and natural gas combustion, plus remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes global gridded (0.5°×0.5°) emission fluxes with monthly time resolution for each compound, sector, and fuel-type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default calibration procedure, and modifications to the final procedures for emissions gridding and aggregation to retain sector and fuel-specific information. Relative to the previous CEDS data released for CMIP6 (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to-date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel-types across multiple source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors, as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), as well as emissions from waste. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture serving as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories, including uncertainties in the underlying activity data and sector- and region-specific emission factors. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS. The CEDSGBD-MAPS emission inventory dataset (both annual country-total and global gridded files) is publicly available and registered under: https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020).

scholarly journals A global anthropogenic emission inventory of atmospheric pollutants from sector- and fuel-specific sources (1970–2017): an application of the Community Emissions Data System (CEDS)

2020 ◽  
Vol 12 (4) ◽  
pp. 3413-3442
Author(s):  
Erin E. McDuffie ◽  
Steven J. Smith ◽  
Patrick O'Rourke ◽  
Kushal Tibrewal ◽  
Chandra Venkataraman ◽  
...  
Keyword(s):  
Emission Inventory ◽  
Data System ◽  
Atmospheric Pollutants ◽  
Emission Inventories ◽  
Anthropogenic Emission ◽  
Fuel Type ◽  
Road Transportation ◽  
International Shipping ◽  
Global Emission ◽  
Global Emissions

Abstract. Global anthropogenic emission inventories remain vital for understanding the sources of atmospheric pollution and the associated impacts on the environment, human health, and society. Rapid changes in today's society require that these inventories provide contemporary estimates of multiple atmospheric pollutants with both source sector and fuel type information to understand and effectively mitigate future impacts. To fill this need, we have updated the open-source Community Emissions Data System (CEDS) (Hoesly et al., 2019) to develop a new global emission inventory, CEDSGBD-MAPS. This inventory includes emissions of seven key atmospheric pollutants (NOx; CO; SO2; NH3; non-methane volatile organic compounds, NMVOCs; black carbon, BC; organic carbon, OC) over the time period from 1970–2017 and reports annual country-total emissions as a function of 11 anthropogenic sectors (agriculture; energy generation; industrial processes; on-road and non-road transportation; separate residential, commercial, and other sectors (RCO); waste; solvent use; and international shipping) and four fuel categories (total coal, solid biofuel, the sum of liquid-fuel and natural-gas combustion, and remaining process-level emissions). The CEDSGBD-MAPS inventory additionally includes monthly global gridded (0.5∘ × 0.5∘) emission fluxes for each compound, sector, and fuel type to facilitate their use in earth system models. CEDSGBD-MAPS utilizes updated activity data, updates to the core CEDS default scaling procedure, and modifications to the final procedures for emissions gridding and aggregation. Relative to the previous CEDS inventory (Hoesly et al., 2018), these updates extend the emission estimates from 2014 to 2017 and improve the overall agreement between CEDS and two widely used global bottom-up emission inventories. The CEDSGBD-MAPS inventory provides the most contemporary global emission estimates to date for these key atmospheric pollutants and is the first to provide global estimates for these species as a function of multiple fuel types and source sectors. Dominant sources of global NOx and SO2 emissions in 2017 include the combustion of oil, gas, and coal in the energy and industry sectors as well as on-road transportation and international shipping for NOx. Dominant sources of global CO emissions in 2017 include on-road transportation and residential biofuel combustion. Dominant global sources of carbonaceous aerosol in 2017 include residential biofuel combustion, on-road transportation (BC only), and emissions from the waste sector. Global emissions of NOx, SO2, CO, BC, and OC all peak in 2012 or earlier, with more recent emission reductions driven by large changes in emissions from China, North America, and Europe. In contrast, global emissions of NH3 and NMVOCs continuously increase between 1970 and 2017, with agriculture as a major source of global NH3 emissions and solvent use, energy, residential, and the on-road transport sectors as major sources of global NMVOCs. Due to similar development methods and underlying datasets, the CEDSGBD-MAPS emissions are expected to have consistent sources of uncertainty as other bottom-up inventories. The CEDSGBD-MAPS source code is publicly available online through GitHub: https://github.com/emcduffie/CEDS/tree/CEDS_GBD-MAPS (last access: 1 December 2020). The CEDSGBD-MAPS emission inventory dataset (both annual country-total and monthly global gridded files) is publicly available under https://doi.org/10.5281/zenodo.3754964 (McDuffie et al., 2020c).

scholarly journals Impact of spatial proxies on the representation of bottom-up emission inventories: A satellite-based analysis

2017 ◽  
Vol 17 (6) ◽  
pp. 4131-4145 ◽  
Author(s):  
Guannan Geng ◽  
Qiang Zhang ◽  
Randall V. Martin ◽  
Jintai Lin ◽  
Hong Huo ◽  
...  
Keyword(s):  
Population Density ◽  
Rural Areas ◽  
Urban Areas ◽  
Model Performance ◽  
Road Transport ◽  
Industrial Sector ◽  
Transport Sector ◽  
Emission Inventories ◽  
Bottom Up ◽  
The Impact

Abstract. Spatial proxies used in bottom-up emission inventories to derive the spatial distributions of emissions are usually empirical and involve additional levels of uncertainty. Although uncertainties in current emission inventories have been discussed extensively, uncertainties resulting from improper spatial proxies have rarely been evaluated. In this work, we investigate the impact of spatial proxies on the representation of gridded emissions by comparing six gridded NOx emission datasets over China developed from the same magnitude of emissions and different spatial proxies. GEOS-Chem-modeled tropospheric NO2 vertical columns simulated from different gridded emission inventories are compared with satellite-based columns. The results show that differences between modeled and satellite-based NO2 vertical columns are sensitive to the spatial proxies used in the gridded emission inventories. The total population density is less suitable for allocating NOx emissions than nighttime light data because population density tends to allocate more emissions to rural areas. Determining the exact locations of large emission sources could significantly strengthen the correlation between modeled and observed NO2 vertical columns. Using vehicle population and an updated road network for the on-road transport sector could substantially enhance urban emissions and improve the model performance. When further applying industrial gross domestic product (IGDP) values for the industrial sector, modeled NO2 vertical columns could better capture pollution hotspots in urban areas and exhibit the best performance of the six cases compared to satellite-based NO2 vertical columns (slope  =  1.01 and R2 = 0. 85). This analysis provides a framework for information from satellite observations to inform bottom-up inventory development. In the future, more effort should be devoted to the representation of spatial proxies to improve spatial patterns in bottom-up emission inventories.

scholarly journals Molecular hydrogen (H2) combustion emissions and their isotope (D/H) signatures from domestic heaters, diesel vehicle engines, waste incinerator plants, and biomass burning

2012 ◽  
Vol 12 (3) ◽  
pp. 6839-6875
Author(s):  
M. K. Vollmer ◽  
S. Walter ◽  
J. Mohn ◽  
M. Steinbacher ◽  
S. W. Bond ◽  
...  
Keyword(s):  
Biomass Burning ◽  
Molecular Hydrogen ◽  
Fossil Fuel ◽  
Ambient Air ◽  
Waste Incinerator ◽  
Emission Inventories ◽  
Road Transportation ◽  
Global Emission ◽  
Combustion Emissions ◽  
Combustion Processes

Abstract. Molecular hydrogen (H2), its stable isotope signature (δD), and the key combustion parameters carbon monoxide (CO), carbon dioxide (CO2), and methane (CH4) were measured from various combustion processes. H2 in the exhaust of gas and oil-fired heaters and of waste incinerator plants was generally depleted compared to ambient intake air, while CO was significantly elevated. These findings contradict the often assumed co-occurring net H2 and CO emissions in combustion processes and suggest that previous H2 emissions from combustion may have been overestimated when scaled to CO emissions. For the heater exhausts, H2 and δD generally decrease with increasing fuel-to-air ratio, from ambient values of ∼0.5 ppm and +130‰ to 0.2 ppm and −206‰, respectively. These results are interpreted as a combination of an isotopically light H2 source from fossil fuel combustion and a D/H kinetic isotope fractionation of hydrogen in the advected ambient air during its partial removal during combustion. Diesel exhaust measurements from dynamometer test stand driving cycles show elevated H2 and CO emissions during cold-start and some acceleration phases. Their molar H2/CO ratios are <0.25, significantly smaller than those for gasoline combustion. Using H2/CO emission ratios, along with CO global emission inventories, we estimate global H2 emissions for 2000, 2005, and 2010. For road transportation (gasoline and diesel), we calculate 8.6 ± 2.1 Tg, 6.3 ± 1.5 Tg, and 4.1 ± 1.0 Tg, respectively, whereas the contribution from diesel vehicles has increased from 5% to 8% over this time. Other fossil fuel emissions are believed to be negligible but H2 emissions from coal combustion are unknown. For residential (domestic) emissions, which are likely dominated by biofuel combustion, emissions for the same years are estimated at 2.7 ± 0.7 Tg, 2.8 ± 0.7 Tg, and 3.0 ± 0.8 Tg, respectively. Our wood combustion measurements are combined with results from the literature to calculate biomass burning emissions. For these estimates, we propose a molar H2/CH4 ratio of 3.3, when using CH4 emission inventories. When using this approach, our resulting global biomass burning H2 emissions agree well with published results, suggesting that CH4 emissions may be a good proxy for H2 emissions.

scholarly journals Multiannual changes of CO<sub>2</sub> emissions in China: indirect estimates derived from satellite measurements of tropospheric NO<sub>2</sub> columns

2013 ◽  
Vol 13 (18) ◽  
pp. 9415-9438 ◽  
Author(s):  
E. V. Berezin ◽  
I. B. Konovalov ◽  
P. Ciais ◽  
A. Richter ◽  
S. Tao ◽  
...  
Keyword(s):  
Time Series ◽  
Co2 Emission ◽  
Emission Inventory ◽  
Emission Inventories ◽  
Satellite Measurements ◽  
Top Down ◽  
Global Emission ◽  
Tropospheric No2 ◽  
Emission Changes ◽  
Emission Ratios

Abstract. Multiannual satellite measurements of tropospheric NO2 columns are used for evaluation of CO2 emission changes in China in the period from 1996 to 2008. Indirect top-down annual estimates of CO2 emissions are derived from the satellite NO2 column measurements by means of a simple inverse modeling procedure involving simulations performed with the CHIMERE mesoscale chemistry–transport model and the CO2-to-NOx emission ratios from the Emission Database for Global Atmospheric Research (EDGAR) global anthropogenic emission inventory and Regional Emission Inventory in Asia (REAS). Exponential trends in the normalized time series of annual emissions are evaluated separately for the periods from 1996 to 2001 and from 2001 to 2008. The results indicate that the both periods manifest strong positive trends in the CO2 emissions, and that the trend in the second period was significantly larger than the trend in the first period. Specifically, the trends in the first and second periods are best estimated to be in the range from 3.7 to 8.3 and from 11.0 to 13.2% per year, respectively, taking into account statistical uncertainties and differences between the CO2-to-NOx emission ratios from the EDGAR and REAS inventories. Comparison of our indirect top-down estimates of the CO2 emission changes with the corresponding bottom-up estimates provided by the EDGAR (version 4.2) and Global Carbon Project (GCP) glomal emission inventories reveals that while acceleration of the CO2 emission growth in the considered period is a common feature of both kinds of estimates, nonlinearity in the CO2 emission changes may be strongly exaggerated in the global emission inventories. Specifically, the atmospheric NO2 observations do not confirm the existence of a sharp bend in the emission inventory data time series in the period from 2000 to 2002. A significant quantitative difference is revealed between the bottom-up and indirect top-down estimates of the CO2 emission trend in the period from 1996 to 2001 (specifically, the trend was not positive according to the global emission inventories, but is strongly positive in our estimates). These results confirm the findings of earlier studies that indicated probable large uncertainties in the energy production and other activity data for China from international energy statistics used as the input information in the global emission inventories. For the period from 2001 to 2008, some quantitative differences between the different kinds of estimates are found to be in the range of possible systematic uncertainties associated with our estimation method. In general, satellite measurements of tropospheric NO2 are shown to be a useful source of information on CO2 sources collocated with sources of nitrogen oxides; the corresponding potential of these measurements should be exploited further in future studies.

A review on powertrain subsystems and charging technology in battery electric vehicles: Current and future trends

2021 ◽  
pp. 095440702110259
Author(s):  
Kunal Wagh ◽  
Pankaj Dhatrak
Keyword(s):  
Electric Vehicles ◽  
Combustion Engine ◽  
Future Research ◽  
Future Trends ◽  
Road Transportation ◽  
Market Prices ◽  
Local Pollution ◽  
Battery Electric Vehicles ◽  
Global Emission ◽  
Battery Technology

The transport industry is a major contributor to both local pollution and greenhouse gas emissions (GHGs). The key challenge today is to mitigate the adverse impacts on the environment caused by road transportation. The volatile market prices and diminishing supplies of fuel have led to an unprecedented interest in battery electric vehicles (BEVs). In addition, improvements in motor efficiencies and significant advances in battery technology have made it easier for BEVs to compete with internal combustion engine (ICE) vehicles. This paper describes and assesses the latest technologies in different elements of the BEV: powertrain architectures, propulsion and regeneration systems, energy storage systems and charging techniques. The current and future trends of these technologies have been reviewed in detail. Finally, the key issue of electric vehicle component recycling (battery, motor and power electronics) has been discussed. Global emission regulations are pushing the industry towards zero or ultra-low emission vehicles. Thus, by 2025, most cars must have a considerable level of powertrain electrification. As the market share of electric vehicles increases, clear trends have emerged in the development of powertrain systems. However, some significant barriers must be overcome before appreciable market penetration can be achieved. The objective of the current study is to review and provide a complete picture of the current BEV technology and a framework to assist future research in the sector.

Scientific approach using AHP to prioritize low volume rural roads for pavement maintenance

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Akhilesh Nautiyal ◽  
Sunil Sharma
Keyword(s):  
Rural Areas ◽  
Socioeconomic Development ◽  
Public Works ◽  
Relative Importance ◽  
Road Transportation ◽  
Rural Roads ◽  
Content Type ◽  
Pavement Maintenance ◽  
Low Volume ◽  
The Government

PurposeA large number of roads have been constructed in the rural areas of India to connect habitations with the nearest major roads. With time, the pavements of these roads have deteriorated and they need some kind of maintenance, although they all do not need maintenance at the same time, as they have all not deteriorated to the same level. Hence, they have to be prioritized for maintenance.Design/methodology/approachIn order to present a scientific methodology for prioritizing pavement maintenance, the factors affecting prioritization and the relative importance of each were identified through an expert survey. Analytic Hierarchy Process (AHP) was used to scientifically establish weight (importance) of each factor based on its relative importance over other factors. The proposed methodology was validated through a case study of 203 low volume rural roads in the state of Himachal Pradesh in India. Ranking of these roads in order of their priority for maintenance was presented as the final result.FindingsThe results show that pavement distresses, traffic volume, type of connectivity and the socioeconomic facilities located along a road are the four major factors to be considered in determining the priority of a road for maintenance.Research limitations/implicationsThe methodology provides a comprehensive, scientific and socially responsible pavement maintenance prioritization method which will automatically select roads for maintenance without any bias.Practical implicationsTimely maintenance of roads will also save budgetary expenditure of restoration/reconstruction, leading to enhancement of road service life. The government will not only save money but also provide timely benefit to the needy population.Social implicationsRoad transportation is the primary mode of inland transportation in rural areas. Timely maintenance of the pavements will be of great help to the socioeconomic development of rural areas.Originality/valueThe proposed methodology lays special emphasis on rural roads which are small in length, but large in number. Instead of random, a scientific method for selection of roads for maintenance will be of great help to the public works department for better management of rural road network.

scholarly journals A Study on the Trend of the Gasoline Consumption in Road Transportation Sector by Improvement of Income Level

2005 ◽  
Vol 35 (2) ◽  
pp. 355-368
Author(s):  
Mariko WADA ◽  
Yoshitaka AOYAMA ◽  
Dai NAKAGAWA ◽  
Yuka KARATANI
Keyword(s):  
Income Level ◽  
Road Transportation ◽  
Gasoline Consumption ◽  
Transportation Sector
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