A long-term historical emission inventory of air and
climate pollutants in East, Southeast, and South Asia during 1950–2015 was developed as the Regional Emission inventory in ASia version 3 ...(REASv3).
REASv3 provides details of emissions from major anthropogenic sources for
each country and its sub-regions and also provides monthly gridded data with
0.25∘ × 0.25∘ resolution. The average total
emissions in Asia during 1950–1955 and during 2010–2015 (growth rates in these 60 years estimated from the two averages) are as follows: SO2: 3.2 Tg,
42.4 Tg (13.1); NOx: 1.6 Tg, 47.3 Tg (29.1); CO: 56.1 Tg, 303 Tg (5.4);
non-methane volatile organic compounds: 7.0 Tg, 57.8 Tg (8.3); NH3: 8.0 Tg, 31.3 Tg (3.9); CO2: 1.1 Pg, 18.6 Pg (16.5) (CO2 excluding
biofuel combustion 0.3 Pg, 16.8 Pg (48.6)); PM10: 5.9 Tg, 30.2 Tg
(5.1); PM2.5: 4.6 Tg, 21.3 Tg (4.6); black carbon: 0.69 Tg, 3.2 Tg
(4.7); and organic carbon: 2.5 Tg, 6.6 Tg (2.7). Clearly, all the air
pollutant emissions in Asia increased significantly during these 6 decades, but situations were different among countries and regions. Due to
China's rapid economic growth in recent years, its relative contribution to
emissions in Asia has been the largest. However, most pollutant species
reached their peaks by 2015, and the growth rates of other species were found to be reduced or almost zero. On the other hand, air pollutant emissions
from India showed an almost continuous increasing trend. As a result, the
relative ratio of emissions of India to that of Asia has increased recently. The trend observed in Japan was different from the rest of Asia.
In Japan, emissions increased rapidly during the 1950s–1970s, which
reflected the economic situation of the period; however, most emissions
decreased from their peak values, which were approximately 40 years ago, due
to the introduction of control measures for air pollution. Similar features
were found in the Republic of Korea and Taiwan. In the case of other Asian countries, air pollutant emissions generally showed an increase along with
economic growth and motorization. Trends and spatial distribution of air
pollutants in Asia are becoming complicated. Data sets of REASv3, including table of emissions by countries and sub-regions for major sectors and fuel
types, and monthly gridded data with 0.25∘ × 0.25∘ resolution for major source categories are available through
the following URL: https://www.nies.go.jp/REAS/index.html (last access: 31 October 2020).
To understand the atmospheric behavior of radioactive materials emitted from the Fukushima Daiichi nuclear power plant after the nuclear accident that accompanied the great Tohoku earthquake and ...tsunami on 11 March 2011, we simulated the transport and deposition of iodine‐131 and cesium‐137 using a chemical transport model. The model roughly reproduced the observed temporal and spatial variations of deposition rates over 15 Japanese prefectures (60−400 km from the plant), including Tokyo, although there were some discrepancies between the simulated and observed rates. These discrepancies were likely due to uncertainties in the simulation of emission, transport, and deposition processes in the model. A budget analysis indicated that approximately 13% of iodine‐131 and 22% of cesium‐137 were deposited over land in Japan, and the rest was deposited over the ocean or transported out of the model domain (700 × 700 km2). Radioactivity budgets are sensitive to temporal emission patterns. Accurate estimation of emissions to the air is important for estimation of the atmospheric behavior of radionuclides and their subsequent behavior in land water, soil, vegetation, and the ocean.
Key Points
We simulated the deposition of I‐131 and Cs‐137 from Fukushima in March 2011
The model reproduced observed deposition rates over 15 Japanese prefectures
About 13% of I‐131 and 22% of Cs‐137 were deposited over land in Japan
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
A better understanding of land cover/land use changes (LCLUC) and their interactions with the atmospheric environment is essential for the sustainable management of natural resources, environmental ...protection, air quality, agricultural planning and food security. The 15 papers published in this focus issue showcase a variety of studies relating to drivers and impacts of LCLUC and air pollution in different South/Southeast Asian (S/SEA) countries. This synthesis article, in addition to giving context to the articles in this focus issue, also reviews the broad linkages between population, LCLUC and air pollution. Additionally, we identify knowledge gaps and research priorities that are essential in addressing air pollution issues in the region. We conclude that for effective pollution mitigation in S/SEA countries, quantifying drivers, sources and impacts of pollution need a thorough data analysis through ground-based instrumentation, models and integrated research approaches. We also stress the need for the development of sustainable technologies and strengthening the scientific and resource management communities through capacity building and training activities to address air pollution issues in S/SEA countries.
Understanding the impacts of land use cover changes (LUCC) on the environment is one of the most important scientific challenges in global change research. LUCC is one of the critical drivers of ...environmental change in South/Southeast Asia. Several studies suggest that LUCC in these countries is driven by population growth and economic development. In the region, LUCC is manifested in a variety of phenomena such as urban expansion, agricultural land loss, land abandonment, deforestation, logging, reforestation, etc. Documenting the LUCC and associated impacts gain significance as the results can aid improved land management. This editorial provides a summary and discussion of the nine different articles of the Focus issue, focusing on ground-based measurements, remote sensing, and modeling to quantify LUCC impacts. The results will be useful to academics, practitioners, government, and policymakers to quantify and address sustainable LUCC issues in South/Southeast Asian countries. The published papers add significant new science to the existing literature.
The MIX inventory is developed for the years 2008 and 2010 to support the Model Inter-Comparison Study for Asia (MICS-Asia) and the Task Force on Hemispheric Transport of Air Pollution (TF HTAP) by a ...mosaic of up-to-date regional emission inventories. Emissions are estimated for all major anthropogenic sources in 29 countries and regions in Asia. We conducted detailed comparisons of different regional emission inventories and incorporated the best available ones for each region into the mosaic inventory at a uniform spatial and temporal resolution. Emissions are aggregated to five anthropogenic sectors: power, industry, residential, transportation, and agriculture. We estimate the total Asian emissions of 10 species in 2010 as follows: 51.3 Tg SO2, 52.1 Tg NOx, 336.6 Tg CO, 67.0 Tg NMVOC (non-methane volatile organic compounds), 28.8 Tg NH3, 31.7 Tg PM10, 22.7 Tg PM2.5, 3.5 Tg BC, 8.3 Tg OC, and 17.3 Pg CO2. Emissions from China and India dominate the emissions of Asia for most of the species. We also estimated Asian emissions in 2006 using the same methodology of MIX. The relative change rates of Asian emissions for the period of 2006–2010 are estimated as follows: −8.1 % for SO2, +19.2 % for NOx, +3.9 % for CO, +15.5 % for NMVOC, +1.7 % for NH3, −3.4 % for PM10, −1.6 % for PM2.5, +5.5 % for BC, +1.8 % for OC, and +19.9 % for CO2. Model-ready speciated NMVOC emissions for SAPRC-99 and CB05 mechanisms were developed following a profile-assignment approach. Monthly gridded emissions at a spatial resolution of 0.25° × 0.25° are developed and can be accessed from http://www.meicmodel.org/dataset-mix.
Purpose
Health damage from ambient fine particulate matter (PM
2.5
) shows large regional variations and can have an impact on a global scale due to its transboundary movement. However, existing ...damage factors (DFs) for human health in life cycle assessments (LCA) are calculated only for a few limited regions based on various regional chemical transport models (CTMs). The aim of this research is to estimate the human health DFs of PM
2.5
originating from ten different regions of the world by using one global CTM.
Methods
The DFs express changes in worldwide disability-adjusted life years (DALYs) due to unit emission of black carbon and organic carbon (BCOC), nitrogen oxides (NO
x
), and sulfur dioxide (SO
2
). DFs for ten regions were calculated as follows. Firstly, we divided the whole world into ten regions. With a global CTM (MIROC-ESM-CHEM), we estimated the concentration change of PM
2.5
on the world caused by changes in the emission of a targeted precursor substance from a specific region. Secondly, we used population data and epidemiological concentration response functions (CRFs) of mortality and morbidity to estimate changes in the word’s DALYs occurring due to changes in the concentration of PM
2.5
. Finally, the above calculations were done for all ten regions.
Results and discussion
DFs of BCOC, NO
x
, and SO
2
for ten regions were estimated. The range of DFs could be up to one order of magnitude among the ten regions in each of the target substances. While population density was an important parameter, variation in transport of PM
2.5
on a continental level occurring due to different emission regions was found to have a significant influence on DFs. Especially for regions of Europe, Russia, and the Middle East, the amount of damage which occurred outside of the emitted region was estimated at a quarter, a quarter, and a third of their DFs, respectively. It was disclosed that the DFs will be underestimated if the transboundary of PM
2.5
is not taken into account in those regions.
Conclusions
The human health damage factors of PM
2.5
produced by BCOC, NO
x
, and SO
2
are estimated for ten regions by using one global chemical transport model. It became clear that the variation of transport for PM
2.5
on a continental level greatly influences the regionality in DFs. For further research to quantify regional differences, it is important to consider the regional values of concentration response function (CRF) and DALY loss per case of disease or death.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OBVAL, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Chemical transport models played key roles in understanding the atmospheric behaviors and deposition patterns of radioactive materials emitted from the Fukushima Daiichi nuclear power plant after the ...nuclear accident that accompanied the great Tohoku earthquake and tsunami on 11 March 2011. However, model results could not be sufficiently evaluated because of limited observational data. We assess the model performance to simulate the deposition patterns of radiocesium (137Cs) by making use of airborne monitoring survey data for the first time. We conducted ten sensitivity simulations to evaluate the atmospheric model uncertainties associated with key model settings including emission data and wet deposition modules. We found that simulation using emissions estimated with a regional-scale (∼500 km) model better reproduced the observed 137Cs deposition pattern in eastern Japan than simulation using emissions estimated with local-scale (∼50 km) or global-scale models. In addition, simulation using a process-based wet deposition module reproduced the observations well, whereas simulation using scavenging coefficients showed large uncertainties associated with empirical parameters. The best-available simulation reproduced the observed 137Cs deposition rates in high-deposition areas (≥10 kBq m–2) within 1 order of magnitude and showed that deposition of radiocesium over land occurred predominantly during 15–16, 20–23, and 30–31 March 2011.
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IJS, KILJ, NUK, PNG, UL, UM
No observed data have been found in the Fukushima Prefecture (FP) for the time-series of atmospheric radionuclides concentrations just after the Fukushima Daiichi Nuclear Power Plant (FD1NPP) ...accident. Accordingly, current estimates of internal radiation doses from inhalation, and atmospheric radionuclide concentrations by atmospheric transport models are highly uncertain. Here, we present a new method for retrieving the hourly atmospheric (137)Cs concentrations by measuring the radioactivity of suspended particulate matter (SPM) collected on filter tapes in SPM monitors which were operated even after the accident. This new dataset focused on the period of March 12-23, 2011 just after the accident, when massive radioactive materials were released from the FD1NPP to the atmosphere. Overall, 40 sites of the more than 400 sites in the air quality monitoring stations in eastern Japan were studied. For the first time, we show the spatio-temporal variation of atmospheric (137)Cs concentrations in the FP and the Tokyo Metropolitan Area (TMA) located more than 170 km southwest of the FD1NPP. The comprehensive dataset revealed how the polluted air masses were transported to the FP and TMA, and can be used to re-evaluate internal exposure, time-series radionuclides release rates, and atmospheric transport models.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
To assess the contribution of biomass burning to the emissions of atmospheric trace species in China, we estimated various biomass-burning activities using statistical data, survey data, expert ...estimates and a satellite data set. Fuel wood and crop residue burned as fuel and in the field are the major sources of biomass burning in China, accounting for nearly 90% of the total biomass burning on dry weight base. Field burning of crop residue estimated from satellite burned area is less than 1% of that estimated from ground survey data; because of this and because biofuel is burned indoor, the majority of biomass burning in China is not seeable from satellite. Statistical data showed that the occurrence of forest fire in China has decreased dramatically since the 1980s; however, the forest fire area detected by satellites in 2000 was 13 times that shown by statistics. Grassland fires are a minor source of biomass burning in China. We estimated carbon monoxide (CO) emission from open biomass burning (field burning of crop residue and forest and grassland fires) to be 16.5
Tg in 2000, with a 90% uncertainty range of 3.4–34
Tg. Uncertainties in CO emission factors, especially for field burning of crop residue, contributed much more to the variance than those in the activity data. This suggests the importance of narrowing the uncertainty range of emission factors.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Several different inventories of global and regional anthropogenic and biomass burning emissions are assessed for the 1980–2010 period. The species considered in this study are carbon monoxide, ...nitrogen oxides, sulfur dioxide and black carbon. The inventories considered include the ACCMIP historical emissions developed in support of the simulations for the IPCC AR5 assessment. Emissions for 2005 and 2010 from the Representative Concentration Pathways (RCPs) are also included. Large discrepancies between the global and regional emissions are identified, which shows that there is still no consensus on the best estimates for surface emissions of atmospheric compounds. At the global scale, anthropogenic emissions of CO, NO
x
and SO
2
show the best agreement for most years, although agreement does not necessarily mean that uncertainty is low. The agreement is low for BC emissions, particularly in the period prior to 2000. The best consensus is for NO
x
emissions for all periods and all regions, except for China, where emissions in 1980 and 1990 need to be better defined. Emissions of CO need better quantification in the USA and India for all periods; in Central Europe, the evolution of emissions during the past two decades needs to be better determined. The agreement between the different SO
2
emissions datasets is rather good for the USA, but better quantification is needed elsewhere, particularly for Central Europe, India and China. The comparisons performed in this study show that the use of RCP8.5 for the extension of the ACCMIP inventory beyond 2000 is reasonable, until more global or regional estimates become available. Concerning biomass burning emissions, most inventories agree within 50–80%, depending on the year and season. The large differences between biomass burning inventories are due to differences in the estimates of burned areas from the different available products, as well as in the amount of biomass burned.
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CEKLJ, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
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