Fine particulate matter, or PM2.5, is a serious air pollutant and has significant effects on human health, including premature death. Based on a long-term series of satellite-retrieved PM2.5 ...concentrations, this study analyzed the spatial and temporal characteristics of PM2.5 in South and Southeast Asia (SSEA) from 1999 to 2014 using standard deviation ellipse and trend analyses. A health risk assessment of human exposure to PM2.5 between 1999 and 2014 was then undertaken. The results show that PM2.5 concentrations increased in most areas of SSEA from 1999 to 2014 and exceeded the World Health Organization average annual limit of primary PM2.5 standards. Bangladesh, Pakistan and India experienced average PM2.5 values higher than the total average for SSEA. From 1999 to 2014, the entirety of SSEA exhibited an increased rate of 0.02μg/m3/year on average. Bangladesh and Myanmar witnessed greater incremental rates of PM2.5 than India. Correspondingly, the center of the average regional PM2.5 concentration gradually shifted to the southeast during the study period. The proportion of areas with PM2.5 concentrations exceeding 35μg/m3 increased consistently, and the areas with PM2.5 concentrations below 15μg/m3 decreased continuously. The proportion of the population exposed to high PM2.5 (above 35μg/m3) increased annually. The extent of high-health-risk areas in SSEA expanded in size and extent between 1999 and 2014, particularly in North India, Bangladesh and East Pakistan. Therefore, all of SSEA should receive special attention, and strict controls on PM2.5 concentrations in SSEA countries are urgently required.
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•PM2.5 increased in most areas of South-Southeast Asia from 1999 to 2014.•Bangladesh and Pakistan had higher PM2.5 than other countries in South-Southeast Asia.•South-Southeast Asia had an increased rate of 0.02μg/m3/year from 1999 to 2014.•The population proportion exposed to high PM2.5 (>35μg/m3) increased notably.•Areas with high health risk expanded in size and extent between 1999 and 2014.
Fine particulate matter (PM2.5) poses a potential threat to human health, including premature mortality under long-term exposure. Based on a long-term series of high-resolution (0.01°×0.01°) ...satellite-retrieved PM2.5 concentrations, this study estimated the premature mortality attributable to PM2.5 in South and Southeast Asia (SSEA) from 1999 to 2014. Then, the long-term trends and spatial characteristics of PM2.5-induced premature deaths (1999–2014) were analyzed using trend analyses and standard deviation ellipses. Results showed the estimated number of PM2.5-induced average annual premature deaths in SSEA was 1,447,000. The numbers increased from 1,179,400 in 1999 to 1,724,900 in 2014, with a growth rate of 38% and net increase of 545,500. Stroke and ischemic heart disease were the two principal contributors, accounting for 39% and 35% of the total, respectively. High values were concentrated in North India, Bangladesh, East Pakistan, and some metropolitan areas of Southeast Asia. An estimated 991,600 deaths in India was quantified (i.e., ~69% of the total premature deaths in SSEA). The long-term trends (1999–2014) of PM2.5-related premature mortality exhibited consistent incremental tendencies in all countries except Sri Lanka. The findings of this study suggest that strict controls of PM2.5 concentrations in SSEA are urgently required.
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•Multi-year premature death due to PM2.5 in South-Southeast Asia reached 1,447,000.•Premature deaths attributed to PM2.5 have grown 38% from 1999 to 2014.•Stroke and ischemic heart disease were the two principal PM2.5-related diseases.•India and Bangladesh were the major contributors of deaths in South-Southeast Asia.•South Asia estimated more premature deaths than Southeast Asia during 1999–2014.
This study compared five widely used globally gridded biomass burning emissions inventories for the 2002–2011 period (Global Fire Emissions Database 3 (GFED3), Global Fire Emissions Database 4 ...(GFED4), Global Fire Assimilation System 1.0 (GFAS1.0), Fire INventory from NCAR 1.0 (FINN1.0) and Global Inventory for Chemistry-Climate studies-GFED4 (G-G)). Average annual CO2 emissions range from 6521.3 to 9661.5 Tg year−1 for five inventories, with extensive amounts in Africa, South America and Southeast Asia. Coefficient of Variation for Southern America, Northern and Southern Africa are 30%, 39% and 48%. Globally, the majority of CO2 emissions are released from savanna burnings, followed by forest and cropland burnings. The largest differences among the five inventories are mainly attributable to the overestimation of CO2 emissions by FINN1.0 in Southeast Asia savanna and cropland burning, and underestimation in Southern Africa savanna and Amazon forest burning. The overestimation in Africa by G-G also contributes to the differences.
•Five widely used global biomass burning emissions inventories were compared.•Global CO2 emissions compared well while regional differences are large.•The largest differences were found in Southeast Asia and Southern Africa.•Savanna burning emission was the largest contributor to the global emissions.•Variations in savanna burning emission led to the differences among inventories.
Differences of the five biomass burning CO2 emissions inventories were found in Southeast Asia and Southern Africa due to the variations in savanna burning emissions estimation.
The thermal infrared imager TIR onboard Hayabusa2 has been developed to investigate thermo-physical properties of C-type, near-Earth asteroid 162173 Ryugu. TIR is one of the remote science ...instruments on Hayabusa2 designed to understand the nature of a volatile-rich solar system small body, but it also has significant mission objectives to provide information on surface physical properties and conditions for sampling site selection as well as the assessment of safe landing operations. TIR is based on a two-dimensional uncooled micro-bolometer array inherited from the Longwave Infrared Camera LIR on Akatsuki (Fukuhara et al.,
2011
). TIR takes images of thermal infrared emission in 8 to 12 μm with a field of view of
16
×
12
∘
and a spatial resolution of
0.05
∘
per pixel. TIR covers the temperature range from 150 to 460 K, including the well calibrated range from 230 to 420 K. Temperature accuracy is within 2 K or better for summed images, and the relative accuracy or noise equivalent temperature difference (NETD) at each of pixels is 0.4 K or lower for the well-calibrated temperature range. TIR takes a couple of images with shutter open and closed, the corresponding dark frame, and provides a true thermal image by dark frame subtraction. Data processing involves summation of multiple images, image processing including the StarPixel compression (Hihara et al.,
2014
), and transfer to the data recorder in the spacecraft digital electronics (DE). We report the scientific and mission objectives of TIR, the requirements and constraints for the instrument specifications, the designed instrumentation and the pre-flight and in-flight performances of TIR, as well as its observation plan during the Hayabusa2 mission.
The monitoring of thermal anomalies such as from wildfires, coal fires, and volcanoes has been a major application of satellite remote sensing. The Landsat 8 Operational Land Imager (OLI) has ...achieved sufficient enhanced radiometric performance to quantify visible and near infrared (VNIR) to shortwave infrared (SWIR) radiance emitted from thermal anomalies during nighttime. We propose a method to simultaneously retrieve the brightness temperature and corresponding area of a subpixel hotspot assuming a single isothermal heat source using the spectral radiances in VNIR and SWIR regions (bands 3–7) from nighttime Landsat 8 OLI data. We conducted a prescribed fire experiment coincident with a Landsat 8 overpass on January 24, 2015. The brightness temperature retrieved from the OLI data agreed with the peak temperature of the time series thermocouple record within 60K. The retrieved area of fire was 19% of the true fire area. The blackbody assumption (emissivity=1) might cause the underestimated retrieved area. We applied the hotspot brightness temperature and area retrieval to 17 Landsat 8 scenes that cover Kanto, Japan to validate the proposed method. More than 79% of the detected results were confirmed as true positives based on the land use for each scene. Meanwhile, the obvious false positive was only up to 1% of the detected results. The remaining ambiguous results, mostly found in areas regarding agriculture, were possibly caused by occasional burnings because these locations were never repetitively detected. Time series comparison of the retrieved results in cement plants as a typical stable heat source revealed that the brightness temperature is accurately retrieved, though the retrieval of area is somewhat sensitive to noise on OLI imagery. The proposed method had founded more than twice of the hotspots detected using Visible Infrared Imaging Radiometer Suite (VIIRS) fire products in the studied area. More than 82% among the hotspots from VIIRS were detected by OLI. However our method failed to detect spatially broad but slightly cool hotspots. Higher spatial resolution at an appropriate spectral configuration enabled enhanced sensitivity to detect small heat sources, as well as quantification of the subpixel hotspots.
•We developed a hotspot detection method using nighttime Landsat 8 OLI data.•We proposed a retrieved method of the brightness temperature and area of hotspots.•The retrieved temperature agreed with ground truth at a prescribed fire within 200K.•Temperature and area are accurately retrieved over homogeneous heat sources.
Quantification of spatial and temporal variations in premature mortality attributable to PM2.5 has important implications for air quality control in South and Southeast Asia (SSEA). The number of ...PM2.5-induced premature deaths during 1999–2014 in SSEA was estimated using an integrated exposure-response model based on 0.01° × 0.01° satellite-retrieved PM2.5 data, population density, and spatially and temporally variable baseline mortality data. The results showed extremely high premature death rates in North India and Bangladesh. PM2.5-induced premature deaths in SSEA increased with small interannual variations from 1999 to 2014 owing to the interannual variations in PM2.5 concentrations. Moreover, four scenarios on the effects of premature deaths by PM2.5 mitigation efforts based on World Health Organization (WHO) air quality guidelines (AQG) and interim targets (ITs) were investigated for each disease and each country during 1999–2014. Four scenarios based on WHO AQG (10 μg/m3), IT-3 (15 μg/m3), IT-2 (25 μg/m3), and IT-1 (35 μg/m3) resulted in 69.3%, 49.1%, 25.4%, and 12.8% reductions compared to the total reference premature deaths (1256,300), which was calculated using the original PM2.5 datasets. Overall, stroke was the most serious disease associated with air pollution, causing 40% of total premature deaths. Ischemic heart disease was the largest contributor (58%) to the deaths in relatively cleaner air (Scenario 1). The annual rate of change in premature deaths in South Asian countries (India, Bangladesh, and Pakistan) was higher than that in Southeast Asian countries under all scenarios. The results for different scenarios provide insight into the largest health benefits of PM2.5 reduction efforts.
•PM2.5-induced premature deaths in South and Southeast Asia (SSEA) were estimated.•Total premature deaths increased during 1999–2014 with minor interannual variations.•Mitigation scenarios explored the effects of PM2.5 reductions on premature deaths.•India contributed most to total premature deaths in SSEA.•Stroke was the most likely disease to cause premature deaths in polluted air.
TIR, the thermal infrared imager on Hayabusa2, acquired high-resolution thermal images of the asteroid 162173 Ryugu for one asteroid rotation period on August 1, 2018 to investigate the ...thermophysical properties of the asteroid. The surface temperatures of Ryugu suggest that the surface has a low thermal inertia, indicating the presence of porous materials. Thermophysical models that neglect or oversimplify surface roughness cannot reproduce the flat diurnal temperature profiles observed during daytime. We performed numerical simulations of a thermophysical model, including the effects of roughness on the diurnal brightness temperature, the predictions of which successfully reproduced the observed diurnal variation of temperature. The global thermal inertia was obtained with a standard deviation of 225 ± 45 J m−2 s−0.5 K−1, which is relatively low but still within the range of the value estimated in our previous study (Okada et al., Nature 579, 518–522, 2020), confirming that the boulders on Ryugu are more porous in nature than typical carbonaceous chondrites. The global surface roughness (the ratio of the variance of the height relative to a local horizontal surface length) was determined as 0.41 ± 0.08, corresponding to a RMS surface slope of 47 ± 5°. We identified a slightly lower roughness distributed along the equatorial ridge, implying a mass movement of boulders from the equatorial ridge to the mid-latitudes.
•Thermophysical model using a shape model of rough surface reproduces observations.•We obtain a global thermal inertia of 225 ± 45 J m−2 s−0.5 K−1.•We obtain a global RMS surface slope of 47 ± 5°.•We confirm Ryugu's low global thermal inertia owing to porous constituent boulders.
Abstract Considering the significant role of global methane emissions in the Earth’s radiative budget, global or regionally persistent increasing trends in its emission are of great concern. ...Understanding the regional contributions of various emissions sectors to the growth rate thus has policy relevance. We used a high-resolution global methane inverse model to independently optimize sectoral emissions using GOSAT and ground-based observations for 2009–2020. Annual emission trends were calculated for top-emitting countries, and the sectoral contributions to the total anthropogenic trend were studied. Global total posterior emissions show a growth rate of 2.6 Tg yr −2 ( p < 0.05), with significant contributions from waste (1.1 Tg yr −2 ) and agriculture (0.9 Tg yr −2 ). Country-level aggregated sectoral emissions showed statistically significant ( p < 0.1) trends in total posterior emissions for China (0.56 Tg yr −2 ), India (0.22 Tg yr −2 ), United States (0.65 Tg yr −2 ), Pakistan (0.22 Tg yr −2 ) and Indonesia (0.28 Tg yr −2 ) among the top methane emitters. Emission sectors contributing to the above country-level emission trend are, China (waste 0.35; oil and gas 0.07 Tg yr −2 ), India (agriculture 0.09; waste 0.11 Tg yr −2 ), United States (oil and gas 1.0; agriculture 0.07; coal −0.15 Tg yr −2 ), Brazil (waste 0.09; agriculture 0.08 Tg yr −2 ), Russia (waste 0.04; biomass burning 0.15; coal 0.11; oil and gas −0.42 Tg yr −2 ), Indonesia (coal 0.28 Tg yr −2 ), Canada (oil and gas 0.08 Tg yr −2 ), Pakistan (agriculture 0.15; waste 0.03 Tg yr −2 ) and Mexico (waste 0.04 Tg yr −2 ). Additionally, our analysis showed that methane emissions from wetlands in Russia (0.24 Tg yr −2 ) and central African countries such as Congo (0.09 Tg yr −2 ), etc. have a positive trend with a considerably large increase after 2017, whereas Bolivia (−0.09 Tg yr −2 ) have a declining trend. Our results reveal some key emission sectors to be targeted on a national level for designing methane emission mitigation efforts.
Top-down approaches, such as atmospheric inversions, are a promising tool for evaluating emission estimates based on activity-data. In particular, there is a need to examine carbon budgets at ...subnational scales (e.g. state/province), since this is where the climate mitigation policies occur. In this study, the subnational scale anthropogenic CO2 emissions are estimated using a high-resolution global CO2 inverse model. The approach is distinctive with the use of continuous atmospheric measurements from regional/urban networks along with background monitoring data for the period 2015–2019 in global inversion. The measurements from several urban areas of the U.S., Europe and Japan, together with recent high-resolution emission inventories and data-driven flux datasets were utilized to estimate the fossil emissions across the urban areas of the world. By jointly optimizing fossil fuel and natural fluxes, the model is able to contribute additional information to the evaluation of province–scale emissions, provided that sufficient regional network observations are available. The fossil CO2 emission estimates over the U.S. states such as Indiana, Massachusetts, Connecticut, New York, Virginia and Maryland were found to have a reasonable agreement with the Environmental Protection Agency (EPA) inventory, and the model corrects the emissions substantially towards the EPA estimates for California and Indiana. The emission estimates over the United Kingdom, France and Germany are comparable with the regional inventory TNO–CAMS. We evaluated model estimates using independent aircraft observations, while comparison with the CarbonTracker model fluxes confirms ability to represent the biospheric fluxes. This study highlights the potential of the newly developed inverse modeling system to utilize the atmospheric data collected from the regional networks and other observation platforms for further enhancing the ability to perform top-down carbon budget assessment at subnational scales and support the monitoring and mitigation of greenhouse gas emissions.
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