Eliminating the interference of water for direct sensing of submerged plastics using hyperspectral near-infrared imager.

Interference from water in the reflectance spectra of plastics is a major obstacle to optical sensing of plastics in aquatic environments. Here we present evidence of the feasibility of sensing plastics in water using hyperspectral near-infrared to shortwave-infrared imaging techniques. We captured hyperspectral images of nine polymers submerged to four depths (2.5-15 mm) in water using a hyperspectral imaging system that utilizes near-infrared to shortwave-infrared light sources. We also developed algorithms to predict the reflectance spectra of each polymer in water using the spectra of the dry plastics and water as independent variables in a multiple linear regression model after a logarithmic transformation. A narrow 1100-1300 nm wavelength range was advantageous for detection of polyethylene, polystyrene, and polyvinyl chloride in water down to the 160-320 µm size range, while a wider 970-1670 nm wavelength range was beneficial for polypropylene reflectance spectrum prediction in water. Furthermore, we found that the spectra of the other five polymers, comprising polycarbonate, acrylonitrile butadiene styrene, phenol formaldehyde, polyacetal, and polymethyl methacrylate, could also be predicted within their respective optimized wavelength ranges. Our findings provide fundamental information for direct sensing of plastics in water on both benchtop and airborne platforms.

Characteristics of atmospheric black carbon and other aerosol particles over the Arctic Ocean in early autumn 2016: Influence from biomass burning as assessed with observed microphysical properties and model simulations.

We conducted ship-based measurements of marine aerosol particles (number concentration, size distribution, black carbon (BC), autofluorescence property, and PM2.5 composition) and trace gases (ozone (O3) and carbon monoxide (CO)) during a cruise of the R/V Mirai (23 August to 4 October 2016) over the Arctic Ocean, Northwest Pacific Ocean, and Bering Sea. Over the Arctic Ocean at latitudes >70°N, the averaged BC mass concentration was 0.7 ± 1.8 ng/m3, confirming the validity of our previously-reported observations (~1 ng/m3) over the same region during September 2014 and September 2015. The observed levels over the Arctic Ocean need to be used as a benchmark when testing the atmospheric transport models over the ocean, while they are substantially lower than those reported at Barrow (Utqiagvik), a nearby ground-based station. We identified events with elevated BC mass concentrations and CO mixing ratios over the Arctic Ocean and Bering Sea as influenced by biomass burnings, with evidences from elevated levoglucosan levels, mixing states of BC particles, and particle size distributions. With WRF-Chem model simulations, we confirmed Siberian Forest fire plumes traveled over thousands of kilometers and produced substantially high BC and CO levels over the Bering Sea. The ΔBC/ΔCO ratios during these periods were estimated as ~1 ng/m3/ppbv, which are lower than those values reported, indicating that the results might have been affected by the wet removal process during transportation and/or by emission in smoldering conditions.

Prokaryotic Community Succession in Bulk and Rhizosphere Soils Along a High-Elevation Glacier Retreat Chronosequence on the Tibetan Plateau.

Early colonization and succession of soil microbial communities are essential for soil development and nutrient accumulation. Herein we focused on the changes in pioneer prokaryotic communities in rhizosphere and bulk soils along the high-elevation glacier retreat chronosequence, the northern Himalayas, Tibetan Plateau. Rhizosphere soils showed substantially higher levels of total organic carbon, total nitrogen, ammonium, and nitrate than bulk soils. The dominant prokaryotes were Proteobacteria, Actinobacteria, Acidobacteria, Chloroflexi, Crenarchaeota, Bacteroidetes, and Planctomycetes, which totally accounted for more than 75% in relative abundance. The dominant genus Candidatus Nitrososphaera occurred at each stage of the microbial succession. The richness and evenness of soil prokaryotes displayed mild succession along chronosequene. Linear discriminant analysis effect size (LEfSe) analysis demonstrated that Proteobacteria (especially Alphaproteobacteria) and Actinobacteria were significantly enriched in rhizosphere soils compared with bulk soils. Actinobacteria, SHA_109, and Thermoleophilia; Betaproteobacteria and OP1.MSBL6; and Planctomycetia and Verrucomicrobia were separately enriched at each of the three sample sites. The compositions of prokaryotic communities were substantially changed with bulk and rhizosphere soils and sampling sites, indicating that the communities were dominantly driven by plants and habitat-specific effects in the deglaciated soils. Additionally, the distance to the glacier terminus also played a significant role in driving the change of prokaryotic communities in both bulk and rhizosphere soils. Soil C/N ratio exhibited a greater effect on prokaryotic communities in bulk soils than rhizosphere soils. These results indicate that plants, habitat, and glacier retreat chronosequence collectively control prokaryotic community composition and succession.

Optimization of a hyperspectral imaging system for rapid detection of microplastics down to 100 µm.

Plastic pollution has become one of the most emergent issues threating aquatic and terrestrial ecosystems. However, it is still challenging to rapidly detect small microplastics. Here, we present a method to rapidly detect microplastics using hyperspectral imaging in which we optimized a commercially available hyperspectral imaging system (Pika NIR-640, Resonon Inc., USA). The optimizations included: (1) changing the four-lamp assembly to a symmetrical set of converged-light near-infrared lamps that are placed sideways instead of above the sample stage; (2) adopting a macro-photography technique by applying an extension tube between the camera and the lens, and moving the lens of the hyperspectral camera to the imaging target (working distance of ~3 cm); (3) adjusting the exposure and aspect ratio by tuning the frame rate and scan speed of the imaging system. After optimization, the detection resolution of each pixel improved from 250 µm to 14.8 µm. With the optimized system, microplastics down to 100 µm in size were rapidly detected. This result is promising for the application of our new method in the accelerated detection of microplastics and will contribute to a better understanding of the microplastic pollution situation.

Light-absorption properties of brown carbon aerosols in the Asian outflow: Implications of a combination of filter and ground remote-sensing observations at Fukue Island, Japan.

Brown carbon (BrC) aerosols have important warming effects on Earth's radiative forcing. However, information on the evolution of the light-absorption properties of BrC aerosols in the Asian outflow region is limited. In this study, we evaluated the light-absorption properties of BrC using in-situ filter measurements and sky radiometer observations of the ground-based remote sensing network SKYradiometer NETwork (SKYNET) made on Fukue Island, western Japan in 2018. The light-absorption coefficient of BrC obtained from filter measurements had a temporal trend similar to that of the ambient concentration of black carbon (BC), indicating that BrC and BC have common combustion sources. The absorption Angstrom exponent in the wavelength range of 340-870 nm derived from the SKYNET observations was 15% higher in spring (1.81 ± 0.30) than through the whole year (1.53 ± 0.50), suggesting that the Asian outflow carries light-absorbing aerosols to Fukue Island and the western North Pacific. After eliminating the contributions of BC, the absorption Angstrom exponent of BrC alone obtained from filter observations had a positive Spearman correlation (rs = 0.77, p < 0.1) with that derived from SKYNET observations but 33% higher values, indicating that the light-absorption properties of BrC were successfully captured using the two methods. Using the atmospheric transport model FLEXPART and fire hotspots obtained from the Visible Infrared Imaging Radiometer Suite product, we identified a high-BrC event related to an air mass originating from regions with consistent fossil fuel combustion and sporadic open biomass burning in central East China. The results of the study may help to clarify the dynamics and climatic effects of BrC aerosols in East Asia.

Dominance of the residential sector in Chinese black carbon emissions as identified from downwind atmospheric observations during the COVID-19 pandemic.

Emissions of black carbon (BC) particles from anthropogenic and natural sources contribute to climate change and human health impacts. Therefore, they need to be accurately quantified to develop an effective mitigation strategy. Although the spread of the emission flux estimates for China have recently narrowed under the constraints of atmospheric observations, consensus has not been reached regarding the dominant emission sector. Here, we quantified the contribution of the residential sector, as 64% (44-82%) in 2019, using the response of the observed atmospheric concentration in the outflowing air during Feb-Mar 2020, with the prevalence of the COVID-19 pandemic and restricted human activities over China. In detail, the BC emission fluxes, estimated after removing effects from meteorological variability, dropped only slightly (- 18%) during Feb-Mar 2020 from the levels in the previous year for selected air masses of Chinese origin, suggesting the contributions from the transport and industry sectors (36%) were smaller than the rest from the residential sector (64%). Carbon monoxide (CO) behaved differently, with larger emission reductions (- 35%) in the period Feb-Mar 2020, suggesting dominance of non-residential (i.e., transport and industry) sectors, which contributed 70% (48-100%) emission during 2019. The estimated BC/CO emission ratio for these sectors will help to further constrain bottom-up emission inventories. We comprehensively provide a clear scientific evidence supporting mitigation policies targeting reduction in residential BC emissions from China by demonstrating the economic feasibility using marginal abatement cost curves.

Development of robust models for rapid classification of microplastic polymer types based on near infrared hyperspectral images.

Hyperspectral data in the near infrared range were examined for nine common types of plastic particles of 1 mm and 100-500 µm sizes on dry and wet glass fiber filters. Weaker peak intensities were detected for small particles compared to large particles, and the reflectances were weaker at longer wavelengths when the particles were measured on a wet filter. These phenomena are explainable due to the effect of the correlation between the particle size and the absorption of infrared light by water. We constructed robust classification models that are capable of classifying polymer types, regardless of particle size or filter conditions (wet vs. dry), based on hyperspectral data for small particles measured on wet filters. Using the models, we also successfully classified the polymer type of polystyrene beads covered with microalgae, which simulates the natural conditions of microplastics in the ocean. This study suggests that hyperspectral imaging techniques with appropriate classification models allow the identification of microplastics without the time- and labor-consuming procedures of drying samples and removing biofilms, thus enabling more rapid analyses.

Characterization of microplastics on filter substrates based on hyperspectral imaging: Laboratory assessments.

Microplastic pollution has become an urgent issue because it adversely affects ecosystems. However, efficient methods to detect and characterize microplastic particles are still in development. By conducting a series of laboratory assessments based on near-infrared hyperspectral imaging in the wavelength range of 900-1700 nm, we report the fundamental spectral features of (i) 11 authentic plastics and (ii) 11 filter substrate materials. We found that different plastic polymers showed distinct spectral features at 1150-1250 nm, 1350-1450 nm and 1600-1700 nm, enabling their automatic recognition and identification with spectral separation algorithms. Using an improved hyperspectral imaging system, we demonstrated the detection of three types of microplastic particles, polyethylene, polypropylene and polystyrene, down to 100 µm in diameter. As a filter substrate, a gold-coated polycarbonate filter (GPC0847-BA) showed constant reflectance over 900-1700 nm and a large radiative contrast against loaded plastic particles. Glass fiber filters (GF10 and GF/F) would also be suitable substrates due to their low cost and easy commercial availability. This study provides key parameters for applying hyperspectral imaging techniques for the detection of microplastics.

Sources of atmospheric black carbon and related carbonaceous components at Rishiri Island, Japan: The roles of Siberian wildfires and of crop residue burning in China.

A field study was conducted to clarify sources of atmospheric black carbon and related carbonaceous components at Rishiri Island, Japan. We quantified equivalent black carbon (eBC) particle mass and the absorption Ångström exponent (AAE), atmospheric CO and CH4, in addition to levoglucosan in total suspended particles, a typical tracer of biomass burning. Sixteen high eBC events were identified attributable to either anthropogenic sources or biomass burning in Siberia/China. These events were often accompanied by increases of co-emitted gases such as CH4 and CO. Specifically, we observed pollution events with elevated eBC, AAE, levoglucosan, and CH4CO slope in late July 2014, which were attributed to forest fires in Siberia by reference to the FLEXPART model footprint and fire hotspots. In autumn, drastic increases of eBC, AAE, and levoglucosan were observed, accompanied by an eBC-CO slope of >15 ng m-3/ppb, resulting from long-range transport of emissions from extensive burning of crop residue on the Northeast China Plain. Other than the sources of fossil fuel combustion in China and forest fires in Siberia, we report for the first time that pollution events in northern Japan are caused by crop residue burning in China. This study elucidated valuable information that will improve understanding of the effects of biomass burning in East Asia on atmospheric carbonaceous components.

Size-dependent validation of MODIS MCD64A1 burned area over six vegetation types in boreal Eurasia: Large underestimation in croplands.

Pollutants emitted from wildfires in boreal Eurasia can be transported to the Arctic, and their subsequent deposition could accelerate global warming. The Moderate Resolution Imaging Spectroradiometer (MODIS) MCD64A1 burned area product is the basis of fire emission products. However, uncertainties due to the "moderate resolution" (500 m) characteristic of the MODIS sensor could be introduced. Here, we present a size-dependent validation of MCD64A1 with reference to higher resolution (better than 30 m) satellite products (Landsat 7 ETM+, RapidEye, WorldView-2, and GeoEye-1) for six ecotypes over 12 regions of boreal Eurasia. We considered the 2012 boreal Eurasia burning season when severe wildfires occurred and when Arctic sea ice extent was historically low. Among the six ecotypes, we found MCD64A1 burned areas comprised only 13% of the reference products in croplands because of inadequate detection of small fires (<100 ha). Our results indicate that over all ecotypes, the actual burned area in boreal Eurasia (15,256 km2) could have been ~16% greater than suggested by MCD64A1 (13,187 km2) when applying the correction factors proposed in this study. This implies the effects of wildfire emissions in boreal Eurasia on Arctic warming could be greater than currently estimated.

Diversity and succession of autotrophic microbial community in high-elevation soils along deglaciation chronosequence.

Global warming has resulted in substantial glacier retreats in high-elevation areas, exposing deglaciated soils to harsh environmental conditions. Autotrophic microbes are pioneering colonizers in the deglaciated soils and provide nutrients to the extreme ecosystem devoid of vegetation. However, autotrophic communities remain less studied in deglaciated soils. We explored the diversity and succession of the cbbL gene encoding the large subunit of form I RubisCO, a key CO2-fixing enzyme, using molecular methods in deglaciated soils along a 10-year deglaciation chronosequence on the Tibetan Plateau. Our results demonstrated that the abundance of all types of form I cbbL (IA/B, IC and ID) rapidly increased in young soils (0-2.5 years old) and kept stable in old soils. Soil total organic carbon (TOC) and total nitrogen (TN) gradually increased along the chronosequence and both demonstrated positive correlations with the abundance of bacteria and autotrophs, indicating that soil TOC and TN originated from autotrophs. Form IA/B autotrophs, affiliated with cyanobacteria, exhibited a substantially higher abundance than IC and ID. Cyanobacterial diversity and evenness increased in young soils (<6 years old) and then remained stable. Our findings suggest that cyabobacteria play an important role in accumulating TOC and TN in the deglaciated soils.

Seven years of observational atmospheric CO2 at a maritime site in northernmost Japan and its implications.

Surface atmospheric CO2 mixing ratio reflects both natural fluctuation of the carbon cycle and the effect of anthropogenic activities. Long-term observation of atmospheric CO2 forms the basis for model simulations of the carbon cycle both in the straightforward and the inversion ways. Atmospheric CO2 has been measured on Rishiri Island (45.1°N, 141.2°E) in the western North Pacific since May 2006. We report the first 7-year temporal CO2 variations from diurnal to inter-annual scales and the implications on the vegetation phenology. Diurnally, an obvious cycle appeared as a minimum in the afternoon and maximum at midnight in the summer months, caused by local vegetation. Seasonally, the maximum CO2 concentration appeared around the beginning of April, while the minimum appeared around the middle of August. This seasonal variation implied the natural cycle of terrestrial biological activities of the boreal forest, mostly in the east Eurasia. A mean growing season length of ~126 days was estimated. In the period from 2007 to 2012, the peak-to-peak amplitude increased until 2009 and decreased thereafter, with a mean value of 19.7 ppm. Inter-annually, atmospheric CO2 is increasing by a mean growth rate of 2.1 ppm year(-1). The study provides invaluable dataset and useful information to better understand the carbon cycle and its interaction with climate change.