Light, Energy and the Environment, 2018: introduction to the joint feature issue.

This joint feature issue of Optics Express and Applied Optics highlights contributions from authors who presented their latest research at the OSA Light, Energy and the Environment Congress, held in Sentosa Island, Singapore from 5 to 8 November 2018. The joint feature issue comprises 11 contributed papers, which expand upon their respective conference proceedings. The published papers introduced here cover a broad range of timely research topics in optics and photonics for lighting and illumination, solar energy, hyperspectral imaging, and environmental sensing.

Light, Energy and the Environment, 2018: introduction to the joint feature issue.

This joint feature issue of Optics Express and Applied Optics highlights contributions from authors who presented their latest research at the OSA Light, Energy and the Environment Congress, held in Sentosa Island, Singapore from 5-8 November 2018. The joint feature issue comprises 11 contributed papers, which expand upon their respective conference proceedings. The published papers introduced here cover a broad range of timely research topics in optics and photonics for lighting and illumination, solar energy, hyperspectral imaging, and environmental sensing.

Validation of mobile in situ measurements of dairy husbandry emissions by fusion of airborne/surface remote sensing with seasonal context from the Chino Dairy Complex.

Mobile in situ concentration and meteorology data were collected for the Chino Dairy Complex in the Los Angeles Basin by AMOG (AutoMObile trace Gas) Surveyor on 25 June 2015 to characterize husbandry emissions in the near and far field in convoy mode with MISTIR (Mobile Infrared Sensor for Tactical Incident Response), a mobile upwards-looking, column remote sensing spectrometer. MISTIR reference flux validated AMOG plume inversions at different information levels including multiple gases, GoogleEarth imagery, and airborne trace gas remote sensing data. Long-term (9-yr.) Infrared Atmospheric Sounding Interferometer satellite data provided spatial and trace gas temporal context. For the Chino dairies, MISTIR-AMOG ammonia (NH3) agreement was within 5% (15.7 versus 14.9 Gg yr-1, respectively) using all information. Methane (CH4) emissions were 30 Gg yr-1 for a 45,200 herd size, indicating that Chino emission factors are greater than previously reported. Single dairy inversions were much less successful. AMOG-MISTIR agreement was 57% due to wind heterogeneity from downwind structures in these near-field measurements and emissions unsteadiness. AMOG CH4, NH3, and CO2 emissions were 91, 209, and 8200 Mg yr-1, implying 2480, 1870, and 1720 head using published emission factors. Plumes fingerprinting identified likely sources including manure storage, cowsheds, and a structure with likely natural gas combustion. NH3 downwind of Chino showed a seasonal variation of a factor of ten, three times larger than literature suggests. Chino husbandry practices and trends in herd size and production were reviewed and unlikely to add seasonality. Higher emission seasonality was proposed as legacy soil emissions, the results of a century of husbandry, supported by airborne remote sensing data showing widespread emissions from neighborhoods that were dairies 15 years prior, and AMOG and MISTIR observations. Seasonal variations provide insights into the implications of global climate change and must be considered when comparing surveys from different seasons.

Japan's efforts to promote global health using satellite remote sensing data from the Japan Aerospace Exploration Agency for prediction of infectious diseases and air quality.

In this paper we review the status of new applications research of the Japanese Aerospace Exploration Agency (JAXA) for global health promotion using information derived from Earth observation data by satellites in cooperation with inter-disciplinary collaborators. Current research effort at JAXA to promote global public health is focused primarily on the use of remote sensing to address two themes: (i) prediction models for malaria and cholera in Kenya, Africa; and (ii) air quality assessment of small, particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3). Respiratory and cardivascular diseases constitute cross-boundary public health risk issues on a global scale. The authors report here on results of current of a collaborative research to call attention to the need to take preventive measures against threats to public health using newly arising remote sensing information from space.

Characterization and correction of spectral distortions induced by microvibrations onboard the GOSAT Fourier transform spectrometer.

Microvibrations onboard greenhouse gases observing satellite (GOSAT) cause scan speed variations in the TANSO Fourier transform spectrometer. The associated periodic sampling errors generate ghost features in O2 A-band spectra, where surface pressure and aerosol properties are retrieved to determine the optical path through the atmosphere. A correction algorithm has been developed to re-compute the interferograms at equally spaced sampling intervals. The key is to determine iteratively the amplitude and phase of sinusoidal perturbations with predetermined frequencies to minimize the magnitude of the out-of-band ghosts artifacts after correction of the sampling grid. This correction algorithm drastically reduces errors in retrieved surface pressure and improves agreement with ground-based observations.

Mountaintop observation of CO2 absorption spectra using a short wavelength infrared Fourier transform spectrometer.

The absorption spectra of surface-scattered solar radiation were measured from the top of Mount Tsukuba (altitude 833 m) in the short wavelength infrared region using a Fourier transform spectrometer (FTS). The FTS used in this experiment was the breadboard model of the FTS on the Greenhouse Gases Observing Satellite, which was launched on 23 January 2009. In situ measurement of carbon dioxide (CO(2)) from a Cessna airplane was performed simultaneously with the FTS observation. The CO(2) column abundances were retrieved from the observed spectra under the assumption of the absence of aerosol. The retrieved CO(2) column abundances over a few minutes dispersed within 1%. The remaining bias was considered to be caused by the no-aerosol assumption.

Thermal and near infrared sensor for carbon observation Fourier-transform spectrometer on the Greenhouse Gases Observing Satellite for greenhouse gases monitoring.

The Greenhouse Gases Observing Satellite (GOSAT) monitors carbon dioxide (CO(2)) and methane (CH(4)) globally from space using two instruments. The Thermal and Near Infrared Sensor for Carbon Observation Fourier-Transform Spectrometer (TANSO-FTS) detects gas absorption spectra of the solar short wave infrared (SWIR) reflected on the Earth's surface as well as of the thermal infrared radiated from the ground and the atmosphere. TANSO-FTS is capable of detecting three narrow bands (0.76, 1.6, and 2.0 microm) and a wide band (5.5-14.3 microm) with 0.2 cm(-1) spectral resolution (interval). The TANSO Cloud and Aerosol Imager (TANSO-CAI) is an ultraviolet (UV), visible, near infrared, and SWIR radiometer designed to detect cloud and aerosol interference and to provide the data for their correction. GOSAT is placed in a sun-synchronous orbit 666 km at 13:00 local time, with an inclination angle of 98 degrees . A brief overview of the GOSAT project, scientific requirements, instrument designs, hardware performance, on-orbit operation, and data processing is provided.