Models and Application of Firefighting Vulnerability

AbstractGeographic information systems (GIS) have been applied to analyze the efficiency and effectiveness of public facility services such as fire stations, police stations and day-care centers. Regardless of the scientific contribution of such an approach, there are numerous limitations to follow the rules or optimized suggestions due to high land price and other societal factors. In the present study, we narrowed the scope to firefighting services: how to decrease firefighting dismissals and help firefighters recognize the situation of fire events before arriving at the fire scenes. The absolute time from the fire station to the fire scene was considered to be the Mobility Kill Zone. Narrow roads and illegal parking were classified as the Operation Kill Zone. Areas with identified hazardous commodities and toxic substances were classified as the Identified Hazardous Zone. The areas cluttered with fire safety management objects were classified as the Fire Vulnerability Zone. Four models were suggested in our previous research and in the present study, we elaborated upon the models and examined new information technology (IT) to implement the models in rural and urban areas

Intercontinental transport of pollution manifested in the variability and seasonal trend of springtime O3 at northern middle and high latitudes

Observations (0–8 km) from the Tropospheric Ozone Production about the Spring Equinox (TOPSE) experiment are analyzed to examine air masses contributing to the observed variability of springtime O3 and its seasonal increase at 40°–85°N over North America. Factor analysis using the positive matrix factorization and principal component analysis methods is applied to the data set with 14 chemical tracers (O3, NOy, PAN, CO, CH4, C2H2, C3H8, CH3Cl, CH3Br, C2Cl4, CFC-11, HCFC-141B, Halon-1211, and 7Be) and one dynamic tracer (potential temperature). Our analysis results are biased by the measurements at 5–8 km (70% of the data) due to the availability of 7Be measurements. The identified tracer characteristics for seven factors are generally consistent with the geographical origins derived from their 10 day back trajectories. Stratospherically influenced air accounts for 14 ppbv (35–40%) of the observed O3 variability for data with O3concentrations \u3c100 ppbv at middle and high latitudes. It accounts for about 2.5 ppbv/month (40%) of the seasonal O3 trend at midlatitudes but for only 0.8 ppbv/month (\u3c20%) at high latitudes, likely reflecting more vigorous midlatitude dynamical systems in spring. At midlatitudes, reactive nitrogen-rich air masses transported through Asia are much more significant (11 ppbv in variability and 3.5 ppbv/month in trend) than other tropospheric contributors. At high latitudes the O3 variability is significantly influenced by air masses transported from lower latitudes (11 ppbv), which are poor in reactive nitrogen. The O3 trend, in contrast, is largely defined by air masses rich in reactive nitrogen transported through Asia and Europe across the Pacific or the Arctic (3 ppbv/month). The influence from the stratospheric source is more apparent at 6–8 km, while the effect of O3 production and transport within the troposphere is more apparent at lower altitudes. The overall effect of tropospheric photochemical production, through long-range transport, on the observed O3 variability and its seasonal trend is more important at high latitudes relative to more photochemically active midlatitudes

Computationally efficient air quality forecasting tool: implementation of STOPS v1.5 model into CMAQ v5.0.2 for a prediction of Asian dust

This study suggests a new modeling framework using a hybrid Eulerian-Lagrangian-based modeling tool (the Screening Trajectory Ozone Prediction System, STOPS) for a prediction of an Asian dust event in Korea. The new version of STOPS (v1.5) has been implemented into the Community Multi-scale Air Quality (CMAQ) model version 5.0.2. The STOPS modeling system is a moving nest (Lagrangian approach) between the source and the receptor inside the host Eulerian CMAQ model. The proposed model generates simulation results that are relatively consistent with those of CMAQ but within a comparatively shorter computational time period. We find that standard CMAQ generally underestimates PM10 concentrations during the simulation period (February 2015) and fails to capture PM10 peaks during Asian dust events (22-24 February 2015). The underestimation in PM10 concentration is very likely due to missing dust emissions in CMAQ rather than incorrectly simulated meteorology, as the model meteorology agrees well with the observations. To improve the underestimated PM10 results from CMAQ, we used the STOPS model with constrained PM concentrations based on aerosol optical depth (AOD) data from the Geostationary Ocean Color Imager (GOCI), reflecting real-time initial and boundary conditions of dust particles near the Korean Peninsula. The simulated PM10 from the STOPS simulations were improved significantly and closely matched the surface observations. With additional verification of the capabilities of the methodology on emission estimations and more STOPS simulations for various time periods, the STOPS model could prove to be a useful tool not just for the predictions of Asian dust but also for other unexpected events such as wildfires and oil spillsopen0

First Top-Down Estimates of Anthropogenic NO_x Emissions Using High-Resolution Airborne Remote Sensing Observations

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions

Lightning and anthropogenic NO_x sources over the United States and the western North Atlantic Ocean: Impact on OLR and radiative effects

The migration of enhancements in NO_2 concentration, outgoing longwave radiation (OLR), and radiative effects associated with the onset of the North American Monsoon in July 2005 has been investigated using satellite data and the Regional Chemical Transport Model (REAM). The satellite data include the tropospheric NO2 columns, tropospheric O_3 profiles, and OLR from OMI, TES and NOAA-16 satellite, respectively, for June and July 2005. The simulated OLR captures the spatial distribution of the remotely sensed OLR fields with relatively small biases (≤5.7%) and high spatial correlations (R ≥ 0.88). This study reveals that the lightning-generated NOx exerts a larger, by up to a factor of three, impact on OLR (up to 0.35 Wm^(−2)) and radiative effects (up to 0.55 Wm^(−2)) by enhancing O_3 in the upper troposphere than anthropogenic NO_x that increases O_3 in the lower troposphere, despite the fact that the lightning-generated NO_x and O_3 are much smaller than those from the anthropogenic emissions. The radiative effect by lightning-derived upper tropospheric O_3 over the convective outflow regions is affected by the changes in lightning frequency. Thus the changes in convection due to global warming may alter the geographical distribution and magnitude of the radiative effect of lightning-derived O3, and this paper is a first step in quantifying the current radiative impact

Survey of whole air data from the second airborne Biomass Burning and Lightning Experiment using principal component analysis

Hydrocarbon and halocarbon measurements collected during the second airborne Biomass Burning and Lightning Experiment (BIBLE-B) were subjected to a principal component analysis (PCA), to test the capability for identifying intercorrelated compounds within a large whole air data set. The BIBLE expeditions have sought to quantify and understand the products of burning, electrical discharge, and general atmospheric chemical processes during flights arrayed along the western edge of the Pacific. Principal component analysis was found to offer a compact method for identifying the major modes of composition encountered in the regional whole air data set. Transecting the continental monsoon, urban and industrial tracers (e.g., combustion byproducts, chlorinated methanes and ethanes, xylenes, and longer chain alkanes) dominated the observed variability. Pentane enhancements reflected vehicular emissions. In general, ethyl and propyl nitrate groupings indicated oxidation under nitrogen oxide (NOx) rich conditions and hence city or lightning influences. Over the tropical ocean, methyl nitrate grouped with brominated compounds and sometimes with dimethyl sulfide and methyl iodide. Biomass burning signatures were observed during flights over the Australian continent. Strong indications of wetland anaerobics (methane) or liquefied petroleum gas leakage (propane) were conspicuous by their absence. When all flights were considered together, sources attributable to human activity emerged as the most important. We suggest that factor reductions in general and PCA in particular may soon play a vital role in the analysis of regional whole air data sets, as a complement to more familiar methods

First Top-Down Estimates of Anthropogenic NO_x Emissions Using High-Resolution Airborne Remote Sensing Observations

A number of satellite‐based instruments have become an essential part of monitoring emissions. Despite sound theoretical inversion techniques, the insufficient samples and the footprint size of current observations have introduced an obstacle to narrow the inversion window for regional models. These key limitations can be partially resolved by a set of modest high‐quality measurements from airborne remote sensing. This study illustrates the feasibility of nitrogen dioxide (NO_2) columns from the Geostationary Coastal and Air Pollution Events Airborne Simulator (GCAS) to constrain anthropogenic NO_x emissions in the Houston‐Galveston‐Brazoria area. We convert slant column densities to vertical columns using a radiative transfer model with (i) NO_2 profiles from a high‐resolution regional model (1 × 1 km^2) constrained by P‐3B aircraft measurements, (ii) the consideration of aerosol optical thickness impacts on radiance at NO_2 absorption line, and (iii) high‐resolution surface albedo constrained by ground‐based spectrometers. We characterize errors in the GCAS NO_2 columns by comparing them to Pandora measurements and find a striking correlation (r > 0.74) with an uncertainty of 3.5 × 10^(15) molecules cm^(−2). On 9 of 10 total days, the constrained anthropogenic emissions by a Kalman filter yield an overall 2–50% reduction in polluted areas, partly counterbalancing the well‐documented positive bias of the model. The inversion, however, boosts emissions by 94% in the same areas on a day when an unprecedented local emissions event potentially occurred, significantly mitigating the bias of the model. The capability of GCAS at detecting such an event ensures the significance of forthcoming geostationary satellites for timely estimates of top‐down emissions

New Era of Air Quality Monitoring from Space: Geostationary Environment Monitoring Spectrometer (GEMS)

GEMS will monitor air quality over Asia at unprecedented spatial and temporal resolution from GEO for the first time, providing column measurements of aerosol, ozone and their precursors (nitrogen dioxide, sulfur dioxide and formaldehyde). Geostationary Environment Monitoring Spectrometer (GEMS) is scheduled for launch in late 2019 - early 2020 to monitor Air Quality (AQ) at an unprecedented spatial and temporal resolution from a Geostationary Earth Orbit (GEO) for the first time. With the development of UV-visible spectrometers at sub-nm spectral resolution and sophisticated retrieval algorithms, estimates of the column amounts of atmospheric pollutants (O3, NO2, SO2, HCHO, CHOCHO and aerosols) can be obtained. To date, all the UV-visible satellite missions monitoring air quality have been in Low Earth orbit (LEO), allowing one to two observations per day. With UV-visible instruments on GEO platforms, the diurnal variations of these pollutants can now be determined. Details of the GEMS mission are presented, including instrumentation, scientific algorithms, predicted performance, and applications for air quality forecasts through data assimilation. GEMS will be onboard the GEO-KOMPSAT-2 satellite series, which also hosts the Advanced Meteorological Imager (AMI) and Geostationary Ocean Color Imager (GOCI)-2. These three instruments will provide synergistic science products to better understand air quality, meteorology, the long-range transport of air pollutants, emission source distributions, and chemical processes. Faster sampling rates at higher spatial resolution will increase the probability of finding cloud-free pixels, leading to more observations of aerosols and trace gases than is possible from LEO. GEMS will be joined by NASA's TEMPO and ESA's Sentinel-4 to form a GEO AQ satellite constellation in early 2020s, coordinated by the Committee on Earth Observation Satellites (CEOS)