North Korean CO emissions reconstruction using DMZ ground observations, TROPOMI space-borne data, and the CMAQ air quality model

Emission uncertainty in North Korea can act as an obstacle when developing air pollution management plans in the country and neighboring countries when the transboundary transport of air pollutants is considered. This study introduces a novel approach for adjusting and reallocating North Korean CO emissions, aiming to complement the limited observational and emissions data on the country's air pollutants. We utilized ground observations from demilitarized zone (DMZ) and vertical column density (VCD) data from a TROPOspheric Monitoring Instrument (TROPOMI), which were combined with the Community Multi-Scale Air Quality (CMAQ) chemistry transport model simulations. The Clean Air Support System (CAPSS) and Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) emissions inventories served as the basis for our initial simulations. A two-step procedure was proposed to adjust both the emission intensity and the spatial distribution of emissions. First, air quality simulations were conducted to explore model sensitivity to changes in North Korean CO emissions with respect to ground concentrations. DMZ observations then constrained these simulations to estimate corresponding emission intensity. Second, the spatial structure of North Korean CO emission sources was reconstructed with the help of TROPOMI CO VCD distributions. Our two-step hybrid method outperformed individual emissions adjustment and spatial reallocation based solely on surface or satellite observations. Validation using ground observations from the Chinese Dandong site near the China-North Korea border revealed significantly improved model simulations when applying the updated CO emissions. The adjusted CO emissions were 10.9 times higher than those derived from the bottom-up emissions used in this study, highlighting the lack of information on North Korean pollutants and emission sources. This approach offers an efficient and practical solution for identifying potential missing emission sources when there is limited on-site information about air quality on emissions.

Updating emission inventories for vehicular organic gases: Indications from cold-start and temperature effects on advanced technology cars

How would the organic gas emission inventories of future urban vehicles change with new features of advanced technology cars? Here, volatile organic compounds (VOCs) and intermediate volatile organic compounds (IVOCs) from a fleet of Chinese light-duty gasoline vehicles (LDGVs) were characterized by chassis dynamometer experiments to grasp the key factors affecting future inventory accuracy. Subsequently, the VOC and IVOC emissions of LDGVs in Beijing, China, from 2020 to 2035, were calculated and the spatial-temporal variations were recognized under a scenario of fleet renewal. With the tightening of emission standards (ESs), cold start contributed a larger fraction of the total unified cycle VOC emissions due to the imbalanced emission reductions between operating conditions. It took 757.47 ± 337.75 km of hot running to equal one cold-start VOC emission for the latest certified vehicles. Therefore, the future tailpipe VOC emissions would be highly dependent on discrete cold start events rather than traffic flows. By contrast, the equivalent distance was shorter and more stable for IVOCs, with an average of 8.69 ± 4.59 km across the ESs, suggesting insufficient controls. Furthermore, there were log-linear relationships between temperatures and cold-start emissions, and the gasoline direct-injection vehicles performed better adaptability under low temperatures. In the updated emission inventories, the VOC emissions were more effectively reduced than the IVOC emissions. The start emissions of VOCs were estimated to be increasingly dominant, especially in wintertime. By winter 2035, the contribution of VOC start emissions could reach 98.98 % in Beijing, while the fraction of IVOC start emissions would decrease to 59.23 %. Spatially allocation showed that the high emission regions of tailpipe organic gases from LDGVs have transferred from road networks to regions of intense human activities. Our results provide new insights into tailpipe organic gas emissions of gasoline vehicles, and can support future emission inventories and refined assessment of air quality and human health risk.

Spatial allocation of LID practices with a water footprint approach

Urban water problems due to stormwater have been aggravated by the higher frequency of high-intensity precipitation events and the increase of paved surfaces. However, with appropriate stormwater management practices, such as low-impact development (LID), stormwater can provide an additional urban water resources rather than cause damage. This study aims to apply a water footprint to location determination of LID practices in the urban area. The LID planning procedure was demonstrated with the highest population density region in Taipei, Taiwan. In order to improve the spatial resolution of LID allocation, the "first-level dissemination area" with 450 residents was used as a spatial unit. The performance of LID practices was then evaluated with the simulation using the Storm Water Management Model (SWMM). Three LID practices, rainwater harvesting systems, permeable pavements, and bioretention systems, were selected. After the water footprint accounting, ten sites were suggested for LID implementation. The runoff reduction rate reached up to 65 % by rainwater harvesting systems or at least 3 % by permeable pavements. This study provides a simpler and more effective approach to ways of integrating an urban water footprint into LID planning and stormwater management in urban areas.

A two-stage spatial allocation model for elderly healthcare facilities in large-scale affordable housing communities: a case study in Nanjing City

Background

As the proportion of elderly residents living in large-scale affordable housing communities (LAHCs) increases in China, serious problems have become apparent related to the spatial allocation of elderly healthcare facilities (EHFs), e.g., insufficient provision and inaccessibility. To address these issues, this study developed a location allocation model for EHFs to ensure equitable and efficient access to healthcare services for the elderly in LAHCs.

Methods

Based on discrete location theory, this paper develops a two-stage optimization model for the spatial allocation of EHFs in LAHCs. In the first stage, the candidate locations of EHFs are specified using geographic information system (GIS) techniques. In the second stage, the optimal location and size of each EHF are determined based on the greedy algorithm (GA). Finally, the proposed two-stage optimization model is tested using the Daishan LAHC in Nanjing, Eastern China.

Results

The demand of the elderly for accessibility to EHFs is in line with Nanjing’s planning standards. Deep insights into spatial data are revealed by GIS techniques that enable candidate locations of EHFs to be obtained. In addition, the model helps EHF planners achieve equity and efficiency simultaneously. Two optimal locations for EHFs in the Daishan LAHC are identified, which in turn verifies the validity of the model.

Conclusions

As a strategy for allocating EHFs, this two-stage model improves the equity and efficiency of access to healthcare services for the elderly by optimizing the potential sites for EHFs. It can also be used to assist policymakers in providing adequate healthcare services for the low-income elderly. Furthermore, the model can be extended to the allocation of other public-service facilities in different countries or regions.

An improved gridded polycyclic aromatic hydrocarbon emission inventory for the lower reaches of the Yangtze River Delta region from 2001 to 2015 using satellite data

An improved gridded polycyclic aromatic hydrocarbon (PAH) emission inventory for the lower reaches of the Yangtze River Delta (YRD) region from 2001 to 2015 was developed using satellite data. Despite rapid increases in energy consumption, the annual total emissions of the 16 PAHs showed overall decreasing trends, from a maximum of 5445 t in 2001 to a minimum of 2619 t in 2015, with the largest decline (84.6%) observed in the residential sector. Different spatial allocation methods used in gridded PAH emission inventories have substantial influences on the distributions of PAHs; therefore, we improved the accuracy of the spatial allocation of industrial and open biomass burning PAH emissions using various satellite data. The gridded secondary and tertiary industrial GDP (GDP₂₃) calculated using corrected nighttime light data was the best spatial proxy for the spatial allocation of industrial PAH emissions in the YRD region. We generated a gridded burned area for 2001-2015 by coupling the MCD64A1 and MCD14ML fire products, which was used to allocate PAH emissions from open biomass burning. Finally, we found that changes in the spatial distribution of PAH emissions were mainly driven by energy consumption and degree of technological advancement in different regions during 2001-2015.

Global land-use allocation model linked to an integrated assessment model

We developed a global land-use allocation model that can be linked to integrated assessment models (IAMs) with a coarser spatial resolution. Using the model, we performed a downscaling of the IAMs' regional aggregated land-use projections to obtain a spatial land-use distribution, which could subsequently be used by Earth system models for global environmental assessments of ecosystem services, food security, and climate policies. Here we describe the land-use allocation model, discuss the verification of the downscaling technique, and explain the influences of the downscaling on estimates of land-use carbon emissions. A comparison of the emissions estimated with and without downscaling suggested that the land-use downscaling would help capture the spatial distribution of carbon stock density and regional heterogeneity of carbon emissions caused by cropland and pasture land expansion.