Urban heat island impacted by fine particles in Nanjing, China

Synergistic interactions of fine particles and radiative effects in modulating urban heat islands during winter haze event in a cold megacity of Northeast China

Severe air pollution and urban heat islands (UHI) intensity (UHII) are two challenging problems that have attracted wide attention in populated cities. However, previous studies mostly focused on the relationship between fine particulate matter (PM_2.5) and UHII, but how UHII responds to the interactions between radiative effects (direct effect (DE), indirect effect (IDE) with slope and shading effects (SSE)) and PM_2.5 during heavy pollution is still unclear, especially in the cold region. Therefore, this study explores the synergistic interactions between PM_2.5 and radiative effects in influencing UHII during a heavy pollution event in the cold-megacity of Harbin-China. Hence, we designed four scenarios: non-aerosol radiative feedback (NARF), DE, IDE, and combined effects (DE + IDE + SSE) in December 2018 (clear-episode) and December 2019 (heavy-haze-episode) using numerical modeling. The results showed that the radiative effects influenced the spatial distribution of PM_2.5 concentration leading to a mean drop in 2-m air-temperature by approximately 0.67 °C (downtown) and 1.48 °C (satellite-town) between the episodes. The diurnal-temporal variations revealed that the daytime and nighttime UHIIs were strengthened in the downtown during the heavy-haze-episode, while a reverse effect was observed in the satellite-town. Interestingly, during the heavy-haze-episode, the considerable difference between excellent and heavily polluted PM_2.5 levels showed a decrease in UHIIs (1.32 °C, 1.32 °C, 1.27 °C, and 1.20 °C) due to the radiative effects (NARF, DE, IDE, and (DE + IDE + SSE)), respectively. In assessing other pollutants' interactions with the radiative effects, PM₁₀ and NOx had a considerable impact on the UHII during the heavy-haze episode while O₃ and SO₂ were discovered to be very low in both episodes. Moreover, the SSE has uniquely influenced UHII, especially during the heavy-haze-episode. Therefore, insight from this study provides an understanding of how UHII responds uniquely in the cold region, which in turn could help to formulate effective policies and co-mitigation strategies for air pollution and UHI problems.

Reconsidering the effects of urban form on PM2.5 concentrations: an urban shrinkage perspective

The phenomenon of urban shrinkage is currently occurring worldwide; however, the "growth-oriented" planning paradigm is not suitable for these shrinking cities. Reconsidering the relationship between urban form and PM_2.5 concentrations from the perspective of urban shrinkage can help provide a research reference for controlling air pollution and optimizing the spatial layout of shrinking cities. This study takes shrinking areas in China as the research subject, which are divided into four research groups according to their shrinkage degree. The empirical results indicate that the average PM_2.5 concentrations decrease with the aggravation of urban shrinkage. In terms of the effect of urban form on PM_2.5 concentrations, the urban size is always positively related to PM_2.5 concentrations, while the impact of urban fragmentation on PM_2.5 concentrations is negligible. Further, urban shape positively affects PM_2.5 concentrations only in moderately and severely shrinking cities. Cities with sprawling urban forms have higher PM_2.5 concentrations, except for those facing severe shrinking trends. This study suggests that governments in shrinking cities should reasonably adjust both the urban form and land use to improve air quality based on the degree of urban shrinkage.

Urban Heat Island Mitigation: GIS-Based Analysis for a Tropical City Singapore

To reduce the pace of climate change and achieve the goals set in Paris Agreement by 2030, Association of Southeast Asian Nations (ASEAN) countries have started to prioritize sustainability as one of their top agendas. Numerous studies have demonstrated that one of the most important issues that must be addressed to halt climate change is the urban heat island (UHI). Given the different mitigation strategies available, the focus of our study here is to assess the influence of green spaces and Green Mark commercial buildings on Singapore's temperature distribution using non-exhaustive factors related to energy consumption and efficiency. Additionally, this paper examines the effectiveness of green spaces and commercial buildings in reducing the rate of temperature change. This study uses ArcGIS software to map data, perform spatial analysis through cloud-based mapping, and produce visual representations with geographic information systems (GIS) to promote greater insight on the formulation of goals and policy making for strategic management. In comparison to non-commercial districts, our findings show that commercial districts have the lowest percentage of temperature change, an estimated 1.6 percent, due to a high concentration of green spaces and Green Mark commercial buildings. Our research also helps to close the research gaps in determining the efficacy of Green Mark commercial buildings, skyrise greeneries, gardens, and national parks. It also helps to minimize the bottleneck of expensive building costs and environmental damage that would have occurred from a design flaw found too late in the urban planning and construction process.

The Effect of Small Particulate Matter on Tourism and Related SMEs in Chiang Mai, Thailand

In northern Thailand, the problem of small particulate matter arises every year, with the primary source being agricultural-weed burning and wildfire. The tourism industry is strongly impacted and has been in the spotlight for the past few years. Thus, this study aims to investigate the effect of small particulate matter on tourism and related SMEs in Chiang Mai, Thailand. The data were collected from 286 entrepreneurs in the tourism and related SMEs sectors. The data were analyzed using data mining and association-rule techniques. The study revealed that small particulate matter has a considerable impact on customer factors, especially when the number of customers has decreased. Operational factors and product/service factors are also affected by the dust in the form of adjustments to keep the business running and the protection of the health of employees and customers. Certainly, financial factors are affected by the small particulate matter situation, both lower revenues and higher costs.

The Urban–Rural Heterogeneity of Air Pollution in 35 Metropolitan Regions across China

Urbanization and air pollution are major anthropogenic impacts on Earth’s environment, weather, and climate. Each has been studied extensively, but their interactions have not. Urbanization leads to a dramatic variation in the spatial distribution of air pollution (fine particles) by altering surface properties and boundary-layer micrometeorology, but it remains unclear, especially between the centers and suburbs of metropolitan regions. Here, we investigated the spatial variation, or inhomogeneity, of air quality in urban and rural areas of 35 major metropolitan regions across China using four different long-term observational datasets from both ground-based and space-borne observations during the period 2001–2015. In general, air pollution in summer in urban areas is more serious than in rural areas. However, it is more homogeneously polluted, and also more severely polluted in winter than that in summer. Four factors are found to play roles in the spatial inhomogeneity of air pollution between urban and rural areas and their seasonal differences: (1) the urban–rural difference in emissions in summer is slightly larger than in winter; (2) urban structures have a more obvious association with the spatial distribution of aerosols in summer; (3) the wind speed, topography, and different reductions in the planetary boundary layer height from clean to polluted conditions have different effects on the density of pollutants in different seasons; and (4) relative humidity can play an important role in affecting the spatial inhomogeneity of air pollution despite the large uncertainties.

A Specific Study on the Impacts of PM2.5 on Urban Heat Islands with Detailed In Situ Data and Satellite Images

Rapid urbanization often results in serious urban heat islands (UHI) and fine particulate matter (PM2.5) concentration. Previous studies found it was hard to evaluate the haze contribution to the UHI quantitatively, because of the complex properties of the atmosphere aloft and the irregular alteration of PM2.5 loads. Taking Beijing as the study site, where detailed in situ PM2.5 concentration data, canopy thermal data and MODIS land surface temperature (LST) products were all available in 2015, this study investigated the impacts of PM2.5 on both surface UHI intensity (SUHII) and canopy UHI intensity (CUHII) at daytime and night. The results reveal that the CUHII are almost unchanged throughout the year, while SUHII varies greatly in both temporal axis and spatial distribution. PM2.5 concentration has significant negative impacts on mean SUHII (r = −0.6115) and daytime SUHII (r = −0.6164), and less significant negative impact on CUHII (r = −0.51999). However, the contribution of PM2.5 concentration to nighttime SUHI is not significant. This specific study checked and improved previous works on this topic, with detailed in situ data and satellite images. The results of this work can enhance our understanding of the dynamics and driving mechanism of urban thermal environment.

Impacts of AOD Correction and Spatial Scale on the Correlation between High-Resolution AOD from Gaofen-1 Satellite and In Situ PM2.5 Measurements in Shenzhen City, China

Satellite-derived aerosol optical depth (AOD) is widely used to estimate surface PM2.5 concentrations. Most AOD products have relatively low spatial resolutions (i.e., ≥1 km). Consequently, insufficient research exists on the relationship between high-resolution (i.e., <1 km) AOD and PM2.5 concentrations. Taking Shenzhen City, China as the study area, we derived AOD at the 16-m spatial resolution for the period 2015–2017 based on Gaofen-1 (GF-1) satellite images and the Dark Target (DT) algorithm. Then, we extracted AOD at spatial scales ranging from 40 m to 5000 m and applied vertical and humidity corrections. We analyzed the correlation between AOD and PM2.5 concentrations, and the impacts of AOD correction and spatial scale on the correlation. It was found that the DT-derived GF-1 AOD at different spatial scales had statistically significant correlations with surface PM2.5 concentrations, and the AOD corrections strengthened the correlations. The correlation coefficients (R) between AOD at different spatial scales and PM2.5 concentrations were 0.234–0.329 and 0.340–0.423 before and after AOD corrections, respectively. In spring, summer, autumn, and winter, PM2.5 concentrations had the best correlations with humidity-corrected AOD, uncorrected AOD, vertical and humidity-corrected AOD, and uncorrected AOD, respectively, indicating a distinct seasonal variation of the aerosol characteristics. At spatial scales of 1–5 km, AOD at finer spatial scales generally had higher correlations with PM2.5 concentrations. However, at spatial scales <1 km, the correlations fluctuated irregularly, which could be attributed to scale mismatches between AOD and PM2.5 measurements. Thus, 1 km appears to be the optimum spatial scale for DT-derived AOD to maximize the correlation with PM2.5 concentrations. It is also recommended to aggregate very high-resolution DT-derived AOD to an appropriate medium resolution (e.g., 1 km) before matching them with in situ PM2.5 measurements in regional air pollution studies.

Interannual variations in surface urban heat island intensity and associated drivers in China

The spatial, diurnal and seasonal variations of surface urban heat islands (SUHIs) have been investigated in many places, but we still have limited understanding of the interannual variations of SUHIs and associated drivers. In this study, the interannual variations in SUHI intensity (SUHII, derived from MODIS land surface temperature (LST) data (8-day composites of twice-daily observations), urban LST minus rural) and their relationships with climate variability and urbanization were analyzed in 31 cities in China for the period 2001-2015. Significant increasing trends of SUHII were observed in 71.0%, 58.1%, 25.8% and 54.8% the cities in summer days (SDs), summer nights (SNs), winter days (WDs) and winter nights (WNs), respectively. Pearson's correlation analyses were first performed from a temporal perspective, which were different from a spatial perspective as previous studies. The results showed that the SUHII in SDs and WDs was negatively correlated with the background LST and mean air temperature in most of the cities. The nighttime SUHII in most cities was negatively and positively correlated with total precipitation and total sunshine duration, respectively. Average wind speed has little effect on SUHII. Decreasing vegetation and increased population were the main factors that contributed to the increased SUHII in SDs and SNs, while albedo only influenced the SUHII in WDs. In addition, Pearson's correlation analyses across cities showed that cities with higher decreasing rates of vegetation exhibited higher increasing rates of the SUHII in SDs and WDs. Cities with larger population growth rates do not necessarily have higher increasing rates of SUHII.

A Review of Recent Advances in Research on PM2.5 in China

PM_2.5 pollution has become a severe problem in China due to rapid industrialization and high energy consumption. It can cause increases in the incidence of various respiratory diseases and resident mortality rates, as well as increase in the energy consumption in heating, ventilation, and air conditioning (HVAC) systems due to the need for air purification. This paper reviews and studies the sources of indoor and outdoor PM_2.5, the impact of PM_2.5 pollution on atmospheric visibility, occupational health, and occupants’ behaviors. This paper also presents current pollution status in China, the relationship between indoor and outdoor PM_2.5, and control of indoor PM_2.5, and finally presents analysis and suggestions for future research.