Summertime surface energy balance fluxes at two Beijing sites

Summertime (June to August 2015) radiative and turbulent heat fluxes were measured concurrently at two sites (urban and suburban) in Beijing. The urban site has slightly lower incoming and outgoing shortwave radiation, lower atmospheric transmissivity and a lower surface albedo compared to the suburban site. Both sites receive similar incoming longwave radiation. Although the suburban site had larger daytime outgoing longwave radiation (L_↑), differences in the daily mean L_↑ values are small, as the urban site has higher nocturnal L_↑. Overall, both the midday and daily mean net all-wave radiation (Q^*) for the two sites are nearly equal. However, there are significant differences between the sites in the surface energy partitioning. The urban site has smaller turbulent sensible heat (Q_H) (21-25% of Q^* (midday – daily)) and latent heat (Q_E) fluxes (21-45% of Q^*). Whereas, the suburban proportions of Q^* are Q_H 32-32% and Q_E 39-66%. The daily (midday) mean Bowen ratio (Q_H⁄Q_E ) was 0.56 and 0.49 (0.98 and 0.83) for the urban and suburban sites, respectively. These values are low compared to other urban and suburban areas with similar or larger fractions of vegetated cover. Likely these are caused by the widespread external water use for road cleaning/wetting, greenbelts, and air conditioners. Our suburban site has quite different land cover to most previous suburban studies as crop irrigation supplements rainfall. These results are important in enhancing our understanding of surface–atmosphere energy exchanges in Chinese cities, and can aid the development and evaluation of urban climate models and inform urban planning strategies in the context of rapid global urbanization and climate change

Traffic restrictions during the 2008 Olympic Games reduced urban heat intensity and extent in Beijing

Satellite thermal remote sensing has been utilized to examine the urban heat dynamics in relation to the urban traffic restriction policy. During the 2008 Olympic Games in Beijing, the traffic volume was approximately cut off by half through the road space rationing. Based on daily MODIS satellite thermal observations on the surface temperature, statistical models were developed to analyze the contribution of traffic volume reduction to the urban heat intensity and spatial extent. Our analyses show that cutting off half of the traffic volume has led to a marked decrease in the mean surface temperature by 1.5–2.4 °C and shrinkage of the heat extent by 820 km2 in Beijing. This research suggests that the impact of urban traffic on heat intensity is considerably larger than previously thought, and the management of urban traffic and vehicle fossil fuel use should be included in the future urban heat mitigation plan

中国における都市化総合評価及び環境への影響に関する研究

In Chapter one, research background and significance is investigated. In addition, previous studies and current situation in the research fields was reviewed and discussed. In Chapter two, an in-depth review of prior studies associated with the research topic was conducted. The literature review was carried out from three aspects: urbanization and eco-environment evalution and coordination, urban sprawl assessment and urban heat island investigation. In Chapter three, maximum entropy method was applied to help generate the evaluation system of eco-environment level and urbanization level at provincial scale. Comparison analysis and coordinate analysis was carried through to assess the development of urbanization and eco-environment as well as the balance and health degree of the city develops. In Chapter four, DMSP/OLS stable nighttime light dataset was used to measure and assess the urban dynamics from the extraction of built up area. Urban sprawl was evaluated by analyzing the landscape metrics which provided general understanding of the urban sprawl and distribution pattern characteristics could be got from the evaluation. In Chapter five, the investigation of surface urban heat island effects in Beijing city which derive from land surface temperature retrieval from remote sensing data of Landsat TM was carried out. In addition, spatial correlation and relationship between the urbanization level, vegetation coverage and surface urban heat island was carried out in this chapter. In Chapter six, all the works have been summarized and a conclusion of whole thesis is deduced.北九州市立大

The impact of aerosols on the sensible and latent heat fluxes in Beijing

In recent decades, rapid urbanization together with industrialization has led to an increase in anthropogenic emissions, resulting in high air pollution concentrations and poor air quality particularly in developing countries, such as in China. Due to both the enhanced environmental and severe public health risks poor air quality is causing and the climate impacts of aerosols, it is of great interest to study and understand aerosol particles and their impact on our surroundings. Aerosols affect the radiative properties of the atmosphere and the surface energy balance. The impact of aerosols on the surface radiative fluxes of the urban surface energy balance is widely known, but the impact on the turbulent energy fluxes, which are important components in the energy balance, has until now remained unclear. To extend the knowledge of aerosol impacts on all the energy balance components, a simple urban land surface model (SUEWS) during the period of 2006-2009 is used, together with aerosol data, Aerosol Optical Depth (AOD), received from an AERONET station located in Beijing. With the use of commonly measured meteorological variables together with parameters defined for the study area of 1 km radius around a meteorological tower, the components of the urban surface energy balance are simulated by the model. For further data analysis, the data are divided into thermal seasons and pollutant categories according to the available AOD-data. Extreme polluted conditions are achieved during 24 % for the time of available AOD-data, additionally showing relatively less situations with poor air quality (8 %) in winter compared to 27 % observed in summer. The aim of this study is to analyse how much aerosol particles can modify the different surface energy balance components, particularly focusing on the turbulent fluxes. The model is evaluated against observed turbulent fluxes in the same tower, showing an overestimation of the sensible heat flux and an underestimation and a better model performance of the latent heat flux. Still, the diurnal behaviour of the fluxes is shown to be well reproduced by the model. The behaviour of the modelled components is further investigated, showing a clear monthly variation for almost all the fluxes contributing to the surface energy balance. The behaviour of the total energy balance is in general controlled by the wet (occurring from May to October) and dry periods, distinguishing the climate in Beijing. The sensible heat flux is the dominant flux in March, accounting for 59 % of the available energy, whereas during the wet periods, higher portion of the available energy is consumed by the turbulent latent heat flux (61 % in August). Adding the effect of aerosols, the results clearly show how the net radiative flux is decreased in poor air quality conditions, giving differences of 138 W/m2 in the median flux due to aerosol loading in the atmosphere. The main finding of this study is that aerosols also influence the turbulent fluxes, with largest aerosol impact on the sensible heat flux occurring during thermal spring (66 W/m2 difference between clean and polluted air conditions). Likewise, in summer, when the latent heat flux is the largest contributor for consuming the available energy, the influence of aerosols is most visible (25 W/m2 difference). This study highlights the importance of maintaining measurements of aerosol concentrations and characteristics of the pollutants over urban areas due to their influence not only on the radiative fluxes, but all the components of the surface energy balance, which can further alter the water circulation and give rise to other environmental risks. These findings can therefore be used in urban planning and issues related to water management and air pollution regulations.Antropogena utsläpp har ökat i och med snabb urbanisering och industrialisering, vilket har skett under de senaste årtionden och gett upphov till dålig luftkvalitet, speciellt i utvecklingsländer, så som in Kina. Dålig luftkvalitet ökar både miljörisker samt orsakar allmänna hälsoproblem, vilket tillsammans med klimatinverkan av aerosoler ökar intresset hos forskare att förstå aerosol partiklar samt hur de påverkar vår omgivning. Ett välkänt fenomen är hur aerosoler påverkar nettostrålningen vid markytan, medan oklarheter uppstår gällande hur de inverkar på de turbulenta energitermerna, som består av sensibla och latenta värmeflöden. Med hjälp av en enkel modell (SUEWS), som kan simulera de olika energitermerna i urbana miljöer, tillsammans med aerosoldata (Aerosol Optical Depth, AOD) från Beijing, försöker jag i min studie utvidga kunskapen gällande aerosolernas inverkan på alla energitermer. Modellen är kompetent att simulera dessa termer med hjälp av allmänna meteorologiska data för forskningsperioden 2006–2009, samt parametrar som på det bästa möjliga sättet motsvarar forskningsområdet, som omfattar en cirkel med 1 km radie runt det meteorologiska tornet i Beijing. För vidare dataanalys delas data i termiska årstider samt i föroreningskategorier enligt tillgänglig AOD-data. Förhållanden med extremt förorenad luft påträffas för 24 % av studietiden. Graden av hur förorenad luften är varierar per årstid, då förhållanden med dålig luftkvalitet förekommer till endast 8 % på vintern jämfört med 27 % under sommaren. Syftet med mitt arbete är därmed att analysera till hur stor grad aerosolpartiklar påverkar de olika energitermerna i markytans energibalans, med speciell betoning gällande de turbulenta termerna. Modellen utvärderas med hjälp av observerade värden av turbulenta energitermerna erhållna av mätningar vid tornet i Beijing. Fastän modellen tydligt övervärderar sensibla värmeflödet och undervärderar latenta värmeflödet, visar det sig att modellen dock klarar av att återskapa dygnsvariationen av energitermerna väl. Beteendet av de simulerade energitermerna undersöks, vilket även framhäver hur termerna tydligt varierar per månad. Klimatet i Beijing, kännetecknat med torr (november till april)- och regnperioder (maj till oktober), bestämmer i stort sett hur de olika turbulenta termerna förhåller sig till varandra. Förnimbara värmeflödet dominerar i mars och står för 59 % av energin som finns tillgängligt, medan en större del av energin förbrukas av latenta värmeflödet under regnperioder (61 % i augusti). Då aerosolernas inverkan tas i beaktan, visar resultaten av denna studie hur nettostrålningen tydligt minskar vid sämre luftförhållanden (maximalt 138 W/m2 skillnad mellan rena och förorenade förhållanden). Huvudforskningsresultatet är dock att aerosolerna även tydligt påverkar de turbulenta energitermerna. Aerosoler påverkar sensibla värmeflödet mest under våren (66 W/m2 skillnad) då även största delen av energin som är tillgängligt förbrukas av samma term. Samma trend påträffas även hos latenta värmeflödet, där aerosolernas inverkan är tydligast på sommaren (25 W/m2 skillnad). Studien framhäver hur viktigt det är att bibehålla information gällande aerosolkoncentrationer i luften samt deras egenskaper i urbana miljöer, eftersom aerosoler inte bara påverkar nettostrålningen, men också alla andra termer i markytans energibalans och kan därmed vidare påverka vattencirkulationen samt öka andra miljörisker i tättbefolkade urbana områden. Resultaten av denna studie kan ytterligare användas som hjälp i urban planering samt ärenden gällande vattenförvaltning och reglering av luftutsläpp

The increase in the proportion of impervious surfaces and changes in air temperature, relative humidity, and cloud cover in Poland

The aim of the study is to characterise the changes in the proportion of impervious surfaces (ISs) in Poland and their impact on changes in temperature, air humidity, and cloud cover. The results of satellite image classification from 1990, 2000, 2010 and 2020, as well as meteorological data from the period 1981–2020 for the warm half of the year, were used. An analysis was performed making it possible to compare the changes in the proportion of ISs in 3 decades, i.e. 1991–2000, 2001–2010 and 2011–2020. In Poland, in the years 1991–2020, the total area of ISs increased by approximately 30%. At the same time, statistically significant positive trends in maximum temperature are visible throughout Poland, ranging from $0.48^{\circ}C$ per 10 years to $>0.90^{\circ}C$ per 10 years. Trends in the magnitude of low-level cloud cover are negative throughout Poland and range from −2.7% to −2.3% per 10 years. The frequency of stratiform clouds is decreasing, while that of mid-level Cirrus and Cumulus clouds is increasing. The results show a relationship between the increase in ISs in Polish cities and changes in meteorological elements in their area and in the immediate vicinity, which were most pronounced in the first decade of the 21st century

Modelling spatiotemporal variations of the canopy layer urban heat island in Beijing at the neighbourhood scale

Information on the spatiotemporal characteristics of Beijing's urban–rural near-surface air temperature difference, known as the canopy layer urban heat island (UHI), is important for future urban climate management strategies. This paper investigates the variation of near-surface air temperatures within Beijing at a neighbourhood-scale resolution (∼ 100 m) during winter 2016 and summer 2017. We perform simulations using the urban climate component of the ADMS-Urban model with land surface parameters derived from both local climate zone classifications and OpenStreetMap land use information. Through sensitivity simulations, the relative impacts of surface properties and anthropogenic heat emissions on the temporal variation of Beijing's UHI are quantified. Measured UHI intensities between central Beijing (Institute of Atmospheric Physics) and a rural site (Pinggu) during the Atmospheric Pollution and Human Health in a Chinese Megacity (APHH-China) campaigns, peak during the evening at ∼ 4.5 ∘C in both seasons. In winter, the nocturnal UHI is dominated by anthropogenic heat emissions but is underestimated by the model. Higher-resolution anthropogenic heat emissions may capture the effects of local sources (e.g. residential buildings and adjacent major roads). In summer, evening UHI intensities are underestimated, especially during heatwaves. The inability to fully replicate the prolonged release of heat stored in the urban fabric may explain this. Observed negative daytime UHI intensities in summer are more successfully captured when surface moisture levels in central Beijing are increased. However, the spatial correlation between simulated air temperatures and satellite-derived land surface temperatures is stronger with a lower urban moisture scenario. This result suggests that near-surface air temperatures at the urban meteorological site are likely influenced by fine-scale green spaces that are unresolved by the available land cover data and demonstrates the expected differences between surface and air temperatures related to canopy layer advection. This study lays the foundations for future studies of heat-related health risks and UHI mitigation strategies across Beijing and other megacities

Mapping regional land cover and land use change using MODIS time series

Coarse resolution satellite observations of the Earth provide critical data in support of land cover and land use monitoring at regional to global scales. This dissertation focuses on methodology and dataset development that exploit multi-temporal data from the Moderate Resolution Imaging Spectroradiometer (MODIS) to improve current information related to regional forest cover change and urban extent. In the first element of this dissertation, I develop a novel distance metric-based change detection method to map annual forest cover change at 500m spatial resolution. Evaluations based on a global network of test sites and two regional case studies in Brazil and the United States demonstrate the efficiency and effectiveness of this methodology, where estimated changes in forest cover are comparable to reference data derived from higher spatial resolution data sources. In the second element of this dissertation, I develop methods to estimate fractional urban cover for temperate and tropical regions of China at 250m spatial resolution by fusing MODIS data with nighttime lights using the Random Forest regression algorithm. Assessment of results for 9 cities in Eastern, Central, and Southern China show good agreement between the estimated urban percentages from MODIS and reference urban percentages derived from higher resolution Landsat data. In the final element of this dissertation, I assess the capability of a new nighttime lights dataset from the Visible Infrared Imaging Radiometer Suite (VIIRS) Day/Night Band (DNB) for urban mapping applications. This dataset provides higher spatial resolution and improved radiometric quality in nighttime lights observations relative to previous datasets. Analyses for a study area in the Yangtze River Delta in China show that this new source of data significantly improves representation of urban areas, and that fractional urban estimation based on DNB can be further improved by fusion with MODIS data. Overall, the research in this dissertation contributes new methods and understanding for remote sensing-based change detection methodologies. The results suggest that land cover change products from coarse spatial resolution sensors such as MODIS and VIIRS can benefit from regional optimization, and that urban extent mapping from nighttime lights should exploit complementary information from conventional visible and near infrared observations

Doctor of Philosophy

dissertationChina’s retail sector has undertaken tremendous transformation since its opening to foreign investment in 1992. Retail transnational corporations have expanded rapidly in this emerging market. Yet relatively little is known about how they have embedded in the Chinese market and expanded spatially and temporally. China has experienced unprecedented urbanization since the onset of economic reform in 1978. Dramatic land use and land cover (LULC) change and urban expansion have taken place in the past three decades. Detailed time-series analysis of LULC change and urban growth in Chinese cities is still scant. This dissertation focuses on the expansion of foreign hypermarket retailers in China and the urban growth in one Chinese city, Suzhou. This research analyzes the penetration strategy and local embeddedness of foreign hypermarket retailers, examines their spatial inequality and dynamics at different geographical levels, and identifies their location determinants through binary logistic regression models. This study applies random forest classification to multitemporal Landsat Thematic Mapper (TM) images of Suzhou for LULC change analysis, employs landscape metrics and Geographic Information System (GIS) analysis to investigate urban growth patterns, and develops global and local logistic regression models to identify determinants of urban growth. The results indicate that spatiotemporal expansion of foreign hypermarket retailers has been largely dictated by the gradual liberalization policy of the Chinese government. Their local embeddedness has been impacted by both home and host economies. Relative gaps in foreign hypermarkets among three macro regions are narrowing while absolute gaps are widening. Provincial foreign hypermarket distribution has shown significant clustering in the Yangtze River Delta since 2005. Their distribution in Shanghai has changed from dispersion to intensified clustering and shown a clear trend of suburbanization. This study confirms that the random forest algorithm can effectively classify the heterogeneous landscape in Suzhou and LULC change has accelerated from 1986 to 2008. Three urban growth types, edge-expansion, infilling, and leapfrog are identified. Compared with the global model, the geographically weighted logistic regression model has overall better goodness-of-fit and provides more insights to spatial variations of the influence of underlying factors on urban growth