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Many novel research algorithms have been developed to analyze urban heat island (UHI) and UHI regional impacts (UHIRIP) with remotely sensed thermal data tables. We present a comprehensive review of some important aspects of UHI and UHIRIP studies that use remotely sensed thermal data, including concepts, datasets, methodologies, and applications. We focus on reviewing progress on multi-sensor image selection, preprocessing, computing, gap filling, image fusion, deep learning, and developing new metrics. This literature review shows that new satellite sensors and valuable methods have been developed for calculating land surface temperature (LST) and UHI intensity, and for assessing UHIRIP. Additionally, some of the limitations of using remotely sensed data to analyze the LST, UHI, and UHI intensity are discussed. Finally, we review a variety of applications in UHI and UHIRIP analyses. The assimilation of time-series remotely sensed data with the application of data fusion, gap filling models, and deep learning using the Google Cloud platform and Google Earth Engine platform also has the potential to improve the estimation accuracy of change patterns of UHI and UHIRIP over long time periods. [ABSTRACT FROM AUTHOR]

As a result of urbanization, natural surfaces are replaced by artifcial surfaces that trap heat such as buildings, pavements and asphalt, so residential areas have higher temperature values than rural areas. This effect, defned as the urban heat island, causes an increase not only in air temperature but also in the subsurface and groundwater. Groundwater temperature values were measured during one year in an area approximately 53 km2 consisting of different types of settlement areas to determine the urban heat island effect on the subsurface of Kütahya. As a result of the measurements, urban heat island maps were prepared. It was observed that the groundwater temperature anomalies increased towards the urban/industrial areas. The difference of groundwater temperature in urban/rural areas reached up to 7°C by well. This heat energy increasing with the effect of urban heat island can be used in the heating processes of buildings by utilizing systems called "shallow geothermal energy". For this reason, the heat potential of the alluvial aquifer under Kütahya was calculated. The theoretical heat potential values of the this aquifer range between 1.64 x 1013 kJ K-1 and 5.55 x 1013 kJ K-1 with a mean value of 3.50 x 1013 kJ K-1. It is thought that urban heat island maps and the heat potential calculations of the aquifers may be important parameters for applicability of shallow geothermal systems in the city center of Kütahya. [ABSTRACT FROM AUTHOR]

This paper presents an impact of hydro-meteorological extreme events and urban catchment to water quality in small rivers in Białystok (Poland). The results from a five-year study have taken into account droughts, continuous precipitation, and storm precipitation causing flash floods. Extreme hydro-meteorological events has a different impact on the physical and chemical parameters of water. It was found that the largest change in water quality occurs on the 2nd day after the rainfall and changed concentration of some chemical parameters persists for a long time. The majority but, what's important, not all of them are diluted after floods and concentrated after droughts. Flash flooding results in a large increase concentrations of DOC and selected forms of phosphorus. Higher values of EC, Eh, Mg2+, HCO3-, Cl-, SiO32-, NO3-N, TN were observed during drought compared to the average values from 2014–2018. A high degree of naturalness of the river valley and increased water retention results in a decreased concentration of NH4+-N, DOC and phosphorus forms. The buffer zone plays an important role in limiting the inflow of pollutants and nutrients from the catchment area. That is why it is worth undertaking restoration of river valleys in urban areas. [ABSTRACT FROM AUTHOR]

Anthropogenic activities, by far the largest source of NOx into the atmosphere, induce a weekly cycle of NO2 abundances in cities. Comprehensive analysis of the 2005–2017 OMI NO2 dataset reveals significant weekly cycles in 115 of the 274 cities considered. These results are corroborated by a full year of high-resolution TROPOMI NO2 observations. The OMI dataset permits us to identify trends in the weekly cycle resulting from NOx emissions changes. The data show a clear weakening of the weekly cycle over European and U.S. cities, an evolution attributed to the decline in anthropogenic emissions and the resulting growing importance of background NO2, whereas NO2 lifetime changes also play a minor role. In particular, the Sunday NO2 columns averaged over all U.S. cities are found to increase, relative to the weekly average, from 0.72 during 2005–2007 to 0.88 in 2015–2017. The opposite tendency is recorded in regions undergoing rapid emission growth. Multiyear simulations over the U.S. and the Middle East using the chemistry-transport model MAGRITTEv1.1 succeed in capturing the observed weekly cycles over the largest cities, as well as the observed long-term trends in the weekly cycle. [ABSTRACT FROM AUTHOR]

Cool roof is the technique that delivers higher solar reflectance and higher thermal emittance than standard roofing products. Its fastest developing applications in the built environment comes with various benefits, such as reducing the urban heat island effect by decreasing surface temperatures, which reduces the flow of heat into the atmosphere, and offsetting warming caused by greenhouse gases. In this study, a Cool Coating Paint has been experimented while the impact was measured in terms of an integration with the Solar PV technology. This research investigated cool roof applications on building's rooftop together with PV panels for the Middle East climatic conditions, and its impact on the electricity generation. The preliminary findings of the experimental study indicated that there is a likely impact of 5–10% improvement of electricity generation with the cool roof applications. [ABSTRACT FROM AUTHOR]

In this work an Operational Street Pollution Model was used to define the minimum number and the expected position of the stations for an air quality network with three monitoring stations to be installed in Battipaglia (Italy). The features of the urban background, the type of daily traffic, all the meteorological parameters typical of the investigated area, were implemented in the software to simulate the hourly emissions. These allowed to determine the feasible number of air sampling station and their best location points. [ABSTRACT FROM AUTHOR]

To keep up with world Rapid population growth in many countries including Egypt, the Egyptian government adopted polices to establish new urban communities, which many of them located in severe conditions of hot arid climate. However, the urban plans of those new cities do not prioritize the local climate considerations in its planning, which negatively effect on the thermal performance of urban spaces. In recent decades, greater attention was given to study the relationship between urban features and the local climate, developing mitigation and adaptation strategies with the aim of improving the thermal performance of urban spaces. So, this study aims to formulate a matrix of guidelines for urban heat islands mitigation strategies concerning urban geometry that can be helpful in improving the thermal performance of outdoor spaces in the existing new Egyptian cities -which allocated in hot arid climate zone, to enhance thermal comfort in these spaces. To achieve this goal, a comprehensive review, and analysis of the impacts of different urban geometrical thermal mitigation strategies on outdoor spaces in hot-arid climate, is presented. The geometrical variables of urban spaces which have been investigated in the reviewed researches classified into two main groups (squares and plazas, canyons). The geometrical variables of squares and plazas include; side compactness, and Sky View Factor (SVF). Canyons geometrical variables are; SVF, aspect ratio and side profile shape. These variables depend on the features of those spaces which resulting from the urban pattern form and geometry. These guided values have been applied theoretically and practically on three real cases, to illustrate the mechanism of matrix guidelines applying on urban outdoor spaces thermal behavior initial evaluation and determine the most suitable environmental mitigation strategies directly. Applying of guidelines help in mitigating thermal behavior of plaza with about 18.73 k degree and the canyon space with 3.28 k degree. The discussion of this research clearly reflects the importance of urban planning guidelines that can be applied to help enhancing outdoor thermal comfort. This study is useful in controlling the climatic consequences of urban planning at an early stage. [ABSTRACT FROM AUTHOR]

Abstract This paper develops a new paradigm to analyze the eco-efficiency of Yangtze River Economic Belt (YREB) in China and makes a first empirical attempt at examining whether the eco-efficiency in urban agglomerations (UA-s) outperform Non-urban agglomerations (Non-UA-s), or driving the Non-UA-s in promoting eco-efficiency using a dataset of 108 prefectural-level cities during 2003–2014. The main findings are as follows. First, the eco-efficiency of YREB gradually increases during the study period. Cities in UA-s with higher eco-efficiency experience an increasing spatial agglomeration while those in Non-UA-s show a slight downward shift. Second, in terms of eco-efficiency, both statistical test and econometrical test confirm that cities in UA-s outperform those in Non-UA-s. Third, the global and club convergence of eco-efficiency in YREB is ascertained. Forth, the eco-efficiency of UA-s exerts backwash effects on those in Non-UA-s, along with decreasing the convergence speed of eco-efficiency. Special issues are briefly discussed, lastly. Highlights • A new analysis paradigm is developed to explore the YREB's eco-efficiency. • Temporal-spatial evolution and empirical tests are conducted, indicating a proof that eco-efficiency in urban agglomerations outperform that in Non-urban agglomerations. • Urban agglomerations have backwash effects and slight constraints to Non-urban agglomerations in terms of eco-efficiency. • Some special issues are discussed. [ABSTRACT FROM AUTHOR]

Abstract As a major consumer of fossil fuels, the transportation sector in Shanghai presents a wide range of problems, including air pollution, noise, and traffic congestion. This study aims to explore the energy substitution effect based on a trans-log production function to evaluate the contribution of each input factor to sectoral output, and reveal the substitution possibilities between capital, labor, and energy. To deal with a multicollinearity problem, we adopt ridge regression to obtain the coefficient of each variable under the appropriate penalty value. The bootstrap method is used for making statistical inferences, and the 95% confidence interval is obtained with 1000 bootstrap samples. The empirical results demonstrate the following. (1) The output elasticities of capital (0.13–0.15), labor (0.24–0.25), and energy (0.43–0.48) are positive and show an increasing trend over the study period. (2) The substitution elasticity between labor and energy is the highest among the input factors (around 1.0095), with a slight decreasing trend. (3) The substitution elasticity between energy and capital ranges from 1.0018 to 1.0021, and the substitution elasticity between capital and labor is infinitely close to 1. Graphical abstract Image 1 Highlights • We analyze the energy substitution effect of Shanghai's transportation sector. • Elasticity of substitution between energy and labor trended down during 2000–2014. • Substitution between energy and labor can occur by mechanization and automation. • Elasticity of substitution between energy and capital ranges from 1.0018 to 1.0021. • Energy consumption can be cut by increasing capital inputs. [ABSTRACT FROM AUTHOR]

Abstract China has become the world's largest energy consumer, accounting for approximately 30% of global CO 2 emissions. City contributions make up 84% of China's commercial energy consumption. However, energy consumption data for most Chinese cities are not accessible. Many studies have focused on the estimation of carbon emissions at the provincial or national level; city-level carbon emissions are not well studied. In order to solve this problem, this research constructed a top-bottom method for city-scale energy-related carbon emissions estimation in China. Typically, cities are considered the constituent units of a province. Relying on provincial energy balance tables and utilizing the available city-level socioeconomic data as indicators, we scaled down provincial energy consumption to the city level. We compared our estimation results with city-level point-source data, and found that for the 41 Chinese cities to which we applied this method, the difference was within 10%, while for 25 of these cities, the difference was within 5%. Thus, we believe our method is reasonably accurate. We also subdivided the city carbon emissions into three major energy categories (coal-related, oil-related, and gas-related) and found that the difference could be attributed mainly to coal-related energy emissions. The results of the uncertainty analysis indicated that the uncertainty of the coal emission factor was the largest, thus demonstrating that it is critical not only to choose appropriate indicators to characterize coal-based industrial carbon emissions, but also to identify accurate emission factors for coal-related fossil fuels. Both analyses demonstrated China's coal-dominant energy structure. We believe our method is practical and can provide detailed data support for the establishment of city-level carbon emission inventories, furthermore, it will also be helpful for Chinese cities to negotiate carbon reduction responsibilities and allocating carbon reduction tasks. Highlights • A new city-scale CO2 emission estimation method was proposed. • Spatial differences of energy consumption in three different regions were analyzed. • Uncertainties caused by three types of fossil fuels' emission factors were analyzed. • City CO2 emission data was provided for formulating climate policies. [ABSTRACT FROM AUTHOR]

The data of lightning flash density, total rainfall, surface temperature, surface humidity, convective available potential energy (CAPE) and particulate matter up to 10 μm in size (PM 10 ) over Nanning, China from July 2009 to December 2017 were studied on a yearly/monthly/hourly scale. It was found that the correlation between lightning and precipitation varies in various seasons, and the influencing factors of lightning/precipitation are different in various seasons. CAPE is the most important influencing factor of lightning on an hourly scale. Quantitative analysis showed the joint effects of surface temperature, surface humidity, CAPE and PM 10 on lightning. For dry cases, lightning increases with increasing PM 10 for the low value of PM 10 , and decreases with increasing PM 10 for the high value of PM 10 . While the situation is the opposite for wet cases. It was also found that surface temperature and CAPE can affect the correlation between aerosol and lightning. [ABSTRACT FROM AUTHOR]

Changes in climate extremes are studied based on the daily precipitation in North Sikkim Himalaya. The Coupled Model Intercomparison Project Phase 5 (CMIP5) Global Climate Models GCMs) and their Representative Concentration Pathways (RCPs) and India Meteorological Department (IMD) daily precipitation dataset are used for future and observed time periods, respectively. The purpose of this study is to examine the copula-based probabilistic behavior of precipitation extremes over the eastern Himalayan region. Seven extreme combinations were developed based on the eight defined precipitation indices. The extreme combination designates the duration, frequency and amount of heavy and weak precipitation in the same year. Statistical downscaling model (SDSM) and copulas are used for downscaling and bivariate behavior of precipitation extremes, respectively. Trend analysis result exhibits that the precipitation and its extremes (intensity, wet days, heavy precipitation days and very heavy precipitation days) are increasing significantly during 2006–2100. The spatial distributions of joint return period (JRP) of (T5, T10 and T20) marginal values are quite same during 1979–2005. In addition, the co-occurrences of heavy and weak precipitation would be more frequent in future, resulting higher risk of floods and droughts within the same year. The North Sikkim region may be at high risk of floods because precipitation extremes are increasing along with co-occurrence of flood and drought in the same year. [ABSTRACT FROM AUTHOR]

Drought severity in regions North and Northwest of Rio de Janeiro state (SRJ) was evaluated using the Standardized Precipitation Index (SPI) for the monthly (SPI-1) and annual (SPI-12) scales, as well as its relationship with El Niño - Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). Data of 14 rainfall stations from a time series considering the period of 1967–2013 was used. The SPI calculation was based on the SCI package available at R software version 3.4.2 library. SPI categories used are Very Dry, Moderately Dry and Extremely Dry associated with the hot and cold phases of the PDO, followed by ENSO events according to the Oceanic Niño index (ONI) in El Niño region 3.4 using an interaction matrix. The matrix was evaluated by the coefficients of Kendall ( τ ), Sperman ( ρ ), Pearson ( r ) and R 2 determination, followed by Willmott's concordance index ( d ), Standard Error of Estimation ( SEE ) and Student's t- test. The intense activity of La Niña in the cold 1st phase of the PDO increased rainfall with greater intensity in the Northwest region compared to the North. In the 2nd cold phase of the PDO, the events of El Niño, La Niña and Neutral years of the ENSO mutually contribute to the changes in rainfall regime of both regions. The most frequent SPI categories are Moderately Dry and Extremely Dry. SPI-1 was efficient in perceiving extreme droughts, while SPI-12 results were not significant in the revealing of extreme droughts. In addition, there was no relational pattern through statistical indexes between droughts detected by SPI, ENSO and PDO. Nevertheless, when ENSO cycles were persistent within both phases of the PDO, droughts occurred, mainly on the monthly scale. [ABSTRACT FROM AUTHOR]

Developing reliable frameworks to estimate the potential of CO 2 emission abatement and its associated costs merits urgent attention. This study aims to estimate the potential as well as macroeconomic costs of CO 2 emission abatement in Beijing. Using the industrial economy as the basis, multiobjective programming and genetic algorithm are integrated into the input–output analysis. Several important findings have been gathered in the study: (1) The abatement cost varies between $259.97 and $535.46 per ton at different rates of economic growth. (2) A reinforced emission abatement target can induce higher macroeconomic costs. (3) An inverse U-shaped relationship between CO 2 reduction cost and GDP growth rate was found. When GDP growth rate is above the threshold value of 7%, marginal abatement costs decrease rapidly in parallel with GDP growth. When the GDP growth rate is below 7%, the marginal abatement cost increases significantly with economic growth. (4) Industries that have the highest and least potential of abatement have been identified. For effectively reducing CO 2 emissions, Beijing needs to promote economic restructuring to maximize the potential of emission abatement and also fulfil the emission abatement target in a cost-effective way. This paper provides a quantitative approach to rationalize the policy design process of enacting emission targets and recommends cost-effective abatement strategies. [ABSTRACT FROM AUTHOR]

PM 2.5 samples were collected simultaneously at three urban sites including Beijing (BJ), Tianjin (TJ), Shijiazhuang (SJZ) and one background site Xinglong (XL) from June 2014 till April 2015. Typical polar organic aerosol tracers including 2-methylglyceric acid, 2-methyltetrols, 3-hydroxyglutaric acid, anhydrous saccharides and phthalic acid were analyzed by gas chromatography-mass spectrometry. Both Isoprene secondary organic aerosol (SOA) tracers and pinene SOA tracers had higher mass concentrations at background site than those at urban sites. But they showed different seasonal variations. The former had the highest mass concentration in summer while the latter had the highest mass concentration in spring. Anhydrous saccharides and phthalic acids at urban sites had higher mass concentrations than those at background site and showed higher mass concentration in autumn and winter, respectively. Corresponding estimated secondary organic carbons (SOCs) showed similar variation trends with tracers. In general, biogenic sources had more influence on background site while urban sites were more affected by anthropogenic sources. [ABSTRACT FROM AUTHOR]

Background Despite high fish consumption levels of Hong Kong residents, little is known about the MeHg exposure levels of Hong Kong high-risk populations (i.e. young children and women of childbearing age). Objectives To investigate the MeHg levels in fish commonly consumed in Hong Kong and assess the exposure levels of local kindergarten children and women of childbearing age. Methods A community-based survey was conducted in randomly recruited local kindergartens. The MeHg concentrations of the most commonly consumed fish items were measured. Based on their fish consumption data, subjects’ MeHg exposure levels were estimated and compared with the reference dose (RfD) set by U.S. Environmental Protection Agency. Results A total of 2917 mother-child pairs were recruited. The MeHg levels of the fish samples ranged from < 2–1498.7 ng/g. Six frozen cod fish samples contained MeHg levels exceeding the local legal limit of 500 ng/g. The median estimated MeHg intake for children and mothers were 0.29 and 0.22 µg/kg bw/wk, respectively. Approximately 16% children and 9% mothers exceeded the RfD. Conclusions Apart from frozen cod fish, most fish species commonly consumed in Hong Kong had low MeHg content. Although the majority of our subjects were exposed to low MeHg levels, high fish consumers could still exceed the RfD and are potentially at risk of MeHg toxicity. To avoid excessive MeHg exposure, we suggest that young children and their mothers may consume a variety of locally available fish, but avoid consumption of frozen cod fish. [ABSTRACT FROM AUTHOR]

China suffers from severe hazy conditions, and the central government has introduced a mandatory target responsibility system to curb haze pollution. It is of policy importance to explore whether the mandatory target responsibility system is effective at improving the performance of environmental governance in China. However, studies have tended to ignore the impact of mandatory targets on PM 2.5 concentration control. To fill this gap, this study, based on a nationwide dataset of 267 Chinese cities, applies a novel two-stage regression approach to identify the causal relationship between mandatory targets and PM 2.5 concentration reduction by solving the endogeneity bias. The results demonstrate that a 1% increase in mandatory PM 2.5 performance targets helped reduce the annual average PM 2.5 concentrations by 0.5283 μg/m 3 on average after nearly 2 years of implementation. Moreover, the PM 2.5 concentrations of Chinese cities showed strong positive spatial dependence, and when spatial dependence is controlled, the average marginal impact of mandatory targets on PM 2.5 concentration reduction decreased to 0.1998 μg/m 3 . This research confirms the spatial agglomeration of PM 2.5 concentrations across Chinese cities and highlights the effectiveness of the mandatory target responsibility system for the control of China's haze pollution. [ABSTRACT FROM AUTHOR]

The North China Plain (NCP) has experienced frequent severe haze pollution events in recent years. While extensive measurements have been made in megacities, aerosol sources, processes, and particle growth at urban downwind sites remain less understood. Here, an aerosol chemical speciation monitor and a scanning mobility particle sizer, along with a suite of collocated instruments, were deployed at the downwind site of Xingtai, a highly polluted city in the NCP, for real-time measurements of submicron aerosol (PM1) species and particle number size distributions during May and June 2016. The average mass concentration of PM1 was 30.5 (±19:4) µgm-3, which is significantly lower than that during wintertime. Organic aerosols (OAs) constituted the major fraction of PM1 (38 %), followed by sulfate (25 %) and nitrate (14 %). Positive matrix factorization with the multilinear engine version 2 showed that oxygenated OA (OOA) was the dominant species in OA throughout the study, on average accounting for 78% of OA, while traffic and cooking emissions both accounted for 11% of OA. Our results highlight that aerosol particles at the urban downwind site were highly aged and mainly from secondary formation. However, the diurnal cycle also illustrated the substantial influence of urban emissions on downwind sites, which are characterized by similar pronounced early morning peaks for most aerosol species. New particle formation and growth events were also frequently observed (58% of the time) on both clean and polluted days. Particle growth rates varied from 1.2 to 4.9 nm h-1 and our results showed that sulfate and OOA played important roles in particle growth during clean periods, while OOA was more important than sulfate during polluted events. Further analyses showed that particle growth rates have no clear dependence on air mass trajectories. [ABSTRACT FROM AUTHOR]

The rapid mass increase of atmospheric nitrate is a critical driving force for the occurrence of fine-particle pollution (referred to as haze hereafter) in Beijing. However, the exact mechanisms for this rapid increase of nitrate mass have not been well constrained from field observations. Here we present the first observations of the oxygen-17 excess of atmospheric nitrate (Δ17O(NO-3)) collected in Beijing haze to reveal the relative importance of different nitrate formation pathways, and we also present the simultaneously observed δ15N(NO-3). During our sampling period, 12 h averaged mass concentrations of PM2.5 varied from 16 to 323 µgm-3 with a mean of (141±88(1SD)) µgm-3. The observed Δ17O(NO-3) ranged from 27.5% to 33.9% with a mean of (30.6±1.8) %, while δ15N(NO-3) ranged from -2.5 % to 19.2% with a mean of (7.4±6.8)%. Δ17O(NO-3)-constrained calculations suggest nocturnal pathways (N2O5 CH2O=Cl- and NO3 CHC) dominated nitrate production during polluted days (PM2.5 ≥ 75 µgm-3), with a mean possible fraction of 56-97 %. Our results illustrate the potentiality of Δ17O in tracing nitrate formation pathways; future modeling work with the constraint of isotope data reported here may further improve our understanding of the nitrogen cycle during haze. [ABSTRACT FROM AUTHOR]

In an attempt to take effective action towards mitigating pollution episodes in Athens, precise knowledge of PM2.5 composition and its sources is a prerequisite. Thus, a 2-year chemical composition dataset from aerosol samples collected in an urban background site in central Athens from December 2013 to March 2016 has been obtained and a positive matrix factorization (PMF) was applied in order to identify and apportion fine aerosols to their sources. A total of 850 aerosol samples were collected on a 12 to 24 h basis and analyzed for major ions, trace elements, and organic and elemental carbon, allowing us to further assess the impact of residential heating as a source of air pollution over Athens. The ionic and carbonaceous components were found to constitute the major fraction of the PM2.5 aerosol mass. The annual contribution of the ion mass (IM), particulate organic mass (POM), dust, elemental carbon (EC), and sea salt (SS) was calculated at 31 %, 38 %, 18 %, 8 %, and 3 %, respectively, and exhibited considerable seasonal variation. In winter, the share of IM was estimated down to 23 %, with POMC EC being the dominant component accounting for 52% of the PM2.5 mass, while in summer, IM (42 %) and carbonaceous aerosols (41 %) contributed almost equally. Results from samples collected on a 12 h basis (day and night) during the three intensive winter campaigns indicated the impact of heating on the levels of a series of compounds. Indeed, PM2.5, EC, POM, NO-3, C2O2-4, non sea salt (nss) K+ and selected trace metals including Cd and Pb were increased by up to a factor of 4 in the night compared to the day, highlighting the importance of heating on air quality in Athens. Furthermore, in order to better characterize wintertime aerosol sources and quantify the impact of biomass burning on PM2:5 levels, source apportionment was performed. The data can be interpreted on the basis of six sources, namely biomass burning (31 %), vehicular emissions (19 %), heavy oil combustion (7 %), regional secondary (21 %), marine aerosols (9 %), and dust particles (8 %). Regarding night-to-day patterns their contributions shifted from 19 %, 19 %, 8 %, 31 %, 12 %, and 10% of the PM2.5 mass during day to 39 %, 19 %, 6 %, 14 %, 7 %, and 7% during the night, underlining the significance of biomass burning as the main contributor to fine particle levels during nighttime in winter. [ABSTRACT FROM AUTHOR]

The air quality of the Texas Gulf Coast region historically has been influenced heavily by regional shipping emissions. However, the effects of the recently established North American Emissions Control Area on aerosol concentrations and properties in this region are presently unknown. In order to better understand the current sources and processing mechanisms influencing coastal aerosol near Houston, a high-resolution time-of-flight aerosol mass spectrometer (HR-ToF-AMS) was deployed for 3 weeks at a coastal location during May-June 2016. Total mass loadings of organic and inorganic non-refractory aerosol components during onshore flow periods were similar to those published before establishment of the regulations. Based on estimated methanesulfonic acid (MSA) mass loadings and published biogenic MSA/ non-sea-salt sulfate (nss-SO4) ratios, an average of over 75% of the observed nss-SO4 was from anthropogenic sources, predominantly shipping emissions. Mass spectral analysis indicated that for periods with similar backwardtrajectory-averaged meteorological conditions, air masses in- fluenced by shipping emissions had an increased mass fraction of ions related to carboxylic acids and larger oxygen-tocarbon ratios than those that avoided shipping lanes, suggesting that shipping emissions increase marine organic aerosol (OA) oxidation state. Amine fragment mass loadings were correlated positively with anthropogenic nss-SO4 during onshore flow, implying anthropogenic--biogenic interaction in marine OA production. Model calculations also suggest that advection of shipping-derived aerosol may enhance inland aqueous-phase secondary OA production. These results imply a continuing role of shipping emissions on aerosol properties over the Gulf of Mexico and suggest that further regulation of shipping fuel sulfur content will reduce coastal submicron aerosol mass loadings near Houston. [ABSTRACT FROM AUTHOR]

Presents a series of photographs taken in May 1992 during a trip to the province of Chelyabinsk by a group of 23 activists and professionals, and a conference arranged by Russian environmentalists to call attention to the damage caused by nearly 50 years of bomb work. Providing information on monitoring the environment and pushing bureaucracy to clean up the mess; Wastes dumped in the area; Chelyabinsk people becoming more assertive; History of the area; Contradictions.

Bogota is a Latin American megacity located at an average altitude of 2600 m in the tropical Andes. It registers frequent episodes of poor air quality due to high PM 10 concentrations. The carbonaceous fraction is the main PM 10 component (>50%), but there is a lack of specific studies analyzing the characteristics and temporal variability of organic carbon (OC) and elemental carbon (EC) aerosols. In this study, daily samples (24±1h) were collected from June 2015 to May 2016 (a total of 308 samples) at an urban background site during an El Niño year, and the quartz filters were analyzed using a thermal-optical method. Results showed that EC and organic matter accounted for ~60% of the PM 10 mass. The OC and EC averages were 8.92 ± 4.52 μg/m 3 and 3.25 ± 1.59 μg/m 3 , respectively. The months with the highest average OC values were January to March, while EC concentrations were relatively constant throughout the year. Regarding daily values, the highest mean concentrations of OC (10.2 ± 5.13 μg/m 3 ) and EC (3.73 ± 1.74 μg/m 3 ) were obtained on Thursdays, and the lowest on Sundays (OC = 6.67 ± 3.04 μg/m 3 and EC = 2.46 ± 0.94 μg/m 3 ). The OC/EC ratio ranged from 1.66 (June) to 4.88 (March), with an annual average of 3.16 ± 2.01. The secondary organic carbon (SOC) contributions, measured using the EC-tracer method, accounted for 45% of the total OC. The effective carbon ratio, which indicates an association between carbonaceous particles and climate change, ranged from 0.12 (July) to 0.74 (May). The study of air-mass origins revealed that days with air mass from E + NE registered the highest OC concentrations. This research provides new data on the variability of carbonaceous aerosols over the course of a year. It also highlights forest fires as a significant source of OC and EC, and indicates the high impact of SOC on OC concentration at the sampling site. [ABSTRACT FROM AUTHOR]

Observational black carbon (BC) data are needed at high resolution in vast areas to better study the climatic and environmental effect of BC aerosols. The BC concentration from Shanghai to Arctic Ocean was measured with an aethalometer (AE31) by the 7th Chinese National Arctic Research Expedition (CHINARE) during July to September 2016. A generally decreasing distribution of BC was shown from mid to high latitudes. The average BC concentration of the 7th CHINARE was higher than previous expeditions, at 22.77 ng m −3 in the Arctic Ocean. Moreover, we found heavy BC aerosols appearing occasionally during the CHINARE navigation. Therefore the impact of terrestrial transport was discussed based on the Arctic Transport Potential model. It was found that air pollution sources such as fires in the Arctic Circle of Eurasia could lead to BC transport to the high Arctic, inducing a high BC concentration of 95.62 ng m −3 . [ABSTRACT FROM AUTHOR]

Fine urban aerosol particles with aerodynamic equivalent dimeter ≤2.5 μm (PM 2.5 ) were collected in Mainz (a city within the Rhine-Main area, the third largest metropolitan region in Germany) and Beijing (Chinese megacity). A solvent mixture of acetonitrile-water was used to extract the organic aerosol fraction (OA) from the particle samples. The extracts were analyzed by an ultrahigh resolution mass spectrometer (UHRMS) Orbitrap coupled with ultra-high-performance liquid chromatography (UHPLC) both in the negative and positive ion mode. The number of compounds observed in Beijing is a factor of 2–10 higher compared to Mainz. The clear differences on chemical composition of OA in the two cities were observed. The majority of organics in Beijing OA is characterized by lower elemental H/C and O/C ratio but a higher degree of unsaturation and a larger aromaticity equivalent (X C ) compared to Mainz OA, suggesting that aromatics, which are related to direct combustion compounds (e.g., oxidized polycyclic aromatic hydrocarbon (PAH)), play an important role for OA in Beijing. A significant number of organosulfates (OSs) with long-carbon chain and low degree of unsaturation were observed in Beijing OA, indicating that long-chain alkanes emitted by vehicle might be their precursors. [ABSTRACT FROM AUTHOR]

Background Epidemiologic studies of PM 2.5 (particulate matter with aerodynamic diameter ≤2.5 μm) and black carbon (BC) typically use ambient measurements as exposure proxies given that individual measurement is infeasible among large populations. Failure to account for variation in exposure will bias epidemiologic study results. The ability of ambient measurement as a proxy of exposure in regions with heavy pollution is untested. Objective We aimed to investigate effects of potential determinants and to estimate PM 2.5 and BC exposure by a modeling approach. Methods We collected 417 24 h personal PM 2.5 and 130 72 h personal BC measurements from a panel of 36 nonsmoking college students in Shanghai, China. Each participant underwent 4 rounds of three consecutive 24-h sampling sessions through December 2014 to July 2015. We applied backwards regression to construct mixed effect models incorporating all accessible variables of ambient pollution, climate and time-location information for exposure prediction. All models were evaluated by marginal R 2 and root mean square error (RMSE) from a leave-one-out-cross-validation (LOOCV) and a 10-fold cross-validation (10-fold CV). Results Personal PM 2.5 was 47.6% lower than ambient level, with mean (±Standard Deviation, SD) level of 39.9 (±32.1) μg/m 3 ; whereas personal BC (6.1 (±2.8) μg/m 3 ) was about one-fold higher than the corresponding ambient concentrations. Ambient levels were the most significant determinants of PM 2.5 and BC exposure. Meteorological and season indicators were also important predictors. Our final models predicted 75% of the variance in 24 h personal PM 2.5 and 72 h personal BC. LOOCV analysis showed an R 2 (RMSE) of 0.73 (0.40) for PM 2.5 and 0.66 (0.27) for BC. Ten-fold CV analysis showed a R 2 (RMSE) of 0.73 (0.41) for PM 2.5 and 0.68 (0.26) for BC. Conclusion We used readily accessible data and established intuitive models that can predict PM 2.5 and BC exposure. This modeling approach can be a feasible solution for PM exposure estimation in epidemiological studies. [ABSTRACT FROM AUTHOR]

Aerosol size distributions were measured using a scanning mobility particle sizer (SMPS), and also PM 1 (particulate matter ≤ 1 μm in aerodynamic diameter) samples were collected in parallel at a representative site in New Delhi during spring in 2013 and 2014. Based on the temporal variation of particle count mean diameter (CMD), sampling periods are characterized as growth events and non-growth events. Particle size distribution measurements suggest that some consecutive nights experienced unique nighttime subsequent growth of particles, which sustained for a longer period. Average particle growth rate measured during growth events was 5.64 ± 3.03 nm h −1 . Atmospheric trace gas concentrations and meteorological data show that these growth events (nighttime) are influenced by higher concentrations of gases, e.g., NO 2 (56.5 ± 29.7 μg m −3 ), SO 2 (9.34 ± 1.14 μg m −3 ) and RH (45.7 ± 9.5%) than those of non-growth events (daytime) (37.9 ± 18.6 μg m −3 , 7.19 ± 2.08 μg m −3 and 37.7 ± 6.9%, respectively). Further, analysis of PM 1 samples collected during the study period shows that the particulate water-soluble organic carbon (WSOC) (12.7 ± 4.1 μg m −3 ), NH 4 + (9.4 ± 3.2 μg m −3 ), SO 4 2− (2.03 ± 0.70 μg m −3 ), K + (1.06 ± 0.40 μg m −3 ), and NO 2 − + NO 3 − (0.59 ± 0.36 μg m −3 ) are the major contributors of particulate mass, wherein NH 4 + , SO 4 2− , K + , NO 2 − + NO 3 − mass concentrations were higher during growth events. Correlation study shows that nighttime aerosol composition during growth (in sub-micron range) events are more enriched by inorganic species (i.e., NH 4 NO 3 , (NH 4 ) 2 SO 4 and H 2 SO 4 vapors) as compared to organics (i.e., WSOC, does not show much difference in growth events and non events). Our results suggest that nighttime sulfate formation at the site is mostly mediated by high NO 2 and NH 3 at elevated RH. For the formation of sulfate and other inorganic species, a nighttime atmospheric chemistry is proposed, which is linked to particle growth. Growth events observed typically in nighttime have both biomass burning and anthropogenic influences as indicated by high concentrations of WSOC, K + and black carbon in PM 1 and carbon monoxide in gas phase. [ABSTRACT FROM AUTHOR]

Classifying “urban” and “rural” environments is a challenge in understanding urban climate, specifically urban heat islands (UHIs). Stewart and Oke developed the “local climate zone” (LCZ) classification system to clarify these distinctions using 17 unique groups. This system has been applied to many areas around the world, but few studies have attempted to utilize them to detect UHI effects in smaller cities. Our aim was to use the LCZ classification system 1) to detect UHI in two small cities in Alabama and 2) to determine whether similar zones experienced similar intensity or magnitude of UHIs. For 1 week, we monitored hourly temperature in two cities, in four zones: compact low-rise, open low-rise, dense forests, and water. We found that urban zones were often warmer for overall, daytime, and nighttime temperatures relative to rural zones (from −0.1° to 2.8°C). In addition, we found that temperatures between cities in similar zones were not very similar, indicating that the LCZ system does not predict UHI intensity equally in places with similar background climates. We found that the LCZ classification system was easy to use, and we recognize its potential as a tool for urban ecologists and urban planners. [ABSTRACT FROM AUTHOR]

While residential coal/biomass burning might be a major and underappreciated emission source for PM2:5, especially during winter, it is not well constrained whether burning solid fuels contributes substantially to ambient volatile organic compounds (VOCs), which are precursors to secondary organic aerosols (SOAs) that typically have a higher contribution to particulate matter during winter haze events. In this study, ambient air samples were collected in 2014 from 25 October to 31 December at a rural site on the campus of the University of Chinese Academy of Sciences (UCAS) in northeastern Beijing for the analysis of VOCs. Since temporary intervention measures were implemented on 3-12 November to improve the air quality for the Asian-Pacific Economic Cooperation (APEC) summit held on 5-11 November in Beijing, and wintertime central heating started on 15 November in Beijing after the APEC summit, this sample collection period provided a good opportunity to study the influence of temporary control measures and wintertime heating on ambient VOCs. As a result of the temporary intervention measures implemented during 3--12 November (period II), the total mixing ratios of non-methane hydrocarbons averaged 11.25 ppb, approximately 50% lower than the values of 23.41 ppb in period I (25 October-2 November) and 21.71 ppb in period III (13 November-31 December). The ozone and SOA formation potentials decreased by ~ 50% and ~ 70 %, respectively, during period II relative to period I, with the larger decrease in SOA formation potentials attributed to more effective control over aromatic hydrocarbons mainly from solvent use. Back trajectory analysis revealed that the average mixing ratios of VOCs in southerly air masses were 2.3, 2.3 and 2.9 times those in northerly air masses during periods I, II and III, respectively; all VOC episodes occurred under the influence of southerly winds, suggesting much stronger emissions in the southern urbanized regions than in the northern rural areas. Based on a positive matrix factorization (PMF) receptor model, the altered contributions from traffic emissions and solvent use could explain 47.9% and 37.6% of the reduction in ambient VOCs, respectively, during period II relative to period I, indicating that the temporary control measures on vehicle emissions and solvent use were effective at lowering the ambient levels of VOCs. Coal/biomass burning, gasoline exhaust and industrial emissions were among the major sources, and they altogether contributed 60.3 %, 78.6% and 78.7% of the VOCs during periods I, II and III, respectively. Coal/biomass burning, mostly residential coal burning, became the dominant source, accounting for 45.1% of the VOCs during the wintertime heating period, with a specifically lower average contribution percentage in southerly air masses (38.2 %) than in northerly air masses (48.8 %). The results suggest that emission control in the industry and traffic sectors is more effective in lowering ambient reactive VOCs in non-heating seasons; however, during the winter heating season reducing emissions from residential burning of solid fuels would be of greater importance and would have health co-benefits from lowering both indoor and outdoor air pollution. [ABSTRACT FROM AUTHOR]

Ulaanbaatar, the capital of Mongolia, is subject to high levels of atmospheric pollution during winter, which severely threatens the health of the population. By analyzing surface meteorological data, ground-based LIDAR data, and radiosonde data collected from 2008 to 2016, we studied seasonal variations in particulate matter (PM) concentration, visibility, relative humidity, temperature inversion layer thickness, and temperature inversion intensity. PM concentrations started to exceed the 24-h average standard (50 μg/m3) in mid-October and peaked from December to January. Visibility showed a significant negative correlation with PM concentration. Relative humidity was within the range of 60-80% when there were high PM concentrations. Both temperature inversion layer thickness and intensity reached maxima in January and showed similar seasonal variations with respect to PM concentration. The monthly average temperature inversion intensity showed a strong positive correlation with the monthly average PM2.5 concentration. Furthermore, the temperature inversion layer thickness exceeded 500 m in midwinter and overlaid the weak mixed layer during daytime. Radiative cooling enhanced by the basin-like terrain led to a stable urban atmosphere, which strengthened particulate air pollution. [ABSTRACT FROM AUTHOR]

Black carbon (BC) particles can have deleterious human health consequences and impact regional and global climate. Uncertainties remain in part due to incomplete knowledge on the evolution of physical properties and mixing state of black carbon from sources to the remote atmosphere. We aim to understand how "road-to-ambient" processing and longer timescale aging in an urban plume affect black carbon physical properties. Refractory black carbon (rBC) was measured during summer 2016 using a singleparticle soot photometer (SP2) in two distinct environments: near a major freeway and downwind of downtown Los Angeles. The near-road measurements were made at distances ranging from 30 to 114m downwind of Interstate 405 in Los Angeles. These results were compared with measurements performed 100 km east of Los Angeles in Redlands, California. Coatings on rBC particles were quantified using two methods. As distance from the highway increased at the nearroad site, we observed decreases in rBC mass and number concentrations and increases in the number fraction of rBC particles with thick coatings (f). The latter likely occurred due to rapid processing of the highway plume and entrainment of urban background particles. Most rBC-containing particles measured near the highway were either uncoated or thinly coated. In Redlands, we found that rBC mass concentrations on weekdays were similar to those observed at the furthest measured distance from the highway (114 m). However, rBC number concentrations for the smallest measured sizes were an order of magnitude lower in Redlands than all measured distances from the highway. Observations of findicate that values in Redlands during periods when estimated photochemical age (PCA) was highest (6-8 h) were similar to corresponding values at the furthest measured distance from the highway. This suggests that the residence time of air in the Los Angeles Basin under typical summertime conditions measured during this campaign may not be sufficient for rBC to acquire thick coatings. However, under certain meteorological conditions, f was observed to be ~ 0:20 in Redlands, with coating thickness histograms showing a larger contribution of rBC particles with coating thickness>80 nm. This occurred during a weekend day when local emissions from diesel vehicles were lower (compared to weekdays) and winds brought air from the desert regions to Redlands, both of which would increase the relative contribution of remote sources of rBC. Afternoon values of f (and O3) were found to be systematically higher on weekends than weekdays, suggesting that the "weekend effect" can create more thickly coated rBC particles presumably due to enhanced secondary organic aerosol (SOA) and reduced available rBC as condensation sites. [ABSTRACT FROM AUTHOR]

Urbanization destroys natural habitats, displaces native ecosystems and results in regional extinction of native species. Urbanization is also argued to cause homogenization during which native species are replaced with non-native species. Negative impact of urbanization on ecosystems and biodiversity is usually focused upon while the fact that high levels of biodiversity may flourish inside cities are frequently ignored. Cities comprise a mixture of remnants of the pre-existing urban habitats and new urban habitats. The remaining fragments of natural landscapes, and other vegetation areas constitute the green infrastructure supporting the biological diversity of cities. Several biotopes such as lawns, hedges, parklands and street trees occur in the cities. In the cities ambient temperatures are higher than those of the surrounding rural areas, exhibiting the phenomenon of urban heat island. Urban vegetation experiences longer growing seasons and exhibits earlier greening than vegetation in the surrounding rural areas. Trees comprise the natural capital assets for cities as they provide immense benefits and ecosystem services for the wellbeing of city dwellers, although there are some disservices also. Studies on urban vegetation are very few in the tropics and particularly in India. In this article we review several aspects of plant diversity in cities in order to sensitize scientists, city managers and lay public to the need for more research on socioeconomic benefits and costs of city vegetation and to augment the vegetation within cities through conservation. [ABSTRACT FROM AUTHOR]

Industrial structures in China's resource-based cities are unlikely to materially change in the short term, and the large quantities of air pollutants emitted by residents' energy consumption cause serious air pollution. It is therefore urgently required to frame policies that can be adopted to realize the sustainable development of a social economy under the constraint of atmospheric environment in China's resource-based cities. In this paper, we develop a dynamic optimization model by using input–output analysis with gross regional product (GRP) maximization as the objective function. This model contains three submodels: the socioeconomic submodel, atmo-environmental control submodel, and energy submodel. The model is applied to Tangshan City, a typical resource-based industrial city, to conduct a dynamic simulation with 13 terms from 2013 to 2025 and based on the data in 2012. The goal for the model operation is to realize the optimal development of a social economy under the restrain of certain emission levels of air pollutants. This goal is achieved by introducing a comprehensive policy that includes a residential clean energy promotion policy and an industry emission reduction policy, and industrial restructuring also plays a role by industrial subsidies. The simulation results demonstrate that sulfur dioxide ( S O 2 ) and nitrogen oxides ( N O x ) can be reduced by 53% and 45%, respectively, in Tangshan City in 2025 compared with their values in 2012 with an annual GRP growth rate of 6.2%. The total output of the clean energy in the simulation period is 41.4 million tons of standard coal. The goal of improving the atmospheric environment and sustainable development of social economies in resource-based cities can be achieved by coordinating the relationship among economic development, atmospheric environmental protection, and energy consumption through a dynamic optimization model with a comprehensive policy and industrial restructuring. [ABSTRACT FROM AUTHOR]

Our study focuses on the carbon emission and mitigation potential in the domain of daily travel in Beijing. Using a sample with the focus on working class, the average individual carbon emissions from daily travel are computed as 1.46 kg/day•person and 2.40 kg/day•person for weekday and weekend. Except for residents who need to conduct more long-distance trips, the main contributor to the emissions of the rest high emitters are not the need of longer daily travel distances or the need to conduct more long distance trips, but the need to use cars more intensively for trips with similar distances compared with low emitters. High emitters are associated with the characteristics of being male, having higher income, owning cars, and being in the age between 30s and 40s. On the other hand, living within fifth ring and having good accessibility to public transport are associated with lower emissions. We innovatively use trip-based information to obtain a more relevant and realistic assessment of mitigation potential through mode shift under the current transport system. The mitigation percentage can be as high as 20%–25% if only travel time is considered, but will be substantially constrained by practical barriers. Therefore mitigation policy for daily transport should not only focus on improving travel time of low emission modes to comparable levels with cars but also tackle practical barriers for car drivers to use low emission modes. [ABSTRACT FROM AUTHOR]

Walkability and livability in cities can be enhanced by creating comfortable environments in the streets. The profile of an urban street canyon has a substantial impact on outdoor thermal conditions at pedestrian level. This paper deals with the effect of asymmetrical street canyon profiles, common in the historical centre of Camagüey, Cuba, on outdoor thermal comfort. Temporal-spatial analyses are conducted using the Heliodon2 and the RayMan model, which enable the generation of accurate predictions about solar radiation and thermal conditions of urban spaces, respectively. On these models, urban settings are represented by asymmetrical street canyons with five different height-to-width ratios and four street axis orientations (N-S, NE-SW, E-W, SE-NW). Results are evaluated for daytime hours across the street canyon, by means of the physiologically equivalent temperature (PET index) which allows the evaluation of the bioclimatic conditions of outdoor environments. Our findings revealed that high profiles (façades) located on the east-facing side of N-S streets, on the southeast-facing side of NE-SW streets, on the south-facing side of E-W street, and on the southwest-facing side of SE-NW streets, are recommended to reduce the total number of hours under thermal stress. E-W street canyons are the most thermally stressed ones, with extreme PET values around 36 °C. Deviating from this orientation ameliorates the heat stress with reductions of up to 4 h in summer. For all analysed E-W orientations, only about one fifth of the street can be comfortable, especially for high aspect ratios (H/W > 3). Optimal subzones in the street are next to the north side of the E-W street, northwest side of the NE-SW street, and southwest side of the SE-NW street. Besides, when the highest profile is located on the east side of N-S streets, then the subzone next to the east-facing façade is recommendable for pedestrians. The proposed urban guidelines enable urban planners to create and renovate urban spaces which are more efficient in diminishing pedestrian thermal stress. [ABSTRACT FROM AUTHOR]

Background Although epidemiological studies have reported associations between mortality and both ambient air pollution and air temperature, it remains uncertain whether the mortality effects of air pollution are modified by temperature and vice versa. Moreover, little is known on the interactions between ultrafine particles (diameter ≤ 100 nm, UFP) and temperature. Objective We investigated whether the short-term associations of particle number concentration (PNC in the ultrafine range (≤100 nm) or total PNC ≤ 3000 nm, as a proxy for UFP), particulate matter ≤ 2.5 μm (PM 2.5 ) and ≤ 10 μm (PM 10 ), and ozone with daily total natural and cardiovascular mortality were modified by air temperature and whether air pollution levels affected the temperature-mortality associations in eight European urban areas during 1999–2013. Methods We first analyzed air temperature-stratified associations between air pollution and total natural (nonaccidental) and cardiovascular mortality as well as air pollution-stratified temperature-mortality associations using city-specific over-dispersed Poisson additive models with a distributed lag nonlinear temperature term in each city. All models were adjusted for long-term and seasonal trend, day of the week, influenza epidemics, and population dynamics due to summer vacation and holidays. City-specific effect estimates were then pooled using random-effects meta-analysis. Results Pooled associations between air pollutants and total and cardiovascular mortality were overall positive and generally stronger at high relatively compared to low air temperatures. For example, on days with high air temperatures (>75th percentile), an increase of 10,000 particles/cm 3 in PNC corresponded to a 2.51% (95% CI: 0.39%, 4.67%) increase in cardiovascular mortality, which was significantly higher than that on days with low air temperatures (<25th percentile) [−0.18% (95% CI: −0.97%, 0.62%)]. On days with high air pollution (>50th percentile), both heat- and cold-related mortality risks increased. Conclusion Our findings showed that high temperature could modify the effects of air pollution on daily mortality and high air pollution might enhance the air temperature effects. [ABSTRACT FROM AUTHOR]

Both climate change and intensive human activities are thought to have contributed to the impairment of atmospheric visibility in Beijing. But the detailed processes involved and relative roles of human activities and climate change have not been quantified. Optical extinction of aerosols, the inverse of meteorological visibility is especially sensitive to fine particles <1.0 μm. These submicron particles are considered more hazardous than larger ones in terms of cardiovascular and respiratory diseases. Here we used the aerosol optical extinction (inverse of visibility) as the indicator of submicron particles pollution to estimate its inter-annual variability from 1980 to 2015. Our results indicated that optical extinction experienced two different periods: a weakly increasing stage (1980–2005) and a rapidly increasing stage (2005–2015). We attributed the variations of optical extinction to the joint effects of human activities and climate change. Over the past 36 years, human activities played a leading role in the increase of optical extinction, with a positive contribution of 0.077 km −1 /10 y. While under the effects of climate change, optical extinction firstly decreased by 0.035 km −1 /10 y until 2005 and then increased by 0.087 km −1 /10 y. Detailed analysis revealed that the abrupt change (around 2005) of optical extinction resulted from the trend reversals of climate change. We found since 2005 the decreasing trend by 0.58 m·s −1 /10 y in wind speed, the growing trend at 8.69%/10 y in relative humidity and the declining trend by 2.72 hPa/10 y in atmospheric pressure have caused the rapid increase of optical extinction. In brief, the higher load of fine particles <1.0 μm in Beijing in recent decades could be associated with both human activities and climate change. Particularly after 2005, the adverse climate change aggravated the situation of submicron particles pollution. [ABSTRACT FROM AUTHOR]

A bi-level fuzzy programming (BFLP) method was developed for energy systems planning (ESP) and carbon dioxide (CO 2 ) mitigation under uncertainty. BFLP could handle fuzzy information and leader-follower problem in decision-making processes. It could also address the tradeoffs among different decision makers in two decision-making levels through prioritizing the most important goal. Then, a BFLP-ESP model was formulated for planning energy system of Beijing, in which the upper-level objective is to minimize CO 2 emission and the lower-level objective is to minimize the system cost. Results provided a range of decision alternatives that corresponded to a tradeoff between system optimality and reliability under uncertainty. Compared to the single-level model with a target to minimize system cost, the amounts of pollutant/CO 2 emissions from BFLP-ESP were reduced since the study system would prefer more clean energies (i.e. natural gas, LPG and electricity) to replace coal fuel. Decision alternatives from BFLP were more beneficial for supporting Beijing to adjust its energy mix and enact its emission-abatement policy. Results also revealed that the low-carbon policy for power plants (e.g., shutting down all coal-fired power plants) could lead to a potentially increment of imported energy for Beijing, which would increase the risk of energy shortage. The findings could help decision makers analyze the interactions between different stakeholders in ESP and provide useful information for policy design under uncertainty. [ABSTRACT FROM AUTHOR]

Economic development, accompanying with environmental damage and energy depletion, becomes essential nowadays. There is a complicated and comprehensive interaction between economics, environment and energy. Understanding the operating mechanism of Energy-Environment-Economy model (3E) and its key factors is the inherent part in dealing with the issue. In this paper, we combine System Dynamics model and Geographic Information System to analyze the energy-environment-economy (3E) system both temporally and spatially, which explicitly explore the interaction of economics, energy, and environment and effects of the key influencing factors. Beijing is selected as a case study to verify our SD-GIS model. Alternative scenarios, e.g., current, technology, energy and environment scenarios are explored and compared. Simulation results shows that, current scenario is not sustainable; technology scenario is applicable to economic growth; environment scenario maintains a balanced path of development for long term stability. Policy-making insights are given based on our results and analysis. [ABSTRACT FROM AUTHOR]

Few studies have linked social factors to air pollution exposure in China. Unlike the race or minority concepts in western countries, the Hukou system (residential registration system) is a fundamental reason for the existence of social deprivation in China. To assess the differences in ozone (O 3 ) exposure among social groups, especially groups divided by Hukou status, we assigned estimates of O 3 exposure to the latest census data of the Beijing urban area using a kriging interpolation model. We developed simultaneous autoregressive (SAR) models that account for spatial autocorrelation to identify the associations between O 3 exposure and social factors. Principal component regression was used to control the multicollinearity bias as well as explore the spatial structure of the social data. The census tracts (CTs) with higher proportions of persons living alone and migrants with non-local Hukou were characterized by greater exposure to ambient O 3 . The areas with greater proportions of seniors had lower O 3 exposure. The spatial distribution patterns were similar among variables including migrants, agricultural population and household separation (population status with separation between Hukou and actual residences), which fit the demographic characteristics of the majority of migrants. Migrants bore a double burden of social deprivation and O 3 pollution exposure due to city development planning and the Hukou system. [ABSTRACT FROM AUTHOR]

This article proposes a method for estimating the surface urban heat island intensity (SUHI) of urban areas, which addresses prior difficulties in the determination of rural contexts that may be used as a point of comparison. Based on indexes produced using this method, as well as remotely sensed datasets, the article compares the temporal and spatial characteristics of SUHIs within three major urban agglomerations (the Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Pearl River Delta) and six typical metropolises. The article also examines the influence of socioeconomic factors on SUHI. The study revealed that this method is able to objectively monitor regional-scale SUHIs. The climate of the area studied is probably a determining factor in the seasonal variation of SUHIs. Research from the last 5 years (2010-2014) demonstrates that the urban heat island effect within the three urban agglomerations and five metropolises is serious. From 1994 to 2014, the average SUHI value for central urban areas rose from 0.4 to 2.3 K, while the total area where the SUHI value was >3.0 K increased from 1938 to 29,690 km2. The morphology of heat islands is significantly influenced by urbanization, meaning that heat islands within the areas studied will only continue to grow. Urban population and electricity consumption are the socioeconomic factors that exerted the greatest influence on the size of heat islands in China’s major urban agglomerations. However, it is likely that economic measures designed to mitigate the UHI effect will differ in effectiveness from one urban agglomeration to another. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) effect changes heat and water cycles in urban areas, and has been accused of elevating energy consumption, deteriorating living environment, and increasing mortality rates. Understanding various UHI effects necessitates a systematic modeling approach. A major problem in UHI simulations is that urban areas were either considered to have only one category of land use/cover or outdated in land use/cover patterns due to the lack of high resolution data. Therefore, this study aims at integrating up-to-date remotely sensed land use/cover data with the Weather Research and Forecasting (WRF/UCM)/Urban Canopy Model modeling systems to simulate surface temperature patterns in Atlanta, Georgia. In addition, three land-use scenarios, i.e., spontaneous scenario (SS), concentrated scenario (CS), and local policy scenario (LPS), were designed and incorporated into the modeling. Five numerical experiments were conducted by using the Weather Research and Forecasting (WRF) model to explore the impact of urbanization-induced land-cover changes on temperature patterns. Land use and land-cover patterns under all three scenarios suggested that urban growth would continue through in-filling development and outward expansion. Compared to temperature simulations in 2011, temperature maps corresponding to the three urban growth scenarios showed warmer and cooler temperature patterns outside and inside the urban core, respectively. Analysis of the mean diurnal temperature cycle suggested that the highest temperature difference of 3.9 K was observed between 2011 and the LPS, and occurred around 22:00 local time. Overall, the simulations showed different UHI effects respond to the land-use scenarios in the summer. It is recommended for urban managers and policy makers to reflect on the potential impacts of alternative urban growth policies on thermal environment. [ABSTRACT FROM AUTHOR]