Evidence for a significant urbanization effect on climate in China

Persistent urban heat

Urban surface and near-surface air temperatures are known to be often higher than their rural counterparts, a phenomenon now labeled as the urban heat island effect. However, whether the elevated urban temperatures are more persistent than rural temperatures at timescales commensurate to heat waves has not been addressed despite its importance for human health. Combining numerical simulations by a global climate model with a surface energy balance theory, it is demonstrated here that urban surface and near-surface air temperatures are significantly more persistent than their rural counterparts in cities dominated by impervious materials with large thermal inertia. Further use of these materials will result in even stronger urban temperature persistence, especially for tropical cities. The present findings help pinpoint mitigation strategies that can simultaneously ameliorate the larger magnitude and stronger persistence of urban temperatures.

Regional proximity effects of landscape pattern evolution: Evidence from 325 county-level areas in the middle reaches of the Yangtze River, China

Unravelling the evolution of landscape patterns is essential to understand regional socio-ecological processes and to solve conflicts between environment protection and human development. However, the role of landscape transition in regional landscape pattern evolution remains unclear. Taking 325 county-level areas in the middle reaches of the Yangtze River (MRYR) as an example, this study explored the spatiotemporal associations between landscape quantity and pattern from the 1970s to 2020. Employing the methods of landscape metrics and trend and correlation analysis, associations between landscape transition and landscape pattern were found. The main results were as follows: (1) From the 1970s to 2020, urban land nearly doubled from 0.93 to 1.89 million km2. Arable land and forest showed the largest quantity reductions of 0.88 million km2 and 0.28 million km2, respectively. Other landscapes showed both decreasing and increasing trends with a spatial overlap among counties. (2) Transition in landscape quantity drives the change in landscape patches, thus affecting the landscape pattern in counties. The percentage of landscape area at the class level (CPLAND) showed relative changes in the quantities of landscape categories in each observation year, but their extreme outliers presented larger changes. (3) Diverse correlation coefficients in terms of magnitude and direction suggested that the transition from natural landscape to human-influenced landscape and the reverse processes occurred. Aggregation and diversity metrics showed spatial interaction with similar distances and the perimeter-area fractal dimension (PAFRAC) showed spatial autocorrelation at local scale. Optimal bandwidths among arable land, forest, and urban land (129.2 km) revealed direct spatial interactions and causal relationships, as did waters and unused land (66.7 km). The findings explained the evolution of landscape patterns and highlighted key areas where various landscape changes occurred, and can provide scientific support for policy-making in regional landscape transition governance.

The rapid increase of urban contaminated sites along China's urbanization during the last 30 years

Contaminated sites pose serious threats to the soil environment and human health. However, the location and temporal changes of urban contaminated sites across China remain unknown due to data scarcity. Here, we developed a machine-learning model to identify the contaminated sites using public data. Results show that the trained model with 2,005 surveyed site samples and six variables can achieve a model performance evaluation value of 0.86. 43,676 contaminated sites were identified from 83,498 polluting enterprise plots in China. However, these contaminated sites have significant spatiotemporal heterogeneity, mainly located in economically developed provinces, urban agglomerations, and core urban areas. Moreover, the contaminated sites increased by 325% along with urban expansion from 1990 to 2018. The abandoned contaminated sites increased rapidly, but the contaminated sites in production decreased continuously. This methodological framework and our findings contribute to the precise management of contaminated sites and provide insights into urban sustainable development.

Urbanization can accelerate climate change by increasing soil N2 O emission while reducing CH4 uptake

Urban land-use change has the potential to affect local to global biogeochemical carbon (C) and nitrogen (N) cycles and associated greenhouse gas (GHG) fluxes. We conducted a meta-analysis to (1) assess the effects of urbanization-induced land-use conversion on soil nitrous oxide (N₂ O) and methane (CH₄ ) fluxes, (2) quantify direct N₂ O emission factors (EF_d ) of fertilized urban soils used, for example, as lawns or forests, and (3) identify the key drivers leading to flux changes associated with urbanization. On average, urbanization increases soil N₂ O emissions by 153%, to 3.0 kg N ha^-1  year^-1 , while rates of soil CH₄ uptake are reduced by 50%, to 2.0 kg C ha^-1  year^-1 . The global mean annual N₂ O EF_d of fertilized lawns and urban forests is 1.4%, suggesting that urban soils can be regional hotspots of N₂ O emissions. On a global basis, conversion of land to urban greenspaces has increased soil N₂ O emission by 0.46 Tg N₂ O-N year^-1 and decreased soil CH₄ uptake by 0.58 Tg CH₄ -C year^-1 . Urbanization driven changes in soil N₂ O emission and CH₄ uptake are associated with changes in soil properties (bulk density, pH, total N content, and C/N ratio), increased temperature, and management practices, especially fertilizer use. Overall, our meta-analysis shows that urbanization increases soil N₂ O emissions and reduces the role of soils as a sink for atmospheric CH₄ . These effects can be mitigated by avoiding soil compaction, reducing fertilization of lawns, and by restoring native ecosystems in urban landscapes.

A systematic review of urban green space research over the last 30 years: A bibliometric analysis

Worldwide, due to rapid urbanization, the provision of urban green spaces (UGSs) has become a primary goal of urban planning. As such, research on the benefits, effects, and challenges of UGSs has gained widespread attention among scholars. This paper comprehensively analyzes three decades of UGS research and its evolution; it conducts a bibliometric analysis of approximately 4000 articles and reviews from the Web of Science platform to discover the patterns and trends characterizing UGS research over time. We found that the pioneers of initial UGS research were the United States and Canada, whereas recently the European Union and China have become the global engines of research in the field. UGS research initially focused on studying urban forests, gradually shifting toward green spaces located in inner urban areas. Early on, researchers investigated UGSs (i.e., urban forests) from an ecological perspective. However, the most current research phase focuses on the social aspects of UGSs, characterized by such keywords as environmental justice and accessibility. Furthermore, the introduction of geographic information systems (GIS) has given new impetus to the evolution of UGS research and has remained the most used technological advancement besides remote sensing techniques. As the social aspects of UGS research have gained importance, new research methods have been employed, such as machine learning, big data and social media data analysis, and artificial intelligence, most recently.

New-type urbanization ecologically reshaping China

Addressing critical ecological issues is one of the core objectives of the Chinese National New-type Urbanization Plan (NTU). However, there is not enough research to clearly demonstrate NTU's impact on environmental pollution. There is a need to provide solid empirical evidence from evaluation of the effects of NTU on environmental pollution. This study implements a series of propensity score matching and difference-in-difference analyses based on a comprehensive panel dataset spanning the period 2006-2017. The quantitative results show that NTU is largely conducive to curbing environmental pollution, with PM_2.5 concentrations as a proxy, and its robustness is demonstrated by the parallel trend test and placebo test. Further, the ecological effect of NTU is heterogeneous in terms of city level, location, and former pollution level. Small and medium cities benefit more than larger or central cities from NTU, and eastern cities exhibit better air quality improvement than cities in western regions. In addition, through quantile regression, we find that the positive outcomes of NTU are restricted by level of pollution, i.e., heavier pollution adds greatly to the difficulty of abatement.

Uncertainty and sensitivity analysis of deep learning models for diurnal temperature range (DTR) forecasting over five Indian cities

In this article, the maximum and minimum daily temperature data for Indian cities were tested, together with the predicted diurnal temperature range (DTR) for monthly time horizons. RClimDex, a user interface for extreme computing indices, was used to advance the estimation because it allowed for statistical analysis and comparison of climatological elements such time series, means, extremes, and trends. During these 69 years, a more erratic DTR trend was seen in the research area. This study investigates the suitability of three deep neural networks for one-step-ahead DTR time series (DTRTS) forecasting, including recurrent neural network (RNN), long short-term memory (LSTM), gated recurrent unit (GRU), and auto-regressive integrated moving average exogenous (ARIMAX). To evaluate the effectiveness of models in the testing set, six statistical error indicators, including root mean square error (RMSE), mean absolute error (MAE), coefficient of correlation (R), percent bias (PBIAS), modified index of agreement (md), and relative index of agreement (rd), were chosen. The Wilson score approach was used to do a quantitative uncertainty analysis on the prediction error to forecast the outcome DTR. The findings show that the LSTM outperforms the other models in terms of its capacity to forget, remember, and update information. It is more accurate on datasets with longer sequences and displays noticeably more volatility throughout its gradient descent. The results of a sensitivity analysis on the LSTM model, which used RMSE values as an output and took into account different look-back periods, showed that the amount of history used to fit a time series forecast model had a direct impact on the model's performance. As a result, this model can be applied as a fresh, trustworthy deep learning method for DTRTS forecasting.

Integrated Insights into Source Apportionment and Source-Specific Health Risks of Potential Pollutants in Urban Park Soils on the Karst Plateau, SW China

Polycyclic aromatic hydrocarbons (PAHs) and heavy metal(loid)s (HMs) pose risks to environmental and human health. Identification of priority control contaminants is important in guiding the management and control of these synchronous pollutants. A total of 247 soil samples were collected from 64 urban parks in the karst plateau city of Guiyang in SW China to determine the concentrations, spatial distributions, and health risks of PAHs and HMs. The results indicate that dibenz(ah)anthracene and benzo(a)pyrene are the main PAHs species of high ecological risk, and Cr, Mn, and Ni pose elevated ecological risk among the HMs. Four sources were identified for PAHs (biomass burning, coke oven, traffic sources, and coal burning) and HMs (traffic sources, coal burning, industrial sources, and natural sources). The non-carcinogenic risk (NCR) and total carcinogenic risk (TCR) of PAHs were all determined to be negligible and at acceptable levels, several orders of magnitude below those of HMs. The NCR and TCR values of HMs were relatively high, especially for children (11.9% of NCR > 1; 79.1% of TCR > 10-4). Coal burning and natural sources make the greatest contributions to the NCR and TCR values from karst park soils in Guiyang. Considering HMs bioavailability, NCR and TCR values were rather low, due to the high residual HM fractions. Integrated insights into source specific ecological and human health risk indicate future directions for management and control of synchronous PAH and HM pollution, particularly for karst plateau areas.

Supplementary Information

The online version contains supplementary material available at 10.1007/s12403-023-00534-3.

Assessment of Summer Regional Outdoor Heat Stress and Regional Comfort in the Beijing-Tianjin-Hebei Agglomeration Over the Last 40 Years

Outdoor thermal comfort (OTC) is critical for public health, labor productivity, and human life. Growing extreme heat events caused by climate change have a serious impact on OTCs, especially in urban areas. Quantitatively characterizing and evaluating the spatiotemporal changes in OTCs are essential, and more applications are needed in urban agglomerations. Therefore, taking the Beijing-Tianjin-Hebei (BTH) urban agglomeration as the study area, this study aimed to quantitatively assess the summer regional OTC from 1981 to 2020. First, the Universal Thermal Climate Index (UTCI) was used as the indicator of daily thermal stress, and then a Composite Thermal Comfort Score was proposed to evaluate the long-term, summertime, regional OTC considering the extent, duration, and intensity of daytime and nighttime thermal stress. The results showed that (a) the increase in UTCI (0.32°C/10a at daytime and 0.21°C/10a at nighttime) and heat stress frequency (0.88 at daytime and 0.39 d/10a at nighttime) were manifested over BTH, indicating a worse OTC. Spatial and temporal heterogeneity was also demonstrated. (b) The general OTC showed a decreasing north-south gradient pattern. At daytime, the northern mountainous zone presented the best OTC, the southern plain zone, especially Hengshui, Langfang, and Cangzhou, showed the worst. At nighttime, the mountain-plain transition zone showed the best OTC, the northern mountainous zone showed the worst since more cold stress occurred. Our findings will be useful in informing climate change adaptation strategies to ensure urban resilience as extreme heat increases in the context of climate change.

A multi-perspective study of atmospheric urban heat island effect in China based on national meteorological observations: Facts and uncertainties

The atmospheric urban heat island (AUHI) effect, traditionally measured by in-situ sensors mounted on fixed meteorological stations, has been extensively studied by different and imperfect methods. However, facts and uncertainties of the AUHI estimates revealed by the different methods are not well understood at a large scale. Here we examined the spatial-temporal variations of the AUHI effects from multiple perspectives in China's 86 large cities as revealed by national-level meteorological observations at 2-m height from 1981 to 2017. We find relatively consistent patterns of larger urban heating effects in daily minimum temperature, winter, and Northeast China than their counterparts in terms of multiyear mean intensity (AUHII), long-term trend (△AUHII), and contribution to local warming (according to the CTRUMR "urban minus rural" and CTROMR "observation minus reanalysis" methods). Concurrently, a cooling impact or a reduction in the heating effect has been observed in some cities randomly, especially in daily maximum temperature. On average across cities, the AUHII, △AUHI, CTRUMR, and CTROMR for the daily mean temperature amount to 0.33 °C, 0.013 °C 10a-1, 53 %, and 23 % at an annual mean time scale, respectively. Nevertheless, the poor representativeness of weather stations, discrepancies among the quantification methods, nonlinearity of the long-term tendencies, and coupling effects with rural crop land use activities lead to large uncertainties of the AUHI estimates. Our results emphasize the limitations of national-level meteorological stations in characterizing AUHI in China and suggest that the urban heat island remains a "well described but rather poorly understood" phenomenon warranting further investigation by a combined uses of multiple techniques like high-density sensor networks, remote sensing techniques, and high-resolution numerical models.

Urbanization affects spatial variation and species similarity of bird diversity distribution

Although cities are human-dominated systems, they provide habitat for many other species. Because of the lack of long-term observation data, it is challenging to assess the impacts of rapid urbanization on biodiversity in Global South countries. Using multisource data, we provided the first analysis of the impacts of urbanization on bird distribution at the continental scale and found that the distributional hot spots of threatened birds overlapped greatly with urbanized areas, with only 3.90% of the threatened birds' preferred land cover type in urban built-up areas. Bird ranges are being reshaped differently because of their different adaptations to urbanization. While green infrastructure can improve local bird diversity, the homogeneous urban environment also leads to species compositions being more similar across regions. More attention should be paid to narrow-range species for the formulation of biodiversity conservation strategies, and conservation actions should be further coordinated among cities from a global perspective.

The trend and spatial spread of multisectoral climate extremes in CMIP6 models

Climate change could exacerbate extreme climate events. This study investigated the global and continental representations of fourteen multisectoral climate indices during the historical (1979-2014), near future (2025-2060) and far future (2065-2100) periods under two emission scenarios, in eleven Coupled Model Intercomparison Project (CMIP) General Circulation Models (GCM). We ranked the GCMs based on five metrics centred on their temporal and spatial performances. Most models followed the reference pattern during the historical period. MPI-ESM ranked best in replicating the daily precipitation intensity (DPI) in Africa, while CANESM5 GCM ranked first in heatwave index (HI), maximum consecutive dry days (MCCD). Across the different continents, MPI-LR GCM performed best in replicating the DPI, except in Africa. The model ranks could provide valuable information when selecting appropriate GCM ensembles when focusing on climate extremes. A global evaluation of the multi-index causal effects for the various indices shows that the dry spell total length (DSTL) was the most crucial index modulating the MCCD for all continents. Also, most indices exhibited a positive climate change signal from the historical to the future. Therefore, it is crucial to design appropriate strategies to strengthen resilience to extreme climatic events while mitigating greenhouse gas emissions.

Waterbody loss due to urban expansion of large Chinese cities in last three decades

Urban waterbodies are one of the most pertinent issues involved in multiple aspects of Sustainable Development Goals (SDGs). However, waterbodies in large Chinese cities are highly vulnerable to urban-land expansion, which is mostly due to economic development, population growth, and rural-urban migration. In this work, we selected 159 Chinese cities of over one million in population to investigate the encroachment on waterbodies due to rapid urbanization from 1990 to 2018. Overall, 20.6% of natural waterbody area was lost during this period to urban expansion, and this fraction varied from city to city which was related to waterbody abundance. With the acceleration of urbanization, waterbody occupation is becoming more serious (P < 0.01). However, in all cities, this encroachment has eased since 2010, which justifies the effective implementation of national-scale policies to conserve urban waterbodies. Meanwhile, gains have occurred during urbanization, in addition to the loss of waterbodies. Especially, cities lacking waterbody placed a greater emphasis on ecological factors, whose urban waterbody areas showed an increasing trend. In the future, ecological resources, including waterbody, should be considered in urban planning to provide reasonable protection to waterbodies in the quest for urban sustainability.

Anthropogenic influence of temperature changes across East Asia using CMIP6 simulations

The present study explores the impact of anthropogenic forcings (ANT) on surface air temperatures (SATs) across East Asia (EA) over a long period (1850–2014) using the new Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets. Based on CMIP6 multi-model ensemble simulations, the historical simulations (twentieth century) and future (twenty-first century) SAT projections were investigated. Our calculations show that during 1850–2014, the combination of ANT and natural (NAT) (‘ALL = ANT + NAT’) forcings increased the EA’s SAT by 0.031 °C/decade, while a high increase of 0.08 °C/decade due to greenhouse gas (GHG) emissions. The ANT forcing rapidly increased after 1969. As a result, SAT change was enhanced at a rate of 0.268 °C/decade and 0.255 °C/decade due to GHG and ALL forcings, respectively. Human-induced GHG emissions were the dominant factors driving SAT warming and will also contribute to substantial future warming trends. Additionally, the optimal fingerprinting method was used to signify the influence of ANT forcing on climate change in EA. In a two-signal analysis, the ANT forcing was distinctly detected and detached from NAT forcing. In three-signal analyses, GHG forcing was dominant and separated from AER and NAT forcings. The future projections from 2015 to 2100 were examined based on CMIP6 socioeconomic pathway emission scenarios.

Performance of air temperature from ERA5-Land reanalysis in coastal urban agglomeration of Southeast China

Near-surface air temperature is an important indicator of climate change and extreme events. ERA5-Land reanalysis products feature finer spatial and temporal resolutions, and have been widely adopted in global climate-related research. However, the performance of ERA5-Land air temperature data in coastal urban agglomerations has received little attention. In this study, a comprehensive evaluation is conducted in the Guangdong-Hong Kong-Macau Greater Bay Area (GBA) using the observations of 1080 automatic weather stations in 2018 as reference. Generally, ERA5-Land underestimates temperature (an average bias of 0.90 °C), and performs better at low temperatures than at high temperatures. At the station level, it is observed that the correlation shows a strong positive linear relationship with the distance to the coastline in summer, and that the bias increases with increasing altitude throughout the year. With respect to different land cover types, data accuracy over urban and built-up lands is the lowest. The spatial pattern of ERA5-Land is generally consistent with that of stations but relatively poor in urban areas. In addition, ERA5-Land properly captures daily and monthly variations, as well as intraday temperature fluctuations. These conclusions provide a reference for the implementation of ERA5-Land in coastal urban agglomerations.

Interaction of aerosol with meteorological parameters and its effect on the cash crop in the Vidarbha region of Maharashtra, India

Regional weather variability depends on various meteorological variables such as temperature and rainfall. The current research focuses on the variability and trends in annual aerosol optical depth (AOD), temperature (T), and rainfall (RF) in 11 Vidarbha districts. The annual trend analysis of AOD, T, and R is determined using the non-parametric Sen slope and Mann-Kendall (MK) test at a 5% significant level from 1980 to 2019. Annual T and AOD indicate a substantial increase in this study, whereas rainfall shows a non-significant trend (MK, test) over the study period. According to Sen's slope trends, the relatively high rainfall area (Chandrapur = 1.273 and Garchiroli = 4.06) got positive trends, but Gondia and Bhandara districts have negative (Sen's slope =  - 2.79 and - 2.56) trends. The moderate rainfall areas are showing a less negative Sen slope (Wardha =  - 0.21, Washim =  - 1.13 and Yavatmal =  - 2.75), whereas Nagpur districts' Sen's slope shows a positive value (Sens's slope = 0.72). The assured rainfall area districts show Sen's slope trends are positive (Akola = 0.45, Amravati = 1.17 and Buldana = 0.42). Sen's slope trend indicates rising rainfall, whereas negative trends indicate decreasing rainfall in the time series. This study has also looked at the effect of RF, AOD, and T on the last two decades' cash crop production (2000-2019) for Vidarbha districts. The relationship between rainfall departure (DRF) and cash crop yield has also been highlighted. Five cash crops, such as cotton (Ct), total cereals (TCrl), total oilseeds (TOsd), total pulses (TPS), and sugarcane (Sc), are selected for the present study.

Climatic Trends of Variable Temperate Environment: A Complete Time Series Analysis during 1980–2020

The western Himalayan region is susceptible to minor climate changes because of its fragile ecology, which might threaten the valley’s prestigious ecosystems and socio-economic components. The Himalayas’s local climate and weather are vulnerable to and interlinked with world-scale climatic changes since the region’s hydrology is predominantly dominated by snow and glaciers. The Himalayas, notably the Jammu and Kashmir region in the western Himalayas, has clearly shown distinct and robust evidence of climate change. This study used observed data to examine the climatic variability and trends of change in precipitation and temperature for the Kashmir valley between 1980 and 2020. Gulmarg, Pahalgam, Kokernag, Qazigund, Kupwara, and Srinagar (Shalimar) meteorological stations in the Kashmir valley were studied in detail for long- and short-term as well as localized fluctuations in temperature and precipitation. The annual temperature and precipitation fluctuations were calculated using Sen’s slope approach, and the sloping trend was determined using linear regression. The research showed statistically insignificant growing trends in maximum and minimum temperatures throughout the Kashmir valley. The average annual temperature in the Kashmir valley increased by 1.55 °C during the last 41 years (from 1980 to 2020), with a higher rise in maximum and minimum temperature by 2.00 and 1.10 °C, respectively. However, precipitation showed a non-significant decreasing trend concerning time series analysis over 1980 to 2020 in Kashmir valley. Results of annual average maximum temperature at all the stations revealed that Pahalgam (2.2 °C), Kokernag (1.8 °C), and Kupwara (1.8 °C) displayed a steep upsurge and statistically significant trends; however, annual average minimum temperature followed an increasing trend from 1980 to 2020 at all the stations except Shalimar. However, non-significant declining trends in precipitation were recorded at all the locations in Kashmir valley. This changing pattern of temperature and precipitation could have significant environmental consequences, affecting the western Himalayan region’s food security and ecological sustainability.

Beyond city expansion: multi-scale environmental impacts of urban megaregion formation in China

Environmental degradation caused by rapid urbanization is a pressing global issue. However, little is known about how urban changes operate and affect environments across multiple scales. Focusing on China, we found urbanization was indeed massive from 2000 to 2015, but it was also very uneven, exhibiting high internal city dynamics. Urban areas in China as a whole became less green, warmer, and had exacerbated PM_2.5 pollution. However, environmental impacts differed in newly developed versus older areas of cities. Adverse impacts were prominent in newly urbanized areas, while old urban areas generally showed improved environmental quality. In addition, regional environmental issues are emerging as cities expand, connect and interact to form urban megaregions. To turn urbanization into an opportunity for, rather than an obstacle to, sustainable development, we must move beyond documenting urban expansion to understand the environmental consequences of both internal city dynamics and the formation of urban megaregions.

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.

Urbanization-driven increases in summertime compound heat extremes across China

Summertime extreme heat events exert severe impacts on the natural environment and human society, especially in densely populated and highly urbanized regions. While previous studies have focused on independent heat day/night, there is a lack of attention to the changes in compound events with cooccurring daytime and nighttime extreme temperature on the same day. In this study, we examine the spatio-temporal changes of summertime compound heat extremes (including compound heat day and compound heatwave) across China, with a particular focus on 20 major urban agglomerations (UAs), and quantify the urbanization effects on these changes. We find that the frequency and fraction of compound heat events show obvious spatial disparities across China. The compound heat events occur more frequently in highly populated and urbanized areas such as the Pearl River Delta. Moreover, the frequency and fraction of compound heat events have significantly increased in recent decades in most parts of China, especially in more developed UAs. These intensifying trends have even accelerated in more recent decades. Our further investigations suggest that most UAs of China experienced an intensifying urbanization effect on compound heat events, and few UAs in northwestern and central China (e.g., UAs of the north Tianshan mountain and the middle reaches of the Yangtze River) display a weakening effect of urbanization. Our findings highlight the important role of urbanization in increasing compound heat extremes and suggest that the increasing threats of compound events in urban areas should be given more attention under the context of global warming and local urbanization.

The agglomeration and dispersion dichotomy of human settlements on Earth

Human settlements on Earth are scattered in a multitude of shapes, sizes and spatial arrangements. These patterns are often not random but a result of complex geographical, cultural, economic and historical processes that have profound human and ecological impacts. However, little is known about the global distribution of these patterns and the spatial forces that creates them. This study analyses human settlements from high-resolution satellite imagery and provides a global classification of spatial patterns. We find two emerging classes, namely agglomeration and dispersion. In the former, settlements are fewer than expected based on the predictions of scaling theory, while an unexpectedly high number of settlements characterizes the latter. To explain the observed spatial patterns, we propose a model that combines two agglomeration forces and simulates human settlements' historical growth. Our results show that our model accurately matches the observed global classification (F1: 0.73), helps to understand and estimate the growth of human settlements and, in turn, the distribution and physical dynamics of all human settlements on Earth, from small villages to cities.

Impacts of Temperature Trends and SPEI on Yields of Major Cereal Crops in the Gambia

Variations in the climate constitute a significant threat to the productivity of food crops in the Gambia. A good understanding of the influence of climate variability on crop production is vital for climate resilience and improved food security. This study examined the trends, relationships, and the extent to which growing season temperatures and the SPEI (Standardized Precipitation and Evapotranspiration Index) impacted sorghum, millet, maize, and rice yields in three agro-ecological regions of the Gambia during 1990–2019. Mean temperatures and the SPEI exhibited increasing trends while observed yields showed a decline across all regions. The SPEI had a significant positive relationship with yields, and temperatures were negatively associated with yields. Though yield response to climate variability differs among regions, 20% to 62% of variations in the four crop yields were due to climate trends. The combined effect of the SPEI and temperatures decreased yields from 3.6 kg ha−1 year−1 to 29.4 kg ha−1 year−1, with the most severe decline observed in rice and maize yields in the Sahelian zone. Although uncertainties might arise from not considering related extreme climate events, this study highlights how past climate trends affect cereal yields in the Gambia; thus, any unfavorable change in the local climate could have severe repercussions on the country’s food security. There is a need for concerted efforts to increase investments in adaptation strategies to lessen the effects of the climate for improved crop productivity.

Identifying Surface Urban Heat Island Drivers and Their Spatial Heterogeneity in China’s 281 Cities: An Empirical Study Based on Multiscale Geographically Weighted Regression

The spatially heterogeneous nature and geographical scale of surface urban heat island (SUHI) driving mechanisms remain largely unknown, as most previous studies have focused solely on their global performance and impact strength. This paper analyzes diurnal and nocturnal SUHIs in China based on the multiscale geographically weighted regression (MGWR) model for 2005, 2010, 2015, and 2018. Compared to results obtained using the ordinary least square (OLS) model, the MGWR model has a lower corrected Akaike information criterion value and significantly improves the model’s coefficient of determination (OLS: 0.087–0.666, MGWR: 0.616–0.894). The normalized difference vegetation index (NDVI) and nighttime light (NTL) are the most critical drivers of daytime and nighttime SUHIs, respectively. In terms of model bandwidth, population and Δfine particulate matter are typically global variables, while ΔNDVI, intercept (i.e., spatial context), and NTL are local variables. The nighttime coefficient of ΔNDVI is significantly negative in the more economically developed southern coastal region, while it is significantly positive in northwestern China. Our study not only improves the understanding of the complex drivers of SUHIs from a multiscale perspective but also provides a basis for urban heat island mitigation by more precisely identifying the heterogeneity of drivers.

Spatiotemporal Characteristics of the Surface Urban Heat Island and Its Driving Factors Based on Local Climate Zones and Population in Beijing, China

The increasing degree of urbanization has continuously aggravated the surface urban heat island (sUHI) effect in China. To investigate the correlation between spatiotemporal changes of sUHI and urbanization in Beijing, land surface temperature in summer from 2000 to 2017 and the distribution of local climate zones (LCZs) in 2003, 2005, 2010, and 2017 was retrieved using remote sensing data and used to analyze the sUHI area and intensity change. The statistical method GeoDetector was utilized to investigate the explanatory ability of LCZs and population as the driving factors. The year of 2006 was identified as the main turning year for sUHI evolution. The variation the sUHI from 2000 showed first an increasing trend, and then a decreasing one. The sUHI pattern changed before and after 2009. Before 2009, the sUHI mainly increased in the suburbs, and then, the enhancement area moved to the central area. The sUHI intensity change under different LCZ conversion conditions showed that the LCZ conversion influences the sUHI intensity significantly. Based on population distribution data, we found that the relationship between population density and sUHI gets weaker with increasing population density. The result of GeoDetector indicated that the LCZ is the main factor influencing the sUHI, but population density is an important auxiliary factor. This research reveals the sUHI variation pattern in Beijing from 2000 and could help city managers plan thermally comfortable urban environments with a better understanding of the effect of urban spatial form and population density on sUHIs.

Disentangling the trend in the warming of urban areas into global and local factors

Large cities account for a significant share of national population and wealth, and exert high pressure on local and regional resources, exacerbating socioenvironmental risks. The replacement of natural landscapes with higher heat capacity materials because of urbanization and anthropogenic waste heat are some of the factors contributing to local climate change caused by the urban heat island (UHI) effect. Because of synergistic effects, local climate change can exacerbate the impacts of global warming in cities. Disentangling the contributions to warming in cities from global and local drivers can help to understand their relative importance and guide local adaptation policies. The canopy UHI intensity is commonly approximated by the difference between temperatures within cities and the surrounding areas. We present a complementary approach that applies the concept of common trends to extract the global contributions to observed warming in cities and to obtain a residual warming trend caused by local and regional factors. Once the effects of global drivers are removed, common features appear in cities' temperatures in the eastern part of the United States. Most cities experienced higher warming than that attributable to global climate change, and some shared a period of rapid warming during urban sprawl in the mid-20th century in the United States.

Pathways of Climate Change Impact on Agroforestry, Food Consumption Pattern, and Dietary Diversity Among Indigenous Subsistence Farmers of Sauria Paharia Tribal Community of India: A Mixed Methods Study

Climate change poses severe threats to the social, cultural, and economic integrity of indigenous smallholder subsistence farmers, who are intricately linked with their natural ecosystems. Sauria Paharia, a vulnerable indigenous community of Jharkhand, India, are smallholder farmers facing food and nutrition insecurity and have limited resources to cope with climate change. Eighteen villages of Godda district of Jharkhand inhabited by Sauria Paharia community were randomly selected to conduct a mixed methods study. In 11 out of 18 study villages, we conducted focus group discussions (FGDs) to examine the perception of this indigenous community regarding climate change and its impact on agroforestry and dietary diversity. In all 18 villages, household and agricultural surveys were conducted to derive quantitative estimates of household food consumption patterns and agroforestry diversity, which were triangulated with the qualitative data collected through the FGDs. The FGD data revealed that the community attributed local climatic variability in the form of low and erratic rainfall with long dry spells, to reduced crop productivity, diversity and food availability from forests and waterbodies. Declining agroforestry-produce and diversity were reported to cause reduced household income and shifts from subsistence agricultural economy to migratory unskilled wage laboring leading to household food insecurity. These perceptions were supported by quantitative estimates of habitual food consumption patterns which revealed a predominance of cereals over other food items and low agroforestry diversity (Food Accessed Diversity Index of 0.21 ± 0.15). The adaptation strategies to cope with climate variability included use of climate-resilient indigenous crop varieties for farming, seed conservation and access to indigenous forest foods and weeds for consumption during adverse situations and lean periods. There were mixed views on cultivation of hybrid crops as an adaptation strategy which could impact the sustained utilization of indigenous food systems. Promoting sustainable adaptation strategies, with adequate knowledge and technology, have the potential to improve farm resilience, income, household food security and dietary diversity in this population.

Challenges to Mitigating the Urban Health Burden of Mosquito-Borne Diseases in the Face of Climate Change

Cities worldwide are facing ever-increasing pressure to develop mitigation strategies for all sectors to deal with the impacts of climate change. Cities are expected to house 70% of the world's population by 2050, and developing related resilient health systems is a significant challenge. Because of their physical nature, cities' surface temperatures are often substantially higher than that of the surrounding rural areas, generating the so-called Urban Heat Island (UHI) effect. Whilst considerable emphasis has been placed on strategies to mitigate against the UHI-associated negative health effects of heat and pollution in cities, mosquito-borne diseases have largely been ignored. However, the World Health Organization estimates that one of the main consequences of global warming will be an increased burden of mosquito-borne diseases, many of which have an urban facet to their epidemiology and thus the global population exposed to these pathogens will steadily increase. Current health mitigation strategies for heat and pollution, for example, may, however, be detrimental for mosquito-borne diseases. Implementation of multi-sectoral strategies that can benefit many sectors (such as water, labor, and health) do exist or can be envisaged and would enable optimal use of the meagre resources available. Discussion among multi-sectoral stakeholders should be actively encouraged.

The impact of urbanization on body size of Barn Swallows Hirundo rustica gutturalis

Urbanization implies a dramatic impact on ecosystems, which may lead to drastic phenotypic differences between urban and nonurban individuals. For instance, urbanization is associated with increased metabolic costs, which may constrain body size, but urbanization also leads to habitat fragmentation, which may favor increases in body mass when for instance it correlates with dispersal capacity. However, this apparent contradiction has rarely been studied. This is particularly evident in China where the urbanization process is currently occurring at an unprecedented scale. Moreover, no study has addressed this issue across large geographical areas encompassing locations in different climates. In this regard, Barn Swallows (Hirundo rustica) are a suitable model to study the impact of urbanization on wild animals because they are a widely distributed species tightly associated with humans. Here, we collected body mass and wing length data for 359 breeding individuals of Barn Swallow (H. r. gutturalis) from 128 sites showing different levels of urbanization around the whole China. Using a set of linear mixed-effects models, we assessed how urbanization and geography influenced body size measured using body mass, wing length, and their regression residuals. Interestingly, we found that the impact of urbanization was sex-dependent, negatively affecting males' body mass, its regression residuals, and females' wing length. We also found that northern and western individuals were larger, regarding both body mass and wing length, than southern and eastern individuals. Females were heavier than males, yet males had slightly longer wings than females. Overall, our results showed that body mass of males was particularly sensitive trait to urbanization, latitude, and longitude, while it only showed a weak response to latitude in females. Conversely, while wing length showed a similar geographical pattern, it was only affected by urbanization in the case of females. Further research is needed to determine whether these phenotypic differences are associated with negative effects of urbanization or potential selective advantages.

Allelic variation in rice Fertilization Independent Endosperm 1 contributes to grain width under high night temperature stress

A higher minimum (night-time) temperature is considered a greater limiting factor for reduced rice yield than a similar increase in maximum (daytime) temperature. While the physiological impact of high night temperature (HNT) has been studied, the genetic and molecular basis of HNT stress response remains unexplored. We examined the phenotypic variation for mature grain size (length and width) in a diverse set of rice accessions under HNT stress. Genome-wide association analysis identified several HNT-specific loci regulating grain size as well as loci that are common for optimal and HNT stress conditions. A novel locus contributing to grain width under HNT conditions colocalized with Fie1, a component of the FIS-PRC2 complex. Our results suggest that the allelic difference controlling grain width under HNT is a result of differential transcript-level response of Fie1 in grains developing under HNT stress. We present evidence to support the role of Fie1 in grain size regulation by testing overexpression (OE) and knockout mutants under heat stress. The OE mutants were either unaltered or had a positive impact on mature grain size under HNT, while the knockouts exhibited significant grain size reduction under these conditions.

Assessing the Impact of Land Use and Land Cover Data Representation on Weather Forecast Quality: A Case Study in Central Mexico

In atmospheric modeling, an accurate representation of land cover is required because such information impacts water and energy budgets and, consequently, the performance of models in simulating regional climate. This study analyzes the impact of the land cover data on an operational weather forecasting system using the Weather Research and Forecasting (WRF) model for central Mexico, with the aim of improving the quality of the operative forecast. Two experiments were conducted using different land cover datasets: a United States Geological Survey (USGS) map and an updated North American Land Change Monitoring System (NALCMS) map. The experiments were conducted as a daily 120 h forecast for each day of January, April, July, and September of 2012, and the near-surface temperature, wind speed, and hourly precipitation were analyzed. Both experiments were compared with observations from meteorological stations. The statistical analysis of this study showed that wind speed and near-surface temperature prediction may be further improved with the updated and more accurate NALCMS dataset, particularly in the forecast covering 48 to 72 h. The Root Mean Square Error (RMSE) of the average wind speed reached a maximum reduction of up to 1.2 m s−1, whereas for the near-surface temperature there was a reduction of up to 0.6 °C. The RMSE of the average hourly precipitation was very similar between both experiments, however the location of precipitation was modified.

An Analysis of Spatio-Temporal Urbanization Patterns in Northwest China

Chinese metropolitan areas have been experiencing urbanization over the past decades, impacting biodiversity, carbon emissions, urban heat islands, and food security. Yet, systematic research on spatio-temporal urbanization patterns and drivers along the urban–rural gradient is rarely reported for northwest China. Here, we use land-use data from 1980 to 2015 to explore land-use change, urbanization intensity, and drivers in northwest China. Our results display direct and indirect effects of urban expansion on farmland loss, but also spatio-temporal heterogeneity in the urbanization patterns. While the earlier years were dominated by infill and land conversion close to city centers, the later years displayed sprawling urbanization following the constraints of terrain and administrative boundaries at the cost of farmland. Our regression analysis of spatial variables found a strong relationship with urban planning factors. The spatial analysis of urbanization patterns revealed indirect land-use change on former farmland. Furthermore, we found that regional geography and historic sites considerably influenced land conversion. Overall, our findings indicate the need for sustainable planning strategies that synthesize approaches to farmland and historic site protection and consideration of regionally specific landscape characteristics.

Rapid Local Urbanization around Most Meteorological Stations Explains the Observed Daily Asymmetric Warming Rates across China from 1985 to 2017

The increasing rate of the observed daily minimum temperatureTminhas been much higher than that of the observed daily maximum temperatureTmaxduring the past six decades across China. In this study, the local urbanization impact on these observed asymmetric warming rates was investigated. The latest released land-cover data with a 30-m spatial resolution and annual temporal resolution from 1985 to 2017 were used to quantify the urbanization ratios around weather stations. Although urbanized areas occupied only 2.25% of the landmass in China, the percentage of stations with an urbanization ratio over 20% increased from 22.1% to 68.2% during the period 1985–2017. Significant asymmetric warming rates at urban stations were identified, which were approximately 3 times larger compared to the average asymmetry observed at all 2454 stations in China. However, this asymmetry disappeared at rural stations. These differences are mainly due to the rapid local urbanization around most meteorological stations in China since 1985, which affected the spatial representation of observations and led to the observed asymmetry warming rates. The results reported here indicate that the observed asymmetric warming rate over China from 1985 to 2017 is an observational bias due to local urbanization around most stations rather than large-scale climate change. The results also explain the phenomenon that the observed warming rate ofTminremains higher than that ofTmaxafter 1990 when the surface solar radiation stops decreasing in China.

The impact of the Three Gorges Dam on the fate of metal contaminants across the river-ocean continuum

The Three Gorges Dam (TGD) is the world's largest hydropower construction. It can significantly impact contaminant transport in the Yangtze River-East China Sea Continuum (YR-ECSC). In addition to evaluating the impact of the TGD on the deposition of contaminants in the reservoir, we also address their cycles in the river below the dam and in the coastal East China Sea. A comprehensive study of metal contaminant transport along the YR-ECSC has not been previously attempted. We quantified the fates of mercury (Hg), arsenic (As), lead (Pb), cadmium (Cd) and chromium (Cr) within the YR-ECSC, and the impacts of the TGD, by sampling water and suspended particles along the Yangtze River during spring, summer, fall, and winter and by modeling. We found that the Yangtze River transports substantial amounts of heavy metals into the coastal ocean. In 2016, riverine transport amounted to 48, 5900, 11,000, 230, and 15,000 megagrams (Mg) for Hg, As, Pb, Cd, and Cr, respectively, while other terrestrial contributions were negligible. Metal flux into the coastal ocean was primarily derived from the downstream portion of the river (84-97%), while metals transported from upstream were largely trapped in the Three Gorges Reservoir (TGR, 72%-96%). For example, 34 Mg of Hg accumulated in the TGR owing to river damming, large-scale soil erosion, and anthropogenic point source releases, while 21 Mg of Hg was depleted from the riverbed downstream owing to the altered river hydrology caused by the TGD. Overall the construction of TGD resulted in a 6.9% net decrease in the Hg burden of the East China Sea, compared to the pre-TGD period.

Cool Roof and Green Roof Adoption in a Metropolitan Area: Climate Impacts during Summer and Winter

This study, for the first time, estimates the climate impacts of adopting green roofs and cool roofs on the seasonal urban climate of 16 cities that comprise the Yangtze River Delta metropolitan. We use a suite of regional climate simulation to compare the local climate impacts of the implementation of different roof strategies in summer and winter. The results indicate that in summer, the 2 m surface temperature reduced significantly when these two roof strategies are adopted, with peak reductions of 0.74 and 1.19 K for green roofs and cool roofs, respectively. The cooling impact of cool roofs is more effective than that of green roofs under the scenarios assumed in this study. Besides, rooted in the different mechanisms influencing urban heat flux, significant indirect effects were also observed: adopting cool roofs leads to a decreased precipitation in summer and an apparent reduction in wintertime temperatures in the urban area. Although cool roofs can be an effective way to reduce high temperatures during the summer, green roofs have fewer adverse impacts on other climate conditions. These results underline the need for comprehensive climate change policies that incorporate place-based solutions and extend beyond the nearly exclusive focus on summertime cooling.

Quantitatively evaluating the effect of urbanization on heat waves in China

In this study, the long-term trends and spatial characteristics of heat waves (HW) were analyzed using observations at a dense network of 2000 meteorological stations in China during 1961-2014. The contribution of urbanization to HW was quantitatively evaluated at the national scale based on a method of dynamically classifying urban and rural stations. The results based on different HW measures showed that HW in China became increasingly frequent, intense and longer, and emerged earlier and terminated later. More significant variation trends of HW were observed in southern and northern China, whereas relatively weaker and negative trends occurred in the Jianghuai-Plain region. The effect of urbanization on HW was evaluated in eight subregions of China, the results showed that the urbanization had an notable impact on the progression of HW. The urbanization contribution was pronounced in all subregions, especially in the southwestern, northern and southern China, where contributions were found to be >45%. In northwestern China, a negative urbanization effect was found in some HW measures, which was inferred to be related to the local dry climate. Overall, the contribution of urbanization to HW reached 30-50% for the urban areas of China. This study provided great insights in understanding the variations in extreme weather events and their relationships with urbanization.

Effects of Urbanization on Regional Extreme-Temperature Changes in China, 1960–2016

Urbanization in China has been expanding dramatically since 1978, significantly affecting the extreme temperature changes in cities, which is a vital indicator of urban climate change. To assess urban-related effect on regional extreme-temperature changes in China, this study employed high-resolution land use data to divide meteorological stations into rural stations, suburban stations, and urban stations, and evaluated the annual and seasonal changes in extreme minimum temperature (TNN), mean temperature (Tavg) and extreme maximum temperature (TXX) at each meteorological station. The result revealed that extreme temperature indices (TNN, TXX) and Tavg increased significantly from 1960 to 2016 with varied degrees in different seasons and different regions. Extreme temperature indices in high latitudes increased more rapidly than in low latitudes; while the trends in summer are slower than in other seasons. Urbanization effects on the trends of TNN, Tavg and TXX were all statistically significant, but urbanization effects on TNN and Tavg were more significant than TXX. The urbanization effects were more significant in low altitudes, especially in North, South, Northwest and Northeast China. In North, Northwest and Northeast China, the urban-related effects on temperature increase were mainly observed in spring and winter, but in South China, the urban-related effects were more evident in summer. This study is valuable for sustainable urban planning in China.

Inter- and intra-annual wind speed variabilities in wide valley regions of the middle reaches of the Yarlung Tsangpo River, China

Wind speed and variability are the most critical climatic factors affecting sand/dust storms, which have not been sufficiently studied in the middle reaches of the Yarlung Tsangpo River (MYR). In this study, wind speed variability was investigated using the moving average over shifting horizon method (MASH), combined with the modified Mann-Kendall test and Sen's slope based on data from the Tsetang, Lhasa, and Nyêmo meteorological stations during 1960-2015. The results indicated that annual wind speeds for the MYR wide valley regions declined significantly at decadal rates of - 0.216 m/s and underwent three stages from 1960 to 2015: an increasing trend from 1960 to 1975 (0.44 m/s per decade), a weakening until 2006 (- 0.46 m/s per decade), and a remarkable subsequent recovery (1.05 m/s per decade). Different variability trends were observed for the three stations: wind speed decreased significantly during all months at the Tsetang and Nyêmo stations, particularly in the spring, while for Lhasa, a non-significant wind speed increase was detected in summer, and the highest decline occurred in winter. The MASH method resulted in the effective visualization of different patterns, making seasonal process analysis and trend detection easier. In addition, the possible main causes for wind speed change were also discussed. The wind speed change in the study region was strongly associated with the large-scale atmospheric patterns, and the surface pressure gradient variability between the mid and low latitudes may have been a primary driving force. Positive/negative phases of the Pacific Decadal Oscillation (PDO) corresponded well with wind speed decreases/increases and were regarded as an indicator of wind speed variations. The effects of human activities associated with surface roughness change in the MYR were minor compared with the climatic changes.

Investigating Future Urbanization’s Impact on Local Climate under Different Climate Change Scenarios in MEGA-urban Regions: A Case Study of the Pearl River Delta, China

Urbanization is one of the most significant contributing factors to anthropogenic climate change. However, a lack of projected city land use data has posed significant challenges to factoring urbanization into climate change modeling. Thus, the results from current models may contain considerable errors in estimating future climate scenarios. The Pearl River Delta region was selected as a case study to provide insight into how large-scale urbanization and different climate change scenarios impact the local climate. This study adopts projected land use data from freely available satellite imagery and applies dynamic simulation land use results to the Weather Research and Forecasting Model (WRF). The simulation periods cover the summer periods in 2010 and 2029–2031, the latter of which is averaged to represent the year 2030. The WRF simulation used the observed local climate conditions in 2010 to represent the current scenario and the projected local climate changes for 2030 as the future scenario. Under all three future climate change scenarios, the warming trend is prominent (around 1–2 °C increase), with a widespread reduction in wind speed in inland areas (1–2 ms−1). The vulnerability of human health to thermal stress was evaluated by adopting the wet-bulb globe temperature (WBGT). The results from the future scenarios suggest a high public health risk due to rising temperatures in the future. This study provides a methodology for a more comprehensive understanding of future urbanization and its impact on regional climate by using freely available satellite images and WRF simulation tools. The simulated temperature and WBGT results can serve local governments and stakeholders in city planning and the creation of action plans that will reduce the potential vulnerability of human health to excessive heat.

Effects of Different Urbanization Levels on Land Surface Temperature Change: Taking Tokyo and Shanghai for Example

The influence of different urbanization levels on land surface temperature (LST) has attracted extensive attention. Though both are world megacities, Shanghai and Tokyo have gone through different urbanization processes that urban sprawl characterized by impervious surfaces was more notable in Shanghai than in Tokyo over the past years. Here, annual and seasonal mean LST in daytime (LSTday), in nighttime (LSTnight), and LSTdiff (annual and seasonal mean difference of LST in daytime and nighttime) were extracted from the MODIS LST product, MYD11A2 006, for 9 typical sites in Shanghai and Tokyo from 2003 to 2018, respectively. Then the effects of the urbanization levels were analyzed through Mann-Kendall statistics and Sen’s slope estimator. The trends of change in LSTday and LSTdiff for most sites in Shanghai, an urbanizing region, rose. In addition, there was no obvious regularity when considering seasonal factors, which could be due to the increasing fragmentized landscapes and scattered water bodies produced by urbanization. By comparison, the change in LST in Tokyo, a post-urbanizing region, was regular, especially in the spring. In other seasons, there was no obvious trend in temperature change regardless of whether the land cover was impervious surface or mountain forest. On the whole, vegetation cover and water bodies can mitigate the urban heat island (UHI) effect in urban regions. For more scientific urban planning, further analysis about the effect of urbanization on LST should focus on the compound stress from climate change and urbanization.

Impact of variations in vegetation on surface air temperature change over the Chinese Loess Plateau

Studying the drivers and combating the effects of climate change is more urgent than ever, particularly in regions with limited water and sensitive ecosystems. This study evaluated the effect of vegetation variation on surface air temperature (SAT) change in the Chinese Loess Plateau over 1982-2015 based on the 'observation minus reanalysis' (OMR) method. Observed temperature, ERA-Interim reanalysis temperature, and Global Inventory Modeling and Mapping Studies normalized difference vegetation index (NDVI) 3rd generation were used to analyze the relationship between OMR temperature (representing vegetation impact on SAT) and NDVI. Results showed that the Loess Plateau, especially its central-east areas, has undergone a rapid increase in NDVI and rapid decrease in OMR temperature during 1982-2015. This implies a strong cooling effect of vegetation restoration on SAT change. The mean annual NDVI (M_NDVI) and NDVI trend (Slope_NDVI) were negatively correlated with OMR temperature trend (Slope_OMR) on the Loess Plateau (P < 0.001). However, the relationships between M_NDVI (Slope_NDVI) and Slope_OMR varied among the arid, semi-arid, and semi-humid regions. As a result, the impacts of restoration of vegetation condition on SAT change during 1982-2015 were estimated to be 0.04, -0.01, and -0.07 °C decade^-1 in the arid, semi-arid, and semi-humid regions, respectively. For the entire Loess Plateau, the restoration of its vegetation condition led to a cooling effect of -0.02 °C decade^-1 during 1982-2015 and a cooling effect of -0.05 °C in the period following the implementation of the Grain for Green Project (GGP). Moreover, among the three major land use types of the Loess Plateau (i.e., grassland, farmland, and forest), vegetation restoration of forest demonstrated the most obvious cooling effect (-0.06 °C decade^-1 during 1982-2015). These results are the first quantitative estimation of the impact of vegetation variation on SAT across the entire Loess Plateau, and demonstrate the ecological effect of afforestation efforts in the southeastern areas in terms of climate warming alleviation.

Variable Urbanization Warming Effects across Metropolitans of China and Relevant Driving Factors

Urbanization is mainly characterized by the expansion of impervious surface (IS) and hence modifies hydrothermal properties of the urbanized areas. This process results in rising land surface temperature (LST) of the urbanized regions, i.e., urban heat island (UHI). Previous studies mainly focused on relations between LST and IS over individual city. However, because of the spatial heterogeneity of UHI from individual cities to urban agglomerations and the influence of relevant differences in climate background across urban agglomerations, the spatial-temporal scale independence of the IS-LST relationship still needs further investigation. In this case, based on Landsat-8 Operational Land Imager and Thermal Infrared Sensor (Landsat 8 OLI/TIRS) remote sensing image and multi-source remote sensing data, we extracted IS using VrNIR-BI (Visible red and NIR-based built-up Index) and calculated IS density across three major urban agglomerations across eastern China, i.e., the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) to investigate the IS-LST relations on different spatial and temporal scales and clarify the driving factors of LST. We find varying warming effects of IS on LST in diurnal and seasonal sense at different time scales. Specifically, the IS has stronger impacts on increase of LST during daytime than during nighttime and stronger impacts on increase of LST during summer than during winter. On different spatial scales, more significant enhancing effects of IS on LST can be observed across individual city than urban agglomerations. The Pearson correlation coefficient (r) between IS and LST at the individual urbanized region can be as high as 0.94, indicating that IS can well reflect LST changes within individual urbanized region. However, relationships between IS and LST indicate nonlinear effects of IS on LST. Because of differences in spatial scales, latitudes, and local climates, we depicted piecewise linear relations between IS and LST across BTH when the IS density was above 10% to 17%. Meanwhile, linear relations still stand between IS density and LST across YRD and PRD. Besides, the differences in the IS-LST relations across urban agglomeration indicate more significant enhancing effects of IS on LST across PRD than YRD and BTH. These findings help to enhance human understanding of the warming effects of urbanization or UHI at different spatial and temporal scales and is of scientific and practical merits for scientific urban planning.

Desertification Control Practices in China

Desertification is a form of land degradation principally in semi-arid and arid areas influenced by climatic and human factors. As a country plagued by extensive sandy desertification and frequent sandstorms and dust storms, China has been trying to find ways to achieve the sustainable management of desertified lands. This paper reviewed the impact of climate change and anthropogenic activities on desertified areas, and the effort, outcome, and lessons learned from desertification control in China. Although drying and warming trends and growing population pressures exist in those areas, the expanding trend of desertified land achieved an overall reversal. In the past six decades, many efforts, including government policies, forestry, and desertification control programs, combined with eco-industrialization development, have been integrated to control the desertification in northern China. Positive human intervention including afforestation, and the rehabilitation of mobile sandy land, and water conservation have facilitated the return of arid and semi-arid ecosystems to a more balanced state. China’s practices in desertification control could provide valuable knowledge for sustainable desertified land management on a global scale.

Proposing a Paradigm Shift in Rural Electrification Investments in Sub-Saharan Africa through Agriculture

Almost one billion people in the world still do not have access to electricity. Most of them live in rural areas of the developing world. Access to electricity in the rural areas of Sub-Saharan Africa is only 28%, roughly 600 million people. The financing of rural electrification is challenging and, in order to accomplish higher private sector investments, new innovative business models have to be developed. In this paper, a new approach in the financing of microgrid electrification activities is proposed and investigated. In this approach, agriculture related businesses take the lead in the electrification activities of the surrounding communities. It is shown that the high cost of rural electrification can be met through the increased value of locally produced products, and cross-subsidization can take place in order to decrease the cost of household electrification. The approach is implemented in a case study in Rwanda, through which the possibility of local agricultural cooperatives leading electrification activities is demonstrated.

Heat health risk assessment in Philippine cities using remotely sensed data and social-ecological indicators

More than half of the world’s population currently live in urban areas and are particularly at risk from the combined effects of the urban heat island phenomenon and heat increases due to climate change. Here, by using remotely sensed surface temperature data and social-ecological indicators, focusing on the hot dry season, and applying the risk framework of the Intergovernmental Panel on Climate Change, we assessed the current heat health risk in 139 Philippine cities, which account for about 40% of the country’s total population. The cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high. The most vulnerable cities are, however, found mainly outside the national capital region, where sensitivity is higher and capacity to cope and adapt is lower. Cities with high levels of heat vulnerability and exposure must be prioritized for adaptation. Our results will contribute to risk profiling in the Philippines and to the understanding of city-level heat health risks in developing regions of the Asia-Pacific.

Evaluating the heat risk among city dwellers is important. Here, the authors assessed the heat risk in Philippine cities using remote sensing data and social-ecological indicators and found that the cities at high or very high risk are found in Metro Manila, where levels of heat hazard and exposure are high.

Research on Ecological Infrastructure from 1990 to 2018: A Bibliometric Analysis

Ecological infrastructure (EI), as the composite system on which the sustainable development of cities depends, has attracted worldwide attention. Considering refined methodologies and broad scope, researchers lacked overall understanding of research patterns and evolutionary processes on EI-related issues. In this study, we applied the bibliometric approach to describe the current situation of EI-related research, and reveal research trends. Based on the Web of Science Core Collection, the bibliometric analysis of EI-related publications from 1990 to 2018 was performed to discuss the history and present research situation of EI, and preview research prospect. The results showed that: (1) the number of EI-related publications has surged astonishingly worldwide over the last three decades; (2) countries in Europe and North America were the first to invest heavily in EI-related research, while China started later but subsequently developed rapidly; (3) the EI-related research focuses were EI-related management, methods for countering extreme meteorological phenomena, providing ecosystem services, and protecting biodiversity; and (4) the EI-related research frontiers included the design of EI, policy research on EI, role of EI in environmental governance, and research on the adaptability of EI.

The effect of urbanization and climate change on the mosquito population in the Pearl River Delta region of China

The rising incidence of mosquito-borne diseases is a global concern. Changes in regional climate, due to urbanization and global greenhouse gas concentrations, may affect the ecology of mosquitoes and mosquito-transmitted pathogens. The effects of changes in climate on mosquito population dynamics are complex but critical and urgent for implementing more effective public health policies. This study quantified the impact of urbanization and global climate change on the population of the mosquito species, Culex quinquefasciatus, in the Pearl River Delta region in southern China-an area that has undergone substantial urbanization and is expected to experience changes in climate. This study employed a mechanistic model to simulate mosquito population dynamics under various greenhouse gas emission and land-cover change scenarios based on climate data provided by a state-of-the-art regional climate model. Our results show a 12.6% decrease in the annual mosquito population in newly urbanized areas and a 5.9% increase in the annual mosquito population in existing urban areas. Furthermore, changing climate conditions are projected to cause a 15-17% reduction in the total annual mosquito population; however, the change will not be uniform throughout the year. Peak months exhibit a reduction in population, whereas non-peak months show a significant increase. These findings suggest mosquito control strategies may need to be adjusted to respond to the impacts of urbanization and climate change on mosquito population dynamics to maximize effectiveness. Region specific, quantitative analyses of environmental impacts on mosquito-borne disease ecology, like this study, are needed to provide policy makers with a scientific reference to guide the formation of effective transmission intervention strategies.

The Double-Edged Sword of Urbanization and Its Nexus with Eco-Efficiency in China

Urbanization has made tremendous contributions to China's economic development since its economic reforms and opening up. At the same time, population agglomeration has aggravated environmental pollution and posed serious challenges to China's environment. This article empirically investigates the impacts of China's urbanization on eco-efficiency, comprehensively reflecting economic growth, resource input, and waste discharge. We first measured the provincial eco-efficiency in China from 2005 to 2015 using the Super Slack-Based model (Super-SBM). We then constructed a spatial model to empirically analyze the effects of urbanization on eco-efficiency at the national level, and at four regional levels. The results indicated that the regional eco-efficiency in China has fluctuated, but is generally improving, and that a gap between regions was evident, with a trend toward further gap expansion. We observed an effect of spatial spillover in eco-efficiency, which was significant and positive for the whole country, except for the western region. The influence of urbanization on China's eco-efficiency exhibited a U-curve relationship. The changing trend in the eastern, central, and western regions was the same as that in the whole country; however, the trend exhibited an inverted U-curve relationship in the northeastern region. To the best of our knowledge, covering a time period of 2005-2015, this article is the first of its kind to study the impact of urbanization on eco-efficiency in China at both the national and regional levels. This study may help policy-makers to create sustainable policies that could be helpful in balancing urbanization and the ecological environment.

Trend Analysis of Urban Heat Island Intensity According to Urban Area Change in Asian Mega Cities

Urban heat island (UHI) is a phenomenon that occurs in cities worldwide. Therefore, there is an increasing need for studies on the changes in UHI intensity and long-term trends based on macroscopic characteristics related to urbanization. In this study, changes in seasonal UHI intensity based on urban area were analyzed for eight Asian mega cities from 1992–2012. The results indicate that the change in pattern of UHI intensity varies for different cities and seasons. UHI intensity increased as the urban area size increased. Furthermore, the dependency of UHI intensity on the economic situation was also demonstrated. With respect to the seasons, significantly increasing trends appeared during the summer. Moreover, depending on urban characteristics such as geography and climate, increasing trends appeared during other seasons. Population was also found to affect UHI intensity by generating anthropogenic heat; however, its effect as an individual factor appeared to be insignificant. This is a macroscale study that analyzes the effect of urban area size on UHI intensity. Future studies on urbanization factors and levels influencing the UHI intensity using higher resolution materials are required