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Wastewater-based epidemiology (WBE) was applied to estimate illicit drugs consumption at a provincial scale in southwest China. A large-scale wastewater sampling campaign was carried out from October to November in 2021 in 156 different wastewater treatment plants (WWTPs). Two 24-h composite influent wastewater samples were collected in each WWTP. Concentrations of 11 illicit drugs or their metabolites were determined using liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS). Benzoylecgonine, cocaine, 6-monoacetylmorphine, norketamine, 3,4-methylenedioxymethamphetamine (MDMA), and MDA were not detected in any of the wastewater samples. Methamphetamine and morphine were detected in >84% of samples, while ketamine was found in about 6% of the samples. The city-specific population-weighted consumption of methamphetamine and ketamine were in the range of 0.6-49.7 and N.D.-7.0 mg 1000 inh -1 day -1 , respectively, with provincial population-weighted values of 22.6 and 2.4 mg 1000 inh -1 day -1 in southwest China. The city-specific load of morphine varied from 3.2 to 10.2 mg 1000 inh -1 day -1 , with provincial population-weighted load of 6.7 mg 1000 inh -1 day -1 . Taking into account therapeutic use of morphine and codeine, the provincial heroin consumption was estimated to be 10.3 mg 1000 inh -1 day -1 , ranging from 1.7 to 18.5 mg 1000 inh -1 day -1 in 21 cities. Overall, the patterns of illicit drugs use were similar across southwest China, with high prevalence of methamphetamine and heroin, but relatively low use of ketamine. These findings could provide accurate drugs consumption information for timely identifying potential hotspots of illicit drugs use in southwest China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

As a significant carbon emission source with high growth potential, the air transport sector plays a crucial role in China's decarbonisation efforts. However, the spatial pattern and evolutionary dynamics of aviation carbon emissions in China have not been thoroughly studied. This study proposed a framework to reveal the spatial characteristics and influencing factors of aviation carbon emissions at the city level. Using data from 2019 to construct the aviation carbon emissions network of China (ACENC), the novelty of the study lies in the subdivision of carbon emissions of air passenger transport into cities and intercity lines in China, which helps to reveal the spatial characteristics of individual cities in the intercity network. Beijing, Shanghai, Shenzhen, Chengdu, and Guangzhou were the cities with the highest carbon emissions, and the routes between these cities caused a significant amount of carbon emissions. >80 % of the total carbon emissions can be attributed to two communities in the network, owing to their large size and strong connections. Correlation analysis indicates that a city's carbon emissions are significantly related to its demographic and economic attributes as well as its connection with other cities, while a city's carbon emission intensity may be influenced by its centrality in the whole network and the structure of the community to which it belongs. Overall, the presented results provide directions for stakeholders and policymakers to regulate carbon emissions from air transportation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This study intends to further reveal the relationship between air pollution and public health on a city scale in China and explore the spillover effect among cities. On the basis of collecting the panel data of 110 cities in the Yangtze River Economic Belt from 2010 to 2018, we establish a spatial econometric model to analyze the impacts of air pollution, economic development, and other factors on public health. According to the results, a significant spatial correlation exists between the public health and air pollution levels in all of the cities in the Yangtze River Economic Belt. Air pollution also shows a spillover effect among these cities; the relationships between the industrial fume (dust) emissions, industrial sulfur dioxide emissions, and particulate matter (PM 2.5) concentration and the public health level are not simple linear relationships, but instead U-shaped curvilinear relationships. The economic development in recent years has contributed to the improvement of the public health level of the cities in the Yangtze River Economic Belt. The economic development of their neighboring cities, however, has adversely affected the public health levels of these cities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The complexity and heterogeneity of urban land surfaces result in inconsistencies in near-surface winds, which in turn influence the diffusion and dispersion of air pollutants. In this study, we classified urban surface wind fields, quantified their steadiness, duration, and influence on air quality using hourly wind observations from 50 meteorological stations, as well as hourly PM 2.5 and NO 2 concentrations from 18 monitoring stations during 2017-2018 in Shenzhen, a mega city in southern China. We found that the K-means clustering technique was reliable for distinguishing surface wind patterns within the city. Urban surface-wind patterns greatly affected pollutant concentrations. When dominated by calm, northerly wind, high PM 2.5 /NO 2 concentration episodes occurred more frequently than those during other surface wind patterns. The urban surface transport index (USTI) was used to quantify the steadiness of surface wind classes. High pollutant concentrations were present during both high wind speed periods with a large USTI, indicating external pollutant transport, and during low wind speed periods with a small USTI, indicating pollutant accumulation. The threshold durations for surface wind fields (TDSWF) was proposed to quantify the impacts of surface wind persistence on air quality. We found that poor air quality occurred during the first several hours of a dominant wind pattern, indicating that transitions between wind patterns should be a particular focus when assessing air-quality deterioration. USTI and TDSWF are potentially applicable to other urban areas, owing to their clear definitions and simple calculation. In combination with wind speeds, these indices are likely to improve air quality forecasting and strategic decisions on air pollution emergencies, based on long time series of multiple wind and pollutant concentration observations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Introduction: In France, a heat warning system (HWS) has been implemented almost two decades ago and rely on some official heat wave (HW) definitions. However, no study has compared the burden associated with a large set of alternative HW definitions to the official definitions. Such comparison could be particularly helpful to identify HW conditions for which effective HWS would minimize the health burden across various geographical contexts and possibly update thresholds to trigger HWS. The aim of this study is to identify (and rank) definitions that drive the highest health burden in terms of mortality to inform future HWS across multiple cities in France., Methods: Based on weather data for 16 French cities, we compared the two official definitions used in France to: i) the Excess Heat Factor (EHF) used in Australia, and ii) 18 alternative hypothetical HW definitions based on various combinations of temperature metrics, intensity, and duration. Propensity score matching and Poisson regressions were used to estimate the effect of each HW exposure on non-accidental mortality for the May-September period from 2000 to 2015., Results: The associations between HW and mortality differed greatly depending on the definition. The greatest burden of heat was 1,055 (95% confidence interval "CI": [856; 1,302]) deaths per summer and was obtained with the EHF. The EHF identified HW with 2.46 (95% CI: [1.92; 3.58]) or 8.18 (95% CI: [6.63; 10.61]) times the global burden at the national level obtained with the climatological indicator of the French national weather service and the HW indicator of the French national HWS, respectively and was the most impactful definition pattern for both temperate oceanic and Mediterranean climate types., Conclusion: Identifying the set of extreme heat conditions that drive the highest health burden in a given geographical context is particularly helpful when designing or updating heat early warning systems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Background: Many studies have explored the epidemiological characteristics of influenza. However, most previous studies were conducted in a specific region without a national picture which is important to develop targeted strategies and measures on influenza control and prevention., Objectives: To explore the association between ambient temperature and incidence of influenza, to estimate the attributable risk from temperature in 30 Chinese cities with different climatic characteristics for a national picture, and to identify the vulnerable populations for national preventative policy development., Methods: Daily meteorological and influenza incidence data from the 30 Chinese cities over the period 2016-19 were collected. We estimated the city-specific association between daily mean temperature and influenza incidence using a distributed lag non-linear model and evaluated the pooled effects using multivariate meta-analysis. The attributable fractions compared with reference temperature were calculated. Stratified analyses were performed by region, sex and age., Results: Overall, an N-shape relationship between temperature and influenza incidence was found in China. The cumulative relative risk of the peak risk temperature (5.1 °C) was 2.13 (95%CI: 1.41, 3.22). And 60% (95%eCI: 54.3%, 64.3%) of influenza incidence was attributed to ambient temperature during the days with sensitive temperatures (1.6°C-14.4 °C). The ranges of sensitive temperatures and the attributable disease burden due to temperatures varied for different populations and regions. The residents in South China and the children aged ≤5 and 6-17 years had higher fractions attributable to sensitive temperatures., Conclusions: Tailored preventions targeting on most vulnerable populations and regions should be developed to reduce influenza burden from sensitive temperatures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Recently, elevated blood pressure (BP) and hypertension (HTN) have caused a huge burden of health loss. Previous studies used ambient air pollutants as a proxy for individual exposure, limiting the assessment of its multiple exposure to health effects. For the first time, this study constructed individual PM 2.5 component (SO 4 2- , NO 3 - , NH 4 + , OM, and BC) exposure model DAG (Directed Acyclic Graph), DAG-oriented generalized linear model and random forest model, and explored the effects of single and multiple exposures to PM 2.5 components on BP at different stages by the generalized linear model (GLM) and Quantile g-Computation (QgC) model based on a large cohort study in China. We defined BP in four stages according to the 2017 ACC/AHA guidelines. After excluding the lack of key information, the cohort analyses ultimately included 9031 participants. Our results showed that the individual PM 2.5 component exposure model had good efficacy. Single or multiple exposure to PM 2.5 components had significant positive effects on normal BP to elevated BP and elevated BP to stage 1 HTN. In addition, males, the elderly and urban residents were more sensitive to PM 2.5 components. This study provided implications for environmental exposure assessment and control of particulate pollution in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Many studies have shown that fine particulate matter can cause health problems. Thus, effectively controlling fine particulate matter concentration is an important issue around the world. The Taiwan Environmental Protection Administration (TWEPA) divides Taiwan into seven air quality zones based on counties and cities for managing air quality and analyzing pollution transmission. However, this artificial division by administrative areas relatively poorly match natural conditions and topographical and geographic factors and hence poorly represent air quality characteristics. This study proposes an air quality sensitive map analysis framework, which uses hierarchical agglomerative clustering with empirical orthogonal function and analysis of variance methods, to provide more detailed, reasonable, and township-level air quality zones incorporating the different spatial-temporal characteristics over the region. The risk concept is introduced to evaluate PM 2.5 risk sensitivity for each administrative district, combining three aspects: hazard (PM 2.5 exceedance probability), exposure (population density of sensitive groups), and vulnerability (average wind speed). Considering air quality spatial-temporal characteristics, Taiwan can be optimally divided into 14 air quality zones. PM 2.5 risk is highest for western inland towns than western coastal towns, with eastern regions exhibiting least risk. Adopting the proposed air quality zones and clarifying high risk areas allows PM 2.5 causes to be identified for different air quality zones. This allows a targeted control strategy for high risk areas to effectively improve domestic air quality. The proposed model also provides powerful reference for environmental management and environmental impact assessment for future construction and development., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Soon after its emergence, COVID-19 became a global problem. While different types of vaccines and treatments are now available, still non-pharmacological policies play a critical role in managing the pandemic. The literature is enriched enough to provide comprehensive, practical, and scientific insights to better deal with the pandemic. This research aims to find out how the built environment and human factors have affected the transmission of COVID-19 on different scales, including country, state, county, city, and urban district. This is done through a systematic literature review of papers indexed on the Web of Science and Scopus. Initially, these databases returned 4264 papers, and after different stages of screening, we found 166 relevant papers and reviewed them. The empirical papers that had at least one case study and analyzed the effects of at least one built environment factor on the spread of COVID-19 were selected. Results showed that the driving forces can be divided into seven main categories: density, land use, transportation and mobility, housing conditions, demographic factors, socio-economic factors, and health-related factors. We found that among other things, overcrowding, public transport use, proximity to public spaces, the share of health and services workers, levels of poverty, and the share of minorities and vulnerable populations are major predictors of the spread of the pandemic. As the most studied factor, density was associated with mixed results on different scales, but about 58 % of the papers reported that it is linked with a higher number of cases. This study provides insights for policymakers and academics to better understand the dynamic roles of the non-pharmacological driving forces of COVID-19 at different levels., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Vertical greening systems (VGS) are implemented in the building envelope to address challenges such as the urban heat island effect, energy reduction, air purification, support of biodiversity and recently greywater treatment (wastewater without urine and faeces) for reuse purposes. In this context, providing and using treated wastewater is a crucial point, as generally VGS are irrigated with tap water and thereby increase urban water depletion and pollution. In this study, we evaluate the multifunctionality of a pot-based VGS irrigated with untreated greywater and capable, as well, of acting as a greywater treatment system. The full-scale experimental system uses a low-tech irrigation technique and was investigated for different irrigation water volumes to identify the needed water demand to maximize local cooling by evapotranspiration and suitable plants for the different water conditions and water types. Plant development and greywater treatment capabilities were monitored from April 2020 until September 2021. Based on the highest irrigation volume, a local air temperature reduction of up to 3.4 °C was measured. The removal efficiencies for treating greywater were COD 80 %, TOC 74 %, TNb 70 %, NH 4 -N 81 % and Turbidity 79 %, respectively, and showed a decrease in the second year of operation. Therefore, the results support the need to develop more robust systems, since up to now mainly short-term experiments have been reported in literature., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Author(s). Published by Elsevier B.V. All rights reserved.)

Ammonia (NH 3 ) is the most prevalent alkaline gas in the atmosphere and plays a critical role in air pollution and public health. However, scientific debate remains over whether agricultural emissions (e.g., livestock and fertilizer application) dominate NH 3 in urban atmosphere in China, which is one of the largest NH 3 emitters in the world. In this study, we first simultaneously collected the fine atmospheric particles (PM 2.5 ) at two heights (ground and 488 m) using the atmospheric observatories in Canton Tower, Guangzhou city, China for the measurements of stable nitrogen isotope composition in ammonium (δ 15 N-NH 4 + ). Our results showed that the average δ 15 N-NH 4 + value at the ground and the 488 m observatory were 16.9 ‰ and 3.8 ‰, respectively, implying that NH 4 + aerosols between the two heights probably have different sources. Moreover, we found that the δ 15 N-NH 4 + in Guangzhou or maybe in adjacent cities of the Pearl River Delta region as well, suggesting that the emission inventory of NH 4 + aerosol at the ground observatory was mainly derived from non-agricultural activities (76 %, e.g., vehicular exhaust), with the rest from agricultural sources (24 %). As for the 488 m observatory, the contribution of non-agricultural sources was 53 %, which is lower than the ground observatory. This is expected as the lower air receives more impacts from the local urban emission. However, the current "bottom-up" emission inventory illustrates that only ~20 % NH 3 in Guangzhou is associated with non-agricultural emissions, which is significantly lower than our δ 15 N-based results. Overall, our findings strongly imply that non-agricultural sources dominate the urban NH 3 in Guangzhou or maybe in adjacent cities of the Pearl River Delta region as well, suggesting that the emission inventory of NH 3 in this region probably is urgently needed to be revisited in future studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Already in early 2000s, concerns have been growing in the EU about increasing use of cocaine and it is estimated that below 1 % of the population administer the drug by smoking crack cocaine. New available data suggests an increase in the use of crack cocaine and an increase in the number of crack cocaine users entering treatment has been reported in several European countries. Robust estimations of crack cocaine use are however not available yet. The use of crack cocaine has long been associated with severe adverse socio-economic conditions as well as mental health problems, such as suicide ideation and depression. The aim of this study was to assess spatial trends in population-normalized mass loads of crack cocaine biomarkers (i.e., anhydroecgonine and anhydroecgonine methyl ester) in 13 European cities in six countries (the Netherlands, Belgium, Ireland, Portugal, Spain and Italy). Furthermore, temporal trends over a five-year period were evaluated through the analysis of historic samples collected in the Netherlands. Finally, the stability of the crack cocaine biomarkers in wastewater was investigated through batch experiments. The samples were analyzed with a new developed and validated hydrophilic interaction liquid chromatography coupled to mass spectrometry method. Targeted crack cocaine biomarkers were found in all cities. Also, crack cocaine biomarker was detected in wastewater from 2017 to 2021 in the Netherlands, but no significance between the years were found. With respect to biomarker in-sample stability, AEME was found to be stable in wastewater. This study assessed crack cocaine use for the first time on a broad scale, both temporal and in cities across Europe, with wastewater-based epidemiology and it shows the importance of wastewater analysis to monitor community loads of crack cocaine use., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Excessive urban temperature exerts a substantially negative impact on urban sustainability. Three-dimensional (3D) landscapes have a great impact on urban thermal environments, while their heat conditions and driving factors still remain unclear. This study mapped urban 3D neighborhoods and their associated SUHI (surface urban heat island) intensities in summer daytime across 57 Chinese cities, and then explored their relationships, driving factors as well as implications. Nine categories of urban 3D neighborhoods existed in Chinese cities and the 3D neighborhood of High Density & Medium Rise (HDMR) contributed the largest share of urban areas. The distribution of 3D neighborhoods varied among cities due to their distinct natural and economic traits. The average SUHI intensity can amount to 4.27 °C across all Chinese 3D neighborhoods. High Density & Low Rise (HDLR) and HDMR presented higher SUHI intensities than other 3D neighborhoods in China. Urban green space (UGI) and building height (BH) had great influences on SUHI intensities. The relative contribution of UGI decreased with the increase of building density and building height, but BH presented the opposite trend. The interaction of urban 3D landscapes and function zones led to highly complicated urban thermal environments, with higher SUHI intensities in industrial zones. Besides, the SUHI intensities of 3D neighborhoods presented great diurnal and seasonal variations, with higher SUHI intensities in HDHR and HDMR at nighttime in winter and summer. What's more, urban residents may suffer unequal heat risk inside cities due to the deviations of SUHI intensities among different 3D neighborhoods. It could be a highly effective way to mitigate SUHI effects in cities by increasing urban greening and improving urban ventilation., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The improvement of carbon emission efficiency is crucial to the realization of the global carbon peaking and carbon neutrality goals. Based on the panel data of 282 cities from 2004 to 2018 in China, this paper employs the stochastic frontier analysis approach combined with the Sheppard distance function to calculate the total factor carbon emission efficiency of each city. Regarding the low-carbon pilot city policy as a quasi-natural experiment, we evaluate the impact of the pilot policy on carbon emission efficiency and its spatial spillover effect using the spatial difference-in-differences model. The results show that the pilot policy can significantly improve the carbon emission efficiency and has long-term dynamic effects. Also, the effect of the policy has spatial spillover, and has a positive impact on the neighboring cities. Mechanism analysis implies that optimal allocation of resources, energy conservation and green technology innovation make the low-carbon policy play an important intermediary role in promoting carbon emission efficiency. Besides, the effects of the pilot policy have obvious heterogeneity, especially cities in large, higher population densities and the north. These findings reveal that low-carbon pilot city policies are indispensable for both implementing the dual-carbon strategy and winning the defense for the blue sky., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The emissions reduction of CO 2 and air pollutants are the main task in China. The two have the same roots and they interact with each other. However, CO 2 and air pollutants are quite different in space, so it is of great practical significance to explore the spatial differences of their synergy. As PM 2.5 and O 3 are more concerned at present, thus, this paper examined the decoupling of CO 2 , PM 2.5 and O 3 from GDP in China's 296 cities using the latest available data from 2015 to 2016. And the spatial differences of synergy among CO 2 , PM 2.5 and O 3 were quantitatively analyzed by using spatial autocorrelation analysis and geographically weighted regression model. The results showed that: (1) The cities achieving the three synergy emissions reduction were mainly in the southeast of China. (2) Only 26 cities had achieved the strong decoupling of CO 2 , PM 2.5 and O 3 from GDP. (3) The synergy characteristics between CO 2 and PM 2.5 , CO 2 and O 3 were different. This paper put forward the policies according to the conclusions., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

This study used panel data for 2166 county-level units in China between 2000 and 2017 to characterize carbon productivity's temporal and spatial evolution in Chinese counties. The "catch-up effect" of carbon offsets between counties was examined, and this was used to measure the carbon offset potential and analyze its spatial differences. The results indicated that: (1) China's carbon productivity increased from 2000 to 2017; carbon productivity in eastern China was the highest, and carbon productivity in northeast China was the lowest. A polarization to unipolarization evolutionary trend was evident. (2) Considering the spatial differences in carbon productivity, the overall difference in carbon productivity in China from 2000 to 2017 first decreased and then increased; the contribution rate of differences between cities and counties to the overall difference was relatively stable, at around 39.88 %. The contribution rate of the differences between zones to the overall difference was the lowest, remaining stable at around 2.49 %. (3) In terms of the spatial distribution of the carbon offset potential, the eastern region exhibited the highest average carbon offset potential. The carbon offset potential of China exhibited a "high in the north and low in the south; low in the west and high in the east" spatial pattern., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Background: Studies on the obesogenic effect of air pollution on children have been mixed and sparse. Moreover, due to insufficient air monitoring, few studies have investigated the role of more tiny but unregulated particles (ambient particles with a diameter of 0.1 μm or less, ultrafine particles)., Objective: We sought to explore the associations between long-term exposure to ambient ultrafine particles (UFPs) and childhood obesity in Chinese children., Methods: In this cross-sectional study, we randomly recruited 47,990 children, aged 6-18 years, from seven cities in Northeastern China between 2012 and 2013. Child age- and sex-specific z-scores for body mass index (BMI Z-score) and weight status were generated using the World Health Organization growth reference. Four-year average concentrations of UFPs and airborne particulates of diameter ≤ 1 μm (PM 1 ), ≤2.5 μm (PM 2.5 ), and ≤10 μm (PM 10 ) were estimated at home, using neural network simulated WRF-Chem model and spatiotemporal model, respectively. Confounder-adjusted generalized linear mixed models examined the associations between air pollution and BMI Z-score and the prevalence of childhood obesity., Result: We found that UFPs exposure was associated with greater childhood BMI Z-score and a higher likelihood of obesity. Compared with the lowest quartile, higher quartiles of UFPs were associated with greater odds for obesity prevalence in children (i.e., the adjusted OR was 1.25; 95 % CI, 1.12-1.39; 1.43; 95 % CI, 1.27-1.61; and 1.41; 95 % CI, 1.25-1.58 for the second, third, and fourth quartile, respectively). Similar associations were observed for PM 1 , PM 2.5 , and PM 10 , and were greater in boys and children living close to roadways., Conclusions: Long-term UFPs exposure was associated with a greater likelihood of childhood obesity, and stronger associations on BMI Z-score were observed in boys and children living close to roadways. This study indicates that more attention should be paid to the health effects of UFPs, and routinely monitoring of UFPs should be considered., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

PM 2.5 characterizations are essential in understanding its impact on the health of the exposed population. Sampled PM 2.5 by Mani et al. (2020) was characterized to determine atmospheric metal concentration and inhalation health risk in Suva and Lautoka Cities, the only two cities in Fiji and one of the largest in the South Pacific Islands. Twenty-two elements (Al, As, Ba, Ca, Cd, Co, Cr, Cu, Fe, K, Mg, Mn, Mo, Na, Ni, P, Pb, S, Si, Sr, V, Zn) were analyzed using ICP-OES. Black Carbon (BC) sampling was also done at three different sites in Suva City, namely, Fiji National University Samabula Intersection site, Suva City Bus Station site and the Reservoir Road Community Settlement Site as well as at Lautoka City Bus Station. Mean BC concentrations over the sampling period were found to be 3.9 ± 2.9 (median = 3.3 μg/m 3 ), 2.6 ± 2.7 μg/m 3 (median = 1.7 μg/m 3 ), 2.4 ± 2.3 μg/m 3 (median = 1.7 μg/m 3 ) and 4.0 ± 4.7 μg/m 3 (median = 2.4 μg/m 3 ) respectively. Health risk assessments (Carcinogenic Risk (CR) and Non-Carcinogenic Risk (HQ)) were also done to assess the risk of inhalation exposure in adults and children. The Hazard Index for children in Lautoka (HI = 1.03) was found to slightly exceed the safe level of 1. This study provides the first inventory of atmospheric particulate bound metal concentrations and diurnal BC profiles in Fiji and informs policy makers and scientists for further studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Dengue is an endemic disease in more than 100 countries, but there are few studies about the effects of hydroclimatic variability on dengue incidence (DI) in tropical dryland areas. This study investigates the association between hydroclimatic variability and DI (2008-2018) in a large tropical dryland area. The area studied comprehends seven municipalities with populations ranging from 32,879 to 2,545,419 inhabitants. First, the precipitation and temperature impacts on interannual and seasonal DI were investigated. Then, the monthly association between DI and hydroclimatic variables was analyzed using generalized least squares (GLS) regression. The model's capability to reproduce DI given the current hydroclimatic conditions and DI seasonality over the entire time period studied were assessed. No association between the interannual variation of precipitation and DI was found. However, seasonal variation of DI was shaped by precipitation and temperature. February-July was the main dengue season period. A precipitation threshold, usually above 100 mm, triggers the rapid DI rising. Precipitation and minimum air temperature were the main explanatory variables. A two-month-lagged predictor was relevant for modeling, occurring in all regressions, followed by a non-lagged predictor. The climate predictors differed among the regression models, revealing the high spatial DI variability driven by hydroclimatic variability. GLS regressions were able to reproduce the beginning, development, and end of the dengue season, although we found underestimation of DI peaks and overestimation of low DI. These model limitations are not an issue for climate change impact assessment on DI at the municipality scale since historical DI seasonality was well simulated. However, they may not allow seasonal DI forecasting for some municipalities. These findings may help not only public health policies in the studied municipalities but also have the potential to be reproducible for other dryland regions with similar data availability., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Previous research has shown that walking and cycling could help alleviate stress in cities, however there is poor knowledge on how specific microenvironmental conditions encountered during daily journeys may lead to varying degrees of stress experienced at that moment. We use objectively measured data and a robust causal inference framework to address this gap. Using a Bayesian Doubly Robust (BDR) approach, we find that black carbon exposure statistically significantly increases stress, as measured by Galvanic Skin Response (GSR), while cycling and while walking. Augmented Outcome Regression (AOR) models indicate that greenspace exposure and the presence of walking or cycling infrastructure could reduce stress. None of these effects are statistically significant for people in motorized transport. These findings add to a growing evidence-base on health benefits of policies aimed at decreasing air pollution, improving active travel infrastructure and increasing greenspace in cities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Residential formaldehyde pollution is one of the leading residential harmful pollutants with a large production and consumption globally and remains much uncertainty in Chinese families with huge health burden for children worldwide. A multi-center observation study from 11 cities was conducted to investigate residential formaldehyde pollution levels measured by phenol reagent spectrophotometry. Data on household characteristics and schoolchildren's health were collected by questionnaire. The median concentration of residential formaldehyde was 0.025 (0.002-0.281) mg/m 3 among 11 cities with the total exceeding standard rate of 7.40% according to the reference value of 0.10 mg/m 3 (1-h average). Residential formaldehyde pollution in warm season, bedrooms and northern cities was more serious than that in cold season, living rooms and southern cities, respectively. The potential influencing factors of residential formaldehyde included household characteristics (distance from a traffic road, building history, residence duration, window glass layers, decoration and furniture) and use of air conditioner. The positive regulation effect of temperature on residential formaldehyde was explored with the approximately turning-point temperature of 28.9 °C for peak concentration. Long-term exposure to residential formaldehyde of low concentrations (0.010-0.090 mg/m 3 ) would increase the prevalence of childhood pneumonia and a more stringent criteria value for residential formaldehyde should be discussed cautiously., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier Inc. All rights reserved.)

The rapid industrialization has contributed to the miracle of economic growth in China, while also caused a series of environmental problems. As one of the most concerning urban disease in China, the aggravation of haze pollution is closely related to the accelerating urbanization and industrialization process in recent years, and the strong spatial diffusion makes the negative externality of haze pollution more harmful. This characteristic of haze pollution is closely related to the spatial structure of industrial sectors, especially the agglomeration of industrial sectors. This paper established a spatial economic framework to investigate the spillover effect of industrial agglomeration on haze pollution based on satellite raster map data of PM 2.5 and location entropy index, and further discuss the question that whether industrial agglomeration can achieve a balanced development for both economic growth and environmental quality. The results indicated that there is an inverted U-shaped relationship between industrial agglomeration and haze pollution, and the indirect effect from spatial spillover dominated this impact. Industrial agglomeration has a single threshold effect on the knowledge spillover and the utilization of pollution disposal infrastructure of industrial sectors. Only when the agglomeration level reaches the threshold value, the scale effect can be realized to promote the air quality. The resource allocation efficiency and knowledge spillovers of industrial agglomeration need to be promoted in order to reach the inflection point and realize the win-win situation., Competing Interests: Declaration of competing interest We confirm that no conflict of interest exists in the submission of this manuscript (Industrial Agglomeration and Haze Pollution: Evidence from China), and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described is original research that has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed., (Copyright © 2022 Elsevier B.V. All rights reserved.)

The ambient air quality is a complex dynamical system that is shocked by a number of subsystems, such as government policies, industry regulation adjustment and internationalization. To identify the drivers for ambient air quality, a grey spatial extension relational analysis model is proposed. Firstly, a spatial extension method for one-dimensional time series of complex systems is introduced, and the two key parameters are obtained based on the grey similarity and proximity relational analysis models. Secondly, grey relational coefficient is calculated by the difference of the three-dimensional vector, and a grey spatial extension relational analysis model is presented. Furthermore, the properties of the proposed model were investigated. Finally, the model is used to identify the drivers of the ambient air quality in eastern coastal Shandong Province, China. Results suggest that the drivers of the ambient air quality vary among cities, but with some common ones. Therefore, this paper provides an important reference for the improvement of ambient air quality., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Numerous scientific studies, applying different approaches, have provided evidence of the links between the environment and people's health. Green spaces have been the subject of research aimed at exploring their benefits as components of the urban environment. We investigated possible causal relationships between green spaces and health, with the aim of addressing the following question. Does the mere material presence of green spaces contribute to the health of people who live in its vicinity, or are the health-promoting qualities of green spaces attributed to the ability of people to actually see, access, and enjoy them? The latter view highlights the relational dimension of places, and it entails personal relationships with places which are imbued with psychological meaning and significance for those who visit and experience them. We reviewed relevant literature, comprising a total of 189 papers on this topic that have been published over the first two decades of this century. Our findings showed that the material aspects of green spaces, such as their abundance and proximity to residences, received much more attention in studies than their quality and characteristics. However, relational rather than material measures of green spaces demonstrated statistically greater positive impacts of green spaces on health. These findings indicate that both sensory stimuli and activities and feelings attached to green spaces are essential for better health outcomes. Incorporating a relational perspective of green place-thinking into the existing literature on green spaces and health could contribute to optimizing the positive effects of green spaces and thus to the creation of healthy and livable cities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier Inc.)

At present, the deterioration of the water ecosystem has constituted a bottleneck for the further development of the Yangtze River Economic Belt (YREB). As a crucial indicator for evaluating the degree of water pollution, grey water footprint (GWF) is of great significance for rationally evaluating the water environment of the YREB. In this study, we calculated the GWF efficiency of the YREB based on the panel data of 9 provinces and 2 cities from 2005 to 2019. On this basis, spatiotemporal methods and Logarithmic Mean Divisia Index (LMDI) model were adopted to analyze the spatial-temporal evolution characteristics and driving factors of GWF efficiency in the YREB. This study drew the following conclusions: (1) the GWF efficiency in the YREB was on an uptrend, with the average annual growth rates of the upstream, midstream and downstream being 17.35 %, 18.31 % and 17.8 % respectively from 2005 to 2019. (2) The GWF efficiency in the YREB showed a weak trend of polarization and the gap between different regions continued to widen. Besides, it was characterized by stability and owned a positive spatial correlation in both geographic distance and economic distance. (3) The improvement of the technology level, water use efficiency, wastewater treatment capacity, economic development level and the reduction in the industrial pollution intensity contributed positively to boosting the GWF efficiency. Meanwhile, the effect of environmental regulation made a significant negative contribution to GWF efficiency. Therefore, in the process of building the YREB, while emphasizing the coordinated development of the economy, all regions should also carry out joint pollution control., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Seawater intrusion (SWI) seriously affects the economic development of coastal areas in southern China, and understanding its mechanisms is the basis for effective control of SWI. Hydrogeochemical methods and slack-based measurement data envelopment analysis (SBM-DEA) are used to study the characteristics and potential risk of SWI in coastal cities of southern China. Types and distribution of SWI, coastal groundwater evolution, geological-geographic and economic threatens of SWI, potential SWI risk, and environmental management recommendations are explored. The results show that the intrusion areas of Zhejiang and Guangdong account for 94.1 % of the total intrusion area of southern China, and the intrusion degree in Zhejiang is the highest, followed by Guangdong and Fujian. SWI is prone to occur on the sandy and silty coasts of the plain area of southern China; it accelerates the groundwater evolution speed and shortens the evolution path. SBM-DEA can be well applied to evaluate the potential risk of SWI events, and the results indicate a noticeable difference in the environmental performance level of coastal cities in southern China. The low environmental performance level (<0.3) and severe SWI of Taizhou and Zhanjiang indicate that SWI gradually worsens with economic development. In contrast, the high environmental performance level (>0.7) and low SWI of Wenzhou, Fuzhou, Quanzhou, Shantou, and Beihai indicate that the potential risk of SWI is gradually decreasing. Moreover, this study confirms that the environmental Kuznets curve (EKC) phenomenon exists in SWI events for southern China, and SWI-EKC indicates that the urban development of south China is approaching maturity. The specific case of SWI and EPL in coastal cities of south China jointly indicates that optimizing industrial structure, implementing a resources management policy, and improving citizens' environmental awareness are fundamental measures to resolve the contradiction between economic development and environmental problems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

The patterns and determinants of different types of agricultural water footprints in China are poorly understood at the prefecture-city level. In this paper, we evaluate Chinese agricultural water footprints from 2000 to 2017 and analyzed their spatio-temporal characteristics. Our estimation results show that the annual average agricultural water footprint in China was 5.038 × 10 9 m 3 , and the proportions of green water, blue water, and gray water were 70%, 9%, and 21%, respectively. In addition, high agricultural water-footprint cities with obvious urban agglomeration effects are mainly located in the Northeast, the Huanghuai River, the Yangtze River Basin, and Northwestern of Xinjiang, while low agricultural water-footprint cities are concentrated in high coastal urbanization-level areas or less developed agricultural areas of the west. We also investigate their determinants using a spatio-temporal fixed-effect model and find that GDP per capita, total investment in fixed assets, the income level of rural residents, the proportion of food grown, spray and drip irrigation technology, low-pressure pipe irrigation technology and seepage control irrigation technology have significant positive impacts on the agricultural water footprint. In contrast, the proportion of secondary and tertiary industries, social retail consumption, urbanization, technology expenditure, and the effective irrigation area proportion have a significant inhibitory effect. The primary determinants of the agricultural water footprint also vary substantially across water footprint categories (green, blue, and gray water footprints) and regions. Our findings imply that the agricultural water footprint should be incorporated into city water resource management and monitoring system., Competing Interests: Declaration of competing interest No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for publication. I would like to declare on behalf of my co-authors that the work described is original research that has not been published previously. The manuscript has also not been submitted to another journal for the consideration of publication. All the authors listed have approved the enclosed manuscript., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Although COVID-19 lockdown policies have improved air quality in numerous countries, there is a lack of empirical evidence on the extent to which recovery has resulted in air pollution rebound, and the differences and similarities among regions' recovery modes during the period of easing COVID-19 restrictions. Here, we used daily air quality data and the recovery index constructed by a city-pair inflow index for 119 cities in China to quantify the impact of recovery on air pollution from March 2 to October 30, 2020. Findings show that recovery has significantly increased air pollution. When the recovery level increased by 10 %, the concentration of PM 2.5 , SO 2 , and NO 2 respectively deteriorated by 1.10, 0.33, 1.25 μg/m 3 , and the average growth rates of three air pollutants were about 3 %-6 %. Moreover, we used the counterfactual framework and time series clustering with wavelet transform to cluster the rebound trajectory of air pollution for 17 provinces into five recovery modes. Results show that COVID-19 has further intensified regional differentiations in economic development ability and green recovery trend. Three northwestern provinces dependent on their resource endowments belong to energy-intensive recovery mode, which have experienced a sharp rebound of air pollution for two months, thereby making green recovery more challenging to achieve. Three regions with a diversified industrial structure are in industrial-restructuring recovery mode, which has effectively returned to a normal level through adjusting industrial structure and technological innovation. Owing to local policies and the outbreak of COVID-19 in other countries, six provinces in policy-oriented and international trade-oriented recovery modes have not fully recovered to the level without COVID-19 until October 2020. The result highlights the importance of diversifying industrial structure, technological innovation, policy flexibility and industrial upgrading for different recovery modes to achieve long-term green recovery in the future., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Surface urban heat islands (SUHIs) are a global concern. Although their spatial pattern and the cooling effect of blue-green landscapes have been documented, exploring more accurate and quantitative results is still necessary. For Hangzhou, we combined nighttime light (NTL) data with LST images to investigate the spatial morphology of SUHIs and analyze the cooling effect of blue-green landscapes. The radiative transfer equation (RTE) method was used to derive the land surface temperature (LST). Then, based on the unique feature of Luojia1-01 NTL data, the concentric zone model (CZM) was proposed to depict the urban spatial structure. The CZM was applied to construct a number of equal-area concentric belts along the urban-rural gradient to determine the SUHI range and the corresponding blue-green landscape cooling effects. Finally, local Moran's I indices were adopted to identify the cold-hot spots of the SUHI and the relationship with land use. The minimum, average and maximum LSTs were 21.81 °C, 32.79 °C and 44.79 °C, respectively. Additionally, 59.16 % of the study area was affected by the SUHI, and the mean LST inside the SUHI was 36.4 °C, clearly higher than that of the rural area. The SUHI hotpots were clustered in regions with intensive human activities, forming archipelagos. Due to the different blue-green landscape densities, the cooling capacity had spatial heterogeneity in different urban rural belts (URBs), and the cooling capacity of URB 16 was approximately 71 times that of URB 1 . The cooling efficiency increased with blue-green landscape density in general; hence, blue-green landscape density thresholds of 40 % and 70 % were recommended in the urban planning of different urban function zones. Relating the pattern of NTL data to LST images provide meaningful insight into the spatial pattern of SUHIs and the optimization of urban planning., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Risk-taking in birds is often measured as the flight initiation distance (FID), the distance at which individuals take flight when approached by a potential predator (typically a human). The ecological factors that affect avian FID have received great attention over the past decades and meta-analyses and comparative analyses have shown that FID is correlated with body mass, flock size, starting distance of the approaching human, density of potential predators, as well as varying along rural to urban gradients. However, surprisingly, only few studies (mainly on reptiles and mammals) have explored effects of different types of refugia and their availability on animal escape decisions. We used Bayesian regression models (controlling for the phylogenetic relatedness of bird species) to explore changes in escape behaviour recorded in European cities in relationship to the birds' distance to the nearest refuge and distance fled to the refuge. In our analyses, we also included information on the type of refuge, built-up and vegetation cover, starting distance, flock size, urbanization level, and type of urban habitat. We found that birds preferred tree refuges over artificial and bush refuges. Birds escaped earlier if the distance to the nearest refuge of any type was longer and if birds fled longer distances to the refuge. FID was shorter when birds used bushes as refugia or landed on the ground after flushing compared to using artificial refugia. Similarly, the distance fled to a refuge was shortest when using bushes, and increased when escaping to artificial substrates and trees. Birds were more timid in suburban than core areas of cities, cemeteries than parks, and in areas with higher bush cover but lower cover of built-up areas and trees. Our findings provide novel information regarding the importance of refuge proximity and type as factors affecting the escape behaviour of urban birds., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Exposure to ambient fine particulate matter (PM 2.5 ) air pollution is a significant driver of premature deaths. We estimate the number of cardiovascular and respiratory (CR) premature deaths attributed to long-term exposure to PM 2.5 in 33 global megacities based on long-term remotely sensed observations from 2000 to 2019. Our analysis uses high-resolution (0.01 degree) PM 2.5 concentration data and cause-specific integrated exposure-response (IER) functions developed for the Global Burden of Disease Project. From 2000 to 2019, PM 2.5 -related CR death rates per 1000 people increased in 6 of 33 megacities, decreased in 9, and remained constant in 18 megacities. The increase in PM 2.5 -related CR mortality in 11 megacities located in South and East Asia during the period 2000-2019 can be attributed to the increases in PM 2.5 concentrations. All 33 megacities could avoid 30,248 (9 %), 62,989 (20 %), 128,457 (40 %), 198,462 (62 %) and all of the estimated 322,515 CR deaths attributed to PM 2.5 pollution in 2019 if they were to attain the World Health Organization's four interim PM 2.5 targets (IT-1, IT-2, IT-3, and IT-4) and the new air quality guideline (AQG), respectively. Major improvements in air quality are needed to reduce the number of CR deaths attributed to PM 2.5 in South and East Asia, in addition to ny reductions that would likely follow shifts in the population structures of these megacities moving forward., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

One of the most severe climate risks that is expected to affect all regions is related to stormwater. Climate models, constructed based on long-term trends, show that extreme weather events such as storms, cloudbursts and a large rise in sea level will be significant in the coming decades. Moreover, even the frequency and intensity of "normal" rainfall events, such as microbursts, are expected to be remarkably higher than today in some regions. The efficiency of urban drainage systems is affected by the land use in its whole catchment. In addition to the climate stress, there is ongoing continuous densification of urban space, resulting in more buildings and larger areas being covered with impervious surfaces. Planning decisions today approving such compaction do not consider the impacts beyond the close proximity of the land parcel. As a result, by following the current planning practices, cities are becoming extremely vulnerable to stormwater flooding (flash floods). This study presents a holistic and dynamic planning method - the Extreme Weather Layer (EWL) - that makes it possible to analyse the impact of a single development (e.g. paving a gravel parking lot with asphalt or turning an area of urban greenery into a shopping centre) on the performance of the urban drainage system and therefore on the flooding risk of the whole catchment. The EWL is based on a widely accepted drainage modelling engine coupled with GIS system and other databases which provide spatial information. Thus, the EWL combined with the systemic approach of turning from grey to green infrastructure could be a smart tool for implementing NBS solutions for stormwater management in climate adaptation in urban areas. This smart tool could indicate how much more green infrastructure is needed and which places in the city the mitigative NBS measures would help significantly., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The role of urban green space (UGS) in mitigating the urban heat island (UHI) effect has been demonstrated in a growing body of literature. However, the potential influence of the spatial equity of UGS distribution on the UHI effect has largely been overlooked. The present study aims to identify this potential influence using the spatial equity of UGS and the land surface temperature (LST) as measures of UGS spatial distribution and UHIs, respectively. A comprehensive spatial distribution map of UGS was generated by combining the UGS coverage fraction data within urban impervious pixels and the green cover data outside urban impervious pixels. Then, the spatial equity of UGS distribution across all urban impervious pixels was determined using the Gini coefficient. In addition, an LST map was derived using the thermal infrared spectral bands of Landsat 8 OLI/TIRS products. A case study of Dongguan, a highly urbanized city in China, showed that (1) the distribution of both UGS and LSTs were spatially aggregated in all the towns of the city, (2) the LST of urban impervious pixels was negatively correlated with the area of surrounding UGS, and (3) the Gini coefficient of UGS was positively correlated with the proportion of hot and cool areas, but negatively correlated with the proportion of medium-hot and medium-cool areas. These findings indicate that increasing the amount of UGS is beneficial to the reduction of urban average LSTs, while promoting the spatial equity of UGS distribution is conducive to reducing the spatial aggregation of LSTs within urban areas, thereby improving the overall urban thermal environment. Therefore, as a nature-based solution, promoting the spatial equity of UGS distribution could enhance the overall cooling effect of UGS more effectively at the city scale, and thus further underpin the sustainable development of the urban environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Air temperature is a crucial variable of urban meteorology and is essential to many urban environments, urban climate and climate-change-related studies. However, due to the limited observational records of air temperature and the complex urban morphology and environment, it might not be easy to map the hourly air temperature with a fine resolution at the surface level within and around cities via conventional methods. Thus, this study employed machine learning (ML) algorithms and meteorological and landscape data to develop hourly air temperature mapping techniques and methods at the 1-km resolution over a multi-year warm seasons period. Guangdong Province, China was selected for the case study. Random forest algorithm was employed for the hourly air temperature mapping. The validation results showed that the hourly air temperature maps exhibit good accuracy from 2008 to 2019, with mean R 2 , root mean square error (RMSE) and mean absolute error (MAE) values of 0.8001, 1.4821 °C and 1.0872 °C, respectively. The importance assessment of the driving factors showed that meteorological factors, especially relative humidity, contributed the most to the air temperature mapping. Simultaneously, landscape factors also played a non-negligible role. Further analysis revealed that the maps steadily maintained high accuracy at nighttime (20:00-7:00), which is essential for investigating nighttime urban climate conditions, especially the urban heat island effect. Moreover, a correlation existed between the nighttime air temperature changes and urban morphology represented by the local climate zones. Air temperatures tended to fall more slowly in the core of metropolitan areas than in the urban fringe. Using ML, this study reliably improves the spatial refinement of hourly air temperature mapping and reveals the spatially explicit air temperature patterns in and around cities at different times in a day during the warm seasons. Moreover, it provides a novel valuable and reliable dataset for air-temperature-related implementation and studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Urban geometry is known to be one of the major factors in explaining the intra-urban temperature variations. A commonly used indicator to describe the urban geometry is the sky view factor. However, the existing studies have shown that the relationship between SVF and urban temperature is quite contradictory. This suggests that a single SVF cannot accurately quantify the urban geometry. For comparison, we here propose to use view factors, including sky, building and tree view factors (SVF, BVF, and TVF, respectively), to accurately quantify the three-dimensional urban geometry. Based on microclimate measurements conducted in Beijing Olympic Park and its surrounding urban environment in Beijing, China, the impact of view factors on intra-urban air temperature and thermal comfort was evaluated. Measurements were conducted along a selected path during hot summer days with clear skies and light winds by mobile traverses. The obtained results showed that SVF was positively correlated with air temperature during the day but negatively correlated with air temperature at night. BVF mainly played a warming role in both daytime and nighttime. Especially at night, BVF was the main geometric warming factor. TVF had a significant cooling effect during the day but did not have a negative effect at night due to reduced SVF. There was a strong point-to-point correlation between SVF and outdoor thermal comfort in the daytime. The mean differences in Mean Radiant Temperature and Physiologically Equivalent Temperature between shaded and unshaded sites were 12.0 °C and 6.8 °C, respectively, which suggested that providing effective shading is extremely important for improving outdoor daytime thermal comfort., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

With the rapid development of ports in the world today, the ecological environment pollution of port cities is becoming more and more serious. How to coordinate the port industry and the urban environment is an urgent problem to be solved. This article proposes a system to evaluate the coordination between port industry chain development and the urban ecological environment by taking Shanghai Port as an example. The Principal Component Analysis (PCA) method was applied to calculate the weights of various indexes, then the Coupling Coordination Degree Model (CCDM) was adopted to systematically study the coordination relationship between port industry development and the urban ecological environment. Our research finds the coupling coordination degree between Shanghai Port's economic development and the urban ecological environment shows an overall upward trend, changing from severely misaligned in 2000 (0.125) to barely coordinated in 2019 (0.691). Shanghai has achieved some results in constructing the ecological environment and green port, but there is still much room for improvement. Shanghai port needs to strengthen container transportation, enhance energy conservation and emission reduction, and vigorously promote the development of a green port. This study will provide a basis and reference for relevant institutions, government departments, and policymakers to formulate scientific and effective green port industry chain development strategies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

In this paper, we propose a coronavirus disease (COVID-19) epidemiological model called SEIR-FMi (Susceptible-Exposed-Infectious-Recovery with Flow and Medical investments) to study the effects of intra-city population movement, inter-city population movement, and medical resource investment on the spread of the COVID-19 epidemic. We theoretically derived the reproduction number of the SEIR-FMi model by using the next-generation matrix method and empirically simulate the individual impacts of population movement and medical resource investment on epidemic control. We found that intra- and inter-city population movements will increase the risk of epidemic spread, and the effect of inter-city population movement on low-risk areas is higher than that on high-risk areas. Increasing medical resource investment can not only speed up the recover rate of patients but also reduce the growth rate of infected cases and shorten the spread duration of the epidemic. We collected data on intra-city population movement, inter-city population movement, medical resource investment, and confirmed cases in the cities of Wuhan, Jingzhou, and Xiangyang, Hubei Province, China, from January 15 to March 15, 2020. Using the collected data, we validated that the proposed SEIR-FMi model performs well in simulating the spread of COVID-19 in the three cities. Meanwhile, this study confirms that three non-pharmaceutical interventions, namely community isolation, population mobility control, and medical resource aid, applied during the epidemic period are indispensable in controlling the spread of COVID-19 in the three cities., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Monitoring the communal incidence of COVID-19 is important for both government and residents of an area to make informed decisions. However, continuous reliance on one means of monitoring might not be accurate because of biases introduced by government policies or behaviours of residents. Wastewater surveillance was employed to monitor concentrations of SARS-CoV-2 RNA in raw influent wastewater from wastewater treatment plants serving three Canadian Prairie cities with different population sizes. Data obtained from wastewater are not directly influenced by government regulations or behaviours of individuals. The means of three weekly samples collected using 24 h composite auto-samplers were determined. Viral loads were determined by RT-qPCR, and whole-genome sequencing was used to charaterize variants of concern (VOC). The dominant VOCs in the three cities were the same but with different proportions of sub-lineages. Sub-lineages of Delta were AY.12, AY.25, AY.27 and AY.93 in 2021, while the major sub-lineage of Omicron was BA.1 in January 2022, and BA.2 subsequently became a trace-level sub-variant then the predominant VOC. When each VOC was first detected varied among cities; However, Saskatoon, with the largest population, was always the first to present new VOCs. Viral loads varied among cities, but there was no direct correlation with population size, possibly because of differences in flow regimes. Population is one of the factors that affects trends in onset and development of local outbreaks during the pandemic. This might be due to demography or the fact that larger populations had greater potential for inter- and intra-country migration. Hence, wastewater surveillance data from larger cities can typically be used to indicate what to expect in smaller communities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Crown Copyright © 2022. Published by Elsevier B.V. All rights reserved.)

The spatial correlation of carbon emissions poses new challenges to constructing ecological civilisation and sustainable development in the Yangtze River Economic Belt. This study explains the formation mechanism of the carbon emission efficiency network and attempts to explore its structural complexity and spatial directivity. It focuses on the carbon emission efficiency network's structural entropy, node efficiency, hierarchy, connection symmetry, and transmission characteristics. The main conclusions are as follows: (1) The carbon emission efficiency of the Yangtze River Economic Belt has significantly improved, and the gap between cities is narrowing, but there is gradient differentiation on the provincial spatial scale that exhibits a strong Matthew effect; (2) There is an imbalance in carbon emission efficiency, which is primarily reflected in spatial distribution and hierarchical structure. Low-efficiency cities have played an important role in promoting the spatial evolution of carbon emission efficiency in the Yangtze River Economic Belt, but they have not completely changed the imbalance in carbon emission efficiency; (3) Supporting sub-networks and basic sub-networks have emerged as critical groups in promoting the complexity of carbon emission efficiency network structures, and have formed distinctive network structures in different basins of the Yangtze River; (4) The overall convergence of the carbon emission efficiency network has improved, and it exhibits preference attachment characteristics. The connection symmetry has been reduced from 5 to 7 times to 1 to 3 times, and the situation of unilateral unequal connection has been alleviated. Finally, this study puts forward some policy suggestions to improve carbon emission efficiency from the aspects of low-carbon technology research and development and carbon emission rights market construction., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Understanding the emission characteristics in the evolution of private vehicle fleet composition has become a key issue to be addressed to develop appropriate emission mitigation strategies in transportation sector. In this study, the influence of such evolution on on-road emissions was investigated based on a comprehensive dataset encompassing vehicle fleet composition, demographic, economic, and energy features from a representative small-medium automotive city in North America. The decoupling analysis was carried out to assess the dynamic linkage between environmental pressure exerted by the transportation sector and economic growth at both city level and national level in North America. We also developed an approach that supports the long-term traffic-related air pollutant prediction and investigated the potential influence on urban air quality. A sharp upward trajectory was observed in the quantity of SUVs from 2001 to 2018, gradually replacing the dominance of the quantity of four-door cars. There was a significant shift in the GHG emissions emitted from vehicle types used for passenger transport: emissions from SUVs and trucks rose by 374.0% and 69.3%, respectively, whereas emissions from four-door cars, two-door cars, station wagons, and vans all decreased. The changes in vehicle composition, along with the steady trend in GHG emissions from private fleet and decrease in on-road air pollutant concentrations found in Regina, were a response to the establishment of federal fuel economy standards and improved fuel economy. Relative decoupling was observed in aggregate for Regina and Canada in most of the years while both experienced economic downturns and increases in environmental pressure in the form of emissions from 2014 to 2015. The predicted results also demonstrate the high capability of XGboost machine learning algorithm in predicting on-road air pollutant concentrations of CO, PM 2.5 , and NO X ., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Coal is well known as the primary energy consumption in China, and the coal chemical industry (CCI) can serve as an important source of volatile organic compounds (VOCs) emissions. However, the characteristics of VOCs emitted from CCI along with their environmental consequences are still poorly understood. To pin down this, an intensive field campaign was carried out at a typical CCI city in northwestern China (Yulin) from February 26 to March 7, 2021. Results showed that VOC compositions in Yulin were distinct from those in the megacities of China as well as in the typical oilfields over the world. The concentration of naphthalene (1.6 ± 1.1 ppbv), an important byproduct of CCI, was significantly higher than that in other cities (<0.2 ppbv). Positive matrix factorization (PMF) model analysis revealed that the direct contribution of the CCI source for VOC emissions is 8.8 ± 1.8%. More importantly, these VOCs emitted from the CCI can account for 17.9 ± 6.8% of ozone (O 3 ) formation potential and 16.9 ± 7.4% of OH reactivity of VOCs, suggesting the significant impacts of the CCI on the air quality and atmospheric oxidizing capacity. During the observation, a rapid increase in O 3 concentration after a snowfall was encountered. The changing rate of O 3 concentration in the daytime was significantly higher than in its peripheral cities. The increased O 3 formation was partially attributed to the CCI, and this enhancement can be further magnified by snow cover due to the increment of surface albedo. These findings deepen the understanding of the characteristics and air quality impact of VOCs related to the CCI and provide valuable insights for the development of air quality control measures in the region influenced by intensive coal chemical production., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Black carbon (BC) inventories for cities are scarce, especially in developing countries, despite their importance to tackle climate change and local air pollution. Here, we draw on results from a case study in a Brazilian city to discuss the challenges of compiling a BC inventory for different activity sectors. We included traditionally inventoried sectors, such as industries and on-road transportation, other less reported sectors (food establishments and aviation), and open burning of household solid waste (HSW), typically found in developing countries. We present a machine-learning technique (Random Forest) as a novel approach to obtain HSW burning activity using a set of spatial predictors. The BC inventory was based on PM 2.5 emissions weighted by the fraction of PM 2.5 emitted as BC and developed for the year 2018. We also reported the disaggregated spatial PM 2.5 emissions for the same combustion sources, and documented the databases used for activity data and emission factors (EF). The total estimated BC and PM 2.5 emissions amounted to 57.88 and 234.75 tons, respectively, with on-road vehicle exhaust emissions and industrial combustion as the main BC sources (63 and 22%, respectively). For PM 2.5 emissions, on-road transportation (exhaust and non-exhaust) contributed 48%, followed by industrial combustion (21%) and food establishments (20%). Population density, number of vacant lots, and property tax values were identified as the most important features to predict the HSW fire activity. A comparison with other inventories revealed that the BC emission profile of Londrina is similar to the profile reported for Greater Mexico City, another Latin American city. Thus, the methodology used in this study could be extended to other cities with similar local BC sources. Finally, we highlight that the lack of local activity data, representative EF, and even methodology may undermine the development of reliable BC inventories, and intensive research should be conducted to characterize the emission sources., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

China is facing dual challenges of air pollution and climate change. By using city-level data, we comprehensively assessed air quality and CO 2 emission changes from 2015 to 2019 for 335 Chinese cities. We selected important regions for air pollution control and categorized all cities into different classes according to their development levels. Our novel approach revealed new insights on different patterns of changes of PM 2.5 , O 3 , and CO 2 by region and city class. We found that PM 2.5 concentrations decreased remarkably due to mandatory city-level reduction targets, especially in the Beijing-Tianjin-Hebei (-27%) region. Nonetheless, O 3 concentrations and CO 2 emissions increased in 91% and 69% of Chinese cities, respectively. Observed CO 2 emission reductions in more developed cities were mainly due to prominent energy intensity reduction and energy structure improvement. Our study indicates a lack of synergy in air pollution control and CO 2 mitigation under current policies in China. To address both challenges holistically, we suggest setting mandatory city-level CO 2 emission reduction targets and reinforcing clean energy and energy efficiency measures., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Phthalates (PAEs) are widely used in daily products but can cause a variety of adverse effects in humans. Few studies have been carried out on human internal exposure levels of PAEs on a large-scale, especially in developing countries. In the present study, 1161 urine samples collected from residents of 26 provincial capitals in China were analyzed for nine phthalate metabolites (mPAEs). The chemicals were widely detected, and the median specific gravity adjusted urinary concentration of Σ 9 mPAEs was 278 μg/L. Di-(2-ethylhexyl) phthalate (DEHP) and di-n-butyl phthalate (DnBP) were the main parent PAEs that the residents were exposed to. Demographic characteristics, such as age and educational level, were significantly associated with PAE exposure. Children and the elderly had higher mPAE levels. Subjects with lower educational levels were more frequently exposed to DnBP and DEHP. However, mono-ethyl phthalate showed the opposite trend, i.e., higher concentrations in subjects aged 18-59 years and with higher educational levels. Geographic differences were detected at the national scale. Residents in northeastern and western China had higher levels of mPAEs than those in central China, most likely because of different industrial usage of the chemicals and different living habits and living conditions of the residents. Health risk assessment showed that hazard indices of PAEs ranged from 0.07 to 9.34, with 20.0% of the subjects being concern for potential non-carcinogenic risk as assessed by Monte Carlo simulation. DEHP and DnBP were the primary contributors, representing 96.7% of total risk. This first large-scale study on PAE human internal exposure in China provides useful information on residents' health in a developing country, which could be used for chemical management and health protection., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

A clear understanding of the factors governing dual isotopes (δ 15 N-NO 3 - and δ 18 O-NO 3 - ) in typhoons is essential for understanding their NO 3 - sources and its formation mechanisms. In this study, sequential precipitation samples during typhoons, including In-fa and Chanthu, were collected from Ningbo, Hangzhou and Huzhou. The chemical compositions, nitrogen and oxygen isotopes of NO 3 - and oxygen isotopes of H 2 O (δ 18 O-H 2 O) were measured. The results showed that the δ 15 N-NO 3 - and δ 18 O-NO 3 - values ranged from -6.3‰ to 6.0‰, and 38.0‰ to 66.5‰, respectively. The lower δ 18 O-NO 3 - values (less than 52‰) indicated the importance of peroxy radicals (RO 2 ) during the OH· pathway ranged from 0% to 27% of In-fa and from 0% to 32% of Chanthu, respectively, in the three cities. More NO 2 ) in NO x oxidation to NO 3 - formation pathways. By the Monte Carlo simulation of δ 18 values in sequential samples in In-fa reflected the decreased marine sources (lightning) and the increased anthropogenic sources in land (coal combustion and microbial N cycle) from Phrase I to Phrase II and III. Based on the improved Bayesian model with nitrogen isotopic fractionation, the contributions of lightning + biomass burning, coal combustion, mobile sources and the microbial N cycle were 35.7%, 22.5%, 27.1% and 14.7% in In-fa, and 28.3%, 32.3%, 28.0% and 11.4% in Chanthu, respectively, in the three cities, emphasizing the influence of marine NO 3 - values of typhoons, the calculated oxidation proportions of NO by RO 2 (or HO 2 ) during the OH· pathway ranged from 0% to 27% of In-fa and from 0% to 32% of Chanthu, respectively, in the three cities. More NO x emissions from marine microbial processes caused the lower δ 15 N-NO 3 - values of typhoons in Ningbo than those in Hangzhou and Huzhou. The variation in δ 15 N-NO 3 - values in sequential samples in In-fa reflected the decreased marine sources (lightning) and the increased anthropogenic sources in land (coal combustion and microbial N cycle) from Phrase I to Phrase II and III. Based on the improved Bayesian model with nitrogen isotopic fractionation, the contributions of lightning + biomass burning, coal combustion, mobile sources and the microbial N cycle were 35.7%, 22.5%, 27.1% and 14.7% in In-fa, and 28.3%, 32.3%, 28.0% and 11.4% in Chanthu, respectively, in the three cities, emphasizing the influence of marine NO x sources (lightning). The results highlight the importance of RO 2 (or HO 2 ) in NO x oxidation pathways in typhoons and provide valuable insight into the NO x sources of typhoons., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Digitisation is gaining importance with 3D workflow for architecture-specific annotation of built heritage. The objective is to use the Building Information Modeling (BIM) methodology in order to carry out a study of alternatives of impact on environmental sustainability associated with the potential allergenicity with green infrastructure on a new housing, located in Mérida (SW Spain). It is intended to simulate the meteorology (direction and speed of the wind) in the study city with the compass rose for 18 years (2003-2020) to assess the meteorological pattern associated with the wind on the studied housing. 3 green infrastructure garden alternatives (considering 5 ornamental species of cypress trees) were designed to evaluate the potential impact of allergenicity on the housing. AIROT index was applied to project the results on the frontage of the housing. This index was developed in the field of large areas of urban environments. The calculation was carried out in the most exact way possible in specific sections of the frontage of the housing and automatically with tools associated with the BIM environment (such as Autodesk Revit, Dynamo, Enscape, Wrplot and Bim One) to the discipline of Architecture (such as Autodesk Autocad and Autodesk Flow Design). The obtained results were applied to evaluate 3 scenario designs, trying to minimize the potential exposure to urban green infrastructure (focus on cypress trees) in this current project, and offering a health reference guide in future projects, from the design phase considering appropriate measures and proposing recommendations., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

With the rapid growth of China's economy, the increase in water demand has threatened the sustainable development of groundwater. Construction of the South-to-North Water Diversion Project alleviated this problem. Zhengzhou, with a large population and high-intensity energy consumption, is a water-receiving city of the South-to-North Water Diversion Central Line Project (CLP). A series of ecological risks caused by the excessive exploitation of groundwater have been exposed. It is urgent to strengthen the assessment and management of groundwater to ensure sustainable development. In this study, the multi-criteria decision analysis (MCDA) underpinned the assessment of the sustainable groundwater development (ASGD) framework. Eight assessment factors were established based on the resource supply function (RSF) and eco-environment stability function (ESF). The novelty of this study lies in the integration of ASGD results with the impact of the CLP on the evolution of groundwater levels in Zhengzhou. Thus, more comprehensive and scientific management suggestions for groundwater development in Zhengzhou were obtained. GIS technology was integrated with the ASGD framework to identify five visualized areas: centralized groundwater supply area (8.61%), decentralized groundwater supply area (27.91%), vulnerable eco-environment area (14.34%), recharge protection area (45.67%), and unsuitable exploitation area (3.47%). The CLP changed the groundwater evolution pattern in Zhengzhou. The results showed that the operation of the CLP effectively slowed the decline in groundwater levels, thus confirming that the CLP has a positive impact on the rational utilization of groundwater. The disuse of two groundwater sources (G1 and G9) were able to enhance sustainable groundwater development. Meanwhile, five groundwater sources in the plain area proved unsuitable. Overall, this study provides a scientific basis for groundwater management in Zhengzhou City, while generating new ideas for sustainable groundwater development in cities affected by large-scale hydraulic projects worldwide., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Urbanization witnessed unprecedented development globally, which causes citizens and urban temperature to become increasingly intertwined. Although researchers were interested in the field, most studies focused on holistic linear links between the characteristics of the urban built-up environment and temperature. The study used Bayesian optimization ensemble learning and Shapley value to decouple the urban thermal environment by Landsat satellite data. This work's novelties reveal the specific driving effect of different value ranges of urban features in the overall process on the urban thermal environment and advancing an optimum observation buffer zone of the urban surface temperature. The study's results were only for daytime and Beijing scope. The following are the main findings: (1) The 2 km observation buffer zone is best to analyze the urban thermal environment for this dataset. (2) The ecological environment factors have a more significant effect on the urban temperature than the urban morphology factors. (3) In summer, when the vegetation coverage exceeds 58.1%, every 10% increase could reduce the temperature by 0.84 °C. In contrast to summer, when vegetation coverage exceeds 64.7% and 73.2%, respectively, in spring and fall, there will be a significant marginal utility. (4) The effect of the building height has seasonal variations. It has the greatest cooling effect in the spring when the height is between 18 m and 75 m, and the daytime surface temperature at the time of Landsat overpass will drop by 1.25 °C. These findings will aid in understanding how building construction influences urban surface temperature and provide statistical support for planners., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022. Published by Elsevier B.V.)

Resource-based cities (RBCs) have made outstanding contributions to China's social and economic development over recent decades. Nevertheless, with the worsening climate change and the exhausted resources, how to curb carbon emissions of RBCs to deliver their low-carbon transformation is becoming a problem plaguing the world. To facilitate the low-carbon transformation of RBCs, the Chinese government has formulated many policies, including the Sustainable Development Policy of National Resource-based Cities, 2013-2020 (SDPRC). However, the implementation of SDPRC has not yielded a clear environmental influence. Therefore, this study employs the Propensity Score Matching-Difference in Difference to investigate this influence based on the panel data of 285 prefecture-level cities from 2006 to 2017 while exploring the related heterogeneity and impact mechanisms. It is found that: (1) the implementation of SDPRC has significantly reduced carbon emissions and intensities of RBCs, with this effect becoming more conspicuous with the advancement of the policy. A robust test also verifies these findings. (2) Results from the heterogeneity test demonstrate that the implementation of SDPRC has imposed a suppressive effect on CO 2 emissions in eastern, central, and western Chinese regions, especially pronounced in the latter two regions. Except for the growing cities, which are not significantly affected by the policy, the other three types of cities have seen a catalytic effect on CO 2 emission reduction from the implementation of the policy, with the most significant impact observed in the declining cities. (3) Analyses of related mechanisms reveal that thanks to the implementation of SDPRC, RBCs suppress CO 2 emissions mainly by optimizing their industrial structures and relieving their energy intensities. Finally, some policy recommendations are proposed based on the findings of this study to facilitate the low-carbon transformation of RBCs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Implementing an inter-regional synergistic control policy for fine particulate matter (PM 2.5 ) and ground-level ozone (O 3 ) could improve regional air quality. However, little is known about the effectiveness and accuracy of synergistic control region delineation. This study aimed to construct a network model and apply it to a case study of regional delineation in China at different scales to quantify the interactions between regions. Firstly, the Cumulative Risk Index (CRI) was proposed and quantified from a health risk perspective based on the daily mean PM 2.5 and daily maximum 8-h average O 3 concentrations from 2015 to 2020 in China. Then, the complex network topology parameters were introduced to determine the optimal threshold for different network constructions, and the Girvan-Newman (GN) algorithm was used to divide the network into independent regions. Results showed that the correlation between cities is more robust than that between provinces. There are four-seven major provincial-scale regions with strong synchronicity in CRI, suggesting that PM 2.5 and O 3 synergistic control policies shall be implemented jointly within these demarcated regions. Moreover, urban-scale CRI network analysis indicated that the existing key control areas (2 + 26 cities) need to be expanded to 40-50 cities and refined into seven independent urban regions. Meanwhile, the Fen-Wei Plain can be focused on six cities: Xi'an, Baoji, Xianyang, Weinan, Yuncheng, and Tongchuan. This study could improve our understanding of the synergistic control regions for PM 2.5 and O 3 pollution, and the results could be used to develop joint control policies for both pollutants., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 Elsevier B.V. All rights reserved.)