The spatiotemporal heterogeneity of new-type urbanization in Chinese cities, with its emphasis on ecological development, interacts with the low-carbon technology development (LCT), a critical initiative for achieving carbon peak and neutrality targets. This interplay may lead to varied outcomes in air pollution control. This study investigates the spatiotemporal interplay between the four innovation priorities of new-type urbanization and LCT in influencing urban sulfur dioxide (SO2) emissions and emission intensity. By constructing the Geographically and Temporally Weighted Regression (GTWR) model, we estimate the spatiotemporally varying coefficients across 294 cities and 18 urban agglomerations in China from 2012 to 2022. Our findings reveal that: (1) LCT has a strengthening effect on the inhibitory effect of new-type urbanization on urban industrial SO2 emission intensity across all Chinese cities and in 73 % of the cities for SO2 emissions. (2) LCT alleviates the energy rebound effect caused by population and land use changes accompanying new-type urbanization. (3) In 41 % of the cities, the relationship between economic new-type urbanization and SO2 emissions was identified to be an inverted U-shaped correlation. (4) Urban agglomerations have better SO2 control impacts during their new-type urbanization process, where the strengthening effect of LCT on inhibiting SO2 emissions is 1.6 times higher. This study provides empirical evidence to inform nuanced new-type urbanization strategies and targeted SO2 pollution control measures at city and urban agglomeration scales.

Coastal cities play a pivotal role in China's strategic approach to fostering external connectivity through coastal regional development. This study constructed an evaluation system by employing a Pressure-State-Response (P-S-R) framework and evaluated the ecological efficiency of the 13 coastal cities in China from 2017 to 2021. The super-efficiency Slacks-Based Measure (SBM) model has been applied to evaluate the comprehensive eco-efficiency at the city level from the dimensions of resource input, economic development, and environmental pollution. The Geographically and Temporally Weighted Regression (GTWR) was implemented to examine the spatial and temporal impacts of urban green space and additional influential factors on ecological efficiency. The findings indicate notable variations in ecological efficiency across diverse cities. The comprehensive evaluation scores of coastal cities in the Bohai Sea region exhibited a general upward trend across resource input, economic development, and environmental pollution, resulting in an increase in ecological efficiency over the years. In terms of economic development and resource input, the evaluation scores of cities showed a similar trend, with economic development scores generally higher than resource input scores. However, cities with higher economic development scores generally faced more serious environmental pollution issues. Green space was the main driving force of ecoefficiency in coastal cities, which ranged from - 2.487 to 7.831, indicating different levels of impact on ecological efficiency. The main reasons may be because green space can regulate the water cycle, reduce waste and loss of water resources, maintain the balance of the hydrological cycle, filter and purify runoff water, etc. This study offers a theoretical framework and policy suggestions for the future planning and ecoefficiency development of coastal cities.

Clean energy development and employment promotion are two essential Sustainable Development Goals (SDGs) adopted by the United Nations. However, limited evidence exists on how industrial energy transition policies impact employment at the city level. This research uses exogenous changes in clean heating intensity resulting from the implementation of a clean heating policy, as a quasi-natural experiment. Using a Continuous Spatial Difference-in-Difference (CSDID) model, it examines the direct and spillover effects of the clean heating transition on employment in 130 cities across northern China. The results show that the clean heating transition can significantly increase the total employment in both the local city and nearby cities. Direct effects are most pronounced in the tertiary industry, while spillover effects are concentrated in the secondary industry. These effects are driven through three key channels: air quality control, capital substitution, and technology innovation. Notably, the impacts of clean heating transformation on employment have shown significant heterogeneity based on a city's geographic location (eastern vs. central), marketization level, foreign investment levels, and the extent of clean energy use in the heating sector. It is estimated that for every 1 % marginal increase in a city's clean heating intensity can promote approximately 667-937 new employment positions. These findings provide policy implications for achieving sustainable development goals in the context of industrial energy transitions.

With urbanization and city facility development, cities have become major contributors to carbon emissions. This study examines the influence of urbanization on carbon dioxide emissions from the district heating industry (CEDH) in cities between 2012 and 2020. By adopting a STIRPAT approach, CEDH was quantified, and urbanization levels evaluated through nighttime light (NTL) imagery. The results of Geographically Temporally Weighted Regression model reveal both temporal and spatial variations in how urbanization affects CEDH. The median coefficients are 0.41 (95 %CI: 0.15,0.63) and 0.91 (95 %CI: 0.66,0.32) in 2012 and 2020, respectively. Socioeconomic indicators including population density, per capita GDP, carbon intensity, showed significant positive impacts on CEDH. The GTWR model demonstrated the best performance among the models applied, with the percentage of explained variance reaching 91.5 %, the lowest value of AIC values (498.87), the lowest value of residual-sum-of-squares (RIS) (34.86). To accounting for the temporal and geographical heterogeneity in impacts of urbanization level on CEDH, detailed analysis on four clustered groups of cities. In cities with higher urbanization, the coal-based boilers dominate CO2 emissions with a rising portion of CEDH attributed to the gasbased boilers, while in less urbanized cities, CHP systems and coal-based boilers contribute 94 % of the emission increase from 2012 to 2020. This study underscores the importance of city-specific clean heating policies to address the diverse impacts of urbanization, socio-economic, and meteorological factors on carbon mitigation.

Humans have intentionally mined and released mercury (Hg) from the Earth's lithosphere over millennia. Here, we synthesize past, present, and future anthropogenic Hg emissions and releases and use a global geochemical box model to characterize accumulation in the atmosphere, land, and ocean. We project an upper-bound for emissions and releases between 2010 and 2300 (Shared Socioeconomic Pathway (SSP)5-8.5; 1.7 Tg) that surpasses the historical total over the past half millennium (1.5 Tg). In contrast, the lower-bound for emissions and releases (SSP1-2.6; 0.7 Tg) is substantially smaller than the historical total. Observational constraints on global modeling suggest that most Hg released to land and water prior to 2010 remains sequestered at contaminated sites. Substantial oceanic enrichment by anthropogenic Hg (270% ca. 2010) has been driven mainly by atmospheric emissions. Cumulative future releases to land and water are projected to be approximately six-times greater than primary anthropogenic emissions to the atmosphere. This Hg is mainly sequestered in legacy Hg waste pools and is unlikely to impact Hg pollution in the global ocean unless it is mobilized by climate change. Modeling results suggest that by 2100 atmospheric Hg concentrations may be similar to present levels if society follows SSP5-8.5. Declines in the surface ocean (-19%) and atmosphere (-45%) are expected under SSP1-2.6, emphasizing the benefits of reductions in future Hg releases.

This study evaluates the spatiotemporal heterogeneous effects of decarbonizing the central heating industry on employment from the perspective of new-type urbanization based on an innovative theoretical framework. Our average estimated CO2 emission intensity of the central heating industry in China at the city-level decreased from 54.51 tCO2/100 m2 in 2012 to 47.24 tCO2/100 m2 in 2019. Decarbonization of the central heating industry may promote total employment in 72 % of the Chinese cities with the median effect is 0.005 % for each 1 % reduction of the heating carbon intensity. However, the promotion effect may be inhibited by ecological and environmental urbanization, while strengthening through population and land, economic, social, and urban-rural integration dimensions of urbanization. Our findings can provide policy implications for carbon emission control and newtype urbanization planning in cities to achieve stable employment.

Humans are exposed to toxic methylmercury mainly by consuming marine fish. While reducing mercury emissions and releases aims to protect human health, it is unclear how this affects methylmercury concentrations in seawater and marine biota. We compiled existing and newly acquired mercury concentrations in tropical tunas from the global ocean to explore multidecadal mercury variability between 1971 and 2022. We show the strong inter-annual variability of tuna mercury concentrations at the global scale, after correcting for bioaccumulation effects. We found increasing mercury concentrations in skipjack in the late 1990s in the northwestern Pacific, likely resulting from concomitant increasing Asian mercury emissions. Elsewhere, stable long-term trends of tuna mercury concentrations contrast with an overall decline in global anthropogenic mercury emissions and deposition since the 1970s. Modeling suggests that this limited response observed in tunas likely reflects the inertia of surface ocean mercury with respect to declining emissions, as it is supplied by legacy mercury that accumulated in the subsurface ocean over centuries. To achieve measurable declines in mercury concentrations in highly consumed pelagic fish in the near future, aggressive emission reductions and long-term and continuous mercury monitoring in marine biota are needed.

Abstract Mercury (Hg) is a naturally occurring element that has been greatly enriched in the environment by human activities like mining and fossil fuel combustion. Despite commonalities in some carbon dioxide (CO2) and Hg emission sources, the implications of long‐range climate scenarios for anthropogenic Hg emissions have yet to be explored. Here, we present comprehensive projections of anthropogenic Hg emissions extending to the year 2300 and evaluate impacts on global atmospheric Hg deposition. Projections are based on four Shared Socioeconomic Pathways (SSPs) ranging from sustainable reductions in resource and energy intensity to rapid economic growth driven by abundant fossil fuel exploitation. There is a greater than two‐fold difference in cumulative anthropogenic Hg emissions between the lower‐bound (110 Gg) and upper‐bound (235 Gg) scenarios. Hg releases to land and water are approximately six times those of direct emissions to air (600–1,470 Gg). At their peak, anthropogenic Hg emissions reach 2,200–2,600 Mg a−1 sometime between 2010 (baseline) and 2030, depending on the SSP scenario. Coal combustion is the largest determinant of differences in Hg emissions among scenarios. Decoupling of Hg and CO2 emission sources occurs under low‐to mid‐range scenarios, though contributions from artisanal and small‐scale gold mining remain uncertain. Future Hg emissions may have lower gaseous elemental Hg (Hg0) and higher divalent Hg (HgII), resulting in a higher fraction of locally sourced Hg deposition. Projected reemissions of previously deposited anthropogenic Hg follow a similar temporal trajectory to primary emissions, amplifying the benefits of primary Hg emission reductions under the most stringent mitigation scenarios.

Cities play an essential role in industrial nitrogen oxides (NOx) control actions. Few studies have considered the spatiotemporal heterogeneity of the key influence factors that affect industrial NOx emissions at the city level. This work evaluates the impacts of urbanization level on industrial NOx emissions during 2017–2019 at the prefecture-city in China. We construct an extended Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) framework based on the Geographically Weighted Regression (GWR), and Geographically and Temporally Weighted Regression (GTWR) model. The urbanization level was measured based on nighttime light (NTL) data. The results suggest that, first, the GTWR model has a better goodness of fit. Urbanization has a significant spatiotemporal heterogeneous effect on industrial NOx emissions. The median coefficient estimations of urbanization are −0.34 (95%CI: −1.38, 1.47), demonstrating a positive correlation in eastern China, yet negative in the western region. Other socioeconomic factors such as industrial electricity consumption, the share of secondary industry, population density, and research and development (R&D) expenditures have a significantly positive influence on industrial NOx emissions, while gross domestic production (GDP) has a negative impact. Our findings reveal that, due to the variances in urbanization levels and socio-economic factors, NOx control policies and regional emission reduction strategies in China implemented in a tailor-made form (such as “One-City-One-Policy”) will be more effective.

The new-type urbanization which emphasizes urban infrastructure improvement, together with neighboring cities, may influence CO2 emissions of urban facilities and energy-intensive industrial sectors. This study analyzes the spillover effects of new-type urbanization on CO2 emissions of the central heating sector in northern China during 2012-2019. We measured the new-type urbanization from six dimensions, then built three spatial Environmental Kuznets Curve (EKC) models based on an extended stochastic impact by regression on population, affluence, and technology (STIRPAT) framework. Our results show that CO2 emissions at the city level increased by 18.0% for every 1% increase in that city's own new-type urbanization level, while decreasing by 7.58% every 1% rise in the average new-type urbanization level of its neighboring cities. The results indicate inverted "U-shaped" relationship between new-type urbanization and CO2 emissions, and the peak will be earlier due to the spillover effects of urbanization at the city level.

Cities and urban agglomerations are carriers of greenhouse gas emissions and show significant heterogeneity. China has entered a transitional period of new-type urbanization, which emphasizes high-quality and coordinated regional development. However, evidence of the spatiotemporal heterogenous effects of new-type urbanization on carbon emissions in cities, and especially in urban agglomerations are still lacking. This study estimated the new-type urbanization level and investigated its spatiotemporal heterogenous impacts on carbon dioxide emissions (CO₂) in 288 Chinese cities and 18 urban agglomerations. The results show that for each 1% increase in new-type urbanization level, the median estimation of CO₂ emissions per capita can decrease by 171.0% (46.8%,338.4%) at city-level. The inverted “U-shaped” relationships between new-type urbanization and CO₂ emissions per capita were observed in more than 60% of the cities. The average impacts of new-type urbanization and its square term of the cities which are located in urban agglomerations are estimated to be approximately 0.8 and 1.7 times of cities that are not, which indicates that cities in urban agglomerations are peaking their CO₂ emissions per capita with a higher enhancement of new-type urbanization. The results add new insights for formulating dynamic phase-to-phase carbon reduction policies and urban planning in cities and urban agglomerations.

China has been placing a substantial focus on biogas for reducing energy consumption and carbon dioxide (CO2) emissions. The operation mode of biogas systems may make the CO2 reduction target over-optimistic. There is limited research to investigate the influential factors that may be causing the gap between the actual and theoretical CO2 reduction costs of biogas systems in China. In this research, by using field survey data of 209 biogas users and 489 non-biogas users from 19 villages in 2015, the gap between actual and theoretical unit CO2 reduction cost is quantified at approximately 156 USD/t CO2. By employing the Logarithmic Mean Divisia Index I (LMDI) model, it is found that both the cost effect (48%) and the reduction effect (52%) contribute to the unit CO2 reduction cost gap. Four influential factors–household labor, accessibility to the energy resource, acceptance of biogas technology, and subsidy–significantly narrow the gap between actual and theoretical CO2 reduction costs, while the levelized subsidy contributes to widening the gap. On average, biogas systems should be operated for at least four years and the substitution rate should be more than 67% in order to keep the gap between actual and theoretical CO2 reduction costs under 50%.

The chlorine radical (Cl-center dot) plays an important role in the formation of secondary pollutants such as ozone and secondary organic aerosols. However, primary emissions of reactive chlorine species are not well known. Here, we develop an up-to-date emission inventory of major primary reactive chlorine precursors, including chlorine gas (Cl-2), hypochlorous acid (HOCl), hydrogen chloride (HCl), and particulate chloride (pCl) in mainland China for the year 2019 with a spatial resolution of 0.1 degrees x 0.1 degrees. The anthropogenic sources considered in this study include six major source categories (coal combustion, industrial processes, municipal solid waste incineration, biomass burning, cooking, and chlorine-containing disinfectants) and 22 sub-categories. The Cl-2, HOCl, HCl, and pCl emissions in mainland China in the year 2019 are estimated to be 7.8, 27.6, 270.3, and 183.5 Gg, respectively, with the major source contributors being use of chlorine-containing disinfectant (46%), use of chlorine-containing disinfectant (100%), biomass burning (36.1%), biomass burning (78.0%), respectively. The emission intensity of Cl-2, HOCl, HCl, and pCl for most provinces range from 0 to 3 tons.year(-1).km(-2). Emissions are highest in Eastern China, especially in the Beijing-Tianjin-Hebei and surrounding area, and the Yangtze River Delta region. The temporal distribution varies in different regions due to different human activities, industrial structures, and climatic conditions. The Monte Carlo method was applied to quantify the uncertainty of this emission inventory. The ranges of uncertainty in the emission of Cl-2, HOCl, HCl, and pCl were estimated to be 4.4-14.2, 9.7-51.6, 207.2-422.7, and 106.4-321.1 Gg.yr(-1), respectively. This study provides an updated chlorine emission inventory with improved spatial and temporal resolution, enabling better quantification of chlorine production and its impact on the air quality in China.

Understanding the spatio-temporal heterogeneous effects of socioeconomic and meteorological factors on CO2 emissions from combinations of different district heating systems with "Coal-to-Gas" transition can contribute to the development of future low-carbon energy systems that are efficient and effective. This work downscales city-level CO2 emissions to a 3 × 3 km2 gridded level in northern China during 2012 to 2018. By employing the Geographically and Temporally Weighted Regression (GTWR) model, nighttime light (NTL) data are adopted as a proxy of the level of urbanization, and the Temperature-Humidity-Wind (THW) Index is used as a proxy of meteorological factors in the downscaling model. The results show that, for more than 85% of the cities, urbanization significantly enhances the CO2 emissions of district heating systems, while the THW Index shows negative impacts on CO2 emissions. Significant spatial and temporal heterogeneity exists. The grids with the highest CO2 emissions from coal-fired boilers (grids with annual variation >0.59 Gg CO2/year) are mainly located in nonurban areas of the two megacities Beijing and Tianjin and also in the capital cities of each province. Urbanization has larger effects on the CO2 emissions of natural gas-fired boilers than of coal-fired boilers and combined heat and power (CHP). The average growth rate of CO2 emissions of gas-fired boilers in the urban areas of the study regions was approximately 4.7 times that of nonurban areas. The spatio-temporal heterogeneous impacts of urbanization on CO2 emissions should therefore be considered in future discussions of clean heating policies and climate response strategies.

Improving air quality is an important driving force for China’s move toward clean energy. Since 2017, the “coal-to-gas” and “coal-to-electricity” strategies have been extensively implemented in northern China, aiming at reducing dispersed coal consumption and related air pollution by promoting the use of clean and low-carbon fuels. Our analyses show that on top of meteorological influences, the effective emission mitigation measures achieved an average decrease of fine particulate matter (PM2.5) concentrations of ∼14% in Beijing and surrounding areas (the “2+26” pilot cities) in winter 2017 compared to the same period of 2016, where the dispersed coal control measures contributed ∼60% of the total PM2.5 reductions. However, the localized air quality improvement was accompanied by a contemporaneous ∼15% upsurge of PM2.5 concentrations over large areas in southern China. We find that the pollution transfer that resulted from a shift in emissions was of a high likelihood caused by a natural gas shortage in the south due to the coal-to-gas transition in the north. The overall shortage of natural gas greatly jeopardized the air quality benefits of the coal-to-gas strategy in winter 2017 and reflects structural challenges and potential threats in China’s clean-energy transition. Our finding highlights the importance and necessity of synergy between environmental and energy policymaking to address the grand challenge of an actionable future to achieve the cobenefits of air quality, human health, and climate.

Abstract Observing the spatial heterogeneities of NO2 air pollution is an important first step in quantifying NOX emissions and exposures. This study investigates the capabilities of the Tropospheric Monitoring Instrument (TROPOMI) in observing the spatial and temporal patterns of NO2 pollution in the continental United States. The unprecedented sensitivity of the sensor can differentiate the fine‐scale spatial heterogeneities in urban areas, such as emissions related to airport/shipping operations and high traffic, and the relatively small emission sources in rural areas, such as power plants and mining operations. We then examine NO2 columns by day‐of‐the‐week and find that Saturday and Sunday concentrations are 16% and 24% lower respectively, than during weekdays. We also analyze the correlation of daily maximum 2‐m temperatures and NO2 column amounts and find that NO2 is larger on the hottest days (>32°C) as compared to warm days (26°C–32°C), which is in contrast to a general decrease in NO2 with increasing temperature at moderate temperatures. Finally, we demonstrate that a linear regression fit of 2019 annual TROPOMI NO2 data to annual surface‐level concentrations yields relatively strong correlation (R2 = 0.66). These new developments make TROPOMI NO2 satellite data advantageous for policymakers and public health officials, who request information at high spatial resolution and short timescales, in order to assess, devise, and evaluate regulations.

Emission inventory development for air pollutants, by compiling records from individual emission sources, takes many years and involves extensive multi-national effort. A complementary method to estimate air pollution emissions is in the use of satellite remote sensing. In this study, NO 2 observations from the Ozone Monitoring Instrument are combined with re-analysis meteorology to estimate urban nitrogen oxide (NO X ) emissions for 80 global cities between 2005 and 2019. The global average downward trend in satellite-derived urban NO X emissions was 3.1%–4.0% yr −1 between 2009 and 2018 while inventories show a 0%–2.2% yr −1 drop over the same timeframe. This difference is primarily driven by discrepancies between satellite-derived urban NO X emissions and inventories in Africa, China, India, Latin America, and the Middle East. In North America, Europe, Korea, Japan, and Australasia, NO X emissions dropped similarly as reported in the inventories. In Europe, Korea, and Japan only, the temporal trends match the inventories well, but the satellite estimate is consistently larger over time. While many of the discrepancies between satellite-based and inventory emissions estimates represent real differences, some of the discrepancies might be related to the assumptions made to compare the satellite-based estimates with inventory estimates, such as the spatial disaggregation of emissions inventories. Our work identifies that the three largest uncertainties in the satellite estimate are the tropospheric column measurements, wind speed and direction, and spatial definition of each city.

The spatial distribution and the identification of the influential factors of industrial sulfur dioxide (SO2) emissions have received extensive attention. However, evidence is still lacking on the spatial impacts of urbanization on industrial SO2 emissions at the city scale in China. This work builds a Geography Weighted Regression (GWR) model on a Stochastic Impacts by Regression on Population, Affluence and Technology (STIRPAT) framework to investigate the spatially heterogeneous impacts of potential influencing factors on city-level industrial SO2 emissions from 288 prefecture-level cities in China. The results show that the GWR model significantly improved the goodness-of-fit of the model. The influence of night-time light intensity of the cities, as a proxy of the urbanization level, was calculated to be median (min, max): -0.505(-0.918, -0.413). The highest impacts of urbanization were observed in the Northeast and Southwest regions. Industrial influencing factors had generally promoted the growth of SO2 emissions, with higher positive impacts in western cities. We concluded that urbanization had a significant and negative effect on industrial SO2 emissions in most Chinese cities. It is necessary to formulate emission reduction and city development policies simultaneously based on the trade-offs between urbanization and air pollution control targets.