How to perceive and map the synergy between CO2 and air pollutants: Observation, measurement, and validation from a case study of China.

Cities occupy a central position in addressing climate change and promoting sustainable regional development. Synergistic control of urban gas emissions at the city level is one of the main issues typically explored. The confounding effect and the interactions between the urban indicators of population and area have been ignored in previous studies. In this study, we examined the spatial distribution characteristics and synergy between greenhouse gases (CO2) and air pollutants (SO2 and NOX) using spatial population and gas emission data. By upgrading the city clustering algorithm (CCA), we established a method for defining active areas of gas emissions (spatial element-coupled clustering, SECC) and identified active areas of gas emissions in China. In this study, we created a research framework that can simultaneously consider the effects of population and area, as well as the possible interactions between these indicators in active areas. The superlinear scaling relationship between the above three gases was revealed at the active zone level, and the existence of synergy between the emission patterns of the three gases was confirmed. Via further model application, we measured the synergistic efficiency of the three gases. It was found that for every 1% increase in SO2 and NOX in an active zone, CO2 increases by 0.86%. In this study, we explored a new perspective and approach to explain the synergy between greenhouse gases and air pollutants. This is essential to promote national competition among cities to achieve synergistic control of CO2 and local air pollutants.

Modelling monthly-gridded carbon emissions based on nighttime light data.

Timely and accurate implementation of carbon emissions (CE) analysis and evaluation is necessary for policymaking and management. However, previous inventories, most of which are yearly, provincial or city, and incomplete, have failed to reflect the spatial variations and monthly trends of CE. Based on nighttime light (NTL) data, statistical data, and land use data, in this study, a high-resolution (1 km × 1 km) monthly inventory of CE was developed using back propagation neural network, and the spatiotemporal variations and impact factors of CE at multiple administrative levels was evaluated using spatial autocorrelation model and spatial econometric model. As a large province in terms of both economy and population, Guangdong is facing the severe emission reduction challenges. Therefore, in this study, Guangdong was taken as a case study to explain the method. The results revealed that CE increased unsteadily in Guangdong from 2013 to 2022. Spatially, the high CE areas were distributed in the Pearl River Delta region such as Guangzhou, Shenzhen, and Dongguan, while the low CE areas were distributed in West and East Guangdong. The Global Moran's I decreased from 2013 to 2022 at the city and county levels, suggesting that the inequality of CE in Guangdong steadily decreased at these two administrative levels. Specifically, at the city level, the Global Moran's I gradually decreased from 0.4067 in 2013 to 0.3531 in 2022. In comparison, at the county level, the trend exhibited a slower decline, from 0.3647 in 2013 to 0.3454 in 2022. Furthermore, the analysis of the impact factors revealed that the relationship between CE and gross domestic product was an inverted U-shaped, suggesting the existence of the inverted U-shaped Environmental Kuznets Curve for CE in Guangdong. In addition, the industrial structure had larger positive impact on CE at the different levels. The method developed in this study provides a perspective for establishing high spatiotemporal resolution CE evaluation through NTL data, and the improved inventory of CE could help understand the spatial-temporal variations of CE and formulate regional-monthly-specific emission reduction policies.

Facility-Level Emissions and Synergistic Control of Energy-Related Air Pollutants and Carbon Dioxide in China.

Boilers involve ∼60% of primary energy consumption in China and emit more air pollutants and CO2 than any other infrastructures. Here, we established a nationwide, facility-level emission data set considering over 185,000 active boilers in China by fusing multiple data sources and jointly using various technical means. The emission uncertainties and spatial allocations were significantly improved. We found that coal-fired power plant boilers were not the most emission-intensive boilers with regard to SO2, NOx, PM, and mercury but emitted the highest CO2. However, biomass- and municipal waste-fired combustion, regarded as zero-carbon technologies, emitted a large fraction of SO2, NOx, and PM. Future biomass or municipal waste mixing in coal-fired power plant boilers can make full use of the advantages of zero-carbon fuel and the pollution control devices of coal-fired power plants. We identified small-size boilers, medium-size boilers using circulating fluidized bed boilers, and large-size boilers located in China's coal mine bases as the main high emitters. Future focuses on high-emitter control can substantially mitigate the emissions of SO2 by 66%, NOx by 49%, PM by 90%, mercury by 51%, and CO2 by 46% at the most. Our study sheds light on other countries wishing to reduce their energy-related emissions and thus the related impacts on humans, ecosystems, and climates.

Closing the Gap between Carbon Neutrality Targets and Action: Technology Solutions for China's Key Energy-Intensive Sectors.

Facing significant carbon emissions annually, China requires a clear decarbonization strategy to meet its climate targets. This study presents a MESSAGEix-CAEP model to explore Chinese decarbonization pathways and their cost-benefit under two mitigation scenarios by establishing connections between five energy-intensive sectors based on energy and material flows. The results indicated the following: 1) Interaction and feedback between sectors should not be disregarded. The electrification process of the other four sectors was projected to increase electricity production by 206%, resulting in a higher power demand than current forecasts. 2) The marginal abatement cost to achieve carbon neutrality across all five sectors was 2189 CNY/tCO2, notably higher than current Chinese carbon emission trading prices. 3) The cost-benefit analysis indicates that a more ambitious abatement strategy would decrease the marginal abatement cost and result in a higher net carbon abatement benefit. The cumulative net benefit of carbon reduction was 7.8 trillion CNY under ambitious mitigation scenario, 1.3 trillion CNY higher than that under current Chinese mitigation scenario. These findings suggest that policy-makers should focus on the interaction effects of decarbonization pathways between sectors and strengthen their decarbonization efforts to motivate early carbon reduction.

Heterogeneous effects of China's low-carbon city pilots policy.

Global south countries, including China, have faced a challenging dilemma of reducing carbon emissions while maintaining rapid economic growth. The low-carbon city pilots (LCCPs) policy in China is a demonstration of how state power intervenes and commands national low-carbon development through voluntary policy tools. Our study, based on panel data of 331 cities from 2005 to 2019, evaluates the policy effect of all three batches of LCCPs and presents an analysis of time-varying effects through batch decomposition and synthetic difference-in-difference models. The study found that implementing low-carbon policies can significantly reduce total carbon emissions and carbon emissions per capita. However, the reduction in carbon emissions per unit of GDP is insignificant, and the policy effect varies according to the batches and their characteristics. The reduction effects in the first and second batches, as well as the insignificance or even increasing effects of the third batch, may be due to carbon leakage between different batches of LCCPs. Overall, this research provides novel and quantitative evidence on low-carbon development in China, making theoretical and empirical contributions to the field, and expanding econometric assessment methods to evaluate the effectiveness of environmental and climate change policies.

Exploring the spatiotemporal pattern evolution of carbon emissions and air pollution in Chinese cities.

Based on data from 335 cities in China, this study employs the standard deviation ellipse method to portray unbalanced and differential spatiotemporal evolution patterns of environmental emissions and socioeconomic elements. A logarithmic mean Divisia index analysis and in-depth discussion are carried out to disclose the main driving factors and underlying reasons for the differences. Decoupling trends exist among carbon emissions, gross domestic product (GDP) and population in terms of their gravity center migrations. The standard deviation ellipse direction of carbon emissions gradually changed from 'northeast‒southwest' to 'northwest‒southeast', and the standard deviation ellipse areas of carbon emissions and air pollution continuously expanded over time; at the same time, that of GDP contracted. Economic growth has always been the main driver of carbon emissions and air pollution nationally, but its role has weakened. Moreover, decreases in the energy intensity and carbon and pollution intensities are the main factors contributing to emissions reductions. Differentiated spatiotemporal economic structure evolution, regional heterogeneities in the energy intensity and efficiency, and cross-region power energy transmissions are identified as the underlying reasons for the unbalanced spatiotemporal patterns of the environmental emissions and socioeconomic elements. Based on these findings, policy suggestions can be made to address the imbalances and promote carbon mitigation, air quality improvement and high-quality social-economic development at the city level.

Co-benefits of peaking carbon dioxide emissions on air quality and health, a case of Guangzhou, China.

Cities play a key role in making carbon emission reduction targets achievable and tackling air pollution. Using Guangzhou city as a case, this paper explored the air quality and health co-benefits of peaking carbon dioxide emissions under three scenarios and developed an integrated assessment framework by combining a local air pollutant emission inventory, an atmospheric chemistry transport model, and a health assessment model. The results showed that SO2, PM10, and PM2.5 could achieve larger emission reductions than NH3, VOCs, and NOx among all the scenarios we examined. Under the enhanced peaking scenario with the most stringent mitigation strategies, Guangzhou could meet the local ambient air quality standard for PM2.5 (34 µg/m3), with the most reduction observed in the annual average PM2.5 concentration (28.4%) and related premature deaths (17.08%), compared with the base year 2015. We also identified hotspot grids, which were areas with high concentrations of carbon emissions, high concentrations of air pollution and poor air quality in Guangzhou. Our analysis highlighted the importance of promoting peaking carbon dioxide emission for the improvement of air quality and public health at the city level.

Impacts of the COVID-19 event on the NOx emissions of key polluting enterprises in China.

The unprecedented cessation of human activities during the COVID-19 pandemic has affected China's industrial production and NOx emissions. Quantifying the changes in NOx emissions resulting from COVID-19 and associated governmental control measures is crucial to understanding its impacts on the environment. Here, we divided the research timeframe into three periods: the normal operation period (P1), the Spring Festival period (P2), and the epidemic period following the Spring Festival (P3). We then calculated the NOx operating vent numbers and emission concentrations of key polluting enterprises in 29 provinces and 20 industrial sectors and compared the data for the same periods in 2020 and 2019 to obtain the impacts of COVID-19 on industrial NOx emissions. We found that spatially, from P1 to P2 in 2020, the operating NOx vent numbers in North China changed the most, with a relative change rate of -33.84%. Comparing the operating vent numbers in P1 and P3, East China experienced the largest decrease, approximately -32.72%. Among all industrial sectors, the mining industry, manufacturing industry, power, heat, gas, and water production and supply industry, and the wholesale and retail industry, were the most heavily influenced. In general, the operating vent numbers of key polluting enterprises in China decreased by 24.68%, and the standardized NOx (w)5-day decreased by an average of -9.54 ± -6.00 due to the COVID-19 pandemic. The results suggest that COVID-19 significantly reduced the NOx emission levels of the key polluting enterprises in China.

Establishment of High-Resolution Atmospheric Mercury Emission Inventories for Chinese Cement Plants Based on the Mass Balance Method.

China is the world's largest cement-related mercury emitter. Atmospheric mercury inventories for China's cement industry are essential for appraising global mercury emissions and have been widely developed in previous studies associated with considerable uncertainties. In this study, we compiled high tempo-spatial resolution atmospheric mercury emission inventories for Chinese cement plants using the mass balance method and plant-level input-output data. The effects of industry policies were investigated based on the inventories for 2007 and 2015. Nationwide emissions increased from 80 to 113 t due to rapid expansion of production and kiln-type substitution yet partly offset by policies involving capacity structure reformation. Pollution decreased in winter in northern China, thanks to the targeting policies. Mercury input, output, and storage in cement kilns in China were estimated. The uncertainty remarkably decreased relative to previous inventories. This study demonstrates the feasibility of establishing high-resolution emission inventories with the application of the mass balance method for all the individual plants nationwide and thus has implications for similar studies. This work also improves our understanding of the spatial patterns and temporal evolution of mercury emissions in China, thus offering references for the implementation of environment policies and the Minamata Convention on Mercury in China.

Toward low-carbon development: Assessing emissions-reduction pressure among Chinese cities.

Assessing emissions-reduction pressure among Chinese cities is a critical task for local governments formulating and implementing environmental policies. From the perspectives of carbon intensity and carbon inequality, this study develops an improved carbon dioxide (CO2) emissions-reduction index to quantify emissions-reduction pressure on 284 cities in China. Results indicate that driven by the decrease of overall carbon intensity and the rise of inter-city carbon inequality, emissions-reduction pressure on 41.38% of provinces and 49.65% of cities was greater than the overall national level; emissions-reduction pressure on 52.35% of cities exceeded the provincial average level. The central government determines national emissions-reduction pressure by adjusting carbon-inequality tolerance between cities and determines carbon-inequality preference based on population and economic output principles. These determinations become benchmarks for local governments' CO2 emissions-reduction pressure. Provinces and cities that exceed benchmarks become foci for promoting energy savings, emissions reduction, and low-carbon development in the future.

Who is a good neighbor? Analysis of frontrunner cities with comparative advantages in low-carbon development.

A well-developed economy and low-carbon emission intensity are important characteristics of low-carbon cities; they also represent important tasks for achieving global climate change mitigation goals. It is seldom discussed, however, how we should identify frontrunner cities from which low-carbon development experiences can be gleaned and then implemented in neighboring cities. This study, therefore, proposed a simple indicator-the "good neighbor index"-to identify frontrunner cities in low-carbon transformation based on economic and emission performance. Based on this indicator, we identified "good neighbors" in static and dynamic views for China. The results showed that the static good neighbors in 2015 were mostly large cities with higher incomes and better industrial structures whereas the dynamic neighbors achieved better economic growth and emission reductions from 2005 to 2015, though their economic and emissions statuses were generally worse. The good neighbor list is not consistent with the list of national low-carbon pilot cities, which has largely overlooked the experiences of some fast-growing cities. These results have policy implications for the Chinese government in terms of promoting the low-carbon transformation of cities. The study can also provide a reference for other countries in addressing climate change at the city level.

Incorporating health impacts into a differentiated pollution tax rate system: A case study in the Beijing-Tianjin-Hebei region in China.

This paper argues for an efficient pollution tax rate system that reflects the differentiation of marginal health damages of the individual emission sources. Although China is the first country in the world to launch a regionally differentiated pollution tax rate program, due to the absence of marginal damage estimation, whether this policy is efficient and equitable remains unknown. In this paper, we build an Integrated Assessment Model to measure the marginal damage of SO2, NOx and PM2.5 emitted from 38 coal-fired power plants in the Beijing-Tianjin-Hebei region, and evaluate the policy performance of tax rate systems with different differentiation magnitudes. Results show that the spatial variations are huge, the range of marginal health damages of coal-fired power plants in the BTH region between the lowest and highest emission source is $2375 to $33245 per ton for SO2, $307 to $4984 per ton for NOx, and $11513 - $163126 per ton for PM2.5. Shifting from the uniform tax rate system to the current partially differentiated tax rate system will increase the total health benefits by 51.6% but with some regions worse-off than the uniform tax rate system. If we incorporate the source-specific variations of marginal health damages into the tax rate system, such a fully differentiated tax rate system will further increase the total health benefits of current partially differentiated tax rate system by 43.1% with every region better-off. Furthermore, even though the policy benefits of both differentiated tax rate systems are much more unequally distributed than uniform tax rates, their impacts on environmental inequalities are better than the uniform tax rate system. Because uniform tax rate systems do not offset the original inequalities of environmental health burdens while differentiated tax rate systems achieve this buy efficiently allocate mitigation targets among regions with different burdens.

Cleaner heating choices in northern rural China: Household factors and the dual substitution policy.

Household heating is a major contributor to frequent winter haze in northern China. Transition to cleaner household heating is associated with multiple benefits including improved environmental conditions and health of local residents. This study presents an analysis of data from an indoor survey covering 1030 households in 136 villages of Hebi City in the winter of 2018. The main purpose of this study was to reveal the key factors that affect cleaner heating choices under the national pilot program of the dual substitution policy, which targets the replacement of coal heating with gas and electric heating. The survey showed that electric heating is the most popular heating method, and the adoption of cleaner heating rises with income, and energy and device costs may be the major barriers to adopting cleaner heating. Further, multinomial logit regression was used to investigate the household factors and found that income, heating area, energy cost, and education had significant impacts on heating choices. In addition, the gas substitution policy was more effective in promoting the cleaner heating transition than was the electric substitution policy. Results show that more freedom to choose energies and devices, as well as infrastructure for gas supply and centralized heating, is also vital for the adoption of cleaner heating. Our study provides new insights to improve the details of implementation of the dual substitution policy.

Source data supported high resolution carbon emissions inventory for urban areas of the Beijing-Tianjin-Hebei region: Spatial patterns, decomposition and policy implications.

This paper developed internationally compatible methods for delineating boundaries of urban areas in China. By integrating emission source data with existing official statistics as well as using rescaling methodology of data mapping for 1 km grid, the authors constructed high resolution emission gridded data in Beijing-Tianjin-Hebei (Jing-Jin-Ji) region in China for 2012. Comparisons between urban and non-urban areas of carbon emissions from industry, agriculture, household and transport exhibited regional disparities as well as sectoral differences. Except for the Hebei province, per capita total direct carbon emissions from urban extents in Beijing and Tianjin were both lower than provincial averages, indicating the climate benefit of urbanization, comparable to results from developed countries. Urban extents in the Hebei province were mainly industrial centers while those in Beijing and Tianjin were more service oriented. Further decomposition analysis revealed population to be a common major driver for increased carbon emissions but climate implications of urban design, economic productivity of land use, and carbon intensity of GDP were both cluster- and sector-specific. This study disapproves the one-size-fits-all solution for carbon mitigation but calls for down-scaled analysis of carbon emissions and formulation of localized carbon reduction strategies in the Jing-Jin-Ji as well as other regions in China.

Evaluating the impact of odors from the 1955 landfills in China using a bottom-up approach.

Landfill odors have created a major concern for the Chinese public. Based on the combination of a first order decay (FOD) model and a ground-level point source Gaussian dispersion model, the impacts from odors emitted from the 1955 landfills in China are evaluated in this paper. Our bottom-up approach uses basic data related to each landfill to achieve a more accurate and comprehensive understanding of impact of landfill odors. Results reveal that the average radius of impact of landfill odors in China is 796 m, while most landfills (46.85%) are within the range of 400-1000 m, in line with the results from previous studies. The total land area impacted by odors has reached 837,476 ha, accounting for 0.09% of China's land territory. Guangdong and Sichuan provinces have the largest land areas impacted by odors, while Tibet Autonomous Region and Tianjin Municipality have the smallest. According to the CALPUFF (California Puff) model and an analysis of social big data, the overall uncertainty of our calculation of the range of odor impacts is roughly -32.88% to 32.67%. This type of study is essential for gaining an accurate and detailed estimation of the affected human population and will prove valuable for addressing the current Not In My Back Yard (NIMBY) challenge in China.

High resolution carbon dioxide emission gridded data for China derived from point sources.

A high spatial resolution carbon dioxide (CO2) emission map of China is proving to be essential for China's carbon cycle research and carbon reduction strategies given the current low quality of CO2 emission data and the inconsistencies in data quality between different regions. Ten km resolution CO2 emission gridded data has been built up for China based on point emission sources and other supporting data. The predominance of emissions from industrial point sources (84% of total emissions) in China supports the use of bottom-up methodology. The resultant emission map is informative and proved to be more spatially accurate than the EDGAR data. Spatial distribution of CO2 emissions in China is highly unbalanced and has positive spatial autocorrelation. The spatial pattern is mainly influenced by key cities and key regions, i.e., the Jing-Jin-Ji region, the Yangtze River delta region, and the Pearl River delta region. The emission map indicated that the supervision of 1% of total land could enable the management of about 70% of emissions in China.

City level water withdrawal and scarcity accounts of China.

In the context of China's freshwater crisis high-resolution data are critical for sustainable water management and economic growth. Yet there is a dearth of data on water withdrawal and scarcity regardless of whether total or subsector amount, for prefectural cities. In administrative and territorial scope, we accounted for water withdrawal of all 63 economic-socio-environmental sectors for all 343 prefectural cities in China, based on a general framework and 2015 data. Spatial and economic-sector resolution is improved compared with previous studies by partitioning general sectors into industrial and agricultural sub-sectors. Construction of these datasets was based on selection of 16 driving forces. We connected a size indicator with corresponding water-withdrawal efficiency. We further accounted for total blue-water withdrawal and quantitative water scarcity status. Then we compared different scopes and methods of official accounts and statistics from various water datasets. These disaggregated and complete data could be used in input-output models for municipal design and governmental planning to help gain in-depth insights into subsector water-saving priorities from local economic activities.

Expanding carbon neutrality strategies: Incorporating out-of-boundary emissions in city-level frameworks.

Cities are increasingly vital in global carbon mitigation efforts, yet few have specifically tailored carbon neutrality pathways. Furthermore, out-of-boundary indirect greenhouse gas (GHG) emissions, aside from those related to electricity and heat imports, are often overlooked in existing pathways, despite their significance in comprehensive carbon mitigation strategies. Addressing this gap, here we introduce an integrated analysis framework focusing on both production and consumption-related GHG emissions. Applied to Wuyishan, a service-oriented city in Southern China, this framework provides a holistic view of a city's carbon neutrality pathway, from a full-scope GHG emission perspective. The findings reveal the equal importance of carbon reduction within and outside the city's boundaries, with out-of-boundary emissions accounting for 42% of Wuyishan's present total GHG emissions. This insight highlights the necessity of including these external factors in GHG accounting and mitigation strategy development. This framework serves as a practical tool for cities, particularly in developing countries, to craft effective carbon neutrality roadmaps that encompass the full spectrum of GHG emissions.

Machine learning approaches reveal highly heterogeneous air quality co-benefits of the energy transition.

Estimating health benefits of reducing fossil fuel use from improved air quality provides important rationales for carbon emissions abatement. Simulating pollution concentration is a crucial step of the estimation, but traditional approaches often rely on complicated chemical transport models that require extensive expertise and computational resources. In this study, we develop a machine learning framework that is able to provide precise and robust annual average fine particle (PM2.5) concentration estimations directly from a high-resolution fossil energy use dataset. Applications of the framework with Chinese data reveal highly heterogeneous health benefits of avoiding premature mortality by reducing fossil fuel use in different sectors and regions in China with a mean of $19/tCO2 and a standard deviation of $38/tCO2. Reducing rural and residential coal use offers the highest co-benefits with a mean of $151/tCO2. Our findings prompt careful policy designs to maximize cost-effectiveness in the transition toward a carbon-neutral energy system.

A new method of hotspot analysis on the management of CO2 and air pollutants, a case study in Guangzhou city, China.

Emission inventory plays an important role in designing effective emission control strategies. Currently, there is unbalanced development of CO2 and air pollutant emission inventories in China and the spatial information of both cannot be obtained simultaneously, which prevents a collaborative control strategy. In this study, we developed a unified emission inventory including both CO2 and air pollutants, then utilized spatial mapping methods to identify the co-hotspots of both CO2 and air pollutants at a high spatial resolution (1 × 1 km2). We applied Guangzhou city as a case study to illustrate the method. The results showed that CO2 and air pollutants were mainly emitted from the stationary combustion sector and the transportation sector. These two sectors contributed 95 %, 67 %, and 93 % to total CO2, SO2, and NOx emissions, respectively. Up to 86 %, 86 %, 66 %, and 72 % of total CO2, SO2, NOx, and PM2.5 emissions were attributed to the top 10 % emission grids with 1 × 1 km2 resolution. However, our results showed high emission grids were not surrounded by other high emissions grids for all types of emissions analyzed in this study. The co-hotspot analysis enables accurate identification of high-emission grids, which helps environment managers to prioritize resource allocation when designing control strategies. Our study underscores the importance of managing CO2 and air pollutants simultaneously at the city level.