The impact of public demands on local environmental governance performance: Evidence from civil environmental complaints placed on leaders at different government levels in China.

The joint participation of multiple subjects is crucial for environmental governance. Using panel data for 273 Chinese cities during 2013-2019, this study investigates the impact and mechanism of public demands on environmental pollution. The results demonstrate that public demands measured by the number of environmental complaints placed on government leaders significantly reduce environmental pollution. Furthermore, increases in the rate and speed of government responses improve the effect of public demands on environmental governance. Public demands placed on provincial leaders reduce local environmental pollution to a greater extent than public demands placed on prefectural and county leaders. Province-level governments are more willing to consider public opinions and attach more importance to environmental governance; Prefecture-level governments prioritize province-level governments' attention to the environment when implementing environmental governance. Moreover, strong political ties between provincial and prefectural leaders and long tenures among prefectural leaders strengthen the pollution reduction effect of public demands placed on provincial leaders. The reduction effect of environmental complaints on pollution emission is more significant in cities with high level of Internet construction and environmental disclosure. Our results illustrate the role of public demands in environmental governance, offering a reference for developing effective environmental policies.

How does early-life famine experience influence household energy transition?

The transition of households towards cleaner energy is crucial for achieving sustainable development goals. However, the impacts and associated mechanisms of early-life experiences on household energy transition have not been considered. Based on data from the 2015 Chinese General Social Survey, this study aimed to investigate whether people experiencing China's Great Famine (1959-1961) in their early life promoted household energy transition in adulthood. The varying severity of the Great Famine in different provinces was characterised as a quasi-natural experiment and was used to perform difference-in-differences (DID) estimation analysis for birth cohorts. The results showed that the transitions from firewood, agricultural waste, and animal waste to liquefied petroleum gas and electricity were significant in households with the Great Famine experiences. Specifically, the long-term energy transition effect of the famine was exhibited mostly in those who experienced the famine during childhood (4-11 years old) and adolescence (12-17 years old). Besides, early-life famine experiences led to poor physical health, and more modern forms of energy, such as electricity, were consumed to avoid further deteriorating health. Early-life famine experience also brought psychological trauma to people at that time, which led them to increase Internet use to gain emotional support, and the increased Internet use provided better access to information about the energy transition. Moreover, the household energy transition influenced by early-life famine experience occurred more in female-headed, rural, more educated, and low-income households. Our results illustrated the role of early-life famine experience in household energy transition and provided new insights into developing effective energy policies.

Potential benefits of public-private partnerships to improve the efficiency of urban wastewater treatment.

For emerging economies lacking public budgets, continuous improvement of urban wastewater treatment efficiency (UWTE) requires effective government supervision of wastewater treatment infrastructures (WTIs) and participation of private capital seeking to profit-maximising. However, to what extent this public-private partnership (PPP) model, aimed at a reasonable sharing of benefit and risk, in delivering WTIs can improve the UWTE is unknown. We evaluated the impact of the PPP model on the UWTE by collecting data from 1303 urban wastewater treatment PPP projects in 283 prefecture-level cities in China from 2014 to 2019 and used data envelopment analysis and Tobit regression model. The UWTE was significantly higher in prefecture-level cities that introduced the PPP model in the construction and operation of WTIs, particularly those with a feasibility gap subsidy, competitive procurement, privatised operation, and non-demonstration. Moreover, the effects of PPPs on UWTE were limited by the economic development level, marketisation, and climatic conditions.

Spatio-Temporal Variation and Decomposition Analysis of Livelihood Resilience of Rural Residents in China.

The key to sustainable rural development and coordinated regional development is to properly measure the livelihood resilience of rural residents (LRRR), and investigate its regional differences, distribution characteristics, and evolutionary patterns. This study combined the entropy method, the Dagum Gini coefficient and decomposition, kernel density estimation, and convergence analysis to measure the LRRR in 30 provinces of China from 2006 to 2020, and to analyze its regional differences and sources, dynamic distribution, and characteristics of convergence. The LRRR in China overall declined 2006-2020, with an east-to-west spatial gradient toward lower livelihood resilience. Intra-regional differences in LRRR narrowed in the Eastern and Central Regions, while those in the Western Region widened. Inter-regional differences were the main source of differences in LRRR. The LRRRs in most provinces in China were gradually reaching the same level over time (i.e., σ convergence and ß convergence). This research provides a factual reference for policies related to reducing inter-provincial differences in the LRRR in China.

Global 1 km × 1 km gridded revised real gross domestic product and electricity consumption during 1992-2019 based on calibrated nighttime light data.

As fundamental data, gross domestic product (GDP) and electricity consumption can be used to effectively evaluate economic status and living standards of residents. Some scholars have estimated gridded GDP and electricity consumption. However, such gridded data have shortcomings, including overestimating real GDP growth, ignoring the heterogeneity of the spatiotemporal dynamics of the grid, and limited time-span. Simultaneously, the Defense Meteorological Satellite Program's Operational Linescan System (DMSP/OLS) and National Polar-orbiting Partnership's Visible Infrared Imaging Radiometer (NPP/VIIRS) nighttime light data, adopted in these studies as a proxy tool, still facing shortcomings, such as imperfect matching results, discontinuity in temporal and spatial changes. In this study, we employed a series of methods, such as a particle swarm optimization-back propagation (PSO-BP) algorithm, to unify the scales of DMSP/OLS and NPP/VIIRS images and obtain continuous 1 km × 1 km gridded nighttime light data during 1992-2019. Subsequently, from a revised real growth perspective, we employed a top-down method to calculate global 1 km × 1 km gridded revised real GDP and electricity consumption during 1992-2019 based on our calibrated nighttime light data.

City- and county-level spatio-temporal energy consumption and efficiency datasets for China from 1997 to 2017.

Understanding the evolution of energy consumption and efficiency in China would contribute to assessing the effectiveness of the government's energy policies and the feasibility of meeting its international commitments. However, sub-national energy consumption and efficiency data have not been published for China, hindering the identification of drivers of differences in energy consumption and efficiency, and implementation of differentiated energy policies between cities and counties. This study estimated the energy consumption of 336 cities and 2,735 counties in China by combining Defense Meteorological Satellite Program/Operational Line-scan System (DMSP/OLS) and Suomi National Polar-Orbiting Partnership/Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) satellite nighttime light data using particle swarm optimization-back propagation (PSO-BP). The energy efficiency of these cities and counties was measured using energy consumption per unit GDP and data envelopment analysis (DEA). These data can facilitate further research on energy consumption and efficiency issues at the city and county levels in China. The developed estimation methods can also be used in other developing countries and regions where official energy statistics are limited.

China's city-level carbon emissions during 1992-2017 based on the inter-calibration of nighttime light data.

Accurate, long-term, full-coverage carbon dioxide (CO2) data in units of prefecture-level cities are necessary for evaluations of CO2 emission reductions in China, which has become one of the world's largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program's Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership's Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO2 emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO2 dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China's future CO2 research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world.

Potential Role of Fiscal Decentralization on Interprovincial Differences in CO2 Emissions in China.

Spatial differences in CO2 emissions must be taken into account in CO2 mitigation. In this work, a spatial within-between logarithmic mean Divisia index decomposition model was developed by using cluster analysis to evaluate the potential role of fiscal decentralization in driving interprovincial differences in CO2 emissions in China. The results revealed that the direct impact of fiscal decentralization emerged as a major emission driver after 2009. The differences of provincial CO2 emissions from the national average can be mainly attributed to emission differences between the distinct provincial clusters. The direct and indirect impacts of fiscal decentralization contributed to the shaping of differences in CO2 emission between provinces and their provincial cluster average, and between provincial cluster average and the national average. Reducing the differences in CO2 emission between distinct provincial clusters should be considered a breakthrough for the Chinese government. The provinces with CO2 emissions below the national average and above the average emissions of its provincial cluster still have the potential for further mitigation. Optimizing the expenditure authority of the central and provincial governments and improving the energy efficiency of the provincial fiscal expenditure are the two effective ways to further promote CO2 mitigation.

County-level CO2 emissions and sequestration in China during 1997-2017.

With the implementation of China's top-down CO2 emissions reduction strategy, the regional differences should be considered. As the most basic governmental unit in China, counties could better capture the regional heterogeneity than provinces and prefecture-level city, and county-level CO2 emissions could be used for the development of strategic policies tailored to local conditions. However, most of the previous accounts of CO2 emissions in China have only focused on the national, provincial, or city levels, owing to limited methods and smaller-scale data. In this study, a particle swarm optimization-back propagation (PSO-BP) algorithm was employed to unify the scale of DMSP/OLS and NPP/VIIRS satellite imagery and estimate the CO2 emissions in 2,735 Chinese counties during 1997-2017. Moreover, as vegetation has a significant ability to sequester and reduce CO2 emissions, we calculated the county-level carbon sequestration value of terrestrial vegetation. The results presented here can contribute to existing data gaps and enable the development of strategies to reduce CO2 emissions 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.