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Enhancing the green economy efficiency (GEE) is crucial for building a sustainable economy. How can the rapidly advancing digital transformation contribute to this process? The paper empirically examines the direct and spatial spillover effects of digital transformation on cities' GEE in China. This study utilizes the National E-commerce Pilot City (NEPC) policy as a quasi-natural experiment of regional digital transformation and employs the staggered difference-in-differences (DID) method with heterogeneous effects. The findings reveal that (i) implementing the NEPC policy significantly increases urban GEE by 2.6%, corresponding to a 16% increase in the mean of GEE. This effect is particularly pronounced in non-resource-based cities and cities with high Internet penetration. (ii) The mechanism test shows that the pilot policy positively affects GEE by promoting green structural transformation, enhancing green innovation, and strengthening public environmental concerns. (iii) The study highlights a positive spatial spillover effect of the NEPC policy on the GEE of nonpilot cities. (iv) The adoption of the NEPC plays a pivotal role in advancing energy use and carbon emission efficiency. This paper expands the existing knowledge on the green development effects of the digital economy while offering valuable policy insights for building an "Inclusive Green Economy". [Display omitted] • The staggered differences-in-differences method is employed to examine the direct and spatial spillover effects of NEPC on cities' GEE in China. • This paper uses NEPC as a quasi-experiment for digital transformation. • NEPC significantly improves green economic efficiency by 2.6%. • Green structural transformation, innovation, and environmental concerns are main channels. • Positive spillover effect of NEPC on green economy efficiency in non-pilot cities. [ABSTRACT FROM AUTHOR]

Organic pollutants are important harmful components in atmospheric fine particulate matters (PM 2.5), health risks of which varied with temporal and spatial distributions. To clarify the characteristics of atmospheric organic pollution, the concentrations, sources, and human health risks of typical organic compositions in PM 2.5 samples from both industrial and urban areas of Nanjing in eastern China were investigated monthly for a year. Results showed that, the concentrations of PM 2.5 -bound polycyclic aromatic hydrocarbons (PAHs) and n-alkanes were higher in winter and spring than those in summer and autumn. The organic pollution was slightly higher in industrial than urban area, though the PAHs in autumn and the n-alkanes in warm season (summer and autumn) were higher in urban area. With regards to the pollutant sources, the atmospheric PAHs were dominated by motor vehicle exhaust in the urban area, and combined with coal combustion emission in the industrial area. Airborne n-alkanes were mainly from biological source accompanied by fossil fuel combustion in industrial area. The PM 2.5 -bound PAHs indicated higher risks to adults in industrial area than in urban area with the seasonal patterns: winter > spring > autumn > summer. More attention should be paid to the health risks of exposure to organic pollutants accumulated in PM 2.5 during cold season. Controlling vehicle emissions might be the key measure for alleviating atmospheric PAHs and n-alkanes pollution in megacities, while coal purification can be an effective control method in industrial areas. • Organic pollutants are typical harmful components in PM 2.5 • Concentrations, sources, and health risks of PM 2.5 show spatio-temporal patterns. • PAHs and n-alkanes pollution were serious in cold season and industrial area. • Vehicle emission is a key target for alleviating particulate organic pollution. • Coal purification can be an effective pollution control method in industrial area. [ABSTRACT FROM AUTHOR]

A high-resolution nutrient emission inventory can provide reliable and accurate identification of priority control areas, which is crucial for efficient decisions on water quality restoration. However, the inventories widely used in large-scale modeling are usually based on provincial inputs, which induce the challenges of lacking localized parameters and missing localized characteristic when provincial scale inputs are converted to finer scales with the down-scale methods. Based on elaborate investigations and statistical data at the county scale with multi-scale data conversion, the China Emission Inventory of Nutrients (CEIN) was developed with a spatial resolution of a 0.1° grid and sub-basin scales. The Yangtze River Basin was used as a case study to illustrate the potential applications of CEIN. The emissions of total nitrogen (TN) and total phosphorus (TP) of Yangtze River Basin is 0.43 Mt and 0.04 Mt for point sources, 11.09 Mt and 4.64 Mt for diffuse sources in 2017. The hotspot analysis for 2606 sub-basins indicated that cropland is the key source of nutrient emissions, accounting for 58.88% and 79.15% of TN and TP, respectively. Industrial sewage and freshwater aquaculture accounted for 27.39% (TN) and 21.98% (TP) of the point sources, which is substantial due to their direct discharge into surface waters. The current results also reveal that, in contrast to CEIN, the previously used common emission factors based on GDP per capita produced considerable overestimations of 2.37 and 2.65 times the actual TN and TP emissions, respectively. Additional advantages of the CEIN have been demonstrated in identifying priority control areas more accurately with reduced bias and quantifying the effects of policies at much smaller scales. For example, the CEIN helps to distinguish hotspots, which was neglected when identifying sources at the level-III sub-basin scale, and indicates that the management of fractional areas (TN: 16.97%; TP: 13.44%) provides the highest nutrient emissions control (TN: 44.34%; TP: 48.65%) for the entire basin. The evaluation of China's toilet revolution policy demonstrates that achieving equitable access to safe sanitation has resulted in a reduction of 7240 t of TN and 833 t of TP, which is extremely critical for rural water quality and health. [Display omitted] • High-resolution China Emission Inventory of Nutrients (CEIN) is developed with 0.1° grid. • Priority control areas were identified for 2606 sub-basins in the Yangtze River Basin. • Previous emission factors with GDP per capita produced considerable overestimations. • CEIN can quantify effects of policies at much smaller scales with reduced bias. [ABSTRACT FROM AUTHOR]

Accurately obtaining the pollution sources and their contribution rates is the basis for refining watershed management. Although many source analysis methods have been proposed, a systematic framework for watershed management is still lacking, including the complete process of pollution source identification to control. We proposed a framework for identification and abatement of pollutants and applied in the Huangshui River Basin. A newer contaminant flux variation method based on a one-dimensional river water quality model was used to calculate the contribution of pollutants. The contributions of various factors to the over-standard parameters of water quality sections at different spatial and temporal scales were calculated. Based on the calculation results, corresponding pollution abatement projects were developed, and the effectiveness of the projects was evaluated through scenario simulation. Our results showed that the large scale livestock and poultry farms and sewage treatment plants were the largest sources of total nitrogen (TP) in Xiaoxia bridge section, with contribution rates of 46.02% and 36.74%, respectively. Additionally, the largest contribution sources of ammonia nitrogen (NH 3 –N) were sewage treatment plants (36.17%) and industrial sewage (26.33%). Three towns that contributed the most to TP were Lejiawan Town (14.4%), Ganhetan Town (7.3%) and Handong Hui Nationality town (6.6%), while NH 3 –N mainly from the Lejiawan Town (15.9%), Xinghai Road Sub-district (12.4%) and Mafang Sub-district (9.5%). Further analysis found that point sources in these towns were the main contributor to TP and NH 3 –N. Accordingly, we developed abatement projects for point sources. Scenario simulation indicated that the TP and NH 3 –N could be significantly improved by closing down and upgrading relevant sewage treatment plants and building facilities for large scale livestock and poultry farms. The framework adopted in this study can accurately identify pollution sources and evaluate the effectiveness of pollution abatement projects, which is conducive to the refined water environment management. • A framework of pollution source identification and abatement is proposed. • Contaminant flux variation method was put forward for quantifying contribution. • Water quality scenarios models provide pollution management strategies. • Point source contributes the biggest for ammonia nitrogen and total phosphorus. • Impact from point sources on water quality was greater during the dry season. [ABSTRACT FROM AUTHOR]

China produces a large amount of industrial effluent with multiple pollutants contained, along with a flourishing economy. This study aims to examine the dynamics between China's industrialization and accompanying environmental pressure based on the gray water footprint (GWF) concept. A newly proposed net GWF (NetGWF) and the decoupling index (DI) are applied to evaluate China's industrial activities during 2002–2015 in different modes considering typical, all, and individual pollutants. The NetGWF dynamics are further quantitatively decomposed into 17 effects of not only commonly assessed drivers but also industrial fixed capital formation, inventory variation, and import, using an advanced dynamic decomposition analysis approach. Results show NetGWF is an effective indicator measuring domestic water pollution stress from industrialization, with NetGWF-AllPlt (estimated using all pollutants) validated to be more reliable and sensitive than NetGWF-COD&NH3N (estimated using Chemical oxygen demand and Ammonia nitrogen). An overall decoupling between China's industrialization and wastewater pollution is identified with most of DIs less than 1.0 caused mainly by decreased (by around 40%) industrial NetGWFs for 2002–2015. Industrial fixed capital formation and export have caused main components of China's industrial GWF, with proportions of 37.3% and 30.8%, respectively, followed by urban household consumption (16.8%). Volatile phenol, Petroleum, and Ammonia nitrogen are recognized as three decisive contaminants to the industrial NetGWFs. Technological development is the dominant contributor (−50%) to decreasing China's industrial NetGWFs, while fixed capital formation (18%) and export (16%) are principal drivers increasing the NetGWFs. Based on these, we expect to provide informative findings for building a pollution-decoupled industrialization. • NetGWF is effective in measuring domestic water pollution stress. • Implies an overall decoupling of industrialization and effluent pollution. • Industrial fixed capital formation and export are main sources of pollution stress. • Volatile phenol, Petroleum, and NH3N are decisive pollutants of NetGWF. • 17 drivers behind evolving industrial NetGWFs are quantitatively examined. [ABSTRACT FROM AUTHOR]

Decades of intensifying human activities have caused dramatic changes in land use and land cover (LULC) in the ecologically fragile areas of the Qinghai-Tibet Plateau, which have led to significant changes in ecosystem service value (ESV). Taking the ecologically fragile Sanjiangyuan region of the Qinghai-Tibet Plateau as the research object, we focused on understanding the impact of LULC changes on the Sanjiangyuan's landscape pattern and its corresponding ESV, which was combined with a Markov-Plus model to predict LULC changes in 2030. The results showed: (1) from 2000 to 2020, the LULC of Sanjiangyuan has changed to varying degrees, respectively. In the central and southern regions where animal husbandry is the mainstay activity, the area of grass land converted to bareland had expanded; (2) from 2000 to 2010, the total regional ESV increased sharply. However, the total amount of ESV decreased from 2010 to 2020; (3) the overall ESV in the study area was observed to be trending down and is expected to decrease by approximately 4.25 billion CNY by 2030; (4) the fragmentation and complexity of regional landscape patterns will negatively affect local ecosystem stability and biodiversity. Overall, there is a strong temporal and spatial correlation between LULC and ESV. This study will provide a reference for the local government to provide targeted and sustainable land management policies, thereby promoting the improvement of the Qinghai-Tibet Plateau regional ecology value., 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 Ltd. All rights reserved.)