Combined role of industrialization and urbanization in determining carbon neutrality: empirical story of Pakistan

Synthesizing the role of urbanization and oil prices in achieving carbon neutrality in Africa: do financial crisis and renewable energy play a role?

Higher oil prices can incentivize urban planners to adopt energy-saving behaviors, such as using public transportation or investing in energy-efficient appliances, which can help achieve carbon neutrality. Notwithstanding this, empirical studies ignored the role played by oil prices in the urbanization-carbon emissions nexus. Therefore, this study aims to examine the moderating role of oil prices on the urbanization-CO2 emission relationship, along with renewable energy consumption and the global financial crisis. Using Driscoll-Kraay and IV-GMM techniques on panel data from 35 African countries, the results confirmed an inverted U-shaped relationship between urbanization and CO2 emissions in Africa, which is consistent with the ecological modernization theory. The results also show that oil prices, financial crisis, and renewable energy contribute to reducing carbon emissions, while the EKC hypothesis curve between GDP and CO2 emissions is validated. Additionally, urbanization has a favorable oil price effect on carbon emissions in Africa. The heterogeneity analysis validates the EKC curve between urbanization and CO2 emissions in low- and high-emission countries, while oil prices and financial crisis mitigate CO2 emissions only in low-emission countries. Further, oil prices moderate urbanization to reduce carbon emissions in low- and high-emission countries. The findings also indicated that renewable energy mitigates carbon emissions and that the inverted U-shape is confirmed in low- and high-emission countries. These results suggest that policymakers should put more effort into the adoption of renewable energy and the use of energy-saving technologies in urban development to achieve carbon neutrality.

Probing environmental sustainability pathways in G7 economies: the role of energy transition, technological innovation, and demographic mobility

Global warming remains the most devastating environmental issue embattling the global economies, with significant contributions emanating from CO₂ emissions. The continued rise in the level of greenhouse gas (GHG) emissions serves as a compelling force which constitutes the core of discussion at the recent COP26 prompting nations to commit to the net-zero emission target. The current research presents the first empirical investigation on the roles of technological advancement, demographic mobility, and energy transition in G7 pathways to environmental sustainability captured by CO₂ emissions per capita (PCCO2) from 2000 to 2019. The study considers the additional impacts of structural change and resource abundance. The empirical backings are subjected to pre-estimation tests consisting of cross-sectional dependence, second-generation stationarity, and panel cointegration tests. The model estimation is based on cross-sectional augmented autoregressive distributed lag, dynamic common correlated effects mean group, and augmented mean group for the main analysis and robustness checks. The findings reveal the existence of EKC based on the direct and indirect effects of the components of economic growth. The indicators of demographic mobility differ in the direction of influence on PCCO2. For instance, while rural population growth negatively influences PCCO2 in the short-run alone, urban population growth increases PCCO2 in the short-run and long-run periods. Nonrenewable energy, information computer technology (ICT) imports, and mobile cellular subscriptions serve as positive predictors of PCCO2, while ICT exports and renewable energy moderate the surge in PCCO2. Policy implications that enhance environmental sustainability are suggested following the empirical verifications.

Insights from BRICS-T economies on the impact of human capital and renewable electricity consumption on environmental quality

This paper evaluates the impact of electricity consumption from renewable and nonrenewable sources on the load capacity factor for BRICS-T nations using data from 1990 to 2018. The paper used linear and nonlinear autoregressive distributed lag (ARDL) approaches to explore these associations. The results of the Westerlund co-integration show long-run co-integration between load capacity factor and the independent variables. The results show that renewable electricity energy and human capital contribute to the sustainability of the environment, while electricity consumption, economic growth, and industrialization impede environmental sustainability. Similarly, the nonlinear effect of renewable electricity energy on LCF shows interesting findings. The positive (negative) shift in renewable electricity energy increases ecological sustainability in the BRICS-T nations. Furthermore, the Dumitrescu Hurlin panel causality gives credence to both linear and nonlinear ARDL results. The study suggests policy recommendations based on these results.

Assessment of Multiple Ecosystem Services and Ecological Security Pattern in Shanxi Province, China

The ecological security pattern construction could effectively regulate ecological processes and ensure ecological functions, then rationally allocate natural resources and green infrastructure, and, finally, realize ecological security. In view of serious soil erosion, accelerated land desertification, soil pollution and habitat degradation in Shanxi Province, the spatial distribution of six key ecosystem services, including water conservation (WC), soil conservation (SC), sand fixation (SF), carbon storage (CS), net primary productivity (NPP) and habitat quality (HQ), was analyzed by using multiple models. The comprehensive ability of multiple ecosystem services in different regions was quantified by calculating multiple ecosystem services landscape index (MESLI). Combined with ecosystem services hotspots, the ecological security pattern of Shanxi Province was constructed by using the minimum cumulative resistance model. The results showed that the spatial differences in ecosystem services in Shanxi Province were obvious, which was low in the seven major basins and Fen River valley, and high in the mountains (especially Taihang and Lvliang Mountains) for WC, SC, CS, NPP and HQ, while high SF was only distributed in the northern Shanxi. The MESLI showed that the ability to provide multiple ecosystem services simultaneously was low in Shanxi Province, with the medium and low grade MESLI regions accounting for 58.61%, and only 18.07% for the high grade MESLI regions. The important protected areas and ecological sources of the ecological security pattern were concentrated in the Lvliang and Taihang Mountains, which were consistent with the key areas of ecosystem services. The ecological corridors illustrated network distribution with ecological sources as the center, the low-, medium- and high-level buffers accounted for 26.34%, 17.03% and 16.35%, respectively. The results will provide important implications for economic transformation, high-quality development and ecological sustainable development in resource-based regions worldwide.

The symmetric and asymmetric impacts of green energy, eco-innovation, and urbanization in explaining low-carbon economy for Pakistan

Over the past three decades, global economic development patterns have considerably affected the natural environment, and economies have endured a plethora of environmental concerns as a result of the negative effects of climate change. Among them, Pakistan is the fifth most vulnerable country, and climate change has harmfully affected the ecological and socio-economic conditions of the country. In this regard, this study aimed to investigate the role of green energy consumption, eco-innovation, and urbanization while explaining the dream of low-carbon economy and environmental sustainability in the context of Pakistan using annual time series dataset spanning from 1990 to 2020. The short-run and long-run associations among explained and explanatory variables were investigated using the symmetric, asymmetric, and quantile autoregressive distributed lag models. The findings of the study demonstrated that low-carbon economy, green energy consumption, ecological innovation, urbanization, GDP per capita, and labor force are cointegrated for the long-term association in symmetric, asymmetric, and quantile autoregressive distributed lag models. Furthermore, green energy consumption and effective eco-innovation are the most important paths to ensure environmental sustainability, while urbanization, GDP per capita, and labor force contribute negatively to the low-carbon economy. The findings of the study provide a policy framework for the development of a comprehensive strategy to promote environmental sustainability in Pakistan by emphasizing green energy consumption, ecological innovation, and controlled urbanization, as well as the incorporation of environment friendly policies into economic development policies.

Heading towards sustainable environment: does renewable and non-renewable energy generation matter for the effect of industrialization and urbanization on ecological footprint? Evidence from China

This study examines how renewable and non-renewable energy generation interacts with both to affect the ecological footprint in China during 1990-2019 by using FMOLS, DOLS, and CCR estimation techniques and ARDL simulation models to assess the impact of industrialization and urbanization on environmental sustainability based on the environmental Kuznets curve hypothesis model framework. Firstly, the findings verify the applicability and validity of the EKC hypothesis in China. Secondly, renewable energy generation, industrialization, and urbanization facilitate the reduction of ecological footprint and the improvement of environmental quality in the long run, while non-renewable energy generation increases the ecological footprint and leads to the intensification of ecological pollution. However, the short-term estimates give evidence that industrialization, urbanization, and renewable and non-renewable energy generation can all increase the ecological footprint, which is not conducive to ecological sustainability. Thus, from the perspective of ecological sustainability in China, our findings are important in that they provide clear directions for ecological policy formulation, and we also provide some targeted policy recommendations for them to promote sustainable development as a goal.

Assessing the low-carbon city pilot policy on carbon emission from consumption and production in China: how underlying mechanism and spatial spillover effect?

The low-carbon city pilot (LCCP) policy is an important initiative for China to fulfill its international commitment to carbon emission reduction and achieve low-carbon transformation. In this context, this study investigated whether the LCCP policy of China has achieved carbon emission reduction from the production and consumption perspectives and how its underlying mechanism and spatial spillover effect. Using the panel dataset of 285 Chinese prefecture-level cities from 2003 to 2019, this study applied the staggered DID model to examine the effects and its underlying mechanism of the LCCP policy on carbon intensity (CI) and carbon emission per capita (CP). We also conducted heterogeneity and spatial spillover effect analyses using the textual quantification method and spatial DID. Our results show that the LCCP policy effectively reduced CI and CP, but these effects did not appear until the third year of implementation. The above conclusions passed a series of robustness and endogeneity tests. Reducing industrial emissions, improving technological innovation, and optimizing the efficiency of energy usage were three important mechanisms to reduce CI and CP, validating the effectiveness of the LCCP policy. Command-mandatory and voluntary LCCP policy tools achieved better results, and the LCCP policy exerted a significant emission reduction effect on second-tier pilot cities as compared to others. The carbon emission abatement of the LCCP policy has also demonstrated a spatial spillover impact on neighboring cities. This study focused on analyzing the mechanism paths and spatial spillover effects of the LCCP policy impact and provided an important decision-making reference in promoting the LCCP policy for not only China but also other developing countries. Specifically, low-carbon pilot experiences and typical cases should be refined, ways for accelerating the greening and cleaning of energy usage must be explored, and regional joint control and collaborative governance should be established to achieve China's low-carbon transformation.

The impact of land price distortion on green development efficiency: mechanism discussion and empirical test

Based on the panel data of 30 Chinese provinces, the Cobb-Douglas production function and GML index were constructed to measure the degree of land price distortion and green development efficiency, respectively, in China, and the System Generalised Method of Moments model was employed to explore the relationship between land price distortion and green development efficiency, and a mediating effect model was further constructed to analyse the transmission mechanism. The results show that, first, land price in China is characterised by a negative distortion, but the degree of negative distortion tends to decrease after 2010. Second, land price distortion significantly inhibits the improvement of green development efficiency; this conclusion still holds after a series of robustness tests, and land price distortion significantly promotes the progress of green technology, while significantly inhibiting the improvement of green technology efficiency. Third, the results of the mediating effect show that the inhibiting effect of land price distortion on green development efficiency is mainly achieved through three channels: house price, industrial structure and infrastructure. Finally, policy recommendations for green sustainable development are put forward from the aspects of land supply structure adjustment and so on.

The Spatiotemporal Evolution and Prediction of Carbon Storage in the Yellow River Basin Based on the Major Function-Oriented Zone Planning

Land use/cover change is the main reason for the variation of ecosystem carbon storage. The study of the impact of land use on carbon storage has certain reference values for realizing high-quality development in the Yellow River Basin. In this paper, the InVEST model was used to simulate the variation of carbon storage in the Yellow River Basin in 2000, 2005, 2010, 2015, and 2020, and to predict the carbon storage in 2030 in combination with the CA-Markov model, as well as to discuss the impact of land use on carbon storage. The results showed that: (1) The variation trend of carbon storage for different land use types in the Yellow River Basin was different and was mainly manifested as a decrease of cultivated land and unused land, and an increase of forest land, grassland, water, and construction land. The carbon storage in the provincial key development prioritized zone, national development optimized zone, and provincial development optimized zone showed decreasing trends, while the national key development prioritized zone and national major grain producing zone presented a fluctuating downward trend. (2) The ecosystem carbon storage function weakened after 2000, and part of the carbon sink area transformed into a carbon source area. The area with low carbon storage was distributed in the west of the provincial key ecological function zone, and the area with high carbon storage was concentrated in the south and middle of national key ecological function zone and the east of the provincial key ecological function zone. (3) The carbon loss was largest in the urban expansion scenario (UES), followed by the natural development scenario (NDS) and ecological protection scenario (EPS). The carbon storage of different scenarios presented significant positive correlations with land use intensity.

The role of innovation investment and institutional quality on green total factor productivity: evidence from 46 countries along the "Belt and Road"

Based on the panel data of 46 countries in "Belt and Road" (B&R) from 2004 to 2016, this paper studies the impact of innovation investment and institutional quality on green total factor productivity (GTFP). Firstly, the ICRG database, World Bank WDI database, Traditional Foundation database, and Wind database are matched to obtain the balanced panel data of 46 countries along the B&R from 2004 to 2016. Secondly, the Malmquist-Luenberger index, which can be included in the unexpected output, is used to calculate the GTFP of countries along B&R. Thirdly, the evaluation system of national institutional quality of B&R is constructed from three dimensions (political institutional quality, economic institutional quality, and legal institutional quality), and the overall system quality of different countries is measured by entropy method. Finally, an empirical study is made on the relationship among innovation investment, institutional quality, and green total factor productivity. The results show that innovation investment has significantly promoted the GTFP of the B&R countries. It is worth noting that there is a non-linear relationship between innovation investment and GTFP in the B&R countries. With the improvement of overall system quality, political system quality, economic system quality, and legal system quality, the promotion effect of innovation investment on GTFP is further enhanced. In addition, the heterogeneity regression results show that the impact of innovation investment on GTFP is significantly heterogeneous in different regions of the B&R countries. Specifically, innovation investment has the greatest impact on GTFP in South Asia, followed by East Asia and Pacific, Europe and Central Asia, Middle East, and North Africa.

Long-Term Air Pollution Exposure and Ischemic Heart Disease Mortality Among Elderly in High Aging Asian Economies

In the epidemiological literature, the impact of environmental pollution on cardiac mortality has been well documented. There is, however, a paucity of evidence on the impact of air pollution exposure on ischemic heart disease (IHD) mortality among the Asian aged population. In response, this research seeks to investigate the degree of proximity between exposure to ambient PM2.5, household PM2.5, ground-level ozone (O3), and IHD mortality in the top seven Asian economies with the highest aging rates. This investigation is held in two phases. In the first phase, grey modeling is employed to assess the degree of proximity among the selected variables, and then rank them based on their estimated grey weights. In addition, a grey-based Technique for Order of Preference by Similarity to Ideal Solution (G-TOPSIS) is adopted to identify the key influencing factor that intensifies IHD mortality across the selected Asian economies. According to the estimated results, South Korea was the most afflicted nation in terms of IHD mortality owing to ambient PM2.5 and ground-level O3 exposure, whereas among the studied nations India was the biggest contributor to raising IHD mortality due to household PM2.5 exposure. Further, the outcomes of G-TOPSIS highlighted that exposure to household PM2.5 is a key influencing risk factor for increased IHD mortality in these regions, outweighing all other air pollutants. In conclusion, this grey assessment may enable policymakers to target more vulnerable individuals based on scientific facts and promote regional environmental justice. Stronger emission regulations will also be required to mitigate the adverse health outcomes associated with air pollution exposure, particularly in regions with a higher elderly population.