Changes in paleo-groundwater levels revealed by water wells and their relationship with climate variations in imperial Southern China.

Based on records of the bottom elevations of 511 ancient water wells from published archaeological reports, we reconstructed the paleo-groundwater levels (PGWL) in urban areas of Chengdu, Changsha, Nanjing, Suzhou, Suqian, Yancheng, Fuzhou, and Guangzhou cities in southern China. Our PGWL reconstruction shows that PGWL varied in two patterns. In the inland monsoon region (Chengdu and Changsha), there was a low PGWL in Jin (AD 266-420) and South Song (AD 1127-1279), and a high PGWL in Tang (AD 618-907) and Ming (AD 1368-1644). In the coastal region (Yancheng, Fuzhou, and Guangzhou), there was a low PGWL in Jin (AD 266-420) and Ming (AD 1368-1644) but a high PGWL in Tang (AD 618-907) and Song (AD 960-1279). Via cross-wavelet transform and wavelet transform coherence analyses, we found that monsoon and temperature significantly drove the PGWL fluctuations at the inter-centennial scale. East Asian Summer Monsoon-induced precipitation has continuously affected cities in the inland monsoon area represented by Chengdu and Changsha over the past 2,500 years. It has also intermittently affected Nanjing and Suzhou when EASM intensified. In parallel, temperature influenced the PGWL in coastal cities such as Yancheng, Fuzhou, and Guangzhou via the changes in the sea level. Also, the temperature affected the PGWL in relatively inland cities during climatic anomalies such as the Medieval Warm Period and Little Ice Age. This study demonstrates the value of archaeological records in learning how climatic factors influence the PGWL variation and its mechanism.

Does the low-carbon city pilot policy work in China? A company-level analysis based on the PSM-DID model.

To reduce carbon emissions and pursue sustainable economic development, China's central government formulated the low-carbon city pilot (LCCP) policy. Current studies focus primarily on the impact of the policy at the macro level (provinces and cities). So far, no study has looked at the impact of the LCCP policy on companies' environmental expenditures. Besides, as the LCCP policy is a weak-constraining central policy, it is interesting to see how it works at the company level. We employ company-level empirical data and the Propensity Score Matching - Difference in Differences (PSM-DID) method, which outperforms the traditional DID model in avoiding sample selection bias, to address the above issues. We concentrate on the second phase of the LCCP policy from 2010 to 2016, encompassing 197 listed companies in China's secondary and transportation industries. Our statistical results show that if the listed company's host city has piloted the LCCP policy, the company's environmental expenditures are reduced by 0.91 points at the 1% significance level. The above finding calls attention to the policy-implementation gap between the central and the local governments in China, which may make those weak-constraining central policies like the LCCP policy have purpose-defeating outcomes at the company level.

Tourism's long- and short-term influence on global cities' economic growth: The case of Hong Kong.

This research examines how tourism development has impacted economic growth in a global city-Hong Kong. A large body of research has investigated national tourism-led growth in developed and developing countries. However, many such studies have overlooked how policies aimed at fostering the development of tourism affect the local economic development of global cities. The Chinese and Hong Kong governments liberalized their visa policies with the launch of the Individual Visit Scheme in 2003. Such liberalization has led to significantly more tourist arrival from China. Our autoregressive distributed lag model of tourism-related data from 2003 to 2019 provides strong evidence that more tourism can spur short-run economic growth. Yet, such tourism can lead to uncertain effects on local economic development in the longer run. Hong Kong's transient tourism-led growth has almost entered the stagnation stage of the Tourism Area Life Cycle model. During such stagnation, jurisdictions like Hong Kong can expect limited long-term economic growth from their tourist sector. Our findings thus sound a warning for global cities looking to tourism to sustain longer-term economic growth.

Did Hydro-climatic Extremes, Positive Checks, and Economic Fluctuations Modulate the Epidemics Outbreaks in Late Imperial China?

Empirical research has shown that climate-related variables, the decline in economic well-being, and the mutual reinforcement of positive checks are the primary drivers of epidemic outbreaks in recent human history. However, their relative importance in causing the outbreak of epidemics is rarely examined quantitatively in a single study. I sought to address this issue by analyzing the 1402 epidemic incidents in China between 1841 and 1911, which partially overlaps partly with the Third Pandemic period. Fine-grained historical big data, multiple regression, and wavelet coherence analysis were employed. Statistical results show that economic fluctuations drove the country-wide epidemics outbreaks in China in inter-annual and decadal time scales. Economic fluctuations could cause short-term hardship and long-term impoverishment to the underprivileged social groups since a large portion of the Chinese population lived at the subsistence level in the past. The fluctuations might have sustained the repeated waves of epidemic outbreaks during the Third Pandemic period. Supplementary Information: The online version contains supplementary material available at 10.1007/s10745-021-00272-7.

The delayed effect of cooling reinforced the NAO-plague connection in pre-industrial Europe.

Previous studies on the connection between climate and plague were mostly conducted without considering the influence of large-scale atmospheric circulations and long-term historical observations. The current study seeks to reveal the sophisticated role of climatic control on plague by investigating the combined effect of North Atlantic Oscillation (NAO) and temperature on plague outbreaks in Europe from 1347 to 1760 CE. Moving correlation analysis is applied to explore the non-linear relationship between NAO and plague transmission over time. Also, we apply the cross-correlation function to identify the role of temperature in mediating the NAO-plague connection and the lead-lag relationship in between. Our statistical results show that the pathway from climate change to plague incidence is distinctive in its spatial, temporal, and non-linear patterns. The multi-decadal temperature change exerted a 15-22 years lagged impact on the NAO-plague correlation in different European regions. The NAO-plague correlation in Atlantic-Central Europe primarily remained positive, while the correlation in Mediterranean Europe switched between positive and negative alternately. The modulating effect of temperature over the NAO-plague correlation increases exponentially with the magnitude of the temperature anomaly, but the effect is negligible between 0.3 and -0.3 °C anomaly. Our findings show that a lagged influence from the temperature extremes dominantly controls the correlation between NAO and plague incidence. A forecast from our study suggests that large-scale plague outbreaks are unlikely to happen in Europe if NAO remains at its current positive phase during the earth's future warming.

Climate change fostered cultural dynamics of human resilience in Europe in the past 2500 years.

Humans possess limited knowledge on what generated cultural dynamics to strengthen human resilience to overcome climate-induced stresses. Although the highly developed mental ability of humans could have enabled significant human resilience in history, no study has empirically explained or has even scientifically confirmed how and when such dynamics arose. To fill the current research gap, this study therefore explores the associations among climatic conditions, the evolutional dynamics of human thinkers and their thoughts, and human ecological-socioeconomic conditions in the past 2500 years in Europe. Results from quantitative modellings and causal analyses confirm that climatic-ecological stresses led to human ecological-socioeconomic crises, and thereby dramatically increased twice of the thinkers' number and their thoughts' impact across different philosophies in truth, knowledge, and ethics for adaptation at multi-decadal to centennial temporal scales, especially in spirituality oriented mentality. The process of the stress-generated cultural dynamics displays some similarities with the stress-induced mutagenesis in organism evolution. Ultimately, climatic-ecological stresses prompt the escalation in the number of thinkers and impacts of their thoughts and flourishing of philosophy. Such stress-regenerated cultural dynamics imply that the current climate change threat may stimulate another thriving phase of cultural selection and lift humans to the next homeostatic plateau of civilization. Findings also extend the cognate scope of psychological, sociological, and civilization studies.

Revisiting the impact of vehicle emissions and other contributors to air pollution in urban built-up areas: A dynamic spatial econometric analysis.

Whether vehicle emissions are the primary source of PM2.5 in urban China remains controversial, which may be attributable to the insufficient consideration of the spatial autocorrelation and the spatial spillover effects of PM2.5. We employ data from built-up areas of 285 prefecture-level cities in China spanned 2001-2016 and dynamic spatial panel data analysis to resolve this controversy. Our results show that the direct and indirect effects of vehicles on PM2.5 concentration (annual mean and spatial variation within the city) in urban China are not significant in the short- and long-term. Alternatively, SO2 emission directly increases the mean and spatial variation of PM2.5 within the city in the short- and long-term. Short-term direct and indirect positive association and long-term indirect positive association are found relative to economic growth and PM2.5. Population density increases PM2.5 directly and indirectly in the short-term and yet, directly decreases and indirectly increases PM2.5 in the long-term. In the short- and long-term, the spatial spillover effect of secondary industry increases PM2.5, and industry also directly increases the spatial variation of PM2.5 within the city. Although real estate investment directly increases PM2.5 in the long-term, the spatial spillover effect of investment reduces PM2.5 in the short- and long-term. Our results show that other factors, rather than vehicle emissions, are the major contributors to PM2.5 in urban China. Furthermore, the Environmental Kuznets Curve hypothesis does not apply to the relationship between economic growth and PM2.5 proliferation in urban China. When tackling air pollution, owing to the significant spatial spillover of PM2.5 that is driven by multiple contributing factors, short- and long-term inter-regional coordination is required to achieve an effective positive outcome.

Drought-induced spatio-temporal synchrony of plague outbreak in Europe.

Plague synchronously swept across separated regions in Europe throughout history. However, the spatio-temporal synchrony of plague and its driving mechanism have not been thoroughly investigated. In this study, we transformed the historical European plague database spanned 1347-1800 CE into country-level time-series that differentiated large-scale plague outbreak from counted data. We found that there are 74 years in which two or more countries in our study region (UK, France, Germany, Spain, and Italy) experienced large-scale plague outbreak in the same year. Our Multivariate Ripley's K-function results showed that the onset year and the cessation year of large-scale plague outbreak are synchronized at the 0-23-year and 0-20-year windows, respectively. The temporal association between such synchrony and climatic forcing was further investigated using the Superposed Epoch Analysis, and drought was found to be responsible for the synchrony. Integrating our results with a literature survey, we suggested that prior to the peak of plague, the occurrence of drought and the subsequent reintroduced rainfall dampened both the rodent community and human society and boosted the number of fleas that carried plague. Such a synthesis facilitated the outbreak of plague. At the same time, high temperature associated with such drought also confined the geographic diffusion of the plague. Hence, although continental mega-drought could initiate the synchrony of plague outbreak, the synchrony actually consisted of a number of localized plague outbreak events scattering across different regions in Europe. According to the projected rising trend of drought in terms of its magnitude, duration, and geographic extent, the risk of synchrony of rodent-borne diseases in Europe will be significantly elevated, especially in France, Italy, and Spain.

Pre-industrial plague transmission is mediated by the synergistic effect of temperature and aridity index.

BACKGROUND: Although the linkage between climate change and plague transmission has been proposed in previous studies, the dominant approach has been to address the linkage with traditional statistical methods, while the possible non-linearity, non-stationarity and low frequency domain of the linkage has not been fully considered. We seek to address the above issue by investigating plague transmission in pre-industrial Europe (AD1347-1760) at both continental and country levels. METHODS: We apply Granger Causality Analysis to identify the casual relationship between climatic variables and plague outbreaks. We then apply Wavelet Analysis to explore the non-linear and non-stationary association between climate change and plague outbreaks. RESULTS: Our results show that 5-year lagged temperature and aridity index are the significant determinants of plague outbreaks in pre-industrial Europe. At the multi-decadal time scale, there are more frequent plague outbreaks in a cold and arid climate. The synergy of temperature and aridity index, rather than their individual effect, is more imperative in driving plague outbreaks, which is valid at both the continental and country levels. CONCLUSIONS: Plague outbreaks come after cold and dry spells. The multi-decadal climate variability is imperative in driving the cycles of plague outbreaks in pre-industrial Europe. The lagged and multi-decadal effect of climate change on plague outbreaks may be attributable to the complexity of ecological, social, or climate systems, through which climate exerts its influence on plague dynamics. These findings may contribute to improve our understanding of the epidemiology of plague and other rodent-borne or flea-borne infectious diseases in human history.

Trade routes and plague transmission in pre-industrial Europe.

Numerous historical works have mentioned that trade routes were to blame for the spread of plague in European history, yet this relationship has never been tested by quantitative evidence. Here, we resolve the hypothetical role of trade routes through statistical analysis on the geo-referenced major trade routes in the early modern period and the 6,656 geo-referenced plague outbreak records in AD1347-1760. Ordinary Least Square (OLS) estimation results show that major trade routes played a dominant role in spreading plague in pre-industrial Europe. Furthermore, the negative correlation between plague outbreaks and their distance from major trade ports indicates the absence of a permanent plague focus in the inland areas of Europe. Major trade routes decided the major plague outbreak hotspots, while navigable rivers determined the geographic pattern of sporadic plague cases. A case study in Germany indicates that plague penetrated further into Europe through the local trade route network. Based on our findings, we propose the mechanism of plague transmission in historical Europe, which is imperative in demonstrating how pandemics were spread in recent human history.

Relationship between ancient bridges and population dynamics in the lower Yangtze River Basin, China.

It has been suggested that population growth dynamics may be revealed by the geographic distribution and the physical structure of ancient bridges. Yet, this relationship has not been empirically verified. In this study, we applied the archaeological records for ancient bridges to reveal the population growth dynamics in the lower Yangtze River Basin in late imperial China. We investigated 89 ancient bridges in Yixing that were built during the Ming and Qing dynasties (AD1368-1911). Global Position System information and structure (length, width, and span) of those bridges was measured during our field investigations. Their distribution density was calculated by ArcGIS. The historical socio-economic dynamics of Yixing was inferred from the distribution and structure of ancient bridges. Based on the above information, the population growth dynamics in Yixing was projected. Our results show that 77 bridges were built in Yixing during the Qing dynasty, which is 6.41 times more than the number built during the Ming dynasty. In the Ming dynasty, bridges were built on pivotal routes; in the Qing dynasty, bridges were scattered across various places. Over the period, the density distribution of bridges shifted northwestward, while the average length and width of bridges decreased. The increasing number of bridges corresponded to population growth, largely attributable to massive clan migration from northern China during the Little Ice Age. The shift in the density distribution of bridges corresponded to the formation of settlements of large clans and the blossoming of Yixing Teapot handicrafts. The scattering and the reduction in average length and width of bridges was due to the dispersal of population and the associated formation of small settlements in the latter period. Our approach is innovative and robust, and could be employed to recover long-term historical population growth dynamics in other parts of China.

Habitat Variability and Ethnic Diversity in Northern Tibetan Plateau.

There are 56 officially-recognized ethnic groups in China. However, the distinct geographic patterns of various ethnic groups in relation to the physical environment in China have rarely been investigated. Based on the geo-referenced physical environmental parameters of 455 Han, Tu, Hui, Salar, Mongolian, and Tibetan communities in Qinghai, we found that the communities could be statistically demarcated by temperature and aridity threshold according to their ethnicity, implying that the geographic distribution of each ethnic group is mediated by the physical environment. We also observed that the habitat of each ethnic group is ecologically compatible with current subsistence strategies. Tibetans settle in cold and humid high-altitude regions owing to the cultivation of highland barley and the breeding of yak, dzo, Tibetan sheep and Tibetan goat. Mongolians survive by animal husbandry in cold and dry grassland areas. Han and Tu people settle in the Huangshui River Valley, which offers relatively humid climate and flat land for agriculture. Hui and Salar people occupy the Yellow River Valley with its relatively arid environment and grassland vegetation suitable for animal breeding. Our findings offer a new perspective in explaining the geographic patterns and the varieties of ethnic groups in China and elsewhere.

Two centuries of April-July temperature change in southeastern China and its influence on grain productivity.

China is a traditional agriculture based country and one main region for crop production is southeastern China where temperature is a dominant climate variable affecting agriculture. Temperature and social disturbances both influence crop production, yet distinguishing their relative impacts is difficult due to a lack of reliable, high-resolution historical climatic records before the very recent period. Here we present the first tree-ring based warm-season temperature reconstruction for southeastern China, a core region of the East Asian monsoon, for the past 227years. The reconstruction target was April-July mean temperature, and our model explained 60.6% of the observed temperature variance during 1953-2012. Spatial correlation analysis showed that the reconstruction is representative of April-July temperature change over most of eastern China. The reconstructed temperature series agrees well with China-scale (heavily weighted in eastern China) agricultural production index values quite well at decadal timescales. The impacts of social upheavals on food production, such as those in the period 1920-1949, were confirmed after climatic influences were excluded. Our study should help distinguish the influence of social disturbance and warm-season temperature on grain productivity in the core agricultural region of China during the past two centuries.

Climate change and epidemics in Chinese history: A multi-scalar analysis.

This study seeks to provide further insight regarding the relationship of climate-epidemics in Chinese history through a multi-scalar analysis. Based on 5961 epidemic incidents in China during 1370-1909 CE we applied Ordinary Least Square regression and panel data regression to verify the climate-epidemic nexus over a range of spatial scales (country, macro region, and province). Results show that epidemic outbreaks were negatively correlated with the temperature in historical China at various geographic levels, while a stark reduction in the correlational strength was observed at lower geographic levels. Furthermore, cooling drove up epidemic outbreaks in northern and central China, where population pressure reached a clear threshold for amplifying the vulnerability of epidemic outbreaks to climate change. Our findings help to illustrate the modifiable areal unit and the uncertain geographic context problems in climate-epidemics research. Researchers need to consider the scale effect in the course of statistical analyses, which are currently predominantly conducted on a national/single scale; and also the importance of how the study area is delineated, an issue which is rarely discussed in the climate-epidemics literature. Future research may leverage our results and provide a cross-analysis with those derived from spatial analysis.

Navigable rivers facilitated the spread and recurrence of plague in pre-industrial Europe.

Infectious diseases have become a rising challenge to mankind in a globalizing world. Yet, little is known about the inland transmission of infectious diseases in history. In this study, we based on the spatio-temporal information of 5559 plague (Yersinia pestis) outbreaks in Europe and its neighboring regions in AD1347-1760 to statistically examine the connection between navigable rivers and plague outbreak. Our results showed that 95.5% of plague happened within 10 km proximity of navigable rivers. Besides, the count of plague outbreak was positively correlated with the width of river and negatively correlated with the distance between city and river. This association remained robust in different regression model specifications. An increase of 100 m in the width of river and a shortening of 1 km distance between city and river resulted in 9 and 0.96 more plague outbreaks in our study period, respectively. Such relationship shows a declining trend over our study period due to the expansion of city and technological advancement in overland transportation. This study elucidates the key role of navigable river in the dissemination of plague in historical Europe.

Quantifying the Intra-Regional Precipitation Variability in Northwestern China over the Past 1,400 Years.

There has been a surge of paleo-climatic/environmental studies of Northwestern China (NW China), a region characterized by a diverse assortment of hydro-climatic systems. Their common approach, however, focuses on "deducing regional resemblance" rather than "exploring regional variance." To date, efforts to produce a quantitative assessment of long-term intra-regional precipitation variability (IRPV) in NW China has been inadequate. In the present study, we base on historical flood/drought records to compile a decadal IRPV index for NW China spanned AD580-1979 and to find its major determinants via wavelet analysis. Results show that our IRPV index captures the footprints of internal hydro-climatic disparity in NW China. In addition, we find distinct ~120-200 year periodicities in the IRPV index over the Little Ice Age, which are attributable to the change of hydro-climatic influence of ocean-atmospheric modes during the period. Also, we offer statistical evidence of El Niño Southern Oscillation (Indo-Pacific warm pool sea surface temperature and China-wide land surface temperature) as the prominent multi-decadal to centennial (centennial to multi-centennial) determinant of the IRPV in NW China. The present study contributes to the quantitative validation of the long-term IRPV in NW China and its driving forces, covering the periods with and without instrumental records. It may help to comprehend the complex hydro-climatic regimes in the region.

Climate change and the macroeconomic structure in pre-industrial europe: new evidence from wavelet analysis.

The relationship between climate change and the macroeconomy in pre-industrial Europe has attracted considerable attention in recent years. This study follows the combined paradigms of evolutionary economics and ecological economics, in which wavelet analysis (spectrum analysis and coherence analysis) is applied as the first attempt to examine the relationship between climate change and the macroeconomic structure in pre-industrial Europe in the frequency domain. Aside from confirming previous results, this study aims to further substantiate the association between climate change and macroeconomy by presenting new evidence obtained from the wavelet analysis. Our spectrum analysis shows a consistent and continuous frequency band of 60-80 years in the temperature, grain yield ratio, grain price, consumer price index, and real wage throughout the study period. Besides, coherence analysis shows that the macroeconomic structure is shaped more by climate change than population change. In addition, temperature is proven as a key climatic factor that influences the macroeconomic structure. The analysis reveals a unique frequency band of about 20 years (15-35 years) in the temperature in AD1600-1700, which could have contributed to the widespread economic crisis in pre-industrial Europe. Our findings may have indications in re-examining the Malthusian theory.

Epidemics in Ming and Qing China: Impacts of changes of climate and economic well-being.

We investigated the mechanism of epidemics with the impacts of climate change and socio-economic fluctuations in the Ming and Qing Dynasties in China (AD 1368-1901). Using long-term and high-quality datasets, this study is the first quantitative research that verifies the 'climate change â†’ economy â†’ epidemics' mechanism in historical China by statistical methods that include correlation analysis, Granger causality analysis, ARX, and Poisson-ARX modeling. The analysis provides the evidences that climate change could only fundamentally lead to the epidemics spread and occurrence, but the depressed economic well-being is the direct trigger of epidemics spread and occurrence at the national and long term scale in historical China. Moreover, statistical modeling shows that economic well-being is more important than population pressure in the mechanism of epidemics. However, population pressure remains a key element in determining the social vulnerability of the epidemics occurrence under climate change. Notably, the findings not only support adaptation theories but also enhance our confidence to address climatic shocks if economic buffering capacity can be promoted steadily. The findings can be a basis for scientists and policymakers in addressing global and regional environmental changes.

Climate change and macro-economic cycles in pre-industrial europe.

Climate change has been proven to be the ultimate cause of social crisis in pre-industrial Europe at a large scale. However, detailed analyses on climate change and macro-economic cycles in the pre-industrial era remain lacking, especially within different temporal scales. Therefore, fine-grained, paleo-climate, and economic data were employed with statistical methods to quantitatively assess the relations between climate change and agrarian economy in Europe during AD 1500 to 1800. In the study, the Butterworth filter was adopted to filter the data series into a long-term trend (low-frequency) and short-term fluctuations (high-frequency). Granger Causality Analysis was conducted to scrutinize the associations between climate change and macro-economic cycle at different frequency bands. Based on quantitative results, climate change can only show significant effects on the macro-economic cycle within the long-term. In terms of the short-term effects, society can relieve the influences from climate variations by social adaptation methods and self-adjustment mechanism. On a large spatial scale, temperature holds higher importance for the European agrarian economy than precipitation. By examining the supply-demand mechanism in the grain market, population during the study period acted as the producer in the long term, whereas as the consumer in the short term. These findings merely reflect the general interactions between climate change and macro-economic cycles at the large spatial region with a long-term study period. The findings neither illustrate individual incidents that can temporarily distort the agrarian economy nor explain some specific cases. In the study, the scale thinking in the analysis is raised as an essential methodological issue for the first time to interpret the associations between climatic impact and macro-economy in the past agrarian society within different temporal scales.

The causality analysis of climate change and large-scale human crisis.

Recent studies have shown strong temporal correlations between past climate changes and societal crises. However, the specific causal mechanisms underlying this relation have not been addressed. We explored quantitative responses of 14 fine-grained agro-ecological, socioeconomic, and demographic variables to climate fluctuations from A.D. 1500-1800 in Europe. Results show that cooling from A.D. 1560-1660 caused successive agro-ecological, socioeconomic, and demographic catastrophes, leading to the General Crisis of the Seventeenth Century. We identified a set of causal linkages between climate change and human crisis. Using temperature data and climate-driven economic variables, we simulated the alternation of defined "golden" and "dark" ages in Europe and the Northern Hemisphere during the past millennium. Our findings indicate that climate change was the ultimate cause, and climate-driven economic downturn was the direct cause, of large-scale human crises in preindustrial Europe and the Northern Hemisphere.