Agricultural Communities’ Risk Assessment and the Effects of Climate Change: A Pathway Toward Green Productivity and Sustainable Development

Abstract

This study was carried out to assess agricultural communities’ understanding of climate change, the adaptation measures being undertaken against climate change, and industrial wastewater irrigation. It was considered important to check agricultural communities’ understanding of climate change, as the majority of the study area belongs to the farming and industry sector. This study was based on primary data collected through a survey in the study area. The results of present study showed that agricultural communities with sufficient resources and assets consider themselves to be safer and more capable of coping with the negative effects of climate change. Agricultural communities used different techniques to deal with the impacts of climate change in present study area. This study produced findings about agricultural households’ adaptation tactics that are unique and will aid policymakers in assisting agricultural communities in their day-to-day activities and farming practices, as well as in the implementation of proper monitoring and public policies to ensure integration and sustainability. This research is based on the sustainable livelihoods approach (SLA), which investigates how livelihood assets support agricultural communities by combining household adoption/adaptation strategies and livelihood outcomes.

Introduction and Literature Review

In the agricultural sector, one major challenge is the effect of climate change on agriculture. Inconsistent temperatures have been shown to alter crop respiration requirements, resulting in a shorter maturation period and a decrease in net growth and productivity. Increasingly, lives and livelihoods are being impacted by climate change, particularly in mountainous regions where much of the population may belong to ethnic minorities. A large majority of the population is unable to understand and interpret climate data, making them more vulnerable (Bogner et al., 2009; McDowell et al., 2014; Rehman et al., 2021), despite their best efforts. It is critical to access and implement adaptation measures to better understand farm households’ beliefs, mitigation measures, and attitudes toward climate change (Singh et al., 2017; Ozturk et al., 2019). Studies have shown that climate change has an enormous impact on farmers’ lives (Field et al., 2012). The agricultural sectors of many countries face a serious threat from climate change, which necessitates the implementation of adaptation strategies to protect future agricultural production and the livelihoods of agricultural communities (Chandra et al., 2017; Amir et al., 2020; Sohail MT. et al., 2021). Water for irrigation is vital in Pakistan’s agricultural sector (Fiaz et al., 2016; Sohail et al., 2019a); without it, the country’s food production will be severely limited (Lee et al., 2020). The water used for agriculture is also applied to other uses in many countries; it provides nutrients that increase crop yields without using fertilizer, but it also contains organic compounds and heavy metals that can harm the environment, human health, and agricultural productivity, which must be taken into consideration when deciding what means to use in disposing of wastewater (Mahfooz et al., 2019; Sohail et al., 2019; Sohail et al., 2020). Canal water and wastewater are commonly used by agricultural communities, and wastewater is thought to have beneficial effects on crops (Yamin et al., 2015; Sohail et al., 2022b). Unsuitable wastewater can harm crops, soil, vegetables, and the environment, as well as human health (Hassan et al., 2013; Ullah et al., 2013; Lan et al., 2022). Some agricultural communities do not have or are running low on canal water. As a result, they turn to wastewater pumping as a substitute source of irrigation water (Anwar et al., 2010; Sohail et al., 2022a). This has gravely impacted Pakistan’s crop production (Lobell and Gourdji, 2012). Its agricultural output, ecosystems, agricultural livelihoods, and food security have all suffered as a result of the country’s growing climate vulnerability in recent years (Saeed et al., 2012; Akhtar et al., 2019). Pakistan is the seventh most vulnerable developing region to extreme weather to extreme weather in the world (Schilling et al., 2013). Because of the increased vulnerability and food insecurity that rural farm households face as a result of environmental hazards such as rising temperatures and irregular precipitation (Ozturk 2016; Fahad and Wang 2018; Jian et al., 2021; Fareed et al., 2022; Sohail et al., 2022b; Zhenyu and Sohail, 2022). The agricultural industry and rural communities will be hit harder by increasingly frequent extreme weather events in the future (Reidsma et al., 2015; Yen et al., 2017; Zhao et al., 2019; Jiang et al., 2021). Hence, timely and innovative adaptation measures and agricultural practices are needed to ensure sustainable development, poverty reduction, and food security (Zabel et al., 2014; Jezeer et al., 2019). It is difficult to find research on how farm households in developing countries like Pakistan are adapting to climate change. This study conducts an investigation into the decision-making processes of agricultural communities regarding climate change adaptation. It takes into account the importance and adverse situation in the study area as well as current research gaps. This research is based on the sustainable livelihoods approach (SLA), studying how livelihood assets support agricultural communities by combining household adoption/adaptation strategies and livelihood outcomes (Shinbrot et al., 2019). Our main research question is the following: How important is it to investigate of agricultural communities’ risk assessment and adaptation techniques in response to the effects of climate change? The objectives of this study were to analyze i) agricultural communities’ perceptions toward climate change, ii) their adaptation techniques in response to the effects of climate change, and iii) their livelihood assets and life status in the Kasur district of Pakistan.

Methodology

Study Area and Data

This study was carried out in one of agriculture area Kasur in Punjab Province Pakistan, Pakistan’s most populous and second-largest province. Kasur has a more than 1,000-year history. During the period of the Indus Valley Civilization, the Kasur region was an agricultural region with forests. It had a population of 3,454,881 people at the time of the 2017 census, with 1,788,617 men and 1,666,044 women. The population of this area was 2,564,101 rural and 890,780 urban (Pakistan Bureau of Statistics, 2017). In the Kasur district, the Bambawali-Ravi-Bedian Canal was built, boosting the area’s agricultural development. Commercial and industrial development has occurred, but the area remains primarily agricultural. The district’s farmland covers 393,000 ha, with about 295,000 ha under cultivation. Rice, cotton, sugarcane, wheat, and fodder are among the main crops grown in the district. The district features a sub-tropical climate and vegetation, making it unsuitable for horticulture development, except for certain areas in the southwest of the district, near Patoki, where a large number of nurseries have sprouted. However, these nurseries do not have a market within the district and primarily serve the needs of Lahore (Figure 1). The results of this study may be of use for other agricultural countries. In this study, agricultural communities’ experiences with climate change, the use of wastewater irrigation, and climate change adaptation techniques were examined (Sohail M. et al., 2021). Based on existing literature, a semi-structured questionnaire was developed and adapted to collect data in Kasur Punjab Pakistan (Teh. Kasur, Teh. Chunian, and Teh. Patoki) (Fahad and Wang, 2018; Fahad et al., 2020; Sohail et al., 2022a). Ethics in basic research were taken into account when defining the research goals and collecting data from agricultural communities, and the research goal was clearly explained to agricultural communities (Resnik et al., 2015). Furthermore, agricultural communities were made aware that the information they provided would only be used for research and that they were not obligated to provide any answers (Bell et al., 2005; Rasool et al., 2017; Mustafa et al., 2022; Rehman et al., 2022; Ullah et al., 2022; Atchike et al., 2022). This instrument contained a brief introduction to the study’s purpose, followed by a demographic questionnaire to determine the participants’ ages, occupations, and other relevant information. The remainder of the questionnaire is focused on irrigation methods and agricultural communities’ livelihoods. As part of this research, a pre-test was performed on all 800 completed questionnaires to ensure that the data was accurate and free of inconsistencies. SPSS 25 was used to analyze the data that had been gathered (regression).

FIGURE 1

Results and Discussion

Table 1 shows the 800 agricultural communities sampled in this study from the District Kasur Punjab Province of Pakistan (in Teh. Kasur, Teh. Chunian, and Teh. Patoki). Personal characteristics, circumstances, and farming practices define individual agricultural communities’ responsiveness and adaptation potential (Bryan et al., 2013; Qasim et al., 2015; Sohail et al., 2022b). Table 1 also presents demographic information on the agricultural communities in these three tehsils of the Kasur District in Punjab province: the participants from Tehsil Kasur were 83% male and 17% female, those from Tehsil Chunian were 70% male and 30% female, and those from Tehsil Patoki were 85% male and 15% female. Most members of agricultural communities in the selected tehsils of the Kasur District were young, experienced, and energetic in agriculture. The majority of respondents were uneducated, and their level of education was low; the majority had only primary education, while some had more than 6 years of education. The majority of the agricultural communities were seasoned, with some having about 10 years of experience in the field. According to Mehmood et al. (2021), farmer’s awareness has a significant relationship with education and farming experience. Most families in agricultural communities in the Kasur District are large. The majority of respondents plowed their land with a tractor, while some used bullocks, and a small group used both methods. The majority of people in the agricultural communities received information about farming from their friends, particularly from older agricultural communities in the area. The awareness of climate change in agricultural communities was also identified in a survey item. The results showed that 60%, 75%, and 55% of respondents in Kasur, Chunian, and Patoki, respectively, were well aware of climate change (Table 1). Agricultural communities’ perceptions of climate change and its effects are mediated by farmland features and demographic assets, according to the literature (Bhadwal et al., 2019). Agricultural communities benefit from knowledge, information sharing, and communication in their decision-making, and are adopting proper measures against climate change and associated factors (Drafor and Agyepong, 2005; Deressa et al., 2009). The literature also indicates the importance of agricultural communities’ demographic and socioeconomic characteristics in relation to the climate change adaptation they used. Table 1 depicts the lifestyles and assets of agricultural communities, for example. Tractor/plow, bicycles, motorcycles, tube wells, spraying devices, electric generators, automobiles/jeeps, air conditioners, gas generators, televisions, and livestock (Sohail et al., 2022a). The majority of agricultural communities in these three tehsils of district Kasur feature all of the above-mentioned assets related to their farming and daily life. Although some agricultural communities own tractors, the majority use bullocks and may rent a tractor for land preparation. Many other secondary types of luxuries, such as automobiles, air conditioners, generators, and tube wells, were not available to all agricultural communities in the study area, indicating a less luxurious lifestyle and demonstrating the need to mitigate climate change (Ullah et al., 2022). Better access should be provided to cutting-edge farming technology and agricultural assets to promote agricultural progress and reduce poverty (Fahad, et al., 2018). Some expert have found that agricultural communities that desired to reduce climate change risk had sufficient resources to adapt (Deressa et al., 2009). Natural calamities such as severe rain, droughts, and floods threaten small agricultural settlements. Agricultural communities with sufficient resources and assets feel safer and can better withstand climate change (Goh, 2012).

The climate in Pakistan ranges from semiarid to arid, which impacts its water resources and leads to a scarcity of freshwater (Shah et al., 2019). The agricultural communities examined in this study used canal water, freshwater, and industrial waste water for irrigation. Groundwater in many parts of Pakistan is of poor quality due to high levels of soluble salts and hazardous metals (Murtaza et al., 2019; Hussain et al., 2020). Industrial wastewater is used for irrigation in some areas, and due to prevailing water scarcity, its use may increase in the coming years (Afzal et al., 2014). Many industrial companies discharge their wastewater to nearby waterways or into fields (Hussain et al., 2020; Shahid et al., 2020; Sohail et al., 2022a). The infrastructure for collecting and treating wastewater in Pakistan is inadequate (Kanwal et al., 2020; Khan et al., 2020). Residents in this research region used drains or combined drains and freshwater for irrigation. According to some studies, low-quality irrigation water can have an impact on soil and groundwater quality, as well as human health (Bruvold and Crook, 1981). As some individuals used industrial wastewater for irrigation, the following question was posed: “Is industrial wastewater a cheaper fertilizer than conventional fertilizer?” The majority of respondents, 70%, 60%, and 55% in Kasur, Chunian, and Patoki, respectively, responded “yes.” The majority of agricultural communities identified three key benefits to the use of drain water: 1) lower water prices, 2) lower fertilizer costs, and 3) increased crop yield (Sohail and Ehsan, 2022). The majority of rural communities were unaware of the dangers of using drain water. While some agricultural communities were aware of potential threats, 55%, 30%, and 75% in Kasur, Chunian, and Patoki, respectively, were unaware of possible hazards due to industrial wastewater irrigation, while 45%, 70%, and 25% in Kasur, Chunian, and Patoki, respectively, reported awareness of this (Carr et al., 2011). Agricultural communities prefer to use wastewater for irrigation when it is freely available and usually they were unaware of its impacts on human health and on environment (Shahid et al., 2020). Many farmers in agricultural communities prefer to use wastewater because of its good effects and the presence of nutrients for crops, although the level of nutrients in the wastewater they use has not been extensively investigated (Khalid et al., 2020; Sohail et al., 2022a). Studies have shown the potential health risks associated with toxic metal deposition in wastewater-irrigated topsoil (Kanwal et al., 2020, Shahid et al., 2020). Many farmers say that no one in their families experience any ill effects, although some report that they do (McCusker and Gunaydin, 2015; Shahid et al., 2020) (Table 2). Heavy metals in wastewater, soil, and vegetables should be tested regularly to avoid accumulating in the food chain and human health risks (Hussain et al., 2020). Kasur’s leather industry, according to M. Afzal, damages soil, agriculture, and groundwater (Afzal et al., 2014).

Figure 2A depicted agricultural communities’ views on climate change in the Kasur. Over the past few decades, the effects of climate change have become increasingly evident (Patt and Schröter, 2008; Sohail et al., 2022b; Liu et al., 2022). The primary indicators used to measure perception were drought, flooding, soil issues, irrigation, animal diseases, rainfall issues, and crop pests. The agricultural communities in Kasur and Chunian reported flood rates of 66% and 64%, respectively, while the rest of the tehsils put it at a moderate or low rate. The lives of members of agricultural communities have been adversely affected by high temperatures and floods (Douglas, 2009). For the most part, people in Pakistan’s rural areas, particularly those who are agricultural communities, continue to live in substandard conditions, despite the country’s efforts to improve their lives in many different areas (Fahad, et al., 2018). Pakistan has experienced several devastating floods, including in 2010 and 2011, which resulted in the loss of approximately 250,000 (numbers) farm households and 1 million cultivated land, as well as the destruction of forests, fisheries, infrastructure, fertilizers, and animal sheds (Holt et al., 2006;Harvey. 2014; NDMA, 2014). Many agricultural communities in Pakistan are concerned about soil issues (Irfan and Husnain, 2022). In this study area, most respondents report low to moderate soil issues, but some face larger challenges (Sohail et al., 2014; Javed et al., 2020). Animals have always been a valuable resource for agricultural communities around the world, and the threat of animal disease adds another layer of complexity to their already taxing lives (Musungu, 2020; Sohail et al., 2022a). Some agricultural communities were facing animal diseases problem in District Kasur. Most of district Kasur is dry, and rainfall is always a severe challenge for farming. Pests are expected to be severe in south Punjab for several years (Iqbal et al., 2022). Many respondents indicate a high level of pests in the study area, 45%, 42%, and 55% in Kasur, Chunian, and Patoki, respectively. Adaptation techniques for climate change were also examined in this study (Figure 2B), Many families deal with choosing their own crop varieties, adjusting fertilizer, finding agricultural finance, and facing livelihood risks regularly (Kuang et al., 2020). Agricultural communities in Pakistan have been reported to use similar adaptation measures such as changing planting dates, crop types, variety changes, and input mix changes (Gorst et al., 2015; Maqbool et al., 2020). Agricultural communities occasionally face pest-related attacks on crops, which have been comparatively high in the Kasur District for many years and have the potential to affect production, so they use different techniques to reduce risk at different times (Ishtiaq et al., 2020). In recent years, crop production has fallen due to plant diseases, climate change, poverty, or irrigation concerns (Sohail et al., 2022a). Small agricultural communities are more vulnerable to climate change adoption than larger ones (Jamshidi et al., 2019), and climate hazards have a greater influence on low-resource farming populations’ income, food, and security (Shukla et al., 2019). The literature describes climate change’s effects on crop output and affecting Pakistan’s crop production, which accounts for a substantial amount of its GDP (Hay and Mamura, 2010; Tingju et al., 2014; Kuang et al., 2020). Climate risk and adaptation methods can assist agricultural communities in minimizing risk and boosting crop yield (Sohail et al., 2022b). Physical, environmental, and social assets influence agricultural communities’ adaptation strategies (Singh et al., 2022).

FIGURE 2

Table 3 shows the results of linear regression for the research variables. Explanatory factors, including animal disease, have a significant relationship with adaptation strategies (p-value of 0.003 and coefficient of 0.153). Agricultural communities can safe animal from different diseases if they adopt suitable strategies (Musungu, A. L. 2020). Animal illnesses are managed in different ways by agricultural communities in different areas. Soil issues are highly significant as well (with a p-value of 0.000 and a coefficient of 0.044). With proper resources and measurement, soil issues can be resolved. Droughts and floods have a substantial association with adaptation measures (p-value 0.000 and coefficient 0.132) and (p-value 0.045 and coefficient 0.073) respectively, which indicates that adoption measures can help with droughts and floods. Pests have a significant relationship with the dependent variable as well (p-value 0.000 and coefficient 0.035). This demonstrates that agricultural communities can control pests using reasonable methods. Adaptation measures and storage of water for irrigation showed statistical significance (p = 0.000, positive correlation of 0.124). The dependent variable has a considerable link with potential dangers induced by industry wastewater (p-value 0.000 and coefficient 0.178). More effective adoption strategies can help lessen the negative effects of industrial wastewater on human health and increase access to information about the dangers of industrial wastewater use.

Conclusion

Pakistan is largely an agricultural country, and the vast majority of its population is engaged in farming. A majority of our respondents had no idea that industrial wastewater could pose a health risk. A variety of statistical methods were employed to examine the correlation between various variables. Agricultural communities with a sufficient amount of assets and resources believe that they are secure enough to withstand the negative effects of climate change. In this study, correlation values of selected variables are significant across all variables. The study’s findings will help policymakers support agricultural communities’ daily activities and farming techniques and provide adequate monitoring and public policies to ensure integration and sustainability. In the context of Pakistan, the findings of this study on agricultural households’ adaptation tactics are unique. They offer information on adaptation measures and their advantages, as well as the value of change awareness programs delivered by extension workers in the Kasur District. Risk-mitigating investment measures can aid impoverished farming households. Climate-related endowments, such as access to services and alternative livelihood opportunities, must be prioritized by policymakers.

References

• 1

  AfzalM.ShabirG.IqbalS.MustafaT.KhanQ. M.KhalidZ. M. (2014). Assessment of Heavy Metal Contamination in Soil and Groundwater at Leather Industrial Area of Kasur, Pakistan. Clean. Soil Air Water42 (8), 1133–1139. 10.1002/clen.201100715

  • CrossRef
  • Google Scholar

• 2

  AkhtarS.LiG.-c.NazirA.RazzaqA.UllahR.FaisalM.et al (2019). Maize Production under Risk: the Simultaneous Adoption of Off-Farm Income Diversification and Agricultural Credit to Manage Risk. J. Integr. Agric.18 (2), 460–470. 10.1016/s2095-3119(18)61968-9

  • CrossRef
  • Google Scholar

• 3

  AmirS.SaqibZ.KhanM. I.KhanM. A.BokhariS. A.Zaman-ul-HaqM.et al (2020). Farmers ‘perceptions and Adaptation Practices to Climate Change in Rain-Fed Area: a Case Study from District Chakwal, Pakistan. Pak. J. Agric. Sci.57 (2), 465–475.

  • Google Scholar

• 4

  AnwarH. N.NosheenF.HussainS.NawazW. (2010). Socio-economics Consequences of Reusing Industry Wastewater in Agriculture in Faisalabad. Pak. J. Life Soc. Sci.8 (2), 102–105.

  • Google Scholar

• 5

  AtchikeD. W.IrfanM.AhmadM.RehmanM. A. (2022). Waste-to-Renewable Energy Transition: Biogas Generation for Sustainable Development. Front. Environ. Sci.107, 840588. 10.3389/fenvs.2022.840588

  • CrossRef
  • Google Scholar

• 6

  BellD.GrayT.HaggettC. (2005). The 'Social Gap' in Wind Farm Siting Decisions: Explanations and Policy Responses. Environ. Polit.14 (4), 460–477. 10.1080/09644010500175833

  • CrossRef
  • Google Scholar

• 7

  BhadwalS.SharmaG.GortiG.SenS. M. (2019). Livelihoods, Gender and Climate Change in the Eastern Himalayas. Environ. Dev.31, 68–77. 10.1016/j.envdev.2019.04.008

  • CrossRef
  • Google Scholar

• 8

  BognerA.LittigB.MenzW. (2009). “Interviewing Experts,” in ECPR Research Methods (Springer).

  • Google Scholar

• 9

  BruvoldW.CrookJ. (1981). What the Public Thinks: Reclaiming and Reusing Wastewater. Water Eng. Manage128 (4), 65–71.

  • Google Scholar

• 10

  BryanE.RinglerC.OkobaB.RoncoliC.SilvestriS.HerreroM. (2013). Adapting Agriculture to Climate Change in Kenya: Household Strategies and Determinants. J. Environ. Manag.114, 26–35. 10.1016/j.jenvman.2012.10.036

  • CrossRef
  • Google Scholar

• 11

  CarrG.PotterR. B.NortcliffS. (2011). Water Reuse for Irrigation in Jordan: Perceptions of Water Quality Among Farmers. Agric. Water Manag.98 (5), 847–854. 10.1016/j.agwat.2010.12.011

  • CrossRef
  • Google Scholar

• 12

  ChandraA.McNamaraK. E.DarguschP.CaspeA. M.DalabajanD. (2017). Gendered Vulnerabilities of Smallholder Farmers to Climate Change in Conflict-Prone Areas: A Case Study from Mindanao, Philippines. J. Rural Stud.50, 45–59. 10.1016/j.jrurstud.2016.12.011

  • CrossRef
  • Google Scholar

• 13

  DeressaT. T.HassanR. M.RinglerC.AlemuT.YesufM. (2009). Determinants of Farmers' Choice of Adaptation Methods to Climate Change in the Nile Basin of Ethiopia. Glob. Environ. change19 (2), 248–255. 10.1016/j.gloenvcha.2009.01.002

  • CrossRef
  • Google Scholar

• 14

  DouglasI. (2009). Climate Change, Flooding and Food Security in South Asia. Food Sec.1 (2), 127–136. 10.1007/s12571-009-0015-1

  • CrossRef
  • Google Scholar

• 15

  DraforI.AgyepongK. A. (2005). “Local Information Systems for Community Development in Ghana,” in Improving Information Flows to the Rural Community (FAO).

  • Google Scholar

• 16

  FahadS.WangJ.HuG. Y.WangH.YangX. Y.ShahA. A.et al (2018). Empirical Analysis of Factors Influencing Farmers Crop Insurance Decisions in Pakistan: Evidence from Khyber Pakhtunkhwa Province. Land Use Policy75, 459–467. 10.1016/j.landusepol.2018.04.016

  • CrossRef
  • Google Scholar

• 17

  FahadS.InayatT.WangJ.DongL.HuG.KhanS.et al (2020). Farmers' Awareness Level and Their Perceptions of Climate Change: A Case of Khyber Pakhtunkhwa Province, Pakistan. Land Use Policy96, 104669. 10.1016/j.landusepol.2020.104669

  • CrossRef
  • Google Scholar

• 18

  FahadS.WangJ. (2018). Farmers' Risk Perception, Vulnerability, and Adaptation to Climate Change in Rural Pakistan. Land use policy79, 301–309. 10.1016/j.landusepol.2018.08.018

  • CrossRef
  • Google Scholar

• 19

  FareedZ.RehmanM. A.AdebayoT. S.WangY.AhmadM.ShahzadF. (2022). Financial Inclusion and the Environmental Deterioration in Eurozone: The Moderating Role of Innovation Activity. Technol. Soc.69, 101961. 10.1016/j.techsoc.2022.101961

  • CrossRef
  • Google Scholar

• 20

  FiazS.MobeenN.NoorM.MuddassirM.MubusharM. (2016). Implications of Irrigation Water Crisis on Socio-Economic Condition of Farmers in Faisalabad District, Punjab, Pakistan. Ajaees10 (1), 1–7. 10.9734/ajaees/2016/22883

  • CrossRef
  • Google Scholar

• 21

  FieldC. B.BarrosV.StockerT. F.DaheQ. (2012). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation: Special Report of the Intergovernmental Panel on Climate Change. Report. Cambridge University Press.

  • Google Scholar

• 22

  GohA. H. (2012). A Literature Review of the Gender-Differentiated Impacts of Climate Change on Women’s and Men’s Assets and Well-Being in Developing Countries. Report. International Food Policy Research Institute, 1–44.

  • Google Scholar

• 23

  GorstC.KwokC. S.AslamS.BuchanI.KontopantelisE.MyintP. K.et al (2015). Long-term Glycemic Variability and Risk of Adverse Outcomes: a Systematic Review and Meta-Analysis. Diabetes Care38 (12), 2354–2369. 10.2337/dc15-1188

  • CrossRef
  • Google Scholar

• 24

  HarveyD. (2014). Seventeen Contradictions and the End of Capitalism. USA: Oxford University Press.

  • Google Scholar

• 25

  HassanN. U.MahmoodQ.WaseemA.IrshadM.PervezA. (2013). Assessment of Heavy Metals in Wheat Plants Irrigated with Contaminated Wastewater. Pol. J. Environ. Stud.22 (1), 115–123.

  • Google Scholar

• 26

  HayJ.MimuraN. (2010). The Changing Nature of Extreme Weather and Climate Events: Risks to Sustainable Development. Geomatics, Nat. Hazards Risk1 (1), 3–18. 10.1080/19475701003643433

  • CrossRef
  • Google Scholar

• 27

  HoltM. S.TuongT. P.JohnW. G. (2006). Sources of Chemical Contaminants and Routes into the Freshwater Environment. Food Chem. Toxicol.38, S21–S27. 10.1016/s0278-6915(99)00136-2

  • CrossRef
  • Google Scholar

• 28

  HussainA.BukhariS.AndleebS.RehmanK. U.MaqsoodI.JavidA.et al (2020). Heavy Metal Levels in Vegetables and Soil Cultivated with Industrial Wastewater from Different Sites of Chunian and Jamber, District, Kasur. jasem24 (2), 271–277. 10.4314/jasem.v24i2.13

  • CrossRef
  • Google Scholar

• 29

  IqbalS.FaridM.ZubairM.AsamZ. U. Z.AliS.AbubakarM.et al (2022). “Efficacy of Various Amendments for the Phytomanagement of Heavy Metal Contaminated Sites and Sustainable Agriculture. A Review,” in Managing Plant Production under Changing Environment (Singapore: Springer), 239–272. 10.1007/978-981-16-5059-8_9

  • CrossRef
  • Google Scholar

• 30

  IrfanM.HasnainN. (2022). “Nitrogen Emissions from Agriculture Sector in Pakistan: Context, Pathways, Impacts and Future Projections,” in Nitrogen Assessment (Academic Press), 99–125. 10.1016/b978-0-12-824417-3.00008-3

  • CrossRef
  • Google Scholar

• 31

  IshtiaqM.SadiqueM.FariedN.Naeem-UllahU.HamzaM. A. (2020). First Record of Tomato Leaf Miner, Tuta Absolute (Meyrick 1917) (Lepidoptera: Gelechiidae) from Southern Part of Punjab, Pakistan. J. Animal Plant Sciences-Japs30 (6), 1604–1611. 10.3391/bir.2017.6.4.01

  • CrossRef
  • Google Scholar

• 32

  JamshidiO.AsadiA.KalantariK.AzadiH.ScheffranJ. (2019). Vulnerability to Climate Change of Smallholder Farmers in the Hamadan Province, Iran. Clim. Risk Manag.23, 146–159. 10.1016/j.crm.2018.06.002

  • CrossRef
  • Google Scholar

• 33

  JavedA.FarooqiA.BaigZ. U.EllisT.van GeenA. (2020). Soil Arsenic but Not Rice Arsenic Increasing with Arsenic in Irrigation Water in the Punjab Plains of Pakistan. Plant Soil450, 601–611. 10.1007/s11104-020-04518-z

  • CrossRef
  • Google Scholar

• 34

  JezeerR. E.VerweijP. A.BootR. G. A.JungingerM.SantosM. J. (2019). Influence of Livelihood Assets, Experienced Shocks and Perceived Risks on Smallholder Coffee Farming Practices in Peru. J. Environ. Manag.242, 496–506. 10.1016/j.jenvman.2019.04.101

  • CrossRef
  • Google Scholar

• 35

  JianL.SohailM. T.UllahS.MajeedM. T. (2021). Examining the Role of Non-economic Factors in Energy Consumption and CO2 Emissions in China: Policy Options for the Green Economy. Environ. Sci. Pollut. Res.28 (47), 67667–67676. 10.1007/s11356-021-15359-3

  • CrossRef
  • Google Scholar

• 36

  JiangA.CaoY.SohailM. T.MajeedM. T.SohailS. (2021). Management of Green Economy in China and India: Dynamics of Poverty and Policy Drivers. Environ. Sci. Pollut. Res.28 (39), 55526–55534. 10.1007/s11356-021-14753-1

  • CrossRef
  • Google Scholar

• 37

  KanwalS.SajjadM.GabrielH. F.HussainE. (2020). Towards Sustainable Wastewater Management: A Spatial Multi-Criteria Framework to Site the Land-FILTER System in a Complex Urban Environment. J. Clean. Prod.266, 121987. 10.1016/j.jclepro.2020.121987

  • CrossRef
  • Google Scholar

• 38

  KhalidS.ShahidM.NatashaShahA. H.SaeedF.AliM.DumatC.et al (2020). Heavy Metal Contamination and Exposure Risk Assessment via Drinking Groundwater in Vehari, Pakistan. Environ. Sci. Pollut. Res.27 (32), 39852–39864. 10.1007/s11356-020-10106-6

  • CrossRef
  • Google Scholar

• 39

  KhanN. A.GaoQ.AbidM. (2020). Public Institutions' Capacities Regarding Climate Change Adaptation and Risk Management Support in Agriculture: the Case of Punjab Province, Pakistan. Sci. Rep.10 (1), 14111–14112. 10.1038/s41598-020-71011-z

  • CrossRef
  • Google Scholar

• 40

  KuangF.JinJ.HeR.NingJ.WanX. (2020). Farmers' Livelihood Risks, Livelihood Assets and Adaptation Strategies in Rugao City, China. J. Environ. Manag.264, 110463. 10.1016/j.jenvman.2020.110463

  • CrossRef
  • Google Scholar

• 41

  LanH.ChengC.SohailM. T. (2022). Asymmetric Determinants of CO₂ Emissions in China: Do Government Size and Economic Size Matter?. Environ. Sci. Pollut. Res., 1–8.

  • Google Scholar

• 42

  LeeS.-H.ChoiJ.-Y.HurS.-O.TaniguchiM.MasuharaN.KimK. S.et al (2020). Food-centric Interlinkages in Agricultural Food-Energy-Water Nexus under Climate Change and Irrigation Management. Resour. Conservation Recycl.163, 105099. 10.1016/j.resconrec.2020.105099

  • CrossRef
  • Google Scholar

• 43

  LiuY.SohailM. T.KhanA.MajeedM. T. (2022). Environmental Benefit of Clean Energy Consumption: Can BRICS Economies Achieve Environmental Sustainability through Human Capital?Environ. Sci. Pollut. Res.29 (5), 6766–6776. 10.1007/s11356-021-16167-5

  • CrossRef
  • Google Scholar

• 44

  LobellD. B.GourdjiS. M. (2012). The Influence of Climate Change on Global Crop Productivity. Plant Physiol.160, 1686–1697. 10.1104/pp.112.208298

  • CrossRef
  • Google Scholar

• 45

  MahfoozY.YasarA.SohailM. T.TabindaA. B.RasheedR.IrshadS.et al (2019). Investigating the Drinking and Surface Water Quality and Associated Health Risks in a Semi-arid Multi-Industrial Metropolis (Faisalabad), Pakistan. Environ. Sci. Pollut. Res.26 (20), 20853–20865. 10.1007/s11356-019-05367-9

  • CrossRef
  • Google Scholar

• 46

  MaqboolA.AshrafM. A.KhaliqA.HuiW.SaeedM. (2020). Efficient Water Allocation Strategy to Overcoming Water Inequity Crisis for Sustainability of Agricultural Land: a Case of Southern Punjab, Pakistan. Stoch. Environ. Res. Risk Assess.35, 1–10. 10.1007/s00477-020-01903-z

  • CrossRef
  • Google Scholar

• 47

  McCuskerK.GunaydinS. (2015). Research Using Qualitative, Quantitative or Mixed Methods and Choice Based on the Research. Perfusion30 (7), 537–542. 10.1177/0267659114559116

  • CrossRef
  • Google Scholar

• 48

  McDowellG.StephensonE.FordJ. (2014). Adaptation to Climate Change in Glaciated Mountain Regions. Cli-matic Change126 (1), 77–91. 10.1007/s10584-014-1215-z5

  • CrossRef
  • Google Scholar

• 49

  MehmoodY.ArshadM.KaecheleH.MahmoodN.KongR. (2021). Pesticide Residues, Health Risks, and Vegetable Farmers' Risk Perceptions in Punjab, Pakistan. Hum. Ecol. Risk Assess. Int. J.27 (3), 846–864. 10.1080/10807039.2020.1776591

  • CrossRef
  • Google Scholar

• 50

  MurtazaG.Zia-ur-RehmanM.RashidI.QadirM. (2019). “Use of Poor-Quality Water for Agricultural Production,” in Research Developments in Saline Agriculture (New York: Springer), 769–783. 10.1007/978-981-13-5832-6_26

  • CrossRef
  • Google Scholar

• 51

  MustafaS.SohailM. T.AlroobaeaR.RubaieeS.AnasA.OthmanA. M.et al (2022). Éclaircissement to Understand Consumers’ Decision-Making Psyche and Gender Effects, a Fuzzy Set Qualitative Comparative Analysis. Front. Psychol., 2971.

  • Google Scholar

• 52

  MusunguA. L. (2020). Assessment of Livestock Farmers’ Preferences for Integration of Community-Owned Resource Persons and Interrelationships in Animal Trypanosomiasis Management Methods in Kwale County. Kenya: University of Nairobi. Doctoral dissertation.

  • Google Scholar

• 53

  NDMA (2014). Pakistan Floods 2014: Recovery Needs Assessment and Action Framework 2014-16. NDMA Report. Available at: http://www.ndma.gov.pk/BooksPublications.php (Accessed November 21, 2015).

  • Google Scholar

• 54

  OzturkI.Al-MulaliU.SolarinS. A.ShahzadF.FareedZ.RehmanM. A. (2019). The Control of Corruption and Energy Efficiency Relationship: an Empirical noteRevisiting the EKC Hypothesis with Export Diversification and Ecological Footprint Pressure Index for India: A RALS-Fourier Cointegration Test. Front. Environ. Sci. Pollut. ResEnviron. Sci.2610 (17), 17277886515–17277917283. 10.1007/s11356-019-05016-1

  • CrossRef
  • Google Scholar

• 55

  OzturkI. (2016). The Relationships Among Tourism Development, Energy Demand, and Growth Factors in Developed and Developing Countries. Int. J. Sustain. Dev. World Ecol.23 (2), 122–131. 10.1080/13504509.2015.1092000

  • CrossRef
  • Google Scholar

• 56

  Pakistan Bureau of Statistics (2017). Pakistan Bureau of Statistics. AvaliableAt: https://www.pbs.gov.pk/node/3391/?name=054.

  • Google Scholar

• 57

  PattA.SchröterD. (2008). Perceptions of Climate Risk in Mozambique: Implications for the Success of Adaptation Strategies. Glob. Environ. Change18 (3), 458–467. 10.1016/j.gloenvcha.2008.04.002

  • CrossRef
  • Google Scholar

• 58

  QasimS.KhanA. N.ShresthaR. P.QasimM. (2015). Risk Perception of the People in the Flood Prone Khyber Pakhtunkhwa Province of Pakistan. Int. J. Disaster Risk Reduct.14, 373–378. 10.1016/j.ijdrr.2015.09.001

  • CrossRef
  • Google Scholar

• 59

  RasoolA.JundongH.SohailM. T. (2017). Relationship of Intrinsic and Extrinsic Rewards on Job Motivation and Job Satisfaction of Expatriates in China. J. Appl. Sci.17 (3), 116–125.

  • Google Scholar

• 60

  RehmanM. A.FareedZ.SalemS.KanwalA.PataU. K. (2021). Do diversified Export, Agriculture, and Cleaner Energy Consumption Induce Atmospheric Pollution in Asia? Application of Method of Moments Quantile Regression. Front. Environ. Sci.497, 781097. 10.3389/fenvs.2021.781097

  • CrossRef
  • Google Scholar

• 61

  RehmanM. A.FareedZ.ShahzadF. (2022). When Would the Dark Clouds of Financial Inclusion Be over, and the Environment Becomes Clean? the Role of National Governance. Environ. Sci. Pollut. Res.29, 1–13. 10.1007/s11356-021-17683-0

  • CrossRef
  • Google Scholar

• 62

  ReidsmaP.BakkerM. M.KanellopoulosA.AlamS. J.PaasW.KrosJ.et al (2015). Sustainable Agricultural Development in a Rural Area in the Netherlands? Assessing Impacts of Climate and Socio-Economic Change at Farm and Landscape Level. Agric. Syst.141, 160–173. 10.1016/j.agsy.2015.10.009

  • CrossRef
  • Google Scholar

• 63

  ResnikD. B.ElliottK. C.MillerA. K. (2015). A Framework for Addressing Ethical Issues in Citizen Science. Environ. Sci. Policy54, 475–481. 10.1016/j.envsci.2015.05.008

  • CrossRef
  • Google Scholar

• 64

  SaeedR.SattarA.IqbalZ.ImranM.NadeemR. (2012). Environmental Impact Assessment (EIA): an Overlooked Instrument for Sustainable Development in Pakistan. Environ. Monit. Assess.184 (4), 1909–1919. 10.1007/s10661-011-2088-5

  • CrossRef
  • Google Scholar

• 65

  SchillingJ.VivekanandaJ.KhanM. A.PandeyN. (2013). Vulnerabil-ity to Environmental Risks and Effects on Community Resiliencein Mid-west Nepal and South-East Pakistan. Environ. Nat. ResourRes3, 27. 10.5539/enrr.v3n4p27

  • CrossRef
  • Google Scholar

• 66

  ShahidM.NatashaM.KhalidS.MurtazaB.AnwarH.ShahA. H.et al (2020). A Critical Analysis of Wastewater Use in Agriculture and Associated Health Risks in Pakistan. Environ. Geochem Health, 1–20. 10.1007/s10653-020-00702-3

  • CrossRef
  • Google Scholar

• 67

  ShahS. I. A.ZhouJ.ShahA. A. (2019). Ecosystem-based Adaptation (EbA) Practices in Smallholder Agriculture; Emerging Evidence from Rural Pakistan. J. Clean. Prod.218, 673–684. 10.1016/j.jclepro.2019.02.028

  • CrossRef
  • Google Scholar

• 68

  ShinbrotX. A.JonesK. W.Rivera-CastañedaA.López-BáezW.OjimaD. S. (2019). Smallholder Farmer Adoption of Climate-Related Adaptation Strategies: The Importance of Vulnerability Context, Livelihood Assets, and Climate Perceptions. Environ. Manag.63, 1–13. 10.1007/s00267-019-01152-z

  • CrossRef
  • Google Scholar

• 69

  ShuklaR.AgarwalA.SachdevaK.KurthsJ.JoshiP. K. (2019). Climate Change Perception: an Analysis of Climate Change and Risk Perceptions Among Farmer Types of Indian Western Himalayas. Clim. Change152 (1), 103–119. 10.1007/s10584-018-2314-z

  • CrossRef
  • Google Scholar

• 70

  SinghR. K.ZanderK. K.KumarS.SinghA.SheoranP.KumarA.et al (2017). Perceptions of Climate Variability and Livelihood Adaptations Relating to Gender and Wealth Among the Adi Community of the Eastern Indian Himalayas. Appl. Geogr.86, 41–52. 10.1016/j.apgeog.2017.06.018

  • CrossRef
  • Google Scholar

• 71

  SinghR.VermaP.SinghV. K.SrivastavaP.KumarA.BalS. K.et al (2022). Urban Ecology and Climate Change. Nat. Hazards1, 29. 10.1002/9781119807216.ch1

  • CrossRef
  • Google Scholar

• 72

  SohailM.DelinH.TalibM.XiaoqingX.Muhammad AkhtarM. (2014). An Analysis of Environmental Law in Pakistan-Policy and Conditions of Implementation. Rjaset8 (5), 644–653. 10.19026/rjaset.8.1017

  • CrossRef
  • Google Scholar

• 73

  SohailM.LinX.LizhiL.RizwanullahM.NasrullahM.XiuyuanY.et al (2021b). Farmers' Awareness about Impacts of Reusing Wastewater, Risk Perception and Adaptation to Climate Change in Faisalabad District, Pakistan. Pol. J. Environ. Stud.30, 4663–4675. 10.15244/pjoes/134292

  • CrossRef
  • Google Scholar

• 74

  SohailM. T.XiuyuanY.UsmanA.MajeedM. T.UllahS. (2021a). Renewable Energy and Non-renewable Energy Consumption: Assessing the Asymmetric Role of Monetary Policy Uncertainty in Energy Consumption. Environ. Sci. Pollut. Res. Int.28 (24), 31575–31584. 10.1007/s11356-021-12867-0

  • CrossRef
  • Google Scholar

• 75

  SohailM. T.AftabR.MahfoozY.YasarA.YenY.ShaikhS. A.et al (2019). Estimation of Water Quality, Management and Risk Assessment in Khyber-Pakhtunkhwa and Gilgit Baltistan Pakistan. Dwt171, 105–114. 10.5004/dwt.2019.24925

  • CrossRef
  • Google Scholar

• 76

  SohailM. T.EhsanM. (2022). Investigating the Drinking Water Quality and Associated Health Risks in Metropolis Area of Pakistan. Front. Mater.155, 20853–20865. 10.3389/fmats.2022.864254

  • CrossRef
  • Google Scholar

• 77

  SohailM. T.KlkeedE.SohaibM. (2022a). Determining Farmers’ Awareness about Climate Change Mitigation and Wastewater Irrigation: A Pathway towards Green and Sustainable Development. Front. Environ. Sci.10. 10.3389/fenvs.2022.900193

  • CrossRef
  • Google Scholar

• 78

  SohailM. T.MahfoozY.AftabR.YenY.TalibM. A.RasoolA. (2020). Water Quality and Health Risk of Public Drinking Water Sources: a Study of Filtration Plants Installed in Rawalpindi and Islamabad, Pakistan. Dwt181, 239–250. 10.5004/dwt.2020.25119

  • CrossRef
  • Google Scholar

• 79

  SohailM. T.MahfoozY.AzamK.YatY.GenfuL.FahadS. (2019a). Impacts of Urbanization and Land Cover Dynamics on Underground Water in Islamabad, Pakistan. Dwt159, 402–411. 10.5004/dwt.2019.24156

  • CrossRef
  • Google Scholar

• 80

  SohailM. T.MajeedM. T.ShaikhP. A.AndlibZ. (2022b). Environmental Costs of Political Instability in Pakistan: Policy Options for Clean Energy Consumption and Environment. Environ. Sci. Pollut. Res.29 (17), 25184–25193. 10.1007/s11356-021-17646-5

  • CrossRef
  • Google Scholar

• 81

  TingjuZ.XieH.WaqasA.RinglerC.IqbalM. M.GoheerM. A.et al (2014). Climate Change and Extreme Events, Impacts on Pakistan’s Agriculture. International Food Policy Research Institute.

  • Google Scholar

• 82

  UllahI.RehmanA.SvobodovaL.AkbarA.ShahM. H.ZeeshanM.et al (2022). Investigating Relationships between Tourism, Economic Growth, and CO2 Emissions in Brazil: An Application of the Nonlinear ARDL Approach. Front. Environ. Sci.52, 843906. 10.3389/fenvs.2022.843906

  • CrossRef
  • Google Scholar

• 83

  UllahZ.KhanH.WaseemA.MahmoodQ.FarooqU. (2013). Water Quality Assessment of the River Kabul at Peshawar, Pakistan: Industrial and Urban Wastewater Impacts. J. Water Chem. Technol.35, 170–176. 10.3103/s1063455x1304005x

  • CrossRef
  • Google Scholar

• 84

  YaminM.NasirA.SultanM.IsmailW. I. W.ShamshiriR.AkhbarF. N. (2015). Impact of Sewage and Industrial Effluents on Water Quality in Faisalabad, Pakistan. Adv. Environ. Biol.9 (18), 53–58.

  • Google Scholar

• 85

  YenY.WangZ.ShiY.XuF.SoeungB.SohailM. T.et al (2017). The Predictors of the Behavioral Intention to the Use of Urban Green Spaces: The Perspectives of Young Residents in Phnom Penh, Cambodia. Habitat Int.64, 98–108. 10.1016/j.habitatint.2017.04.009

  • CrossRef
  • Google Scholar

• 86

  ZabelF.PutzenlechnerB.MauserW. (2014). Global Agricultural Land Resources - A High Resolution Suitability Evaluation and its Perspectives until 2100 under Climate Change Conditions. PLoS ONE9, e107522. 10.1371/journal.pone.0107522

  • CrossRef
  • Google Scholar

• 87

  ZhaoP.YenY.BaileyE.SohailM. (2019). Analysis of Urban Drivable and Walkable Street Networks of the ASEAN Smart Cities Network. Ijgi8 (10), 459. 10.3390/ijgi8100459

  • CrossRef
  • Google Scholar

• 88

  ZhenyuW.SohailM. T. (2022). Short-and Long-Run Influence of Education on Subjective Well-Being: The Role of ICT in China. Front. Psychol., 3027.

  • Google Scholar